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==== Front Polymers (Basel) Polymers (Basel) polymers Polymers 2073-4360 MDPI 10.3390/polym14091876 polymers-14-01876 Article High Mechanical Properties of Stretching Oriented Poly(butylene succinate) with Two-Step Chain Extension Li Xun 1 https://orcid.org/0000-0002-0729-4086 Xia Min 2 Dong Xin 1 Long Ren 1 Liu Yuanhao 1 https://orcid.org/0000-0002-3697-7409 Huang Yiwan 1 Long Shijun 1 Hu Chuanqun 1* https://orcid.org/0000-0001-5082-1008 Li Xuefeng 1* Kasmi Nejib Academic Editor Bikiaris Dimitrios Academic Editor Hakkarainen Minna Academic Editor 1 School of Materials and Chemical Engineering, Hubei University of Technology, Wuhan 430068, China; lixun.hubu@foxmail.com (X.L.); dx2418483912@163.com (X.D.); lr302842520@163.com (R.L.); a1361856356@163.com (Y.L.); yiwanhuang@hbut.edu.cn (Y.H.); longshijun.hp@163.com (S.L.) 2 School of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, China; xminbit@bit.edu.cn * Correspondence: nanohu@126.com (C.H.); li_xf@mail.hbut.edu.cn (X.L.) 04 5 2022 5 2022 14 9 187607 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/). The structure, morphology, fracture toughness and flaw sensitivity length scale of chain-extended poly(butylene succinate) with various pre-stretch ratios were studied. PBS modification adopted from a multifunctional, commercially available chain-extension containing nine epoxy groups (ADR9) as the first step chain extension and hydroxyl addition modified dioxazoline (BOZ) as the second step. Time-temperature superposition (TTS) studies show that the viscosity increased sharply and the degree of molecular branching increased. Fourier transform infrared spectroscopy (FT-IR) confirm successful chain extension reactions. The orientation of the polymer in the pre-stretch state is such that spherulites deformation along the stretching direction was observed by polarized light optical microscopy (PLOM). The fracture toughness of sample (λfix = 5) is Γ ≈ 106 J m-2 and its critical flaw sensitivity length scale is Γ/Wc ≈ 0.01 m, approximately 5 times higher than PBS without chain-extension (Γ ≈ 2 × 105 J m-2 and Γ/Wc ≈ 0.002 m, respectively). The notch sensitivity of chain-extended PBS is significantly reduced, which is due to the orientation of spherulites more effectively preventing crack propagation. The principle can be generalized to other high toughness material systems. poly(butylene succinate) chain extension fracture toughness flaw sensitivity crystal morphology National Natural Science Foundation of China (NSFC)52073083 Open Fund of Hubei Provincial Key Laboratory of Green Materials for Light Industry202007A01 National Natural Science Foundation of China (NSFC) (Contract no. 52073083) and the Open Fund of Hubei Provincial Key Laboratory of Green Materials for Light Industry (Contract no. 202007A01). ==== Body pmc1. Introduction Poly(butylene succinate) (PBS) is a commercially available, synthetic polyester possessing many advantages such as biodegradability, renewability, and biocompatibility. The extensive application of the polymers can not only mitigate the negative effect of nondegradable plastics on the environment, but also reduce the dependence on fossil resources [1,2,3]. PBS is a semicrystalline aliphatic polyester that has been gaining attention as a material for developing sustainable solutions oriented towards the worldwide environmental problem of white pollution caused by traditional nondegradable plastics [4,5]. The linear molecular chain structure of PBS contains two carbonyl groups and one butyl group, which leads to the high crystallinity of PBS. PBS’s high-crystallinity paired with its malleability make it widely used in film products [6,7]. PBS has a relatively low molecular weight and its low ductility cannot meet the requirements of some extrusion product applications such as film, monofilament, sheet, strip, sectional material, etc. [8] A general strategy toward the design of anti-fracture polyester material has remained a critical need and a central challenge for long-term applications of polyester in renewable and biodegradable applications [9]. Thus, the method of chain extension has been used to improve its physical properties, especially its toughness and anti-fracture performance. Simultaneously increasing the melt viscosity and toughness to broaden the application range of PBS materials is important. At present there are methods of chemical modification used to solve this problem in PBS. Chemical modifications include forming a branched chain structure on the molecular chain by reacting the chain extender with the end group on PBS (PBS–OH or PBS–COOH), so as to improve the molecular weight and mechanical toughness of PBS. Therefore, a large number of researchers are devoting their efforts to exploring effective PBS chain extenders. In recent years, chain extension agents used for polyester chain extension mainly contain epoxides [10], acid anhydrides [11] or isothiocyanates [12]. In some chain extension reaction processes the chain end carboxyl polymer is extended, while others extend the chain end hydroxyl polymer. Using 1,6-hexmethylene diisocyanate (HDI) as a chain extender, Zhang et al. [13] successfully synthesized multiblock co-polyester, which greatly increased the molecular weight of PBS and excellent mechanical properties were obtained. Zhang et al. [14] focused on the use of toluene-2,4-di-iso-cyanate (TDI) as a chain extender to modify PBS and improved its molecular weight. Zou et al. [15] used 2,2′-bis (2-oxazoline) as a chain extension functional end group. The researchers found that the molecular weight and viscosity of PBS were increased and the crystallization property of PBS was controlled via chain extension. However, although a single chain extender can increase the molecular weight of PBS, it may cause the processing disadvantage of enhanced gel fraction via cross-linking. Effects of orientation and material isotropy on the exact elastic field are necessary design considerations because strength, toughness, and all other mechanical properties of any orthotropic depend on its orientation structure [16]. Under loading progress, the stress and displacement components of any orthotropic composite vary with the variation of material orientation. Stress-orientation analysis of composite structures is carried out using different analytical and semi-analytical approaches where loading is applied along the parallel plane of the composite [17]. Due to the simple structure of PBS, the flexibility of the molecular chain and the relaxation time of the chain segment lead to easy orientation of the chain. Monakhova et al. [18] investigated the mechanical properties of PBS using plane orientation. The researchers found that the addition of a low content of Al2O3 and TiO2 micro- and nanoparticles resulted in a twofold increase in the elastic modulus of the composite, and found the phenomenon of crack propagation. Although studies on polymer chain orientation are rather abundant, the stretching orientation of chain-extended PBS and the significant effect of orientation structure on flaw sensitivity are rarely reported. The flaw sensitivity of an elastic PBS can be estimated by the critical length scale Γ/Wc [19], where Γ is the fracture toughness and Wc is the work to rupture measured with no or negligible flaw. The flaw sensitivity and fracture toughness Γ of PBS can be effectively improved by simple pre-stretching in chain-extended compounds. Here, we achieve crack propagation in PBS through the vertical tensile of polymer chains. The aligned polymer spherulites induce anisotropy, making the PBS mechanically weaker between the chains due to the low crystallinity, but stronger along the chains due to the preferred orientation of its spherulites. When the polymer is loaded along the aligned direction, pre-existing flaw deflects from its initial direction of propagation run along propagation of the tensile direction, peel off the material and protects the remaining polymer sample [19]. To demonstrate this principle, we prepared a series of modified PBS samples via pre-stretching progress with two-step chain extension. The goal of the research was to improve the toughness performance of PBS via a two-step chain extension using modified polyfunctional epoxy (ADR9) and2,2′-(1,3-phenylene)-dioxazoline (BOZ). We recently developed the two-steps chain extension method utilized ADR9 as the first-step chain extender and BOZ as the second-step entrapping polybutylene terephthalate (PBT) formation of the branched structure to enable excellent mechanical properties and damp-heat aging resistance [20]. In this work, we further improved the mechanical properties of PBS under optimal conditions. On the basis of two-steps chain extension via two different PBS chain extenders, carboxyl addition (ADR9) and hydroxyl addition (BOZ), the transformation of spherulite morphology was studied by uniaxial stretching to different pre-stretch ratios (degree of orientation) at 95 °C (the oriented structure is stable after cooling). Finally, orientated samples with different pre-stretch ratios were obtained and the morphology, crystallinity, and mechanical properties of the PBS samples were investigated by different techniques. Analysis of the integrated performance of PBS is performed and evaluated to determine potential future applications. 2. Materials and Methods 2.1. Materials PBS (1020MD) (MFI = 25 g 10 min−1 at 140 °C, 2.16 kg) was supplied by Showa Denko, Japan. Commercially available ADR-4468 chain extender containing nine epoxy groups (ADR9) with a molecular weight of 6800 g mol−1 was supplied by BASF Corporation, USA. 2,2′-(1,3-phenylene)-dioxazoline (BOZ) as a hydroxyl chain extender was supplied by Tiexi Aicheng Industrial Development Co., Ltd, Shanghai, China. Phenol (CP grade) and 1,1-2,2-tetrachloroethane (CP grade) were provided by Shanghai Sinopharm Groups. 2.2. Preparation of Two-Step Chain-Extended and Pre-Stretched Sample All PBS granules were pre-dried in a vacuum oven at 65 °C for 8 h in order to reduce the possibility of hydrolytic degradation. The PBS and chain extenders were well mixed before adding to a rheometer manual-mixer (RM-200C, Harbin, China). The chain-extended PBS was prepared by melt mixing with ADR9 and BOZ with a rotation speed of 30 rpm. The first step of the PBS (50 g) chain extension modification by ADR9 (0.4 or 0.6 wt%) fed into a rheometer manual-mixer at 140 °C and allowed to react for 3 min and thus prepared are denoted as PBSA0.4 or PBSA0.6. And then the second chain extender BOZ (0.6 or 0.8 wt%) was fed into the mixer containing the PBSA0.6 sample. The two-step chain extension sample was obtained and denoted as PBSA0.6B0.6 or PBSA0.6B0.8 after reacting for 10 min. Afterward, the prepared chain extension samples were injected into plastic molds 75 mm (length) × 4 mm (width) × 1 mm (thickness) in order to obtain the dumbbell-shaped splines, and then uniaxial stretched at 95 °C and pre-stretch ratio (λpre = 1, 3, 5, 7 and 9) prior to unloading. It is not necessary to anneal in order to ensure the crystal structure integrity of the samples. The pre-stretch ratio (λpre) is defined by L1/L0, here L0 =20 mm is the initial length in the sample. After pre-stretching, the length of the sample changed to L1. The samples were released from the extension device to the free state, accompanied by a length change from L1 to L2. L2 was measured after release for 2 days. Compared to the initial state, a fixed stretch ratio exists at the free state, defined as λfix = L2/L0 and shown in Table 1. Significantly, all pre-stretching (λfix = 1, 2, 3…9) samples are based on the two-step chain-extended PBS (the PBS A0.6B0.8 sample). 2.2.1. Mechanical Properties Mechanical testing. Mechanical tests were carried out on dumbbell-shaped samples with the standard tensile machine (GMT4000, Yangzhou, China) with a 10000 N load cell at room temperature. The initial length L0 between the two clamps of the tester was 20 mm and the tensile deformation was performed at a series of stretch velocities ν from 20 to 200 mm min−1, yielding a stretch rate έ = ν/L0 from 0.017 to 0.17 s−1 [21]. The nominal stress σ was estimated from the stretch force divided by the cross-section area of the undeformed sample. Unless otherwise specified, all the testing samples were prepared as dumbbells 75 mm in length, 4 mm wide and 1 mm thick, measured individually for different sample types (e.g., under different λfix). In the test, Wf was defined as the essential work of fracture. The essential work of fracture represents the work at the break region in the integral area of stress–stretch curve. Fracture toughness measurement. Crack propagation of the PBS samples was measured following the notched stretch. The PBS samples were pre-cut by a razor blade with an initial crack 0.2 times its width and then stretched under a strain rate of 0.008 s−1. Fracture toughness Γ was calculated as Γ = W(λc) L0, where W(λ) is the integral of the stress–stretch curve of the uncut sample and λc is the critical stretch when a fast fracture is observed. In the test, λc was defined as the stretch where the stress–stretch curve of the pre-cut sample reaches the peak (the displacement corresponding to the peak force) [19]. Cyclic tensile testing. Cyclic tensile tests were carried out at room temperature on PBS samples with a pre-stretch ratio of λfix = 7. The rate of loading and unloading were 5 mm min−1. The dumbbell-shaped sample was stretched to the set strain rate, then the tensile force was released at the same speed until the sample returned to the initial position. Hence the stretching-unloading process is considered as a cycle, and a series of stress–strain cycle curves were obtained by gradually increasing the tensile strain rate (εn) to n times, and increasing the εn step by step until it exceeded the maximum strain of the sample to failure. The dissipative energy (Un) of each cycle was calculated from the area between the n loading and unloading curves, and the total dissipative energy (Un) from first to n was determined as the superposition of the single dissipation energy of 1–n. The total dissipate energy (Un) and work of tension (Wn) of n times sample stretching-unloading were estimated by the following Equation (1–3) [22]:(1) Un=∫0εnσndε−∫0εnσn’dε (2) Un=∑i=1nUi (3) Wn=Un+∫0εnσn’dε where εn is the nth tensile strain rate, σn is the nth tensile stress, and σ’n is the nth unloading stress. The ratio of dissipated energy to destructive work (U/W) in the destruction process indicates the irreversible work generated by internal failure in the tensile process. The larger the U/W value, the more serious the internal structure damage of the material. 2.2.2. Crystallization Process and Crystalline Structure Characterization Crystallization Process. The non-isothermal crystallization behaviors of the PBS samples were examined by differential scanning calorimetry (DSC) using a (DSC-8000, Perkin Elmer MA, USA) under a nitrogen atmosphere. For as-prepared chain-extended PBS and pre-stretched PBS (λfix), maximizing the formation of further crystalline domains during the tensile induced crystallization. After testing, the sample was sealed in an aluminum crucible (about 4 mg) and tested in the temperature range between 30 °C and 180 °C at a heating and cooling rate of 10 °C min−1 under a nitrogen atmosphere with a flow rate of 30 mL min−1. The peak crystallization temperature was recorded during cooling and identified as the “standard” crystallization temperature (Tc). In order to ensure the crystal structure integrity of the pre-stretched samples, it is not necessary to erase the thermal history except for with virgin PBS. Crystallinity is a mathematical statistics concept expressed as percentage of crystal (χc). It can be calculated from the PBS melt content according to Equation (4), where ΔHm is the melting enthalpy and ΔHm0 is the melting enthalpy of fusion of the complete crystallization equal to 110.5 J g−1 [23]. (4) χc[%]=ΔHmΔHm0×100% X-ray Diffraction Scattering (WAXS and SAXS). Wide-angle X-ray diffraction (WAXS) analysis was measured in a diffractometer at room temperature on a diffractometer (D/max 2500 VB2C/Pc, Panaco Instruments Co., Ltd, Netherlands) with CuKa X-ray radiation and a computerized data collection. The operating conditions of the X-ray source were set to 40 kV and 200 mA in the 2θ scan range of 5° to 90°. The data were normalized with respect to the incident beam intensity in order to correct for primary beam intensity fluctuations. The sample was irradiated with X-rays with a wavelength of 1.542 Å (λ = 0.1542 nm) as the radiation source. Notably, the X-ray profiles were recorded in the meridional direction. The prepared products were made into samples 1 mm thick. Small-angle X-ray scattering (SAXS) patterns were acquired at room temperature, operated with a 0.02 step size of 2θ from 0.5° to 10.0°. The absolute intensity for I(q) was determined using a four slit collimation system and the measurement of absolute intensity was carried out on standard samples. The scattering vector q was defined as q = 4π λ−1 sin θ with 2θ being the scattering angle. Raw SAXS and WAXS pattern data were processed with corrections by mathematic-based JADE software before analysis. 2.2.3. Morphological Characterization Scanning Electron Microscopy (SEM). An SEM (SU8010, Hitachi Limited Co., Ltd, Tokyo, Japan) was used to characterize virgin and pre-stretched PBS sample morphology. Samples were coated with gold before analysis. Electron micrographs were taken with an acceleration voltage of 7.0 kV. In this study, we used concentrated sulfuric acid (30 mL), concentrated phosphoric acid (20 mL) and potassium permanganate (0.2 g) to etch the amorphous regions of PBS to observe its crystal morphology. Polarized Light Optical Microscopy (PLOM). Spherulitic morphologies were observed by PLOM using a (Leica DM2500P, Weztlar, Germany) polarized microscope equipped with polarizers and a sensitive red tint plate (this was employed to determine the sign of the spherocrystal). A British Linkam hot stage connected to a liquid nitrogen system was used to control the temperature. The samples were pressed on a glass slide and covered with a glass coverslip. They were heated to a temperature of 130 °C (above the DSC melting peak). Similar to DSC testing, all samples except pre-stretched samples were kept at this temperature for 10 min to erase previous thermal history. Samples were then quickly cooled to the selected crystallization temperature 80 °C for 10 min to allow the crystals size to grow fully. Micrographs were taken with a Leica DC420 digital camera. 2.2.4. Rheological Analysis Rotational rheometer. The rheological behavior of PBS samples was investigated at 140 °C in dynamic mode using a rotational rheometer (DHR-2, TA-2 Instruments company, USA) with a parallel-plate (25 mm in diameter with a gap of 1.0 mm). The complex viscosity (η*), storage modulus (G′), and loss modulus (G″) were monitored at various frequencies. The frequency range was 0.1~100 rad s−1, and the maximum strain was fixed at 0.5% to ensure that these analyses were within the linear viscoelastic region under nitrogen. The real shear rates and zero-shear-viscosity were calculated using the Carreau-Yasuda model. 2.2.5. Infrared Spectroscopic Analysis FT-IR Analysis. FT-IR spectra were recorded at 25 °C and then subjected to thin film analysis using a Fourier-transform infrared spectrometer (Vertex 70, Bruker, Germany). The spectra were recorded in absorbance mode with a spectral resolution of 2 cm−1. PBS thin films were laid on a zinc selenium disk. Each spectrum was obtained within the range of 4000 ~ 500 cm−1. 3. Results and Discussion 3.1. The Influence of Chain Extension Reaction on PBS PBSA0.6 and PBSA0.6B0.8 polymers were produced via chain extension of PBS–COOH with PBS–OH using ADR9 and BOZ as two-steps chain extenders at 140 °C for 15 min. The possible mechanism diagram is illustrated in Figure 1. In our previous work, we modified PBT with chain extenders ADR9 and BOZ [20]. The epoxy multifunctional groups react to have higher activity with carboxyl groups. The epoxy functional groups of ADR9 can be applied to the linear polymer chain of PBS to generate a product that includes a large number of short-branched chains. This product will form part of the hydroxyl groups which will react with BOZ, forming a kind of polymer with a long-branched, star-like molecular chain structure, which has high mechanical properties as well as processability. We performed a series of measurements to demonstrate the effectiveness of the chain extension reaction in PBS. Gel fraction (GF) characterizes the degree of cross-linking and carboxylic terminal concentration group (CTCG) characterizes the degree of PBS–COOH or PBS–OH consumption during the chain extension reaction. These measurements are the most direct evidence for the chain extension reaction of PBS. It can be seen from Figure 2a, the GF of PBSA0.6 and PBSA0.6B0.8 samples increased with single component chain extension and collaborative chain extension. The GF of PBSA0.6B0.8 was 1.61%, which was not shown to have significantly affected the machining performance of PBS during the chemical chain extension reaction progress. The CTCG decreased to 28.2 mol t−1 for PBSA0.6B0.8 samples compared with 37.4 mol t−1 for virgin PBS samples. These results show that the end group (–OH and –COOH) concentrations of PBS were consumed by chain extension. Low-gel (low-crosslinked) content resulting from chain extension reactions often results in high mechanical properties. As shown in Figure 2b, the tensile strength of PBSA0.6B0.8 increased from 32.5 MPa (virgin PBS) to 45.1 MPa, while the elongation at break increased to 484%. Molecular weight is closely related to viscosity; therefore, we measured the characteristic viscosity and average molecular weight of the polymer via Ubbelohde viscometer. Intrinsic viscosity ([η]) characterizes the branching and coupling of the molecular chain and the average molecular weight ([Mη]) describes the change in the molecular weight after chain extension. Figure 2c shows that the intrinsic viscosity of PBSA0.6B0.8 increased from 0.71 dL g−1 to 1.19 dL g−1 compared with unmodified PBS, while the average molecular weight increased to approx. 40,000 g mol−1. These results indicate both ADR9 and BOZ were effective chain extenders for PBS. The relationship between complex viscosity (η*) and angular frequency is shown in Figure 2d. Table S1 show shear thinning behavior occurred in the high frequency range. Compared with virgin PBS, the viscosity of the system increased after chain extension. Identical conclusions were obtained in infrared spectroscopic analysis shown in Figure S1. The observed variations confirm the occurrence of chain extension reaction between PBS and the chain extenders. We used DSC to measure the crystallization behavior of PBS before and after chain extension, shown in Figure 2e,f. The relevant data are presented in Table S2. The crystallization temperature decreased with chain extension progress while the melting temperature increased. Moreover, after chain elongation, the regularity of chain segments increases, resulting in entanglement between chain segments at the molecular level for the gradual increase in crystallinity. To further elucidate the rheology character of PBS samples in a large angular frequency range [24], we used time temperature equivalence shift (TTS) data to obtain a wider η* range and G′ and G″ curves in Figure 2g,h and Figure S2. Equation and method details can be found in the Supplementary Information. The Carreau-Yasuda model was used to fit the virgin PBS viscosity curve resulting in λ = 3.49 s and η0 = 515 Pa s. The modified Carreau-Yasuda model represents the best fit for the viscosity function of long-chain branched PBS-ADR9/BOZ samples. Two characteristic relaxation times were determined: λ1 = 9.21 s, λ2 = 0.5 s, and η0 = 1482.78 Pa s. These results show the long-chain branched structure formed after the two-step chain extension relaxation time was reduced. According to the analysis above, the addition of chain extender effects the molecular chain structure. To achieve a better understanding of how the chain extension reaction affect the crystal structure of PBS, Figure 2i illustrates the WAXS diffraction pattern of the samples. The samples show peaks at 2θ = 19.7° and 22.6°, corresponding to the diffraction peaks of the (320) and (130) crystal planes, respectively. The results of DSC and WAXS show that the crystal structure of PBS was not changed by chain extension. 3.2. The Energy Release Rate of PBS Samples The energy dissipation mechanism of PBS can be further analyzed by studying the relationship between dissipated energy U and strain εn, and the relationship between U/Wt and strain εn. We used dumbbell-spline samples and performed cyclic tensile tests on both notched (Figure 3a,b) and unnotched samples (Figure S3a,b). In this research, the excellent mechanical performance of these PBS samples were closely related to the effective energy dissipation, which can be demonstrated by hysteresis of the loading−unloading curves of the samples stretched to different maximum strain ε1, ε2 … and ε5. As shown in Figure 3, large hysteresis was observed during the loading−unloading process of the chain extension sample, indicating the distinctive energy dissipation through the destruction of the interior structure under loading. The ratio of dissipated energy (energy release rate U1, U2 … and U5) and tensile failure work in the failure process (U/Wt) was calculated as Equation (1 ~ 3). As εn increased from 5% to 30% of the chain extension sample, U increased from 0.15 to 1.9 × 106 J m−2, while the dissipated energy U of pristine samples increased from 0.1 to 1.0 × 106 J m-2 as εn increased from 2% to 22%, indicating that compared with the virgin sample, the gradual fracture of the internal structure of the reinforced sample requires more dissipate energy due to its high degree of molecular chain entanglement and branching. The curve of dissipated energy to tensile work U/Wt shows a near linear relationship, indicating the continuous structural destruction of the PBS during the cyclic loading−unloading process. 3.3. Characterization of the Crystalline Morphology in PBS Samples We use the chain-extended sample (λfix = 1) and then pre-stretched them in a drying oven (accessories are provided by universal tensile testing machine) at 95 °C. Higher toughness of chain-extension modified PBS allows the modified sample to have a higher pre-stretching ratio than virgin PBS. As shown in Figure 4a and b (quantitative data are shown in Table S2) both the pre-stretching and virgin PBS show distinctly endothermic peaks, with measured crystallinities of 35.6 (virgin PBS), 41.2 (λfix = 3) and 43.3 wt% (λfix = 5), respectively. Moreover, when the higher pre-stretching PBS is λfix = 7, the crystallinity of PBS increased to 45.7 wt% (Figure 4c). The increased crystallinity implies more crystalline domains nucleate during the chain extension reaction and pre-stretching process [25]. The crystallinity gradually increased further by increasing the pre-stretch ratio. When the sample was pre-stretched for λfix = 9 at 95 °C, the crystallinity reached 47.6 wt%. During the pre-stretching process, on account of the change of crystalline morphology of the polymer, the amorphous part undergoes stress-induced crystallization along the stress direction. To further elucidate the change of crystalline morphology, we measured the average distance between adjacent crystalline domains d using SAXS and average crystallite sizes perpendicularly across the planes D using WAXS. SAXS measurements on samples of pre-stretching PBS measured the scattering intensity [I (q)]2 versus the scattering vector q shown in Figure 4d, there is no other peak in the plot of intensity [I (q)]2 versus the scattering vector q for the PBS samples (Figure S4), which implies that neither the chain extension reaction nor the pre-stretching of PBS crystal generate a new crystal structure on the basis of the original PBS crystal morphology. The average distance between adjacent crystalline domains d can be calculated from the critical vector corresponding to the peak intensity qmax, following the Bragg expression in Equation (5) [26]. (5) d=2π/qmax To achieve a better understanding of the crystal morphology of PBS, we perform WAXS measurements on various PBS samples shown in Figure 4e, the corresponding diffraction peaks have strikingly different positions, distributions, and intensities of the (320) and (130) crystal planes and amorphous halo, respectively. As can be seen from Figure 2i and Figure 4e, the crystal structure of PBS is monoclinic crystal system, and its lattice parameters (β crystalline form) are as follows: a = 0.523 nm, b = 0.908 nm, c = 1.079 nm, and β = 123.78° [26]. In addition, small peaks at 2θ = 28.5° and 33.1° are also observed in the PBS samples. It is seen in Figure S4 that the positions of the diffraction peaks of the samples did not change as the pre-stretching ratio was increased, indicating the crystal form of the samples had not changed. By identifying the half width of the maximum diffraction peak β, the average crystallite sizes perpendicularly across the planes D can be approximated using Scherrer’s Equation (6) [27], (6) D=kλβcosθ where k is a constant varying with the actual shape (is related to FMHM) of the crystalline domain, λ is the wavelength of x-ray diffraction (1.542 Å), and θ a half of testing angle (2θ) from (hkl) plane. Here, β is the FMHM of the measured sample (double-line correction and instrument factor correction must be performed in radian), and the dimensionless shape factor k is set as 1, approximating the spherical shape of the crystalline domains. The average crystallite size is spread perpendicularly across the planes (Dhkl). As shown in Figure 4f, by increasing the pre-stretch ratio from 1 to 9, the Dhkl decreased from 17.1 to 11.2 nm. This trend is consistent with the increase of Dhkl with different pre-stretch ratios, because orientation promotes the refinement of the crystal domain and induces crystallization for the amorphous polymer chain. Compared with the virgin PBS, the pre-stretched samples had a smaller average distance between adjacent crystalline domains d and average crystallite size perpendicularly across the planes D, and contains more crystals per unit volume (Figure 4d inset). As shown in Figure 4f, the average distance between adjacent crystalline domains for the λfix = 1 was calculated to be 45.2 nm in the chain extension state. As the pre-stretch ratio increased to 9 (λfix = 9), d increased to 53.5 nm. As a control case, we also measured SAXS profiles of the pristine sample (virgin PBS). The value of d in virgin PBS was approx. 30 nm, smaller than the distance in the pre-stretched sample (48 nm). These results indicate that in the process of stretching, the amorphous polymer chains and the crystal region of the polymer extend in the orientation of the stretching direction, resulting in crystal refinement and increasing the average distance between adjacent crystalline domains. The PBS spherulites deform and orientation along the stress direction, resulting in reduction of average crystal size. With the crystalline morphology changes along the stretching direction the regularity of chain segments increases by high orientation, there are more oriented crystals per unit volume, which improves the crystallinity of the sample, which is also confirmed in the crystallinity test results of DSC in Figure 4a,b. PLOM was used to obtain phase images of the pristine sample and the pre-stretched samples. As shown in Figure 4g, large and clear spherulites morphology domains were observed in the pristine samples, while the pre-stretched sample shows thick and thin “stripes” in the crystalline domains. The phase images show that compared with the pristine sample, the crystal morphology of the pre-stretching sample was transformed from spherulite shape to elliptic crystal or extend-chain crystal. 3.4. Characterization of Flaw Sensitivity Properties of PBS We used the single-notch method widely used in fracture tests to measure the flaw sensitivity of PBS. Notably, all fracture toughness tests in this study were performed on pre-cut samples with an initial crack 0.2 times its width. We tested the flaw sensitivity of both before and after chain-extended PBS samples by cutting an initial flaw ~0.8 mm on the edge of each sample, and uniaxially stretching the sample. In virgin PBS, the flaw quickly fractured throughout the entire sample once the sample stretching started (Figure S5 and Movie S1 ). In contrast, the crack propagation occurred along the loading direction in the chain extension sample with λfix = 1, leaving the sample fractured by crack propagation at a larger displacement. The low molecular weight part of PBS molecular chain decreased as a result of chain extension, which led to a decrease in notch sensitivity. The degree of anisotropy in PBS was tunable by the pre-stretch λfix. For all chain extension samples with different values of λfix, we observed a strengthened stress–stretch curve in the tensile direction. With chain extension in PBS and mechanical fixed λfix, the tensile strength of the PBS sample increased by nearly 6 times reaching up to 185 MPa for 1 day fixed after pre-stretching in the stress–stretch curve (Figure 5a). By contrast, the stress–stretch curve of virgin PBS increased 4 times (Figure S6a). Work of tension (Wc) is an important parameter to characterize material toughness and is calculated from the integral area under the stress–stretch curve of uncut samples. Sample work of tension reached 1.8 × 108 J m−3, which was higher in toughness than the 1.6×108 J m−3 in virgin PBS (Figure S6b). Characterizing the degree of anisotropy in terms of the fracture toughness when λfix > 2.0, the material is anisotropic and the crack will propagate along its initial direction under uniaxial loading. When the fracture toughness of the material is approaching 106 J m−2 (λfix = 5), the sensitivity of a soft, elastic material to flaw can be estimated by a critical length scale Γ/Wc, where Wc is the work to rupture measured with no or negligible flaw. The elastic-toughness sample during its first-time loading had Γ ≈ 106 J m−2 and Wc ≈ 108 J m−3, leading to a critical flaw sensitivity length scale of Γ/Wc ≈ 0.01 m. In comparison to the without chain-extended PBS sample, Γ ≈ 2 × 105 J m-2, Wc ≈ 108 J m−3, and Γ/Wc ≈ 0.002 m (Figure S6d). As the pre-stretch ratios increased, the flaw sensitivity critical length further increased. In particular, for the pre-stretch ratio 7 (λfix = 7), the flaw sensitivity critical length achieved 0.02 m. These results show the flaw sensitivity of PBS decreased after chain extension, indicating that pre-stretching improves the orientation of molecular chains, and the interaction between molecular chains is increased by increasing crystallinity. The chain-extension samples suffer a toughness fracture and gradual crack extension from an initial flaw under uniaxial tension. In addition to flaw sensitivity and stretch toughness tests, we also measured nominal stress versus stretch curves of all PBS samples to obtain their Young’s moduli and tensile strengths shown in Figure 6a,b, both the Young’s modulus and tensile strength increase with pre-stretching and show marked enhancements when the pre-stretching state reached λfix = 5. Compared with the pristine sample, the Young’s modulus and tensile strength of the chain-extension reinforced sample (λfix = 5) increased from 220 MPa up to 320 MPa and from 125 MPa up to 179 MPa, respectively. The notion of flaw sensitivity applies to all materials. We collected data of fracture toughness Γ and work of tension W of various materials, e.g., ceramics, polymers, biomaterials, metals, etc. [28] We plotted the data for various materials in a material space with W and Γ as coordinate axes (Figure 7). This serves to show that the length of flaw sensitivity has a large range, from nanometers for brittle materials to centimeters for tough materials. For non-inorganic materials like silica glass and alumina, measuring the fracture energy in the small-flaw limit is a difficult laboratory experiment and relative results are rarely reported because the small-flaw limit rupture of the cracks approach an infinitesimally tiny size (<10−12 m) [28]. By contrast, for elastomers or high toughness materials (e.g., polyethylene and natural rubber) and gels, the small-flaw limit is readily reached when the cracks are below millimeters. In practice, tough materials and gels can work in the small-flaw limit, the large-flaw limit, and anywhere in between. As we have commented before, the scatter of the rupture data measured using uncut samples is large for brittle hard solids, but small for tough materials and gels. In this work, the length of flaw sensitivity Γ/W of the strong and tough PBS is higher after chain extension and pre-stretching process. 3.5. Spherulite Morphology and Crystal Structure Orientation has a significant effect on spherulitic morphology and spherulite size of crystalline aliphatic polyesters. As mentioned above, orientation has an effect on crystallization. Here, the effect of chain extension with pre-stretch on crystalline morphology was studied using PLOM. Both the spherulite morphologies of virgin PBS polyesters formed at the 75 °C crystallization temperature and the spherulitic morphologies of the pre-stretched state (with chain-extension) are shown in Figure 8, the virgin state and the self-nucleation process see Figures S7 and S8. The characteristic “Maltese Cross” extinction patterns of banded spherulites were observed despite the different states (virgin PBS and λfix = 1). The spherulites of virgin PBS show the spherulite diameter is about 50 μm before the spherulites impinge with each other. Nonetheless, the pre-stretching (λfix = 1) state developed negative spherulitic superstructural aggregates that resemble those of virgin PBS, but exhibit irregular edges (not perfectly circular). It is clear that the size of the spherulites shrunk, and the number of spherulites increase with chain-extension. These results show the difficulty of nucleation because of the molecular chain extension and increased degree of branching. As the pre-stretch ratio increased, the polyesters show deformation of spherulites (λfix = 3). To determine the change of the samples from folded-chain crystal (FCC) to extended-chain crystals (ECC) along the stretching direction were measured based on the condensed state. As shown in Figure 9, these crystalline morphology changes from FCC to ECC mechanism should influence the stretching scaling relationship. Through uniaxial stretching, we noted that the crystal morphology also deforms along the stress direction (by PLOM). It is further assumption that the crystalline morphology changes from FCC to ECC along the stretching direction. We carried out preliminary research on orientation of the crystalline regions using Raman spectrometry to analyze samples with different stretching ratios (λfix = 1 and 9, Figure S9). From the point of view parallel to the orientation direction (ZZ) and perpendicular to the orientation direction (XX), except that the peak intensity of 1720 cm−1 is the same, the residual peak strength ZZ is greatly increased compared with XX. It shows that the anisotropy of the crystal is obviously enhanced after the sample is taken. Comparing ZZ and XX, after applying vertically polarized light to the sample, the C-O-C peaks corresponding to 950, 1091 cm−1 and 1471, 1431 cm−1 of the sample have obvious changes and Raman shifts. Our research on orientation by 2D WAXS and related follow-up experiments are being carried out. Some spherulites are initially stretched into FCC (λfix = 5), and finally aligned into regular and complete ECC along the stretching direction. A more systematic study refers to the methods in the reference according to Michel levy diagram [35] on the mechanism of crystalline morphology transition is ongoing. In addition, under the action of tensile stress, PBS samples are inclined, slipped and twisted to form crack chains under high orientation (λfix = 9), and the original spherulite structure is destroyed forming a “microfilament crystal” structure. Results of PLOM and SAXS are consistent with the significant influence of orientation on PBS spherulites. Tensile orientation has a significant effect on spherulitic deformation of PBS, which is consistent with the results of PLOM and SAXS. In order to further observe the morphology of PBS, the effect of orientation on the crystal structure of PBS was observed by SEM. As shown in Figure 9, the spherulite structure is obvious in virgin PBS (a—i) and chain-extended PBS (b—i). The spherulite size decreased after chain extension with the former measuring approx. 50 μm, while the latter is approx. 40 μm. Similar crystal orientation structure was also observed in (a)—(i–viii) and (b)—(i–viii) images. With the increased degree of orientation, a fibrous crystal morphology was observed (λfix = 9). 4. Conclusions In summary, we have described a principle of flaw-insensitive materials under chain-extension and load through crack propagation. This work analyzed the flaw sensitivity of stretchable and high toughness materials. We measured work of tension W using uncut samples and fracture toughness Γ using samples containing large cuts (0.2 times its width). We identified a length of flaw sensitivity Γ/W. We have also proposed that the design principle for fracture toughness materials is to make the crack fracture of chain-extended PBS requiring energies per unit area much higher than that for fracturing a polymer chain of virgin PBS. We have demonstrated that the fracture toughness can be greatly enhanced by designing pre-stretch orientation in chain-extended PBS samples. We further confirmed the average size of crystalline domains decreased while the average distance increased with the tensile orientation process. The reported mechanism and strategy for designing anti-fracture and low flaw sensitive PBS can enhance the fracture toughness performance of PBS making a number of future research directions of the extrusion product applications possible. Acknowledgments The authors acknowledge with gratitude the support from the National Natural Science Foundation of China (NSFC) (Contract no. 52073083) and from the Open Fund of Hubei Provincial Key Laboratory of Green Materials for Light Industry (Contract no. 202007A01). We thank the associate/chief editor and the reviewers for their useful feedback that improved this paper. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/polym14091876/s1; Figure S1: FTIR spectrum of PBS and chain-extended PBS samples (a) a hydroxyl vibration region from 3460 to 3420 cm−1; (b) from 3000 to 600 cm−1; Figure S2: The relationship of angular frequency and storage modulus (a) and loss modulus (b) at 150 °C. Figure S3: The notch tensile stress–stretch curves of (a) virgin PBS and (b) chain extension state under uniaxial forces (λfix = 7). Stretch virgin PBS and chain-extended PBS samples in cycle five times before the maximum critical strain λc, and recorded as ε1, ε2 … and ε5. Figure S4: Representative SAXS profiles of various pre-stretching states, with pre-stretch ratios. Figure S5: The notch tensile stress–stretch curves of (a) chain extension state and (b) virgin PBS under uniaxial forces. The notch is 0.2 times the width of the entire sample (0.4 mm). Figure S6: The effect on the crack propagation prescribed by λfix of virgin PBS. (a) The stress–stretch curve and the stretch rate from 25 to 100 mm min−1 under uniaxial forces. (b) The work of tension W of the sample was the integral of stress–stretch curve with pre-stretch ratio of λfix = 1, 3, 5 and 7. (c) The relationship between the fracture toughness Γ and pre-stretch ratio of λfix = 1, 3, 5, and 7. (d) The critical flaw sensitivity length scale Γ/W of the sample, and it becomes lower notch sensitivity with increasing λfix. Figure S7: Polarized light optical micrographs of the pre-stretching samples. The virgin PBS was cooled from the melt (at 130 °C) and held at 75 °C for 15 min. Micrograph of its surface taken after the sample in the pre-stretch state, λfix = 1, 3, 5 and 7. The scale bar is 10 μm. All the samples were oriented with pre-stretch at 95 °C. Figure S8: Representation of the crystal-growth domains for the PBS chain extension sample (λfix = 1) on top of the standard DSC melting trace. Insets include PLOM micrographs taken during cooling at T = 75.5 °C (domain II, the annealing time for 10 min) and heating at T = 118.6 °C (domain III, the annealing time for 10 minutes). Figure S9: Raman spectra of PBS films oriented by polarization. (a) pristine sample (λfix = 1); (b) pre-stretched sample (λfix = 9). Table S1: Mechanical properties and Carreau-Yasuda model constants for PBS and PBS composites; Table S2: Parameters of PBS and PBS composites obtained from non-isothermal crystallization at a cooling rate of 10 °C min−1; Video S1: The notched tension of the virgin sample and the chain extension sample. Click here for additional data file. Author Contributions Conceptualization: X.L. (Xun Li) and X.L. (Xuefeng Li); methodology: X.L. (Xun Li), C.H. and S.L.; software: X.L. (Xun Li), X.D., R.L., Y.L. and Y.H.; validation: X.L. (Xun Li), M.X. and X.L. (Xuefeng Li); formal analysis: X.L. (Xun Li), investigation: X.L. (Xun Li) and X.L. (Xuefeng Li); resources: X.L. (Xuefeng Li); data curation: X.L. (Xun Li) and X.L. (Xuefeng Li); writing—original draft preparation: X.L. (Xun Li) and X.L. (Xuefeng Li); writing—review and editing: X.L. (Xun Li); visualization: X.L. (Xun Li); ve read and agreed to the psupervision: X.L. (Xun Li); supervision: X.L. (Xun Li); project administration: X.L. (Xuefeng Li); funding acquisition: X.L. (Xuefeng Li) All authors haublished version of the manuscript. Institutional Review Board Statement Institutional review board approval of Hubei Provincial Key Laboratory of Green Materials for Light Industry was obtained for this study. Informed Consent Statement All authors involved in this study gave their informed consent. Data Availability Statement The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study. Conflicts of Interest The authors declare no competing financial interest. Figure 1 Mechanism diagram of collaborative chain extension of PBS. Figure 2 Measurement of two-steps chain extension factors of PBS. (a) Variation of gel fraction and carboxyl group content of PBS samples. (b) The tensile strength and elongation at break of chain-extended PBS were obtained at a rate of extension of 20 mm min−1 at room temperature. (c) Intrinsic viscosity and average-molecular weight of PBS samples. Non-isothermal crystallization curves for PBS samples at 140 °C. (d) Double logarithm diagram of complex viscosity changing with angular frequency at 150 °C and 1 ~ 100 rad s−1. (e) Cooling curve (10 °C min−1), (f) heating curve (10 °C min−1). Viscosity function (η*), storage (G′) and loss modulus (G″) of (g) virgin PBS and (h) long-chain branched PBSA0.6B0.8 with best fits based on the Carreau-Yasuda model. Detailed measure methods can be found in the Supplementary Information. (i) WAXS patterns of PBS samples by fitting in Jade with 2θ from 5° to 90°. Figure 3 Cyclic tensile and energy release rate of PBS samples. Hysteresis curves of virgin samples (a) and chain extension states (b) with various strains and cyclic tensile loading–unloading curves. Virgin PBS and chain-extended PBS samples were stretched five times in cycles before the maximum critical strain εn, recorded as ε1, ε2 … and ε5. The corresponding dissipated energy (U) of one loop at different maximum strain εmax, recoded as U1, U2 … and U5. The relationship between the ratio of dissipated energy to tensile work U/Wt and strain of the virgin state (c) and chain extension state (d). The loading and unloading stretch rates were 5 mm min−1. Figure 4 Characterization of crystalline domains in PBS. (a,b) Representative DSC curves for crystallization and melting of the various pre-stretching states, with pre-stretch ratios. (c) Measured crystallinity in virgin PBS, chain-extended PBS and pre-stretching states with pre-stretch ratios. (d) SAXS profiles of the pristine sample and the pre-stretching sample with qmax values extracted from the [I(q)]2 ~ q curve. (e) Representative WAXS profiles of virgin PBS and various pre-stretching states with pre-stretch ratios of λfix = 1, 3, 5, 7 and 9. (f) Estimated the average distance between adjacent crystalline domains d and average crystallite sizes perpendicularly across the planes D of pre-stretching states with pre-stretch ratios. (g) PLOM phase images of the pristine state and the pre-stretching state (scale bar = 10 μm). Figure 5 The analysis of the effect on fracture toughness prescribed by λfix of chain-extended PBS. (a) The stress–strain curve shows the sample becomes stiffer in the aligned direction with increasing λfix. (b) The work of tension W of the sample is the integral of stress–strain curve with a pre-stretch ratio. (c) The relationship between the fracture toughness Γ and pre-stretch ratios. (d) The critical flaw sensitivity length scale Γ/W of the sample becomes a measure of lower notch sensitivity with increasing λfix. (e) The PBS samples was pre-cut with an initial crack 0.2 times the width of the sample. An initial flaw (≈ 0.8 mm) in an unaligned pristine sample quickly propagates throughout the sample once the tensile spline is stretched, while the chain extension sample is slowly pulled apart. The notched tension of the virgin sample and the chain extension sample (λfix = 1) can be observed in Movie S1. Figure 6 The Young’s moduli and tensile strengths of PBS samples. (a) Young’s moduli and tensile strength versus fixed stretch (λfix) in virgin PBS. (b) Young’s moduli and tensile strength versus fixed stretch (λfix) in chain-extended PBS. Figure 7 A space of material properties with fracture toughness Γ and the work of tension W on the axes. Also included are the slashes of constant values of the length of flaw sensitivity Γ/W. The stretchable materials in the current work are compared with other materials, e.g., natural rubbers [29,30], polyacrylamide hydrogels [30], alginate hydrogels [30,31], and tough hydrogels, [32,33], as well as steel, aluminum, bone, human skin, acrylic glass, epoxy, aluminum oxide, and silica glass [34]. Figure 8 Polarizing microscope analysis of stretch oriented samples. Polarized light optical micrographs of the pre-stretched samples. (a) Micrograph of the sample surface taken in the pre-stretching state. The scale bar is 10 μm. All the samples were oriented with pre-stretch at 95 °C. (b) After uniaxial stretching, the crystal deformation and molecular chains are disentangled, and the molecular chains show anisotropy along the stretching direction. Figure 9 Scanning electron microscope analysis of orientated PBS before and after chain extension. The surface of virgin PBS (a)—(i–viii) and chain-extended PBS (b)—(i–viii) has as oriented spherular structure, (i) uniaxial tensile orientation diagram, (ii–iii) PLOM of spherulite structure change after crystal orientation, (iv) structural diagram of the fibrous crystal. polymers-14-01876-t001_Table 1 Table 1 Sample type, name abbreviation, and characterizations. Sample Code Chain Extension for PBS a) Pre-Stretching b) PBS ADR9 BOZ λ pre λ fix ε (%) L0 (mm) Virgin PBS 100 0 0 1.2 1 120 20 PBSA0.4 99.6 0.4 0 3.2 3 320 20 PBS A0.6 99.4 0.6 0 5.3 5 530 20 PBS A0.6B0.6 98.8 0.6 0.6 7.5 7 750 20 PBS A0.6B0.8 98.6 0.6 0.8 9.8 9 980 20 a) Samples names correspond to the mass ratio (wt%) of ADR9 (A) and BOZ (B). b) All pre-stretching samples are based on the two-step chain-extended PBSA0.6B0.8. 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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/ijerph19095028 ijerph-19-05028 Article Healthy Community-Life Circle Planning Combining Objective Measurement and Subjective Evaluation: Theoretical and Empirical Research Wan Jiangjun 1† Zhao Yutong 1† Zhang Kaili 1† https://orcid.org/0000-0002-5852-8022 Ma Chunchi 2* Sun Haiying 1 Wang Ziming 1 Wu Hongyu 1 Li Mingjie 1 https://orcid.org/0000-0002-1204-6917 Zhang Lingqing 1 Tang Xiaohong 1 Cao Ying 1 Tang Li 1 Yang Jinxiu 3* Tchounwou Paul B. Academic Editor 1 School of Architecture and Urban-Rural Planning, Sichuan Agricultural University, Chengdu 611830, China; wanjiangjun@sicau.edu.cn (J.W.); 201608383@stu.sicau.edu.cn (Y.Z.); 2019225001@stu.sicau.edu.cn (K.Z.); lijia@stu.sicau.edu.cn (H.S.); 2020425034@stu.sicau.edu.cn (Z.W.); 201808259@stu.sicau.edu.cn (H.W.); limingjie@stu.sicau.edu.cn (M.L.); 41360@sicau.edu.cn (L.Z.); 41344@sicau.edu.cn (X.T.); yingcao@sicau.edu.cn (Y.C.); 201708620@sicau.edu.cn (L.T.) 2 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China 3 School of Economics, Sichuan Agricultural University, Chengdu 610101, China * Correspondence: machunchi17@cdut.edu.cn (C.M.); yangjx@sicau.edu.cn (J.Y.) † These authors contributed equally to this work. 21 4 2022 5 2022 19 9 502813 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: The world faces vast health challenges, and urban residents living in high-density areas have even greater demand for healthy lifestyles. Methods: Based on the data of points of interest, a field survey, and an interview, we explored the healthy community-life circle in the downtown area of Chengdu, China from two perspectives: objective measurement and subjective perception of residents. We evaluated the coverage rate and convenience in accessing eight types of health service facilities within a 15-min walk using linear and logistics regression models to explore the degree of resident satisfaction with facilities and influencing factors. Results: Results showed significant differences in coverage rates between different districts. The overall convenience in accessing health service facilities decreased gradually from the city center to the outskirts. The social environment, the layout of health service facilities, and residents’ travel habits were related to health service facility satisfaction. Results also showed significant differences in various facilities’ accessibility satisfaction between objective measurement and residents’ perception measurement. Compared with subjective measurement, the objective measurements of accessibility for sports venues (objectively measured average minus perceived average: −1.310), sports zones (−0.740), and specialized hospitals (−1.081) were lower; those for community hospitals (0.095), clinics (1.025), and pharmacies (0.765) were higher; and facility accessibility measured by subjective perception had a more significant impact on health facility satisfaction. Pharmacies (OR: 1.932) and community hospitals (OR: 1.751) had the largest impact among the eight types of facilities. Conclusion: This study proposed to construct a healthy community-life circle with a category and hierarchy system. fitness medical and health POI ==== Body pmc1. Introduction In the 21st century, the population is continuing to increase rapidly, and the speed of urbanization is accelerating. According to the United Nations Population Division statistics, the global population in 2019 reached 7.7 billion [1], an increase of 1.7 billion since 2000. The world faces huge health challenges, including health equity, obesity, and disease; unhealthy diet; lack of exercise; and other issues [2], forcing people to think repeatedly about preventive, healthy lifestyles. Since the outbreak of the COVID-19 epidemic, many countries have adopted measures to restrict residents’ travel and range of activities to prevent the spread of the virus [3], increasing the demand and willingness to improve health service facilities in the community and surrounding areas. According to the World Health Organization’s latest statistical report 2021, the Universal Health Coverage Service Index increased from a global average of 45 (100) in 2000 to 66 in 2017, indicating that more and more people can access high-quality health services without financial difficulties. However, as a special public event, the emergence of COVID-19 and policy control has posed major challenges to the planning and management of urban health service facilities. Physical activity is always an effective means to maintain health, but studies have shown that global physical activity levels have not improved since 2001. In 2016, over a quarter (1.4 billion) of the world’s adult population was physically inactive, putting it at risk of noncommunicable diseases and premature death [4]. Lack of physical activity causes 5.3 million deaths every year globally, and the COVID-19 pandemic has further frustrated the slow-moving work of promoting sports activities of global residents [5,6]. Some scholars have pointed out that the government must promote physical activity as a basic human need beyond and independent of COVID-19 [4]. As residents have increasingly demanded physical exercise, they have also paid more attention to the surrounding medical service facilities. Accessibility and quality of nearby medical treatment have become critical criteria for residents to measure the community space and management level [7]. At the same time, achieving equitable access to health care is an essential embodiment of social equity [8]. In response to the COVID-19 epidemic, temporary hospitals were built to treat severe patients in many Chinese cities, which played a huge role in China’s rapid control of the spread of the epidemic. Thus, medical and health facilities play a decisive role in health emergencies. Therefore, rational layouts and availability of spaces for fitness activities and health care facilities are critical in the fight against various urban disasters and public health emergencies and have great significance for improving the health level of the world’s public [9]. The health of the community has become one of the most critical issues for governments in formulating public health and planning policies in metropolitan areas [10]. The World Health Organization was the first to put forward the concept of a “healthy community”, which extends the concept of health to the whole community. All community organizations can cooperate to improve the quality of life of all residents. To date, the research on healthy communities has focused only on evaluation index systems and standards of healthy communities; design and construction strategies for healthy communities; the participation of residents in the construction of healthy communities; and the governance model and management systems for healthy communities. The research on health-related service facilities has focused on their geographical distribution, but these models have largely reflected previous planning layouts. Although the needs of residents have been considered from the regional population scale, the rational layout of the life circle has seldom been made from the actual perception and evaluation of residents. Following the concept of the healthy community, the idea of 15-min community-life circles was proposed. The Japanese government first proposed the concept of a “community residential area”, which refers to an area within a radius of 1000–2000 m, a 15-min walk from the residential center, where residents can obtain their daily needs [11]. The concept later developed into a “community-life circle”, introduced to China in the early 1990s. In recent years, cities such as Beijing, Shanghai, and Hangzhou have announced the establishment of 15-min community-life circles. The 15-min community-life circle is the space, centering on a person’s residence, in which they carry out various daily activities, including shopping, leisure, medical visits, education, employment, commuting, and other life-related services, which emphasizes walking as the transportation mode [12]. The new urbanism proposed in the 1990s also combined the elements of traditional housing design in walkable and mixed-use blocks instead of the typical low-density and curved-street layout of traditional suburbs. Research on the community-life circle has focused mainly on the configuration of public service facilities. The coverage rate [13], compliance rate [14], completeness and quality [15], and travel accessibility of various public service facilities on residential land in the community have been taken as indices [16,17,18,19]. Various public service facilities were analyzed using quantitative point of interest (POI) and geographic information system (GIS) approaches [20]. In studies on the optimal configuration of the 15-min community-life circles, community-life circles have usually been divided based on streets, administrative boundaries, and community buffer zones formed by people walking for 15 min. Most studies have used methods such as the standard deviation ellipse, the minimum convex polygon, and nuclear density analysis. However, these methods and standards for demarcating boundaries have some problems. They cannot reflect the actual 15 min community-life circle range of residents [21]. For community-life circle studies, the main focus has been on configuring comprehensive public services within community circles. Although some special studies on medical and health facilities and sports, leisure, and fitness activities have been conducted, the research focusing on healthy community-life circles is still relatively weak. Some of this research has been limited to the macro level, without considering the needs of different residents. The fitness facilities are known as health promotion services and resources include green parks and squares, sports venues, and sports zones, which provide people with opportunities to exercise and improve their health. The most important resources for health protection are medical and health facilities. Primary health care is the first point of entry between patients and the health system. Thus, strengthening primary health care at the community level is key to achieving universal health coverage. Scholars have conducted relevant research on all of these facilities. Most research has focused on assessing the accessibility, availability, and fairness of parks and squares, fitness facilities, and medical facilities at all levels [22,23,24]. GIS tools and two-step floating catchment area methods are often used to analyze and improve evaluation methods continuously [24,25]. To understand the relationship between leisure and fitness spaces and health further, Zhang et al. explored the impact of parks and sports venues on people’s physical activities [26]. Furthermore, many scholars have compared differences in access to health-related resources among different groups and explored the impacts of differences in health; among these groups, the elderly and the poor have received special attention [27,28]. Previous studies have examined singular aspects of fitness facilities or medical and health facilities but have rarely combined the two to assess the impact on health. Some scholars have integrated health into the 15 min community-life circles and proposed to build a healthy community-life circle. On the one hand, aiming at the growing number of chronic diseases, urban planners need to add green space, open space, fitness facilities, and slow walking systems with high accessibility to promote residents’ physical activity and social interaction. On the other hand, aiming at the epidemic emergency, urban planners need to increase institutions and facilities related to epidemic emergencies to meet the need for prevention, isolation, treatment, and assistance during an epidemic [29]. The construction of healthy community-life circles can delineate the basis for the research scope and provide proposed path guidance for planning proposals. The most critical thing is that the healthy community-life circle connects health service facilities with people’s life circles. Therefore, healthy community-life circles were constructed that included medical and health facilities and fitness activity facilities as the basis of the current study. Many scholars believe that accessibility is an effective means to evaluate the rationality of the layout of public service facilities. When accessibility is associated with walking, it is considered to be an indicator to measure the quality and operational effectiveness of a community. Walking accessibility is a critical factor among residents’ ability to benefit from facilities, resources, and services and is considered a measure of whether a community’s built environment encourages people to walk [30,31]. In recent years, the quality of the walking environment has gradually become an essential element of urban planning and design, and more and more studies have attempted to explore the relationship between, and influence the effect of the former on the latter for, characteristics and attributes of the neighborhood environment and walking. Walking has attracted more and more attention from scholars, mainly because it can affect people’s physical and mental health, promote the balanced development of urban and public service facilities, and improve community satisfaction [32,33]. As walking is an important means of transportation, walking accessibility has often been regarded by scholars as an important indicator to analyze the fairness of facility distribution in studies on evaluating the distribution of park squares, sports activity facilities, and medical and health facilities [34,35,36]. These studies have mainly used surveys, global positioning systems, GIS, and other methods to study the correlation between neighborhood environment and walking empirically, which provided a basis for studying neighborhood environments suitable for walking. In addition to walking accessibility, perception evaluation also plays a key role in influencing community environmental satisfaction. The neighborhood satisfaction model constructed by Amerigo and Aragones in 1997 conceptualized the residential environment as objective and subjective attributes [37]. Some studies have found inconsistency between perceptual and objective measurement. In the existing literature, the objective evaluation of neighborhood environmental attributes has mainly relied on the GIS, whereas the subjective measurement method has usually involved collecting residents’ perceptual data for evaluation and analysis [38,39]. Furthermore, some studies have attempted to combine quantitative analysis based on objective data, such as GIS data, with qualitative analysis based on subjective/perceived data collected from residents for comparative and comprehensive analysis to explain the impact of neighborhood environmental attributes fully [40]. Although some studies have shown that subjective assessments of community environments are more important than objective assessments in explaining community environmental satisfaction [41], objective measurements have the advantage that they can be accessed through public datasets. They have the potential to guide urban planning better based on their specific and repeatable parameters. Thus, this study combined the objective measurement method of the GIS and the subjective measurement method of the questionnaire interview to explore the difference in terms of health service facilities’ walking accessibility between the perceived satisfaction of residents and objective measurement. Thus, this study took the community-life circle of residents in the main urban area of Chengdu as its research focus to investigate the layout of community medical and health facilities and fitness facilities from the perspective of healthy urbanization development and explore the weak links in the city’s development. This study aimed to solve three problems: (1) from a macrospatial perspective, to construct an evaluation index system for healthy community-life circles in big cities and evaluate the strengths and weaknesses of these healthy community-life circles objectively; (2) from a micro perspective, to explore the difference between residents’ micro perception and objective measurement in the healthy community-life circle and analyze the key factors that affect the satisfaction of health service facilities; (3) to examine how to build healthy community-life circles reasonably and improve residents’ satisfaction with said healthy community-life circles. Our study offers the following potential contributions: exploration of the layout of healthy community-life circles of the metropolis and key influencing factors affecting health service facilities based on macrospatial analysis and the micro perspective of residents’ awareness and evaluations of the community; constructing a new theory of healthy community-life circles and putting forward corresponding optimization suggestions and policies on the basis of the theory of the original community-life circle in Chengdu. Furthermore, this study intended to use a novel analysis method: comparatively analyzing the perceived and objectively measured accessibility of health service facilities. Unlike traditional health facility studies that mainly focus on medical and health facilities, this study combined fitness facilities and medical and health facilities to analyze together to develop a new conceptual framework for a healthy community-life circle. This study provides a basis for optimizing healthy community-life circles in China and a reference for decision makers in urban planning. 2. Research Area and Data Resources 2.1. Study Area The research area in this study was the central city of Chengdu, Sichuan Province (104:04 E and 30:39 N) (Figure 1), which includes Jinjiang District, Qingyang District, Jinniu District, Wuhou District, and Chenghua District. According to official government statistics in 2020, the gross study area was approximately 424.06 square kilometers, holding a population of 4.232 million in 2019. According to the local government’s population data, the population density in the core urban areas was 10,300 people per square kilometer by the end of 2016. Chendu’s population is expected to be close to or exceed the critical value for pressure on natural resources by 2035. High-quality, harmonious, and livable communities are currently the focus for improving the quality of the living environment in Chengdu. In December 2018, Chengdu issued the “Working Plan for Creating a New Community Commercial Area and Building a Community Quality-of-life Service Circle (2018–2022)”. It proposed promoting the construction of a 15 min community-life circle vigorously by taking the community as the central point to allocate services for the population scientifically and reasonably using a set radius to ensure that basic public services could be reached within 15 min of travel on foot or by bicycle. Therefore, downtown Chengdu was taken as the case study herein. 2.2. Data Sources This study’s data mainly came from spatial POI data and field survey data. The POI data consisted of specific point data of spatial entities closely related to daily lives with accurate geographic and attribute information including longitude, latitude, name, address, type, and label [42,43]. They provided accurate locations and detailed categorical information for commercial businesses, services, and public places and had the advantages of being abundant and free to access [44]. Using the Python programming language, websites were crawled by looping through the URLs to collect road network and POI data for the Jinjiang, Qingyang, Jinniu, Wuhou, and Chenghua Districts of Chengdu in 2019. In the collected POI data, after screening and checking of locations and attributes, 3658 POI data in the study area were selected and used as the starting points of residents’ daily travel to measure the health service facilities within 15 min community circles, which was one of the bases for delimiting healthy community-life circles. Field research data came from the issuance of questionnaires and in-depth interviews with individuals. Finally, 371 valid questionnaires were obtained. Therefore, the data of this study were sourced from community POI and survey data. 3. Methods To evaluate healthy community-life circles, the Delphi method was used at the macro level to determine the weights of various health service facilities. The UNA tool was also adopted to delineate the boundary of each 15 min healthy community-life circle, calculate the coverage and convenience of each urban facility, and conduct comparative analyses between them. Questionnaires were distributed on site, and in-depth interviews with individuals were conducted to analyze resident satisfaction with facilities and influential factors. The data were analyzed in SPSS25. The test was conducted to establish the reliability and validity of the questionnaire to verify the scientific rigor of the research. This study thoroughly analyzed the influence mechanisms of objective measurement (coverage rate and convenience) and subjective, perceived satisfaction of residents using linear regression and logistic regression models (Figure 2). 3.1. Classification and Model Weighting of Health Service Facilities Existing studies have shown that the use of parks, squares, and sports facilities exerts a positive influence on the improvement of mental and physical health and can also reduce the risk of anxiety and a variety of chronic diseases, whereas medical and health facilities are the most important safeguard for maintaining the health of the population [45,46,47]. Therefore, two broad categories were selected for evaluating the service facilities within healthy community-life circles: medical and health facilities and fitness facilities. The types of facilities included in these broad categories were determined by referring to the classification of medical and fitness facilities in previous studies [13,48]. Medical and health facilities were divided into five categories: general hospitals, specialized hospitals, community hospitals, clinics, and pharmacies. Strictly speaking, general hospitals and specialized hospitals are outside the scope of facilities in the healthy community living circle. However, Chinese residents have low trust in lower-level medical facilities, so they choose to go to large hospitals to treat even minor illnesses. Therefore, general hospitals and specialized hospitals were included in the facilities to be evaluated in this study. Fitness facilities were divided into three categories: parks and squares, sports venues, and sports zones. This study employed a classic Delphi method to ensure scientific and subjective weighting. As a long-term forecasting method, the Delphi method, which makes recommendations based on experts’ opinions, has been widely used for auxiliary decision-making [49]. We sent a letter to 20 experts introducing the study and the Delphi process and inviting them to participate in this phase, which was completed between August and October 2020. The experts were required to score the eight facilities in Table 1, ranging from “very important” to “not important”, from which a facility grade average was calculated. The order of importance of these health services was used to obtain the weights for the various analyses (Table 1). 3.2. Delimitation of the Scope of Healthy Community-Life Circles Chengdu Municipal Government aims to optimize the spatial layout of the city’s medical and health resources and improve the accessibility of medical and health services by compiling the “Chengdu City Medical and Health Resources Layout Plan (2017–2035)” and proposing the construction of 15 min healthy circles that incorporate at least one community health service center within a 15 min walking distance (800–1000 m) for residents to carry out diagnosis and treatment measures. In this study, a healthy community-life circle was defined as integrating health into the 15 min community-life circle. In such a circle, within walking distance from home, various health service facilities can meet residents’ daily health needs, such as fitness exercises and medical services, and have health-promotion effects and the ability to respond to public health emergencies. Previous studies have usually employed a certain straight-line distance as the scope of residents’ activities to delimit their community-life circles, ignoring factors such as buildings, roads, and topography. For the purposes of reflecting the scope of people’s community-life circles more truthfully, this study used UNA in Arc-GIS to construct a city network dataset for network data analysis. The selected community POIs were used as the starting points of residents’ daily travel, taking walking as the travel mode, streets as network links, and intersections of the streets as odes of the network to create the network dataset. In the “SHANGHAI PLANNING GUIDANCE OF 15-MINUTE COMMUNITY-LIFE CIRCLES” issued by the Shanghai Municipal Government, the 15 min walking distance is 800–1000 m, and people’s normal walking speed is between 0.75–1.2 m per second [50]. Given the speed differences between different genders and age groups, this study adopted an average speed of 1.0 m/s as the residents’ walking speed. To build a new service area, the walking mode was chosen as impedance, the interruption value was 15 min, and the corresponding surface generated was the actual walking range of the residents in 15 min. This mode was used within the constructed network to generate a surface that represented residents’ actual walking range in 15 min. This method better reflected the distance people walk in 15 min and more scientifically delimited the 15 min community-life circle. For larger communities, given the greater differences in the coverage area of a 15 min walk, these areas were divided into several smaller surfaces, and the corresponding centroid was generated as the starting point [51]. 3.3. Coverage Rate and Convenience Evaluation This study used Arc-GIS to calculate the coverage rate and convenience in accessing medical and health facilities and fitness facilities. Based on the selected POI data, the coverage rate of the health service facilities in the community-life circles was measured. If a particular type of facility was reachable within a 15 min walk, the living circle was said to be covered. After calculating the coverage rate of each facility, the overall coverage rate of health service facilities in each community-life circle was determined:(1) Ci,j,s={1,∃Fj,∈N1(Communityi,s)0,others (2) CRi,j=(∑s=1miCi,j,s/m)/mi (3) Fi=∑j=1nFij×Wj where Cis represents community s in the urban area i; Cijs represents whether there is a health service facility Fj within the community-life circles (if it exists, this means it is covered); CRij represents the coverage rate of the health service facility Fj in the ith urban area, showing the coverage level of different areas; mi is the number of living circles in the urban area i; Fi is the overall coverage rate of the health-related facilities in the ith community-life circle; Fij is the coverage rate of category j facilities in the ith community-life circle; and Wj is the weight of the j facilities. The coverage rate reflected only the overall spatial distribution of the various facilities. It was also necessary to define the convenience of residents in each healthy community-life circle in accessing various health service facilities. Arc-GIS was used to calculate the number of each kind of facility that was accessible within each community-life circle. The convenience of accessing the health service facilities in each community-life circle was graded according to this number. The grading of convenience followed the natural discontinuous grading method, which divides the elements into multiple classes. For these classes, the boundary was set at the position where the differences in the data values were relatively large, keeping similar group values appropriately grouped while maximizing the difference between each category. On this basis, the convenience in accessing the various health facilities was divided into eight levels, and the convenience in accessing the various health service facilities in the healthy community-life circles was evaluated. 3.4. Questionnaire Design and Distribution The questionnaire mainly investigated residents’ usage habits and satisfaction with various facilities, the distribution of various facilities near their places of residence, their suggestions for the improvement of various facilities, and protective measures they had taken following the outbreak of the COVID-19 epidemic. The questionnaire was based on four dimensions: frequency of facility use, walking time from residence to the facility, the ideal walking time between residence and facility, and satisfaction evaluation. Satisfaction included two aspects: residents’ satisfaction with accessibility of health service facilities and service satisfaction. In the questionnaire, each respondent evaluated their satisfaction with each health service facility’s accessibility and service (general hospitals, specialized hospitals, community hospitals, clinics, pharmacies, sports venues, sports zones, parks, and squares) closest to home. A five-level Likert scale was adopted to provide satisfaction indexes. This study assigned values as follows: 5 points—very satisfied, 4 points—relatively satisfied, 3 points—generally satisfied, 2 points—relatively dissatisfied, and 1 point—very dissatisfied. The walking time was divided into levels of “less than 5 min”, “5–10 min”, “11–15 min”, “15 min or more” and “unclear” for the purpose of analyzing the relationship between walking time and satisfaction. Considering the impact of different individuals on satisfaction, we also classified individual factors, including gender, age, education, job, annual income, type of dwelling, and other variables (Table 2). The “type of dwelling” option was based on the respondents’ answer to the question “Which one of the following does your residential area belong to?” The classification standard of residential type referred to previous studies and the actual situation of Chengdu. The type of dwelling was divided into four categories: (1) low-end housing types, including shanty towns; old, unrenovated city housing; and agricultural residential houses; (2) mid-range houses, including ordinary commercial houses; (3) high-end houses, including villas and high-end commercial houses; and (4) units and school dormitories. During the survey, randomly sampled interviews were conducted with residents in the five urban areas of Chengdu in different time spans selected between 9:00 and 22:00 to obtain data for different periods. First, a presurvey was conducted, during which 63 questionnaires were issued. After all valid presurvey questionnaires were collected, reliability and validity tests (see details below) were conducted on the data. After deleting a single invalid question, the final questionnaire was formed, and the survey was carried out. (1) Reliability Test Reliability refers to the degree of consistency and stability of the data obtained from multiple responses to the questionnaire. Values range from 0 to 1. The larger the value, the higher the reliability. To take into account the repeated tests, Cronbach’s reliability coefficient method was adopted (abbreviated as a). The mathematical formula of Cronbach’s alpha reliability coefficient is:(4) a=(k/(k−1))(1−(∑i=1kσi2)/σT2) where K represents the total number of items, σi2 represents the in-question variance of the score of the ith question, and σT2 represents the variance of the total score. The 40 variables were statistically analyzed, and the output showed that the Cronbach’s alpha reliability coefficient was 0.885, indicating that the reliability of the data was excellent, so further analyses could be performed. (2) Validity Test Reliability examines the consistency across all items in the scale, while validity specifically examines the consistency of each individual item, that is, whether each item plays an important role in the scale [52]. To test the suitability of the data, it was necessary to perform the KMO (Kaiser–Meyer–Olkin) and Bartlett sphere tests on the samples. The KMO index was 0.861 (Table 3), which was close to 1, indicating that the data was suitable for factor analysis. 3.5. Data Processing The study evaluated residents’ accessibility and service satisfaction for fitness and medical and health facilities by calculating the average and standard deviation to analyze the basic situation of residents’ accessibility satisfaction evaluation. The differences among the interview subjects had specific impacts on their satisfaction scores, among which differences in gender, age, education level, occupational status, annual income, and housing type were considered. We constructed an ordered multiclass logistic regression model to analyze the impacts of the differences in the subjects on satisfaction. We adopted a classical linear regression analysis, taking satisfaction with the eight types of facilities as the dependent variables. The frequency at which the facility was used, the mode of transportation used to get there (What is your most common mode of transportation to the following locations?), the perceived walking time from the residential point to the facility, the expected walking time from the residential point to the facility, and convenience (according to the place of residence filled in the questionnaire, convenience was evaluated in a city network dataset) were used as independent variables to explore the factors influencing residents’ satisfaction scores. Because the transportation mode used by residents was a categorical variable, it was analyzed with a chi-square test. Chi-square is a nonparametric hypothesis-based method used to calculate the degree of fit between actual observation values and the theoretical inferred values of two or more samples. The calculation formula is as follows:(5) x2=∑(A−T)2/T where A is the actual observation value and T is the theoretical inferred value. By using SPSS, chi-square test results for the eight health service facilities were obtained. Paired-sample T-tests were used to compare and analyze the differences between the residents’ perceived value and the actual value of the distance between their residences and the facilities. Residents’ perceptions of the walking time from their residential areas to the facilities were assessed by the subjects’ responses to the question “from home, the time to walk to the nearest place below is”. The answers included “less than 5 min”, “5–10 min”, “11–15 min”, “16–20 min”, “more than 20 min”, and “unclear”. The actual distances between their residence and the facilities were based on the addresses filled in by the respondents. A network dataset was created in Arc-GIS to generate the corresponding range and calculate the actual walking time of 5, 10, 15, or 20 min from their residence to the nearest facility. The samples with unclear answers selected in the questionnaire were deleted, and a paired sample t-test was performed on the remaining actual and perceived values. Simultaneously, we constructed a logistic regression model for eight health service facilities to explore the relationship between objective and perceived measures of accessibility of and satisfaction with health service facilities. 4. Results 4.1. Evaluation of the Healthy Community-Life Circles 4.1.1. Evaluation of Spatial Differences in the Coverage Rate of Health Service Facilities The average coverage rates of the various health-related facilities in the main Chengdu urban area were general hospitals (93.22%) > community hospitals (88.19%) > parks and squares (84.99%) > pharmacies (84.39%) > sports venues (82.53%) > sports zones (73.53%) > clinics (65.88%) > specialized hospitals (48.85%). The corresponding standard deviations were specialized hospitals > sports zones > park and squares > clinics > pharmacies > sports venues > community hospitals > general hospitals. The greater the standard deviation, the greater the difference in the average coverage rate of the facility in each urban area, and the more uneven the overall distribution of the facility in downtown Chengdu. Figure 3 and the sizes of the standard deviations show that the two facilities with the most pronounced differences between urban areas were the specialized hospitals and sports zones. These two types of facilities had low coverage rates in each urban area as a whole. 4.1.2. Evaluation of the Spatial Characteristics of the Degree of Convenience in Accessing Health Service Facilities From the results presented in Figure 4, we drew the following inferences: the overall convenience index of the five urban areas of Chengdu gradually decreased from the city center. Figure 5 shows that the park and square facilities in the Qingyang District offered a high level of convenience. At the highest level, 64 parks and squares were accessible, and the areas with highly convenient parks and squares were concentrated. Most other urban areas had lower convenience scores for parks and squares. The gap in convenience scores for sports venues in the different urban areas was not significant. The scores were distributed more uniformly within healthy community-life circles. The distribution of sports zones did not follow the trend of decreasing from the city center to the outside. The convenience scores of general hospitals and community hospitals were generally higher than those of other facilities, but the convenience scores of general hospitals in urban centers were not high. The convenience scores of specialized hospitals were the lowest of all of the facilities. The areas with high convenience scores for clinics and pharmacies were mainly concentrated in the central urban area, and most of the central area had high convenience scores for pharmacies. 4.2. Evaluation of Resident Satisfaction and Analysis of Influencing Factors 4.2.1. Evaluation of Resident Satisfaction Results According to Table 4, the overall satisfaction with accessibility (3.20) was slightly higher than the satisfaction with service (3.12), which indicates that residents were relatively satisfied with the accessibility and services offered by these eight types of facilities. No significant difference was found in the average values of accessibility and service satisfaction of residents for the same health service facilities, indicating that facilities’ service quality and accessibility may jointly affect the evaluation of residents’ satisfaction. Residents were more satisfied with the accessibility and service of pharmacies and park squares. Satisfaction with specialized hospitals, sports venues, and sports zones was low, and the standard deviation was significant, indicating that residents’ satisfaction with these three facilities was significantly different. 4.2.2. Residents’ Satisfaction Was Related to Their Attributes and Usage Habits Table 5 and Table 6 show a significant positive correlation among age, occupational type, and accessibility and service satisfaction of health service facilities. With increasing age, residents’ satisfaction with the walkability of health service facilities and service quality gradually increased. Residents with permanent jobs generally had higher satisfaction than those without permanent employment. Furthermore, compared with residents with annual incomes of more than 100,000 yuan, residents with annual incomes of less than 50,000 yuan rated the accessibility and service quality of park squares and pharmacies more positively. Residents of upscale neighborhoods reported poorer satisfaction with the accessibility of pharmacies and clinics than those living in dormitories. Table 7 shows that only the frequency of residents using community hospitals positively correlated with accessibility satisfaction. In contrast, the frequency at which other facilities were used had no significant impact on their accessibility satisfaction. No linear correlation was found between the degree of convenience and the degree of satisfaction with the accessibility of various facilities. In the analysis of the relationship between the accessibility satisfaction with various facilities and the mode of transportation used by residents, we found that walking mode had a positive effect on improving the accessibility satisfaction of parks and squares, sports venues, sports zones, community hospitals, clinics, and pharmacies. There was no significant correlation between walking and accessibility satisfaction with general hospitals and specialized hospitals (p > 0.1). However, using nonmotor vehicles to travel to specialized hospitals could significantly improve accessibility satisfaction of specialized hospitals. Therefore, we can infer that walking was not the best choice for either facility in the 15 min healthy community-life circle. The preference to use nonmotorized vehicles or public transportation also positively affected satisfaction with the accessibility of sports venues, sports zones, community hospitals, and clinics. By analyzing the relationship between the expected walking time and the satisfaction of eight types of health service facilities, we found that the shorter the expected walking time was, the higher the satisfaction evaluation of residents was. 4.3. Resident Perception and Objective Measurement Analysis for Health Service Facilities 4.3.1. Analysis of Residents’ Perceptions of Distance between Residential Sites and Facilities Table 8 shows that residents’ perception of various health service facilities around their living places was inaccurate. First, in the paired sample correlation test, except for sports zones (p < 0.05), the p-values of all of the other facilities were >0.05, indicating a significant correlation between the objectively measured distance to sports zones and people’s perception of the distance. No significant correlation was found between the objectively measured and perceived distances for the other seven facilities. In the paired sample tests, the p-values for the sports venues, sports zones, specialized hospitals, community hospitals, clinics, and pharmacies were less than 0.05, indicating significant differences between the perceived values and the objectively measured values, and no significant differences were found between the perceived and objectively measured values for parks and squares and general hospitals. The average differences in the objectively measured and perceived values for sports venues, sports zones, and specialized hospitals were negative, indicating that the objectively measured values were significantly lower than the perceived values. The average differences in the objectively measured and perceived values for community hospitals, clinics, and pharmacies were positive, indicating that the objectively measured values were significantly higher than the perceived values. 4.3.2. Relationship between Objective and Perceived Measures of Accessibility of and Accessibility Satisfaction with Health Service Facilities We constructed an ordered logistic regression model for eight health service facilities. Three facilities (sports venues, general hospitals, and clinics) had p-values under parallelism tests of less than 0.05, indicating that the grade spacing of dependent variables was not equal. Disordered logistic regression model analysis was required (Table 9). The accessibility satisfaction with all health service facilities in the table was significantly correlated with perceived accessibility. In contrast, no significant correlation was found with objective accessibility measures (Table 10), which further proves the importance of residents’ perception of accessibility satisfaction. By comparing the OR value of perceptual measurement in each model, we analyzed the impact of residents’ perceived accessibility between different health service facilities and its implications. Pharmacies and community hospitals had the most significant effect of the eight types of facilities. When the perceived accessibility level of pharmacies and community hospitals increased by 1 unit, the probability of improving the accessibility satisfaction level of residents was 93.2% and 75.1%, respectively. These were followed by sports zones, parks and squares, and specialized hospitals. 5. Discussion 5.1. Nonuniform Spatial Distribution in Health Service Facilities Although the number of health service facilities was relatively evenly distributed across various urban areas, the development of various facilities was disproportionate, and the overall convenience in accessing facilities near the city center was significantly higher than that in other areas. Regarding coverage and convenience of comprehensive sports facilities, the distribution of sports zones in the healthy life circle was worse than that of the other two facilities, and satisfaction with their service (2.87) and accessibility (2.99) was also relatively low. Sports zones’ construction time and cost are lower than those of other facilities, but the current situation is still far from satisfactory. Do residents prefer to use other fitness facilities? Are planners too focused on parks and squares, neglecting sports zones? Is there another reason for this phenomenon? Further discussion is needed. The park and square facilities in Qingyang District were slightly more convenient than those in other urban areas, mainly because all kinds of large and small parks and squares in downtown Chengdu, such as Huanhuaxi Wetland Park, People’s Park, and Cultural Park, were concentrated in the central area of Qingyang District. Most of the parks were close enough for residents to use conveniently. Although other urban areas had large parks, the geographical location of these large parks was far away from residential areas and could not radiate to more residential sites. Therefore, small parks and squares were important to improve the construction of healthy community-life circles. Studies have shown that people prefer to use the boundary of the park space rather than entering the park, and that if a park or square’s shape is more complex, the usage rate of the residents is higher [53]. It is better to build a strip or ribbon park according to the river and terrain than to build a park square, as the former can cover more residential areas and improve the usage rate of residents. More complex or varied shapes should be designed in the planning of new parks and squares. After establishing the 15 min healthy community circle in Chengdu, as shown in the study results, the convenience and coverage of community hospitals emphasized by the healthy community circle were above the medium level. However, the distribution of general hospitals and specialized hospitals was far less even than that of community hospitals, and the coverage of specialized hospitals and clinics was also lower, which may be related to the incomplete coverage of the population in specialized hospitals and clinics being able to provide only basic health services. Furthermore, most respondents (53%) said they barely used specialized hospitals and clinics. On the one hand, the distribution of the two types of facilities was uneven. On the other hand, the number of specialized hospitals was smaller, and the targeted audience was relatively single. The clinic use group is mainly a low-consumption crowd. People with medical insurance are less likely to use clinics. Specialized hospitals and clinics are all private hospitals, and urban residents prefer to use public hospitals with higher quality and usage levels [54]. Chengdu carried out graded diagnosis and treatment measures in the existing health circle. Clinics and community health centers played an important role in the initial stage of graded diagnosis and treatment. Although during the COVID-19 pandemic in China, higher-level general hospitals have taken on most of the treatment work for COVID-19 patients and received more attention and investment, clinics have played a considerable role in late-stage COVID-19 screening, vaccinations, and residents’ daily hospital visits. Planners should consider how clinics can play an important role in the healthy life circle. 5.2. Residents’ Behavior Characteristics Affect Their Satisfaction with Various Health Facilities With the growth of age, the walking range of middle-aged and elderly residents becomes smaller, and their walking accessibility satisfaction with health service facilities may decrease. However, our results showed the opposite. This does not indicate that the activity ability of middle-aged and elderly residents was enhanced but may be related to the mental and vision changes brought by age. At the same time, one reason to consider is that young residents spend more time working and commuting than middle-aged and elderly residents. Less time at their disposal may lead to higher requirements for the accessibility of health facilities. Residents’ estimated time needed for travel may affect residents’ medical choices [55]. Our results showed a positive correlation between the expected walking time required from the residential site to a hospital and the degree of satisfaction with the accessibility of said hospital. This implies that residents do not want to live close to hospitals, which may be because most residents use hospitals less frequently, while hospitals bring more negative effects (e.g., infectious diseases, pedestrian traffic, and security concerns) to residents. Therefore, some measures should be taken around general hospitals to reduce this phenomenon, such as using commercial entertainment facilities or green space to separate residential areas from general hospitals. Although, on average, residents were relatively satisfied with the levels of service at the studied facilities, the interviewees still pointed out the shortcomings of various health service facilities. Nearly half of the interviewees (45%) thought that the number of sports venues was insufficient. Some interviewees also pointed out that the stadiums near their homes had short opening times, old facilities, poor environments, sanitation concerns, and high fees and had been closed since the COVID-19 epidemic outbreak, among other problems due to insufficient policy support, investment, and imperfect management by Chengdu’s stadiums [56]. The long waiting time for medical treatment was the issue most in need of improvement in general hospitals. The main problems for community hospitals and clinics were the limited medical functions available and the low level of medical care. Talen et al. found that the medical technology level of hospital facilities was the primary consideration for residents when choosing hospital treatment [57,58]. This finding was supported in the present study. Most interviewees preferred to select small medical and health facilities. However, given that the existing medical standards of community hospitals and clinics were unable to meet the medical needs of the residents, they were obliged to choose higher-level medical and health service facilities, such as general hospitals [59]. The supply and demand of medical facilities are imbalanced [60]. This study also found that more residents chose higher-level medical institutions (27.2%) than lower-level medical institutions (18.3%). The main reasons for choosing low-level medical facilities were affordability, residents’ fear of contracting COVID-19 in a health care environment, and residents’ delay or avoidance of medical treatment [1]. Some interviewees mentioned that private medical services (clinics and specialized hospitals) were not as good as public medical services or that they were not clear about whether their medical insurance could be used in private hospitals. Thus, they preferred to choose public medical and health facilities [61]. By analyzing the relationship between residents’ daily use of transportation and accessibility satisfaction of various health service facilities, we found that residents’ preferences for different health service facilities were different. For parks, squares, and pharmacies, only walking had a significant positive impact on improving accessibility satisfaction. However, for general hospitals, specialized hospitals, sports venues, sports zones, and other facilities, nonwalking transportation could also improve accessibility satisfaction. Thus, we believe that residents have different physical endurance when they go to various health service facilities and have “optimal” or “threshold” walking time. Given that general hospitals, for example, can provide higher-quality nursing services, and many interviewees may accompany their family members when they go to general hospitals, residents are more willing to pay higher transportation costs [54]. Thus, even within a 15 min healthy community-life circle, accessibility requirements may vary for different health service facilities. Only building walkable community-life circles may not be enough to meet the health needs of residents. Thus, the construction of healthy community-life circles should not be limited to 15 min healthy community-life circles. A model could be considered on the basis of the Chengdu healthy circle, that is, to build a 15 min walking healthy community-life circle to guarantee the basic healthy life of residents and a 15 min traffic accessible healthy community-life circle to meet all the healthy life needs of residents. However, promoting and improving healthy community-life circles still requires related research and actual verification in the future. This conclusion also has some generalized significance for other similar cities in the world. 5.3. Residents’ Perceptions of Health Services Accessibility Are the Key Factors Influencing the Degree of Satisfaction Except for parks, squares, and general hospitals, the objectively measured accessibility of health service facilities was significantly different from the accessibility perceived by residents. This was consistent with the results of other studies [23,62]. This time, we adopted the perception of people living for a long time and reliance on experience rather than instantaneous time perception. Therefore, people’s daily habits, experiences, activities, or health degrees impacted their perception of health service facilities [63]. Furthermore, the residents’ perception of the physical environment was inseparable from the social environment [64]. The current social environment does not pay much attention to health. One reason why is that residents pay less attention to health facilities and services. Residents perceived fewer sports venues, sports zones, and specialized hospitals within a 15 min walk than the objectively measured number, and the numbers of community hospitals, clinics, and pharmacies were perceived to be greater than the objectively measured numbers. Combined with our field research, this study suggests that this perception may be related to the fact that some sports zones and sports venues are not open and do not attract residents’ attention. Thus, managers must strive to improve and maintain the environmental aesthetics of parks, squares, and small sports zones in the community to attract more people and enhance residents’ perceptions of them. At the same time, the health service department can promote physical activity through educational content and other means to improve the perception and health level of the population [65]. Our study further proved the importance of residents’ perception for accessibility satisfaction. Residents’ perceived travel time had a significant impact on their accessibility satisfaction with various facilities. The closer to their homes facilities were perceived to be, the more satisfied residents were with the accessibility of these facilities, and the objectively measured accessibility had no significant correlation. At present, studies have found that residents’ perception of the environment is more important than the objective reality. Of course, the lack of connection between objective measurement and accessibility satisfaction may be caused by some unstudied characteristics affecting residents’ perception in ways related to their satisfaction [40]. In future studies, it will be important to understand how changes in the neighborhood lead to neighboring health services being perceived by residents as adjacent. Although building more health service facilities would improve residents’ perceived accessibility and accessibility satisfaction, it is obvious that building facilities is insufficient for making qualified, healthy community-life circles. 5.4. Implications The study results provided new evidence for constructing healthy community-life circles in China and have certain reference significance for the construction of similar cities and communities around the world. We believe that this study has contributed to the existing literature from two perspectives. First, unlike traditional health facility studies that mainly focus on medical and health facilities, the present study combined fitness facilities and medical and health facilities to analyze together, optimized the Chengdu healthy community-life circle, proposed building a healthy community-life circle with categories and hierarchical systems, and developed a new conceptual framework for a healthy community-life circles. Furthermore, a novel analysis method was adopted. Comparatively analyzing the perceived and objectively measured accessibility of health service facilities and emphasizing the importance of people’s perception of health service facilities are important concerns for policymakers but tend to be overlooked in many studies. The results of this study also had several important policy implications. First, the government plays a leading role in the spatial configuration, planning, and construction of medical and health facilities and health service facilities, such as parks and squares; thus, the government should reoptimize the layout according to people’s needs [66]. The transportation system should be supplemented and improved to make up for the current low usage rates of pedestrian transportation to general hospitals, large sports venues, sports zones, specialized hospitals, community hospitals, and clinics. Furthermore, given the difficulty of building large-scale sports facilities in existing cities, the support of the private sector by the state and society is crucial for the development of fitness facilities [35], and improvements to the opening hours and accessibility of existing facilities are needed. For example, extending the business hours of public gymnasiums and opening school gymnasiums and playgrounds during nonclass time to the public are effective and feasible options [67]. Venues that offer activities suitable for different age groups could be added. As one interviewee mentioned, “I think several adjacent communities can jointly organize a fitness facility or gym, and the activities and content of the facilities could be specific for children, young people, women, and the elderly. Their physical needs and living habits are different, and some facilities are not suitable for the elderly or young people”. For existing fitness facilities, such as parks, squares, and other fitness facilities, attention should be paid to the maintenance of their environment and their content. When we surveyed satisfaction with parks, an interviewee said, “Now, the park is too noisy and iteratively updated so quickly. Many of the memories and feelings of youth that once filled the park are gone. Now, it is sometimes strange to go to the park I used to go to because it lacks some cultural things”. Therefore, the quality of parks and squares affects their attractiveness to people, which is paramount. The government also ought to strengthen its support for the construction of small hospitals, especially community hospitals and clinics, and improve their medical level and coverage to promote better medical resource allocation [66]. Standardized policies or rewards should also be adopted to improve the service level of private medical service facilities. Second, in addition to building and opening up new facilities, alternative or low-cost construction between facilities is a method worth considering. For example, health service facilities with similar functions can replace one another. Planning and maintaining appropriate pedestrian infrastructure improves residents’ perception of accessibility. Furthermore, when residents go to medical and health facilities urgently, the time and distance are the most important. However, distance and time may be less important for residents using sports facilities than their service and quality. Therefore, improvements should be made according to the different characteristics of different health service facilities. Finally, policymakers should promote the intersection between neighborhood design and health and encourage the participation of citizens with different socioeconomic attributes in the planning and construction of healthy community-life circles to improve understanding and consider the diverse health needs of residents in the neighborhood environment development process. 6. Conclusions The sudden large public health incident of the COVID-19 pandemic has made people more aware of the importance of healthy community-life circles. We obtained POI data and used GIS tools to evaluate the medical and health facilities and fitness facilities in the main urban areas of Chengdu. Using a questionnaire survey, we compared the accessibility of health service facilities as actually measured and residents’ perception of accessibility and analyzed the difference in the impact of each on facility satisfaction. The results showed that the social environment, the service level and layout of facilities, and residents’ travel habits were related to facility satisfaction. Residents could not accurately perceive the surrounding health service facilities. Objectively measured walkability did not significantly affect the satisfaction of the facilities. Only residents’ perception of low walking time between the residence and the facility positively impacted satisfaction. These factors can reduce residents’ negative perceptions by optimizing facility layout and replacing low-cost facilities to meet residents’ basic health needs in a 15 min healthy community-life circle. Furthermore, we put forward corresponding improvement measures for each health service facility and built a healthy community-life circle with a category and hierarchy system. These findings and suggestions provide some reference for Chengdu and other similar cities to optimize the healthy life circle and have practical significance for improving residents’ health and health service facilities satisfaction. However, this study also had certain limitations. The high coverage rate of the health service facilities did not mean that residents utilized the facilities within 15 min of walking distance at high speed. Demographic characteristics and population density were also influencing factors. Given that the scale, capacity, service radius, and specific service content of similar health service facilities are difficult to obtain, this work did not consider these factors in the analyses therein, but the health benefits brought by each facility are likely different. In future studies, the indicators of health service evaluation should not only be medical and health facilities and fitness facilities. More places or environmental elements with health-related behavioral activities, such as entertainment venues, can also be regarded as health-related facilities. In addition, “population density” and “accessibility of other transportation (nonmotorized, public transport, private cars, etc.)” can be taken into account in future studies. Acknowledgments We would like to thank two anonymous reviewers for their constructive comments that significantly improved this article. Author Contributions Conceptualization, K.Z.; data curation, K.Z. and J.Y.; funding acquisition, J.W.; investigation, M.L. and H.W.; methodology, C.M., L.Z. and K.Z.; software, Y.Z., H.S. and Z.W.; validation, X.T., Y.C. and L.T.; writing—original draft, Y.Z. and J.W.; writing—review and editing, J.W. and Y.Z. All authors have read and agreed to the published version of the manuscript. Funding We would like to acknowledge support from the Key Social Science Project of Sichuan Agricultural University (2020PTZD05); the Sichuan Provincial Social Science Key Research Base—Sichuan County Economic Development Research Center 2020 General Project (xy2020006); the Soft Science Project of Sichuan Provincial Science and Technology Department (2021JDR0076); and the New Pattern of Incorporating Dual-Circular Development Research Center of Chengdu (CDNUSXH2021ZD-03). 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 Sichuan Agricultural University (CN21-490, 2021). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent was obtained from the patient(s) to publish this paper. Data Availability Statement The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Location of the study area. Figure 2 Research framework. Figure 3 Coverage rates of health facilities within the 15 min community-life circles in the main urban area of Chengdu. Figure 4 Analysis of the overall degree of convenience and comprehensive assessment of eight types of facilities. Figure 5 The degree of convenience in accessing various facilities. ijerph-19-05028-t001_Table 1 Table 1 Classification and weighting of health service facilities in healthy community-life circles. Category Item Content Total Quantity Weights Medical and Health Facilities General Hospitals Hospitals with a certain number of beds, separated departments, and corresponding personnel and equipment 1249 0.075 Specialized Hospitals Hospitals with only one or a few medical branches, such as cancer hospitals, children’s hospitals, plastic surgery hospitals, etc. 1640 0.025 Community Hospitals Provide public health and basic medical services for community members with characteristics of public welfare 201 0.100 Clinics Primary medical and health service institutions, no inpatient beds 2514 0.075 Pharmacies Facility for daily drug purchase 3101 0.100 Fitness Facilities Sports Venues Swimming pools, football fields, basketball courts, badminton courts, table tennis courts, etc. 1120 0.175 Sports Zones Places where people play sports in the community, usually small in area 858 0.200 Parks and Squares Parks: public green space with facilities and a green environment for the public to visit and carry out physical exercise Squares: open spaces for all kinds of activities 1248 0.250 Note: “Total quantity” is the POI quantity of facilities within the study area. ijerph-19-05028-t002_Table 2 Table 2 Basic profile of the sample (n = 371). n Weighted (%) Gender Male Female 186 185 50.1 49.9 Age (years) Young (18–44) Middle-aged (45–59) 293 56 79.0 15.1 Old (≥60) 22 5.9 Education High school degree or below Junior college Bachelor degree or above 102 78 191 27.5 21.1 51.4 Permanent job Yes No 248 123 66.8 33.2 Annual income (RMB) <50,000 50,000–100,000 >100,000 133 138 100 35.8 37.2 27.0 Type of dwelling Low-end Mid-range High-end 60 256 18 16.2 69.0 4.8 Unit/dormitory 37 10.0 ijerph-19-05028-t003_Table 3 Table 3 KMO and Bartlett sphere tests. KMO Test Bartlett Sphere Test Chi-Square Value Degree of Freedom Significant Level 0.861 7711.709 496 0.000 ijerph-19-05028-t004_Table 4 Table 4 Descriptive statistics of the resident satisfaction scores. Accessibility Satisfaction Mean SD Service Satisfaction Mean SD Parks and Squares 3.60 1.276 Parks and Squares 3.43 1.322 Sports Venues 2.94 1.606 Sports Venues 2.91 1.651 Sports Zones 2.99 1.605 Sports Zones 2.87 1.690 General Hospitals 3.17 1.408 General Hospitals 3.17 1.476 Specialized Hospitals 2.82 1.603 Specialized Hospitals 2.76 1.696 Community Hospitals 3.15 1.522 Community Hospitals 3.08 1.546 Clinics 3.28 1.518 Clinics 3.19 1.548 Pharmacies 3.64 1.342 Pharmacies 3.54 1.383 Overall Degree 3.20 1.114 Overall Degree 3.12 1.214 ijerph-19-05028-t005_Table 5 Table 5 Ordinal logistic model parameters for satisfaction with accessibility. Parks and Squares Sports Venues Sports Zones General Hospitals Specialized Hospitals Community Hospitals Clinics Pharmacies Gender Male 1.131 0.809 0.907 0.886 0.843 0.911 0.870 0.867 Female — — — — — — — — Age Young 2.210 * 3.251 ** 4.651 *** 2.936 ** 2.092 2.445 * 3.755 *** 3.881 *** Middle-aged 4.035 *** 2.354 * 4.402 *** 2.273 * 1.868 2.992 ** 5.124 *** 7.221 *** Old — — — — — — — — Permanent job Yes 1.718 ** 1.697 ** 2.069 *** 1.365 1.313 1.473 * 1.590 ** 1.788 *** No — — — — — — — — Education High school degree or below 0.937 0.912 1.001 0.661 * 0.847 0.925 1.026 0.986 Junior college 1.373 0.948 1.556 * 0.897 1.123 1.106 1.254 1.314 Bachelor’s degree or above — — — — — — — — Annual income (RMB) <50,000 1.784 ** 0.902 1.239 1.142 0.970 1.528 1.379 2.030 ** 50,000–100,000 0.961 0.715 0.944 0.765 1.046 0.951 1.039 0.879 >100,000 — — — — — — — — Type of dwelling Low-end 0.659 0.887 0.697 0.879 0.991 0.706 0.860 0.610 Mid-range 0.862 0.736 0.777 0.791 0.757 0.960 0.754 0.811 High-end 0.596 0.613 0.544 0.770 0.467 0.495 0.298 ** 0.397 * Unit/dormitory — — — — — — — — Note: The values in the table are OR values. ***, **, and * represent p < 0.01, p < 0.05, and p < 0.10, respectively. When respondents filled out the questionnaire, 1 USD = 6.8148 RMB. ijerph-19-05028-t006_Table 6 Table 6 Ordinal logistic model parameters for satisfaction with service. Parks and Squares Sports Venues Sports Zones General Hospitals Specialized Hospitals Community Hospitals Clinics Pharmacies Gender Male 1.011 0.961 1.203 0.999 1.130 0.981 1.077 0.771 Female — — — — — — — — Age Young 1.531 3.414 *** 5.624 *** 3.428 *** 3.508 *** 4.450 *** 5.557 *** 2.826 ** Middle-aged 1.950 1.878 3.232 ** 3.149 ** 2.866 ** 4.459 *** 5.217 *** 4.162 *** Old — — — — — — — — Permanent job Yes 2.102 *** 1.525 ** 1.879 *** 1.702 ** 1.198 1.174 1.464 * 1.324 No — — — — — — — — Education High school degree or below 0.839 1.225 1.411 0.958 1.339 1.046 1.094 0.773 Junior college 1.112 1.530 * 1.694 ** 1.342 1.649 ** 1.240 1.448 0.999 Bachelor’s degree or above — — — — — — — — Annual income <50,000 2.358 *** 1.373 1.287 1.759 * 1.204 1.621 1.718 * 1.702 * 50,000–100,000 1.184 1.175 1.023 1.106 0.912 0.870 1.141 0.950 >100,000 — — — — — — — — Type of dwelling Low-end 0.831 1.242 0.778 1.326 1.017 0.788 0.95 1.033 Mid-range 0.952 1.250 1.208 1.820 * 0.857 1.065 0.907 1.309 High-end 0.930 1.358 0.656 1.281 0.512 0.595 0.386 * 0.597 Unit/dormitory — — — — — — — — Note: The values in the table are OR values. ***, **, and * represent p < 0.01, p < 0.05, and p < 0.10, respectively. When respondents filled out the questionnaire, 1 USD = 6.8148 RMB. ijerph-19-05028-t007_Table 7 Table 7 Regression analysis of satisfaction with accessibility. Parks and Squares Sports Venues Sports Zones General Hospitals B P B P B P B P Constant 0.000 0.000 0.000 0.000 Frequency 0.066 0.236 0.063 0.240 0.021 0.686 0.008 0.888 Expected distance −0.261 0.000 *** −0.174 0.001 *** −0.252 0.000 *** −0.194 0.001 *** Degree of convenience −0.037 0.500 −0.059 0.259 0.027 0.586 0.105 0.065 * Walking 0.160 0.012 ** 0.248 0.000 *** 0.311 0.000 *** 0.063 0.272 Nonmotor vehicles −0.045 0.431 0.154 0.004 *** 0.153 0.004 *** −0.009 0.870 Public transport 0.014 0.810 0.170 0.003 *** 0.175 0.002 *** 0.016 0.788 Private cars 0.036 0.535 −0.007 0.904 0.041 0.458 −0.033 0.590 Specialized Hospitals Community−Hospitals Clinics Pharmacies B P B P B P B P Constant 0.000 0.000 0.000 0.000 Frequency 0.011 0.839 0.114 0.034 ** 0.039 0.451 0.009 0.864 Expected distance −0.202 0.000 *** −0.238 0.000 *** −0.323 0.000 *** −0.382 0.000 *** Degree of convenience 0.026 0.619 −0.014 0.783 −0.009 0.853 −0.035 0.503 Walking 0.061 0.270 0.221 0.000 *** 0.264 0.000 *** 0.195 0.001 *** Nonmotor vehicles 0.089 0.098 * 0.091 0.095 * 0.030 0.554 0.040 0.450 Public transport 0.016 0.782 0.068 0.230 0.091 0.085 *** 0.016 0.774 Private cars 0.089 0.121 0.016 0.779 0.063 0.226 0.056 0.321 Note: B: Standardized coefficient. ***, **, and * represent p < 0.01, p < 0.05, and p < 0.10, respectively. ijerph-19-05028-t008_Table 8 Table 8 Paired Sample Tests. Correlation of Paired Samples Paired Sample t-Test Objectively Measured Average—Perceived Average N Correlation P Mean Standard Error Sig. (2-Tailed) Parks and Squares 258 0.047 0.453 0.0426 1.821 0.707 Sports Venues 210 −0.085 0.220 −1.3095 1.836 0.000 Sports Zones 227 0.148 0.026 −0.7400 1.556 0.000 General Hospitals 232 0.123 0.061 0.0948 1.733 0.406 Specialized Hospitals 186 0.082 0.264 −1.0806 1.862 0.000 Community Hospitals 224 0.060 0.372 0.7098 1.751 0.000 Clinics 239 0.083 0.198 1.0251 1.709 0.000 Pharmacies 255 0.031 0.628 0.7647 1.609 0.000 ijerph-19-05028-t009_Table 9 Table 9 Disordered logistic regression analysis of objective and perceptual measurements of accessibility of and accessibility satisfaction with health service facilities. Objective Measurement Perceptual Measurement Satisfaction Level OR 95% CI p-Value OR 95% CI p-Value Sports Venues 1 0.786 0.37–1.69 0.536 4.727 × 10−9 2 0.852 0.51–1.43 0.544 0.295 0.17–0.51 0.000 3 0.866 0.61–1.24 0.427 0.396 0.27–0.58 0.000 4 1.367 0.91–2.05 0.130 0.520 0.36–0.75 0.001 General Hospitals 1 0.304 0.06–1.61 0.162 0.194 0.04–1.00 0.050 2 0.520 0.31–0.87 0.013 0.555 0.37–0.84 0.005 3 1.223 0.90–1.67 0.203 0.585 0.43–0.79 0.001 4 0.967 0.71–1.31 0.827 0.594 0.44–0.80 0.001 Clinics 1 0.833 0.31–2.23 0.716 1.197 × 10−9 2 0.668 0.42–1.07 0.093 0.410 0.22–0.75 0.004 3 0.868 0.67–1.13 0.299 0.525 0.35–0.80 0.003 4 0.943 0.74–1.20 0.636 0.579 0.39–0.86 0.007 ijerph-19-05028-t010_Table 10 Table 10 Ordered logistic regression analysis of objectively measured and perceived measurement accessibility and accessibility satisfaction of health service facilities. Objective Measurement Perceptual Measurement OR 95% CI p-Value OR 95% CI p-Value Parks and Squares 1.100 −0.07–0.27 0.272 1.608 0.29–0.65 0.000 Sports Zones 1.006 −0.21–0.23 0.954 1.672 0.30–0.73 0.000 Specialized Hospitals 1.243 0.00–0.43 0.045 1.467 0.18–0.59 0.000 Community Hospitals 1.194 −0.01–0.37 0.065 1.751 0.34–0.78 0.000 Pharmacies 1.089 −0.09–0.26 0.344 1.932 0.42–0.90 0.000 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. World Health Organization World Health Statistics World Health Organization Geneva, Switzerland 2006 2. Giles-Corti B. Vernez-Moudon A. Reis R. Turrell G. Dannenberg A.L. Badland H. Foster S. Lowe M. Sallis J.F. Stevenson M. City planning and population health: A global challenge Lancet 2016 388 2912 2924 10.1016/S0140-6736(16)30066-6 27671668 3. Anderson R.M. Heesterbeek H. Klinkenberg D. Hollingsworth T.D. 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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/ijerph19095012 ijerph-19-05012 Article Long-Term Health Impacts of Wildfire Exposure: A Retrospective Study Exploring Hospitalization Dynamics Following the 2016 Wave of Fires in Israel https://orcid.org/0000-0002-2427-6381 Cohen Odeya 1* https://orcid.org/0000-0001-6258-4935 Shapira Stav 2 Furman Eyal 3 Saez Marc Academic Editor 1 Department of Nursing, Recanati School for Community Health Professions, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, Beer Sheva 8410501, Israel 2 School of Public Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, Beer Sheva 8410501, Israel; stavshap@bgu.ac.il 3 Maccabi Healthcare Services, Haifa 3508510, Israel; furman_e@mac.org.il * Correspondence: odeyac@bgu.ac.il; Tel.: +972-86477737 20 4 2022 5 2022 19 9 501213 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/). Background: Climate-related events, including wildfires, which adversely affect human health, are gaining the growing attention of public-health officials and researchers. Israel has experienced several disastrous fires, including the wave of fires in November 2016 that led to the evacuation of 75,000 people. The fires lasted six days (22–27 November) with no loss of life or significant immediate health impacts. The objective of this study is to explore the long-term hospitalization dynamics in a population exposed to this large-scale fire, including the effects of underlying morbidity and socio-economic status (SES). Methods: This is a retrospective crossover study, conducted in 2020, analyzing the electronic medical records of residents from areas exposed to a wildfire in northern Israel. The study spans from one year before exposure to two years after it (22 November 2015–27 November 2018). The hospitalization days during the study period were analyzed using the Poisson regression model. The rate of hospitalization days along with 95% confidence intervals (CIs) were plotted. Results: The study included 106,595 participants. The median age was 37 (IQR = 17–56), with a mean socio-economic ranking of 6.47 out of 10 (SD = 2.01). Analysis revealed that people with underlying morbidity were at greater risk of experiencing long-term effects following fires, which was manifested in higher hospitalization rates that remained elevated for two years post-exposure. This was also evident among individuals of low socio-economic status without these background illnesses. Conclusions: Healthcare services should prepare for increased hospitalization rates during the two years following wildfires for populations with underlying morbidity and those of low socio-economic status. Implementing preventive-medicine approaches may increase the resiliency of communities in the face of extreme climate-related events and prevent future health burdens. Additional research should focus on the specific mechanisms underpinning the long-term effects of wildfire exposure. climate change natural disasters wildfires long-term health impact socio-economic factors healthcare utilization ==== Body pmc1. Introduction Wildfires are known to adversely affect human health through a variety of mechanisms and are thus gaining attention as a major public health concern [1,2,3,4]. Their main—and most studied—influence on human health is exposure to smoke containing elevated ambient air pollutants [5]. Despite some inconsistencies, epidemiological evidence has broadly associated smoke exposure with respiratory and cardiovascular morbidity, all-cause mortality [6]; ophthalmic effects such as eye irritation [7]; and adverse pregnancy and birth outcomes such as increased preterm deliveries, low birth weight, and stillbirths [8,9]. Other reported mechanisms that lead to harmful health effects are related to direct flame and heat exposure causing burns [10]. Water and land pollution resulting from the incineration of various materials may also lead to toxic chemical exposure [11,12]. Decreased access to healthcare services may also occur due to traffic congestion caused by population evacuation [13], or the need to evacuate healthcare institutions directly impacted by the fire [14], potentially leading to delays in receiving medical aid or disruptions to the continuity of routine care. Population evacuation may also lead to difficulty accessing vital resources such as food and water [15]—posing a significant threat to vulnerable populations such as young children and those suffering from chronic illnesses requiring special nutrition, such as diabetics. Most studies concerning the health effects associated with exposure to wildfires have focused on short-term outcomes, with relatively sparse evidence of long-term health consequences. A recent review that evaluated the long-term health impacts and health needs among populations exposed to wildfires reported an increased risk of premature deaths, respiratory complications, and population-based increases in cancer risk [16]. However, the researchers stressed that the existing evidence is scant and pointed to significant gaps in the literature concerning the demographic profile of vulnerable populations such as medically vulnerable and socially disadvantaged populations, despite evidence that these populations are more susceptible to the adverse effects of wildfires [1,2,6]. Another recent Canadian study examined the effects of an extreme wildfire on the long-term mental health of the population that was evacuated. The findings indicated relatively increased rates of major depressive disorder, anxiety, and post-traumatic stress disorder eighteen months following exposure. Limited or non-existent social and municipal support after the wildfire was associated with an increased likelihood of experiencing adverse mental impacts [17]. Climate change has resulted in prolonged and more frequent heatwaves, increasing the frequency and intensity of wildfires [18]. Israel has experienced several disastrous and deadly fires including the 2010 mega-fire on Mount Carmel, and the wave of fires in November 2016—the focus of the present study. The 2016 wave of fires lasted six days (22–27 November) and in terms of property and environmental damage, this wave of fires is considered the worst in the history of Israel. Over 1700 fires were reported in various locations across the country. More than 10,000 acres were burned, and approximately 2000 residential structures were damaged. Of these, approximately 600 were destroyed completely. The largest and most destructive fires spread across the city of Haifa, the third-largest city in Israel with a population of 280,000 residents. The spread of the fires led to the evacuation of 68,000 people, almost 25% of the urban population in the Haifa Bay region [19]. Despite extensive damage, no loss of life or significant direct health impacts were reported. As projections indicate the Mediterranean region to become dryer and warmer, resulting in increased fire risk [20], it is important to study the health effects of wildfires and identify those populations most susceptible to such events. Based on former studies, hospitalization rates are a common indicator for evaluating the impact of wildfires on human health, with clinical and logistical implications for preparedness [5,6,21]. This study aims to explore long-term hospitalization dynamics in a population that was exposed to a large-scale fire, including the effects of underlying morbidity and socio-economic status on hospitalizations. 2. Materials and Methods 2.1. Design and Setting of the Study—A Retrospective Study 2.1.1. Data Collection Maccabi Health Services (MHS) is Israel’s second-largest health fund, providing medical services to 2.3 million members, about one-quarter of the Israeli population. In the northern district of MHS, there are 430,000 members with socio-demographic characteristics similar to the general population in terms of age, gender, ethnicity, and socio-economic status. Healthcare in Israel is primarily provided at the community level, by a large network of community-based clinics [22]. A primary clinic is assigned to each MHS member, usually based on geographical proximity to the member’s home. For this project, we relied on MHS data retrieved in January 2020 to obtain information on 106,595 members whose primary clinic was in the area impacted by the 2016 wildfires in the Haifa Bay area. As detailed in the previous section, the entire city of Haifa was highly impacted by the wildfires. Several combustion events occurred within the city itself, wreaking havoc, producing heavy smoke in several neighborhoods, and leading to massive population evacuation. Thus, our inclusion criteria were: (1) residents of areas that had been evacuated in the fire of 2016; (2) belonging to MHS clinics in those areas. We used a continuous sampling method in which a potential participant who met the general inclusion criteria entered the study without further constraints. For each study participant, we obtained information on:(A) Morbidity factors based on established MHS registries—We used MHS registries for four chronic morbidities for each patient: cardiovascular, obstructive pulmonary disease, overweight, and diabetes. We chose to focus on these specific morbidities following the well-documented short-term impacts of wildfires on them [4,6,7]. Overweight was chosen due to its increased prevalence in the general population and the association of obesity with other non-communicable diseases. The registries are updated automatically every day, drawing data from many sources: diagnoses, hospital discharge codes, billing information from providers, and prescription information [23]. The study population was divided into two sub-populations: the offset population that did not appear in any of these registries at the time of exposure (n = 56,966, 54%), and those with one or more of the chronic morbidities described above at the time of exposure (n = 49,629, 46%). In this study, we did not measure co-morbidity because our pre-analysis to examine the impact of each chronic condition on the hospitalization rate during the study periods revealed similar findings for each. (B) Hospitalization over a three-year period—We included the hospitalization days (based on the number of overnight stays) from all types of Israeli hospitals in all wards, except the maternity wards. The hospitalization information spanned from one year pre-exposure (22 November 2015) to two years post-exposure (27 November 2018). (C) Personal characteristics (age and gender). (D) Socio-economic status (SES) on a scale of 1–10 (1 = low to 10 = high), based on a poverty index calculated for each residential location. The enumeration area was calculated for each location based on a geographical unit (usually consisting of several thousand individuals) defined by the Israeli Central Bureau of Statistics, based on the homogeneity of the socio-demographic characteristics of the residing population. The poverty index is based on several factors, including: educational level, physical conditions, household income, crowding, and car ownership [24]. The study was approved by MHS’s Institutional Review Board for the Protection of Human Subjects (0028-19-MHS). 2.1.2. Statistical Analysis Descriptive statistics were used to characterize the study population. SES was divided into three sub-populations: low (1–4), medium (5–7), and high (8–10). The hospitalization dynamic over the study periods was analyzed through three methods: (1) The means of hospitalization days over study periods. (2) A generalized linear model with family set to Negative Binomial, and log link was used as an approximation to Poisson regression with zero inflation. The dependent variable was the number of hospitalization days during the pre-exposure year, the year after the exposure, and two years after the exposure. The independent variables included: age; gender; time-varying indicators for the three time periods; SES categories, and an indicator variable for individuals who appeared in at least one of the morbidity registries mentioned above, with second-order interactions between time periods, SES categories, and morbidity. (3) The rates of hospitalization days along with 95% confidence intervals (CIs) were plotted based on the estimated means of hospitalization days from the regression model. 3. Results The study included 106,595 participants, of whom 51.8% were women (n = 55,291), with a median age (in 2016) of 37 (IQR = 17–56). Table 1 describes the socio-demographic characteristics of the study population. The mean amount of hospitalization days over each of the study periods was: (a) during the pre-exposure year: 0.15 (SD = 0.67) days; (b) during the first year post-exposure: 0.17 (SD = 0.75) days; and (c) through the second year post-exposure: 0.15 (SD = 0.70) days. About 46% (n = 49,629) of the participants appeared in one registry or more. Table 2 presents the socio-demographic characteristics of the participants in each registry. Participants with obstructive pulmonary disease had a higher median age of 70 (IQR = 64–77) and the lowest SES 6.19 (SD = 2.21, 2–10). Overweight participants had a lower median age = 50 (IQR = 36–62). Fewer than 50% of the participants with cardiovascular diseases were women (40.6%). The percentage of participants born in Israel was lower in all registries than their ratio in the study population. The results of the Poisson regression model are presented in Table 3 (Likelihood Ratio Chi-Square = 28,781.334, df = 19, p < 0.001). Among the main effects, age at the time of exposure and gender (male vs. female) were risk factors. In regard to study periods, the two years post-exposure show a significant risk compared to the pre-exposure year. Among main effects and interactions, underlying morbidity presented the highest risk (exp(B) = 1.593, 95% CI 1.466–1.730). High SES was found as a protective factor compared to low SES (exp(B) = 0.678, 95% CI 0.621–0.741). Based on the estimated means of the regression model, hospitalization patterns both pre- and post-exposure revealed that participants with underlying morbidity show an increase in hospitalization rates that persists two years post-exposure. Furthermore, the disparity in hospitalization rates between the low and high SES groups increased from 54% pre-exposure to 61% at two years post-exposure. Among participants with no underlying morbidity, only those of low SES demonstrated a significant increase in hospitalization rates post-exposure, from a disparity of 57% pre-exposure to 75% at two years post-exposure. Figure 1 and Table A1 present the hospitalization rates (along with 95% CIs) during study periods according to sub-population SES. 4. Discussion This study was designed to explore the long-term effects of exposure to a large-scale fire, comparing pre- and post-exposure hospitalization dynamics. The results indicate that individuals with underlying morbidity and those with low SES are at increased risk for experiencing long-term health effects, which manifested in higher hospitalization rates that remained elevated for two years post-exposure. Another important finding relates to the growing gap in hospitalization rates between the low and high SES groups. These findings demonstrate the compounding long-term effects on both health and healthcare utilization following wildfires. Furthermore, the current results stress that structural conditions of disadvantage (i.e., low SES) undermine the recovery capacities of populations exposed to natural disasters such as wildfires [25]. The results resonate with previous studies which indicated that medically vulnerable and socially disadvantaged populations are susceptible to the immediate impacts of wildfires including health consequences [5,6], property damage, and other economic impacts such as loss of livelihood [26]. With regard to the long-term effects of wildfire exposure, there is well-known difficulty in determining causality as well as in identifying the specific mechanisms and pathways linking exposure and outcome [27]. In the current context, one can speculate that additional personal or environmental factors—that may have changed over the study period and were not controlled in the current analysis—have also contributed to the long-term changes in hospitalization dynamics observed. A particular example of such a factor is the well-documented exposure to air pollutants from the petrochemical industry located in the Haifa Bay [28]. However, the present study clearly indicates that the contribution of the initial exposure, especially when combined with specific pre-existing risk factors, should not be overlooked, and further raises important questions regarding the specific mechanisms underpinning the observed changes. An additional limitation of this study is related to the nature of the data and the use of the participants’ primary clinic address as a proxy for personal exposure to the wildfires. This method does not allow for a clear verification of the participants’ presence in the Haifa Bay during the event and may lead to a potential bias. However, our study relates to ‘exposure’ in this specific context in a broad sense—i.e., even if a person was not present during the event itself, he/she was probably indirectly impacted, for example, through experiencing property damage, or even by witnessing the destruction caused to their residential environment. Thus, a possible path to long-term health deterioration following wildfires may stem from the psychological effects of these devastating events. A recent review pointed to the far-reaching mental health effects of wildfire exposure, revealing elevated rates of various conditions such as anxiety, depression, and insomnia between 6 and 18 months following a massive wildfire in Canada [29]. These findings were supported by two other Israeli studies. One study found increased mental distress among firefighters who responded to the 2010 Mount Carmel fire during the three years following the fire [30]. Another study reported elevated levels of distress among community-dwelling individuals affected by the fire explored in this current study four months following the fire [31]. Ample evidence identifies the strong link between mental disorders and physical health [32]; this association is even stronger among individuals with chronic health conditions such as COPD [33], diabetes [34], and cardiovascular diseases [35]. Thus, it is possible that mental health effects following exposure to the 2016 wave of fires played a crucial role in the long-term adverse health effects that were shown in the current study. This remains an issue for further exploration. In a broader context, as the frequency and intensity of climate-related extreme events are expected to increase, it is of the utmost importance to invest time and resources into mitigating their adverse health effects [2]. One course of action to mitigate the long-term outcomes of wildfire exposure would be to improve the delivery of preventive services in the primary-care setting provided in the community. This would reduce morbidity in the pre-exposure phase, especially among vulnerable populations such as socio-economically deprived individuals, and potentially have an effect on the health outcomes of disadvantaged populations both on a daily basis and, as suggested by our results, following emergencies. Additionally, future studies should focus on the mechanisms underpinning long-term health effects following wildfire exposure. Gaining such understanding will advance current knowledge regarding determinants of disaster vulnerability and health risks. 5. Conclusions Despite the limitations mentioned above, the current study was exploratory and provided new evidence of the long-term adverse health consequences of wildfire exposure. The World Health Organization (WHO) called for vulnerable populations to be assessed and for interventions to be specified in response to climate-related events [36]. We suggest that healthcare services should prepare for increased hospitalization rates at least two years post-event for these populations. Increasing preventive activities in community healthcare settings offers a potential path for mitigating the expected long-term health impacts of wildfires, especially among low-SES populations and those who suffer from poor health. Combining these insights when planning future health services can help communities increase their resilience to wildfires and other climate-related extreme events and prevent likely future health burdens. Acknowledgments The authors would like to thank Diklah Geva, integriStat Tel Aviv, for her assistance in data analysis. Author Contributions Conceptualization, O.C. and E.F.; methodology, O.C. and S.S.; formal analysis, O.C. and S.S.; resources, E.F.; data curation, E.F. and O.C.; writing—original draft preparation, O.C. and S.S.; writing—review and editing, O.C., S.S. and E.F.; visualization, O.C.; supervision, O.C. and E.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 approved by MHS’s Institutional Review Board for the Protection of Human Subjects (0028-19-MHS). Informed Consent Statement Patient consent was waived due to the retrospective nature of the study and the anonymous data analysis. Data Availability Statement The data that support the findings of this study are available from Maccabi Health Services (MHS), but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are, however, available from the authors upon reasonable request and with the permission of MHS. Conflicts of Interest The authors declare no conflict of interest. Appendix A ijerph-19-05012-t0A1_Table A1 Table A1 Estimated means of hospitalization rates during study periods based on a Poisson regression model. Socio-Economic Status Period Hospitalization Rate Mean 95% Wald Confidence Interval Lower Upper Participants with underlying morbidity (n = 49,629) High One year pre-exposure 0.11 0.11 0.11 One year post-exposure 0.13 0.12 0.13 2nd year post-exposure 0.13 0.13 0.14 Medium One year pre-exposure 0.15 0.14 0.15 One year post-exposure 0.16 0.16 0.17 2nd year post-exposure 0.17 0.17 0.18 Low One year pre-exposure 0.17 0.17 0.18 One year post-exposure 0.19 0.19 0.20 2nd year post-exposure 0.21 0.20 0.21 Participants with no background illnesses (n = 56,966) High One year pre-exposure 0.07 0.07 0.08 One year post-exposure 0.08 0.08 0.09 2nd year post-exposure 0.08 0.08 0.08 Medium One year pre-exposure 0.10 0.10 0.11 One year post-exposure 0.11 0.10 0.11 2nd year post-exposure 0.10 0.10 0.11 Low One year pre-exposure 0.11 0.10 0.12 One year post-exposure 0.14 0.13 0.15 2nd year post-exposure 0.14 0.13 0.15 Figure 1 Hospitalization rates by SES and morbidity status based on estimated means of Poisson regression during the study period (2015–2018). ijerph-19-05012-t001_Table 1 Table 1 Socio-demographic characteristics of the study population. Variable Study Population (n = 106,595) n % Gender Female 55,291 51.8 Male 51,304 48.1 Country of birth Israel 76,735 72.0 Other 29,860 28.0 Median age at exposure 37 (IQR = 17–56) Mean SES at exposure 6.74 (SD = 2.01, rank 2–10) Registry Cardiovascular 7925 7.4 Overweight 36,850 34.6 Obstructive pulmonary disease 1253 1.2 Diabetes 27,425 25.7 ijerph-19-05012-t002_Table 2 Table 2 Socio-demographic characteristics of study participants in different registries. Disease Variable Cardiovascular n = 7925 (7.4%) Median age 69 (IQR = 57–78) SES 6.47 (SD = 2.18, 2–10) Gender Male 4706 (59.4%) Birth country Israel 3856 (48.7%) Obstructive pulmonary disease n = 1253 (1.2%) Median age 70 (IQR = 64–77) SES 6.19 (SD = 2.21, 2–10) Gender Male 596 (47.6%) Birth country Israel 556 (44.4%) Diabetes n = 27,425 (25.7%) Median age 61 (IQR = 50–79) SES 6.39 (SD = 2.53, 2–10) Gender Male 12,605 (46%) Birth country Israel 13,623 (49.7%%) Overweight n = 36,850 (34.6%) Median age 50 (IQR = 36–62) SES 6.51 (SD = 2.11, 2–10) Gender Male 18,789 (51%) Birth country Israel 22,801 (61.9) ijerph-19-05012-t003_Table 3 Table 3 Results of the final regression model. Variables B Exp(B) 95% Confidence Interval for Exp(B) Sig. Lower Upper Gender Male 0.081 1.085 <0.001 1.064 1.106 Female 1 Age at exposure (years) 0.028 1.028 <0.001 1.028 1.029 Study periods 2nd year post exposure 0.240 1.272 <0.001 1.154 1.401 1st year post-exposure 0.220 1.246 <0.001 1.130 1.372 One year pre-exposure 1 Registry With underlying morbidity 0.465 1.593 <0.001 1.466 1.730 With no underlying morbidity 1 SES categories High −0.388 0.678 <0.001 0.621 0.741 Medium −0.066 0.936 0.141 0.857 1.022 Low 1 Interactions With morbidity × High SES × 2nd year post-exposure −0.138 0.871 0.121 0.732 1.037 With morbidity × High SES × 1st year post-exposure −0.156 0.856 0.080 0.719 1.019 With morbidity × High SES × 1 year pre-exposure −0.069 0.933 0.188 0.842 1.034 With morbidity × Medium SES × 2nd year post-exposure −0.190 0.827 0.032 0.696 0.983 With morbidity × Medium SES × 1st year post-exposure −0.218 0.804 0.014 0.676 0.957 With morbidity × Medium SES × 1 year pre-exposure −0.106 0.899 0.041 0.812 0.996 With morbidity × Low SES × 2ndyear post-exposure −0.074 0.928 0.186 0.831 1.037 With morbidity × Low SES × 1st year post-exposure −0.119 0.888 0.036 0.795 0.992 With morbidity × Low SES × 1 year pre-exposure 1 With no morbidity × High SES × 2nd year post-exposure −0.167 0.847 0.006 0.751 0.954 With no morbidity × High SES × 1st year post-exposure −0.091 0.913 0.138 0.810 1.030 With no morbidity × High SES × 1 year pre-exposure 1 With no morbidity × Medium SES × 2nd year post-exposure −0.220 0.802 <0.001 0.711 0.905 With no morbidity × Medium SES × 1st year post-exposure −0.160 0.852 0.009 0.755 0.961 With no morbidity × Medium SES × 1 year pre-exposure 1 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092294 jcm-11-02294 Article Myopia Control Effect Is Influenced by Baseline Relative Peripheral Refraction in Children Wearing Defocus Incorporated Multiple Segments (DIMS) Spectacle Lenses https://orcid.org/0000-0003-4932-1887 Zhang Hanyu 12 https://orcid.org/0000-0002-6808-5018 Lam Carly S. Y. 12* Tang Wing-Chun 1 Leung Myra 3 Qi Hua 4 https://orcid.org/0000-0002-5729-6450 Lee Paul H. 5 https://orcid.org/0000-0002-1938-8397 To Chi-Ho 12 Pereira António Queirós Academic Editor 1 Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong SAR, China; andrea.zhang@cevr.hk (H.Z.); wing922tang@gmail.com (W.-C.T.); chi-ho.to@polyu.edu.hk (C.-H.T.) 2 Centre for Eye and Vision Research (CEVR), Hong Kong SAR, China 3 Discipline of Optometry and Vision Science, Faculty of Health, University of Canberra, Canberra 2617, Australia; myra.leung@canberra.edu.au 4 Hoya Corporation, Tokyo 1608347, Japan; hua.qi@hoya.com 5 Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK; paul.h.lee@leicester.ac.uk * Correspondence: carly.lam@polyu.edu.hk 20 4 2022 5 2022 11 9 229410 3 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/). The aim of this study is to investigate if baseline relative peripheral refraction (RPR) influences the myopia control effects in Chinese myopic children wearing Defocus Incorporated Multiple Segments (DIMS) lenses. Peripheral refraction at 10°, 20°, and 30° nasal (10 N, 20 N, 30 N) and temporal (10 T, 20 T, 30 T) retina were measured at six-month intervals for children who participated in a 2-year randomized controlled trial. The relationship between the baseline peripheral refractions and myopia progression and axial length changes were analysed. A total of 79 children and 81 children in the DIMS and single vision (SV) group were investigated, respectively. In the DIMS group, more baseline myopic RPR spherical equivalent (SE) was associated with more myopic progression (10 N: r = 0.36, p = 0.001; 20 N: r = 0.35, p = 0.001) and greater axial elongation (10 N: r = −0.34, p = 0.001; 20 N: r = −0.29, p = 0.006) after adjusting for co-factors. In the SV group, baseline RPR had association with only myopia progression (10 N: r = 0.37, p = 0.001; 20 N: r = 0.36, p = 0.001; 30 N: r = 0.35, p = 0.002) but not with axial elongation after Bonferroni correction (p > 0.008). No statistically significant relationship was found between temporal retina and myopia progression or axial elongation in both groups. Children with baseline myopic RPR had statistically significant more myopia progression (mean difference around −0.40 D) and more axial elongation (mean difference 0.15 mm) when compared with the children having baseline hyperopic RPR in the DIMS group but not in the SV group. In conclusion, the baseline RPR profile may not influence future myopia progression or axial elongation for the SV lens wearers. However, DIMS lenses slowed down myopia progression and was better in myopia control for the children with baseline hyperopic RPR than the children with myopic RPR. This may partially explain why myopia control effects vary among myopic children. Customised myopic defocus for individuals may optimise myopia control effects, and further research to determine the optimal dosage, with consideration of peripheral retinal profile, is warranted. myopia myopia control myopic defocus relative peripheral refraction ==== Body pmc1. Introduction The prevalence of myopia has increased substantially worldwide [1,2] in the last two decades, especially in Asia [3]. High myopia increases the risk of many ocular pathologies, such as glaucoma, retinal detachment, and chorioretinal degeneration, resulting in visual impairment and subsequent deterioration in the quality of daily life [4,5]. Apart from the central foveal area, the peripheral retina also appears to have an important function in emmetropisation [6,7]; animal studies suggest that peripheral myopic defocus can inhibit myopia progression [8], while peripheral hyperopic defocus can induce myopia progression [6,9]. It has been reported that myopic children wearing single vision (SV) spectacles lenses to correct myopia can result in increased hyperopic defocus at the peripheral retina [10], which could promote myopia progression. However, other studies argued that this phenomenon is unlikely to impact myopia progression [11]. Some optical devices applied myopic defocus as a potential way to slow myopia progression in human subjects [12,13,14]. These clinical trials reported that the Defocus Incorporated Soft Contact (DISC) lenses [12], MiSight soft contact lens (Cooper Vision, Inc., Pleasanton, CA, USA) [14], and Defocus Incorporated Multiple Segments (DIMS) spectacle lenses [13] all impose myopic defocus in the central and peripheral retina, with myopia progression being slowed by 50% to 60%. However, the optimal amount of myopic defocus has not yet been determined. Hyperopic relative peripheral refraction (RPR) has been observed in myopes in cross-sectional studies [15,16,17], while longitudinal studies indicated that changes in RPR, which is typically becoming more hyperopic, might be a consequence of myopia progression rather than a trigger for myopia [18,19,20]. It is not known if baseline RPR influences the result when using DIMS lenses for myopia control. The DIMS lens was designed with a best-corrected zone at the centre and surrounded by multiple segments of constant myopic defocus (+3.50 D) at the mid-periphery, providing clear central vision and peripheral myopic defocus simultaneously [13]. Using real ray tracing and wave optics calculations, we found that viewing a target through the defocus region of the lens leads to ghosting, and the level of ghosting depends on the relative refractive error at the retina [21]. When wearing DIMS lenses, children with lower baseline hyperopic RPR (or with higher myopic RPR) would experience more myopic defocus than children with higher hyperopic RPR. Although the DIMS lens is designed to provide constant myopic defocus of +3.50 D, children might receive a different amount of myopic defocus depending on their actual RPR across the retina. We hypothesised that baseline RPR could influence the effects of myopia control. Our previous paper described the characteristics of RPR in Chinese myopic children who participated in a myopia control clinical trial using the DIMS lens [22]. Thus, the current study aims to investigate the link between the baseline RPR and myopia control effects from wearing DIMS lenses and, in this way, provide further insights into optimising myopia control. 2. Materials and Methods 2.1. Measurements The children in the current study were participants in a 2-year randomised clinical trial, testing the efficacy of Defocus Incorporated Multiple Segments (DIMS) spectacle lenses for myopia control (Registration Number: NCT02206217) [13]. The recruitment period was from August 2014 to August 2015. All eye examinations and data collection were performed by a registered optometrist at the Centre for Myopia Research at the Hong Kong Polytechnic University. The study was approved by the Human Subject Ethics Sub-committee of the Hong Kong Polytechnic University and adhered to the tenets of the Declaration of Helsinki. Written informed consent was obtained from the parents or guardians of all participating children. Subject inclusion criteria were [13]:Age at enrolment: 8–13 years Central spherical equivalent refraction (SE): −1.00 to −5.00 D Astigmatism: up to 1.50 D Anisometropia: up to 1.25 D Exclusion criteria were: Strabismus and binocular vision abnormalities Ocular and systemic abnormalities Prior experience with myopia control Cycloplegia was induced by one drop of proparacaine (Alcaine 0.5%, Alcon Laboratories, Inc., Fort Worth, TX, USA), followed by 1–2 drops of cyclopentolate HCL 1% (Cyclogyl 1%, Alcon Laboratories, Inc.). Cycloplegic central refraction and peripheral refraction, across the horizontal retina, and corneal power (without cycloplegia) were measured using the Shin-Nippon NVision-K 5001 autorefractor (Ajinomoto Trading Inc., Tokyo, Japan). Central refractive error was measured with the child fixating on a Maltese cross-target placed 3 metres straight ahead [23]. Peripheral refraction was measured at 10°, 20°, and 30° nasally (10 N, 20 N, 30 N) and temporally (10 T, 20 T, 30 T) for the right eye while the left eye was covered. Both central and peripheral refraction were measured without correcting lenses. Axial length (AL) was measured using an IOL Master 500 (Carl Zeiss, Oberkochen, Germany). The standard procedure used for data collection has been described in our previous reports [13]. The spherocylindrical refractions (with the cylinder in negative form) in terms of spherical power (S), cylindrical power (C), and axis (θ) were converted into power vectors using a conventional formula for statistical analysis, namely [24]:SE = S + C/2 J0 = −(C/2) cos (2θ) J45 = −(C/2) sin (2θ) RPR at a particular eccentricity was calculated by subtracting the central refraction from the respective peripheral refraction. Subjects were subdivided into two subgroups according to baseline RPR: the myopic RPR (RPR ≤ 0 D) and hyperopic RPR (RPR > 0 D) group. Myopia progression and axial elongation over 2 years were further compared between myopic RPR and hyperopic RPR groups within the SV and DIMS group, respectively. 2.2. Data Analysis As there is a high correlation between right and left eyes, only right eye data were analysed [13]. All statistical analyses were performed using IBM SPSS v.16.0 (IBM Corporation, Armonk, NY, USA). The distribution of all data was not significantly different from normal for any of the variables measured (Kolmogorov-Smirnov p > 0.05), and data are expressed as mean ± standard deviation (SD). The relationships between baseline RPR (independent variable) and myopia progression and axial elongation were determined by multiple linear regression, adjusting for gender, age, and baseline refractive error or AL. Pearson correlation was used to investigate the relationship between baseline RPR, age, myopia progression, and axial elongation. One-way analysis of variance (ANOVA) was conducted to detect the difference in baseline RPR among ages; the Bonferroni post hoc test was applied if necessary. Paired t-tests were used to determine if there were differences in peripheral refraction between the nasal and temporal retina data. An independent t-test was used to compare the difference in myopia progression and axial elongation between children with myopic RPR and hyperopic RPR in the DIMS and SV group, separately. As six retinal eccentricities were being considered, a Bonferroni correction was applied, and the significance level was adjusted to 0.008 when analysing parameters related to peripheral refraction. 3. Results Data from 79 children and 81 children in the DIMS and SV group were analysed respectively. There was no statistically significant difference in baseline characteristic data between DIMS and SV groups [13]. 3.1. RPR SE At baseline, there was no statistically significant difference in RPR between DIMS and SV groups after Bonferroni correction (p > 0.008), and an asymmetrical pattern of RPR profile was found in both the DIMS and SV group. Hyperopic RPR SE was observed at most eccentricities across the horizontal retina, except at 10 T in both the DIMS (mean −0.03 ± 0.47 D) and SV group (mean −0.01 ± 0.35 D) (Figure 1). A broad range of hyperopic RPR SE was present at 30 N, ranging from 0.00 to 6.50 D (Figure 2). In the DIMS group, there was asymmetry in RPR SE between the temporal and nasal retina with a more hyperopic RPR SE at 10 N (mean difference: −0.19 ± 0.74, p = 0.03), 20 N (mean difference: 0.62 ± 1.36 D, p < 0.0001), and 30 N (mean difference: 0.61 ± 1.53 D, p = 0.007) compared with the temporal retina. Similarly, in the SV group, there was more hyperopic RPR SE at 10 N (mean difference: −0.15 ± 0.51, p = 0.009), 20 N (mean difference: 0.67 ± 1.06 D, p < 0.0001), and 30 N (mean difference: 1.09 ± 1.81 D, p < 0.001) than in the temporal retina. Only 20 N and 30 N showed a difference that reached a statistically significant level after Bonferroni correction (p < 0.008) in both groups. 3.2. RPR J0, J45 Relative astigmatism showed no statistically significant difference between the DIMS and SV groups at baseline. Relative J0 and relative J45 in both DIMS and SV groups showed a similar profile at baseline, without a statistically significant difference after Bonferroni correction (p > 0.008, Figure 1). Both relative J0 and relative J45 increased in magnitude with increasing eccentricity, and the change in magnitude of relative J45 was less than relative J0. There were no significant differences in relative J45 between the nasal and temporal retina in both groups (p > 0.05). An asymmetrical profile between the temporal and nasal retina was also found in relative J0, with relative J0 being more negative at the temporal retina than at the nasal retina in the DIMS group (10° mean difference: −0.28 ± 0.39 D, p < 0.0001; 20° mean difference: −0.59 ± 0.75 D, p < 0.0001; 30° mean difference: −0.94 ± 0.74 D, p < 0.0001) and SV group (10° mean difference: −0.28 ± 0.34 D, p < 0.0001; 20° mean difference: −0.77 ± 0.66 D, p < 0.0001; 30° mean difference: −1.22 ± 1.06 D, p < 0.0001). 3.3. RPR and Age There was no statistically significant difference in baseline RPR among different ages in the SV group and children older than 8 years in the DIMS group (ANOVA, p > 0.05). In the DIMS group, only the 8-year-old group had statistically significantly more myopic RPR than the 11-year-old group (Bonferroni post hoc test, mean difference: −0.65 ± 0.16 D, p = 0.002). The RPR profile among each age group is shown in Figure 3. Within each age group, there was no statistically significant difference in baseline RPR between DIMS and SV group after Bonferroni correction (Independent t-test, p > 0.008). 3.4. Relationship between Baseline RPR and Myopia Progression and Axial Elongation RPR at nasal retina showed a statistical association with myopia progression for both DIMS and SV groups, and statistical association with axial elongation in only the DIMS group (p < 0.0008 after Bonferroni correction) (Table 1, Figure 2). There was no statistically significant association of either relative J0 or J45 with myopia progression or axial elongation in both the DIMS and SV group (p > 0.05). In the DIMS group, baseline RPR SE at 10 N (multilinear regression, r = 0.36, p = 0.001) and 20 N (r = 0.35, p = 0.001) were positively associated with myopia progression (more baseline myopic RPR, more myopia progression), after adjusting for the co-factors of age, gender, and initial refractive error, and reached a statistically significant level after Bonferroni correction (Table 1). Baseline RPR was negatively associated with axial elongation (10 N, r = −0.35, p = 0.001; 20 N, r = −0.30, p = 0.004), after adjusting for the co-factors of age, gender, and initial axial length, and reached a significant level after Bonferroni correction (Table 1). In the SV group, baseline RPR SE at 10 N (r = 0.37, p = 0.001), 20 N (r = 0.36, p = 0.001), and 30 N (r = 0.35, p = 0.002) were positively associated with myopia progression after adjusted for co-factors (Table 1), but no statistically significant relationship between RPR and axial elongation was found after Bonferroni correction (p > 0.008) (Table 1). The correlation between RPR at the nasal retina and myopia progression and between RPR at the nasal retina and axial elongation in the DIMS and SV groups are illustrated, respectively, in Figure 2. 3.5. Comparison between Baseline Myopic RPR and Hyperopic RPR at 10 N and 20 N Subgroups Only the comparison in myopic RPR (10 N, 20 N) and hyperopic RPR (10 N, 20 N) was presented because other positions did not show a statistically significant correlation with myopia progression and axial elongation. In the SV group, there were no statistically significant differences in myopia progression (mean difference: −0.26 ± 0.14 D, p = 0.06) and axial elongation (mean difference: 0.04 ± 0.05 mm, p = 0.48) between the myopic RPR (n = 27) and hyperopic RPR (n = 54) groups at 10 N (Table 2). There was also no significant difference in myopia progression (mean difference: −0.25 ± 0.20 D, p = 0.19) and axial elongation (mean difference: 0.08 ± 0.08 mm, p = 0.27) between myopic RPR (n = 11) and hyperopic RPR (n = 70) groups at 20 N (Table 3). On the contrary, in the DIMS group, myopic RPR at the 10 N subgroup (n = 27) showed statistically significantly more myopia progression (mean difference: −0.36 ± 0.14 D, p = 0.009) and axial elongation (mean difference: 0.16 ± 0.05 mm, p = 0.001) than the hyperopic RPR at the 10 N subgroup (n = 52) (Table 2). Meanwhile, myopic RPR at the 20 N subgroup (n = 12) showed statistically significantly more myopia progression (mean difference: −0.40 ± 0.16 D, p = 0.01) and axial elongation (mean difference: 0.15 ± 0.07 mm, p = 0.02) than the hyperopic RPR at the 20 N subgroup (n = 67) (Table 3). In summary, there was a statistically significant difference in myopia progression and axial elongation between children with baseline myopic RPR and hyperopic RPR in the DIMS group but not in the SV group. 4. Discussion This study investigated baseline RPR and its influence on myopia control effect using the DIMS spectacle lens; this lens is designed to provide simultaneous vision correction and myopic defocus in the mid-periphery of the retina. In the 2 years, RCT has shown an efficacy of 52% in myopia retardation and 62% in less axial length growth [13]. A number of visual functions were shown not to be affected by wearing the DIMS lens [21]. The current study focused on peripheral refraction and how DIMS lens wear affects the change in peripheral refraction. Only horizontal peripheral refraction was measured, as previous studies found no significant association between myopia and peripheral refraction along the vertical meridian [16,25]. Our results suggest that, using the DIMS lens for myopia control, children with baseline hyperopic RPR showed less myopia progression and less axial elongation than children with baseline myopic RPR, which suggests that children with hyperopic RPR showed a more effective treatment effect. 4.1. RPR in Young Children Consistent with previous studies, there were no significant differences in baseline RPR among the ages in the SV group and children older than 8 years in the DIMS group [26]. Interestingly, 8-year-old children showed more myopic RPR at nasal retina compared with other ages in the DIMS group (Figure 3). 4.2. RPR in Relation with Myopia Progression and Axial Elongation Hyperopic RPR SE was observed at most eccentricities among myopic children and increased with eccentricity; these findings were consistent with the results from previous studies [15,16,25]. The RPR profile in myopic children was asymmetric, with more hyperopic RPR at the nasal retina than the temporal retina, and such asymmetry was also reported by previous studies [18,22]. The asymmetry pattern has been suggested to be related to asymmetries in vitreous chamber depth [9] or corneal curvature [25]. Although the association between baseline RPR, at the nasal retina, and myopia progression reached a statistically significant level after Bonferroni correction (p < 0.008), baseline RPR at the nasal retina only influenced less than 10% of myopia progression variation among the SV wearers (R2 < 0.10). The baseline RPR was not associated with axial elongation in the SV group. Similar results have also been reported by previous studies [20,27]. Atchison [27] followed a group of emmetropic, hyperopic, and myopic children, and found that, although myopes with myopic RPR at baseline were associated with more myopia progression, the emmetropes with myopic RPR at baseline remained emmetropic after the study [20,27]. They suggested that there was a shift from myopic RPR to hyperopic RPR when myopia developed together with eyeball stretching. RPR may not be a trigger of myopia progression [28,29] but a consequence of myopia development or progression, as the eyeball becomes more prolate during axial elongation [25]. Similarly, we also observed hyperopic shifts from myopic RPR to hyperopic RPR in the SV group over 2 years in our previous paper [22]. We further divided the children, according to their baseline RPR, into myopic RPR and hyperopic RPR subgroups. In the SV group, there was no statistically significant difference in myopia progression and axial elongation between myopic RPR and hyperopic RPR at 10 N and 20 N subgroups. Such findings indicate that, whether the baseline RPR profile was myopic or hyperopic, it may not influence future myopia progression or axial elongation for the SV lens wearers. 4.3. RPR in Myopia Control Using Myopic Defocus Our previous studies suggested that, inducing peripheral myopic defocus while simultaneously maintaining clear central vision, such as with the DISC contact lenses [12] or the DIMS spectacle lenses [13], would result in significant myopia control effects. The mechanism was based on the signals of the blur images generated by the myopic defocus received by the retina. This takes into account other factors such as the lag of accommodation [30]. Several studies have demonstrated a reasonable myopic control effect with myopic defocus power ranging from +1.25 D to +3.5 D [12,14,31,32]. If the retinal shape varies at different eccentricities, would the resultant myopic defocus power be different at different eccentric retinal positions? Furthermore, would the baseline RPR profile influence the effects of myopia control? It is possible that the initial RPR profile, when superimposed with myopic defocus (+3.50 D) from the DIMS lens, would have a different summation of defocus perceived by the eye at different locations of the retina. For the children with hyperopic RPR at the mid-periphery retina, the defocus power would counterbalance the existing hyperopic RPR. Therefore, less than +3.50 D myopic defocus would be perceived by the retina. However, for the children with myopic RPR, the existing myopic RPR combined with myopic defocus from the DIMS lens would lead to more than +3.50 D of myopic defocus. In the subgroup analysis, we found that children with baseline myopic RPR showed significantly more myopia progression and axial elongation than children with baseline hyperopic RPR. The mean myopia progression was −0.72 ± 0.64 D and the mean axial length growth was 0.34 ± 0.24 mm in the children with myopic RPR at 20 N in the DIMS lens group, and was −0.31 ± 0.48 D and 0.19 ± 0.20 mm in the children with hyperopic RPR at 20 N in the DIMS lens group, over 2 years. There was statistically significantly more myopia progression (mean difference −0.40 D) and more axial elongation (mean difference 0.15 mm) in the myopic RPR group than in the children with baseline hyperopic RPR. (Table 3) When compared with the SV group in the RCT (n = 81) who had no myopia control treatment, their mean myopia progression was −0.93 ± 0.06 D and mean axial length growth was 0.53 ± 0.03 mm [13]; it is apparent that children wearing the DIMS lens benefitted with less myopia progression, but the effect was more pronounced in children with hyperopic RPR. The results showed that children with myopic RPR had less effect on myopia control than children with hyperopic RPR, when receiving the additional myopic defocus exposure from the DIMS lens. In fact, in the DIMS group, 8- and 9-year-old children showed more baseline myopic RPR than the older age groups, and they showed less myopia control effects compared with the other age group who had baseline hyperopic RPR [13]. We have reported previously that the effects of myopia control with DIMS lenses have no association with a lag of accommodation, initial myopia, or parental myopia [13]. The possible explanation for the variation of the effectiveness of myopia control was due to the fact that the actual amount of myopic defocus, from the DIMS lenses, received by the eye was influenced by the initial RPR profile. Our findings pointed out that children with baseline myopic RPR might not benefit as much as the children with baseline hyperopic RPR when using DIMS lenses. Without the myopic defocus interference, as in the DIMS group, there was no age variation of myopia progression in the SV group. 4.4. The Effective Range of Myopic Defocus in Myopia Control The range of adequate defocus power to manipulate refractive error varies between animals, such as between −10 and +20 D in chicks [33], −30 to +5 D in mice [34], and −2 to +8 D in monkeys [35]. There is a decreasing range of defocus for eye compensation from mice, avian, to primate; thus, we assume that humans may have a narrow range of defocus power where eye growth can be manipulated. Garcia et al. [36] reported in a study that superimposing myopic defocus for compensating hyperopic RPR in myopes, in some cases, could degrade the peripheral image quality. DIMS lens wearers with baseline myopic RPR received too much myopic defocus at the mid-periphery retina, which can result in an overall peripheral image blur beyond the threshold of signal detection, and myopia control would therefore be less effective [37,38]. Berntsen et al. [39] studied whether peripheral defocus was associated with myopia progression and suggested that, although peripheral myopic defocus was associated with significantly less myopia progression, a higher amount of peripheral myopic defocus did not slow myopia progression as much when compared with lesser amounts of myopic peripheral defocus. A study imposing +4.00 D or −4.00 D lenses in guinea pigs found that myopia progression and axial elongation were enhanced when superimposing a +4.00 D peripheral myopic defocus lens [38]. This suggested that the local retinal area can decode whether it is a clear or blurred signal. If the defocus is above the threshold of signal detection, this function will fail, and might lead to myopia progression [38]. The depth of focus (DOF), which could represent the threshold of blur detection, has been investigated in a human study. It was reported that DOF increased with eccentricity [40] and DOF could reach ±6 D in the mid-periphery [41], which suggested that the amount of myopic defocus in myopia control lenses may need to be varied across the retinal eccentricities to maintain a myopic defocus image shell. The myopic children in the current study showed a large variation in RPR, from −1.25 D to as much as +4.00 D, at the 10 N and 20 N retina. Those children in the DIMS group who had baseline myopic RPR might be considered to have received too much myopic defocus at mid-periphery and failed to benefit from the myopic defocus signal. For a better myopia control efficacy, further modification of DIMS lenses may point to different dosage myopic defocus (such as, +1.50 D and +2.50 D) for the children with baseline myopic RPR or less hyperopic RPR. Notably, the relationship that baseline RPR influenced myopia control effects was only found within 20° of the nasal retina. There have been suggestions that the nasal retina is more sensitive to defocus signals to slow eye growth [9,42], and one study reported that the influence of myopic defocus on refractive development is reduced with increasing eccentricity [43]. Therefore, mapping the peripheral retinal profile, or at least the nasal near-peripheral retina, for customising the required defocus and avoiding producing a strong peripheral myopic defocus could be vital for optimising myopia control effects. Although the baseline RPR in the DIMS group can only explain 15% to 20% of myopia progression and axial elongation according to the multilinear analysis, other factors such as incorrect centration of the pupil centre and eye-foveal axis might influence the actual peripheral defocus exposure and final myopia control effects. Another possible factor, which has not been considered in this study, was the hyperopic retinal blur due to the lag of accommodation during near work, which might also contribute to the summation of defocus power and affect the final myopic defocus effectiveness [30]. Further studies to incorporate individual lag of accommodation for resultant myopic defocus analysis would provide additional information and understanding. The current study described the RPR profile in myopic schoolchildren 8 to 13 years old, and reported the role of RPR in myopia control. Peripheral refraction can be measured rapidly in clinical settings, and the RPR can be calculated easily by clinicians. Thus, RPR may provide a clinically useful measure for optimising and monitoring myopia control. 5. Conclusions The DIMS lens provides effective myopia control and is more effective in myopia control for children with baseline hyperopic RPR than for children with myopic RPR, and this may partially explain why myopia control effects vary among myopic children. Customised myopic defocus for individual subjects may optimise myopia control effects, and further research to investigate the optimal dosage, with consideration of peripheral retinal profile, is warranted. Acknowledgments We are grateful for the advice and edit of the manuscript from Marion Edwards, Roger Pak Kin Lee for data collection, and Yee Mui Kwok for liaison with the parents and data entry. Author Contributions Conceptualization, C.S.Y.L. and H.Z.; methodology, H.Z., C.S.Y.L., C.-H.T., W.-C.T., and P.H.L.; investigation, W.-C.T., H.Z., and M.L.; writing—original draft preparation, H.Z. and C.S.Y.L.; writing—review and editing, H.Z., C.S.Y.L., W.-C.T., M.L., P.H.L., and H.Q.; visualization, H.Z., C.S.Y.L., and W.-C.T.; project administration, C.S.Y.L., H.Z., and M.L. All authors have read and agreed to the published version of the manuscript. Funding This was a collaborative research project supported by HOYA, Tokyo, Japan and Hong Kong PolyU grants: RUQT, 848K, ZVN1 and ZG5N. The sponsor also provided specially manufactured spectacle lenses and frames. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Human Subjects Ethics Sub-committee of the Hong Kong Polytechnic University (Approval number: HSEARS20140630003-01) in 2014. Informed Consent Statement Written assent and informed consent were obtained from the children and their parents before participation. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest This collaborative research was partially supported by HOYA Corporation, Tokyo, Japan. Dr Hua Qi is an employee in the R&D of HOYA Corporation, Tokyo, Japan. Patents titled ‘Spectacle Lens’ in China (CN104678572 B) and USA (US10268050 B2) were issued on 27 April 2018 and 23 April 2019, respectively. Figure 1 The profile of RPR (SE, J0, J45) across the horizontal retina of children in DIMS group (n = 79) and SV group (n = 81) at baseline. No statistically significant difference in baseline RPR (SE, J0, J45) between two groups after Bonferroni correction (p > 0.008). Error bars denote SEM. Zero horizontal lines have been shown as dashed lines. Figure 2 (A–C): Correlation between baseline RPR, at 10 N, 20 N, 30 N, and myopia progression in the DIMS and SV group over 2 years. (D–F): Correlation between baseline RPR, at 10 N, 20 N, 30 N, and axial elongation in the DIMS and SV group over 2 years. Figure 3 Baseline RPR among each age subgroup in the DIMS and SV group, respectively. * Indicated the significant difference in RPR among age subgroups after Bonferroni correction (ANOVA, p < 0.008). Error bars denote SEM. Zero horizontal lines have been shown as dashed lines. jcm-11-02294-t001_Table 1 Table 1 Multiple linear regressions between relative peripheral refraction and myopia progression, axial elongation with relative peripheral refraction as the independent variable. Relative Peripheral Refraction at Baseline Myopia Progression Axial Elongation Regression Coefficient 95% CI for B p † Regression Coefficient 95% CI for B p † B Lower Bound Upper Bound B Lower Bound Upper Bound Adjusting for Age, Gender and Initial Refractive Error Adjusting for Age, Gender and Initial Axial Length DIMS group 10 T 0.00 −0.24 0.24 0.99 0.03 −0.08 0.11 0.74 20 T −0.08 −0.17 0.08 0.45 0.03 −0.04 0.05 0.77 30 T 0.03 −0.08 0.10 0.81 −0.08 −0.05 0.02 0.53 10 N 0.36 0.19 0.74 0.001 −0.35 −0.29 −0.08 0.001 20 N 0.35 0.08 0.33 0.001 −0.30 −0.12 −0.02 0.004 30 N 0.25 0.01 0.20 0.03 −0.22 −0.08 −0.002 0.05 SV group 10 T 0.06 −0.28 0.48 0.59 0.03 −0.12 0.15 0.77 20 T −0.06 −0.18 0.11 0.62 0.11 −0.02 0.08 0.29 30 T −0.07 −0.13 0.08 0.65 0.14 −0.02 0.06 0.29 10 N 0.37 0.23 0.90 0.001 −0.15 −0.22 0.03 0.13 20 N 0.36 0.12 0.49 0.001 −0.23 −0.14 −0.01 0.02 30 N 0.35 0.07 0.29 0.002 −0.24 −0.09 0.009 0.02 †p < 0.008 was considered as the statistical significance. jcm-11-02294-t002_Table 2 Table 2 The difference in myopia progression and axial elongation between children with myopic RPR and hyperopic RPR at 10 N in the DIMS and SV group, respectively. Myopic RPR at 10 N Hyperopic RPR at 10 N Mean Difference †p Value Mean ± SD n Mean ± SD n DIMS group Myopia progression (D) −0.61 ± 0.60 27 −0.25 ± 0.44 52 −0.36 ± 0.14 0.009 Axial elongation (mm) 0.32 ± 0.24 27 0.16 ± 0.18 52 0.16 ± 0.05 0.001 SV group Myopia progression (D) −1.10 ± 0.58 27 −0.84 ± 0.59 54 0.26 ± 0.14 0.06 Axial elongation (mm) 0.55 ± 0.27 27 0.51 ± 0.22 54 0.04 ± 0.05 0.48 †p < 0.05 was considered as the statistical significance. jcm-11-02294-t003_Table 3 Table 3 The difference in myopia progression and axial elongation between children with myopic RPR and hyperopic RPR at 20 N in the DIMS and SV group, respectively. Myopic RPR at 20 N Hyperopic RPR at 20 N Mean Difference †p Value Mean ± SD n Mean ± SD n DIMS group Myopia progression (D) −0.72 ± 0.64 12 −0.31 ± 0.48 67 −0.40 ± 0.16 0.01 Axial elongation (mm) 0.34 ± 0.24 12 0.19 ± 0.20 67 0.15 ± 0.07 0.02 SV group Myopia progression (D) −1.14 ± 0.53 11 −0.89 ± 0.60 70 −0.25 ± 0.20 0.19 Axial elongation (mm) 0.60 ± 0.28 11 0.51 ± 0.23 70 0.08 ± 0.08 0.27 †p < 0.05 was considered as the statistical significance. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Villarreal M.G. Ohlsson J. Abrahamsson M. Sjöström A. Sjöstrand J. Myopisation: The refractive tendency in teenagers. Prevalence of myopia among young teenagers in Sweden Acta Ophthalmol. 2000 78 177 181 10.1034/j.1600-0420.2000.078002177.x 10794252 2. Pan C.W. Ramamurthy D. Saw S.M. Worldwide prevalence and risk factors for myopia Ophthalmic Physiol. 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PMC009xxxxxx/PMC9099702.txt

==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093054 materials-15-03054 Article Degradation Mechanism and Numerical Simulation of Pervious Concrete under Salt Freezing-Thawing Cycle Xiang Junzheng 1 Liu Hengrui 1* Lu Hao 1 Gui Faliang 2 Zhang Lihai Academic Editor De Domenico Dario Academic Editor 1 College of Water Conservancy and Hydropower Engineering, Hohai University, Xikang Road No. 1, Nanjing 210098, China; junzhengx@163.com (J.X.); 180402020005@hhu.edu.cn (H.L.) 2 School of Hydraulic & Ecological Engineering, Nanchang Institute of Technology, Nanchang 330099, China; guifaliang@126.com * Correspondence: 171302020037@hhu.edu.cn; Tel.: +86-188-520-006-61 22 4 2022 5 2022 15 9 305403 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/). In order to explore the occurrence area of pervious concrete freeze-thaw deterioration, the mass loss, strength deterioration, ultrasonic longitudinal wave velocity and dynamic elastic modulus attenuation of pervious concrete under freeze-thaw cycles were measured, and a prediction model of freeze-thaw damage was established. The mechanical properties of hardened cement pastes with the same W/C ratio under freeze-thaw cycles were also measured. Mercury intrusion porosimetry (MIP) was used to measure the pore structure characteristic parameters and pore size distribution changes of cement paste under freeze-thaw cycle, and the microstructure evolution of interfacial transition zone (ITZ) of paste and aggregate was observed by SEM scanning electron microscopy. Finally, a pervious concrete model was established by DEM to analyze the relationship between the number of freeze-thaw cycles and the mesoscopic parameters. The results indicated that the quality, strength and dynamic elastic modulus of pervious concrete deteriorate to different degrees under the conditions of water freezing and salt freezing. The damage sensitivity and strength loss of freeze-thaw damage is greater than the dynamic elastic modulus loss, which is greater than mass loss. In the pervious concrete paste which underwent 100 freeze-thaw cycles, the pore structure and macro strength had no obvious change, and hardened paste and the aggregate-interface-generated defects increased with the increase in freezing and thawing times, indicating that the deterioration of pervious concrete performance under freeze-thaw cycles was closely related to the deterioration of the interface strength of the aggregate and hardened paste. The pervious concrete model established by DEM can accurately simulate the change of the compressive modulus and the strength of pervious concrete during freeze-thaw cycles. pervious concrete freeze-thaw cycle deterioration law interfacial transition zone (ITZ) of hardened paste and aggregate discrete element simulation ==== Body pmc1. Introduction Pervious concrete is a porous and lightweight concrete made of aggregate, cement, reinforcer, mineral admixture and water. As the surface of the coarse aggregate is covered with thin layers of cement paste and it bonds to itself, a honeycomb structure is formed with evenly distributed pores; this gives pervious concrete the characteristics of air permeability, water permeability and light weight, and is widely used in the engineering field [1,2,3]. However, pervious concrete also has the characteristics of easy clogging and low strength, which is damaged more by freezing and thawing in a cold environment than ordinary concrete [4,5]. In cold conditions, pervious concrete also faces the double damage of salt freezing and chemical erosion; these factors affected its large-scale promotion and application in cold areas [6]. The frost resistance of pervious concrete increased with the decrease in aggregate particle size, increased with the increase in paste to aggregate mass ratio, and decreased significantly with the increase in water–cement ratio [7,8]. For the external environment, deicing salts negatively affected the strength and durability of conventional concrete pavements. The porosity of pervious concrete may increase the surface area vulnerable to a chemical attack [9,10,11]. Previous studies have shown that the porosity of pervious concrete was negatively correlated with strength [12,13]. Therefore, the effects of different types of salts on pervious concrete have been studied by some researchers, including freeze-thaw cycles, dry–wet cycles, or immersing in deicing salt solutions of different concentrations and temperatures. Concrete soaked in a sodium chloride solution had no significant negative effect on the dry–wet cycle, while calcium chloride and magnesium chloride (MgCl2) did significant damage to the mass loss and stiffness reduction of concrete [14]. The three deicing salts are sodium chloride, calcium chloride, and magnesium calcium acetate (CMA). Cutler et al. tested the freeze-thaw resistance of pervious concrete under saturated and unsaturated conditions. The damage degree was evaluated by measuring the mass loss and compressive strength periodically. It was found that calcium chloride caused the most damage, followed by sodium chloride and magnesium chloride, and the saturation test caused more damage than the unsaturated test [15]. Anderson et al. soaked pervious concrete samples in sodium chloride solutions of different concentration gradients and then discharged the solution for an unsaturated freeze-thaw cycle test. The results showed that 4% and 8% salt concentrations did the greatest damage to the denudation of cement paste, and did little damage to the aggregate [16]. Hassan Bilal et al. reported that the damage and mass loss caused by the combined actions of calcium leaching and freeze-thaw cycles were greater than those caused by freeze-thaw cycles and calcium leaching alone, and the combined erosion significantly increased the deterioration and damage of the pervious concrete [17]. Some researchers have improved the freeze-thaw resistance of pervious concrete under extreme cold conditions. Mehmet Gesoğlu et al. found that rubber was an effective solution to the freeze-thaw durability problem of pervious concrete. After 300 freeze-thaw cycles, rubber utilization significantly improved their results. The performance of small size rubber particles was better than that of large size rubber particles [18]. D. Tarangini et al. had proved that nano silica can increase the micro voids of pervious concrete, thus significantly increasing the freeze-thaw resistance of concrete, and this effect was better than other mineral admixtures [19]. Similarly, AoYang Li et al. reported that the addition of glass powder content resulted in a decrease in internal porosity and permeability coefficient of pervious concrete, which enhanced the freeze-thaw resistance [20]. In addition to mineral admixtures, other factors can also affect the freeze-thaw resistance of pervious concrete. Taheri B.M. et al. conducted tests and statistical analysis on the water–cement ratio (W/C), entrained gas volume, sand content, coarse aggregate particle size and other parameters that affected the freeze-thaw durability of pervious concrete, and believed that the strength and freeze-thaw durability of concrete could be improved by replacing 8% coarse aggregate with sand and a high W/C. It was found that the change of air entrainment and coarse aggregate particle size had no significant effect on the freeze-thaw durability of pervious concrete [21]. Rui Zhong et al. evaluated the influence of the matrix type, pore system characteristics and fiber on the F-T durability of the pervious concrete. The main influence of pore system characteristics on the F-T durability of PC was that of pore size and bending degree. Using a larger aggregate resulted in larger void sizes, higher bending, and premature F-T failure [22]. The correlation between the strength of pervious concrete and freeze-thaw durability was also explored. Pervious concrete with a higher strength usually had better durability, while tensile strength had a more significant impact on freeze-thaw durability than compressive strength. The tensile strength and freeze-thaw durability of pervious concrete were significantly enhanced by polypropylene fibers of different lengths (3~12 mm) [23]. Almeida et al. found that natural carbonization can improve the resistance of pervious concrete to deicing salts [24]. Bilal et al. added silica fume, metakaolin, and SBR (styrene-butadiene rubber) polymer emulsions to pervious concrete mixtures at different levels to improve their strength and durability. The results showed that the increase of supplementary cementitious materials (SCMs) from 5% to 10% significantly improved the resistance to rapid FT cycling [15]. Yang reported that the freeze-thaw durability of pervious concrete cured with saturated lime water was significantly higher than that of pervious concrete cured slowly in air. In addition, it was found that silica fume helped to improve the freeze-thaw resistance of pervious concrete cured with saturated lime water with deicing salts [25]. Most of the above studies were based on improving the properties of the cement base to improve the freeze-thaw durability of pervious concrete, and these methods also appeared in most studies of ordinary concrete [26,27,28,29,30,31]. However, compared with ordinary concrete, whether improving cement-based materials was the most effective way to improve frost resistance required further research on the freeze-thaw failure mechanism of pervious concrete. The mechanical behavior and failure mechanism of cement-based materials under freeze-thaw cycles has been studied by many scholars [32,33,34]. The ice formation began in the capillary pores of the cement matrix, and then unfrozen water was pushed around. The cracks appeared when the high expansion pressure exceeded the matrix strength and was not released in time [35]. When the water was impure, the water in the microscopic pores of the cementitious base contained high concentrations of salts used for deicing. After freezing, solutes may disrupt the chemical equilibrium in the connected pores, causing osmotic pressure disruption [36]. On the other hand, the water–cement ratio of pervious concrete was usually between 0.27 and 0.33, and the low water–cement ratio cement-based microstructure was more resistant to freezing and thawing. Vancura found cracks suspected of freezing and thawing from pervious concrete cores taken from a pavement in cold regions, and these cracks passed through the aggregate–cement interface [37]. Zhou et al. used two silane emulsion modification methods to change the properties of the recycled aggregate surface and cement matrix, thereby improving the freeze-thaw durability of recycled aggregate pervious concrete. The results showed that surface modification of the recycled aggregate can more effectively improve the compressive strength and freeze-thaw durability of recycled aggregate pervious concrete than overall modification of the cement matrix [35]. These results reflected that cement-based deterioration may not be the main cause of freeze-thaw deterioration of pervious concrete, but whether it was mainly from interface deterioration requires further research to analyze the microscopic mechanism of the permeable concrete’s freeze-thaw damage. In recent years, many researchers have studied the freeze-thaw deterioration process of concrete through numerical simulations, such as the finite element method (FEM) and discrete element method (DEM), to deepen the understanding of this process [38,39,40,41]. The macro-mechanical behavior of general materials was determined by the meso-structural properties of the constituent materials, such as the strength and deformation properties of particles, the bonding strength between particles, particle size and gradation distribution, etc. [42]. The discrete element method can overcome the limitations of the traditional continuum model theory, and comprehensively simulate the damage process and failure mode of materials from being intact to failure. The damage and failure mechanisms of the material can also be explained from the perspective of micro mechanics [43]. Pervious concrete consisted of granular materials whose different components were not interconnected at the material level. Therefore, DEM was one of the best options for modeling such materials [44,45]. In order to further deepen the understanding of the freeze-thaw damage of permeable concrete, this study used PFC3D discrete element software to establish a freeze-thaw damage model of permeable concrete based on physical experiments, so as to understand the effect of freeze-thaw cycles on meso-parameters such as the bond strength between permeable concrete particles. Based on the above introduction, this paper deeply explored the freeze-thaw cycle deterioration area of permeable concrete through a combination of macroscopic and microscopic tests. The strength loss, mass loss and relative dynamic elastic modulus change of pervious concrete under freeze-thaw cycles were measured macroscopically, and the strength loss, mass loss and morphology change of hardened cement paste under the same W/C ratio were compared. Microscopically, the morphology evolution of the aggregate–cement interface was explored by a scanning electron microscopy (SEM) test, and the pore structure change of the hardened cement slurry was obtained by a mercury intrusion porosimetry (MIP) test. Therefore, the damage degradation a model undergoing freeze-thaw cycles was proposed. On the basis of the test, a discrete element model of pervious concrete’s freeze-thaw damage was established, which effectively indicated the relationship between the number of freeze-thaw cycles and the bond strength between particles. The research results can enrich the theoretical system of damage mechanisms of pervious concrete under freeze-thaw cycles, and provide theoretical support for pervious concrete construction under freeze-thaw scenarios. 2. Materials and Methods 2.1. Materials All mixtures were made of ordinary Portland cement with a strength grade of 42.5. Coarse aggregate was limestone with a particle size of 2.5~10.0 mm, and a particle size of 2.5~5.0 mm accounted for 25% of the limestone. In order to make the pervious concrete in this test similar to the actual pervious pavement material, an SR-5 commercial additive produced by Nanjing Jiuherun Engineering Technology Company was used as the admixture. The recommended additive amount was 3~6% of the cement quality; the additive amount in this test was 4% of the cement quality. According to the supplier′s product introduction, the reinforcer mechanism of the strengthening agent is to participate in the cement hydration reaction to form a high-molecular polymer structure, which can significantly improve the compressive strength and bonding strength of the hydration production. The chemical composition of the additive is shown in Table 1. According to the Chinese standard CJJ/T 135-2009 [46], the filling theory and volume method were used to calculate the mixture ratio, and the target pore was set as 12%. Previous research results showed that the compressive strength of pervious concrete increased when the water–cement ratio was 0.25–0.31 and decreased when the water–cement ratio was larger than 0.34. When the water–cement ratio was lower than 0.31, the mixture was too dry to affect the molding. When the water–cement ratio was 0.34, it was easy to segregate the paste and affect the water permeability rate. Therefore, a water–cement ratio of 0.31 was used in this test. The amount of each material of pervious concrete was calculated, as shown in Table 2. 2.2. Preparation and Maintenance of Samples (1) Pervious concrete sample The size of the permeable concrete sample was a 150 mm cube, and the molding adopted a combination of ramming and vibration. The mixture was assembled into the mold three times, and then it was vibrated on a vibrating table for 15 s, and the mold was removed after 24 h. The samples were covered with geotextiles and watered for 28 days. (2) Hardened cement slurry sample The ratio of the prepared cement stone material was the same as that of the permeable concrete cementitious material. The sample size was a cylinder with a diameter of 20 mm and a height of 20 mm. The preparation process was that the cementitious material was put into the vessel and fully stirred, and then the slurry was loaded into the mold and then vibrated on a vibrating table for 30 s and placed in the mold for curing. The sample was demolded after 24 h, and the curing was the same as that of the pervious concrete. The above concrete and paste experiments were carried out in a laboratory with a room temperature of 20 °C and humidity of 70%. 2.3. Test Methods 2.3.1. Effective Porosity The pore structure of the pervious concrete was composed of connected pores, semi-connected pores and closed pores, among which connected pores and semi-connected pores belonged to effective pores [47]. Volumetric and gravimetric methods were used to measure the effective porosity of the pervious concrete. This test used the gravimetric method to test the permeability coefficient of the pervious concrete [48]. The gravimetric method was mainly to measure the difference between the drying mass of the sample and the floating weight in water, which can demonstrate the actual buoyancy of the structure after pore saturation. Working on the assumption that the sample does not absorb water, porosity P can be obtained by using the difference between actual and theoretical buoyancy. The specimen size was a 150 mm cube and the average value of the three samples was obtained. The calculation formula of porosity P was as follows:(1) P=[1−m2−m1V]×100% where P is the effective porosity (%); m1 is the floating weight of the sample (g); m2 is the drying quality of the sample (g); V is the sample volume (cm3). 2.3.2. Ultrasonic Velocity Ultrasonic wave velocity was an important parameter in ultrasonic testing of concrete, which was related to the number and complexity of pores in the internal structure of concrete. If there were defects (holes, honeycombs) inside the concrete, the ultrasonic waves will be refracted and diffracted there, resulting in a lower ultrasonic wave velocity. The ultrasonic wave velocity was related to the material components, and the W/C ratio and aggregate content all affected the ultrasonic wave velocity of concrete [49,50]. In a word, the ultrasonic wave velocity of concrete can reflect the performance and internal characteristics of concrete. In order to study the internal structure evolution of pervious concrete under freeze-thaw cycles, ultrasonic tests were carried out on concrete samples with different erosion times, and the changes in ultrasonic wave velocity and density of concrete samples with different erosion ages were tested. The transmitting and receiving transducers were placed in the center of two opposite surfaces of the pervious concrete. In order to reduce the influence of the gap between the transducer and the concrete surface on the ultrasonic test results, Vaseline was applied as a coupling agent at the contact position between the transducer and the pervious concrete. The ultrasonic detection frequency was set to 28.2 kHz, and the sampling was started after the relevant test parameters were set. When the ultrasonic wave speed and waveform were stable, the sampling was stopped and the data were saved to record the ultrasonic wave speed. The specimen size was a 150 mm cube and the test results were taken as the average value of the three samples. 2.3.3. Compressive Strength According to the Chinese standard GB/T50081-2002 [51], the 150 mm cubic sample was placed between the upper and lower pressure plates, and the test instrument was started. The loading stress rate was 0.3 MPa/s. The peak load was recorded and the average value of three pervious concrete blocks was obtained. The calculation formula for the peak compressive strength of pervious concrete is shown in Equation (2):(2) P=FA where P is the compressive strength, MPa; F is the peak pressure of specimen failure, kN; A is the compressive surface area of the sample, mm2. A strain gauge was applied to the hardened cement paste sample to measure the transverse and longitudinal strain under compression. The strain gauge was connected with the strain gauge, and the upper and lower surfaces of the cement stone sample were coated with butter and placed on the bottom support of the electronic universal testing machine. The test control mode was set as displacement control, and the displacement control speed was set as 0.1 mm/min. The peak load was recorded, and the average strength of three cement blocks was obtained. 2.3.4. Freeze-Thaw Cycle Test The freeze-thaw cycle test of pervious concrete conforms to the Chinese standard GBT 50082-2009 [52]. There were 5 groups of pervious concrete samples which were 150 mm cubes, and 3 samples in each group. The number of freeze-thaw cycles was set at 100, and damage detection was performed every 25 cycles. The mass and ultrasonic speed of one group were recorded until the final compressive strength test. The freeze-thaw test block was immersed in the test tank for two days. After it was removed, the test block was wrapped and sealed with plastic wrap until there was no water dripping from the bottom of the test block. Then it was quickly put into the freezer. The freeze-thaw test was started with a freezing temperature of −25 °C and a freezing time for each cycle of 10 h. Then, the test block was put into a water tank (20 °C) to thaw for 4 h. The specimens were dried after curing for 28 days, and the initial mass of group A was weighed. When group A reached the number of freeze-thaw cycles, the samples were thawed, cleaned with water, and weighed after drying for 24 h, and then their ultrasonic speeds were measured. When the number of freeze-thaw cycles was reached, three samples outside group A were selected for a compressive strength test. After curing for 25 days, the sample was immersed in a 3% sodium chloride solution for three days. After soaking, the sample was removed from the sodium chloride solution, covered with plastic film and left to stand for 10 min to drain the water. The pervious concrete test block was sealed with plastic wrap to prevent evaporation of water during the freeze-thaw cycle. The number of test blocks, method steps, sizes and testing methods of freezing and thawing deterioration in the salt freezing test was consistent with that in the water freezing test. The sample size of the clean cement slurry was a cylindrical sample with a diameter of 20 mm and a height of 20 mm. There were 8 groups of samples with 3 pieces in each group. Three groups were tested for mass loss (25 measurements per freeze-thaw cycle) and compressive strength (50 measurements per freeze-thaw cycle). The other 5 groups were subjected to a mercury injection test (25 measurements per freeze-thaw cycle). The freeze-thaw cycle of the cement slurry was consistent with that of pervious concrete. 2.3.5. Mercury Intrusion Porosimetry (MIP) Test Mercury injection (MIP) of cement paste specimens was measured by an AutoPore IV 9500 automatic porometer in the pressure range of 0.10 to 61,000.00 Psia, and the contact angle between the mercury and the pore surface was θ = 130°. The sample size of the cement paste prepared in this test was 20 mm in diameter and 20 mm in height, which can be directly used for the mercury injection test. Prior to mercury injection testing, MIP specimens were placed in anhydrous ethanol for at least 24 h to dehydrate and terminate hydration. Then, the sample was put into the oven at 45 °C to dry for 24 h until it reached a constant mass so that free water and alcohol evaporation was achieved. 2.3.6. Scanning Electron Microscope (SEM) Test The scanning electron microscopy (SEM, XRADI410 Versa, ZEISS, Jena, Germany) was used to observe the microstructure of the interface zone between the aggregate and the hardened paste and the paste zone. After the freeze-thaw test was repeated 50 and 100 times, a thin fragment of 5 mm2 was knocked off at the aggregate interface. The samples were soaked with anhydrous ethanol to stop hydration. Before the experiment, the samples were taken out and dried to a constant weight at 60 °C for testing. 2.3.7. Discrete Element Method The calculation principle of PFC3D discrete element software was mainly based on the force-displacement law and Newton′s second law. It adopted the explicit finite difference method for the cyclic iteration solution and interacted with the internal force and torque. There is bonding strength between particles, and the bond is broken when the force acting on the cohesive bond due to external loads exceeded the strength of the bond itself [40]. In this study, the freeze-thaw damage of pervious concrete was characterized as the damage to the bonds between particles. Therefore, a parallel bond constitutive model, which was similar to the mechanical properties of cementitious materials, was selected to simulate the contact of cement paste between permeable concrete aggregates [53,54]. When the parallel bonding model was bonded, it can resist the torque and behave as linear elasticity when the force did not reach the strength limit. When the force exceeded the strength limit and the load cannot be transmitted after the bond fails, it degenerated into a linear model, as shown in Figure 1 [55]. Aggregate is constructed through six discrete particle units embedded with each other, as shown in Figure 2a. The aggregate model is divided into two groups according to particle gradation, with particles of 2.5–5 mm accounting for 25% and particles of 5–10 mm accounting for 75%. The generated model is shown in Figure 2b. The loading rate used in the PFC compressive strength test was different from the loading rate used in a laboratory test. The compressive strength of the traditional loading program was obviously different at various speeds. In the PFC simulation, the time step was 10–8 s and the loading rate was 1.0 m/s. The model should be quasi-static, so the strength value should be unrelated to the loading rate [56]. Since the loading rate did not have a great impact on the model, the loading rate of this test was 0.05 m/s under comprehensive consideration. The axial loading of the DEM model is shown in Figure 2c. 3. Results and Discussion 3.1. Experimental Results 3.1.1. Macroscopic Performance Deterioration Test Results Surface Morphologic Figure 3 shows the morphological changes of pervious concrete in two freeze-thaw environments: water freezing and salt freezing. Cement paste was eroded from the aggregate surface during freeze-thaw cycles. Comparing the changes before and after a freeze-thaw cycle, it was found that the shedding parts of the aggregate were concentrated at the forming surface and corners of the sample, as shown in Figure 3e,f,o,p. It can be seen from Figure 3p that the aggregate paste structure fell off significantly in the lower right corner of the pervious concrete which was salt frozen 100 times. Comparing the damage of water freezing and salt freezing, it was found that salt freezing caused more serious shedding of aggregate paste structure in pervious concrete. These phenomena were the reasons for the quality loss of the pervious concrete. Figure 4 presents the changes in the cement paste with the same water–cement ratio in the freeze-thaw process. It can be seen from Figure 4b that the freeze-thaw cycle did not cause obvious damage to the cement paste with the same water–cement ratio. During the test process, the macroscopic pore defects on the sample surface were not observed to be significantly aggravated. After 100 freeze-thaw cycles, the mass loss of the cement paste was 0.16%, and the compressive strength was basically unchanged and only slightly increased, as shown in Figure 4a. This indicated that the strength improvement brought by the continued hydration of cement paste was greater than the damage caused by the freeze-thaw cycle. In summary, it can be inferred from the macroscopic properties that the cement paste will not deteriorate significantly after 100 freeze-thaw cycles. The structure of the dropped aggregate slurry was observed in Figure 5, and it was found that the aggregate surface was clearly visible and smooth. If the freeze-thaw damage was primarily from the cement paste, then the detached aggregate should be encased in the cement paste rather than peeling off directly from the interface. Therefore, it can be considered that the main reason for the quality loss of the pervious concrete was not the deterioration of the cement paste, but the freeze-thaw deterioration of the interface transition zone between the aggregate and hardened paste. Compressive Strength The strength changes of the pervious concrete during freeze-thaw under water freezing and salt freezing are shown in Figure 6. The compressive strength of pervious concrete decreased with the increase in freeze-thaw times. After 100 freeze-thaw cycles, the strength of the pervious concrete decreased by 23% in the salt-frozen environment and 16% in the water-frozen environment, indicating that salt freezing did greater damage to the pervious concrete. According to the salt freezing failure mechanism of ordinary concrete, after the concrete was attached with deicing salt, the increases in hygroscopicity led to a greater degree of saturation [57,58]. Moreover, a NaCl solution with a concentration of 2–6% (3% in this experiment) will produce the maximum icing pressure, making the concrete more prone to denudation [59]. Therefore, the damage caused by salt freezing was manifested as a significant attenuation of the mechanical strength. In the water freezing environment, the stress of the pervious concrete increased obviously for the 25th freeze-thaw cycle. The strength of the pervious concrete increased with the increase in hydration degree. Compared with the influence of the freeze-thaw cycle on the strength of concrete, the hydration effect played a leading role. Dynamic Elastic Modulus It can be seen from Figure 7a that the ultrasonic velocity of pervious concrete decreased with the increase in freeze-thaw times. Under 100 freeze-thaw cycles, the ultrasonic velocity loss after water freezing was 3.8%, and after salt freezing it was 5.5%. In the freeze-thaw process, the pervious concrete deteriorated continuously, which was characterized by the shedding of cement paste and an increase in micro-cracks and pores. This phenomenon is explained in Figure 3 and the following SEM experiments. As a result, ultrasonic waves needed to undergo more refraction and diffraction in the transmission process, resulting in more complex and changeable transmission paths, which had an increasingly serious impact on ultrasonic waves. Therefore, the increase in the ultrasonic wave velocity attenuation rate will lead to an increase in cracks and pore expansion in the pervious concrete. The attenuation of the wave velocity can provide a reference evaluation for freeze-thaw damage of pervious concrete. The changes in pervious concrete quality during freeze-thaw cycles in both water and salt freezing environments are shown in Figure 7b. After 100 freeze-thaw cycles, the salt freezing mass loss was 0.82% and the water freezing mass loss was 0.47%. The quality loss was more serious in a salt freezing environment, indicating that deicing salt caused more serious freeze-thaw damage to pervious concrete. However, it should be noted that without freeze-thaw conditions, sodium chloride did not have a significant negative effect on concrete, because the Freidel′s salt produced by the reaction of sodium chloride with cement slurry was not a highly destructive component of concrete [60]. The higher mass loss in a salt-frozen environment was not caused by the chemical erosion of NaCl. The addition of deicing salt gave the pervious concrete higher hygroscopicity, higher saturation, made it reach critical saturation faster, and higher expansion pressure generated by the freezing [61]. Figure 7c shows that after 100 freeze-thaw cycles, the dynamic elastic modulus of pervious concrete in the water-frozen environment and the salt-frozen environment decreased by 7.9% and 11.4%, respectively. The decrease in the dynamic elastic modulus was about half of the strength loss of 100 freeze-thaw cycles. For ordinary concrete, when the strength loss of concrete reached 20%, the loss rates of the dynamic elastic modulus of concrete with water-binder ratios of 0.35, 0.45 and 0.55 were about 3.5%, 7% and 8%, respectively [62]. The effect of freeze-thaw cycles on the dynamic elastic modulus and strength of pervious concrete was similar to that of ordinary concrete. The strength loss was more sensitive than the dynamic elastic modulus under freeze-thaw conditions. Effective Porosity Figure 8 shows that the effective porosity of pervious concrete increased with the increase in freeze-thaw times. After 100 freeze-thaw cycles, the effective porosity of salt freezing increased by 12%, and that of water freezing increased by 7%. The main reason was that the aggregate paste structure at the edges and corners of the pervious concrete fell off, and the volume of the aggregate paste structure directly transformed into increased effective pores. In addition, the denudation of cement in the connected pores enlarged the connected pores. As mentioned above, salt freezing was more serious for denudation of pervious concrete, which also explains why the increase in the effective porosity of salt-frozen samples was greater than that of water-frozen samples. However, it was also found that the fluctuation of the effective pore variation of water freezing in the sample did not seem to come from a measurement error, which may be caused by the coupling agent in the ultrasonic test. The coupling agent Vaseline can fill the surface of pervious concrete and reduce the number of connected pores. The effect of water freezing and salt freezing denudation on effective pores was greater than that of coupling agent filling. Salt freezing was more serious because of mass loss, so this effect was not obvious. 3.1.2. Evaluation of Freeze-Thaw Damage Establishment of a Freeze-Thaw Damage Model In order to evaluate the deterioration degree of freeze-thaw damage, the quality loss rate, strength loss rate and freeze-thaw damage model based on ultrasonic wave velocity attenuation were used as evaluation indexes, where the mass loss rate Lm, strength loss Lσ and dynamic elastic modulus loss LE are calculated according to Equations (3)–(5) below:(3) Lm=(1−mdm0)×100% (4) Lσ=(1−σc,dσc,0)×100% (5) LE=(1−EdE0)×100% where m0, σc,0 and E0 are the initial mass, compressive strength, and dynamic elastic modulus, respectively, and md, σc,d and Ed are the mass, compressive strength, and dynamic elastic modulus after reaching the specified number of freeze-thaw cycles, respectively. Freezing-thawing cycles can cause irreversible damage to pervious concrete, such as cracks, aggregate spalling and fractures, which makes it difficult to guarantee the mechanical properties and service functions of pervious concrete. In damage mechanics, it was generally considered that material damage was irreversible and was a process of energy dissipation. It was believed that the damage to materials was caused by the microscopic defects of materials, resulting in the reduction of the effective bearing area (A) of materials. This microscopic defect process was difficult to measure and needed to be linked to specific measurable macro variables. The continuum (Ψ, the ratio of the effective load area before and after the damage) was used to describe the damage state of the material, and the damage variable D (1 − Ψ) corresponding to the continuum was introduced. The principle of strain equivalence was proposed, and the damage degree can be expressed by the change of elastic modulus:(6) D=1−E¯E=1−A¯A where E is the elastic modulus of the material before damage, Gpa; E¯ is the elastic modulus of the material after damage, Gpa; A¯ is the effective bearing area after material damage. Figure 9 is calculated according to Equation (5). The freeze-thaw damage model of the pervious concrete was constructed using the first-order decay exponential function (ExpDec1), that is, DE = (ae(−N/b) + c)/100, where DE freeze-thaw damage characterization, N was the number of freeze-thaw cycles, a, b and c were undetermined parameters, and the model was as follows:(7) DE,w=(104.83373e(N/1250.56021)−104.92892)/100, R2=0.98337 (8) DE,s=(15.70047e(N/184.39276)−15.62693)/100, R2=0.99835 The degree of damage can be expressed by elastic modulus. Therefore, the freeze-thaw damage model of the water-frozen pervious concrete is represented by Equation (7), and the freeze-thaw damage model of the salt-frozen pervious concrete is represented by Equation (8). Prediction and Evaluation of Freeze-Thaw Durability Based on the data of 100 freeze-thaw tests, a prediction model of the freeze-thaw quality loss of pervious concrete was established by using the first-order decay exponential function (ExpDec1), namely Dm = (ae(−N/b) + c)/100, where Dm is the quality damage characterization, N is the number of freeze-thaw cycles, a, b and c are undetermined parameters, and the model is as follows: (9) Dm,w=(0.0531e(N/43.13277)−0.04347)/100, R2=0.97391 (10) Dm,s=(0.04114e(N/33.0477)−0.03528)/100, R2=0.99877 Equation (9) is the quality loss prediction model of the water-frozen pervious concrete, and Equation (10) is the quality loss prediction model of the salt-frozen pervious concrete. The fitting curve of mass loss of permeable concrete under freeze-thaw cycles is shown in Figure 10. Due to the dispersion of the 25 freeze-thaw data in the water freezing test, the strength loss model only considered the salt freezing condition. The strength loss model of the pervious concrete is constructed by using the quadratic function (Dσ = aN2 + kN), where Dσ is the strength damage characterization and a and k are undetermined coefficients. The model is as follows:(11) Dσ,s=(0.0001N2+0.25N)/100, R2=0.92827 Equation (11) was the strength loss prediction model of the salt-frozen pervious concrete. The fitting curve of strength loss of the permeable concrete undergoing freeze-thaw cycles is shown in Figure 11. It should be noted that although the regression equation with a higher goodness of fit can be obtained by using other curves here, its deterioration law was not consistent with the reality. The freeze-thaw strength loss of the pervious concrete did not slow down with the increase in freeze-thaw times. In addition, the strength test was different from the nondestructive testing index, which only needed to consider the error caused by testing by using the same group of samples, and it also had discreteness between different samples. Considering the above situation comprehensively, the monotone increasing quadratic function was selected in combination with the error bar range in Figure 6. 3.2. Microscopic Property Test Results 3.2.1. Mercury Intrusion Porosimetry (MIP) Results The variations of various parameters of the cement pore structure with different freeze-thaw cycles are shown in Figure 12. The 100 freeze-thaw cycles had little effect on the four pore size parameters of cement paste at a water–cement ratio of 0.31, which was consistent with the macroscopic properties of freeze-thaw cycles mentioned above. When freeze-thawed 25 times, the porosity of the cement paste decreased by 10% compared with the initial state, which may be due to the formation of hydration products such as CSH and CH in the cement paste, which can effectively fill the pores, therefore making the internal structure of the paste more compact. The porosity remained stable after 25 freeze-thaw cycles, and increased slightly after 100 freeze-thaw cycles. The paste accumulative quantity of different freeze-thaw cycles was shown in Figure 13. With the decrease in pore size, the volume of mercury in the pore size of the cement paste increased in a curve form. When the pore size was in the range of approximately 69–106 nm, there was almost no mercury in the pore size, but the mercury in the pore size below 69 nm increased sharply, indicating that the pore size of the cement paste at a water–cement ratio of 0.31 was mainly concentrated in the range of 5–69 nm. However, it was also noted that the initial curve also increased greatly at 69 nm, but the final cumulative volume of mercury was about twice that after a freeze-thaw cycle. The paste with a water–cement ratio of 0.31 became denser through the hydration reaction at 5–69 nm during the freeze-thaw cycle. Mehta′s tests showed that pores smaller than 132 nm had no effect on the strength of concrete [63]. This may explain the large porosity of the initial cement paste but the macroscopic strength was not significantly different from that of the freeze-thaw paste. The pore size distribution of the cement paste with a 0.31 water–cement ratio under different freeze-thaw times was plotted, as shown in Figure 14. The pore size distribution figure clearly showed the change in the small pore size of the freeze-thaw circulation paste. With the increase in freeze-thaw times, pore sizes of 5–20 nm and >200 nm did not change remarkably. Studies had shown that the lower the water–cement ratio, the lower the degree of early hydration [64]. Therefore, in the early freeze-thaw stage, hydration makes the 50–200 nm pores tighter and gradually transformed them into 20–50 nm pores. Later, due to the weakening of hydration, the freeze-thaw cycle played a leading role in the damage caused by the cement paste, and the 20–50 nm pores gradually changed into 50–200 nm pores. The pore size distribution showed that the proportion of the 20–50 nm pores first increased and then decreased, and the proportion of the 50–200 nm pores first decreased and then increased. Microcapillary pores of 5~100 nm will exhibit the capillary condensation phenomenon, increasing the hygroscopicity of the pores [65]. The higher capillary pressure and osmotic force strengthened the self-shrinkage of the cement paste and accelerated the penetration rate of the cement paste’s surface and atmospheric pressure, thus reducing the impermeability of the cement paste’s surface and atmospheric pressure impermeability. These phenomena enhanced the diffusion of chloride ions and pore water in the cement paste. Although 100 freeze-thaw cycles had no obvious influence on the macroscopic properties and micropore structure of cement paste with a 0.31 water–cement ratio. However, the increase in the transport of the freeze-thaw medium may have caused the freeze-thaw damage to the pervious concrete′s interfacial transition zone (ITZ) of the paste and the aggregate. 3.2.2. Scanning Electron Microscope (SEM) Results The components of the aggregate paste structure can be determined by EDS analysis. Figure 15 shows the EDS spectra of the aggregate and cement paste area, respectively. The various element content of aggregate and hardened cement paste is described in Table 3. The results showed that the aggregate elements in the aggregate paste structure were Ca, O and C, and the content of Ca was the highest because the aggregate was mainly composed of limestone, and the limestone was composed mainly of calcium carbonate (CaCO₃). In addition to the elements contained in the aggregate, there were other elements such as Al and Fe in the cement paste, which proved that the observation area was actually the interface area between the aggregate and the cement. Figure 16 shows the microscopic morphology of the interface area between the aggregate and the cement paste during a freeze-thaw cycle. According to Cwirzen et al. [66], ordinary concrete with a water–cement ratio of 0.3 had a dense cement paste structure, and electron microscopic observations of these concretes confirmed the existence of an almost undetectable transition zone (less than 5 μm wide), while the interface zone of the sample with a 0.42 water–cement ratio was 40 μm. This experiment showed similar observation results. As the pervious concrete did not contain sand, its transition zone was denser and more difficult to observe than ordinary concrete. There was almost no interface transition zone in the pervious concrete with a water–cement ratio of 0.31. The interface area of aggregate and cement paste showed great differences under different freeze-thaw cycles. With the increase in freeze-thaw times, the two-phase contact area of aggregate and hardened paste deteriorated obviously. In the unfreeze-thawing of the concrete sample, the interface between aggregate and cement paste was smooth. It can be seen by comparing Figure 16a,b that after 50 freeze-thaw cycles, obvious cracks appeared at the interface between the two phases, and the aggregate and paste structure separated. The elastic modulus and temperature sensitivity of the two-phase materials between the aggregate and the cement paste were different, which produced different shrinkages and expansions during freeze-thaw cycles. The uncoordinated material deformation caused high interfacial stress in the interface area, which caused the obvious expansion of micropores or cracks in the interface area, and finally led to the interface cracking and delaminating. The long and narrow interface cracks speed up the entry of freeze-thaw media and further accelerated the deterioration of the interface area. It can be seen from Figure 16c that the interface cracks with 100 freeze-thaw cycles expanded further than those with 50 freeze-thaw cycles. The presence of an interfacial zone promoted the diffusion of chloride ions, and the diffusion rate was 6–12 times faster than that of the cement paste zone [67]. Therefore, the presence of the interface zone facilitated the entry of harmful ions from the external environment, leading to various harmful chemical reactions, such as chemical erosion and salt-freezing damage of concrete from deicing salts. 3.3. Establishment of Freeze-Thaw Damage in DEM The failure process of pervious concrete under freeze-thaw cycles is essentially the process of internal deterioration of the material. Microdefects in the pervious concrete can be regarded as a damage field continuously distributed within the material. In the freeze-thaw cycle, freeze-thaw damage is constantly generated and expanded, which reduces the strength, stiffness, service function and residual life of the pervious concrete material [68]. Therefore, the effect of the freeze-thaw cycle on the microstructure parameters of the bond affected the microstructure parameters of the whole model. The DEM simulated the macroscopic mechanical response of concrete by means of the law of bond contact at the particle scale, so the macroscopic material parameters obtained through experiments cannot be directly applied to the numerical model. The DEM simulated the macroscopic mechanical response of concrete by means of regular bond contact at the particle scale, so the macroscopic material parameters obtained through experiments cannot be directly applied to the numerical model [69]. The compressive elastic modulus and peak compressive strength of the parallel bond model materials were affected by the effective modulus of the parallel bond, normal bond strength and tangential bond strength [70,71]. The formula for compression modulus Et is as follows:(12) Et=σcεc where Etis the compression–elastic modulus, Gpa; σc is the peak stress; εc is the peak stress corresponding strain. In this model, the bond strength ratio of normal shear was set as 1:1, and the two were collectively referred to as bond strength. Both effective modulus and compressive strength tests were performed to obtain the relation between the effective modulus and compressive modulus, as shown in Figure 17. Figure 18 presents the relationship between the bond effective modulus, bond strength and peak compressive strength and the fitting equation was established, as shown in Equation (13). The bond effective modulus and bond strength were the main influencing factors of the compressive modulus and peak stress, respectively. At the same time, the change of the bond effective modulus had a slight influence on the peak stress, and the change of the bond strength also had the same effect on the compressive elastic modulus. However, for a more accurate simulation, the interaction of the two should be considered using macro parameters. (13) {Et=0.52165c¯−0.055c¯2+2.73867E*¯−0.09931E*¯2−0.7854, R2=0.99761σc=6.08544c¯−0.03441c¯2+0.05666E*¯−0.06233E*¯2−0.5919,R2=0.99949 where Et is the compression–elastic modulus, Gpa; E¯* is the effective modulus of parallel bonding, Gpa; σc is the peak stress (compressive strength), MPa; c¯ is bond strength, MPa. It can be seen from Equation (13) that in order to establish the relationship between the number of freeze-thaw cycles and the meso-parameters of the model, the relationship between the compressive elastic modulus Et, the peak stress σc and the number of freeze-thaw cycles should be established first. Since only the initial peak strain was measured in this study, so the relationship between the relative peak strain of concrete and the number of freeze-thaw cycles and the cube′s compressive strength (peak stress) is shown as follows [72]:(14) εc,Dεc,0=(−7.57σc,0+408.85)N×10−4+1 where εc,D is the compressive peak strain of concrete after freeze-thaw; εc,0 is the compressive peak strain of unfreeze-thawed concrete; σc,0 is the compressive strength of unfreeze-thawed concrete; N is the number of freeze-thaw cycles. The relationship between the peak stress σc and the number of freeze-thaw cycles can be obtained according to the previous strength loss model Equation (11), the following Equation (15) can be obtained:(15) (1−σc,s,dσc,0)×100%=(0.0001N2+0.25N)/100 According to Equations (14) and (15) and the initial compressive strength of freeze-thaw 23.13 MPa, the measured peak strain was 2.78 × 10−3. The compressive stress and strain of the concrete undergoing freeze-thaw cycles in a salt freezing environment are shown in Table 4. Equations (12)–(15) were combined to obtain the relationship between the number of freeze-thaw cycles N and the microscopic parameters of the discrete element model, as shown below:(16) {23.13−2.313×10−5N2−0.0578255406.77395N×10−4+23.13=0.52165c¯−0.055c¯2+2.73867E*¯−0.09931E*¯2−0.785423.13−2.313×10−5N2−0.057825N=6.08544c¯−0.03441c¯2+0.05666E*¯−0.06233E*¯2 We substitute the freeze-thaw times N of 0, 25, 50, 75 and 100 into Equation (16) to obtain the model′s microscopic parameters under different freeze-thaw times, as shown in Table 5. The mesoscopic parameters of different freeze-thaw times were input into the established discrete element model. After PFC software calculation, the initial stress–strain curve simulation curve and the compressive strength values of different freeze-thaw cycles are obtained, as shown in Figure 19a,b. It can be seen from Figure 19a that there was a certain deviation between the physical test results and the DEM simulation results. The physical compressive strength test of the permeable concrete initially had a compaction stage, and then it was linearly elastic. The DEM simulation directly entered the linear elastic stage, and the DEM simulation of the descending section of the post-peak curve was more advanced. Such deviations may arise from the simplifications assumed in the constitutive model of this model, or due to imperfections in the contact between the specimen and the loading plate in the experimental tests [73]. However, this error did not affect the accuracy of compressive elastic modulus and peak stress. It can be seen from Figure 19b that the DEM simulation value of the compressive strength of pervious concrete with different freeze-thaw times had some deviation from the experimental value, and the existence of such a deviation was reasonable. This was because the discrete element freeze-thaw damage model was established based on the regression equation of test strength loss, as shown in Equation (11), and the deviation between the regression equation and the test value resulted in the deviation of the discrete element fitting value. It can be seen that DEM simulation intensity loss was close to the intensity loss model. The previous section explained why model curves that fit better with experimental values were not selected. The relationship between the mesoscopic bond strength and macro strength of the pervious concrete is shown in Figure 19c. The variation of the mesoscopic bond strength of the model undergoing freeze-thaw cycles was highly consistent with the variation of the macroscopic bond strength in the physical test, indicating that the strength deterioration of the pervious concrete came from the reduction of bond strength between the aggregate particles. Although the DEM model had a good simulation of the strength changes of pervious concrete under freeze-thaw cycles, the model was simplified in the following aspects. In the simulation, the ratio of normal and tangential bond strengths was fixed, and the failure modes of specimens were not compared and calibrated. The coarse aggregate was a rigid body without fracture and there was a single aggregate shape. This also led to the limited applicability of the model in the study of other problems, such as the study of failure morphology changes of pervious concrete with different cycles. 4. Conclusions In this study, through freeze-thaw cycle tests (water freezing and salt freezing) on pervious concrete and paste with the same W/C ratio, the mass loss, dynamic elastic modulus and compressive strength attenuation laws were investigated, and the freeze-thaw damage prediction model of pervious concrete was established. The relationship between the freeze-thaw damage of a hardened cement paste and the freeze-thaw damage of pervious concrete was studied. At the micro-scale, the evolution of porosity, characteristic pore size and pore size distribution of frozen and thawed paste (at the same W/C ratio as pervious concrete) was studied by the mercury intrusion porosimetry (MIP) method. The damage process and mechanism of the freeze-thaw cycle (water freezing and salt freezing) on the microstructure of pervious concrete were analyzed by scanning electron microscopy (SEM) and energy dispersive spectrometry (EDS). The relationship between the mesoscopic parameters and the macroscopic properties of the pervious concrete specimens was analyzed by the discrete element method (DEM) in combination with the experimental mixed-ratio parameters. The conclusions of this paper were as follows: After 100 cycles of freezing and thawing, the mass loss of the pervious concrete was 0.47% and 0.82%, the strength loss was 16% and 23% and the dynamic elastic modulus loss was 7.9% and 11.4%, respectively. The water–cement ratio did not change the strength significantly. Considering the interfacial crack propagation observed by electron microscopy, it can be concluded that the freeze-thaw deterioration of the pervious concrete mainly came from the interfacial zone. The pore size of the cement paste with a water–cement ratio of 0.31 was concentrated at 5–69 nm, and the change of pore size distribution below 200 nm did not affect the macro-strength of the cement paste. There is almost no aggregate cement interface zone in pervious concrete at a water–cement ratio of 0.31. The DEM model can better simulate strength changes of pervious concrete undergoing freeze-thaw cycles, and its macroscopic strength changes were consistent with the microscopic bond strength changes between particles in the DEM model, indicating that the strength deterioration of pervious concrete was caused by the reduction of the bond strength between the aggregate particles. However, due to the limitation of the assumptions of the model, this model was only applicable to the study of strength loss, and it had limitations in the study of other freeze-thaw deterioration indexes or the change of failure forms of pervious concrete. Therefore, the model can be further improved in the future, and more mesoscopic parameter changes need to be considered and calibrated with physical tests in terms of failure modes. Author Contributions Conceptualization, J.X.; formal analysis, J.X.; Methodology, J.X.; writing original draft, H.L. (Hengrui Liu); writing review and editing, H.L. (Hengrui Liu); Investigation, H.L. (Hao Lu); supervision, F.G. All authors have read and agreed to the published version of the manuscript. Funding This study was financially supported by the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Funding sponsor Hengrui Liu). Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data Sharing is not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Failure transformation of linear parallel bonding. Figure 2 (a) Aggregate model (b) DEM model of pervious concrete (c) Axial loading diagram. Figure 3 Change of pervious concrete morphology under different freeze-thaw cycles (a) aqueous solution; (b) salt solution; (e, f, o, p represent F-T 0 times, e*, f*, o*, p* represent F-T 100 times). Figure 4 Changes of cement paste under freeze-thaw cycles (a) changes in quality and strength; (b) changes in morphology. Figure 5 Structure of aggregate paste falling off. Figure 6 Relative strength change of pervious concrete under freeze-thaw cycles. Figure 7 The average index of freeze-thaw durability of permeable concrete (a) Relative ultrasonic wave velocity; (b) Mass remaining; (c) Relative dynamic elastic modulus. Figure 8 Relative effective porosity change of permeable concrete under freeze-thaw cycles. Figure 9 Fitting curve of dynamic elastic modulus loss of permeable concrete under freeze-thaw cycles. Figure 10 Fitting curve of mass loss of permeable concrete under freeze-thaw cycles. Figure 11 Fitting curve of strength loss of permeable concrete under freeze-thaw cycles. Figure 12 Variation of pore structure characteristic parameters of cement paste with different freeze-thaw cycles. (a) Changes of pore size parameter; (b) Changes of porosity change. Figure 13 Relationship between pore size distribution and cumulative mercury content of cement paste under different freeze-thaw cycles. Figure 14 Pore size distribution of cement paste under freeze-thaw cycles. Figure 15 EDS spectrum of ITZ (a) aggregate area; (b) hardened cement paste area. Figure 16 SEM image of aggregate interface with different freeze-thaw cycles (a) Initial; (b) F-T 50 times; (c) F-T100 times. Figure 17 Relationship between bond effective modulus, bond strength and compressive elastic modulus. Figure 18 Relationship between bond effective modulus, bond strength and peak stress. Figure 19 (a) Comparison of initial stress and strain curves of pervious concrete by discrete element simulation; (b) Comparison of strength loss DEM simulation value and test value; (c) Comparison of relative compressive strength and relative meso bond strength. materials-15-03054-t001_Table 1 Table 1 Performance parameters of Jiuherun brand additive agent. Solid Content/% Moisture Content/% Fineness/% Total Alkalinity/% NaSO4/% CaO/% SiO2/% Bulk Density/g/cm3 96 3.17 16.87 6.46 4.83 0.92 64.6 0.678 materials-15-03054-t002_Table 2 Table 2 Amount of each material per cubic meter of permeable concrete. Cement kg/m3 Aggregate kg/m3 Water kg/m3 Reinforcer kg/m3 417.28 1600 129.35 16.69 materials-15-03054-t003_Table 3 Table 3 Contents of each element in energy spectrum. Energy Spectrum Analysis Region Element (wt%) O Ca C Si Al Fe Other Aggregate 25.64 68.13 6.23 - - - - Cement paste 45.83 28.73 15.42 5.68 1.91 0.75 1.68 materials-15-03054-t004_Table 4 Table 4 Compressive stress and strain values of concrete under freeze-thaw cycles (salt freezing). Number of Freeze-thaw Cycles (N) 0 25 50 75 100 Peak stress (MPa) 23.13 21.67 20.18 18.66 17.12 Peak strain (×10−3) 2.78 4.38 6.03 7.65 9.28 materials-15-03054-t005_Table 5 Table 5 Changes of meso parameters of model under freeze-thaw cycles. Number of Freeze-thaw Cycles Bond Effective Modulus (Gpa) Cohesion (MPa) Bond Normal-to-Shear Stiffness Ratio Friction Angle (°) Fric 0 3.22 4.120 1.5 40 0.5 25 1.776 3.754 1.5 40 0.5 50 1.136 3.485 1.5 40 0.5 75 0.795 3.221 1.5 40 0.5 100 0.585 2.958 1.5 40 0.5 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Hwang S. Yeon J.H. Fly Ash-Added, Seawater-Mixed Pervious Concrete: Compressive Strength, Permeability, and Phosphorus Removal Materials 2022 15 1407 10.3390/ma15041407 35207946 2. Baneviciene V. Malaiskiene J. Boris R. Zach J. The Effect of Active Additives and Coarse Aggregate Granulometric Composition on the Properties and Durability of Pervious Concrete Materials 2022 15 1035 10.3390/ma15031035 35160981 3. Zhu H. Wen C. Wang Z. Li L. Study on the Permeability of Recycled Aggregate Pervious Concrete with Fibers Materials 2020 13 321 10.3390/ma13020321 31936714 4. Tsang C. 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PMC009xxxxxx/PMC9099703.txt

==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093596 sensors-22-03596 Communication High-Frequency Vibration Analysis of Piezoelectric Array Sensor under Lateral-Field-Excitation Based on Crystals with 3 m Point Group Xu Jiachao 1 Shi Hao 1 Sun Fei 1 Tang Zehuan 1 Li Shuanghuizhi 1 Chen Dudu 1 Ma Tingfeng 1* https://orcid.org/0000-0002-1564-7179 Kuznetsova Iren 2 Nedospasov Ilya 2 Zhang Chao 3 Zampetti Emiliano Academic Editor Dirri Fabrizio Academic Editor 1 Piezoelectric Device Laboratory, School of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China; 1911081015@nbu.edu.cn (J.X.); shihao1990@nbu.edu.cn (H.S.); 2011081153@nbu.edu.cn (F.S.); 2011081009@nbu.edu.cn (Z.T.); 2111081008@nbu.edu.cn (S.L.); 1911081041@nbu.edu.cn (D.C.) 2 Kotelnikov Institute of Radio Engineering and Electronics of RAS, Moscow 125009, Russia; kuziren@yandex.ru (I.K.); ianedospasov@mail.ru (I.N.) 3 Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China; zhangchao1969@tsinghua-sz.org * Correspondence: matingfeng@nbu.edu.cn 09 5 2022 5 2022 22 9 359611 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/). Based on Mindlin’s first-order plate theory, the high-frequency vibrations of piezoelectric bulk acoustic wave array sensors under lateral-field-excitation based on crystals with 3 m point group are analyzed, and the spectral-frequency relationships are solved, based on which, the optimal length–thickness ratio of the piezoelectric crystal plate is determined. Then, the dynamic capacitance diagram is obtained by a forced vibration analysis of the piezoelectric crystal plate. The resonant mode conforming to good energy trapping is further obtained. The frequency interferences between different resonator units are calculated, and the influences of the spacing between two resonant units on the frequency interference with different electrode widths and spacings are analyzed. Finally, the safe spacings between resonator units are obtained. As the electrode spacing value of the left unit increases, the safe spacing d0 between the two resonator units decreases, and the frequency interference curve tends to zero faster. When the electrode spacings of two resonator units are equal, the safe distance is largest, and the frequency interference curve tends to zero slowest. The theoretical results are verified further by finite element method. The analysis model of high frequency vibrations of strongly coupled piezoelectric bulk acoustic array device based on LiTaO3 crystals with 3 m point group proposed in this paper can provide reliable theoretical guidance for size optimization designs of strongly coupled piezoelectric array sensors under lateral-field-excitation. bulk acoustic wave sensor array devices 3 m point group crystals lateral-field-excitation energy trapping National Natural Science Foundation of China12172183 11772163 Natural Science Foundation of Zhejiang ProvinceLY21A020007 LY19A020003 Ningbo Municipal Bureau of Science and Technology2019B10122 Russian Ministry of Science and Higher EducationFFWZ-2022-0002 This work was supported by the National Natural Science Foundation of China (Nos. 12172183, 11772163), the Natural Science Foundation of Zhejiang Province (Nos. LY21A020007, LY19A020003), the Ningbo Municipal Bureau of Science and Technology (No. 2019B10122). Prof. Iren Kuznetsova and Dr. Ilya Nedospasov thank to Russian Ministry of Science and Higher Education (FFWZ-2022-0002) for partial financial support. ==== Body pmc1. Introduction The traditional electric field excitation mode for piezoelectric bulk acoustic wave devices is thickness-field-excitation (TEF) [1,2,3,4,5,6], for which the electrodes are arranged on the upper and lower surfaces of the crystal plate, and the direction of the electric field is along the thickness direction of the crystal plate. Later, it was found that bulk acoustic devices can also operate in lateral-field-excitation (LFE) mode. Initially, the electrodes of LFE devices were arranged on either side surface of the crystal plate [7]. However, because the crystal plate is too thin, it is difficult to place electrodes on the side surface. In recent years, an effective method emerges, namely, the electrodes of LFE devices were placed on the same surface (top or bottom surface) of the crystal plate [8,9,10,11,12], and the direction of the electric field is perpendicular to the thickness direction of the crystal plate. LFE devices have the following advantages: because of the electrode arrangement, it is easier to package the device; the unnecessary vibration modes can be eliminated by changing the orientation of the electrodes; there is only weak vibration in the middle unelectroded region, which reduces the aging rate of the device [9,10,11]. For piezoelectric bulk acoustic wave sensors with a single resonator unit, the measurement accuracy is influenced by the ambient temperature and humidity [13]. In addition, in biological detection and mixed gas composition analysis, the bulk acoustic wave sensor with a single resonant unit cannot measure multiple components simultaneously [14]. In recent years, piezoelectric crystal microbalance array emerged. For this type of device, there are several resonator units made on a single crystal plate [15,16,17], among which, a reference unit can be set to eliminate the influence of environmental factors. Different selective adsorption films can be made on different units to achieve simultaneous measurement of multiple components [16,17]. Piezoelectric bulk acoustic wave array devices excited by lateral electric fields have a good application prospect in multi-component sensing. At present, quartz crystal is usually the crystal plate material used in LFE piezoelectric bulk acoustic wave array device, but the quartz crystal has low piezoelectric coupling coefficients, and is difficult to meet the requirements of measurement with high precision, high sensitivity, and large damping [18]. Cubic 3 m point group piezoelectric crystals (LiTaO3, LiNbO3, etc.) have high piezoelectric coupling coefficients [19,20], thus LFE bulk acoustic wave devices based on such crystal materials have obvious advantages. However, due to its high piezoelectric coupling coefficient, the electric field and displacement distributions of strongly coupled LFE array devices are more complex than that base on quartz crystals, and the energy trapping characteristics of the device are still not clear. In addition, the frequency interferences between adjacent units are obvious, the effect of the structure parameters on which need to be clarified. In this paper, the high-frequency vibration analysis model of strongly coupled piezoelectric bulk acoustic devices based on 3 m point group crystals excited by lateral electric fields is established, the coupling relationships between vibration modes are clarified, and the influence of structural parameters on the frequency interference between resonator units are revealed, which provides reliable guidance for the size design of strongly coupled LFE array devices based crystals with 3 m point group. The mathematical model in this work is based on Mindlin’s first-order plate theory, which is an approximate two-dimensional theory. The calculation error of the frequency shift is negligible [7]. Compared with the finite element method, the method based on Mindlin’s first-order plate theory could clarify the mechanisms of frequency interferences between different resonator units conveniently, and the calculation time is shortened obviously. 2. Frequency Spectrum Calculation Figure 1 shows the structure diagram of LiTaO3 LFE bulk acoustic wave array devices. Two pairs of electrodes are placed in the top surface of the crystal plate, forming two resonator units RU-A and RU-B. b1 and b2 are the electrode widths of RU-A and RU-B, respectively. d1 and d2 are the electrode spacings of RU-A and RU-B, respectively. d0 is the spacing between the two resonator units; 2 L and 2 h are the length and thickness of the crystal plate. ρe and 2he are the density and thickness of the electrodes, respectively. For 3 m point group piezoelectric single crystal, the motion control equation of unelectroded region is: (1) k1C65u3,11(0)+k12C66u2,11(0)+k12C66u1,1(1)+k1e16ϕ,11(0)=ρu¨2(0),C55u3,11(0)+k1C56u2,11(0)+k1C56u1,1(1)+e15ϕ,11(0)=ρu¨3(0),γ11u1,11(1)−3h−2k1C65u3,1(0)+k12C66u2,1(0)+k12C66u1(1)+k1e16ϕ,1(0)=ρu¨1(1),e15u3,11(0)+k1e16u2,11(0)+u1,1(1)−ε11ϕ,11(0)=0, Where cpq(=cpqE), eip and εij=εijS are elastic stiffness, piezoelectric constant, and dielectric constant, respectively. The motion control equation of electroded region is: (2) k¯1C65u3,11(0)+k¯12C66u2,11(0)+k¯12C66u1,1(1)=1+Rρu¨2(0),C55u3,11(0)+k¯1C56u2,11(0)+k¯1C56u1,1(1)=1+Rρu¨3(0),γ11u1,11(1)−3h−2k¯1C65u3,1(0)+k¯12C66u2,1(0)+k¯12C66u1(1)=1+3Rρu¨1(1). According to the standing wave hypothesis of the finite plate, the forms of displacement and potential are assumed to be:(3) u20=A1sinξx1eiωt,u30=A2sinξx1eiωt,u11=A3cosξx1eiωt,ϕ0=A4sinξx1eiωt. By substituting (3) into the governing Equation (1), a set of four-order linear equations for amplitudes A1−A4 is obtained. Since the amplitudes has non-zero solutions, the determinant of its coefficient matrix is zero, and a four-order polynomial about the wave number can be obtained. Finally, four corresponding solutions are obtained by solving this polynomial, including three non-zero solutions and one zero solution. When ξm2=0, ϕ,10=−Eeiωt is assumed to be the form of electric field excitation, and E is the voltage of excitation. ϕ0 is a linear function about coordinate x1, namely ϕ0=ϕ0x1. After substituting that into Equation (3), displacements and electric potential can be obtained in the form:(4) u20=0,u30=0,u11=A3eiωt,ϕ0=ϕ0x1. Substituting (4) into (1), we obtain:(5) −3h−2k12C66u11+k1e16ϕ,10=ρu¨11, where u11=−B1Eeiωt. By solving Equation (5), we obtain:(6) B1=−k1e16k12C66−π212C66Ω2. Based on the above equation, the forms of displacement and potential solution are set as follows:(7) u20u30u11ϕ0=∑m=13cmβ1msinξmx1β2msinξmx1β3mcosξmx1β4msinξmx1+c400B1x1, where βim is the amplitude ratio, namely AriA4ir=1−4,i=1-4, which can be determined by (8) C66Ω2−k12C66Zi2−k1C65Zi2−2hπk12C66Zi−k1C56Zi2C66Ω2−C55Zi2−2hπk1C56Zi−6πhk12C66Zi2−6πhk1C65Zi2C66Ω2−γ11Zi2−12π2k12C66A1iA4iA2iA4iA3iA4i=k1e16Zi2e15Zi2−6πhk1e16Zi. Boundary conditions are as follows:(9) T60=0,T50=0,T11=0,D10=0,x1=±L. Substituting Equation (7) into Equation (9), we obtain (10) H1cosπZ12chH2cosπZ22chH3cosπZ32chH4I1sinπZ12chI2sinπZ22chI3sinπZ32ch0β31sinπZ12chβ32sinπZ22chβ33sinπZ32chx3β41cosπZ12chβ42cosπZ22chβ43cosπZ32chB=0, where (11) Hi=2hk1C65β2iπZi2h+k12C66β1iπZi2h+β3i+k1e16πZi2hβ4i,H4=2hk12C66B1+k1e16,Ii=2hC55β2iπZi2h+k1C56β1iπZi2h+β3i+e16πZi2hβ4i,I4=2hk1C56B1+e15,Ji=2h33−γ11β3iπZi2h,Wi=2he15β2iπZi2h+k1e16β1iπZi2h+β3i−ε11πZi2hβ4iW4=2hk1e16B1−ξ11. By solving Equation (10), the spectrum diagram of the LiTaO3 crystal plate excited by lateral electric fields can be obtained, as shown in Figure 2. In Figure 2, the horizontal line is the main vibration mode, namely the thickness- shear mode. The slanted curved lines in the upper part represent the bend modes, and the slanted straight lines represent the face-shear modes. In the figure, two types of curves will form an intersection point, which is with the strongest coupling between different modes. The middle point between two intersections is with the weakest coupling, such as the mode showed by the red point. 3. Electrically Forced Vibration As shown in Figure 3, the device is divided into 9 regions, 1 and 3 are the unelectroded regions of Ru-A, 2 and 4 are the electroded regions of Ru-A, 5 are the unelectroded region between the two units, 6 and 8 are the electroded regions of Ru-B, and 7 and 9 are the unelectroded regions of Ru-B. m0 and m9 are boundary points of the device. m1~m8 is the junction point of unelectroded and electroded regions of two resonator units. The forms of the displacements and potential of the unelectroded regions are assumed to be (12) u2(0)=A1eiξx1eiωt,u3(0)=A2eiξx1eiωt,u1(1)=A3eiξx1eiωt,ϕ(0)=A4eiξx1eiωt. By substituting Equation (12) into the governing Equation (1), a set of fourth-order linear equations about amplitudes A1–A4 are obtained. Since the amplitude has non-zero solutions, the determinant of coefficient matrix of equations is zero, and a fourth-order polynomial about wave number can be obtained. Finally, eight frequency solutions corresponding to wave number are obtained by solving this polynomial, including six non-zero solutions and two zero solutions:(13) u2(0)u3(0)u1(1)ϕ(0)=∑m=16c˜(m)β˜1(m)eiξ(m)x1β˜2(m)eiξ(m)x1β˜3(m)eiξ(m)x1β˜4(m)eiξ(m)x1+c˜(7)00B˜1x1+c˜(8)0001 For unelectroded regions 3 and 7, (14) B1=−k1e16k12C66−π212C66Ω2. For unelectroded regions 1, 5, and 9, B2=−B1. c(1)−c(8) are undetermined constants, β˜im is the amplitude ratio, namely AriA4ir=1−4,i=1-8, which can be determined by (15) C66Ω2−k12C66Zj2−k1C65Zj2i2hπk12C66Zj−k1C56Zj2C66Ω2−C55Zj2i2hπk1C56Zj−i6πhk12C66Zj−i6πhk1C65ZjC66Ω2−γ11Zj2−12π2k12C66β˜1(m)β˜2(m)β˜3(m)=k1e16Zj2e15Zj2i6πhk1e16Zj The forms of the displacements and potential of the electroded regions are assumed to be (16) u20=A1eiξ¯x1eiωt,u30=A2eiξ¯x1eiωt,u11=A3eiξ¯x1eiωt. Substituting (16) into (2), a set of third-order linear equations with respect to A1−A3 are obtained. When the determinant of the coefficient matrix of the equations is zero, non-zero solutions exist. Base on that we can obtain a third order polynomial with wave number. By solving the third-order polynomial, six wavenumber solutions are obtained, namely three pairs of non-zero conjugate solutions. (17) u2(0)u3(0)u1(1)=∑m=16C¯(m)β¯1(m)eiξ¯(m)x1β¯2(m)eiξ¯(m)x1β¯3(m)eiξ¯(m)x1, where C¯mm=1−6 are undetermined constants, β¯im is the amplitude ratio, which can be determined by (18) (1+R)C66Ω2−k¯12C66Zj2−k¯1C65Zj2−k¯1C56Zj2(1+R)C66Ω2−C55Zj2β¯1(m)β¯2(m)=−i2hπk¯12C66Zj2−i2hπk¯1C56Zj2. For m0 and m9, boundary conditions are (19) T50x1=m0=0,T60x1=m0=0,T11x1=m0=0,D10x1=m0=0. (20) T50x1=m9=0,T60x1=m9=0,T11x1=m9=0,D10x1=m9=0. For m1~m8, continuous conditions are (21) u20x1=m1−=u20x1=m1+u30x1=m1−=u30x1=m1+u11x1=m1−=u11x1=m1+T50x1=m1−=T50x1=m1+T60x1=m1−=T60x1=m1+T11x1=m1−=T11x1=m1+ϕ(0)x1=m1−=−Veiωt (22) u20x1=m2−=u20x1=m2+u30x1=m2−=u30x1=m2+u11x1=m2−=u11x1=m2+T50x1=m2−=T50x1=m2+T60x1=m2−=T60x1=m2+T11x1=m2−=T11x1=m2+ϕ(0)x1=m2−=−Veiωt (23) u20x1=m3−=u20x1=m3+u30x1=m3−=u30x1=m3+u11x1=m3−=u11x1=m3+T50x1=m3−=T50x1=m3+T60x1=m3−=T60x1=m3+T11x1=m3−=T11x1=m3+ϕ(0)x1=m3−=Veiωt (24) u20x1=m4−=u20x1=m1+u30x1=m4−=u30x1=m1+u11x1=m4−=u11x1=m1+T50x1=m4−=T50x1=m1+T60x1=m4−=T60x1=m1+T11x1=m4−=T11x1=m1+ϕ(0)x1=m4−=Veiωt (25) u20x1=m5−=u20x1=m5+u30x1=m5−=u30x1=m5+u11x1=m5−=u11x1=m5+T50x1=m5−=T50x1=m5+T60x1=m5−=T60x1=m5+T11x1=m5−=T11x1=m5+ϕ(0)x1=m5−=−Veiωt (26) u20x1=m6−=u20x1=m6+u30x1=m6−=u30x1=m6+u11x1=m6−=u11x1=m6+T50x1=m6−=T50x1=m6+T60x1=m6−=T60x1=m6+T11x1=m6−=T11x1=m6+ϕ(0)x1=m6−=−Veiωt (27) u20x1=m7−=u20x1=m7+u30x1=m7−=u30x1=m7+u11x1=m7−=u11x1=m7+T50x1=m7−=T50x1=m7+T60x1=m7−=T60x1=m7+T11x1=m7−=T11x1=m7+ϕ(0)x1=m7−=Veiωt (28) u20x1=m8−=u20x1=m8+u30x1=m8−=u30x1=m8+u11x1=m8−=u11x1=m8+T50x1=m8−=T50x1=m8+T60x1=m8−=T60x1=m8+T11x1=m8−=T11x1=m8+ϕ(0)x1=m8−=Veiωt Substitution of (13), (17) to (19)–(28) results in 64 non-homogeneous linear equations, then 64 undetermined constants can be solved. The charge Qe on the electrode and the motion capacitance C could be obtained as (29) Qe=−D30x3=j⋅2w,C=Qe2V,C0=4ε33hw/2L, where C0 is the static capacitance. The curve of C/C0 with respect to the frequency could be used to determine the resonance modes. 4. Results and Discussion 4.1. Resonance Modes According to the theoretical model established above, the forced vibration analysis of the device is carried out through an example. Structural parameters of the array device are shown in Table 1 below. Substituting of (13), (17) to (29) results the according non-homogeneous linear equations, based on which the capacitance ratio vs. frequency of the device are obtained, which is shown in Figure 4. In Figure 4, the abscissa and ordinate are the normalized resonance frequency and the absolute value of capacitance ratio of the device, respectively. For Mode 1, Mode 2, and Mode 3, the displacement distribution curves of thickness-shear, bending and face-shear modes are presented in Figure 5, Figure 6 and Figure 7, respectively. As can be seen from Figure 5, for Mode 1, strong vibrations exist in the electroded regions of the two resonator units, and the vibrations become weaker obviously in the unelectroded regions of the two resonant units. In the electroded region, the acoustic wave can transmit normally [7]. When the acoustic wave meet the unelectroded region, the wave number become an imaginary number, thus the amplitude of the acoustic wave decrease exponentially, which is the energy-trapping effect [7]. Although Modes 2–3 also have the energy trapping characteristics, their vibration intensity are obviously lower than that of Mode 1. It is shown in Figure 6, the bending vibration intensity of Mode 2 and Mode 3 is much larger than that of Mode1, namely for Mode 1, parasitic modes can be effectively suppressed. As can be seen from Figure 7, for face-shear mode, the vibration of Mode 1 is very weak, and the vibrations of Mode 2 and Mode 3 are stronger, which meets the requirement of parasitic mode suppression of the device. Therefore, Mode 1 is an ideal operating frequency of the device. There are two units in the array device, the approximate operating mode obtained in this work cannot applied to multi-units devices. However, the method used in this work is suitable for multi-units devices. 4.2. Frequency Interferences between Two Resonator Units When the adsorption mass is increased on RU-B, the change of resonant frequency of RU-A reflects the frequency interference of two units. Theoretically, when two resonant units are far enough apart, the frequency interference approaches zero [15]. This spacing is defined as safety spacing. It is necessary to analyze the influence of electrode parameters on the safe spacing. Table 2 and Table 3, respectively, show the safe spacing d0 between two resonator units under different electrode widths. Figure 8 and Figure 9, respectively, show the frequency interference curves when changing the spacing d0 between two resonator units under different electrode widths of RU-A and RU-B. Finite element simulation using COMSOL Multiphysics (Burlington, MA, USA), a commercially available modeling package, was performed to obtain the resonance frequency of the array device. This model is a three-dimensional model and the model size parameters are the same as the theoretical model parameters. A frequency domain analysis is carried out to simulate the wave propagation. The calculation results obtained by FEM are slightly higher than the theoretical ones. The observed errors may be due to the differences between the Mindlin plate theory with two-dimensional approximations and the three-dimensional model in the FEM method. It can be seen from Table 2 and Table 3, as well as Figure 8 and Figure 9, that, with the increase in electrode width of RU-A b1 or the decrease in electrode width of RU-B b2, the faster the frequency interference curve tends to 0, the safe distance d0 between two resonator units also decreases. When the electrode width of RU-A increases, the effective electric field is enhanced, and the vibration intensity of RU-A region is also enhanced, so the anti-interference ability of RU-A becomes stronger. When the electrode width of RU-B decreases, its effect on RU-A is weakened due to the weakening of the effective electric field. When the electrode widths of two resonator unit are equal, the decreasing speed of the frequency interference is smallest, and the safe distance d0 is maximum. Table 4 and Table 5 show the safe spacing d0 of the two resonator units with different electrode spacing of RU-A d1 and electrode spacing of RU-B d2. Figure 10 and Figure 11, respectively, show the frequency interference curves under different electrode spacings of RU-A and RU-B, respectively. As can be seen from Table 4 and Figure 10, as the electrode spacing value d1 of RU-A increases, the safe spacing d0 between the two resonator units decreases, and the frequency interference curve tends to zero faster. As can be seen from Table 5 and Figure 11, as the electrode spacing value d2 of RU-B increases, the safe spacing d0 between the two resonator units increases, and the frequency interference curve tends to zero with a lower speed. When the electrode spacings of two resonator unit are equal, the safe distance d0 is largest, and the frequency interference curve tends to zero slowest. 5. Conclusions In this paper, a theoretical model for analyzing the high-frequency vibration of the LFE bulk acoustic wave array devices based on 3 m point group crystals excited is established, the coupling relationships between vibration modes are clarified, and the influences of structural parameters on the frequency interference between resonator units are revealed. The following conclusions have been obtained: (1) With the increase in electrode width of RU-A or the decrease in electrode width of RU-B, the faster the frequency interference curve tends to 0, the safe distance d0 between two resonator units also decreases; (2) when the electrode widths of two resonator units are equal, the decreasing speed of the frequency interference is smallest, and the safe distance d0 is maximum; (3) as the electrode spacing value of RU-A increases, the safe spacing d0 between the two resonator units decreases, and the frequency interference curve tends to zero faster; (4) when the electrode spacings of two resonator unit are equal, the safe distance is largest, and the frequency interference curve tends to zero slowest. When the electrode structure parameters of the two units are closer, the resonance frequencies of the two units are more similar, thus the frequency interferences are more obviously. There are two units in the array device, the approximate operating mode obtained in this work cannot applied to multi-units devices. However, the method used in this work is suitable for multi-units devices. The theoretical model proposed in this work can provide reliable theoretical basis for parameter optimization designs of strongly coupled array sensors under lateral-field-excitation. Author Contributions J.X., H.S. and T.M. presented the idea and performed the theoretical analysis. F.S., Z.T., S.L., D.C., I.K., I.N. and C.Z. accomplished the FEM simulations and result verifications. The manuscript writing are contributed by J.X. and T.M. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors state that there is no conflict of interest. Figure 1 Structure diagram of LiTaO3 LFE bulk acoustic wave array devices. Figure 2 Relationship between the frequency and the ratios of the length to thickness of the LiTaO3 crystal plate excited by lateral electric fields. Figure 3 The partition diagram of LiTaO3 array devices with lateral-field-excitation. Figure 4 The relationship between the normalized frequency and capacitance ratio of the device. Figure 5 Thickness–twist strain distribution near resonance (u1,11). Figure 6 Flexure strain distribution near resonance (u2,10). Figure 7 Face-shear strain distribution near resonance (u3,10). Figure 8 Influences of RU-A’s electrode width on the frequency interference. Figure 9 Influences of RU-B’s electrode width on the frequency interference. Figure 10 Effect of RU-A’s electrode gap on frequency interference. Figure 11 Effect of RU-B’s electrode gap on frequency interference. sensors-22-03596-t001_Table 1 Table 1 Parameter setting. Parameter Value Description ω 10 MHz Fundamental frequency 2 h 0.01755 mm Thickness of the crystal plate L 239.6 h Length of the crystal plate 2 w 119.8 h Width of the crystal plate R 0.05 Mass ratio (Electrode/crystal) b 30 h Width of the electrode d 5 h Space of the two electrodes d 0 15 h Space of the two resonator units sensors-22-03596-t002_Table 2 Table 2 The safe distance d0 between the two resonant units under different electrode width b1 of Ru-A. b1 20 h 25 h 30 h 35 h Theoretical FEM Theoretical FEM Theoretical FEM Theoretical FEM d0 45 h 50 h 40 h 45 h 60 h 65 h 35 h 40 h sensors-22-03596-t003_Table 3 Table 3 The safe distance d0 between the two resonator units under different electrode width b2 of Ru-B. b2 20 h 25 h 30 h 35 h Theoretical FEM Theoretical FEM Theoretical FEM Theoretical FEM d0 35 h 40 h 40 h 45 h 60 h 65 h 45 h 50 h sensors-22-03596-t004_Table 4 Table 4 The safe distance d0 between the two resonator units with different electrode gap of RU-A. d1 4 h 5 h 6 h 7 h Theoretical FEM Theoretical FEM Theoretical FEM Theoretical FEM d0 55 h 60 h 60 h 65 h 45 h 50 h 35 h 40 h sensors-22-03596-t005_Table 5 Table 5 The safe distance d0 between the two resonator units with different electrode gap of RU-B. d2 4 h 5 h 6 h 7 h Theoretical FEM Theoretical FEM Theoretical FEM Theoretical FEM d0 35 h 40 h 60 h 65 h 45 h 50 h 55 h 60 h Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095203 ijms-23-05203 Article Genetic Deficiency of Indoleamine 2,3-dioxygenase Aggravates Vascular but Not Liver Disease in a Nonalcoholic Steatohepatitis and Atherosclerosis Comorbidity Model https://orcid.org/0000-0002-2789-2593 Arora Aastha 12† Tripodi Gustavo Luis 13† https://orcid.org/0000-0002-2528-9264 Kareinen Ilona 1 Berg Martin 1 https://orcid.org/0000-0003-4907-4783 Forteza Maria Josefa 1 https://orcid.org/0000-0002-4614-8030 Gisterå Anton 1 Griepke Silke 2 https://orcid.org/0000-0003-1117-4754 Casagrande Felipe Beccaria 3 https://orcid.org/0000-0003-2630-7038 Martins Joilson O. 3 Abdalla Dulcineia Saes Parra 3 Cole Jennifer 4 Monaco Claudia 4 https://orcid.org/0000-0002-0087-116X Ketelhuth Daniel F. J. 12* Tan Nguan Soon Academic Editor 1 Division of Cardiovascular Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institute, Karolinska University Hospital, 17164 Stockholm, Sweden; gustavolt.90@gmail.com (G.L.T.); ilona.kareinen@gmail.com (I.K.); martin.berg@skane.se (M.B.); maria.forteza.de.los.reyes@ki.se (M.J.F.); anton.gistera@ki.se (A.G.) 2 Department of Cardiovascular and Renal Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense-C, Denmark; arora@health.sdu.dk (A.A.); sgnielsen@health.sdu.dk (S.G.) 3 Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo 05508-000, Brazil; felipe.casagrande@ki.se (F.B.C.); martinsj@usp.br (J.O.M.); dspa@usp.br (D.S.P.A.) 4 Kennedy Institute of Rheumatology, University of Oxford, OX3 7FY Oxford, UK; jennifer.cole@kennedy.ox.ac.uk (J.C.); claudia.monaco@kennedy.ox.ac.uk (C.M.) * Correspondence: daniel.ketelhuth@ki.se or ketelhuth@health.sdu.dk † These authors contributed equally to this work. 06 5 2022 5 2022 23 9 520307 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/). Nonalcoholic steatohepatitis (NASH) is a chronic liver disease that increases cardiovascular disease risk. Indoleamine 2,3-dioxygenase-1 (IDO1)-mediated tryptophan (Trp) metabolism has been proposed to play an immunomodulatory role in several diseases. The potential of IDO1 to be a link between NASH and cardiovascular disease has never been investigated. Using Apoe−/− and Apoe−/−Ido1−/− mice that were fed a high-fat, high-cholesterol diet (HFCD) to simultaneously induce NASH and atherosclerosis, we found that Ido1 deficiency significantly accelerated atherosclerosis after 7 weeks. Surprisingly, Apoe−/−Ido1−/− mice did not present a more aggressive NASH phenotype, including hepatic lipid deposition, release of liver enzymes, and histopathological parameters. As expected, a lower L-kynurenine/Trp (Kyn/Trp) ratio was found in the plasma and arteries of Apoe−/−Ido1−/− mice compared to controls. However, no difference in the hepatic Kyn/Trp ratio was found between the groups. Hepatic transcript analyses revealed that HFCD induced a temporal increase in tryptophan 2,3-dioxygenase (Tdo2) mRNA, indicating an alternative manner to maintain Trp degradation during NASH development in both Apoe−/− and Apoe−/−Ido1−/mice−. Using HepG2 hepatoma cell and THP1 macrophage cultures, we found that iron, TDO2, and Trp degradation may act as important mediators of cross-communication between hepatocytes and macrophages regulating liver inflammation. In conclusion, we show that Ido1 deficiency aggravates atherosclerosis, but not liver disease, in a newly established NASH and atherosclerosis comorbidity model. Our data indicate that the overexpression of TDO2 is an important mechanism that helps in balancing the kynurenine pathway and inflammation in the liver, but not in the artery wall, which likely determined disease outcome in these two target tissues. IDO inflammation atherosclerosis NASH immunometabolism Swedish Heart-Lung FoundationNovo Nordisk Foundation (MSAM consortium)NNF15SA0018346 Novo Nordisk Foundation (MeRIAD consortium)0064142 ‘Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil’001 ‘The São Paulo Research Foundation’2019/13598-8 FAPESP2020/03175-0 This study was supported by the Swedish Heart-Lung Foundation, the Novo Nordisk Foundation (MSAM consortium, NNF15SA0018346; MeRIAD consortium, 0064142), and the University of Southern Denmark. F.B.C. was supported by the foundation ‘Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil’ (CAPES; Finance Code 001). G.L.T. was supported by ‘The São Paulo Research Foundation’ (FAPESP; 2019/13598-8). J.O.M. was supported by FAPESP (2020/03175-0). ==== Body pmc1. Introduction Atherosclerosis is the underlying cause of most cardiovascular diseases (CVDs) and the leading cause of morbidity and mortality worldwide [1,2]. Atherosclerosis development is influenced by several risk factors, including dyslipidaemia, hypertension, smoking, and diabetes; targeting these risk factors is currently the main strategy to combat the CVD burden. Despite all the recent developments in medicine, only up to one-third of major clinical consequences of atherosclerosis, e.g., myocardial infarction, seem to be prevented by using the current guidelines [3]. It is now well recognized that atherosclerosis is a chronic inflammatory disease that is likely initiated by the accumulation of low-density lipoprotein (LDL) in the artery wall. The accumulation and modifications of LDL trigger maladaptive innate and adaptive immune responses in the artery wall, driving the formation of an atherosclerotic plaque, as well as a fibrous cap that, upon rupture, can cause thrombosis and a CVD event [4]. Large preclinical and, more recently, clinical evidence indicate that immunomodulation of vascular inflammation could be used to reduce the CVD burden beyond current guidelines for handling classic disease risk factors [5]. Activation of the immune system is not only well established within the pathophysiology of atherosclerosis, but also plays a major role in the development of nonalcoholic fatty liver disease (NAFLD), which can progress to nonalcoholic steatohepatitis (NASH); the latter that is defined as the combination of liver steatosis, parenchymal damage (hepatocyte apoptosis and ballooning, and focal necrosis), lobular and/or portal inflammation, and variable degrees of fibrosis [6,7]. Due to its association with obesity, type 2 diabetes, and the ectopic accumulation of lipids in the liver parenchyma, NASH has been considered an advanced hepatic component of metabolic syndrome and an additional risk factor for CVD [7]. Indoleamine 2,3-dioxygenase-1 (IDO1), the rate-limiting enzyme of the kynurenine pathway of tryptophan (Trp) metabolism, has been identified as a key immunomodulatory enzyme implicated in different diseases, including atherosclerosis and liver disease. It has been proposed that the local depletion of Trp and/or the production of potent bioactive metabolites of this pathway, collectively known as kynurenines, can modulate immune cell functions such as activation, proliferation, and migration [8]. While increased IDO1 expression, in the great majority of cases, has been implicated in atheroprotection [8,9,10,11,12,13,14,15,16], its role in liver inflammation and NAFLD/NASH is less clear. It has been shown that, upon high-fat diet feeding or the injection of CCL4, Ido1-deficient mice present increased hepatic inflammation and fibrosis [17,18]. IDO-dependent regulation of IL-17 release has been suggested as a major mechanism attenuating liver fibrosis [19,20]. However, IDO expression has also been associated with obesity and worsening insulin resistance through the regulation of intestinal permeability, which also influences liver steatosis [21]. Although NAFLD/NASH-related mortality is usually linked to adverse hepatic outcomes such as cirrhosis, liver failure, and hepatocellular carcinoma, CVDs are the main cause of mortality among patients with liver disease [22,23]. Thus, it has been hypothesized that NAFLD/NASH-related steatosis is a chronic inducer of low-grade hepatic inflammation and the source of several immunomodulatory mediators, which, when systemically released, could accelerate vascular inflammation and the development of CVDs [24]. Yet, the precise molecular mechanisms underlying the relationship between NASH and atherosclerosis remain unclear. In this study, we validated a new murine model that develops both NASH and atherosclerosis. Using Apoe−/− and Apoe−/−Ido1−/− mice that were fed a high-fat and cholesterol-rich diet, we demonstrate an essential role of IDO1 in accelerating vascular but not liver disease in the same animals. Our results indicate that disease-related factors promote the upregulation of tryptophan 2,3-dioxygenase (Tdo2) in the liver, which could help maintain local Trp degradation and prevent the aggravation of NASH. 2. Results 2.1. Apoe−/− Is a Suitable Strain for Studying Atherosclerosis and NASH as Comorbidities—Model Validation Both male and female Apoe−/− mice were fed HFCD for 3.5 and 7.0 weeks, and systemic organ-specific changes were evaluated. As expected, HFCD feeding led to significantly accelerated atherosclerosis, and after 7.0 weeks, a twofold increase in plaque area in the aortic arch was observed compared to chow-fed mice (Table 1; Figure 1A,B). A systematic review of the literature showed that, in the context of experimental atherosclerosis, a higher plaque burden is seen in young female hyperlipidaemic mice compared with their male counterparts [25]. Although we observed a trend towards females developing larger lesions than males after 7.0 weeks of HFCD, no significant difference was observed. No significant difference in lesion size between the HFCD- and chow-fed groups was observed at the 3.5-week time point (Table 1). In line with the atherosclerosis data, HFCD-fed mice presented significantly higher levels of plasma cholesterol and triglycerides, especially after 7.0 weeks of diet feeding (Table 1). Although not significant within 7 weeks, HFCD presented a clear trend towards a faster weight gain than chow-fed mice (Supplementary Figure S1). After confirming the atherosclerotic phenotype in our mice, we evaluated the effects of HFCD feeding on liver-related parameters. The liver-to-body ratio was significantly increased in Apoe−/− mice after 3.5 and 7.0 weeks of HFCD feeding (Table 1). These results were paralleled by significantly increased levels of plasma AST and ALT (Table 1). Additionally, hepatic accumulation of free iron was significantly increased in HFCD-fed mice compared to controls at the 7.0 weeks’ time point (Table 1). Altogether, the previous results indicated that HFCD feeding of Apoe−/− mice promoted liver damage. Corroborating the latter affirmation, 7.0 weeks of HFCD feeding increased the hepatic levels of TNF and CCL2 (Table 1). Interestingly, the hepatic levels of IL-10 followed a different pattern, and substantially lower levels of the cytokine were seen after 7.0 weeks, which was independent of the diet (Table 1). Considering that atherosclerosis and the first signs of NASH were observed after 7.0 weeks of HFCD, we selected this time point for further analyses. At this time point, HFCD clearly promoted hepatocyte ballooning (Figure 1A,B) and increased the accumulation of collagen, as evidenced by picrosirius red staining (Figure 1A,B). Further analyses showed that HFCD-fed mice presented significantly higher levels of hepatic cholesterol and triglycerides (Table 1), which was followed by a close to significant increase in hepatic hydroxyproline (Table 1) and a significant increase in Col1a1 mRNA levels, which encodes for the pro-alpha1 chain of type I collagen (Table 1). 2.2. Genetic Ablation of IDO1 in Apoe−/− Mice Accelerates Vascular, but Not Liver, Disease Our data indicated that 7.0 weeks of HFCD feeding represents a suitable time point to study both atherosclerosis and NASH as concomitant diseases, and this protocol was selected to evaluate the role of IDO1 in disease. In line with our previous studies [9,10], ablation of IDO activity (Apoe−/−Ido1−/−) significantly increased atherosclerosis in the aortic arch compared to Apoe−/− mice (Figure 2A,B). Hence, Apoe−/−Ido1−/− mice also presented more lesions in the aortic root and increased Mac-2+ macrophage infiltration compared to Apoe−/− controls (Figure 2C,D). Next, we evaluated whether IDO1 ablation would impact NASH-related parameters in our model. There was no difference in plasma cholesterol and triglycerides (Figure 2E,F) or bodyweight between groups (Supplementary Figure S2). In line with the plasma data, Apoe−/− and Apoe−/−Ido1−/− mice presented no difference in the hepatic accumulation of cholesterol and triglyceride levels (Figure 2G,H), and similar hepatocyte ballooning was observed between groups (Figure 2I). Further analyses showed that Apoe−/− and Apoe−/−Ido1−/− also did not differ in terms of the liver-to-body weight ratio (Figure 2J), plasma levels of ALT and AST (Figure 2K,L), hepatic Col1a1 mRNA levels (Figure 2M), and hydroxyproline content (Figure 2N). Corroborating with the latter result, no difference in the picrosirius red staining of collagen was observed between groups (Figure 2O). IDO1 ablation is usually followed by increased inflammation in different disease models [26,27], including atherosclerosis [8,9,10]. Immunofluorescence and macrophage-related transcript analyses revealed that Apoe−/− and Apoe−/−Ido−/− mice presented no differences in the hepatic infiltration of macrophages and the mRNA levels for the Kupfer cell marker Clec4f (Figure 3A–D) and no clear shift towards M1- or M2-like macrophage polarization patterns (Figure 3E,F). Of note, M1 and M2 terminologies are an oversimplification of a vast repertoire of phenotypes that can develop within an inflamed tissue, including atherosclerosis [28]. 2.3. Apoe−/−Ido1−/− Mice Presented Intact Hepatic Trp Degradation Rates despite Reduced Systemic and Aortic Trp Degradation Rates The Kyn/Trp is used as a surrogate marker of IDO1 activity and the degradation of Trp within the kynurenine pathway. As expected, the Kyn/Trp ratio was reduced in plasma and aortas from Apoe−/−Ido1−/− mice compared to Apoe−/− mice (Figure 4A,B). Unexpectedly, no difference in the hepatic Kyn/Trp ratio was observed between the groups (Figure 4C). In line with the fact that increased rates of Trp degradation are usually associated with decreased inflammation, we found that the aortic Kyn/Trp ratio was inversely correlated with the percentage of lesions in the aortic arch (Figure 4D). Despite no difference between groups on Mac-2+ macrophage numbers, the hepatic Kyn/Trp ratio was also inversely correlated with the macrophage marker CD68 (Figure 4E), suggesting that hepatic inflammation could be regulated by the degree of Trp degradation in the liver. 2.4. HFCD Increases Hepatic TDO2 Expression Although IDO1 has been implicated in the regulation of inflammation, another enzyme, tryptophan-2,3-dioxygenase (TDO2), is also involved in the first and rate-limiting step of the kynurenine pathway [29]. We observed a clear trend towards a temporal increase in the hepatic levels of Tdo2 mRNA between 3.5 and 7.0 weeks of HFCD feeding in Apoe−/−Ido1−/− mice (Figure 5). Interestingly, a similar increase in Tdo2 mRNA was observed in Apoe−/− (Figure 5). Although hepatic expression of TDO2 could be one explanation for the maintenance of Trp degradation and protection against the aggravation of liver disease in Apoe−/−Ido1−/−, the similar increase seen in the liver of Apoe−/− mice suggests that other mechanisms could influence Trp degradation in the presence of IDO1. Interestingly, aortic TDO2 protein levels were decreased in Apoe−/−Ido1−/− compared to Apoe-/- mice after 3.5 weeks of HFCD feeding, while no difference was observed between groups at the 7.0 weeks’ time point (Supplementary Figure S3). We have shown that the kynurenine pathway metabolism can regulate inflammasome activation and IL-1β secretion by macrophages [30]. In line with these data, IL-1β levels have been found to be increased in the plasma of Tdo2−/− mice injected with LPS [31]. In our comorbidity model, Apoe−/− and Apoe−/−Ido1−/− mice showed a time-dependent increase in the hepatic levels of TNF and CCL2, while a concomitant decrease in the hepatic levels of IL-1β was observed (Figure 5), suggesting that the latter could be regulated by TDO2. An increased accumulation of lipids and free iron are well-known characteristics of NASH progression [32], which was also observed in our model (Table 1 and Figure 1). Interestingly, TDO2 is a tetrameric haemoprotein that requires Fe2+ for its full activation as other catalytic haemoproteins, and iron has been proposed to upregulate TDO2 mRNA expression levels [33]. Considering all the previous, we tested whether excess palmitic acid (PA) or iron (FeSO4) could regulate the expression of TDO2 in the liver hepatoma cell line HepG2, and whether TDO2-mediated Trp metabolism on hepatic cells could influence IL-1β secretion by macrophages. Forty-eight hours of incubation of HepG2 cells with PA downregulated, while FeSO4 substantially increased, TDO2 mRNA levels (Figure 5C). Analyses of the supernatant of these cultures showed a decrease in the Kyn/Trp ratio in the supernatants of HepG2 cells treated with PA, while no changes were observed in cells treated with FeSO4 (Figure 5D). Interestingly, the concomitant addition of the TDO2 inhibitor LM10 to HepG2 cells treated with FeSO4 showed a reduced Kyn/Trp ratio compared to the control (Figure 5D). Next, we tested whether the regulation of TDO2 expression on HepG2 cells, and reflected alterations in Kyn/Trp ratio, could, in a paracrine manner, influence the response of THP1-differentiated macrophages to secrete IL-1β in vitro. We observed that conditioned media from HepG2 cells cultured with PA, which reduced their TDO2 expression and Kyn/Trp ratio, increased the secretion of IL-1β by THP1 macrophages (Figure 5E). Contrary to the effects of PA, the conditioned media from FeSO4-treated HepG2 cells, which upregulated TDO2 and maintained an unchanged the Kyn/Trp ratio, significantly inhibited IL-1β secretion; these protective properties were lost when HepG2 cells concomitantly received FeSO4 and the TDO2 inhibitor LM10 (Figure 5E). 3. Discussion NAFLD/NASH typically exists within the ‘‘milieu” of major diseases that play a central role in increasing the risk of CVD, including obesity, diabetes, and dyslipidaemia. Not surprisingly, myocardial infarction and stroke are highly prevalent in patients with metabolic liver disease [23]. Increasing our knowledge of the underlying mechanisms by which NAFLD/NASH accelerates atherosclerosis and increases cardiovascular risk can help improve the diagnosis and management of CVDs. In this study, we show that HFCD feeding promotes NASH and atherosclerosis in parallel in Apoe−/− mice, establishing a new viable dual comorbidity model. By feeding Apoe−/−Ido1−/− mice with HFCD, we show that IDO1-dependent Trp metabolism plays a distinctive role in regulating vascular versus fatty liver disease. There have been numerous attempts to generate animal models, especially murine models, that can recapitulate the aetiology, natural history, and/or progression that are inherent to atherosclerosis or NAFLD/NASH [34,35]. In this context, the two most common hypercholesterolaemic mouse strains used to study atherosclerosis, Apoe−/− and Ldlr−/−, have been evaluated regarding their susceptibility to developing NASH. Schierwagen et al., (2015) showed that 7 weeks of HFCD feeding led Apoe−/− mice to develop several features common to human NASH, including hepatic steatosis, inflammation, and a moderate degree of fibrosis [36]. Bieghs et al., (2012) showed that Ldlr−/− mice present increased sensitivity to hepatic inflammation, apoptosis, and fibrosis after 12 weeks of HFCD compared to the human APOE2 knock-in mouse (APOE2ki) and C57BL/6 strains [37]. Despite the potential within these models, atherosclerosis has not been investigated in these studies. To date, only a few studies have attempted to explore disease-modifying targets that could concomitantly influence NASH and CVD. Recently, van den Hoek et al., (2020) have shown that Ldlr−/−. Leiden mice develop NASH with progressive liver fibrosis, as well as atherosclerosis, upon 28 weeks of special high caloric diet feeding [38]. In our study, we established that HFCD feeding of Apoe−/− mice could also be a suitable strain for studying NASH and atherosclerosis simultaneously with a swift 7-week protocol. Thus, in addition to CVD, our mice presented all clinical signs that are characteristic of NASH, including liver steatosis, cytoskeletal damage (hepatocellular ballooning and increased levels of liver enzymes), inflammation, and a moderate degree of fibrosis, which, although not required for disease diagnosis, may indicate the aggravation of the disease state [39,40]. Inflammation is the major regulator of IDO1-dependent Trp metabolism in different cells and organs [41]. Increased IDO1 activity has been considered an important immune metabolic feedback mechanism regulating innate and adaptive immune cell responses [8]. Whether operating directly or indirectly, increased Trp metabolism through the kynurenine pathway has been linked with CVD because of its role in regulating vasculature [42], insulin resistance [30,43,44,45], or skewing of the gut microbiota [21]. Taking all previous knowledge into account, IDO1 emerged as an interesting target to be investigated in our dual model. As we have previously shown using pharmacological and genetic approaches [9,10], IDO1 ablation increases vascular inflammation and accelerates atherosclerosis, which could now be reproduced using a HFCD. Unexpectedly, in the current study, we did not observe an acceleration of liver disease. In light of the fact that using a downstream metabolite of IDO in the kynurenine pathway, 3-hydroxyanthranilic acid (3-HAA), could regulate cholesterol synthesis as well as plasma and hepatic cholesterol levels [30], our new data might appear counterintuitive. While further research will be needed to fully understand the potential causes of these differences, some hypothetical lines of reasoning could be drawn. We previously showed that 3-HAA mediated strong lipid-lowering effects in Ldlr−/− mice [30,46]. Hence, it was shown that genetic ablation of IDO in Ldlr−/− led to a significant increase in plasma lipids [47]. When using Apoe−/− mice, the pharmacological inhibition of IDO promoted only mild alterations to their lipoprotein profile, while four weeks of treatment with 3-HAA did not reverse the effects of IDO1 inhibition on lipids [46]. Interestingly, the original work from Cole et al., (2015) showed that Apoe−/−Ido−/− mice presented no overt alteration in plasma lipids under a chow diet [10], suggesting that the strain background could play a major role in how mice respond to variations in IDO1-mediated Trp metabolism. Considering that the kynurenine pathway has been implicated in the regulation of SREBP-2 [30], which, in addition to regulating cholesterol synthesis, also regulates LDLR expression, it seems plausible that the presence of LDL-receptor in the model could have implications to the degree of hepatic lipid accumulation [47]. As expected, we found that the Kyn/Trp ratio was decreased in the arteries and plasma from Apoe−/−Ido1−/− mice, compared to Apoe−/− mice. Surprisingly, the Kyn/Trp ratio in the liver of both groups was not different at the end of the experiment, suggesting that compensatory mechanisms might have been triggered in Apoe−/−Ido1−/− mice under HFCD or NASH that could maintain Trp degradation rates. In the context of human liver disease, it has been shown that high Kyn/Trp ratio is associated with greater liver fibrosis in the context of HIV and HCV infections, as well as in patients with acute decompensation and acute-on-chronic liver failure cirrhosis [48,49]. Considering that in the current work, after 7.0 weeks of HFCD, our model developed just early stages of liver disease and mild fibrosis, we can speculate that worsening of NASH could lead to altered kynurenine pathway metabolism, which needs to be validated in future studies. In line with the previous thought, it has been shown that kynurenine pathway activity was found to be normal in patients with compensated cirrhosis, and only changed with aggravation of the disease [49]. While IDO1 is thought to be an inducible enzyme triggered especially by proinflammatory factors such as interferon-γ (IFNγ), Trp can also be degraded by two other enzymes, the IDO1 paralogues IDO2 and TDO2. It has been suggested that TDO2 is constitutively expressed in the brain and in the liver. While some regulation redundancy/overlap between IDO1 and IDO2 expression has been suggested, it has been thought that TDO2 expression is mainly mediated by glucocorticoids and other hormones [29]. In our study, we observed that TDO2 is upregulated in the liver of Apoe−/−Ido1−/−, as well as Apoe−/− mice over time on diet, suggesting that alterations in lipids and/or inflammation, known to be induced in hyperlipidaemic mice over time [50], could regulate hepatic TDO2 regulation. Hence, the fact that TDO2 protein expression in the aortas do not follow the same pattern suggests that this enzyme plays a rather liver-specific role. It has been shown in a murine model of liver fibrosis with CCL4 that hepatic Tdo2 is upregulated in Ido1−/− mice [18]. In this study, the authors showed that Tdo2 upregulation was associated with increased expression of the general control nonderepressive-2 kinase (GCN2), a key nutrient sensor that is also known to be regulated by changes in amino acid metabolism [51]. As mentioned earlier, TDO2 is a haemoprotein that requires Fe2+ for its full activation. Hence, it has been proposed that haem promotes the de novo synthesis of TDO2, which constitutes an important mechanism of regulation of Trp degradation by this enzyme [33]. Using HepG2 hepatoma cultures, we found that excess fatty acids significantly downregulated, while iron upregulated TDO2 mRNA levels. Considering that lipid and iron accumulation are common features of NAFLD/NASH progression, our data suggest that these ‘nutrients’ could be involved in the transcription regulation of hepatic TDO2, regulation of Trp metabolism, as well as control of hepatic inflammation. As previously mentioned, IDO1-mediated immunoregulatory mechanisms could be the consequence of Trp depletion or the production of bioactive metabolites. In this context, there are bulk data indicating that kynurenines can influence immune responses in a paracrine fashion, e.g., the overexpression of IDO1 by tumours increases the production of L-Kyn and 3-HAA that can signal to inhibit effector T-cell responses or promote Treg differentiation [52,53]; the latter two outcomes have been recognized as an important mechanism of immune escape by tumours. Using conditioned media from HepG2 cells that were treated with palmitic acid or iron, on THP-1 macrophages, indicated that the regulation of TDO2 expression and Trp hepatic catabolism, through the kynurenine pathway, could constitute an important mechanism of communication between hepatocytes and macrophages, and the development of liver inflammation, particularly driven by IL-1β. Surprisingly for us, Tdo2 expression increased over time, not only in the livers of Apoe−/− Ido1−/− but also in Apoe−/− mice fed HFCD, which can express Ido1; however, the upregulation of Tdo2 in the latter strain did not result in increased hepatic Trp degradation. These results raise two major thoughts: first, that TDO2-associated Trp metabolism and its potential influence on liver inflammation is independent of IDO1; and second, that in the context of NAFLD/NASH, hepatic Trp levels and metabolism is more complex than we anticipated. The uptake of Trp is thought to be driven essentially by the L-type neutral amino acid transporter 1 (LAT1 or Slc7a5). In this context, it has been shown that LPS and TNF significantly reduce LAT1 and Trp uptake in neuron-like cells [54], while IL-1β upregulates LAT1 levels in fibroblast-like synoviocytes [55]. These findings suggest that LAT1 is an interesting candidate for future research involving Trp metabolism in the context of liver disease. Notably, the uptake of Trp can be regulated due to competition with other amino acids, and alterations in the levels and metabolism of amino acids, besides Trp, have been associated with NAFLD, e.g., the other aromatic amino acids tyrosine and phenylalanine, arginine, and branched-chain amino acids [56,57]. However, less is known about these other amino acids and their role in the regulation of immunometabolic responses, warranting further investigation. In conclusion, despite the small size and short study design, we demonstrate that Apoe−/− mice fed HFCD for 7 weeks is a plausible model to study liver disease with atherosclerosis as a major comorbidity. Evaluation of the effects of Ido1 genetic ablation revealed that this model may be used to better understand the dichotomies between vascular and hepatic inflammatory processes. A complete understanding of the role of IDO1 in the modulation of cardiovascular and liver disease as a comorbidity warrants further investigations. These could include the compensatory effects of other kynurenine pathway enzymes, and the potential crosstalk between hepatic and immune cells mediated by different Trp metabolites. A better understanding of these molecular processes could have implications for the design of high-precision therapies that can benefit both atherosclerosis and NAFLD/NASH. 4. Methods 4.1. Animal Model The Apoe−/−Ido1−/− mouse strain was generated by crossing Apoe−/− mice with Ido1−/− mice at the Kennedy Institute of Rheumatology, Oxford, UK [10]. The strain was transferred to the Center for Molecular Medicine at the Karolinska Institute in Stockholm and bred with Apoe−/− (B6.129P2-Apoetm1Unc/J, strain code 622, JAX™, Charles River, The Netherlands) to generate Apoe−/− and Apoe−/−Ido1−/− littermate control mice that were used in the study; all mice were kept in specific pathogen-free (SPF) conditions with a 12-h light/dark cycle throughout the study. The model of concomitant development of atherosclerosis and NASH was achieved by adapting the protocol from Schierwagen et al. (2015) [36]. Briefly, 10-week-old male mice were fed normal chow or a high-fat, cholesterol-rich diet (HFCD) containing 42% kcal from fat, 43% kcal from carbohydrate, 15% kcal from protein, and 1.25% cholesterol (E15723-34, Sniff, Germany) ad libitum for 3.5 or 7 weeks. All animal experiments were performed in accordance with national guidelines and approved by the Stockholm Norra Regional Ethics Board (N28-15, approved on 26 March 2015), which conforms to the guidelines from Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. 4.2. Atherosclerosis Burden Analyses At the end of treatment, mice were euthanized with CO2. Blood was collected by cardiac puncture, and vascular perfusion was performed with sterile RNase-free PBS. After perfusion, the heart and aortic arch were dissected and preserved for lesion and immunohistochemistry analyses. We have previously shown that Ido1 genetic and pharmacological ablation increases plaque burden in the aortic root [9,10]. In this study, aortic root sections obtained from cryopreserved hearts were used to obtain representative micrographs of plaque burden, which confirmed our previous publications. Lesion size was visualized on haematoxylin- and oil red O-stained sections as previously described [58]. Macrophage content in plaques was visualized using primary antibodies against Mac-2 (Cedarlane Laboratories, Burlington, ON, Canada) that were applied to acetone-fixed cryosections. Detection was performed using an ABC alkaline phosphatase kit (Vector Laboratories, Burlingame, CA, USA) as previously described [59]. En face lipid accumulation in the mouse aortic arch was determined using Sudan IV staining. Images were captured using a Leica DC480 camera connected to a Leica MZ6 stereomicroscope (Leica, Wetzlar, Germany). The lesion area was calculated using ImageJ software (NIH, Bethesda, MD, USA). Samples that were damaged during processing or analysis were excluded from the study. For the assessment of plaques, samples were coded, and the evaluation was performed by trained personnel who were blinded to the treatment groups. 4.3. Histological Analysis of Liver Disease Burden The livers were dissected, and analogous samples were either snap-frozen or fixed in 4% phosphate-buffered formaldehyde for histopathology analyses. After fixation for 24–48 h, samples were dehydrated in a series of graded alcohols and embedded in paraffin wax. Serial sections of 5 μm were rehydrated and subjected to haematoxylin and eosin staining for morphological visualization of liver damage, and Picrosirius red (Fluka-Sigma Aldrich, Switzerland) to evaluate the extent of fibrosis. Hepatic macrophage content was evaluated using a primary antibody against Mac-2 (Cedarlane Laboratories, Burlington, Canada) that was detected using goat anti-rat IgG (DyLight® 594) as the secondary antibody (Abcam, Cambridge, UK), and nuclei were stained with DAPI (Sigma Aldrich, St. Louis, MO, USA). All histological assessments were performed by a trained examiner who was blinded to the groups. 4.4. Biochemical Parameters in Liver and Blood Analogous segments of snap-frozen livers were lysed in RIPA buffer using a TissueLyser II (Qiagen, Germantown, MD, USA). Hepatic hydroxyproline content was evaluated using a colorimetric assay kit (Sigma-Aldrich, St. Louis, MO, USA) according to the manufacturer’s instructions. Liver lipids were extracted from liver samples using the Folch method [60]. Briefly, lysates were homogenized in methanol, and lipids were extracted by chloroform separation (methanol: chloroform (1:2)). After drying, the extracts were redissolved in 1% Triton-100, and cholesterol and triglyceride contents were measured using enzymatic colorimetric kits (Randox Lab. Ltd. Crumlin, UK) according to the manufacturer’s instructions. Biochemical parameters (alanine aminotransferase (ALT) and aspartate aminotransferase (AST)) in blood were evaluated on a Samsung PT10V clinical chemistry analyser. Plasma cholesterol and triglycerides were measured using enzymatic colorimetric kits (Randox Lab. Ltd., Crumlin, UK) according to the manufacturer’s instructions. Hepatic free iron content was determined using a colorimetric assay kit (Sigma-Aldrich, St. Louis, MO, USA) following the manufacturer’s instructions. 4.5. Evaluation of Inflammatory Markers In addition to immunohistological analyses, inflammation was evaluated in liver samples by qPCR. RNA was isolated from mouse livers using a RNeasy kit (Qiagen, Hilden, Germany). After approving the quality of the RNA on a NanoDrop (Thermo Scientific, Waltham, MA, USA), it was reverse transcribed with a High-Capacity RNA-to-cDNA™ Kit (Thermo Scientific, Waltham, MA, USA ) and amplified by real-time PCR using assay-on-demand primers and probes (Il12, Cd80, Cxcl10, Chil3, Arg1, Cd206, Tdo2, TDO2; all from Thermo Scientific, Waltham, MA, USA) in an ABI 7700 Sequence Detector (Applied Biosystems, Foster City, CA, USA). Hypoxanthine guanidine ribonucleosyl transferase (HPRT) was used as a housekeeping gene. Assay-on-demand primers and probes are provided in Supplementary Table S1. Data were analysed based on the relative expression method with the formula 2−ΔΔCT, where ΔΔCT = ΔCT (sample)–ΔCT (calibrator = average CT values of all samples within the control group) and ΔCT is the average CT of the housekeeping genes subtracted from the CT of the target gene. The levels of cytokines, including TNF- α, IL-1β, CCL2, and IL-10, were measured by ELISA according to the manufacturer’s instructions (all from R&D Systems, Minneapolis, MN, USA). 4.6. HepG2 Culture and Treatments The human hepatoma cell line HepG2 was purchased from ATCC (VA, USA) and cultured as previously described [30]. Briefly, cells were maintained in low glucose (1 g/L) Dulbecco’s modified Eagle’s medium (DMEM, Sigma-Aldrich, St. Louis, MO, USA) supplemented with 10% foetal bovine serum (FBS), 2 mM L-glutamine, 100 units/mL penicillin, and 100 µg/mL streptomycin (all from Gibco, UK). At least 14 days prior to the experiment, the cells were passaged, and the medium was replaced with low glucose (1 g/L) DMEM supplemented with 2% AB+ human serum (Blodcentralen Karolinska Universitetssjukhuset, Sweden), 2 mM L-glutamine, 100 units/mL penicillin, and 100 µg/mL streptomycin. For mRNA analysis, cells were treated for 24 h with 500 μM palmitic acid (Sigma-Aldrich, St. Louis, MO, USA), 100 μM FeSO4 (Sigma Aldrich, St. Louis, MO, USA), 0.62 μM TDO inhibitor LM10 (Sigma-Aldrich, St. Louis, MO, USA) in different combinations, or vehicle as detailed in the figure legends. In parallel experiments, cells were washed after 24 h of treatment with palmitic acid or FeSO4, and the TDO inhibitor LM10 (all from Sigma-Aldrich, St. Louis, MO, USA), and new media was added. Supernatants of these cultures were saved after 48 h and used as conditional media in THP-1 cultures. 4.7. IL-1β Secretion by THP-1 Macrophages Treated with HepG2-Conditioned Media The human monocytic cell line THP-1 was maintained in culture using RPMI 1640 (Invitrogen, MA, USA) culture medium containing 10% heat-inactivated FBS (Gibco, UK) supplemented with 2 mM L-glutamine, 100 units/mL penicillin, and 100 µg/mL streptomycin (all from Gibco, UK). THP-1 monocytes were then differentiated into macrophages by 24 h incubation with 100 ng/mL phorbol 12-myristate 13-acetate (PMA; Sigma-Aldrich, St. Louis, MO, USA), followed by 24 h incubation with conditioned media from HepG2 cells subjected to different treatments and upon stimulation with 10 ng/mL LPS (Sigma-Aldrich, St. Louis, MO, USA) for 4 h. After 4 h of incubation with LPS, cells were treated with 5 μM ATP for inflammasome activation and the release of IL-1β was measured by ELISA as previously described. 4.8. Kyn/Trp Ratio The L-Kyn/Trp ratio, determined by ELISA (ImmuSmol, Bordeaux France), was used as a surrogate marker of IDO1-TDO2 activity in the aorta, liver, and plasma from 7-week HFCD-fed Apoe−/− and Apoe−/−Ido1−/− mice. 4.9. Statistical Analysis The results are presented as the mean ± SEM if not otherwise stated. The Mann–Whitney U-test was used for comparisons between two groups, and Kruskal–Wallis ANOVA with Dunn’s post-test was used for comparisons between more than two groups. Correlations were calculated using simple linear regression analysis. p values < 0.05 were considered significant. Acknowledgments We thank Anneli Olsson and Linda Haglund for their technical assistance. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23095203/s1. Click here for additional data file. Author Contributions Conceptualization, A.A., G.L.T., I.K. and D.F.J.K.; methodology, A.A., G.L.T., I.K. and D.F.J.K.; formal analysis, A.A. and G.L.T.; investigation, A.A. and G.L.T., with support from M.B., M.J.F., A.G., S.G. and F.B.C.; resources, J.C., C.M. and D.F.J.K.; data curation, A.A. and G.L.T.; writing—original draft preparation, A.A., G.L.T. and D.F.J.K.; writing—review and editing, A.A., G.L.T., J.O.M., C.M. and D.F.J.K.; supervision, J.O.M., D.S.P.A., C.M. and D.F.J.K.; project administration, D.F.J.K.; funding acquisition, G.L.T., D.S.P.A., F.B.C., J.O.M. and D.F.J.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The animal study protocol was approved by the Stockholm Norra Regional Ethics Board (N28-15, approved on 26 March 2015). Informed Consent Statement Not applicable. Data Availability Statement Available on request from the corresponding author. Conflicts of Interest I.K. reports personal fees from Orion Pharma unrelated to the submitted work. The remaining authors declare no conflict of interest. Figure 1 Characterization of the NASH and atherosclerosis dual model. Apoe−/− mice were fed chow or a high-fat-cholesterol diet (HFCD) for 7 weeks, and representative pictures of atherosclerotic disease and NASH are shown; complete descriptive data of chow- and HFCD-fed mice are shown in Table 1. Top panels show en face lipid staining with Sudan-IV; middle panels show H&E staining showing hepatocyte ballooning; and the bottom panels show collagen deposition detected by picrosirius red staining in (A) chow- and (B) HFCD-fed Apoe−/− mice. Bar = 50 µm. Figure 2 Effects of IDO1 genetic ablation on NASH and atherosclerosis development. Apoe−/− or Apoe−/−Ido1−/− mice were fed a high-fat cholesterol diet (HFCD) for 7 weeks; pooled data from two independent experiments are shown. (A) Quantification of en face Sudan IV-stained aortic arches (n = 14–15). (B) Representative pictures of the aortic arches. (C) Representative pictures of the atherosclerotic burden stained by ORO in aortic root sections of Apoe−/− or Apoe−/− Ido1−/− mice (n = 2/group). (D) Representative picture of Mac-2+ macrophage infiltration in the aortic roots of Apoe−/− or Apoe−/− Ido1−/− mice (n = 2/group). Panel (E) shows total cholesterol and (F) triglyceride levels in plasma (n = 15–16). (G,H) Total levels of cholesterol and triglycerides in Apoe−/− and Apoe−/−Ido1−/− mice livers (n = 15–16). (I) Representative pictures of H&E-stained liver sections. (J) Liver/body ratio (n = 15–16), (K,L) plasma ALT and AST levels (n = 15–16). (M) Relative hepatic collagen (Col1a1) mRNA expression (n = 15–16) and (N) hepatic hydroxyproline levels (n = 15–16). (O) Representative pictures of picrosirius red-stained liver sections. ** p < 0.01; differences were detected using the Mann–Whitney U test; dotted lines refer to baseline levels of Apoe−/− mice fed a chow diet for 7 weeks (Table 1); orange and blue colours are used to identify female and male mice, respectively. Bar = 50 µm. Figure 3 Effects of IDO1 genetic ablation on liver inflammation. Apoe−/− or Apoe−/−Ido1−/− mice were fed a high-fat cholesterol diet (HFCD) for 7 weeks; pooled data from two independent experiments are shown. (A) Relative Cd68 mRNA expression (n = 15–16); (B) Relative Clec4f mRNA expression (n = 15); (C) Quantification of immunofluorescently stained Mac-2+ macrophages (n = 15); and (D) representative Mac-2+ fluorescence staining of liver from Apoe−/− or Apoe−/−Ido1−/−; Bar = 50 µm. (E) Relative hepatic mRNA expression of M1-like macrophage markers (Cd80, Il12, and Cxcl10 mRNA, and CCL2 and TNF protein) (n = 15–16) and (F) M2-like macrophage markers (Chil3, Arg1, and Cd206 mRNA, and IL-10 protein) (n = 15–16). Orange and blue colours are used to identify female and male mice, respectively; no differences between groups were detected using a Mann–Whitney U test. Figure 4 Systemic and local tryptophan degradation rates. Apoe−/− or Apoe−/− Ido1−/− mice were fed a high-fat cholesterol diet (HFCD) for 7 weeks; pooled data from two independent experiments are shown. The L-kynrenine to Trp ratio (Kyn/Trp) in (A) plasma (n = 15–16), (B) artery homogenate (n = 14), and (C) liver homogenate (n = 15–16), was estimated using specific ELISA kits, as described in the methods. (D) shows the correlation between % lesion and Kyn/Trp ratio in the aorta. (E) shows the correlation between relative Cd68 mRNA and the Kyn/Trp ratio in the liver. *** p < 0.001; Differences were detected using the Mann–Whitney U test. Correlations were determined using simple linear regression. Figure 5 Fatty acids and iron regulate TDO2-dependent Trp degradation and consequences for THP-1 macrophage activation. (A,B) TNF, CCL2, and IL-1β protein levels and relative Tdo2 mRNA expression in livers from Apoe−/− and Apoe−/−Ido1−/− mice fed a high-fat cholesterol diet (HFCD) for 3.5 and 7 weeks. (A,B) Pooled data from two independent experiments are shown; n = 14–15/group. © Relative expression of TDO2 mRNA in HepG2 cells treated with palmitic acid (PA, 500 μM) or iron (FeSO4, 100 μM) (n = 5). (D) Kyn/ Trp ratio in the supernatants of HepG2 cells treated with PA (500 μM), FeSO4, (100 μM), or FeSO4 + TDO2-inhibitor LM10 (0.62 μM) (n = 7). (E) IL-1β release from THP-1 macrophages pre-treated with conditioned media from HepG2 cells incubated with PA (500 μM), FeSO4 (100 μM), or FeSO4 + TDO2-inhibitor LM10 (0.62 μM); in addition, cells were stimulated with LPS (10 ng/mL, 4 h) and ATP (5 mM, 30 min) for activation of the inflammasome and IL-1β release (n = 8). & p < 0.06; # p < 0.08; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. (A) Differences were detected using the Mann–Whitney U test. (B,C) Differences were detected using a one-way ANOVA and Dunn’s post hoc test. ijms-23-05203-t001_Table 1 Table 1 Characterization of HFCD-induced vascular and liver disease as comorbidities. Apoe−/− Chow (c) HFCD (d) 3.5 Weeks (n = 10–12) 7.0 Weeks (n = 10–12) 3.5 Weeks (n = 11–14) 7.0 Weeks (n = 14–16) Aorta % Lesion (aortic arch) 0.99 ± 0.29 2.88 ± 0.85 #3.5c 0.48 ± 0.22 5.56 ± 0.89 ****3.5d Plasma Cholesterol (mg/dL) 381.9 ± 55.6 370.6 ± 38.2 739.8 ± 64.2 ***3.5c 732.6 ± 73.8 ***7.0c Triglycerides (mg/dL) 160.4 ± 22.2 144.6 ± 13.5 254.2 ± 43.9 226.9 ± 27.4 ***7.0c ALT (μkatl/L) 0.46 ± 0.04 0.62 ± 0.09 1.79 ± 0.44 ***3.5c 1.45 ± 0.29 ***7.0c AST (μkatl/L) 1.72 ± 0.17 1.92 ± 0.17 3.25 ± 0.62 *3.5c 3.79 ± 0.61 ***7.0c Liver Liver/Body weight (mg/g) 0.052 ± 0.002 0.050 ± 0.002 0.065 ± 0.002 ***3.5c 0.062 ± 0.001 *** Iron (ng/μL) 4.01 ± 0.60 3.54 ± 0.16 4.60 ± 0.22 5.13 ± 0.37 *7.0 TNF (pg/mg tissue) 31.62 ± 2.77 38.72 ± 3.08 19.76 ± 2.82 **3.5c 93.19 ± 10.18 ***7.0c; ***3.5d CCL2 (pg/mg tissue) 69.7 ± 10.7 200.3 ± 36.2 78.21 ± 12.4 880.6 ± 81.4 ****7.0c; ****3.5d IL-10 (pg/mg tissue) 476.2 ± 44.4 28.07 ± 3.26 ****3.5c 1594 ± 145.4 164.1 ± 8.478 ****3.5d Cholesterol (mg/mg tissue) — 3.42 ± 0.39 — 7.556 ± 0.49 ****7.0c Triglycerides (mg/mg tissue) — 18.45 ± 2.53 — 40.74 ± 4.41 ****7.0c Hydroxyproline (μg/mg tissue) — 4.05 ± 0.59 — 6.97 ± 1.47 Col1a1 (relative expression) — 1.09± 0.134 — 4.03 ± 1.08 *7.0c #) p < 0.07; *) p < 0.05; **) p < 0.01; ***) p < 0.001; ***) p < 0.0001; 3.5c or d and 7.0c or d indicates the made comparison; (c) chow; (d) HFCD. 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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092151 cancers-14-02151 Article Role of Amino Acid Transporter SNAT1/SLC38A1 in Human Melanoma Böhme-Schäfer Ines Lörentz Sandra https://orcid.org/0000-0001-8147-394X Bosserhoff Anja Katrin * Pardo Luis A. Academic Editor Department of Biochemistry and Molecular Medicine, Institute of Biochemistry, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054 Erlangen, Germany; ines.boehme@fau.de (I.B.-S.); sandra.loerentz@fau.de (S.L.) * Correspondence: anja.bosserhoff@fau.de 26 4 2022 5 2022 14 9 215122 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/). Simple Summary Malignant melanoma originates from melanocytes. Due to its high metastatic potential and its increasing incidence, it is one of the most aggressive types of cancer. Cancer cells generally exhibit an elevated metabolism, consequently adapting their expression of transport proteins to meet the increased demand of nutrients, such as amino acids. The aim of this study was to analyze the expression and function of the amino acid transporter SNAT1 in human melanoma. In addition, we wanted to determine its role in development and progression of malignant melanoma. We revealed that SNAT1 is overexpressed in melanoma tissue samples, as well as primary and metastatic cell lines. Moreover, we were able to show that SNAT1 plays an important role in forcing proliferation, colony formation, migration and invasion, and inhibiting senescence of melanoma cells. Amino acid transporters like SNAT1 are therefore promising targets for the development of novel therapeutic strategies against melanoma. Abstract The tumor metabolism is an important driver of cancer cell survival and growth, as rapidly dividing tumor cells exhibit a high demand for energetic sources and must adapt to microenvironmental changes. Therefore, metabolic reprogramming of cancer cells and the associated deregulation of nutrient transporters are a hallmark of cancer cells. Amino acids are essential for cancer cells to synthesize the necessary amount of protein, DNA, and RNA. Although cancer cells can synthesize glutamine de novo, most cancer cells show an increased uptake of glutamine from the tumor microenvironment. Especially SNAT1/SLC38A1, a member of the sodium neutral amino acid transporter (SNAT) family, plays an essential role during major net import of glutamine. In this study, we revealed a significant upregulation of SNAT1 expression in human melanoma tissue in comparison to healthy epidermis and an increased SNAT1 expression level in human melanoma cell lines when compared to normal human melanocytes (NHEMs). We demonstrated that functional inhibition of SNAT1 with α-(methylamino) isobutyric acid (MeAIB), as well as siRNA-mediated downregulation reduces cancer cell growth, cellular migration, invasion, and leads to induction of senescence in melanoma cells. Consequently, these results demonstrate that the amino acid transporter SNAT1 is essential for cancer growth, and indicates a potential target for cancer chemotherapy. tumor metabolism melanoma amino acid transporter ==== Body pmc1. Introduction In the last 50 years, the incidence of melanoma has increased significantly. Melanoma cells are very invasive and have a high metastatic potential already at early stages. Patients with metastatic melanoma (stage IV) exhibit a five-year survival rate of only 22.5% [1]. Despite major advances in targeted and immunotherapy in recent years, the emergence of therapy resistance demonstrates that there is still a great need for research to better understand the development and progression of melanoma. Tumor cells can reprogram their cellular metabolism and upregulate transport proteins to acquire necessary nutrients and maintain tumor survival and growth. Whereas differentiated, non-dividing cells metabolize nutrients via the tricarboxylic acid cycle and the respiratory chain, resulting in the production of CO2 and H2O, rapidly proliferating cancer cells are able to change the metabolic pathways they depend on. For instance, melanoma cells upregulate the gene expression of glucose transporter isoform 1 and 3 (GLUT1/SLC2A1 and GLUT3/SLC2A3) to take up a high amount of glucose [2]. Under aerobic conditions, glucose is metabolized to pyruvate, which is mainly utilized for lactic acid production. This metabolic pathway of aerobic glycolysis is called Warburg effect [3]. The increased production and secretion of lactate and H+ into the extracellular environment causes an acidification of the tumor microenvironment, which triggers the development of a therapy-resistant and senescence-like phenotype in melanoma [3,4]. Besides the Warburg effect, glutaminolysis [5] is considered as another important hallmark of tumor cell metabolism. Although cancer cells have the capacity to synthesize glutamine (Gln) de novo, they exhibit an increased uptake of glutamine from the tumor microenvironment. Whereas the Na+-dependent neutral amino acid transporter ASCT2/SLC1A5 [6,7] and large amino acid transporters LAT1/SLC7A5 [8,9] and LAT2/SLC7A8 are described to accomplish exchange of amino acids to achieve amino acid homeostasis in cells, Na+-coupled neutral amino acid transporter SNAT1/SLC38A1 mediates net glutamine uptake for glutaminolysis [10]. SNAT1 is a member of the SNAT/SLC38 family. This SNAT family can be divided in group “A” and group “N” transporters. The “A”-transporters SNAT1/SLC38A1, SNAT2/SLC38A2, and SNAT4/SLC38A4 mediate the transport of a variety of small neutral amino acids, whereas the “N”-transporters SNAT3/SLC38A3, SNAT5/SLC38A5, and SNAT8/SLC38A8 mediate a more specific transport of glutamine, asparagine, and histidine, respectively [11]. Although SNAT1 is able to transport small neutral amino acids, it is described as the main glutamine loader [10]. Physiologically, SNAT1 is mainly expressed in testis, placenta, brain, endocrine tissues, respiratory system, and gastrointestinal tract (www.proteinatlas.org, accessed on 22 November 2021). The amino acids that are transported by SNAT1 serve as a carbon and nitrogen source for anabolism, but are also used for glutathione synthesis, which neutralizes reactive oxygen species (ROS). SNAT1 is also implicated in cellular signaling. It is a positive regulator of mTORC1 in healthy mouse neurons [12]. Additionally, SNAT1 overexpression increases the phosphorylation level of Akt (p-Akt) and mTOR (p-mTOR) in osteosarcoma [13], breast cancer [14], and hepatocellular carcinoma (HCC) [15]. Studies demonstrated that SNAT1 is overexpressed in colorectal cancer [16], breast cancer [14], HCC [17], gastric cancer [18], osteosarcoma [13], acute myeloid leukemia (AML) [19], and endometrial cancer [20]. SNAT1 overexpression is associated with increased tumor size, tumor invasion depth, migration, metastasis and proliferation, and poorer prognosis for patients [13,14,16,18,19,20]. Therefore, amino acid transporters such as SNAT1 that are overexpressed in cancer cells represent potential drug targets. Functional inhibition leads to nutrient deprivation in cancer cells, resulting in growth arrest and cell death, whereas normal cells may remain unaffected [21]. In this study, we observed that the Gln transporter SLC38A1/SNAT1 is highly expressed in human melanoma tissue, as well as many melanoma cell lines and investigated the functional role of SNAT1 in cell proliferation, migration, invasion, and senescence induction in melanoma. 2. Materials and Methods 2.1. Culturing of Melanoma Cell Lines The human melanoma cell line Mel Juso (derived from primary cutaneous melanoma) was cultured in RPMI-1640 medium (Roswell Park Memorial Institute, Buffalo, NY, USA) with NaHCO3 and the cell lines Mel Im (isolated from melanoma metastases) and HEK293 were cultured in DMEM D6046 (Dulbecco’s Modified Eagle’s Medium, Sigma Life Science, St. Louis, MO, USA) low glucose. Both media were supplemented with penicillin (400 U/mL), streptomycin (50 g/mL), and 10% fetal calf serum (Sigma-Aldrich, München, Germany) at 37 °C in a humidified atmosphere containing 8% CO2 for Mel Im and Mel Juso and 5% CO2 for HEK293 (see Table 1 for an overview of all used cell lines). For functional inhibition of SNAT1, the amino acid analog MeAIB (Sigma-Aldrich, München, Germany) was used in 10 mM and 20 mM on melanoma cells. Control cells (CTR) were treated with equal amount of solvent ddH2O. 2.2. mRNA Expression Analysis Total cellular RNA was isolated from melanoma cell lines using the Total RNA Kit I (Omega Bio-Tek, Norcross, GA, USA). Molecular generation of cDNA by reverse transcription was performed by using the SuperScript II Reverse Transcriptase Kit (Invitrogen). Relative mRNA expression was performed via quantitative real-time PCR (qRT-PCR) analysis on a LightCycler480 II device (Roche, Mannheim, Germany) with specific primers (see Table 2 for primer sequences) and normalized to β-actin as previously described [4]. 2.3. Protein Analysis with Western Blotting For protein isolation, cells were lysed in RIPA buffer (50 mM Tris/HCl pH 7.4, 150 mM NaCl, 1% N-P40, 0.1% SDS, 0.5% sodium deoxycholate, and protease inhibitor). An amount of 20 μg protein per lane were loaded and separated on 12.75% sodium dodecyl sulfate polyacrylamide gel electrophoresis gels. Proteins were transferred onto a polyvinylidene difluoride membrane and blocked in 3% bovine serum albumin (BSA) and 5% milk powder for 45 min. The membranes were incubated with primary antibodies: SNAT1/SLC38A1 (1:1000, HPA052272, Sigma-Aldrich, München, Germany) overnight at 4 °C and β-actin (1:5000, A5441, Sigma-Aldrich, München, Germany) in 5% BSA 1 h at room temperature followed by incubation with the secondary antibody (anti-rabbit–horseradish 1:2000 and anti-mouse–horseradish, 1:5000) for 1 h at room temperature. For protein staining, the ClarityTM Western ECL Substrate kit (Bio-Rad Laboratories Inc., Hercules, CA, USA) was used, and protein signal intensity was detected by gel documentation system (Intas ECL Chemocam, Intas Science Imaging Instruments GmbH, Göttingen, Germany). 2.4. siRNA Transfection For SNAT1 downregulation, 90,000 cells of melanoma cell lines Mel Im and Mel Juso were seeded into 6-well plates and were transiently transfected using Lipofectamine RNAiMAX reagent (Life Technologies, Darmstadt, Germany) with an siPool (containing approx. 30 specific siRNAs) against SNAT1 (functionally verified by siTOOLs Biotech, Planegg/Martinsried, Germany) or a negative control siPool. After 72 h incubation, the cells were transfected for additional 24 h and subsequently seeded for experimental analysis (total siPool incubation was 96 h). For siPools from this manufacturer, a previous study demonstrated low rate of off-target effects, as the global gene expression is not affected, and high reliability of siPools in comparison to siRNAs [22]. 2.5. Immunohistochemical Analysis Standard 5 µm sections of formalin-fixed and paraffin-embedded tissue blocks were used for immunohistochemical analysis of human tissue samples (tissue microarray), comprising specimens from benign nevi, primary melanoma, and melanoma metastases. Immunohistochemical staining was performed using an anti-SNAT1 antibody (SNAT1/SLC38A1, 1:100, HPA052272, Sigma-Aldrich, München, Germany). Sampling and handling of patient material were carried out in accordance with the ethical principles of the Declaration of Helsinki. The use of human tissue material had been approved by the local ethics committee of the University of Regensburg. 2.6. Immunofluorescence Staining For immunofluorescence analysis, cells were fixed, permeabilized, and stained as described previously [4]. Images were acquired using the inverted microscope IX83 (Olympus Life Science, Tokyo, Japan). Microscope images were analyzed using Olympus CellSens Dimension Software 1.12 (Olympus Cooperation, Tokyo, Japan). 2.7. XTT Viability Assay Cell proliferation and mitochondrial activity was analyzed using the Cell Proliferation Kit II (XTT) (Roche Diagnostics GmbH, Mannheim, Germany). MeAIB-Inhibitor treatment started 6 h after cell seeding. XTT analysis of siSNAT1-downregulated cells compared to control-transfected (siCTR) cells started 120 h after siPool transfection. XTT reagent was added 24, 48, 72, 96, 120, and 144 h after cell seeding to adherent cells according to the manufacturer’s instructions, and absorbance was measured with a CLARIOstar plate reader (BMG Labtech GmbH, Ortenberg, Germany) at 490 nm. 2.8. Analysis of Cell Proliferation Real-time cell proliferation was measured using the xCELLigence System (Roche Diagnostics GmbH, Mannheim, Germany) and E-plates (ACEA Bioscience, San Diego, CA, USA), as described in [23]. 2.9. Clonogenic Assay To analyze attachment-dependent colony formation and growth of cancer cells, clonogenic assays were performed as described before [24]. 2.10. Scratch Wound Healing Assay The migratory behavior of cells was analyzed with the scratch wound healing assay. 300,000 melanoma cells were seeded into 6-well plates. After 24 h, the cell monolayer was scratched with a pipette tip in a definite area. Migration rate into the scratch was measured 24 and 48 h after siSNAT1-downregulation, compared to siCTR cells, using microscope IX83 (Olympus Life Science). Diameters of the scratches were analyzed using CellSens Dimension Software 1.12 (Olympus Cooperation, Tokyo, Japan). 2.11. Migration and Invasion Analysis with Boyden Chamber Assay Migration and invasion of cells were analyzed using Boyden chambers containing polycarbonate filters with an 8 µm pore size (Neuro Probe Inc, Gaithersburg, MD, USA). For migration assay, a gelatin-coated filter was used and for invasion assay, Matrigel-coated filters (diluted 1:3 in DMEM without FCS; Omnilab, Bremen, Germany) were used. Fibroblast-conditioned medium was used as a chemoattractant and was filled into the lower compartment of the chamber. After typsination, 40,000 cells for migration and 200,000 cells for invasion were resuspended in DMEM without FCS and subsequently placed in the upper compartment of the chamber. After incubation for 4 h at 37 °C, the cells adhering to the lower surface of the filter were fixed, stained, and counted as described previously [25]. 2.12. Apoptosis Analysis For apoptosis analysis, 200,000 cells were seeded into 6-well plates. Apoptotic cells were investigated by flow cytometry using the Annexin V-FITC PromoKine Detection Kit (PromoCell GmbH, Heidelberg, Germany) according to the manufacturer’s instructions. The flow cytometry analysis was performed with a BD LSRFortessaTM X-20 cytometer (Becton Dickinson, Franklin Lakes, NJ, USA). Flow cytometry data were analyzed using FLOWJO v10 Software (BD Bioscience, Franklin Lakes, NJ, USA). 2.13. Cell Cycle Analysis For cell cycle analysis, 200,000 of siCTR and siSNAT1-transfected cells were fixed and stained with propidium iodide (PI) as described previously [4]. Cytometric measurement was performed with a BD LSRFortessaTM X-20 instrument (BD Biosciences) and flow cytometry data were analyzed using FlowJo Software. 2.14. Senesce-Associated β-Galactosidase Staining For senescence detection, melanoma cells were fixed and stained by using the Senescence β-Galactosidase Staining Kit (Cell Signaling Technology, Danvers, MA, USA) according to the manufacturer’s instructions. Imaging was conducted by using the microscope IX83 (Olympus Life Science). Analysis of the images was performed with the Cell Counter Plugin of Image J 1.48v software (NIH, Bethesda, MD, USA) and the percentage of senescent cells (blue) to the total cell number of cells per field of view was calculated. 2.15. Statistical Analysis All experiments were performed in at least 3 independent assays. The results are shown as the mean ± standard error of the mean (SEM) calculated with the GraphPad Prism software (GraphPad Software, Inc., San Diego, CA, USA). Comparisons between groups (NHEM vs. melanoma, inhibitor MeAIB vs. control, siSNAT1 vs. siCTR) were conducted using the Student’s unpaired t-test. A p-value of <0.05 was considered statistically significant (*: p < 0.05). 3. Results 3.1. SNAT1 Is Upregulated In Vitro and In Vivo in Melanoma RNA-sequencing analysis of primary melanoma cell lines and metastatic melanoma cell lines compared to NHEMs revealed that SNAT1 expression is significantly elevated in melanoma cells (Figure 1A). To confirm the differential gene expression, we performed qRT-PCR with melanoma cell lines obtained from primary (Sbcl2, WM3211, WM1366, Mel Juso) and metastatic melanoma (WM1158, Mel Im, SKMel28), compared to NHEMs, demonstrating an upregulation of SNAT1/SLC38A1 gene expression, except for cell line Sbcl2 (Figure 1B). Investigation of SNAT1 protein expression via Western blot analysis showed an increased amount of SNAT1 protein in all melanoma cell lines when compared to NHEMs (Figure 1C), including Sbcl2. On the basis of siPool-mediated SNAT1 downregulation, we observed that SNAT1 protein includes protein sizes from 50–70 kDa in Western blot analysis (Supplementary Figure S1A). In addition to these in vitro results, we analyzed SNAT1 expression in vivo by immunohistochemical staining of healthy epidermis, benign nevi, primary, and metastatic human melanoma tissue, and observed an elevated SNAT1 expression level in primary tumors and even higher expression in metastatic tissue (Figure 1D). To emphasize the importance of glutamine transporters in melanoma, we investigated the gene expression of glutamine transporters SLC38A1/SNAT1, SLC38A2/SNAT2, SLC1A5/ASCT2, and SLC7A5/LAT1, which showed expression in RNA sequencing analysis in several melanoma cell lines (Supplementary Figure S2A). 3.2. Competitive Inhibition of SNAT1 Reduces Proliferative Potential of Melanoma Cells In Vitro The aim of this study was to determine the functional importance of the amino acid transporter SNAT1 in human melanoma. Initially, we functionally inhibited SNAT1 with the competitive inhibitor MeAIB (Km~0.5 mM). MeAIB is an amino acid analogue, which is not metabolized and has been used extensively to study the transport function of system “A” transporters of the SNAT-family, including SNAT1/SLC38A1 [26]. We investigated the effect of functional inhibition of SNAT1 by 10 and 20 mM MeAIB, respectively, on melanoma cell growth using the XTT cell viability assay. Here, we revealed a significant reduction of proliferation in melanoma cell lines Mel Im and Mel Juso when compared to untreated control cells (Figure 2A,B). With further analysis of cell proliferation using the xCELLigence real-time cell analysis (RTCA) system, we were able to confirm these findings for melanoma cell line Mel Im (Figure 2C,D). Although having effects on both tested cell lines, the strength of effects of SNAT1 inhibition differed, suggesting a variability or heterogeneity between different tumors, which needs to be kept in mind. Using clonogenic assays, we examined the reproductive and proliferative ability of cells to form large colonies from single cells, and revealed a significant reduction of colony number in both cell lines and a significant reduction of colony size in Mel Im (Figure 2E,F). To evaluate alterations of glutamine transporter expression after MeAIB treatment, we determined the expression of SLC38A1/SNAT1, SLC38A2/SNAT2, SLC1A5/ASCT2, and SLC7A5/LAT1 after 10 mM MeAIB treatment for different time periods by qRT-PCR analysis. We detected a significant upregulation of these transporters, in particular in the cell line Mel Juso, in response to treatment with the inhibitor MeAIB (Supplementary Figure S2B,C). These results suggest a potential compensatory upregulation after inhibition by MeAIB, which may explain small differences in the proliferative effects of MeAIB treatment when comparing Mel Juso to Mel Im. To evaluate the effect of MeAIB on non-malignant HEK293 cells, we conducted an XTT viability assay (Supplementary Figure S3A,B). The data revealed that MeAIB has no significant effect on HEK293 cells. 3.3. SNAT1 Knockdown Reduces Proliferation Rate of Melanoma Cells In Vitro As MeAIB does not just selectively inhibit SNAT1/SLC38A1, but also SNAT2/SLC38A2 and SNAT4/SLC38A4, we further analyzed specific SNAT1 effects using an siPool for selective downregulation of SNAT1 mRNA in melanoma cells. Initially, the siRNA-mediated downregulation of SNAT1 was confirmed by mRNA (Figure 3A) and protein levels (Supplementary Figure S1). As significant downregulation of SNAT1 mRNA and protein was achieved after 96 h, we used a 96 h duration for our siRNA transfection period in our experimental design. As we observed a partly compensatory upregulation of some glutamine transporters after inhibition of the group A-amino acid transporters SNAT1/2/4 after MeAIB-inhibitor treatment, we additionally investigated the SLC38A1/SNAT1, SLC38A2/SNAT2, SLC1A5/ASCT2, and SLC7A5/LAT1 expression after siSNAT1 silencing and detected no significant effect (Supplementary Figure S2D). To determine the effect of SNAT1 downregulation on the proliferative potential of melanoma cells, we examined proliferation rate using XTT assay and observed a significant reduction in cell line Mel Juso and a strong tendency for cell line Mel Im (Figure 3B,C). With the RTCA system we analyzed cell proliferation and revealed a significant increase of cell index (CI) doubling time in melanoma cell line Mel Juso after siSNAT1 downregulation when compared to control cells (Figure 3D,E). Surprisingly, siSNAT1-transfected cell line Mel Im showed a significant decrease of CI doubling time (Figure 3E). Notably, the RTCA system measures impedance, which is not exclusively dependent on cell number, but also on cell morphology and changes in cell–surface adhesion. Therefore, we analyzed attachment after siSNAT1 downregulation and revealed a significantly elevated impedance after siSNAT1 silencing in cell line Mel Im (Supplementary Figure S3A), which might suggest changes in adhesion. Moreover, we investigated whether siSNAT1 downregulation has an impact on the cell size of Mel Im and determined an increase in cell size after siSNAT1 silencing (Supplementary Figure S3B), which further contributes to the elevated impedance (Figure 3E). Additionally, colony forming potential was determined using a clonogenic assay, demonstrating a significant decrease of colony number and colony size in Mel Im and Mel Juso cells after siSNAT1 downregulation when compared to control-transfected cells (Figure 3F,G). In summary, SNAT1 downregulation showed a significant inhibitory effect on the proliferative capacity and colony forming potential of melanoma cells. In contrast, transfection of the non-malignant cell line HEK293 with siSNAT1 had no effect on proliferation (Supplementary Figure S3C). 3.4. SNAT1 Downregulation Leads to Reduction of Cellular Migration and Invasion In further assays, we determined whether the migratory behavior of melanoma cells is influenced by SNAT1 downregulation. We examined cell migration using a wound healing assay and revealed a significantly reduced migratory capacity after siSNAT1 knockdown of both investigated cell lines Mel Im and Mel Juso (Figure 4A,B). To further evaluate cellular migration, a standardized Boyden chamber assay with gelatin-coated filters was conducted after siSNAT1 downregulation. Here, we observed a significant decrease of migrated cells of the cell lines Mel Im and Mel Juso after siSNAT1 downregulation (Figure 4C,D). Additionally, cellular invasion was assessed by Boyden chamber assay with Matrigel-coated filter membranes. We found a significant reduction of the invasive potential of Mel Im and Mel Juso after siSNAT1 downregulation when compared to control-transfected cells (Figure 4E,F), indicating that SNAT1 plays an important role in cell proliferation, migration, and invasion. 3.5. Reduction of SNAT1 Expression Induces Cell Cycle Arrest and Senescence in Melanoma Cells To understand whether the reduced proliferation detected by RTCA and XTT analysis is caused by induction of cell death, we determined the percentage of apoptotic Mel Im and Mel Juso cells after siSNAT1-downregulation, compared to siCTR-treated melanoma cells using PI/annexin V staining and subsequent flow cytometric analysis (Figure 5A,B). We observed no increase of apoptotic cells due to SNAT1 downregulation, suggesting that reduced SNAT1 expression mainly affects the proliferative behavior of melanoma cells. To shed light on the reduced cell growth after reduction of SNAT1 expression, we investigated the cell cycle by flow cytometry using PI to stain DNA content, and revealed a significant increase of G1/G0 phase in siSNAT1-treated cells when compared to siCTR-transfected control cells (Figure 5C,D). As we observed G1/G0 cell cycle arrest of the melanoma cells after siSNAT1 downregulation, we elucidated the cellular phenotype in more detail. For this purpose, we examined the induction of cellular senescence using senescence-associated (SA)-β-galactosidase staining. Downregulation of SNAT1 led to a significant increase of senescent melanoma cells (Figure 5E,F). The formation of promyelocytic leukemia protein nuclear bodies (PML-NB) is functionally implicated in cellular senescence in melanoma [27] and is commonly used as senescence marker [4,28]. We assessed PML-NB formation via immunofluorescence analysis and observed a significant increase of PML immunofluorescence intensity after siSNAT1 downregulation when compared to control cells (Figure 5G,H). These data indicate that a reduction of SNAT1 expression in melanoma results in reduced cell proliferation by induction of cellular senescence. 4. Discussion In this study, we revealed an elevated SNAT1 expression in human primary melanoma and an even higher expression in metastatic melanoma tissue when compared to normal epidermis. Moreover, we demonstrated that SNAT1 is upregulated on the mRNA and protein level in various human melanoma cell lines obtained from primary and metastatic tumors when compared to NHEM. In our RNA sequencing analysis of the SNAT family, we found an elevated expression in comparison to NHEM only of SNAT1 and SNAT2, which emphasizes their functional importance in melanoma. Studies focusing on other cancer entities also reveal an overexpression of SNAT1 in human tumors, such as breast cancer [14], colorectal cancer [16], HCC [17], gastric cancer [18], and osteosarcoma [13], indicating an oncogenetic role of SNAT1 in cancer. To elucidate the role of SNAT1 in human melanoma, we performed a comprehensive experimental investigation. All pharmacological inhibitors that are proposed to work for different glutamine transporters are not transporter-subtype specific [10]. Therefore, besides using the unspecific inhibitor MeAIB, we also established an siPool to downregulate SNAT1 expression, which allowed us to assess specific SNAT1 effects in melanoma cells. We demonstrated that functional inhibition using the competitive inhibitor MeAIB and siRNA targeting SNAT1 attenuated cell proliferation as determined by XTT, RTCA, and clonogenic assay. These findings are in accordance with previous studies which revealed that SNAT1 promotes proliferation and tumor growth in colorectal cancer [16], breast cancer [14], osteosarcoma [13], and gastric cancer [18]. Interestingly, in the RTCA assay, we observed a decrease of CI doubling time and enhanced attachment after SNAT1 silencing of the cell line Mel Im. A decrease of doubling time and increase of cell attachment can be caused by changes of cell morphology, in particular, enlargement of cell bodies, which represents a sign for cellular senescence [29]. In previous studies, we demonstrated that especially the melanoma cell line Mel Im exhibits an enlargement of cell bodies and extension of cellular processes during senescence [4]. Here, we confirmed an induction of senescence after SNAT1 downregulation by G1/G0 cell cycle arrest, SA-β-galactosidase staining, and PML-NB formation in both cell lines. However, until today no direct link between SNAT1 and senescence has been demonstrated. One study showed that treatment of AML cells with the tyrosine kinase inhibitor gilteritinib reduces the expression of several proteins, including SNAT1, which is associated with an increased SA-β-galactosidase activity [30]. It is not clear which cellular mechanism induced by gilteritinib leads to the induction of senescence, nonetheless, this study supports our finding that the amino acid transporter SNAT1 is connected to the repression of senescence in tumor cells. Reduced transport of glutamine and leucine by inhibition of ASCT2 in melanoma cells leads to decreased mTOR signaling, resulting in cell cycle arrest [31]. Therefore, we hypothesize that cell cycle progression of melanoma is promoted by signaling pathways that are activated by SNAT1-transported amino acids. Another possible mechanism by which SNAT1 regulates senescence might involve ROS, which is a critical mediator of senescence [32,33]. Reduced transport of glutamine by silencing of SNAT1 could lead to decreased synthesis of glutathione, resulting in elevated ROS levels and induction of cellular senescence. In melanoma, the role of glutamine and glutathione in senescence remains to be elucidated, but our proposed mechanism is consistent with previous studies. In pancreatic ductal adenocarcinoma and breast cancer, glutamine deprivation leads to elevated ROS levels, thereby inducing senescence [34,35]. Breast cancer cells that were able to escape from therapy-induced senescence exhibit upregulation of the glutamine transporter ASCT2 and, to smaller extent, also of SNAT1 and SNAT2. In addition, glutamine starvation of several cancer types suppresses escape from therapy-induced senescence [36], promoting the assumption that there is a direct connection between glutamine transport and thereby enhanced glutamine metabolism and senescence in cancer cells. The increase of 10–20% of cells arrested in G1/G0 phase after knockdown of SNAT1 expression, as assessed by cell cycle analysis, does not completely explain the great extent of reduced proliferative and colony forming capacity of siSNAT1-transfected melanoma cells. This finding indicates that melanoma cells respond heterogeneously to SNAT1 silencing. This assumption is supported by the fact that melanoma is a highly heterogenous tumor. Here, melanoma cells are able to shift between different transcriptional programs, cell cycle states and cellular phenotypes to adapt to various exogenous effects [37]. A phenomenon that might explain why the population of cells arrested in G1/G0 phase is only moderately increased when compared to the greater effect on proliferation might be the development of slow-cycling melanoma cells due to amino acid depletion. Subpopulations of slow-cycling tumor cells were described in some cancer types, including melanoma [38,39,40,41]. Studies showed that slow-cycling JARID1Bhigh melanoma cells maintain a continuous tumor growth, are resistant to various chemotherapeutic drugs [37,42], and are involved in tumor recurrence [41]. Based on our findings, the reduction in cell growth and colony formation capacity after SNAT1 silencing are caused by a combinatory effect of reduced viability, by impaired metabolism due to amino acid depletion, and by an elevated induction of cellular senescence. Besides a reduction of cell growth, SNAT1 silencing also decreased the cell migration and invasion rate of melanoma cells, suggesting a role of SNAT1 during melanoma progression and the formation of metastases. These data are in accordance with other cancers, where SNAT1 overexpression is associated with increased proliferation rate, tumor size, tumor invasion, and migration [13,14,16,18,19]. Our data suggest that inhibition of SNAT1 can be a promising therapeutic option in treating melanoma. However, the choice of the way of inhibition will be crucial, as the inhibitor MeAIB showed cell line-dependent effects, whereas the knockdown resulted in strong effects in all cell lines. Our data provide novel evidence that SNAT1 plays an essential role in melanoma development and progression by promoting cell proliferation, colony formation, migration, and invasion, but also by inhibiting cellular senescence. Moreover, SNAT1 overexpression is associated with a poorer prognosis of patients with breast cancer [14], osteosarcoma [13], AML [19], and gastric cancer [18], hinting at SNAT1 as a potential drug target for cancer therapy. Therefore, the development of pharmacological inhibitors that selectively and effectively target SNAT1 will be a fruitful work program for the future. Acknowledgments We thank Silke Kuphal, Lisa Linck-Paulus, Sonja Schmidt and Chafia Chiheb for critical discussions. Additionally, we want to thank Michaela Pommer and Jessica Schirmer for technical support. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/cancers14092151/s1, Figure S1: Downregulation of SNAT1 on the protein level, Figure S2: Expression of glutamine transporters in melanoma, Figure S3: Effects of MeAIB and siSNAT1 on HEK293 cell line. Figure S4: Attachment and cell size of melanoma cells after downregulation of SNAT1. Figure S5: Uncropped Western blots. Click here for additional data file. Author Contributions Conceptualization, A.K.B. and I.B.-S.; methodology, A.K.B. and I.B.-S.; validation, all authors; formal analysis, S.L.; investigation, S.L. and I.B.-S.; resources, A.K.B.; data curation, S.L.; writing—original draft preparation, I.B.-S. and S.L.; writing—review and editing, S.L. and A.K.B.; visualization, I.B.-S. and S.L.; supervision, A.K.B. and I.B.-S.; project administration, A.K.B. and I.B.-S.; funding acquisition, A.K.B.; All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the German Research Association (DFG), grant number BO1573/39, and the IZKF Erlangen (ELAN P081). 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 RNA and protein expression of SNAT1/SLC38A1 in different melanoma cell lines. (A) Mean expression from RNA-sequencing analysis of SNAT1/SLC38A1 mRNA in primary and metastatic melanoma cells in comparison to NHEM. Values represent the mean ± SEM of 2 independent experiments for NHEM and metastasis and of 6 independent experiments for primary tumor. (B) Confirmation of SNAT1/SLC38A1 mRNA expression with qRT-PCR of indicated melanoma cell lines obtained from primary and metastatic melanoma, normalized to β-actin and compared to NHEM. Values represent the mean ± SEM of at least 3 independent experiments. (C) Western blot analysis (left) and densitometric analysis (right) of SNAT1 protein level of indicated melanoma cell lines normalized to β-actin and compared to NHEM. The siPool-mediated SNAT1 downregulation confirmed that SNAT1 protein sizes range from 50–70 kDa in Western blot analysis, potentially due to glycosylation (Supplementary Figure S1). Values represent the mean ± SEM of at least 3 independent experiments. (D) Representative immunohistochemical staining of SNAT1 protein in healthy epidermis, benign nevi, primary, and metastatic melanoma tissue samples of formalin-fixed and paraffin-embedded tissue blocks (left). Percentage of no, low, medium, and high SNAT1 expression level in benign nevi (n = 10), primary (n = 9), and metastatic melanoma (n = 7) tissue IHC-staining (right). p-value < 0.05 was considered statistically significant (*). The uncropped western blot figures are presented in Supplementary Figure S5. Figure 2 Effects of functional inhibition of SNAT1 on cell proliferation. (A,B) Proliferation analysis using XTT-assay of Mel Im (2000 cells) and Mel Juso (4000 cells) cell lines during 10 and 20 mM MeAIB-inhibitor treatment in comparison to control cells (0 mM MeAIB, equal amount of ddH20 was added). (B) XTT absorbance after 144 h. Values represent the mean ± SEM of 4 independent experiments. (C,D) Quantification of cell proliferation by RTCA of Mel Im and Mel Juso cell lines during 10 and 20 mM MeAIB-inhibitor treatment in comparison to control cells. (C) Exemplary image of RTCA curve measuring the delta cell index. (D) Quantified doubling time of RTCA–proliferation curve (CTR = 1). p-value for 10 mM MeAIB in Mel Im is 0.0746, p-values for 10 and 20 mM MeAIB in Mel Juso are 0.8855 and 0.4797, respectively. Values represent the mean ± SEM of 3 independent experiments. (E,F) Clonogenic assay of melanoma cell lines Mel Im and Mel Juso after 10 and 20 mM MeAIB-inhibitor treatment in comparison to control cells. Exemplary images (E) and quantification of colony number (F left) and colony size (F right). p-values for 10 mM MeAIB and 20 mM MeAIB in Mel Juso are 0.3750 and 0.2297, respectively. Values represent the mean ± SEM of 4 independent experiments. p-value < 0.05 was considered statistically significant (*). Figure 3 Influence of SNAT1 downregulation on cell proliferation. (A) Relative SNAT1 mRNA-expression normalized to β-actin after 48, 72, and 96 h siSNAT1 transfection, compared to siCTR cells of indicated melanoma cell lines. Values represent the mean ± SEM of 3 independent experiments. (B,C) Proliferation analysis using XTT assay of indicated melanoma cell lines after siSNAT1 downregulation in comparison to siCTR cells. (B) Exemplary absorbance at 490 nm 24, 48, 72, and 96 h after seeding siSNAT1 and siCTR cells of Mel Im and Mel Juso into the XTT assay. (C) Quantification of absorbance 96 h after starting the XTT assay. (Mel Im p-value = 0.1301.) Values represent the mean ± SEM of 3 independent experiments. (D,E) Quantification of cell proliferation with RTCA of Mel Im and Mel Juso cells after 96 h siSNAT1 transfection in comparison to siCTR cells. (D) Exemplary image of real time cell proliferation curve of siSNAT1 and siCTR-transfected cells. (E) Quantified RTCA doubling time. Values represent the mean ± SEM of at least 3 independent experiments. (F,G) Exemplary images (F) and quantification (G) of the clonogenic assay. Colony number (G left) and colony size (G right) of melanoma cell lines Mel Im and Mel Juso after siSNAT1 downregulation when compared to siCTR cells. Values represent the mean ± SEM of at least 3 independent experiments. p-value < 0.05 was considered statistically significant (*). Figure 4 Effects of SNAT1 downregulation on migratory and invasive potential of melanoma cells. (A,B) Analysis of cell migration using scratch wound healing assay of Mel Im and Mel Juso cell lines after siSNAT1 downregulation when compared to siCTR cells. (A) Representative images of cell monolayer scratch of Mel Im cells 24 h and of Mel Juso cells 48 h after scratching. (B) Scratch width of Mel Im cells 24 h and of Mel Juso cells 48 h after scratching (siCTR = 1). Values represent the mean ± SEM of 4 independent experiments. (C,D) Analysis of cellular migration using Boyden chamber assay of Mel Im and Mel Juso cell lines after siRNA-mediated SNAT1 downregulation, compared to siCTR-transfected melanoma cells. (C) Representative images of Boyden chamber gelatine-coated filter membrane. (D) Quantification of migrated cells (siCTR = 1). Values represent the mean ± SEM of 4 independent experiments. (E,F) Analysis of cellular invasion using Boyden chamber assay of Mel Im and Mel Juso cell lines after siRNA-mediated SNAT1 downregulation, compared to siCTR-transfected melanoma cells. (E) Representative images of Boyden chamber Matrigel-coated filter membrane. (F) Quantification of invasive cells (siCTR = 1). Values represent the mean ± SEM of 4 independent experiments. p-value < 0.05 was considered statistically significant (*). Figure 5 Effects of SNAT1 downregulation on apoptosis, cell cycle progression, and senescence induction. (A,B) Analysis of apoptotic and living cells using PI/ annexin-V staining examined with cytometric analysis after siRNA-mediated SNAT1 downregulation, compared to siCTR-transfected melanoma cell lines Mel Im and Mel Juso. Values represent the mean ± SEM of 3 independent experiments. (B) Exemplary image of flow cytometry-based apoptosis analysis of cell line Mel Im. (C,D) Flow cytometric analysis of cell cycle after siSNAT1 downregulation, compared to siCTR transfected melanoma cell lines Mel Im and Mel Juso. Values represent the mean ± SEM of 3 independent experiments. (D) Representative image of cytometric analysis of cell line Mel Juso. G1/G0-phase in blue, S-phase in olive green, G2-phase in light green. (E) Exemplary images of light microscopic examination of senescence-associated-β-galactosidase staining of siSNAT1 and siCTR-treated Mel Im and Mel Juso cells. Arrows indicate senescent melanoma cells. (F) Quantification of SA-β-galactosidase positive cells (siCTR = 1). Values represent the mean ± SEM of 3 independent experiments. (G,H) PML immunofluorescence staining of cell lines Mel Im and Mel Juso after siSNAT1 and siCTR transfection. (G) Quantification of PML-immunofluorescence intensity (siCTR = 1). (H) Representative image of PML-NB. Panels show overlay of PML (red) and DAPI (blue) staining. Arrows indicate formation of PML-NB. Values represent the mean ± SEM of 3 independent experiments. p-value < 0.05 was considered statistically significant (*). cancers-14-02151-t001_Table 1 Table 1 Overview of used cell lines. Cell Line Origin Mutation NHEM Healthy tissue - Sbcl2 Primary tumor (radial growth phase) N-RASQ61K WM3211 Primary tumor (vertical growth phase) p53T724G WM1366 Primary tumor (vertical growth phase) N-RASQ61L Mel Juso Primary tumor N-RASQ61L WM1158 Metastasis BRAFV600E, PTENDel/V343E Mel Im Metastasis BRAFV600E SKMel28 Metastasis BRAFV600E, PTENT167A, CDK4R24C, p53L145R HEK293 Embryonic kidney - cancers-14-02151-t002_Table 2 Table 2 Primers for qRT-PCR. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092349 jcm-11-02349 Review In Vivo Confocal Microscopy in Different Types of Dry Eye and Meibomian Gland Dysfunction Sim Ralene 1 Yong Kenneth 2 https://orcid.org/0000-0001-5408-0382 Liu Yu-Chi 13 https://orcid.org/0000-0002-3986-6552 Tong Louis 13* Gomi Fumi Academic Editor van Setten Gysbert-Botho Academic Editor Mazzotta Cosimo Academic Editor 1 Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore; ralene.sim@mohh.com.sg (R.S.); liuchiy@gmail.com (Y.-C.L.) 2 Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore; e0345868@u.nus.edu 3 Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore 169857, Singapore * Correspondence: louis.tong.h.t@singhealth.com.sg; Tel.: +65-9818-6221 22 4 2022 5 2022 11 9 234909 1 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/). In vivo confocal microscopy (IVCM) imaging is increasingly popular in ocular surface disease diagnosis and management. We conducted a systematic review to update the use of IVCM in the diagnosis and treatment of dry eye and meibomian gland dysfunction (MGD). A literature review was conducted on IVCM studies in MGD, dry eye disease, systemic disease causing dry eye, dry eye in glaucoma patients, contact lens-associated ocular conditions, graft-versus-host disease, and Sjogren’s syndrome-related dry eye. The articles were identified through PubMed and a total number of 63 eligible publications were analyzed in detail. All primary research studies on confocal microscopy on dry eye and related conditions from 2017 onwards were included. The reports were reviewed for their contribution to the existing literature as well as potential biases and drawbacks. Despite limitations such as small field of view, lack of population-based norms, and lack of standardization of image acquisition, interpretation, and quantification, IVCM is useful as a complementary technique for clinical diagnosis in various ocular surface disorders related to dry eye. With advances in hardware and software in the near future, it has the potential for further practical impact. diagnostic device dry eye in vivo confocal microscopy (IVCM) inflammation ocular surface tear disorder review ==== Body pmc1. Introduction There are many common ocular surface disorders (OSD), such as Dry Eye Disease (DED), blepharitis, and meibomian gland dysfunction (MGD), whose management requires visualization of certain ocular surface structures via slit-lamp biomicroscopy. In vivo confocal microscopy (IVCM), a more recent imaging technique has been evaluated in clinics for similar visualization [1]. The ocular surface consists of the conjunctiva, cornea, and the ocular mucosal adnexa (eyelid margins, eyelid glands, and lacrimal apparatus). The cornea, though uniquely suitable for IVCM due to its transparency, is not the only structure that can be visualized with this technique. It consists of the epithelium, basement membrane, Bowman’s layer, stroma, pre-Descemet, Descemet membrane, and endothelium [2]. The stroma contains keratocytes, dendritic cells (DCs), and nerve bundles that give rise to multiple branches which penetrate the epithelium [1]. Many of these corneal structures are not visible at the cellular level by conventional slit-lamp biomicroscopy but are clearly visible on IVCM. Unlike conventional light microscopy, IVCM directs light with a 670-nm wavelength laser [3] to pass to the desired focal spot using a pinhole aperture, which overcomes the problem of light scattering and provides clearer images at the cellular level. The resolution and magnification of IVCM (800-fold) are also much better than that of slit-lamp microscopy (40 fold), thus allowing improved and even cellular resolution of the ocular surface [4]. The resolution is also superior, with a lateral resolution of 1–2 μm and axial resolution of 5–10 μm [5]. Previously, Cruzat et al. [6] wrote an extensive review in 2017 on the pathological changes of corneal nerves in various ocular surface diseases. Other recent reviews [7,8] published in 2020 have not delved in-depth into various clinical applications of IVCM nor covered the spectrum of non-infective ocular surface diseases, and hence, there is a need for an update. In this article, we aim to review the literature on the clinical use of IVCM, focusing on studies published after 2017. 2. Materials and Methods 2.1. Study Objective and Definition of Reference Standard A systematic review was conducted (Figure 1) and the results were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. The main objective of this systematic review and meta-analysis is to evaluate the clinical applications of IVCM in dry eye, focusing on new observations. Because this study did not directly involve patients, an ethics committee approval was not required. 2.2. Literature Search Strategy We determined the criteria and search strategy before the start of the study. An entrez PubMed literature search of the PubMed database using the terms and a detailed combination of keywords to capture ocular surface disease and dry eye was performed from inception until 9 November 2021. The search terms included the following keywords and keyword combinations (((“in vivo” OR in vivo OR in-vivo) AND confocal) OR IVCM) AND keywords to identify a set of ocular surface articles (Please refer to Supplementary File S1). 2.3. Eligibility Criteria Two reviewers (R.S. and K.Y.) screened all retrieved articles by title and abstract initially. Only original research articles written in English were included and not analysis reviews, editorials, opinions, single case reports, and ex-vivo studies. The articles found were curated manually for their relevance to the ocular surface. The following conditions were not considered to be ocular surface disease: infectious keratitis, bullous keratopathy, ocular cystinosis, and Iridocorneal Endothelial Syndrome (ICE) syndrome. The full text of the remaining studies was curated. Additionally, the reference lists of the remaining studies were checked to identify further relevant articles that may have been overlooked during the initial process. Hard copies of all of the eligible articles were obtained and fully read. We excluded articles where IVCM findings were not mentioned in the results of the full-text article. Studies where recovery of the full text was not possible, even after searching the available medical databases and contacting the corresponding authors, were excluded. Disagreements were settled through discussion with a third reviewer (L.T.). 2.4. Data Extraction and Quality Evaluation of the Studies The initial database search with the above keywords identified 248,257 papers. The database search for publication dates from 2016 to 22 November 2021 identified 71,265 studies. After excluding articles where full text was not available (2285), 68,980 studies were left. After excluding non-human studies (33,164), 35,816 studies were left. After going through the title and screening through the abstract and applying our inclusion/exclusion criteria (4281 were reviews, 799 were systematic reviews, and 5056 were case reports), 632 studies were left. After full text-retrieval and further curation, 71 studies remained. A risk of bias assessment was then evaluated using the AMSTAR2 tool (Supplementary Table S1) [9] and the methodological quality of eligible articles was assessed using bias using the Revised Cochrane risk-of-bias tool for randomized trials RoB2 tool (Supplementary Table S2) [10]. Supplementary Table S2 presents the risk of bias summary per domain for individual studies and for all 4 included studies. The overall risk of biased judgment has been ascertained to reflect concerns in these studies as they have some concerns in at least one domain. 3. Results 3.1. Meibomian Gland Dysfunction Meibomian glands (MG) have been classically described to compose of acini constituted by convoluted borders lined by large cells with fine cellular material within the lumen [11], interstitial space between acini, ductules, and terminal ducts. Abnormal meibum quality and quantity can lead to a decreased or altered tear film lipid layer, tear hyperosmolarity, tear instability, and inflammation, leading to ocular surface damage and DED [12]. Significant fibrosis (demonstrated via loss of MG architecture with extensive fibrotic tissue surrounding MG remnants) has been observed in chronic MG dysfunction [13]. Recent studies on MGD are summarized in Table 1. A decrease in the size of the MG acinar unit was also observed [14]. IVCM has also been used to analyze the palpebral conjunctiva to visualize and quantify the density of immune cells [15]. These cells have been evaluated in different locations: epithelial (EIC), intraglandular (IGIC), stromal (SIC), and periglandular (PGIC) regions. The immune cells in EIC and IGIC were increased in MGD patients with more severe dry eye symptoms, even in those with minimal corneal staining [16]. Basal epithelial cell density was also found to be reduced with greater stromal nerve thickness in the MGD group [17]. Hence IVCM may provide reliable and clinically relevant metrics of inflammation and serve as clinical endpoints in future clinical trials targeting inflammation in MGD. 3.2. Dry Eye Disease Dry eye disease (DED) is defined as a “multifactorial disease of the ocular surface characterized by a loss of homeostasis of the tear film and accompanied by ocular symptoms, in which tear film instability and hyperosmolarity, ocular surface inflammation and damage, and neurosensory abnormalities play etiological roles” [16]. The ocular surface, epithelial sensory receptors, the innervation of the epithelial sensory receptors, secretory centers in the brain, and efferent nerves supplying the meibomian glands, goblet cells, and the main lacrimal gland form a functional unit. Any or all of these structures may be affected in DED [18]. The cornea is the most densely innervated part of the body. The cornea nerves serve the protective blink reflexes, help in tear secretion, and release neurotransmitters necessary for epithelial and stromal support as well as ocular homeostasis. They also serve the nociceptors associated with mechanical stimuli, pain, and cold sensations. Corneal nerves and their morphological changes can be seen under IVCM. With the help of analytic software, the corneal nerve plexuses can be evaluated quantitatively, typically by measuring the nerve fiber density, length, nerve branch density, and tortuosity [19,20]. The IVCM studies related to dry eye are summarized in Table 2. Corneal dendritic cells (DC) have been shown to be increased in dry eye patients compared to controls [21]. In the pathogenesis of dry eye, DCs play an important role in inducing the activation of T cells [22], thus triggering an inflammatory cascade reaction. Reduced corneal nerve density and length indicate a greater degree of neural damage induced by ocular pathology [23]. It has been shown that reduced density of corneal nerves results in impairment of protective functions such as tear secretion and blink reflexes. This results in a reduction in the tear quality and even aqueous tear deficiency. A study has suggested that patients with DED (diagnosed using TBUT and Schirmer’s, as well as the presence of symptoms) had decreased corneal nerve density [24]. Nerve tortuosity, defined by the frequency and the amplitude of the variations in the nerve fiber orientation, suggests active regeneration of nerve fibers in damaged nerves [25]. Studies by Liu et al. [26], Tepelus et al. [24], and Baikai et al. [27] have shown that nerve tortuosity is positively correlated with the diagnosis of DED. A greater nerve tortuosity is linked to ocular discomfort, visual function disturbance, and tear film instability [27]. 3.3. Sjogren’s-Related Dry Eye (SSDE) Sjogren syndrome (SS) is a systemic autoimmune disease that initially targets the lacrimal and salivary glands primarily, resulting in keratoconjunctivitis sicca (SSDE) and stomatitis sicca (dry mouth). The prevalence of primary SS in the USA approaches 1.3 million, with a range of 0.4–3.1 million [28]. The IVCM studies related to Sjogren’s-related dry eye are summarized in Table 2 as well. Certain IVCM parameters in sub-basal nerves have been reported to be altered in SS. Nerve fiber density is significantly decreased in SS [29,30], and SSDE is associated with greater nerve tortuosity than non-Sjogren’s Syndrome Dry Eye (NSSDE) [29]. Light backscattering (LB) measured in light reflectivity unit (LRU) at the Bowman’s membrane (BM) at 50 μm, 100 μm, and 200 μm deep to the BM has been evaluated in SS using IVCM—this is a measure of corneal inflammation [31]. Higher levels of LB in each corneal layer compared with healthy controls could indicate increased levels of corneal inflammation in SSDE [32]. The corneal epithelium of DED patients shows morphological changes, such as areas of enlarged and irregularly-shaped cells, which can be quantified by IVCM. Compared to controls, the density of superficial epithelial cells was decreased in both the NSDE and SSDE groups [33]. In summary, IVCM represents a reliable technique for examining nerve tortuosity in DED, as well as documenting corneal epithelial changes and immune cell densities in SSDE. 3.4. The Use of IVCM to Evaluate the Treatment for Dry Eye While disease outcomes have typically been measured using symptomatic questionnaires and clinical tools such as Schirmer Test, corneal and conjunctival staining, tear break up time (TBUT), and tear osmolarity, there has been increasing interest to document treatment outcomes with IVCM [34,35,36]. The IVCM studies performed as part of interventional trials in DED are summarized in Table 3. The most common anti-inflammatory treatment for DED is cyclosporin A (CsA), an immunosuppressant and a calcineurin inhibitor. It has been used in several trials since 1986 and continues to be the major anti-inflammatory drug in the treatment of DED. Six months following treatment with topical CsA in SSDE patients [37], symptoms of dry eye documented by the Ocular Surface Disease Index (OSDI) score improved together with a decrease in corneal nerve tortuosity. The same study reported an increase in sub-basal nerve plexus (SNP) density and a decrease in DC density after treatment. Though increased nerve reflectivity was found, the association was not significant. The decrease in DC density was attributed to the decrease in antigen-presenting cells and local inflammation, and the increase in SNP density was due to the normalization of innervation by controlling the inflammatory reaction [37]. Similarly, Laccheri et al. [38] also found a decrease in nerve tortuosity in SSDE after treatment with cyclosporine. They also found a decrease in nerve reflectivity, the number of sub-basal nerves, and an increase in intermediate corneal epithelial cells. The reduction of sub-basal nerves, reflectivity, and nerve tortuosity could be related to decreased nerve growth factor (NGF) post-treatment, though NGF levels were not checked for in this study. This is uniquely expressed in the human limbal basal epithelium, along with its two corresponding receptors: the low-affinity receptor p75NTR and the high-affinity receptor TrkA. The first receptor, when activated, transmits a signal mainly of apoptosis; the latter, when activated, promotes a molecular cascade aimed at the proliferation and cell activation, which replaces apoptotic cells. NGF secretion is stimulated by high levels of IL-1 and TNF during inflammation and hence treatment of DED would reduce inflammation and the level of NGF. The increase in epithelial cell density after using cyclosporine has also been postulated to be due to decreased NGF and reduction of apoptotic signals through the p75NTR [38]. The apparent discrepancies in these studies could be due to the difference in severities of the disease or demographic differences in the patients recruited. More recently, homologous sera obtained from healthy donors (i.e., allogeneic peripheral blood serum [allo-PBS] and cord blood serum [CBS]) have been proposed as treatment alternatives in patients with severe DED. Both treatments significantly improved corneal SNP parameters, and in particular, nerve density, length, width, and fractal dimension [39]. Giant epithelial cells, beading, and neuromas have also been shown to be decreased. Corneal nerve fractal dimension (CNFrD) is a novel IVCM metric that measures the structural complexity of corneal nerves, and its reduction represents nerve degeneration. It has been demonstrated that the CNFrD value has a diagnostic efficiency comparable with conventional IVCM parameters for identifying diabetic corneal neuropathy [40]. On the other hand, corticosteroids did not alter the quantitative measurements of the corneal SNP even though they decreased corneal DC density [41]. IVCM was used in a clinical trial that evaluated the use of omega-3 fatty acid supplements in DED [42]. These supplementations may have neuroprotective effects on corneal nerves, shown by an increase in corneal total nerve branch density (CTBD) and corneal nerve branch density on the main fiber (CNBD) after 90 days. 3.5. Systemic Disease Certain systemic diseases associated with DED are shown in Table 4. Diabetic neuropathy, including diabetic corneal neuropathy, is one of the most common microvascular complications in diabetes [43]. There is increasing evidence to show that impairment of microvascular components is preceded by early neurodegenerative alterations primarily involving small nerve fibers, which can be demonstrated by IVCM [44,45]. Moreover, as small-fiber neuropathic changes can be picked up by IVCM, corneal nerve metrics have been used as surrogate markers for diabetic peripheral neuropathy [46]. Studies have shown that IVCM parameters such as CNFL [47,48], CNBD, CNFD, and CNFrD are reduced in patients with diabetes compared to controls, especially at the inferior whorl site [49,50]. A significant reduction in nerve beading frequency was also reported, which may be due to reduced metabolomic activity in diabetic patients [51]. IVCM is useful in analyzing the cornea and MG structures as well as the skin epidermis and dermis in ocular rosacea. It can quantify MG alterations based on meibum reflectivity, inflammation, and fibrosis, which correlated with the number of Demodex mites in both MG and cheek. However, no correlation was found between IVCM scores and both subjective and objective tests of dry eye [52]. Graves’ ophthalmopathy (GO) is often associated with DED, the most frequent cause of ocular discomfort in such patients [53]. GO is an autoimmune disease in which autoantibodies to the thyroid-stimulating hormone receptor lead to an inflammatory response in the orbital tissues [54]. Recent studies with IVCM have found changes in corneal nerves and MGs. Abnormal corneal SNP has been reported in active and inactive GO, suggesting nerve degeneration in GO. These central corneal SNP parameters of GO patients were significantly decreased compared with those of controls: corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), corneal nerve fiber length (CNFL), corneal nerve fiber total branch density (CTBD), corneal nerve fiber area (CNFA), corneal nerve fiber width (CNFW) and corneal nerve fiber fractal dimension (CNFrD). In addition, CNFD and ACNFrD values were significantly lower in the active GO compared with inactive GO patients. However, this study did not adjust for potential differences in DED between GO states [55]. Hence, further studies could further stratify the active TAO further into mild, moderate, and severe states before comparing the difference in nerve parameters. IVCM also effectively revealed microstructural changes of MGs in eyes with GO and provided strong in vivo evidence for the roles of obstruction and inflammation in the disease process [56]. However, the patients in both groups had differing OSDI scores. Hence, it is unclear if the MG changes are related to concomitant DED in the GO patients or related to an extension of GO orbitopathy. Previous studies have discovered an association between DED and migraine headaches [57,58]. It has been hypothesized that the trigeminal system plays a critical role in the pathogenesis of ocular symptoms in migraine. The pain or photophobia associated with migraine is believed to arise from the release of vasoactive neuropeptides at the peripheries of the three main branches of the trigeminal nerve, which innervates the dura, cranium, face, and eye. The ophthalmic branch (V1), in particular, also serves as the afferent for ocular discomfort associated with dry eye [59,60]. IVCM can also study the structural changes in nociceptive corneal axons in the SNP, which showed a decrease in corneal nerve fiber length, total branch density, nerve branch density, and fiber area in patients with migraine and photophobia compared to patients with migraine without photophobia. Hence, SNP changes on IVCM may serve as a potential imaging marker for ocular symptoms of chronic migraine [61]. Unfortunately, the study did not include controls without migraine and did not assess the DED parameters in the participants. Hence, it is difficult to conclude whether the presence of DED parameters is indicative of the severity of migraines. 3.6. Glaucoma Treatment-Related Dry Eyes Glaucoma is the leading cause of global irreversible blindness. The number of people with glaucoma worldwide will increase to 111.8 million in 2040, disproportionally affecting people residing in Asia and Africa [62]. Glaucoma is the leading cause of global irreversible blindness. The most common initial treatment for glaucoma is topical medical therapy and about half of glaucoma patients on topical anti-glaucomatous medications have the ocular surface disease [63]. Previous studies have demonstrated that toxic and proinflammatory effects of antiglaucoma ophthalmic solutions are mainly due to preservatives, though prostaglandins by themselves can cause periorbitopathy [64,65]. IVCM studies related to glaucoma are summarized in Table 5. Such imaging is useful in evaluating proinflammatory ocular surface changes induced by anti-glaucoma eye drops. These parameters may be affected: basal epithelial cell density, stromal reflectivity, number of sub-basal nerves, sub-basal nerve tortuosity, sub-basal nerve reflectivity, and endothelial cell density. One study found increased basal epithelial cells density, stromal reflectivity, sub-basal nerve tortuosity, and reduced sub-basal nerves in patients using glaucoma drops compared to healthy controls [66]. IVCM can also document changes in the cornea after glaucoma filtration surgery to evaluate for surgical success. For instance, preoperative DC density and goblet cell density (GCD) are correlated with filtration surgery outcomes [67]. These parameters were measured at the upper bulbar conjunctiva corresponding to the bleb site pre-operatively and at the bleb site postoperatively. Images were acquired from the epithelium and subepithelium (10–50 microns of depth). GCs may transport aqueous humor through the bleb wall [68] and DCs are the source of immune-regulatory cytokines [69], so increased GC and decreased DC are predictors of good outcomes. Hence, IVCM of the conjunctiva may represent an imaging tool to predict surgical success in glaucoma [67]. However, the study did not assess objective markers of dry eye, such as Schirmer’s test or TBUT. In addition, IVCM can be used to describe and compare the conjunctival filtering bleb features after XEN gel implantation and trabeculectomy, providing objective evaluation at a cellular level. For instance, IVCM was used to evaluate parameters like stromal meshwork reflectivity (SMR). As SMR represents an indirect indicator of the collagen content within the conjunctival stroma, a hyper-reflective pattern was a sign of collagen deposition, scarring, and potentially poorer clinical outcomes. After trabeculectomy, blebs showing a low degree of reflectivity and a thick wall are more likely to have a good filtering function [70]. However, this study did not evaluate the success or failure of these procedures in the long term as it only included blebs with a completely successful filtering function. 3.7. Corneal Graft Versus Host Disease (GVHD) IVCM studies related to inflammation-related dry eyes from immune, toxic, or environmental causes are summarized in Table 6. For example, DED can also be mediated by severe immune reactions such as Graft-versus-host disease (GVHD), which is an inflammatory immune disease arising from an immunologic attack by donor alloreactive T cells that result in damage to vital organs, including the ocular surface of the eye [71]. Patients with ocular GVHD adjusted for ODSI and corneal staining displayed significantly decreased corneal epithelial cell density, SNP fiber density, and reflectivity compared to DED from other causes and healthy controls, while nerve tortuosity and epithelial DC density were increased in both oGVHD and DED groups [72]. This is in agreement with previous cross-sectional studies done [73,74,75]. As patients with DED unrelated to GVHD and ocular GVHD typically present with similar symptoms, IVCM could be used to evaluate and monitor patients with dry eyes due to GVHD and non-GVHD. Patients with chronic GVHD had worse meibography scores, reduced corneal sub-basal nerve plexus densities, lower TBUT scores, lower Schirmer I values and higher corneal staining scores. There was extensive loss of meibomian glands in both superior and inferior eyelids. In patients with chronic GVHD, the ensuing long-term inflammation often results in fibrosis of the ocular surface and cicatrizing conjunctivitis [76]. Hence, patients with chronic GVHD are at high risk for developing DED and MG dysfunction [77]. It is unclear if the IVCM signs of GVHD are linked to the more severe MG dysfunction compared to the DED group. 3.8. Contact Lens-Related Conditions Clinical studies using IVCM for contact lens-related problems are summarized in Table 7. Estimates of total contact lens (CL) wearers worldwide in 2005 were as high as 140 million and hence even complications with a low incidence may affect a large number of individuals [78]. While the majority of complications are minor such as conjunctival hyperemia and corneal edema from overwear, there are serious sight-threatening complications such as infectious keratitis [79]. IVCM of the central cornea observed a higher density of DCs in contact lens wearers compared with non–contact lens wearers. CL lens has been known to activate and increase DC, contributing to ocular surface inflammation and a decrease in SNP. This decrease in SNP has been hypothesized to be due to increased DC and activated inflammation [80]. This finding has also been confirmed in soft lens wearers [81]. The precise etiology of “corneal infiltrative events” (CIE) which arise during CL wear, including both corneal infections and noninfectious inflammatory events [82], is not well understood. The incidence of symptomatic CIEs during extended soft lens wear ranges from 2.5 to 6%; when asymptomatic CIEs are included, the incidence can be as high as 20–25% [83]. IVCM can thus be potentially used to assess the subclinical response of the ocular surface in CL wearer. The risk of developing CIEs is 12.5 times higher in reusable lenses (those stored overnight in disinfecting solution throughout their usage period, which is typically 2 weeks or 1 month) compared with daily disposable lenses [80]. Interestingly, DC density was higher in reusable lens wearers than in daily disposable CL wearers [82]. IVCM can also study changes in corneal nerves associated with contact lenses. Orthokeratology (OK) involves using specially designed and fitted GP contact lenses to reshape the corneal surface for the temporary correction of refractive error. Lenses are only worn at night during sleep and removed on waking to provide clear, unaided vision throughout the day. IVCM has found that nerve fiber density (NFD) is decreased in OK wear [84,85]. This reduced NFD is associated with reduced corneal sensitivity and increased nerve tortuosity as well [85]. 4. Discussion 4.1. Limitations Several studies were limited by their cross-sectional nature and hence inability to prove causation between the disease and IVCM parameters studied [14,38,52,55,56,61,70,77]. In addition, many studies were limited by their small sample size [14,24,55,61,66,68,70,77,80]. Some study designs include biases, with either no placebo group for comparison [37] or a lack of standardized treatment [68]. A study had no control groups or insufficient control (controls had dry eye symptoms) [52]. Others had study populations that may not be representative. For instance, in one study, most participants were female, and hence the results may not be extrapolated to the general population [24]. There were also limitations in the IVCM technique. A central area for analysis was selected to ensure consistent measurements across patient groups [66], but multiple scans in different areas could potentially give a more comprehensive assessment. There may be significant inter-observer and intra-observer variability with poor repeatability and manual processing is laborious and time-consuming. Furthermore, IVCM can only image a very small field of view, hindering reproducible imaging of the same areas over time. A limitation of our study was complying with all items for a systematic review. We did not register the protocol for this review in a review registry which is a flaw according to AMSTAR-2 (Supplementary Table S1). We have tried to reflect, in the material and methods section, the entire search protocol as it was carried out and the search strategy designed. For conducting a proper systematic review, out of sixteen questions, we answered “Yes” to nine questions, with partial “Yes” to one and “No” to five questions. We missed item 7 (justification for excluding individual studies—we did not provide the full list of excluded articles, but this can be made available on request), item 10 (funding sources of papers as the paper would be too lengthy), item 11, 12, and 15 as these questions are not relevant when meta-analysis are not performed. We have a partial “Yes” to item 4 (we searched only 1 database instead of 2, but we have provided the keywords and search strategy used). However, this review is about an imaging diagnostic tool, IVCM, not about specific therapy. As there were no studies that evaluated health outcomes based on the use of IVCM vs. the lack of such imaging, the AMSTAR2 and ROB2 could only be applied to study outcomes of specific treatment interventions. 4.2. Future Research Directions Due to the high cost of this technology, the widespread deployment and use of IVCM in clinical practice are limited. Hopefully, improvement in hardware and wider use may bring the cost down. Analysis of corneal SNP on IVCM images can be fully automated, semi-automated, or manual. The fully automated technique requires no manual input from the observer and is faster and more suited for large trials and longitudinal studies requiring analysis of a large number of images. However, there might be more false-negative and false-positive errors that require improvement of these algorithms in the future [86]. As mentioned earlier, one of the drawbacks of IVCM is its small field of view, preventing an overview of SNP architecture and necessitating subjective image sampling of small areas of the SNP for analysis. Hence, future directions also include large-area imaging and mapping or mosaic technique. Corneal SNP can be reconstructed by automated mosaicking, with an average mosaic image size corresponding to 48 individual IVCM fields of view [87]. The use of artificial intelligence (AI) and increasing automation will improve the speed and accuracy of image analysis. Freeware, including ImageJ (NIH) and image processing packages for python (e.g., scikit-image, OpenCV) and others, have many built-in functions which allow for custom scripting. Future advances are likely to include advances in machine-learning algorithms, which are currently making their way into commercial software packages [88]. High-speed networks will also improve the ease of using IVCM images in digital medicine. 5. Conclusions IVCM is useful as a complementary technique for clinical diagnosis in various ocular surface disorders related to dry eye. With advances in hardware and software in the near future, it has the potential for further practical impact and can be used for a multitude of OSD for diagnosis, management, and prognostication. Acknowledgments Singapore National Eye Centre, Singapore Eye Research Institute. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/jcm11092349/s1, Supplementary File S1: TFOS Lifestyle Workshop 2021—Standardised Electronic Searches. Table S1: Table to summarize the results of AMSTAR-2. Table S2: Risk of bias summary for individual studies (n = 4) in accordance with Rob2. Click here for additional data file. Author Contributions Conceptualization, L.T.; methodology, L.T.; literature review, R.S., K.Y.; data curation; writing—original draft preparation, K.Y. and R.S.; writing—review and editing, R.S., L.T., and Y.-C.L.; visualization, L.T., R.S.; supervision, L.T. All authors have read and agreed to the published version of the manuscript. Funding National Medical Research Council\Clinician Scientist Award\017\2017. 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 PRISMA flowchart of a systematic review of in vivo confocal microscopy in different types of dry eye and meibomian gland dysfunction. jcm-11-02349-t001_Table 1 Table 1 Studies on Meibomian Gland Dysfunction (MGD). Area of Study Authors Main Contribution to Literature Design Sample Size (Eyes) Source of Participants No. of Visits HRT Main Outcomes Main Findings Limitations Immune cellular metrics of inflammation Qazi Y. Only study which uses IVCM-based immune-cellular metrics to assess the inflammation of MGD. Cross-sectional, retrospective 29 Outpatient 1 HRT III-RCM Density of immune cell, epi, or stromal No. of periglandular immune cell Area of IGIC Luminal width, length, and thickness of internal luminal hyperreflective ring in ductules EIC and IGIC increased in highly symptomatic patients that have minimal corneal staining and correlate with symptoms and clinical signs. A cross-sectional study does not demonstrate that the progression of MGD causes increases in immune cells. Small sample size. Evaluation of corneal layers in MGD Azizi S. Evaluating individual corneal layers using IVCM Single-center, prospective 92 Outpatient 1 HRT III-RCM Surface area and cell coverage of basal epithelial anterior keratocytes, posterior keratocytes, and endothelial cells. Stromal nerve thickness Basal epithelial cell density reduced, the area increased, and stromal nerve thickness greater in the MGD group. Study repeats the older methodology (no new findings) Classification in the diagnosis of MGD Randon M. Using IVCM as a new way to classify the various pathophysiological system for MGD Cross-sectional, retrospective 115 Outpatient 1 HRT II-RCM Combination of grades of meibum reflectivity, intraepithelial/interglandular inflammation, glandular fibrosis Strong correlation between IVCM score (Type 0 normal MG; type 1 obstructed MG without inflammation or fibrosis; type 2 MG inflammation without fibrosis; type 3 MG fibrosis), and meibography score. Study about the grading severity of MGD needs more studies to confirm accuracy. MGD with different symptoms Zhao H. Attempted to differentiate symptoms of MGD using IVCM Cross-sectional, retrospective 60 Outpatient 1 HRT II-RCM MG acinar unit density palpebral conjunctival inflammatory cell density periglandular inflammatory cell density MG acinar unit area MG acinar unit longest diameter MG acinar unit shortest diameter More severe symptoms had more significant fibrosis and a severe decrease in the size of MG acinar units. DED symptoms negatively correlated with confocal microscopic parameters and positively correlated with conjunctival inflammatory cells and Langerhans cells Unable to test MG lipid and inflammatory factors which could contribute to DED. DED: dry eye disease; EIC: epithelial immune cell; IGIC: intraglandular immune cell; IVCM: in vivo confocal microscopy; MGD: meibomian gland dysfunction; HRT: Heidelberg Retinal Tomograph; RCM: Rostock Cornea Module. jcm-11-02349-t002_Table 2 Table 2 Studies on Sjogren Syndrome (SS) and Non-Sjogren Syndrome Dry Eye (NSSDE). Area of Study Authors Main Contribution to Literature Design Sample Size Source of Participants No. of Visits HRT Main Outcomes Main Findings Limitations Imaging of POV in DED Ghouali In all quadrants, fewer POVs were detected in DED patients than in normal subjects Prospective case-control 163 Outpatient 1 HRT II-RCM POV found predominantly in superior (p < 0.001) and inferior (p < 0.001) quadrants compared to nasal and temporal quadrants En-face SD-OCT showed POV as a radially oriented network located in the superficial corneoscleral limbus, with a good correlation with IVCM features Depth of analysis (70 μm below the corneal/conjunctiva surface) might not capture the entire POV structure. Corneal Sub-basal Nerve Plexus in DED (New Fully Automated System) Giannaccare ACC Metrics detected SNP alterations in DED, good diagnostic performance in discriminating DED. Cross-sectional 69 Outpatient 1 HRT-RCM CNBD CNFL CNFW Lower CNBD, CNFL & higher CNFW in DED compared to controls Small sample size ACC metrics cannot analyze and quantify nerve tortuosity, a well-recognized metric affected in DED DED and Low Sub-basal Nerve Density and Corneal Endothelial Cell Loss Kheirkhah DED associated with accelerated corneal endothelial cell loss Retrospective 33.2 ± 10.2 months 40 Outpatient 2 (baseline, next visit) HRT III-RCM Densities of corneal endothelial cells and sub-basal nerve Initial visit DED: lower densities of corneal endothelial cells and sub-basal nerves than control Endothelial cell loss negative correlation with initial sub-basal nerve density Retrospective design, small sample size, did not evaluate the morphology of endothelial cells Only central CECD was measured. Evaluation of Objective Visual Quality in Dry Eye Disease and Corneal Nerve Changes. Ma, Jiahui Longer and wider corneal nerves were associated with better objective visual quality in DED Prospective study 98 Outpatient 1 Not specified CNFL, objective scatter index, mean objective scattering index, modulation transfer function, Strehl ratio. Patients with longer and wider corneal nerves had better objective visual quality No control group. Changes in Langerhans cells not summarized. Small sample size Quantification of Corneal Sub-basal Nerve Tortuosity in DED and Its Correlation With Clinical Parameters Ma, Baikai New parameter: Aggregated measure of tortuosity (Tagg) for quantification of corneal sub-basal nerve tortuosity. Cross-sectional case-control 49 Outpatients 1 RCM Tagg higher in DED than controls (p < 0.001). Tagg correlated with OSDI (r = 0.418) & negatively correlated with BUT Higher Tagg may be linked to ocular discomfort, visual function disturbance, and tear film instability Excluded images with DCs and obvious neuromas because DCs co-segmented with nerves Corneal Sub-basal Nerve Analysis in DED and Clinical Correlations Liu Yan IVCM is a useful tool to evaluate corneal changes in DED, such as in sub-basal nerves and Langerhans cells (LCs) Cross-sectional study 107 Outpatient 1 HRT II-RCM CNFL CNFT CNFW Langerhans cells no. not correlated with symptoms. CNFL negatively correlated with sensitivity to light; CNFW positively correlated with OSDI, pain, blurred vision; CNFT positively correlated with sensitivity to light No healthy controls. Cross-sectional study. IVCM in Primary Sjögren Syndrome and Sicca Syndrome Patients Joana C. Using IVCM to diagnose and differentiate immune-mediated DED from other forms of DED Cross-sectional, retrospective 136 Outpatient 1 HRT III-RCM SNPNerve density Nerve length Nerve tortuosity pSS and non-SS sicca pts had lower corneal SNP plexus density and length, increased tortuosity compared to healthy controls, unable to differentiate between pSS and non-SS Some patients in immune-mediated DED groups did not meet the criteria for DED. Ocular Surface Alterations in Patients With Fibromyalgia Turan E. First study to evaluate corneal microstructures in FM. Cross-sectional, retrospective 76 Outpatient 1 HRT III-RCM Basal epithelial cell density SNP density SNP tortuosity Basal epithelial cell density, total nerve density, long new fibers, total no. of nerves lower in patients with FM. Small sample size. IVCM in SSDE Michele L. Using light backscattering as a parameter in IVCM to evaluate SSDE Cross-sectional, retrospective 110 Outpatient For 6 cont. months HRT III-RCM Light backscattering LB is higher in patients with SSDE, which is postulated to be due to higher levels of inflammation in SSDE. Cross-sectional study does not prove causation. Corneal epithelium in SSDE vs. NSDE Olivia L. Assessing reproducibility and reliability of other studies on the same topic. Cross-sectional, prospective 78 Outpatient 1 HRT III-RCM Superficial, basal, outer wing, and inner wing epithelial cell density Superficial epithelial, inner wing, and basal cell density are lower in SSDE and NSDE compared to control. No diff in SSDE and NSDE. Outer wing cell density lower in SSDE compared to NSDE and control, no sig difference Cross-sectional study does not prove causation. Cornea nerve structure with primary SSDE vs. NSDE Fangting L. Evaluate IVCM morphology of corneal SNP and its relationship with clinical parameters Cross-sectional, prospective 42 Outpatient 1 HRT III-RCM SNPNerve density Length, max length Number Tortuosity SS lower density, no. of nerves than NSDE Greater nerve tortuosity in SSDE than NSDE Mean length and max length similar in both Small sample size, area selected for IVCM analysis is not representative of the whole plexus Tear lacritin levels in patients with SSDE Nancy M. First study to inv association between tear lacritin levels and SS patients Cross-sectional, prospective 20 Outpatient 1 Nidek Confoscan 4 SNPNerve fiber density Nerve fiber length Nerve branch density Tortuosity Nerve fiber density and length sig decreased in SSDE No mention of branch density or tortuosity. Small sample size, focus of study is not on IVCM Corneal Innervation, Inflammation, and Symptoms in DED Tepelus NSDE and SSDE: alterations in corneal innervation and increased DCs. Corneal nerve density and reflectivity are correlated with OSDI. Prospective case-control study 78 Outpatient 1 HRT III-RCM CNBD CNFT, Reflectivity of corneal nerves, CDCD CNBD decreased in SSDE & NSDE, Increased CNFT & decreased reflectivity in both. DCs increased in SSDE & NSDE compared to controls Correlations between DNF & DC (r = −0.57), between DNF & OSDI (r = −0.91) and between RNF & OSDI (r = −0.75). Relatively small no. of patients Topical and systemic corticosteroids have a potential effect on epithelial DC density and OSDI Most participants females—results may not be extrapolated to male patients. Proinflammatory Markers, Chemokines, and Enkephalin in DED Pierre Nicolle DED patients have significantly higher corneal DC density compared to controls Prospective case-control study 47 Outpatient 1 HRT-RCM Sub-basal nerve density CDCD Sub-basal nerve density was significantly lower in DED compared to controls; DED patients had a significantly higher corneal DC density compared to controls. Not all participants had IVCM in both eyes. Low quantity of mRNA in some impressions. No protein level markers nor immune composition. Correlation of Corneal Immune Cell Changes with Clinical Severity in DED Aggarwal DC density and morphology correlated with DED severity, DC density increased in mild DED, morphological changes in severe DED. Retrospective, cross-sectional 349 Outpatient 1 HRT III-RCM DCD Size Morphology DC density is higher in DED compared to controls. Morphologically, the number of dendrites, DC size, and field were significantly larger in DED than in controls. Retrospective. Only analyzed central corneal images. Tear Nociception-Associated Factors, Cornea DCD in DED Khamar Altered tear fluid soluble factors associated with ocular surface discomfort, TBUT, Schirmer’s test, and cornea DCD Case-control cross-sectional 80 Outpatient 1 HRT II-RCM Cornea DCD, SNP features Cornea DCD is significantly higher in DED patients. No significant difference was observed in SNP features. Cross-sectional design CNBD: Corneal nerve branch density; CNFL: Corneal nerve fiber length; CNFT: corneal nerve fiber tortuosity; CNFW: corneal nerve width; DC: dendritic cell; DCD: dendritic cell density DED: dry eye disease; HRT: Heidelberg Retinal Tomograph; LCs: Langerhans cells; POV: Palisade of Vogt; OSDI: ocular surface disease index; RCM: Rostock Cornea Module; SD-OCT: spectral-domain optical coherence tomography; SNP: sub-basal nerve plexus; SSDE: Sjogren’s Syndrome Dry Eye; TBUT: tear break-up time. jcm-11-02349-t003_Table 3 Table 3 Studies on Treatment-Induced Changes in Dry Eye. Area of Study Authors Main Contribution to Literature Design Sample Size Source of Participant No. of Visits HRT Main Outcomes Main Findings Limitations Corneal SNP density in SSDE treated with cyclosporin A Ora L. Evaluate SNP changes in SSDE treated with cyclosporin A Longitudinal, prospective, observational 45 Outpatient 2 (base, 6 months) HRT III-RCM SNP density, number, reflectivity, tortuosity DC density SNP density sig increased after CsA, a/w decreased tortuosity, and DCs number Lack of placebo group and repeated IVCM in healthy group 6 months later. 2-month treatment of CBS eye drops in ocular surface disease Giannaccare G. Reported corneal cell morphology and corneal nerves after CBS therapy Prospective, observational, cross-sectional 20 Outpatient 1 HRT III-RCM Giant epithelial cells SNP number and tortuosity Neuromas, beading, and DCs in the central cornea. Higher total nerve number and lower tortuosity Giant epithelial cells, beading, and neuromas decreased. DC density unchanged Cause of DED in 20 patients was different DED treated with different sources of homologous eye drops Giannaccare G. RCT to investigate the difference in the effect of allo-PBS and CBS eye drops on corneal nerve morphology Randomized, double-blinded RCT 30 Outpatient 2 (base, 30 days) HRT III-RCM CNFD CTBD CNFL CTBD CNFA CNFW CNFrD Overall CNFD, CNFL, CNFrD sig increased CNFW decreased CNFrD increase higher in CBS eye drops than in allo-PBS Small sample size, follow-up time too short to draw a conclusion on eye drop efficacy Patients with DED treated with topical cyclosporin Iaccheri B. No studies have yet evaluated topical cyclosporine on IVCM parameters in DED Prospective, observational, cross-sectional 42 Outpatient 4 (base, 1, 3, 6 months) HRT II-RCM SNP density, number, tortuosity, reflectivity Activation of stromal keratocytes Density of intermediate epithelial cells increased Keratocyte activation decreased. SNP number, reflectivity, and tortuosity decreased Small sample size, causes of DED in the patient group, not constant Mild DED Trial with artificial tears or steroids and relationship to corneal DCs Li Bei Topical steroids can reduce corneal DCs Case-control 72 Outpatient 1 Not specified Tear and conjunctival cytokines, amount of DCs More DCs in cornea epithelium of dry eye s with symptoms outweighing signs than common mild dry eye and control groups. After glucocorticoid treatment, the number of DCs significantly decreased IVCM findings are limited to DCs Efficacy of 2% Topical Rebamipide on Conjunctival Squamous Metaplasia and Goblet Cell Density in DED Simsek Topical use of 2% rebamipide for 3 months associated with improvements in ocular surface differentiation due to mucosal changes Prospective interventional study 15 Outpatient 2 (baseline, 3 months) HRT II RCM Evaluation of nucleocytoplasmic ratios and corneal ECs Significant improvements in mean corneal epithelial cell density and nucleocytoplasmic ratios after treatment. Small sample size Omega-3 on corneal nerves in DED Chinnery H. RCT to investigate the effect of omega-3 on nerve parameters in DED Randomized, double-blinded, RCT 12 Outpatient 2 (base, 90 days) HRT III-RCM CNFD, CNFL, CNBD, CTBD, CNFW, and CNFA Hyperreflective DCs CTBD and CNBD increased after 90 days of omega-3 Sig crossover interaction for CNFL CNFA, CNFD, CNFW no difference Small sample size IVCM in DED after autologous eye drop Mahelkova G. Added to the current literature of IVCM findings after topical therapies on DED Prospective, observational, cross-sectional 26 Outpatient 2 (base, 3 month) SSCM, Confoscan 3, NIDEK Technologie, Padua, Italy Superficial and basal epithelial cell density Density of keratocytes Density of epithelial cells. SNP total nerve length, number, number of branches, tortuosity DC density Basal EC density decreased sig Sup EC, no. of DCs, activated keratocytes did not change sig. No differences in the other corneal cell layers or in the status of the nerve fibers Small sample size, no control group to compare against Combined hyaluronic acid (HA) and coenzyme Q10 eyedrops vs. HA alone eyedrops in DED Postorino E. Added to IVCM findings in the dry eye after novel medication (XLHA and CoQ10)—the study of epithelial cell reflectivity, keratocytes, stromal matrix parameters Randomized, single-blinded RCT 40 Outpatient 4 (base, 15, 30, 90 days) Confoscan 4 confocal microscope (Nidek Technologies) Hyperreflectivity of ECs Morphological features of keratocytes Stromal matrix EC hyperreflectivity decreased in the combination group Sig improvement in keratocyte and stromal matric in the combination group Small sample size Ocular nebulization of Vitamin B12 vs. oxytocin in DED Yang J. First to report IVCM changes after nebulization in ophthalmology Randomized, double-blinded RCT 38 Outpatient 3 (base, 1, 3 month) HRT III-RCM Basal epithelial cell density Sub-basal DC density Nerve density Nerve tortuosity Basal EC and SNP density increased, DC density decreased in all groups Tortuosity no change Higher EC density at 3 months, lower DC density at 1 month in the B12 group Ages in both groups different, no control group CBS: cord blood serum; CNBD: corneal nerve branch density; CNFA: corneal nerve fiber area; CNFD: corneal nerve fiber density; CNFL: corneal nerve fiber length; CNFrD: corneal nerve fractal dimension; CNFW: corneal nerve fiber width; CTBD: corneal nerve fiber total branch density; DC: dendritic cells; DED: dry eye disease; EC: epithelial cell; HRT: Heidelberg Retinal Tomograph; IVCM: in vivo confocal microscopy; PBS: peripheral blood serum; RCM: Rostock Cornea Module; RCT: randomized controlled trial; SNP: sub-basal nerve plexus; SSDE: Sjogren’s syndrome Dry Eye. jcm-11-02349-t004_Table 4 Table 4 Studies on Systemic Disease-related Dry Eye. Area of Study Authors Main Contribution to Literature Design Sample Size Source of Participants No. of Visits HRT Main Outcomes Main Findings Limitations Corneal nerve alterations in children and youths with T1DM Tiziano C Early signs of corneal nerve degeneration were found in children and youths with T1DM Retrospective case-control study 201 Outpatient 1 HRT III-RCM CNFL CNFD CNBD CTBD CNFrD All IVCM parameters, except CTBD, were significantly lower in the T1D patients. Glycometabolic control (HbA1c, visit-to-visit HbA1c variability, and mean HbA1c) and blood pressure were inversely correlated with IVCM parameters. Small sample size; sample had European ancestry, so results cannot necessarily be extended to children and adolescents with other ethnic backgrounds. Reduced Corneal Nerve Fiber in T2DM Neil S Lagali Wide-area mosaic images provide reference values for mosaic CNFL (mCNFL) and whorl CNFL (wCNFL) and reveal a progressive degeneration of the SBP with increasing duration of type 2 diabetes. Population-based study 163 Outpatient 1 HRT III-RCM mCNFL Apical wCNFD mCNFL in T2DM reduced relative to non-diabetic subjects Lower mCNFL is associated with diabetes and increased HbA1c levels Apical wCNFD was unaffected by diabetes or HbA1c Global SNP patterns revealed marked degeneration of secondary nerve fiber branches outside the whorl region in long-duration diabetes. Small sample size DC maturation in corneal epithelium associated with TNF receptor superfamily member 9 Neil S Lagali Develop a non-invasive means to monitor the status of inflammatory DC subsets in the corneal epithelium as a potential biomarker for the onset of inflammation in T2DM Cohort study 81 Outpatient 1 HRT III-RCM Quantification of DCs With the onset of diabetes, the proportion of mature, antigen-presenting DCs increased and became organized in clusters. TNF receptor superfamily member 9 (TNFRSF9) is associated with the observed maturation of DCs from an immature to mature antigen-presenting phenotype. Small cohort size, narrow focus on the relationship between systemic markers of inflammation and corneal DCs Sub-basal nerves in wide-area corneal nerve plexus mosaics in T2DM Reza A Badian Sub-basal nerve degeneration in T2DM can vary according to anatomic location Cross-sectional study 163 Outpatient 1 HRT III-RCM SNP CNFL In long-term T2DM, nerve density in the left superior sector of SNP decreased while that in the central superior SNP increased relative to healthy subjects with normal glucose tolerance CNFL is not affected by diabetes Cross-sectional nature Imaging of Corneal Sub-basal Whorl-like Nerve Plexus Tsugiaki Utsunomiya IVCM measurements of whorl-like patterns may accurately define the extent of corneal nerve damage to monitor diabetic peripheral neuropathy. Observational study 68 Outpatient 1 HRT III-RCM CNFL Total CNFL is significantly shorter in DM group than in the control group and decreases with the progression of diabetic retinopathy, nephropathy, neuropathy, and decreased corneal sensation. Small no of patients, captured a whorl-like pattern in half of the subjects (visual fixation unstable with fatigue)’ T1DM and T2DM subjects combined with analysis IVCM of Corneal Nerves: Ocular Biomarker for Peripheral and Cardiac Autonomic Neuropathy in T1DM Stuti L Misra Correlation of corneal SNP density with total neuropathy score suggests that reduced corneal nerve density reflects peripheral neuropathy in diabetes. Case-control study 93 Outpatient 1 HRT II-RCM Corneal SNP density Corneal sensitivity Corneal SNP density and corneal sensitivity were significantly lower in diabetes compared to controls. A modest negative correlation between total neuropathy score and SBN density was observed. Sub-basal nerve branching and tortuosity were not considered nor analyzed Epithelial changes with corneal punctate epitheliopathy and correlation with time to healing in T2DM Jing-Hao Qu Increased LC and decreased SNP in T2DM with corneal punctate epitheliopathy Retrospective study 160 Outpatient 1 HRT III-RCM Density of BEC, SNP, and LC LC density, SNP density, and BEC density were reduced in the T2DM group compared with controls. LC density in the T2DM group showed a negative correlation with SNP density. SNP density in the T2DM group showed a positive correlation with BEC density. BEC density in the T2DM group showed a negative correlation with healing time. IVCM images only from the first patient visit and no post-treatment images for comparison. Glycemic control data was not collected in T2DM patients. Association between alterations of corneal SNP and long-term glycemic variability Marco P HbA1c and disease duration were independent predictors of damage to SNP in T1DM. Consecutive cross-sectional study 40 Outpatient 1 HRT-RCM CNFD CNFL CNFrD CTBD CNFA CNFW Diabetes duration and all-time SD of HbA1c were independently associated with CNFD, CNFL, and CNFrD. Analysis of the association among IVCM parameters and specific subtypes of diabetic neuropathy showed that altered cold sensitivity was independently associated with CNFD. Small no of patients, lack of longitudinal IVCM analysis, included only T1DM Ocular and Cutaneous Rosacea Liang, Hong IVCM features of rosacea patients combined with quantification of Demodex Case-control cross-sectional study 44 Outpatient 1 HRT-RCM MG (IVCM-MG) cheek (IVCM-Cheek) alterations, Demodex counts: IVCM-MG-Dex IVCM-Cheek-Dex IVCM-MG correlated with IVCM-Cheek IVCM-MG-Dex correlated with IVCM-Cheek-Dex cannot image deeper structure no normal controls Sub-basal Nerve Plexus Changes in Chronic Migraine Shetty, Rohit, Changes in SNPP support the role of the trigeminal system in the pathogenesis of ocular symptoms in migraine Cross-sectional study 84 Outpatient 1 HRT-RCM II CNFD NFL CNBD CTBD CNFA Average CNFW SNPP: a significant decrease in CNFL, CTBD, CNBD, and CNFA in migraine with photophobia Changes during ictal period not done Small sample Chinese TAO Wu LQ Abnormal corneal sub-basal nerves observed in active and inactive Chinese TAO Cross-sectional study 58 Outpatient 1 HRT III-RCM CNFD CNBD CNFL CTBD CNFA CNFW ACNFrD SNP parameters of TAO decreased compared to controls; correlations between CNFD, CNBD, CNFL, CTBD, CNFA, and ACNFrD Small sample size No adjustment for dry eye or tear function Meibomian Glands structure in Graves’ Orbitopathy Cheng S IVCM found obstruction and inflammation in MG of GO patients Cross-sectional observational study 142 Outpatient 1 HRT III-RCM MAD, MALD, MASD MOA, MAI, MSR, AWI, API, MG fibrosis. Compared to controls, GO: lower MOA, MAD; greater MALD, MASD, MAI, MSR, and MG fibrosis Active GO: higher MAI, AWI, & API, Inactive GO: higher MSR and MG fibrosis GO: AWI and API positively correlated with CAS, MG fibrosis negatively correlated with CAS. Control group is not representative of the healthy population—some had dry eye symptoms and inadequate MG performance Corneal changes in Mucous Membrane Pemphigoid (MMP) Tepelus Microstructural corneal changes in MMP Prospective single-center cross-sectional study 40 Outpatient 1 HRT III-RCM Morphology of corneal epithelial layers, stroma, and endothelium, corneal nerves, and presence of DCs Decreased corneal nerve density and elevated DC in non-end-stage MMP compared with controls. Small sample size Corneal Nerve in Parkinson’s Disease. Misra, Stuti L. Significant reduction in corneal SNP density in Parkinson’s, which is associated with cognitive dysfunction Cross-sectional study 30 Outpatient 1 HRT II-RCM Corneal SNP density Corneal SNP density markedly reduced in Parkinson’s compared with controls Limited sample size mild disease excluded API: acinar periglandular interstices inhomogeneity; AWI: acinar wall inhomogeneity; BEC: basal epithelial cell; CNFrD: corneal nerve fiber fractal dimension; CNBD: corneal nerve branch density; CNFA: corneal nerve fiber area; CNFD: corneal nerve fiber density; CNFL: corneal nerve fiber length; CNFW: corneal nerve fiber width; CTBD: corneal nerve fiber total branch density; DC: dendritic cell; Hba1c: hemoglobin A1c; LC: Langerhans cells; MAD: MG acinar density; MAI: MG acinar irregularity; MALD and MASD: MG longest and shortest diameters; MOA: MG orifice area; MSR: meibum reflectivity; SD: standard deviation; SNP: sub-basal nerve plexus; TAO: Thyroid-Associated Ophthalmopathy; TNF: tumor necrosis factor; T1DM: Type 1 Diabetes Mellitus; T2DM: Type 2 Diabetes Mellitus. jcm-11-02349-t005_Table 5 Table 5 Studies on Glaucoma-Related Dry Eye. Area of Study Authors Main Contribution to Literature Design Sample Size Participants No. of Visits HRT Main Outcomes Main Findings Limitations Structural Imaging of Conjunctival Filtering Blebs in XEN Gel Implantation and Trabeculectomy Sacchi First paper to use IVCM on epithelial cysts and a hypo-reflective bleb wall Retrospective, cross-sectional, observational study 52 Outpatient 2 (baseline, 6 months) HRT III-RCM MMD, MMA, SMR MMA and SMR values were lower in the XEN gel implantation compared with trabeculectomy Retrospective, small sample size, inclusion of only completing successful filtering blebs Prospective, Masked, 36 Months Study on Glaucoma Patients Medically Treated with PF or Preserved Monotherapy Rossi PF-tafluprost formulation does not alter corneal structures after 36 months of topical daily therapy Prospective, Masked Study 93 Outpatient 7 (Baseline and every 6 months for 3 years) Confoscan 4 (Nidek technologies) Activation of keratocytes, number of sub-basal plexus nerve fibers, tortuosity, number of bead-like formations, endothelial cellular density. At baseline, keratocyte activation similar in the 3 groups Over months, naïve patients treated with PF-tafluprost reduced keratocyte activation. Sub-basal nerves increase in patients switched to PF-tafluprost Investigation limited to the center of the cornea, different results were obtained by inspecting the corneal periphery Limited sample size Long Term Safety and Tolerability of Tafluprost 0.0015% vs. Timolol 0.1% Preservative-Free in Ocular Hypertensive and in Primary Open-Angle Glaucoma Patients: A Cross-Sectional Study Rolle, Teresa Both therapy: show alterations in corneal microstructure but no side effects on tear function. Retrospective, single-masked, observational, cross-sectional study 108 Outpatient 1 HRT II-RCM Basal EC density Stromal reflectivity (keratocytes activation) No. sub-basal nerves, Sub-basal nerve tortuosity, Sub-basal nerve reflectivity, Endothelial cell density. Tafluprost: higher OSDI score, basal EC density, stromal reflectivity, sub-basal nerves tortuosity, and less number of sub-basal nerves than control Timolol: higher OSDI, basal EC density, stromal reflectivity, and sub-basal nerve tortuosity, less no. of sub-basal nerves than controls. Only examine the central cornea, Retrospective nature IVCM of Conjunctiva as a Predictive Tool for the Glaucoma Filtration Surgery Outcome Mastropasqua Preoperative DCD, GCD, SMR are parameters correlated with filtration surgery outcome, with DCD presenting the strongest correlation Prospective, single-center, case-control 81 Outpatient 2 (baseline, 12 months) HRT III-RCM Conjunctival DCD, GCD, SMR 12 month IOP reduction negatively correlated with baseline DCD and SMR and positively with GCD IVCM of the conjunctiva may represent an imaging tool to predict the surgical success in glaucoma. SMR is arbitrary. Unsure if DCD, GCD, and SMR are different before therapy between groups. Possible normal interindividual variability in DCs and GCs, and in the stromal density of conjunctiva Uveo-Scleral Outflow Pathways after UCCC in Refractory Glaucoma Mastropasqua UCCC induced modifications of sclera and conjunctiva structures Prospective interventional, case-control study 44 Outpatient 2 (baseline, 1 month) HRT III-RCM Area of conjunctival microcysts (MMD: cysts/mm2; MMA: µm2) at IVCM MMA and MMD increased in both groups of UCCC (4 s and 6 s), with values higher in 6 s UCCC Cases and controls differ because controls did not have refractory glaucoma due to ethical concerns; Did not evaluate the intra-subject agreement. In Vivo Distribution of Corneal Epithelial DCs in Medically Controlled Glaucoma Patients (MCGP) Mastropasqua DCs increase in the entire cornea, with a higher density at the limbus, may induce glaucoma-related ocular surface disease Retrospective observational study 80 Outpatient 1 HRT III-RCM Limbal and central DC density, DCs morphology and distribution. DC density is higher in glaucoma & DED than in controls DC density is higher in patients taking preserved than patients taking PF drops DC density correlated with staining Retrospective nature; Did not investigate other corneal features such as sub-basal nerve plexus or the superficial epithelial layers. The Ocular Surface after Successful Glaucoma Filtration Surgery Agnifili Whole ocular surface system objectively improved after completely successful glaucoma filtration surgery. Prospective case-control study 54 Outpatient 2 (baseline, at 6 months) HRT III-RCM GCD, limbal DCD, SCNI; MGD, MGI, and HLA-DR positivity. At the 6th month, surgical group: GCD increase, and limbal DCD, SCNI, MGI, HLA-DR, OSDI decrease OSDI correlated with GCD, MGI, SCNI, limbal DCD, & HLA-DR Cannot ascertain whether changes are due to drug discontinuation, topical steroids, or both. Did not analyze structural corneal nerve parameters; MMC has a cytotoxic effect No MMC-independent glaucoma surgery as a comparison. Meibomian Gland Features and Conjunctival Goblet Cell Density in Glaucomatous Patients Controlled With PTFCs Agnifili PTFCs were less toxic towards MGs and goblet cells compared with the L + T unfixed combination, with PF-BTFC presenting the most tolerated profile. Case-control cross-sectional study 90 Outpatient 1 HRT III-RCM MMAD, MMAA, InI, InAW, GCD IVCM documented lower GCD, MMAD, and MMAA, and greater InI and InAW in glaucoma patients compared with controls. Cross-sectional study Cannot provide MG and GC status before initiation of therapy. Possible unreported/transient ocular surface problems. Limited sample and for grouping. Conjunctival GCs in Medically-Controlled Glaucoma DI Staso Glaucoma therapy leads to a marked reduction of GCs Case-control, cross-sectional, non-interventional study 72 Outpatient 1 HRT III-RCM GCD GCD was reduced in both glaucoma groups and those with DED compared to healthy controls, markedly lower in group 2 compared to group 1. GCD was not different between DED and group 2. Negative correlation between GCD with OSDI and with TBUT Did not allow evaluation of the racial differences in the GC population. Baseline GC before therapy unavailable, Did not consider patients controlled with three medications. DCD: dendritic cell density; DED: dry eye disease; EC: epithelial cell; GC: goblet cell; GCD: goblet cell density; InAW: inhomogeneity of acinar wall (InAW); InI: inhomogeneity of glandular interstice; MCGP: medical controlled glaucoma patients; MMC: mitomycin-C; MMD: mean microcyst density; MMA: mean microcyst area; MMAA: mean Meibomian acinar area; MMAD: Mean Meibomian acinar density; MG: meibomian gland; MGD: meibomian gland density; MGI: meibomian gland inhomogeneity; PF: preservative-free; PTFCs: Prostaglandin/Timolol Fixed Combinations; OSDI: ocular surface disease index; SCNI: sub-basal corneal nerve inhomogeneity; SMR: stromal meshwork reflectivity; TBUT: tear break-up time; UCCC: Ultrasonic Cyclocoagulation. jcm-11-02349-t006_Table 6 Table 6 Studies on Inflammation-Related Dry Eye. Area of Study Authors Main Contribution to Literature Design Sample Size Participants No. of Visits HRT Main Outcomes Main Findings Limitations DED with and without chronic GVHD Kheirkhah A Only study concludes that symptomatology may be linked to local disease rather than the underlying systemic disease. Retrospective, cross-sectional 52 Outpatient 1 HRT III-RCM Corneal epithelium DC density Corneal sub-basal nerves Conjunctival EICs No significant differences in IVCM parameters for both groups. GVHD group treated with anti-inflammatory medications, lowering inflammatory changes. Corneal features in ocular GVHD Tepelus TC IVCM revealed distinct microstructural changes in the corneas of patients with oGVHD and DED Cross-sectional, observational 33 Population 1 HRT III-RCM Epithelial cell density SNP (nerve density, tortuosity, reflectivity) DC density Superficial EC density, basal cell density are lower in oGVHD and DED groups, with a significant difference in the former results (oGVHD lower). Nerve fiber density and nerve reflectivity were higher in decreased in oGVHD only. Cross-sectional study cannot prove causation. Limited patients in the oGVHD group. Treatments not standardized Association between Meibomian Gland Atrophy and Corneal Sub-basal Nerve Loss in Chronic Ocular GVHD O Dikme tas Patients with chronic GVHD are at high risk for developing DED and MG dysfunction. In chronic GVHD-related DED, MG loss does not appear to be a significant factor for corneal sub-basal nerve damage. Cross-sectional 50 Outpatient 1 Confoscan 4, Nidek, Japan Corneal sub-basal nerve densities Meibography scores Chronic GVHD had worse meibography scores, reduced corneal sub-basal nerve plexus densities, lower TBUT scores, lower Schirmer I values and higher corneal staining scores Corneal sub-basal nerve densities of patients with GVHD did not correlate with meiboscores but showed a weak correlation with Schirmer I test values. Small sample size No separate group for non-GVHD dry eye patients. Face Mask-Related Ocular Surface Modifications During COVID-19 Pandemic Mastropaqua The use of FM increases ocular surface inflammation and negatively impacts the quality of life in patients with DED. Prospective 128 Outpatient 2 (baseline, 90 days) HRT-RCM CDCD GCD DCD significantly increased in prolonged wear, whereas GCD did not significantly change. No controls not using FMs. Short-term study Long-term studies may reveal FM-related GCD changes. Ocular Surface, Meibomian Gland Alterations, and Cornea changes in Chronic Cigarette Smokers. Ağın Corneal nerve changes are found in chronic smokers. Smoking has an adverse effect on ocular surface parameters Cross-sectional case-control 100 Outpatient 1 Confoscan 3.0 (Nidek) Basal EC density, anterior and posterior keratocytes, endothelial cell density, long and total sub-basal nerve numbers Decreased corneal basal epithelium, anterior and posterior keratocytes, endothelial cell density, meibomian gland density, and sub-basal nerve numbers in chronic smokers. Systemic concentrations of cigarette toxic substances are not assessed in the blood, unclear whether ocular alterations due to systemic effects or direct damage from smoking. UV Damage to the Anterior Ocular Surface Grupcheva Summer sun exposure leads to changes in the cornea, bulbar and palpebral conjunctiva Prospective 400 Outpatient 2 (baseline, 1 year) HRTII-RCM No and area of cystic changes Characteristic cystic lesions with dark centers and bright borders in only 25 eyes (6%) before and affecting 118 eyes (29.5%) after summer. The total area of the cysts after the summer increased fivefold. Same population used as a control—may not have adequate time for washout of effects CDCD: Corneal DC density; EC: epithelial cell; GCD: goblet cell density; GVHD: graft versus host disease; SNP: sub-basal nerve plexus. jcm-11-02349-t007_Table 7 Table 7 Studies on CL-Related Dry Eye. Area of Study Authors Main Contribution to Literature Design Sample Size Participants No of IVCM HRT Main Outcomes Main Findings Limitations Corneal Alterations of New Hybrid CL in Advanced Keratoconus Dikmetas Hybrid CL: no adverse effects on corneal endothelial cells in advanced keratoconus. Retrospective study 32 Outpatient 2 (baseline, at 6 months) IVCM; Confoscan4; Nidek Corneal endothelial cell density No significant reduction in epithelial cell density noted at the 6-month compared to baseline after wear Retrospective design, limited sample size, no control group did not study nerve alterations CL Wear on Corneal Epithelial DC Distribution, Density, and Morphology Golebiowski Density, distribution, and morphology of CEDC do not differ in established CL wearers Investigator-masked cross-sectional observational pilot study 40 Outpatient 1 HRTII-RCM Corneal epithelial DCs Relatively lower density of corneal epithelial DCs in the central cornea of younger patients may allude to a more naive immune status in lens wearers Small sample size Microstructural Evaluation of Mucin Balls and Relations to Corneal Surface Grupcheva Mucin balls affect the corneal surface, including both epithelial disintegration as well as keratocyte “activation”. Prospective case-control study 42 Outpatient 2 (baselined at 28 ± 2 days HRT III-RCM Appearance and size of the mucin balls Qualitative analysis of shape (round, elliptical, and irregular), reflectivity (bright, homogenous and dark, heterogonous). Negative correlation between the size of balls and impact on basal epithelium morphology and “activation” of anterior stroma in adjacent areas Small sample size Silicone Hydrogel CL Wear and Corneal Sub-basal Nerve Plexus. Kocabeyoglu Sensory adaptation to CL wear is not mediated through sub-basal nerve or reduction of corneal tactile sensitivity in CL-naive users. Prospective longitudinal study 40 Outpatient 2 (baseline, 6 months) Confoscan 3.0 (Nidek, Vigonza, Italy) Corneal sub-basal nerve densities mean total sub-basal nerve fiber length, mean total sub-basal nerve branch density, or the mean long nerve fiber density No significant changes in outcomes at 6-month follow-up in CL users. Small sample size CL-Related Complications Li, Weiwei Complications related to CL wear-most common is dry eye, then SPK Retrospective 141 Outpatient 1 Not specified Visualizing Acanthoemoeba cysts, examining meibomian glands No cysts found. Meibomian glands described Mild or asymptomatic complications not observed Only one hospital Changes in Tarsal Conjunctiva Associated With Ocular Symptoms and CL Wear López-de la Rosa Soft CL wear modifies papillae of epithelial-lamina propria junction into a more rounded shape; however, CL cessation appears to resolve this alteration. Retrospective 92 Outpatient 1 HRT III-RCM Papillae density, shortest diameter, longest diameter, area, circularity, lumen/wall brightness ratio, irregularity, reflectivity, inhomogeneous appearance of the wall, and inhomogeneous appearance of rete ridges CL wearers, compared to previous wearers and non-wearers, showed higher circularity. Subjects with symptoms, compared to asymptomatic participants, showed higher circularity and lower irregularity Retrospective nature of study, 2 different questionnaires used for CL wearers and non-CL-wearers, CL material type not controlled Changes in Corneal Sub-basal Nerve Morphology and Sensitivity During OK Lum, Edward Alterations in corneal nerve morphology occur rapidly with OK and underpin functional sensitivity loss. Nerve fiber orientation provides an index for changes in corneal nerve morphology. Prospective case-control study 39 Outpatient 3 (baseline, D30, D90) HRT II RCM NFD GNFO In the central cornea, both NFD and corneal sensitivity decreased by Day 30, 90. Reduced NFD is associated with reduced corneal sensitivity. In the mid-peripheral cornea, GNFO rotated clockwise on Day 30, with further rotation on Day 90. Corneal sensitivity reduction plateaued by Day 30. Difficulties in locating the same exact corneal location with IVCM at multiple visits for each subject, leading to a potential sampling error Long-Term Impacts of OK on SNP and Corneal Sensitivity Responses and Their Reversibility Nombela-Palomo Long-term OK treatment led to reduced SNP nerve density, directly correlated with corneal tortuosity. After one month of treatment interruption, nerve density was still reduced. Prospective case-control study 47 Outpatient 3 (baseline, one year, one month after removing lens) Not specified SNP OK wearers: reductions in SNP density and no. of nerves in the central and mid-peripheral cornea Increased central objective tortuosity After lens removal for 1 month, baseline nerve density was not recovered. One year: Increased mid-peripheral Langerhans cell density, Increase in mid-peripheral nerve tortuosity. Small sample size Subclinical Inflammation of the Ocular Surface in Soft CL Wear Saliman Daily disposable CL produces minimal subclinical inflammatory response vs. no lens wear over 1 week. Prospective, longitudinal, observational 20 Outpatient 6: 3 dispensing, 3 follow-up visits HRT III/RCM DC density DC morphology All metrics increase in reusable lenses (A2 and AO), while only 3 of 6 IVCM parameters increase in daily disposable group. Small sample size Corneal Health during Three Months of Scleral Lens Wear Tse V Scleral lens wear for 3 months does not affect corneal epithelial barrier function, nerve fiber, and DC densities Prospective, longitudinal, observational 27 Outpatient 3 (baseline, 1, 3 months) HRT-RCM Corneal epithelial permeability DC density Corneal Nerve Fiber Morphology Endothelial Cell Density No differences between CL solutions. No changes after 1 and 3 months of CL use. No comparison with patients who did not have a scleral lens or other lens types. Impact of Lens Care Solutions and Daily Silicone Hydrogel CL Wear on Cornea Epithelium Zhang XL IVCM can detect epithelial cellular changes during CL wear Prospective, investigator masked, cohort study 274 Outpatient 2 (baseline and at 5 months) ConfoScan4 (Nidek) Morphologic differences (hyper-reflectivity) in the superficial ECs and epithelial basal cell density Hyper-reflective superficial ECs associated with PHMB preserved solution; decreased basal EC density associated with bacterial bioburden. No washout period prior to study entry Corneal DC and Sub-basal Nerve in Long-Term CL Wear Liu Q IVCM enabled direct observation of increased corneal DC and correlated with loss of SNP. 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==== Front Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells11091578 cells-11-01578 Review Glatiramer Acetate Immunomodulation: Evidence of Neuroprotection and Cognitive Preservation https://orcid.org/0000-0002-6612-6357 Kasindi Arielle 1 Fuchs Dieu-Trang 1 Koronyo Yosef 1 Rentsendorj Altan 1 Black Keith L. 1 https://orcid.org/0000-0003-2864-8442 Koronyo-Hamaoui Maya 12* Gozes Illana Academic Editor Sayas Carmen Laura Academic Editor 1 Department of Neurosurgery, Maxine Dunitz Neurosurgical Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; arielle.kasindi@cshs.org (A.K.); dieu-trang.fuchs@cshs.org (D.-T.F.); yosef.koronyo@cshs.org (Y.K.); altan.rentsendorj@cshs.org (A.R.); keith.black@cshs.org (K.L.B.) 2 Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA * Correspondence: maya.koronyo@csmc.edu 07 5 2022 5 2022 11 9 157822 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/). Novel, neuroprotective uses of Copaxone (generic name: glatiramer acetate—GA) are being examined, primarily in neurological conditions involving cognitive decline. GA is a well-studied synthetic copolymer that is FDA-approved for immune-based treatment of relapsing remitting multiple sclerosis (RRMS). Clinical studies have explored the potential mechanism of action (MOA) and outcomes of GA immunization in patients. Furthermore, results from these and animal studies suggest that GA has a direct immunomodulatory effect on adaptive and innate immune cell phenotypes and responses. These MOAs have been postulated to have a common neuroprotective impact in several neuroinflammatory and neurodegenerative diseases. Notably, several clinical studies report that the use of GA mitigated MS-associated cognitive decline. Its propensity to ameliorate neuro-proinflammatory and degenerative processes ignites increased interest in potential alternate uses such as in age-related macular degeneration (AMD), amyotrophic lateral sclerosis (ALS), and Alzheimer’s disease (AD). Preclinical studies are exploring less frequent subcutaneous administration of GA, such as once weekly or monthly or a single dosing regimen. Indeed, cognitive functions were found to be either preserved, reversed, or improved after the less frequent treatment regimens with GA in animal models of AD. In this systematic review, we examine the potential novel uses of GA across clinical and pre-clinical studies, with evidence for its beneficial impact on cognition. Future investigation in large-size, double-blind clinical trials is warranted to establish the impact of GA immunomodulation on neuroprotection and cognitive preservation in various neurological conditions. Copolymer-1 (Cop-1) glaucoma Parkinson’s disease Huntington’s disease experimental autoimmune encephalomyelitis AD retinal inflammation optic neuropathy cerebral ischemia neuropsychology National Institutes of Health (NIH)NIA R01AG056478 NIA R01AG055865 AG056478-04S1 The Haim SabanThe Tom Gordon Private FoundationsCSR 20847 The authors acknowledge funding support from the National Institutes of Health (NIH) grant numbers NIA R01AG056478, NIA R01AG055865 and AG056478-04S1 (M.K.-H.). This work was also supported by The Haim Saban and The Tom Gordon Private Foundations (CSR 20847) (M.K.H.). ==== Body pmc1. Introduction The synthetic immunoactive copolymer glatiramer acetate (GA; formula C25H45N5O13), branded Copaxone (also known as Copolymer-1 or Cop-1), is comprised of four amino acids in random order, resembling myelin basic protein (MBP) [1]. MBP is highly expressed during central nervous system (CNS) damage, specifically in autoimmune and/or inflammatory states such as multiple sclerosis (MS) or central degeneration [2]. GA was first synthesized in 1967 to induce experimental autoimmune encephalitis (EAE) in murine models of relapsing remitting multiple sclerosis (RRMS) [3]. Unexpectedly, GA was found to reduce signs and progression of EAE in these models [1,3]. Rather than inducing an autoimmune disease, GA was found to serve as a weak agonist to myelin-derived proteins and induce regulatory and protective neuroimmune responses [4,5]. Thus, GA was translated to clinical trials and was approved for use as an RRMS treatment in 1996 [6]. Multiple sclerosis (MS) is an inflammatory, demyelinating disease of the CNS with a prevalence of >1% in North America and Europe, and 0.002% in Eastern Asia and sub-Saharan Africa [7]. RRMS, a subtype of MS, accounts for around 85% of MS cases worldwide [7]. It is characterized by asymptomatic periods followed by a relapse or reoccurrence of symptoms [8]. Current treatments for RRMS include Interferon-β (IFN-β), S1P inhibitors such as fingolimod, monoclonal antibodies such as natalizumab, and anti-CD20 therapies (rituximab, ocrelizumab, ofatumumab) [5]. IFN-β is an immunomodulatory drug, and fingolimod also acts on the immune system by inhibiting peripheral lymphocytic egress [5]. Although IFN-β is immunomodulatory and a first-line RRMS therapy option, like GA, it has not been shown to enter the brain parenchyma or spinal cord and have a direct effect in the CNS. Instead, it is believed to express an indirect immunomodulatory effect in the CNS [9]. Natalizumab, a second-line agent, is a recombinant IgG4 monoclonal antibody which blocks the α4 subunit of integrin on leukocytes, preventing leukocytes from entering the CNS [5]. Fingolimod and Natalizumab are newer drugs often used as second-line agents to treat RRMS due to their extensive side-effect profiles. Despite this broad range of therapy options, both novel and established, GA remains a first-line immunomodulation therapy option for RRMS due to its effectiveness and generally low side-effect profile [7]. However, recent studies are beginning to examine the full scope of GA’s immunomodulatory effects as well as its potential to ameliorate various aspects of RRMS and other neurological diseases. Most notably, studies are exploring the potential for GA to protect from cognitive decline. This paper aims to provide a comprehensive review of studies investigating novel applications and uses of GA in various neuroinflammatory and neurodegenerative processes, including age-related macular degeneration (AMD), Alzheimer’s disease (AD), cerebral ischemia, amyotrophic lateral sclerosis (ALS), neuropsychological conditions, glaucoma, Parkinson’s disease (PD), and Huntington’s disease (HD), and its potential impact on cognition. 1.1. Mechanism of Action Although GA remains an established agent for treating RRMS and its disease course [6], its exact mechanism of action is not fully understood. However, to have a clear understanding of its known and hypothesized roles in RRMS, it is important to understand the pathophysiology of the disease. Multiple sclerosis is an autoimmune disease in which CD4+ autoreactive T cells target myelin and mount an inflammatory response in central neurons causing demyelination which leads to neurological deficits [9]. Various immune cell lines and inflammatory mediators are implicated in the pathophysiology of the disease. These include multiple derivatives of T cells, B cells, antibodies/autoantibodies, monocytes, macrophages, cytokines, and resident CNS immune cells such as microglia [10]. The impact of GA on CNS tissues as well as on peripheral immune cells is under investigation, with new properties of this agent being discovered. It has been extensively shown that one principal mechanism of action of GA is on the adaptive immune response [11]. Specifically, as GA resembles MBP, it has been found to competitively and antagonistically binds to major histocompatibility (MHC) II complexes, thereby blocking and/or displacing myelin antigens from presenting to T cells [12,13]. GA further exerts its effects by altering the differentiation of T cells—preferentially stimulating T-helper 2 (Th2) over T-helper1 (Th1) cells [14]. Th1 cells are critical for effective immune responses against acute infection, injury, and tissue damage, and are responsible for inducting the innate cellular immune and phagocytic responses. Th1 cells are typically also implicated in the pathogenesis of autoimmune processes [15]. Th1 cells’ function includes the release/stimulus of proinflammatory cytokines including interleukin- 12 (IL-12) (inhibits Th2 cells, increases macrophages), IL-18 (induces IFN-γ, monocytes, macrophages, and dendritic cells), IFN-γ, and TNF-α [16]. T-helper 17 cells (Th17) are also known to induce an inflammatory immune response via proinflammatory cytokines such as IL-17 and INF-γ. A 2020 study examined the potential effects of GA against CD4+ Th17 cells and the cytokines they produce. Results from these in vitro experiments show that GA is successful in suppressing and/or decreasing Th17 cells and their associated proinflammatory signaling pathways [17]. Moreover, Th1 and Th17 cell subtypes both exert proinflammatory responses and are involved in tissue injury [13,17]. Conversely, Th2 cells have an anti-inflammatory response. GA-specific Th2 cells can cross the blood–brain barrier (BBB) and release anti-inflammatory and protective cytokines such as IL-4, IL-5, IL-10, TGF-β, and IL-13, all of which can terminate an immune response and mediate tissue repair and regeneration [15]. Interestingly, studies have demonstrated that GA-activated Th2 cells increase the secretion of protective neurotrophic factors including insulin-like growth factor-1 (IGF-1), IGF-2, and brain-derived neurotrophic factor (BDNF) [18,19,20]. Additionally, in RRMS patients, GA is shown to elevate the prevalence and function of T regulatory (Treg) cells as well as activation of FOXP3, a gene which helps regulate the immune system. Treg cells have an immunosuppressive effect which leads to immune regulation and homeostatic maintenance [16]. Similarly, B regulatory cells (Breg) suppress autoimmune pathologies, pathogenic T cells, proinflammatory cytokines and stimulate/produce anti-inflammatory cytokines IL-10, IL-35, and TGF-β. Both Treg and Breg cells’ regulatory effects on the immune response lead to self-tolerance and/or immunological tolerance. GA was additionally found to downregulate granulocyte–macrophage colony-stimulating factor (GM-CSF), which typically functions as a cytokine by stimulating granulocytes and monocytes. A downregulation of GM-CSF was correlated with an elevation in IL-10, Th2 cells, Treg cells, and Breg cells [16]. Recent studies have found that GA has broader immunomodulatory effects on both central and peripheral immune systems [21]. Importantly, in MS patients treated with GA, monocytes were seen to cross the BBB into the brain parenchyma and differentiate into immunoregulatory macrophages [12]. GA is shown to increase and augment the phagocytic activity of monocytes, both in vitro and in vivo [22]. These experiments found an in vitro phenotypic shift from CD14+CD16− monocytes to CD14+CD16+ monocytes, or intermediate monocytes, which have higher phagocytic activity. Specifically, GA’s effects lead to enhanced recruitment of protective monocytes and directly modulated microglia as well as an increase in IL-10 and a decrease in TNF-α [22,23]. Overall, GA promotes and improves phagocytic activity of monocytes and microglia towards myelin debris [13,22,23]. Thus, GA has been shown to impact the phenotype of myeloid cells, including monocytes and microglia, within the periphery and cerebral microenvironment [18,22,24,25]. One cytokine that has been explored more thoroughly in pre-clinical and clinical studies in relation to RRMS and GA is IL-1/IL-1β and IL-1 receptor antagonist (IL-1ra). IL-1ra is a naturally occurring inhibitor of the proinflammatory cytokine, IL-1. Previous studies have hypothesized the possibility of targeting IL-1ra in inflammatory and autoimmune disease therapies [26,27]. Studies found that IFN-β, an alternative therapy for RRMS, was able to modulate the serum levels of IL-1ra which were within normal range in remitting phases, elevated during exacerbations, and elevated after 6 months of IFN-β treatment [27]. More recent studies explored GA’s effect on IL-1β and IL-1ra [10,26]. IL-1β, alongside various cytokines such as IL-19, IL-6, and TNF-α, is known to initiate the innate immunity and is a key mediator of the immune response [10]. In an animal model of RRMS, increased IL-1ra levels were shown to improve disease outcomes. Importantly, in this study, GA was shown to strongly diminish IL-1β expression and enhanced IL-1ra [26]. GA has also been shown to inhibit a very specific receptor, purinergic P2X7 ionotropic receptor (P2X7R), which is found to be increased in inflammatory states, specifically MS. P2X7R is a receptor expressed on monocytes and microglia and is imperative in the activation and proliferation of microglia, potentially leading to destructive, repetitive neuroinflammation and tissue damage. It is also associated with the production of several cytokines responsible for initiating the innate immune response. This clinical study examined GA’s potential effects against this receptor, and it found that GA downregulated P2X7R and its associated inflammatory effects [10]. Although counterintuitive, microglial inflammation is an important negative regulator of the neurogenic microenvironment, as microglia uniquely can both support and interfere with synaptic and neuronal processes [28]. How microglial cells respond to their environment can be influenced by several different factors, not all of which are fully understood. Depending on the environment, GA has been shown to enhance the proinflammatory effects on monocytes in the periphery as well as induce phenotypic shift of brain microglia to both the pro- and anti-inflammatory profiles [18]. For example, GA displayed a direct modulation of microglia cells, leading to phagocytosis [23]. Additionally, there is a bystander expression of anti-inflammatory cytokines such as IL-10 and TGF-β by resident astrocytes and microglia. In fact, there are several central outcomes seen with GA administration beyond phagocytosis of myelin debris. GA is shown to augment remyelination, improve axonal length, increase proliferation of oligodendrocyte progenitor cells, and increase proliferation and differentiation of neuronal progenitor cells [13]. Importantly, GA does not appear to suppress the peripheral immune response as so many Disease Modifying Therapies (DMT) typically do. Instead, this copolymer appears to have an immunogenic effect and enhances the protective peripheral and central immune responses [11]. Studies have demonstrated that a complete suppression of the immune system is not productive for long-term neuronal health [29]. In fact, recent reports have shown that this can later lead to exacerbations of neurodegenerative disease progression in the brain [18]. GA-mediated autoreactive T cells have expressed protective autoimmunity within the brain parenchyma leading to neuroprotection [9]. GA is currently administered subcutaneously at 20 mg daily or 40 mg thrice weekly. This regimen allows for immunomodulation, inflammatory suppression, and peripheral tolerance [13]. Interestingly, this regimen is well-tolerated in RRMS outcomes but not in other disease states in which GA’s role is being explored [13]. 1.2. Current and Potential Uses of Glatiramer Acetate As it affects separate aspects of the immune system, GA is a suitable option for targeting several components of MS pathogenesis, and perhaps other neuro-inflammatory conditions [25,29]. Emerging studies are gaining a new understanding of GA’s mechanism of action—one that is not just immunogenic or immunomodulatory but also includes a neuroprotective effect [30]. These effects are believed to be exerted in a multitude of ways including reduction in CNS injury by modifying innate and adaptive immune cell phenotypes. These in turn can lead to prevention of demyelination, inhibition of motor neuron loss, protection against ischemic changes and reduction in scar tissue formation, as well as elevated secretion of neurotrophic factors promoting synaptogenesis and neurogenesis [31,32]. Indeed, GA may aid in resolving both acute and chronic neurodegenerative lesions by enhancing neurogenesis and synaptic plasticity [32,33]. More specifically, studies have demonstrated that GA-activated Th2 cells increase the secretion of insulin-like growth factor-1 (IGF1) and brain-derived neurotrophic factor (BDNF) [18,19,20]. BDNF is critical for neuronal and glial cell differentiation and survival and for axonal protection. It can restrict neuronal damage and promote repair [19,20]. Interestingly, BDNF has been tightly linked with cognitive function and studies show that there are lower levels of BDNF in the brains of MS patients, which is hypothesized to be correlated to MS-related cognitive deficits [34,35]. These new findings are most relevant for the potential of GA to exert neuroprotection and preservation of cognitive function in various neurodegenerative and neuroinflammatory conditions. This is a novel concept that is on the forefront of current research. In this review, we cover findings from numerous pre-clinical and clinical studies utilizing GA under various neurodegenerative conditions. 2. GA in Clinical Trials 2.1. Role of GA in Preventing Cognitive Decline in Multiple Sclerosis Since GA is known to have therapeutic effects in MS, other aspects of the disease beyond the inflammatory progression were examined. As previously mentioned, BDNF levels in the brain have been proven to be significantly lower in individuals with MS and have been associated with brain atrophy and cognitive impairment [34]. Indeed, there are a growing number of studies suggesting that GA has protective effects on cognitive functioning. Twelve clinical trials were conducted, all of which utilized several assessments to ascertain the link between GA and neurocognitive protection and improvement, as summarized in Table 1. GA’s effect on both motor function and cognition were analyzed. The expanded disability status score (EDSS) [36], a test that approximates the degree of MS-related motor dysfunctionality via ambulatory status, was frequently used to correlate cognitive findings to disease state. Table 1 delineates the various outcomes of these twelve clinical studies in MS patients following GA treatment. The results of several assessments showed improvements in physical disability, higher reported quality of life, and reduced levels of fatigue and stress [45,46,47,54]. Additionally, GA showed signs of enhanced information-processing speed and working memory [42,52]. In fact, multiple aspects of memory, including short-term, working, and long-term, were preserved in GA-treated test subjects across three studies [49,50,52]. MS is not only linked to a decline in cognitive processes such as memory, executive functioning, and comprehension but also to psychological issues, primarily depression [55]. Studies have found that depression and its concomitant conditions significantly affect MS patients [55]. Despite this, there are few standardized approaches to diagnose and treat MS-related depression [56]. However, in four out of twelve studies analyzed, GA was found to decrease depression rates in MS and displayed a reduction in comorbidities associated with MS and depression, such as fatigue [45,46,50,52]. Eight of the twelve studies analyzed found GA-driven improvements in multiple cognitive domains including comprehension, evaluation, and analysis of complex situations, and synthesis of appropriate responses [42,45,46,47,49,50,52,54], revealing a possible correlation between GA and cognition. Across these studies, GA administration was linked to mild and/or moderate amelioration of cognitive decline in memory, fatigue, evaluation of new information, processing time, critical thinking, synthesis of novel concepts, decision making, and application of ideas [42,45,46,47,49,50,52,54]. This finding is in line with the proposed neuroprotective effects of GA to reestablish neuroplasticity and reverse degenerative and inflammatory lesions [25]. Despite these findings, it should be argued that the data represent modest improvements in cognitive decline in MS and does not show a definitive link between GA and cognitive preservation or improvement. However, it is important to ascertain the research design and methodology utilized to obtain the data. The studies employed various cognitive assessments. Only two studies utilized standardized assessments which can be applied to the general population, such as the Montreal cognitive assessment (MoCA), the Beck depression inventory (BDI) and Center for Epidemiological Studies Depression scale (CES-D) [57,58,59]. The rest of the studies utilized assessments which are specific to MS patients, including: multiple sclerosis inventory of cognition (MUSIC), multiple sclerosis functional composite (MSFC), modified fatigue impact scale (MFIS), fatigue impact scale (FIS), multiple sclerosis impact scale (MSIS-29), functional assessment of multiple sclerosis (FAMS), Brief International, Cognitive Assessment for Multiple Sclerosis (BICAMS), and multiple sclerosis quality of life (MSQoL)-54 [60,61,62,63,64,65,66,67]. These MS-specific assessments have a skewed perspective and fail to consider multifactorial components of cognitive decline, making it difficult to correlate these findings to generalized outcomes. When taking into consideration the limited scope of these assessments, it is worth contemplating the implications this has on future research of GA’s potential use. Additionally, many of these tests can be “learned”, meaning that once a participant is administered a cognitive assessment, they are able to retain some of the information and can perform better when given the test at a later time to track progression. Thus, participants’ performance might be artificially improved due to learning of the test and not actual improvements from the tested therapy. Unfortunately, most of the studies are observational and/or utilize a retrospective research design and have not examined real-time effectiveness of GA. For this reason, we performed statistical analyses of cognitive test outcomes amongst several study groups. A careful review was undertaken to identify studies that had utilized the same cognitive assessments and similar study designs of the GA studies. Participants in the studies were age-, sex-, and ethnicity-matched to the participants in the baseline GA study, as well as matched within disease-specific parameters including disease severity (per EDSS), years since disease onset, form of MS (RRMS exclusively), etc. The cohorts examined in these studies were healthy controls, non-GA-treated RRMS controls, and other treatment RRMS. IFN-β was commonly used as the “other treatment” since, like GA, it is utilized as a first-line therapy for RRMS, is also immunomodulatory and is considered an older drug in RRMS [68]. The extensive statistical analyses (one-way ANOVA, paired—between groups with the same participants, i.e., GA-treated—and unpaired post-hoc analysis, etc.) from the comparisons of these articles are displayed in Figure 1A–G. The figures graphically show these variations utilizing mean scores and standard error means to calculate group comparisons. Meca-Lallana et al. examined changes in GA-treated RRMS patients’ cognition over six months using three separate cognitive assessments: MSIS-29, MFIS, and the Work Productivity Activity Impact Questionnaire (WPAIQ) [47,69]. The MSIS-29 examines the physical, cognitive, and psychological impacts of multiple sclerosis on participants’ lives; Figure 1A displays the statistical analyses between three studies [62,70,71]. The results of cross-cohort comparisons between MFIS scores, a test for physical and cognitive fatigue, are displayed in Figure 1B [66,72,73,74]. FIS scores, an older version of the MFIS, were compared from four studies and the results are displayed in Figure 1C [64,73,75,76,77]. Group comparisons of WPAIQ scores, which represent disease impact on activity/productivity, are displayed in Figure 1D [69,78,79]. Natalizumab, a newer biologic medication often utilized in refractory/severe RRMS, was the alternative treatment in this comparison [80]. Importantly, there were stable patterns amongst the statistical analyses of scores from each of these cognitive tests. One commonality was that there was no significant change in INF-β-treated cohorts’ scores (or natalizumab in the WPAIQ) from baseline to completion of each study. Additionally, IFN-β and natalizumab treatment had no statistical improvement in scores as compared longitudinally to RRMS controls. This implies that alternative treatment for RRMS has no effect on cognition in these studies. When comparing RRMS controls to GA-treated participants longitudinally, GA participants had a statistically significant improvement in cognition, ranging from 33 to 46% improvement. In the WPAIQ, there was no significant difference between healthy controls and GA-treated RRMS patients after 6 months—conveying the potential for GA to improve scores to the level of healthy controls. Finally, the most substantial and remarkable trend amongst these cognitive tests was seen between RRMS patients’ scores at baseline and after 6 months of GA therapy. These same group comparisons had statistically significant improvements in mean scores of the MSIS-29, MFIS, FIS, and WPAIQ (p < 0.001, p < 0.001, p = 0.005, p = 0.002; Figure 1A–D). Cinar et al. examined the changes in BICAMS scores between RRMS patients after twelve months of GA use as compared to healthy controls and INF-β [50] but did not compare to non-GA-treated RRMS controls. Therefore, an additional article was reviewed that studied cognition in GA treatment naïve RRMS participants via the BICAMS test over 12 months [81]. The BICAMS is comprised of three tests that assess different cognitive domains. The California Verbal Learning Tests II (CVLT-II) examines the cognitive domains of verbal learning and memory; results are displayed in Figure 1E [82]. The Symbol Digit Modality Test (SDMT) tests short-term, visual, and working memory; results are displayed in Figure 1F [83]. The Brief Visuospatial Memory Test-Revised (BVMT-R) examines the cognitive domain of visuospatial memory; results are displayed in Figure 1G [84]. Across all three BICAMS tests, several trends emerged. For example, there was a nearly 50% difference in the average score decrease seen between healthy controls and RRMS controls (19–34%) and the decrease seen amongst healthy controls and GA RRMS patients (10–18%), meaning a smaller deviation from healthy controls following GA administration. Additionally, there was a statistically significant increase (21–25%) in mean scores between GA RRMS patients and naïve RRMS controls, with GA-12 months participants scoring 21–25% better on each cognitive test. Conversely, INF-β was shown to have similar trends in its effects on cognition as compared to GA. However, both INF-β and GA displayed improved cognition after 12 months of use. Specifically, there were highly statistically significant improvements in same group comparisons of GA at baseline and GA 12-months seen in each assessment, the CVLT-II, SDMT, and BVMT-R (p = 0.006, p = 0.003, p = 0.005). Overall, the findings from this meta-analysis display the propensity of GA to improve and/or preserve various cognitive domains when compared to healthy controls, RRMS controls, IFN-β therapy, and/or natalizumab therapy. Thorough statistical testing across multi-cohort studies repeatedly displayed cognitive improvements within GA-treated patients in longitudinal same group comparisons and when compared to other cohorts. To see GA consistently improve cognition, as compared to several cohorts, across multiple studies is promising for ongoing research. It is important to consider the scope of these cognitive changes associated with GA. A commonly held counterargument to the articles that found mild/moderate improvement in cognition with GA use is that GA has little or no effect on cognition [85]. Two articles compared GA to other established RRMS therapies and were unable to establish a statistically significant difference between the therapies’ effect on RRMS-related cognitive decline [86,87]. One study found that GA’s effect was similar to IFN-β in improving cognition and the improvements were mild [88]. An additional study found there was no measurable decline or improvement in cognition in the patient groups treated with GA, challenging GA’s potential effectiveness in protecting cognition [38]. Yet another study found that cognitive functioning was stable across ten years in GA-treated patients [40]. Findings such as these could be argued multiple ways. Either GA has no effect on cognition and there are no improvements with continued use, or alternatively, GA is protective against cognition deficit and can prevent decline seen in RRMS. Thus, multiple issues are presented when studying GA’s effect on cognition in RRMS. It is difficult to establish when cognitive decline occurs at disease onset, before disease onset, after disease onset, etc. [89]. Similarly, the natural history as well as pathophysiology of cognitive decline in RRMS needs to be considered and better understood when studying GA’s potential use. Previous and ongoing research examines these relationships with promising findings, such as correlations between MS plaques and cognitive decline [89]. However, more understanding is necessary to explore therapeutic options. Otherwise, it will continue to be difficult to ascertain how to target and track RRMS-related cognitive decline. It is imperative to understand the process and signs of cognitive decline in RRMS patients for accurate analysis of potential therapies’, particularly GA, effects on cognition. Overall, the understanding of GA’s use in cognition is complex—while some studies show statistically significant improvement, others show none. There are several reasons to consider why these discrepancies exist including the aforementioned cognitive assessments, the understanding of RRMS-related cognitive decline, and several other confounding variables. Although GA’s cognitive benefits are not robust or consistent across all studies, the fact that it was found is still noteworthy for future studies. Each of these studies consistently stated the need for further research into the role of GA in RRMS-related cognitive decline. The unique MOAs of GA, both neuroprotective and anti-inflammatory, are of great interest. With GA’s potential to improve/protect cognition, it is worth exploring alternative applications of GA. One of the most common first presenting symptoms of MS is ocular in nature: optic neuritis, which can cause significant vision problems. For this reason, studies have begun to examine the potential benefit of utilizing GA to treat ophthalmic pathologies related to MS. Optical coherence tomography (OCT) was typically utilized to assess retinal nerve fiber layer thickness (RNFLT) and total macular volume, two values that are typically found to be lower in MS patients with ocular signs/symptoms [90]. OCT findings revealed that there was an absence and/or reduction in retinal changes or damage after GA administration [38,40]. These studies found that GA had a beneficial, neuroprotective role in retinal axonal degeneration in MS. GA has been shown to improve MS-associated visual pathology, which is in alignment with the other established use of GA in both MS and ADM [51,53]. GA is already a well-established treatment option for RRMS [91]. The new understanding of GA’s mechanism of action describes an immune-driven protective effect in the central microenvironment against damage and degeneration [21]. The effects of GA are already known to improve MS-related inflammatory processes, resulting in amelioration of physical symptoms associated with the disease pathology [29]. However, as research continues this already well-established copolymer, new roles for its use are being discovered [30]. GA has been shown to not only be protective against inflammation, but also shows potential to have ameliorative effects in MS cognitive decline [25]. Even if these findings are mild, moderate, or inconsistent, it is an interesting concept that could give insight in future research endeavors into the use of GA in not only RRMS-related cognitive decline but other neuroinflammatory or degenerative states. 2.2. Therapeutic Roles of GA in Ophthalmic Disorders Beyond RRMS, GA has become a proposed therapy for the treatment of age-related (adult-onset) macular degeneration (AMD) [24]. AMD is a degenerative disease that occurs when drusen, waste products from retinal rods and cones, accumulate over time in the macula causing changes in central and color vision [92]. An animal model found that mice deficient in monocytes and/or macrophages developed hallmarks of AMD while a clinical trial similarly found a reduction in phagocytic activity in AMD patients [24,92]. Therefore, it was hypothesized that the depletion of monocytes and their phagocytic activity was part of the pathophysiological process of AMD. Monocytes and their phagocytic activity were studied in both in vivo and in vitro experiments. GA was found to enhance phagocytosis in classic monocytes (CD14+CD16−), and non-classic (CD14dimCD16+) monocytes in intermediate and advanced AMD. Additionally, non-classic and intermediate (CD14+CD16+) monocytes were significantly correlated with drusen area. The phenotypic heterogeneity of monocytes after GA immunization appeared to provide protection against drusen formation and reduced established total drusen area. Additionally, GA-mediated Th2 cells were shown to reduce retinal microglial cytotoxicity, likely induced by amyloid [24]. Another AMD study found a decrease in macular plaque formation [93]. One study also examined GA’s effect on cognitive decline in AMD and identified a decrease in cognitive impairment, which was attributed to the GA-induced brain neurogenesis and neuronal survival [94]. GA’s potential role in glaucoma was reviewed in an animal model as well as a clinical trial. Glaucoma has several forms and a multitude of suspected mechanisms of disease. However, it is generally understood that glaucoma occurs due to increased intraocular pressure causing retinal and optic nerve damage. A severe form of glaucoma, known as acute primary angle-closure glaucoma (APACG), occurs when there is an abrupt disruption of aqueous humor outflow causing a rapid increase in intraocular pressure, greatly increasing the risk of blindness [95,96]. A study in APACG patients found that GA administration was inversely correlated with disease progression. In this study, visual fields were improved [96]. Similarly, an animal model of glaucoma induced chronically elevated intraocular pressure in rats, which led to retinal ganglion cell death and optic nerve damage. This study found that GA induced neurogenesis, repressed retinal ganglion cell death, and attenuated functional decline in rats [95]. Overall, AMD and glaucoma studies identified that GA led to drusen reduction and amelioration of clinical signs related to disease progression, such as visual disturbances. Table 2 summarizes both animal models and clinical trials examining GA’s effectiveness in AMD and glaucoma. All the studies that were reviewed displayed a positive correlation between GA administration and improvement in disease progression and/or clinical symptoms. 2.3. GA Immunization in Amyotrophic Lateral Sclerosis (ALS) The only other neuropathological state that has moved to clinical human trials with GA is Amyotrophic lateral sclerosis (ALS). ALS is a motor neuron disease in which the specific mechanism of disease is not known but is thought to be due to inflammation and/or degeneration of motor neurons in the brainstem and spinal cord [97,98]. There are various known and suspected etiologies, with genetics being the most studied cause of the disease process [99]. Few completed human studies examining the effects of GA in ALS have been conducted. In these studies, participants with ALS were given 20 mg of GA either bi-weekly or daily [97,98]. Table 3 outlines the immunomodulatory outcomes of these clinical studies in ALS patients following GA treatment. These studies primarily examined GA’s immune cellular response, both centrally and peripherally [97]. GA was linked to a robust humoral response, leading to enhanced cytokine production [98]. Additionally, it was found that there was improved T-cell proliferation and increased levels of Th2 in these patients after GA administration as compared to controls [97]. The enhanced humoral response caused a preferential increase in anti-inflammatory cytokines [97,98]. Th2 proliferation and expansion also led to a similar anti-inflammatory response. Interestingly, one study found that changes in the dosage and frequency of GA, daily versus twice weekly, led to different outcomes [98]. Daily dosage was found to increase Th2 cytokines and IL-4 levels and diminish IL-10 levels while twice weekly regimens were associated with enhanced Th1 cytokines and IL-10 levels and diminished IL-4 levels. In fact, all the clinical trials had varying GA dosage and frequency depending on the disease state being studied. With this information, it is important to consider the potential need to alter the regimen of GA depending on disease type and state. For example, in the successful clinical trial in MS patients, GA immunizations were given either daily or three times weekly, potentially inducing immune tolerance to CNS antigens. In ALS or AMD patients, trials involving less frequent GA immunization regimens had more success [24,46,93]. It is worth citing another clinical study for which a regimen of 40 mg/day did not show any improvement in ALS patients [100]. This study underlines the importance of continued exploration of GA’s potential neuroprotective effects in multiple dosages, regimens, and disease states. 3. Preclinical Studies Using GA in Neurodegenerative Disease Models As the neuroprotective mechanisms of action of GA are better understood, more studies are being developed to identify its potential novel uses. Its unique mechanisms, while not fully understood, prove to be relevant in several other pathological states outside of MS. This is likely because GA has been shown to improve a broad range of immunocytes both centrally and peripherally. Recent animal studies have shown that increased levels of IFN-γ, which are associated with inflammatory autoimmune diseases, impeded neurogenesis (especially oligodendrogenesis). However, GA raised levels of IL-4 centrally, which then reversed the effects of IFN-γ [101]. IL-4, increased by GA, was also found to attenuate TNF-α production—an important aspect of protective immunity [29]. Overall, these findings in rodent models for neurodegenerative diseases concluded that GA enhanced neurogenesis and improved symptoms of several disease states, not just RRMS. Recent data continue to display overwhelming evidence of GA’s potential to reduce neuroinflammation, degenerative processes, synaptic and cognitive deficits, and psychiatric burden [31,95,102,103,104]. These findings allow for an expanded exploration of proposed GA uses in several other neurological disease states, including neurodegenerative processes such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD) as well as cerebral ischemia and psychological disorders. Some studies even show that if GA is given early in disease course or at onset, it may prevent cognitive decline [99,105].The exploration of the novel use of GA in other central pathologies is still in the early stages of pre-clinical trials/animal studies, allowing researchers to investigate changes in neural tissue after GA administration and correlate it to physical and behavioral exam findings. Early findings across multiple studies show promise for GA’s ability to mitigate disease progression and cognitive loss. 3.1. Effects of GA Immunization in EAE Murine Models of MS Alternative uses of GA in MS continue to be explored via animal studies. While it is well-established that GA works to reduce the inflammatory processes of MS, more information is needed on its other potential benefits. The cognitive effects of GA are beginning to be examined in clinical trials more regularly. However, animal studies continue to allow for neural tissue analysis and easier control of variables. Table 4 summarizes cognitive and motor outcomes of animal experiments in MS models following GA immunization. The induced experimental autoimmune encephalitis (EAE) mouse model, which replicates multiple sclerosis inflammatory progression, is commonly used [106]. EAE studies allow the assessment of long-term effectiveness of GA in MS. Several of these studies found that mice treated with GA had similar, or in some instances better, cognitive scores compared to naïve, healthy controls [102,111]. Improved cognitive testing scores were seen in various tests such as the Longa Score Scale (LSS), Cross-Maze Test (CMT), and Delayed Non-Matching to Sample T-Maze (DNMSTM) [112,113,114], implying that GA treatment conserved or even improved cognitive functions [107,110]. Specifically, these animal-model studies found, via histological examination of brain tissue, that GA alleviated neuroinflammatory and neurodegenerative damage to the frontal cortex and hippocampus [102,109,110,111]. Since the hippocampus and frontal cortex are both important in executive functions and memory, it stands to reason that a reduction in inflammation in these areas would lead to improved cognitive findings. Of note, the role of GA in downregulation of lymphocytic infiltration and reactive gliosis was positively correlated to the prevention of long-term neurological deficits [95,113]. After GA administration, astrocytes morphologically resembled their pre-inflammatory state, indicating the possibility of GA’s reversal of inflammatory effects and disease progression [102,109,111]. GA was found to greatly reduce neurological impairments, correlating to lessened cognitive decline, as displayed by improvements in motor as well as cognitive testing [107,109]. Additionally, neuroinflammation and neurodegenerative progression was slowed or even halted completely in some studies, as seen via laboratory tests such as flow cytometry and/or immunohistochemistry and electron microscopy [102,107]. These analyses showed a reduction in proinflammatory mediators and reduced signs of astrogliosis, oligodendrogliosis, inflammation, and destruction in the central microenvironment [102,109,110,111]. Due to its immunomodulation effects leading to neuroprotection, GA mitigated the clinical evolution of RRMS and provided disease stability [102,110]. Improvements were visualized in neuronal survival, axonal growth, remyelination, formation of new synapses, and axonal regeneration [95,106]. Furthermore, GA offered protection against memory decline, cognitive deterioration, and alleviated disability in established cases of EAE models [102,110,111]. GA prevented disease development and cognitive decline with a significant reduction in the pre-existing clinical manifestations in RRMS animal models [102,107,111]. Studies found that GA can not only prevent disease progression, but also conserves and/or enhances cognitive capacities. 3.2. Effects of GA in Animal Models of ALS Three studies were conducted with ALS disease mouse models examining the effect of GA immunization. Table 5 reviews cognitive and motor findings of these animal experiments. Several methods were utilized to induce an ALS disease state: via an artificial increase in levels of the defective human SOD1 gene, via facial nerve axotomy, or via crossbreeding SOD1 transgenic and non-transgenic mice [97,115]. In one study, motor neurons were examined after GA administration. The findings indicated that GA’s neuroprotective effects extended to motor neurons and motor activity. Specifically, both acute and chronic degeneration of motor neurons was prevented and/or improved. Additionally, GA-treated mice’s lifespan was significantly increased as compared to untreated controls [99]. However, in other ALS models, the findings were less promising. One study found that GA-immunized mice displayed improvements in motor function, with animals reaching approximately 10% of their pre-symptomatic motor activity and demonstrated a significant diminution in disease progression [116]. Importantly, although there were improvements in symptomatic aspects of the disease, the administration of GA did not change the outcome—lifespan was not extended [116]. Another study examined the utilization of TV-5010, a synthetic high-molecular weight polymer formulation of the same amino acids of GA. This study analyzed motor functions and muscle strength, with no significant improvements either [117]. Additionally, there were no appreciable improvements in lifespan in this experiment. However, the study utilized several different dosing regimens of TV-5010 with some variations in findings. This study utilized a synthetic polymer that is similar to GA and had different findings than other similar studies, so its results may or may not be applicable here [117]. Again, further research is needed to determine the optimal dosing regimens (quantity and timing) of GA. 3.3. Role of GA in Repair, Regeneration, and Cognitive Preservation in AD-Model Mice Neurodegenerative diseases are being thoroughly examined as potential targets for GA. Alzheimer’s Disease (AD) is a neurodegenerative disease characterized by chronic inflammation which alters amyloid β-protein (Aβ) metabolism, Aβ plaques and neurofibrillary tangles formation, leading to impairment of synaptic plasticity and cognitive function [118]. This may be the mechanism behind AD’s disease progression, presentation, and cognitive decline [119]. Numerous animal studies have been conducted examining the effects of GA on the degenerative processes associated with AD. Current research shows that AD has similarities to MS in the central degenerative and inflammatory processes [120]. Specifically, mitochondrial injury is typically part of the process causing degeneration of various central microstructures such as neurons, axons, and synapses [121]. Additionally, astrogliosis and microglial activation are very similar in MS (specifically RRMS subtypes) and AD [118,119,121]. Considering the similarities in pathophysiology between these diseases, several studies have been exploring the potential for GA to treat AD. Studies examining AD have found that the resident immune cells of the CNS are not sufficient in clearing Alzheimer’s-related inflammation and Aβ plaques. However, animal models show that GA-enhanced peripheral immune cells can cause central immunomodulation via elevation of protective anti-inflammatory cytokines [20]. Studies are also examining the potential role of the innate immune system response in targeting AD-associated Aβ accumulation and plaques [122]. The findings from these new and interesting studies could be very beneficial to the understanding of natural immune responses’ effects in neurodegeneration and how GA might be able to assist in this via immunomodulation. Since GA has been found to boost peripheral immune responses, studies have begun to examine GA’s potential use in AD, including the well-established APPSWE/PS1ΔE9 transgenic (ADtg) murine model of AD [123]. Cerebral recruitment of specific, protective monocytes is found to be induced by GA, specifically to Aβ lesion. The peripherally derived monocytes are highly active, with roles in Aβ degradation, immune regulation via secretion of anti-inflammatory cytokines and downregulation of proinflammatory cytokines, and neurotrophic support/neuroprotection [32]. GA immunomodulation was found to restore pre- and post-synaptic density and induce both synaptogenesis and neurogenesis, resulting in preservation of cognitive functions [124]. Table 6 summarizes cognitive and motor outcomes in animal experiments of AD models following GA administration. These studies found an increase in the Th2-derived regulatory anti-inflammatory cytokines Interleukin-4 (IL-4) and Interleukin-10 (IL-10), primarily around Aβ plaques, and a reduction in proinflammatory mediators (i.e., TNFα, IL-6) [31,104,105,125]. In fact, several studies found that there is an important role for GA-driven immunomodulation, affecting both the central and peripheral immune responses, leading to regulation and repair causing Aβ removal in AD models [31,32,95,124,126,127]. One study found that GA-activated central immune cells, such as microglia, degraded, engulfed, and cleared soluble fibrillar Aβ plaques [125]. Our group found that these GA-activated microglia, macrophages, and bone-marrow-derived monocytes (MΦBM) aided in degradation of Aβ plaques [32,124] and that GA promoted neuroprotective, phagocytic, pro-healing and anti-inflammatory phenotypes in macrophages [95]. The new phenotypes were associated with proliferation and survival of oligodendrocytes, preserved synaptic processes and increased levels of neural progenitor cells, showing signs of enhanced neurogenesis and neuroprotection [95,127]. AD animal models underwent thorough CNS analyses for AD-like pathology such as Aβ plaques. Neural tissue taken from the GA-treated ADtg mice displayed enzymatic degradation of Aβ plaques as well as reduction in and regulation of central inflammation [31,95,126,127,128]. All the observed ADtg had decreased Aβ42 levels, likely due to a GA-stimulated increase in macrophage-aided removal of the Aβ plaques [31,104,105,124,125,127,128]. Specifically, GA was shown to reduce Aβ depositions in the cerebral vasculature, retina, and parenchyma [18,104,105] and was linked to amelioration of AD signs, both in the cerebrum, the retina, hippocampus, brain cortex, and other parenchymal areas [105,124,126,129]. Additionally, levels of MMP9 protein, an enzyme known to degrade Aβ, were increased [31,32]. GA-enhanced immune cells reduced Aβ42 oligomers and protected the integrity of synapses and neuronal structure [31,124]. Substantial reductions in Aβ plaque burden were detected after GA immunizations [18,104,105,126,128]. Additionally, GA was found to induce neurogenesis, neuroplasticity, synaptoprotection and preservation, regeneration of the cortical microenvironment and eliminate highly toxic Aβ42 and Aβ40 oligomers [95,104]. GA induced monocyte recruitment and phenotype shift, causing a regulation of local inflammation and leading to a decrease in vascular and parenchymal Aβ plaque burden [18,124,127]. Similar to previous disease states, GA was found to enhance the expression of IFN-γ and the protective neurotrophic factors, BDNF and IGF-1 in AD [129]. Unlike findings from EAE animal models and RRMS clinical trials, weekly administration of GA was found to reduce Foxp3+ Treg levels. Moreover, studies found that GA’s immunomodulation efficiently cleared cerebral Aβ, diminishing astrogliosis and detrimental neuroinflammation [31,32,104,105,124,127,129]. Therefore, GA could mitigate AD’s effects since the drug is able to increase protective peripheral immune cells, modulate T-cell response, and aid in protection of the central microenvironment. Cognitive functioning was also examined, and a significant statistical decrease in cognitive deficits associated with AD was found. The increase in insulin-like growth factor-1 (IGF-1) that was detected in the brains of mice following GA immunization may further explain the enhanced neurogenesis and cognitive function in these mice. Interestingly, there was also evidence of improvements from baseline in cognitive functioning and protection against decline [31,32,96,101,102,123]. Importantly, GA was also associated with an improvement in cognition, demonstrating that GA has the potential to reverse cognitive decline [31,80,81]. Cognitive domains such as memory, learning, spatial memory, discrimination index and special recognition were assessed. This was performed utilizing various behavioral tests, such as the Longa Score Scale (LSS), Morris Water Maze Test, (MWMT), Radical Arm Water Maze (RAWM), and the Barnes Maze Test (BMT) [103,132,133,134]. Several studies found that rodents displayed stable and enhanced cognitive functioning [18,31,104,126,128,129]. GA protected against cognitive decline and preserved neurofunction, largely due to GA’s robust immunomodulatory and neuroprotective effects. Overall, these studies found that GA attenuated pathological and neurodegenerative processes in AD animal models. GA’s immunomodulation was linked to expansion of Th2-type cells and increased cerebral recruitment of neuroprotective monocyte-derived macrophages. The recruited monocytes contributed to a phenotype shift of the local cellular and inflammatory milieu, including tilting the balance between levels of pro- and anti-inflammatory cytokines and metalloproteinases—all of which contributed to ameliorating AD pathology [31,32,101,105,125,128]. Evidence continues to show that GA abrogates the accumulation of various toxic forms of Aβ in the CNS [31,104,124]. Importantly, GA mitigates cognitive decline and protects against degenerative processes, at least in part by secreting neurotrophic factors such as TGFβ, OPN and IGF-1, affecting neurogenesis and neurocognition processes [18,31,104,105,126,128]. It is important to note that certain studies compared daily versus weekly administration of GA in AD animal models. Although weekly administration was beneficial, daily injections of GA were detrimental leading to moderately worsened cognition and there was no evidence of Aβ plaque clearance [129]. Due to its dual mechanism of action, immunomodulatory effects and neuroprotective benefits, GA could potentially be a very important component of AD care, targeting neurodegeneration and cognitive functioning. 3.4. GA Immunization in Animal Models of Parkinson’s Disease (PD) Parkinson’s disease (PD) is the second most common neurodegenerative disease, following AD. It is characterized by the degeneration of the dopaminergic neurons within the substantia nigra pars compacta and a reduction in dopamine. This leads to movement deficits, particularly causing impaired initiation of movement [135]. With this understanding of the neurodegenerative pathophysiological process of PD, it could potentially benefit from the neuroprotective effects of GA. Thus, animal studies have recently been conducted to examine this possibility. Table 7 outlines cognitive and motor outcomes in two animal models of PD following GA treatment. The MPTP (1-methyl-1,2,3,6-tetrahydropyridine) neurotoxin model is commonly used to induce a pathological state similar to PD in mice [136]. Like previous studies, one PD model found that GA led to an increase in BDNF, IL-4 and IL-10, implying neuroprotection [137]. GA was found to improve gait and movement behaviors [137]. Enhancements in motor behaviors were visualized via results from laboratory testing methods [138]. Animals displayed a tendency to explore novel areas of mazes, relating to cognitive improvements, and had improved gait [135]. These studies also identified that GA protects the substantia nigra from PD-related neurodegeneration and motor complications [135,137]. 3.5. GA Immunization in Murine Models of Huntington’s Disease (HD) Huntington’s Disease (HD) is yet another neurodegenerative disease that could potentially benefit from GA’s neuroprotective effects. HD is associated with a genetic mutation: a trinucleotide repeat expansion, CAG, in the Huntingtin (HTT) gene of humans. This mutation leads to progressive parenchymal tissue damage causing a broad range of central deficits including sensory, motor, and cognitive [139]. Recent studies exploring the specific mechanisms of degeneration in HD have found increased free radicals, increased excitotoxicity, suspected inflammatory processes, and importantly, altered/lower levels of BDNF [140]. Therefore, mouse models of HD were utilized to assess GA’s effect in HD-like pathological states. Male mice on a B6CBA genetic background and female mice on a FVB background were crossbred. The offspring were tested for CAG nucleotide repeats, which were confirmed with PCR and genotyping [141]. Table 8 examines the cognitive and motor outcomes in animal experiments of HD models after GA immunization. Studies examined BDNF expression and its effect on reducing pathogenic astroglial cells. In these models, GA restored BDNF levels and decreased neurodegeneration [139,140,142]. With GA use, lifespan was prolonged and disease progression was delayed [139,140]. GA also was associated with improved cognitive functioning and motor/neurofunction [139,140,142]. Cognition was preserved by GA, as observed in the open field behavioral analysis (OFBA) and the rotarod tests [147,148]. The rodents in the OFBA tests showed less aggression, more purposeful movements, and improved decision-making [139,140]. The drug was also linked to less severe presentation and a later onset of behavioral issues [136]. GA was additionally found to ameliorate hyperactivity often seen in HD [140]. Motor functions and stereotyped behavior or movements were also improved after GA administration [140,142]. Additionally, the neuroplasticity and neurogenesis enhancements garnered by GA use was clear in these studies. Overall, these studies show that GA could play an important role in future studies of HD treatment. 3.6. Role of GA in Neuropsychology In previous studies, GA has been shown to improve not only cognitive domains but also psychiatric conditions and symptoms. Recent reports have implemented animal models of various psychiatric conditions to evaluate the potential for GA to mitigate their symptoms. Table 9 summarizes the outcomes in animal models of neuropsychiatric pathologies following GA immunization. One article studied genetically induced immunodeficiency in rodents and then administered psychoactive drugs that have a negative effect on mental status and cognition [103]. This combination of genetic and environmental effects was meant to represent a schizophrenia model, as well as other similar psychiatric conditions. This article found that GA reversed the effects of psychoactive agents, despite a weakened immune system. In particular, test subjects were found to have better communicative behavior as well as memory. In a study examining stress, rodents were exposed to chronic mild stressors (CMS) via brief periods of oxygen deprivation or small shocks [154]. Levels of nitric oxide synthase (NOS) as well as reactive oxygen species (ROS) were then measured. Higher levels of ROS, which are free radicals, cause damage via oxidative stress [162]. Conversely, NOS is an antioxidant that is associated with protection from destructive processes such as infection, inflammation, and cell death. Therefore, when evaluating the effects of ROS and NOS, ROS will cause neurodegeneration and cognitive deficits [163], whereas NOS is associated with neuroprotection and found in higher levels of anti-inflammatory states [140]. Here, GA’s effects on the brain were examined in relation to stress [154]. Treatment with GA resulted in an increase in NOS and a decrease in ROS, leading to lower rates of negative outcomes and complications from stress and ROS. One study implemented the use of lipopolysaccharides to cause short-term memory impairments in mice and found that GA injection improved axonal growth and remyelination [157], which correlated with memory improvement and shorter latency times in task completion. In the model of radiation injury, rodents had significant short-term and spatial memory deficits. However, in treatment groups, GA was linked with restoration of hippocampal neurogenesis [161]. Due to this GA-mediated improvement in neurogenesis and neuroplasticity, multiple aspects of memory including short-term, long-term, and spatial were improved. Additionally, GA was linked to reversal of behavior impairment associated with the radiation. The neuropsychological models found a positive correlation between GA use and improved memory, communicative behavior, psychosocial interactions, and stress response [98,154,157,161]. These promising results warrant further exploration into potential neuropsychiatric applications of GA. Disease states that GA is known to ameliorate, such as RRMS, often have neuropsychiatric components. Therefore, this drug could potentially serve dual purposes for many disease states: both the psychiatric burdens and inflammatory complications could be targeted, thereby lowering multiple aspects of the morbidity of these diseases. 3.7. Role of GA in Central Ischemia and Vascular Dementia Ischemia within the central nervous system (CNS), particularly within the brain itself, can be caused by a multitude of etiologies. Most commonly ischemic brain injury is due to a thromboembolic stroke and/or cerebral hemorrhaging. Central ischemia can cause significant neuropathological changes. The functional deficits of sustained CNS ischemia are dependent on the area the ischemia is located in. However, clinical signs/deficits are typically motor, sensory, verbal, and cognitive in nature [164]. Cerebral ischemia specifically due to stroke has been shown to increase neural inflammation. This is thought to be due to the breakdown in BBB integrity, leading to an influx of immune cells into the brain. Additionally, a local immune response is triggered by endogenous tPA endothelial release, activating astroglia and microglia [165]. Therefore, several studies have begun to examine what effects anti-inflammatory therapy has on cerebral ischemia complications. Table 10 summarizes cognitive and neurofunctional outcomes in animal models of cerebral ischemia following GA immunization. In these animal models, cerebral ischemia was induced via several techniques, one of which was permanent middle cerebral artery occlusion (pMCAo) in mice [170], whereby cognitive decline was induced, and inflammation was exacerbated in the brain. This allowed for an analysis of the ischemic pathological state and the potential improvements via GA treatment. Studies specifically examined memory and sensorimotor functioning before and after GA treatment following a cerebral ischemic injury. As seen in several other studies, GA displayed an immunomodulatory effect, with increase in anti-inflammatory mediators [31,164,169]. In nearly all CNS ischemia (CNSi) animal models, the immunomodulatory and neuroprotective effects of GA were linked to an enhancement in early neurogenesis, improved neuroplasticity, and strong neuroprotection. With these improvements, GA was found to prevent long-term memory loss and reduce cognitive deficits. Vascular dementia was induced via permanent cerebral artery occlusions, similarly to cerebral ischemia [175]. GA was once more found to increase the expression of BDNF and modulate the hippocampal balance of Th1/Th2 cells and associated cytokines [174]. These effects positively correlated to a reduction in cognitive deficits. In each CNSi study, there was a significant reduction in post-ischemic infarct volume [164,167,169,174]. Novel effects of GA, demonstrated in the reduction in the neurovascular damage to cortical regions, can be related to the immunomodulatory activity of GA. Treatment with this copolymer prevented neurodegeneration associated with ischemic injury and inflammation [164,167,169]. Additionally, GA was associated with an accelerated recovery of sensorimotor functions [164,174]. A significant improvement in neurological functions was identified in GA-treated subjects as compared to controls [167,168,174]. Collectively, these models of vascular dementia and cerebral ischemia demonstrated the benefit of using GA in the early phase following a stroke with signs of improvement in inflammation, memory loss and sensorimotor deficits [164,167,168,169,174]. In summary, Figure 2 describes the current knowledge regarding the molecular mechanisms of GA in eight different neurological diseases outlined in this review, including evidence of therapeutic effects and functional benefits. 4. Conclusions and Future Directions GA has been a first-line treatment to target the uncontrolled, detrimental inflammatory processes found in relapse-remitting forms of MS. However, recent studies have found that GA has more therapeutic benefits than previously thought. With emerging evidence that GA immunization induces cerebral BDNF and IGF-1 expression and neuroprotective effects in the CNS (Figure 2), it is imperative to continue to study its implications in various pathologies. The neuroprotection of GA has been found to assist in preservation of synapses and cognitive function and to be prophylactic against cognitive decline. While these effects are useful in the treatment of MS and its related neurocognitive complications, it is also feasible that GA has additional benefits in other disease states. AMD is an already established condition that GA targets; however, visual pathologies in MS have the potential to be targeted by GA as well. Neuroplasticity restoration and cellular repair is another, well-studied role of GA that has proven to be beneficial in treating degenerative and inflammatory lesions in several pathological states outside of MS, including Alzheimer’s, Parkinson’s, and Huntington’s disease. Additionally, the cognitive findings in these neurodegenerative diseases as well as in neuropsychiatric conditions and cerebral ischemia have the potential to be ameliorated by GA’s neuroprotective effects. A key finding among some studies is that GA may reverse inflammatory damage and improve cognitive function, resulting in improved functional status from baseline after GA administration. However, further study of the GA regimen dosing and frequency for each of these unique diseases and pathologies is needed. For example, in acute presentations a one-time administration or short course of GA may be sufficient but for chronic diseases, more intervention could be necessary. As the inflammatory and immune cells are key players in all of these diseases and the effects of GA, future studies could potentially evaluate the ongoing role of other, less studied cells. For example, macrophage migration inhibitory factor (MIF) and its homolog D-dopachrome tautomerase (D-DDT) are inflammatory factors with a common receptor, CD74. They are thought to be implicated in the pathogenesis of immunoinflammatory diseases and disease worsening. This is thought to be due to their multi-functional, pleiotropic effects leading to several pro-inflammatory states [176,177,178]. Recent studies have examined the possible role of these cytokines in MS. In an animal model, higher level of MIF and D-DT were correlated to increased EAE disease severity. Conversely, animals that lacked MIF and D-DT had a less severe progression of EAE [176]. Another study examined these cytokines in MS patients with clinically isolated syndrome (CIS). It was found that MIF and D-DT were overexpressed in CD4+ T cells of MS patients [177]. Similarly, IL-37 is hypothesized to help determine onset and progression of MS [179]. The findings from such studies display the possibility of targeting MIF and D-DT for pharmacological purposes and even diagnostic markers of disease progression [176,177,178]. Overall, it is imperative that the effects of GA continue to be examined and tested to better understand its myriad of neuroprotective benefits and the potential treatments it could offer. 5. Review Methods To perform this meta-analysis, a thorough and careful literature review was conducted. Articles and studies from peer-reviewed journals were assessed that examined potential novel effects of GA with a focus on cognition. Due to the burgeoning nature of this research concept, both clinical trials and animal studies were considered for the review. The online database and search engine, PubMed, was utilized to search for studies that were in line with this review’s goals. Key words and phrases selected for the PubMed search included: glatiramer acetate and cognitive function, GA cognition, Copaxone cognitive function, GA alternative effects, GA neurodegeneration, GA neuroinflammation cognition, Coplymer-1 cognition, Cop-1 cognition, GA Alzheimer’s disease, GA movement disorders, GA psychology, et cetera. There were approximately 1000 articles produced on average from the search utilizing these words and/or phrases. However, not every article fit the criteria of this literature review. To quickly evaluate the relevance of these articles, the abstract was reviewed. If the abstract expressed a focus on GA and cognition within neurological pathologies, the study was further analyzed. However, if it was found that the article was itself a review paper, meta-analysis, or any other non-experimental paper, it was not accessed for review. Additional exclusion criteria included studies published before 2000 (with the exception of MS clinical trials), studies with several confounding variables (e.g., multiple drugs studied in various patient cohorts), and studies not available in English (the primary language of the reviewer). Out of the approximately 1000 articles populated from the first search, another 100 on average had abstracts which coincided with the topic of interest. Once reviewed more carefully, approximately 25 articles further met the search criteria. Articles that were excluded did not have goals or outcomes that were in line with the purpose of this review. For example, if a study was examining the effects of GA in Alzheimer’s dementia but did not focus on cognition, it was not utilized. In general, articles were excluded that did not focus on cognitive effects of GA in specific neurological disease states. Several articles commented on cognition and GA but only those that specifically studied the relationship between GA and cognition were included in this review. A final exclusion criterion was implemented to evaluate the studies: improved or maintained cognitive performance. With this criterion in mind, an average of 10–15 articles were extrapolated from the search and utilized in this review. The main information obtained from these articles was constructed into a table to allow for a quick overview of the findings. While assessing these articles, the main points considered for inclusion were as follows: GA’s neuroprotective effect, novel uses for GA, research design and methodology, scoring mechanisms/research tools used (e.g., MFIS, Modified Fatigue Impact Scale), findings, analysis of the suspected mechanism of action for GA and emphasis on neurological and psychological pathologies. The results from each article were analyzed carefully for validity, reproducibility, accuracy, and relevance to the current research question. After reviewing the relevant articles, the information obtained was assessed with the overarching theme of novel uses for GA driving this analysis. Once the information was organized appropriately, a deeper evaluation was completed of the findings. The general findings were reported on and divided into categories based on the potential new target for GA use. A further analysis was made, specifically within the clinical trials examining cognitive effects of GA in multiple sclerosis. Articles were obtained for the purpose of the review with the above-mentioned methods. However, articles were then further selected with more stringent criteria. If they did not present detailed results and statistical analyses, they were not included. For example, if an article did not include specific results such as mean scores from cognitive testing or p-values from comparison analyses, it was not eligible. Additional articles were then selected that had similar study designs testing cohorts with the same cognitive assessments. For example, articles included in this review almost exclusively examined RRMS patients treated with GA and the cognitive effects were studied via various established assessments. Unfortunately, several of these articles did not have control groups that were well-established or any comparisons to other patient cohorts. Therefore, articles were found to perform a comparison analysis of various groups. Articles were found that included cohorts which were matched by age, sex, education status, disease status (if applicable), disease type (if applicable), and disease duration (if applicable). Cohorts were examined with the following group comparisons in mind: healthy controls, RRMS controls (no treatment), or alternative treatment (typically IFN-γ since this is relatively comparable to GA). Once these articles were identified, a rigorous statistical analysis and comparison was carried out. The digital program, GraphPad Prism, was utilized to run these analyses and obtain values for the group comparisons. Comparisons were made amongst groups within specific cognitive assessments. For example, groups were matched and compared within cohort results for MFIS and then analyses were made for that specific test. A one-way ANOVA was utilized with a post-test Tukey to obtain comparative values and determine the statistical significance of the group variations within individual cognitive assessments. Then, Prism was further utilized to graphically display the statistical findings including standard error means and p-values between the groups. The graphs represented a visual display of the statistical significance of these important findings. 6. Side Effects and Safety Since GA is a relatively old drug that is already widely used, the side-effect profile is well understood and tolerated. Additionally, GA is relatively safe with few, if any, significant, strong risks or contraindications. The majority of side effects found in GA are associated with injection-site reactions (pain, erythema, soreness, swelling, and hard indurations) [180]. Additional side effects include nausea, vomiting, chills, arthralgias, myalgias, neck pain, back pain, dyspnea, chest pain, headache, diplopia, polyuria, weakness, rhinorrhea, fever, sore throat, and tremors [181]. The only reported contraindication is a known hypersensitivity to mannitol or GA itself [180,181]. Overall, GA is a well-tolerated and safe drug with few associated risks. Acknowledgments We thank Mia Oviatt for editing assistance. This article is dedicated to the memory of Salomon Moni Hamaoui and Lillian Jones Black, both of whom died from Alzheimer’s disease. Author Contributions Conceptualization and writing, A.K. and M.K.-H. Assistance writing and editing, Y.K., D.-T.F. and A.R. Illustration, A.K., D.-T.F., Y.K. and M.K.-H. Project administration, A.K., M.K.-H. and K.L.B. All authors contributed to the discussions and presentations. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The research investigators have no conflict of interest to report. Figure 1 Cognitive and Behavioral studies involving RRMS patients following GA immunization treatment. (A) MSIS-29 examines the physical, cognitive, and psychological impacts of multiple sclerosis on participants’ lives. Statistically significant improvement between RRMS controls and GA after 12 months group with a 33% decrease. A statistically significant improvement between GA baseline and 12 months of GA treatment, with a 14% decrease (p < 0.001). No significant change in INF-β-treated RRMS cohort. There was a 12% decrease in scores between RRMS controls and INF-β treated as compared to 33% decrease between RRMS controls and RRMS GA-treated cohort. (B) MFIS examines fatigue. Statistically significant improvement between RRMS controls and GA after 12 months group with a 46% decrease. A notable improvement between GA baseline and 12 months of GA treatment, with a 25% improvement (p < 0.001). No significant change in RRMS controls and INF-β-treated cohorts. (C) FIS examines fatigue. Statistically significant improvement between RRMS controls and GA after 12 months group with a 35% decrease. An even more notable statistically improvement between GA baseline and 12 months of GA treatment, with a 45% increase (p = 0.002). No significant change in natalizumab treated RRMS cohort. Additionally, no significant difference between healthy controls 6 months of natalizumab treatment. (D) WPAIQ examines productivity and disease impact on activity/productivity. Important to note, no significant difference between healthy controls and GA-treated RRMS patients. Statistically significant improvement between RRMS controls and GA after 12 months group with a 35% decrease. An even more notable statistically improvement between GA baseline and 12 months of GA treatment, with a 45% increase (p = 0.002). No significant change in IFN-β treated RRMS cohort. Additionally, no significant difference between RRMS controls and 6 months of IFN-β treatment. Graphs (E–G) represent the 3 tests that make up the BICAMS. (E) CVLT-II examines verbal learning and memory. No significant change in healthy controls. A 19% decrease in scores between healthy controls at 12 months and RRMS controls as compared to 10% decrease between healthy controls and RRMS GA-treated cohort. Statistically significant improvement between RRMS controls and GA after 12 months group with a 25% increase. No statistical difference between INF-β-treated cohorts at 12 months and GA-treated cohorts at 12 months. Statistically significant increase/improvement/change between GA baseline and 12 months of GA treatment (p = 0.006). (F) SDMT, a test of short-term, visual, and working memory. No significant change in healthy controls. A 34% decrease in scores between healthy controls at 12 months and RRMS controls as compared to 18% decrease between healthy controls and GA-treated RRMS cohort. Statistically significant improvement between RRMS controls and GA after 12 months group with a 25% increase. No statistical difference between INF-β-treated cohorts at 12 months and GA-treated cohorts at 12 months. Statistically significant increase/improvement/change between GA baseline and 12 months of GA treatment (p = 0.003). (G) BVMT-R of visuospatial memory. No significant change in healthy controls. A 29% decrease in scores between healthy controls at 12 months and RRMS controls as compared to 14% decrease between healthy controls and GA-treated RRMS cohort (nearly half the percent change). Statistically significant improvement between RRMS controls and GA after 12 months group with a 21% increase. No statistical difference between INF-β-treated cohorts at 12 months and GA-treated cohorts at 12 months. Statistically significant increase/improvement/change between GA baseline and 12 months of GA treatment (p = 0.005). * p < 0.05, ** p < 0.01, **** p < 0.0001. ns: no significance. Figure 2 Mechanism of action and therapeutic effects of GA neuroimmunomodulation across various neurologic disorders. The synthetic immunoactive copolymer glatiramer acetate (GA; formula C25H45N5O13), branded Copaxone (also known as Copolymer-1 or Cop-1), is comprised of four amino acids, Lysine, Arginine, Glutamic acid and Tyrosine, in random order, resembling myelin basic protein (MBP). In the CNS under injury or inflammatory conditions, MBP level is increased, and GA is considered as its weak agonist. GA causes expansion of specific populations of helper T type 2 (Th2) cells that secrete anti-inflammatory cytokines and recruitment of monocytes-derived macrophages into the diseased brain, spinal cord, and retina. PD: data is based on pre-clinical studies. GA immunization (200 μg/s.c. or 3.5 mg/kg/s.c. daily for four weeks) increased BDNF, IL-4 and IL-10 levels and protected the substantia nigra from dopaminergic neuron degeneration thus limiting disease progression and improving motor functions. AMD: data is based on clinical studies, where GA immunization (20 mg/s.c.) was given once a week for 12–16 weeks. GA was found to enhance the phagocytic ability of classic (CD14+CD16−) and non-classic (CD14dimCD16+) monocytes. GA immunization induced a phenotypic heterogeneity of monocytes which seemed to provide a protection against drusen formation. Additionally, GA-mediated Th2 cells were shown to reduce retinal microglial cytotoxicity. Overall, GA reduced retinal atrophy and improved visual functions. Neuropsychology disease: pre-clinical data showed that GA treatment (100–250 μg/s.c./daily or weekly for 1–2 weeks) increased neuroprotection and improved cognition (as demonstrated with various behavioral tests) with elevating levels of NOS and neurotrophic factors (BDNF, IGF-1 and IGF-2) along with decreased levels of ROS. AD: data is based on pre-clinical and in vitro studies where GA immunization (100 μg/s.c./weekly for 4–12 weeks) increased infiltration of CD115+LyC6hiCD45hi-OPN+ monocytes to the CNS as well as Th2 population. Infiltrating monocytes-derived macrophages (CD68+) and their scavenger receptors (CD36, SCARA1, CD163) contributed to enhancing clearance of Aβ plaques and other Aβ assemblies from the parenchyma and blood vessels. Neuroinflammation in the form of reduced GFAP+ astrogliosis and Iba1+ microgliosis was reduced along with decreased levels of TNF-α and increase in IL-10 levels. Secretion of neurotrophic factors such as IGF-1, OPN, and increased expression of transcription factor EGR1 enhanced hippocampal synapses and neurogenesis. As a result, a phenotype shift from pro- to anti-inflammatory microglia is observed. Overall, GA reduced cerebral inflammation and improved Aβ clearance, preserved synapses and cognition. Interestingly, GA given daily revealed to be detrimental. HD: pre-clinical data of GA treatment (100–750 μg/s.c./daily, weekly, thrice weekly, or five times weekly for 4–12 weeks) showed elevated BDNF levels in striatal cells, decreased motor neuron damage and hyperactivity and improved motor function and cognition thus overall increasing lifespan. ALS: pre-clinical (100 μg/s.c./daily, weekly, bi-weekly, or monthly for 1–4 weeks) and clinical (5–20 mg/s.c./daily or twice monthly for six months) studies demonstrated immunomodulation by GA leading to Th2 proliferation along with increased levels of IL-4 and IL-10, which may reduce neuroinflammation, preserve motor neurons, and improve motor function, thus possibly prolonging lifespan. CNSi: pre-clinical data (100–200 μg/s.c./weekly or thrice weekly for 1–4 weeks) showed that GA treatment ameliorated neuro-deficit, improved cognition and neurogenesis associated with increased level of BDNF, and anti-inflammatory cytokines (IGF-1, IL-10), decreased pro-inflammatory cytokines (TNF-α, IL-6, IFN-γ). GA was also associated with recovery of sensorimotor functions and reduction in post-ischemic infarct volume. RRMS: pre-clinical (200–250 μg/s.c./daily for 1–3 weeks) and clinical (20–40 mg/sc/daily or thrice weekly for six months to ten years) data demonstrated that GA increased levels of anti-inflammatory cytokines (IL-4, IL-5, IL-9, and IL-13) derived from Th2 cells in the CNS. Increased infiltrating-monocytes-derived macrophages decreased TNF-α and increased IL-10, leading to reduction in neuroinflammation, relapse, and lesions. Elevated levels of neurotrophic factors such as BDNF and IGF-1 and 2 were associated with improved cognitive domains such as information processing, verbal, and visuospatial learning and memory. More importantly, GA prevented the formation of anti-myelin antibodies and thus reduced demyelination and promoted remyelination, axonal growth, regeneration, and improved quality of life such as reducing EDSS, fatigue, and depression. Data are derived from pre-clinical (mouse icon) and/or clinical (human head icon) studies. Aβ: amyloid-β; AD: Alzheimer’s disease; Ala: Alanine; ALS: Amyotrophic lateral sclerosis; AMD: adult-onset macular degeneration; As: Astrocyte; BDNF: brain-derived neurotrophic factor; BMT: Barnes maze test; CD: cluster of differentiation; CNSi: central nervous system ischemia; EDSS: expanded disability status score; EGR1: Early Growth Response Protein 1; HD: Huntington’s disease; IGF: insulin-like growth factor; Glu: Glutamic Acid; Inf. Proc.: information processing; IL: Interleukin; INF: Interferon; L-Arg: L-Arginine; L-Cit: L-Citrulline; Lys: Lysine; Mφ: macrophage; MG: microglia; Mo: monocyte; MWM: Morris water maze; NO: nitric oxide; NOR: novel object recognition; NOS: nitric oxide synthase; OFBA: open field behavioral assessment; OPN: Osteopontin; PD: Parkinson’s disease; PPI: pre-pulse impulse; RAWM: radial arm water maze; ROS: reactive oxygen species; RRMS: relapse-remitting multiple sclerosis; s.c.: subcutaneous; TGF: transforming growth factor; Th: T helper cell; TNF: tumor necrosis factor; Tyr: Tyrosine. Figure was created with Biorender.com (accessed on 16 June 2021). cells-11-01578-t001_Table 1 Table 1 Clinical Trials Examining Cognitive Outcomes of Glatiramer Acetate Immunization in Multiple Sclerosis Patients. Disease State Research Design and Methodology Findings Ref. MS 248 MS patients, EDSS < 5 GA (n = 125) Placebo (n = 126) Longitudinal: years GA—b vs. GA—2 years: stable or improved EDSS scores Placebo—b vs. placebo—2 years: large variations in EDSS scores Neuropsychological tests (PASAT [37], spatial recall, word list generation, etc.) showed no improvements in GA-treated participants Lack of measurable cognitive decline Weinstein, A. et al., 1999 [38] MS 251 RRMS patients, EDSS < 5 GA (n = 79) Placebo (n = 74) Longitudinal: 10 years BRBNT [39] GA—b vs. GA—10 years: <0.5 SD, statistically insignificant BRBNT placebo—b vs. placebo—10 years: decline more than 0.5 SD seen Stable cognitive performance Schwid, R. et al., 2007 [40] MS 30 RRMS patients Gd+ GA (n = 18) Gd−: GA (n = 12) Longitudinal: 3 months PASAT [mean ± SD]: Gd+ [42.16 ± 1.33] vs. Gd− [48.92 ± 1.51] (p < 0.05) iTBS induced LTP-like response [41] [mean ± SD]: Gd+ [1.38 ± 1.73] vs. Gd− [1.51 ± 2.59] (p < 0.05) Improved cognition (PASAT, LTP) correlated to reduced Gd+ lesions Mori, F. et al., 2012 [42] MS 67 RRMS patients GA (n = 67) Observational study Longitudinal: 24 months FIS [mean ± SD]: GA—b [61.96 ± 31.04] vs. GA—24 months [45.94 ± 27.54] 26% decrease (p < 0.001) MSQoL-54 [mean ± SD]: GA—b [19.3 ± 3.69] vs. GA—24 months [21.8 ± 4.43] Decreased fatigue and improved QoL; remained decreased/improved Jongen, P. et al., 2014 [43] MS 37 MS patients, no prior use of DMT [44] GA (n = 23) Placebo (n = 14) Longitudinal: 12 months EDSSGA—b vs. GA—12 months: decreased scores (p = 0.003) Placebo—b vs. placebo—12 months: increased scores (p = 0.008) MSFCGA—b vs. GA—12 months: increased scores (p = 0.0001) Placebo—b vs. placebo–12 months: lowered scores (p = 0.0001) MoCA GA–b vs. GA–12 months: no significant change (p < 0.083) Placebo–b vs. placebo–12 months: significantly lower scores (p < 0.025) Improved cognition in MSFC and MFIS; maintained cognition in MoCA scores. Vacaras, V. et al., 2014 [45] MS 428 RRMS patients, EDSS < 5.5, GA Observational study Control group: meta-analysis of general MS population statistics Depression prevalence: GA 13.4% vs. gen. MS population 36–54% Lower depression (BDI scores) correlated w/higher MSQoL-54 EDSS: lower median score Reduced disease activity, antidepressant effect, and improved QoL. Fricksa-Nagy, Z. et al., 2016 [46] MS RMMS patients, previously on INF-β w/MFIS > 38 Observational study GA (n = 54) Longitudinal: 6 months MFIS GA–b vs. GA–6 months [mean ± SD]:Physical: [27.6 ± 4.8] vs. [20.0 ± 7.3] (p < 0.001) Cognition: 21.9 ± 8.4 vs. 17.5 ± 7.2 (p < 0.001) Psychosocial.: 5.6 ± 1.8 vs. 3.9 ± 1.9 (p < 0.001) WPAIQ GA–b vs. GA–6 months [mean ± SD]:Activity impairment: [63.1 ± 23.1] vs. [42.0 ± 23.3] (p < 0.001) MSIS-29 GA—b vs. GA—6 months [mean ± SD]:Physical: 51.2 ± 13.3 vs. 44.8 ± 12.0 (p < 0.001) Psychological: 23.1 ± 6.0 vs. 19.8 ± 5.3 (p < 0.001) Amelioration in fatigue. Improved QoL, cognition and work/daily activities. Meca-Lallana, J. et al., 2016 [47] MS 754 MS patients Observational study Previous DMT treatment, started GA (n = 481) Treatment naïve, started GA (n = 273) Longitudinal: 2 years GA—b vs. GA—2 yearsRelapse rate: 87% vs. 49% (p < 0.001) PASAT [mean]: [41.63] vs. [45.76] (p < 0.001) MSFC: 64.2% improved, 35.8% deteriorated FSMC [48]: 43.6% improved, 51.3% deteriorated, 5.1% unchanged FAMS: 51% improved, 47.1% deteriorated, 1.9% unchanged MUSIC: 56.5% improved, 26.7% deteriorated, 16.8% unchanged CES-D: reduced depressive symptoms (p < 0.001) Mitigated disease progression; improved cognition; reduced depression. Ziemssen, T. et al., 2016 [49] MS MS patients, GA-treated (n = 161) Naïve healthy controls (n = 102) Longitudinal: 12 months BICAMS GA—b vs. GA—12 months [mean ± SD]:SDMT: [40.8 ± 20.5] vs. [44 ± 16.4] (p = 0.003) CVLT-II: [52.7 ± 14.8] vs. [56.1 ± 14.3] (p = 0.006) BVMT-R: [23.9 ± 10.4] vs. [26.5 ± 11.6] (p = 0.005) Improved cognition and slowed onset of cognitive impairments. Cinar, B. et al., 2017 [50] MS 19 RMMS patients, GA-treated Observational study Longitudinal: 2 years OCT: reduction in signs of retinal inflammation w/GA Reduced neurodegenerative processes in the retina Sazonov, D. et al., 2018 [51] MS 33 MS patients, GA-treated Observational study Longitudinal: 4 years PASAT: improved information processing/speed and working memory Shorobura, M., 2018 [52] MS RRMS patients, GA-treated (n = 60) Naïve healthy controls (n = 40) Longitudinal: 2 years EDSS [mean ± SD]: [2.0 ± 1.0–3.5] vs. [2.5 ± 1.5–3.5] Relapses [mean ± SD]: [0.18 ± 0.46] vs. [0.36 ± 0.58] OCT imaging, RNFLT [mean]: [86.5] vs. [92.3] (p = 0.046) OCT imaging, TMV [mean]: [0.67] vs. [0.93] Reduced damage in RNFLT, similar findings to healthy controls Zivadinov, R. et al., 2018 [53] Participants in the treatment groups of these studies were given 20 mg/s.c./qd of GA (subcutaneous, daily); MS: multiple sclerosis; RMMS: relapsing remitting multiple sclerosis; GA: glatiramer acetate; EDSS: expanded disability status scale; BRBNT: brief repeatable battery of neuropsychological tests; RR: relapse rates; Gd+: gadolinium positive; Gd−: gadolinium negative; HRQoL: (health-related quality of life); iTBS: intermittent theta burst stimulation; BDNF: brain-derived neurotrophic factor; PASAT: paced auditory serial addition test; MRI: magnetic resonance imaging; LTP: long-term plasticity; DMT: disease-modifying therapy; MSFC: multiple sclerosis functional composite; MFIS: modified fatigue impact scale; MoCA: Montreal cognitive assessment; MSQoL-54: multiple sclerosis quality of life-54; BDI: Beck depression inventory; INF-β: Interferon-β; WPAIQ: work productivity and activity impairment questionnaire; MSIS-29: multiple sclerosis impact scale-29; MSIC: multiple sclerosis inventory cognitive scale; CES-D: Center for Epidemiological Status-Depression; FAMS: functional assessment of multiple sclerosis; FSMC: fatigue scale for motor and cognition; MUSIC: multiple sclerosis inventory cognition; BICAMS: brief international cognitive assessment for multiple sclerosis; w/o: without; SD-OCT: spectral domain—optical coherence tomography; RNFLT: retinal nerve fiber layer thickness; TMV: total macular volume; SD: standard deviation. cells-11-01578-t002_Table 2 Table 2 Clinical Trials and an Animal Model Examining Alternative Outcome of Glatiramer Acetate Treatment in Ophthalmological Patients. Disease State Research Design and Methodology Findings Ref. AMD 17 AMD patients GA-treated (n = 4) Placebo (n = 4) Longitudinal: 12 weeks TDA, GA—b vs. GA—12 weeks (mean): (48,130) vs. (16,205), improved TDA, placebo—b vs. placebo—12 weeks (mean): (32,294) vs. (32,781), no significant change Reduced TDA Landa, G. et al., 2008 [93] Glaucoma (animal model) 8-week-old m Lewis rats elevated IOP (glaucoma model) GA vs. PBS and naïve control (n = 6 per group) Increased Egr, potential GA-induced repair mechanism Five altered genes in elevated IOP rats (Cspg2, Fbn1, Enpp2, Ncam1 and Stat1) were restored to homeostatic levels Induced neurogenesis and cell migration/communication Repressed cell death, scar tissue formation, immune response, and protein degradation Prevention of RGC death and attenuation of functional decline Bakalash et al., 2011 [95] AMD 14 AMD patients GA-treated (n = 7) Placebo (n = 7) Longitudinal: 12 weeks Drusen shrinkage rate, GA—12 weeks vs. placebo—12 weeks: 27.8% vs. 6.8% (p = 0.008) Drusen disappearance, GA—12 weeks vs. placebo—12 weeks: 19.2% vs. 6.5% (p = 0.13) Reduced drusen Landa et al., 2011 [94] Glaucoma 38 glaucoma patients GA-treated (n = 19) Placebo (n = 19) Longitudinal: 16 weeks Visual field mean deviation: GA, improved (p = 0.01) vs. placebo, worsened (p = 0.004) Less disease progression and improved visual fields Fan et al., 2019 [96] AMD 104 AMD patients iAMD GA-treated (n = 72) iAMD GA-treated (n = 32) Healthy controls (n = 74) Longitudinal: 15 weeks GA—12 weeks vs. healthy controls—15 weeks: enhanced phagocytosis of non-classical monocytes (p < 0.0001) and classical monocytes (p = 0.0002) GA—12 weeks vs. healthy controls—15 weeks: reduced drusen and retinal atrophy, iAMD (p = 0.02); late AMD (p = 0.078) Improved monocyte activity/phagocytosis—correlated to drusen levels and retinal tissue integrity Gu, B. et al., 2021 [24] Participants in the treatment group of these studies were given GA 20 mg/s.c./qw (weekly); AMD: age-related macular degeneration; TDA: total drusen area; iAMD: intermediate adult-onset macular degeneration; lAMD: late adult-onset macular degeneration; IOP: intraocular pressure; RGC: retinal ganglion cell. cells-11-01578-t003_Table 3 Table 3 Clinical Trials Examining Alternative Glatiramer Acetate Uses in Amyotrophic Lateral Sclerosis Patients. Disease State Research Design and Methodology Findings Ref. ALS 30 ALS patients GA-treated, qd (n = 20) GA-treated, q2w (n = 20) Placebo (n = 10) GA: protective T-cell proliferation increased compared to placebo (p = 0.02) Destructive immune cell lines diminished Immunomodulatory effects enhanced neuroprotection Gordon, P. et al., 2006 [97] ALS 31 ALS patients GA, qd (n = 10) GA, q2w (n = 10) Treatment naïve (n = 11) Longitudinal: 6 months Inverse correlations in IgG3 and IL-4 and IL-10 levels qd GA: enhanced Th2 cytokine levels q2w GA: enhanced Th1 cytokine levels qd GA: diminished IL-10 levels q2w GA: diminished IL-4 levels; increased IL-10 levels Improved protective immune response. Findings varied based on dosage/frequency of GA administration. Mosley, R. et al., 2007 [98] Participants in the treatment groups of these studies received 20 mg/s.c.; Monthly plasma samples obtained in ALS models; ELISA and flow cytometry utilized to assess for immune responses; ALS: amyotrophic lateral sclerosis; qd: daily; q2w: biweekly; Th1: T-helper 1 cells; T-helper 2 cells; IL -4: Interleukin-4; IL-10: Interleukin-10. cells-11-01578-t004_Table 4 Table 4 Animal Studies Examining Alternative Glatiramer Acetate Outcomes in Multiple Sclerosis. Disease Model Research Model and Methodology Findings Ref. MS 6–8-week-old m&f SJL/L mice (n = 8 mice/group) EAE, MOG 33–55 peptide (MS model) [106] GA-immunized, q2d (Or treated with EGCG 300 μg/oral/q2d) PBS-injected or naïve wild type IHC and EM: improved neuronal survival, axonal growth, remyelination, formation of new synapses and axonal regeneration ELISA: increased BDNF LSS: improved motor and cognitive functioning Improved neurogenesis, reduced disease progression and higher BDNF levels. Herges, K. et al., 2011 [102] MS 8–10-week-old m&f, C57BL/6 mice GA-treated (n = 27) PBS-injected (n = 22) or naïve wild type (n = 24) CMT, GA vs. placebo and WT: higher levels of STM LSS, GA vs. placebo: No decline appreciated or a slower rate of decline IHC and EM, GA vs. placebo: reduced cortical damage Improved STM/cognition and less memory decline (LSS and CMT). LoPresti, P. 2015 [107] MS 8–12-week-old f C57BL/6 mice GA-immunized (n = 12) PBS-injected (n = 12) or naïve wild type (n = 10) Improved short-term memory, reduced mistakes in CMT IHC and EM [mean ± SD], GA vs. placebo: astrocyte processes overlap barrel boundaries [13.1 ± 0.5] vs. [5.8 ± 0.3] (p < 0.001) GM-CSF [108] Clasping score GA vs. placebo: less GM-SCF expressing cells 20% of T-cells (p < 0.01), 72% of macrophages (p < 0.05), 31% of leukocytes (p < 0.0001) Reduced cognitive decline (LSS and CMT) and improved astrocyte morphology/vascular connections Eilam, R. et al., 2018 [109] MS 5–8-week-old m&f SJL/L mice GA-immunized, 50 μg/s.c./q2d (n = 13) PBS-injected (n = 12) or naïve wild type (n = 10) DNMSTM GA vs. placebo: χ2(4) = 7.506 (p = 0.111) IHC and EM GA vs. placebo: smaller, lower number of cellular infiltrations and moderate/absent astrocyte and microglial activation Preserved cognitive function and provided neuroprotection against cellular invasion/inflammation Aharoni, R. et al., 2019 [110] MS 8–10-week-old f mice GA-immunized (n = 22), ABAH treated (n = 19), or combo treatment (n = 31) PBS-injected controls (n = 22) GA and combo treatment vs. placeboDisease onset, [mean # of days]: [10.4] and [11.3] vs. [9.0] (p < 0.05) Disease severity, GA and GA-combo treatment vs. placebo [mean]: [3.1] and [1.8] vs. [3.9] (p < 0.05) MPO+ lesions GA and combo treatment vs. placebo [mean]: [64.8] and [30.2] vs. [67.2] (p < 0.05) Reduced inflammatory plaques #/activity/size (monitored w/MPO on Gd-MRI). Improved cognition (LSS scores). Li, A. et al., 2019 [111] EAE: Experimental Autoimmune Encephalomyelitis; EAE model used to induce MS-like state in all studies. Test subjects were administered 200–250 μg/s.c./qd, unless otherwise specified; MS: multiple sclerosis; m&f: male and female; MOG: myelin oligodendrocyte protein; s.c.: subcutaneous; q2d: every 2 days; EGCG: Epigallocatechin 3-Gallate; LSS: Longa scoring scale; IHC: immunohistochemistry; EM: electron microscopy; ELISA: enzyme-linked immunosorbent assay; BDNF: brain-derived neurotrophic factor; qd: daily; CMT: cross-maze test; GM-CSF: granulocyte–macrophage colony-stimulating factor; DNMSTM: delayed non-matching to sample T-maze; ABAH: 4-aminobenzoic acid hydrazide; MRI: magnetic resonance imaging; MPO: Myeloperoxidase; Gd+: gadolinium positive. cells-11-01578-t005_Table 5 Table 5 Animal Studies Examining Alternative Uses of Glatiramer Acetate in Amyotrophic Lateral Sclerosis. Disease Model Research Model and Methodology Findings Ref. ALS 10–12-week-old f B6SJ/L mice Overexpression of G93A-SOD1 gene (ALS model) GA-immunized (n = 14) PBS-injected (n = 13) and naïve wild type (n = 12) Lifespan GA vs. control [mean days ± SD]: [211 ± 7] vs. [263 ± 8] Higher levels of motor neurons after facial nerve axotomy, compared to controls (p < 0.05) Improved/protected motor activity via biometrically analyzed whisking behavior Increased life expectancy, motor number, and improved motor activity/function. Angelov, D. et al., 2003 [99] ALS Male tg B6SJL-tg (SOD1-G93A)1Gur mice crossbred with female non-tg B6SJLF1-mice; offspring tested at 40 days old (n = 9 mice/group) GA-immunized vs. PBS-injected controls RAWM GA vs. placebo: Delayed impairment of motor function and lessened disease progression GA vs. placebo: reached 10% of pre-symptomatic functional activity Motor function improved/protected. Disease progression slowed Habisch, H. et al., 2007 [116] ALS 50-day-old m&f B6SJL-tg [SOD1-G93]1Gur mice; B6. cg-tg [SOD1-G93A]1Gur/J mice; SOD1 G37R mice (n = 15–17 mice/group) TV-5010, 75,200 or 500 μg/s.c. qw, q2w or monthly GA-immunized vs. PBS-injected controls Muscle strength (disease onset): no significant change No significant changes in lifespan (delayed lifespan phenotype) Significant diminution of survival for mice treated qw compared to other treatment regimens (p < 0.05) Rotarod: no significant improvements/changes in motor function Regimens had minor differences in findings Study utilized TV-5010 (synthetic HMW polymer formulation of the same amino acids of GA). Haenggeli, C. et al., 2007 [117] Animals in the treatment groups received 100 μg/s.c./qw unless otherwise specified; ALS: amyotrophic lateral sclerosis; SOD1: superoxide dismutase 1; tg: transgenic; RWA: running wheel activity; HMW: high molecular weight. cells-11-01578-t006_Table 6 Table 6 Animal Studies Examining Alternative Uses of Glatiramer Acetate in Alzheimer’s Disease. Disease Model Research Model and Methodology GA Effects/Findings Ref. AD 10–12-week-old m&f APPSWE/PS1ΔE9 mice * and non-Tg WT littermates GA-immunized (n = 5) PBS-injected (n = 8) and naïve WT (n = 7) Aβ fibrils: 70% reduction (p < 0.02) Aβ fibrils in hippocampus: 92% reduced (p < 0.01) 31% reduction in astrocytosis (p = 0.039) GA-enhanced microglial activation correlated w/decreased Aβ fibrils. Frenkel, D. et al., 2005 [125] AD 8–10-month-old m&f APPSWE/PS1ΔE9 mice @ and non-Tg WT littermates GA-immunized vs. PBS-injected and naïve WT (n = 7–8 mice/group) GA enhanced protective microglia (CD11b+/CD11c+/MHC class II+/TNF-α−) Eliminated Aβ plaque formation (p < 0.05) MWMT: GA learning and memory improved (p < 0.0001) Reduced cognitive decline (MWMT) and increased neurogenesis. Butovsky, O. et al., 2006 [18] AD 3-month-old m&f APPSWE/PS1ΔE9 (ADtg)-CD11cDTR–GFP chimeric mice # GA-immunized vs. GA-immunized with DT, vs. untreated ADtg chimeric mice Nonchimeric ADtg mice controls: GA-immunized vs. untreated (n = 3–4 mice/group) Reduced CD11+ proinflammatory cells Promoted/enhanced neuroprotection and neurogenesis Enhanced removal of Aβ-plaque Lessened Aβ plaque formation and provided neuroprotection Butovsky, O. et al., 2007 [128] AD 7-month-old m&f APPSWE/PS1ΔE9 mice @ and non-Tg WT littermates Weekly GA or PBS for 12 weeks (n = 7 mice per group) and naïve WT GA vs. controls, mice and rats Scar tissue: 8% vs. 15% Protein degradation/ubiquitination: 0% vs. 6% Growth/neurogenesis: 13% vs. 9% Development/migration/differentiation: 115% vs. 8% Transcription regulation: 14% vs. 5% 35% increase in hippocampal EGR1 (p < 0.01) Enhanced neurogenesis in hippocampus Induced neurogenesis, neuroplasticity and neuroprotective gene activation-Egr1 likely to be involved in GA-mediated enhanced capacity for regeneration in the DG and improved cognition. Bakalash, S. et al., 2011 [95] AD 10-month-old m APPswe/PS1∆E9 mice @ and non-Tg WT littermates Weekly GA or PBS vs. GA-plus CD115+ MoBM adoptive transfer ** vs. and naïve WT for 8 weeks in 10-month-old (n = 6–8 per group) GA vs. controlsAβ levels reduced (p < 0.001) and astrogliosis reduced (p < 0.0001) Enhanced monocyte recruitment—associated w/IL-10 driven phagocytosis of Aβ plaques Increased MMP9 protein (p < 0.05) Enhanced macrophage-phagocytosis of fibrillar Aβ42 (p < 0.0001) Significant plaque reductions, 40–53% (hippocampus) and 61–78% (cortex) (p < 0.0001–0.001) Improved BMT scores (p < 0.001) Synaptic preservation Enhanced Aβ degradation, attenuated disease progression, improved memory and learning Koronyo, Y. et al., 2015 [32] AD 4–7-month-old 5xFAD mice ^ and non-Tg WT littermates Four conditions: (a) Weekly GA for 1 or 4 weeks in 4-month-old mice; (b) Weekly GA for 4 weeks in 5-month-old mice; (c) Twice a week GA for 1 week in 6-month-old mice; (d) Daily vs. weekly for 4 weeks in 7-month-old mice GA-immunized vs. PBS-injected 5xFAD mice and naïve WT mice (n = 4–8 per group) Enhanced expression of BDNF and IGF-1; increased IFN-γ RAWM: improved spatial memory Reduced neuroinflammation and Foxp3+ Treg levels Weekly GA injections reversed Aβ plaque formation and improved RAWM cognitive performance Daily GA injections led to moderately worsened cognition (RAWM results) and no clearance of Aβ plaques Weekly GA improved cognition (spatial memory), reduced neuro and peripheral inflammation, and decreased Aβ plaque burden Baruch et al., 2015 [129] AD 10-month-old m APPSWE/PS1ΔE9 mice @ and WT littermates In vivo: (a) Weekly GA or PBS vs. GA- plus CD115+ MoBM adoptive transfer ** for 8 weeks in 10-month-old mice (n = 4–6 per group); (b) Weekly GA for 4 weeks in 3-month-old mice (n = 3 per group) In vitro: WT MΦBM CD115+ treated with 30 μg/mL GA for 24 h (n = 3–5 replicates) GA vs. controlsIncreased OPN-expressing MΦ Enhanced Aβ phagocytosis Reduced Aβ cerebral and vascular pathology GA increased OPN and MΦBM, 1.4–2.5 times higher than controls (p < 0.01–0.0001) Enhanced OPN expression and reduced Aβ plaques Rentsendorj, A. et al., 2018 [127] AD 20-month-old m&f APPSWE/PS1ΔE9 mice @ and wild type littermate mice Weekly GA or PBS for 8 weeks and naïve WT (n = 6–7 mice per group) GA vs. controlsDiminished vascular and parenchymal Aβ deposition Restoration of post-synaptic biomarker PSD-95 density Reduced Aβ42/40 ratio levels in retina (p = 0.0246) 63% reduction in vascular amyloidosis (p = 0.0093) Reduced microgliosis and reactive astrocytosis (p = 0.0361) Increased cerebral infiltrating CD45hi/Iba1+ monocyte-derived macrophages (p < 0.001–0.0001) Restored homeostatic astrocyte phenotype (i.e., GFAP, GS expression) (p = 0.005) Aβ-plaque reduction—brain regions and plaque subtypes:Hippocampus: 40% reduction (p = 0.0003) Cortex: 48% reduction (p = 0.0001) Total brain: 46% reduction (p = 0.0001) Large, hard-core plaques: 28% reduction (p = 0.0017) Synaptic preservation Correlation and similar reduction in retinal and brain Aβ plaques; tissue homeostasis and regeneration Doustar, J. et al., 2020 [105] AD 10-month-old m APPSWE/PS1ΔE9 mice @ and WT littermates In vivo: Weekly GA or PBS vs. CD115+—MΦBM adoptive transfer ** for 8 weeks and naïve WT mice (n = 6 mice/group) In vitro: WT MΦBM treated with 30 μg/mL GA for 1, 3, or 24 h (n = 3–4 replicates) GA vs. controlsGA-induced MΦBM phagocytosed f/oAβ42 fibrils BMT: Improved cognitive function 36% decrease in Aβ42 of GA-macrophages (p < 0.01) Synaptic preservation Increased levels of protective MΦBM and enhanced cognition Li, S. et al., 2020 [124] AD 15-month-old f 3xTg mice $ and non-Tg mice Weekly GA or PBS for 8 weeks, 500 ng/μL and naïve wild type (n = 9–11 mice per group) Increased discrimination index (novel object recognition vs. former object) over 8 weeks (p = 0.01) and significant difference from placebos (p = 0.04) IHC: decrease in hippocampal Aβ1–42 after 8 weeks of GA use (p = 0.02) Improved cognition, reduced amyloid plaque deposition Dionisio-Santos, D. et al., 2021 [126] All studies utilized transgenic models of AD. Animals in the treatment groups received 100 μg/s.c./qw, unless otherwise specified; AD: Alzheimer’s disease; Aβ: Aβ; MWMT: Morris water maze test; RAWM: radical arm water maze; SGZ: subgranular zone; m: male; qm: monthly; BMT: Barnes maze test; MΦBM: bone-marrow-derived monocytes/macrophages; DG: dentate gyrus; MEA: multi-electrode analysis; f/oAβ42: fibrillar/oligomeric Aβ42; IOP: intraocular pressure; RT-PCR: real time-polymerase chain reaction; WB: Western blot; EGR1: early growth response gene 1; MMP9: matrix metallopeptidase 9; FAD—familial Alzheimer’s disease; DT—diphtheria toxin. ** CD115+ MoBM: Adoptive transfer of CD115+ bone-marrow-derived monocytes isolated from 8- to 10-week-old GFP-labelled C57BL/6 mice. MΦBM: bone-marrow-derived monocytes/macrophages isolated from 8- to 10-week-old C57BL/6 mice injected monthly for 2 months. Murine models (listed age is at the start of the experiment): * Double-transgenic amyloid precursor protein (APP) barring the Swedish FAD mutations (K595N, M596L) + presenilin 1 (PS1) with deletion in exon 9 mice, called APPSWE/PS1ΔE9 on C57/BL6-SJL background. @ The APPSWE/PS1ΔE9 on C57BL/6 background [B6.Cg-Tg (APPswe, PSEN1dE9) 85Dbo/J mouse strain]. # Chimeric APPSWE/PS1ΔE9 on C57BL/6 background after lethal whole-body irradiation and reconstitution with 5 × 106 bone marrow cells isolated from 2-month-old C57BL/6 J-CD11cDTR–GFP mice. The latter is a transgenic CD11cDTR–GFP mouse, carrying a transgene encoding a human diphtheria toxin receptor (DTR)–green fluorescent protein (GFP) fusion protein under control of the murine CD11c promoter [130]. ^ Heterozygous 5XFAD transgenic mice (Tg6799; on a C57/BL6-SJL background) co-overexpressing FAD mutant forms of human APP (the Swedish mutation, K670N/M671L; the Florida mutation, I716V; and the London mutation, V717I) and mutant PS1 (M146L/L286V) transgenes under control of the neuron-specific mouse Thy-1 promoter. $ 3xTg AD mice express mutated human APP Swedish, MAPT P301L, and PSEN1 M146V genes under transcriptional control of the neuron-specific mouse Thy1.2 promoter [131]. Control mice: Wild type (WT) non-transgenic (Tg) littermates. cells-11-01578-t007_Table 7 Table 7 Animal Studies Examining Alternative Uses of Glatiramer Acetate in Parkinson’s Disease. Disease Model Research Model and Methodology Findings Ref. PD 7–10-week-old m&f C57BL/6 mice MTPT (neurotoxin PD model) MTPT mice—injected w/ serum from mice immunized with GA 200 μg/s.c. weekly PBS-injected controls (n = 14) TH+-neuron levels correlated to immune cell number (regression analysis, r = 0.96) Protected SN from MPTP-induced neurodegeneration Enhanced anti-inflammation cytokine proliferation and BDNF/GDNF Inhibited dopaminergic neurodegeneration Improved density of dopaminergic striatal termini Reduced disease progression, increased BDNF/GDNF, IL-4 and IL-10 Laurie, C. et al., 2007 [137] PD 8-week-old m&f C57BL/65 MPTP mice GA 3.5 mg/kg/s.c./daily (n = 25) PBS-injected (n = 30) and naïve wild type (n = 24) GA vs. controls Diggigait test: improvement/reversal of motor dysfunction TH: smaller decrease 16% (p = 0.1953) 51% increase in grip strength (F(5,90) = 63.38, p < 0.0001) Brake time was restored, equal to healthy controls (p = 0.0439) Higher levels of TH linked to enhanced cognition and motor activities Churchill, M. et al., 2019 [135] All studies utilized the MPTP PD model; MPTP: 1-Methyl-1,2,3,6-Tetrahydropyridine; TH: Tyrosine Hydroxylase; PD: Parkinson Disease; SN: Substantia Nigra. cells-11-01578-t008_Table 8 Table 8 Animal Studies Examining Alternative Uses of Glatiramer Acetate in Huntington’s Disease. Disease Model Research Model and Methodology Findings Ref. HD 10–12-week-old m N171-82Q and f C3B6F1 mice (n = 6–7 mice/group) Induced CAG repeat GA-immunized, 750 μg/s.c./qd PBS-injected and naïve wild type GA vs. controls OFBA decreased hyperactivity and stereotypic behavior (F(1,110) = 8.81; p = 0.01) Elevated BDNF in striatal cells: [2.48 pg/mg] vs. [0.90 pg/mg] (p = 0.003) Prevented onset of motor deficits and cognitive issues—particularly if treatment began early in disease process Corey-Bloom, C. et al., 2014 [142] HD 10-week-old m&f B6CBA, C57BL/6, FVB and YAC128 mice (n = 4–10 mice/group) GA-immunized, 100 μg/s.c./qw vs. PBS-injected GA vs. controls Increased average lifespan; increased levels of active BDNF Rotarod and Clasping Score [143]: improved motor performance OFBA: improved cognitive behaviors Preservation of damaged motor neurons Lengthened lifespan, improved cognition and motor function Reick, C. et al., 2016 [140] HD 1-year-old m&f CAG140 rats and 7-month-old m&f N171-82Q mice HD rats (n = 18), GA 100 μg/s.c./q5w and GA 625 μg/s.c./q3w PBS-injected, (n = 30) GA vs. controls ATM [144]: Jump time (p = 0.029; F(1,150) = 4.8) OFBA and Rotarod: Less stereotypic time (F(1,150) = 16.5; p < 0.0001) Climbing test [145]/Grip test [146]: Resting time improved (F(1,150) = 9.0; p = 0.003) Delayed disease onset and improved lifespan Elevated BDNF and decreased proinflammatory cytokines Improved stereotyped behavior, reduced behavioral issues, delayed disease onset and prolonged lifespan Corey-Bloom, J. et al., 2017 [139] All studies utilized the SOD1-induced HD model; HD: Huntington’s disease; OFBA: open field behavioral analysis; ATM: alternating T-maze. cells-11-01578-t009_Table 9 Table 9 Animal Studies Examining Alternative Uses of Glatiramer Acetate in Neuropsychology. Disease Model Research Model and Methodology Findings Ref. Psych 8–12-week-old m C57BL/6J and BALB/c/OLA mice RAG ½ knockout/nude mice (SCID model) [149] MK-80 [150] and AMPH [151] GA-immunized, qd, (n = 6) vs. PBS-injected (n = 7) Less cognitive impairment linked to psychometric agents (MK-80 and AMPH) PPI [152]: Enhanced communicative behavior MWMT: Sensorimotor dysfunction was prevented Enhanced cognition and behavior, improved impairments induced by psychomimetic agents Kipnis, J. et al., 2004 [103] Neuro psych 6-week-old m Sprague–Dawley rats (n = 7 rats/group) Cranially irradiated [153] GA-immunized, qw PBS-injected and naïve non-irradiated rats MWMT: Reversal of behavior impairment; better cognitive abilities; shorter latency times (p < 0.01) Restored hippocampal neurogenesis Increased BDNF, IGF-1, and IFN-γ levels; decreased TNF-α, IL-6, and IL-4 levels Reversal of cognitive deficits, enhanced GA-mediated/immune-induced hippocampal neurogenesis and increased protective cytokines He, F. et al., 2014 [154] Neuro psych 12–16-week-old f BALB/c mice (n = 25 mice/group) CMS exposure [155] GA-immunized, qw PBS-injected CMS and non-CMS OFBA and OIPT [156] GA vs. controlReversed effects of CMS on learning and memory (p < 0.0001) Regulated hipp. NOS activity/reduction in ROS Number of crossings: (t(18) = 4.461, p < 0.001) Rearing: (t(18) = 7.313, p < 0.001) Corner time: (t(18) = 3.478, p < 0.001) Improved cognition and neuronal functioning and repaired cortical damage Pascuan, G. et al., 2015 [157] Neuro psych 6–8-week-old m C57BL/6 mice (n = 6–10 mice/group) LPS induction [158] (memory impairment model) GA-immunized, 250 μg/s.c./qw vs. PBS-injected GA vs. controlYMT [159] and PAT [160]: Less time exploring maze arms; [F(2,20) = 7.407], (p < 0.01, [F(2, 20) = 10.433]) Increased novel arm time; improved spatial recognition and memory Shock fear memory: Shorter latency times (p < 0.01) Improved retention trials [F(1,11) = 16.773; p < 0.001] Neuroprotective effects were notably seen in a dose-dependent manner Mohammadi, F. et al., 2016 [161] Test subjects in the treatment group received 100 μg/s.c., unless otherwise specified; Neuropsych: Neuropsychology; Psych: Psychology; SCID: severe combined immunodeficiency; MK-80: dizocilpine maleate; AMPH: d-amphetamine sulfate; PPI: pre-pulse inhibition; MWMT: Morris water maze test; CMS: chronic mild stress; OFBA: open field behavioral analysis; OIPT: object in place test; NOS: nitrous oxide; ROS: reactive oxygen species; LPS: lipopolysaccharide; YMT: Y-maze test; PAT: passive avoidance task. cells-11-01578-t010_Table 10 Table 10 Animal Studies Examining Alternative Uses of Glatiramer Acetate in Vascular Dementia and Central Nervous System Ischemia. Disease Model Research Model and Methodology Findings Ref. CNSi 12-week-old m Sprague–Dawley rats tMCAo (CNSi model) [166] GA-immunized (n = 6) PBS-injected (n = 6) LSS: Improvement in neurological function (1.2 ± 0.4 and 2.8 ± 0.5; p = 0.008) Higher tissue preservation Reduced infarct volume (4.8 ± 1.5), vs. controls (32.2 ± 8.6; p = 0.004)Neuroprotective effects; improvements in neurocognition and infarct volume Ibarra, A. et al., 2007 [164] CNSi 10-week-old m Lewis rats Chronic cerebral hypoperfusion (VD model) GA-immunized, 100 μg/s.c./qw (n = 8) PBS-injected (n = 8) MWMT, GA vs. control Shorter latency swim times (p < 0.01) More time in novel maze areas (p < 0.5) Higher number of platform crossings (p < 0.01) Reduced # of GFAP+ cells in hippocampus (p < 0.01) Less IFN-γ, IL-6, and TNF-α (p < 0.05, p < 0.01, p < 0.01) Increased BDNF in hippocampus (p < 0.01) Reduced pathology changes and attenuated cell loss Restored brain’s immune microenvironment Restored cognitive and neuronal functioning; slowed disease progression Chen, L. et al., 2015 [167] CNSi 7-week-old Sprague–Dawley m rats (n = 4–8 rats/group) GA-immunized vs. PBS-injected controls GA vs. control [mean ± SD]LSS: [1.0 ± 0.8] vs. [1.9 ± 0.6] (p < 0.01) Infarcts’ volume: [8.9 ± 1.9] vs. [18.5 ± 1.1%] (p < 0.05) Cognitive function recovery time: [0.5 ± 0.5] vs. [1.4 ± 0.5] (p < 0.01)Neurogenesis, ipsilateral SVZ: [260 ± 86] vs. [155 ± 61] (p < 0.05) Neurogenesis, contralateral SVZ: (170 ± 63 vs. 107 ± 53; p < 0.05) Enhanced neuroprotective/neural progenitor cells in SVZ, SGZ, and cortex Enhanced neurogenesis and decreased infarct volume. Improved neurogenesis, less cognitive decline, reduced infarct volume, accelerated movement recovery Cruz, Y. et al., 2015 [168] CNSi 5-week-old m Sprague–Dawley rats GA-immunized (n = 6) PBS-injected (n = 7) and naïve non-tMCAo (n = 6) GA vs. control LSS: Reduction in neuro deficit (p < 0.001) Upregulated BDNF, IGF-1, and IL-10; downregulation of IL-17 Increase neuroblasts, SVZ (p < 0.0001) and neurogenesis, SVZ/SGZ Increased neuroblasts, SVZ—negative correlation w/neuro deficits (r = −0.86, p < 0.05) Neurogenesis SVZ, reduced neuro deficits (r = 0.86, p < 0.05) Ameliorated neuro deficits, more neurogenesis and increased BDNF Cruz, Y. et al., 2018 [169] CNSi 6-week-old m C57BL/6J mice Induction of diabetes and cerebral ischemia by pMCAo [170] GA-immunized, q3d (n = 16) vs. PBS-injected (n = 17) GA vs. controlNormalized neuro scores in sensorimotor domains (p = 0.0018) Increased BMT scores (p < 0.01) Retention task [171] was improved Grip test/beam walking [172] better long-term spatial memory BMT and Pole test [173]: increased latency (p < 0.05) Reduced infarct volume by 40% [11.78 ± 1.60 mm3] (p = 0.016) Less proinflammatory mediators: COX2, CD32, TNFα, and IL-1β Reduced infarct volume, little/no cognitive impairments or long-term deficits Mangin, G. et al., 2019 [174] Test subjects in the treatment group received 200 μg/s.c./qw, unless otherwise specified; VD: vascular dementia; CNSi: central nervous system ischemia; pMCAo: permanent middle cerebral artery occlusion; q3d: every 3 days; SVZ: subventricular zone; SGZ: subgranular zone; DG: dentate gyrus; tMCAo: temporary middle cerebral artery occlusion. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094894 ijms-23-04894 Article Calprotectin and Imbalances between Acute-Phase Mediators Are Associated with Critical Illness in COVID-19 Kassianidis Georgios 1 https://orcid.org/0000-0001-7942-6159 Siampanos Athanasios 2 Poulakou Garyphalia 3 Adamis George 4 Rapti Aggeliki 5 https://orcid.org/0000-0003-3958-2266 Milionis Haralampos 6 https://orcid.org/0000-0001-7075-8464 Dalekos George N. 7 Petrakis Vasileios 8 Sympardi Styliani 9 Metallidis Symeon 10 Alexiou Zoi 11 Gkavogianni Theologia 2 https://orcid.org/0000-0003-4713-3911 Giamarellos-Bourboulis Evangelos J. 2* https://orcid.org/0000-0002-1598-460X Theoharides Theoharis C. 12131415* Novick Daniela Academic Editor 1 Intensive Care Unit, Korgialeneion-Benakeion Athens General Hospital, 115 26 Athens, Greece; georgekassianidis@gmail.com 2 4th Department of Internal Medicine, ATTIKON University General Hospital, Medical School, National and Kapodistrian University of Athens, 1 Rimini Street, 124 62 Athens, Greece; thansiampanos@gmail.com (A.S.); gkavtheo@yahoo.gr (T.G.) 3 3rd Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, 115 27 Athens, Greece; gpoulakou@gmail.com 4 1st Department of Internal Medicine, G. Gennimatas General Hospital of Athens, 115 27 Athens, Greece; geo.adamis@gmail.com 5 2nd Department of Pulmonary Medicine, Sotiria General Hospital of Chest Diseases, 115 27 Athens, Greece; aggeliki.rapti@gmail.com 6 1st Department of Internal Medicine, Medical School, University of Ioannina, 455 00 Ioannina, Greece; hmilioni@uoi.gr 7 Department of Medicine and Research Laboratory of Internal Medicine, National and European Expertise Center in Autoimmune Liver Diseases, General University Hospital of Larissa, 412 21 Larissa, Greece; georgedalekos@gmail.com 8 2nd Department of Internal Medicine, Medical School, Democritus University of Thrace, 681 00 Alexandroupolis, Greece; vasilispetrakis1994@gmail.com 9 1st Department of Internal Medicine, Thriasio General Hospital of Eleusis, 196 00 Magoula, Greece; lianasympa@hotmail.com 10 1st Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, 546 21 Thessaloniki, Greece; metallidissimeon@yahoo.gr 11 2nd Department of Internal Medicine, Thriasio General Hospital of Eleusis, 196 00 Magoula, Greece; z_alexiou@yahoo.gr 12 Laboratory of Molecular Immunopharmacology and Drug Discovery, Department of Immunology, Tufts University School of Medicine, Boston, MA 02111, USA 13 School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, MA 02111, USA 14 Department of Internal Medicine, Tufts University School of Medicine and Tufts Medical Center, Boston, MA 02111, USA 15 Institute of Neuro-Immune Medicine, Nova Southeastern University, Clearwater, FL 33759, USA * Correspondence: egiamarel@med.uoa.gr (E.J.G.-B.); drtheoharides@gmail.com (T.C.T.); Tel.: +30-210-58-31-994 (E.J.G.-B.); Fax: +30-210-53-26446 (E.J.G.-B.) 28 4 2022 5 2022 23 9 489412 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 trajectory from moderate and severe COVID-19 into acute respiratory distress syndrome (ARDS) necessitating mechanical ventilation (MV) is a field of active research. We determined serum levels within 24 h of presentation of 20 different sets of mediators (calprotectin, pro- and anti-inflammatory cytokines, interferons) of patients with COVID-19 at different stages of severity (asymptomatic, moderate, severe and ARDS/MV). The primary endpoint was to define associations with critical illness, and the secondary endpoint was to identify the pathways associated with mortality. Results were validated in serial measurements of mediators among participants of the SAVE-MORE trial. Levels of the proinflammatory interleukin (IL)-8, IL-18, matrix metalloproteinase-9, platelet-derived growth factor (PDGF)-B and calprotectin (S100A8/A9) were significantly higher in patients with ARDS and MV. Levels of the anti-inflammatory IL-1ra and IL-33r were also increased; IL-38 was increased only in asymptomatic patients but significantly decreased in the more severe cases. Multivariate ordinal regression showed that pathways of IL-6, IL-33 and calprotectin were associated with significant probability for worse outcome. Calprotectin was serially increased from baseline among patients who progressed to ARDS and MV. Further research is needed to decipher the significance of these findings compared to other acute-phase reactants, such as C-reactive protein (CRP) or ferritin, for the prognosis and development of effective treatments. ARDS COVID-19 cytokines IL-18 IL33r IL-38 S100A8/A9 Hellenic Institute for the Study of SepsisAll reagent kits were provided for free by Bio-Techne (Minneapolis, MN, USA). Funding was provided in part by the Hellenic Institute for the Study of Sepsis. Collection of biomaterial and clinical information from patients enrolled in the ESCAPE trial was funded by the Horizon 2020 Grant RISCinCOVID. ==== Body pmc1. Introduction The SARS-CoV-2 coronavirus infects human cells by first binding to their surface receptor, angiotensin-converting enzyme 2 (ACE2), via its corona spike protein [1], leading to the development of COVID-19 [2,3]. This condition involves a complex immune response that includes the release of a “storm” of acute phase mediators [4,5,6]. This is a positive response of the host to prime recruitment of neutrophils and other inflammatory cells and associated production of cytokines and chemokines [7] but may reflect a worsening of the clinical situation if the cause is not eliminated. Prominent among them have been IL-6 [8,9,10] and IL-1β [11], but also the family of S100 alarmins, among which S100A8/A9 is otherwise known as calprotectin [12]. This knowledge led to early consideration of severe COVID-19 as a hyperinflammatory disorder and encouragement of the administration of modifiers of the biological response, such as dexamethasone, tocilizumab, anakinra and baricitinib, early in the course of management. Although this treatment strategy appears plausible, its rationale remains a field of active debate. This debate is stimulated by the contribution of acute-phase mediators to the immune defense and by the lack of knowledge as to whether hyperinflammation is still present at the time point of acute respiratory distress syndrome (ARDS) necessitating mechanical ventilation (MV). It is thus necessary to better identify what drives the transition from moderate and severe COVID-19 to severe ARDS and MV after the initial viral infection. This may be the only way to prevent or efficiently address the most ominous consequences of COVID-19. In this paper, we investigated serum levels of alarmins, as well as pro- and anti-inflammatory molecules leading to ARDS and MV and how their presence tracks with disease severity. 2. Results 2.1. Study Participants The sampling for the study took place between April and November 2020. Serum samples from 181 patients and 40 non-infected comparators were studied. Among the patient population, on the day of blood sampling, 19 patients were asymptomatic, 42 patients had moderate disease, 78 patients had severe disease, and 42 patients had ARDS and were on MV. Sampling took place within the first 24 h after admission. Patients with ARDS on MV had higher sequential organ failure assessment (SOFA) scores, lower respiratory ratios and higher circulating C-reactive protein and ferritin (Table 1). None of the 181 patients was in need of hemodialysis at the time of blood sampling. Patients with ARDS under MV were sedated; mean ± SD creatinine on the day of sampling was 1.0 ± 0.2 mg/dL; mean ± SD albumin was 3.2 ± 0.5 g/dL. In the first stage of the study, the samples were analyzed in an effort to identify a set of mediators that may drive progression toward ARDS and MV. In the second stage of the study, the mediators were serially followed over time to define if the levels change over-time until ARDS and MV (Figure 1). 2.2. First Stage: Presence of Inflammation-Associated Mediators Among the proinflammatory mediators, interleukin (IL)-1β, IL-6, IL-17, IL-33 and tumor necrosis factor alpha (TNFα) did not differ between the stages of severity. However, IL-8 and IL-18 levels were significantly higher among patients with critical ARDS necessitating MV compared to less severely ill patients. Among anti-inflammatory cytokines, IL-33r (soluble ST2) levels were significantly higher among patients with critical ARDS. IL-1ra (soluble receptor antagonist) levels were higher among patients with mild to critical COVID-19, although there was no significant difference between patients with severe and critical disease. IL-10 did not differ among patients and controls. IL-38 levels were decreased in asymptomatic patients relative to patients at more severe stages (Figure 2). Interferons did not differ between patients (Supplementary Figure S1). Platelet-derived growth factor (PDGF)-B and, to a lesser extent, PDGF-A were increased among critically ill ARDS patients; PAF did not differ. The same was the case for calprotectin and matrix metalloproteinase (MMP)-9. PAF and S100B did not differ among different stages of severity (Figure 3). 2.3. First Stage: Associations between Inflammatory Mediators and Progression into Acute Respiratory Distress Syndrome (ARDS) Necessitating Mechanical Ventilation (MV) ROC curve analyses identified that IL-8, IL-18, MMP-9, IL-33r, PDGF-B and calprotectin were associated with ARDS necessitating MV (Figure 4A). The cut-offs of each of the six mediators providing the best trade-off of sensitivity and specificity were defined and entered into the equation of multivariate analysis. Only increased IL-33r, increased PDGF-B and increased calprotectin were found to be drivers of ARDS necessitating MV (Figure 4B). 2.4. First Stage: Associations between Biomarkers and 28-Day Mortality Analysis involved hospitalized patients with moderate and severe COVID-19, as well as patients with ARDS necessitating MV. For this analysis, we decided to implement a pathway-like division of biomarkers into clusters. To this end, nine pathways were defined as follows: (a) IL-1ra activation, when both IL-1β and IL-1ra were above the median of the entire cohort; (b) IL-6 pathway, when IL-6 was above the median of the entire cohort; (c) IL-18 pathway, when IL-18 was above the cut-off defined for critical illness; (d) neutrophil activation, when at least two of the following conditions were met: IL-8 > 100 pg/mL, MMP-9 > 870 pg/mL or IL-17 above the lower limit of detection; (e) interferon pathway, when at least one of the three measured interferons was above the median of the entire cohort; (f) IL-33 pathway, when IL-33r was above 170 ng/mL; (g) IL-38 pathway, when IL-38 was above the median of the entire cohort; (h) PDGF-B pathway, when PDGF-B was above 2.7 ng/mL; and (i) calprotectin pathway, when calprotectin was above 7.8 μg/mL (Figure 5 and Figure 6A). Multivariate ordinal regression analysis showed that the pathways of IL-6, IL-33 and calprotectin were associated with allocation into more severe states of the WHO-CPS after 28 days (Figure 6B). On the contrary, IL-1ra and IL-38 pathways were associated with allocation into less severe states of the WHO-CPS after 28 days. The IL-6, IL-33 and calprotectin pathways were independent drivers for mortality, acting synergistically. On the contrary, the IL-1ra and IL-38 pathways did not affect survival (Figure 6C,D). 2.5. Second Stage: Validation of the Role of S100A8/A9 (Calprotectin) in Progression into ARDS Necessitating MV The SAVE-MORE trial enrolled patients who were in neither the ARDS nor MV category [13]. Among participants allocated to placebo treatment, samples collected serially from patients who progressed into ARDS and MV were analyzed. This was done because patient follow-up under placebo is considered to represent the progression of COVID-19 under the current standard-of-care management. At baseline, circulating levels of calprotectin and PDGF-B were similar among patients who eventually progressed into ARDS and MV and among those who did not progress into ARDS and MV (Figure 7A,B). On day 4, there was a trend toward increasing calprotectin from baseline among patients who developed ARDS and necessitated MV. This trend became a largely significant difference on day 7 (Figure 7C). No similar changes were found for PDGF-B (Figure 7D). Following ROC curve analysis, it was found that any increase in calprotectin from baseline was associated with the development of ARDS and MV. This association was proven to be independent of disease severity and of dexamethasone treatment after multivariate forward stepwise Cox regression analysis (Figure 7E). None of these patients needed hemodialysis before day 8 (Figure 7F). 3. Discussion Our results highlight, for the first time, the conditions necessary for patients with COVID-19 to demonstrate the most worrisome features of critical illness with ARDS necessitating MV. The pathways of danger-associated molecular patterns (DAMPs), IL-33 (ST2) and coagulation drive ARDS and MV, whereas final outcome is dominated by excess of a proinflammatory state through the IL-6, IL-33 and DAMPs pathways, as well as by decreased levels of the anti-inflammatory pathways IL-38 and IL-1ra. Several studies suggest that serum calprotectin is increased with COVID-19 severity. Twelve studies were subjected to systemic review [14] and eight studies were meta-analyzed [15]. Our findings regarding elevated serum levels of S100A8/A9 (calprotectin) are in line with previous results in the serum and in the bronchoalveolar lavage of COVID-19 patients [16,17], as well as with the results of the systemic review [14] and of the meta-analysis [15], showing, as we did, that calprotectin levels are higher among patients with the more severe state of disease. Most of these studies enrolled limited numbers of patients. Among these studies, only one failed to show that calprotectin is an indicator of unfavorable outcome. This study reported on the measurements of calprotectin of 222 hospital admissions in an emergency department; 25 patients had an unfavorable outcome, which was defined as a composite of need of non-invasive ventilation, MV or death [18]. Our study presents two main differences in design compared to previous publications: (a) the comparison of the trajectories of COVID-19 from asymptomatic to moderate severe and critical disease where calprotectin steadily increases; and (b) the independent association of calprotectin with the progression into critical illness and unfavorable outcome through a pathway-like approach, including multivariate analysis. Others have also recently reported that calprotectin is further increased from a state of non-invasive ventilation to the need of MV [19]. It is known that SARS-CoV-2 per se cannot elicit large amounts of inflammatory mediators leading to ARDS and MV [20]. However, rapid viral replication in the lungs leads to the destruction of lung epithelial cells and to the subsequent release of intracellular DAMPs, such as calprotectin. Our findings suggest that as the disease progresses and the patient worsens towards ARDS, increased calprotectin could contribute to the need for MV. This DAMPs pathway acts synergistically with the IL-6 and IL-33 pathways, mediating unfavorable outcomes. The crucial role of calprotectin in the pathogenesis of COVID-19 is further supported by a mouse model of lethal SARS-CoV-2 infection in which expression of S100A8 in the lungs was increased, whereas infection by the influenza A virus, encephalomyelitis virus and herpes simplex virus were not accompanied by an increase in the expression of S100A8. Treatment of mice infected by SARS-CoV-2 with the calprotectin inhibitor paquinimod increased survival by 100% and attenuated infiltration of the lungs by neutrophils, suggesting a possible role of calprotectin for neutrophil chemotaxis and activation [21]. Although PDGF-B was not increased over time towards progression into ARDS and MV, the increased circulating PDGF-B described herein is interesting, given reports of widespread pulmonary microthromboses in lungs of deceased COVID-19 patients [22]. Our findings of increased levels of IL-1ra and IL-33r are intriguing, as serum levels of IL-1β and IL-33 levels were not significantly increased. This apparent contradiction may be explained by the autocrine mode of action of these cytokines following their production, implying that COVID-19 patients, especially those with severe disease, produce soluble IL-1ra and IL-33r (sST2) in an apparent effort to curtail the effect of IL-1β and IL-33, respectively. Elevated sST2 has also been reported in severe (especially non-surviving) patients with COVID-19 [23]. A recent publication reported that published scRNseq data from bronchoalveolar lavage fluid from patients with mild to severe COVID-19 contained a population of cells that produce IL-33 and correlate with severity of disease [24]. Two other publications reported a unique correlation of IL-12p70/IL-33 with disease severity [25] and increased expression of IL-33 in cultured epithelial cells infected with SARS-CoV-2 [26]. Taken together, these findings seem to imply that there may be local synthesis of IL-33, especially in the lungs, leading to reactive production of IL-33r (sST2). IL-33 can stimulate resident mast cells to produce impressive amounts of proinflammatory cytokines [27,28], and the findings of increased IL-33r should be interpreted as a counterbalance to the increased IL-33. Similarly to the increased levels of IL-1ra and IL-33r, the anti-inflammatory IL-38 was increased only in asymptomatic patients as compared to non-infected comparators but decreased significantly in the more severe patient groups. This finding implies that patients cannot produce sufficient IL-38 to counteract the proinflammatory cytokines produced during COVID-19. IL-38 belongs to the IL-1 family [29] and has been reported to exhibit anti-inflammatory activity [30]. IL-38 exists intracellularly as a precursor in full-length form and must be cleaved at the N terminus before it is secreted extracellularly in an active form [31]. We showed that IL-38 can inhibit the release of IL-1β from cultured human microglia stimulated by bacterial lipopolysaccharide (LPS) [32]. The final outcome of patients appears to be determined by the excess activation of the IL-6, IL-33 and DAMP pathways, and the anti-inflammatory IL-1ra and IL-38 pathways are not sufficient to counterbalance them. A recent paper reported that elevated plasma levels of IL-6, IL-10 and IP-10 anticipated clinical progression of COVID-19 patients [33]. Our results are in line with the positive treatment outcomes with IL-6 receptor antagonists and with anakinra (the recombinant non-glycosylated form of IL-1ra), as they have shown the need to attenuate the increased IL-6 response and to increase the reduced IL-1ra responses [34]. Tocilizumab and sarilumab were shown to decrease the number of days under organ dysfunction and 28-day mortality in the REMAP-CAP [35] and RECOVERY [36] platform adaptive trials respectively. In these trials, the two IL-6 receptor antagonists were administered in patients already diagnosed with critical illness. In the open-label SAVE trial [37] and in the double-blind, randomized trial SAVE-MORE [13], anakinra was administered to hospitalized non-critical patients with plasma levels of the biomarker suPAR (soluble urokinase plasminogen activator receptor) 6 ng/mL or more; suPAR was used in these studies as a biomarker of an attack of the host by DAMPs. Results of the large-scale RECOVERY study show that the use of dexamethasone improves outcomes in COVID-19 patients, mainly those requiring oxygen and under MV [38]. Part of the action of dexamethasone is associated with decreased neutrophil production of S100A8/A9 [39]. This is one of few studies reporting on coadministered drugs among mechanically ventilated patients with ARDS. Unfortunately, information on exact dosing and nutrition was not provisioned to be captured because such information was beyond the scope of the study. This can be conceived as a limitation. 4. Methods 4.1. Patient Cohorts Studied patients were adults with molecular detection of SARS-CoV-2 and were classified into four groups using the WHO classification of COVID-19 severity: (a) asymptomatic, (b) hospitalized with moderate COVID-19, (c) hospitalized for severe COVID-19 or (d) hospitalized with acute respiratory distress syndrome (ARDS) necessitating mechanical ventilation (MV). Blood samples (10 mL) were collected in pyrogen-free tubes without anticoagulant (Becton Dickinson, Cockeysville Md) within the first 24 h after admission in the emergency department, the general ward or the intensive care unit. Patients had already participated as comparators, receiving usual care in the ACHIEVE [40], SAVE [37] and ESCAPE [41] studies. Patients were enrolled after written informed consent was provided by themselves or their legal representatives. A volume of 10 ml of blood was also collected from comparators matched for age and sex with the patients and who were admitted to emergency departments for unspecified complaints. These comparators were adults without any specific diagnosis of disease; this was certified by a phone call after 30 days. Their inclusion was provisioned in the above studies, and they also signed a written informed consent. In order to provide evidence for the role of the mediators for progression into ARDS necessitating MV, samples collected from 52 patients participating in the SAVE-MORE trial were studied. SAVE-MORE is a double-blind, randomized clinical trial where patients were allocated to treatment with placebo or anakinra plus standard of care to prevent progression into severe respiratory failure [13]. The studied samples were from patients with severe disease in need of treatment with oxygen and who were allocated to the placebo group so that comparative levels of the mediators at serial time points may dictate their role towards development into ARDS and MV. With this aim, only patients from the placebo group not under modulation with biologicals during all three time periods of sampling (baseline, day 4 and day 7) were studied; 19 patients progressed into ARDS and MV within the first 28 days; another 33 patients matched for age, gender and comorbidities who did not progress into ARDS and MV were studied as comparators. 4.2. Laboratory Assays All blood samples were processed immediately, and the serum was stored at −80 °C until assayed. Levels of biomarkers were quantified by using commercially available kits of enzyme immunosorbent assays from Bio-Techne (R&D Systems, Minneapolis, MN, USA) according to the manufacturer’s instructions. The lower limits of detection were 16 pg/mL for tumor necrosis factor-alpha (TNFα), 8 pg/mL for interleukin (IL)-1β, 31 pg/mL for IL-1ra (receptor antagonist), 40 pg/mL for IL-6, 31 pg/mL for IL-8 and IL-10, 8 pg/mL for IL-17, 62 pg/mL for IL-18, 31 pg/mL for IL-33r (receptor), 62 pg/mL for IL-38, 156 pg/mL for interferon (IFN) alpha; 78 pg/mL for IFNβ, 156 pg/mL for IFNγ, 80 pg/mL for platelet activation factor (PAF), 313 p/mL for platelet-derived growth factor (PDGF)-A and PDGF-B, 61 pg/mL for S100A8/A9, 31 pg/mL for matrix metallopeptidase (MMP)-9 and 46 pg/mL for S100B. 4.3. Study Endpoints The primary study endpoint was to define a set of cytokines and inflammatory mediators that are independently associated with progression into critical ARDS necessitating mechanical ventilation. The secondary study endpoints were to define a set of cytokines and inflammatory mediators that are independently associated with the outcome of COVID-19 after 28 days, as this is expressed both by the strata of the WHO Clinical Progression Scale (CPS) and by mortality. 4.4. Statistical Analysis Concentrations of biomarkers between groups of patients were compared using the Mann–Whitney non-parametric U test following Bonferroni correction for multiple testing. Receiver operator characteristic (ROC) curve analysis was performed for each of the measured mediators to define a cut-off that can significantly discriminate patients with ARDS necessitating MV; the areas under the curve of the ROC (AUC), 95% confidence intervals (CIs) and p values were determined. For significant variables, the cut-off concentration providing the best trade-off for sensitivity and specificity was determined by the Youden index. In order to define the variables that were drivers of ARDS necessitating MV, forward stepwise logistic regression analysis was performed. ARDS necessitating MV was entered into the equation as a dependent variable and all significant mediators at the predefined cut-offs as independent variables. Mediators were divided with a pathway-like approach. Nine pathways were defined as follows: (a) IL-1ra activation using IL-1β and IL-1ra; (b) IL-6 pathway using IL-6; (c) IL-18 pathway using IL-18; (d) neutrophil activation using IL-8, MMP-9 and IL-17; (e) interferon pathway using the three measured IFNs; (f) IL-33 pathway using IL-33 and IL-33r; (g) IL-38 pathway using IL-38; (h) platelet-activation pathway using PAF, PDGF-A and PDGF-B; and (i) calprotectin/alarmin pathway using S100A8/A9. The pathways were defined in a hierarchical order, using the cut-offs of ROC curve analysis as the first step in the case of significant mediators and the median levels of the entire cohort as the second step (Figure 5). Patients were subgrouped as belonging or not belonging to each of the nine pathways of activation (Yes/No). Comparisons of the WHO-CPS strata in each subgroup were performed by univariate ordinal regression analysis, followed by multivariate ordinal regression analysis. Next, 28-day mortality was compared between subgroups by Cox forward stepwise multiple regression analysis. In this analysis, 28-day mortality was the dependent variable, and variables significant for WHO-CPS were the independent variables. The fold change of mediators determined to be associated with ARDS and MV on days 4 and 7 from baseline was calculated and compared by the Mann–Whitney U test. The cut-off of fold change that was associated with ARDS and MV was defined by the area under the ROC curve using the Youden index. The value of this cut-off was further validated by forward stepwise Cox regression analysis. Progression into ARDS and MV was the dependent variable; the defined cut-offs, baseline severity and dexamethasone treatment were the independent variables. 5. Conclusions Multivariate ordinal regression showed that IL-6, IL-33 and calprotectin pathways were significantly associated with worse outcome. Further research is needed to decipher the significance of these findings compared to other acute-phase reactants, such as C-reactive protein (CRP) or ferritin. Our results further suggest that the innate increase in IL-1ra and IL-33r, along with the drop in IL-38, is not sufficient to halt the progression of COVID-19. Attenuating the IL-6, IL-33 and DAMP pathways while administering IL-1ra, IL-33r and, potentially, recombinant IL-38, seems to be the most promising strategy to combat severe COVID-19. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094894/s1. Click here for additional data file. Author Contributions G.K., A.S., G.P., G.A., A.R., H.M., G.N.D., V.P., S.S., S.M. and Z.A. collected patient data, revised the manuscript and gave permission for the version to be submitted. T.G. performed measurements, revised the manuscript and gave permission for the version to be submitted. E.J.G.-B. supervised the study, analyzed and plotted the results, wrote the manuscript and takes full responsibility for data integrity. T.C.T. conceived the study, secured the reagents, participated in data analysis and wrote the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Studies ACHIEVE, SAVE and ESCAPE were approved by the National Ethics Committee of Greece and by the National Organization for Medicines of Greece (approval numbers 45/20 and IS 36/20, respectively, for ACHIEVE; approval numbers 38/20 and IS 28/20 respectively for SAVE; and approval numbers 30/20 and IS 021-20, respectively, for ESCAPE). The SAVE-MORE was approved by the National Ethics Committee of Greece (approval 161/20) and by the Ethics Committee of the National Institute for Infectious Diseases Lazzaro Spallanzani, IRCCS in Rome (approval 1 February 2021). Informed Consent Statement Informed consent was provided by patients or legal representatives for patients unable to consent. Data Availability Statement Data are available from the corresponding author upon request. Conflicts of Interest G. Poulakou has received independent educational grants from Pfizer, MSD, Angelini and Biorad. H. Milionis reports receiving honoraria, consulting fees and non-financial support from healthcare companies, including Amgen, Angelini, Bayer, Mylan, MSD, Pfizer and Servier. G. N. Dalekos is an advisor or lecturer for Ipsen, Pfizer, Genkyotex, Novartis and Sobi; received research grants from Abbvie and Gilead; and has served as PI in studies for Abbvie, Novartis, Gilead, Novo Nordisk, Genkyotex, Regulus Therapeutics Inc., Tiziana Life Sciences, Bayer, Astellas, Pfizer, Amyndas Pharmaceuticals, CymaBay Therapeutics Inc., Sobi and Intercept Pharmaceuticals. E. J. Giamarellos-Bourboulis has received honoraria from Abbott CH, bioMérieux, Brahms GmbH, GSK, InflaRx GmbH, Sobi and XBiotech Inc; independent educational grants from Abbott CH, AxisShield, bioMérieux Inc, InflaRx GmbH, Johnson & Johnson, MSD, Sobi and XBiotech Inc.; and funding from the Horizon2020 Marie-Curie Project European Sepsis Academy (granted to the National and Kapodistrian University of Athens) and the Horizon 2020 European Grants ImmunoSep and RISKinCOVID (granted to the Hellenic Institute for the Study of Sepsis). The other authors do not have any competing interest to declare. Figure 1 Study flow chart. Abbreviations: ARDS = acute respiratory distress syndrome; MV = mechanical ventilation; n = number of patients. Figure 2 Concentrations of acute-phase mediators. Mediators are divided into proinflammatory and anti-inflammatory cytokines. Dot plots with horizontal lines indicate the median of each group. The number of subjects evaluated is listed in parentheses. Double arrowhead lines indicate comparisons between groups. Only statistically significant differences are indicated as follows: * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. Abbreviations: ARDS = acute respiratory distress syndrome; IL = interleukin; MV = mechanical ventilation; n = number of patients; NIC = non-infected comparators; TNFα = tumor necrosis factor alpha. Figure 3 Concentrations of platelet-associated mediators and of other measured inflammatory mediators. Dot plots with horizontal lines indicate the median of each group. The number of subjects evaluated is listed in parentheses. Double arrowhead lines indicate comparisons between groups. Only statistically significant differences are indicated as follows: * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. Abbreviations: ARDS = acute respiratory distress syndrome; MMP: matrix metalloproteinase; MV = mechanical ventilation; n = number of patients; NIC = non-infected comparators; PAF = platelet activation factor; PDG = platelet-derived growth factor. Figure 4 Main acute-phase mediators associated with acute respiratory distress syndrome (ARDS) necessitating mechanical ventilation. (A) Receiver operator characteristic (ROC) curves of the six studied mediators with a statistically significant area under the ROC curve (AUC) for the detection of ARDS necessitating mechanical ventilation (MV). The AUCs, their 95% confidence intervals and significant p values are provided. The ROC curves of the other 14 mediators measured are not provided because they were not statistically significant. (B) Following Youden index analysis, the cut-offs of each of the six mediators shown in panel A were determined. These cut-offs were used in univariate and multivariate forward stepwise logistic regression analyses to select the mediators associated with ARDS necessitating MV. * variables excluded after three steps of forward analysis. Abbreviations: CI = confidence interval; OR = odds ratio. Figure 5 Principles of pathway analysis. Abbreviations: ARDS = acute respiratory distress syndrome; DAMP = danger-associated molecular pattern; IFN = interferon; IL = interleukin; MV = mechanical ventilation; PAF = platelet activation factor; PDG = platelet-derived growth factor. Figure 6 Main associations between mediators and 28-day outcome. The analysis involved patients with COVID-19 hospitalized with moderate COVID-19 and severe COVID-19, as well as those hospitalized with ARDS necessitating mechanical ventilation. (A) Univariate ordinal regression analysis of mediators associated with patterns of activation or inhibition of the inflammatory response. Ordinal regression analysis was performed. The principles for the selection of variables used to classify pathways are provided in Figure 5. (B) Multivariate ordinal regression analysis of pathways of the inflammatory response. (C) The three mediators associated with high risk for worse outcome according to the multivariate ordinal regression analysis were analyzed by Cox regression for their impact on 28-day mortality. (D) The two mediators associated with low risk for worse outcome according to the multivariate ordinal regression analysis were analyzed by Cox regression for their impact on 28-day mortality. Abbreviations: ARDS = acute respiratory distress syndrome; CI = confidence interval; IL = interleukin; n = number of patients; OR = odds ratio; PDGF = platelet-derived growth factor. Figure 7 S100A8/A9 (calprotectin) as an independent variable of progression into acute respiratory distress syndrome (ARDS) necessitating mechanical ventilation (MV). The analysis involved serial measurement among 52 patients with severe COVID-19 participating in the SAVE-MORE study. (A) Circulating concentrations of calprotectin at baseline. No significant differences were found between patients who progressed into ARDS in need of MV and those who did not progress into ARDS in need of MV. (B) Circulating concentrations of PDGF-B at baseline. No significant differences were found between patients who progressed into ARDS in need of MV and those who did not progress into ARDS in need of MV. (C) Changes of circulating concentrations of calprotectin on days 4 and 7 of follow-up from baseline. The p values of comparisons are provided. (D) Changes of circulating concentrations of PDGF-B on days 4 and 7 of follow-up from baseline. No significant differences were found between patients who progressed into ARDS in need of MV and those who did not progress into ARDS in need of MV. (E) Univariate and multivariate forward stepwise Cox regression analysis of variables associated with progression into ARDS and MV; * HR cannot be calculated because one value is zero; ** excluded after two steps of forward analysis. (F) Serum concentrations of creatinine and albumin. The p values of comparisons are provided. Abbreviations: CI = confidence interval; HR: hazard ratio; PDGF = platelet-derived growth factor. ijms-23-04894-t001_Table 1 Table 1 Demographic characteristics of participants in the first stage of the study. Comparators Asymptomatic Moderate Severe ARDS and MV Number 40 19 42 78 42 Age (years) mean ± SD 58.3 ± 15.8 59.5 ± 10.8 55.3 ± 14.8 61.4 ± 13.9 64.9 ± 12.8 Male gender, n (%) 28 (70) 12 (63.2) 25 (59.5) 56 (71.8) 35 (83.3) SOFA, mean ± SD NA NA 0.9 ± 0.9 2.3 ± 1.6 6.5 ± 2.5 CCI, mean ± SD 1.0 ± 0.2 1.3 ± 1.9 2.3 ± 2.3 2.6 ± 2.1 2.4 ± 1.5 Comorbidities, n (%) Type 2 diabetes mellitus 0 (0) 5 (26.3) 13 (31.0) 20 (25.6) 6 (14.3) Chronic heart failure 0 (0) 0 (0) 3 (7.1) 5 (5.1) 0 (0) Chronic renal disease 0 (0) 0 (0) 2 (4.8) 3 (3.8) 2 (4.8) Coronary heart disease 0 (0) 0 (0) 5 (11.9) 8 (10.3) 6 (14.3) Dyslipidemia 0 (0) 4 (21.1) 14 (33.3) 17 (21.8) 4 (9.5) Hypothyroidism 0 (0) 2 (10.5) 7 (16.7) 7 (9.0) 3 (7.1) Hypertension 0 (0) 2 (10.5) 16 (38.1) 24 (30.8) 7 (16.7) Stroke 0 (0) 0 (0) 2 (4.8) 1 (1.3) 1 (2.4) Atrial fibrillation 0 (0) 0 (0) 2 (4.8) 6 (7.7) 3 (7.1) COPD 0 (0) 0 (0) 3 (7.1) 2 (2.6) 0 (0) pO2/FiO2, mean ± SD NA NA 397.5 ± 84.3 274.5 ± 103.8 127.1 ± 72.2 White blood cell count, mean ± SD (/mm3) NA NA 5394.3 ± 2379.8 7000.1 ± 2945.8 11,977.8 ± 6094.2 CRP, median (IQR), mg/L NA NA 4.9 (30.6) 39.0 (80.1) 82.9 (173.5) Ferritin, median (IQR), ng/mL NA NA 293.2 (534.2) 485.3 (832.5) 1189.5 (1686.8) Administered drugs, n (%) β-lactamase inhibitor NA 0 (0) 1 (2.4) 21 (29.2) 0 (0) Ceftriaxone NA 0 (0) 30 (71.4) 41 (56.9) 10 (23.8) Ceftaroline NA 0 (0) 0 (0) 17 (23.6) 10 (23.8) Piperacillin/tazobactam NA 0 (0) 8 (19.0) 10 (13.9) 16 (38.1) Ceftaziidme/avibactam NA 0 (0) 0 (0) 0 (0) 6 (14.3) Glycopeptides/linezolid NA 0 (0) 0 (0) 3 (4.2) 12 (28.6) Remdesivir NA 0 (0) 20 (47.6) 30 (41.7) 9 (21.4) Dexamethasone NA 0 (0) 4 (9.5) 72 (100) 42 (100) Nor-adrenaline NA 0 (0) 0 (0) 0 (0) 27 (64.3) Furosemide NA 0 (0) 0 (0) 0 (0) 29 (69.0) Midazolam NA 0 (0) 0 (0) 0 (0) 29 (69.0) Fentanyl NA 0 (0) 0 (0) 0 (0) 24 (57.1) Propofol NA 0 (0) 0 (0) 0 (0) 29 (69.0) Dexmetomidine NA 0 (0) 0 (0) 0 (0) 7 (16.7) Cisatracurium NA 0 (0) 0 (0) 0 (0) 7 (16.7) Abbreviations: ARDS = acute respiratory distress syndrome; CCI = Charlson’s comorbidity index; CRP = C-reactive protein; COPD = chronic obstructive pulmonary disease; FiO2: fraction of inspired oxygen; IQR = interquartile range; MV = mechanical ventilation; NA = not available; pO2: partial oxygen pressure; SD = standard deviation; SOFA = sequential organ failure assessment score. 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PMC009xxxxxx/PMC9099709.txt

==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092634 molecules-27-02634 Article Quality Assessment of Artemisia rupestris L. Using Quantitative Analysis of Multi-Components by Single Marker and Fingerprint Analysis Cao Xueqin 123 Li Muchun 123 Ma Liuchun 3 Wang Miaomiao 123 https://orcid.org/0000-0003-3682-7387 Hou Xueling 1 https://orcid.org/0000-0003-2328-3974 Maiwulanjiang Maitinuer 1* Locatelli Marcello Academic Editor 1 State Key Laboratory Basis of Xinjiang Indigenous Medicinal Plants Resource Utilization, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi 830011, China; caoxueqin8095@163.com (X.C.); limuchun20@mails.ucas.ac.cn (M.L.); wangmiao.1988.li@163.com (M.W.); xlhou@ms.xjb.ac.cn (X.H.) 2 University of Chinese Academy of Sciences, Beijing 100049, China 3 Xinjiang Uyger Autonomous Region Academy of Instrumental Analysis, Urumqi 830011, China; 15199122582@163.com * Correspondence: mavlanjan@ms.xjb.ac.cn; Tel.: +86-0991-6631740; Fax: +86-0991-3838957 20 4 2022 5 2022 27 9 263415 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/). The chromatographic fingerprint of 14 batches of Artemisia rupestris L. samples were established in this study. The constituents of ten components in Artemisia rupestris L. were determined using quantitative analysis of multi-components by single marker (QAMS) and the external standard method (ESM). Due to their stability and accessibility, chlorogenic acid and linarin were used as references to calculate the relative correction factors (RCFs) of apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, chrysosplenetin B, and sbsinthin, based on high-performance liquid chromatography (HPLC). The value calculated by QAMS was consistent with that of the ESM, and the reproducibility of RCFs was found to be reliable. In conclusion, simultaneous determination of the ten components by the QAMS method and chromatographic fingerprint analysis were feasible and accurate in evaluating the quality of Artemisia rupestris L. and can be used as reference in traditional Chinese medicine quality control. Artemisia rupestris L. high-performance liquid chromatography quantitative analysis of multi-components by single marker fingerprint analysis quality control ==== Body pmc1. Introduction Artemisia rupestris L. is a commonly used herbal medicine in Xinjiang for reducing fever and other symptoms of cold by acting as an anti-inflammatory and analgesic agent, as well as for detoxification and treating hepatitis [1]. Wild A. rupestris is distributed in Xinjiang, Middle Asian countries, and Northern Europe [2]. A. rupestris extracts contain sesquiterpenoids [3,4], flavonoids [5,6], alkaloids [7,8] and volatile oils [9,10]. A. rupestris has certain antiviral [11,12], anti-inflammatory activities and immune regulation [13,14,15] properties. Many studies have been conducted on the analysis of related components of A. rupestris and its preparations. In a previous study, the quality of Yizhihao capsules was assessed by quantitative analysis of rupestonic acid using the HPLC method [16]. Lan et al. [17] established an HPLC method to simultaneously determine rupestonic acidartesunone, chlorogenic acid, and luteolin in A. rupestris. Zhang Suwan et al. [18] determined the content of rupestonic acidartesunone, 6-dimethoxy-4, methyl artemisinin, and artemisinin in A rupestris using HPLC. Furthermore, Cai Xiaocui et al. [19] simultaneously determined the contents of chlorogenic and rupestonic acid, luteolin, vitexin, and apigenin in A. rupestris by liquid chromatography tandem-mass spectrometry (LC-MS/MS). In the global market, herbal medicines are treated or dried using different methods, which may result in unstable levels of single components. Fingerprinting can comprehensively reflect the overall chemical information of traditional Chinese medicine (TCM). It is usually used for origin identification, species certification and quality control of herbal medicine, and to evaluate the authenticity, excellence and stability of the quality of traditional Chinese medicine and semi-finished products of traditional Chinese medicine preparations [20,21]. By confirming the main common fingerprint peaks in the HPLC fingerprint, the qualitative and quantitative research of traditional Chinese medicine and its preparations can be carried out to evaluate and control quality [22,23]. The determination of the content of a single component cannot be used to accurately and sufficiently evaluate the quality of A. rupestris. Therefore, an effective strategy in determining the quality of A. rupestris will be to evaluate multiple components. In this study, we established a qualitative fingerprint method for A. rupestris, and ten principal components were confirmed and analyzed quantitatively. QAMS enables the quantitative analysis of multiple components by using a cheap and easily available standard [24]. The combination of QAMS and fingerprint method showed the convenience and economic advantages of the QAMS method, meanwhile exhibiting the integrity and comprehensive advantages of the fingerprint method. Based on the chromatographic fingerprinting method and QAMS, the qualitative and quantitative determination of A. rupestris was evaluated in the present study. Chlorogenic acid and linarin were used as internal references for phenolic acids and flavonoids, respectively, to calculate the average RCFs. The proposed method of QAMS and fingerprint analysis provides a reliable, comprehensive and efficient way for evaluating A. Rupestris quality. 2. Results and Discussion 2.1. HPLC Conditions Due to the complexity of chemical constituents in A. rupestris, it is crucial to separate the target components efficiently by optimizing chromatographic conditions. The HPLC chromatographic peaks of A. rupestris were most informative with the ultraviolet (UV) wavelength of detection set at 350 nm. Therefore, we chose 350 nm for the assay of the selected components. The mobile phase consisted of acetonitrile-0.2% phosphoric acid at 1.0 mL/min of flow rate. The gradient elution program used is described in Section 3.5 and the favorable column temperature was set at 35 °C. The extraction solvent was ethanol-water (7:3, v/v) solution, and samples were treated for 30 min by ultrasonic extraction. The samples of A. rupestris, and the mixed standard solutions containing the 10 reference substances, were analyzed under the conditions described in Section 3.5. The chromatographic peak position of the standard substances was determined as follows: chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin (Figure 1). According to the retention time in the chromatogram of the sample and standard solution, peaks 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 were identified to be chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin, respectively. In addition, each peak was well separated in the present HPLC system. 2.2. Method Validation In order to support its application in the quantitative analysis of the ten compounds, the HPLC method was validated in terms of linearity, stability, precision, and accuracy. 2.2.1. Linearity Within the setting concentration range, the extent of direct linear relationship between the test results and the concentration of analytes in the samples was investigated. The mixed standard solutions were serially diluted to obtain desired concentrations with methanol. The 10 standard solutions were analyzed, and the calibration curves were formed by the relationship between the peak area of each component and corresponding concentration. The standard curve of each component was stable and the obtained linear regression equation was suitable for QAMS analysis (Table 1). 2.2.2. Stability We investigated whether the sample solution was stable for 24 h storage at room temperature. The sample solution stability (S1) at room temperature (22 ± 3 °C) was tested at 0, 4, 8, 12, 16, 20, and 24 h, to obtain the RSDs. The RSD values of the stability tests were <2% (Table 1). The method could be considered stable, suggesting that within 24 h the sample solution was stable. 2.2.3. Accuracy To verify the accuracy of the study, the mixed standard solutions of the analytes at low, medium, and high concentration levels were added into a sample (S1) of a certain amount (0.5 g), using six replicates. Then the mixed samples were subsequently extracted and analyzed. The average recovery of the 10 components was between 86.1–106%, and the RSDs of the accuracy values are shown in Table 2. 2.2.4. Precision To evaluate the intra-day and inter-day precision, the sample solution was analyzed within a single assay day and on three separate days for six replicates at each concentration level, respectively. The RSDs of intra-day and inter-day were all less than 3% (Table 2). The HPLC method was verified in terms of stability, accuracy, and precision (Table 1 and Table 2), and the results suggested that this verified method was stable, accurate, precise and reproducible. Therefore, it could be used to determine chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, and 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin simultaneously in the A. rupestris samples. 2.3. Fingerprints Analysis Traditional Chinese medicine fingerprint is a comprehensive and quantifiable identification method, and is mainly used to evaluate the authenticity and the quality of traditional Chinese medicine and semi-finished products of traditional Chinese medicine preparations. For establishment of a novel method for multiple components from A. rupestris, high-performance liquid chromatograms of each sample were imported into the software recommended by SFDA, which was called chromatographic fingerprint similarity evaluation system for traditional Chinese medicine (version 2012a). Then, the chromatographic fingerprints were collected. Among the 14 samples, S1 was selected as the reference spectrum, while 18 common fingerprint peaks were recorded in the chromatograms (Figure 2). Meanwhile, the similarity of the 14 batches of A. rupestris samples was analyzed and obtained (Table 3). S11 gave the lowest similarity among the samples, and the simiarity of S1, S2, S3, S5, S6, S10, S14 were all above 0.8. According to the software requirements, similarity greater than 0.9 is generally required. In the similarity analysis, only 3 batches of samples were greater than 0.9, which were S1, S2 and S5, suggesting that the quality of medicinal materials from different producing areas and growth conditions is quite different. 2.4. Quantitative Analysis by QAMS and ESM Ten components were identified in the fingerprint with reference materials, including chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin. ESM and QAMS were used to quantify the ten components in the sample to verify consistency between QAMS and ESM. In ESM, the mixed standard solution and sample solutions were analyzed by liquid chromatography, and the content of each component calculated according to the regression equations listed in Table 1. Choosing a suitable standard for internal reference using the QAMS method for analyzing multiple components in traditional Chinese medicinal substances is important. The component selected as internal reference should be selected on grounds of ease of acquisition, low price, and stable properties, and should be separable from the other compounds under chromatographic conditions [25]. In the present study, chlorogenic acid and linarin were used as internal references for phenolic acids and flavonoids. respectively. QAMS calculates the RCF between the component which was selected as internal reference and other components in medicinal materials. Furthermore, by calculating the amounts of other components through RCF, the simultaneous determination of multiple components [24,26] can be accomplished. The deviations (RE) between QAMS and ESM were calculated using the following formula (Equation (1)). RCF = (Ci/Ai)/(Cs/As)(1) where As is the peak area of the internal reference substance, Cs is the concentration of the internal reference substance, Ai is the peak area of the component to be tested, and Ci is the concentration of the component to be tested. To analyze the 10 components simultaneously in A. rupestris by QAMS, the RCFs were calculated based on the ratio of peak area and corresponding concentration between internal references and the other analytes. The RCFs are shown in Table 4 and Table 5. Overall, 14 batches of A. rupestris samples from various production areas were analyzed using the validated ESM and QAMS methods. The deviations (RE) between QAMS and ESM were calculated using the following formula (Equation (1)). RE = (QAMS − ESM)/ESM × 100%(2) The quantitative results of the 10 compounds in A. rupestris calculated by ESM and QAMS methods are shown in Table 6 and Table 7. The REs were less than 5%, which is the requirement of Chinese Pharmacopoeia. It was indicated that there was no significant difference in the content results obtained by QAMS and ESM Analysis of the 14 batches of A. rupestris samples revealed the contents of chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin. The determination acquired by QAMS was consistent with that of ESM. Therefore, it was proven that the QAMS method for simultaneous quantitative analysis of the 10 components in A. rupestris was reliable and feasible. Fingerprints analysis and quantitative data showed significant differences among various samples from different sources. According to the results in Table 6 and Table 7, it can be seen that the content of ten components fluctuates greatly between batches. It may be related to the production environment, planting methods, growth time and harvest season. Among phenolic acids, the contents of chlorogenic acid and 3,5-dicaffeoylquinic acid were relatively high, and there was positive correlation. Among the flavonoids, the contents of linarin and chrysosplenetin B were relatively high. Next, we studied the relationship between the content of each component and the related efficacy. 2.5. Cluster Analysis All the 14 samples of A. rupestris were selected from different regions or planting methods, and the content of their 10 main compounds might differ. Our QAMS methods could accurately analyze the composition, and the contents of the 10 compounds in the 14 batches of A. rupestris samples selected as clustering variable. The samples were divided into two categories by cluster analysis. S2, S3, and S4 are one category, which were artificially planted in Fuyun County of Altay Region and the other samples formed one category, to ascertain whether artificial planting or origins would change the composition of A. rupestris. 3. Materials and Methods 3.1. Plant Material A. rupestris samples used in the study were collected from different production areas, as shown in Table 8. 3.2. Chemicals Standard substances of chlorogenic acid (Batch No. 110753–201817, purity HPLC ≥ 96.8%), luteolin (Batch No. 111720–201810, purity HPLC ≥ 93.5%), 3,5-dicaffeoylquinic acid (Batch No. 111782–201807, purity HPLC ≥ 94.3%), 4,5-dicaffeoylquinic acid (Batch No. 111894–201102, purity HPLC ≥ 94.1%), linarin (Batch No. 111528–201911, purity HPLC ≥ 98.5%), and sbsinthin (Batch No. 111879–201102, purity HPLC ≥ 97.2%) were purchased from the National Institute for Food and Drug Control, (Beijing, China). 3,4-dicaffeoylquinic acid (Batch No. S0990020, purity HPLC ≥ 98.7%) was purchased from ANPEL Laboratory Technologies Inc., (Shanghai, China), chrysosplenetin B (Batch No. PRF10121942, purity HPLC ≥ 98.0%) was purchased from Biopurify Phytochemicals Ltd. (Chengdu, China). Apigenin-C-6,8-pentoside-hexoside and apigenin-C-6,8-di-pentoside were determined based on their spectral structure, and their purities were calculated by the peak area normalization method (purity HPLC ≥ 98.0%). Acetonitrile and methanol (Thermo Fisher Scientific, Inc. Shanghai, China) were of HPLC grade. Phosphoric acid (YSHC Chemical Company Limited, Tianjin, China) and absolute ethanol (Tianjin Xinbote Chemical Company Limited, Tianjin, China) were analytical grade. Ultrapure water was prepared by a Milli-QAC SP Reagent Water System (Millipore Corporation, Billerica, MA, USA). Other chemicals used in the study were all analytical grade. 3.3. Procedure of Sample Solution Preparation The A. rupestris samples were ground using a high-speed traditional Chinese medicine pulverizer to make powder, and passed through a 10-mesh sieve. Next, 0.5 g of sample was weighed precisely into a bottle with a plug. The sample powder was extracted with 30 mL of the extraction solvent (ethanol:water, 7:3, v/v). The mixed solution was sonicated for 30 min (250 W, 40 kHz) at room temperature (25 ± 5 °C). After cooling, additional extraction solvent was added to the sample solution to compensate for weight loss, followed by thorough shaking. Before injection, the supernatant of the sample solution was filtered through membranes of 0.22 μm. 3.4. Preparation of the Reference Solution Appropriate amounts of chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin were weighed, and methanol were added to make 1.0 mg/mL stock solutions. These solutions were diluted with methanol serially, thereby making a mixture to obtain the desired concentrations for establishing the calibration curves of phenolic acids and flavonoids. 3.5. Instruments and Chromatographic Procedures An Agilent 1260 series high-performance liquid chromatograph, equipped with a quaternary pump, UV detection, an autosampler, a column temperature controller, and a vacuum degasser (Agilent Technologies, Palo Alto, CA, USA) was used in the HPLC assay of A. rupestris. The samples were separated using a Hypersil GOLD C18 column (5 μm, 250 × 4.6 mm). The injection volume of sample and standards were all 10 μL, and the column temperature was maintained at 35 °C. A mixture of acetonitrile (A) and 0.2% phosphate solution (B) was used as the mobile phase at a flow rate of 1.0 mL/min. The gradient elution mode was modified as follows: 0–15 min, 5–18% A; 30 min, 20% A; 35 min, 21% A; 40 min, 40% A; 47 min, 45% A; 51–55 min, 80% A; 55.1–65.0 min, 5% A. The detection wavelength was sat at 350 nm. 4. Conclusions A novel method to determine multiple components from A. rupestris was established and reported using QAMS in this study, which was reproducible and accurate. The A. rupestris samples from different regions or planting methods were determined by HPLC, and the content determination of ten components (chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin in different laboratories) in the A. rupestris samples was simultaneously accomplished by the proposed QAMS, applying an exclusive identification and evaluation method for qualitative and quantitative analysis of A. rupestris. The chromatographic fingerprint showed the details of A. rupestris chromatographic spectrum, while the cluster analysis identified that region and growth conditions could influence the content of A. rupestris. Therefore, this method might be suitable both for A. rupestris quantitative analysis and for quality examination. The similarity analysis suggested that the quality of medicinal materials from different producing areas and growth conditions is quite different. Thus, the proposed method could be an accurate and feasible approach for provision of supporting qualitative and quantitative data for A. rupestris quality evaluation. QAMS can be applied to determine chlorogenic acid, apigenin-C-6,8-pentoside-hexoside, apigenin-C-6,8-di-pentoside, luteolin, 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 4,5-dicaffeoylquinic acid, linarin, chrysosplenetin B, and sbsinthin simultaneously, and there might be potential for establishment of a universal and unified standard for the quality control of A. rupestris. Author Contributions X.C.: methodology, validation, data curation, project administration, writing—original draft preparation, writing—review and editing; M.L.: methodology, validation; L.M.: methodology, validation; M.W.: methodology, validation; X.H.: methodology, supervision; M.M.: methodology, project administration, resources, supervision, writing—original draft preparation, writing—review and editing. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Natural Science Foundation of Xinjiang Province of China (2020D01A90). Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data are contained within the article. Conflicts of Interest The authors declare no conflict of interest. Sample Availability Samples of the compounds apigenin-C-6,8-pentoside-hexoside and apigenin-C-6,8-di-pentosideare available from the authors. The others are from MDPI. Abbreviations The following abbreviations have been used in this manuscript. HPLC High performance liquid chromatography QAMS Qualitative and quantitative analysis of multi-component by single marker ESM External standard method RSD Relative standard deviation TCM Traditional Chinese medicine RCF Relative correction factor Figure 1 HPLC chromatograms of the mixed standards and A. rupestris sample. (a) the mixed standards; (b) A. rupestris sample. 1—Chlorogenic acid; 2—Apigenin-C-6,8-pentoside-hexoside; 3—Apigenin-C-6,8-di-pentoside; 4—Luteolin; 5—3,4-Dicaffeoylquinic acid; 6—3,5-Dicaffeoylquinic acid; 7—4,5-Dicaffeoylquinic acid; 8—Linarin; 9—Chrysosplenetin B; 10—Sbsinthin. Figure 2 The fingerprints of A. rupestris samples. 1—Chlorogenic acid; 2—Apigenin-C-6,8-pentoside-hexoside; 3—Apigenin-C-6,8-di-pentoside; 4—Luteolin; 5—3,4-Dicaffeoylquinic acid; 6—3,5-Dicaffeoylquinic acid; 7—4,5-Dicaffeoylquinic acid; 8—Linarin; 9—Chrysosplenetin B; 10—Sbsinthin. molecules-27-02634-t001_Table 1 Table 1 The Regression Equation, Linear Range, and Stability of the 10 Components Analyzed by HPLC (n = 6). Analytes Regression Equations r2 Linear Ranges (μg/mL) Stability (RSD%) Chlorogenic acid Y = 12.8332 X + 0.3077 0.999 4 0.50–100 0.4 Apigenin-C-6,8-pentoside-hexoside Y = 19.858 X − 1.2861 0.999 5 0.50–50.0 0.6 Apigenin-C-6,8-di-pentoside Y = 20.056 X + 1.8584 0.999 3 0.50–50.0 0.8 Luteolin Y = 26.19249 X + 1.2730 0.999 0 0.50–50.0 0.9 3,4-Dicaffeoylquinic acid Y = 15.76744 X + 1.36516 0.999 3 0.50–100 0.5 3,5-Dicaffeoylquinic acid Y = 13.62685 X + 1.25882 0.999 2 0.50–100 0.7 4,5-Dicaffeoylquinic acid Y = 19.40530 X + 2.40872 0.999 1 0.50–100 1.1 Linarin Y = 18.4154 X + 1.7983 0.999 8 0.50–50.0 0.5 Chrysosplenetin B Y = 36.9728 X + 2.5677 0.999 8 0.50–50.0 0.9 Sbsinthin Y = 18.5140 X + 1.4366 0.999 9 0.50–50.0 1.2 Y—peak area; X—concentration (μg/mL); r2—correlation coefficient of the equation. molecules-27-02634-t002_Table 2 Table 2 Accuracy and Precision of the 10 Components. Analytes Recovery (n = 6) Precision (n = 6) Added Level Recovery (%) Added Level Recovery (%) Added Level Recovery (%) Intra-Day a (%RSD) Inter-Day b (%RSD) Chlorogenic acid Low 89.6 Middle 90.2 High 93.1 1.9 2.5 apigenin-C-6,8-pentoside-hexoside Low 88.3 Middle 93.6 High 104 2.2 2.4 Apigenin-6, 8-di-C-pen Low 90.1 Middle 101 High 96.1 1.8 2.1 Luteolin Low 93.1 Middle 98.1 High 98.2 2.0 2.4 3,4-Dicaffeoylquinic acid Low 89.5 Middle 102 High 103 1.8 2.5 3,5-Dicaffeoylquinic acid Low 86.1 Middle 96.3 High 101 1.3 1.6 4,5-Dicaffeoylquinic acid Low 90.2 Middle 95.2 High 95.4 1.4 1.5 Linarin Low 103 Middle 106 High 96.1 2.1 2.4 Chrysosplenetin B Low 91.5 Middle 91.4 High 92.4 0.9 2.6 Sbsinthin Low 92.8 Middle 95.3 High 99.8 1.8 1.9 a Intra-day precision tested six times during the same day. b Inter-day precision tested on three separate days. molecules-27-02634-t003_Table 3 Table 3 The Similarity of 14 batches A. rupestris Samples. No. Similarity No. Similarity S1 0.949 S8 0.766 S2 0.916 S9 0.672 S3 0.858 S10 0.811 S4 0.744 S11 0.620 S5 0.917 S12 0.693 S6 0.824 S13 0.712 S7 0.770 S14 0.897 molecules-27-02634-t004_Table 4 Table 4 Relative Correction Factor (RCF, fx) Values of Phenolic Acids. Con. (μg/mL) f chlorogenic acid/3,4-Dicaffeoylquinic acid f chlorogenic acid/ 3,5-Dicaffeoylquinic acid f chlorogenic acid/ 4,5-Dicaffeoylquinic acid 0.50 0.918 0.954 0.713 2.0 0.877 1.024 0.709 5.0 0.871 1.015 0.697 10.0 0.841 0.980 0.661 50.0 0.837 0.962 0.685 100 0.843 0.990 0.684 Means 0.865 0.987 0.692 RSD (%) 3.6 2.8 2.8 molecules-27-02634-t005_Table 5 Table 5 Relative Correction Factor (RCF, fx) Values of Flavonoids. Con. (μg/mL) f linarin/ apigenin-C-6,8-pentoside-hexoside f linarin/ apigenin-C-6,8-di-pentoside f linarin/luteolin f linarin/chrysosplenetin B f linarin/sbsinthin 0.50 0.663 0.492 0.847 0.958 0.885 1.0 0.707 0.504 0.870 0.951 0.879 2.0 0.707 0.505 0.876 0.943 0.871 5.0 0.727 0.511 0.893 0.951 0.879 10.0 0.709 0.499 0.876 0.949 0.876 20.0 0.684 0.482 0.844 0.902 0.833 Means 0.700 0.499 0.868 0.942 0.870 RSD (%) 3.2 2.1 2.1 2.2 2.2 molecules-27-02634-t006_Table 6 Table 6 Contents of Phenolic Acids in A. rupestris using different methods (mg/g). No. Chlorogenic Acid 3,4-Dicaffeoylquinic Acid 3,5-Dicaffeoylquinic Acid 4,5-Dicaffeoylquinic Acid ESM ESM QAMS RE/% ESM QAMS RE/% ESM QAMS RE/% S1 1.685 0.266 0.278 4.3 3.326 3.210 3.5 0.574 0.586 2.1 S2 5.223 0.279 0.291 4.5 5.506 5.310 3.6 0.746 0.761 2.0 S3 2.013 0.238 0.249 4.6 4.789 4.612 3.7 0.949 0.964 1.6 S4 1.247 0.096 0.099 3.2 1.934 1.874 3.1 0.402 0.412 2.5 S5 2.708 0.150 0.156 4.1 3.512 3.392 3.4 0.885 0.901 1.8 S6 2.528 0.110 0.112 1.5 2.457 2.381 3.1 0.552 0.564 2.3 S7 0.559 0.0580 0.0590 1.8 0.936 0.915 2.3 0.187 0.195 3.9 S8 0.132 0.0186 0.0190 3.4 0.294 0.294 0.1 0.0176 0.0180 2.3 S9 2.103 0.134 0.142 6.4 3.540 3.416 3.5 0.946 0.962 1.6 S10 3.163 N.D. N.D. / 1.560 1.515 2.9 0.391 0.400 2.4 S11 0.874 0.212 0.223 5.0 4.376 4.222 3.5 0.989 1.006 1.7 S12 1.008 N.D. N.D. / 0.699 0.693 0.8 0.168 0.176 5.0 S13 0.590 N.D. N.D. / 0.179 0.186 4.2 0.182 0.190 4.1 S14 1.470 N.D. N.D. / 1.580 1.538 2.7 0.359 0.369 2.8 N.D.: not detected. molecules-27-02634-t007_Table 7 Table 7 Contents of Flavonoids in A. rupestris using different methods (mg/g). No. Linarin Apigenin-C-6,8-Pentoside-Hexoside Apigenin-C-6,8-di-Pentoside Luteolin Chrysosplenetin B Sbsinthin ESM ESM QAMS RE/% ESM QAMS RE/% ESM QAMS RE/% ESM QAMS RE/% ESM QAMS RE/% S1 0.828 0.500 0.482 3.6 0.297 0.301 1.3 0.366 0.356 2.6 0.727 0.714 1.8 0.130 0.125 3.9 S2 1.298 0.521 0.514 1.3 0.898 0.905 0.8 0.392 0.379 3.3 1.060 1.080 1.9 0.859 0.852 0.9 S3 0.338 0.374 0.385 2.9 0.212 0.207 2.4 0.234 0.225 3.9 1.795 1.751 2.4 0.138 0.137 1.0 S4 0.409 0.390 0.393 0.8 0.286 0.281 1.7 0.354 0.344 2.8 1.346 1.339 0.5 0.0366 0.0362 1.0 S5 0.483 0.527 0.521 1.1 0.345 0.341 1.2 0.236 0.237 0.4 0.842 0.874 3.7 0.0401 0.0395 1.5 S6 0.428 0.279 0.285 2.2 0.174 0.176 1.1 0.324 0.326 0.7 0.509 0.500 1.7 0.0909 0.0889 2.2 S7 0.248 0.241 0.249 3.3 0.211 0.209 0.9 0.0522 0.0501 4.0 1.145 1.147 0.2 0.0532 0.0512 3.8 S8 0.558 N.D. N.D. / 0.596 0.600 0.7 0.0347 0.0344 0.7 0.124 0.126 1.3 0.103 0.107 3.4 S9 0.940 0.627 0.63 0.5 0.427 0.431 0.9 0.238 0.230 3.2 1.122 1.137 1.3 0.101 0.105 4.3 S10 1.090 0.151 0.153 1.3 0.180 0.177 1.7 0.270 0.261 3.4 0.552 0.543 1.7 0.408 0.398 2.4 S11 0.047 0.205 0.211 2.9 0.103 0.102 1.0 0.290 0.251 3.3 0.614 0.622 1.3 0.0550 0.0523 4.8 S12 0.645 0.158 0.155 1.9 0.107 0.105 1.9 0.0793 0.0753 5.0 0.0575 0.0549 4.5 0.0284 0.0288 1.3 S13 0.696 0.121 0.118 2.5 0.0953 0.0950 0.3 0.0512 0.0496 3.1 0.156 0.151 3.4 0.0783 0.0748 4.5 S14 1.076 0.188 0.190 1.1 0.119 0.121 1.7 0.174 0.171 1.6 0.280 0.267 4.6 0.150 0.146 2.3 molecules-27-02634-t008_Table 8 Table 8 The different production areas of A. rupestris. No. Production Areas S1 Urumqi, Xinjiang S2 Altay Prefecture, Xinjiang S3 Altay Prefecture, Xinjiang S4 Altay Prefecture, Xinjiang S5 Altay Prefecture, Xinjiang S6 Urumqi, Xinjiang S7 Urumqi, Xinjiang S8 Urumqi, Xinjiang S9 Fukang, Xinjiang S10 Urumqi, Xinjiang S11 Altay Prefecture, Xinjiang S12 Urumqi, Xinjiang S13 Urumqi, Xinjiang S14 Fukang, Xinjiang Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Liu Y.M. Liu W.X. Yikemu Y.W.T. Pharmacography of Uighur Xinjiang People’s Publishing House Urumqi, China 1985 1 5 2. Nayak M.K. Daglish G.J. Byrne V.S. Effectiveness of Spinosad as a grain protectant against resistant beetle and psocid pests of stored grain in Australia J. Stored Prod. Res. 2005 41 455 467 10.1016/j.jspr.2004.07.002 3. Liu Y.M. Yu D.Q. Studies on chemical constituents in herb from Artemisia rupestris Acta Pharm. Sin. 1985 20 514 518 4. Xu G.S. Chen X.Y. Yu D.Q. 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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/ijerph19095049 ijerph-19-05049 Article Mission Himalaya: Exploring the Impact of a Supported High-Altitude Mountaineering Expedition on the Well-Being and Personal Development of UK Military Veterans https://orcid.org/0000-0001-8291-7282 Kay Christopher William Philip 1* Wingfield Harriet Laura 2 https://orcid.org/0000-0001-6779-3939 McKenna Jim 1 Tchounwou Paul B. Academic Editor Spickett Jeffery Academic Editor 1 Centre for Human Performance, Performance in Extreme Environments, Leeds Beckett University, Leeds LS1 3HE, UK; j.mckenna@leedsbeckett.ac.uk 2 Social & Economic Research Institute, Sheffield Hallam University, Sheffield S1 1WB, UK; harriet.wingfield@student.shu.ac.uk * Correspondence: chris.kay@leedsbeckett.ac.uk 21 4 2022 5 2022 19 9 504918 2 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/). Meaningful, positive, emotional and challenging adventurous activities may generate personal growth or recovery from ill health or injury. In this study, we used a distinctive longitudinal and immersive research approach to explore the psychological impact of a high-altitude expedition to the Nepalese Himalaya on 10 (9 males) UK military veterans with longstanding well-being concerns. In the 12 months prior to the expedition, participants took part in three training weekends in the UK mountains. During the expedition, instructors—who were all experienced health coaches—facilitated reflective practices with the beneficiaries throughout, focusing on experiential transfer to day-to-day lives after the expedition. Follow-up interviews, conducted up to 18-months post-expedition, identified that the most desirable changes aligned with the three innate psychological needs of self-determination theory: autonomy, competence and relatedness. The routines established during the preparation stage and during the expedition itself activated a renewed energy for personal improvement. At 18 months post-expedition, the key changes reflected altered perspective, employment skills and work–life balance, increased physical activity and enhanced personal awareness and mindfulness. Importantly, supported by regular health coaching and focused on the transfer of learning, expeditions can activate meaningful long-term changes to the well-being and personal development of military veterans. psychological well-being veterans behaviour change mental health adventure therapy recovery health coaching post-expedition growth expedition mountaineering psychosocial development self-determination theory ==== Body pmc1. Introduction Military personnel can experience circumstances during their time in service or as a part of their transition to civilian life that have a negative impact on their physical or mental health. A recent increase in service personnel reporting mental health concerns has identified that issues are not exclusive to those with deployment experience [1,2]. Notwithstanding, the prevalence of mental health problems is higher in deployed veterans [3]. Mental health problems are the second most prominent reason for medical discharge behind musculoskeletal disorders and injuries [4]. In the last 10 years, in the UK, medical discharges from the Army due to mental and behavioural disorders has increased from 15 to 33% [4]. The Parliamentary Defence Committee reported that some departing personnel are not adequately served by the system [5]. Many services that aim to support veterans stem from clinical models of recovery and continue to dominate rehabilitation services, focusing on symptom reduction and physical functioning [6]. Research has highlighted the need to explore additional and alternative approaches to recovery beyond conventional practice as an adjunct to the clinical services which “are not associated with hospitals, rehabilitation centres, or other clinical settings” [1]. One such area is sport and outdoor and adventurous physical activity (OAA), which is thought to complement mainstream practices by “facilitating a faster return to healthy levels of psychological functioning” [7]. The emerging literature examining the use of OAA programmes for veterans attributes such initiatives with some success in demonstrating improved well-being. This can be achieved through OAA provision, when delivered in a way that successfully provides an immersive experience, meets the bespoke needs of participants and is evidenced in an appropriate form [8]. Several studies have shown that conditions experienced on an expedition can result in improved psychological well-being [9,10,11,12]. However, few studies have examined the impact of expeditions for people adjusting to life-changing circumstances, such as sustaining career-ending physical injuries or the diagnosis of a trauma-related mental health disorder. Only a few studies have reported on how short-term expeditions influence well-being benefits and these are limited by focusing on the immediate expedition, meaning that longer-term impacts are unclear [9,10,11,12]. Further, only one study has addressed the unique context of expeditions involving military veterans [13]. That study focused on the psychosocial impact of a mountaineering expedition on four individuals. The expedition influenced how individuals understood their own capabilities and reshaped their personal understanding of being a veteran, encouraging them to take more responsibility for their own recovery. Greer and Vin-Ravi [14] emphasised that more research is needed to establish the viability and appropriateness of expeditions to determine the durability and “real world” relevance to their outcomes. In response, the aim of this study was to use a high-altitude expedition to the Himalaya to investigate the impacts on personal development and well-being that occurred amongst a small group of UK military veterans with a range of mental and physical health challenges. Further, given the pre-existing skills of the expedition staff, we aimed to activate expedition impacts by deploying health coaching, emphasising increased self-determination. 2. Methods 2.1. Study Design To assess sustained positive impacts on health and well-being arising from participation in an OAA, semi-structured interviews were conducted with participants before, during and up to 18 months after a demanding month-long Himalayan mountaineering expedition. In this longitudinal study design, interviews with participants were carried out by a single individual researcher. Pre-expedition research was conducted to understand the existing changes participants wanted to make to their lives to improve their well-being and how they believed the expedition could facilitate this. The longitudinal element of this study design allowed the effects of this OAA intervention to be examined over an extended period of time, to assess the lasting effects of the expedition on the well-being and personal development of the military veterans. 2.2. The Expedition Through an immersive expedition to Nepal, supplemented by three UK-based training weekends, the Mission Himalaya expedition was developed in line with the theoretical framework that underpins the delivery of developmental courses for veterans at the Battle Back Centre [15]. The expedition involved a 23-day trek in the Everest region of the Nepalese Himalaya, including an attempt to summit Mera Peak (6476 m/21,247 ft). 2.3. Theoretical Orientation of Health Coaching Beyond exploring the impact of the expedition itself, this study also explored how self-determination coaching could amplify well-being benefits over a long-term period. Ryan and Deci [16] define well-being as “a complex concept, primarily concerned with optimal psychological experience and functioning”. As a key well-being theory, self-determination theory (SDT) is concerned with the motivation of behaviours, holding that positive growth, integrity and well-being rely on an individual’s basic psychological needs for autonomy, competence and relatedness [16]. Autonomy refers to the ability for an individual to make independent decisions and take control of one’s actions. Competence is associated with an individual successfully achieving mastery of activities and goals. Relatedness entails an intrinsic need to feel connectedness through both care of others and experiencing a sense of belonging. These three concepts provide practical actionable levers for any health coaches seeking to optimise intervention outcomes focused on psychological well-being. 2.4. Recruitment and Ethical Consent The only inclusion criterion was to be a veteran member of the Mission Himalaya Expedition. Initially, all veteran expedition members were invited to participate in the study on a training weekend three months prior to the expedition. Prior to acceptance, all participants received a verbal briefing about the purpose of the study, reassurances about anonymity and confidentiality, made by the expedition researcher (CK). All agreed, giving a sample of nine males and one female. Subsequently, participants were provided with an information sheet, via email, detailing the aims and methodology of the study and explaining in lay terms what would be expected of them if they agreed to participate. Potential participants were asked to take a minimum of 24 h before acknowledging that they had read and understood the participant information sheet after which time informed consent was obtained from those wishing to take part in the study through completion of an electronic consent form. Ethical approval for the study was obtained from the Leeds Beckett University Ethics Committee (50538). 2.5. Participants All 10 participants were UK veterans of the armed forces, all of whom had faced personal, physical or mental health difficulties in their lives, some of whom were medically discharged from service. They were members of the Royal British Legion’s (TRBL) Mission Himalaya expedition to Nepal in 2018. None had trekked in the Himalaya before and only two had any mountaineering experience. The length of time since the participants had served ranged from 2 to 31 years, and participants were aged 29 to 62 years. Pseudonyms are used to maintain participants’ anonymity. 2.6. Health Coaching on a High-Altitude Mountaineering Expedition The Mission Himalaya experience was developed from the five-day Battle Back courses that support UK veterans and recovering serving personnel. The courses use adaptive sport and adventurous activities as a context for personal growth and development. Staff operate in a health coaching capacity with the participants they support and host meaningful reflective practices to facilitate sustainable positive behaviour change [17]. This ethos was transferred to the development of the Mission Himalaya trip for the 10 veteran beneficiaries. All expedition staff were experienced Battle Back health coaching staff, meaning they were fully inducted into using the self-determination theory that characterises those courses, namely that of encouraging long-term behaviour change through the improvement of participants’ psychological needs of autonomy, competence and relatedness. Three of the four expedition coaching staff were veterans themselves, with years of military experience, and all were experienced mountaineers who built close, positive working relationships with team members across the 12 months of expedition training prior to the expedition. The dual role of coach and mountaineering instructor led to a wide acceptance of their physical and emotional role in supporting the participants. Intentionally, the coaching staff worked specifically with two or three of the participants to develop a close, supportive relationship. They proactively engaged in reflective practices with their veterans at appropriate times on the expedition, on rest days and while at camp in the evenings, etc. 2.7. The Expedition Researcher The expedition researcher (CK) was a climbing and mountaineering instructor. From three months prior to the expedition taking place, he took part in all aspects of the pre-expedition, training weekends, camping and hill walking with the participants, etc. He then participated fully in the expedition to Nepal, trekking with the participants, spending time with them on rest days and at camp. He also summited Mera Peak with one of the veterans and coaches. This immersion helped to build familiarity, trust and rapport and allowed for an in-depth account of what took place throughout the expedition. Creating the opportunity to build such a close relationship with the participants was intended to improve the likelihood of gathering meaningful and honest accounts of the participants’ experiences during the research interviews. Field notes, maintained throughout the expedition, detailed key events and participant concerns, personal development progress and challenges. 2.8. Data Collection The researcher conducted semi-structured interviews with the 10 participants in two distinct phases. Phase one interviews were conducted before and during the expedition. Phase two interviews took place after the expedition over 6–18 months. Interviews involved the researcher using a list of topics or questions as a guide to cover relevant subjects during the discussion [18]. The use of semi-structured interviews allowed continuity between meetings and gave flexibility to the themes, encouraging a more relaxed discussion, aiming for rich and detailed data [19]. The Stages of Change model, which includes a series of five stages (pre-contemplation, contemplation, preparation, action and maintenance) that an individual will experience for behaviour transformation, was used as a guide to structure the phase one interviews [20]. Phase one interviews therefore focused on participants’ responses in terms of readiness to change. Conducting pre-expedition research aimed to understand what participants believed they could gain from the expedition and provided an individualised understanding of what success meant to everyone. Phase two interviews all took place via telephone, with a focus on the outcomes of the expedition and personal development of the participants. 2.9. Data Analysis Semi-structured interviews were audio recorded, then transcribed and analysed using Braun and Clarke’s [21] six-step thematic analysis (TA) method. Researchers categorised the text data into codes, which were then grouped into coding sets based on key themes. This “inductive analysis” is a data-driven form of TA, involving the coding of data beyond constrictions of a pre-existing coding frame. The resulting flexibility allowed themes to emerge from the data. To avoid overlooking close details, NVivo software package was used in the coding process. Direct quotes were taken from the interview transcripts to illustrate the participants’ experiences within each key theme. To address the guiding framework of the health coaching underpinning the expedition experience, SDT concepts (autonomy, competence and relatedness) were also used as sensitising themes. 3. Results 3.1. Phase One—Before and during the Expedition 3.1.1. Worthiness of Recovery Support Unsurprisingly, the experiences of all 10 participants varied during and after their time in the armed forces. Some participants had been medically discharged, others were diagnosed with healthcare issues or injuries and some had no clinical diagnosis of illness or injury. Despite various struggles with their mental health, when posed with the opportunity to participate in the expedition, many of the veterans felt “undeserving of being a participant” (Ellis) or “a little bit of a fraud” (Sam). This was particularly common in cases where the participants had not sustained severe physical injuries but mental or moral injuries and considered themselves “not a veteran that has been blown up” (Ellis). When faced with the expedition application, several of the participants demonstrated high levels of self-doubt, stating how they had felt there was “no point in applying” (Ashley) and described having a “definite lack of belief” (Jo) that good things could come from the expedition. The extent to which participants felt the expedition could facilitate positive changes in their lives varied from very little to complete belief that it would “be a beneficial part of recovery” (Ellis) and significantly benefit their well-being. Some of the participants also recognised that the expedition had the potential to benefit their physical health positively, enabling them to “get a bit fitter” and “lose a bit of weight” (Pat). The participants’ lack of self-confidence in relation to their eligibility for the expedition highlights their inability to take control of their own actions or make decisions and demonstrates a low level of autonomy and competence before the trip. 3.1.2. What Did the Participants Want to Change in Their Lives? General State of Mental Well-Being The most common desired life change mentioned by the participants during the pre-trip interviews was in relation to improving their general mental well-being and personal development or growth. For differing reasons, the grounds behind leaving the armed forces had left many of the participants in a poor state of mental ill health or a “bad place” (Jo). Before the expedition, some participants described their personal situation and state of mental health negatively, for instance, as “suffering terribly from social anxiety” (Dan) and feeling “tearful and stressed out” (Ellis). One participant stated that they were “really struggling with suicidal thoughts” (Charlie) and another described themselves back then as “a pretty negative person” (Pat), going on to explain that they had been “in therapy, trying to juggle different medications” at that time. Others similarly recalled “things breaking down at home… and that’s when I went off the rails” (Jo). Following significant personal setbacks experienced around the time of being medically discharged from the armed forces, one participant explained wanting to return to “operating at full potential” (Ellis) following the trip. After undertaking training weekends for the expedition, the participants began to recognise the potential “amount of time to reflect on stuff” (Elliot) the trip would provide them with and the satisfaction they could feel from completing tasks and goals during the trip. They deduced that these tasks could enable them to “come back in a mentally better place… with something concrete and say yeah I have done this or done that” (Charlie). In speaking generally about their mental well-being, the majority of the participants hoped that the experiences on the trip would act as “a period of growth” (Ellis) and enable them to feel “mentally enriched” (Sam) on their return, with a rejuvenated sense of meaning and purpose. The descriptions of the participants’ personal situations before the expeditions demonstrated that their mental state of well-being was generally quite negative. They recognised that by achieving goals associated with the trip, they would feel more satisfaction in life, which would be a result of increased competence. 3.1.3. Communication and Relationships with Others In addition to improved general mental well-being, many of the participants expressed desires for the expedition to enable them with the skills and experiences to improve their communication and relationships with others. Before the expedition, a number of the participants described their struggles in tolerating others or “maintaining healthy working relationships with people” (Jo) and being “able to work well in a team” (Jamie). The desire to develop more empathy for others was commonly discussed amongst multiple participants, recognising how this could benefit them “generally through life and day to day situations” (Jamie) and reduce the risk of them getting angry. Jamie, in particular, acknowledged how, before the expedition, his angry outbursts had resulted in violent exchanges which could have resulted in imprisonment, recognising that significant changes needed to be made to avoid recurrence of this situation. In addition to improving tolerance and team-bonding skills, some of the participants recognised that the expedition could facilitate them in “developing a social network of friends” (Frankie) and enable them to build relationships with other veterans in a similar situation to themselves. By spending an extended period of time with a variety of different individuals on the expedition, the participants noted that their communication skills and team-working ability would be tested. One participant commented in depth on how they imagined the expedition may help to improve their ability to interact with others: “It will put me in a challenging position where I might be tired and stressed, but let’s take that back to a workplace where I might be under pressure […] translate that to being absolutely knackered at altitude and being sick and stressed; and the relationships might be under strain in the group. The expedition will replicate the most extreme circumstances where you will have to kind of really apply that team ethic and understanding of other people and tolerance.” (Jo) Expressing a distinct need for improvement in their ability to interact with others and build stronger relationships through more tolerance exemplified the participants’ lack of satisfaction with their basic psychological need for relatedness. 3.1.4. Employment Many participants talked about wanting to improve their employment situation, improve their job satisfaction, find work or take up a more prolific job to increase their earnings to support themselves and their family. Many participants noted their struggles in settling into a new career since leaving the armed forces. Before the trip, participants described feeling “fed up with the same s*** every day… and hated every minute” (Ashley) of their working lives. Many of the participants displayed a level of dissatisfaction with their employment situation, for instance, Frankie expressed not having “a career as such yet”. Frankie did however recognise that the expedition could “open a few doors for myself and maybe others… show me a new world and you never know a future career”. Four of the participants discussed wanting to use the expedition to improve their mountain skills and subsequently enhance career opportunities in the outdoor sector or as a future leader on trips such as Mission Himalaya to support other military veterans. Ellis noted that the expedition would be “a really fantastic experience personally to get something great out of it… and see people doing stuff that I would like to do at some point”. The expedition was viewed by the participants as a potential opportunity to unlock knowledge about “going to the Himalayas and being on expeditions with a group… all experience that goes towards my CV” (Elliot). Changes regarding their ability to secure employment was key for the majority of the participants. They maintained that if changes such as improving their ability to “work in a challenging professional manner again and… make an impact” (Ellis) were not made, they risked being left not working to their full potential or settling on something they would be dissatisfied with. Charlie stated that by going on the expedition and learning “what limitations I have” would enable a better understanding of “what kind of career I could be best suited to”. By increasing their skills and confidence levels during the expedition, the participants foresaw that Mission Himalaya could help their future job applications, such as Ashley in “applying for the Fire Brigade next year”. Increasing their confidence to independently undertake tasks associated with employment had the potential to address the low levels of competence that many of the participants displayed whilst also enabling them to feel a greater sense of purpose. 3.1.5. Physical Health and Routine Physical health and fitness were also a key theme of the phase one interviews. Every participant mentioned physical health and fitness in relation to aspects of their life they wanted to change. For some, this was wanting to “get back to who I used to be, physically… and use the expedition as a way of driving me back into the outdoors environment” (Charlie). Many of the participants recalled a previously high level of physical fitness from their days in the armed forces, describing how, since becoming a military veteran, they had “let themselves go” (Jo) or “got quite fat… and sort of been up and down with weight” (Frankie). During the discussions about their physical health before the trip, the participants discussed in depth how their poor state of mental health had impacted their physical health and fitness or motivation to go out and exercise: “A typical day was getting up around four o’clock every morning, erm, sorting the dog out if he was at home and then going to work. Doing a twelve to fifteen hours day lorry driving and then if I wasn’t sleeping out in the cab I was coming home and was basically chilling out or lying around on the settee before bed because I was knackered.” (Ashley) In the lead up to the expedition, with the motivation of the trip and training weekends, many of the participants recognised the positive mental health benefits that resulted from them becoming more active again, stating how they “felt happy… and your mind feels much clearer” (Ashley) after exercise or outdoor physical activity. Most of the participants noted that even at this early-stage interview, having the motivation to train for the expedition helped them “lose weight” (Pat) and become “so active” (Frankie) which gave them “more get up and go… and confidence to grow by the day” (Jo). Many participants linked the aspiration to improve their fitness levels with their desire to create more routine in their lives. They surmised that the “regular routine and getting up early” (Jamie) during the four-week expedition would re-introduce them into the positive rhythm of having a daily routine and instil habits they wanted to maintain “doing when I get home” (Dan). Charlie stated that a “mindset which involves getting up and doing physical activity is going to improve my physical and mental health”. The process of preparing for the expedition clearly aided the participants in an improved sense of confidence, physical fitness and overall mental well-being, much of which they “largely attributed to being able to use the training weekends as short-term goal setting for fitness” (Jo). By utilising the expedition to regain ability in controlling their own behaviours, the participants had the opportunity to improve their autonomy. 3.1.6. Readiness to Make Change When asked if they felt ready to use the expedition to facilitate making the aforementioned positive changes to their lives, the majority of the participants demonstrated their commitment in feeling ready for change. The intensity or level of readiness for change ranged from some individuals reporting feeling slightly less confident about their ability to make these changes, to others feeling “100% committed to those changes” (Jo). Despite some concerns, the majority of the participants were confident in feeling “beyond ready… with no hesitation” (Sam) and many noted that the risk of not making these changes could result in lower moods, reduced motivation and well-being, described by Frankie as a “spiral down into depression again I suppose, just not going anywhere and just going around in circles”. The findings from the interviews before the expedition highlighted the need for improvements to the levels of autonomy, competence and relatedness for the participants, who had all struggled with their mental health to varying extents and in multiple areas of their lives, following their exit from the military. The findings from the phase one interviews highlight the desire and readiness for change in the majority of the participants. 3.2. Phase Two—6–18 Months after the Expedition The findings from the phase two interviews are grouped based on the topic areas that emerged from the conversations. This section will present the evidence for the extent of attribution, expressed by participants, of the transfer of the experience to their day-to-day lives. 3.2.1. Altered Perspective A key theme to emerge from the follow-up interviews was the altered perspectives of many participants, which they experienced following their involvement in the expedition. The key factors for this change in outlook were identified as emerging via mental and physical challenge, cultural exposure and learning about other people’s recovery journey. Physical and mental challenges were an almost daily occurrence on the expedition, which involved being at an altitude of between 3000 and 5000 m for most of the trek. The nature of this high-altitude expedition additionally involved disturbed sleep and emotional strains of working as a group. For many, the expedition was extremely challenging, for instance, Jamie described it as “mentally and physically the hardest thing I have done”. Multiple participants reported that the tough moments they faced and the challenges they overcame led to a shift in their perspective of what was possible for them, both physically and mentally: “If you overcome adversity in your life, then you end up being able to cope with it... I am not worried about panicking so much because I know I can control it, but I am also not worried about saying no and saying actually I don’t want to do it... I don’t want to push myself beyond that... whether that be exercise or whether that be at work.” (Pat) In addition to the challenges that altered their perspectives, many participants spoke about the way in which the exposure to “Nepal as a whole country and the people” (Sam) influenced their perspective on their own lives, their ways of thinking and their ability to be more content with their living circumstances: “If everyone could go to Nepal and sort of see how it is actually possible to be happy with very much less than what we have over here […] so much stuff that we have and do is really unnecessary. I certainly look at things differently. I think we all appreciated that to a degree at the end, having the perspective that I have from Nepal, it’s really helped.” (Charlie) Learning about the recovery journey of others emerged as another way in which the perspectives of the participants were altered. The time away in Nepal presented multiple occasions in which the participants could interact with other veterans in smaller sub-groups and have open conversations, sharing experiences. For many, understanding “the mental health issues and trauma some people have been through” (Sam) helped to influence their perspective on their own situation and enabled these participants to “draw strength from how others dealt with it” (Charlie). Impacting the perspective of the participants and potentially influencing their outlook or purpose in life aligns with improved well-being, undoubtedly initiated by their experience on the expedition. 3.2.2. Employment Skills and Work Life Balance In discussing some of the changes made in their lives as a result of the expedition, over half of the participants discussed substantial changes in their careers. One participant in particular, Pat, a veteran of the Royal Army Medical Corps, described a significant change in their employment situation. Before the expedition, Pat was unable to work and was in a state described by themself as very “negative”, undergoing therapy and taking multiple medications. Pat had been advised to seek employment outside of medicine, since attempts to return to work had been so unsuccessful. When exploring Pat’s perspective of attribution, Pat described how the expedition had enabled a “change in where I was positioned” which helped in being “more confident in my ability to make choices” and “taking on more responsibility”. The expedition also helped Pat with learning to control anxiety attacks, providing opportunities to “practice breathing and controlling it”. Pat attributed the expedition as partially responsible for the regained confidence in themself and their ability to work, stating, “I don’t know if I would have ended up at this point had I not gone on an expedition. I don’t know if I would have ended up back at work”. The confidence in decision making described by Pat, which resulted from the experiences of the expedition and translated into the participants’ daily work or lives, was supported by others who also felt they had “more confidence” (Jamie) in their “own decision making ability” (Charlie). Having a higher level of self-belief with regard to making independent decisions and feeling in control of one’s behaviours and destiny illustrates the increased autonomy that resulted from the expedition and subsequently improved the participants’ mental state of well-being. Multiple other participants found they could attribute the expedition to helping them have a new perspective on the importance of their work style, which emerged when discussing the changes to their careers following the expedition. Ashley, for instance, fulfilled a long-term goal of “working for The Fire Service”, despite the struggles in applying for this position before the expedition. Other participants attributed the expedition to providing them with “more structure and stuff to aim for” (Charlie) in relation to financial security and employment. Having the ability to master tasks, such as securing new job roles and achieve goals linked to financial security, represents improved satisfaction with the basic psychological need for competence in these participants following the expedition. 3.2.3. Relationships with Others Two key relationships on the expedition for the participants were those with the staff and those with the other team members. The influence both of those had on subsequent relationships with friends, family members and the community after the expedition was commented on widely by the participants. The verbal encouragement and support received by the staff members on the expedition was described by the participants as “a massive pick-me-up” (Charlie), with many mentioning how beneficial they had found being able to have multiple ongoing one-to-one conversations with staff members. Pat described these chats as useful to “talk through things and focus on the smaller things and managing me”. In addition to the support from the expedition staff, all the participants mentioned the “camaraderie and togetherness of the group… the strengths and the weaknesses that we pulled each other through, the good and the bad times” (Sam). The strength in the relationships the participants built amongst one another were enabled through the “shared experience” (Charlie) and the nature of a high-altitude expedition. For instance, sharing a tent with another team member on the expedition enabled the participants to “build those relationships and bonds” (Ellis) that were perhaps less easy to achieve back home. The unique nature of spending three weeks walking with others enabled the veterans to “speak to people a lot more and you got to know them a lot deeper as a person… it was so easy to speak about very deep things, without people being afraid” (Sam). Charlie confirmed the depth of these relationships through the distinctive characteristics of an expedition, stating that going to Nepal was a: “… unique experience for those involved, it’s quite a long way different from the, sort of, day to day experiences of the vast majority of people. I think all of those things sum up together to make it a much stronger bonding experience.” (Charlie) Some of the participants felt that the relationships they built with others on the expedition motivated them in wanting to help others when they got home and “put something back into the veterans community” (Pat). The importance of “maintaining those contacts… and being amongst others, being able to talk freely and more openly” (Charlie) was important to many participants, who used the expedition to build strong relationships with individuals that became “lifelong friends” (Pat). Upon returning to their partners and families after the expedition, some of the participants discussed how their experiences and the personal development they had undergone throughout the expedition and afterwards had impacted their existing relationships at home: “When you come back, I certainly made more of an effort to do things together, which probably I did before, but not as much. And we make time for conversation now, and we sit outside and just talk a lot more. So yeah, so I certainly appreciate my partner a lot more.” (Sam) Increasing the ability of the participants to feel a sense of attachment and belonging to others, during and after the trip, highlights the impact a high-altitude expedition of this kind can have on the relatedness of military veterans. 3.2.4. Behaviour Change: Physical and Mental Health The physically demanding nature of the expedition had a generally positive influence on the activity levels and physical health of the participants. One participant described the trip to Nepal as significant because “it revalidated me physically” (Charlie) or encouraged the participants to “start doing a bit more training” (Jamie). Others described how they had maintained high levels of physical activity following the trip to Nepal and attributed their motivation to the expedition: “I’m still probably doing somewhere between 60 and 70 km a week, walking and I don’t lack motivation to do it... honestly, I don’t think I would have the mental strength and the mental thinking, without doing what I was lucky enough to do on the expedition.” (Sam) These reported behavioural changes resulting from expedition participation indicate improvements in the participants’ confidence to perform physical activities or tasks. All the participants made statements suggesting an improvement in their satisfaction of their psychological need to feel competent. In addition to the longer-term physical health benefits, many participants discussed the changes to their behaviours associated with mental health, such as to their enhanced personal awareness following the trip. The intentional focus that was put on personal development by the coaching staff developed participants’ reflective practice after the expedition and enabled them to “function better” (Jo). Many of the participants described how their “thinking process is now totally different to how it used to be… the whole thing made me a better thinker” (Sam). Being a “better thinker” translated into the participants describing how they felt calmer and more relaxed in difficult situations and like they can now “deal with stuff much better” (Charlie). The experiences on the expedition enhanced the ability for individuals to feel independently in control of their mental health, reflecting improved autonomy. 3.3. Summary of Results In the interviews before and during the expedition, all participants alluded to a lack of fulfilment of the basic psychological needs of autonomy, competence or relatedness. For some, it was in expressing their lack of worthiness for support, intolerance of other people, displeasure with their work circumstances or lack of self-belief. In the phase two interviews, all the participants had shifted to describing improvements in aspects of their life, behaviour and thinking that align with the basic psychological needs from the SDT. Interview evidence, drawn from multiple timepoints, indicates the ongoing and sustained change in well-being and personal development. The three needs and their alignment with the resultant themes are identified and summarised in Table 1. 4. Discussion 4.1. Summary of Key Findings The principle finding from this study, involving 18 months of engagement with members of Mission Himalaya, was that the experience of a high-altitude expedition involving intentional health coaching can facilitate long-term meaningful change for participants. This prolonged and intentionally designed experience helped participants to detach themselves from their home contexts, to focus on the context of the expedition, and as a result, to regard themselves—and describe themselves—“with more distance”. Most participants had successfully begun to see themselves as a “project” and were working to become more successful back at home. Post-expedition, many had successfully adopted new behaviours, such as regular physical activity, that many in their home contexts continued to find difficult. The findings from the pre-expedition interviews highlighted the deep desire to improve levels of autonomy, competence and relatedness. All participants had experienced some struggle with mental health—to varying extents and in multiple areas of their lives—after leaving the military. The findings also highlighted that a majority desire and have a readiness for change. Describing their histories, pre-expedition, many discussed lacking in self-belief or the ability to make independent decisions over their actions. This extended to not feeling worthwhile enough to apply for recovery support and/or to the expedition. Selection for the expedition was a powerful signal of redirection. Future expeditions should make the application process as welcoming as possible. Early interviews highlighted the many areas where participants wanted to change; interviews afforded an opportunity to stand back and reflect on personal progress desires. These needs underlined the relevance of using the SDT to ground our health coaching approach. Equally, the scale of change that had been transferred to life back home confirms the utility of the transfer of learning approaches used. Shortfalls in relatedness were often linked to poor communication skills, limited empathy for others and a weak sense of belonging. Competence was undermined by widespread difficulties with employment: some participants had failed to re-enter employment after leaving the military, while others lacked confidence in their work environments. It was common that physical activity had reduced upon leaving the military; lack of routine was commonly a problem here. For some, the preparatory training weekends mandated additional physical activity, and this helped to re-establish motivation and structure. Many participants also hoped the routines of the expedition would re-establish lost routines or behaviours back home, leading to improved autonomy. The majority of the participants demonstrated a strong commitment and readiness to make changes to their lives through the Mission Himalaya expedition. Those with a greater receptiveness for change tended to experience more significant effects and changes following the expedition. The results of this study therefore support the observation of Smith et al. [11] that participants’ agreeableness and openness play a key part in post-expedition growth. Despite this, one participant in particular (Pat), who expressed less readiness for change and belief the expedition may facilitate this, subsequently reported significant positive changes in their occupational circumstances, which were partly attributed to the expedition, following a “light bulb” (Pat) experience whilst being extremely challenged at high altitude. This illustrates that openness and readiness to change does not necessarily always correlate to the total possible change. The findings from the follow-up interviews that took place in the 18-month post-expedition period evidence the changes that were made by the participants and to what extent they attributed the changes to the expedition. The majority of the participants discussed an altered perspective on their own lives. This change in their outlook was attributed to a number of factors. First, undertaking challenging tasks during the expedition increased their confidence and ability to undertake tasks back home. Successful mastery of tasks in specific environments has the potential to improve the self-efficacy and competence of an individual [22]. Second, cultural exposure to Nepalese people who had significantly lower standards of living and money, compared with the participants, enabled them to feel more grateful for their own lives. Tourism literature widely supports the notion that exposure to host cultures and subsequent reflection is often a mechanism for transformation [23]. The participants supported this in reporting a greater sense of meaning and purpose in their own lives after these cultural experiences on the trip. Additionally, learning about the recovery journey of others stimulated reflective thought in the participants about their own lives, compared to the problems faced by others similar to themselves. This also influenced their perspectives and provided them with a greater sense of meaning, contributing to their ongoing personal development and enhanced well-being. The interview conversations following the trip highlighted multiple occurrences in which the participants attributed involvement in the expedition to the changes they had managed to achieve in relation to their employment or job satisfaction. Many participants reported an improved ability to master tasks such as job applications, which they had not been able to undertake before the expedition, demonstrating an improvement in their basic psychological need for competence. Building strong relationships with the staff and other military veterans during the expedition enabled many of the participants to improve their interactions with friends, family and colleagues back home afterwards. The specific characteristics of a challenging OAA intervention of this kind, such as sharing tents, multiple days spent walking and time away with the expedition team, were all found to contribute towards the improvement of the participants’ relatedness. The physically demanding nature of the expedition had numerous positive effects on the physical health of the participants, who reported training more in preparation for and as a result of the expedition. In line with positive physical health changes, many participants discussed the changes to their mental health after the expedition. This improvement to the thinking processes and mental strength of the participants was aided through the specific coaching of the staff who intentionally focused on personal development during the trip. The findings demonstrate that Mission Himalaya is another development in the application of adventurous activities to positively influence behaviour change and the well-being of participants. Previous studies to examine the use of OAA interventions with military veterans were cross-sectional in nature and therefore, despite their results confirming the positive impacts on the personal development and well-being of veterans, the studies were unable to observe whether these findings had a longer-term effect [13]. This research addresses the shortfalls of previous research studies and is the first study to follow the participants longitudinally. The results demonstrate that the observed positive impact of the expedition on the lives of the veterans persisted over the course of the study (up to 18 months after the expedition). The results of this study address Greer and Vin-Ravi’s [14] request for future OAA intervention processes and mechanisms that lead to positive outcomes to be better explained by providing a deeper insight into the ways in which this expedition facilitated enhanced well-being and personal development. Additionally, an improved understanding of life enrichment for veterans through the challenges presented by a meaningful goal, such as an expedition, could illuminate longer-term understanding and better knowledge surrounding the transition to civilian life as well as personal development [14]. This study has enhanced our understanding of the influence that challenging expedition experiences can have on participants’ lives to an extent that has not previously been achieved. 4.2. Strengths and Limitations Many expeditions have previously failed to collect satisfactory data sets regarding participant well-being [24]. The resulting database has been dominated by low compliance, short expeditions, fee-paying civilian participants and a lack of longitudinal research periods. By embedding a researcher throughout the preparatory, expedition and post-expedition periods, the study is unique. Developing the delivery to be theory-guided and to address transfer of learning to ensure prolonged impacts makes it totally unique. As a result, our study represents an unrivalled database, generated from ten UK veterans across 18 months of qualitative data gathering. Participants will continue to be invited to contribute follow-up interviews for five years, until November 2023. A small number of programmes, similar to Battle Back’s Mission Himalaya expedition, exist in other countries, such as the USA, where veterans from recent wars reside. Some of these programmes are similar in nature to Mission Himalaya, with the use of OAA to improve the lives of military veterans. Examples of these similar programmes in the USA include the Warrior Hike Program (WHP) and “Adventure Not War”. The WHP consists of a 6-month hike of the Appalachian Trail, aiming to provide a positive therapeutic effect by immersing participants in the natural environment [25]. Adventure Not War took military veterans back to Iraq for a mountaineering expedition, aiming to empower them to reclaim their lives despite their history with the country [26]. Although similar to Mission Himalaya in the context of using OAA to improve the well-being and development of military veterans, these expeditions differ in their lack of longitudinal investigation of the lasting effects on the veterans, a strength of the Mission Himalaya study. Limitations include the significant investment of time and resources and being able to participate as an expedition member. This is likely to have built the rapport and respect that contributed to the high-retention rate in the follow-up interviews. The overall process is unlikely to be a viable research method and/or process for researchers who are not also mountaineering instructors. An additional limitation of the study includes the gender balance of the sample. The predominance of males to females in the study sample is however reflective of the current UK Armed Forces which comprises 11% females [27]. Future studies could actively recruit more females. An important realisation emerged through follow-up data collection; a return to normal domestic life in the UK left some members missing the social support, the physical challenges and the personal attention of the expedition. This left them framing the highs of the expedition with the lows of feeling let down when back in the UK. Expedition funders and organisers must ensure appropriate support is put in place to help participants manage post expedition “come down”. 4.3. Future Application The study confirmed that positive health coaching can support participants in a high-altitude expedition. By intentionally including health coaching that accentuated “transfer of learning”, participants became skilled in applying their in-expedition learning to their day-to-day lives after the trip. This health coaching approach is suited to the expedition context as it is a principle-guided technique, meaning it can fit within the opportunities that emerge in the moment and/or unexpectedly. This research has useful transferable potential to provide a future template for expeditions centred on recovery and personal development. Practically, organisers of future OAA interventions could apply this knowledge to shorter expeditions in less extreme environments or destinations. 5. Conclusions To our knowledge, this is the first study to research the long-term influence of participating in a high-altitude trekking expedition that involves health coaching on the lives of UK military veterans. The expedition itself is also believed to be the first of its kind. Our findings support the prolonged use of health coaching, focused on self-determination, to encourage experiential transfer back into what had often been “troubled” daily lives. The intentional blend of health coaching into a prolonged expedition was recognised as helping to make this a meaningful, long-term positive influence for these participants, beyond the expedition itself. In a mutually reinforcing way, the delivery approach and research style can be replicated in subsequent initiatives to positively influence the lives of participants. Acknowledgments Our thanks go to the expedition staff of Himalayan Ecstasy who supported the expedition and the researcher during their time on the expedition, the coaching staff who welcomed the additional element of a research study to be conducted throughout the expedition and to the Royal British Legion who funded the expedition. Author Contributions Conceptualisation, C.W.P.K. and J.M.; methodology, C.W.P.K. and J.M.; validation, C.W.P.K. and J.M.; formal analysis, C.W.P.K. and H.L.W.; investigation, C.W.P.K.; data curation, C.W.P.K.; writing—original draft preparation, C.W.P.K. and H.L.W.; writing—review and editing, J.M.; visualisation, C.W.P.K. and J.M.; supervision, C.W.P.K. and J.M.; project administration, C.W.P.K. and J.M.; funding acquisition, C.W.P.K. and J.M. All authors have read and agreed to the published version of the manuscript. Funding This research study 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 Ethics Committee of Leeds Beckett University (protocol code 50862 10 October 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. Conflicts of Interest The authors declare no conflict of interest. ijerph-19-05049-t001_Table 1 Table 1 Alignment of the desired life changes prior to the expedition and subsequent reported changes by the participants with the three basic psychological needs from SDT. Desired Behaviour Changes Prior to the Expedition Reported Behaviour Change after the Expedition Autonomy Gaining better control of their minds and thoughts Having more routine and structure in their lives To be liberated from external pressures Autonomy Altered perspective through the challenge of the expedition Adjusting work–life balance and gaining routine Improved self-worth and confidence in decision making Personal awareness and increased mindfulness Competence Reducing a busy lifestyle and addressing issues with their occupation Desire to progress in their careers Improving physical health and fitness Have an opportunity to succeed in a challenge Competence Altered perspective through the challenge of the expedition Employment skills Improved health and physical activity levels Relatedness Improving relationships with others, family, work colleagues, etc. Sense of belonging, connectedness with others Regaining dignity Being more understanding of others circumstances Relatedness Altered perspective through cultural tourism Altered perspective through learning about other people’s recovery journey Relationships with others Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092287 cancers-14-02287 Review CD123 and More: How to Target the Cell Surface of Blastic Plasmacytoid Dendritic Cell Neoplasm Bôle-Richard Elodie 1* https://orcid.org/0000-0002-1670-6513 Pemmaraju Naveen 2 Caël Blandine 1 Daguindau Etienne 13 Lane Andrew A. 4* Funaro Ada Academic Editor Bertolini Francesco Academic Editor 1 INSERM, EFS BFC, UMR1098, RIGHT, University of Bourgogne Franche-Comté, Interactions Greffon-Hôte-Tumeur/Ingénierie Cellulaire et Génique, F-25000 Besancon, France; blandine.cael.ext@efs.sante.fr (B.C.); edaguindau@chu-besancon.fr (E.D.) 2 Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; npemmaraju@mdanderson.org 3 Service Hématologie, CHU Besançon, F-25000 Besancon, France 4 Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA * Correspondence: elodie.bolerichard@efs.sante.fr (E.B.-R.); andrew_lane@dfci.harvard.edu (A.A.L.) 03 5 2022 5 2022 14 9 228728 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/). Simple Summary Until recently, there were no approved therapies for the aggressive blood cancer blastic plasmacytoid dendritic cell neoplasm (BPDCN). Survival for patients diagnosed with BPDCN is under two years, and improved treatments are needed. In 2018, tagraxofusp became the first approved drug for BPDCN. Tagraxofusp is an interleukin 3-dipththeria toxin recombinant fusion protein that targets CD123, a component of the interleukin 3 receptor, on the surface of BPDCN cells. Here, we discuss the development of tagraxofusp and other newer agents that also target CD123. We also present rationale for several other cell surface proteins, expressed on BPDCN, that are targets for therapies already in development for other cancers and that might be also considered for evaluation in BPDCN. Abstract Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and aggressive leukemia derived from plasmacytoid dendritic cells (pDCs). It is associated with a remarkably poor prognosis and unmet need for better therapies. Recently, the first-in-class CD123-targeting therapy, tagraxofusp, was approved for treatment of BPDCN. Other CD123-targeting strategies are in development, including bispecific antibodies and combination approaches with tagraxofusp and other novel agents. In other blood cancers, adoptive T-cell therapy using chimeric antigen receptor (CAR)-modified T cells represents a promising new avenue in immunotherapy, showing durable remissions in some relapsed hematologic malignancies. Here, we report on novel and innovative therapies in development to target surface molecules in BPDCN currently in clinical trials or in preclinical stages. We also discuss new cell surface targets that may have implications for future BPDCN treatment. BPDCN leukemia AML CD123 tagraxofusp bispecific antibody CAR-T cell Programme de Recherche Translationnelle INCaPRTK N°PRT-K-20-107 MD Anderson Cancer Centre Support Grant (CCSG)CA016672 MD Anderson Cancer Center Leukemia SPORECA100632 This study was supported by Programme de Recherche Translationnelle INCa (PRTK N°PRT-K-20-107). This study was supported in part by the MD Anderson Cancer Centre Support Grant (CCSG) CA016672 and the MD Anderson Cancer Center Leukemia SPORE CA100632. AAL is a Scholar of the Leukemia & Lymphoma Society. ==== Body pmc1. Introduction Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and aggressive leukemia characterized by a clonal expansion of plasmacytoid dendritic cells (pDCs). There has not historically been a standard-of-care therapy for these patients, and they were treated with leukemia or lymphoma chemotherapies. However, conventional chemotherapy is largely inadequate in BPDCN, since although many patients initially respond, the responses are short-lived and relapsed BPDCN is quite chemoresistant. This has prompted the evaluation of alternative therapies such as targeted cytotoxins and immunotherapy. Recently, tagraxofusp became the first drug approved for BPDCN in the US and Europe. Tagraxofusp is an interleukin 3-diphtheria toxin fusion protein that targets the IL3 receptor alpha subunit, or CD123, which is highly expressed on the surface of BPDCN cells [1]. Some patients do not tolerate tagraxofusp or it may not be available, and therefore standard chemotherapy is still used. The most efficient regimens are broadly separated into these sub-types: acute leukemia treatment (AML or ALL-like), lymphoma-like treatment, and asparaginase/methotrexate-based treatments that are also used in aggressive leukemias and lymphomas. Retrospective data imply a better rate of response with first-line therapy that includes asparaginase/MTX and in ALL-like compared to AML-like or lymphoma-like treatment. However, this assumption would ideally be confirmed in prospective cohorts. Beyond those “classical” chemotherapies, innovative approaches have been developed through the integration of data on the physiopathology and oncogenesis of BPDCN. Proof of concept of the efficacy of targeted therapies such as bortezomib or venetoclax has been recently provided with in vitro models and pre-clinical data [2,3,4,5]. The recent increased use of BCL-2 inhibition in myeloid malignancies and its approval in acute myeloid leukemia along with azacitidine lead to the assessment of the venetoclax alone or in combination in ongoing clinical trials enrolling patients with BPDCN. Even if most patients respond to initial tagraxofusp or chemotherapy, relapse is common without consolidation by hematopoietic cell transplantation (HCT). In the setting of HCT, overall survival can reach 40% after a follow-up of 5 years [6,7,8,9,10]. However, relapse still occurs in at least 2/3 of allograft patients. Transplantation in first complete remission (CR1) is associated with a better outcome compared to patients not in CR1. However, HCT is associated with a significative toxicity that limits its indication to fit and younger patients. Altogether, the data reporting outcomes with chemotherapy and HCT demonstrate a large medical need for refractory patients and/or elderly patients that may not be able to undergo intensive treatments. The long-lasting remissions that have been obtained after HCT demonstrate the curative potential of adoptive therapies or immunotherapies and support the design of such novel approaches. Anti-tumor immunotherapy is a therapeutic strategy based on the principle of immunosurveillance of cancers: since the immune system is naturally capable of recognizing cancer cells and destroying them, immunotherapy consists of artificially mobilizing immune cells to recognize and eliminate malignant cells [11]. Thanks to the various clinical successes that have occurred, immunotherapy has been considered a major breakthrough in terms of cancer treatment [12]. Today, there are different types of immunotherapy: passive immunotherapy based on monoclonal antibodies, active immunotherapy using cytokines such as IFNα, IL-2, or TNF, and adoptive immunotherapy that uses effectors of the immune response such as T cells. Indeed, over the last twenty-five years, new cellular therapies against cancer based on the ex vivo manipulation and re-infusion of autologous or allogeneic immune cells have been widely tested in the clinic. These different immunotherapy approaches have shown great potential for the treatment of cancers, especially those resistant to conventional therapies (surgery, radiotherapy, and chemotherapy) [13]. 2. Targeted Therapies with Results or in Evaluation for BPDCN 2.1. Tagraxofusp CD123, the interleukin (IL)-3 receptor alpha chain, is overexpressed in 100% of BPDCN cases, and not expressed or weakly expressed on normal cells other than normal plasmacytoid dendritic cells and basophils [14,15]. CD123 was identified as a promising therapeutic target for BPDCN patients. Frankel et al. launched the first pilot studies investigating a CD123-targeted agent which featured a novel recombinant protein drug consisting of a modified diphtheria toxin payload that was fused to recombinant human IL-3 [16]. The unique drug construct, originally known as “DT-IL3”, was tested initially in patients with MDS and AML, and the trial also included a small number of patients with BPDCN [17]. Although the drug was found to have modest single-agent activity in AML and MDS in these early clinical trials, what stood out was the early efficacy signal in BPDCN [18]. Therefore, Frankel et al. embarked on a pilot early phase study specifically focusing on patients with BPDCN with the same targeted therapy, which was renamed SL-401 (Stemline Therapeutics, New York, NY, USA) [19]. In this clinical trial, a total of 11 patients, all male with a median age of ~70 years, were enrolled. Most patients were only able to receive one cycle (5 doses, days 1–5) of therapy. Among the 11 patients, 9 were deemed eligible for evaluation. The authors reported an overall response rate (ORR) of 78% (7 of 9 patients responding), including five complete responses (CRs) and two partial responses (PRs). Toxicity was notable for the vascular leak syndrome (VLS), which is now known as the capillary leak syndrome (CLS). The authors noted that CLS was found to be manageable overall and tracked with low or decreased serum albumin and weight gain [19]. The accompanying editorial by Fitzgerald noted the novel agent as a potential breakthrough in the rare disease field of BPDCN [18]. Building upon the momentum generated by these early results, Pemmaraju et al. sought to further investigate this agent in a larger population of patients with BPDCN [1]. They conducted the first prospective, multi-institutional study of a targeted agent in BPDCN using this agent, SL-401 (now known as tagraxofusp). Including both frontline (FL) and relapsed/refractory (R/R) subjects, this four-stage study consisted of: (1) a dose-escalation 3 + 3 design (FL and R/R) for safety; (2) an expansion stage (FL and R/R); (3) a pivotal confirmatory stage focusing only on FL patients (n = 13); and (4) an expanded access fourth stage. The first three stages were reported in The New England Journal of Medicine by Pemmaraju and Lane et al. in 2019 demonstrating that among the first 29 patients enrolled and treated at the target dose of 12 µg/kg/day dosing, in the FL setting, SL-401 monotherapy yielded a 90% overall response rate including 72% rate of CR/CRc (CR or CR “clinical”–CR in all sites except minimal residual skin abnormality). They found that the median overall survival (OS) at 2 years was 52%, and 45% of patients were bridged to stem cell transplantation in the first-line treatment setting. In the R/R setting, a 67% ORR was observed among the 13 patients treated, with a median OS of 8.5 months. CLS was the most important toxicity, which was reported in approximately 20% of patients and was the cause of two deaths [1]. Based on these data, SL-401 (tagraxofusp) was granted US FDA approval on 21 December 2018, for patients with previously untreated or relapsed/refractory BPDCN ages 2 and older, and then later in the EU for adults for first-line treatment in January 2021 [20]. The CLS toxicity appropriately was designated as a “black box warning” on the package label insert [21]. This approval marked an important milestone in the field, as it was not only the first targeted agent approved specifically for patients with BPDCN, but also the first ever CD123-targeted agent approved in hematology/oncology [22,23]. Tagraxofusp is now being tested in combination with azacitidine and venetoclax in clinical trials for patients with BPDCN, AML, and myelodysplastic syndrome (MDS) with early reports of safety and efficacy reported at the American Society of Hematology Meeting in 2021 [24]. 2.2. Monoclonal or Conjugated Antibodies Given the high and uniform expression of CD123 in all BPDCNs, several antibody-based drugs targeting CD123 have been developed. Early efforts were composed of iterations targeting CD123 via “naked” monoclonal antibodies [25] or antibody–drug conjugates (ADCs) [25] in patients with AML, and plans to apply the same agents to BPDCN. Unfortunately, most did not reach the stage of testing in patients with BPDCN in clinical trials. However, from a disease-specific trial that is still ongoing, we now have data in patients with BPDCN using the CD123-ADC IMGN632 (ImmunoGen, Waltham, MA, USA). IMGN632 is a humanized IgG1 monoclonal antibody specific for CD123 with a payload consisting of an indolinobenzodiazepine pseudodimer (IGN) with a peptide linker [26]. IMGN632 binds to CD123-expressing cells, is internalized, and releases FGN849, which is a potent DNA alkylating agent. Treatment of CD123+ AML cells with IMGN632 causes DNA damage, S-phase cell cycle arrest, and apoptosis [27]. IMGN632 potently kills the BPDCN cell line CAL1 and is active in vivo in patient-derived xenograft (PDX) models of BPDCN. Laboratory studies suggest that, by virtue of their lower CD123 expression, normal hematopoietic stem and progenitor cells are not as sensitive to IMGN632 as CD123+ BPDCN and AML leukemia cells [28]. IMGN632 is being tested as a single agent in patients with previously untreated or relapsed/refractory (R/R) BPDCN (ClinicalTrials.gov (accessed on 21 March 2022) Identifier: NCT03386513). Results in the first 23 patients with R/R BPDCN were presented at the American Society of Hematology meeting in December 2020 [29]. Seven of twenty-three patients had an objective response (2 CR, 2 CRc, 1 CRi, and 2 PR) for an overall response rate of 30% (95% CI, 13–53%) and a composite complete remission rate of 22%. The duration of response for the four CR/CRc patients was between 3 and 9 months, all without receiving stem cell transplantation. The drug was well tolerated with no grade 3 or higher adverse events in more than one patient. The most common grade 1–2 events were nausea, peripheral edema, and infusion-related reactions. In contrast to tagraxofusp, no capillary leak syndrome (CLS) was observed. After these data were reported, the study was expanded to include previously untreated patients with BPDCN and is ongoing in the US and Europe. As a result of this encouraging preliminary evidence of activity, IMGN632 received breakthrough therapy designation (BTD) from the US Food and Drug Administration in October 2020 specifically for treatment of BPDCN. This grants priority review to the agent and manufacturer for future evaluation by the agency. IMGN632 is also being tested in combination with azacitidine, venetoclax, or both, in a Phase 1b/2 study for patients with AML (ClinicalTrials.gov (accessed on 21 March 2022) Identifier: NCT04086264). Based on safety and efficacy data from this study, IMGN632 combinations might also be explored in BPDCN in the future. 2.3. Bispecific Antibodies Bispecific antibodies are protein drugs that have two different antigen binding sites. In general, most bispecific antibodies bind to a target on tumor cells (e.g., CD123) and a target on T cells (e.g., CD3; forming a BiTE or Bispecific T-cell Engager) to bring the immune cell in proximity to the tumor cells. This results in more specific tumor cell killing [30]. Modifications of the bispecific antibody constructs to improve activity or to recruit different immune cells, such as natural killer cells, have alternative names such as dual-affinity retargeting antibodies (DARTs) or bi-specific killer engager antibodies (BiKEs). Blinatumomab is an approved bispecific antibody for the treatment of B-cell acute lymphoblastic leukemia (B-ALL) that engages CD19 on leukemia cells and CD3 on T cells. There are no currently approved bispecific antibodies that target BPDCN surface antigens. Results from trials using bispecific antibodies have not yet been reported in patients with BPDCN. However, encouraging results from trials testing CD123 bispecifics in AML suggest they have the potential to be active in both diseases. Flotetuzumab (MacroGenics; Rockville, MD) is an anti-CD123 x CD3 DART that has been evaluated in the setting of primary induction failure or early relapsed/refractory AML. Among 88 patients treated in an open-label phase 1/2 study, 30 patients who received the recommended phase 2 dose achieved a complete remission (CR)/CR with a partial hematologic recovery (CRh) rate of 26.7%. In patients who achieved CR/CRh, median overall survival (OS) was 10.2 months (range 1.87–27.27). A 10-gene expression signature predicted CR/CRh to flotetuzumab and correlated with bone marrow immune cell infiltration at baseline. Adverse events were mostly infusion-related reactions and cytokine release syndrome (CRS), largely grade 1–2 [31]. Capillary leak syndrome was not a prominent toxicity. Flotetuzumab is currently being tested in a basket trial for relapsed/refractory CD123-positive malignancies, including BPDCN (NCT04681105), but data from this trial have not yet been reported. Other bispecific antibodies targeting CD123 × CD3 that are being tested in patients with AML include the BiTEs vibecotamab (XmAb14045) [32] and APVO436 [33] (that have been reported only in abstract form to date). Both have demonstrated activity in relapsed/refractory AML and have similar safety profiles as flotetuzumab, with relatively frequent but low-grade CRS. These agents may also be tested in BPDCN in the future. 2.4. CAR-T Cells A CAR is a chimeric antigen receptor composed of three domains: (i) an extracellular domain that determines specificity—this is the scFv (single-chain variable fragment) of a monoclonal antibody specific to a tumor antigen; (ii) an intracellular signaling domain derived from a T-cell signaling molecule; (iii) a transmembrane domain (hinge or spacer) that links the two preceding domains and plays a role in the conformation and accessibility of the receptor to its target [34]. This strategy allows for direct recognition of tumor antigens expressed on the cell surface, independent of major histocompatibility complex presentation to T-cell receptors. Furthermore, by using the scFv of an antibody, CARs can be used to recognize a wide range of structures including proteins and non-protein structures, such as carbohydrate antigens [35]. The first CARs were developed in the late 1980s and corresponded to the variable region of a monoclonal immunoglobulin for the extracellular portion and to the regions of a TCR for the intracellular region [36,37,38,39]. However, the first “true” CAR was developed in 1993. This so-called “T-body” construct consisted of an scFv fused to the CD3ζ chain [40,41]. This first generation of CARs provided proof of concept despite limited clinical effect [42,43]. Indeed, cellular therapies modified with this type of CAR showed poor expansion and limited persistence. These weaknesses reflect a failure of T-cell activation by CARs in the absence of co-stimulatory molecules such as CD80 or CD86. The interaction with these co-stimulatory molecules is part of the three signals required for full activation of a CAR-T cell. Second- and third-generation CARs, including several co-stimulatory domains, have been developed [43,44]. These CARs that include 4-1BB or CD28 or both domains have been evaluated as a mechanism to promote tonic signaling and enhance in vivo persistence [45,46,47]. The expected promise of CARs has been highlighted with the success of anti-CD19 CARs in ALL (acute lymphocytic leukemia) and NHL (non-Hodgkin’s lymphoma), where complete remissions have been induced in numerous patients resistant to multiple lines of chemotherapy [48,49,50,51]. The first published clinical trial used a second-generation CD19-specific CAR (CD28/CD3ζ) for the treatment of ALL in relapsed adult patients [48]. In this trial, the authors evaluated 32 patients and observed a 91% response rate. Numerous clinical studies using CARs targeting CD19-positive malignancies then followed. Although each trial had its own criteria for patient recruitment and conditioning, as well as the configuration of the CAR, similar results were obtained with a response percentage between 70 and 100% in patients with leukemia and non-Hodgkin lymphoma [52,53]. Since 2017, two CD19 CARs (Tisagenlecleucel [Kymriah], Novartis; and Axicabtagene ciloleucel [Yescarta], Kite Pharma/Gilead) have been approved in the USA first, then subsequently in Europe and several other countries. Since 2013, several groups have developed and published preclinical studies using CD123-directed CAR-T cells [54,55,56,57,58] in AML and BPDCN (Figure 1). These CARs are often second generation, but some of them are third generation constructs based on the costimulatory and other domains used [57]. Today, 28 phase 1 or 2 CD123 CAR trials are listed in clinicaltrials.gov (accessed on 21 March 2022), mainly in AML. Most trials are open in China using second- or third-generation CARs, but none have communicated results to date. In the USA, several CD123 CAR-T trials are ongoing, some of which include patients with BPDCN (Table 1). Cellectis conducted a clinical trial in BPDCN using allogeneic engineered T cells expressing an anti-CD123 chimeric antigen receptor. This is a second-generation CAR (CD123 scFv-41BB-CD3ζ) with a safety switch based on the RQR8 depletion ligand (confers susceptibility to the anti-CD20 monoclonal antibody rituximab). The expression of the endogenous T-cell receptor αβ (TCRαβ) is abrogated through the inactivation of the TCRα constant (TRAC) gene, using Cellectis’ TALEN gene-editing technology. In a pre-clinical study, they demonstrated a specific cytotoxic effect on BPDCN cells and prolonged survival in mouse xenograft models of BPDCN [59]. In the phase 1 trial, one patient with BPDCN was treated with a dose of 6.25 × 105 CAR-T cells/kg (NCT03203369). Unfortunately, this patient had severe cytokine release syndrome (CRS) and died on day 9 after cell infusion. This trial has been closed for patients with BPDCN. However, the trial is ongoing in AML (NCT03190278) and is currently in dose escalation, with goals to evaluate the safety and clinical activity of UCART123v1.2 and to determine the maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D). Mustang Bio developed an autologous CD123 CAR-T cell product called MB-102. This CAR has a second-generation construct composed of a CD123 single-chain variable fragment, an optimized IgG4 CH2CH3 linker, with CD28 and CD3ζ signaling domains. Previously, this CAR demonstrated a strong activity on CD123+ AML cells in vitro and in vivo [54] without ablation of normal hematopoietic progenitors (CFU and BFU) from cord blood. A safety switch composed of EGFRt is incorporated in the construct, targetable by the anti-EGFR monoclonal antibody cetuximab. Today, two clinical trials are ongoing using this cell product (NCT02159495 and NCT04109482). The first one is a phase 1 trial aimed to study anti-tumor activity and safety of administration of ex vivo-expanded genetically modified T cells with two cohorts (AML and BPDCN). The second one is an expanded phase 1/2 study to assess the safety and efficacy of MB-102 in patients with relapsed or refractory BPDCN. To date, two patients with BPDCN have been treated with 100 × 106 cell doses. Complete remissions have been observed with well-tolerated side-effect profiles, including only reversible and expected toxicities seen (e.g., all CRS was ≤grade 3). Mireya Paulina Velasquez’s team in St. Jude Children’s Research Hospital is also evaluating a CD123-specific CAR in patients with recurrent/refractory CD123+ disease (AML, B-ALL, T-ALL, or BPDCN) as a bridge-to-transplant phase 1 clinical study (CATCHAML, NCT04318678). This is a second-generation CAR with a CD28 H/TM region and CD28ζ signaling domain and includes a CD20 sequence as a safety switch [60]. The University of Pennsylvania is conducting two phase 1 clinical trials using second-generation CD123 CARs based on 4.1BB and CD3ζ with different delivery methods (RNA electroporated CAR, NCT02623582; lentivirally-transduced, NCT03766126). Another trial is recruiting at the Children’s Hospital of Philadelphia (NCT04678336) to evaluate CD123 CAR-4.1BB-CD3z in pediatric AML. No results have been published to date. In Europe, groups in France and Germany are developing CAR-T cells targeting CD123. The German group of Cartellieri et al. developed a rapidly switchable universal CAR-T platform called UniCAR that was redirected against CD123+ leukemia cells to allow a highly controlled and dose-dependent activation of the CAR-T cells [58]. This strategy is proposed to control off-target toxicities as an alternative to needing a suicide gene. This strategy is under clinical evaluation in AML, B-ALL, and BPDCN, with CD123 positivity of more than 20% of blasts is required for study entry (NCT04230265). To date, three patients with AML have been treated and no DLTs were observed. Mild and expected adverse events have been observed (grade 1 CRS, grade 1 fever) and all patients treated have shown a clinical response (two complete remissions with incomplete hematologic recovery, one partial response) [61]. In France, Garnache-Ottou and team investigated the anti-leukemia efficacy and safety of a third generation lentiviral CD28/4-1BB CAR-T cell product targeting CD123 (CAR123), and provided strong preclinical rationale for the clinical assessment of this autologous cell therapy [57]. This CAR is currently undergoing clinical translation to meet good manufacturing practice (GMP) requirements using a closed automated system. A phase 1/2 clinical trial to validate the clinical proof of concept of CAR123 for patients with BPDCN will be the next step and is planned. 2.5. Promising New Targets 2.5.1. CD38 CD38 is a cell surface antigen that is expressed or overexpressed in several different hematologic malignancies including multiple myeloma (MM), T-cell acute lymphoblastic leukemia (T-ALL), and others including some BPDCNs. In BPDCN, CD38 is not usually included as part of the standard diagnostic workup, but of interest, several groups have demonstrated that it can be expressed in BPDCN, with perhaps 50% or more of cases being positive [62]. This finding is not only of potential diagnostic relevance, but also may be considered therapeutically important. The monoclonal antibody agent known as daratumumab is an already available, approved targeted therapy directed against CD38, currently used in patients with MM. Iverson et al. demonstrated monotherapy activity with daratumumab in a 70-year-old patient with untreated CD38+ BPDCN [63]. Another recent report by Mirgh et al. demonstrated efficacy of daratumumab in combination with bortezomib in a 75-year-old patient with BPDCN, who had extensive CD38+ disease involvement that was relapsed/refractory after standard treatments [64]. Therefore, it would be of interest for the BPDCN field to perform further studies both into expression of CD38+ in BPDCN and development of formal clinical trials for monotherapy and combination studies with daratumumab or other novel immunotherapies in CD38+ BPDCN. 2.5.2. HA-1H CARs directed at cell-surface targets associated with other more common tumor types may also be adapted for treating BPDCN. For example, the minor histocompatibility antigen HA-1 is exclusively expressed on hematopoietic cells and is presented to the immune system in the context of HLA-A*02:01 [65]. The antigenic HA-1H isoform is relatively common in the general population and TCR gene transfer can create HA-1H antigen-specific T cells, including in the setting of allogeneic stem cell transplantation [66]. Therefore, a basket CAR-T cell trial is underway for patients with multiple types of leukemias, including BPDCN, that express HLA-A*02:01 and who have persistent or relapsed disease after an allogeneic SCT from an HLA-A*02:01 or HA-1H negative donor (clinicaltrials.gov (accessed on 21 March 2022): NCT03326921). No data have been released to date. 2.5.3. CD56 As CD56 is also expressed on BPDCN blasts, and this antigen could be a target to eliminate leukemia cells. Some strategies using antibody or CAR-T cells targeting CD56 are under evaluation in other pathologies, suggesting these strategies could also be evaluated in BPDCN. For example, a new CD56-targeting monomethyl auristatin E-conjugated antibody–drug conjugate is active in preclinical models of Merkel cell carcinoma [67]. Similarly, a CD56-targeted CAR-T is active in models of small-cell lung cancer and neuroblastoma [68]. These preclinical data indicate that CD56-targeted therapies merit further investigation as a potential treatment for CD56+ hematologic malignancies such as BPDCN. However, CD56 is also expressed on NK cells and a subset of T cells. Therefore, CD56-directed therapy, particularly if long-lasting such as via anti-CD56 CAR-T cells, may need to be used as a bridge to hematopoietic stem cell transplantation, which would eliminate residual CAR-T cells and restore CD56+ lymphocytes. 2.5.4. ILT3 Immunoglobulin-like transcript 3, ILT3, encoded by the gene LILRB4, is an important cell surface regulator of dendritic cell function [69]. ILT3 is highly expressed on normal pDCs and monocytes, and similarly is expressed on most BPDCNs and monocytic (FAB subtype M4/M5) AMLs. An ILT3/LILRB4-directed CAR-T cell preclinical model was active against monocytic AML cells and was not toxic to normal progenitors derived from normal CD34+ umbilical cord blood in vitro or humanized hematopoiesis in a mouse model [70]. These data suggest that an ILT3-directed immunotherapy could also be tested in patients with BPDCN. 3. Conclusions Despite the significant increase in disease-specific research on BPDCN in recent years, patients are still in need of better treatments. The success of tagraxofusp demonstrated the potential for targeting CD123 and for the discovery and evaluation of BPDCN-specific therapies as a feasible drug-development endeavor. This strategy may be particularly effective in the long-term when there are target antigens, like CD123, that are shared with other cancers. This can expand the reach of novel agents to more patients while also directly helping those with BPDCN. Several other classes of immunotherapeutic agents that also target CD123 are in development for other hematologic malignancies, as outlined here. We hope that design of preclinical experiments and clinical trials will include BPDCN where possible, to extend the toolbox of therapies in this still orphan disease. We also propose that there are even advantages to making the initial focus of an agent’s development on an orphan disease indication, such as BPDCN, as “proof-of-concept.” This is particularly helpful if the orphan disease is relatively homogenous between patients and if the target is highly expressed and/or essential for the biology of the malignant cell. Dramatic responses only require small patient numbers to support early clinical evaluation. For these reasons, we believe that several additional targets and therapies being tested in other malignancies also hold promise for co-development in BPDCN. A thoughtful approach in this way is essential to bring novel therapies to rare diseases that would otherwise be less likely to be selected for drug development on their own. Author Contributions E.B.-R. and A.A.L. designed the study. E.B.-R., N.P., B.C., E.D. and A.A.L. wrote the manuscript, E.B.-R. drew the figure. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest N.P.: Board of Directors: Dan’s House of Hope; Consulting: AbbVie, Aptitude Health, Astellas Pharma US, Inc., Blueprint Medicines, Bristol-Myers Squibb, Celgene Corp, Cimeio Therapeutics AG, ClearView Healthcare Partners, CTI BioPharma, Dava Oncology, Immunogen, Incyte, Intellisphere, LLC., Novartis AG, Novartis Pharmaceuticals Corp, OncLive (Owned by Intellisphere, LLC), Patient Power, PharmaEssentia, Protagonist Therapeutics, Sanofi-aventis, Stemline Therapeutics, Inc., Total CME; Financial Relationship (e.g. Stock, Royalty, Gift, Employment or Business Ownership): Karger Publishers; Scientific/Advisory Committee Member: Cancer.Net, CareDx, CTI BioPharma, EUSA Pharma, Inc., Novartis Pharmaceuticals Corp, Pacylex, PharmaEssentia; Speaker/Preceptorship: AbbVie, Aplastic Anemia & MDS International Foundation, Curio Science LLC, Dava Oncology, Imedex, Magdalen Medical Publishing, Medscape, Neopharm, PeerView Institute for Medical Education, Physician Education Resource (PER), Physicians Education Resource (PER), Postgraduate Institute for Medicine, Stemline Therapeutics, Inc. A.A.L.: Consulting: Qiagen; Research Support: AbbVie, Stemline Therapeutics. Other authors have no conflicts of interest. Figure 1 Therapies that target cell surface antigens in patients with BPDCN, highlighting tagraxofusp as the only approved therapy as well as others in clinical trials or agents and targets in earlier preclinical development. cancers-14-02287-t001_Table 1 Table 1 Clinical trials using CAR-T cells targeting CD123 in patients with leukemia including BPDCN and active non-CAR-T cell BPDCN trials (extracted from clinicaltrials.gov (accessed on 21 March 2022)). CD123 CAR T-Cell Trials NCT System Safety Switch Condition/Disease Dose Phase Status NCT04318678 CD123-CAR CD28 TM-CD28-CD3z CD20 AML, B-ALL, T-ALL, BPDCN 3 × 105, 1 × 106, 3 × 106, 1 × 107 cells/kg 1 Recruiting NCT02159495 CD123-CAR IgG4 TM-CD28-CD3z EGFRt CD123+ diseases 1 Recruiting NCT04109482 CD123-CAR IgG4 TM-CD28-CD3z (MB-102) EGFRt BPDCN Up to 600 × 106 cells 1/2 Recruiting NCT02623582 CD123-CAR 41BB-CD3z (RNA electroporated) AML Early phase 1 Terminated NCT03766126 CD123-CAR 41BB-CD3z (lentiviral transduced) AML 1–5 × 106 cells/kg 1 Active, not recruiting NCT03203369 Allogenic UCART123-41BB-CD3z RQR8 BPDCN 6.25 × 105 –6.25 × 106 cells/kg 1 Terminated NCT03190278 Allogenic UCART123 v1.2 -41BB-CD3z RQR8 AML 1 Recruiting NCT04678336 CD123-CAR 41BB-CD3z Pediatric AML 2 × 106 cells/kg 1 Recruiting Other active non-CAR-T cell BPDCN trials NCT Agent(s) Condition/Disease Phase Status NCT03113643 SL-401, venetoclax, azacitidine BPDCN, AML, MDS 1 Recruiting NCT03386513 IMGN632 BPDCN 1/2 Recruiting NCT04216524 SL-401, venetoclax, Hyper-CVAD BPDCN 1 Recruiting NCT04317781 SL-401 BPDCN after stem cell transplant 2 Active, not recruiting Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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Rapidly Switchable Universal CAR-T Cells for Treatment of CD123-Positive Leukemia Mol. Ther. Oncolytics. 2020 17 408 420 10.1016/j.omto.2020.04.009 32462078 59. Cai T. Galetto R. Gouble A. Smith J. Cavazos A. Konoplev S. Lane A.A. Guzman M.L. Kantarjian H.M. Pemmaraju N. Pre-Clinical Studies of Anti-CD123 CAR-T Cells for the Treatment of Blastic Plasmacytoid Dendritic Cell Neoplasm (BPDCN) Blood 2016 128 4039 10.1182/blood.V128.22.4039.4039 60. Riberdy J.M. Zhou S. Zheng F. Kim Y.-I. Moore J. Vaidya A. Throm R.E. Sykes A. Sahr N. Bonifant C.L. The Art and Science of Selecting a CD123-Specific Chimeric Antigen Receptor for Clinical Testing Mol. Ther.—Methods Clin. Dev. 2020 18 571 581 10.1016/j.omtm.2020.06.024 32775492 61. Wermke M. Kraus S. Ehninger A. Bargou R.C. Goebeler M.-E. Middeke J.M. Kreissig C. von Bonin M. Koedam J. Pehl M. Proof of Concept for a Rapidly Switchable Universal CAR-T Platform with UniCAR-T-CD123 in Relapsed/Refractory AML Blood 2021 137 3145 3148 10.1182/blood.2020009759 33624009 62. Deotare U. Yee K.W.L. Le L.W. Porwit A. Tierens A. Musani R. Barth D. Torlakovic E. Schimmer A. Schuh A.C. Blastic Plasmacytoid Dendritic Cell Neoplasm with Leukemic Presentation: 10-Color Flow Cytometry Diagnosis and HyperCVAD Therapy Am. J. Hematol. 2016 91 283 286 10.1002/ajh.24258 26619305 63. Iversen K.F. Holdgaard P.C. Preiss B. Nyvold C.G. Plesner T. Daratumumab for Treatment of Blastic Plasmacytoid Dendritic Cell Neoplasm. A Single-Case Report Haematologica 2019 104 e432 e433 10.3324/haematol.2018.214635 30975908 64. Mirgh S. Sharma A. Folbs B. Khushoo V. Kapoor J. Tejwani N. Ahmed R. Agrawal N. Choudhary P.S. Mehta P. Daratumumab-Based Therapy after Prior Azacytidine-Venetoclax in an Octagenerian Female with BPDCN (Blastic Plasmacytoid Dendritic Cell Neoplasm)—A New Perspective Leuk. Lymphoma 2021 62 3039 3042 10.1080/10428194.2021.1941938 34151693 65. van Loenen M.M. de Boer R. Hagedoorn R.S. van Egmond E.H.M. Falkenburg J.H.F. Heemskerk M.H.M. Optimization of the HA-1-Specific T-Cell Receptor for Gene Therapy of Hematologic Malignancies Haematologica 2011 96 477 481 10.3324/haematol.2010.025916 21109688 66. van Balen P. Jedema I. van Loenen M.M. de Boer R. van Egmond H.M. Hagedoorn R.S. Hoogstaten C. Veld S.A.J. Hageman L. van Liempt P.A.G. HA-1H T-Cell Receptor Gene Transfer to Redirect Virus-Specific T Cells for Treatment of Hematological Malignancies After Allogeneic Stem Cell Transplantation: A Phase 1 Clinical Study Front. Immunol. 2020 11 1804 10.3389/fimmu.2020.01804 32973756 67. Esnault C. Leblond V. Martin C. Desgranges A. Baltus C.B. Aubrey N. Lakhrif Z. Lajoie L. Lantier L. Clémenceau B. Adcitmer®, a New CD56-Targeting Monomethyl Auristatin E-Conjugated Antibody, Is a Potential Therapeutic Approach in Merkel Cell Carcinoma Br. J. 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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/ijerph19094992 ijerph-19-04992 Editorial Introduction to the Special Issue “Emerging Trends in Combustible Tobacco and Vaping Product Use” Dunbar Michael S. 1* Tucker Joan S. 2 1 RAND Corporation, 4750 Fifth Avenue, Suite 600, Pittsburgh, PA 15213, USA 2 RAND Corporation, 1776 Main Street, Santa Monica, CA 90401, USA; jtucker@rand.org * Correspondence: mdunbar@rand.org; Tel.: +1-412-683-2300 (ext. 4219); Fax: +1-412-683-2800 20 4 2022 5 2022 19 9 499214 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/). ==== Body pmcTobacco use remains a leading cause of preventable death and disease worldwide [1]. While combustible products pose the greatest and most well-established harm, the emergence of noncombustible vaping products (e.g., electronic nicotine delivery systems (ENDS) or e-cigarettes; heat-not-burn or heated tobacco products (HTPs)) has afforded greater access to a wide array of products with varying health risk profiles [2,3,4]. Such shifts in the tobacco product landscape, in concert with evolving tobacco control efforts, are driving changes in the ways in which individuals consume nicotine and tobacco via combustible, vaping, and other products. For example, the prevalence of combustible cigarette smoking has reached historic lows in the United States (U.S.) in recent years [2]. However, smoking prevalence remains high among some segments of the population compared with others [2], and the rate of vaping product use among youths and young adults [5,6] has raised serious concerns about the potential net public health impact of vaping products. Outside of the U.S., some evidence suggests that new-generation HTPs are becoming popular among former established adult cigarette smokers [7] and, potentially, adolescents [8]. Concurrent use of different types of nicotine/tobacco products (i.e., poly-tobacco use) has also become common in some population subgroups [9]. In this dynamic context, monitoring current use trends and assessing factors associated with use of combustible and noncombustible nicotine/tobacco products is critical for gauging the potential impact of different products on global public health, and for informing ongoing efforts to reduce tobacco-related harm. This Special Issue of the International Journal of Environment Research and Public Health was developed with these factors in mind, with the goal of including a range of articles that address various facets relevant to characterizing the “emerging trends” in combustible and noncombustible nicotine/tobacco use. This Special Issue includes a diverse set of ten open access articles that focus broadly on patterns and correlates of combustible tobacco and noncombustible nicotine/tobacco product use. In this editorial letter, we discuss some of the key contributions of these studies—which employ different methods and focus on different countries, populations of interest, products, and research questions—to advance our understanding of emerging trends in product use. Multiple studies present data on poly-tobacco use (e.g., ENDS + cigarettes; ENDS + HTPs; ENDS + cigarettes + other tobacco products) and the associated factors in adults [10,11,12]. For example, Mattingly et al. [12] leverage data from two nationally representative U.S. surveys to describe longitudinal trends in single-product and poly-product use among U.S. adults between 2014 and 2019. Findings from this study indicate increases in exclusive use of ENDS over time and decreases in poly-product use involving combustible cigarettes. Many articles in this Special Issue also point to group differences in product use patterns by tobacco use history and sociodemographic factors, such as age, sex/gender identity, sexual orientation, and race/ethnicity (e.g., [10,11,12,13,14,15,16,17]). Such findings underscore the importance of ongoing efforts to assess differences in use patterns, while product and policy contexts continue to evolve to understand and address potential health disparities across population subgroups. Product use and/or future susceptibility among young people is of particular importance, and several studies focus specifically on youth and young adults. For example, Gaiha et al. [13] report on factors associated with future ENDS or e-cigarette product use susceptibility among a sample of U.S. adolescents and young adults. In this study, the authors identified differences in future intentions to use different types of e-cigarette devices (e.g., pod/cartridge-based products, disposable, refillable mod/tank) across sexual orientation/gender identity and racial/ethnic groups. In a longitudinal study of adolescents in the Netherlands, Hiemstra et al. [14] report on associations between personality characteristics and future use of combustible cigarettes and “alternative tobacco products” (e.g., e-cigarettes, waterpipes). In this study, factors such as hopelessness and sensation-seeking behavior were associated with future onset of both e-cigarette and combustible cigarette use, with slightly different patterns observed for other tobacco products (e.g., hookah or waterpipe). Additionally, Vogel et al. [15] report on nicotine/tobacco use history and other factors associated with perceptions and future willingness to use modern oral nicotine products in a sample of U.S. young adults. In this study, willingness to use these products was significantly higher among individuals who endorsed other nicotine/tobacco use (e.g., e-cigarettes, combustible cigarettes) and nearly half of survey respondents (49%) reported uncertainty as to whether oral nicotine pouches were less harmful than combustible cigarettes. Such findings underscore the importance of ongoing surveillance of poly-product use while the range of products continues to expand, as well as the need to communicate accurate information about relative product harms to the public. Other studies describe patterns and correlates of nicotine/tobacco product use in specific policy environments and/or settings. For example, a study from Mistry et al. [16] reports on perceived changes in tobacco use during the COVID-19 pandemic among older adults in Rohingya refugee camps. In this article, the authors underscore the importance of surveillance activities and tobacco-control efforts to mitigate tobacco-related harm for at-risk groups during periods of crisis. In a separate study, Koyama et al. [11] present information on use of e-cigarettes, combustible cigarettes, and HTPs in a sample of individuals who report e-cigarette use in Japan, where e-cigarettes containing nicotine e-liquid have been prohibited for over a decade. The authors of this study show that, in this sample of over 4000 survey respondents, a majority (62%) reported the use of nicotine e-liquid and nearly half of the sample (49%) reported concurrent use of e-cigarettes with combustible cigarettes and/or HTPs. This illustrates the importance of—and notable challenges associated with—characterizing use patterns, product characteristics (e.g., nicotine content), and associated factors under more restrictive policy conditions. Given the importance of marketing and promotional practices for nicotine/tobacco product uptake and continued use, two studies in this Special Issue examine these areas in more detail. A study by Miller et al. [17] used nationally representative survey data from the U.S.-based National Survey on Drug Use and Health to assess changes in cigarette brand market share between 2014 and 2019. Findings from this study suggest that menthol may have contributed to growth in market share over time for several top brands, which is particularly notable in the context of pending action on menthol cigarettes from the U.S. Food and Drug Administration. The authors also highlight a substantial increase in market share during the study’s time period for some top brands that utilized “natural” descriptor language in their advertising. In a qualitative study that leveraged data from the social media platform TikTok, Morales et al. [18] describe user-generated promotional content and the emerging online culture related to the disposable e-cigarette brand Puff Bar. Findings from this study highlight the potential role of social media platforms in driving product use trends, particularly among younger people who are disproportionately represented on some platforms, and the utility of social media data in staying on top of emerging product use trends. Some studies also report novel data on understudied nicotine/tobacco use behaviors and device modification practices. For example, Heckman et al. [10] describe a series of pilot investigations examining cigarette relighting—that is, the practice of partially smoking, extinguishing, and subsequently relighting a cigarette. Findings from this pilot work suggest that this understudied behavior may be common among those who smoke cigarettes, particularly individuals with lower socioeconomic status, and suggest a need for more research on this phenomenon. In a qualitative study, Massey et al. [19] report on motivations for modifying ENDS devices based on focus groups with adults who use ENDS in the U.S. and highlight a number of reasons for device modifications, such as perceived satisfaction and enjoyment, controlling nicotine intake, and the use of cannabis products with ENDS. The authors emphasize the importance of shifts in device characteristics over time and point to a potential need for regulatory decision makers to consider such factors in developing and enforcing product standards to protect public health. As nicotine/tobacco markets, products, and policies continue to change throughout the world, ongoing research is critical for informing decisions to further reduce the global burden of tobacco use. The articles included in this Special Issue highlight some of the research questions and methods that are important for monitoring and understanding emerging trends in use of different nicotine/tobacco products across population subgroups. Such diverse efforts are essential for ensuring that the state of science stays in pace with these real-world shifts—to the greatest possible extent—and that current and future research priorities and policy actions across the world are informed by the available evidence. Acknowledgments The authors would like to thank William Shadel for feedback on an early version of this article. Author Contributions M.S.D. and J.S.T. shared an equal contribution. All authors have read and agreed to the published version of the manuscript. 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. World Health Organization Tobacco-Fact Sheet 2021 Available online: https://www.who.int/health-topics/tobacco (accessed on 18 March 2022) 2. Cornelius M.E. Loretan C.G. Wang T.W. Jamal A. Homa D.M. Tobacco Product Use Among Adults—United States, 2020 Morb. Mortal. Wkly. Rep. 2022 77 397 405 10.15585/mmwr.mm7111a1 35298455 3. The National Academies of Sciences Engineering and Medicine Public Health Consequences of E-Cigarettes The National Academies of Sciences Engineering and Medicine Washington, DC, USA 2018 4. U.S. Department of Health and Human Services The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health Centers for Disease Control and Prevention Washington, DC, USA 2014 5. Gentzke A.S. Wang T.W. Cornelius M. Park-Lee E. Ren C. Sawdey M.D. Cullen K.A. Loretan C. Jamal A. Homa D.M. Tobacco Product Use and Associated Factors Among Middle and High School Students—National Youth Tobacco Survey, United States, 2021 MMWR Surveill. Summ. 2022 71 1 29 10.15585/mmwr.ss7105a1 35271557 6. Schulenberg J.E. Johnston L.D. O’Malley P.M. Bachman J.G. Miech R.A. Patrick M.E. Monitoring the Future National Survey Results on Drug Use, 1975–2019: Volume II, College Students and Adults Ages 19–60 Institute for Social Research, The University of Michigan Ann Arbor, MI, USA 2020 7. Sutanto E. Miller C. Smith D.M. O’Connor R.J. Quah A.C.K. Cummings K.M. Xu S. Fong G.T. Hyland A. Ouimet J. Prevalence, Use Behaviors, and Preferences among Users of Heated Tobacco Products: Findings from the 2018 ITC Japan Survey Int. J. Environ. Res. Public Health 2019 16 4630 10.3390/ijerph16234630 31766410 8. Kang S.Y. Lee S. Cho H.-J. Prevalence and predictors of heated tobacco product use and its relationship with attempts to quit cigarette smoking among Korean adolescents Tob. Control 2021 30 192 198 10.1136/tobaccocontrol-2019-055114 32108085 9. Chen D.T.-H. Girvalaki C. Mechili E.A. Millett C. Filippidis F.T. Global Patterns and Prevalence of Dual and Poly-Tobacco Use: A Systematic Review Nicotine Tob. Res. 2021 23 1816 1820 10.1093/ntr/ntab084 34009377 10. Heckman C. Wackowski O. Mukherjee R. Hatsukami D. Stepanov I. Delnevo C. Steinberg M. Cigarette Relighting: A Series of Pilot Studies Investigating a Common Yet Understudied Smoking Behavior Int. J. Environ. Res. Public Health 2021 18 6494 10.3390/ijerph18126494 34208528 11. Koyama S. Tabuchi T. Miyashiro I. E-Cigarettes Use Behaviors in Japan: An Online Survey Int. J. Environ. Res. Public Health 2022 19 892 10.3390/ijerph19020892 35055714 12. Mattingly D.T. Zavala-Arciniega L. Hirschtick J.L. Meza R. Levy D.T. Fleischer N.L. Trends in Exclusive, Dual and Polytobacco Use among U.S. Adults, 2014–2019: Results from Two Nationally Representative Surveys Int. J. Environ. Res. Public Health 2021 18 13092 10.3390/ijerph182413092 34948704 13. Gaiha S.M. Rao P. Halpern-Felsher B. Sociodemographic Factors Associated with Adolescents’ and Young Adults’ Susceptibility, Use, and Intended Future Use of Different E-Cigarette Devices Int. J. Environ. Res. Public Health 2022 19 1941 10.3390/ijerph19041941 35206132 14. Hiemstra M. Rozema A. Jansen M. van Oers H. Mathijssen J. Longitudinal Associations of Substance Use Risk Profiles with the Use of Alternative Tobacco Products and Conventional Smoking among Adolescents Int. J. Environ. Res. Public Health 2021 18 13248 10.3390/ijerph182413248 34948856 15. Vogel E.A. Barrington-Trimis J.L. Kechter A. Tackett A.P. Liu F. Sussman S. Lerman C. Unger J.B. Halbert C.H. Chaffee B.W. Differences in Young Adults’ Perceptions of and Willingness to Use Nicotine Pouches by Tobacco Use Status Int. J. Environ. Res. Public Health 2022 19 2685 10.3390/ijerph19052685 35270385 16. Mistry S.K. Ali A.M. Yadav U.N. Huda N. Ghimire S. Rahman A. Reza S. Huque R. Rahman M.A. Perceived Change in Tobacco Use and Its Associated Factors among Older Adults Residing in Rohingya Refugee Camps during the COVID-19 Pandemic in Bangladesh Int. J. Environ. Res. Public Health 2021 18 12349 10.3390/ijerph182312349 34886073 17. Lo E.J.M. Young W.J. Ganz O. Talbot E.M. O’Connor R.J. Delnevo C.D. Trends in Overall and Menthol Market Shares of Leading Cigarette Brands in the USA: 2014–2019 Int. J. Environ. Res. Public Health 2022 19 2270 35206458 18. Morales M. Fahrion A. Watkins S.L. #NicotineAddictionCheck: Puff Bar Culture, Addiction Apathy, and Promotion of E-Cigarettes on TikTok Int. J. Environ. Res. Public Health 2022 19 1820 35162846 19. Massey Z.B. Fairman R.T. Churchill V. Ashley D.L. Popova L. “It’s Cool, Modifying and All, but I Don’t Want Anything Blowing Up on Me:” A Focus Group Study of Motivations to Modify Electronic Nicotine Delivery Systems (ENDS) Int. J. Environ. Res. Public Health 2021 18 11735 10.3390/ijerph182211735 34831491

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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/ijerph19095774 ijerph-19-05774 Perspective Implementation of Mental Health Centres Pilots in Poland since 2018: A Chance to Move towards Community-Based Mental Health Services https://orcid.org/0000-0002-9304-8286 Sagan Anna 12* https://orcid.org/0000-0003-3728-2323 Kowalska-Bobko Iwona 3 https://orcid.org/0000-0002-7323-6626 Biechowska Daria 4 Rogala Maciej 3 Gałązka-Sobotka Małgorzata 5 Tchounwou Paul B. Academic Editor 1 European Observatory on Health Systems and Policies, London School of Economics and Political Science, London WC1H 9SH, UK 2 European Observatory on Health Systems and Policies, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK 3 Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, 31-066 Kraków, Poland; iw.kowalska@uj.edu.pl (I.K.-B.); maciej.rogala@uj.edu.pl (M.R.) 4 Department of Public Health, Institute of Psychiatry and Neurology, 02-957 Warszawa, Poland; dbiechowska@ipin.edu.pl 5 Institute of Healthcare Management, Faculty of Economics and Management, Lazarski University, 02-662 Warszawa, Poland; m.galazka-sobotka@lazarski.edu.pl * Correspondence: a.sagan@lse.ac.uk 09 5 2022 5 2022 19 9 577430 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/). Provision of mental health care in Poland has long been characterised by an overreliance on psychiatric hospitals and the underdevelopment of community care. The introduction of the first National Mental Health Protection Programme for 2011–2015, with the explicit goal to base provision of mental care on the community mental health centres, failed to achieve any tangible results. The ensuing critique led to the launch of the second National Mental Health Protection Programme for 2017–2022 and the establishment, from mid-2018 onwards, of 41 (33 in operation) mental health centres across Poland. These will be piloted until the end of 2022 but have already shown positive results in terms of access to non-stationary care and a small fall in hospitalisations. They have also performed well during the COVID-19 pandemic, allowing for a quick reorganization of care and continued provision of mental health services. Some of the key innovations of the new model include the introduction of recovery assistants (a new profession) and mental health coordinators (a new role); liaison with social assistance services; and a shift to budget financing. The key obstacles to the national rollout of mental health centres are the low financing of mental health care in Poland, which is among the lowest in Europe, and acute workforce shortages. mental health healthcare coordination integrated care Poland This research received no external funding. ==== Body pmc1. Introduction About 12% of the population in the WHO European Region suffers from mental disorders at any given time [1]. Inclusion of substance use disorders increases this share to 15%, while the inclusion of neurological disorders such as dementia raises it to 50%. According to the WHO, by 2030, depression will be the greatest contributor to the global burden of disease [2]. While there are no systematic epidemiological studies of mental disorders in the general population in Poland [3], a representative survey conducted in 2012 found that about 23% of the Polish population aged 18–64 suffered from mental disorders [4]. Of these, the most common were alcohol abuse (11.90%), specific phobias (4.3%) and depression (3.0%). The number of patients diagnosed with these disorders and receiving treatment increased steadily between 2014 and 2016 [3]. Death by suicide, which is one of the leading symptoms of mental health problems, remains much higher in Polish men (21 per 100,000 in 2018) compared to the EU average (17 per 100,000 in 2016) [5]. Mental and behavioural disorders account for the largest share (over 17%) of the benefits paid out by the Social Insurance Institution to persons with short- and long-term incapacity to work [6]. In much of Europe, mental health had long been one of the most neglected areas of public health, with systemic, organisational, legal, and social barriers contributing to the exclusion of people with mental health problems [7]. The need to develop community-based mental health care as an alternative to institutional care in mental health asylums has been widely recognized (e.g., [7,8]). Over the past two decades, many countries in Europe have managed to significantly reduce the number of psychiatric hospital beds, with the largest reductions observed in Cyprus and Ireland (over 70%), followed by Italy, Malta, Netherlands, Finland, Iceland, Norway, and the United Kingdom (over 40%) [9]. In comparison, the number of psychiatric hospital beds in Poland fell by only about 10% in this period. The purpose of this perspective piece was to describe the introduction of a pilot of coordinated mental health care in mental health centres as a primary means for achieving a shift from asylum-based to community-based mental health provision in Poland. Section 2 describes the policy background, including earlier efforts to improve provision of mental health services. Section 3 summarises the content of the new policy and its early results. Finally, Section 4 offers conclusions and policy recommendations. 2. Policy Background The first National Mental Health Protection Programme introduced in Poland was adopted in 2010 and was in place between 2011–2015 [10]. The goal of this programme, in line with the developments in other countries in Europe, was to shift provision of mental care from hospitals to the community by introducing a network of mental health centres as the core element of mental health service provision. These were first to be piloted at a smaller scale and the Minister of Health was charged with working out details of the pilot and ensuring its financing and implementation. The National Health Fund (NHF), the sole payer in the public health care system, was mandated with developing an appropriate financing model for the centres. Unfortunately, the Ministry did not fulfil its tasks and did not establish the principles for creating and financing the centres, precluding other actors, including the NHF, from implementing theirs. The inaction on the part of the Ministry was ascribed to the lack of financial resources to implement the programme but also to the lack of agreement among the key stakeholders about the details of the pilots and the overall model of psychiatric care that should be pursued in Poland [11]. Given the problems mentioned above, the assessment of the programme conducted by the National Audit Office in 2016 was unsurprisingly scathing [11]. According to the report, the number of fatal suicide attempts—one of the key indicators available for monitoring the implementation of the programme—increased by over 60% between 2011 and 2015. Financing of mental care services remains extremely low, with psychiatric care and addiction treatment accounting for just over 3% of the NHF’s expenditure [12], which is among the lowest shares in Europe [13]. About 70% of these funds are allocated to residential care, mostly to dedicated psychiatric hospitals, where 11,000 or two-thirds of psychiatric beds are located (only 5450 beds are in general hospitals) [14], and which may contribute to social stigmatisation of psychiatric patients [15]. Only about 30% of public funds are allocated to non-residential care. Further, the majority of service providers (about two-thirds) are contracted to provide only one form of care (i.e., either outpatient, community, day, or emergency (hospital) care), which combined with poor cooperation among the various providers means that most patients do not have access to comprehensive and coordinated psychiatric care [16]. Many patients diagnosed with mental health disorders thus turn to primary health care (PHC) to seek help (about 875,000 out of 1.5 million patients in 2019) and many do not receive specialist care [17]. Although the number of psychiatric wards decreased slightly (by 4%) between 2010 and 2016 and the number of community care units increased, the percentage of patients with mental disorders using these community forms of treatment remained small—only 1.9% of patients used community mental care and 1.6% used day mental care [18]. Access to community care remains highly unequal, with only a third of the counties having a community (home) treatment team and a similar share having a day ward [13,16]. For example, in 2018, over 95% if patients with schizophrenia were treated in hospital settings and only 5% had access to a comprehensive care in both hospitals and other settings, including day and community care [19]. Analysis of treatment pathways between 2010 and 2016 further revealed that emergency wards were most often used by those patients who were also treated at outpatient mental health clinics and hospitalised in 24 h care wards. This may be a further indicator that the availability of outpatient services is not sufficient, and that the emergency wards were used to access needed care [18]. At the same time, better access to day care seems to prevent round-the-clock hospitalisation and visits to emergency wards. The lowest rates of hospitalisations in general psychiatric departments could be found in the counties in which all forms of mental health care were available [18]. It was not until after the scathing report by the National Audit Office was published [11] that the Minister of Health appointed (in April 2016) a dedicated team of experts charged with designing the details of the pilot of community mental health centres. In March 2017, the second National Mental Health Protection Programme for 2017–2022 [20] was introduced offering a new chance to accelerate transformation of mental health service provision. The programme defined a set of actions aimed at providing people with mental disorders with comprehensive, multifaceted, and universally accessible health and other care and support services to enable them to function in their familial and social environments—as before, this was to be achieved by implementing a network of mental health centres, with the structure of the centres remaining similar to the one proposed in the previous programme and in line with the general approach to organising community mental health services in Europe [21]. These goals were supported in the consecutive editions of the National Health Programme—for 2016–2020 [22] and for 2021–2025 [23]—which is one of the key strategic planning documents in public health in Poland. 3. Policy Content and Early Results The piloting of mental health centres started in July 2018 [24]. The centres are meant to provide adult populations living in their catchment areas with tailored and comprehensive psychiatric assistance close to their place of residence. All centres should provide the following types of services: active long-term treatment and support for people with chronic mental health disorders; short-term assistance for people with episodic or recurrent disorders; ad hoc assistance for people with urgent problems; as well as consultations for other people requiring diagnostic services or advice [20]. Their catchment areas should cover between 50,000 and 200,000—and ideally 100,000–120,000—adult inhabitants and may comprise an area of a larger county or several smaller counties, a smaller city, or a district of a larger city, depending on the population density. The centres receive lump-sum financing (a form of global budgets), allowing them flexibility in spending and to tailor provision of services to local needs. The financing is calculated as a product of the number of inhabitants and a capitation rate, which is the same for all centres and is indexed annually to account for changes in prices. In terms of their organizational structure, the centres should comprise at least the following units (Figure 1): an outpatient unit or clinic providing medical and psychological advice, individual and group psychotherapeutic assistance, nursing services, and social interventions; a mobile community unit providing home visits, individual and group (incl. family) therapy, skills training, rehabilitation services, and general assistance to patients in building a social support network; a day unit providing day psychiatric hospitalisation to support provision of diagnostic, therapeutic or rehabilitation interventions; and a hospital unit, ideally located within a local general hospital rather than a specialist psychiatric hospital, providing round-the-clock hospital care for patients suffering from or at risk of severe disorders [20]. The centres may also sign agreements with providers of addiction treatment services. Depending on local needs, the centres may comprise additional specialized teams catering to the needs of selected groups of patients (e.g., psychogeriatric teams) or provide special services and other support mechanisms, such as crisis assistance, crisis housing, etc. To ensure ease of access, all these forms of assistance should be accessible within a single institution—the local mental health centre—and located within the designated catchment areas. Each centre should have a registration and coordination point (approx. one point per 80,000 inhabitants) and be accessible for at least 10 h a day (8:00 a.m.–6:00 p.m.), Monday to Friday, that ensures quick (referral-free) access to a wide range of services and support from trained staff, including community therapists, psychiatric nurses, and psychologists. A new healthcare profession—recovery assistant—has been introduced through the pilots, emulating similar solutions implemented in countries such as Germany, Switzerland, Great Britain, Sweden, Norway, and the Netherlands [25]. Recovery assistants are people who have experienced a mental problem themselves, and after appropriate training, provide peer support to people who are currently experiencing such problems. They work with therapeutic teams, providing a link between people seeking medical help and medical staff. A new role—mental care coordinator (case manager)—has also been introduced. Care coordinators are appointed by the head of the mental health centre from those among non-medical staff who have completed community therapy training. They ensure that a treatment and recovery plan is in place and is implemented and support patients and their relatives not only in the treatment process, but also in other areas, e.g., pertaining to their social life. So far, the education of existing health care professionals has not been adapted in line with the shift towards community mental care but the inclusion of a compulsory internship in community care in psychiatric specialist training is being considered. Mental health centres should also cooperate with PHC, such as with primary care doctors consulting with the centres, as needed, to manage mild cases or for referring patients to the centres. The centres can also consult PHC doctors on specific cases [26]. They should also cooperate closely with the entities providing social support, social and professional activation, and other social assistance services. These close links with PHC and social services are meant to improve access to the centres and reduce stigmatisation of people with mental health problems [27]. The centres meet regularly (once a month) to exchange their experiences and learn from each other. Figure 1 Organization of the mental health centre model of community mental care. Source: authors based on [28]. At the end of 2021, there were 41 mental health centres across the 16 regions of Poland, out of which 33 were in operation, covering 3.8 million people or 12% of the adult (18+) population (Figure 2) [29]. This reflects slow progress given that the reform assumed that 250–300 centres would be created by the end of 2027. This can be partly explained by the rigid inclusion criteria, precluding some of the interested entities from participation. Further, not all elements of the new model have been implemented. For example, in about half of the centres, lump-sum financing accounted for less than 50% of contracts, and care coordination and recovery plans were also only partially implemented [13]. At the end of 2020, the Ministry of Health and the Piloting Office of the National Mental Health Protection Programme published an assessment of the pilot in 27 centres between 2018 and 2019 [13]. The report compared two types of centres: in 17 centres, lump-sum financing constituted over 50% of the value of the contracts (or the total value of the contracts was less than PLN 10 million)—these centres usually operated out of psychiatric wards of general hospitals (Group 1); in the remaining 10 centres, lump-sum financing accounted for less than 50% of the contracts and they typically operated out of psychiatric hospitals (Group 2). The control group comprised all adult populations not covered by the pilot. Despite its slow and partial implementation, positive effects of the pilot have been determined, particularly in the centres belonging to Group 1 (see Table 1). Between 2018 and 2019, access to mental health services in counties participating in the pilot improved while differences in access between these counties became smaller. For example, the difference between the number of treated patients between the countries with the highest and lowest numbers of treated patients per 100,000 inhabitants decreased by 10.5% and the difference in the number of patients receiving ambulatory and community care between the counties with the highest and lowest rates of access to such care decreased by 11.2%, while at the same, the average and median values for these two indicators increased across the participating countries [13]. Improved access to care could be linked to the increased spending in the centres which rose by 125% per patient between 2018 and 2019 [31]. The centres are also thought to have contributed to reducing access barriers and improving coordination of care. This was ascribed to provision of services in the registration and coordination points and the introduction of care coordination mechanisms, such as the new role of care coordinator, but care coordination and quality have not been comprehensively studied. Further, there were essentially no queues and almost no complaints to the Patient Rights Ombudsman at the centres compared to the control group [13]. In contrast, access to psychologists and psychotherapists outside of the pilots is only available upon a referral (although psychiatrists can be seen without a referral) and waiting times for consultations can be long—about 50 days on average according to 2019 data [32]. In terms of differences between different centres, centres in Group 1 noted an increase in the shares of their populations receiving mental health care: there was a significant increase in the provision of non-stationary care, with the number of outpatient and community services increasing by almost 7%; the number of psychological counselling and therapy services by 26%; and the number of inhabitants covered by community care by 27%. At the same time, hospitalisations have fallen slightly by just over 3% in the centres in Group 1. Centres in Group 2 have seen much smaller improvements, often smaller than in the control group. This has been attributed to the ‘institutional culture’ dominating in large psychiatric facilities where Group 2 centres are located; a smaller share of lump-sum financing compared to Group 1; as well as the lack of organisational and financial separation of the centres from the structures of the hospital and, related to that, the weak position of the centres’ managers, among other factors [13]. The new model also seems to have performed well during the COVID-19 pandemic [28,33]. While many psychiatric treatment wards were closed in the initial stages of the pandemic, mental health centres—thanks to their organisational and financial flexibility—managed to quickly adapt their operations and switch to remote provision. 4. Discussion Early results of mental health centre pilots appear to be promising and they have been perceived positively by the regional medical consultants [16]. More information, including on care coordination and quality of care as mentioned above and on health outcomes, are needed to provide a more comprehensive assessment of the new model and inform any adaptations. What is worrying is that many centres that have been created so far operate out of psychiatric hospitals with strong ‘institutional culture’. Progress towards community care may be slower in such centres and their location may not be conducive to reducing the social stigmatisation of mental health patients. The report of the Piloting Office recommended to extend the pilot to other entities, such as those participating in the EU-funded project “Deinstitutionalization of services provided to people with mental disorders and diseases” [28]. This project, in operation since 2015, comprises many entities that do not provide hospital services, including private entities and other non-governmental organisations, and has also been assessed positively in terms of improving access to mental health services in the community [34,35]. Inclusion of these entities in the pilot can offer potential for learning and for transfer of best practices to the centres and can help reinforce shifting mental care to the community. From 2022, entities without their own psychiatric ward have been permitted to apply for inclusion in the pilot—this should also help move mental care to the community and increase take up of the new model across Poland [36]. Based on the new applications from early 2022, the number of centres included in the pilot is expected to increase to about 80 in the first half of the year, reaching about 30% of the adult population [37]. Yet, there are many threats that can undermine the national rollout of the pilot. The key problem is the extremely limited public financing of mental health services. While the EU funds may provide the needed financial means to support the deinstitutionalisation of mental care, the level of national public financing is likely too low to ensure adequate provision in the long term. However, increasing public spending in this area may be difficult to achieve given other competing priorities and the relatively low interest of both central and local public authorities in addressing mental health problems (although this may also be explained by the limited local budgets) [16]. Ambivalent attitudes towards the reform are particularly notable in regions that are homes to large psychiatric hospitals. Acute shortages of health workers constitute another major threat. In 2019, there were 10.2 psychiatrists per 100,000 inhabitants in Poland—much lower than the number recommended by the National Consultant in Psychiatrics (20 per 100,000; [17]), which is in line with the EU/EEA average [38]. However, mental health centres’ more flexible organisational structures which allow them to employ other mental care professionals other than psychiatrists may to some extent help mitigate the problem of staff shortages. Initial plans assumed that the piloting phase would last three years, but due to the outbreak of the COVID-19 pandemic, this was extended until the end of 2022. In mid-2021, when the pilot was originally meant to end, the team of experts charged with the implementation of the pilot of community mental health centres also ceased to work and their operation was not extended. Instead, the Ministry of Health established a new team charged with the continuation of the reform and development of a new Mental Health Strategy for 2022–2027. Some health analysts have been concerned by the fact than none of the original experts were involved, especially since the results of the pilot have been generally perceived as promising. At the same time, the key strategic documents in the health sector, the National Transformation Plan for 2022–2026 published in late 2021 [39] and the framework document “Healthy future. Strategic framework for the development of the health care system for the years 2021–2027, with a perspective until 2030” [14] along with the Transformation Plan, postulate the development of community mental health care, including investments in human resources and infrastructure, and explicitly foresee further development of mental health centres over 2022–2027. While it remains unclear whether any additional entities will be included in the pilot in 2022, these strategic postulates seem to bode well for its national rollout when it comes to an end at the end of 2022. 5. Conclusions Mental health centres offer a breakthrough in achieving a shift to community-based mental care in Poland. They provide local populations with an easily accessible entry point to comprehensive and coordinated mental and related services close to their place of residence and without a referral. The pilot covers 12% of the adult population and its early results have been promising: it has led to improved access to non-stationary care as well as a small fall in hospitalisations. However, its further implementation may be undermined by the acute health workforce shortages and low financing of mental health services in Poland and there is some uncertainty about the future direction of the reform. Given the increasing burden of mental health problems, intensified by the COVID-19 pandemic, it is now a good time to push for more investment and improving mental health services. Author Contributions Conceptualization, A.S., I.K.-B. and M.G.-S.; formal analysis, A.S., I.K.-B., M.G.-S., M.R. and D.B.; resources, A.S., M.R. and D.B.; writing—original draft preparation, A.S., I.K.-B. and M.G.-S.; revisions, A.S. and D.B.; visualisation, A.S.; supervision, M.G.-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 The authors declare no conflict of interest. Figure 2 Number and location of mental health centres at the end of December 2021. Source: authors based on [30]. Notes: grey areas = regions; blue areas = catchment areas of mental health centres (this could be an area of one or more counties, or of a municipality or a smaller city, depending on the population density). The numbers represent the number of mental health centres in each region. ijerph-19-05774-t001_Table 1 Table 1 Changes in access to mental health services within and outside of the pilot, % age change between 2018 and 2019. Group 1 (Hospital Wards); 1.45 Million People Group 2 (Psychiatric Hospitals); 1.43 Million People Control Group; 28.56 Million People Outpatient and community care (number of consultations, sessions, and visits per 100,000 inhabitants) +6.7% (11.6% *) +0.0% (+0.1% *) +2% (+2.0% *) Psychological counselling and psychotherapy * (number of consultations, psychotherapy sessions, group sessions, community therapist visits per 100,000 inhabitants) +25.6% +8.8% +9.9% Number of patients receiving community care per 100,000 inhabitants +26.9% −0.5% +4.6% Hospitalisations (number of bed-days per 100,000 inhabitants) −3.3% −1.8% −0.5% * Including services in the registration and coordination points. Source: authors based on [13]. 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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/ijerph19094959 ijerph-19-04959 Review Health Statistics in Australia: What We Know and Do Not Know Madden Richard 1* https://orcid.org/0000-0003-1489-5709 Fortune Nicola 23 https://orcid.org/0000-0002-3136-5323 Gordon Julie 4 Gulis Gabriel Academic Editor Tchounwou Paul B. Academic Editor 1 Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia 2 Centre for Disability Research and Policy, University of Sydney, Sydney, NSW 2006, Australia; nicola.fortune@sydney.edu.au 3 Centre of Research Excellence in Disability and Health, University of Melbourne, Carlton, VIC 3053, Australia 4 WHO Collaborating Centre for Strengthening Rehabilitation Capacity in Health Systems, University of Sydney, Sydney, NSW 2006, Australia; julie.gordon@sydney.edu.au * Correspondence: richard.madden@sydney.edu.au 19 4 2022 5 2022 19 9 495914 12 2021 02 2 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/). Australia is a federation of six states and two territories (the States). These eight governmental entities share responsibility for health and health services with the Australian Government. Mortality statistics, including causes of death, have been collected since the late 19th century, with national data produced by the (now) Australian Bureau of Statistics (ABS) from 1907. Each State introduced hospital in-patient statistics, assisted by State offices of the ABS. Beginning in the 1970s, the ABS conducts regular health surveys, including specific collections on Aboriginal and Torres Strait Islander peoples. Overall, Australia now has a comprehensive array of health statistics, published regularly without political or commercial interference. Privacy and confidentiality are guaranteed by legislation. Data linkage has grown and become widespread. However, there are gaps, as papers in this issue demonstrate. Most notably, data on primary care patients and encounters reveal stark gaps. This paper accompanies a range of papers from expert authors across the health statistics spectrum in Australia. It is hoped that the collection of papers will inform interested readers and stand as a comprehensive review of the strengths and weaknesses of Australian health statistics in the early 2020s. health statistics Australian health system health surveys Indigenous data linkage ==== Body pmc1. Introduction Australia is a federation of six states and two self-governing territories (the Australian Capital Territory and the Northern Territory), referred to in this paper for simplicity as ‘the States’. These eight governmental entities share responsibility for health and health services with the Australian (Commonwealth) Government. Many health services are provided by governments, with the private sector also delivering services, notably in primary care, dentistry, private hospitals, and pharmacy. Health constitutes some 10% of the Australian economy [1] (p. 173). Australia introduced a system of universal health insurance (now known as Medicare) in the 1970s and 1980s. This covered privately provided medical services and shared the funding of public hospitals between the Australian and State governments [2]. As a result, there was a need to know much more about the services that the Australian health system delivered across its many arms. The decades that followed have seen great progress in building a national health information infrastructure to inform health policy, resource allocation, and delivery of health care across the nation. That work continues. This paper is a commentary that aims to briefly describe the main components of Australia’s health statistics system, highlight its breadth, successes, and novel features, point out some limitations, and indicate directions for future development. It provides a succinct overview of the current state of health statistics in Australia, set within a historical context, to inform future work to improve and build on Australia’s health information infrastructure, and to demonstrate the crucial role of health statistics in running an effective and responsive health system. In preparing this commentary, we have drawn upon a broad range of reports, technical documents, and other resources available on the websites of Australia’s two main national statistics agencies (the Australian Bureau of Statistics and the Australian Institute of Health and Welfare) and the Australian Department of Health. The paper accompanies, and is informed by, a range of papers from expert authors across the health statistics spectrum in Australia. It is hoped that the collection of papers will inform interested readers and stand as a comprehensive review of the strengths and weaknesses of Australian health statistics in the early 2020s. 2. Australia’s Statistical Agencies Health statistics in Australia come, in large part, from two official statistics agencies—the Australian Bureau of Statistics and the Australian Institute of Health and Welfare. Both agencies are apolitical and explicitly serve all sectors of the community. Their values accord with the UN Fundamental Principles of Official Statistics [3], which state, as Principle 1, ‘Official statistics provide an indispensable element in the information system of a democratic society, serving the Government, the economy and the public with data about the economic, demographic, social and environmental situation’. Principle 1 goes on to emphasise the need for impartiality and that statistics should be of ‘practical utility’. The (now) Australian Bureau of Statistics (ABS) dates from 1905, as the national statistics agency. It conducts a population census every five years, processes and publishes vital statistics, and conducts a range of social surveys, including in health. In 1987, the (now) Australian Institute of Health and Welfare (AIHW) was established to focus on health and community services statistics, especially using administrative data provided by the States. The AIHW works in conjunction with the ABS. Both agencies operate under national legislation which strictly protects the confidentiality and privacy of individual data [4,5]. The AIHW is required to report to Parliament on the state of Australia’s health and health services every two years, in a publication called Australia’s Health, beginning in 1988, with the most recent in 2020 [1]. 3. Development of Health Statistics This paper gives a brief description of various categories of health statistics in Australia, beginning with an outline of developments from the beginning of the 20th century. Sources of health statistics include patient and administrative data, surveys, and clinical registries. Mortality statistics, including causes of death, have been collected since the late 19th century, with national data produced by the ABS from 1907. Each State established a hospital in-patient data collection by the 1970s. Data on each patient episode was provided by the hospital to the State central collection. On its establishment, the first task for the AIHW was to produce national hospital in-patient statistics. This was a vital need as, under Medicare, funding of hospitals was now shared by the Commonwealth and States. To pursue its charter, to bring together State health data into national collections, the AIHW led the development of the National Health Information Agreement in 1992. Under this agreement, all States agreed to establish national minimum datasets for key services, including hospital in-patients, and provide annual data to the AIHW for collation and publication. National minimum dataset specifications were developed, data standards were published in the National Health Data Dictionary (available in electronic form from July 1997) and, in the early 2000s, AIHW established a national online metadata registry for health, housing, and community services statistics and information (METeOR) [6]. National Health Information Plans were developed in 1995 and 2002 [7,8], to identify agreed priorities for national developments in health statistics. Development of a new National Health Information Strategy began in 2019 [9] but was not completed before national health governance arrangements changed in the light of the COVID-19 pandemic. This paper refers to the priorities of the 2002 plan, many of which remain just as relevant today. Australia follows international standards for data collection and analysis where these exist, notably for causes of death (World Health Organization (WHO)) [10] and health expenditure (Organisation for Economic Co-operation and Development (OECD)) [11]. The AIHW is the Australian Collaborating Centre for the WHO’s Family of International Classifications, the focus for Australian work on the development and maintenance of health classifications. Australia’s health statistics are financed through a variety of arrangements, including national direct funding of AIHW and ABS, contract funding by Australian Government departments, and State health department funding for administrative data and some special-purpose collections. 4. Health Surveys The ABS conducted its first National Health Survey in 1977–1978, and these surveys have been repeated at regular intervals. In 2011, a National Nutrition and Physical Activity Survey and a National Health Measures Survey were added, providing biomedical information, in addition to self-reported information on health conditions such as cardiovascular disease, diabetes, kidney function, and risk factors. The first of now regular National Aboriginal and Torres Strait Islander Health Surveys was conducted in 2004 [12]. Some health data are also collected in National Aboriginal and Torres Strait Islander Social Surveys [13]. In addition to these national health surveys, the AIHW has conducted a regular National Drug Strategy Household Survey, beginning in 1985, gathering information on the use of alcohol, tobacco, and illicit drugs [14]. The ABS conducted a National Survey of Mental Health and Wellbeing in 2007, giving a one-off view of the characteristics of people with mental health conditions (employment, housing, etc.) [15]. In 2019–2020, the ABS conducted a Patient Experiences Survey, covering health service use and experiences with health providers, as part of its annual Multipurpose Household Survey [16]. 5. Health Statistics for Aboriginal and Torres Strait Islander Peopless Australia has generally high health status, but notably, Aboriginal and Torres Strait Islander (Indigenous) people experience disadvantages, compared with other Australians, across a range of health outcomes [17]. Up to 1988, statistics on the health of Australia’s Aboriginal and Torres Strait Islander people were almost non-existent. Australia became a nation in 1901. Its Constitution specified that ‘Aboriginal natives’ were not to be included in population estimates. This now-shocking provision ensured that there was little effort on statistics for the Indigenous population. Population estimates were conducted administratively, almost certainly underestimating the actual Indigenous population [18]. The exclusion provision was removed from the Constitution in 1967, and data about Indigenous status have been available since the 1971 Census, with Indigenous identification steadily improving over time [18]. In 1988, the first edition of AIHW’s biennial report, Australia’s Health, brought together an array of data to demonstrate the poor health status of Indigenous Australians. The release of the first National Aboriginal and Torres Strait Islander Survey by the ABS in 1994 [19] marked a considerable step forward by producing a wide range of information on Indigenous people. The survey captured data on positive aspects of Indigenous life and culture, such as connection to land, as well as highlighting the systemic and inter-generational problems Indigenous people live with, including historical separation of children from families. From 1996 on, the AIHW and ABS have worked in collaboration with Indigenous people to improve information on Indigenous health. A highlight was the release in 1997 of the first edition of The Health and Welfare of Australia’s Aboriginal and Torres Strait Islander Peoples, published jointly by the two agencies and launched by the Australian Governor-General [20]. The development of Indigenous health statistics was the number one priority of the 2002 National Health Information Plan [8]. The development of Indigenous health statistics in Australia and many challenging issues are described by Ring and Griffiths [21] in this issue. The continuing, nationally acknowledged but persistent ‘gap’ between the health of Indigenous people and that of other Australians is highlighted each year in national ‘Closing the Gap’ reports [22]. Indigenous health statistics will remain a priority for development and a focus for lively debate into the future. Indigenous people are increasingly leading the development of new Indigenous controlled data and pushing the national statistical agencies to redouble their efforts. 6. Mortality Each Australian state requires registration of deaths that occur in that state, using a standard death certificate that is aligned with international requirements set by the World Health Organization. Data on causes of death have been recorded in line with the International Classification of Diseases (ICD) since 1907, with over 100 years of causes of death available for analysis. In 2006, the AIHW published Mortality over the twentieth century in Australia [23]. This publication showed the path of key diseases over the 20th century. For example, the female death rate for cancer did not vary much over the century, at 150 deaths per 100,000 population, although the composition changed, with lung cancer rising sharply, while cancers of the stomach, cervix, and uterus fell. The male cancer death rate increased from 166 deaths per 100,000 population in 1907 to 287 in 1985 and then fell to 247 by the year 2000, with lung cancer being the major varying cause of death. The male death rate for circulatory diseases increased from 437 deaths per 100,000 population in 1907 to 1020 in 1968, before falling to 319 in 2000. Cause-of-death coding for Australia is centralised at the ABS in Brisbane (using internationally developed automated software), facilitating the development of specialist skills. For the past 15 years, the ABS has worked closely with State registrars and the National Coronial Information System (NCIS), which collates causes of death for all deaths referred to coroners across Australia and New Zealand. One particular result of this collaboration is much more complete data on deaths by suicide. The ABS now revises causes of death where updated information becomes available from coronial investigations which can take several years, and deaths can be coded as suicides based on the information in the NCIS. The paper by Eynstone-Hinkins and Moran [24] in this issue provides up-to-date information on Australian mortality statistics, including COVID-19 deaths. 7. Hospital Treatment As already described, a national collection of hospital in-patient data was the first task of the AIHW on its establishment in 1987. A national minimum dataset was introduced in 1990. Annual data have been published since 1993–1994, and the reporting has become progressively more timely. The collection covers patients in public and private hospitals [25]. Statistics on emergency department presentations are also produced, including principal diagnosis and triage category, as well as demographic characteristics of patients. Non-inpatient data remain limited to administrative characteristics, with no information yet available on reasons for encounter, diagnoses, or interventions. Hospital in-patient data have formed the information base for many important health policy developments at national and state levels, including in relation to casemix funding for hospitals, potentially preventable hospitalisation, and quality and safety developments in hospitals. Additionally, equity issues around hospital access and variations in intervention patterns can be explored. 7.1. Casemix Funding Casemix funding was developed at a national level from the 1980s and was first introduced in Victoria in 1993. Casemix is now referred to in Australia as activity-based funding. Australia adopted the casemix models originally developed in the United States [26]. Casemix is a measure of hospital output for each patient, based on their diagnoses and interventions provided. The Australian casemix system for acute in-patients (Australian Refined Diagnosis Related Groups) is based on hospital in-patient statistics and a hospital costing survey. The classifications used are an Australian modification of ICD-10 for diagnoses (ICD-10-AM) and the Australian Classification of Health Interventions (ACHI). Supplementary systems exist for sub-acute patients such as rehabilitation and palliative care. The Australian activity-based funding system, including its supporting classifications, is not in the public domain. Several countries have licences from the Australian Government to use the system in their countries. 7.2. Potentially Preventable Hospitalisation Potentially preventable hospitalisation is an indicator of the effectiveness of primary care. There is a range of vaccine-preventable, acute, and chronic conditions for which policymakers believe hospitalisation could be prevented by earlier community-based care, particularly significant diagnoses of interest include complications of diabetes and chronic obstructive pulmonary syndrome (COPD) [1] (Section 5). This is an example where statistics from one sector of the health system can be used as a performance indicator for another sector. 7.3. Quality and Safety Selected diagnoses relating to ‘hospital-acquired complications’ are used as indicators of quality and safety issues in Australian hospitals [27]. There are 16 complications, including pressure injuries, health-care-associated infections, and respiratory complications. Hospital funding arrangements now include an adjustment for hospital-acquired complications, taking into account the non-preventable occurrences of these conditions. Regrettably, there is duplication of hospital in-patient data collections. The Independent Hospitals Pricing Authority collects data from the States for its activity-based funding (casemix) functions. The Australian Department of Health collects clinical, demographic, and financial information for privately insured in-patients from private health insurers, and, through the Australian Private Hospital Data Bureau, also collects data from private hospitals covering patient demographics, clinical information, and hospital charges. The AIHW’s collection covers most of the data items collected in these collections, apart from information on charges to private patients. 8. Primary Health Care In contrast to information on hospital in-patients, primary health care statistics have had a chequered history and are a significant weak point in Australian health statistics. Primary health care practitioners, including general practitioners (GPs), nurses, allied health professionals, pharmacists, dentists, and Aboriginal and Torres Strait Islander health workers, provide services in a range of community settings and are critical first points of contact with the health system. In 1998, a national sample-based data collection of general practice encounters (BEACH) was put in place by the University of Sydney and the AIHW, with wide-ranging support from general practitioners’ professional representative groups and in partnership with a number of pharmaceutical companies. This unique partnership offered a publicly accessible dataset and provided information to participating pharmaceutical companies on their products’ uses. The paper by Gordon et al. [28] in this issue outlines the development and uses of this data collection. The Australian Government terminated funding for the BEACH collection in 2016 at short notice and without an alternative data collection in place. Currently, general practice statistical data are limited to extracts from GPs’ electronic records, which come from multiple systems without any common data architecture or standards [29]. The samples drawn are not always structured to enable the production of statistics about all elements of the population, especially those with significant health disadvantages, such as Indigenous Australians. The AIHW is leading the development of a National Primary Health Care Data Asset [30] of which statistics about general practice are one component. 9. Public Health In 1999, a National Public Health Information Plan was published, which focused on the need for improving national health surveys. As a result, information on a range of risk factors has been expanded and systematised over the past 20 years—smoking, alcohol use, exercise, and diet are examples. The Australia’s Health series reports on a range of population health indicators, as well as information on national screening programs. Between 2010 and 2013, Australia had a specialist agency focusing on preventive health. It produced a national report, State of Preventive Health 2013 [31], which has not been repeated. This report brought together the national data on major risk factors, as well as international comparisons. The National Notifiable Diseases Surveillance System brings together reports on notifiable diseases across Australia. Fortnightly reports are produced. Notifications in respect of Indigenous people made up more than half of the 330,000 notifications in 2016, the latest report available [32]. COVID-19 has seen separate and timely reporting of data on infection cases, hospitalisations, and deaths. It remains to be seen whether this results in the quality and timeliness of notifiable diseases information being improved and strengthened. 10. Mental Health The paper in this issue by Rosenberg et al. [33] describes the development of mental health statistics since the 1990s. This development occurred outside the processes established under the National Health Information Agreement, even though the Australian Government and State health agencies were cooperating through their mental health experts. A separate governance arrangement was established through the Mental Health Information Strategy Sub-Committee. The AIHW publishes an annual review of mental health services and associated resources in Australia [34,35]. Data are drawn from across AIHW data collections and other sources, including the 2007 ABS National Survey of Mental Health and Wellbeing. 11. Medicines: Use and Outcomes Comprehensive data on medicines provided to Australians in the community are available from the national Pharmaceutical Benefits Scheme (PBS), established in 1948. Medicines below the cost threshold for the PBS and those provided to public hospital in-patients are not included in the PBS. The use of these data for pharmaco-epidemiological purposes is described by Pearson et al. [36] in this issue. Increasingly, medicines data are linked to other national datasets (see Section 15, Data Linkage, below). The authors note that studies in Australia are relatively few and do not utilise all of the datasets available; they explore possible paths to facilitate a leap forward in medicine outcome studies. 12. Data on Health and Health Disadvantage for Particular Population Groups There have been several references already in this paper to health statistics concerning Indigenous Australians. There are other population groups whose health status and access to health services also need to be monitored, as they experience significant disadvantages in relation to health. People with disability are one such group. Statistics on people with disability and disability support services have been greatly improved over the past 20 years, although the introduction of the National Disability Insurance Scheme, itself a major social reform, has led to a break in the series of nationally consistent data on disability services, which was collected through the Disability Services National Minimum Dataset from 1991 to 2019 [37]. However, information on the health of people with disability and their access to health services has generally come from health and disability surveys, rather than from health services statistics. The paper by Fortune et al. [38] in this issue discusses this in more detail. Medicare, Australia’s universal health insurance system, gives all Australians the capacity to access high-quality medical and hospital services. The reality is that there is a clear excess burden of disease for lower socio-economic groups, notably in coronary heart disease, lung cancer, chronic kidney disease, and COPD [39]. In addition to survey evidence, data linkage is facilitating the examination of socio-economic variables in relation to health. For example, the ABS now links mortality data and census records, which has allowed examination of mortality due to various health conditions according to household equivalised income, highest educational attainment, and housing tenure [40]. Australia has about a quarter of its population born overseas, and almost half have at least one parent born overseas [41] (p. 271). Many health data collections include country of birth and language spoken at home. However, the AIHW has acknowledged that information on culturally and linguistically diverse (CALD) populations is among Australia’s data gaps [1] (p. 6). Australia’s Health 2020 omitted data on CALD populations altogether. The 2018 edition briefly discussed the generally lower age-standardised mortality rates and rates of potentially preventable hospitalisations for people born outside Australia, compared with the Australian-born population. These data gaps have been thoroughly addressed in a recent report by the Federation of Ethnic Communities Councils of Australia (FECCA) [42]. In Australia, prisons and corrective services are the responsibility of the States. Without Australian Government involvement, it took many years for a national effort to report on the health of prisoners, which is the responsibility of State health departments or State correctional services agencies. Since 2009, the AIHW has conducted the National Prisoner Health Data Collection every 3 years. Data reported highlight significant mental health problems, high rates of smoking and drug use, and a high prevalence of disability among prisoners [43]. 13. Health Registries Each Australian State has operated a cancer registry for many years. The AIHW maintains the National Cancer Statistics Clearing House (NCSCH), which was established in 1986 as the national repository of cancer incidence and mortality statistics. The repository is used to produce national cancer statistics. Each jurisdiction uses the national minimum dataset for its reporting. In addition, the jurisdictions collaborate with the AIHW to produce registries for breast, cervical, and bowel cancer screening. There is now a wide range of clinical registries in Australia. These include clinical quality, disease, immunisation, and product registries. A Framework for clinical quality registries has been developed by the Australian Commission on Safety and Quality in Health Care [44]. 14. Oral Health Dental statistics have been well developed in Australia through a specialist centre at the University of Adelaide, which has worked in collaboration with AIHW. Foundation work in South Australia was built to give a rich picture of child and adult dental health, as well as the dental health of Aboriginal and Torres Strait Islander peoples. The paper in this issue by Amarasena et al. [45] describes a recent national oral health survey and the changes in dental health over the past 30 years. 15. Data Linkage Data linkage has been mentioned earlier in this paper. Data linkage involves the development of enriched datasets by linking two or more datasets. Data linkage in Australia commenced in Western Australia in the 1990s and now occurs in all State jurisdictions, and is supported by the Public Health Research Network (see Smith et al. in this issue) [46]. Ethical approval is essential for data linkage because linked data can readily produce identifiable data even if the original datasets are de-identified. The AIHW, as described by Jensen [47] has developed the National Integrated Health Services Information Analysis Asset (NIHSIAA) linking a range of its datasets and other Australian Government datasets, thus bringing together data covering hospitals, Medicare, Pharmaceutical Benefits Scheme, Repatriation Pharmaceutical Benefits Scheme, residential aged care, and the National Death Index. 16. Financing Australia has produced estimates of national health expenditure since 1980, following the OECD’s guidelines. The paper by Goss [48] in this issue discusses this work and presents a fascinating dissection of the growth in Australia’s health expenditure this century. 17. Workforce From its commencement in 1987, the AIHW collated health workforce data from state registration authorities, with a focus on the medical and nursing workforce. At registration (then administered at the state level), individual practitioners were asked to provide demographic and employment information about themselves. The resulting statistics formed a valuable basis for workforce planning, highlighting urban/rural disparities in the medical workforce and the ageing of the nursing workforce. In 2010, national health workforce registration was introduced through the National Registration and Accreditation Scheme, and responsibility for statistical reports remained with AIHW. In 2016, responsibility for workforce statistics was passed to the Australian Department of Health [44]. The AIHW produced comprehensive reports on the health and community services workforces after the 1996, 2001, and 2006 population censuses [49]. 18. Discussion The Australian health system encompasses a mix of Australian Government and State Government responsibilities and is a combination of public and private services. This complexity makes a national health statistics system essential if the Australian health sector is to be understood, accountable, responsive, and improved. Since the 1980s, this system has been established, developed, and maintained. All jurisdictions and sectors have contributed to this effort. The 1992 National Health Information Agreement (NHIA) provided a critical framework for the development of national datasets, ensuring common data standards have been adopted in these datasets. The contrast with health sectors that have stayed outside the NHIA arrangements is stark. Australia now has a comprehensive array of health statistics, published regularly without political or commercial interference. Privacy and confidentiality are guaranteed by legislation. However, there are gaps, as some papers in this issue illustrate; most notable are data on primary care patients and encounters, with no current reliable information on the reason for encounter, consultation outcome, and other aspects of primary health care. Similar gaps exist for patients treated by medical specialists outside hospitals, and for patients of allied health practitioners. Additionally, some datasets (such as health workforce) exist in silos, separate from the national statistical agencies where users would expect to find information readily accessible. The utility of national health statistical collections is dependent on the development and widespread use of national minimum datasets, which ensure the supply of comparable data from different sectors (such as public and private hospitals) and jurisdictions. The more recent emergence of ‘big data’ sets and analysis provides new opportunities, as long as good statistical practices are followed [50] and high ethical and privacy standards are adhered to. The papers in this issue highlight that health statistics must respond to health policy needs and developments, and to emerging health issues. Casemix funding for hospitals energised the development and supply of hospital statistics and now relies on them. COVID-19 has led to more timely incidence and mortality statistics and focused attention on the calculation of excess mortality in a pandemic [35]. Work on the postponed National Health Information Strategy should be resumed so that clear priorities for health statistics developments are identified and committed to by all stakeholders. National consultation had occurred prior to the deferral of the development in 2020, which naturally gave rise to wide-ranging demands for improved data and analysis. It is important that the strategy focuses on a few key areas with clear short- and medium-term priorities. These include the following aspects:Primary health care: Broad-ranging work on a National Primary Health Care Data Asset has been underway for some years by the AIHW. This appears to have an ambitious scope and needs to be seen as a project of long-term development. Immediate steps are needed to fill the gap left by the termination of the BEACH collection, with a robust, statistically reliable, and nationally representative collection. The limitations of generating statistics based on data extraction from GP electronic records must be acknowledged and addressed, as well as methods developed to overcome these. Disability: The development of a National Disability Data Asset is advancing, and significant funding was allocated by the Australian Government in late 2021. This development is broadly focused and relies mainly on the identification of people with disability through disability-specific services and payments. The ability to identify people with disability consistently within health service data systems is necessary for monitoring equity of access and outcomes. Creating a succinct question or short set of questions that can function as a disability ‘identifier’ for use in administrative data collections is a key priority. Mental health: Developments in this sector have occurred outside the mainstream structures under the National Health Information Agreement, so statistics in this crucial health sector remain separate from other health statistics. Data linkage provides a strong platform today to bring together data on services provided in the various sectors: primary health care, community care, and hospitals. The National Health Information Strategy development needs to prioritise mental health statistics and integrate them with other health statistics streams. Hospital in-patient statistics: The duplication of collections described above should be removed, with the national collection for public and private hospitals managed by the AIHW, which should prepare a common dataset for all other national agencies. While some additional data items would need to be added to the AIHW collection, one collection would replace four. 19. Conclusions Australia has a robust and reliable set of health statistics. This is the result of many decades of national governance cooperation, resourcing, and effort. The ongoing commitment of resources and collaboration among stakeholders continues to be essential to ensure a robust evidence base to inform policy and practice, based on nationally consistent data standards, and to underpin research efforts, into the future. Some specific potential improvements have been highlighted, and the full potential of data linkage has yet to be achieved. People provide information about themselves and their health in many settings and are often unaware that this information provides input to health statistics which, in turn, improves health and health services [47]. Respecting individuals’ data remains at the heart of the health statistics effort, and using it as well as possible is a key responsibility for the statistical community. Author Contributions Conceptualization, R.M., N.F. and J.G.; investigation, R.M., N.F., J.G.; writing—review and editing, R.M., N.F., J.G. 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. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095028 ijms-23-05028 Review When the Locus Coeruleus Speaks Up in Sleep: Recent Insights, Emerging Perspectives https://orcid.org/0000-0003-4341-4206 Osorio-Forero Alejandro https://orcid.org/0000-0002-7627-4601 Cherrad Najma https://orcid.org/0000-0001-8333-9672 Banterle Lila https://orcid.org/0000-0002-7942-3369 Fernandez Laura M. J. https://orcid.org/0000-0002-4954-4143 Lüthi Anita * Lazarus Michael Academic Editor Yi-Qun Wang Academic Editor Department of Fundamental Neurosciences, University of Lausanne, CH-1005 Lausanne, Switzerland; alejandro.osorioforero@unil.ch (A.O.-F.); najma.cherrad@unil.ch (N.C.); lila.banterle@unil.ch (L.B.); laura.fernandez@unil.ch (L.M.J.F.) * Correspondence: anita.luthi@unil.ch 30 4 2022 5 2022 23 9 502828 2 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/). For decades, numerous seminal studies have built our understanding of the locus coeruleus (LC), the vertebrate brain’s principal noradrenergic system. Containing a numerically small but broadly efferent cell population, the LC provides brain-wide noradrenergic modulation that optimizes network function in the context of attentive and flexible interaction with the sensory environment. This review turns attention to the LC’s roles during sleep. We show that these roles go beyond down-scaled versions of the ones in wakefulness. Novel dynamic assessments of noradrenaline signaling and LC activity uncover a rich diversity of activity patterns that establish the LC as an integral portion of sleep regulation and function. The LC could be involved in beneficial functions for the sleeping brain, and even minute alterations in its functionality may prove quintessential in sleep disorders. NREM sleep REM sleep monoamine noradrenaline arousability sleep architecture infraslow time scale microvasculature sleep disorder Alzheimer’s disease LifeSciences PhD Fellowship310030-184759 This article was funded by SNF grant number 310030-184759 to AL and Etat de Vaud. AOF was supported by a LifeSciences PhD Fellowship from the University of Lausanne. ==== Body pmc1. Introduction Noradrenaline (NA) is a monoamine neurotransmitter that acts in the brain and body to induce and coordinate states of wakefulness, and to facilitate adaptive behaviors in response to environmental novelty. The mammalian brainstem contains a cluster of up to seven NA-synthetizing nuclei (A1–A7) that have been anatomically identified in >80 mammals [1], from rat [2], to cat [3], to human [4]. The tightly appositioned A4 and A6 nuclei stand out as the largest, often densest, and predominant forebrain-projecting nuclei that share a common embryonic origin [5] and in which activity levels correlate with the degree of wakefulness (for review, see [6,7,8,9]). In tissue sections, these nuclei appear sky-blue because of their pigmentation with neuromelanin, a by-product of catecholamine metabolism, which gave it the name locus coeruleus (LC, Latin for “sky-blue spot”). The LC lies in the pontine brainstem as an anteroposteriorly extended tube with a central ventral extension along the fourth ventricle (for review, see [1,8]) and it is part of the ascending arousal systems, together with other monoaminergic and cholinergic nuclei (for review, see [10,11]). The LC provides brain-wide axonal arborizations and fine meshworks of varicose fibers that arise from a comparatively small number of NA-synthetizing neurons (thousands in rodents [12,13], tens of thousands in humans [14]). The axons from LC cells span the neuraxis from the spinal cord to the cerebellum, midbrain, thalamus, and cortex and are thought to release NA through both synaptic and non-synaptic release mechanisms (for review, see [15,16]) to regulate neurons, glial cells, and fine microvessels (for review, see [17,18,19]), stimulating wakefulness and attentional orienting (for review, see [8]), sensory processing (for review, see [20]), muscle tone (for review, see [21]), and breathing (for review, see [22]), while inhibiting sleep-promoting brain areas (for review, see [10,23]). The LC also plays prominent roles in pathological forms of arousals, commonly linked to acute stress (for review, see [24]), post-traumatic stress disorder (for review, see [25]), pain and analgesia [26], motivation and relapse (for review, see [27]), hypercapnia (for review, see [28]), and hypotension (for review, see [29]), many of which are accompanied by sleep disturbances. Novel anatomical and physiological technologies, together with advanced behavioral measures, are about to bring fundamentally renewed insights into the LC’s functions. The LC shows a genetic and/or functional heterogeneity at multiple levels from its embryonic and evolutionary origins (for review, see [1,5]), its synaptic interactions with the pericoerulear area (for review, see [30]), its input–output connectivity (for review, see [31]), to its cellular identities and neurotransmitter release (for review, see [6,30]), neuronal ensemble formation (for review, see [32]), regulation of whole-brain states [33], brain-state-dependent firing patterns (for review, see [7,30]), and behavioral roles (for review, see [34]). The LC emerges as a dynamic and plastic assembly of functionally specialized LC neuronal subgroups that act locally or globally according to recently lived experiences, ongoing demands, and future challenges (for review, see [30,35]). Time is also ready to complement the prevalent LC-wakefulness association with the appreciation that the LC is important for sleep. The central message of this review is that LC’s role in sleep has remained underestimated. Novel real-time monitoring and interferential approaches now start to indicate that LC contributes to sleep in fundamental ways—to its cellular functions, its micro- and macroarchitectural organization and regulation, associated behaviors, and possible roles in disease. These insights are at their very beginnings, yet they indicate that the LC could become an important factor in profiles of perturbed sleep that arise from diverse conditions. In this review, we discuss these exciting developments primarily based on animal experimentation, but we include human studies whenever they help complement available evidence. For a more human sleep-oriented recent review on the LC’s role in sleep, we refer to Van Egroo et al. [36]. 2. The Activity of the LC in Sleep: Pioneering Studies This chapter reviews studies from the last decades that provided evidence for a maintained activity of the LC in sleep. Quantitatively, these studies revealed that the LC unit activity was clearly lower compared to wakefulness, yet remained distinctly elevated during non-rapid-eye-movement (NREM) sleep compared to REM sleep. NREM and REM sleep are the two major mammalian sleep states, also referred to as “quiescent” and “active” sleep, respectively. These two states show distinct spectral characteristics and functions for sleep (for review, see [37]). Qualitatively, the studies summarized in this chapter suggest that the noradrenergic system appeared to be involved in the alternation of NREM and REM sleep. For these results, diverse techniques in animals and humans were used that span from electrophysiology and pharmacology to microdialysis and functional imaging. A summary of the traditional view that has emerged from these studies is shown in Figure 1 (left). 2.1. Animal Studies Rat [38,39], cat [40,41,42], and monkey [38,43] recordings showed that the action potential discharge rates of LC units during NREM and REM sleep were minor compared to wakefulness. Unit activity was low during NREM sleep, but remained detectable, while it ceased during REM sleep [38,39]. However, researchers also noted that not all putative LC units reduced activity during NREM and/or REM sleep [40,41]. LC activity was also low in quiet—as opposed to active—wakefulness [39,42]. More recent studies indicate that some LC units may even be as active in NREM sleep as in quiet wakefulness and occasionally fire in bursts [44,45,46]. Furthermore, although activity during sleep states was overall low, it nevertheless was not random. For example, LC unit activity has been related to the organization [39] and termination [46] of sleep spindles, an essential NREM sleep rhythm in the 10–15 Hz frequency range originating from the thalamo-cortical loop [47]. Additionally, LC unit activity during NREM sleep preceded the cortical up-state periods from another important NREM sleep-associated slow rhythm, the cortical slow oscillation (~1 Hz) [45], and was increased during a post-learning NREM-sleep period [44]. Microdialysis allows sampling of mean concentrations of neurochemicals present in the extracellular fluid surrounding neural tissue. Microdialysis for NA revealed its levels to be lower for states of sleep compared to wakefulness across rodents, cats, and seals, yet values for NREM sleep consistently were intermediate with respect to the ones for wakefulness and REM sleep in various brain areas (for review, see [48]). This suggested that even low LC unit activity leads to detectable NA release. However, no or minor increases in cortical NA levels in response to electrical or chemical stimulation of the LC were observed at low (1–3 Hz) compared to higher (>5 Hz) stimulation frequencies [49,50,51]. The fast-scan cyclic electrochemical voltammetry technique allows millisecond-resolution assessments of NA levels with nanomolar sensitivity, but it has so far been mostly applied for high-frequency stimulation of the LC [52]. Therefore, the relation between LC unit activity and real-time NA output has remained undefined. Jouvet’s monoaminergic theory of sleep–wake control [53] prompted examinations of the spontaneous sleep–wake cycle after lesion or pharmacological manipulation of LC and NA signaling, or after constitutive removal of genes encoding proteins involved in NA turnover. These approaches made it clear that noradrenergic activity sustains wakefulness at the expense of sleep (for review, see [7,8,9,23]). At the same time, they provided the first hints that NA signaling remained relevant for sleep. For example, neurotoxic lesions of noradrenergic LC neurons or genetic elimination of the NA-synthetizing enzyme dopamine-β-hydroxylase (DBH) altered the relative times spent in NREM and REM sleep [54,55,56]. These approaches lacked the necessary specificity in time and in the site of action to conclude about the LC’s role in regulating the timing of NREM and REM sleep. Furthermore, noradrenergic receptors are expressed both centrally and peripherally, and LC projections target both sympathetic and parasympathetic autonomic pathways (for review, see [29]). Therefore, systemic drug administration may affect sleep–wake states by acting on the autonomic nervous system. Nevertheless, these studies are part of initial evidence that monoaminergic systems, including NA, could remain active in sleep. Particularly noteworthy are the effects of pharmacological α2-adrenergic receptor activation. These receptors are Gi-protein-coupled receptors activated by NA in the central nervous system and periphery. In the brain, they act as both presynaptic negative autoreceptors within the LC and in sleep–wake regulatory centers to suppress NA release and attenuate postsynaptic excitability [57] (for review, see [58]). These receptors are also the target of powerful sedatives used in clinics, such as dexmedetomidine (for review see [58]). The α2 agonist clonidine suppresses the activity of the LC [59,60] but also targets pre- and postsynaptic receptors in sleep-regulatory areas (for review, see [23]). α2 agonists such as clonidine or detomidine, when applied locally in cat pontine brainstem [61] or peri-coerulear areas [62], or systemically in rat [63], suppressed REM sleep while increasing the depth of NREM sleep. The use of clonidine in humans was also found to attenuate REM sleep (see Section 2.2). These effects on sleep macroarchitecture are in line with an active LC during sleep. 2.2. Human Studies The functional activity within dorsal brainstem areas, including the LC, was examined through functional magnetic resonance imaging (MRI) in sleeping healthy individuals [64]. This imaging technique uses magnetic resonance signals to detect changes in brain activity based on increases in the flow of oxygenated over non-oxygenated blood. Signal increases involving the LC were particularly prominent during NREM sleep-associated slow (<1 Hz) waves. More recently, advances in high-resolution neuroimaging techniques allow for a refined investigation of the human LC, which has raised much attention regarding its role in sleep (for review, see [36,65]). Neuromelanin’s paramagnetic properties make MRI-based anatomical measures of the LC possible to determine its location and structural integrity. Positron emission tomography can provide estimates of noradrenergic terminal density. First studies have correlated structural and functional read-outs of the LC to human sleep, finding associations between these and microarchitectural alterations in sleep [66] that are relevant in the context of neurodegenerative disorders (see Section 5.1) (for review, see [36]). Similar to animal models, pharmacological studies in humans using α2-receptor-specific agonists provide evidence for the role of noradrenergic signaling in the timing of NREM and REM sleep. The α2 agonists clonidine or guanfacine produced a reduction of REM sleep [67] and an increase of NREM sleep [68] while the α2 antagonist idazoxan increased the time spent in wake but also reduced the time in REM sleep [68]. Furthermore, clonidine decreased peripheral NA levels during sleep [69], consistent with a suppression of an active LC during sleep. Administration of the NA reuptake inhibitors reboxetine, maprotiline, or nomifensine, for which there is evidence that they elevate peripheral levels of NA, also suppressed REM sleep [69,70]. These studies indicate that noradrenergic signaling, in part through α2 receptor activation, is a pathway for sleep control. How this signaling modulates both local LC networks and their synaptic targets to both NREM and REM sleep control centers remained open for further study. 3. The Activity of the LC in Sleep: Novel Insights The development of genetically encoded sensors for free NA now makes it possible to measure its real-time dynamics with high spatial and temporal resolution [71]. It enables a direct estimation of the relative NA levels released during the natural sleep–wake cycle and how they relate to traditional LC activity measures. These sensors are G-protein-coupled-receptor-activation-based (GRAB) and are constructed from mutated α2 adrenoceptors coupled to an EGFP moiety. When expressed in vivo through viral vectors, these GRAB sensors become localized on membrane surfaces and emit green fluorescence (∼520 nm) upon blue light excitation (∼510 nm) once NA released from LC fiber binds. High (GRABNE1h) and medium (GRABNE1m) affinity versions of these sensors have been presented, and renewed versions keep being developed, expanding the range of sensitivity and kinetics with which measures can be taken (see http://www.yulonglilab.org/faq.html, accessed on 1 February 2022). Furthermore, a mutant version of the sensor that is not responsive to NA should be used to control for potential non-specific alterations of the fluorescence signal that can limit its interpretation. For example, local alterations in neuronal environments, such as in brain temperature or blood pressure accompany transitions between NREM and REM sleep. These could alter light scattering or biosensor properties in vivo. Two studies in mouse, one published [72], one yet to be peer-reviewed [73], have now used these GRABNE sensors to describe the real-time dynamics of free NA levels in the medial prefrontal cortex [73] and in the primary sensory thalamus [72] during the natural sleep–wake cycle. These studies report unexpectedly high levels of NA during NREM sleep compared to wakefulness. Furthermore, they observe a dynamically varying signal during states of sleep. This chapter presents the most important findings derived from these two studies. A summary of the resulting revised view on NA signaling in sleep is shown in Figure 1 (right). 3.1. Mean NA Levels Differ across the Sleep–Wake Cycle The signals provided by the genetic sensor showed characteristic alterations across wakefulness, NREM sleep, and REM sleep. In the prefrontal cortex, mean NA levels during wakefulness were high but variable [73], which is consistent with the large variations in LC activity in wakefulness (see Section 2.1). During NREM sleep, the mean free NA levels became lower but still overlapped with the ones of wakefulness. During REM sleep, the levels of NA were consistently low. In the sensory thalamus, similar measures of NA even revealed that mean levels were significantly higher during NREM sleep when compared specifically to quiet wakefulness (Figure 2) [72]. Again, values were low during REM sleep in this area. These findings provide the first evidence that NA levels remain more elevated in NREM sleep in forebrain areas than what was expected based on unit measures (see Section 2.1). The expected low NA levels during REM sleep appear as a common feature across the recorded areas. The considerable discrepancy between the numerically sparse LC unit activity (see Section 2.1) and high free NA levels generated during NREM sleep shows that much remains to be learned about the mode of operation of LC neuronal ensembles in different states of vigilance. 3.2. NA Levels and LC Activity Fluctuate during NREM Sleep The next notable observation found in both the thalamus and prefrontal cortex is that NA levels were not steady during NREM sleep (Figure 2A–C). Instead, these fluctuated on an infraslow timescale of tens of seconds, with an average cycle length of 30–50 s [72,73]. These fluctuations in NA levels were linked to phasic bouts of LC neuronal activity over the same intervals, as evident by correlated Ca2+ transients in LC somata [73]. This activity pattern points to a periodic synchronization of LC population activity on an infraslow time scale during NREM sleep [74]. The role of these recently identified fluctuations is a current topic of investigation [72,75,76] (for review, see [77]). Optogenetic modulation of noradrenergic LC neuronal activity evoked variations in the appearance of sleep rhythms and heart rate, suggesting that infraslow NA fluctuations are relevant for NREM sleep’s physiological correlates. Thus, NA released by the LC lead to a periodic clustering of sleep spindles, such that they appeared at high density when NA levels were low and they were scarce when these levels were high (Figure 2A) [72,73]. Mechanistically, sleep spindle clustering relied on the α1- and β-adrenergic receptor-mediated modulation of membrane potentials in the thalamic circuits, in which sleep spindles are generated [72]. Sleep spindles are involved in the sleeping brain’s elaboration of sensory input (for review, see [78]), which implies the LC in NREM sleep-related sensory processing (see Section 4.1). NA fluctuations also correlated with infraslow variations in heart rate during NREM sleep (Figure 2A). The LC thus acts bidirectionally to coordinate forebrain sleep spindle rhythms with heart rate variations. Indeed, optogenetic activation of LC noradrenergic neurons disrupted the heart rate variations during NREM sleep and their anticorrelation with the spindle clustering [72,76]. Mechanistically, the coupling of LC activity to the heart rate depended on parasympathetic signaling. Likewise, parasympathetic signaling also underlies coordinated infraslow fluctuations between pupil diameter and sigma power during NREM sleep [79]. 3.3. NA Levels Decay to Low Levels during REM Sleep The NA levels declined in both the prefrontal cortex [73] and the thalamus [72] during REM sleep, in line with the quiescence of LC units in this behavioral state (Figure 2B). As a result, NA levels reached a level that lay below that of wakefulness and NREM sleep. This result directly and strikingly supports the proposition that REM sleep periods are relatively NA-free (see Section 5.2). The quantification of the extent and time course of this decline will now allow us to refine this proposition, in particular in terms of the relation to REM sleep bout duration. 3.4. NA Levels Show Characteristic Dynamics at Behavioral State Transitions The dynamics of NA levels at moments of transition from NREMS to REMS or wakefulness showed characteristic properties. At NREM-to-REM transitions, a decrease in NA levels began ∼40 s before the onset of REM sleep (Figure 2B). This time period recalls a transitional moment of sleep that has been referred to as “intermediate sleep” in rodents [80], cats [81] and humans [82,83]. Intermediate sleep shows a mixed spectral profile combining an increase in sigma power and the density of fast spindles, while hippocampal theta rhythms appear (for review, see [78]). On the time scale of intermediate sleep, there is a cessation of LC unit activity [39,73] and the appearance of cholinergic activity in REM sleep-promoting tegmental nuclei [84,85]. The coincidence of declining NA levels with unit and spectral correlates of intermediate sleep suggests that the activity levels of the LC during NREM sleep may determine the timing of NREM-to-REM sleep transitions. Transition periods from NREM sleep to both sustained wakefulness and to microarousals were both associated with an increase in NA levels in the prefrontal cortex that appeared to start before the transition (∼10 s) [73]. On the same time scale, there was an increase in Ca2+ activity of noradrenergic LC neurons that was higher for transitions to consolidated wakefulness compared to microarousals. This appeared also to be the case for NA levels at NREM sleep-to-wake transitions (Figure 2C). These alterations are in line with unit activity measures around moments of wake-up (see Section 2.1 and Section 4.1). 3.5. Emerging Dynamics of Other Monoamines and Wake-Promoting Neurotransmitters In vivo measures using genetically encoded sensors showed that, in addition to NA, other monoamines and wake-promoting neurotransmitters remain high during NREM sleep. In Ca2+-based fiber photometric measures of spontaneous activity in the dorsal raphe, fluctuations were observed in phase relation to spontaneous brief arousals [86]. Furthermore, measures with a genetically encoded sensor for free serotonin levels revealed slow fluctuations in both the orbital frontal cortex and the bed nucleus of the stria terminalis during NREM sleep, and declines during REM sleep [87]. The time course of these fluctuations, and their consistent appearance at two distant brain sites, are reminiscent of the findings with NA described in this chapter. Given the rapid advance in the availability of novel sensors for dopamine [88,89] but also for other neuromodulatory transmitters involved in sleep–wake control (such as acetylcholine, [90] or hypocretin [91]), more details on the spatiotemporal map of neurotransmitter dynamics during states of sleep will soon become available. Intriguingly, transient free dopamine increases in the basolateral amygdala were just discovered as triggers for NREM-to-REM sleep transitions [92]. 4. The Role of the LC in the Regulation of Sleep and Sleep Functions This chapter builds on the newly revealed real-time dynamics of NA levels described in Section 3. It aims to review how these findings advance insight and motivate experimentation in the quest for the functional roles of the LC during sleep. 4.1. LC as Part of Sensory Arousal Circuits during NREM Sleep Pioneering recordings from LC units found that these respond with a short latency to stimuli from different sensory modalities [38,42,43,93,94]. Increases in LC unit discharge rates also preceded spontaneous, unsolicited awakenings from NREM sleep [38,39,94]. Moreover, activation of LC through electrical, opto-, or chemogenetic stimulation elicited transitions from sleep to wakefulness [46,95,96] and recruited whole-brain networks involved in salience processing [33]. Acute knockdown of DBH specifically in LC neurons disrupted sleep-to-wake transitions elicited by optogenetic LC stimulation, confirming the importance of NA signaling for wake-ups [96]. Given LC’s powerful capacity to drive sleep-to-wake transitions, LC activity might be involved in sensory-induced sleep–wake transitions. Indeed, Hayat et al. [63] showed a causal link between the levels of ongoing LC activity during NREM sleep and the probability of sensory stimulus-evoked awakenings. Mild optogenetic LC stimulation lowered the auditory arousal threshold, whereas inhibiting LC heightened it. In line with this, the natural infraslow fluctuations of LC activity during undisturbed NREM sleep coincided with variations of auditory and somatosensory arousability [75,76]. Furthermore, spontaneous brief arousals from NREM sleep in mice were most frequent at moments of low spindle density, when LC activity is high [72,75]. The exact roles of the LC in the cognitive, motor, and autonomic aspects of arousal remain to be determined. As LC neurons are activated by sensory input (Figure 3A), NA release is promoted by the sensory stimulus itself. It is also noteworthy that even low-frequency LC discharge (1–2 Hz) sharpened sensory responsiveness and receptive fields at the level of the thalamus and cortex [97,98,99]. Through depolarizing thalamic neurons, the LC also suppresses the appearance of sleep spindles that limit sensory throughput in thalamocortical areas [78]. The LC could hence promote sequential arousal-promoting actions that are graded with its activity levels as the transition from sleep to wakefulness takes place. 4.2. The LC as Part of the Regulatory Mechanisms of NREM Sleep The real-time dynamics of NA for the first few hours of the light phase, the predominant resting phase of rodents, underscore the importance of the LC in the regulation of sleep architecture [72]. The elucidation of these dynamics across the light–dark cycle and across major sleep–wake control areas will reveal the full impact of NA on sleep’s brain states and associated sleep–wake behaviors. The LC is part of arousal circuits that are under circadian control [100] and it receives afferents from hypothalamic preoptic areas involved in NREM sleep homeostasis [31]. Therefore, beyond its regulation of sleep architecture and spectral composition, the LC could also contribute to circadian and homeostatic regulation of NREM sleep (Figure 3B). 4.3. The LC in REM Sleep Control In spite of much pioneering work (see Section 2.1 and Section 2.2), how LC regulates REM sleep remains an open question (for review, see [101]). Recent research has focused on glutamatergic and GABA-ergic circuits involved in REM sleep regulation, whereas monoaminergic systems were attributed mostly a modulatory role (for review, see [102]). Measures of real-time NA dynamics, together with NREM sleep-specific optogenetic manipulation of the LC in rodents, instead indicate important changes in LC activity at moments of REM sleep onset. These recent data revive the questions about the LC’s role in REM sleep that we outline here in three aspects that could be important in future studies. First, as described in Section 3, forebrain NA levels remained high during NREM sleep (Figure 2A) and LC neurons continue to be active [73]. This elevated activity in noradrenergic signaling suppresses REM sleep, as suggested by electrical or pharmacological LC stimulation in the rat [103,104] and by NREM sleep-specific optogenetic activation of noradrenergic LC neurons at low frequency [72]. A noradrenergic inhibition of REM sleep-promoting brain areas is a likely underlying mechanism for this suppression [105,106,107]. Importantly, the spontaneous activity of LC during natural undisturbed sleep seems even sufficient to antagonize NREM-to-REM sleep transitions. This was concluded from NREM sleep-specific optogenetic inhibition of the LC in freely sleeping mice, which increased the time spent in REM sleep [72]. This indicates that the LC is a powerful target to manipulate the balance between NREM and REM sleep in response to various regulatory and experience-dependent processes (see below and Section 5.2). Second, NA levels declined in both the thalamus and cortex in REM sleep (Figure 2B). This decline took tens of seconds to complete once REM sleep began, raising the question of which are the determinants of this time course. The LC is inhibited by GABAergic mechanisms [108,109], of which several have been tested for their role in REM sleep control. Monosynaptic inhibitory afferents arise from the local and pericoerulear interneurons [110], ventrolateral periaqueductal gray [111], and from nucleus prepositus hypoglossi and dorsal paragigantocellular reticular nucleus [107,112,113]. Acetylcholine release from cholinergic REM sleep-promoting areas could also act through GABAergic mechanisms [109]. Cholinergic areas are likely initiating the LC inhibition as their discharge onset precedes REM sleep [84], but auto-inhibitory mechanisms within the LC could also play in at this moment [114]. At least one of the dorsal medullar inhibitory afferents increases activity exactly at REM sleep onset [113], suggesting that NA decline could become strengthened due to additional sources of inhibition. NA uptake mechanisms lagging behind synaptic inhibition of the LC could instead retard the decline of free NA levels. How the strength and the efficiency of synaptic inhibition regulate LC silencing and NA decline and/or interact with other excitatory and/or modulatory synaptic mechanisms of LC inhibition (see e.g., [110]) is currently unexplored. The determinants of NA dynamics at NREM-to-REM sleep transitions are critical to understanding how REM sleep evolves into an NA-free state because of its likely role in the regulation of emotional memory (see Section 5.2). Third, the fluctuating levels of NA during NREM sleep indicate that chances for a NREM-to-REM sleep transition increase at moments of relatively low NA levels. Interestingly, the probability to enter REM sleep was indeed found to be phase-locked to the infraslow fluctuation of sigma power measured at the level of the EEG [113]. This lends support to the idea that fluctuating LC activity during NREM sleep generates brain states that are permissive for transitions, such as the ones to REM sleep (Figure 3A) [75,76]. The LC activity oscillating between high and low levels might suppress REM sleep on the one hand, but also open moments where transitions are favored. The LC is, therefore, positioned as a brain area capable of autonomously regulating the timing of REM sleep in a bidirectional manner during NREM sleep, yet how it is integrated into REM sleep regulatory mechanisms will require further research. Alterations in REM sleep propensity, duration, and hippocampal-related theta activity are ubiquitous after stress- and fear-related experiences. These are part of the acute physiological responses to the hormonal and autonomic changes accompanying stress [115], but they also contribute to the consolidation of fear- [116] and extinction-related memories [115]. Increases in REM sleep are part of an adaptive process to mild stress exposure [117]. Given the LC’s high reciprocal connectivity with areas implied in fear, such as the amygdala (for review, see [31]), it is a strong candidate for linking stress-related experiences during the day to the timing of REM sleep. Indeed, acute decreases in REM sleep in response to inescapable footshock could be alleviated by optogenetic inhibition of excitatory neurons in the basolateral amygdala [118] or by dual hypocretin receptor antagonism in the LC or the dorsal raphe [119]. In case of such or even more traumatic experience, states of hyperarousal associated with elevated monoaminergic activity may arise, to which the LC contributes (for review, see [120]) (see Section 5.2). 4.4. The LC in Hippocampus-Dependent and Independent Memory Consolidation LC activity, in part due to its implication in novelty detection, has been found to actively contribute to online memory consolidation. A series of studies found that activation of the LC favors different types of learning such as spatial learning [121,122,123,124], fear learning and reconsolidation [124,125,126], and perceptual learning [127,128]. Optogenetically activating LC tyrosine hydroxylase-positive neurons shortly after memory encoding of food rewards in a navigation task promoted memory retention in mice, which persisted until the next experimental assessment [121]. Such LC stimulation mimicked the effects of environmental novelty on memory encoding. Intriguingly, local pharmacological inhibition of dopaminergic but not noradrenergic receptors in the hippocampus implied a role of LC fiber-dependent dopamine release in novelty enhancement of hippocampus-dependent memory. Optogenetic stimulation of the LC during a spatial object recognition task lead to similar results [122]. Inhibition of the LC had, on the contrary, a detrimental effect on hippocampal place cell formation in goal-directed spatial learning [123]. The LC’s role in cued fear conditioning concerned both, memory acquisition of the pairing between the conditioned and the unconditioned stimulus, and later extinction [126]. Here, a dual role for LC afferent projections to the amygdala and to the medial prefrontal cortex could be identified, with the former implied in the acquisition, and the latter in the extinction of fear memory, demonstrating a modular functionality of LC subgroups depending on their projection targets. Pairing LC activation with stimulus presentation could also accelerate the learning of a new target sound in a perceptual learning paradigm [127] in rats and electrical/optogenetic stimulation of the LC during sound presentation promoted NA-dependent long-term plastic strengthening in auditory tuning curves of primary auditory cortex neurons [128]. The LC’s role as a regulator of memory acquisition likely relies on manifold actions of NA on neuronal excitability, in particular in hippocampal circuits, and on enduring changes in synaptic strength (for review, see [129]). One principal action of endogenously released NA, identified through optogenetic stimulation of LC fibers, appears to be a suppression of postsynaptic potassium currents, which enhanced the excitability of CA1 pyramidal neurons in response to Schaffer collateral stimulation [130]. This effect was blocked by β adrenoceptor antagonists, with no apparent implication of dopamine release. It is noteworthy that this action was already present when fibers were stimulated at low frequency (1 Hz), suggesting that such neuromodulation could be effective during NREM sleep, when the LC discharges at low frequencies (see Section 2.1). In contrast to the strong evidence for the LC’s involvement in the memory acquisition phase, evidence that it plays a role during offline processing, including during sleep, is currently scarce. Pioneering pharmacological studies found that rats trained in an olfactory reward association task performed less well when they were injected with adrenergic antagonists intracerebroventricularly [131] or within prefrontal cortex [132] 2 h after training, but not at shorter or longer time intervals. These authors also provided evidence for a transient increase in NA levels during the time window in which these antagonists were effective. This pointed to a delayed re-activation of the LC that facilitated offline processing and memory consolidation. Follow-up studies suggest that such re-activation of the LC may indeed occur during post-learning sleep stages, as LC unit activity transiently doubled within the presumed re-activation window, without apparent alteration in sleep architecture [44]. The activity of LC units was further observed to be time-locked to slow waves in both rat [45] and human [64] and to hippocampal sleep spindles [46], suggesting that enhanced NA release is linked to the sleep rhythms that enable active systems consolidation. Finally, high-frequency stimulation of the LC disrupted the coupling of sleep spindles with hippocampal ripples that are high-frequency oscillatory patterns critical for memory consolidation [133]. This adds to evidence that the degree of LC activity might be critical in coordinating sleep rhythms relevant for offline processing (for review, see [134]). 4.5. The LC as Mediator of Vagal Afferent Information Among the innervations that the LC receives, one is of particular interest as a gate for interoceptive signals, the Nucleus Tractus Solitarius [135,136] (for review, see [137]). This brainstem nucleus is part of the dorsal vagal complex (nucleus tractus solitarius, area postrema and dorsal motor nucleus of the vagus) which is the first recipient for vagal afferents (for review, see [138]). The vagus nerve is part of the parasympathetic system and it is a mixed nerve containing both motor and sensory fibers. Sensory information arising from the vagus nerve is important for autonomic feedback reflexes, such as the baroreceptor reflex and the Hering–Breuer reflex that serves to control breathing (for review, see [139]), and it reaches the LC via the dorsal vagal complex [140]. Vagus nerve stimulation is well-known for its beneficial role in clinical conditions, as evident from the highly diversified effects of vagus nerve stimulation (VNS). Indeed, this technique has been proposed to facilitate brain plasticity [141] (for review, see [142]) and memory formation (for review, see [143]). Some important domains of clinical application for VNS include drug-resistant epilepsy [144] (for review, see [145,146]), depression [147] (for review, see [148]), eating disorders [149], and neurodegenerative disorders [150]. Several animal studies support the LC as a major target of vagal afferent nerve stimulation. VNS caused an increase in the expression of the immediate-early gene c-fos in LC neurons in conscious unanesthetized rabbits [151] and in anesthetized rats [152]. Moreover, lesioning of the LC led to a suppression of the anticonvulsant effects of VNS in epileptic rats, supporting the idea that the LC is involved in this circuitry [153]. This implication of the LC was further supported by directly recording LC unit activity during VNS [154,155,156,157]. Using in vivo Ca2+ imaging in head-fixed awake mice, a recent study showed an increase in the noradrenergic neuromodulatory system in response to VNS [158]. Furthermore, in vivo microdialysis showed an increase in NA extracellular levels in the hippocampus and cortex during chronic VNS in anesthetized rats [159,160] and an increase in dopamine in extracellular levels in the prefrontal cortex and nucleus accumbens [161]. Additionally, vagal afferent electrical stimulation has been related to pupil dilation in animals and humans [162,163,164,165], consistent with the correlation between pupil diameter and firing of noradrenergic LC cells (for review, see [7]). Together, these results indicate that monoaminergic systems, including the LC, act as monitors of internal stimuli conveyed by vagal afferents (Figure 3A). Given the role of the LC in the regulation of sleep, stimulation of vagal afferents may contribute to LC-dependent sleep regulatory effects. Animals studies suggest that VNS can promote REM sleep [166,167] and/or increase NREM sleep quantity as well as power in the delta and sigma bands [168] in freely moving cats. Several clinical studies also investigated the effects of VNS on sleep regulation. In epileptic and depressive patients, VNS treatment improved daytime alertness [169], increased the mean sleep latency [170], decreased awake time and stage 2 sleep and increased stage 1 sleep [171], increased delta power during NREM sleep and reduced REM sleep quantity [172,173], increased time spent in NREM sleep and decreased sleep latency and stage 1 sleep [174], and increased wakefulness and decreased light sleep and REM sleep [175]. These differences in the outcome could be related to the variability of the VNS parameters and/or the use of antiepileptic drugs which are known to affect sleep architecture (for review, see [176]). So far, the contributions of sensory and motor components of VNS to sleep have not been determined. In a first step in this direction, a chemogenetic stimulation of the sensory afferents of the vagus nerve showed an alteration of sleep architecture and spectral composition, and a strong increase in the latency to REM sleep onset [177]. 4.6. The Role of the LC in the Regulation of Brain Vascular Activity DBH-positive LC terminals are tightly apposed on the fine arborizations of the neurovascular tree, notably the intraparenchymal capillaries. There is also evidence that released NA regulates cerebral blood flow, neurovascular coupling, and the maintenance of the blood–brain barrier (for review, see [178]). For example, the localized increase in blood supply to the somatosensory cortex, in response to paw stimulation depended on an intact LC [179,180]. As NA levels remain high in the forebrain during NREM sleep, it is likely that its actions on the microvasculature continue (Figure 3B). The LC innervates several components of the neurovascular unit, including astrocytic endfeet, as well as peri- and endocytes, which control different aspects of glial and capillary function (for review, see [181]) that are regulated differentially between sleep and wake [73]. One of the most important insights in this field was obtained for the brain’s glymphatic system that regulates the entry of cerebrospinal fluid along the perivascular space of small capillaries (for review, see [182]). Fluid exchange via the glymphatic system is enhanced during NREM sleep and cleanses the brain from toxic products such as amyloid-β-protein [183]. The fluctuating NA levels during NREM sleep could hence contribute to the pulsatile nature of this exchange process, perhaps through acting on vasomotor activity that is thought to be critical for the paravascular clearance of solutes, in particular when occurring at infraslow frequencies [184]. Interestingly, a recent study indicated a temporal correlation between cerebrospinal fluid exchange and the occurrence of slow and infraslow electrical activity in the EEG [185]. In view of these most exciting developments, we speculate that the LC’s dual capability of modulating neural oscillation control and arteriolar vasoconstriction makes it a master regulator of the sleeping brain’s functions because it could potentially play a role in coordinating the timing of sleep architecture, sleep electrical rhythms, and brain waste clearance. An implication of the LC in gross cerebral blood flow arises from functional MRI studies. These have repeatedly reported the presence of spontaneous slow signal fluctuations during rest and sleep, including during N2 sleep in humans. Frequencies involved are in the infraslow range, close to values found for infraslow activity fluctuations of the LC during NREM sleep in rodent [186,187,188]. Furthermore, chemogenetic activation of the LC in lightly anesthetized mice generates a functional activation pattern [33] that overlaps with some of the areas found in early sleep stages [188]. The infraslow activity of the LC during NREM sleep could conceivably impose a time frame for resting-state network activity, which remains a question for future work. 5. The LC and Sleep Function in Pathology As the LC has been known primarily as a wake- and attention-promoting brain area, the idea that LC dysfunctions could play a role in sleep (rather than wake) problems has been less considered. Moreover, the idea that a dysfunctional LC could be involved in a decrement of some major neuroprotective roles of sleep is so far underexplored. As the LC’s profound implication in sleep architecture and sleep function is increasingly recognized, these possibilities come to center stage and open novel inroads for preventive strategies (Figure 3B). 5.1. Aging and Neurodegenerative Disorders Many aspects of sleep, from its timing and initiation to its maintenance and depth deteriorate with aging (for review, see [189]), and this process is aggravated in the case of neurodegenerative dementias, of which Alzheimer’s disease (AD) is the most common form (for review, see [190]). In healthy aging mice, hypothalamic orexin neurons undergo increases in intrinsic excitability that cause sleep fragmentation [191]. In aging accompanied by neurodegeneration, much interest has recently focused on the LC that appears to be afflicted at early stages of AD [192]. Ample evidence further indicates that disturbed sleep adversely affects the progression of AD pathology (for review, see [193]). Therefore, addressing whether early LC pathology links to sleep disruptions bears potential to identify early stages of disease. This potential is strengthened by newest evidence that structural measures of LC integrity in vivo can be related to the initial stages of AD-related neurodegeneration and cognitive decline [194]. It is currently open how exactly LC neuronal activity and NA signaling are altered with aging and pathologically aggravated with the progression of AD. Chemogenetically stimulating LC in a rat model of AD recovered spatial learning capacities, but how much and in which brain areas NA signaling was restored remained an open question [195]. As free NA dynamics have become accessible through biosensors (see Ch. 3), it is now possible to determine when and how these are affected by the neurodegenerative processes and to which types of sleep disruptions they might be linked. Amongst the diverse alterations in sleep in patients with neurodegenerative disorders (for review, see [190]), recent focus has been on alterations in sleep’s microarchitecture [66,196] and possible links to LC dysfunction, which make altered NA signaling during NREM sleep as a reasonable path to be pursued. On top of this, evidence for the LC’s implication in the vascular pathology and decline of glymphatic activity in AD pathogenesis has attracted enormous interest (for review, see [178]). At this stage, deepening the causal links between LC dysfunction and altered NA signaling is a very promising path to the LC’s broad implication in sleep disorders linked to neurodegenerative diseases (for review, see [36,182]. 5.2. Stress-Related Disorders Increased noradrenergic LC activity is a common observation after stressful or traumatic life experiences (for review, see [25]). This increase persists beyond the momentary insult and may continue during sleep. Even comparatively mild stress in rats, such as a simple cage exchange, activates major wake-promoting areas, including the LC, and leads to sleep fragmentation [197]. Both mild and excessive stress, such as the one inflicted by traumatic events, have been related to a maintained hyperactivity of the LC noradrenergic system (for review, see [25]). As stress and various sleep disruptions are tightly linked, it is likely that the NA signaling profile during NREM and REM sleep becomes altered at various levels and adversely affects sleep physiology. First, elevated LC activity and NA signaling is arousal-promoting through its desynchronizing effect on EEG that favors high- over low-frequency oscillatory activity, as demonstrated by pharmacologic [198], electrical [199], chemogenetic [200], or optogenetic [63] activation of LC neurons. Alteration in the LC noradrenergic system may thus contribute to cortical hyperarousal states during sleep. Interestingly, cortical hyperarousal states are a common trait of sleep disruptions arising from neuropsychiatric conditions, but also from pain (for review, see [201]) and primary insomnia (for review, see [202]). Second, elevated LC activity promotes arousability to external stimuli (see Section 4.1), facilitating sleep disruptions. It is well accepted that lightened NREM sleep and more frequent awakenings are part of the disease profile in post-traumatic stress disorder (for review, see [25,203]). Third, elevated LC activity may compromise the decline of NA levels during REM sleep. While this possibility awaits a direct demonstration, the idea that insufficient decline of NA levels during REM sleep has been put forward as a mechanism inhibiting extinction of emotional memory (for review, see [25,202]). Mechanistically, it is thought that the quiescence of LC neurons during REM sleep allows a depotentiation of synaptic strength in anxiety-related networks, including the amygdala. Therefore, during NA-enriched REM sleep, also referred to as “restless REM sleep”, behavioral reactions to emotional stress do not decline overnight [204]. More generally, high and fluctuating levels of NA in NREM sleep may support synaptic plasticity while the low levels during REM sleep could promote synaptic depotentiation and downscaling. As a consequence, aberrant noradrenergic activity during REM sleep may contribute to the maladaptive recall of complex experiences in which emotional aspects remain highly salient. The real-time dynamics of NA during NREM and REM sleep will be essential in refining the proposed picture of the LC as an important coordinator of memory consolidation processes during sleep. 5.3. Sleep and Cardiovascular Regulation The cardiovascular correlates of NREM and REM sleep arise from the interplay of autonomic reflex arcs and central commands that regulate the balance between sympathetic and parasympathetic activity (for review, see [205]). Both circadian and sleep-driven mechanisms contribute to the central control of the cardiovascular system (for review, see [206]). NREM sleep is dominated by parasympathetic influences, whereas sympathetic ones prevail in REM sleep (for review, see [206,207]). LC efferents target both preganglionic sympathetic and parasympathetic output areas, activating the former while inhibiting the latter. Further cardiovascular impact may arise through the LC’s connections with stress- and attention-responsive brain areas (for review, see [29]). However, the LC’s role in the central autonomic commands for cardiovascular control in sleep is not clarified, although brainstem mechanisms are particularly prevalent in cardiovascular control during NREM sleep (for review, see [207]). In mice, infraslow variations in heart rate during NREM sleep were mediated by the parasympathetic system [72]. Furthermore, continuous and global optogenetic stimulation of LC noradrenergic neurons during NREM sleep disrupted previously observed anticorrelations between spindle clustering and heart rate, whereas LC stimulation at infraslow frequencies strengthened this anticorrelation [72]. The LC is thus positioned to regulate central and autonomic activity during NREM sleep. Given the numerous sleep-related cardiovascular alterations in neuropsychiatric and neurodegenerative diseases, it will be of great interest to examine the LC’s and other monoaminergic’s contributions to the pathophysiological manifestations of these conditions [207]. 6. Closing Remarks and Future Directions We outlined novel evidence showing that the noradrenergic LC plays important and previously underestimated roles in sleep. We reviewed and contrasted existing literature with recent findings that unraveled the real-time dynamics of the LC and its NA output during sleep. A central step forward is the recognition that NA signals span an unexpectedly high dynamic range, from high and comparable levels between wakefulness and NREM sleep to low levels in REM sleep, at least in the two forebrain areas measured so far. This dynamic currently is not congruent with what we know about variations in LC unit activity across sleep and wakefulness. Clearly, much is still unknown about how LC neuronal activity determines NA release, possible target-specific presynaptic release properties, and variations in local uptake mechanisms, all of which shape NA dynamics. It is furthermore going to be important to determine whether these fluctuations arise as part of the LC’s spontaneous activity and/or secondarily from its integration into large-scale sleep-regulatory networks within the central and autonomic nervous systems. In this review, we outlined that recognizing NA as a neuromodulator during sleep opens novel mechanistic ideas on how sleep architecture and spectral dynamics are organized to the benefit of sleep functions. Future studies will undoubtedly reveal that fluctuations in other neuromodulators, such as the ones already reported for serotonine [86] and dopamine [92], work conjointly with NA in these processes. An additional unique observation is the infraslow fluctuations in NA levels that characterize NREM sleep. These dynamics bring, for the first time, a neural in vivo foundation to a time scale of brain oscillatory activity that has long revolved in whole-brain measures and behavioral output, but that has not been a systematic part in the check-box list of sleep rhythms that are important for sleep functions [77]. Now, times become ready for speculations about its origins in the coordination of sleep and offline brain functions that are central to brain and bodily health. As they currently stand, these new observations will have manifold implications for the LC’s role in healthy and disordered sleep. Some of these implications have been proposed but not pursued for years, yet they are now accessible with unprecedented spatiotemporal control. Most intriguingly, we may soon come to realize that the high NA levels are integral to enabling restorative NREM sleep and generating its unique benefits for health. Some other implications, however, are newly emerging. The NA, and perhaps other monoamines, present a profile of sleep as a behavioral state that integrates neuromodulation to monitor environmental, bodily, and brain states to enable adaptive behaviors. We propose that NA could show us the way to the neural foundation of a vigilance system for sleep, based on which novel insights into sleep’s benefits and in-roads for therapeutic treatments of sleep disorders arise. Acknowledgments The authors are grateful for the critical and constructive reading of earlier versions of the manuscript, in particular S. Astori, M. Bandarabadi, G. Foustoukos, F. Siclari and M. Tafti. We also acknowledge the many inspiring discussions by colleagues within the DNF and at the University of Lausanne. Author Contributions A.L. and A.O.-F. conceptualized this review; A.O.-F., N.C., L.B., L.M.J.F. and A.L. contributed portions of the main text; L.M.J.F. designed the figure layout. Original data presented in Figure 2 were obtained by A.O.-F. 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 following abbreviations are used in this manuscript: LC Locus Coeruleus NA Noradrenaline NREM Non-Rapid-Eye-Movement REM Rapid-Eye-Movement DBH Dopamine-β-Hydroxylase MRI Magnetic Resonance Imaging 5HT 5-hydroxytryptamine (or serotonin) ACh Acetylcholine GRAB G-Protein-Coupled-Receptor-Activation-Based EEG Electroencephalogram VNS Vagus Nerve Stimulation AD Alzheimer’s Disease Figure 1 Summary of traditional and revised views on the neuromodulatory profiles of wakefulness and sleep, with a focus on noradrenergic signaling. Traditional (left) and revised (right) views derived from animal experimentation are summarized and complemented with data-derived schematic representations of NA dynamics and LC unit activity. From top to bottom: mean levels of major neuromodulators (blue up and gray down arrows symbolize high and low levels in the traditional view), a representative hypnogram of mouse sleep–wake behavior, free NA levels, and representative discharges of a LC unit. Novel insights central to the revised view are highlighted with the red arrow, whereas unaltered neuromodulatory levels are shown with light grey arrows. NA, noradrenaline; 5HT, serotonin; ACh, acetylcholine; NREM, NREM sleep; REM, REM sleep. Figure 2 Real-time dynamics of NA levels in somatosensory thalamus, forebrain sleep spindle power, and heart rate during NREM sleep. Representative simultaneous recordings in a freely behaving mouse combining (from top to bottom): hypnogram (gray), free NA levels in somatosensory thalamus obtained through fiberphotometry imaging (red, A1), local field potential sigma power (10–15 Hz) in somatosensory cortex (dark blue, A2) and heart rate (light blue, A3), with labeled portions (A, B, C) shown expanded on the right. The variations in sigma power reflect the clustering of sleep spindle density ([72]). Insets on the right expand portions of the traces highlighted with letters in the hypnogram to show (A) NREM sleep (double-headed arrow marks the 50 s periodicity); (B) NREM-to-REM sleep transitions (double-headed arrow marks the decay time of NA levels prior to REM sleep onset); (C) NREM-to-wake transitions. Portions of two of these traces have been published previously [72]. NA, noradrenaline; W, wakefulness; NR, NREM sleep; R, REM sleep; ΔF/F, relative fluorescence changes; AU, arbitrary unit; bpm, beats per minute. Figure 3 Perspectives for the implication of the LC in healthy and disrupted sleep. Schematic indicating the types of signals monitored by the LC and the implications of LC function and dysfunction for sleep. (A) The LC monitors external stimuli (e.g., sensory stimuli such as touch or sound, symbolized by a feather and a musical note, see Section 4.1), internal stimuli (symbolized by the heart, see Section 4.5), and internal brain states important for the regulation of NREM-to-REM sleep transitions (symbolized by the brain, see Section 3.4 and Section 4.3). (B) Depending on the LC status (healthy or damaged), beneficial or adverse consequences on sleep can arise. Several outcomes are listed on the right. The LC micrograph was obtained from an immunohistochemically stained brain section of one of the mice used for the data published in [72]. The color choice of cell labeling was made deliberately to mark it as the sky-blue spot. The blurring of the blue color in the bottom micrograph symbolizes both structural and functional alterations that can lead to LC dysfunction. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Manger P.R. Eschenko O. The Mammalian Locus Coeruleus Complex—Consistencies and Variances in Nuclear Organization Brain Sci. 2021 11 1486 10.3390/brainsci11111486 34827485 2. Fuxe D. Evidence for existence of monoamine-containing neurons in central nervous system. I. Demonstration of monoamines in the cell bodies of brain stem neurons Acta Physiol. Scand. 1964 62 1 55 14210262 3. Maeda T. Pin C. Salvert D. Ligier M. Jouvet M. Les neurones contenant des catecholamines du tegmentum pontique et leurs voies de projection chez le chat Brain Res. 1973 57 119 152 10.1016/0006-8993(73)90572-6 4716749 4. Bogerts B. A brainstem atlas of catecholaminergic neurons in man, using melanin as a natural marker J. 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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/ijerph19095029 ijerph-19-05029 Article Arbuscular Mycorrhizal Fungi and Glomalin Play a Crucial Role in Soil Aggregate Stability in Pb-Contaminated Soil Li Yinong 1† Xu Jiazheng 12† Hu Jin 1 Zhang Tianyu 1 Wu Xuefeng 1 Yang Yurong 12* Liu Jinling Academic Editor Zhou Jun Academic Editor 1 Key Laboratory of Vegetation Ecology of the Ministry of Education, Institute of Grassland Science, Songnen Grassland Ecosystem National Observation and Research Station, Northeast Normal University, Changchun 130024, China; liyn129@nenu.edu.cn (Y.L.); xujz541@nenu.edu.cn (J.X.); huj791@nenu.edu.cn (J.H.); zhangty451@nenu.edu.cn (T.Z.); wuxf112@nenu.edu.cn (X.W.) 2 State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, Changchun 130117, China * Correspondence: yangyr422@nenu.edu.cn; Tel.: +86-1594-306-6016; Fax: +86-0431-8916-5610 † These authors contributed equally to this work. 21 4 2022 5 2022 19 9 502911 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/). With the rapid development of industrialization and urbanization, soil contamination with heavy metal (HM) has gradually become a global environmental problem. Lead (Pb) is one of the most abundant toxic metals in soil and high concentrations of Pb can inhibit plant growth, harm human health, and damage soil properties, including quality and stability. Arbuscular mycorrhizal fungi (AMF) are a type of obligate symbiotic soil microorganism forming symbiotic associations with most terrestrial plants, which play an essential role in the remediation of HM-polluted soils. In this study, we investigated the effects of AMF on the stability of soil aggregates under Pb stress in a pot experiment. The results showed that the hyphal density (HLD) and spore density (SPD) of the AMF in the soil were significantly reduced at Pb stress levels of 1000 mg kg−1 and 2000 mg kg−1. AMF inoculation strongly improved the concentration of glomalin-related soil protein (GRSP). The percentage of soil particles >2 mm and 2–1 mm in the AMF-inoculation treatment was higher than that in the non-AMF-inoculation treatment, while the Pb stress increased the percentage of soil particles <0.053 mm and 0.25–0.53 mm. HLD, total glomalin-related soil protein (T-GRSP), and easily extractable glomalin-related soil protein (EE-GRSP) were the three dominant factors regulating the stability of the soil aggregates, based on the random forest model analysis. Furthermore, the structural equation modeling analysis indicated that the Pb stress exerted an indirect effect on the soil-aggregate stability by regulating the HLD or the GRSP, while only the GRSP had a direct effect on the mean weight diameter (MWD) and geometric mean diameter (GMD). The current study increases the understanding of the mechanism through which soil degradation is caused by Pb stress, and emphasizes the crucial importance of glomalin in maintaining the soil-aggregate stability in HM-contaminated ecosystems. heavy metal lead (Pb) pollution symbiotic fungi glomalin soil aggregation ==== Body pmc1. Introduction Arbuscular mycorrhiza fungi (AMF) are a group of soil fungi with a wide distribution and important ecosystem functions. They can establish mutualistic symbiosis with approximately 80% of terrestrial plants [1], and they play an essential role in facilitating plant nutrient uptake, improving plant stress resistance, modifying soil structure, and restoring degraded ecosystems [2,3]. The extraradical hyphae formed by AMF can extend beyond the nutrient-deficient zone of the rhizosphere and enhance the absorption of phosphorus, nitrogen, and water. In turn, the host plant supplies 4–20% of the carbon hydration produced by photosynthesis to AMF to meet its growth and development needs [4]. In addition, AMF can also improve the adaptability of plants to environmental stresses by enhancing the expression of antioxidant enzymes, aquaporin, metallothionein, and other related genes [5,6,7]. AMF form a common mycorrhizal network among different plant species, thereby regulating important ecological processes such as nutrient distribution [8], plant competition [9], and community structure and succession [10]. However, the essential role of AMF in the stability of soil aggregates in degraded ecosystems remains unclear. Soil is not only an important component of the terrestrial ecosystem, but also the source of the nutrients in our food supply. Soil structure is one of the most important soil properties, which determines structure, determines the retention, transformation, and transfer efficiency of water, air, heat, and nutrients in soil. The composition and stability of soil aggregates, which are the foundations of soil structure, are essential factors affecting soil fertility and ecosystem functions. Moreover, AMF hyphae and the produced glycoprotein (glomalin) can bind soil particles together through the “bonding–joining–packing” mechanism, and then act as bio-glue to promote the formation of large aggregates and increase the stability of the soil’s structure [11]. Glomalin is a special type of glycoprotein, produced specifically by hyphae and spores of AMF and released into the soil after decomposition; it is widely distributed, hydrophobic, insoluble, and recalcitrant in nature [12]. Previous studies indicated that AMF inoculation increased the GRSP content, mean weight diameter (MWD), and geometric mean diameter (GMD) of soil aggregates [13]. However, the relationships between the AMF growth index, GRSP, MWD, and GMD, and whether the effects of AMF on soil-aggregate stability are linked to GRSP, remain unclear. Soil contamination by HMs constitutes a serious environmental problem. Pb is one of the most widely distributed and harmful toxic HMs in soil. China is the world’s largest producer of mineral Pb, with 63.9% of the world’s total mineral Pb production in 2020 (China Lead Industry Development Report 2020). In recent years, Pb contamination caused by mining, smelting, processing and other activities is increasing, and HM pollution incidents, such as blood Pb overload, have occurred from time to time [14]. In order to effectively address soil Pb contamination and restore degraded ecosystems, related research and practice have been comprehensively carried out in China. Most previous studies focused on distribution patterns [15,16], health-risk assessments [17,18], and remediation technology related to Pb-contaminated soil [19,20]. However, the positive effects of AMF on HM contamination as a bioremediation strategy to reduce the damage caused by Pb are still unclear. In view of this, a three-compartment root box was used in this study to investigate the effects of AMF inoculation on GRSP and the composition, and stability of soil aggregates under Pb stress. The objectives of this research are (1) to clarify the effects of Pb stress on AMF growth, GRSP, and the composition and stability of soil aggregates; and (2) to analyze of the effect of the AMF pathway on soil aggregates’ stability under Pb stress. This study provides a scientific basis for understanding the physiological and ecological functions of AMF and their potential value in restoring degraded ecosystems. 2. Materials and Methods 2.1. Preparation of Substrate Soil, Plant and AMF Inoculum The substrate soil was prepared by collecting surface-layer (0–15 cm) soil from the experimental station of Jilin Agricultural University, Changchun, China (43°49′07″ N, 125°23′56″ E). The station has a continental monsoon climate with four distinctive seasons. The annual precipitation is about 600–700 mm and the annual average temperature is approximately 6.7 °C. The soil samples were passed through a 2-centimeter mesh sieve to remove any debris, rocks, and large organic matter, and were then air-dried at room temperature for 30 days. Subsequently, the soils were sterilized in clean cloth bags at 121 °C, 0.11 Mpa for 2 h (twice) to eliminate all microorganisms. A subsample was analyzed for physical and chemical properties of the soil. The soil belonged to the chernozem with pH 7.61, soil organic matter 25.7 mg g−1, total nitrogen 15.4 mg g−1, available nitrogen 93.6 mg kg−1, total phosphorus 0.86 mg g−1, available phosphorus 12.7 mg kg−1, and Pb 29.3 mg kg−1. The soils were equilibrated with Pb(NO3)2 solution at the final concentrations of 0, 500, 1000, and 2000 mg kg−1 Pb for 2 weeks, undergoing five cycles of saturation with deionized water and air-drying. The seeds of Bidens parviflora Willd. [1,2] were collected from Longwan National Natural Reserve, Jilin Province, China (42°20′56″ N, 126°22′51″ E). They were surface-sterilized with 75% ethyl alcohol solutions for 10 min, and rinsed with distilled water five times. The seeds were placed on moistened filter paper in 9-centimeter-diameter Petri dishes. Four days later, the germinated seeds with uniform size were transplanted into plastic pots filled with 2.5 kg of autoclaved soil (15-centimeter upper diameter, 12-centimeter lower diameter, and 15 cm deep). The AMF inoculum, Funneliformis mosseae (T.H. Nicolson & Gerd.) C. Walker & A. Schüßler (formerly Glomus mosseae) was obtained from Beijing Academy of Agriculture and Forestry Sciences (BAAFS). The fungus was propagated in pot culture with maize (Zea mays L.) and white clover plants grown in sterilized sand for 3 months before it was used for the experiment. At harvest, the aboveground parts of maize and white clover were discarded, and the dried substrate soils (36 spores g−1) were mixed homogeneously to use as the AMF inoculum to ensure that all treatments could receive the same number of spores. The AMF inoculum containing 500 spores weas placed 2 cm below the germinated seeds and covered with substrate soils. After emergence, seedlings were thinned to a final density of four plants per pot. 2.2. Experimental Design The experiment was conducted in the greenhouse of Northeast Normal University, Changchun, Jilin Province, China (125°25′36″ E, 43°49′30″ N), and lasted 95 days. The experiment had a randomized complete block design with two AMF inoculation treatments (NM, non-mycorrhizal inoculation; AMF, AMF inoculation) and four Pb-addition treatments (Pb 0, 0 mg kg−1; Pb 500, 500 mg kg−1; Pb 1000, 1000 mg kg−1; Pb 2000, 2000 mg kg−1). Each treatment had six replicates for a total of 48 plastic pots. The pots were uniformly irrigated with distilled water every 2 days. 2.3. Sampling, Harvest, and Chemical Analysis At harvest, plant root and soil samples in each pot were collected separately for further analysis. Plant roots were harvested to stain using 0.05% trypan blue [21], and mycorrhizal colonization (MC) was assessed based on proportion of root length colonized by AMF under a microscope [22]. Hyphal length density (HLD) of AMF was determined by the modified grid-line intersection method described by Jakobsen et al. [23]. The soil sample (5 g) was blended with mixed distilled water (200 mL) and sodium hexametaphosphate in a beaker (500 mL). The hyphal suspension was then poured through 180-micrometer and 38-micrometer sieves. The filtrated materials were transferred to a beaker, shaken for 30 s, and then left to settle for 5 min at room temperature. The supernatant passed through a microporous membrane (0.45 μm) using vacuum pump. The hyphae were stained by a 0.05% (w/v) trypan blue solution, and measured according to the gridline intercept method at 200× magnification under a microscope. The HLD was expressed in units of m g−1 dry soil. The spore density (SPD) of AMF was determined by the wet sieving and decanting method proposed by Gerdemann and Nicolson [24]. Specifically, 50 g of soil samples was stirred evenly with 100 mL water, and allowed to settle for 30 min at room temperature. The suspension passed through a sequence of sieves (1000, 750, 500, and 38 μm). The procedure was repeated four times. The filtrated materials were transferred from the last two sieves to the 100-milliliter centrifuge tube with 60% sucrose solution, centrifuged at 3000 r/min for 5 min. The number of AMF spores was counted under a dissecting microscope and the spore density (SPD) was expressed as number of spores in 1 g of dry soil. The concentrations of total glomalin-related soil protein (T-GRSP) and easily extractable glomalin-related soil protein (EE-GRSP) were determined according to procedures described by Wright and Upadhyaya [17]. The air-dried soil (1 g) was incubated with 8 mL of 20 mM sodium citrate solution (pH 7.0), autoclaved at 121 °C and 103 kPa for 30 min, and then centrifuged at 10,000× g for 15 min to extract EE-GRSP. By contrast, the T-GRSP was extracted with 8 mL of 50 mM sodium citrate solution (pH 8.0) by autoclaving at 121 °C and 103 kPa for 60 min. The procedure of extraction was repeated six times and all suspensions were collected. The EE-GRSP and T-GRSP concentrations were measured spectrophotometrically by the Bradford dye-binding assay using bovine serum albumin (BSA) as the standard. Soil aggregates’ stability was determined by the wet sieve method [25]. The undisturbed soil samples were naturally air-dried at room temperature. A total of 50 g of soil samples was placed at the top of a stack of sieves (2 mm, 1 mm, 0.25 mm, and 0.053 mm) and soaked in a bucket overnight. The soils were sieved by raising and lowering at a distance of 5 cm and a stroke of 30 times min−1 for 10 min. Finally, the weights and the mass percentages of the soils with different soil-particle sizes were calculated. The mean weight diameter (MWD) and the geometric mean diameter (GMD) of the soils were used to evaluated the stability of the soil aggregates [26] and were calculated as follows:MWD=∑i=1nx¯iwi GMD=exp(∑i=1nwilnx¯i) where w is the mass of each soil-particle size, wi is the mass percentage of each soil-particle size (%), and x¯i is the average diameter of each soil-particle size. 2.4. Statistical Analysis Prior to statistical analysis, the Kolmogorov–Smirnov test and the Levene test were applied to assess data normality and homogeneity, respectively, using SPSS 21.0. for Windows 10 (SPSS Inc., Chicago, IL, USA). Subsequently, one-way ANOVA was used to assess the significant differences in HLD, SPD, T-GRSP, EE-GRSP, mass percentage of soil particles, MWD, and GMD among different treatments, whereas two-way ANOVA was performed to reveal the interactive effects of Pb stress and AMF inoculation on T-GRSP, EE-GRSP, MWD, and GMD. Pearson’s correlation analysis was used to explore the strength of relationships among HLD, SPD, T-GRSP, EE-GRSP, mass percentage of soil particles, MWD, and GMD. The random forest model was performed to clarify the main factors affecting the stability of soil aggregates using the randomForest function from the randomForest package in R-4.1.1 version [27]. The pathways of Pb pollution affecting the stability of soil aggregates were revealed based on the structural equation model analysis using lavaan package in R-4.1.1 version [28]. 3. Results 3.1. Effects of Pb Stress and AMF Inoculation on Plant Growth The AMF inoculation positively affected the growth and development of the plants under the control and Pb-stress conditions (Figure 1). The shoot dry weight and root dry weight were higher in the mycorrhizal plants than in the non-mycorrhizal plants under all conditions, in spite of the fact that there were no differences in the R/S ratio. Additionally, the AMF inoculation significantly increased the plant height at the Pb 1000 stress level, while no difference was found at the other three Pb stress levels. These findings indicated that the AMF inoculation greatly improved the biomass rather than the height or R/S ratio of the B. parviflora seedlings under Pb-stress conditions. 3.2. Effects of Pb Stress on AMF Growth Parameters The mycorrhizal colonization (MC), hyphal density (HLD), and spore density (SPD) of the AMF increased first, and then decreased with the increase in Pb stress levels (Figure 2). The maximum values of MC, HLD, and SPD were 64.07%, 0.81 m g−1 and 11.5 g−1, and all of them occurred at the Pb 500 level. The MC, HLD, and SPD at Pb 0 levels were significantly higher than at Pb 2000 levels. The Pearson’s correlation revealed that MC (r = −0.593; p = 0.002), HLD (r = −0.831; p < 0.001), and SPD (r = −0.609; p = 0.002) had considerable relationships with the Pb concentration. 3.3. Effects of Pb Stress and AMF Inoculation on Glomalin-Related Soil Protein Content The AMF inoculation increased both the total glomalin-related soil protein (T-GRSP) and easily extractable glomalin-related soil protein (EE-GRSP) contents at all Pb stress levels, whereas the Pb stress exerted harmful effects on the production of glomalin-related soil protein (GRSP) by AMF (Figure 3). There was no significant difference in GRSP content under the control treatment. The correlation analysis showed that the T-GRSP (r = −0.921; p < 0.001) and EE-GRSP (r = −0.827; p < 0.001) in the AMF inoculation treatment were significantly and negatively correlated with the Pb concentration. The results of the two-way ANOVA indicated that the Pb stress and AMF inoculation had significantly interactive effects on the T-GRSP and EE-GRSP (p < 0.001). 3.4. Effect of Pb Stress and AMF Inoculation on Soil Aggregate Distribution The percentage of soil aggregates 2~1 mm, 1~0.25 mm, and 0.25~0.053 mm decreased gradually with the increase in the Pb stress level, while no difference was found at Pb 0 and Pb 500 stress levels (Figure 4). By contrast, the percentage of <0.053 mm soil aggregates increased with the increase in Pb concentration, with a 99% increase at the Pb 2000 compared to the Pb 0 stress level. The change pattern of the percentage of soil aggregates under AMF inoculation treatment was similar to that under non-AMF inoculation treatment, and the percentage of soil aggregates >2 mm, 2~1 mm, and 1~0.25 mm decreased with the increase in Pb concentration. Moreover, the Pb stress enhanced the percentage of soil aggregates <0.053 mm, but had no effect on the percentage of soil aggregates 0.25~0.053 mm. 3.5. Effects of Pb Stress and AMF Inoculation on Soil Aggregate Stability The Pb stress exerted a negative effect on the mean weight diameter (MWD) and geometric mean diameter (GMD), while these were higher under the AMF inoculation treatment compared with under the non-AMF inoculation treatment (Figure 5). The MWD and GMD decreased with increasing Pb concentrations under both the non-AMF and the AMF inoculation treatment. The MWD and GMD were significantly lower at Pb 1000 and Pb 2000 stress levels than at Pb 0 and Pb 500 stress levels. However, no difference in MWD and GMD was observed between Pb 0 and Pb 500 stress conditions. The correlation analysis showed that the MWD (p < 0.001) and GMD (p < 0.001) in both the non-AMF and the AMF inoculation treatment were significantly and negatively correlated with the Pb concentration. Individual Pb stress and AMF inoculation treatments had significant effects on the MWD and GMD, but their interactive effect was not significant on the soil-aggregate stability. 3.6. Correlations between AMF Status, Glomalin-Related Soil Protein, and Stability of Soil Aggregates The results of the correlation analysis showed that there were significant correlations (p < 0.01) between the hyphal density (HLD), spore density (SPD), total glomalin-related soil protein (T-GRSP), easily extractable glomalin-related soil protein (EE-GRSP), mean weight diameter (MWD), and geometric mean diameter (GMD) (Figure 6, p < 0.001). To clarify the important roles of the AMF and GRSP in the stability of the soil aggregates, the random forest model was used to predict the soil-aggregate stability (Figure 7). The model qualified the significance test (p < 0.05) and explained 81.79% of the MWD and 74.28% of the GMD of soil aggregates. The HLD, EE-GRSP, and T-GRSP had significant effects on the stability of the soil aggregates, whereas the HLD and EE-GRSP explained the most important factors for soil aggregate stability, followed by the T-GRSP. 4. Discussion 4.1. Effect of Pb Stress on AMF Growth Parameters and Glomalin-Related Soil Proteins Lead is an extremely dangerous and toxic pollutant for the growth and development of organisms, and it is widely distributed in nature. Pb stress induces the production of large amounts of reactive oxygen species (ROS) in biological cells, mainly including superoxide anion (O2−), hydrogen peroxide (H2O2), and hydroxyl radical (-OH). Small amounts of ROS generated by external stimulation during signal transmission can stimulate signaling pathways, participate in cellular signal transduction processes and activate antioxidant signaling pathways in the body [29]. However, the accumulation of ROS can lead to oxidative stress in cells, causing cell membrane degeneration, ion leakage, lipid peroxidation, DNA/RNA denaturation, and, eventually, cell lysis. In addition, Pb2+ can lead to reduced enzyme activity or even inactivation by both competing for the ion-binding site of the enzyme and inhibiting the active center of the enzyme, further aggravating the accumulation and toxicity of ROS in the cells. In this study, compared with the control treatment (0 mg kg−1 Pb), the hyphal density and spore density of AMF were significantly reduced at medium and high levels of Pb stress (1000 mg kg−1 and 2000 mg kg−1), but there was no significant difference at low levels of Pb stress (500 mg kg−1) (Figure 2). This was mainly due to the oxidative stress response of the AMF cells to medium and high concentrations of Pb stress, and the accumulation of ROS caused lipid peroxidation, cell membrane rupture, and an imbalance in the content and ratio of ions, which finally affected the growth and development of the AMF, resulting in a significant decrease in hyphal density and spore density. However, at low levels of Pb stress, Pb2+ induced an increase in the activities of the AMF cellular antioxidant substances (vitamins, glutathione, etc.) and antioxidant enzymes (oxide dismutase, ascorbate peroxidase, catalase, etc.), which eventually transformed the ROS into harmless H2O molecules through a series of chemical reactions, achieving a balance between ROS production and elimination. It can be seen that the AMF had a certain tolerance to Pb stress, which was closely related to the Pb concentration. When the Pb concentration exceeded 500 mg kg−1, the growth, development, and proliferation of the AMF were significantly inhibited. Additionally, the toxic effect of Pb largely depends on its bioavailability. The slightly alkaline condition (pH = 7.61) in this study might have caused the low mobility of the Pb in the soils, which could also partly explain the low toxic effects of the Pb on the AMF growth parameters [30,31,32]. Glomalin-related soil proteins (GRSP) are a special class of glycoprotein, specifically released by the hyphals and spores of AMF, which are abundant in soil and can be classified into two types: total glomalin-related soil proteins (T-GRSP) and easily extractable glomalin-related soil proteins (EE-GRSP) [12]. GRSPs have a long turnover time in soil and are not easily degradable. They play an important role in promoting soil organic carbon (TOC) accumulation, improving soil water and thermal conditions, improving the stability of soil aggregates, and regulating plant growth and community development. In this study, the T-GRSP and EE-GRSP contents gradually decreased with the increasing Pb stress, while there was no significant difference between the control treatment and the low-concentration Pb-stress treatment (Figure 3). These results were consistent with the pattern of the changes in the hyphal density and spore density of the AMF under Pb stress, indicating that the GRSP was a glycoprotein produced and secreted into the soil by the hyphals and spores of the AMF. A study by Yang et al. showed that both T-GRSP and EE-GRSP contents in AMF inoculation treatments were significantly and negatively correlated with heavy-metal Pb concentration, which was consistent with the results of this study [33]. Nevertheless, the present study found that there was no significant difference in the content of the GRSP (T-GRSP and EE-GRSP). This was mainly because the GRSP was specifically secreted by the AMF, and since there were no hyphals or spores in the uninoculated AMF treatment, no EE-GRSP was produced. 4.2. Effects of Pb Stress on Soil-Aggregate Stability At present, studies on aggregates generally focus on the particle size, composition, and stability, nutrient content characteristics, and organic carbon content of aggregates, but the content and enrichment characteristics of heavy metals in aggregates and their effects on the stability of aggregates are rarely reported [34,35,36]. In this study, it was found that the Pb treatment significantly increased the proportion of soil grains <0.053 mm, while it significantly decreased the proportion of soil grains >2 mm and 2–1 mm, inhibiting the formation of soil macroaggregates (Figure 4), leading to a significant negative correlation between the Pb concentration and the soil-aggregate stability (p < 0.001). This was mainly due to the inhibitory effect of the Pb stress on the growth and development of the AMF (Figure 2), which significantly reduced the glomalin-related soil protein content released into the soil (Figure 3). The glomalin-related soil proteins, as special glycoproteins, played an important role in the formation of soil aggregates, which could bind soil particles together and then gradually form macroaggregate structures through the “bonding–joining–packing” hyphal mechanism, thereby improving the stability of the soil aggregates [37]. Therefore, the reduction in hyphal density and glomalin-related soil protein content caused by Pb stress might be the primary cause of decreases in soil aggregate stability. 4.3. Pathways of Pb Affecting Soil-Aggregate Stability The colonization characteristics of AMF are important factors affecting the stability of soil aggregates. In order to reveal the relationship between AMF and the stability of soil aggregates under Pb stress, previous studies mostly used ANOVA and correlation analysis to analyze the direct relationship between the relevant factors, the mean weight diameter, and the geometric mean diameter while ignoring the complex interactions between these factors and failing to distinguish the possible direct or indirect pathways of action. In this study, we used random forest modeling and structural equation modeling to determine the mechanism through which Pb stress indirectly affects the stability of soil aggregates by impacting the AMF colonization characteristics. The results of the random forest model analysis showed that the hyphal density (HLD), easily extractable glomalin-related soil protein (EE-GRSP), total glomalin-related soil protein (T-GRSP) and spore density (SPD) had significant effects on the mean weight diameter (MWD) (p < 0.05), and the mean square error increases in the four characteristic variables were 6.47%, 6.42%, 5.40%, and 4.46%, respectively (Figure 7). Furthermore, only the HLD, EE-GRSP, and T-GRSP had a remarkable effect on the GMD (p < 0.05), with mean square error increases of 6.32%, 5.80%, and 5.29% for the three characteristic variables, respectively (Figure 7). These results indicated that the HLD, EE-GRSP, and T-GRSP were the dominant factors affecting the stability of the soil aggregates. These findings were consistent with previous findings that AMF colonization characteristics and specific secreted GRSP play an important role in soil-aggregate stability [38]. In this study, we further considered the interaction between multiple factors under Pb stress and used structural equation modeling to reveal the pathway through which Pb indirectly affects soil-aggregate stability through HLD and GRSP (Figure 8). The Pb stress had a negative direct effect on the HLD (−0.831) and GRSP (−0.679), and the GRSP had a positive direct effect on both the MWD (0.956) and the GMD (0.871), but the HLD had a positive indirect effect on the soil-aggregate stability through the GRSP (0.364). This might have been due to the fact that the Pb stress significantly inhibited the growth and development of the AMF, and the hyphal structure was disrupted, releasing a large amount of GRSP into the soil and weakening its direct contribution to the stability of the aggregates. Therefore, in HM-contaminated ecosystems, it is important to focus on maintaining the GRSP content in the soil, thus contributing to the improvement of the soil-aggregate stability and preventing the destruction of the soil structure. 5. Conclusions Medium and high concentrations of Pb stress (>1000 mg kg−1) significantly inhibited the growth and development of AMF, with a significant decrease in MC, HLD, SPD, and AMF-secreted glomalin. Meanwhile, the AMF showed a certain tolerance to Pb stress, and there were no significant differences in the MC, HLD, SPD, and glomalin contents under low concentrations of Pb stress (500 mg kg−1) compared with the control. This was also possibly due to the low availability of Pb under slightly alkaline conditions. The Pb stress increased the mass percentages of fine sand, silt, and clay particles (<0.25 mm), while it decreased the mass percentages of gravel (>1 mm), resulting in a significant negative correlation between the soil-aggregate stability and the Pb concentration. AMF hyphals and glomalin play important roles in the formation of large soil aggregates, and HLD and glomalin content are both significantly and positively correlated with the stability of soil aggregates. According to the random forest model and structural equation model, we further determined that the HLD of the AMF, EE-GRSP, and T-GRSP were the most important factors driving the stability of the soil aggregates, while the Pb stress mainly affected the soil-aggregate stability indirectly, by regulating the HLD and the glomalin. The HLD also indirectly influenced the stability of the soil aggregates by regulating the glomalin. Therefore, focusing on the protection of glomalin and AMF is the key strategy to achieving rapid soil-structure restoration in degraded ecosystems polluted by HM. Acknowledgments We gratefully thank Beitong Huang and Xinyi Liu for field assistance and also to Songtao Yang for assistance with the experiment. Author Contributions Y.L. and Y.Y. designed and conceived the experiment. Y.L., J.X. and X.W. carried out the experiment and collected the empirical data. Y.L., J.H., T.Z. and Y.Y. performed the data analysis. Y.L. and J.X. wrote the paper with contributions from Y.Y. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the National Natural Science Foundation of China (41807052, 42071059) and the National Science and Technology Fundamental Resources Investigation Pro-gram of China (2018FY100300). Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Figure 1 Plant height, shoot dry weight, root dry weight, and root/shoot (R/S) ratio of B. parviflora under different treatments. Dry weight (DW); Pb stress level (0, 500, 1000, and 2000 mg kg−1); non-mycorrhizal inoculation (−AMF); F. mosseae inoculation (+AMF). Data represent mean ± SD for biological replicates (n = 6). The same letter indicates no significant difference (Duncan’s test, p < 0.05). Figure 2 Mycorrhizal colonization (MC), spore density (SPD), and hyphal length density (HLD) of AMF under different Pb−stress levels (0, 500, 1000, and 2000 mg kg−1). Data represent mean ± SD for biological replicates (n = 6). The same letter indicates no significant difference (Duncan’s test, p < 0.05). Figure 3 Total glomalin-related soil protein (T−-GRSP) and easily extractable glomalin-related soil protein (EE−GRSP) contents under different treatments. Non-AMF inoculation (−AMF); AMF inoculation (+AMF); Pb−stress level (0, 500, 1000, and 2000 mg kg−1). Data represent mean ± SD for biological replicates (n = 6). The same letter indicates no significant difference (Duncan’s test, p < 0.05). Figure 4 Soil-aggregate distribution under different treatments. Non-AMF inoculation (−AMF); AMF inoculation (+AMF); Pb stress level (0, 500, 1000, and 2000 mg kg−1). Data represent mean ± SD for biological replicates (n = 6). The same letter indicates no significant difference (Duncan’s test, p < 0.05). Figure 5 The mean weight diameter (MWD) and the geometric mean diameter (GMD) under different treatments. Non–AMF inoculation (−AMF); AMF inoculation (+AMF); Pb stress level (0, 500, 1000, and 2000 mg kg−1). Data represent mean ± SD for biological replicates (n = 6). The same letter indicates no significant difference (Duncan’s test, p < 0.05). Figure 6 Correlation matrix among the selected variables related to AMF growth parameters, GRSP content, and soil-aggregate stability. HLD, hyphal length density; SPD, spore density; T-GRSP, total glomalin-related soil protein; EE-GRSP, easily extractable glomalin-related soil protein; MWD, mean weight diameter; GMD, geometric mean diameter (*** p < 0.001; ** p < 0.01). Figure 7 Random forest variable importance plot. The variables are ranked in order of relevance in predicting soil aggregate stability (MWD and GMD). The importance measure considered for the analysis is the mean decrease in accuracy computed via random forest classification algorithm. HLD, hyphal length density; SPD, spore density; T-GRSP, total glomalin-related soil protein; EE-GRSP, easily extractable glomalin-related soil protein (* p < 0.05). Figure 8 Structural equation model (SEM) illustrating the effects of Pb on soil-aggregate stability, and random forest variable importance score for all analyzed variables. Continuous and dashed arrows represent the significant and non-significant relationships, respectively. Adjacent numbers that are labeled in the same direction as the arrows represent path coefficients, and the width of the arrows are in proportion to the degree of path coefficients. Red and blue arrows indicate positive and negative relationships, respectively. Significance levels are denoted by ** 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. Smith S.E. David J.R. Mycorrhizal Symbiosis Academic Press London, UK 2010 2. Caruso T. Rillig M.C. 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==== Front Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods11091201 foods-11-01201 Article Nutritional Composition of Beach-Cast Marine Algae from the Brazilian Coast: Added Value for Algal Biomass Considered as Waste Mandalka Andrea 12* https://orcid.org/0000-0003-0415-7294 Cavalcanti Maria Irisvalda Leal Gondim 3 Harb Talissa Barroco 4 Toyota Fujii Mutue 3 Eisner Peter 125 https://orcid.org/0000-0003-0223-6124 Schweiggert-Weisz Ute 26 Chow Fungyi 4* Bhunia Arun K. Academic Editor 1 ZIEL-Institute for Food & Health, TUM School of Life Sciences Weihenstephan, Technical University of Munich, 85354 Freising, Germany; peter.eisner@ivv.fraunhofer.de 2 Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Str. 35, 85354 Freising, Germany; ute.weisz@ivv.fraunhofer.de 3 Instituto de Botânica, Av. Miguel Estéfano 3687, São Paulo 04301-902, Brazil; iriscavalcanti@ifpi.edu.br (M.I.L.G.C.); mutue.fujii@gmail.com (M.T.F.) 4 Institute of Bioscience, University of São Paulo, Rua do Matão 321, São Paulo 05508-090, Brazil; talissaharb@hotmail.com 5 Faculty of Technology and Engineering, Steinbeis-Hochschule, George-Bähr-Str. 8, 01069 Dresden, Germany 6 Institute for Nutritional and Food Sciences, University of Bonn, 53115 Bonn, Germany * Correspondence: andrea.mandalka@ivv.fraunhofer.de (A.M.); fchow@ib.usp.br (F.C.) 21 4 2022 5 2022 11 9 120126 11 2021 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/). In some coastal areas, large quantities of beach-cast macroalgae can accumulate and are usually considered waste and disposed of. However, due to their biofunctional and nutritional properties, they have great potential as a new source of raw materials. Increasing population growth has made the search for alternative raw materials with valuable nutritional properties urgent; here, beach-cast macroalgae could provide great potential. Our research goal was to characterize the nutritional profile of 12 beach-cast seaweed species from the Brazilian coast to assess their potential valorization. A considerable number of nutritional compounds was observed, such as ash (6.5–59.3%), total dietary fibers (22.1–65.8%), proteins (5.1–21.5%), and carbohydrates (31.4–81.0%), with an expressive abundance of minerals, free amino acids, and fatty acids. Spatoglossum schroederi and Alsidium seaforthii showed protein contents of 21.5 ± 0.2%, 19.7 ± 0.1%, and high amounts of total dietary fiber of 59.2 ± 0.4%, 61.7 ± 4.9%, respectively. The overall profile suggests that beach-cast seaweeds are suitable for nutritional and other bioeconomical purposes, to which different species with different characteristics contribute. Contamination of these seaweeds with unwanted toxic compounds like micropollutants was not studied. However, this must be considered before they are used for human consumption. amino acids fatty acids food functional ingredient raw material seaweeds ==== Body pmc1. Introduction Population growth together with increasingly limited or overused arable lands and freshwater resources has led to the need for alternative protein sources and raw materials with valuable nutritional properties. Presently, plant proteins are primarily produced by land crops. Macroalgae, which do not compete with traditional food crops for agricultural land, is still underutilized and could provide a valuable, fast-growing protein source together with other nutritious components [1,2,3,4]. Several studies have shown that macroalgae have an interesting nutritional and chemical composition; particularly, red and green seaweed species are gaining interest as protein-rich foods for human consumption and as sources of protein biofunctional peptide components [5,6,7,8]. Seaweeds may contain up to 47% of protein on a dry weight (dw) basis, comparable to those of soybean (47–52%) and lupine (39–55%) [9,10]. They are increasingly recognized as a natural source of proteins, dietary fibers, polysaccharides, polyunsaturated fatty acids (PUFA), minerals, vitamins, pigments, and phytochemicals, such as polyphenols [11,12,13]. In addition, it is known that the chemical composition of macroalgae as well as their nutritional and medicinal value depends on many factors, such as species and their development stages, geographic origin or growing area, habitat, season, environmental conditions, time of harvest, and processing methods, such as various sampling procedures and drying methods [14,15,16,17,18]. Many studies have revealed that their potentially bioactive peptides might have protective effects against allergies, cancer, cardiovascular disease, degenerative diseases, diabetes, digestive disorders, hypertension, inflammation, obesity, and oxidative stress [17,19]. In 2019, seaweed cultivation production increased to 35.8 million tons, which account for 97% of the world’s seaweed production (FAO 2021) [20]. The global use of macroalgae-derived products is now a multi-billion dollar industry. These products are mainly techno-functional polysaccharides, for example, the phycocolloids agar, carrageenans, and alginates for food, cosmetic, and pharmaceutical industries, or fertilizers and feed ingredients. As there are only a few macroalgae species suitable for aquaculture production, and predatory extractive harvesting from natural stocks is no longer a globally accepted practice, many researchers and companies have now focused on the search for new species for aquaculture, natural seabed management, or other available seaweed materials [21,22]. Many studies [23,24,25,26] report the potential nutritional or bioactive content of various algae species worldwide, but there are only a few studies on Brazilian beach-cast algae. Their chemical composition has not been sufficiently investigated [27,28,29,30,31]. Brazil has an insignificant share of the global seaweed market, although the Brazilian coastal area has an excellent potential for collecting beach-harvested seaweeds [27,30,31]. However, every year, tons of beach-cast seaweeds are removed from the beach by local authorities as part of beach cleaning operations and disposed of into landfill sites as part of urban waste [32,33,34]. Despite the richness of the algal flora in Brazil, they are rarely used—only in coastal regions as fertilizer.Since beach-cast algae tend to cover large areas of the coast, harming the local tourism industry and fisheries, their collection could have great potential for exploiting the unused biomass for new marine-related industries in Brazil. Their collection could increase the value of macroalgae, for which there is currently no adequate market price in Brazil. Species richness as well as their abundance are essential information for bioprospecting, uses for beach-cast macroalgae, and the gaps in the studies are pointed out by Harb et al. and Cavalcanti et al. [35,36]. Current production or use of chemicals from seaweeds is focused on a few macroalgae species and individual products, such as hydrocolloids or xanthophylls with little to no use for the remaining biomass. Still, there are still thousands of unexamined species that contain important nutrients such as proteins, minerals, fibres, fatty acids, and other useful bioactives, and could serve as a future alternative food source. Screening the biochemical composition of beach algae would be the first step to determine the potential of these algae for further exploitation [26,37]. This study investigates the nutritional value of Brazilian locally abundant beach-cast seaweeds to evaluate their use as potential biofunctional food ingredients. These findings could also reveal species with a high nutritional value that has not yet been harvested or cultivated [20]. Due to the diversity of algae and the general abundance of species, some species may have a previously unknown potential for value-added ingredients. We selected biomass of twelve abundant beach-cast algal species from the Brazilian coast. We characterized the nutrient profile of the algae to evaluate their potential use as food or other dietary supplements and to assess their potential as a regional and sustainable biomass source. To our knowledge, there are no studies that have previously published proximate composition, dietary fibers, minerals, polyunsaturated fatty acids (PUFA), free amino acids, and protein solubility on the algal species analyzed here. Furthermore, beach-cast algae are an underutilized and underestimated valuable biomass that should be considered a sustainable source of bioactive compounds in the future. However, an important aspect for the exploitation of seaweeds as a healthy or functional food ingredient is the need to identify and quantify heavy metals and other toxic compounds such as pesticides, which could be absorbed from the seawater. Contamination of seaweeds with these unwanted toxic compounds depends on habitat or ecology. More studies of heavy metal toxicokinetics are needed and food safety awareness needs to be raised for a beneficial and safe algae consumption [13]. 2. Materials and Methods 2.1. Sample Collection and Species Identification Twelve different abundant biomass species of red, brown, and green beach-cast macroalgae were collected from the southeast and northeast beaches of the Brazilian coast (Table S1). The seaweeds were collected using systematic sampling, in which only visible healthy individuals were selected. The material was rid of macroepiphytes, washed with abundant tap water, and air-dried under a shade. The pre-dried samples were transported to the laboratory, air circulation oven-dried at 40 °C, and then powdered in a ball mill (MA350, Marconi, Brazil). Three fresh specimens for each species were separated for exsiccates and deposited in the SPF Herbarium (Phycological Section) at the University of São Paulo and the Herbarium of the Instituto de Botânica, São Paulo (SP), Brazil (Table S1). Taxonomic identity was confirmed by Maria Irisvalda Leal Gondim Cavalcanti and Mutue Fujii, both from the Instituto de Botânica, São Paulo, Brazil. 2.2. Proximate Composition Dry matter content (105 °C), ash content (950 °C), and protein content were determined according to AOAC Official Methods [38,39] by means of a thermogravimetric method (TGA 701 Leco, St. Joseph, MI, USA) and the Dumas combustion method (TruMac N, Leco Instruments, Mönchengladbach, Germany), respectively. The organic nitrogen content was quantified, and the total protein content was calculated using the nitrogen-to-protein conversion factor N × 6.25, since the recent study by Angell et al. [2] showed that species-specific factors are rarely used for algae and most authors resort to the traditional conversion factor of 6.25 to allow comparisons to previous studies [40], despite the fact that many studies show that this factor leads to an overestimation of the protein content in macroalgae [41,42,43]. Therefore, we calculated a more accurate estimate of protein content as 5.13 for brown, 3.99 for red, and 4.24 for green algae, respectively, as shown in supplemental Table S2 [44,45]. Total carbohydrates were calculated by the difference, subtracting ash, moisture, total lipid, and protein contents from 100%. Soluble carbohydrates were obtained using three-time aqueous extraction for 2 h each at 70 °C and determined using the phenol-sulfuric acid method [46] by absorbance read at 490 nm. Soluble carbohydrates were calculated by referring to the galactose standard curve. Dietary fiber analysis. Soluble (SDF), insoluble (IDF), and total (TDF) dietary fibers were determined according to the enzymatic-gravimetric method AOAC 993.19 and 991.43 (AOAC, 2016 as provided by Megazymes International Ireland, Bray County Wicklow, Ireland) Soluble (SDF), insoluble (IDF), and total (TDF) dietary fibers were determined using Fibertec. Mineral composition. Macro (N, P, Ca, K, Mg, and Na) and micro (Fe) elements as well as trace metals (Cd, Cu) were determined by hydrolysis with concentrated HNO3 and H2O2 30% (v/v) in a thermal digester block (DigiPrep, SCP Science, Champlain, USA) and an Inductively Coupled Plasma Optical Emission Spectrometry technique (ICP-OES Spectro Arcos, Spectro Analytical Instruments GmbH, Kleve, Germany). Free amino acids. A free amino acid profile was analyzed according to Santa-Catarina, et al. [47] with some modifications. Samples were extracted using 6 mL ethanol (v/v) 80% for 2 h, and the supernatants were concentrated under a speed-vacuum. The concentrated sample was re-suspended in 2 mL ultrapure water. The suspension was filtrated using a 0.2 µm Millipore membrane. Amino acids were derivatized with o-phthaldialdehyde (OPA) and identified through HPLC (Shimadzu Shin-pack CLC ODS) using a C18 reverse-phase column (Supelcosil LC-18, 25 cm × 4.6 mm/L × i.d.). The gradient was developed by mixing increasing proportions of 65% methanol to a buffer solution (50 mM sodium acetate, 50 mM sodium phosphate, 20 mL/L methanol, 20 mL/L tetrahydrofuran, and pH 8.1 adjusted with acetic acid). The gradient of 65% methanol was programmed according to Egydio et al. [48]. Fluorescence excitation and emission wavelengths were 250 nm and 480 nm, respectively. Peak areas and retention times were measured by comparison with known quantities of standard amino acids (Sigma-Aldrich, Louis, MO, USA). Fatty acids. Fatty acid content was determined according to the Büchi Caviezel method, where the measurements of the fatty acids were based on a gas chromatographic separation (Agilent 7890A GC system, Agilent Technologies, Waldbronn, Germany, column ZB FFAP Phenomenex, length 15 m × 0.25 mm × 0.25 µm), and detection by a flame ionization detector. The method considers the free and bonded fatty acids from C4 to C24 with a content of 0.1 to 100% regarding the total content of fatty acids in the sample expressed as triglycerides. A defined amount of oil was saponified with potassium hydroxide. Potassium salts of the fatty acids were converted to their free fatty acids by the addition of sodium hydrogen phosphate. Free fatty acids were quantified by gas chromatographic analysis (carrier gas hydrogen 5.0; combustible gases hydrogen and, synthetic air, start temperature 160 °C, temperature gradient 25 °C/min., end temperature 250 °C). The quantification of the total fat content is based on the ratio between the sum of the peak areas of the detected fatty acids and the peak area of the internal standard. 2.3. Protein Solubility Protein solubility (%) was determined in duplicate according to a standardized method based on Morr et al. [49] for pH values from two until 13. For each measurement, a 1.5-g macroalgae sample was suspended in 50 mL 0.1 M NaCl, and the pH was adjusted with 0.1 M NaOH or 0.1 M HCl, respectively. After stirring for 1 h at room temperature, the non-dissolved fractions of the samples were separated by centrifugation (20,000× g, 15 min, room temperature), and the supernatants were passed through a Whatman No. 1 filter paper to remove any remaining particulates. The protein content of the supernatant was determined following the Dumas method described in Section 2.2. 2.4. Statistical Analysis The analytical determinations were conducted at least in triplicate, except for protein solubility, which was conducted twice. Values were expressed as mean ± standard deviation (SD) in percentage based on a dry weight (dw) content unless stated otherwise. One-way Analysis of Variances (ANOVA) was conducted followed by a Student–Newman–Keuls (SNK) test to determine the significant differences (p < 0.05) among the samples using the software Statistic v.10, by StatSoft, Hamburg, Germany. Additionally, pairwise multiple comparisons with a Euclidean cluster based on Pearson’s correlation were conducted for the global integration of nutritional composition, and the best score was compared for each species using the software PAST version 3.2, Oyvind Hammer, São Paulo, Brazil. The hierarchical cluster analyses were associated with heatmaps, in which raw data were log-transformed followed by correlation and cluster analyses. 3. Results and Discussion 3.1. Sample Collection and Species Identification The beach-cast algae collected from the Brazilian northeast and southeast coasts exhibited great diversity in species: eight red macroalgae (Rhodophyta), three brown macroalgae (Phaeophyceae, Ochrophyta), and one green macroalgae (Chlorophyta) (Table S1). 3.2. Proximate Composition The proximate composition is summarized in Table 1 and Supplementary Figure S1. Dry matter exhibited slight magnitude variation ranging from 89.0 ± 0.1% (Halymenia brasiliana) to 94.9 ± 0.3% (Gracilaria domingensis). The ash content of red beach-cast seaweeds ranged from 25.8 ± 0.2% to 58.3 ± 0.4%, while brown beach-cast seaweeds showed the lowest ash content of 6.5 ± 0.6% to 20.4 ± 0.8%. The ash content was highest in the green macroalga Codium isthmocladum (59.3 ± 1.5%) and in the red macroalga Botryocladia occidentalis (58.3 ± 0.4%). The ash content in seaweeds is high compared to plant vegetables. It includes macro-minerals and trace elements that show seasonal and environmental variation in the composition as described by Holdt and Kraan [16]. The protein content of macroalgae varies according to the species, environmental conditions, habitats, maturity, and seasonal differences, but are low in most brown seaweeds (three to 15%), moderate in green seaweeds (nine to 26%), and can attain 47% in red seaweeds [50,51,52,53]. The protein content varied within the species under study (Table 1, Figure S1) from 7.3 ± 0.1% to 19.7 ± 0.1% for red specimens, 10.9 ± 0.4% to 21.5 ± 0.2% for brown specimens, and lowest protein content of 5.1 ± 0.1% for the green alga Codium isthmocladum. It is worth noting that Spatoglossum schroederi attained 21.5 ± 0.2% protein content, an expressive protein amount for brown macroalgae. The protein content determined for the red and brown macroalgae in this study was similar to that found by other authors [11,18,51]. All these studies calculated the protein content taking 6.25 as a nitrogen-to-protein factor as done in our study for a better comparison. As described in the Materials and Methods section, we also used taxa-specific conversion factors for protein calculation and the data are shown in supplemental Table S2. Each seaweed class produces specific polysaccharides building the composition of the fibrillary and matrix-associated components of the cell wall as well as the storage carbohydrates. The amount of polysaccharides in seaweeds can reach up to 76% [16,54,55]. Tenorio et al. [10] determined a carbohydrate amount of 12% for red, 21% for brown, and 8% for green seaweeds. The analysis of beach-cast samples exhibited total carbohydrate content ranges from 31.4 ± 0.5% to 81.0 ± 0.7% (Table 1, Figure S1). The red seaweeds showed 31.4 ± 0.5% to 60.6 ± 0.3% of total carbohydrates, while total carbohydrates in brown seaweeds range from 59.1 ± 0.2% to 81.0 ± 0.7% and green macroalga Codium isthmocladum is 35.6 ± 1.5%. The total carbohydrate content of Halymenia brasiliana is comparable to that of the three Halymenia species from the Philippines (40.53–53.65%) as reported by Critchley et al. and Hurtado et al. [33,56]. The minimum number of soluble carbohydrates was determined to 5.3 ± 0.1 µg galactose/mg for Codium isthmocladum. The highest amount was found in Dictyopteris jolyana with 146.0 ± 0.1 µg galactose/mg (Table 1, Figure S1). Gracilaria domingensis with a soluble carbohydrate amount of 113.5 ± 0.1 µg galactose/mg is an agarophyte species with high agar yield and low agar strength explored in the Brazilian northeast as a source for the agar industry. These data suggested that red and brown beach-cast seaweeds from Brazil could be a good potential source of protein (respectively 19.7% and 21.5%) and carbohydrates (respectively 60.6% and 59.1%). 3.2.1. Dietary Fibers Seaweeds are rich in dietary fibers (>30%), particularly, in the soluble form, values that frequently exceed those of fruits and vegetables [11,17,57]. Tenorio et al. [10] determined the TDF amounts of 38% for red seaweeds, 36% for brown, and 38% for green seaweeds. Depending on the seaweed phyla, different types of dietary fibers exist. For red seaweeds (Rhodophyta), the soluble fibers are sulfated galactans (agar and carrageenans) or soluble xylans, which are components of the amorphous external cell wall matrix, such as small amounts of cellulose, xylans, galactans, hydroxyproline glycosides, mannans, and fucoidans depending on the taxa. For brown seaweeds (Phaeophyceae), the soluble fibers are alginates, fucans, and laminarans. Insoluble fibers are essentially composed of cellulose, except for some red alga, which consist of insoluble mannan and xylan [17,58,59]. The content of TDF in this study ranges from 22.1 ± 0.2 g/100 g to 65.8 ± 1.1 g/100 g (dry weight). In red seaweeds, TDF ranges from 25.0 ± 0.2 g/100 g to 46.8 ± 0.3 g/100 g. The brown seaweeds showed TDF amounts of 54.5 ± 2.3 g/100 g to 65.8 ± 1.1 g/100 g and Codium isthmocladum exhibited a TDF content of 22.1 ± 0.2 g/100 g. Dictyopteris jolyana and Alsidium seaforthii contained the highest TDF contents with 65.8 ± 1.1 g/100 g and 61.7 ± 4.9 g/100 g, of which 46.4 ± 1.0 g/100 g and 33.5 ± 0.6 g/100 g is SDF, while Codium isthmocladum had the lowest TDF content of 22.1 ± 0.2 g/100 g with 4.7 ± 0.5 g/100 g SDF. These results are consistent with other studies [17,56,60]. More than half of the investigated macroalgae have higher soluble fiber content than insoluble fiber content. Spatoglossum schroederi, Zonaria tournefortii, Botryocladia occidentalis, and Codium isthmocladum exhibited higher insoluble fiber content than soluble ones. The insoluble and soluble dietary fiber content (IDF and SDF) ranges between 5.1 ± 0.9 g/100 g to 46.2 ± 0.3 g/100 g and 4.7 ± 0.5 g/100 g to 46.4 ± 1.0 g/100 g, respectively (Table 1, Figure S1). Water-soluble and water-insoluble fibers have different physiological effects [5,19,61]. This high content of insoluble dietary fiber indicates a beneficial nutritional effect and thus the need to develop attractive fiber-based seaweed products. 3.2.2. Mineral Composition Seaweeds are known for their high mineral content, which is even 10–100 times higher than that of land vegetables [16,62,63]. This high content of minerals and trace elements is attributed to their ability to bind and accumulate inorganic components on the cell wall polysaccharides. [5,25,64]. Most macroalgae have high calcium, magnesium, potassium, sodium, and iron contents [12,63]. These elements were determined in all collected species (Table 2, Figure S2). A wide variation in mineral content was observed among the samples. High calcium content was observed in Alsidium triquetrum of 7.24 ± 0.01% and for Alsidium seaforthii 5.94 ± 0.05%. All red macroalgae contain an extraordinary level of potassium from 4.39 ± 0.01% for Alsidium seaforthii to 11.18 ± 0.06% for Agardhiella ramosissima, which is similar to the natural plasma level [12]. Notably, Codium isthmocladum possesses high magnesium content of 2.11 ± 0.01% and high sodium content of 14.90 ± 0.01%. The average content of iron followed the order Phaeophyceae (316.57 ± 1.88 ppm to 2306.33 ± 15.58 ppm) higher than Rhodophyta (112.72 ± 0.60 ppm to 1879.26 ± 24.36 ppm) and higher than Chlorophyta (310.40 ± 10.84 ppm). The level of minerals detected (Table 2) also fit within the ranges observed in previous reports in seaweeds [63]. Some of the analyzed seaweed species may be seen as good sources of calcium, potassium, magnesium, and iron. Cadmium and copper were not detected. Due to the high mineral content, algae could be a valuable addition to the dietary supplement. However, the linkage of certain minerals with anionic polysaccharides (alginate, agar, or carrageenan) might limit the absorption of these minerals [12]. 3.2.3. Free Amino Acids Most seaweeds contain all essential amino acids at proportions comparable to traditional protein sources used for animal feed, such as soybean meal and fishmeal [2,5]. These amino acids occur as protein constituents and as free amino acids or salts of free amino acids. Free amino acids and peptides are key determinants in food taste, like L-glutamate, which is recognized for Umami taste and is rich in cheese, tomato, and kelps [65]. Other amino acids (alanine and glycine) also contribute to the distinct flavors of some marine algae [16]. As widely described, aspartic and glutamic acids constitute a large part of the amino acid fraction in seaweeds, while tryptophan is the first limiting amino acid in algae proteins. Generally, amino acid composition fluctuates seasonally as affected by environmental conditions and can also vary interspecifically [6,11,66,67]. The content, and the type of proteinaceous molecules, such as peptides and free amino acids, depends on several factors such as available light, salinity, temperature, wave force, nutrient and mineral availability, and carbohydrate levels [68]. Table 3 and Supplementary Figure S3 present the mean values from the analysis of free amino acid contents by HPLC. While aspartic acid (Asp), citrulline (Cit), glutamic acid (Glu), ornithine (Orn), serine (Ser), and tryptophan (Trp) are the most abundant free amino acids in brown seaweeds, red seaweeds possess a high amount of arginine (Arg), Asp, Cit, Glu, Orn, Ser, and Trp. The green species Codium isthmocladum showed a high amount of Arg, Asp, Cit, Glu, Leu, Ser, and Trp. The most significant observation pertains to the content of Cit that, for most species, is significantly higher than the contents of the other free amino acids. Citrulline is a common byproduct of other amino acids, such as Orn and Arg. Like other amino acids, they play many vital functional roles, such as the building of proteins, the synthesis of hormones, and neurotransmitters. The total free amino acids found in the beach-cast algae ranged from 290.4 ± 122.6 µg/g to 11,307.5 ± 4631.8 µg/g with a considerable wide variety of composition profiles and abundant characteristics for each material. Therefore, considering the functional role of free amino acids, immediate availability, and possible seaweed supplementation as a natural source, some species studied here can be proposed as natural amino acid stock. 3.2.4. Fatty Acids Lipids represent up to 4% of the seaweed, and relatively low content of saturated fatty acids, as well as a substantial amount of PUFA, as compared to land vegetables [56]. Lipid levels and composition, including fatty acid profiles, vary according to a taxonomic entity, season, geographic regions, and growth conditions [56]. Marine lipids consist of a substantial number of long-chain PUFAs, with n-3 fatty acids as the significant component and mono-unsaturated fatty acids [16]. PUFAs greater than C18 are abundantly found in marine species, with green algae being rich in C18 PUFAs (ALA, STA, and LA) and red algae being rich in C20 PUFAs (AA and EPA), while brown algae exhibit both appreciable amounts [5,69,70]. The fatty acid composition of the seaweeds under study is shown in Table 4 and Figure S4. In all analyzed seaweeds, palmitic acid (C16:0) was the single most abundant saturated fatty acid. The content of C16:0 was highest in Agardhiella ramosissima with 62.77 ± 10.63 g/100 g, and lower levels were found in Dictyopteris jolyana with 21.05 ± 1.05 g/100 g. Furthermore, the macroalga varieties had minor levels of myristic acid (C14:0) ranging from 1.92 ± 0.21 g/100 g to 14.01 ± 0.77 g/100 g. In agreement with other studies, the most abundant fatty acid in the algae, apart from C16:0, was C18:1, which was not detected in Agardhiella ramosissima [31,71,72]. Eight seaweeds also contained the essential fatty acids C18:2 (linoleic acid) and C18:3 (linolenic acid). Since humans are incapable of synthesizing PUFAs with more than 18 atoms of carbon, n-3 PUFAs are of nutritional importance and must be added as a dietary supplement or as part of a balanced diet [72]. 3.3. Protein Solubility Macroalgae have a robust polysaccharide-rich cell wall, and the cell wall mucilage reduces protein extractability. The extractability of proteins is influenced by both the ionic interactions between the cell wall and the proteins as well as the high viscosity exerted via the polysaccharides in a water solution [73]. Hence, the pH had a significant influence on the solubility of the seaweed proteins. Several studies have shown that the extractability and recovery of seaweed proteins could be increased with the pH-shift process, using alkaline protein solubilization followed by isoelectric precipitation, an efficient way to produce extracts with high protein concentrations [53]. The protein solubility in water at pH values between pH 2 and pH 13 was measured (Table 5). The protein solubility increased with increasing pH in all species. This was also reported by Harrysson et al. [71] and Vilg et al. [74] for Porphyra sp., Ulva sp., Saccharina sp. The maximum solubility of 54.8 ± 1.8% and 52.5 ± 1.5% was achieved at pH 13 for Alsidium seaforthii and Gracilaria domingensis, respectively (Table 4, Figure S5). Both red algae species also exhibited high protein contents of 19.7% and 16.8%, respectively. Lowest values for solubility at pH 13 were observed for Dictyopteris jolyana (25.3%), Spatoglossum schroederi (26.3%), and Spyridia clavata (26.0%). The brown algae Spatoglossum schroederi also showed a comparative high protein content of 21.5 ± 0.2%, but a very low protein solubility of 26.3 ± 1.3% at pH 13. The solubility decreased with declining pH and finally reached a plateau at pH 6–8 with a maximum protein solubility of 35% up to 42% for some studied algae. The protein solubility curve of macroalgae differs from that of legumes, whose solubility curves show a minimum at pH 4–6 (isoelectric point) [75]. These differences result from the type of protein extracted. Legume proteins are storage proteins, whereas alga proteins are mainly structural proteins, enzymes, or chromoproteins, which result in different solubility properties [74]. 3.4. Integrated Cluster Analyses and Heatmaps Biplot hierarchical Euclidean clusters were conducted on the basis of subgroups of chemical characterization associated with heatmaps: proximate composition (Figure 1A), macro (Ca, K, Mg, and Na) and micro (Fe) elements (Figure 1B), amino acid profile (Figure 1C), and fatty acid composition (Figure 1D). From the proximate composition, three subclusters were identified (Figure 1A):(a) an isolated set by the brown alga Dictyopteris jolyana with high amounts of TDF, SDF, and carbohydrates, and moderate amounts of IDF and proteins; (b) a set including red and brown algae with variable number of parameters from high, moderate, and low; (c) a set comprising the red alga Botryocladia occidentalis and green alga Codium isthmocladum with moderate to low values, except for ash content. Large amounts of TDF, especially the IDF, are a preferable feature as health-promoting benefits for gut bacteria [76], in which almost all beach-cast seaweeds from this study exhibited high to moderate contents. The fiber fraction from the beach-cast material contain polysaccharides of high molecular weight that are insoluble in water, except in hot water [16]. They are not found as free carbohydrates, since the soluble carbohydrate content was low. This trait is an interesting advantage, as these fibers can be available after passing through the digestive tract or through specific treatments for their extraction. Therefore, all species studied are profitable sources of dietary fibers, except for Codium isthmocladum, which showed higher ash content associated with an elevated number of minerals, suitable for different applications than dietary fiber sources. A high mineral content is a characteristic of many seaweeds [16,62,63]. From the cluster analysis (Figure 1B), a wide variation was observed for macro (Ca, K, Mg, Na) and micro elements (Fe). A notable observation is the high concentration of magnesium and sodium in Codium isthmocladum, which is of nutritional concern if consumed in excess. All other beach-cast algae, however, possess lower levels of sodium. Other macro and microelements can be appreciated from sources of marine algae as described in our results. As the mineral cluster, the beach-cast seaweeds exhibited a broad variation in free amino acids (Figure 1C). From the cluster, we can identify four major sets:(a) one with relatively small amounts of amino acids, such as Gracilaria domingensis, Spatoglossum schoroederi, Codium isthmocladum, and Agardhiella ramosissima; (b) an alone set by Alsidium triquetrum with high levels of half of the amino acids; (c) a major set with moderate to a high concentration of almost all amino acids, and (d) an alone set by Osmundaria obstusiloba exhibiting high levels of almost all amino acids. This wide amino acid profile is an important feature for the natural ingredient industries. Amino acids like L-glutamate are determinants in Umami taste, typically of Asian cuisine. An important highlight of the amino acid profile from this study represents the quantification of free amino acids; therefore, their immediate availability can make the valorization of beach-cast seaweed supplementation as a natural source of amino acids possible. Seaweeds are not commonly seen as a source of lipids or fatty acids, since lipids represent only up to 4% of the dry matter. Nonetheless, despite their small amounts, they are seen as potential sources of certain fatty acids, especially PUFAs that humans can not synthesize. PUFAs with 18 carbon atoms are of nutritional importance and must be added as a diet, in which the beach-cast seaweeds showed relevance in these fatty acids (Figure 1D), with species exhibiting a large amount of almost all fatty acids and others with high concentrations of half of the fatty acids. 4. Conclusions The data from this study did not show a clear pattern between the phyla and the composition of the individual nutrients. Interesting nutritional profiles were highlighted for Spatoglossum schroederi and Alsidium seaforthii with appreciable protein contents of 21.5 ± 0.2%, 19.7 ± 0.1%, respectively, and high amounts of total dietary fiber of 59.2 ± 0.4%, 61.7 ± 4.9%, respectively, and low ash, and low soluble carbohydrate content. Dictyopteris jolyana revealed the highest amount of TDF (65.8 ± 1.1%), SDF (46.4 ± 1.0%), and total and soluble carbohydrates of 81.0 ± 0.7%, 146.0 ± 0.1 µg galactose/mg on dry mass basis, respectively, compared to the other studied species. The free amino acid composition was highest for Alsidium triquetrum and Osmundaria obtusiloba. Additionally, Osmundaria obtusiloba exhibited high levels of PUFA. These algae are promising for aquaculture cultivation to provide valuable raw materials for future production of functional ingredients for the food industry. The controlled cultivation of beach-cast algae species has huge potential to contribute to a sustainable, environmentally-friendly local marine industry. One of the main challenges in realizing this vision is the development of controlled growing conditions for these algae species in aquaculture. For the extraction of individual compounds as food ingredients, more cost-effective extraction and isolation/concentration methods need to be developed. In addition, undesirable components such as off-flavors and colorants must be removed to increase their sensory perceptions and usability for the food industry. Acknowledgments The authors would like to give special acknowledgement to Cia das Algas for the logistic collection support. Thanks are also due to Sigried Gruppe and Naciye Keklik (Fraunhofer IVV) for experimental contributions in addition to special thanks to Eny I.S. Floh and Amanda Macedo for technical support of amino acids analysis. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/foods11091201/s1, Table S1. Summary of the beach-cast algae collected from southeast and northeast beaches, Brazil. CE: Ceará State, northeast coast. ES: Espírito Santo State, southeast coast. PE: Pernambuco State, northeast coast. Table S2: Proximate composition of beach-cast macroalgae (g/100 g = % and * µg galactose/mg on dry mass basis). Values represent the average of three replicates (mean ± SD) and letters indicate the statistical significance (p < 0.05). Total carbohydrates calculated by difference = 100-total protein-ash. Figure S1. Proximate composition of beach-cast macroalgae. Values represent the average of three replicates (mean ± SD), and letters indicate the statistical significance (p < 0.05). Figure S2. Macro (N, P, Ca, K, Mg, and Na) and micro (Fe) elements as well as trace metals of beach-cast macroalgae. Values represent the average of three technical replicates (mean ± SD), and letters indicate the statistical significance (p < 0.05). Figure S3. Free amino acids composition of beach-cast macroalgae. Values represent the average of three replicates (mean ± SD), and letters indicate the statistical significance (p < 0.05). Figure S4. Fatty acids composition of beach-cast macroalgae. Values represent the average of three replicates (mean ± SD), and letters indicate the statistical significance (p < 0.05). Statistical analysis was conducted only for amounts over 10. Figure S5. Solubility of total proteins from beach-cast macroalgae at different pH levels. Values represent the average of three replicates (mean ± SD), and letters indicate the statistical significance (p < 0.05). Click here for additional data file. Author Contributions Conceptualization, A.M. and F.C.; Methodology, A.M. and F.C.; Investigation, A.M.; Formal and statistical analysis investigation, A.M. and F.C.; Writing—original draft, review and editing, A.M. and F.C.; Supervision, U.S.-W.; Collection, T.B.H., M.T.F., M.I.L.G.C. and F.C.; Identification, M.T.F.; Statistical analysis, A.M., T.B.H. and F.C.; Fiber analysis, A.M.; Soluble carbohydrate analysis, M.I.L.G.C.; Funding acquisition, Project administration, F.C. and P.E. All authors have read and agreed to the published version of the manuscript. Funding This work presented in this manuscript was funded by the Federal Ministry of Education and Research—BMBF) under Grant No. 031B0284. The author is responsible for the content of the publication. T.B.H. thanks CNPq for PhD scholarship (140144/2017-0) and CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Code 001) for funding the postgraduate program in Botany at the Institute of Bioscience. F.C. thanks FAPESP (2018/18015-8, Brazil) and CNPq (303493/2018-6) for research grants. M.T.F. thanks CNPq for the productivity fellowship (Proc. 304899/2017-8). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Heatmap of the biplot hierarchical Euclidean cluster analysis from beach-cast macroalgae for (A) proximate composition; (B) macro (Ca, K, Mg, and Na) and micro (Fe) elements; (C) free amino acid profile (amino acid values < 0.5 are represented as zero); (D) fatty acids composition (not detected fatty acids are represented as zero). Values represent the log transformation. foods-11-01201-t001_Table 1 Table 1 Proximate composition of beach-cast macroalgae (g/100 g = % and * µg galactose/mg on dry mass basis). Values represent the average of three replicates (mean ± SD), and letters indicate statistical significance (p < 0.05). Total carbohydrates calculated by difference = 100-total protein-ash. Species Dry Matter Ash Total Dietary Fibers (TDF) Soluble Fibers (SDF) Insoluble Fibers (IDF) SDF/TDF IDF/TDF Total Proteins Total Carbohydrates Soluble Carbohydrates * Rhodophyta (red algae) Agardhiella ramosissima 92.2 ± 0.2 cd 57.3 ± 0.2 a 40.1 ± 1.5 cd 31.5 ± 2.1 d 8.6 ± 0.7 d 0.79 0.21 7.3 ± 0.1 i 35.4 ± 0.3 i 25.9 ± 0.1 de Alsidium seaforthii 94.5 ± 0.3 a 34.7 ± 1.0 c 61.7 ± 4.9 a 33.5 ± 0.6 d 28.2 ± 4.7 b 0.54 0.46 19.7 ± 0.1 b 45.6 ± 0.9 g 11.9 ± 0.1 de Alsidium triquetrum 92.7 ± 0.1 bc 46.5 ± 0.4 b 45.2 ± 4.8 c 19.3 ± 2.4 e 25.9 ± 2.3 b 0.43 0.57 12.8 ± 0.2 f 40.7 ± 0.5 h 32.3 ± 0.1 d Botryocladia occidentalis 92.7 ± 0.1 bc 58.3 ± 0.4 a 25.0 ± 0.2 e 6.2 ± 0.4 h 18.8 ± 0.6 c 0.25 0.75 10.3 ± 0.2 g 31.4 ± 0.5 j 15.8 ± 0.1 de Gracilaria domingensis 94.9 ± 0.3 a 35.2 ± 0.9 c 45.9 ± 0.8 c 37.5 ± 0.9 c 8.3 ± 0.1 d 0.82 0.18 16.8 ± 0.1 c 47.9 ± 0.8 f 113.5 ± 0.1 b Halymenia brasiliana 89.0 ± 0.1 h 33.7 ± 1.0 c 46.8 ± 0.3 c 41.8 ± 1.1 b 5.1 ± 0.9 d 0.89 0.11 8.2 ± 0.4 h 58.1 ± 1.4 d 30.0 ± 0.1 d Osmundaria obtusiloba 92.9 ± 0.1 b 31.2 ± 0.1 d 36.9 ± 3.5 d 19.8 ± 1.7 e 17.1 ± 1.7 c 0.54 0.46 14.6 ± 0.2 d 54.1 ± 0.2 e 58.9 ± 0.1 c Spyridia clavata 90.8 ± 0.2 g 25.8 ± 0.2 e 33.7 ± 0.2 d 16.0 ± 0.9 ef 17.8 ± 0.9 c 0.47 0.53 13.6 ± 0.2 e 60.6 ± 0.3 c 15.8 ± 0.1 cde Phaeophyceae (brown algae) Dictyopteris jolyana 92.0 ± 0.2 de 6.5 ± 0.6 g 65.8 ± 1.1 a 46.4 ± 1.0 a 19.4 ± 0.2 c 0.71 0.29 12.5 ± 0.2 f 81.0 ± 0.7 a 146.0 ± 0.1 a Spatoglossum schroederi 91.3 ± 0.4 fg 19.4 ± 0.4 f 59.2 ± 0.4 ab 13.1 ± 0.3 fg 46.2 ± 0.3 a 0.22 0.78 21.5 ± 0.2 a 59.1 ± 0.2 cd 16.6 ± 0.1 de Zonaria tournefortii 91.6 ± 0.4 ef 20.4 ± 0.8 f 54.5 ± 2.3 b 10.2 ± 1.8 g 44.3 ± 1.1 a 0.19 0.81 10.9 ± 0.4 g 68.7 ± 0.5 b 19.5 ± 0.1 de Chlorophyta (green algae) Codium isthmocladum 93.1 ± 0.1 b 59.3 ± 1.5 a 22.1 ± 0.2 e 4.7 ± 0.5 h 17.4 ± 0.3 c 0.21 0.79 5.1 ± 0.1 j 35.6 ± 1.5 i 5.3 ± 0.1 e foods-11-01201-t002_Table 2 Table 2 Macro (N, P, Ca, K, Mg, and Na) and micro (Fe) elements as well as trace metals of beach-cast macroalgae (g/100 g = % and * ppm on dry mass basis). Values represent the average of three replicates (mean ± SD), and letters indicate statistical significance (p < 0.05). nd = not detected. Species Ca K Mg Na Fe * Cd Cu Rhodophyta (red algae) Agardhiella ramosissima 0.50 ± 0.01 i 11.18 ± 0.06 a 0.96 ± 0.01 f 2.83 ± 0.01 c 112.72 ± 0.60 j nd nd Alsidium seaforthii 5.94 ± 0.05 b 4.39 ± 0.01 h 0.81 ± 0.01 h 1.72 ± 0.01 e 1879.26 ± 24.36 c nd nd Alsidium triquetrum 7.24 ± 0.01 a 7.76 ± 0.03 c 1.03 ± 0.01 e 2.44 ± 0.01 d 509.17 ± 2.99 h nd nd Botryocladia occidentalis 2.82 ± 0.03 e 5.90 ± 0.01 f 1.74 ± 0.01 b 7.17 ± 0.06 b 1613.59 ± 12.54 d nd nd Gracilaria domingensis 2.29 ± 0.03 f 10.80 ± 0.01 b 0.45 ± 0.01 i 0.65 ± 0.01 i 941.38 ± 14.01 e nd nd Halymenia brasiliana 0.54 ± 0.01 i 7.24 ± 0.03 d 1.12 ± 0.02 d 1.62 ± 0.06 f 153.21 ± 0.49 j nd nd Osmundaria obtusiloba 3.84 ± 0.03 d 6.25 ± 0.02 e 0.44 ± 0.01 i 0.29 ± 0.01 k 832.60 ± 2.24 g nd nd Spyridia clavata 1.70 ± 0.03 g 5.43 ± 0.01 g 1.51 ± 0.01 c 1.04 ± 0.01 g 878.81 ± 14.26 f nd nd Phaeophyceae (brown algae) Dictyopteris jolyana 0.58 ± 0.01 i 0.56 ± 0.01 j 0.33 ± 0.01 j 0.54 ± 0.01 j 316.57 ± 1.88 i nd nd Spatoglossum schroederi 4.31 ± 0.05 c 0.26 ± 0.01 k 0.30 ± 0.01 k 0.15 ± 0.01 l 2021.13 ± 28.13 b nd nd Zonaria tournefortii 2.75 ± 0.01 e 1.28 ± 0.01 i 0.86 ± 0.01 g 0.81 ± 0.01 h 2306.33 ± 15.58 a nd nd Chlorophyta (green algae) Codium isthmocladum 0.93 ± 0.01 h 0.54 ± 0.01 j 2.11 ± 0.01 a 14.90 ± 0.01 a 310.40 ± 10.84 i nd nd foods-11-01201-t003_Table 3 Table 3 Free amino acid composition of beach-cast macroalgae (µg/g on dry mass basis). Values represent the average of three replicates (mean ± SD), and letters indicate the statistical significance (p < 0.05). Species Ala Arg Asn Asp Cit Gln + His Glu Gly Ile Leu Rhodophyta (red algae) Agardhiella ramosissima 0.4 ± 0.1 d 15.4 ± 0.3 c 8.5 ± 0.8 b 12.0 ± 0.8 g 65.8 ± 1.7 d 14.5 ± 0.2 c 11.8 ± 1.1 e 3.2 ± 0.2 c 6.8 ± 0.3 b 30.3 ± 0.2 b Alsidium seaforthii 36.8 ± 14.9 b 4.9 ± 1.5 c 35.7 ± 0.1 b 42.7 ± 6.4 ef 2878.4 ± 211.5 a 8.2 ± 3.3 c 327.1 ± 44.2 b 19.0 ± 7.9 a 2.4 ± 0.5 cd 2.1 ± 0.6 de Alsidium triquetrum 1.2 ± 0.4 d 1682.6 ± 76.7 a 2.6 ± 1.1 b 190.8 ± 5.5 a 0.9 ± 0.5 d 41.1 ± 4.7 b 513.4 ± 9.9 a 16.0 ± 1.7 a 23.7 ± 2.0 a 1.8 ± 0.4 e Botryocladia occidentalis 1.9 ± 0.4 d 2.2 ± 0.4 c 6.3 ± 0.2 b 13.9 ± 1.5 g 9.1 ± 0.9 d 17.6 ± 3.3 c 46.3 ± 3.4 e 3.9 ± 0.6 c 1.4 ± 0.3 d 4.0 ± 0.6 de Gracilaria domingensis 4.0 ± 1.2 d 293.0 ± 78.7 b 4.4 ± 0.9 b 26.3 ± 5.7 fg 8.5 ± 1.6 d 3.9 ± 0.6 c 42.7 ± 9.7 e 8.1 ± 1.9 bc 5.3 ± 0.9 bc 4.3 ± 1.5 d Osmundaria obtusiloba 56.1 ± 5.7 a 2.1 ± 0.2 c 6788.1 ± 751.8 a 139.8 ± 17.4 b 67.4 ± 15.2 d 59.7 ± 8.3 ab 45.8 ± 8.6 e 6.1 ± 1.3 bc 4.1 ± 0.1 bcd 9.9 ± 0.7 c Spyridia clavata 13.6 ± 3.6 cd 2.0 ± 0.5 c 5.9 ± 0.6 b 96.8 ± 5.4 c 416.4 ± 16.7 c 40.8 ± 1.1 b 103.3 ± 3.1 d 1.5 ± 1.9 c 0.9 ± 0.2 d 2.0 ± 0.6 de Phaeophyceae (brown algae) Dictyopteris jolyana 5.8 ± 0.6 d 2.4 ± 0.01 c 51.7 ± 1.0 b 96.0 ± 3.2 c 1832.7 ± 0.1 b 8.8 ± 0.01 c 184.8 ± 0.1 c 13.6 ± 0.01 ab 1.7 ± 0.2 d 2.8 ± 1.3 de Spatoglossum schroederi 4.6 ± 0.1 d 1.3 ± 0.4 c 5.0 ± 0.3 b 44.6 ± 0.1 ef 9.0 ± 4.5 d 15.0 ± 0.01 c 41.2 ± 0.1 e 3.7 ± 0.9 c 2.3 ± 1.5 cd 3.6 ± 0.7 de Zonaria tournefortii 24.9 ± 5.7 bc 1.0 ± 0.3 c 4.9 ± 2.0 b 66.4 ± 0.1 d 24.2 ± 0.1 d 69.0 ± 20.6 a 24.5 ± 0.1 e 1.7 ± 0.4 c 2.0 ± 0.8 cd 2.8 ± 1.2 de Chlorophyta (green algae) Codium isthmocladum 0.9 ± 0.2 d 20.7 ± 0.1 c 5.9 ± 2.3 b 55.8 ± 2.8 de 78.0 ± 0.1 d 18.2 ± 0.9 c 49.6 ± 0.5 e 4.8 ± 1.2 c 6.3 ± 2.5 b 33.7 ± 0.1 a Species Lys Met Orn Phe Ser Thr Trp Tyr + GABA Val Rhodophyta (red algae) Agardhiella ramosissima 15.7 ± 2.7 bcd 0.8 ± 0.2 b 19.8 ± 1.9 e 1.3 ± 0.2 de 46.7 ± 1.6 cde 1.1 ± 0.1 bc 45.8 ± 1.6 cde 2.7 ± 0.3 b 0.7 ± 0.3 e Alsidium seaforthii 2.2 ± 0.6 f 1.0 ± 0.2 b 42.8 ± 3.5 de 7.6 ± 0.4 de 43.9 ± 9.1 cde nd 43.9 ± 9.1 cde 1.8 ± 0.1 b 6.7 ± 1.3 c Alsidium triquetrum 24.6 ± 1.1 b 3.3 ± 1.3 b 67.3 ± 3.9 de 1.0 ± 0.1 de 1128.3 ± 5.2 a 10.1 ± 5.5 a 128.3 ± 5.2 a 0.2 ± 0.1 b 13.0 ± 1.4 b Botryocladia occidentalis 18.0 ± 2.9 bc 0.5 ± 0.2 b 361.7 ± 27.2 b 70.2 ± 9.2 b 2.1 ± 0.5 g 0.2 ± 0.1 c 2.1 ± 0.5 f 1.8 ± 0.5 b 5.8 ± 1.5 cd Gracilaria domingensis 5.4 ± 0.6 ef 732.3 ± 212.7 a 10.8 ± 2.1 e 0.5 ± 0.1 de 91.6 ± 34.6 b 0.9 ± 0.6 bc 91.6 ± 34.6 b 0.8 ± 0.1 b 5.1 ± 1.5 cd Osmundaria obtusiloba 37.9 ± 8.3 a 1.2 ± 0.2 b 814.6 ± 68.2 a 156.2 ± 17.0 a 29.9 ± 4.9 ef 5.6 ± 1.3 ab 29.9 ± 4.9 ef 8.4 ± 1.6 a 22.4 ± 1.0 a Spyridia clavata 4.6 ± 1.4 f 0.5 ± 0.2 b 108.7 ± 0.9 d 18.6 ± 3.9 d 4.2 ± 0.4 g 0.7 ± 0.4 bc 4.2 ± 0.4 f 1.5 ± 0.2 b 3.6 ± 0.6 d Phaeophyceae (brown algae) Dictyopteris jolyana 9.0 ± 0.5 cdef 0.7 ± 0.1 b 289.5 ± 21.4 c 46.8 ± 5.6 c 32.7 ± 5.0 def 1.9 ± 0.1 bc 32.7 ± 5.0 def 1.0 ± 0.1 b 6.0 ± 0.7 cd Spatoglossum schroederi 7.1 ± 4.3 def 1.3 ± 0.7 b 7.3 ± 5.1 e 0.4 ± 0.3 e 64.5 ± 0.0 bcd 0.4 ± 0.3 c 64.5 ± 0.1 bcd 2.0 ± 2.5 b 0.3 ± 0.1 e Zonaria tournefortii 3.1 ± 0.8 f 0.2 ± 0.1 b 50.9 ± 15.9 de 12.7 ± 0.6 de 2.6 ± 1.2 g 1.2 ± 0.2 bc 2.6 ± 1.2 f 4.1 ± 0.5 b 6.7 ± 0.1 c Chlorophyta (green algae) Codium isthmocladum 15.0 ± 4.8 bcde 3.6 ± 3.3 b 17.6 ± 8.5 e 0.7 ± 0.7 de 74.8 ± 5.3 bc 1.0 ± 0.5 bc 74.8 ± 5.3 bc 1.3 ± 0.8 b 0.5 ± 0.4 e foods-11-01201-t004_Table 4 Table 4 Fatty acid composition of beach-cast macroalgae (g/100 g on dry mass basis). Values represent the average of three replicates (mean ± SD), and letters indicate statistical significance (p < 0.05). Statistical analysis was performed only for amounts over 10. nd = not detected. Species 14:0 16:0 17:0 18:0 22:0 24:0 18:1 18:2 18:3 Rhodophyta (red algae) Agardhiella ramosissima nd 62.77 ± 10.63 a nd nd nd nd nd nd nd Alsidium seaforthii 1.92 ± 0.21 g 21.65 ± 0.47 d 3.56 ± 1.43 2.63 ± 0.20 nd nd 10.40 ± 0.87 bcd 4.68 ± 1.05 nd Alsidium triquetrum nd 27.36 ± 0.33 cd nd nd nd nd 7.50 ± 0.31 d 3.24 ± 0.10 nd Botryocladia occidentalis 7.32 ± 0.08 bc 53.58 ± 0.78 b nd 1.11 ± 1.93 nd nd 20.09 ± 0.63 a nd nd Gracilaria domingensis 5.53 ± 0.19 d 68.16 ± 1.15 a nd nd nd nd 8.38 ± 0.10 cd nd nd Halymenia brasiliana 3.32 ± 0.13 f 35.32 ± 1.08 c nd nd nd nd 6.62 ± 0.34 d nd 2.01 ± 1.74 Osmundaria obtusiloba 4.11 ± 0.64 e 21.27 ± 2.50 d 3.52 ± 1.50 4.67 ± 1.05 5.18 ± 2.04 3.14 ± 1.63 9.82 ± 1.69 cd 4.21 ± 1.41 5.86 ± 0.48 Spyridia clavata 4.13 ± 0.32 e 35.50 ± 3.81 c nd 2.45 ± 2.27 3.64 ± 0.00 nd 13.99 ± 1.45 abcd nd nd Phaeophyceae (brown algae) Dictyopteris jolyana 6.89 ± 0.35 c 21.05 ± 1.05 d 0.34 ± 0.58 0.91 ± 0.05 nd 0.37 ± 0.63 17.67 ± 0.90 bcd 7.89 ± 0.40 2.69 ± 0.13 Spatoglossum schroederi 7.86 ± 0.25 b 30.44 ± 1.19 c nd 1.16 ± 0.25 3.54 ± 0.00 0.19 ± 0.16 18.26 ± 0.86 ab 3.93 ± 0.18 2.01 ± 0.06 Zonaria tournefortii 14.01 ± 0.77 a 22.49 ± 1.17 d 0.44 ± 0.75 1.69 ± 0.09 nd nd 15.58 ± 1.24 abc 5.40 ± 0.39 nd Chlorophyta (green algae) Codium isthmocladum 2.20 ± 0.18 g 28.03 ± 2.67 cd nd 1.50 ± 0.12 nd 6.09 ± 0.69 13.66 ± 1.35 abcd 2.36 ± 0.18 2.10 ± 0.19 foods-11-01201-t005_Table 5 Table 5 Solubility of total proteins from beach-cast macroalgae (%) at different pH levels. Values represent the average of three replicates (mean ± SD), and letters indicate statistical significance (p < 0.05). nd = not detected. Species pH 2 pH 4 pH 6 pH 8 pH 10 pH 12 pH 13 Total Proteins Rhodophyta (red algae) Agardhiella ramosissima 27.3 ± 2.5 c 22.4 ± 2.5 cde 34.7 ± 0.1 b 40.9 ± 8.7 a 33.5 ± 1.3 cd 29.8 ± 2.5 d 51.0 ± 1.2 a 7.3 ± 0.1 i Alsidium seaforthii 27.4 ± 4.0 c 39.5 ± 0.9 a 40.4 ± 0.9 a 38.6 ± 0.9 a 40.8 ± 2.2 a 42.2 ± 0.9 b 54.8 ± 1.8 a 19.7 ± 0.1 b Alsidium triquetrum 23.7 ± 0.01 cd 25.9 ± 2.1 cd 25.9 ± 0.7 c 27.3 ± 0.7 b 29.3 ± 0.1 cd 35.6 ± 0.6 c nd 12.8 ± 0.2 f Gracilaria domingensis 32.8 ± 0.5 b 33.9 ± 0.5 a 37.4 ± 0.1 ab 35.9 ± 0.5 a 38.0 ± 1.6 cd 38.5 ± 0.1 bc 52.5 ± 1.5 a 16.8 ± 0.1 c Halymenia brasiliana 18.2 ± 0.1 e 19.4 ± 1.1 de 22.7 ± 0.1 cd 19.3 ± 1.1 cd 20.5 ± 2.3 e 21.6 ± 1.1 e 34.0 ± 2.3 bc 8.2 ± 0.4 h Osmundaria obtusiloba 39.8 ± 1.6 a 37.2 ± 2.1 a 35.0 ± 3.2 b 39.9 ± 0.5 a 32.4 ± 2.7 cd 33.4 ± 3.7 cd 34.0 ± 0.1 bc 14.6 ± 0.2 d Spyridia clavata 27.2 ± 0.7 c 33.2 ± 0.1 ab 42.0 ± 3.3 a 37.2 ± 1.3 a 35.2 ± 3.3 abc 48.6 ± 2.0 a 26.0 ± 0.8 c 13.6 ± 0.2 e Phaeophyceae (brown algae) Dictyopteris jolyana 3.6 ± 0.7 fg 4.3 ± 0.1 f 6.5 ± 0.7 ef 7.3 ± 0.1 ef 6.5 ± 0.7 f 7.2 ± 0.1 f 25.3 ± 0.8 c 12.5 ± 0.2 f Spatoglossum schroederi 0.8 ± 0.1 g nd 2.9 ± 2.1 f 4.2 ± 0.1 ef 5.8 ± 0.8 f 6.3 ± 0.4 f 26.3 ± 1.3 c 21.5 ± 0.2 a Zonaria tournefortii 6.7 ± 0.1 f 15.9 ± 5.9 e 9.2 ± 0.8 e 11.7 ± 1.7 de 24.2 ± 2.5 de 29.2 ± 2.5 d 40.0 ± 6.7 b 10.9 ± 0.4 g Chlorophyta (green algae) Codium isthmocladum nd 1.8 ± 1.8 f 3.5 ± 0.1 f 1.8 ± 1.8 f 3.5 ± 0.1 f 7.0 ± 0.1 f nd 5.1 ± 0.1 j Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091855 nutrients-14-01855 Article Screening for Sarcopenia among Elderly Arab Females: Influence of Body Composition, Lifestyle, Irisin, and Vitamin D Alsaawi Tafany A. 1† Aldisi Dara 1† https://orcid.org/0000-0002-1779-0091 Abulmeaty Mahmoud M. A. 1 https://orcid.org/0000-0002-1493-7297 Khattak Malak N. K. 2 Alnaami Abdullah M. 2 https://orcid.org/0000-0002-5248-2350 Sabico Shaun 2 https://orcid.org/0000-0001-5472-1725 Al-Daghri Nasser M. 2* Cavalier Etienne Academic Editor Bruyère Olivier Academic Editor 1 Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia; tafanyalsaawi@gmail.com (T.A.A.); daldisi@ksu.edu.sa (D.A.); mabulmeaty@ksu.edu.sa (M.M.A.A.) 2 Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia; malaknawaz@yahoo.com (M.N.K.K.); aalnaami@yahoo.com (A.M.A.); ssabico@ksu.edu.sa (S.S.) * Correspondence: ndaghri@ksu.edu.sa † These authors contributed equally to this work. 29 4 2022 5 2022 14 9 185520 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/). Sarcopenia is the loss of skeletal muscle mass, and is most common in older people. The present multi-center cross-sectional study aimed to determine the prevalence of sarcopenia and possible risk factors among Arab elderly females. A total of 131 ambulatory Saudi elderly females aged 60–85 years (mean age 65.9 ± 5.5 years) were recruited to participate. A general questionnaire with questions related to sociodemographic factors, medical history, diet, physical activity, and lifestyle was administered. Anthropometrics and muscle assessments were done. Fasting blood glucose and lipids were measured routinely. Circulating 25(OH)D and irisin levels were measured using commercially available assays. Sarcopenia was assessed using the criteria of the Asian Working Group for Sarcopenia (AWGS). Over-all prevalence of sarcopenia was 19.8% (26 out of 131 participants). Novel measures such as abdominal volume index (AVI), dietary fiber, and irisin were found to be significantly lower in the sarcopenia group than those without sarcopenia, independent of age. No associations were found with physical activity or dietary and lifestyle habits. In conclusion, sarcopenia is relatively common among Arab elderly females. Longitudinal studies are needed to determine whether lifestyle modifications can decrease the incidence of sarcopenia in this population. Irisin maybe a promising biomarker for sarcopenia but needs to be confirmed using larger sample sizes. diet geriatric lifestyle physical activity sarcopenia Deanship of Scientific Research, King Saud UniversityThe authors are grateful to the Deanship of Scientific Research, King Saud University for funding this research project through the Vice Deanship of Scientific Research Chairs. ==== Body pmc1. Introduction Sarcopenia is the gradual and general loss of skeletal muscle mass and strength associated with aging which might lead to serious adverse outcomes such as physical disability and poor quality of life [1]. In 2010, the European Working Group on Sarcopenia in Older People (EWGSOP) established an operational definition and diagnostic criteria for sarcopenia [1]. Subsequently, the Asian Working Group on Sarcopenia (AWGS) adapted its own definition to describe sarcopenia [2]. In 2018, the EWGSOP considered sarcopenia as a muscle disease (muscle failure) [3]. Many factors lead to the progression of sarcopenia and these can contribute to the severity and staging of the reduction in muscle mass, strength, and performance [4]. While older age might be the most important among the reported risk factors, other determinants such as marital status, lifestyle, physical inactivity, poor dietary intake, and diseases (osteoporosis, metabolic diseases, etc.), were also observed to be associated with sarcopenia [5]. Since sarcopenia is a multifactorial syndrome, numerous biomarkers for sarcopenia have been investigated to better understand the different pathophysiologic mechanisms associated with it [6]. Vitamin D level has a well-known effect on muscle performance as it binds to the nuclear vitamin D receptor (VDR) on muscle fibers which leads to an increase in size and hence, improved muscle strength [7,8,9]. Moreover, a recently discovered myokine known as irisin was found to be a strong predictor for sarcopenia [10,11,12,13]. A significant increase or decrease in muscle mass and function from prolonged shifts in muscle protein anabolism, catabolism, or the combination of both processes are controlled by numerous stimuli including physical activity and dietary intake [14]. Furthermore, several studies suggest that with sarcopenia, there is an association between dietary protein intake and physical activity [15,16,17,18,19,20,21,22,23,24]. A systematic review conducted in 37 randomized controlled trials showed that muscle mass and physical activity increased after protein supplementation and exercise interventions [25]. Many studies also suggested the use of anthropometric measurements for the screening of sarcopenia as they were strongly associated with muscle mass strength and performance [26,27,28,29,30,31,32,33]. Despite a surge in sarcopenia research among nations with growing elderly populations, there is scarcity of observational studies in Saudi Arabia and the Middle East in general. To date, studies have been limited to epidemiology and health outcomes, mostly in men [34,35,36,37]. In order to fill this gap, the present study aimed to determine, for the first time in an Arabian elderly female population, the association of dietary intake as well as known markers for musculoskeletal strength such as irisin and vitamin D with sarcopenia. 2. Materials and Methods 2.1. Study Design and Participants In this multi-center cross-sectional study, Saudi females aged 60–85 years with or without sarcopenia were recruited from primary health-care centers (Aldiriyah and Alsalam centers), in addition to community centers (King Salman Social Center and Quran Memorizing Centers) in Riyadh city, Saudi Arabia, from March 2019 to December 2019. Participants who required a cane, wheelchair, or other assistance tools, had artificial limbs or a history of chronic obstructive pulmonary disorder (COPD), congestive heart failure (CHF), chronic renal failure (CRF), active cancer, or cirrhosis liver failure, or had poorly controlled medical problems or refused to participate were excluded. The study was conducted in accordance with the Declaration of Helsinki and was approved by the College of Medicine Institutional Review Board (IRB) in King Saud University, Riyadh, Saudi Arabia (No.19/0300/IRB) as well as by the Ministry of Health (IRB NO.2019-0043E). Written informed consent was provided by all participants prior to inclusion. For the purpose of the present study, participants were stratified according to sarcopenia status. Participants had sarcopenia if they had low muscle mass (muscle mass < 5.7 kg/m2) in addition to low muscle strength (handgrip strength < 18 kg) or low physical performance (TUG < 20 s). Severe sarcopenia was considered if all three criteria were present [2]. 2.2. Demographic and Lifestyle Assessment Demographic data, such as socioeconomic status and medical history were taken from participants through a general questionnaire duly administered by the investigators in designated primary-care centers. Furthermore, a food frequency questionnaire was administered by a certified dietitian to assess macronutrient intake and this was analyzed using Esha food processor software (version 11.7, Esha Research, Salem, OR, USA) [38]. Lifestyle habits and physical activity levels were assessed using the same questionnaire [38]. 2.3. Anthropometric and Body Composition Measurements Anthropometric measurements were carried out by the investigators for all participants. Each participant was asked to stand barefoot on a stadiometer to measure height (cm) to the nearest 0.1 cm followed by a bioelectrical impedance analysis (BIA) (Tanita BC-418, Tanita Co, Tokyo, Japan) to measure weight (kg) to the nearest 0.1 kg. Body mass index (kg/m2) was calculated. Waist circumference (WC) and hip circumference (HC) were measured using a standard tape measure. The mid-arm muscle area (MAMA), mid-arm circumference (MAC), and triceps skinfold-thickness were calculated. The conicity index was determined using the formula (CI = WC (m)/[0.109 × √{weight (kg)/Height (m)}] [39]. The abdominal volume index (AVI) was calculated accordingly [AVI = [2 × (WC)2 + 0.7 × (waist–hip)2]/1000] [40]. 2.4. Muscle Mass, Strength, and Performance Bioelectrical impedance analysis (BIA) (Tanita BC-418, Tanita Co, Japan) was used to determine body composition for each participant. Participants with a muscle mass < 6.4 kg/m2 were considered to have low muscle mass according to the AWGS [2]. Handgrip strength (HS) (Lafayette hydraulic hand dynamometer, USA) was used to measure muscle strength by asking participants to squeeze the hydraulic dynamometer with the right and left hand and the average measure was taken. Low handgrip strength is suggested to be defined as <18 kg for women by the AWGS [2]. Participants’ muscle performance was assessed using a 3 m timed up-and-go test (TUG). Each participant was asked to sit in a chair then rise and walk at normal speed for 3 m and go back to the same seat. The time it took to accomplish the test was recorded, with less than 20 s considered as low muscle performance based on EWGSOP recommendations [1]. All measurements were assessed with the participant standing and in a non-fasting state. 2.5. Biochemical Analysis Five milliliters (5 mL) of fasting blood sample were drawn from each participant by a registered nurse prior to muscle strength assessment. Obtained samples were used to assess fasting glucose and lipid profile using an automated biochemical analyzer (Konelab, Espoo, Finland). Blood samples were centrifuged (3000 RPM for 10 min) then, stored in a −80 °C freezer before the analysis. Total serum 25(OH)D was measured using commercial electrochemiluminescence immunoassay. Intra- and inter-assay coefficients of variations were 4.6% and 5.3%, respectively (Roche Diagnostics, Penzberg, Germany), while commercially available assay (Biovendor, Karasek, Czech Republic) was used to assess circulating irisin levels (intra- and inter-assay coefficients of variations were 6.9% and 9%, respectively), as performed in previous investigations [41,42]. All biochemical analyses were performed in the Chair for Biomarkers of Chronic Diseases (CBCD), King Saud University, Riyadh, Saudi Arabia. 2.6. Statistical Analysis The sample size was derived based on the protective odds against sarcopenia among individuals engaged in high-level activities (OR, 0.29; 95% CI, 0.15–0.56) [22]. The required sample size was N = 127, given alpha = 0.01. Statistical analysis was done using the Statistical Package for Social Sciences (version 25, SPSS) software. Categorical variables were shown as frequency and percentages (%), while continuous variables were shown as mean ± standard deviation (SD). The chi-square test was used to compare differences between sociodemographic factors and medical history. The independent sample T-test was used to compare continuous variables between groups. Binary logistic regression was used to independently assess the factors associated with sarcopenia. Post-hoc power calculation was done using G*power and showed 88.3% actual power using the irisin mean level (effect size = 0.459 with sample sizes n1 = 26 and n2 = 105). Significance was set at p < 0.05. 3. Results 3.1. Participant Characteristics The study population included 131 Saudi females with a mean age of 65.9 ± 5.5 years. Twenty-six of the participants had sarcopenia (prevalence of 19.8%). The majority of the study participants were married (65.9%), illiterate (52.3%), and unemployed (88.6%). The majority of the participants were obese (61.8%) and obesity was significantly more common in the non-sarcopenia group than in the sarcopenia group (70.5% versus 27%; p < 0.001). No differences were observed for the rest of the comorbidities with the exception of hypothyroidism, where all cases were found in the non-sarcopenia group (p = 0.02) (Table 1). The majority of the participants (77%) were not engaged in any type of physical activity (Supplementary Table S1) with no difference being observed between groups. No differences were also observed in lifestyle behaviors in terms of sleeping patterns and sub exposure (Supplementary Table S2). 3.2. Clinical Differences among Participants with and without Sarcopenia Table 2 shows the clinical differences of participants with and without sarcopenia. Significantly lower indices in the sarcopenia group were observed with respect to BMI and waist and hip circumference as well as MAC, MAMA, and AVI (all p-values <0.001) as compared to those without sarcopenia. Furthermore, and as expected, all the indices for muscle mass, strength, and performance were significantly lower in the sarcopenia group than the non-sarcopenia group with the exception of TUG (p = 0.53). Lastly, circulating irisin was significantly lower in the sarcopenia group than in the non-sarcopenia group (p = 0.001). 3.3. Factors Associated with Sarcopenia Table 3 shows anthropometric factors related to sarcopenia using bivariate logistic regression analysis. Participants with high BMI were less likely to have sarcopenia (OR = 0.79; 95% CI, 0.71–0.89; p < 0.001), Similarly, high waist circumference and hip circumference decreased the odds of sarcopenia (OR = 0.91; 95% CI, 0.86–0.96; p < 0.001). Furthermore, high mid-arm circumference (OR = 0.75, 95% CI: 0.64–0.87; p < 0.001), and high mid-arm muscle area (OR = 0.90; 95% CI, 0.85–0.95; p < 0.001) were significantly associated with decreased risk of sarcopenia. High abdominal volume index was found to decrease the odds of sarcopenia by 21% (OR = 0.79; 95% CI, 0.69–0.91; p = 0.001). Among the biochemical parameters assessed, low irisin was associated with sarcopenia (OR = 0.97; 95% CI, 0.95–0.99; p = 0.002). The rest of the biochemical markers analyzed in this study were not found to be correlated with sarcopenia. Lastly, among the macronutrient intake, only low total fiber intake was associated with sarcopenia (OR = 0.94; 95% CI, 0.88–0.99; p = 0.03) (Table 3). Lastly, bivariate associations showed a significant positive correlation between irisin level and waist circumference (r = 0.44, p = 0.05) (Figure 1A) as well as a significant positive correlation between waist to hip ratio (Figure 1B) and conicity index (Figure 1C) (r = 0.51, p = 0.05; and r = 0.45, p = 0.05, respectively), only in the sarcopenia group. 4. Discussion The present study attempted to determine the associations of sarcopenia to several factors among elderly Arab females with or without the condition and the differences between these factors. To the best of our knowledge, the present study is the first of its kind to investigate these associations among Arab elderly females. The main findings of the present investigation included the high prevalence of sarcopenia (19.8%) among elderly Arab women, the significantly lower irisin levels among those with sarcopenia, and the significant positive associations of irisin with body composition measures observed only among those with sarcopenia. Consistent with our results, several studies showed a strong association between anthropometric measures and sarcopenia [29,33,39]. Our findings are supported by a cross-sectional study that reported an inverse association of BMI and WC with sarcopenia; these factors were considered predictors of sarcopenia among elders in the Amazon region [29]. Additionally, a cross-sectional study observed that low BMI in Singaporean elders was strongly correlated with sarcopenia, aside from high WC [28]. On the other hand, BMI was observed to be a determinant of sarcopenia with a comparable risk factor to low physical performance among older adults with diabetes in Japan [27]. Moreover, a prospective cohort study stated that MAC was considered as the best anthropometric measure associated with sarcopenia [31]. Likewise, a multi-ethnic cross-sectional study suggested that high HC was associated with low sarcopenia risk in older Asians [30]. Obese individuals could also have sarcopenia (sarcopenic obesity) if such individuals experience muscle-mass loss with subsequent increase in adiposity [1,27]. Advance loss of skeletal muscle mass occurs with aging and has been linked to impaired skeletal muscle protein synthesis, caused by reduced amino acid delivery to aged skeletal muscle [43]. Consequently, protein intake was found to be strongly associated with sarcopenia [15]. Our findings in contrast found no significant correlation between protein intake and sarcopenia, which was similar to a cross-sectional study which found no difference between protein intake and handgrip strength among elderly women who consumed higher levels of protein [44]. Even though dietary fiber was significantly low in the sarcopenia group and remained significant after using logistic regression, no comparable literature was found to support this finding. Nevertheless, many studies found a strong relationship between the Mediterranean diet, which is high in fiber, and reduced risk of sarcopenia and frailty in older adults [45,46]. Physical activity was not correlated with sarcopenia in the present study, consistent with the findings observed among Chinese elders which also found no relationship between sarcopenia and physical activity [47]. Most of our study participants were not engaged in any physical activity—only 22.1% were engaged in light physical activity, 19% were engaged in moderate activities, and none in vigorous activities. Thus, this low percentage of the population engaged in physical activities might explain our results, in addition to the variety of the assessment methods that have been used in previous studies. Irisin is a myokine that is proteolytically cleaved and secreted from the fibronectin type III domain-containing protein 5 and primarily secreted in the skeletal muscle [48,49]. Therefore, several studies have investigated the association of irisin with muscle mass and strength [10,11,12,13]. In our study, the sarcopenia group had significantly lower irisin levels than the non-sarcopenia group (p = 0.001). Moreover, high irisin was associated with lower odds of sarcopenia (p = 0.002). Our results are consistent with a previous cross-sectional study in South Korea that found that serum irisin levels were significantly lower in postmenopausal females diagnosed with sarcopenia compared to those without [11], but also contradicts a more recent observation, also among South Koreans, that irisin has no association between clinical muscle parameters [50]. This discrepancy in findings within the same population may be due to sample size issues and the assays used, as well as ethnic differences with respect to the present findings. In the current study, we reported that irisin had a significant positive correlation with WC, WHR, and CI in the sarcopenia group. Similarly, a cross-sectional study conducted among 151 Caucasian and African American males and females aged > 35 years reported that irisin was positively associated with WC and WHR in both genders [51]. On the other hand, 1115 obese Chinese adults with a mean age of 53.2 + 7.2 years were enrolled in a cross-sectional study that revealed that irisin level was inversely associated with waist circumference [52]. A cohort study that included 76 middle-aged Caucasian men showed that irisin was inversely correlated with WHR [53]. Although irisin is mostly known as a myokine, it is also released from adipose tissue, which can partially explain its association with indicators of obesity [49,54,55,56,57,58,59]. Our data revealed that vitamin D had no significant correlation with sarcopenia. This is comparable to a similar case-control study which found no difference in the mean serum 25(OH)D of British elders with and without sarcopenia [60]. In contrast, a cross-sectional study conducted among Dutch elderly subjects found that 25(OH)D was significantly lower in sarcopenic subjects than in non-sarcopenic subjects [61]. The inconsistencies between our findings and the studies supporting the association between vitamin D and sarcopenia might be due to supplement use and the season of blood sampling. In Saudi Arabia and the Gulf Cooperation Council (GCC) countries, regional guidelines promote vitamin D supplementation of up to 2000 IU per day among postmenopausal women [62,63], which explains why the mean vitamin D status for both groups in the present study are within the sufficient level. Further studies may be required, particularly intervention trials, to determine whether vitamin D status correction confers beneficial effects among elders with sarcopenia. The authors acknowledge some limitations. First, this was a cross-sectional study thus causality could not be assessed. The lack of bone mineral density assessment limited the study’s ability to determine those with possible osteosarcopenia, which is also impacted by both physical activity and nutrition [64]. Lastly, the small sample size and the female exclusivity of the population used limits the generalizability of findings. 5. Conclusions Sarcopenia is common among elderly Arab females with a multi-causal etiology and many risk factors. Novel measures such as abdominal volume index, dietary fiber, and irisin were found to be significantly lower among those with sarcopenia than those without. Moreover, irisin levels were significantly associated with abdominal obesity among those with sarcopenia. Despite the lack of association between sarcopenia, vitamin D, physical activity, and lifestyle in this population, findings should be further explored prospectively to determine whether lifestyle modifications through nutrition, supplementation, and exercise can decrease the incidence of sarcopenia among elderly Arab females. Acknowledgments We are grateful for the assistance of Chair for Biomarkers of Chronic Diseases Laboratories, King Saud University, Riyadh. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu14091855/s1, Table S1 Physical activity according to sarcopenia status; Table S2 Lifestyle patterns (Sleep and Sun exposure) according to sarcopenia status. Click here for additional data file. Author Contributions Conceptualization, T.A.A., M.M.A.A., and D.A.; methodology, T.A.A. and M.M.A.A.; software, T.A.A. and M.N.K.K.; validation, D.A. and M.M.A.A.; formal analysis, M.N.K.K., S.S., and T.A.A.; investigation, T.A.A.; resources, M.M.A.A., A.M.A., and T.A.A.; data curation, T.A.A.; writing—original draft preparation, T.A.A. and S.S.; writing—review and editing, D.A., M.M.A.A., S.S., and N.M.A.-D.; visualization, T.A.A.; supervision, D.A. and M.M.A.A.; project administration, T.A.A., D.A. and M.M.A.A.; funding acquisition, N.M.A.-D. 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 (IRB) of the College of Medicine in King Saud University, Riyadh, Saudi Arabia (No.19/0300/IRB) and the Ministry of Health (IRB NO.2019-0043E). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data are available upon reasonable request to the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Significant positive associations of irisin with (A) waist circumference, (B) waist to hip ratio, and (C) conicity index in the sarcopenia group. nutrients-14-01855-t001_Table 1 Table 1 General characteristics of participants according to sarcopenia status. Parameters All Non-Sarcopenia Sarcopenia p-Value N 131 105 26 Age (years) 65.9 ± 5.5 65.5 ± 5.4 67.5 ± 5.7 0.11 Education Illiterate 69 (52.3) 55 (51.9) 14 (53.8) 0.86 Elementary 26 (19.7) 19 (17.9) 7 (26.9) Middle school 13 (9.8) 11 (10.4) 2 (7.7) High School 8 (6.1) 7 (6.6) 1 (3.8) College degree 15 (11.4) 13 (12.3) 2 (7.7) Postgraduate 1 (0.8) 1 (0.9) 0 (0.0) Marital Status Married 87 (65.9) 71 (67.0) 16 (61.5) 0.63 Widowed 43 (32.6) 33 (31.1) 10 (38.5) Divorced 2 (1.5) 2 (1.9) 0 (0.0) Employment None 117 (88.6) 94 (88.7) 23 (88.5) 0.75 Retired 13 (9.8) 10 (9.4) 3 (11.5) Home Business 2 (1.5) 2 (1.9) 0 (0.0) Medical history Obesity 81 (61.8) 74 (70.5) 7 (27) <0.001 Type 2 diabetes 78 (59.5) 61 (58.1) 17 (65.4) 0.33 Hypertension 84 (35.9) 66 (62.9) 18 (69.2) 0.36 High cholesterol 55 (42.0) 45 (42.9) 10 (38.5) 0.43 Osteoporosis 9 (6.9) 7 (6.7) 2 (7.7) 0.86 Rheumatoid arthritis 7 (5.3) 6 (5.7) 1 (3.8) 0.70 Asthma 10 (7.6) 9 (8.6) 1 (3.8) 0.42 Hypothyroidism 16 (12.2) 16 (15.2) 0 (0.0) 0.02 Comorbidity 89 (67.9) 72 (68.6) 17 (65.4) 0.46 Note: Data presented as mean ± SD, N (%). nutrients-14-01855-t002_Table 2 Table 2 Clinical characteristics of participants according to sarcopenia status. Anthropometrics All Non-Sarcopenia Sarcopenia p-Value N 131 105 26 BMI (kg/m2) 31.9 ± 5.4 32.9 ± 5.3 27.8 ± 2.7 <0.001 Waist (cm) 95.8 ± 11.7 97.9 ± 11.2 87.5 ± 9.7 <0.001 Hips (cm) 111.1 ± 12.4 113.2 ± 12.7 102.7 ± 6.6 <0.001 WHR 0.86 ± 0.07 0.86 ± 0.08 0.86 ± 0.07 0.82 MAC 29.5 ± 4.6 30.3 ± 4.5 26.2 ± 3.1 <0.001 TSF 17.7 ± 3.6 17.9 ± 3.6 16.8 ± 3.2 0.16 CI 1.2 ± 0.1 1.3 ± 0.10 1.2 ± 0.1 0.48 MAMA 43.6 ± 11.4 45.8 ± 11.0 35.3 ± 8.5 <0.001 AVI 18.4 ± 4.5 19.2 ± 4.4 15.5 ± 3.4 <0.001 Muscle Mass, Strength, and Performance Muscle mass 41.1 ± 5.2 42.4 ± 4.8 35.9 ± 2.8 <0.001 Right leg muscle 6.9 ± 1.1 7.2 ± 1.0 6.1 ± 0.7 <0.001 Left leg muscle 7.0 ± 1.1 7.2 ± 1.0 6.4 ± 1.4 0.002 Right arm muscle 2.0 ± 0.3 2.1 ± 0.3 1.7 ± 0.2 <0.001 Left arm muscle 2.1 ± 0.3 2.2 ± 0.3 1.8 ± 0.2 <0.001 Trunk muscle 22.9 ± 2.8 23.8 ± 2.5 19.9 ± 1.9 <0.001 Predicted muscle 6.8 ± 0.8 7.0 ± 0.8 5.9 ± 0.3 <0.001 HGS 16.3 ± 4.4 17.1 ± 4.3 13.4 ± 3.4 <0.001 TUG 15.6 ± 3.9 15.5 ± 4.1 16.0 ± 3.4 0.53 Biochemistry Glucose (mmol/L) 10.9 ± 4.0 10.9 ± 3.8 11.0 ± 4.6 0.98 HDL-cholesterol (mmol/L) 1.5 ± 0.4 1.5 ± 0.4 1.4 ± 0.4 0.76 Total cholesterol (mmol/L) 5.2 ± 1.1 5.2 ± 1.1 5.3 ± 1.1 0.78 25(OH)D # (nmol/L) 54.6 (39.9–75.9) 54.4 (40.9–75.6) 55.5 (34.6–91.7) 0.35 Irisin (ng/L) 169.1 ± 40.2 180.8 ± 44.3 145.8 ± 11.6 0.001 Note: Data presented as mean ± standard deviation; #denotes non-normal distribution and presented as median (inter-quartile range); BMI, body mass index; WHR, waist–hip ratio, MAC, mid-arm circumference; TSF, triceps skinfold-thickness; CI, conicity index; MAMA, mid-arm muscle area; AVI, abdominal volume index; HGS, hand grip strength; TUG, timed up-and-go test; p-value significant at <0.05. nutrients-14-01855-t003_Table 3 Table 3 Associations of select parameters with sarcopenia. Parameters OR (95% CI) p-Value Anthropometrics BMI (kg/m2) 0.79 (0.71–0.89) <0.001 Waist circumference (cm) 0.91 (0.86–0.96) <0.001 Hip circumference (cm) 0.91 (0.86–0.96) <0.001 WHR 0.50 (0.001–2.6) 0.82 MAC 0.75 (0.64–0.87) <0.001 TSF 0.91 (0.80–1.04) 0.16 CI 0.21 (0.002–16.9) 0.48 MAMA 0.90 (0.85–0.95) <0.001 AVI 0.79 (0.69–0.91) 0.001 Biochemistry Total cholesterol (mmol/L) 1.07 (0.67–1.72) 0.78 HDL-cholesterol (mmol/L) 0.80 (0.19–3.24) 0.76 Glucose (mmol/L) 1.0 (0.88–1.14) 0.98 25(OH) D (nmol/L) 1.28 (0.14–12.2) 0.83 Irisin (ng/l) 0.97 (0.95–0.99) 0.002 Macronutrients Total calories (kcal) 1.0 (0.99–1.01) 0.86 Fats (kcal) 1.0 (0.99–1.02) 0.70 Protein (g) 0.99 (0.97–1.03) 0.93 Carbohydrate (g) 0.99 (0.99–1.01) 0.69 Total fiber (g) 0.94 (0.88–0.99) 0.03 Note: Data presented as odds ratio (OR); 95% confidence interval (95% CI); BMI, body mass index; WHR, waist–hip ratio; MAC, mid-arm circumference; TSF, triceps skinfold-thickness; CI, conicity index; MAMA, mid-arm muscle area; AVI, abdominal volume index; significance at p < 0.05. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095058 ijms-23-05058 Review Tumour Stem Cells in Breast Cancer Ibragimova Marina 123* Tsyganov Matvey 1 https://orcid.org/0000-0002-0714-8927 Litviakov Nikolai 123 Gomes Célia Maria Freitas Academic Editor 1 Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, 5, Kooperativny Street, 634050 Tomsk, Russia; tsyganovmm@yandex.ru (M.T.); nvlitv72@yandex.ru (N.L.) 2 Laboratory of Genetic Technologies, Siberian State Medical University, 2, Moscow Tract, 634050 Tomsk, Russia 3 Biological Institute, National Research Tomsk State University, 36, Lenin, 634050 Tomsk, Russia * Correspondence: imk1805@yandex.ru 02 5 2022 5 2022 23 9 505818 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/). Tumour stem cells (CSCs) are a self-renewing population that plays important roles in tumour initiation, recurrence, and metastasis. Although the medical literature is extensive, problems with CSC identification and cancer therapy remain. This review provides the main mechanisms of CSC action in breast cancer (BC): CSC markers and signalling pathways, heterogeneity, plasticity, and ecological behaviour. The dynamic heterogeneity of CSCs and the dynamic transitions of CSC− non-CSCs and their significance for metastasis are considered. cancer stem cells breast cancer metastasis plasticity the Ministry of Science and Higher Education of the Russian FederationNo. 075-15-2021-1073 State contract of the Ministry of Science and Higher Education of the Russian Federation “Genetic and epigenetic editing of tumor cells and microenvironment in order to block metastasis” No. 075-15-2021-1073. ==== Body pmc1. Introduction All types of malignant neoplasms (MNOs) consist of different populations of tumour cells that give the tumour the property of heterogeneity. Tumour stem cells (CSCs) play a key role in tumour initiation, maintenance of tumour growth and progression [1]. CSCs demonstrate all aspects of stemness. However, despite the physiological role of adult tissue stem cells (SCs), they are unable to maintain tissue homeostasis due to uncontrolled division [1]. Tumour stem cells are a small population of cells in a tumour with stem-like properties that support an increased capacity for self-renewal, growth, metastasis, and reproduction, which causes cancer progression. CSCs can regulate neighbouring cells, supply them with nutrients, create an environment for tumour growth, or vice versa, and use them for their survival by the mechanisms of induction of autophagy and entosis [2]. CSCs form heterogeneous cell populations, most often with a high plasticity potential [2] and high resistance to stress factors within the tumour microenvironment and cell death induction under the influence of chemotherapeutic drugs—resistance to antitumour therapy [3]. Breast tumour stem cells (CSCs) exist in the form of a small fraction of cells in the mammary gland; they are undifferentiated and can produce new CSCs through symmetric division and, through asymmetric division, produce tumour cells that differentiate and leave the main population of tumour cells [4]. It is assumed that asymmetric divisions lead to the appearance of first generation progenitor cells capable of limited proliferative activity [5,6]. It is believed that the functioning of CSCs occurs in close interaction with their specific microenvironment, the breast stem cell niche, which CSCs themselves regulate [7]. The locations of these cells, their unique characteristics of self-renewal, differentiation, and plasticity, and their role in breast cancer are still the subject of discussion. This review is devoted to the analysis of current data on tumour stem cells in breast cancer. 2. Cancer Stem Cell Signalling Pathways Many mutations in tumours are involved in the activation of cell self-renewal pathways, including in CSCs. In cancer, multiple cellular self-renewal pathways are not only continuously activated but can also be amplified. The activation of the self-renewal programme is an important part of the stem nature of CSCs, promoting tumour progression and metastasis, causing high cell turnover and the production of progenitor cells [2]. First, we concentrate mainly on the data currently published in the world literature about signalling pathways that promote self-renewal of stem and/or progenitor cells, the dysregulation of which can contribute to oncogenesis. 2.1. Canonical WNT/Β-Catenin Signalling WNT signalling is activated through an autocrine mechanism in breast cancer. It has been shown that in approximately 50% of clinical cases of breast cancer, there is a high level of stabilised β-catenin, as well as a high frequency of amplification of the positive genes stimulating the WNT-pathway [8]; moreover, when the frequency of amplification of positive stimulating of WNT signalling exceeds the frequency of amplification of negative regulators of WNT, this is combined with the aggressive course of breast cancer [9]. Protein FRP1 (WNT inhibitor) is deleted in 78% of breast cancer cases, and its deletion is associated with a poor prognosis [10]. Activated β-catenin promotes triple-negative and HER2+ breast cancer [11]. In this regard, the restoration of negative WNT regulators, which are not expressed in the tumour due to methylation of promoters or deletion of genes encoding negative WNT regulators in the tumour, has become a new direction of therapy. There is evidence that the restoration of negative regulators effectively slows the growth of experimental tumours [12]. Inhibition of WNT1 changes the phenotype of CD44+CD24−ALDH1 stem cells and reduces their ability to form tumours and cell migration [13], and suppression of GSK3/β-catenin signals by an inhibitor of protein kinase D1 (PRKD1) is sufficient to reduce the stem and chemoresistance of breast cancer cells [14]. Modulation of the nuclear-antigen-associated factor RAF of proliferating cells in mammary CSCs by NVP-AUY922 suppresses their capacity for self-renewal and heterogeneity [15]. Gujral et al. also found that the levels of WNT5A/B and its Frizzled2 receptor are elevated in tumours and in several breast tumour cell lines. Frizzled2 induces epithelial–mesenchymal transition (EMT) in a noncanonical pathway, stimulating stemness [16]. 2.2. Notch Signalling Pathway Notch3 and Jag1 are key regulators of CSC renewal and survival during hypoxia in breast cancer and tumours derived from breast cancer cell lines. Notch expression is significantly increased in CSCs during hypoxia and leads to resistance to inhibition of the PI3K/mTOR pathway [17]. The Notch pathway plays a role in increasing the number of CSCs through symmetric division [18] and contributes to the dedifferentiation of progenitor cells by stimulating EMT [19]. At the same time, inhibition of Notch1 by specific antibodies significantly reduces the subpopulation of CSCs with the CD44+ CD24 phenotype and the frequency of brain metastases in breast cancer [20]. Violation of the negative regulation of Notch signalling initiates the development of several types of cancer, including breast cancer [21]. Notch-positive cells show a better possibility of tumour initiation than Notch-negative cells [22]. 2.3. Hedgehog (HH) and Sonic Hedgehog (SHH) Signalling Pathway Activation of the Hedgehog signalling pathway is associated with the development of several types of cancer, including breast tumours [23]. Hh signalling pathways regulate self-renewal in breast stem cells [24], and destruction of lower transcriptional targets of the SHH, PTCH-1, or GLI-2 pathways leads to severe defects in mammary duct morphogenesis [25]. SHH activation may contribute to relapse and can be used as a predictor of postoperative relapse in breast cancer. High expression levels of SHH, PTCH-1, GLI-1 and SMOH correlate with the invasiveness of breast tumour cells [26]. The transmembrane protein Patched (PTCH) is a receptor of the hedgehog signalling molecule family (Sonic-Shh, Indian-Ihh, and Desert-Dhh) and is associated with early embryonic tumorigenesis. PTCH inhibits the activity of the Hh pathway through its interaction with the Smoothened transmembrane protein (SMO). Overexpression of SHH, PTCH1, and GLI1 is found in most cases of breast cancer [19,27]. Evidence continues to mount and to demonstrate the role of the Hh pathway in the development of metastasis, particularly through the initiation of EMT [28] and the activation of proteins such as MMP-9 and the expression of E-cadherin [29]. 2.4. NRF2 Signalling The NRF2-mediated antioxidant pathway is a novel mechanism that explains the chemo- and radioresistance of tumour stem cells. Significantly higher expression of NRF2 and target genes of this pathway was found in CSCs than in normal breast cells. NRF2 suppression delays mammosphere formation and changes therapy-resistant phenotypes in MCF-7 breast cells [30]. NRF2 can push dormant tumour cells to proliferate or bypass metabolic blocks [31]. Tumour cells generate more reactive oxygen species (ROS) than normal cells, and CSCs require low ROS levels to maintain dormancy and self-renewal. Combining chemotherapeutic agents with CSC antioxidant capacity makes tumours vulnerable to chemotherapy and radiotherapy, while normal tissues are practically unaffected. For this purpose, various natural inhibitors of NRF2, such as apigenin, ATRA, all-trans retinoic acid, brusatol, chrysin, cryptotanshinone, luteolin, trigonelline, and и wogonin have been tested in preclinical tumour models [32]. Unfortunately, the exact mechanisms of the inhibitory effect on NRF2 are poorly understood. 2.5. PI3K/AKT/mTOR Pathway The activation of PI3K signalling in breast cancer has been frequently noted in the last few years in the literature and is mainly due to genetic mutations. For example, mutations in the tyrosine kinase receptor can aberrantly increase PI3K activity [33], and loss of PTEN function is found in approximately 50% of breast cancer patients [34]. PIK3CA mutation triggers centrosome amplification and increases tetraploidization-tolerance in breast cancer cells [35]. PIK3CA mutations induce dedifferentiation of progenitor tumour breast cells into tumour stem cells [36]. The PI3K/Akt/mTOR signalling pathway is associated with metastases in CSCs. Stable stemness is partially dependent on PI3K-regulated transactivation of several self-renewal pathways, including Wnt/β-catenin in triple-negative breast cancer [37]. Inhibition of the PI3K signalling pathway to inhibit tumour growth is not a new idea. However, taking into account the dualism of the PI3K/Akt/mTOR pathway, inhibition of PI3K by a buparlisib inhibitor may stimulated the Wnt pathway, which appropriates a stem-like phenotype in triple-negative breast cancer cells [37]. In addition, PI3K inhibitors can stimulate GLP-1-dependent stemness in MDA-MB-231 and MCF-7 breast cancer cell lines [38]. The signalling pathways regulating the functional activity of CSCs in breast cancer are schematically shown in Figure 1. 3. Markers and Heterogeneity of CSCs The following markers are allocated as breast CSC markers: CD44, CD24, CD133, EpCAM, nestin, GD2, CD49f, CD61, CXCR4, CXCL1, HMGCS, CD166, CD47, ALDH1, and ABCG2 [39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61]. CSCs were first identified and isolated in a xenograft model obtained from a patient with breast cancer in 2003 [40]. The oncogenic subpopulation of cells contained the surface marker CD44+CD24−/low. In the following few years, such subpopulations were found in early disseminated cells from the bone marrow of patients with breast cancer and were associated with the occurrence of relapse and distant metastasis [41]. Undifferentiated CD44+CD24−/low cells in tumours after chemotherapy were associated with poor outcomes in patients with invasive breast cancer. In addition, an increase in the proportion of CD44+CD24−/low cells in the tumour was associated with lymphogenous metastasis [42]. These data suggested the importance of CSCs in the relapse and metastasis of breast cancer. However, CD44+CD24−/low cell markers are not universal CSC markers. For example, in MDA-MB-231 and MDA-MB-361 cell lines, most cells show a CD44+CD24−/low phenotype, but only 5% and 12% of them, respectively, have oncogenic ability [43,62]. The correlation between an increase in the proportion of CSCs in breast tumour tissue and a poor prognosis increases when ALDH1 is used in combination with the CD44+CD24−/low phenotype [44]. It is important to understand that one of the serious and long-standing problems in the study of CSCs is determining the appropriate methodology for the isolation and characterization of cells [45]. The main method for CSC identification is cell-sorting based on the expression of cell surface markers, such as CD44, CD133, CD24, CD26, EPCAM, and CD166, or based on the enzymatic activity of intracellular proteins, such as ALDH1 [46]. However, these markers are not universal and are not expressed on all CSCs, which limits their use. To overcome this limitation, it is necessary to use several markers [45]. Possible CSC phenotypes identified in breast cancer are shown in Table 1. CSCs with the CD44+ phenotype are closely associated with metastasis. The proportion of early disseminated tumour cells with the CD44+CD24− phenotype in the bone marrow of patients with breast cancer was approximately 72% [68]. Labelled nanoparticles to target CD44+ CSCs have shown great potential for the capacity to strengthen the effect of chemotherapy in vitro [69]. The occurrence of spontaneous metastasis to the lungs and lymph nodes during transplantation of CD44+ CSCs in mice was shown by using noninvasive imaging methods [70]. The integrins CD29, CD49f, and CD61 are effective markers for CSCs. CD49f cells in breast tumours are associated with an increased possibility of metastasis and shorter survival time in patients [71]. Subpopulations of tumour cells that were resistant to doxorubicin and paclitaxel had CD49f+ and CD61+ phenotypes in Her2+ primary mammary tumours in mice [57]. The exact role of the CD133 transmembrane protein in breast cancer is unclear. However, BC cells with a CD133+ phenotype have stem-like properties. MDA-MB-231 cells with the CD133+ phenotype have a higher colony-forming efficiency than CD44+ cells [51]. It was also found that the number of CD133+ cells increases in tumours in patients with hormone-resistant breast cancer, contributing to the occurrence of metastasis regardless of the ER status of patients [52]. Exosomes can transfer miR-221 to breast tumour cells and contribute to Notch3 activation, which is required for CD133 cell proliferation [72]. The NAD(P)+/− dependent enzyme ALDH1 acts as an independent predictor of poor survival in breast cancer patients [73]. MDA-MB-231 and MDA-MB-468 cells with the CD44+CD24−ALDH1+ and CD44+CD133−ALDH1+ phenotypes had a stronger oncogenic and metastatic ability than ALDH1−/lowCD44−/low cells [64]. Analysis of mammosphere formation has shown that ALDH blockade increases the proportion of CSCs in several breast cancer cell lines, including 184A1, SUM149, SUM159, and HCC1954 [74]. Mukherjee et al. investigated CXCR4 (membrane chemokine receptor). The authors found that nonmigrating CSCs contributed to the transformation of non-stem tumour cells to metastatic CXCR4+ cells in primary breast cancer tissue. The results not only pointed out the potential of CXCR4 as a marker of breast CSCs but also provided evidence for the transformation of non-stem tumour cells to stem cells. The decrease in E-cadherin and increase in vimentin suggest that they underwent EMT dedifferentiation [53]. CXCR4 hyperactivation is closely related to changes in the tumour microenvironment. Activation of SDF-1/CXCR4 signalling may increase the phosphorylation of 60 proteins associated with the migration and invasion of CD44+CD24− CSCs in breast cancer [75]. The ABCG2 protein is highly expressed in several chemoresistant breast cancer cell lines. Compared to non-stem cells, CD44+CD24−/low cells from MCF-7, MDA-MB-231, and SK-BR-3 breast cancer cell lines showed higher expression of ABCG2 [59]. Higher expression of the endothelial marker ANTXR1 was found on the cell surface of CD44+CD24− and ALDH1+ of the TMD231 breast cancer cell line. Overexpression of ANTXR1 activates key genes for cell proliferation, DNA replication, and WNT signalling pathways, giving increased tumorigenic and metastatic potential to breast cancer cells. Moreover, ANTXR1 partially mediates the induction of tumour cell stemness. The authors argue that it is possible to sort the subpopulation of malignant breast cancer CSCs by the presence of ANTXR1 [48]. EpCAM (CD326 or ESA) plays an important role in the migration and metastasis of tumour cells. EpCAM+ circulating tumour cells in breast cancer contain a subpopulation of metastatic cells [41]. PROCR is a specific CSC marker for triple-negative breast cancer. The PROCR+ cell lines MDA-MB-361 and MDA-MB-231 have a 2-fold and 9-fold increase in the efficiency of colony formation, respectively, compared to PROCR–cells [43,62]. It was shown that the expression of GD3S is visibly increased in GD2+ CSCs of breast cancer. At the same time, GD3S knockdown decreases GD2 expression and disrupts their ability to migrate and form mammospheres, as well as disrupting the initiation and maintenance of EMT [67,76]. Overexpression of GD3S promotes stem properties and metastatic potential in MDA-MB-231, MDA-MB-468, and MCF-7 cell lines [67,76]. Despite the available data on the role of individual markers in determining CSCs in breast cancer, transcriptome analysis showed that many CSC markers can be coexpressed by one cell simultaneously [77], and the expression of CSC markers can change in vivo as a result of plasticity and adaptation to the microenvironment [78]. These observations emphasise the heterogeneity of CSCs and the ineffectiveness of markers used to identify CSCs and non-CSCs [79]. Thus, the CSCs population in BC is heterogeneous and is characterised by the presence of a wide variety of markers associated with stemness properties. 4. Ecological Behaviour of CSCs, Autophagy and Enthosis The consequence of intratumoural heterogeneity is the emergence of various kinds of ecological relationships between CSCs, other tumour cells, and the microenvironment [80]. At the same time, such interactions can be both positive and negative, depending on the internal and external conditions. Tumour cells and the microenvironment observe positive types of interactions (commensalism, mutualism) under favourable conditions between CSCs. For survival, CSCs use negative strategies of ecological behaviour when interacting with their descendants and cells of the microenvironment, such as amensalism in the form of autophagy, parasitism in the form of induction of autophagy of neighbouring cells, predation in the form of cannibalism, and the formation of hybrid heterotypic cells with immunocytes under unfavourable conditions [80]. Positive interactions are widely known (Figure 2a). Tumour cells can carry out M2 polarization of macrophages, which secrete IL-10, TGF-β, and VEGF into the environment, stimulating the growth of breast tumours [81,82]. The MBA-MB-231 cell line with a large number of CSCs produces IL-8 and stimulates the formation of the same interleukin by fibroblasts/macrophages in the case of their joint incubation, which enhances the proliferation and migration of tumour cells [83]. Distant signal transmission is possible due to the paracrine secretion of various biological substances (cytokines, growth factors, microRNA, extravesicles) into the environment [84,85]. Tsuji et al. [102] observed mutually beneficial cooperation of tumour clones initially possessing different biological properties (high metastatic potential but low invasive potential, and vice versa). During coinoculation of tumour clones, animals formed metastases-containing cells with a low metastatic potential, which, in the control, did not form metastases by themselves. CSCs can produce offspring that transdifferentiate and acquire characteristics similar to endothelial cells, forming vascular-like tubular structures [103]. Heterotypic cell fusion is a fundamental developmental mechanism that is well known for normal cells (sperm and egg, fusion of haematopoietic and epithelial cells in response to injury) and is an example of positive cellular interactions or symbiosis [104]. The heterotypic fusion of tumour cells with normal cells can be considered an example of symbiosis. On the one hand, this is a mechanism for the escape of tumour cells from the immune system, including during immunotherapy; on the other hand, the fusion of tumour cells with normal mesenchymal cells is a tool for acquiring a locomotor phenotype. The stem properties of tumour cells are enhanced by heterotypic fusion, and completely new properties are acquired [105]. The circulating hybrid cell (CHC) population (defined as cells with macrophage and epithelial/tumour properties) has been shown to correlate with disease stage and predict disease outcome. These cells expressed the tumour marker EpCam and macrophage markers CD163, CD68, CSFR1, and CD66b (Figure 2). Experimental hybrids of tumour cells and macrophages easily formed liver metastases in mice when injected into the spleen and lungs, i.e., had metastasis-initiating properties. In addition, hybrid clones retained macrophage genotypes with functional phenotypes, thereby imparting macrophage-like behaviour to neoplastic cells [92]. Heterotypic cell fusion most frequently occurs under hypoxic conditions [106]. Recently, there has been wide public activity devoted to the topic of tumour cell hybrids, which reflects that this is an infrequent event. In addition, hybrid cells still undergo post-hybrid selection [93,107,108]. Negative interactions are of great interest; they are much more likely to occur due to unfavourable conditions than positive interactions, and they determine tumour progression after treatment. Autophagy is one of the main mechanisms of negative interactions and has been considered in the past few years as a prerequisite for maintaining stem cells as normal stem cells [109], and CSCs [96,110,111]. The role of autophagy in cancer is multifaceted: it promotes the survival of tumour cells by supplying processed metabolites for growth, modulates mitochondrial function through mitophagy (selective mitochondrial degradation), and participates in the migration and invasion of tumour cells by controlling migrating cytokine secretion [112]. Autophagy plays a central role in the tumour microenvironment [112,113]. Autophagy in CSCs (Figure 2C) increases the expression of stem cell markers such as CD44, as well as the expression of mesenchymal markers such as vimentin. Autophagy also promotes spheroid formation in vivo, which proves its critical role in maintaining CSCs [94,96,112]. Inhibition of autophagy reduces the survival and metastasis of dormant tumour cells in mice [95]. It has been shown that autophagy is required to increase CSC self-renewal in the hormone-independent breast cancer cell line LM38-LP [114]. The autophagy markers Atg5, Atg12 and LC3B are overexpressed in dormant stem cells, such as breast cancer cells, and 3-MA suppression of autophagy removes cells from the dormant state [115]. In 2017, Zhang et al. found that inhibition of autophagy may be partially responsible for the suppression of stem-cell markers in breast cancer [116]. Key transcription factors associated with autophagy induction and stem cell health, such as FOXO3A (which induces the expression of autophagy genes in stem cells), switch themselves by autophagy. Other transcription factors, including the main stemness factors SOX2, NANOG and STAT3, are also associated with the induction of autophagy; they modulate autophagy genes and determine the stemness of CSCs [96,97]. Autophagy allows CSCs to survive despite hypoxia and low nutrient levels in the tumour microenvironment during growth and treatment [94]. Autophagy regulates luminal progenitor-like cells through the TGF-β-Smad and EGFR-Stat3 signalling pathways in MMTV-PyMT breast tumours [117]. Autophagy, which is induced in cancer-associated fibroblasts (CAFs), leads to an increase in the production of amino acids, which are passed through paracrine transmission to support tumour cell growth [118]. The conversion levels of Beclin1 and LC3-II/I proteins in TFA are higher than those in normal fibroblasts in breast cancer, and autophagy of TFA can enhance the proliferation of TNBC cells [119]. In nutrient deficiencies, staining with the autophagic marker Beclin-1 reveals autophagic regions surrounding active proliferating cells [120]. The role of the autophagy effect on CSCs in the antitumour therapy of breast cancer is also discussed. It has been shown that anticancer therapy can induce autophagy, which contributes to the survival of CSCs [121]. Chloroquine, CQ, is an inhibitor of autophagy and causes damage to mitochondria, which leads to excessive oxidative damage to DNA and subsequent death of CSCs TNBC [122]. Inhibition of autophagy can disturb the maintenance of CSCs. Wen Yue has shown that salinomycin is at least 100 times more effective than paclitaxel in reducing the proportion of mammary CSCs, as it can suppress their survival through autophagy [123]. The effects of autophagy blockade on breast cancer CSC activity include suppression of the expression of stem cell factors OCT4, SOX2, NANOG, and CD44; a decrease in the number of mammospheres; an increase in susceptibility to chemotherapeutic agents; and a decrease in the survival of tumour cells and metastasis [114,116,123]. Thus, autophagy can be induced in a tumour and mediate resistance to therapy due to the survival of CSCs in various types of cancer in response to the applied treatment [124,125]. Clinical trials of hydroxychloroquine for targeting autophagy and cancer treatment have been launched [126]. Another interesting type of negative cellular interaction is predation, which manifests itself as a cell-in-cell (CIC) phenomenon (Figure 2D). The first reports describing the presence of cells in other cells in tumour tissues appeared approximately 120 years ago [99,127]. Tumour tissues contained cells with a sickle nucleus because the vacuole displaces the cell nucleus to the periphery. This led to the emergence of the term “cell in a cell” [128]. Cell-in-cell structures can be formed as a result of the activation of cannibalistic mechanisms. They are similar to phagocytosis of macrophages or different actions that involve cell invasion into each other rather than absorption [129]. CICs can be formed by different processes and can be composed of two or more cells of the same origin (e.g., two tumour cells, homotypic) or cells from different origins (e.g., immune cells within tumour cells, heterotypic). Several different terms have been described in the literature to denote the formation of CIC: entosis, uptake, EM teripolysis, and cannibalism [130,131]. The cannibalistic activity of tumour cells is an important metabolic adaptation to an unfavourable microenvironment with a lack of nutrition. Entosis is also characteristic of metastatic cells [99]. Recent studies have highlighted the importance of the CIC phenomenon in the behaviour of many types of cancer [132,133]. The “cell-in-cell” phenomenon for breast cancer is an independent prognostic factor; it is the entotic formations that represent 91% of the CIC structures in the samples of breast ductal carcinoma collected from untreated patients [132]. The entosis process has also been demonstrated in the MDA-MB-231 breast cancer cell line, which cannibalises mesenchymal stem cells at a high rate when mixed in 3D cocultures designed to mimic bone metastases [134]. The anticancer drug paclitaxel induces entosis in the MCF7 breast cancer cell line [135]. Thus, the ecological behaviour of CSCs includes both forms of positive interactions, such as commensalism, mutualism and symbiosis, that appear under favourable conditions for tumour development, and negative forms of ecological behaviour that prevail under unfavourable conditions: amensalism in the form of autophagy, parasitism in the form of induction of autophagy of neighbouring cells, and predation in the form of cannibalism or entosis. 5. Phenotypical Plasticity Determines Dynamic Heterogeneity of CSCs CSCs are dynamic populations and can undergo spontaneous transitions between states and phenotypes [136]. Chaffer et al. showed that cancer non-stem cells spontaneously switch to cancer stem cells in vitro and in vivo by using the example of basal cells of breast cancer. Later, it was discovered that this plasticity is regulated by ZEB1, a key regulator of EMT [137,138]. CSCs form heterogeneous cell populations with high plasticity potential for various forms of cancer [2]. Different markers can identify different CSCs within the same tumour type; they are phenotypically different and can vary from patient to patient depending on the genetic structure of the tumour [139]. CSC BC can be distinguished by epithelial and mesenchymal phenotypes, even if the identification markers are similar. Various subpopulations of CSCs were identified based on the markers ALDH1, CD44, and CD24 and two subpopulations: epithelial-like with the ALDH1+ phenotype and mesenchymal-like with the CD44+CD24− phenotype. This subpopulation is capable not only of mutual transformation among themselves but also of the formation of non-CSCs [140]. CSCs and non-CSCs show a dynamic balance maintained through cytokine-mediated cross-interactions between populations in breast cancer. Thus, tumour-treatment strategies aimed at destroying CSCs appear to be ineffective [141]. In this regard, therapeutic strategies aimed at blocking phenotypic plasticity, in particular, dedifferentiation of non-stem tumour cells into CSCs, may be promising. The results show that phenotypic plasticity is reversible and does not necessarily depend on genetic changes [142]. CSC plasticity was also manifested in the formation of tumour pseudoorgans in vasculogenic mimicry, a characteristic process of tumour cell plasticity in which tumour cells transdifferentiate and acquire endothelial cell characteristics [103]. It was shown that a population of cells with the CD133+ phenotype with CSC-like properties demonstrated the ability to form vascular-like tubular structures in triple-negative breast cancer [143]. Thus, CSCs can not only mutually transform their subpopulations but also give rise to various types of undifferentiated CSCs and differentiate into new tumour pseudoorganoids. 6. CSCs of Primary Tumour and Metastasis BC predominantly metastasises to the bone (47–60%), liver (19–20%), lung (16–34%) and brain (10–16%) [144,145]. The primary tumour that subsequently metastasises is highly heterogeneous, which makes it difficult to assess risk factors for metastasis [146]. Metastasis or relapse spreads from primary tumours with further acquisition of mutations and independent evolution of metastases, and there are acquired mutations in distant metastases that were not detected in primary tumours [147]. Primary tumours and metastases of various types of cancer are closely related from a genetic point of view, but no genetic changes have yet been found that underpin metastasis [148]. Metastatic cells have the ability to differentiate into CSCs and initiate tumours. On the one hand, metastatic cells can originate from a CSC subpopulation that already undergoes genetic changes to initiate tumour growth [145]. CSCs also have the ability to metastasise due to their tumour-initiating ability [149]; in this case, markers of metastasis should be looked for directly in the CSC subpopulation. On the other hand, metastatic potential can be acquired due to the ability to dedifferentiate to CSCs from non-CSCs directly in the focus of possible metastasis. [150] and in this case, it is not necessary to look for markers of metastasis but, rather, markers of the ability to dedifferentiate. It is assumed that the latent phase of breast metastasis may include the spread of cells at an early presymptomatic stage of primary tumour development. Disseminated tumour cells remain undetected for many years before they develop into macrometastases and become clinically significant [151]. Disseminated tumour cells with stem-cell properties and in the dormant state can be activated in response to injury during treatment (chemotherapy, targeted therapy, radiation therapy, surgery, etc.), to promote the formation of a new tumour or metastasis [6]. At the same time, cells initiating metastasis can exist in a subpopulation of breast cancer CTCs in mouse models [41]. CTCs obtained from patients with metastatic breast cancer often show overexpression of stem cell markers, suggesting that metastasis is induced by a subpopulation of CTCs that express a tumour stem-cell marker (CD133 or CD44), have CSCs characteristics and thus can be considered as circulating CSCs (cCSCs) [152,153]. Accordingly, CTCs are important objects for understanding carcinoma metastasis [154]. However, it is important to understand the high degree of heterogeneity of circulating tumour stem cells in invasive breast cancer. The work of Savelieva et al. demonstrated significant heterogeneity among CTCs with stem-like features in the form of co-expression variants of CD44/CD24, CD133 and ALDH1 markers. In patients who had CD44−CD24− CTCs, a subset of cells with the expression of other stem-cell markers (CD133 and ALDH1) were detected. Expression of CD133 and/or ALDH1 may be associated with expression of N-cadherin; all populations of N-cadherin+ CTCs demonstrate stem features [155]. The question remains as to why CSCs under favourable conditions in the primary tumour undergo EMT, begin to migrate, penetrate into secondary organs and form metastases. Unfavourable hypoxia, nutritional deficiencies, etc., do not explain why small tumours can give metastases and do not explain the earlier origin of metastases. More than 10 years ago, evidence began to emerge that CSCs are cells that mediate tumour metastasis, treatment resistance, and disease recurrence in breast cancer. Breast-tumour gene profiling has shown that CSCs have an invasive gene signature that correlates with increased metastasis and poor overall survival [156]. Baccelli et al. identified the population of tumour cells circulating in the blood from breast cancer patients, which initiates metastasis. The number of CSCs with the EpCAM+CD44+MET+CD47+ phenotype increased with tumour progression, while no significant changes were found in the number of CSCs representing the main population of tumour cells [41]. In another study, a subpopulation of BC cells with the phenotype Oct4hi/CD44hi/med/CD24−/+ and CSC properties (self-renewal, cyclic rest, asymmetric division, high metastatic/invasive capacity) was also found in the bloodstream of breast cancer patients who underwent or completed treatment [157]. EMT induction tends to increase gene expression, which is associated with stemness and CSCs in some types of tumours. This has been studied using the example of normal breast tissue and BC. One of these studies showed that EMT induction in immortalised human mammary epithelial cells was sufficient to induce the expression of stem cell markers. This resulted in an increase in mammosphere formation in vitro and metastases in xenografts. Along with this, it has been shown that experimentally induced EMT increases the number of cells with stem-cell properties in mammary epithelial cells [158], and the overexpression of the transcription factors SNAI2 and SOX9 was sufficient to push the cells to acquire the stem phenotype in normal breast tissue [159]. CSCs can enter the bloodstream and become circulating tumour cells with potential metastasis to distal organs [160]. The association between CSCs and metastasis was also confirmed by the observation that disseminated cells in the bone marrow in breast cancer patients have a CSC phenotype [68]. However, this also confirms the second assumption that tumour cells in bone marrow could dedifferentiate there and become CSCs. 7. Importance of Tumour Cell Dedifferentiation in CSCs for Metastasis The assumption that metastatic potential can be acquired due to the ability of non-OSCs to dedifferentiate to CSCs in the focus of possible metastasis [150] is more plausible, given the evidence of the dedifferentiation phenomenon, as one of the forms of tumour cell plasticity, characterised by the formation of CSCs from non-stem cancer cells [137]. It is important to note that dedifferentiation does not occur in normal tissue due to the formation of a large number of genetic barriers. Tumour cells can break down such barriers, and dedifferentiation is a newly acquired property of tumour cells that distinguishes them from normal cells [161], which can be used for dissemination and is quite worthy of classification as a Cancer Hallmark. It is also important to note that not all tumours within the same localization can have this property, and not all tumours are able to metastasise, even if all other links of the metastatic cascade are not disturbed [162]. On the one hand, differentiated tumour cells are capable of dedifferentiation; on the other hand, differentiated tumour cells entering the internal organs are dedifferentiated and metastasise. American scientists have presented evidence of the importance of metastasis dedifferentiation [163]. They showed that selective ablation of Lgr5+ tumour stem cells from colorectal cancer limits the growth of the primary tumour but does not lead to tumour regression. Instead, tumours are supported by proliferative Lgr5 cells, which try to replenish the stem cell pool. This leads to rapid reinitiation of tumour growth after treatment stops. This process is critical for the formation and growth of colorectal cancer metastases in the liver. The MYC stem gene is activated after Lgr5+ destroys colorectal cancer stem cells in the tumour. In a later study, it was directly established that the majority of colorectal cancer metastases were formed by Lgr5− cells. These cells restored the Lgr5+ stem cell population, which gave rise to macrometastasis [164]. Chinese scientists discovered increased expression of Oct4 and Nanog in gefitinib-resistant NSCLC cells. They showed a multidrug resistance (MDR) phenotype and an EMT phenotype. Ectopic co-expression of Oct4/Nanog endowed NSCLC cells with CSC properties, including self-renewal, drug resistance, EMT, and high tumour-initiating activity [165]. Xu et al. (2018) believe that CSCs are not a stationary population of cells but are in dynamic homeostasis with differentiated cells. On the one hand, during asymmetric division, cancer stem cells constantly self-renew and form differentiated tumour cells. On the other hand, differentiated tumour cells are continuously dedifferentiated into stem cells for tumour growth and relapse. According to the authors, this completely cancels the therapeutic strategies aimed at destroying CSCs. Moreover, not all tumours in vivo are capable of dedifferentiation, and there is no homeostasis between non-CSCs and CSCs [166]. In our study, in the example of breast cancer, it was shown that the presence of amplified chromosomal regions with localization of stem genes in the tumour is associated with the ability to metastasise, determining the possibility of dedifferentiation of CD44−CD24− cells of primary breast tumour cultures in CD44+CD24− CSCs with active proliferation and mammary formation [150]. In this direction, we investigated the expression of the MYC and OCT4 proteins in subpopulations of breast tumour cells. Differentiated CD44 tumour cells with MYC and OCT4 stem protein expression are present in breast tumours. The concentration of these proteins is significantly higher in patients with metastases than in patients without metastases, while they express the EMT marker Snai2. These differentiated tumour cells with the expression of stem proteins can enter the bloodstream, and there are many more of them in patients with metastases than in patients without metastases. At the same time, CD44– with the expression of stem proteins in the breast tissue undergo EMT and enter the bloodstream in the form of CTCs, which, under the influence of EMT, become CD44+CD24+Oct3+ progenitor cells and their high concentration is associated with metastasis [167]. So, the dynamic state and mutual transformations of CSCs to non-CSCs and non-CSCs-to-CSCs and their role in metastasis are only just beginning to be investigated, and possible therapeutic strategies that block these transitions may prove successful. 8. Other Forms of CSC Plasticity Tumour cells and CSCs, in addition to dedifferentiation, are capable of a reversible transition between different cellular states, such as transdifferentiation, symmetric/asymmetric division, dormancy/proliferation, EMT/MET, and drug sensitivity/resistance [136,139,168]. Dedifferentiation occurs in the same clone, while transdifferentiation occurs between different cell clones. At the same time, aberrant activation of plasticity contributes to the appearance, maintenance, and progression of the tumour, causing aggressive behaviour of the CSCs [168]. Plasticity allows tumour cells and CSCs to switch between proliferative and calm phenotypic states, which contributes to their survival in distant organs and regulates tumour growth [169]. Highly invasive CSCs (introduced into the organ or dedifferentiated from non-CSCs) can remain dormant for several years before starting to grow [170], causing tumour relapse after therapy [171]. Internal and external factors ensure the acquisition of plasticity properties. Internal factors act through ectopic expression of transcription factors [172], stem genes [150], and EMT markers [173]. Several studies have confirmed the importance of key transcription factors, such as OCT3/4, SOX2, NANOG, and KLF4, in modulating CSC generation and regulating cell plasticity [77,143]. Overexpression of the EZH2 gene can increase the formation of mammospheres and CSC self-renewal in breast cancer [174]. Various mechanisms of epigenetic regulation have been mentioned, such as the state of bivalent chromatin, DNA methylation, and histone modifications that mediate CSC plasticity [175]. Loss of HOXC8 gene function in non-tumour epithelial cells of the mammary gland due to hypermethylation of its promoter DNA is associated with an increase in the CSC pool, increased self-renewal, and the emergence of a transformed phenotype [176]. CSCs are able to use epigenetic modifications to achieve their flexible nature [177], and this reversibility suggests an attractive potential for therapeutic targeting. External factors are signals from the microenvironment, such as TGFb, IL6, HIF, etc. [136,178,179,180]. Doherty et al. showed that macrophages can secrete a factor such as OSM in response to chemotherapy. OCM is a cytokine of the IL-6 family that can activate the dedifferentiation of triple-negative breast cancer cells into aggressive stem cells. This activation can be mediated by the transmission of STAT3/SMAD3 signals [181]. The mechanisms of CSC chemoresistance can also be divided into two main groups: internal resistance, which is associated with genetic changes, and external resistance, which is associated with the effects of the tumour microenvironment [182]. Genetic changes in CSCs include aberrant expression of a protein that detoxifies chemotherapeutic agents. For example, ABC transporters (especially ABCG2) are usually expressed at high levels in CSCs and can cause the leakage of chemotherapy drugs from cells. However, CSCs also usually have high expression of ALDH, which metabolises chemotherapeutic agents such as cyclophosphamide and reverses the toxic effects of chemotherapy [183]. The tumour microenvironment is an important factor in CSC chemoresistance. The activation of HIF expression promotes the formation of new blood vessel and CSC phenotypes in an hypoxic environment. This phenotype contributes to CSC chemoresistance [184]. 9. Conclusions CSCs are an extremely heterogeneous population of cells, and no single marker for CSCs has yet been found. Different studies use different markers as CSC markers. The most studied are the CD44+CD24−, ALDH+ and CD133+ CSC phenotypes. CSCs are dynamic populations and can undergo spontaneous transitions between states and phenotypes. CSCs can give rise to various types of undifferentiated CSCs and differentiate into new tumour pseudoorganoids. In fact, tumours can function as pseudoorgans due to CSCs, also supporting the local immune system and blood supply. The environmental behaviour of CSCs includes all possible forms of positive interactions, such as commensalism, mutualism, and symbiosis, which consists of the formation of heterotypic cells with immunocytes. These forms of CSCs appear in favourable conditions for tumour development. Under unfavourable conditions, especially during the treatment of tumours, negative forms of ecological behaviour dominate: amensalism, in the form of autophagy, parasitism, in the form of induction of autophagy of neighbouring cells, and predation, in the form of cannibalism or entosis. The role of CSCs in metastasis remains controversial. There are two opposing points of view. On the one hand, metastatic cells can originate from a CSC subpopulation with the necessary genetic changes to initiate tumour growth. These cells reach secondary organs via EMT or epithelial amoeboid transition (EAT). However, no markers of metastasis have been found thus far. It is not known why CSCs with favourable conditions in the primary tumour suddenly undergo EMT or EAT migrate, penetrate into secondary organs, and form metastases. On the other hand, metastatic potential can be acquired due to the ability to dedifferentiate non-CSCs to CSCs in possible metastasis. In this case, it is not necessary to look for markers of metastasis, but markers with the ability to dedifferentiate and block metastasis based on the dedifferentiation inhibition process can be developed. This hypothesis has increasingly more evidence. In addition, there is an opinion that CSCs are not a stationary population of cells but are in dynamic homeostasis with differentiated cells. This completely reverses the therapeutic strategies aimed at destroying CSCs. Author Contributions M.I., conceptualisation, writing—original draft; M.T., resources, software; N.L., conceptualization, software, writing—review and editing. 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 The signalling pathways of CSCs in breast cancer. Note: Created with Biorender.com. Wnt signaling pathway (Homo sapiens). https://www.wikipathways.org/index.php/Pathway:WP363 (accessed on 1 March 2022). Notch signaling (Homo sapiens). https://www.wikipathways.org/index.php/Pathway:WP268 (accessed on 1 March 2022). NRF2 pathway (Homo sapiens). https://www.wikipathways.org/index.php/Pathway:WP2884 (accessed on 1 March 2022). Hedgehog signaling pathway (Homo sapiens). https://www.wikipathways.org/index.php/Pathway:WP4249 (accessed on 1 March 2022). PI3K-Akt signaling pathway (Homo sapiens). https://www.wikipathways.org/index.php/Pathway:WP4172 (accessed on 1 March 2022). Figure 2 Ecological behaviour of CSCs, autophagy and entosis. (A) Programming TAM and CAF. Activation of ERK/STAT3 signaling molecules triggers M2 polarization of monocytes in breast tumours [86]. The recruitment of monocytes from the blood is carried out due to the production of chemokines—CCL2, CCL18, and cytokines CSF1, VEGF, etc., by tumor cells. When polarizing monocytes in M2-TAM CSC, CSF1, HIF1a, TLR2, and other factors are used. [87]. CAF could promote monocyte recruitment toward cancer cells through CXCL12/CXCR4 pathway [88]. CAF produces MMPs that degrade the matrix and promote invasion of CSCs. CAFs produce IL17a which stimulates symmetric division of CSCs [89]. M2-TAMs produce IL4, 10, 13, TGFb, and PGE2, which act on CSCs and stimulate their symmetric division, increasing their population [90]. Thus, this type of relationship can be seen as a commensalism between TAM, CAF, and CSCs. The interaction between TAM and CSCs is described in detail in the overview [91]. (B) Heterotypic fusion. Heterotypic fusion cells expressed the tumour marker EpCam and macrophage markers CD163, CD68, CSFR1 and CD66b [92]. The hybrid cells display EMT with a significant downregulation of E-cad and upregulation of N-cad, Vim and Snail, as well as an obviously increased expression of MMP-2, MMP-9, uPA, and S100A4. The TCF/LEF transcription factor activity of the Wnt/β-catenin pathway and the expression of its downstream target genes including cyclin D1 and c-Myc increased in the hybrid cells [93]. This type of relationship can be viewed as a symbiosis with the acquisition of new properties that are not characteristic of individual populations. (C) Autophagy. With the induction of autophagy in CSCs, the expression of ATG5-12 LC3B, and BECLIN1, as well as the transcription factors FOXO3A, SOX2, NANOG, and STAT3, which can lead to the induction of the stem phenotype, increased resistance to chemotherapy, EMT, increased migration activity, and survival of dormant cells [94,95,96,97]. Under starvation and toxicity, CSCs can also induce autophagy of neighboring microenvironmental cells and non-CSCs, through exposure to ROS, IL6, and HIF1a. In this case, cells produce metabolites that feed CSCs, in particular lactate [94]. In this case, the behavior of CSCs can be seen as parasitism. (D) Cel-in-Cell. E-cadherin and P-cadherin are key components of the adherent junctions of cells in entosis process [98]. These molecules bind CSCs and non-CSCs scavenged. Increased RHO–RHO-associated coiled-coil-containing protein kinase (ROCK) and/or diaphanous-related formin 1 (DIA 1)–actomyosin show in losers cells [99]. CSCs express ezrin, actin, and caveolins, which mediate uptake [100]. Absorbed cells undergo apoptosis, autophagy, or are destroyed by lysosomal digestion, providing CSCs with nutrients [99]. In addition, entosis can lead to the formation of aneuploidy in CSCs [101], and this may be a rapid mechanism for the formation of new chemoresistant clones during treatment. ijms-23-05058-t001_Table 1 Table 1 Possible CSC phenotypes of breast cancer according to the literature data. Phenotype Sources of Samples Source ABCG2+ Cell line HCC1937 [49] ANTXR1+ Mouse mammary metastatic tumor, cell line TMD231 [50] CD29+ Cell line MCF-7 [51] CD61+ Mouse mammary tumor MMTV-Wnt-1 [52] CD133+ Primary human breast tumor; cell lines MDA-MB-231, MCF-7, ZR-75 [53,54] CXCR4+ Metastatic breast cancer; cell line MCF-7; mouse cell lines 4T1, 4T07, 168Farn, 67NR [55] PROCR+ Cell line MDA-MB-361; adipose tissue of the mammary gland of mice with MDA-MB-231 [56] CD24+CD29+ Primary breast cancer BRCA1 mouse; mouse mammary tumor tissue MMTV-WNT1 [57] CD24+CD49f+ BRCA1 mouse primary breast tumor [58] CD44+CD24−/low Primary human breast tumor; cell lines MCF-7, BT-549, MDA-MB-231, MDA-MB-361, MDA-MB-468, T47D, ZR75, SK-BR-3, HCC1937 [44] CD49fhiCD61hi Transgenic mouse model HER2/neu [59] CD133+ALDH1+ Invasive ductal breast tumor [60] CD44+CD24−/lowABCG2+ MDA-MB-231 and MCF-7 cell lines [61] CD44+CD24−/lowALDH1+ Invasive ductal human breast cancer; cell lines MDA-MB-231, MDA-MB-453, MDA-MB-468, SUM149, SUM159, SK-BR-3, ZR-75, C 1954 [46,62] CD44+CD24−/lowEpCAM+ Cell lines MCF-7, MDA-MB-231, SUM149 и SUM159 [42] CD44+CD24−/lowSSEA-3+ MCF-7 and MDA-MB-231 cell lines [63] CD44+CD49f+CD133/2+ Primary ER–human breast tumor [64] CD44+CD133+ALDH1+/hi Cell line MDA-MB-468 [65] CD133hiCXCR4hiALDH1hi Invasive ductal human breast cancer [66] EpCAM+CD49f+ Aberrant human progenitor cells from BRCA1-mutant breast tissue [67] EpCAMhiPROCRhiSSEA-3+ MCF-7 and MDA-MB-231 cell lines [63] GD2+GD3+GD3Shi Cell lines MDA-MB-231 and MDA-MB-468 [68] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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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/ijerph19095118 ijerph-19-05118 Article Association of Postpartum Depression with Maternal Suicide: A Nationwide Population-Based Study https://orcid.org/0000-0002-6723-8131 Lee Yi-Liang 12 https://orcid.org/0000-0002-6631-4841 Tien Yun 3 Bai Yin-Shiuan 24 Lin Chi-Kang 1 Yin Chang-Sheng 12 https://orcid.org/0000-0002-4576-9900 Chung Chi-Hsiang 567 https://orcid.org/0000-0001-9041-0537 Sun Chien-An 89 https://orcid.org/0000-0002-9304-3418 Huang Shi-Hao 5610 https://orcid.org/0000-0001-6360-3958 Huang Yao-Ching 5610 https://orcid.org/0000-0002-3286-0780 Chien Wu-Chien 4567* Kang Chieh-Yi 11* Wu Gwo-Jang 125* Tchounwou Paul B. Academic Editor 1 Department of Obstetrics and Gynecology, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan; lylobgyn@gmail.com (Y.-L.L.); kung568@gmail.com (C.-K.L.); ycsobgyn@yahoo.com.tw (C.-S.Y.) 2 Department of Obstetrics and Gynecology, Kang Ning Hospital, Taipei 11490, Taiwan; catebai519@gmail.com 3 Department of Psychiatry, Taoyuan Psychiatric Center, Taoyuan 33058, Taiwan; edward820828@gmail.com 4 Graduate Institute of Life Sciences, National Defense Medical Center, Taipei 11490, Taiwan 5 Department of Medical Research, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan; g694810042@gmail.com (C.-H.C.); hklu2361@gmail.com (S.-H.H.); ph870059@gmail.com (Y.-C.H.) 6 School of Public Health, National Defense Medical Center, Taipei 11490, Taiwan 7 Taiwanese Injury Prevention and Safety Promotion Association, Taipei 11490, Taiwan 8 Department of Public Health, College of Medicine, Fu-Jen Catholic University, New Taipei City 24206, Taiwan; 040866@mail.fju.edu.tw 9 Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City 24206, Taiwan 10 Department of Chemical Engineering and Biotechnology, National Taipei University of Technology (Taipei Tech), Taipei 10608, Taiwan 11 Gynecologic Oncologist Division, Department of Obstetrics & Gynecology, Chi Mei Medical Center, Tainan City 71004, Taiwan * Correspondence: chienwu@ndmctsgh.edu.tw (W.-C.C.); albert0113@yahoo.com.tw (C.-Y.K.); gwojang@yahoo.com (G.-J.W.) 23 4 2022 5 2022 19 9 511821 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/). Background: To examine the association of postpartum depression (PPD) with maternal suicide in the Taiwanese population. Methods: We examined the medical records of women aged 18–50 years who experienced childbirth and had PPD (the study cohort, n = 2882), who experienced childbirth but did not have PPD (comparison cohort 1, n = 5764), and who neither experienced childbirth nor had PPD (comparison cohort 2, n = 5764) between 2000 and 2015. The patients were followed up until suicide, withdrawal from the National Health Insurance program, or 31 December 2015. Results: The rates of anxiety and depression symptoms, as well as the cumulative risk of suicide, were significantly higher in the study cohort. PPD was significantly correlated with an increased risk of maternal suicide and was associated with a greater risk of developing comorbidities such as hypertension, diabetes mellitus, hyperlipidemia, and stroke. The comparison cohorts did not differ significantly in terms of suicide risk. Conclusion: PPD was associated with a significantly higher rate of suicide and a shorter time to suicide after childbirth. Younger age, winter, and subclinical depression and anxiety positively predicted suicide in the study cohort. To prevent maternal suicide, clinicians should be observant of subclinical depression and anxiety symptoms among patients. depression postpartum puerperal disorders suicide ==== Body pmc1. Introduction Postpartum depression (PPD), a major depressive episode that occurs within 4 weeks of delivery, is one of the most common mental illnesses affecting women during and after pregnancy [1]. A meta-analysis including studies from 1989 to 2016 indicated that the prevalence of PPD ranged between 13% and 19% [2]. Studies have noted that PPD has complex pathophysiological mechanisms, from genetic factors to immune function, and rapidly fluctuating reproductive hormone levels [3]. The strong association of PPD with postpartum maternal morbidity and mortality in Western countries has been established. Patients with PPD experience symptoms including mood lability, irritability, obsessional worries, and thoughts of death [4]. Moderate-to-severe depression symptoms can persist for over 40 months after hospitalization and treatment for PPD [5]. PPD causes functional impairment and negatively affects patients’ families, especially their children [6]. The physiologically and psychologically adverse outcomes associated with PPD include preterm delivery, low birth weight, and impaired mother–infant bonding [7]. Regarding the long-term effects of PPD, the children of patients with this condition have higher rates of childhood behavioral problems and adolescent depression. Moreover, they have been documented to have poorer academic performance [8]. Reproductive hormones are pivotal to mood regulation, cognitive function, and responses to environmental stimuli. Menstrual-cycle-related changes in the levels of hormones, especially progesterone, lead to emotional disturbances in reproductive-aged women [9]. Reduced cerebrospinal fluid allopregnanolone levels have been reported in rodent research and clinical studies of depressive patients [10]. A study noted that lower progesterone levels during the postpartum period, among other changes in the levels of reproductive hormones, play a critical role in PPD [11]. An investigation reported that high-intent suicide attempts were more common when progesterone levels were low [12]. A study on Iranian women observed that lower serum progesterone concentrations were associated with a significantly higher rate of recurrent suicide attempts [13]. Despite the distinct hormonal fluctuation in the female population, other factors associated with the risk of depression have been mentioned, including age, gender, seasonality [14], and comorbid physical conditions [15]. However, their association with suicidality, especially in the postpartum population, is rarely discussed. Up to 20% of postpartum deaths were due to suicide, and suicide during pregnancy and the postpartum period is often attempted through more lethal methods than suicide in the general female population [16]. Moreover, several cases of maternal filicide due to severe maternal depression within 12 months of delivery have been reported [17]. Thus, the prediction of and early intervention for severe PPD with high suicidality are critical concerns for clinical gynecologists and psychiatrists. Although depression is highly prevalent worldwide, its characteristics vary across cultures. In a study by Bernert et al., depressive symptoms, especially suicide ideation, varied considerably among individuals from six European countries [18]. Further, cross-national variability in the prevalence of suicide behaviors between Western countries and Asian countries has been reported [19]. Despite the clinical importance of attempted and completed suicide among postpartum women, research on the associated or predictive factors of suicidal events among patients with PPD in the Asian population is lacking. By extracting data from medical records maintained by Taiwan’s Health and Welfare Data Science Center (HWDC), we conducted a retrospective study of women who experienced childbirth and had PPD, women who experienced childbirth but did not have PPD, and women who did not experience childbirth or have PPD. We analyzed the baseline characteristics and factors influencing suicidality among patients with PPD. 2. Materials and Methods 2.1. Data Sources Data on 2882 women who experienced childbirth and were diagnosed as having PPD between 2000 and 2015 were extracted from Taiwan’s National Health Insurance Research Database (NHIRD). The single-payer National Health Insurance program, launched in 1995, covers up to approximately 99% of the Taiwanese population. It maintains contracts with more than 97% of local clinics, regional hospitals, and medical centers in Taiwan [20]. The NHIRD contains comprehensive information on hospital visits and clinical comorbidities, as well as anonymized information on eligibility and enrollment. 2.2. Ethical Approval This study was conducted according to the Code of Ethics of the World Medical Association (Declaration of Helsinki). This study was approved by the Institutional Review Board (IRB) of the Tri-Service General Hospital (TSGH). The TSGH IRB waived the need for individual consent since all the identification data were encrypted in the NHIRD (IRB No. A202005111). 2.3. Study and Comparison Cohorts We examined data on 1,936,512 women who visited the inpatient or outpatient departments of hospitals from January 2000 to December 2015. As shown in Figure 1, patients with a delivery-related discharge code (International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes 650–659, OP73.59, OP73.6, OP74.0-OP74.1, 81004C-81005C, 81017C-81019C, 81024C-81026C, 81028C-81029C, and 81034) or with a diagnosis of PPD (ICD-9-CM code 648.4) or mental disorders (ICD-9-CM codes 290–319) before January 2000 were excluded. Patients who completed suicide, experienced self-inflicted poisoning or injury (ICD-9-CM codes E950–E959) before follow-up, were aged < 18 or >50 years, received radiotherapy (ICD-9-CM code V58.0) or chemotherapy (ICD-9-CM code V58.1) before or during follow-up, or had missing data were also excluded. The study cohort comprised 2882 reproductive-aged women who experienced delivery and had PPD (ICD-9-CM code 648.4) for which they made over three inpatient or outpatient visits between January 2000 and the end of the follow-up period (31 December 2015). The index date was the date of the first inpatient or outpatient visit with a medical record of PPD. We followed up with the patients until the event of suicide (i.e., the outcome of interest), withdrawal from the National Health Insurance program, or 31 December 2015, whichever was the earliest. The years of follow-up (mean ± SD) of study cohort, comparison cohorts 1 and 2 were 9.24 ± 10.01, 9.27 ± 10.37, and 9.98 ± 11.53, respectively. All patients were matched by age, socioeconomic status (indicated by insured premiums in TWD), and the season of their indexed visit to establish comparison cohorts of patients who experienced childbirth but did not have PPD (comparison cohort 1) and patients who did not experience childbirth or have PPD (comparison cohort 2). The comparison cohorts comprised 5764 patients in total. All patients were followed up through the NHIRD until the event of suicide or 31 December 2015. Definitions of the study variables are listed in Table S1. 2.4. Statistical Analysis Statistical analyses were performed using SAS software, Version 9.3, of the SAS System for Unix (SAS Institute Inc., Cary, NC, USA). Categorical variables were compared using the chi-square test for independence, whereas continuous variables were compared using the t test or the Fisher exact test. The cumulative risk of suicide among patients aged 18 to 50 years was estimated using Kaplan–Meier curve analysis. The significance level for all statistical analyses was p < 0.05. 3. Results 3.1. Clinical Characteristics The clinical characteristics of the patients at the time of enrollment and at the end of follow-up are summarized in Tables S1–S3, respectively. At baseline, the medical status of the study cohort for various conditions, including hypertension (HTN), diabetes mellitus (DM), hyperlipidemia, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), ischemic heart disease, coronary heart disease, stroke, cancer, and obesity, were modestly to significantly more favorable than were those of the comparison cohorts. However, the rates of HTN, DM, hyperlipidemia, COPD, CKD, anxiety, depression, and stroke were significantly higher (p < 0.001) in the study cohort at the end of follow-up than those of comparison cohort 1. Similar changes in the characteristics of the study cohort at the end of the follow-up were noted in the comparison of the study cohort with comparison cohort 2. A small proportion of the patients in comparison cohorts 1 and 2 had mood-related symptoms such as anxiety (0.31% and 0.68%, respectively) and depression (0.47% and 0.80%, respectively) (Table 1). The rates of anxiety and depression symptoms were significantly higher in the study cohort (11.55% and 42.26%, respectively). 3.2. Cumulative Risk of Suicide The cumulative risk of suicide among patients aged 18 to 50 years (Figure 2) was stratified by cohort. The mean follow-up period of the study cohort was 9.24 ± 10.01 years, whereas those of comparison cohorts 1 and 2 were 9.27 ± 10.37 and 9.98 ± 11.53 years, respectively (Table S2). The cumulative risk of suicide in the study cohort, estimated to be 20%, 38%, and 50% at the 5-year, 10-year, and 15-year follow-ups, respectively, was significantly higher than those of comparison cohort 1 (log-rank p < 0.001) and comparison cohort 2 (log-rank p < 0.001). The median durations from PPD diagnosis to suicide in the study cohort, comparison cohort 1, and comparison cohort 2 were 0.98, 5.12, and 4.26 years, respectively (Table S2). No significant difference was observed in the cumulative risk of suicide between comparison cohorts 1 and 2 (log-rank p = 0.892). 3.3. Factors Associated with Suicide Over the 15-year follow-up period, 313 patients (290, 13, and 10 in the study cohort, comparison cohort 1, and comparison cohort 2, respectively) completed suicide. PPD was significantly associated with an increased risk of maternal suicide. The hazard ratios (HRs) of the study cohort, with adjustment for the variables listed in Table S1, were 19.300 (95% confidence interval (CI): 5.977–62.255) and 18.743 (95% CI: 6.667–52.689) relative to those of comparison cohort 1 and comparison cohort 2, respectively (Table 2). The other variables listed in the table were subjected to Cox regression analysis to identify the factors associated with suicide. In the comparison cohorts, the adjusted HRs were significantly lower in individuals older than 38 years. In the comparison of the study cohort and comparison cohort 1, the anxiety-symptom subgroup had a significantly higher adjusted HR of 1.353 (95% CI: 1.040–2.473, p = 0.034). The HRs in the depression-symptom subgroup were significantly higher than those of comparison cohort 1 (HR = 2.689, 95% CI: 1.689–4.281, p < 0.001) and comparison cohort 2 (HR = 2.876, 95% CI: 1.805–4.584, p < 0.001; Table 2). The adjusted HRs of suicide in the anxiety- and depression-symptom subgroups in all the patients were 3.053 (95% CI: 1.921–4.852) and 3.053 (95% CI: 1.921–4.852; Table S3), respectively. 4. Discussion 4.1. Suicide and Subclinical Depression In the comparison cohorts of women without PPD, the adjusted HRs of suicide by subclinical depressive symptoms were significantly associated with a higher risk of suicide. Suicide attempts related to subclinical depression should be taken as seriously as suicide attempts related to severe clinical depression. A study reported that young adults with mild-to-moderate depressive symptoms experienced significant suicide ideation [21]. An investigation revealed that 27% of older adults who completed suicide did not satisfy the criteria for major depressive disorder [22]. 4.2. Suicide and Subclinical Anxiety Significantly higher adjusted HRs of suicide were found in the women experiencing anxiety symptoms in the study cohort and in both comparison cohorts. Anxiety symptoms also affected the course and severity of depression. Compared with non-anxious depression, anxious depression was found to be associated with relatively preserved cognitive function but more severe depressive symptoms [23,24]. 4.3. Suicide and Age Patients older than 38 years had a significantly lower risk of suicide than patients younger than 20 years. A study reported that suicide rates varied by sex and age. Moreover, younger age and female sex were protective factors against suicide among the general population [25]. However, age and suicide in reproductive-aged women were inversely correlated. Howard et al. reported that suicidal ideation was associated with younger age, multiparity, and more severe depressive symptoms in the postpartum period [26]. A study conducted in France on female inpatients with postpartum mental illness who were jointly hospitalized with their children revealed that younger age was independently associated with a higher rate of suicide attempts [27]. Another investigation noted that cultural factors played a substantial role in the prediction of suicide attempts [28]. Overall, younger age is a significant risk factor for postpartum suicide. 4.4. Suicide and Season Compared with the women without delivery, the adjusted HR of suicide was significantly higher in winter in the women with delivery and PPD (p = 0.023). However, a significant seasonality effect was not seen in the comparison of the women with and without PPD. In research on the use of light therapy for preventing seasonal affective disorder, a lower prevalence of winter depression in lower-latitude regions was found [29]. However, the seasonal effect on suicidality in patients with PPD has rarely been explored. A prospective study conducted in the United States suggested that seasonal variation in daylight more often increases the severity of depressive symptoms. However, the level of suicidality remained consistent regardless of this variation [30]. Although the population included in this study was from Taiwan, a-lower latitude region, the seasonal difference in suicidality was still significantly affected by delivery but not by PPD. 4.5. Mean Time to Suicide Overall, the study cohort had a significantly shorter time to suicide. In addition, the mean time to suicide (in years) was slightly longer in comparison cohort 1 than in comparison cohort 2. Pregnancy and delivery, as stressful life events in either the biological or the psychosocial dimensions, might increase an individual’s vulnerability to depression. Stressful life events have been demonstrated to be related to low brain-derived neurotrophic factor levels and higher vulnerability to depression in a murine model and in human epigenetic research [31,32,33]. The appropriate management of the stress of delivery and PPD may reflect strength in the biological, psychological, and sociocultural dimensions, which decreases suicidality. 4.6. PDD and Physical Diseases The proportion of patients in the study cohort who developed physical diseases was significantly higher than the corresponding proportions in comparison cohorts 1 and 2. This is notable because at baseline, the rate of physical diseases was significantly lower in the study cohort. Depression has been observed to be associated with stronger insulin resistance and higher risk of cardiac mortality [34,35]. The potential mechanisms of this association include hypothalamic–pituitary–adrenal axis dysfunction, increased proinflammatory factor activity, and reduced self-efficacy [36]. 4.7. Limitations This study has some limitations. First, although the medical records from the HWDC cover the majority of the Taiwanese population, they may not include suicide attempts leading to minor injuries that do not require medical support, or suicide attempts prevented by others. Second, whether the patients with PPD received adequate pharmacotherapy or psychotherapy during the follow-up period was not explored. Third, our data contained no information on depression as a product of biological or psychosocial factors or on other factors related to depression and suicide (e.g., early-life adversity, substance abuse, and lack of social support) [37]. 5. Conclusions PPD contributed to a significantly higher rate of suicide and a shorter time to suicide after childbirth. Younger age, the winter season, and subclinical depression and anxiety were negative predictive factors associated with suicide in individuals with PPD. PPD was associated with a greater risk of physical comorbidities, such as DM, HTN, hyperlipidemia, and stroke, at the end of the follow-up. To prevent suicide among the PPD population, clinicians should be observant of symptoms of subclinical depression and anxiety among their patients. The routine screening of PPD and the close monitoring of patients with this condition might be required for the detection of suicidality and for early coordination with mental health services. Acknowledgments The sponsors had no role in study design, data collection and analysis, the decision to publish, or the preparation of the manuscript. We appreciate Taiwan’s Health and Welfare Data Science Centre and Ministry of Health and Welfare (HWDC, MOHW) for providing access to the National Health Research Database. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095118/s1. Table S1: Characteristics of study in the baseline; Table S2: Years to suicide; Table S3: Factors of suicide by using Cox regression. Click here for additional data file. Author Contributions Conceptualization: Y.-L.L., S.-H.H., W.-C.C., Y.-C.H., C.-K.L., C.-S.Y., Y.T., Y.-S.B., C.-Y.K. and G.-J.W. Formal analysis: S.-H.H., C.-A.S., Y.-L.L., C.-K.L., C.-S.Y., Y.T., Y.-S.B., C.-Y.K., G.-J.W., W.-C.C. and C.-H.C. Investigation: C.-H.C., C.-A.S., S.-H.H., Y.-L.L., C.-K.L., C.-S.Y., Y.T., Y.-S.B., C.-Y.K. and G.-J.W. Methodology: W.-C.C., C.-H.C., C.-A.S., Y.-L.L., C.-K.L., C.-S.Y., Y.T., Y.-S.B., C.-Y.K. and G.-J.W. Project administration: W.-C.C., C.-H.C., Y.-L.L., C.-K.L., C.-S.Y., Y.T., Y.-S.B., C.-Y.K. and G.-J.W. Writing—original draft: S.-H.H., Y.-C.H., Y.-L.L., C.-K.L., C.-S.Y., Y.T., Y.-S.B., C.-Y.K. and G.-J.W. Writing—review and editing: W.-C.C., C.-A.S., Y.-L.L., C.-K.L., C.-S.Y., Y.T., Y.-S.B., C.-Y.K. and G.-J.W. All authors have read and agreed to the published version of the manuscript. Funding This study was supported by the Medical Affairs Bureau, the Ministry of Defense of Taiwan (MND-MAB-D-111134), the Tri-Service General Hospital Research Foundation (TSGH-B-111018, and TSGH-A-111012) and by research grants from the Chi Mei Medical Center (CMNDMC10208, and CMNDMC10304) and Kang Ning General Hospital, Taiwan. Institutional Review Board Statement This study was conducted according to the Code of Ethics of the World Medical Association (Declaration of Helsinki). This study was approved by the Institutional Review Board (IRB No. A202005111) of the Tri-Service General Hospital (TSGH). Informed Consent Statement Not applicable. Data Availability Statement Data are available from the National Health Insurance Research Database (NHIRD) published by the Taiwan National Health Insurance (NHI) Administration. Due to legal restrictions imposed by the government of Taiwan in relation to the “Personal Information Protection Act”, data cannot be made publicly available. Conflicts of Interest The authors declare no potential conflict of interest with respect to the publication of this article. Figure 1 The flowchart of study sample selection. Abbreviations: PPD, postpartum depression; RT, radiotherapy; CT, chemotherapy. Figure 2 Kaplan–Meier for cumulative risk of suicide among females aged 18–50 stratified by different cohorts with log-rank test. Delivery with PPD vs. delivery without PPD: Log-rank p < 0.001. Delivery with PPD vs. without delivery: Log-rank p < 0.001. Delivery without PPD vs. without delivery: Log-rank p = 0.892. Abbreviation: PPD, postpartum depression. ijerph-19-05118-t001_Table 1 Table 1 Characteristics of study at the endpoint of follow-up. Cohort Delivery with PPD Delivery without PPD Without Delivery Variables n % n % p n % p Total 2882 33.33 5764 66.67 5764 66.67 Suicide <0.001 <0.001 Without 2592 89.94 5751 99.77 5754 99.83 With 290 10.06 13 0.23 10 0.17 Age (mean ± SD, years) 31.25 ± 9.76 33.02 ± 7.28 <0.001 33.07 ± 7.39 <0.001 Age groups (years) <0.001 <0.001 ≤20 131 4.55 296 5.14 293 5.08 21–30 1622 56.28 3202 55.55 3223 55.92 31–34 458 15.89 1141 19.80 1198 20.78 35–37 244 8.47 514 8.92 373 6.47 38–40 197 6.84 257 4.46 281 4.88 41–43 126 4.37 102 1.77 98 1.70 ≥44 104 3.61 252 4.37 298 5.17 Insured premium (NT$) 0.991 0.979 <18,000 2527 87.68 5052 87.65 5060 87.79 18,000–34,999 247 8.57 498 8.64 493 8.55 ≥35,000 108 3.75 214 3.71 211 3.66 HTN <0.001 <0.001 Without 2678 92.92 5669 98.35 5653 98.07 With 204 7.08 95 1.65 111 1.93 DM <0.001 <0.001 Without 2714 94.17 5641 97.87 5657 98.14 With 168 5.83 123 2.13 107 1.86 Hyperlipidemia <0.001 <0.001 Without 2804 97.29 5729 99.39 5723 99.29 With 78 2.71 35 0.61 41 0.71 COPD 0.001 0.151 Without 2827 98.09 5707 99.01 5678 98.51 With 55 1.91 57 0.99 86 1.49 CKD <0.001 0.002 Without 2866 99.44 5757 99.88 5755 99.84 With 16 0.56 7 0.12 9 0.16 IHD 0.073 0.392 Without 2813 97.61 5660 98.20 5643 97.90 With 69 2.39 104 1.80 121 2.10 CHD 0.804 0.054 Without 2877 99.83 5752 99.79 5739 99.57 With 5 0.17 12 0.21 25 0.43 Stroke <0.001 <0.001 Without 2820 97.85 5733 99.46 5725 99.32 With 62 2.15 31 0.54 39 0.68 Cancer 0.517 0.317 Without 2803 97.26 5620 97.50 5583 96.86 With 79 2.74 144 2.50 181 3.14 Anxiety <0.001 <0.001 Without 2549 88.45 5746 99.69 5725 99.32 With 333 11.55 18 0.31 39 0.68 Depression <0.001 <0.001 Without 1664 57.74 5737 99.53 5718 99.20 With 1218 42.26 27 0.47 46 0.80 Obesity 0.088 0.088 Without 2872 99.65 5755 99.84 5755 99.84 With 10 0.35 9 0.16 9 0.16 Season <0.001 0.005 Spring 705 24.46 1319 22.88 1302 22.59 Summer 742 25.75 1408 24.43 1493 25.90 Autumn 820 28.45 1511 26.21 1555 26.98 Winter 615 21.34 1526 26.47 1414 24.53 Location <0.001 <0.001 Northern Taiwan 1081 37.51 2624 45.52 2658 46.11 Middle Taiwan 767 26.61 1662 28.83 1771 30.73 Southern Taiwan 806 27.97 1182 20.51 1012 17.56 Eastern Taiwan 213 7.39 283 4.91 294 5.10 Outlets islands 15 0.52 13 0.23 29 0.50 Urbanization level <0.001 <0.001 1 (The highest) 914 31.71 2180 37.82 2141 37.14 2 1300 45.11 2522 43.75 2502 43.41 3 247 8.57 467 8.10 537 9.32 4 (The lowest) 421 14.61 595 10.32 584 10.13 Level of care <0.001 <0.001 Hospital center 951 33.00 2127 36.90 2158 37.44 Regional hospital 1362 47.26 2266 39.31 2435 42.24 Local hospital 569 19.74 1371 23.79 1171 20.32 Abbreviations: HTN, hypertension; DM, diabetes mellitus; COPD, chronic obstructive pulmonary disease; CKD, chronic kidney disease; IHD, ischemic heart disease; CHD, coronary heart disease; p: Chi-square/Fisher exact test on category variables and t-test on continuous variables. ijerph-19-05118-t002_Table 2 Table 2 Factors associated with suicide by using Cox regression. Delivery with PPD vs. Delivery without PPD (Reference) Delivery with PPD vs. without Delivery (Reference) Variables Crude HR 95% CI 95% CI p Adjusted HR 95% CI 95% CI p Crude HR 95% CI 95% CI p Adjusted HR 95% CI 95% CI p Cohort Study cohort 22.958 8.394 62.785 <0.001 18.743 6.667 52.689 <0.001 26.697 8.421 84.638 <0.001 19.300 5.977 62.255 <0.001 Comparison cohort 1/2 Reference Reference Reference Reference Age groups (yrs) ≤20 Reference Reference Reference Reference 21–30 0.446 0.177 1.124 0.091 0.606 0.237 1.549 0.304 0.430 0.171 1.086 0.078 0.595 0.233 1.524 0.288 31–34 0.214 0.078 0.588 0.003 0.384 0.136 1.078 0.072 0.323 0.119 0.873 0.028 0.441 0.159 1.222 0.119 35–37 0.191 0.062 0.588 0.004 0.449 0.141 1.430 0.181 0.314 0.105 0.941 0.040 0.555 0.159 1.717 0.313 38–40 0.160 0.046 0.558 0.004 0.211 0.059 0.751 0.017 0.091 0.022 0.380 0.001 0.124 0.029 0.534 0.005 41–43 0.188 0.050 0.700 0.013 0.222 0.057 0.860 0.031 0.191 0.051 0.717 0.015 0.217 0.056 0.851 0.030 ≥44 0.180 0.066 0.492 0.001 0.183 0.065 0.516 <0.001 0.175 0.064 0.477 0.001 0.178 0.063 0.500 <0.001 Insured premium (NT$) <18,000 Reference Reference Reference Reference 18,000–34,999 0.743 0.104 5.333 0.768 0.578 0.074 4.505 0.602 0.579 0.081 4.160 0.589 0.573 0.074 4.457 0.596 ≥35,000 1.921 0.267 13.778 0.501 4.948 0.635 38.589 0.122 2.901 0.405 20.815 0.280 5.341 0.671 42.479 0.110 HTN Without Reference Reference Reference Reference With 0.174 0.025 1.248 0.083 0.372 0.049 2.836 0.342 0.163 0.023 1.166 0.072 0.376 0.049 2.871 0.347 DM Without Reference Reference Reference Reference With 0.203 0.029 1.459 0.114 0.373 0.498 2.853 0.344 0.193 0.027 1.387 0.104 0.398 0.051 3.088 0.380 Hyperlipidemia Without Reference Reference Reference Reference With 0.000 - - 0.306 0.000 - - 0.946 0.000 - - 0.270 0.000 - - 0.955 COPD Without Reference Reference Reference Reference With 0.498 0.069 3.571 0.490 0.578 0.072 4.630 0.606 0.405 0.056 2.902 0.370 0.568 0.071 4.526 0.594 CKD Without Reference Reference Reference Reference With 0.000 - - 0.641 0.000 - - 0.971 0.000 - - 0.581 0.000 - - 0.974 IHD Without Reference Reference Reference Reference With 0.663 0.093 4.758 0.683 1.164 0.156 8.688 0.861 0.497 0.069 3.571 0.490 1.146 0.153 8.564 0.873 CHD Without Reference Reference Reference Reference With 0.000 - - 0.649 0.000 - - 0.968 0.000 - - 0.572 0.000 - - 0.973 Stroke Without Reference Reference Reference Reference With 1.617 0.399 6.562 0.484 2.314 0.537 9.969 0.250 1.055 0.261 4.281 0.913 2.210 0.511 9.546 0.276 Cancer Without Reference Reference Reference Reference With 0.257 0.036 1.843 0.179 0.591 0.081 4.342 0.606 0.235 0.033 1.683 0.151 0.636 0.087 4.681 0.657 Anxiety Without Reference Reference Reference Reference With 3.185 1.829 5.547 <0.001 1.353 1.040 2.473 0.034 2.727 1.569 4.738 <0.001 1.337 1.004 2.443 0.047 Depression Without Reference Reference Reference Reference With 5.131 3.405 7.733 <0.001 2.689 1.689 4.281 <0.001 4.849 3.225 7.292 <0.001 2.876 1.805 4.584 <0.001 Obesity Without Reference Reference Reference Reference With 0.000 - - 0.742 0.000 - - 0.975 0.000 - - 0.595 0.000 - - 0.973 Season Spring Reference Reference Reference Reference Summer 0.751 0.410 1.377 0.372 0.729 0.392 1.356 0.335 0.871 0.464 1.631 0.685 0.864 0.455 1.640 0.872 Autumn 0.844 0.478 1.490 0.582 0.829 0.461 1.488 0.551 0.997 0.556 1.785 0.961 1.060 0.581 1.931 0.805 Winter 1.522 0.887 2.612 0.114 1.647 0.954 2.843 0.065 1.815 1.031 3.194 0.035 1.916 1.082 3.391 0.023 Location Had collinearity with urbanization level Had collinearity with urbanization level Northern Taiwan Reference Had collinearity with urbanization level Reference Had collinearity with urbanization level Middle Taiwan 1.391 0.861 2.245 0.159 Had collinearity with urbanization level 1.321 0.815 2.143 0.233 Had collinearity with urbanization level Southern Taiwan 1.025 0.603 1.740 0.878 Had collinearity with urbanization level 1.088 0.645 1.836 0.706 Had collinearity with urbanization level Eastern Taiwan 2.025 1.025 3.998 0.038 Had collinearity with urbanization level 1.632 0.806 3.304 0.160 Had collinearity with urbanization level Outlets islands 0.000 - - 0.947 Had collinearity with urbanization level 0.000 - - 0.944 Had collinearity with urbanization level Urbanization level 1 (The highest) 0.494 0.266 0.922 0.030 0.569 0.276 1.132 0.114 0.471 0.252 0.882 0.021 0.543 0.270 1.087 0.090 2 0.949 0.551 1.632 0.874 0.863 0.476 1.565 0.649 0.926 0.539 1.592 0.806 0.901 0.497 1.634 0.755 3 0.361 0.121 1.075 0.070 0.388 0.129 1.159 0.093 0.261 0.076 0.888 0.033 0.295 0.086 1.014 0.054 4 (The lowest) Reference Reference Reference Reference Level of care Hospital center 1.582 0.866 2.891 0.123 1.663 0.860 3.218 0.119 1.377 0.764 2.481 0.265 1.569 0.822 2.996 0.157 Regional hospital 1.840 1.033 3.278 0.034 1.494 0.817 2.735 0.176 1.412 0.801 2.487 0.212 1.326 0.731 2.404 0.327 Local hospital Reference Reference Reference Reference Abbreviations: HTN, hypertension; DM, diabetes mellitus; COPD, chronic obstructive pulmonary disease; CKD, chronic kidney disease; IHD, ischemic heart disease; CHD, coronary heart disease; HR = hazard ratio, CI = confidence interval, Adjusted HR: Adjusted variables listed in the table. 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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091105 animals-12-01105 Article Detection the eDNA of Batrachuperus taibaiensis from the Zhouzhi Heihe River Using a Nested PCR Method and DNA Barcoding https://orcid.org/0000-0001-6846-4125 Ma Hongying 1 Zhang Han 1 https://orcid.org/0000-0002-1330-1254 Deng Jie 1 Zhao Hu 1 Kong Fei 1 Jiang Wei 1 Zhang Hongxing 1 Dong Xianggui 2* Wang Qijun 1* Davis Michael E. Academic Editor 1 Shaanxi Key Laboratory for Animal Conservation, Shaanxi Institute of Zoology, Xi’an 710032, China; mhying7916@163.com (H.M.); hanhanr9@163.com (H.Z.); dengjie0311@ms.xab.ac.cn (J.D.); zhaohu2007@126.com (H.Z.); k.coffee@163.com (F.K.); jiangwei197981@163.com (W.J.); zhs@ms.xab.ac.cn (H.Z.) 2 College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China * Correspondence: xgdong@nwsuaf.edu.cn (X.D.); wqjab1@126.com (Q.W.) 25 4 2022 5 2022 12 9 110509 2 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 The Taibai stream salamander (Batrachuperus taibaiensis) is a protected species endemic to the Zhouzhi Heihe River. Few traditional studies have been conducted on the distribution of B. taibaiensis, leading to irregular discoveries. Environmental DNA (eDNA) is an ideal species detection technique that can increase accuracy and decrease the cost of population surveys. Here, we have established an optimal method for obtaining the eDNA of B. taibaiensis from water samples, which provides a theoretical basis and reference for resource investigation and protection of B. taibaiensis. Moreover, this study highlights the detection of a rare species in a river for use in further research. Abstract The Taibai stream salamander (Batrachuperus taibaiensis) is a recently described species of the genus Batrachuperus that occurs in the Zhouzhi Heihe River and is endangered in its native range. Here, we have established a method for water environmental DNA (eDNA) analysis of Batrachuperus using a series of optimizations. We have designed a specific set of primers for the genus Batrachuperus to amplify a 160 bp fragment of Cytb. The sequences were obtained from nested PCR on eDNA extracted from water samples, after which DNA barcoding was performed according to sequence analysis to determine the presence of the target species in the water. The method was validated using water from the Zhouzhi Heihe River with known B. taibaiensis populations and found that B. taibaiensis eDNA can move at least 150 m downstream from its point of origin. This study is the first to establish an optimal method for obtaining the eDNA of Batrachuperus from water samples, which provides a theoretical basis for resource investigation and the protection of B. taibaiensis in future research. It is also an example of the eDNA extraction of other species that live in similar waters and are less genetically diverse between species. Batarchuperus taibaiensis eDNA genus-specific primer nested PCR DNA barcoding ==== Body pmc1. Introduction Stream salamanders of the genus Batrachuperus (family Hynobiidae, Urodela, Amphibia) mainly live in clear water streams and prey on small shrimp and aquatic insects. The breeding season of Batrachuperus is March to April, and the eggs are laid in crevices where they live [1]. Stream salamanders, used in traditional Tibetan medicine in China, are used to treat traumatic injuries and joint pain. Due to their unique medicinal value, humans have begun to overexploit them, leading to a sharp decline in their population. Therefore, these species have been listed as endangered species [1]. To date, seven species of the genus Batrachuperus have been described in China: B. cochranae, B. karlschmidti, B. londongensis, B. pinchonii, B. taibaiensis, B. tibetanus, and B. yenyuanensis [1,2]. There are three types of Batrachuperus distributed in Shaanxi Qinling: B. pinchonii, B. tibetanus, and B. taibaiensis [1]. B. taibaiensis is a new species of the genus Batrachuperus that was found in the Zhouzhi Heihe River by Song Mingtao in 2001 [3]. The Heihe River rises from Er Ye Sea and Yu Huang Chi of Taibai Mountain in Zhouzhi Country and is characterized by rich plant and animal biodiversity [4]. The altitude of the Heihe River is 1200–3650 m, which is suitable for the survival of B. taibaiensis [5,6]. To date, research on the distribution of B. taibaiensis was conducted by Liang (2010) by combining morphology and molecular biotechnology to perform a statistical analysis based on the collected samples of B. taibaiensis [7]. However, these traditional methods depend on specific expertise and are difficult to standardize, which can create unknown rates of false absences in populations. Environmental DNA (eDNA) is an ideal species detection method that can increase the accuracy and decrease the cost of surveys. eDNA is any DNA that is freely present in the environment in the form of mucus, feces, skin cells, or gametes from an organism [8,9]. The study of aquatic species using eDNA has focused on vertebrate species, such as fish and amphibians [10,11,12,13], and has many applications, such as surveys in conservation biology [11,14,15], investigation of species invasion [12,13,16,17,18,19,20], researching species diversity and distribution [21,22], and estimating biomass measurements in a specific environment [23]. In the past decade, eDNA as a useful tool has seen remarkable interest in targeted species detection and biodiversity assessments [18]. The analysis of water eDNA involves a series of steps, including water eDNA capture, preservation, extraction, amplification, and sequencing to ensure a match with the target species. There are two types of water eDNA capture methods based on water quality and test conditions: direct freezing of water samples and freezing of filter membranes after filtration [17,21,24]. As for the preservation method, Ma (2021) compared common storage methods and found that a membrane directly soaked in alcohol is the best storage method that can increase eDNA yield. For eDNA extraction, Qiagen’s DNeasy Blood and Tissue Kit or the PowerWater DNA Isolation Kit were used as common commercial DNA kits [13,14,15,16,20]. In some cases, the phenol chloroform-isoamyl alcohol (PCI) extraction method was used to extract eDNA [22]. Conventional PCR and qPCR were conducted using a specific primer to identify the target species; the former sequences the target band and compares it with the sequence in the NCBI nucleotide repository to determine whether it is the sequence of the target species [10,11,19,25]; the latter uses the amplification curve to estimate the existence of the species or estimate how many species exist through copy number [12,26]. The nested PCR method is also a good choice when the concentration of aquatic species is low [27]. In the process of species identification, when the taxonomic differences between species are small, the classification of these species is conducted by DNA barcoding and phylogenetic analysis [20,28,29,30]. Here, we combined and optimized a series of eDNA steps to detect B. taibaiensis in the Heihe River and plan to use this method for long-term monitoring of the habitat of B. taibaiensis in the Heihe River. 2. Material and Methods 2.1. Field Sampling and Collection The Heihe River (Zhouzhi County, Shaanxi Province) originates from the Taibai Mountain National Nature Reserve. It is 125 km long, has a drainage area of 2258 km2 [31], and has good water quality and rich fishery resources (e.g., Brachymystax lenok tsinlingensis, Andrias davidianus, Batrachuperus, etc.) [4,32]. There are many tributaries along the Heihe River, such as the Ban Fangzi, Hua Erping, San Cha, and Miao Gou Rivers. Water samples were collected from two locations (San Cha River and Miao Gou River) (Figure 1). Sites were sampled at two time points: 4 April 2021 and 1 August 2021. In April, the water samples were collected from six sites within the San Cha and Miao Gou Rivers, and in August, from five sites at each of the two locations. The coordinates of each site and the distance between sites are shown in Table 1 and Figure 2, respectively. We filtered 2 L of surface water at each site through 0.45 µm cellulose nitrate filters (disposable filter funnel, 47 mm gridded filter, Thermo product no. 145-2405), and precautions were taken not to contaminate the water sample by wearing gloves during filtering. Two filters were used for each site, and 2 L of distilled water was filtered as a negative control for each sample. Each filter was preserved in 95% ethanol in a separate 2 mL cryopreservation tube, stored on ice in the field, returned to the laboratory, and stored at −80 °C until DNA extraction. 2.2. Batrachuperus Genus Specific Primers for Nested PCR Candidate primer sets were designed using default parameters in the Primer 5 software. To obtain sufficient PCR products and a clear band consistent with the expected amplicon size from the field water sample, a nested PCR strategy was used. We designed a new Batrachuperus genus-specific primer pair to nest the Ma (2021) primers inside its amplification product, which amplified a fragment of 160 bp in the Cytb gene. Amplification tests were performed to validate the new Batrachuperus genus-specific primers in vitro. The primer pairs used in this study are listed in Table 2. 2.3. Environmental DNA Extraction and Detection We extracted DNA from the tissue of Batrachuperus species and optimized the primer pair PCR annealing temperatures using the protocols described in Ma (2021) [33]. We used a DNeasy Blood and Tissue Kit (Qiagen, Dusseldorf, Germany) to extract the eDNA from the filter. First, we removed the filters from the ethanol and air-dried them for about 4–5 h. Next, we divided each filter in half with a sterile razor blade and transferred each of them to 2 mL extraction tubes, then added 500 mL ATL buffer into every tube and cut the filter membrane into tiny pieces, and then digested the content of every tube with 30 μL Pk for approximately 48 h at 56 °C. Referring to the instructions of the kit, we made the following adjustments: 400 mL of AL and 400 mL of absolute ethyl alcohol were added to each tube. Negative filters were used as controls for eDNA extraction to confirm that contamination did not occur during the process. The DNA concentration was assessed using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). PCR amplification of Cytb using the P2 primer described by Ma (2021) was performed using the following protocol. The amplification reaction was performed in a total volume of 25 μL, including 12.5 μL high fidelity Mix (Solarbio, Beijing, China), 9 μL double distilled water (ddH2O), 0.5 μL of each primer with final concentration, and 2.5 μL of template DNA. PCR conditions were as follows: an initial denaturation step at 94 °C for 3 min, 50 cycles of 94 °C for 10 s, annealing at 56 °C for 10 s, and elongation at 72 °C for 10 s. The final elongation step was performed at 72 °C for 3 min. The polymerase chain reaction was used as the template for nested PCR. Amplification of a smaller fragment of the Cytb gene with the P1 primer was performed using the same PCR conditions as those mentioned above. Ten µL of the PCR products were visualized on 2% agarose gel at 120 V for 20 min with 2 µL of Nucleic Acid dye (Solarbio, Beijing, China). Amplicon size was determined using a DM2000 ladder (Solarbio, Beijing, China). 2.4. Measures for Avoiding Contamination in eDNA Throughout this study, we used separate rooms for DNA extraction, eDNA extraction, PCR, and post-PCR procedures. During eDNA extraction, we used different clean foam boxes as simple laminar flow hoods when drying each filter. Meanwhile, we ran all PCR and nested PCR reactions in four duplicates to discard false-positive and false-negative results due to technical failures. When the amplification results were not clear (the bands were too weak), the amplification was repeated using 3.5 µL of the PCR template instead of 2.5 µL as described above. A minimum of two positive results from each site were considered valid to corroborate the presence of a species’ DNA in the sample, and we chose two positive PCR products for Sanger sequencing (Tsingke Biotechnology Co., Ltd., Beijing, China). 2.5. DNA Barcoding The reference sequences for Batrachuperus were downloaded from GenBank. The sequences obtained in this study and the additional reference sequences were aligned using ClustalW in MEGA 7 [34]. The aligned sequences in our study were compared for their similarity to those in the NCBI GenBank database (http://www.ncbi.nlm.nih.gov, 15 January 2022) using the basic local analysis search tool (BLAST). The highest similarity of the queried sequence with the database sequences was determined, and the sequences that had a 98–100% similarity with the database sequences were identified as the respective species. MEGA 7 software was used to calculate the interspecific genetic distance and intraspecific genetic distance based on the Kimura-2-parameter (K-2-P) two-parameter model [29,34]. An ML tree was built using MEGA 7 software [34]. The HKY + I + G substitution model was selected using the jModel Test 2.1.4 [35,36]. The other parameters were the default values. 3. Results 3.1. Total eDNA Yield in Different Seasons In this study, we successfully extracted eDNA from water samples from the Zhouzhi Heihe River using the DNeasy Blood and Tissue Kit (Qiagen, Dusseldorf, Germany) with optimized steps. The results showed that eDNA concentrations were higher in the August collections, especially in samples from the Miao Gou River (Table S1). 3.2. Species-Specific Nested PCR PCR was performed using the P2 primer [33] and high-fidelity mix, and four replicates were performed for each site (except for site 4-1-1 with six replicates). This PCR product was used as the template for nested PCR, and the nested PCR provided a clear band of 160 nucleotides (except for the negative controls). The nested PCR with at least two single clear bands from each site was considered valid in both the San Cha and Miao Gou River samples (Figure 3). Single clear bands were sequenced by nested PCR at Tsingke Biotechnology Co., Ltd. (Beijing, China). According to the PCR and nested PCR results, we found that the band intensities from the samples collected in April tended to be brighter than those from August, suggesting a higher concentration of Batrachuperus eDNA in April (Figure 3). We also found clear bands in which the water sites were at least 50 m and 150 m downstream from the source population in the river (Table 1 and Figure 3). 3.3. Detection of Batrachuperus taibaiensis DNA in Water Sample In this study, we chose two clear single bands for every collection site on the Heihe River in April and August (44 sequences in total). Sequence alignment was conducted between the sequences in this study, and Batrachuperus Cytb sequences were downloaded from NCBI, followed by truncation of the aligned sequences. The sequences of the amplified nested PCR products were deposited in the NCBI GenBank database with accession numbers OL351444-OL351487. The Cytb gene sequences obtained in this study were compared with those available in the GenBank (Cytb) database. Each species showed high values of intraspecific homology, and 98–100% of them were among the Batrachuperus species (Figure S1). In the Cytb sequences, the interspecies genetic distances among all Batrachuperus species were between 0.0532 and 0.1077 (Table 3), which were greater than the minimum species identification value of 0.020 suggested by Hebert [29]. The intraspecies genetic distances were between 0.0019 and 0.0322 (Table 4). The interspecies value was larger than the intraspecies value, indicating that Cytb can be used as an effective barcode gene for the accurate identification of Batrachuperus species. Meanwhile, the interspecies genetic distance between our sequence and B. taibaiensis from NCBI was the smallest. Therefore, we can speculate that the sequences in our study belong to B. taibaiensis. A molecular phylogenetic tree was constructed using the Maximum Likelihood Method (Figure 4). B. pinchonii, B. tibetanus, and B. taibaiensis sequences from the NCBI database were clustered separately in the evolutionary tree. Sequences in our study were clustered with B. taibaiensis, indicating that Batrachuperus inhabiting the Heihe River belongs to B. taibaiensis. The phylogenetic tree was consistent with the results of the DNA barcoding analysis. 4. Discussion This study is the first to demonstrate that eDNA methods can provide a basis for investigating the presence of B. taibaiensis in natural river habitats. B. taibaiensis is a vitally important and rare endemic species in the Qingling Mountains, and the application of eDNA techniques requires a series of optimized steps [37]. As shown in previous studies, a high-fidelity enzyme mix can better amplify the target band of water sample eDNA [33], and nested PCR is reliable when organisms are secretive or live at low densities [27]. Therefore, a high-fidelity enzyme mix and nested PCR method were used in our study to amplify the eDNA of Batrachuperus. Since the eDNA fragment of Batrachuperus was amplified using genus-specific primers, DNA barcoding and phylogenetic analysis were performed to determine the classification of the different species [20,28,29,30]. The results showed that the sequences obtained here had the smallest genetic distance from the B. taibaiensis sequence downloaded from NCBI and were also on the same branch as B. taibaiensis in the phylogenetic tree. It is necessary to increase the number of samples in the field and replicate more molecular workflows to enhance the reliability of the eDNA analysis of rare species [14,25]. This was done in our research. Studies on the distribution of B. taibaiensis have shown that this species is mainly located in the upper reaches of the Zhouzhi Heihe River basin [5,38]. Our research also revealed that the species of Batrachuperus inhabiting the Heihe River belonged to B. taibaiensis. Our study showed that overall, the total eDNA concentration in August was higher than that in April in the Heihe River (shown in Table S1), whereas band intensities of the eDNA concentrations of B. taibaiensis were higher in April than those in August (Figure 3). Therefore, we can infer that the total eDNA concentration is not proportional to the target eDNA concentration. This can be explained by factors that influence the eDNA concentration of the target species. More populous species had a higher rate of detection and concentration of eDNA [12]. In our study, the samples of B. taibaiensis collected in April were found at intervals of 20–30 m, whereas in August, the intervals were 50–100 m. We obtained a high concentration of B. taibaiensis eDNA in April. We also need to take into account the sampling season and physiological conditions of the animals [11,39]. Unlike rainy August, April with warm temperatures is also the breeding season for B. taibaiensis [5,40], which leads to increased mobility and metabolism of B. taibaiensis and more DNA released into the environment through skin excretions, sloughed cells, and mucus excretion. We detected B. taibaiensis eDNA in the stream where they live; however, the extent to which the target eDNA can be transported downstream through a flowing stream is unknown. We collected eDNA samples 50 and 150 m downstream from the source population of the river. The first reason for these choices is that the electricity required for the filtering device is often unavailable in the field; therefore, the number of filtered samples is limited. Another reason could be related to the results of previous studies. As both salamanders and B. taibaiensis live in cool, shady stream conditions, their transportation distances may be similar. Pilliod (2014) collected eDNA samples from caged salamanders at 5 m and 50 m downstream of the original source [41]. Although the eDNA of salamanders was only detected at 5 m, the eDNA of B. taibaiensis was also detected at 10 m (Table 1). Therefore, we wanted to identify whether the eDNA of B. taibaiensis could be collected at 50 m, and the answer was yes. The reason for this phenomenon may be that the caged salamanders had some stress response when placed in the river, whereas B. taibaiensis remained calm in the water. In other words, if there is no frequent movement of individuals, the degradation rate of eDNA will decrease [41]. Eichmiller (2014) [12] and Jane (2015) [42] detected target fish eDNA at 100 m and 239.5 m downstream, respectively. Because fish have a higher detection rate, we chose 150 m as the longest distance from the source location of B. taibaiensis, and eDNA could also be detected at this distance. In the future, we can extend the distance to obtain more information about the transport distance of B. taibaiensis eDNA because eDNA may travel much further distances, possibly in the order of kilometers [8]. In summary, B. taibaiensis eDNA can reach at least 150 m downstream from its point of origin, and we suspect that the density of the population has a significant influence on eDNA transport distance. 5. Conclusions We have demonstrated that B. taibaiensis eDNA from the Heihe River can be amplified using genus-specific primers by nested PCR and barcoding sequence analysis. B. taibaiensis eDNA can be obtained at least 150 m downstream from its point of origin. This approach can now be applied for the detection of other rare species in rivers. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ani12091105/s1, Table S1: Total eDNA concentration. Figure S1: List of species identification results using the NCBI GenBank in this study. Click here for additional data file. Author Contributions Conceptualization, H.M.; methodology, H.M.; software, H.M. and X.D.; validation, H.M. and X.D.; formal analysis, H.M. and Q.W.; investigation, H.M. and H.Z. (Han Zhang); resources, H.Z. (Hongxing Zhang); data curation, H.M.; writing—original draft preparation, H.M.; writing—review and editing, H.M., H.Z. (Hongxing Zhang), and Q.W.; visualization, H.M.; supervision, J.D., H.Z. (Hu Zhao) F.K. and W.J.; project administration, H.Z. (Hongxing Zhang); funding acquisition, H.M. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Shaanxi Academy of Science of China (grant No. 2020k-19; grant No. 2017k-10), Shaanxi Science and Technology Department of China (grant No. 2022NY-045), Natural Science Foundation of Shaanxi Province of China (grand No. 2020JQ-972). Institutional Review Board Statement Not applicable. Data Availability Statement The sequences data were deposited in the NCBI GenBank database with accession numbers OL351444-OL351487. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Geographic area of partial Heihe River (red circles represent locations where water samples were collected in our study). Figure 2 Schematic diagram of sampling sites within San Cha River and Miao Gou River (numbers in black represent the data of April collection, and the numbers in purple represent August collection; arrow indicates the direction of river). Figure 3 PCR and nested PCR results of water eDNA sample for San Cha River (A) and Miao Gou River (B). (M, marker; B, blank; 1-6: last number of site name in Table 1). Figure 4 Molecular phylogenetic tree by Maximum Likelihood method (The ML tree is based on the HKY + I + G model; B. p, Batrachuperus pinchonii, B. t, Batrachuperus tibetanus, B. ta, Batrachuperus taibaiensis; red circles show the sample sequences from this study; Liua tsinpaensis and Salamandrella keyserlingii as an outgroup; numbers on branch in the tree are bootstrap values with percentage.). animals-12-01105-t001_Table 1 Table 1 The information on each site where we collected water for eDNA analysis (The site where the Batrachuperus species appeared when we collected water samples is shown with “+”, otherwise with “−”). Collection Time Location Site Name Coordinates Distance between the Most Upstream Site and the Other Site (m) Batrachuperus Species Appeared or Not 4 April San Cha river 4-1-4 33.82884 N, 107.81094 W 0 + 4-1-3 33.82897 N, 107.80912 W 50 + 4-1-2 33.82917 N, 107.81048 W 80 + 4-1-1 33.82938 N, 107.81062 W 90 + 4-1-5 33.82890 N, 107.81094 W 140 − 4-1-6 33.82918 N, 107.81126 W 240 − Miao Gou river 4-2-4 33.82928 N, 107.95356 W 0 + 4-2-3 33.82919 N, 107.95385 W 40 + 4-2-2 33.82918 N, 107.95362 W 65 + 4-2-1 33.82920 N, 107.95325 W 80 + 4-2-5 33.82859 N, 107.95459 W 140 − 4-2-6 33.82858 N, 107.95496 W 240 − 1 August San Cha river 8-1-3 33.82899 N, 107.80912 W 0 + 8-1-2 33.82837 N, 107.80970 W 150 + 8-1-1 33.82951 N, 107.81059 W 250 + 8-1-4 33.82928 N, 107.81107 W 300 − 8-1-5 33.82932 N, 107.81181 W 400 − Miao Gou river 8-2-3 33.82969 N, 107.95307 W 0 + 8-2-2 33.82942 N, 107.95377 W 200 + 8-2-1 33.82925 N, 107.95342 W 300 + 8-2-4 33.82875 N, 107.95449 W 360 − 8-2-5 33.82852 N, 107.95499 W 460 − Note: 4-1-1, 4-2-1, 8-1-1, 8-2-1 are the source population sites in our study. animals-12-01105-t002_Table 2 Table 2 Primer pairs for partial Cytb gene amplification of samples from Batrachuperus genus. Primer Primer Sequence Annealing Temperature (°C) Size (bp) Origin P1 F:5′-GTAGATAAGGCTACTCTTACTC-3′ R:5′-ATGGGTGGAATGGAACT-3′ 46 160 This study P2 F:5′-TTGAGGTGGGTTCTCTGTAGATAAG-3′ R:5′-GGTTGGCGGGTGTAAAA-3′ 52 290 [33] animals-12-01105-t003_Table 3 Table 3 The interspecies genetic distances of Batrachuperus. B. pinchonii B. tibetanus B. taibaiensis Species in Our Study B. pinchonii / 0.0677 ± 0.0204 0.0963 ± 0.0266 0.1077 ± 0.0313 B. tibetanus / / 0.0928 ± 0.0257 0.0947 ± 0.0282 B. taibaiensis / / / 0.0532 ± 0.0195 Note: Data are presented as interspecies genetic distance ± standard deviation. animals-12-01105-t004_Table 4 Table 4 The intraspecific genetic distances of each Batrachuperus species. B. pinchonii B. tibetanus B. taibaiensis Species in Our Study intraspecific genetic distances 0.0253 ± 0.009 0.0310 ± 0.0109 0.0322 ± 0.0113 0.0019 ± 0.0018 Note: Data are presented as intraspecies genetic distance ± standard deviation. 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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093508 sensors-22-03508 Article High Throughput Priority-Based Layered QC-LDPC Decoder with Double Update Queues for Mitigating Pipeline Conflicts https://orcid.org/0000-0003-3709-0188 Li Yunfeng Li Yingchun Ye Nan https://orcid.org/0000-0002-6411-8046 Chen Tianyang Wang Zhijie Zhang Junjie * Fang Yi Academic Editor Gao Yue Academic Editor Niu Kai Academic Editor Yin Feng Academic Editor Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai 200444, China; lyf1282@shu.edu.cn (Y.L.); liyingchun@shu.edu.cn (Y.L.); aslanye@shu.edu.cn (N.Y.); tyral_chen@shu.edu.cn (T.C.); zhijie_wang@shu.edu.cn (Z.W.) * Correspondence: zjj@staff.shu.edu.cn 05 5 2022 5 2022 22 9 350808 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/). A high-throughput layered decoder for quasi-cyclic (QC) low-density parity-check (LDPC) codes is required for communication systems. The preferred way to improve the throughput is to insert pipeline stages and increase the operating frequency, which suffers from pipeline conflicts at the same time. A priority-based layered schedule is proposed to keep the updates of log-likelihood ratios (LLRs) as frequent as possible when pipeline conflicts happen. To reduce pipeline conflicts, we also propose double update queues for layered decoders. The proposed double update queues improve the percentage of updated LLRs per iteration. Benefitting from these, the performance loss of the proposed decoder for the fifth generation (5G) new radio (NR) is reduced from 0.6 dB to 0.2 dB using the same quantization compared with the state-of-the-art work. As a result, the throughput of the proposed decoder improved up to 2.85 times when the signal-to-noise ratio (SNR) was equal to 5.9 dB. double update queues high throughput pipeline conflicts QC-LDPC priority-based National Key Research and Development Program of China2021YFB2900800 This work was supported in part by National Key Research and Development Program of China (2021YFB2900800), the Science and Technology Commission of Shanghai Municipality (Project No. 20511102400, 20ZR1420900) and 111 project (D20031). ==== Body pmc1. Introduction As a forward error correction (FEC) code, low-density parity-check (LDPC) code [1] has an excellent performance close to the Shannon limit. Due to its exploitable parallelism, LDPC decoder was easily implemented on field-programmable gate array (FPGA) devices [2]. Among various LDPC codes, a quasi-cyclic (QC) LDPC code exhibits high facility in structural routing and memory addressing. QC-LDPC code has a parity-check matrix (PCM) that is composed of all-zero submatrices and circularly shifted identity submatrices. PCM can be simply represented by a base graph matrix. Owing to these advantages, QC-LDPC is now widely applied in many communication standards (ITU [3], DVB-S2X [4], WiMAX [5], and 5G NR [6]). With the increase in communication rate, LDPC decoder, as a key component, needs to increase the throughput. The methods involve reducing the iteration number together with the decoding cycles per iteration and increasing the operating frequency [7]. In order to decrease the number of iterations, the layered decoding schedule [8] is widely applied since it shows twice decoding convergence for the same decoding performance compared with the flooding decoding schedule [9]. The decoding cycle per iteration can be reduced by improving the processing parallelism. Considering the tradeoff between the throughput and hardware utilization, the common approach is to use the partially parallel architecture [10]. The parallelism is usually equal to the lifting size (Z), which is the size of submatrix in PCM. Higher operating frequency can be achieved by inserting more pipeline stages. Nevertheless, this will increase the probability and number of pipeline conflicts. Pipeline conflicts will impact the update of log-likelihood ratios (LLRs), result in the loss of decoding performance, and increase extra iteration numbers for the same decoding performance. 1.1. Related Works To address the pipeline conflicts, various solutions have been proposed. The conventional solution is to insert additional stall cycles and wait for a conflict-free pipeline. Pipeline conflicts can be eliminated by adjusting not only the processing order of submatrices in the layer but also the processing order of layers [11]. By adopting this method, [12] a throughput of 1.2 Gbps at eight iterations in 5G NR is achieved. Nevertheless, pipeline conflicts still occur frequently by using this method in a relatively dense base graph matrix. Ref. [13] proposes to split the layer with the size equal to Z into several smaller layers to reduce the occurrence of pipeline conflicts while the throughput is lowered as well. The residue-based layered schedule [14] postpones the update of LLR and stores the contributions of decoding into registers when a pipeline conflict occurs. However, there exists an extreme circumstance that LLR of a variable node may never be updated when pipeline conflicts always happen to it in a dense base graph matrix. This significantly degrades the performance of the layered schedule. In [15], the flooding schedule is adopted when pipeline conflicts occur in a layered decoder, so it is called a hybrid decoder. In [16], an improved normalized probabilistic min-sum algorithm (INPMSA) was proposed to compensate the decline in the decoding performance. In the check node unit (CNU), the probabilistic second minimum is revised by using the first minimum and proportion fixing. 1.2. Overview and Contribution In this paper, we focus on mitigating pipeline conflicts at a high operating frequency in a layered decoding schedule. This is achieved by the following contributions: (1) Double update queues replace the single update queue in the layered LDPC decoder. In comparison with [15], the percentage of up-to-date LLR read operations per iteration with double update queues during the decoding was increased by up to 31%. (2) The priority-based layered decoding schedule is proposed to update LLRs as frequent as possible when the pipeline conflicts cannot be avoided. Due to a higher percentage of updated LLRs and more frequent update of LLRs, the priority-based decoder with double update queues lower performance loss from 0.6 dB to 0.2 dB compared with [15]. Comparing with residue-based decoder [14] using double update queues, the proposed decoder shows an advantage of 0.1 dB. (3) As a direct result of the proposed layered LDPC decoder, the throughput of our proposed decoder for 5G NR is up to 2.85 times that of [15] with the same quantization on the Xilinx VC709 evaluation board at the same signal-to-noise ratio (SNR). The remaining sections are organized as follows. In Section 2, the layered decoding schedule is introduced. In Section 3, the proposed priority-based layered decoding schedule and double update queues are described. The structure of the proposed priority-based layered decoder with double update queues and the flow chart of the proposed decoder are also described. In Section 4, the results of simulation and hardware implementation are presented. Finally, Section 5 provides a conclusion to this paper. 2. Layered Decoding Schedule LDPC code is decoded based on the iterative message-passing algorithm, which means the decoding messages are exchanged frequently between the check nodes and variable nodes. The decoding messages include variable-to-check message, check-to-variable message, and a posterior probability LLR (APP-LLR). In the layered decoding schedule, LLRs are commonly updated after the update of variable-to-check messages and check-to-variable messages in a layer. For convenience of presentation, we make the following definitions. Vv,cit denotes the variable-to-check messages that propagated from the variable node v to the check node c at the it-th iteration. Rc,vit denotes the check-to-variable messages that propagated from the check node c to the variable node v at the it-th iteration. LLR corresponding to the variable node v in the it-th iteration is represented as LLRvit. Before the start of decoding, APP-LLR from an additive white Gaussian noise (AWGN) channel is initialized as given by (1) LLRvinit=logPxv=0|yvPxv=1|yv=2yvσ2, where Pxv=0|yv represents the probability that xv is equal to 0 and Pxv=1|yv represents the probability that xv is equal to 1. The received signal from the channel is represented as yv and channel noise variance is represented as σ2. In the it-th iteration, the variable-to-check messages are generated with the check-to-variable messages from the previous iteration and LLR as given by (2) Vv,cit=LLRvit−Rc,vit−1. In the hardware implementation, the min-sum algorithm (MSA) [17] is employed for the update of check-to-variable messages because of the friendly implementation. It turns the complexity computations into the simple comparison operations at the cost of decoding performance degradations. MSA only needs to select two minimum messages from check nodes. The calculation of MSA is given by (3) Rc,vit=∏v′∈Vc\vsgnVv′,cit·minv′∈Vc\vVv′,cit, where Vc denotes the group of variable nodes that connected to the check node c and Vc\v represents the same group of variable nodes except the variable node v. In order to improve the decoding performance, two improved min-sum algorithms were proposed in [18]. They use a correction factor to correct the magnitude of the two minimum values in the check-to-variable update. The offset min-sum algorithm (OMSA) subtracts a correction factor β from the two minimum values. The normalized min-sum algorithm (NMSA) uses a correction factor α to multiply the two minimum values. The OMSA and NMSA are calculated as given by the two following equations (4) Rc,vit=α∏v′∈Vc\vsgnVv′,cit·minv′∈Vc\vVv′,cit (5) Rc,vit=∏v′∈Vc\vsgnVv′,cit·maxminv′∈Vc\vVv′,cit−β,0. The APP-LLR of the variable node v is updated as the following equation (6) LLRvit=Vv,cit+Rc,vit At the end of an iteration, the codeword C is decided based on the value of APP-LLR. If the APP-LLR of variable node v is no less than zero, the bit will be decided to be 0. If the APP-LLR of variable node v is negative, the bit will be decided to be 1. The decided codeword C and the parity-check matrix H then generate the syndrome S=C×HT. Suppose that the LDPC decoder considers an early termination and the number of iterations is limited in the hardware implementation. There exist two cases to terminate the decoding. One case is that the syndrome is equal to zero and the decoding has not reached the set maximum iteration number. The other case is that the syndrome is not equal to zero when the iteration number has reached the set maximum iteration number. 3. Priority-Based Layered QC-LDPC Decoder with Double Update Queues 3.1. Priority-Based Layered Decoding Schedule In the layered schedule, the LLR in a layer has not been updated yet while the next layer needs this updated LLR. This is called pipeline conflict. When a pipeline conflict occurs, the practical method is to ignore the update of LLR. However, a small percentage of ignored updates will lead to significant performance degradation [19]. For this reason, we propose a priority-based layered schedule. In the layered schedule, the update of LLR can be equivalent to the sum of LLR and difference between the newly calculated check-to-variable messages in the current iteration and the one in the previous iteration [15]. This difference can be understood as a gain that helps the decoding. The update of LLR can be expressed as (7) (7) LLRvLi,it=LLRvLi−1,it+RLi,it−RLi,it−1=LLRvLi−1,it+GvLi,it, where LLRvLi,it represents the LLR for the variable node v at the it-th iteration in the Li  layer, RLi,it represents the check-to-variable messages at the it-th iteration in the Li layer and GvLi,it represents the gain for the variable node v at the it-th iteration in the Li layer. In the priority-based layered schedule, when a pipeline conflict happens to two check nodes between two adjacent layers, Li and Li+1, new LLR will be updated in the layer Li. The gain GLi+1,it will be calculated in the layer Li+1. The gain GLi+1,it then will be added to the newly updated LLR later. In this way, updates of LLRs can be guaranteed no matter how the base graph matrix is dense. Suppose there are three check nodes in layers Li, Lj and Lk connected to the same variable nodes. During decoding, pipeline conflicts happen between Li and Lj, Lj and Lk. The priority-based layered schedule works as follows. The LLR in layer Li can update in priority and get LLRvLi,it. Due to pipeline conflicts, the layer Lj reuses the old LLR value LLRvLi−1,it to calculate the gain GvLj,it. If the update of LLR in layer Li can be done before decoding the layer Lk, then the layer Lk can update the value based on the result of LLRvLi,it and the gain GvLj,it can also be added to the updated LLR in layer Lk. As shown in Figure 1, the update can be expressed as (8) and (9) (8) LLRvLi,it=VLi,it+RLi,it (9) LLRvLk,it=VLk,it+RLk,it+GvLj,it where the variable-to-check message at the it-th iteration in the layer Lk is denoted as VLk,it. 3.2. Structure of the Priority-Based Layered LDPC Decoder with Double Update Queues Figure 2 shows the detailed architecture of priority-based layered LDPC decoder with double update queues. The parallelism of processing units is equal to the size of submatrix in the corresponding PCM. In the WiMAX decoder, the parallelism is equal to 96 [5]. In the 5G NR decoder, the parallelism is equal to 384 [6]. Before decoding, LLRs are initialized and denoted as LLRitits. They are stored into the LLR RAM. LLR RAM is composed of a simple dual-port block RAM (BRAM) which is used to store the latest updated LLR. The old LLR value can be read repeatedly provided that no new LLR value is written in the same address. This feature is conductive to the implementation of the proposed decoding schedule. When the decoding starts, LLR is read out from RAM according to the address given and sent to the LLR barrel shifter. It is not essential to use the reverse barrel shifter to shuffle the submatrix as the identity matrix before storing back to the LLR RAM [20]. Instead, the barrel shifter that shuffles based on the absolute shift value can be well applied in the decoder. After shuffling, LLR is sent into variable node units (VNUs) to calculate Vits. Then, Vits are passed to the CNUs. At the same time, Vits are buffered into FIFOs waiting for the update of LLR. In the CNUs, the minimum (min) and the second minimum (smin) absolute value, the index of the minimum value (min index), and the sign product (sign product) of Vits are achieved. Then, registers will store this intermediate data until new Rits are required for update in the next layer. Rits generated from CNU are added with Vit buffered out from FIFO and achieve the updated LLRs. When LLRs are updated, they are stored back to the LLR RAM. In this paper, we propose double update queues instead of a single update queue [21] to update the LLRs. Compared with a single update queue, double update queues accelerate the update of LLRs in a layer and decrease the occurrence of pipeline conflicts. This will be discussed in detail in Section 3.3. When pipeline conflict happens, the gain calculator module and gain adder module are used to migrate the conflicts. These will also be discussed in detail combining with the flow chart in Section 3.3. Due to the design of priority-based schedule and double update queues, the signs of all the Vits are buffered into four separated FIFOs in the CNU. The two minimum values, the sign product and the index of the minimum are used to generate the Rit−1s for VNU used in the next iteration and Rits for overlapping submatrices, non-overlapping variable nodes (double update queues) and gain (priority-based schedule). 3.3. Double Update Queues There are two reasons for pipeline conflicts in the layered decoder. The first reason is that the inserted pipeline stages result in the highly delayed update to LLRs. When increasing the operating frequency by inserting more pipeline stages, it will inevitably lead to conflict probability. The second reason is the failure to buffer the variable-to-check message out from FIFO and add it to the corresponding check-to-variable message to obtain the updated LLR when the next layer needs this LLR. In order to address this problem, it is necessary to increase the flexibility of data being buffered into FIFO and buffering out from FIFO. If variable-to-check messages in one layer can be stored in several FIFOs separately, then variable-to-check messages can be buffered out in time for the update of LLRs when the next layer needs them. In this way, pipeline conflicts can be eliminated. However, this consumes plenty of memory resources. To trade off the memory resources and the possibility of pipeline conflicts, we proposed the double update queues. In the double update queues, we use two FIFOs to buffer variable-to-check messages. One FIFO is called overlapping FIFO. The other FIFO is called non-overlapping FIFO. Overlapping FIFO is used to buffer those variable-to-check messages whose LLRs will continue to be decoded in the next layer. A non-overlapping FIFO is used to buffer variable-to-check messages whose LLRs will not be needed in the next layer. Note that if an LLR of a submatrix can be updated regularly in the current layer and would suffer pipeline conflicts in the next layer, the variable-to-check message of this submatrix in the current layer will be buffered into the non-overlapping FIFO and its updated LLR will be written back to the LLR RAM. The variable-to-check message of this submatrix in the next layer will not be buffered into any FIFOs because the corresponding LLR cannot be updated. FIFOs for buffering the signs need to be divided into overlapping and non-overlapping FIFOs as well. Two separate queues to generate new Rits in CNU are also needed. In each update queue, variable-to-check messages are added with check-to-variable message to achieve their updated LLR separately. In this way, LLRs can be updated in double queues. Combined with the priority-based schedule and double update queues, we introduce the decoding flow chart in detail as shown in Figure 3. In our design, variable nodes in a layer are processed in units of submatrix. For simplicity of presentation, the variable nodes in a submatrix are denoted as variable node group (VNG). Before decoding, the processing order of VNGs in a layer needs to be reordered. In a layer, the VNGs that have not been decoded in the previous layer are decoded first. Next are the VNGs that have been decoded in the previous layer. When the processing order of VNGs is determined, decoding starts. LLRs are successively read out from LLR RAM. After the processing of barrel shifter and VNU, variable-to-check messages are obtained. According to the mechanism of double update queues, variable-to-check messages are buffered into overlapping FIFO or non-overlapping FIFO. Then, the check-to-variable messages are updated. The next step is the process of the LLR update when the pipeline conflict occurs or does not occur. If no pipeline conflicts happen, LLRs can be normally updated as the layered schedule. After update, LLRs of non-overlapping VNGs will be written back to the LLR RAM. LLRs of overlapping VNGs will be bypassed to the barrel shifter and participate in the decoding in the next layer. At the end of one iteration, the codeword will be decided according to the sign of LLRs. If the iteration has reached the maximum iteration number or the calculated syndrome is equal to zero, the decoding will end. If not, the decoding will continue. If pipeline conflicts happen during the decoding, LLRs of the VNG with conflicts will not be updated. Combining with Figure 2, the impact of pipeline conflicts on decoding can be mitigated as follows. If the LLR in the previous layer has not been updated yet, then the old LLR value is read again from LLR RAM for the current layer. VNU calculates its variable-to-check message Vit and passes it to the CNU. At the same time, Vit is not necessary to be buffered into FIFO because its corresponding LLR will not be updated in this layer. Different from the layered schedule, Rit is calculated separately with sign buffered in a separate FIFO. Then, it will minus the Rit−1 obtained from the previous iteration and obtain the gain Git. Before storing the gain Git into RAM, gain Git should enter the gain barrel shifter and be shuffled to the corresponding position of the submatrix that it will be added with in the other layer. When the LLR is updated in other layers like in the layered decoding schedule, the gain Git then adds to this updated LLR. 3.4. Detailed Illustration of the Proposed Decoder with High Performance To help understand the mechanism of the priority-based layered decoder with double update queues, here we give an example. The timing diagram of decoding with the QC-LDPC code PCM is shown in Figure 2. RD address and WR address represent the addresses that LLR reads from and writes to. All the addresses are unified with the index of VNGs. Double update queues work as follows. During decoding, overlapping FIFO buffers variable-to-check messages Vits of overlapping VNGs that their newly updated LLRs will participate decoding in the next layer. Bypass means those LLRs will be bypassed to the barrel shifter instead of being written back into LLR RAM. Non-overlapping FIFO buffers Vits of non-overlapping VNGs that their newly updated LLRs will be written to memory. LLRs of overlapping and non-overlapping VNGs are updated separately once their respective check-to-variable messages are calculated. As shown in Figure 4, the base graph matrix is dense and has four rows and nine columns. The number of pipeline stages is set to three. When an LDPC code is being decoded in a conventional layered decoder, VNGs in a layer are processed as the order shown in PCM. When a pipeline conflict occurs, stall cycles are necessarily inserted to maintain the full decoding performance. As an example, in the first layer, the first, second, fourth, fifth, and sixth VNGs participate in the decoding in order. In the second layer, the second, third, fourth, sixth, and seventh VNGs participate in the decoding in order. At the ninth cycle shown in Figure 4, LLRs of variable nodes in the first layer are written back to RAM in sequence. To avoid pipeline conflicts, five stall cycles have to be inserted and LLRs of the second VNG in the second layer cannot be read out from RAM until the 11th cycle, since the updated LLRs of the second VNG in the first layer are written back to the RAM at the 10th cycle. The residue-based layered decoder, hybrid decoder, and priority-based layered decoder with double update queues eliminate stall cycles so that LLRs of a VNG can be read out from memory at each cycle. The solution to pipeline conflicts in the residue-based decoder [14] works as follows. At the sixth cycle, there exists a pipeline conflict to the second VNG. LLRs of the second VNG have to read the old LLR values from the RAM and use these values for decoding. At the 10th cycle, the gain of the second VNG in the first layer is saved in a register file for patching. The second VNG in the second layer can be updated normally at the 14th cycle and the gain is added with the updated LLRs when the LLR write operation happens, here referred as patched LLR write. In this way, the performance loss is compensated. However, the residue-based decoder has to postpone updates of LLRs when the pipeline conflicts happen to the LLRs in one variable node [14]. In this example, LLRs in the fourth VNG can never be updated because of the pipeline conflict and postponed patch. In the hybrid decoder, the solution for pipeline conflicts works as follows. In the first layer, updated LLRs of the second, fourth, and sixth VNGs are written to both the LLR memory and FIFO (double write) [15]. The patched LLR update of the second, fourth, and sixth VNGs is done as shown in Equation (7) at the 14th, 16th, and 17th cycle, respectively. In this manner, LLR updates are not postponed and check node gains are added as soon as they are ready. However, the number of the occurrence of pipeline conflicts is still high. In our proposed priority-based decoder with double update queues, the processing of the decoding is shown in detail in Figure 3. Before the start of decoding, the processing order of VNGs is needed to be reordered. As shown in Figure 4, in the first layer, the fifth, and sixth VNGs are first decoded since they are not decoded in the fourth layer in the previous iteration. Then, the first, second, and fourth VNGs are decoded. In the second layer, the third, seventh, second, fourth, and sixth VNGs are decoded in turn. In the third layer, the first, fifth, eighth, seventh, and fourth VNGs are decoded in turn. In the fourth layer, the second, ninth, first, eighth, and fourth VNGs are decoded in turn. After the LLRs are read from memory, they are used to calculate the variable-to-check messages. In the first layer, the variable-to-check messages of the fifth, first, and second VNGs are buffered into the non-overlapping FIFO since LLRs of the fifth and first VNGs will not participate in the decoding in the second layer and the updated LLRs of the second VNG will not be used in the second layer. In the first layer, the variable-to-check messages of the sixth and fourth VNGs are buffered into overlapping FIFO since these variable nodes are needed in the second layer after their LLRs are updated. The VNGs of other layers also buffer in this way. After the update of LLRs, LLRs of the overlapping submatrices are bypassed to the data path. They continue to be decoded in the next layer. LLRs of the non-overlapping variable nodes are written back to the memory. In the first layer, the fifth, first, and second VNGs are non-overlapping. Their LLRs are written back to memory. On the contrary, LLRs of the non-overlapping sixth and fourth VNGs are bypassed to the data path and participate in the decoding in the second layer. In this way, LLRs are updated in double queues and the occurrence of pipeline conflicts is obviously decreased. When a pipeline conflict happens, the solution in the priority-based decoder works as follows. According to the priority-based schedule, LLRs of the second VNG in the first layer have priority to update at the 11th clock. At the eighth cycle, a pipeline conflict happens to the second VNG in the second layer. Therefore, it has to read the old LLR values because the LLR values of the second VNG in the first layer have not been updated yet at the eighth cycle. The variable-to-check messages of the second VNG in the second are calculated and passed to CNU but not buffered into overlapping FIFO or non-overlapping FIFO. The second VNG in the second layer calculates the gain on the basis of variable-to-check messages and stores the gain. At the 24th cycle, LLRs of the second VNG in the fourth layer are first updated normally after the occurrence of the pipeline conflict. At this moment, the gain of the second VNG in the second layer is added to the updated LLRs of the second VNG in the fourth layer. In this way, the loss caused by the pipeline conflict is compensated. 4. Hardware Implementation and Result Discussion 4.1. Verification of Pipeline Conflict Reduction for Double Update Queues From the illustration shown in Section 3.4, it can be seen that double update queues can reduce the pipeline conflicts and increase the percentage of updated LLRs during decoding. To demonstrate the effect of double update queues in making more LLRs updated, we choose the PCM in 5G NR (code rate = 22/27). Figure 5 shows the percentage of updated LLRs per iteration during decoding depending on the number of pipeline stages. With the increase in pipeline stages, the percentage of update LLRs per iteration is gradually getting worse. Compared with optimized results in [15], the double update queues increase the percentage of updated LLRs by 4–31%. Compared with the single update queue, the improvement is between 12% and 63%. 4.2. Analysis of the Decoding Performance In order to directly reflect the effectiveness of the priority-based schedule and double update queues in improving decoding performance, we made a Monte Carlo simulation to obtain the frame error rate (FER) curves in the AWGN channel as shown in Figure 6. One million codewords are sent for each SNR. The maximum iteration number was set to 10 and the modulation format was set to quad-phase shift keyed (QPSK). The PCM is chosen from 5G NR with code rate 22/27. The simulated priority-based decoder with a single update queue, priority-based decoder with double update queues, residue-based decoder with a single update queue, and residue-based decoder with double update queues are all with 13 pipeline stages. All these four decoders were implemented as an offset min-sum decoder with LLRs quantized to eight bits and messages quantized to six bits, as [15] did. In order to compare the decoding performance fairly and reflect the decoding performance accurately, we take FER = 10−5 as the standard as [15] did. From Figure 6, it is apparent to see that double update queues significantly improve the decoding performance. The priority-based decoder with double update queues shows a gain of 0.4dB compared with the one with a single update queue. The residue-based decoder with double update queues achieves a gain of 6.5dB compared with the one with a single update queue, since some LLRs of variable nodes can never be updated with a single update queue during decoding. From Figure 6, it can also be found that the priority-based decoder needs lower SNR than the residue-based decoder when achieving the same decoding performance because it updates LLRs more frequently. Another Monte Carlo simulation was also done in the AWGN channel for 5G NR (code rate 22/27) and WiMAX (code rate 3/4) to show the results between the SNR and frame error rate (FER) of various decoders, as shown in Figure 7. In the Monte Carlo simulation, one million codewords are sent out to calculate the FER for each SNR. The simulation for 5G NR was performed for different maximum iteration numbers (itmax = 10, itmax = 20 and itmax = 30). The simulation for WiMAX was performed when the maximum iteration number was set to 10. For a fair comparison with [15], the number of pipeline stages in 5G NR was set to 13, as [15] did. The number of pipeline stages in WiMAX was set to 10. The detail of the hardware implementation will be discussed in Section 4.3. The algorithm and quantization of LLRs and messages were also set as [15] did, where the algorithm was OMSA, the LLRs are quantized as eight bits and messages are quantized as six bits. The modulation format was set to QPSK. For a fair comparison with the hybrid decoding, we take FER = 10−5 as the standard as [15] did. In Figure 7a, it can obviously be seen that for 5G NR the loss of SNR performance between the layered decoder and the priority-based decoder with double update queues is 0.2 dB. The loss of SNR performance between the layered decoder and the hybrid decoder is 0.6 dB. Thus, the decoding performance loss at FER = 10−5  narrowed from 0.6 dB to 0.2 dB by using the priority-based layered schedule with double update queues when the maximum iteration is set to 10. When the maximum iteration is set to 20 and 30, the loss of SNR performance does not exist. In order to reflect the improvement of the double update queues, performance of residue-based layered decoder with double update queues is also simulated. The loss of the residue-based decoder is just 0.3 dB after using the double update queues at 10 iterations. Note that the priority-based layered schedule has a faster convergence than the residue-based layered schedule. In Figure 7d, for WiMAX, the loss of SNR performance between the layered decoder and the priority-based decoder with double update queues is only 0.1 dB when the iteration number is set to 10. For WiMAX, the loss of SNR performance between the layered decoder and the residue-based decoder with double update queues is 0.2 dB. The simulation results for WiMAX also shows the effect of priority-based decoder with double update queues in reducing the loss of decoding performance caused by pipeline conflicts. Analysis of average iteration number among different decoders is shown in Figure 8. The maximum iteration number is set to 30. The iteration finishes when codeword C and PCM H satisfy C×HT=0 or the decoding has reached the maximum number of iterations. From Figure 8, it can be found that at the same SNR, the average iteration number of the priority-based schedule with double update queues is highly reduced compared with that of the hybrid schedule. This greatly improves the throughput of the decoder. At higher SNR, the iteration of our design is nearly half of the hybrid layered decoder. 4.3. Hardware Implementation The implementation results of our decoders and previous works are shown in Table 1 in detail. In this table, we use {LLRviinit, LLRviit, Rj,iit} to define the quantization as [12] did. For a fair comparison, numbers of pipeline stages for 5G NR and WiMAX decoders were set to 13 and 10 as [15] did. During the calculation, all LLRs and messages were subject to overflow processing. In the decoder, OMSA was used to calculate the check-to-variable messages and offset factor was set to 0.125. The normalized throughput Tnorm represents the throughput for one decoding iteration. From Table 1, it is obvious to see that Tnorm of decoder we designed is as high as previous works. The double update queues bring a little complexity in routing. As a result, the maximum frequency the decoders can operate at is a little lower than [15] but still high enough to provide a high throughput. Our decoders consume a bit more logic resources than [12,15]. The consumed look-up tables (LUTs), flip-flops (FFs), and BRAMs account for only 24%, 10%, and 7% of the xc7vx690t, respectively. Figure 9 exhibits the resource usage of every module in the hardware implementation of the priority-based decoder with double update queues. In our decoders, only the LLR RAM, gain RAM, and check-to-variable FIFO are built with 36k BRAMs. Other FIFOs and buffers are built with Distributed RAMs (DRAMs). Thus, the 36k BRAMs used in our decoders are much less than other decoders. Although the design of double update queues seems to consume a lot of resources, the LUTs used for double update queues account for only 15.5% of the LUTs in the decoder. The FFs used for double update queues account for only 15.4% of the FFs in the decoder. 4.4. Analysis of Throughput According to the results of average iteration number and Tnorm in Section 4.2 and Section 4.3, the throughput ratio between the priority-based decoder and hybrid decoder [15] is exhibited in Table 2. In Table 2, AIN represents the average iteration number and T represents the throughput of decoders. TR represents the throughput ratio between the priority-based layered decoder with double update queues and the hybrid layered decoder. To meet all the practical applications, AIN s are rounded up, slightly different with the results shown in Figure 6. From Table 2, it can be seen that TR ranges from 158% to 285%. 5. Conclusions In this paper, we have proposed: (1) a priority-based layered schedule, enabling LLRs to be frequently updated when pipeline conflicts occur, and (2) double update queues that separately update LLRs of overlapping and non-overlapping submatrices, for reducing pipeline conflicts. The increase in percentage of updated LLRs per iteration is up to 31% compared with the state-of-the-art work. Therefore, the performance loss decreases from 0.6dB to 0.2dB. The throughput rises to 2.85 Gbps when the SNR is equal to 5.9dB. Considering that the consumed LUTs, FFs, and 36k BRAMs only account for 24%, 10%, and 7% of the FPGA device xc7vx690t, respectively, for one QC-LDPC decoder core, it is expected that a higher throughput can be obtained easily through a multi-core architecture. Certainly, a higher-end FPGA device for UltraScale+ series has more resources and can embed more LDPC decoder cores. A 13-core LDPC decoder with four iterations can achieve a throughput beyond 100 Gbps at 6.9dB. The multi-core decoder will be implemented and verified on the UltraScale+ FPGA board in the real-time communication systems in the future work. Author Contributions Conceptualization, Y.L. (Yunfeng Li) and J.Z.; methodology, Y.L. (Yunfeng Li) and Y.L. (Yingchun Li); software, Y.L. (Yunfeng Li); validation, Y.L. (Yunfeng Li), N.Y. and T.C.; formal analysis, Z.W.; investigation, Y.L. (Yunfeng Li); resources, J.Z.; data curation, Z.W.; writing—original draft preparation, Y.L. (Yunfeng Li); writing—review and editing, Y.L. (Yunfeng Li), Y.L. (Yingchun Li), N.Y. and J.Z.; supervision, 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 Illustration of the priority-based layered schedule for pipeline conflicts. Figure 2 Architecture of the priority-based QC-LDPC decoder with double update queues. Figure 3 The flow chart of the priority-based layered schedule. Figure 4 Illustration of the priority-based layered decoder with double update queues compared with the conventional layered decoder, the residue-based decoder and the hybrid decoder. The number of pipeline stages is set to 3. Figure 5 Percentage of updated LLRs per iteration during decoding as a function of number of pipeline stages for rate 22/27 from 5G NR. HS: Decoder with the hybrid schedule. Figure 6 The SNR performance of different schedules. PS: Priority-based decoder with a single update queue. PD: Priority-based decoder with double update queues. RS: Residue-based decoder with a single update queue. RD: Residue-based decoder with double update queues. Figure 7 The SNR performance of different schedules with different maximum iteration numbers. PD: Priority-based decoder with double update queues. RD: Residue-based decoder with double update queues. HS: Decoder with the hybrid schedule. (a) the maximum iteration number is set to 10 for 5G NR. (b) the maximum iteration number is set to 20 for 5G NR. (c) the maximum iteration number is set to 30 for 5G NR. (d) the maximum iteration number is set to 10 for WiMAX. Figure 8 Average iteration number necessary for successful decoding for 5G NR (code rate = 22/27) compared with the result of the hybrid schedule. Figure 9 The resource usage of every module in the hardware implementation of priority-based decoder with double update queues. sensors-22-03508-t001_Table 1 Table 1 Implementation results for 5G NR and WiMAX decoders in comparison with previous works. This Work [15] [12] This Work [15] [14] Length 10,368 (code rate = 22/27) 2304 (code rate = 3/4) Standard 5G NR WiMAX Device xc7vx690t xc7vx690t xc7k160t xc7vx690t xc7vx690t xc7vx485t Quant {8,8,6} {8,8,6} {5,8,6} {8,8,6} {8,8,6} {4,4,4} Algorithm OMSA OMSA OMSA OMSA OMSA / Slice 29,521 30,824 / 7477 7906 12,496 LUT 103,674 100,929 74,373 26,744 24,228 40,700 FF 89,615 85,431 46,517 19,594 23,290 26,925 36k BRAM 108 136.5 198.5 27 33.5 40.5 fmax [MHz] 255.0 261.0 160.0 310.0 314.6 142.8 Tnorm [Gbps] 31.4 31.7 11.96 8.2 8.5 10.8 sensors-22-03508-t002_Table 2 Table 2 Throughput ratio between priority-based layered decoder with double update queues and hybrid layered decoder [15]. This Work [15] SNR [dB] Tnorm [Gbps] AIN T [Gbps] Tnorm [Gbps] AIN T [Gbps] TR [%] 5.9 31.4 11 2.85 31.7 30 1.0 285 6.0 9 3.5 21 1.5 233 6.1 8 3.93 16 2.0 197 6.2 7 4.5 14 2.3 196 6.3 6 5.2 12 2.6 200 6.4 6 5.2 11 2.9 179 6.5 6 5.2 10 3.2 163 6.6 5 6.3 9 3.5 180 6.7 5 6.3 8 4.0 158 6.8 5 6.3 8 4.0 158 6.9 4 7.9 8 4.0 198 7.0 4 7.9 7 4.5 176 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Gallager R. Low-Density Parity-Check Codes IEEE Trans. Inform. Theory 1962 8 21 28 10.1109/TIT.1962.1057683 2. Levine B. Reed Taylor R. Schmit H. Implementation of near Shannon Limit Error-Correcting Codes Using Reconfigurable Hardware Proceedings of the 2000 IEEE Symposium on Field-Programmable Custom Computing Machines (Cat. No. PR00871) Napa Valley, CA, USA 17–19 April 2000 217 226 3. 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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091223 animals-12-01223 Article Multiobject Tracking of Wildlife in Videos Using Few-Shot Learning https://orcid.org/0000-0002-9155-1865 Feng Jiangfan * Xiao Xinxin Pavey Chris R. Academic Editor School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; s200231187@stu.cqupt.edu.cn * Correspondence: fengjf@cqupt.edu.cn 09 5 2022 5 2022 12 9 122305 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/). Simple Summary Video recordings enable scientists to estimate species’ presence, richness, abundance, demography, and activity. The increasing popularity of camera traps has led to a growing interest in developing approaches to more efficiently process images. Advanced artificial intelligence systems can automatically find and identify the species captured in the wild, but they are hampered by dependence on large samples. However, many species rarely occur, such as endangered species, and only a few shot samples are available. Building on recent advances in deep learning and few-shot learning technologies, we developed a multiobject-tracking approach based on a tracking-by-detection paradigm for wildlife to improve multiobject-tracking performance. We hope that it will be beneficial to ecology and wildlife biology by speeding up the process of multiobject tracking in the wild. Abstract Camera trapping and video recording are now ubiquitous in the study of animal ecology. These technologies hold great potential for wildlife tracking, but are limited by current learning approaches, and are hampered by dependence on large samples. Most species of wildlife are rarely captured by camera traps, and thus only a few shot samples are available for processing and subsequent identification. These drawbacks can be overcome in multiobject tracking by combining wildlife detection and tracking with few-shot learning. This work proposes a multiobject-tracking approach based on a tracking-by-detection paradigm for wildlife to improve detection and tracking performance. We used few-shot object detection to localize objects using a camera trap and direct video recordings that could augment the synthetically generated parts of separate images with spatial constraints. In addition, we introduced a trajectory reconstruction module for better association. It could alleviate a few-shot object detector’s missed and false detections; in addition, it could optimize the target identification between consecutive frames. Our approach produced a fully automated pipeline for detecting and tracking wildlife from video records. The experimental results aligned with theoretical anticipation according to various evaluation metrics, and revealed the future potential of camera traps to address wildlife detection and tracking in behavior and conservation. camera trap few-shot learning wildlife management animal behavior National Natural Science Foundation of China41971365 Chongqing Research Program of Basic Science and Frontier Technologycstc2019jcyj-msxmX0131 The work was supported by the National Natural Science Foundation of China (41971365) and the Chongqing Research Program of Basic Science and Frontier Technology (cstc2019jcyj-msxmX0131). ==== Body pmc1. Introduction Biodiversity is an essential component and a key element in maintaining the stability of ecosystems. In the face of the current sharp decline in global biodiversity, it is urgent to take adequate measures to prevent and protect it. Wildlife monitoring and conservation that determine biodiversity patterns is a cornerstone of ecology, biogeography, and conservation biology. Therefore, monitoring animal habits and activity patterns during the rewilding training process is essential. Driven by advances in cheap sensors and computer-vision technologies for detecting and tracking wildlife, biodiversity research is rapidly transforming into a data-rich discipline. Video data have become indispensable in the retrospective analysis and monitoring of endangered animal species’ presence and behaviors. However, large-scale research is prohibited by the time and resources needed to process large data manually. Recent technological advances in computer vision have led to wildlife scientists realizing the potential of automated computational methods to monitor wildlife. This ongoing revolution is facilitated by cost-effective mechanical high-throughput wildlife-tracking methods that generate massive high-resolution images across scales relevant to the ecological context in which animals perceive, interact with and respond to their environment. While applying existing tools is tempting, many potential pitfalls must be considered to ensure the responsible use of these approaches. For example, a large amount of data is required to train these deep-learning models accurately. However, because many species rarely occur, only a few shot samples are available; thus, the performance is typically low. Few-shot learning aims to develop the ability to learn and generalize autonomously from a small number of samples. It can rapidly generalize to new tasks containing only a few samples with supervised information. Multiple recent publications have discussed this approach [1,2,3,4,5]. Generally, the research on multiobject tracking mainly focuses on how to improve the real-time performance of multiobject monitoring [6,7], how to better model the appearance information of the target [8,9,10,11], and how to associate targets efficiently [12,13,14,15]. Multiobject-tracking methods always follow the tracking-by-detection paradigm. In [7], this method was called separate detection and embedding (SDE). This means that the MOT system was broken down into two steps: (1) locating the target in single video frames; and (2) associating detected targets with existing trajectories. Another multi-object tracking learning paradigm, JDE, was also proposed. JDE jointly learned the detector and embedding model in a single deep network. In other words, the JDE method used a single network to output both the detection result and the corresponding appearance embeddings of the detected boxes. The SDE method used two separate networks to accomplish the above two tasks. JDE was closer to real-time performance, but the tracking accuracy was slightly worse than SDE. The small-sample object-detector performance was not as good as that of YOLO [16,17,18,19], Faster R-CNN [20], and other general object detectors [21,22]. In the object detection of each frame, there will be missed detection, which significantly affects the effect of the multiobject-tracking task. Therefore, to ensure the performance effect of a multiobject-tracking model driven by a small amount of data, in addition to selecting the SDE paradigm, we also proposed a trajectory reconstruction module in the data association part to further optimize the tracking accuracy, as shown in Figure 1. The research hotspots of multiobject tracking under the tracking-by-detection paradigm always have the following two aspects: (1) a more accurate detection of targets in complex environments; and (2) the ability to deal with long-term occlusion and short-term occlusion problems and to associate targets more accurately. Some previous works [23,24,25] showed that a multiobject-tracking approach could achieve a state-of-the-art performance when used together with a robust object detector. They used Kalman filtering to predict and update trajectories [23] and proposed an extension [24]. In addition to considering the motion features above, the apparent features of the target were also considered. Feichtenhofer et al. introduced correlation features representing object cooccurrences across time to aid the ConvNet during tracking. Moreover, they linked the frame-level detections based on across-frame tracks to produce high-accuracy detections at the video level [25]. The primary purpose of data association is to match multiple targets between frames, including the appearance of new marks, the disappearance of old targets, and the identity matching of targets between consecutive frames. Many approaches formulated the data-association process as various optimization problems [12,13]. The former mapped the maximum a posteriori (MAP) data-association problem to cost-flow networks with nonoverlapping constraints on trajectories. A min-cost flow algorithm found the optimal data association in the network. The latter believed that re-identification only by appearance was not enough, and long-distance object reproduction was also worthy of attention. They proposed a graph-based formulation that linked and clustered person hypotheses over time by solving an instance of a minimum cost lifted multicut problem. Some works, such as [26,27], emphasized improving the features used in data association. They proposed dual matching attention networks with spatial and temporal attention mechanisms [26]. The spatial attention network generated dual spatial attention maps based on the cross-similarity between each location of an image pair, making the model more focused on matching common regions between images. The temporal attention module adaptively allocated different levels of attention to separate samples in the tracklet to suppress noisy observations. To obtain a higher precision, they also developed a new training method with ranking loss and regression loss [27]. The network considered the appearance and the corresponding temporal frames for data association. Conceptually, tracking technologies using computer vision permit high-resolution snapshots of the movement of multiple animals and can track nontagged individuals, but they are less cost-effective, are usually limited to specific scenarios, and make individual identification challenging. In contrast, here we provide a fully automated computational approach to tracking tasks for wildlife by combining few-shot learning with multiobject tracking to detect, track, and recognize nature. It could represent a step-change in our use of extensive video data from the wild to speed up the procedure for ethologists to analyze biodiversity for research and conservation in the wildlife sciences. This approach represents an automated pipeline for recognizing and tracking species in the wild. Our main contributions can be summarized as follows:We combined few-shot learning with a multiobject-tracking task. To the best of our knowledge, the multiple automated object-tracking frameworks based on few-shot learning are being proposed for the first time. Our approach effectively merged the richness of deep neural network representations with few-shot learning that paves the way for robust detection and tracking of wildlife, which can be adaptive for unknown scenarios by data augmentation. A trajectory reconstruction module was proposed to compensate for the shortcomings of the few-shot object-detection algorithm in the multiobject-tracking tasks, especially in monitoring wildlife. 2. Materials and Methods 2.1. Architecture Overview While camera traps have become essential for wildlife monitoring, they generate enormous amount of data. The fundamental goal of using intelligent frameworks in wildlife monitoring is automated analyses of behaviors, interactions, and dynamics, both individual and group. For example, sampling the quantity of species’ complex interactions for network analysis is a significant methodological challenge. Early approaches require capturing subjects and are labor-intensive. Their application may be location-specific, and the recorded data typically lacks contextual visual information. In this work, we instead sought to learn the unstrained dynamics and be sensitive to the presence of various locations and groups. The aim was to propose a cost-effective wildlife-tracking approach that generated massive high-resolution video records across scales relevant to the ecological context in which animals perceive, interact with and respond to their environment. Figure 2 shows the overall design of the proposed MOT framework, called Few-MOT, which followed the tracking-by-detection paradigm, but without requiring large amounts of training data. An input video frame first underwent a forward pass through a few-shot object detector and a few-shot feature extractor to obtain motion and appearance information. Finally, we followed [24] and made improvements to solve the association problem for a few-shot setting. The upgrades included two parts: (1) a three-stage matching process including cascade matching, central-point matching, and IoU matching; and (2) a trajectory-reconstruction module to compensate for few-shot object detection. 2.2. Few-Shot Detection Module Most object-detection approaches rely on extensive training samples. These requirements substantially limit their scalability to open-ended accommodation of novel classes with limited labeled training data. In general, the detection branch of multiobject tracking is the state-of-the-art of the object-detection field. Given the extreme scarcity of endangered animal scenes, we had very few samples available. This paper addresses these problems by offering a few-shot object detection with spatial constraints to localize objects in our multiobject-tracking framework. Few-shot object detection only requires a k-shot training sample, and its performance is better than that of the general detector under the same premise. First, a note that in few-shot learning, we defined a large number of samples as the base, with their counterparts as the novel. In this paper, the novel class refers to the endangered animal class. Our proposed few-shot object-detection method allowed for few-shot learning in different scenarios with spatial dependencies while adapting to a dynamically changing environment during the detection process. It exploited a set of objects and environments that were processed, composed, and affected by each other simultaneously, instead of being recognized individually. Considering the geographical correlation between species and environmental factors, we thus proposed spatial constraints during the data augmentation. The images were first separated from the front and back views using the pretrained saliency network U2-Net [28]. Then, the pretrained image-inpainting network CR-Fill [29] repaired the missing parts. Finally, the foreground and background, which were separated, were blended and combined into a new sample. We used a perceptual hashing algorithm for spatial constraints during the combinations that did not correspond to the actual situation. For example, an event with a zero probability, such as a giant panda in the sky, would be misleading for training the object-detection model. After the above-constrained data expansion, the samples were learned from each other. The training of the few-shot object-detection task was performed based on a feature-reweighting method [30]. The perceptual hash algorithm pHash reduced the image frequency by the discrete cosine transform (DCT) and then matched similar images by calculating the Hamming distance. The algorithm proceeded as follows: (1) reduce the image to 32 ∗ 32; (2) convert the image to a grey-scale image; (3) calculate the DCT and DCT mean; (4) perform image pairing to calculate the Hamming distance. The equations to calculate the DCT and Hamming distance are shown in Equations (1)–(3) below:(1) F=AfAT, (2) A(i,j)=c(i)cos[(j+0.5)πNi], (3) d(x,y)=∑x[i]⊕y[i], This analysis can be extended toward a graphical representation (Figure 3). 2.3. Learning More Robust Appearance Embedding Based on Few-Shot Learning There is an appearance metric-learning problem in a multiobject-tracking task, and the aim is to learn an embedding space where instances of the same identity are close while instances of different identities are far apart. The metric-learning problem is often defined as a re-identification task in multiobject tracking, mainly aimed at a single category; i.e., pedestrians or vehicles. For example, person re-identification aims at searching for persons across multiple nonoverlapping cameras. The task of Re-ID in this approach shares similar insights with the Re-ID for persons. When presented with an animal-of-interest (query) in video records, an animal Re-ID tells whether this animal has been observed in another place (time). In particular, we tracked nonsingle classes, and each class had very little training data. Thus, we trained the embedding learning process on the few-shot classification task. Typically, few-shot classification approaches include optimization-based, model-based, and metric-based methods. Since our goal was not to classify but to train a feature learner based on the classification task and its feature map to the target, we performed descriptions of categories and changes in behavior. Thus, directly using a few-shot classification network for training was not applicable. We used elastic-distortion data augmentation to ensure the features had single information. Elastic distortion changed the posture of the target, allowing changes in behavior to be focused and adapted to our eventual tracking task. Because the target was moving and the pose of the same target was constantly changing in the video stream, this variation affected the recognition rate of the target identity during the tracking process. Firstly, the affine transformation of the image was performed to obtain a random displacement field generated by each pixel of the image. Then, we convolved the random displacement field with N(0,δ), which obeyed the Gaussian distribution, and multiplied the random displacement field by the control factor α, where δ controlled the smoothness of the image and α controlled the strength of the image deformation. We set δ to 0.07 and α to 5. The experimental results suggested that these parameter values enriched the target pose without distorting the image. Figure 4 shows a partial example of the processed image. We imitated the approach used in [31] in our training process, using self-supervision and regularization techniques to learn generic representations suitable for few-shot tasks. Firstly, we used a pretext task called rotation to construct the self-supervised task on the base classes. In the self-supervised task, the input image was rotated by r degrees and r∈CR={0°,90°,180°,270°}. The secondary purpose of the model was to predict the amount of rotation applied to the image. An auxiliary loss was added to the standard classification loss in the image classification setting to learn the generic representation. Secondly, fine-tuning with a manifold mixup was conducted on the base classes and endangered classes for a few more epochs. The manifold mixup provided a practical way to flatten a given class of data representations into a compact region. The loss function of the first stage is given by:(4) Lrot=1|CR|∗∑x∈Db∑r∈CRL(cWr(fθ(g(x)r)),r), (5) Lclass=E(x,y)∈Db,r∈CR[L(g(x)r,y)] , where Lrot denotes the self-supervision loss, and Lclass denotes the classification loss. The loss function of the fine-tuning stage is given by:(6) Lmm=E(x,y)∈Db[L(Mixλ(fθl(x),fθl(x′)),Mixλ(y,y′))], (7) Mixλ(a,b)=λ∗a+(1−λ)∗b , In addition, we used the input data x and x′ with corresponding feature representations at layer l given by fθl(x) and fθl(x′), respectively. 2.4. Association Module Considering that the current association modules were all associated with the conventional multiobject-tracking task and were not applied to the multiobject-tracking task with a few-shot setting, it was inevitable that there were some shortcomings. To fit the Few-MOT module to the MOT-EA dataset, we made some improvements with the DeepSORT association algorithm. 2.4.1. Three-Stage Matching In addition to cascade matching and IoU matching, we added a central-point matching, which helped to alleviate the mismatched detection boxes and tracks due to an excessive intersection ratio. The IoU matrix iouj,i was calculated as the intersection-over-union (IoU) distance between every detection and object pair. (8) iouj,i=Area(trackj)∩Area(deci)Area(trackj)∪Area(deci),  where Area(trackj) is the area of trackj, and Area(deci) represents the area of deci. The central-point matrix centerj,i was calculated as the central-point distance between every detection and track pair. Figure 5 illustrates the difference between center-point matching and IoU matching. (9) centerj,i=dis(center(trackj),center(deci)),  where center(trackj) and center(deci) are the central-point of the track and detection, respectively. During the experiment, we found that if we only used cascade matching and central-point matching in the matching stage, it did help to reduce ID switching, but at the same time, it was accompanied by an increase in missed targets. Thus, we worked together on IoU matching and central-point matching and designed the following trajectory-reconstruction module to alleviate this problem. In the MOT-EA dataset, we measured the above two matching strategies using the two indicators for FN and FP, and found that three-stage matching was the best matching strategy. A further discussion of the ablation experiment reveals more details. 2.4.2. Trajectory-Reconstruction Module We found an excessive amount of missed detection cases in the tracking process given in the previous section, which damaged the tracking effect. In addition, the performance of the few-shot detector was not as good as YOLO, Faster R-CNN, and other general object detectors. The target was then lost in the video stream. However, according to [32], the tracking accuracy of multiple objects can be written as:(10) MOTA=1−FN+FP+IDSWGT∈(−∞,1],  where FN is false negatives (the sum of missing amounts in the entire video), FP is false positives (the sum of the number of false positives in the entire video), IDSW is the ID switch (the total number of ID switches), and GT is the number of the ground truth objects. The object-detection accuracy significantly affected the tracking accuracy, so we designed a trajectory-reconstruction module to deal with the above problems. This module compensated for the lack of a few-shot detector. First, we specified the central region, as shown in Figure 6 below. Then, if there was no trajectory and the detection box was successfully matched in frame T, we judged the central-point position of the track in frame T-1. If the central point of the bounding box in frame T-1 was located in the central area, we reconstructed the track of frame T-1 to frame T under the present conditions. We allowed the reconstruction of five consecutive frames because the object’s position usually changed slightly in five consecutive frames. The box of frame T-1 could still locate the object’s position in the subsequent four frames. 3. Results 3.1. Implementation Details This framework was written in Python with PyTorch support. First, when training the feature extractor of Few-MOT, we converted the EAOD private object-detection dataset into an image-classification dataset for training. WRN-28-10 [33] was used as the backbone, and the elastic-distortion data-augmentation strategy enhanced the feature robustness of animals in various poses. Then, in the design of the trajectory-reconstruction module, we found through several experiments that when the allowable reconstruction threshold was set to less than 5, there were too many missed trajectories. When the setting was greater than 5, there were too many false trajectories, which reduced the tracking effect. Therefore, we set the threshold for the maximum number of frames allowed to be continuously reconstructed to 5. 3.2. Datasets and Evaluation Metrics Datasets: Currently, there is no multiobject-tracking dataset for endangered animals, so we created the MOT-EA multiobject-tracking dataset in the format of MOT-16 [34]. The dataset included five endangered species: brown-eared pheasant, crested ibis, giant panda, golden snub-nosed monkey, and tiger. Each video was 10 to 20 s in length. Details are shown in Table 1 below. Evaluation Metrics: Following the benchmarks, we evaluated our work using [32]. MOTA and IDF1 are considered the two most important among all metrics. MOTA is an indicator to measure the accuracy of multiobject tracking. Mostly, it considers the matching errors of objects in the tracking process. According to FP, FN, and IDs, MOTA gives a very intuitive measure of the tracker performance, which is independent of the accuracy of object detection. The IDF1 considers the ID accuracy rate and the ID recall rate comprehensively, and considers the ID information more than MOTA. However, IDF1 cannot reflect the phenomenon of ID switch. This is shown in Equations (10) and (11) below. A robust tracking system should show good scores for both MOTA and IDF1. (11) IDF1=2IDTP2IDTP+IDFP+IDFN ,  3.3. Experimental Results Here, we evaluated our system using the MOT-EA dataset. Table 2 shows the tracking performance of our framework on the five endangered categories. Furthermore, we compared the same few-shot object detector with multiple trackers, as shown in the first four rows of Table 3. On the other hand, the general detector YOLOv4 was used for comparison, as shown in row 5 of Table 3. The specific performance of the five methods in Table 3 on the MOT-EA dataset is supplemented in Appendix A Table A1, Table A2, Table A3, Table A4 and Table A5. The results showed that our framework outperformed many previous approaches with small data samples. Both the MOTA and IDF1 scores were in the leading position for MOT-EA. We believe that the following results were obtained because the general detector could not achieve a good detection effect with a small amount of data, which significantly affected the tracking. In addition, the tracker we designed was more suitable for this scenario. It is more robust to various morphological changes in animals, and more targeted to insufficient learning caused by a small amount of data. Two example trajectories of two tigers using the Few-MOT model are shown in Figure 7 below. Our model made it possible to track the targets and plot the movements. We could record the basic trajectories of the endangered animals within the monitoring area. Furthermore, we could also use the trajectories to analyze the areas where the targets were active, determine whether they were involved and the interaction between different targets, etc. In addition, the tracking processes of a giant panda and a golden snub-nosed monkey are shown in Figure 8 and Figure 9, respectively. The targets were continuously located during this process and maintained unique identity IDs. 3.4. Ablation Study and Discussion Here, we discuss the impact of the three parts of the three-stage matching and elastic-distortion data-augmentation strategy and the trajectory-reconstruction module. First, we performed ablation experiments on the MOT-EA dataset for the matching module. The two stages included cascade matching and central matching. The three stages included cascade matching, central matching, and IoU matching. As shown in Table 4, the three-stage matching showed improvement in the cases of false and missed detections. Table 5 shows the impacts of the two parts of the elastic-distortion data-augment strategy and the trajectory-reconstruction module. The baseline model (row 1 in Table 5) consisted of a few-shot detector and an unmodified tracker. The other experimental results in Table 5 shared the same set of few-shot detectors, except for the feature learner’s training process and the tracker’s association module. The results indicated that the feature stability brought by the elastic-distortion data-enhancement strategy slightly improved the MOTA index. However, the more significant effect stemmed from the proposal of the trajectory-reconstruction module. This module handled both false and missed targets well in the tracking process. According to Equation (10), it led to a significant improvement in the MOTA. Figure 10 shows a small segment of the performance of the trajectory reconstruction module during the tracking process. In comparison, we can find that the target lost in the 30th frame was reconstructed. This module made the trajectory of the target more complete. 4. Discussion So-called “big data” approaches are not limited to technical fields because the combination of large-scale data collection and processing techniques can be applied to various scientific questions. Meanwhile, it has never been more critical to keep track of biodiversity than over the past decade, as losses and declines have accelerated with ongoing development. However, multiobject tracking is complicated, with experts relying on human interactions and specialized equipment. While cheap camera sensors have become essential for capturing wildlife and their movements, they generate enormous amounts of data, and have become a prominent research tool for studying nature. Machine- and deep-learning methods hold promise as efficient tools to scale local studies to a global understanding of the animal world [38]. However, the detection and tracking of the target animals are challenging, essentially because the data obtained from wild species are too sparse. Our deep-learning approach detected and tracked the target animals and produced spatiotemporal tracks that following multiple objects through few-shot learning to alleviate instance imbalance and insufficient sample challenges. This study demonstrated how incorporating track methods, deep learning, and few-shot learning can be a research tool for studying wild animals. Turning now to its limitations, we note that our approach heavily relied on the prominent parts’ detection performance, and easily failed to track infant animals. 5. Conclusions In this work, we introduced Few-MOT for wildlife to embed uncertainty into designing a multiobject-tracking model by combining the richness of deep neural networks with few-shot learning, leading to correctable and robust models. The approach systematically provided a fully automated pipeline framework to integrate the few-shot learning method with deep neural networks. Instead of a discriminative model, a spatial-constraints model was created. Furthermore, a trajectory-reconstruction module was also proposed to compensate for the shortcomings of the few-shot object detection. Our model demonstrated the efficacy of using few-shot architectures for biological application: the automated recognition and tracking of wildlife. Unlike older, data-rich automation methods, our method was entirely based on deep learning with few shots. It also improved previous deep-learning methods by combining few-shot learning with a multiobject-tracking task. It also provided a rich set of examples by incorporating contextual details of the environment, which can be valuable for few-shot learning efficiency, especially in wildlife detection and tracking. The data explosion that has come with the widespread use of camera traps poses challenges while simultaneously providing opportunities for wildlife monitoring and conservation [39]. Tracking animals is essential in animal-welfare research, especially when combined with physical and physiological parameters [40,41,42]. It is also challenging to curate datasets large enough to train tracking models. We proposed a deep-learning framework named Few-MOT to track endangered animals based on a few-shot-learning and tracking-by-detection paradigm. It could record the daily movements of the target being tracked, marking areas of frequent activity and other information that could be used for further analysis. This framework offered a few-shot object detection with spatial constraints to localize objects and a trajectory-reconstruction module for a better association. The experimental results showed that our method performed better on the few-shot multiobject-tracking task. Our new datasets open up many opportunities for further research on multiobject tracking. There were some limitations to our study, notably that the detector could detect a nonexistent target in the wrong place when the surroundings were extremely similar to the target. Future work should investigate how multiple variables, such as the features of the training dataset and different network architectures, affect performance. Furthermore, a key driver in the advancement of intelligent video systems for wildlife conservation will be the increasing availability of datasets for sufficient species, and open-source datasets should also be proposed in the future. Author Contributions Methodology, J.F. and X.X.; investigation, J.F.; data curation, X.X.; validation, X.X.; writing—original draft preparation X.X.; writing—review and editing, J.F. 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 used to support the findings of this study are available from the corresponding author upon request. Conflicts of Interest The authors declare no conflict of interest. Appendix A animals-12-01223-t0A1_Table A1 Table A1 Results of the same few-shot object detector in our model combined with BYTETrack tracker on the MOT-EA dataset. Class IDF1 IDP IDR FP ↓ FN ↓ IDs ↓ MOTA MOTP Tiger 59.20% 80.8% 46.7% 52 359 1 43.40% 0.189 Golden snub-nosed monkey 83.70% 97.7% 73.2% 2 89 1 73.50% 0.173 Giant panda 28.70% 36.4% 23.7% 102 385 7 39.10% 0.23 Crested ibis 77.70% 96.9% 64.9% 6 312 1 65.50% 0.255 Brown-eared pheasant 48.20% 70.1% 36.7% 25 594 4 47.80% 0.253 OVERALL 59.50% 76.38% 49.04% 187 1739 14 53.86% 0.22 ↓ means the smaller the better. animals-12-01223-t0A2_Table A2 Table A2 Results of the same few-shot object detector in our model combined with SORT tracker on the MOT-EA dataset. Class IDF1 IDP IDR FP ↓ FN ↓ IDs ↓ MOTA MOTP Tiger 28.20% 50.2% 19.6% 25 468 14 30.40% 0.183 Golden snub-nosed monkey 28.00% 37.9% 22.2% 2 146 14 53.30% 0.174 Giant panda 16.70% 24.9% 12.6% 55 456 21 34.40% 0.214 Crested ibis 30.10% 43.8% 22.9% 1 442 20 49.90% 0.247 Brown-eared pheasant 43.30% 72.0% 31.0% 9 689 16 40.20% 0.237 OVERALL 29.26% 45.76% 21.66% 92 2201 85 41.64% 0.211 ↓ means the smaller the better. animals-12-01223-t0A3_Table A3 Table A3 Results of the same few-shot object detector in our model combined with IoU-tracker tracker on the MOT-EA dataset. Class IDF1 IDP IDR FP ↓ FN ↓ IDs ↓ MOTA MOTP Tiger 14.90% 25.4% 10.6% 41 466 47 23.90% 0.197 Golden snub-nosed monkey 27.30% 32.3% 23.6% 1 94 20 66.90% 0.169 Giant panda 7.70% 10.6% 6.0% 75 424 37 33.90% 0.219 Crested ibis 19.30% 31.0% 14.1% 2 507 50 39.60% 0.251 Brown-eared pheasant 9.50% 19.8% 6.3% 24 839 56 23.00% 0.237 OVERALL 15.70% 23.82% 12.12% 143 2330 210 37.40% 0.215 ↓ means the smaller the better. animals-12-01223-t0A4_Table A4 Table A4 Results of the same few-shot object detector in our model combined with V-IoU-tracker tracker on the MOT-EA dataset. Class IDF1 IDP IDR FP ↓ FN ↓ IDs ↓ MOTA MOTP Tiger 44.30% 78.9% 30.8% 0 444 2 38.70% 0.191 Golden snub-nosed monkey 45.80% 48.4% 43.5% 0 35 3 89.00% 0.172 Giant panda 12.10% 15.9% 9.7% 77 391 14 40.60% 0.22 Crested ibis 45.90% 89.9% 30.8% 1 609 1 33.90% 0.24 Brown-eared pheasant 44.70% 77.6% 31.4% 2 713 7 39.50% 0.238 OVERALL 38.56% 62.14% 29.24% 80 2192 27 48.34% 0.212 ↓ means the smaller the better. animals-12-01223-t0A5_Table A5 Table A5 Results of the YOLOv4 detector combined with DeepSORT tracker on the MOT-EA dataset. Class IDF1 IDP IDR FP ↓ FN ↓ IDs ↓ MOTA MOTP Tiger 18.60% 43.4% 11.8% 6 536 17 23.20% 0.233 Golden snub-nosed monkey 69.40% 80.8% 60.8% 0 86 7 73.20% 0.202 Giant panda 30.90% 41.0% 24.8% 62 383 24 42.20% 0.222 Crested ibis 35.40% 60.3% 25.1% 3 543 5 40.40% 0.213 Brown-eared pheasant 24.70% 59.8% 15.6% 5 888 23 23.30% 0.268 OVERALL 35.80% 57.06% 27.62% 76 2436 76 40.46% 0.227 ↓ means the smaller the better. Figure 1 We aimed to obtain a few-shot multiobject-tracking model based on few-shot learning. In this framework, we used a few-shot object detector as the detector and a classification network trained based on the few-shot method as the feature extractor. In addition, we also designed a trajectory-reconstruction module to optimize the tracking result. Figure 2 The architecture of our proposed few-shot tracker framework: Few-MOT. It consisted of a detection process and a tracking process. The detection process followed a few-shot object detector that directly regressed the objectness score (def), bounding box location (x,y,w,h), and classification score (cls). The tracking process included a few-shot feature-extraction network (Extractor), a matching module, and a trajectory-reconstruction module. The extractor was responsible for extracting the features of each object clip. The matching module then performed the association of targets between frames, and if they met the reconstruction criteria, they were constructed by the trajectory-reconstruction module. The details of this module will be explained in the methods section. Figure 3 Filtering similar background processes: (a) calculating the Hamming distance between pairs of images; (b) sorting them in descending order by similarity; (c) removing the remarkably similar samples to ridding unbalance; (d) selecting the top 60% of reasonable samples, as those that could be subsequently blended for the front and back views. Figure 4 Example comparison of the EAOD dataset after elastic distortion. Each target was appropriately distorted without distorting the image. In this way, the diversity of target poses was enriched. Figure 5 (a) IoU matching; (b) central point matching. Figure 6 Schematic diagram of the division of the central area. The diagram on the left is an abstract representation, where we defined the central area as a fixed-scale area at the boundary of the video screen. The real situation is shown in the diagram on the right. Figure 7 Tracks 1 and 2 are the respective tracks recorded for two tigers, with the red flag representing the starting point and the blue flag representing the endpoint. Figure 8 Tracking example of a giant panda. Figure 9 Tracking example of a golden snub-nosed monkey. Figure 10 Tracking sequence before and after frame 30: (a) performance without trajectory-reconstruction module; (b) performance with the trajectory-reconstruction module. animals-12-01223-t001_Table 1 Table 1 Detail of MOT-EA dataset. Class Duration (s) Brown-eared pheasant 13:26 Crested ibis 16:24 Giant panda 20:00 Golden snub-nosed monkey 10:21 Tiger 14:29 animals-12-01223-t002_Table 2 Table 2 Results of the proposed MOT framework for MOT-EA. Class IDF1 IDP IDR FP ↓ FN ↓ IDs ↓ MOTA MOTP Tiger 59.30% 71.7% 50.5% 66 281 2 52.10% 0.287 Golden snub-nosed monkey 95.50% 99.4% 91.9% 2 28 0 91.40% 0.224 Giant panda 72.10% 83.8% 63.3% 96 295 2 51.50% 0.285 Crested ibis 62.40% 74.1% 53.8% 0 253 7 71.90% 0.278 Brown-eared pheasant 34.10% 50.7% 25.7% 46 634 12 42.00% 0.273 OVERALL 64.68% 75.94% 57.04% 210 1491 23 61.78% 0.27 ↓ means the smaller the better. animals-12-01223-t003_Table 3 Table 3 Comparison with the same few-shot detector and YOLOv4. Class IDF1 IDP IDR FP ↓ FN ↓ IDs ↓ MOTA MOTP BYTETrack [35] 59.50% 76.38% 49.04% 187 1739 14 53.86% 0.22 SORT [23] 29.26% 45.76% 21.66% 92 2201 85 41.64% 0.211 IoU-tracker [36] 15.70% 23.82% 12.12% 143 2330 210 37.40% 0.215 V-IoU-tracker [37] 38.56% 62.14% 29.24% 80 2192 27 48.34% 0.212 YOLOv4 [19] + DeepSORT [24] 35.80% 57.06% 27.62% 76 2436 76 40.46% 0.227 Ours 64.68% 75.94% 57.04% 210 1491 23 61.78% 0.27 ↓ means the smaller the better. animals-12-01223-t004_Table 4 Table 4 Performance comparison for the matching module with different methods. Method FP ↓ FN ↓ Two stages 337 1627 Three stages 210 1491 ↓ means the smaller the better. animals-12-01223-t005_Table 5 Table 5 Effects of using the elastic-distortion data-augmentation strategy and trajectory-reconstruction module for tracking. Augment Trajectory Reconstruction IDs ↓ MOTA - - 30 52.58% √ - 33 52.72% √ √ 23 61.78% ↓ means the smaller the better. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095137 ijms-23-05137 Article DOT1L Methyltransferase Regulates Calcium Influx in Erythroid Progenitor Cells in Response to Erythropoietin Feng Yi 1† Borosha Shaon 1† Ratri Anamika 1 Lee Eun Bee 1 https://orcid.org/0000-0002-3184-4690 Wang Huizhen 2 Fields Timothy A. 1 Kinsey William H. 2 Vivian Jay L. 1 Rumi M. A. Karim 1 Fields Patrick E. 1* Comi Cristoforo Academic Editor Gauthier Benoit Academic Editor Roukos Dimitrios H. Academic Editor Fusco Alfredo Academic Editor 1 Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA; yfeng1@email.unc.edu (Y.F.); sborosha2@gmail.com (S.B.); aratri@kumc.edu (A.R.); elee10@kumc.edu (E.B.L.); tfields@kumc.edu (T.A.F.); jvivian@kumc.edu (J.L.V.); mrumi@kumc.edu (M.A.K.R.) 2 Department of Anatomy and Cell Biology, University of Kansas Medical Center, Kansas City, KS 66160, USA; hwang@kumc.edu (H.W.); wkinsey@kumc.edu (W.H.K.) * Correspondence: pfields@kumc.edu; Tel.: +1-(913)-588-0953 † These authors contributed equally to this work. 05 5 2022 5 2022 23 9 513713 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/). Erythropoietin (EPO) signaling plays a vital role in erythropoiesis by regulating proliferation and lineage-specific differentiation of murine hematopoietic progenitor cells (HPCs). An important downstream response of EPO signaling is calcium (Ca2+) influx, which is regulated by transient receptor potential channel (TRPC) proteins, particularly TRPC2 and TRPC6. While EPO induces Ca2+ influx through TRPC2, TRPC6 inhibits the function of TRPC2. Thus, interactions between TRPC2 and TRPC6 regulate the rate of Ca2+ influx in EPO-induced erythropoiesis. In this study, we observed that the expression of TRPC6 in KIT-positive erythroid progenitor cells was regulated by DOT1L. DOT1L is a methyltransferase that plays an important role in many biological processes during embryonic development including early erythropoiesis. We previously reported that Dot1l knockout (Dot1lKO) HPCs in the yolk sac failed to develop properly, which resulted in lethal anemia. In this study, we detected a marked downregulation of Trpc6 gene expression in Dot1lKO progenitor cells in the yolk sac compared to the wild type (WT). The promoter and the proximal regions of the Trpc6 gene locus exhibited an enrichment of H3K79 methylation, which is mediated solely by DOT1L. However, the expression of Trpc2, the positive regulator of Ca2+ influx, remained unchanged, resulting in an increased TRPC2/TRPC6 ratio. As the loss of DOT1L decreased TRPC6, which inhibited Ca2+ influx by TRPC2, Dot1lKO HPCs in the yolk sac exhibited accelerated and sustained elevated levels of Ca2+ influx. Such heightened Ca2+ levels might have detrimental effects on the growth and proliferation of HPCs in response to EPO. DOT1L erythroid progenitors erythropoietin TRPC6 calcium influx National Institutes of HealthR01DK091277 University of Kansas Medical Center (KUMC) Research InstituteCenter of Biomedical Research Excellence (COBRE) Program ProjectNIH P30 GM122731 University of Kansas Cancer CenterNIH P30 CA168524 This work was supported by the National Institutes of Health (grant: R01DK091277) and by the University of Kansas Medical Center (KUMC) Research Institute. The mouse model was generated in the Transgenic and Gene Targeting Institutional Facility of the University of Kansas Medical Center, supported in part by the Center of Biomedical Research Excellence (COBRE) Program Project in Molecular Regulation of Cell Development and Differentiation (NIH P30 GM122731) and the University of Kansas Cancer Center (NIH P30 CA168524). ==== Body pmc1. Introduction The regulation of erythropoiesis is a highly orchestrated process involving epigenetic and transcriptional regulation in response to a number of cytokines and growth factors [1]. Amongst all external factors, erythropoietin (EPO) is considered the primary regulator of erythropoiesis [2]. Loss of function of either EPO or the EPO receptor (EPOR) indicates that this interaction is crucial for definitive erythropoiesis in the embryo, and developing mice become severely anemic and die by embryonic day 13.5 (E13.5) [3,4]. When EPO binds to EPO receptors, several signaling pathways are initiated, particularly the phospholipase Cγ (PLCγ) signaling pathway [1]. Activation of PLCγ generates the second messenger, inositol-1,4,5-trisphosphate (IP3). A conformational change in the IP3 receptor upon IP3 binding facilitates its association with transient receptor potential channel (TRPC) proteins, which are voltage-independent calcium (Ca2+) channels [1,5,6,7]. TRPC proteins mediate Ca2+ influx into erythroid progenitors [7,8]. It has been demonstrated that regulation of intracellular Ca2+ by EPO plays a critical role in the survival, proliferation, and differentiation of erythroid progenitors [9,10]. Among the six members of the mouse TRPC family, TRPC2 and TRPC6 messenger RNAs (mRNAs) and proteins are expressed in erythropoietic cell lines [7,8] as well as primary murine erythroid cells [7,8,11]. In addition, these proteins can interact to form heteromultimeric channels [11]. Multimeric channel formation has been reported for many other TRPC family members [12,13,14,15,16] and, in at least one other case, formation of this heteromultimeric channel resulted in the cation channel possessing properties that were substantially different from those of the homomeric channel [12]. In erythroid cells, EPO stimulation induces Ca2+ influx through TRPC2 homomeric channels, but when the channels are heteromultimeric and incorporate TRPC6, EPO-induced calcium influx through TRPC2 is attenuated [11]. Thus, it is speculated that the interaction of TRPC2 and TRPC6 plays an important role in erythroid cells to regulate Ca2+ influx in response to EPO stimulation. In eukaryotic cells, DNA is packaged within the nucleus along with histones and other nuclear proteins to form the nucleosome, the fundamental repeating unit of chromatin. The histones can be post-translationally modified in a variety of ways including acetylation, phosphorylation, ubiquitination, and methylation. These modifications influence chromatin structure, facilitate interactions between nucleosomes, and can potentially regulate transcription [17]. Methylation on lysine (K), which is one of the covalent histone modifications, exists in mono, di, and tri states. This modification is found predominantly on lysine residues at the N-terminal tails of histones H3 and H4 and is catalyzed by one of the family members of histone lysine methyltransferases (HLMTs) [18]. Most HLMT family members contain a conserved SET (suppressor of variegation, enhancer of zeste, and trithorax) domain, which is required for enzymatic activity. In contrast, disruptor of telomeric silencing 1-like (DOT1L), a histone methyltransferase that targets lysine 79 of histone H3 (H3K79), is quite different from most other HLMT family members [19]. DOT1 family members do not have a SET domain, and its substrate, K79, is located within the globular domain of histone H3 [20,21]. DOT1L is the only known methyltransferase in eukaryotic cells responsible for mono-, di-, and tri-methylation of H3K79 [21], and these histone modifications are strongly associated with actively transcribed chromatin regions [22]. The enzyme was first described in yeast to play an important role in telomere silencing [23]. It is also required for the DNA damage response and is associated with gene transcription activity [22,24]. After the DOT1L-deficient mouse line was established, it was shown that DOT1L is required for mouse embryonic development [19], and has since been shown to play a crucial role in many embryonic developmental processes [21,25,26]. We previously reported that DOT1L deficiency in knockout (Dot1lKO) mice results in an embryonic erythropoietic defect and embryonic lethality during mid-gestation in these mice [25]. Consistent with our results about DOT1L function in hematopoiesis, two other groups using a conditional Dot1lKO model showed that DOT1L is also required for murine postnatal hematopoiesis [27,28]. Dot1lKO erythroid progenitors failed to develop normally, showing cell cycle arrest and increased apoptosis [25]. However, the molecular mechanisms underlying DOT1L regulation of early erythropoiesis remain unclear. In this study, we sorted KIT-positive cells from yolk sacs of E10.5 mice in order to enrich for yolk-sac-derived hematopoietic progenitor cells. We found that Trpc6 is a direct target of DOT1L in these cells. We detected an enrichment of H3K79 methylation within the Trpc6 gene locus. Moreover, the loss of Trpc6 expression in Dot1lKO HPCs showed accelerated and sustained high levels of Ca2+ influx and correlated with erythroid progenitor cell cycle arrest and death. 2. Results 2.1. Dot1lKO Erythroblasts Displayed Decreased Proliferation, Cell Cycle Arrest, and Increased Apoptosis Embryos and yolk sacs were collected on embryonic day 10.5 (E10.5) (Figure 1A). E10.5 Dot1lKO embryos and yolk sacs were markedly smaller than the wild-type embryos and yolk sacs (Figure 1B,C). While the wild-type yolk sacs and embryos possessed prominent blood vessels and red blood cells, Dot1lKO yolk sacs and embryos were pale (Figure 1B,C). Equal numbers of cells isolated from the E10.5 wild-type and Dot1lKO yolk sacs were cultured in erythroblast expansion medium containing erythropoietin that differentiated the definitive HPCs into extensively self-renewing erythroblasts (ESREs) [29]. Dot1lKO erythroblasts showed severely blunted proliferation, which resulted in a reduced number of growing cells compared to the wild type (Figure 1D,E). On day 4 of the ESRE cultures, cells were harvested for cell cycle analyses and analysis of apoptosis (Figure 2A). We detected that a large number of Dot1lKO erythroblasts underwent a G0/G1 cell cycle arrest, which resulted in significantly reduced numbers of cells in the S and G2/M phases (Figure 2B–D). Moreover, there was a significant increase in the percentage of Dot1lKO erythroid progenitors that expressed annexin V, indicative of cells undergoing apoptosis. (Figure 2E). For the in vitro definitive erythropoietic assays, cells isolated from E10.5 yolk sacs were plated on methylcellulose media in the presence of appropriate cytokines for colony formation [30]. Cells from Dot1lKO yolk sacs formed significantly smaller erythroid (BFU-E) colonies than those of the wild type (Figure 3A,B). In contrast, the wild-type and Dot1lKO myeloid (CFU-GM) colonies were similar in size (Figure 3C,D). However, both erythroid and myeloid colonies grown from the Dot1lKO yolk sac cells appeared less dense than the wild-type colonies (Figure 3B,D). 2.2. TRPC6 Expression Was Downregulated in Dot1lKO Hematopoietic Progenitor Cells We analyzed the gene expression levels of Trpc family members in KIT-positive HPCs isolated from E10.5 wild-type and Dot1lKO yolk sacs. We observed that among the three Trpc members expressed in these cells (i.e., Trpc1, Trpc2, and Trpc6), only Trpc6 levels were significantly reduced in Dot1lKO progenitor cells. Other TRPC members remained relatively unchanged (Figure 4A). We also detected a marked reduction in TRPC6 protein expression in Dot1lKO yolk sacs cells (Figure 4B,C). These data indicate that DOT1L deficiency leads to reduced expression of TRPC6 in mouse HPCs. Since TRPC2 levels are not affected, the TRPC2/TRPC6 ratio in these progenitor cells increased from 0.95 to 4.40. 2.3. H3K79 Methylation Was Closely Associated with the Trpc6 Expression Level We observed that in Dot1lKO progenitor cells, Trpc6 mRNA levels were significantly reduced compared to the wild type (Figure 4A). We investigated whether the Trpc6 expression level correlates with H3K79 di- and tri-methylation status. We chose mouse bone marrow cells as high Trpc6-expressing and liver cells as low Trpc6-expressing cells (Figure 5A). RT-PCR and Western blot analyses confirmed the expression levels of Trpc6 in bone marrow and liver cells (Figure 5A,B). ChIP-qPCR assays were performed for H3K79me2 and H3K79me3 by using PCR primers designed to cover the whole Trpc6 locus including the promoter region, transcription start site, and middle and end of the gene locus (Figure 5C). Our results demonstrated a significant enrichment of H3K79 di- and tri-methylation at the promoter region and transcription start site of Trpc6 in bone marrow cells (Figure 5D,E). In the middle and end regions of the Trpc6 gene locus, enrichment of H3K79 methylation in bone marrow cells was not different from that of the liver cells (Figure 5D,E). 2.4. Abnormal Calcium Influx in Dot1lKO KIT-Positive HPCs in Response to EPO We tested whether Ca2+ influx is affected in Dot1lKO progenitor cells upon EPO treatment. We used the E10.5 yolk sac as the source of progenitor cells and analyzed the KIT-positive cells for Ca2+ influx during a period of 20 min using a fluorescence microscopy-coupled digital imaging system (Figure 6). We observed that when the wild-type yolk sac cells were exposed to EPO, the intracellular Ca2+ concentration began to increase gradually after 5 min and reached a plateau approximately after 15 min. In sharp contrast, the Ca2+ levels of Dot1lKO yolk sac cells increased immediately after EPO stimulation and continued to increase throughout the observation period. After 20 min, the Ca2+ signal reached a level approximately two-fold that of the wild-type yolk sac cells (Figure 6). 3. Discussion The premise of this study was that an abnormal EPO response occurs in Dot1lKO HPCs due to the decreased level of TRPC6 expression. Our data suggest that H3K79 methylation is disrupted in the absence of DOT1L, which is the underlying cause of decreased Trpc6 expression in Dot1lKO HPCs. We recently generated a mouse model that specifically lacks the methyltransferase activity of DOT1L protein [30]. RNA-seq analysis of the methyl mutant yolk-sac-derived erythroblasts showed a nine-fold downregulation of Trpc6 expression (FDR p < 0.00) [31] (PRJNA666736), consistent with the data presented in Figure 4. These data, coupled with our findings of enriched H3K79 di- and tri-methylation in the promoter and transcriptional start sites of the Trpc6 locus (Figure 5), indicate that DOT1L-mediated H3K79 methylation is essential for Trpc6 expression in HPCs. The decreased expression of TRPC6 increases the TRPC2/TRPC6 ratio. An increased TRPC2/TRPC6 ratio results in a prolonged and heightened level of Ca2+ influx in HPCs, in accordance with previously published findings [11]. We propose that the accentuated Ca2+ influx in response to aberrant EPO signaling plays an important role in determining the Dot1lKO erythropoietic phenotype [25,30]. However, our findings do not exclude the possibility that other DOT1L-regulated cellular mechanisms may contribute to the phenotypic abnormalities observed in Dot1lKO HPCs. We observed that the first wave of primitive as well as the second wave of definitive HPCs were present in the Dot1lKO yolk sacs [25,30]. Although the development of progenitors was not impaired, loss of DOT1L severely affected their proliferation and lineage-specific differentiation [25,30]. Despite an increased responsiveness to EPO, Dot1lKO definitive HPCs failed to proliferate. It needs to be noted that the development of erythroid progenitors does not require EPO signaling [3,4]; however, for the proliferation and differentiation of definitive erythroid progenitors, EPO signaling is essential [32,33]. An aberrant EPO response, due to the decreased TRPC6 expression, resulted in a prolonged and heightened influx of intracellular Ca2+ in KIT-positive Dot1lKO definitive HPCs. An increased Ca2+ influx can result in an excessive protein kinase activation, leading to increased levels of reactive oxygen species (ROS) [34,35] and cytotoxicity [36,37], which did not favor normal cell cycle progression as shown in Figure 2. Lack of DOT1L also gave rise to a condition where the HPCs failed to generate the required number of erythroid cells in vivo, to support the survival of the Dot1lKO embryos [25,30]. We also observed that ex vivo culture of HPCs from E10.5 wild-type yolk sacs in the presence of EPO and cytokines resulted in a huge proliferation of definitive erythroblasts [25,31]. In contrast, the HPCs from E10.5 Dot1lKO yolk sacs underwent cell cycle arrest and apoptosis. The cultured HPCs failed to expand (Figure 1 and Figure 2) and did not form erythroid colonies (Figure 3) under the same culture conditions in the presence of EPO and cytokines. While EPO promoted proliferation of wild-type definitive erythroblasts, an opposite response was observed in Dot1lKO erythroblast cells. Our findings also suggest that stimulation with EPO leads to the cell cycle arrest and death of Dot1lKO erythroid progenitor cells instead of sustained self-renewal due to an aberrant EPO response. However, it was not possible to determine if removal of EPO from E10.5 Dot1lKO HPC culture would recover their cell cycle arrest and proliferation, because EPO signaling is essential for the proliferation of definitive erythroblasts. Further experiments with an inducible Dot1lKO model would clarify the issue. Downregulation of TRPC6 expression due to the lack of DOT1L methyltransferase is responsible for the aberrant EPO response resulting in accelerated and heightened Ca2+ influx in KIT-positive HPCs as suggested in previous studies [11]. Both mRNA and protein levels of TRPC6 were reduced in KIT-positive Dot1lKO HPCs. We observed that expression of Trpc6 correlated with the level of Dot1l expression and, thus, H3K79 methylation. Significantly, the level of H3K79 enrichment was substantially higher in cells that expressed higher amounts of TRPC6 (i.e., bone marrow cells) compared to those that expressed lower amounts (i.e., whole liver) (Figure 5). We also detected an enrichment of di- and tri-methyl H3K79 in the promoter and proximal regions of the Trpc6 gene locus near the transcription start site. DOT1L is the only known methyltransferase that meditates H3K79 methylation in mammalian cells. Based on these findings, we can conclude that Trpc6 is a direct target of DOT1L in erythroid progenitor cells. TRPC proteins play an important role in regulating the rate and state of Ca2+ influx [11,38]. Among the TRPC family members, only the expression of TRPC6 was downregulated in Dot1lKO erythroid progenitor cells, while others, including TRPC2 levels, remained intact, resulting in a four-fold increase in the TRPC2/TRPC6 ratio. Previous studies have shown that interaction between TRPC2 and TRPC6 is essential for modulating EPO-induced Ca2+ signaling [11]. Consequently, we observed an accelerated and increased level of sustained Ca2+ entry in Dot1lKO erythroid progenitor cells (Figure 6). Previous studies have also shown that EPO signaling results in Ca2+ influx, which plays an important role in cell survival, proliferation, and regulation of differentiation [5,9,39] (Figure 7A). However, dysregulation of intracellular Ca2+ levels, due to the disruption of TRPC6 expression, may result in toxic effects (Figure 7B). EPO-induced Ca2+ influx induces protein kinase activation that mediates hematopoiesis. However, excessively high levels of Ca2+ influx can result in sustained levels of PI3K, ERK, and AKT activation, which may lead to cell cycle arrest or apoptosis (Figure 7B). Thus, a reduced level of TRPC6 expression due to the loss of DOT1L in erythroid progenitor cells may result in lethal anemia despite normal EPO signaling. 4. Materials and Methods 4.1. Mouse Lines and Isolation of Cells from Yolk Sac The Dot1lKO mouse line was generated in our previous study [25] and maintained by continuous backcrossing into C57BL/6 strains. Heterozygous Dot1lKO male and female mice were set-up for timed mating. Pregnant females were euthanized at E10.5, and the conceptuses were collected and dissected under stereomicroscopic examination [30]. For all the assays in this study, HPCs were derived from yolk sacs on E10.5. Single-cell suspensions were obtained as described previously [25]. Briefly, yolk sacs were incubated in 0.1% collagenase at 37 °C for 30 min. Then, the yolk sacs were aspirated through 25 G needles and filtered through a 70 µM strainer. Genotyping was performed by PCR using DNA extracted from corresponding embryo tissues [25]. All animal experiments were performed in accordance with the protocols approved by the University of Kansas Medical Center (KUMC) Animal Care and Use Committee. 4.2. Assessment of Cell Proliferation, Cell Cycle Analyses, and Apoptosis Assays Single-cell suspensions of E10.5 wild-type and Dot1lKO yolk sacs were cultured in vitro in ESRE media (StemPro34 media containing nutrient supplement; ThermoFisher Scientific, Waltham, MA, USA), 2 U/mL human recombinant EPO (PeproTech, Inc., East Windsor, NJ, USA), 100 ng/mL SCF (PeproTech, Inc.), 10 µM dexamethasone (MilliporeSigma, Saint Louis, MO, USA), 40 ng/mL IGF1 (PeproTech, Inc., East Windsor, NJ, USA) and penicillin–streptomycin (ThermoFisher Scientific, Waltham, MA, USA) [29] as described in our previous publication [31]. After 4 days, cultured cells were imaged for estimation of cell density. Prior to cell cycle studies, E10.5 HPCs were cultured in M3334 medium for 4 days to generate erythroid colonies. The cells were separated by gentle pipetting, fixed by adding cold 70% ethanol slowly to the cell suspensions and treated with RNase. Cells were then stained with propidium iodide and analyzed by flow cytometry core for cell cycle progression [25,26]. Separately, fixed erythroid cells were labeled with annexin V and then analyzed by flow cytometry for signs of apoptosis as described previously [25,26]. Flow cytometry was performed using a FACSCalibur (BD Biosciences, San Jose, CA, USA), and analyses of cytometric data were carried out using CellQuest Pro software (BD Biosciences, San Jose, CA, USA) [25,26] at the KUMC flow cytometry core. 4.3. Analysis of Definitive Erythropoiesis from Yolk Sac Cells Definitive erythropoiesis, erythroid (BFU-E), and myeloid (CFU-GM) colony formation assays were performed as described previously [30]. Approximately equal numbers of dissociated cells from wild-type Dot1lKO yolk sacs were plated in 35 mm culture dishes in M3434 methylcellulose medium (StemCell Technologies, Seattle, WA, USA) containing cytokines SCF (100 ng/mL), EPO (2 U/mL), IL-3 (5 ng/mL), and IL-6 (5 ng/mL) (PeproTech, Cranbury, NJ, USA), which promoted definitive erythroid and myeloid colony formation [30]. The cells were cultured at 37 °C for 10 days and scored according to the manufacturer’s recommendations. 4.4. Isolation of KIT-Positive Yolk Sac Cells Single-cell suspensions were prepared from E10.5 yolk sacs as described above, and KIT-positive cells were separated as reported previously [25,26]. Briefly, HPCs were incubated with an anti-KIT antibody conjugated to phycoerythrin cyanine (ThermoFisher Scientific, Waltham, MA, USA) at 4 °C for 30 min. Then, the KIT-positive cells were isolated by cell sorting using a BD FACS Aria cell sorter (BD Biosciences, San Jose, CA, USA) at the KUMC flow cytometry core. 4.5. RNA Extraction, cDNA Preparation, and RT-qPCR Total RNA was extracted using TRIzol reagent (ThermoFisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions. cDNAs were prepared from 1 µg of total RNA collected from each sample using the SuperScript VILO cDNA Synthesis Kit (ThermoFisher Scientific, Waltham, MA, USA). Quantitative real-time PCR (qPCR) was performed using Power SYBR Green Master Mix (ThermoFisher Scientific, Waltham, MA, USA) and ran on a 7500 real-time PCR system (ThermoFisher Scientific, Waltham, MA, USA). qPCR results were normalized to Rn18S expression and calculated by the comparative ΔΔCT method [40,41,42]. A list of the qPCR primer sequences used in this study is shown in Table 1 (http://pga.mgh.harvard.edu/primerbank/, accessed on 1 May 2011). 4.6. Western Blot Analyses Western blot analyses of TRPC6 were performed following standard protocols. Cells from the whole yolk sac, bone marrow, or liver were lysed in Nonidet-P40 (NP-40) buffer (150 mM sodium chloride, 1.0% NP-40, 50 mM Tris, and pH 8.0) on ice for 30 min. Cell extracts were centrifuged at 12,000× g at 4 °C for 20 min. Supernatants were collected and protein concentrations were measured using the Bradford assay (BioRad, Hercules, CA, USA). Approximately 30 µg of each protein sample was mixed with NuPAGE SDS 4× sample buffer (ThermoFisher Scientific, Waltham, MA, USA) and were electrophoresed on a 10% precast gel in SDS running buffer (250 mM Tris base, 190 mM glycine, 0.1% SDS, and pH 8.3) (BioRad, Hercules, CA, USA). Proteins were transferred to PVDF membranes, and the membranes were blocked in 5% bovine serum albumin (BSA) overnight at 4 °C. Blocked membranes were incubated with 1:300 TRPC6 primary antibody (Abcam, Inc., Cambridge, UK) for 4 h at 4 °C with shaking. Membranes were washed 5 times with TBST buffer at 4 °C with shaking and incubated with 1:5000 secondary antibody (Goat anti-Mouse IRDye CW800) for 45 min at room temperature. Then, the membranes were washed another 5 times with TBST, and images were captured with an Odyssey CLx infrared image system (LI-COR Biosciences; Lincoln, NE, USA). The same membrane was stripped and incubated with an antibody against ACTB (MilliporeSigma, Saint Louis, MO, USA) as a loading control of the protein samples. 4.7. Extraction of Bone Marrow and Liver Cells Bone marrow cells that expressed high levels of Trpc6 [16] were isolated from adult male mouse femurs as described previously [16]. Briefly, skin and muscles from the pelvic and femoral bones were removed. The bones were cleaned, and the ends were cut off at each end. Bone marrows were expelled from the ends of the bone passing cold sterile RNAse-free PBS with a 5 mL syringe fitted with a 25 G needle. Then, the cell aggregates were dispersed, and marrow cells were separated by repeated aspiration with a 5 mL syringe attached with a 27 G needle, passing through a 70 µM strainer. For liver cell isolation, mouse liver tissues were dissected and minced into small pieces in the presence of cold sterile RNAse-free PBS. The tissue pieces were ground between glass slides and passed through 70 µM strainer. Strained bone marrow or liver cells were washed with cold, sterile RNAse-free PBS used for RNA or protein extraction or fixed in formaldehyde for ChIP assays. 4.8. ChIP Assay for H3K79 Di- and Tri-Methylation in Trpc6 Locus Chromatin immunoprecipitation (ChIP) was carried out following standard protocols [43,44]. Briefly, for each assay, 107 cells were resuspended in 10 mL IMDM medium containing 5% FBS and were fixed in 1% formaldehyde for 10 min. Glycine was added to a final concentration of 125 mM and incubated at room temperature with rotation for 10 min to neutralize formaldehyde. The cells were washed twice with cold PBS, lysed in 500 µL SDS lysis buffer with protease inhibitor cocktail (MilliporeSigma, Saint Louis, MO, USA), and incubated on ice for 10 min. The nuclear pellets were washed with a cold lysis buffer and sonicated using a VWR Branson Sonifier 250 probe sonicator (VWR International, Radnor, PA, USA) 4–6 times, 15 s each time, to reduce the chromatin length to between 200 and 1000 bp. Sonicated chromatin solutions were centrifuged at 10,000× g at 4 °C for 10 min. Clear supernatants were collected into 1.5 mL tubes, and ~500 µL chromatin solution was mixed with 75 µL Protein A Agarose/Salmon Sperm DNA and incubated at 4 °C with rotation overnight. The solution was centrifuged at 3000× g for 5 min. The supernatant was transferred to a new tube and diluted 10-fold in ChIP Dilution Buffer. Two micrograms of H3K79me2 or H3K79me3 antibody (Abcam, Inc., Cambridge, UK) was added to 1 mL of the diluted chromatin solution each, and another 1 mL was used as “input”. Two micrograms of normal rabbit IgG (BioSource International, Inc., Camarillo, CA, USA) was used as negative control. Chromatin solutions were incubated at 4 °C with rotation for 4 h in the presence of specific antibodies. Then, 65 µL Protein A Agarose/Salmon Sperm DNA was added to each tube and incubated at 4 °C with rotation for another 2 h. The solutions were centrifuged at 3000× g for 5 min at 4 °C, and the supernatants were discarded. The Protein A Agarose beads were washed for 5 min on a rotating platform sequentially with 1 mL of each of the low-salt wash buffer, high-salt wash buffer, LiCl wash buffer, and 1XTE. Then, the chromatins were eluted with 250 µL elution buffers twice, and the elutes were combined. Twenty microliters of 5 M NaCl and 2 µL RNase were added to each eluted chromatin sample and incubated at 37 °C for 30 min to remove RNAs and then again at 65 °C for 4 h to decrosslink the ChIPed chromatin materials. The chromatin solutions were mixed with 10 µL of 0.5 M EDTA, 20 µL 1 M Tris-HCl, PH 6.5, and 2 µL of 10 mg/mL Proteinase K and incubated at 45 °C for 1 h. Finally, the chromatin DNA fragments were recovered by phenol/chloroform extraction and ethanol precipitation. Real-time PCR was performed to quantify precipitated DNA with the use of the 7500 real-time PCR system. The ChIP-qPCR primers used for analyzing the Trpc6 locus are listed in Table 2. 4.9. Measuring Calcium Influx of Yolk Sac Cells in Response to EPO A fluorescence microscopy-coupled digital imaging system was used to measure the Ca2+ concentration change of HPCs when treated with EPO. Fura2 was used as the detection fluorophore. After the whole yolk sacs were dissociated into single cells, the cells were washed 2–3 times with PBS to completely remove fetal bovine serum (FBS). HPCs were resuspended in 40 µL RPMI 1640 (MilliporeSigma, Saint Louis, MO, USA) without FBS. Cells were loaded into the center of a culture dish coated with poly-lysine and fixed for 10 min at room temperature. The medium was then removed, and the cells were stained with 1 µM Fura2 and Pluronic F127 (ThermoFisher Scientific, Waltham, MA, USA) (1:1 in volume) at 37 °C for 30 min. The staining solution was removed, and the cells were covered with 150 µL RPMI containing 10% FBS. Mouse EPO (R&D Systems, Minneapolis, MN, USA) was added to a final concentration of 10 units/mL. Then, the sample was analyzed immediately by confocal fluorescence microscopy on a Nikon TE2000U microscope (Nikon, Tokyo, Japan). Fura2-loaded cells were visualized by digital video imaging, and the fluorescence was quantitated using the intensity ratio of the emission (510 nm), which was measured following excitation at 340 nm divided by the emission following excitation at 380 nm. Each sample was measured over 20 min. After, the data were calculated and analyzed using Metamorph 6.1 (Universal Imaging Corp., Downingtown, PA, USA). 4.10. Statistical Analyses Each experimental group consisted of a minimum of 6 samples. The experimental results are presented as the mean ± standard error (SE). The results were analyzed for one-way ANOVA, and the significance of the mean differences was determined by Duncan’s post hoc test with p < 0.05. All the statistical calculations were performed using SPSS 22 (IBM, Armonk, NY, USA). Author Contributions P.E.F. conceptualized the study; Y.F., S.B., E.B.L., A.R., H.W. and M.A.K.R. performed the studies, wrote the manuscript, and prepared the figures; T.A.F., J.L.V. and W.H.K. critically read and edited the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All animal experiments were performed in accordance with the protocols approved by the University of Kansas Medical Center’s (KUMC) Animal Care and Use Committee. Informed Consent Statement Not applicable. Data Availability Statement SRA, NLM, USA (PRJNA666736). Conflicts of Interest The authors declare that they have no conflict of interest. Figure 1 Dot1lKO progenitors failed to proliferate in response to EPO. (A) Schematic diagram showing the timeline of the embryo and yolk sac collection and in vitro culture of yolk-sac-derived erythroblasts. Representative images of E10.5 wild-type and Dot1lKO yolk sacs and embryos (B,C). Both the Dot1lKO yolk sacs as well as the embryos were smaller than those of the wild type (B,C). Cells were isolated from E10.5 wild-type and Dot1lKO yolk sacs and equal numbers were cultured in extensively self-renewing erythroblast (ESRE) culture medium as described. The cells were then differentiated from the definitive erythroid progenitors into erythroblasts (D,E). Compared to the wild-type erythroblasts (D), Dot1lKO erythroblasts had severely reduced numbers (E). Figure 2 Dot1lKO progenitors underwent cell cycle arrest during in vitro erythroblast culture. (A) Schematic diagram showing the studies for cell cycle progression and apoptosis analysis. On day 4 of culture, cells were collected, fixed, and either stained with propidium iodide for cell cycle analyses or labeled with annexin V for signs of apoptosis. A large number of erythroid progenitors from Dot1lKO yolk sacs displayed G0/G1 arrest (B–D). In addition, an increased percentage of Dot1lKO erythroid progenitors were found to be annexin V positive (E). Data are expressed as the mean ± SE; n > 6; * p < 0.05. Figure 3 Equal numbers of wild-type and Dot1lKO E10.5 yolk sac cells were cultured in methylcellulose medium containing cytokines that promoted definitive erythroid and myeloid lineage differentiation. While Dot1lKO progenitors formed significantly smaller sized erythroid (BFU-E) colonies (A,B), the wild-type and Dot1lKO myeloid colonies (CFU-GM) were similar in size (C,D). Figure 4 Expression of TRPC6 was markedly reduced in KIT-positive Dot1lKO hematopoietic progenitors. (A) Among the three genes in the Trpc family (i.e., Trpc1, Trpc2, and Trp6), only Trpc6 levels were dramatically reduced in Dot1lKO compared to WT, while the levels of the other members remained relatively unchanged. TRPC6 protein levels in KIT-positive progenitor cells from Dot1lKO yolk sacs were also significantly reduced (B,C). Data are expressed as the mean ± SE; n > 6; * p < 0.05. Figure 5 Enrichment of di- and tri-methyl H3K79 in Trpc6 gene loci. Trpc6 expression was tested by RT-qPCR in bone marrow (BM) and liver cells. Trpc6 mRNA levels were significantly higher in BM cells compared to that in liver cells (A). TRPC6 protein was also detected in BM and liver cells by Western blot analysis, which showed that TRPC6 protein was also markedly higher in BM cells (B). ChIP assays were performed on chromatin preparations from BM and liver cells to assess H3K79 di- and tri-methylation in the Trpc6 gene locus. (C) Several pairs of primers were designed covering the Trpc6 gene locus including the promoter region (P1, P2), transcription start site (TSS), and middle and end of the gene locus (M, E). ChIP assays were performed in the promoter region of Trpc6 gene locus for H3K79 di-methylation (D) and H3K79 tri-methylation (E). There was significantly greater enrichment of both H3K79 di- and tri-methylation at the P1, P2, and TSS sites of the Trpc6 gene in BM cells than that of liver cells. The ChIP-qPCR data represent 3 independent experiments. Data are expressed as the mean ± SE; n > 6; * p < 0.05. Figure 6 Accelerated and enhanced calcium influx in Dot1lKO erythroid progenitors. E10.5 Dot1lKO and wild-type yolk sac cells were stained, treated with EPO, and the Ca2+ signals in individual cells were recorded using fluorescence microscopy. After EPO treatment, progenitor cells from Dot1lKO yolk sacs showed a sustained increase in Ca2+ levels. Data are expressed as the mean ± SE; n > 6; *p < 0.05. Figure 7 Dot1lKO erythroid progenitors exhibited increased calcium influx following decreased TRPC6 expression. TRPC2 allows Ca2+ influx into erythroid progenitors. TRPC6 forms a hetero-tetramer with TRPC2 and negatively regulates TRPC2-dependent Ca2+ influx to maintain the normal intracellular Ca2+ level (A). The loss of DOT1L decreases TRPC6 expression, resulting in an increased TRPC2/TRPC6 ratio. This favors the formation of TRPC2 homo-tetramers over TRPC2/TRPC6 hetero-tetramers leading to an excessive influx of Ca2+ into Dot1lKO erythroid progenitors (B). An elevated Ca2+ level results in toxic intracellular responses and aberrant cell signaling linked to cell cycle arrest and cell death observed in Dot1lKO erythroid progenitors. ijms-23-05137-t001_Table 1 Table 1 Primers used in the qRT-PCR studies. Gene Reference mRNA Forward Primer Reverse Primer Trpc1 NM_0011643.4 366F: cggttgtcagtccgcagat 456R: tcgttttggccgatgattaagta Trpc2 NM_011644.3_ 631F: ctcaagggtatgttgaagcagt 741R: gttgtttgggcttaccacact Trpc6 NM_004621.6 164F: gcttccggggtaatgaaaaca 255R: gtatgctggtcctcgattagc ijms-23-05137-t002_Table 2 Table 2 Primers for the ChIP-qPCR for the promoter, TSS, and intragenic sites within the Trpc6 loci. Target Chromosome 9 Locus Forward Primer Reverse Primer Promoter-1 8543340-680 aagcagggctcactgaatctgg ggcattttccgatggtgtctg Promoter-2 8543915-4113 cccaaataaagaatgtgcctgg cgctgaagagttactatgtcaaccg Trpc6 TSS 8544511-618 gagagccaggactatttgctgatg tgccctcgcccatacttacaag Trpc6 Middle 8549504-630 tctacctcctgatgctgggcttac ggggtttgaagagatgagagtgc Trpc6 End 8679716-902 tgccctacaaagcaatgaaagg aaagagagcgtgagcccaacac Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Tsiftsoglou A.S. Vizirianakis I.S. Strouboulis J. Erythropoiesis: Model systems, molecular regulators, and developmental programs IUBMB Life 2009 61 800 830 10.1002/iub.226 19621348 2. Ingley E. Tilbrook P.A. Klinken S.P. New insights into the regulation of erythroid cells IUBMB Life 2004 56 177 184 10.1080/15216540410001703956 15230344 3. Lin C.S. Lim S.K. D’Agati V. Costantini F. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092509 jcm-11-02509 Article Seroprevalence of SARS-CoV-2 in a Cohort of Patients with Multiple Sclerosis under Disease-Modifying Therapies Sancho-Saldaña Agustín 1 https://orcid.org/0000-0002-0738-5578 Gil Sánchez Anna 2 https://orcid.org/0000-0002-3875-8074 Quirant-Sánchez Bibiana 34 Nogueras Lara 2 Peralta Silvia 5 Solana Maria José 1 https://orcid.org/0000-0002-6387-8764 González-Mingot Cristina 1 https://orcid.org/0000-0003-1379-1991 Gallego Yhovanni 1 Quibus Laura 1 https://orcid.org/0000-0001-8643-5053 Ramo-Tello Cristina 6 Presas-Rodríguez Silvia 6 Martínez-Cáceres Eva 34 https://orcid.org/0000-0001-7903-3478 Torres Pascual 2 Hervás José Vicente 7 Valls Joan 8 Brieva Luis 1* 1 Neurology Department, Hospital Universitario Arnau de Vilanova, IRB Lleida, 25198 Lleida, Spain; agustinsanchosaldana@gmail.com (A.S.-S.); solanamoga@gmail.com (M.J.S.); crismingot@hotmail.com (C.G.-M.); yoga253@hotmail.com (Y.G.); lquibusr@gmail.com (L.Q.) 2 Neuroimmunology Group, Institut de Recerca Biomèdica, Universitat de Lleida, 25001 Lleida, Spain; agil@irblleida.cat (A.G.S.); lara.noguerasp@gmail.com (L.N.); pascual.torres@udl.cat (P.T.) 3 Immunology Division, Hospital Germans Trias i Pujol, LCMN, 08916 Badalona, Spain; bquirant.germanstrias@gcat.cat (B.Q.-S.); emmartinez.germanstrias@gencat.cat (E.M.-C.) 4 Department of Cell Biology, Physiology, Immunology, Autonomous University, Bellaterra, 08193 Barcelona, Spain 5 Multiple Sclerosis Foundation from Lleida, 25198 Lleida, Spain; sipem@hotmail.com 6 Multiple Sclerosis and Clinical Neuroimmunology Unit, Neurosciences Department, Hospital Germans Trias i Pujol, 08916 Badalona, Spain; cramot@gmail.com (C.R.-T.); spresas.germanstrias@gencat.cat (S.P.-R.) 7 Hospital de Sant Joan Despí Moisès Broggi, 08970 Sant Joan Despí, Spain; josevicente.hervas.garcia@gmail.com 8 Biostatistics Group, Institut de Recerca Biomèdica de Lleida, 25198 Lleida, Spain; joanvallsmarsal@gmail.com * Correspondence: lbrieva.lleida.ics@gencat.cat; Tel.: +34-973705200 (ext. 2601) 29 4 2022 5 2022 11 9 250908 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/). Background: Disease-modifying therapies (DMTs) used to treat multiple sclerosis (MS) alter the immune system and therefore increase the risk of infection. There is growing concern about the impact of COVID-19 on patients with MS (pwMS), especially those treated with DMTs. Methods: This is a single-center prospective observational study based on data from the Esclerosis Múltiple y COVID-19 (EMCOVID-19) study. Demographic characteristics, MS history, laboratory data and SARS-CoV-2 serology, and symptoms of COVID-19 in pwMS treated with any DTM were extracted. The relationship among demographics, MS status, DMT, and COVID-19 was evaluated. Results: A total of 259 pwMS were included. The administration of interferon was significantly associated with the presence of SARS-CoV-2 antibodies (26.4% vs. 10.7%, p = 0.006). Although patients taking interferon were significantly older (49.1 vs. 43.5, p = 0.003), the association of interferon with the presence of SARS-CoV-2 antibodies was still significant in the multivariate analysis (OR 2.99 (1.38; 6.36), p = 0.006). Conclusions: According to our data, pwMS present a higher risk of COVID-19 infection compared with results obtained from the general population. There is no evidence of a worse COVID-19 outcome in pwMS. DMTs did not significantly change the frequency of COVID-19, except for interferon; however, these findings must be interpreted with caution given the small sample of pwMS taking each DMT. multiple sclerosis COVID-19 SARS-CoV-2 DMT seroprevalence Carlos III InstituteThis study was funded by a competitive grant from the Carlos III Institute, a public entity. ==== Body pmc1. Introduction Since its origin in Wuhan, China in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing Coronavirus disease 2019 (COVID-19) has rapidly become pandemic [1], affecting countries worldwide. COVID-19 has a wide range of clinical manifestations, ranging from no symptoms to life-threatening acute respiratory distress [2]. Spain is among the countries more heavily affected by COVID-19. Lleida is a region in the northwest of Spain, in Catalonia, with a reported seroprevalence ranging from 3.8% [3] (July 2020) to 10.4% (November 2020) and with a cumulated seroprevalence of 12.2%, according to the ENE-COVID study carried out by the Spanish Ministry of Health to determine the seroprevalence of SARS-CoV-2 in the Spanish population [4]. Multiple sclerosis (MS) is a chronic, inflammatory, and demyelinating disease in which the autoimmune system attacks the myelin sheath in the central nervous system [5]. It is a leading cause of neurologic symptoms in young adults and has no known cure. The disease-modifying therapies (DMTs) used to treat MS alter the immune system, thus increasing the risk of infection, mainly in the upper respiratory and urinary tracts [6]. There is growing concern about the impact of COVID-19 on patients with multiple sclerosis (pwMS). Currently, there is no evidence that pwMS taking DMTs are more susceptible to developing COVID-19 or more likely to present a worse outcome. Data from an Italian registry suggest that COVID-19 is more severe in patients with progressive MS, over 50 years of age, or with a higher Expanded Disability Status Scale (EDSS) score. The infection fatality risk for SARS-CoV-2 in MS was 1.66%. Most nonsurvivors were not taking DMTs [7], and it has even been suggested that immunosuppression in pwMS taking certain DMTs may protect against severe COVID-19 infection [8] Some studies [9,10,11,12] have suggested that each of the DMTs used in MS has a different impact on COVID-19 infection (no risk: interferon beta and glatiramer; low risk: teriflunomide, dimethyl fumarate, and natalizumab; intermediate or high risk: fingolimod, anti-CD20 therapies, cladribine, and alemtuzumab). There are sparse data on the complex natural immunity to SARS-CoV-2 at the population level. A general population study in Catalonia in which a well-validated multiplex serology test was performed in around 5000 subjects revealed a seroprevalence of 18.1% in adults, and extrapolation of the results to the general population of Catalonia suggested a seroprevalence of 15.3% [13]. Antibodies persisted up to 9 months after infection. Immune profiling of infected individuals revealed that the more severe the infection, the more robust the seroresponse, with a shift towards IgG over IgA and antispike over antinucleocapsid responses. Asymptomatic COVID-19 infections account for 28.7% [14], and these patients are more likely to show greater IgA than IgG responses compared to those with more severe disease. In this study performed in the province of Lleida, Spain, we evaluated the prevalence and severity of SARS-CoV-2 in pwMS taking DMTs and its relationship with each DMT. We hypothesize that pwMS taking DMTs are more susceptible to SARS-CoV-2 infection. 2. Material and Methods 2.1. Study Design and Patients This is a single-center, prospective, observational study based on data from the prospective ongoing Esclerosis Múltiple y COVID-19 (EMCOVID-19, by its Spanish acronym) study carried out by 20 centers in Spain that aims to evaluate the seroprevalence of SARS-CoV-2 in a large cohort of pwMS treated with DMTs in order to evaluate the correlation between MS and COVID-19. In EMCOVID-19, patients attended two visits (baseline and 6 months) in which they were asked about their latest or recent manifestations of COVID-19 and their MS symptoms, and a blood sample was taken. All patients diagnosed with MS treated with any DMT in the MS unit in the Hospital Universitario Arnau de Vilanova, Lleida, Spain study were included. Data from the baseline EMCOVID-19 visit were extracted. Baseline characteristics (sex, age, pregnant/not pregnant, smoker history, MS type, and EDSS), MS history (time from MS diagnosis, time from first symptoms, time from latest relapse, use of glucocorticoids in the previous 3 months, and current DMT), laboratory data (lymphocyte count), and symptoms of COVID-19 were recorded, and the correlation among any of these characteristics and the presence of antibodies for SARS-CoV-2 in serum was analyzed. Lymphopenia was defined as total lymphocytes <1000/μL Patients with IgG, IgM, or IgA antibodies against SARS-CoV-2 were considered confirmed cases for SARS-CoV-2 infection and classified as symptomatic or asymptomatic. The results of seroprevalence in this study were compared with those obtained in the general population. Epidemiological data of COVID-19 cases confirmed by serological analysis were obtained from ENE-COVID, a Spanish nationwide, population-based seroepidemiological study performed by the Ministry of Health, Consumer Affairs and Social Welfare [3,4]. 2.2. Blood Samples Peripheral blood samples were taken between March 2020 and September 2020, before the start of COVID-19 vaccination in Spain (28 December 2020). Samples were centrifuged and frozen at −80 °C. ELISA was used to determine IgG, IgM, and IgA against SARS-CoV-2 using 3 recombinant antigens: nucleocapsid, S1, and S2 dominion (Diapro®, Sesto San Giovanni, Italy). 2.3. Statistical Analysis Mean (and standard deviation) and absolute frequency (and percentage) were used to describe the variables analyzed, and the median and interquartile range was also reported when appropriate. Bivariate tests, such as the chi-square test, t-test, and Anova (when a parametric test was required) or Fisher’s and Kruskal–Wallis tests (when a nonparametric test was required) were performed to evaluate the correlation between variables. Prevalence was calculated as a percentage with a 95% confidence interval (CI). Simple logistic regression models were used to estimate odds ratios (OR) to assess the association between different risk factors and positive immunization status. A stepwise multiple logistic regression model was constructed to determine factors with a significant correlation. All analyses were performed using R software, setting the threshold for significance at 0.05. 3. Results A total of 259 patients were included, with a median age of 44.3; 171 (66%) were female, and 88 (33%) were male; 58 patients (23.7%) were active smokers. In terms of MS, 223 (86.1%) presented relapsing-remitting multiple sclerosis (RRMS); 21 (8.11%) presented secondary progressive multiple sclerosis (SPMS), and 15 patients (5.79%) presented primary progressive multiple sclerosis (PPMS). One hundred sixty-seven patients (66.3%) had not had a relapse in the previous year, and only 13 patients (5.2%) had received glucocorticoids in the previous 3 months to treat a relapse. One hundred thirty-three patients (51.3%) were taking some kind of platform DMT (immunomodulatory treatment), and 126 (49.1%) were taking a high-activity DMT (immunosuppressive treatment). More information about baseline characteristics and treatments is shown in Table 1. One hundred thirty-five patients (52.1%) had lymphopenia (<1000 lymphocytes) of which 22 (16.3%) had severe lymphopenia (grade 4; <200 lymphocytes). Fifty-three (20.46%) patients were positive for IgG, IgM, or IgA antibodies against SARS-CoV-2: 28 (10.9%) were IgG positive; 29 (11.4%) were IgM positive, and 17 (6.75%) were IgA positive. In total, 14 patients (5.43%) had COVID-19 symptoms. Half of these patients (7/14) had a fever and/or cough; 4 patients (28%) had nasal congestion and/or dysphonia, and 3 (21%) patients had mild or moderate dyspnea. Fatigue and/or headache was found in 3 patients (21%), and 1 patient had anosmia (7.1%). One patient received empirical treatment with azithromycin, and only 1 patient required hospitalization. This patient received ocrelizumab and presented with fever, moderate dyspnea, and bilateral pneumonia. He received hydroxychloroquine and oxygen therapy and made a good recovery after 15 days of hospitalization. Among symptomatic patients, three (21%) were taking glatiramer, two patients dimethyl fumarate (14.2%), two patients teriflunomide, two patients ocrelizumab, one patient interferon (7.1%), one patient cladribine, one patient natalizumab, and one patient alemtuzumab. The binary analysis showing differences between seropositive and seronegative patients is shown in Table 2. Interferon was significantly associated with the presence of SARS-CoV-2 antibodies (26.4% vs. 10.7%, p = 0.006). Although patients on interferon were significantly older (49.1 vs. 43.5, p = 0.003), the association between interferon and SARS-CoV-2 antibodies was still significant in the multivariate analysis (OR 2.99 (1.38; 6.36), p = 0.006). Alemtuzumab was also associated with the presence of SARS-CoV-2 antibodies (7.7% vs. 4.37%, p = 0.31), but this was not statistically significant. No association was found with the remaining DMTs (Table 2). 4. Discussion It is still unclear whether pwMS have an increased susceptibility to COVID-19 and worse outcomes compared with the general population. Describing the characteristics of the immune response in specific autoimmune pathologies, such as MS, that are treated with immune system-modifying drugs can help us understand how SARS-CoV-2 affects this population and how we can minimize the risks. In a previous study [15], 18 out of 76 pwMS (23.7%) were hospitalized; 8 (10.5%) had COVID-19 critical illness or related death. A similar proportion was reported in other studies [16]. Factors associated with worse outcomes were similar to those found in the general population (older age, presence of comorbidities, progressive disease, and nonambulatory status), and DMT use was not associated with a worse prognosis [15]. Although the proportion of hospitalized patients in the latter study is considerably higher than that reported here, all their pwMS had symptoms suggestive of COVID-19, which constitutes a selection bias. In a survey study performed in Barcelona, a higher incidence of COVID-19 was found in pwMS compared to the general population (COVID-19 was confirmed in 5 patients (1.2%) by PCR and suspected in 46 (11.3%)) [16]. In this study, only symptomatic patients or those admitted to hospital underwent PCR testing, which could explain the lower frequency of COVID-19 cases compared to our data. In this sample, the prevalence of COVID-19 among pwMS treated with DMT is notably higher than that reported in a previous study performed in Lleida (20.4% vs. 12.2%) [3]. In our cohort, 94.6% of patients were asymptomatic. Symptomatic patients presented with mild symptoms, and hospitalization was only required in one case treated with ocrelizumab. Symptoms, however, were not associated with lymphopenia or any specific DMT. Immune response to SARS-CoV-2 plays a critical role in the development of acute respiratory distress syndrome (ARDS) and determines prognosis due to the exacerbation of inflammatory components after dysregulation of the immune system [17]. Based on the hypothesis that an overactive immune response could cause clinical deterioration in SARS-CoV-2 infection, it has been suggested that immunosuppressive or immunomodulatory therapies could protect against some COVID-19 complications [18,19]. Our results show that treatment with a specific DMT was not significantly associated with higher seroprevalence, except in patients taking interferon, and the risk of infection was not higher in patients taking immunosuppressive drugs vs. those taking immunomodulatory drugs. Interferons are naturally occurring cytokines that participate in a wide range of anti-inflammatory processes [20]. Due to its putative antiviral effect, it seems unlikely that interferon would increase susceptibility to infection or would negatively influence the immune response against SARS-CoV-2 [21]. We think that the higher seroprevalence among patients taking interferon could be explained by interferon having less effect on the immune system resulting in a more appropriate humoral response. A meta-analysis of clinical trials revealed that early administration of interferon-β in combination with antiviral drugs was a promising therapeutic strategy against COVID-19 [22]; however, this was not confirmed in a recent clinical trial [23]. Another DMT, fingolimod, is thought to be potentially useful to treat COVID-19 once pneumonia is established, due to some type of ‘polycytokine’ inhibiting properties that may have more beneficial effects compared to selective cytokine inhibitors [24]. The risk of severe COVID-19 in pwMS taking fingolimod or siponimod appears to be similar to the general population [25]. All these findings could support the use of immunosuppressants to reduce the cytokine storm caused by COVID-19, and therefore prevent ARDS [26,27,28]. Based on this new evidence, pwMS treated with DMTs could be more susceptible to SARS-CoV-2 infection for various reasons. For example, immunosuppression derived from some DMTs could make pwMS more susceptible to COVID-19 infection (higher percentage of infections by SARS-CoV-2) without affecting the capacity of the immune response to fight the virus (most infected patients were asymptomatic). However, we found no significant association between lymphopenia and susceptibility to SARS-CoV-2 infection. A recent study characterizing humoral immunity in mRNA-COVID-19 MS vaccinees treated with high-efficacy DMTs found that some developed a humoral response despite a normal absolute lymphocyte count [29]. The entire sample of patients under treatment with DMT in our center underwent ELISA, and all reported cases were confirmed and retested, allowing us to detect asymptomatic cases. In a previously published study performed in Barcelona, DMT was not associated with a risk of infection [16]. In a cross-sectional study performed in Italy between 11 May and 15 June 2020, the prevalence of SARS-CoV-2 IgG/IgM in pwMS, including those receiving systemic immunosuppression treatment, was low (2.9%) and similar to the general population [30]. However, this study used a less sensitive test (lateral flow), which could explain this discrepancy. Fewer patients on ocrelizumab had antibodies against SARS-CoV-2, although this difference was not significant. Ocrelizumab is a humanized monoclonal antibody that targets CD20 on the surface of B-cells, causing prolonged selective B-cell depletion and depleting antibody production. The authors of a recent case series [31] concluded that B-cell depleting therapies, such as rituximab and ocrelizumab, might be associated with greater susceptibility to COVID-19. In this case, the diagnosis of COVID-19 was based on clinical and radiological findings, but not on a serologic test, such as that used in our study. In this regard, Zabalza et al. also reported less serological response in patients on anti-CD20 therapies (15.8%) than those on other DMTs (48.8%; p = 0.045) or no DMTs (68.4%; p = 0.003) [32]. Some authors suggest pwMS taking B-cell-depleting therapies could have a worse COVID-19 prognosis [11,33]. However, others suggest that anti-CD20 does not appear to contribute to the risk of infection by SARS-CoV2 [34]. We believe that patients on B-cell-depleting therapies may be more prone to COVID-19 infection because they produce low, short-lived antibody titers. Although infection is more likely to be due to T-cell dysfunction, B-cells play an important role in T-cell regulation [35]. This study has some strengths and limitations. Among its strengths, pwMS in Lleida were managed in a single MS unit that is far from other MS units in Catalonia. Therefore, the sample is representative of the MS population in the province of Lleida. In addition, the ELISA test used in the analysis is more sensitive to antibodies against SARS-CoV-2 than the techniques used in other studies. This allowed us to detect most of COVID-19 cases, regardless of time of infection or severity. Another strength of this study is the availability of a reference population in the same time period and epidemiological context from the ENECOVID study. In terms of limitations, this is a single-center study that used a relatively small sample of patients taking any DMTs to assess their relationship with immune serologic status. Cell-mediated immunity against SARS-CoV-2 was not evaluated, and the ELISA test could mask false positives with other coronaviruses. Finally, although we used data from the ENECOVID study as our reference population, we did not have a true control group to compare our findings. In conclusion, according to the collected data, pwMS (especially those with RRMS) had a higher seroprevalence of COVID-19 in comparison with previous reports obtained by serological analysis of the general population, although most of them were asymptomatic. There is no evidence of a worse COVID-19 outcome in patients affected by MS. DMTs did not significantly change the severity of COVID-19; however, these findings must be interpreted with caution given the small number of pwMS taking each DMT. Seroprevalence was higher in patients taking interferon, but this could be explained by a “healthier” humoral response against COVD-19 instead of an increased susceptibility to infection. Immunosuppressive drugs did not increase the risk of infection compared with immunomodulatory drugs. This, in turn, may raise other questions regarding the effect of ongoing vaccines in pwMS, especially in those who have already had COVID-19. To the best of our knowledge, this is the largest prospective study analyzing the seroprevalence of SARS-CoV-2 in pwMS and its relationship with DMTs in Spain; however, multicenter studies with even larger sample are warranted to add clarity to some of the questions that concern both neurologists and patients. Acknowledgments We would like to thank the Carlos III Health Institute for the funding received (with possible FEDER cofinancing) under project COV20. The authors would also like to thank Antoni Torres-Collado from MSC consulting for his help in editing the final version of this manuscript. PT received a Margarita Salas postdoctoral fellowship from Ministry of Universities (Spanish Government) supported by NextGenerationEU. Author Contributions A.S.-S.: Writing—original draft and writing—review and editing; A.G.S.: Software, investigation, data curation, writing—review and editing, and project administration; B.Q.-S.: Methodology and validation; L.N.: Methodology and validation; S.P.: Investigation and resources; M.J.S.: Investigation and resources; C.G.-M.: Investigation; Y.G.: Investigation and data curation; L.Q.: Investigation; C.R.-T.: Investigation; S.P.-R.: Investigation; E.M.-C.: Validation; P.T.: Investigation; J.V.H.: Software, investigation, and visualization; J.V.: Formal analysis and data curation; L.B.: Conceptualization, methodology, software, investigation, visualization, writing—review and editing, project administration, supervision, and funding acquisition. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the referral committee of the Hospital Universitario Arnau de Vilanova, Lleida, and by the local Ethics Committee of each participating center. Informed Consent Statement We obtained written informed consent from all patients participating in this study. Conflicts of Interest The IRB LLeida has received financial support for this study from Merck, Sanofy, Biogen, and Roche; Agustin Sancho has received travel and congress expenses from Biogen, Genzyme, Merck, Roche, and Novartis; Anna Gil Sánchez has received travel and congress expenses and speaker fees from Biogen, Genzyme, Merck, Novartis, and Roche; Bibiana Quirant-Sánchez has no conflict of interest to declare; Lara Nogueras Penabad has received travel and congress expenses from Biogen, Genzyme, Merck, Roche, and Novartis; Mª José Solana Moga has received travel, congress expenses, and speaker fees from Biogen, Genzyme, Merck, Novartis, and Roche; Cristina González-Mingot has received travel congress expenses and speaker fees from Biogen, Genzyme, Merck, Roche, and Novartis; Yhovany Gallego has taken courses sponsored by Sanofi Genzyme; Laura Quibus has received congress expenses from Sanofi; Cristina Ramo-Tello has received honoraria, travel expenses, and speaker fees or advisory fees from Biogen, Genzyme, Merck, Novartis, Roche, and Allmiral; Silvia Presas-Rodríguez has received travel and congress expenses from Biogen, Novartis, Roche, and Merck and speaker fees from Biogen and Novartis; Eva Martínez-Cáceres declares the receipt of grants/research support from Biogen, the receipt of honoraria or consultation fees from Merck, Imcyse, and Novartis, and the participation in sponsored speaker’s bureau from Merck, Novartis, and Roche; Pascual Torres has received congress expenses from Sanofi; José Vicente Hervás has received travel, congress expenses, and speaker fees from Biogen, Genzyme, Merck, Roche, and Novartis; Joan Valls has no conflict of interest to declare; Luis Brieva has received honoraria, travel expenses, speaker fees, and advisory fees from Bayer, Celgene, Biogen, Genzyme, Merck, Novartis, Roche, Allmiral, and Teva. jcm-11-02509-t001_Table 1 Table 1 Demographics, clinical characteristics, DMT, and COVID-19 immune status. Baseline Characteristics N = 259 Age, mean (SD) 44.3 (10.3) Female sex, n (%) 171 (66.0) Pregnant, n (%) 0 (0) EDSS, mean (SD) 2.00 (2.19) Current smoker, n (%) 58 (23.7) Former smoker, n (%) 49 (20) Never smoker, n (%) 138 (56.3) Hypertension, n (%) 31 (19.6) Diabetes, n (%) 8 (5.93) Obesity, n (%) 24 (15.9) MS type, n (%) RRMS 223 (86.1) PPMS 15 (5.79) SPMS 21 (8.1) No relapse in previous year 221 (85.3) Steroids in previous 3 months, n (%) 13 (5.2) Platform DMT, n (%) Interferon 36 (13.9) Glatiramer 15 (5.79) Teriflunomide 33 (12.7) Dimethyl Fumarate 49 (18.9) Second-line DMT, n (%) Fingolimod 18 (6.95) Natalizumab 24 (9.27) Rituximab 13 (5.02) Ocrelizumab 41 (15.8) Cladribine 17 (6.56) Alemtuzumab 13 (5.2) Lymphopenia, n (%) 135 (52.1)  ≤200 (Grade 4) 22 (16.3)  201–500 (Grade 3) 19 (14.1)  501–800 (Grade 2) 34 (25.2)  801–1000 (Grade 1) 60 (44.4) Sign and symptoms of COVID19 n (%) 14 (5.43) DMT: Disease-modifying treatment; EDSS: Expanded Disability Status Scale; MS: Multiple sclerosis; PPMS: progressive multiple sclerosis; RRMS: relapsing-remitting multiple sclerosis; SPMS: secondary progressive multiple sclerosis. jcm-11-02509-t002_Table 2 Table 2 Demographics, clinical characteristics, DMT, and COVID-19 immune status. MS Negative for SARS-CoV-2 IgG/IgM/IgA (N = 206) MS Positive for SARS-CoV-2 IgG/IgM/IgA (N = 53) p Age, median (IQR) 44.0 (37.0–50.0) 47.0 (41.0–53.0) 0.076 Female sex, n (%) 133 (64.6) 38 (71.7) 0.41 EDSS, median (IQR) 1.50 (0.0–3.4) 1.00 (0.0–2.5) 0.053 Current smoker, n (%) 49 (25.3) 9 (17.6) 0.52 MS type, n (%) 0.269 RRMS 177(85.9) 46 (86.8) PPMS 14 (6.8) 1 (1.89) SPMS 15 (7.28) 6 (11.3) Steroids previous 3 months, n (%) 10 (5.08) 3 (5.66) 1 Hypertension, n (%) 23(18.7) 8(22.9) 0.76 Diabetes, n (%) 6 (5.6) 2 (6.9) 0.68 Obesity, n (%%) 18 (15.3) 6 (18.2) 0.89 Lymphopenia, n (%) 105 (51) 30 (56.6) 0.56 Platform DMT, n (%) 103 (50) 30 (56.6) 0.48 Interferon 22 (10.7) 14 (26.4) 0.006 Glatiramer 13 (6.31) 2 (3.77) 0.77 Teriflunomide 28 (13.6) 5 (9.43) 0.56 Dimethyl Fumarate 40 (19.4) 9 (17) 0.83 Second-line DMT, n (%) 103 (50) 23 (43.4) 0.48 Fingolimod 15 (7.28) 3 (5.66) 1 Natalizumab 20 (9.7) 4 (7.55) 0.79 Rituximab 11 (5.34) 2 (3.77) 1 Ocrelizumab 34 (16.5) 7 (13.2) 0.65 Cladribine 14 (6.8) 3 (5.6) 1 Alemtuzumab 9 (4.37) 4 (7.75) 0.31 Lymphopenia, n (%) 100 (48.5) 25 (47.2) 0.98 DMT: Disease-modifying treatment; EDSS: Expanded Disability Status Scale; IQR: interquartile range; MS: Multiple sclerosis. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092432 jcm-11-02432 Article Helicobacter pylori Infection in a Pediatric Population from Romania: Risk Factors, Clinical and Endoscopic Features and Treatment Compliance Rosu Oana-Maria 12 Gimiga Nicoleta 23* https://orcid.org/0000-0002-1394-8648 Stefanescu Gabriela 34* Anton Carmen 34 Paduraru Gabriela 23 Tataranu Elena 5 Balan Gheorghe G. 34 Diaconescu Smaranda 6 Durazzo Marilena Academic Editor 1 Doctoral School, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 38 Gheorghe Marinescu Str., 540139 Targu Mures, Romania; oana7772@yahoo.com 2 Clinical Department of Pediatric Gastroenterology, “St. Mary” Emergency Children’s Hospital, 700309 Iasi, Romania; gabyspulber@gmail.com 3 Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 16 Universitatii Str., 700115 Iasi, Romania; carmen_ro2008@yahoo.com (C.A.); balan.gheo@yahoo.com (G.G.B.) 4 Gastroenterology and Hepatology Institute, “St. Spiridon” Emergency Hospital, 1-3 Independetei Str., 700115 Iasi, Romania 5 Clinical Department of Pediatrics, Sf. Ioan cel Nou, Emergency Hospital, 720224 Suceava, Romania; elena8025p@yahoo.com 6 Faculty of Medicine, “Titu Maiorescu” University of Medicine, 67A Gheorghe Petrascu Str., 031593 Bucharest, Romania; turti23@yahoo.com * Correspondence: chiti_nico@yahoo.com (N.G.); gabriela.stefanescu@gmail.com (G.S.) 26 4 2022 5 2022 11 9 243231 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/). Background and Objectives: The aim of this study was to investigate the association between H. pylori positivity with specific symptoms, risk factors and endoscopic patterns among the pediatric population in northeastern Romania. Materials and Methods: A prospective study was performed in 18 months on 185 children aged 6–18 years with an indication for upper digestive endoscopy. Demographic, anamnestic, symptomatic, endoscopic and histologic data were recorded. Results: Of 116 H. pylori-positive children, the most affected group was 15–17 years. Most (65.5%) of them were girls, with a significant association (p < 0.001). The majority (66.4%) lived in a rural area and 47.4% of children had an unsafe source of water and lived in overcrowded houses with no basic sanitary comfort. The most frequent symptom was epigastric pain (56.9%), and the main endoscopic appearance was nodularity and hyperemia. Patients diagnosed with H. pylori started triple-therapy treatment for 14 days. Only 13.8% stopped the treatment, mainly because of a misunderstanding of the treatment protocol (9.5%). Conclusions: Romanian teen girls living in rural areas are at high risk for H. pylori infection. Epigastric pain and endoscopic nodularity of the gastric mucosa were associated with the infection. As the resistance of the bacteria is unknown in our country, future research is needed in order to improve the eradication rate. Helicobacter pylori children endoscopic treatment compliance ==== Body pmc1. Introduction Helicobacter pylori infection is one of the most prevalent in the world. The infection occurs during childhood and can be carried throughout life if left untreated. Epidemiologically, H. pylori infection can be characterized by a linear increase with age in Western industrialized countries and an increased number of infected children in developing countries [1]. The Global Health Epidemiology Research Group conducted a 198-article meta-analysis, concluding that H. pylori infection among children and adolescents globally still has a fairly high prevalence [2]. The interest in H. pylori infection among the pediatric population has been growing in recent years, and gastric disorders due to infectious disease have led to studies in this direction. This association was confirmed for children in several studies, but these studies included a limited number of cases. As shown by many epidemiological studies, the epidemiology of H. pylori in children is constantly changing. Gastric infection with H. pylori is influenced by factors of the host’s gastric mucosa, environmental factors and bacterial virulence [3]. In Romania, there is a lack of studies on the prevalence of H. pylori infection in children. However, there are a few research studies on some regional areas. In northwestern Romania, the prevalence of dyspepsia among children rises to 40%, according to a study from 2002 conducted on 267 patients with an age range of 5 to 18 years old [4]. A more recent study from 2018, which enrolled 7100 pediatric patients from Cluj-Napoca, Romania, also reported a 25% prevalence [5]. In our country, there are important risk factors, mainly in rural areas, namely, the type of housing that influences the sanitation conditions, low socioeconomic status, a large number of family members, sleeping in common beds and the deficiencies of the water supply network. At the same time, only 29.9% of children in Romania are fed exclusively with breast milk in the first months of life, which could be an additional risk factor, if we take into consideration its possible protective factor against H. pylori [6]. According to the European Society of Pediatric Gastroenterology and Nutrition (ESPGHAN)/North American Society of Pediatric Gastroenterology and Nutrition (NASPGHAN) guidelines, H. pylori diagnostics in the pediatric population require a positive culture or a histopathologic finding of H. pylori gastritis, accompanied by one more examination, such as a urease rapid test. In addition, the treatment of pediatric H. pylori infection is based on updated protocols of the ESPGHAN/NASPGHAN guidelines, revised in 2016. The first-line treatment should be administered according to the antimicrobial susceptibility of the H. pylori strain, and if not determined, the guidelines recommend adapting the treatment according to the regional antimicrobial resistance trend or the eradication prescription which is more efficient locally. Clarithromycin resistance is higher than 15%, so triple therapy should not include this antibiotic. In addition, sequential therapy should be avoided in children [7]. Eradication control must be performed preferably by a non-invasive test (urea breath test in children over 6 years or the detection of faecal antigen by ELISA method with monoclonal antibodies) 4–8 weeks after the end of the antibacterial treatment [7,8,9]. The leading causes of treatment failure are side effects, reduced compliance and antibiotic resistance. The standard triple therapy based on clarithromycin, previously recommended [10], is widely prescribed in our country, especially in the primary care network. Alternative schemes are recommended only in tertiary centers. Romania holds a leading position in the European Union in terms of over-the-counter use of antibiotics, estimated at 30% [11]. The widespread use of antibiotics (clarithromycin for respiratory infections) in the general population has led to an increase in the rate of antibiotic resistance at rates between 49.2% in Spain and 0.8% in the Netherlands [12]. In Romania, there are currently no studies on antibiotic resistance of H. pylori in children. This study proposes an investigation of the association between H. pylori positivity with symptoms, risk factors and endoscopic patterns among the pediatric population in northeastern Romania. In addition, we hereby present an assessment of the socioeconomic and demographic factors influencing infection and treatment adherence. 2. Materials and Methods A prospective study consisting of 185 patients, aged 6–17 years, admitted to the Pediatric Gastroenterology Unit of St. Mary Children’s Hospital, Jassy, Romania, who underwent upper digestive endoscopy due to various gastrointestinal complaints was conducted between February 2019 and July 2020. The presence of H. pylori infection was diagnosed by histopathology and rapid urease testing. Patients who were aged less than 6 years or aged over 18 years or who received a proton pump inhibitor, antibiotics or antibacterial therapy four weeks before endoscopy, and patients with other conditions such as ulcerative colitis, Crohn’s disease or celiac disease, were excluded. The study was approved by decision no. 4363/20 February 2019 of the Research and Ethics committee of ”St. Mary” Hospital. All patients included in the study agreed to participate by approval and signature of informed consent by parents or legal guardians and underwent upper digestive endoscopy with gastric biopsy for H. pylori testing. After endoscopy, the H. pylori-positive patients were treated according to ESPGHAN guidelines, with doses depending on bodyweight. For patients weighing 15–24 kg, PPI 40 mg, amoxicillin 500 mg and metronidazole 500 mg divided in 2 doses was prescribed. For patients weighing 25–34 kg, PPI was prescribed 30 mg twice daily, along with amoxicillin 500 mg twice a day and metronidazole 500 mg in the morning and 250 mg in the evening. For pediatric patients over 35 kg, the following was recommended: 40 mg of PPI, 1000 mg of amoxicillin twice daily and 500 mg of metronidazole twice daily. A simple closed-ended questionnaire was completed by telephone, and personal data was protected to maintain the patient’s anonymity; it was completed after the completion of the treatment. The purpose was to collect information about the pediatric patient participating in the study, the type of home toilet, the sources of drinking water from home, the period of breastfeeding, the number of people in their household, family history of upper digestive pathology, history of antibiotic therapy and side effects of the treatment. All children and their families were also questioned about gastrointestinal symptoms or complaints: epigastric pain, recurrent abdominal pain and vomiting. In addition, the study participants were asked about the recommended treatment schedule, if it was administered correctly and completely, and if not, what the causes that led to the discontinuation of treatment were. Statistical analysis: all data was processed (coding, entry, validation and analysis) with IBM SPSS Statistics for Windows, v20.0 (Armonk, NY, USA). Depending on the type of variable, we used Pearson’s chi-squared test and calculated Lambda (for association or asymmetry). Categorical variables are expressed as numbers and/or percentages. All statistical tests are 2-tailed and have a reported p-value < 0.05, which was considered statistically significant for the study, as in all former studies where p-values less than 0.05 or near 0.05 were considered of statistical significance. 3. Results 3.1. Demographic Characteristics of the Study Population The study included 185 children aged 6–17 years admitted in the gastroenterology department for various gastrointestinal complaints who underwent upper digestive endoscopy with gastric biopsies for H. pylori. The children were divided into groups by age, respectively: 6–9 years range, 10–14 years range and 15–17 years range. The mean age of the children was 13.12 years with a standard deviation of 3.27 years. The 15–17 years age group included most children, followed by the 10–14 age group. The majority, 126 (68.10%), were girls and only 59 (31.90%) were boys. Most children, 116 (62.70)%, were living in a rural area, and only 69 (37.30%) were living in an urban area. The children in the sample were breastfed for more than 6 months at a rate of 61.62% (114 children). Table 1 summarizes the study population characteristics. Most of the H. pylori-positive diagnoses in our study were found amongst children older than 15 years old, from rural areas., The prevalence of the H. pylori infection was found to progressively rise with age. (Figure 1). 3.2. Risk Factors in Pediatric Helicobacter Pylori Infection Risk factors are important to correlate with risks of infection. As such, we investigated some of the possible ambient and family factors that could enhance the development of H. pylori infection. These factors regard hygiene routine and sanitary conditions at home, number of people inhabiting the house, family history of dispeptic disorders, breastfeeding and pets present in the household. Nearly half (47.4%) of infected children had improper or unsafe water sources and an outdoor toilet, and 14% had overcrowded families. Infected children were breastfeed less than 6 months at a rate of 42.2%. Only 24.9% of the sample owned pets, with no statistical significance in the study group. Family history of gastric pathology was identified in only 14.7% of cases. Other associatted risk factors may be previous respiratory infections; 77.5% had a history of 1–2 infections/year (p < 0.001). The history of antibiotics previously received for various other pathologies in the case of enrolled patients was extremely varied in preparations and combinations alike. The statistical analysis showed that the main category of patients was treated with clarithromycin and amoxicillin and clavulanic acid (41.3%), as well as clarithromycin monotherapy (32.7%) (Table 2). 3.3. Clinical Characteristics and Endoscopic Patterns Gastrointestinal complaints were reported by 56.8% of patients with epigastric pain, followed by recurrent abdominal pain (14.6%) and subsequently by the concomitant presence of epigastric pain and vomiting (12.9%). Endoscopic aspects were mainly hyperemic lesions (37.8%) and nodular lesions (20.5%) followed by the association between nodular and hyperemic lesions (19.4%) (Table 3). The Sydney System is used internationally to classify chronic gastritis. This system can provide information on the density, activity, chronic inflammation, atrophy and intestinal metaplasia of H. pylori. The diagnostic criteria include confirmed gastritis according to the updated Sydney classification and at least one positive test, such as RUT, molecular tests where available, polymerase chain reaction (PCR) or in situ fluorescent hybridization [7]. The Sydney System semi-quantitatively grades the density of H. pylori infection on a scoale from zero to three (none, mild, moderate and marked). On the histological section, H. pylori can be recognized as a short, curved or spiral bacillus on the epithelial surface or in the mucus layer. We observed in our study that there is a relationship between chronic inflammation and H. pylori (p = 0.002) (Table 4). 3.4. Treatment Regimens and Compliance Most of the Helicobacter pylori-positive patients were treated with two different regimens: 1—amoxicillin, clarithromycin and a selected proton pump inhibitor (PPI) for a period of 14 days (42.2%) or 2—amoxicillin, metronidazole and a PPI for 14 days (53.4%). Only 13.8% of patients stopped the treatment, and the main cause that led to the discontinuation of treatment was the misunderstanding of the treatment protocol (9.5%) or the presence of side effects (4.3%). Epigastric pain was the persisting symptom in 27.5% of patients, and side effects such as nausea, vomiting or diarrhea were present in 29.3% of cases, with no differences in treatment regimen. (Table 5). The method of determining eradication was used according to ESPGHAN guidelines. At least four weeks after completing triple-H. pylori infection eradication therapy, a non-invasive test such as a faecal antigen test was performed. Of all the 116 positive patients, only 43 of them participated in the follow-up, with a negative faecal antigen test (37%). 4. Discussion Helicobacter pylori (H. pylori) is a gram-negative type bacterium, currently known as the source of the most common infection within all age groups and is a challenging health issue [13,14,15,16]. Helicobacter pylori is often transmitted in childhood from saliva by person-to-person interaction [17]. As such, intra-familial routines have the most important role. The spread of the bacteria can also be caused by contamination of food or drinking water. Increased prevalence of infection can be caused by untreated water, overcrowded housing or poor hygiene [10,18]. According to literature and current studies, infection prevalence in Sweden was 13.6% in children aged 18 to 24 months, while in Ireland and Germany the rates of H. pylori infection were 8.6% and 2.4%, respectively. Bulgaria is the country with the most H. pylori-infected children aged between 1 and 17 years, while the lowest infection rate was reported in the Netherlands [19]. According to our current knowledge, the present study is the first to investigate pediatric infection with H. pylori by endoscopic aspects, treatment compliance and risk factors. Colonization with H. pylori starts early in life [20]. As age increases, so does exposure to various sources of infection, increasing the rate of infection. This could be an explanation for the higher rate of infection among schooling children. In our study, there was a progressive increase in the prevalence of H. pylori. The infection rate may be higher for children who attend poorly sanitized schools, who have an outdoor toilet or who do not have clean drinking water [21]. In Romania, the chances of transmitting the infection from person to person increase because there are many overcrowded schools, and the transmission can take place at home too, as long as there is an infected family member [21]. In our study, the prevalence rate was 62.7% among symptomatic children. Corojan et al. summarize studies from the literature on the prevalence of H. pylori infection among children, which has increased since 2003 when it was 20%, reaching 25% in 2018 in northwestern Romania. However, the main measure was the result of serological tests for H. pylori antibodies and not gastric biopsies. The authors also found that over 40% of adult patients in Romania have or had an H. pylori infection. However, similar to the other authors, the infection rate among the pediatric population was found to be constantly increasing [22]. Non-invasive testing for the initial diagnosis of H. pylori in children is not recommended. In addition, the eradication scheme is not recommended to be used after such a test. Our study used diagnostic methods among those recommended by international guidelines [7]. To rule out possible false-negative results, we used previous use of PPIs and antibiotics as exclusion criteria. Prior use of PPIs may give false-negative results of invasive diagnostic tests for H. pylori infection due to suppression of replication. In addition, previous use of antibiotics can suppress the growth of bacteria. It can lead to false-negative results in all recommended diagnostic tests, except serology, which is not recommended as a diagnostic method in children. Biopsies were taken according to the recommendations of current guidelines. These recommendations suggest that at least six biopsies are required. Of these, two from the antrum and two from the corpus should be taken for histopathology. A biopsy of the antrum and one of the corpus are harvested if bacterial culture is available. At least one biopsy is collected for additional diagnostic tests such as RUT [7]. In addition, we took biopsies from the areas with the most suggestive changes in the gastric mucosa. All these biopsies with negative results on histopathology and RUT, to which we add the exclusion criteria, make false-negative results unlikely. Skrebinska et al. conducted a study based on the diagnosis of H. pylori infection on serology and histopathology. The conclusion they reached is that the discrepancy was due to false positive serology rather than false negative histology [23]. The molecular diagnosis at the time of this study was not possible in our unit. Our study confirms a difference of statistical significance in the incidence of H. pylori infection in boys vs. girls (65.5% vs. 34.5%, p < 0.001). The explanation for this difference may be the fact that girls may be more thoughtful about the symptoms they feel and may have a higher predisposition to digestive symptoms, thus leading to greater addressability by medical services. However, there was a slightly higher infection rate in boys (67.7%) compared to girls (60.3%), with no statistically significant difference. In contrast, the meta-analysis by Martel and Parsonnet concluded that there was no significant relationship between sex and the incidence of H. pylori infection [24]. According to the ESPGHAN/NASPGHAN guidelines, the acquisition of gastric infection with H. pylori takes place around the age of 10 years, and most of the patients have fairly long asymptomatic periods [7]. Domsa et al. have conducted studies that have seen an increase in the frequency of infection as the age of the patients studied increases [5]. The Global Health Epidemiology Research Group found that the prevalence of H. pylori infection was higher in older children than in younger children, with the highest percentage being in the 13–18 years age group (41.6%) [2]. Similarly, in our study, the highest incidence was in the 15–17 years group. Compared to developed countries, the risk factors for H. pylori infection are higher in developing countries. These risk factors include poor socio-economic conditions, poor hygiene, overcrowding families and living with an infected family member [25]. Similarly, we found in our study that out of total number of patients, 14.1% had overcrowded housing and 43.2% consumed fountain water. Of the 116 H. pylori-positive children, 14.7% had overcrowded housing and 47.4% of them consumed well water, due to the high addressability of patients from rural areas (62.7% of the total number of study participants). Recent studies in the Japanese literature show a link between H. pylori positivity and daily contact with dogs. Other studies suggest that they found the same strains in two dogs and their owner [26]. In the studied population, the owners of pets consisted of 21.6% of the sample, of which 8.1% had dogs, a finding which was not statistically significant. After researching several studies, Soltani et al. found a significant correlation between H. pylori infection and breastfeeding. The results are inconclusive, as some studies showed a positive correlation between breastfeeding and risk of infection while other studies revealed that breastfeeding could be a protective factor against H. pylori infection. In our study, positive and negative H. pylori children were all breastfed for more than 6 months, therefore, large and long-term clinical observations are further needed for a strong conclusion regarding this correlation [27]. It is recommended that H. pylori infection be investigated among vulnerable groups such as family members inhabiting the same residence as positive H. pylori patients, persons with a family history of dyspeptic disease or a disease associated with H. pylori infection (e.g., active duodenal ulcer). The guidelines and protocols agree on the fact that, once H. pylori infection is identified, therapeutic intervention is mandatory unless there are other medical reasons for not doing so [28]. Of the 185 patients studied, only 31 (16.8%) reported a family history of gastric pathology, of which 17 (14.7%) were related to positive H. pylori patients and 14 (20.3%) were related to negative H. pylori patients. The diagnoses declared by the family members were: a case of gastric cancer in the father of a patient, 23 cases of peptic ulcer disease, 17 of which were H. pylori-positive and 7 cases of chronic gastritis of which five were H. pylori-positive. There was no significant statistical correlation between H. pylori infection and family history of upper digestive pathology (p = 0.32). Few parents reported the history and there is no possibility to verify the accuracy of the information received. In Romania, treatment regimens for respiratory infections in children widely include clarithromycin [29]. Thus, a trend in the history of antibiotic treatment including clarithromycin monotherapy or clarithromycin with amoxicillin and clavulanic acid can be observed in our study, too. The clinical manifestations are non-specific, and some may indicate the presence of complications. In the study by Correa Silva et al., there was no positive correlation between gastrointestinal symptoms, pain, pain features and H. pylori infection but there were some associations with nausea [30]. In addition, in the meta-analysis by Spee et al., no correlation was found between clinical features and infection, other than epigastric pain [31]. Other symptoms such as persistent vomiting, gastrointestinal bleeding, iron deficiency anaemia (ADI) of unspecified cause and malnutrition may be caused by comorbidities or complications of the infection and require further investigations in order to eliminate confusion factors and conduct proper therapy [32]. In Kirdy et al.’s study, the main indication for upper gastrointestinal endoscopy investigation was abdominal pain. They found that there was a statistically significant association between epigastric pain and H. pylori infection [33], which was also reported by Yang et al. and Ng et al. [34,35]. Consistent with these research studies, we found that the main symptom was epigastric pain, both in the H. pylori-positive group (56.9%) and in H. pylori-negative patients (56.5%). Moreover, compared to H. pylori-negative patients, the patients with H. pylori infection had associated vomiting (13.8%) or had recurrent abdominal pain (15.5%). Nodular endoscopic appearance is one of the signs of H. pylori-associated gastritis and may be associated with a severe gastritis in children [36]. Tatevik et al. found in their data that, in the H. pylori-positive group, the most frequent endoscopic lesions were the erosive ones, and the nodular lesions were found exclusively within this group [37]. A report by Toyoshima et al. associated H. pylori infection with the nodular appearance of the cardia, considering this association a more accurate in diagnosis. In addition, the sensitivity of the nodular endoscopic aspect in the cardia was significantly higher than in the antral area. This report concluded that cardia nodularity may be a predictor of H. pylori infection. This nodular aspect varied from 32.9% to 85% in children with H. pyori, an aspect previously considered to be specific [38]. Domsa et al. found in a recent 5-year retrospective study from northwestern Romania, performed on 82 H. pylori-positive children out of 248 patients enrolled, that the endoscopic features such as hyperemia, nodularity pattern and edema were suggestive of pediatric H. pylori infection [39]. Regarding the endoscopic lesions, our study revealed that nodular and hyperemic lesions (31.0%) and nodular aspects (22.4%) were the main macroscopic patterns observed in patients with H. pylori, similar to previous studies. Botija et al. analysed the role of adherence in case of treatment failure in paediatric patients receiving antimicrobial susceptibility treatment. They considered it necessary for patients and their families to be properly informed that treatment adherence could play an important role in improving the success rate of eradication [40]. In our study, 9.5% of the patients stopped the treatment mainly because they misunderstood the treatment protocol, and 4.3% had side effects. As a cause of treatment discontinuation, its cost has not been reported, because in Romania, most children’s treatments are free. Instead, some parents said that they did not understand that the treatment was prescribed for 14 days consecutively, or they forgot to administer a dose on some days. In H. pylori infection in adults, experts in Europe, Canada and U.S.A. have developed new recommendations for treatment of H. pylori infections that promote quadruple therapy containing bismuth as a first-line empirical therapy. As such, combination capsules containing bismuth, tetracycline and metronidazole have been developed that substantially simplify the treatment with good efficacy and safety. This type of medication is not administered to children, and in Romania there is no such option for adults [41]. Vomiting, nausea, diarrhea, constipation, heartburn, stomach cramps, decreased appetite, headache and dry mouth have been reported as side effects of the therapy. Okuda et al. additionally reported abnormal sensation in the tongue and mouth and tongue irritation [42]. In our study, 4.3% of the patients stopped the treatment because they had nausea or forgot to take the PPI in the morning, so they had severe stomach pain after taking the antibiotics. One of the major risk factors for failure to eradicate gastric H. pylori infection may be poor adherence. Other risk factors that can be considered are high gastric acidity, high bacterial load and lack of sensitivity of the specific H. pylori strain to antibiotics. In addition, the lack of awareness of providers of local and national resistance models for specific antibiotics can be considered a risk factor for failure to eradicate the infection [43]. Of the positive patients, 29.3% had persistent symptoms despite treatment. Among the most pronounced symptoms were pain in the epigastric area, diffuse abdominal pain or vomiting. Although these symptoms were present befoare diagnosis, they persisted even after the end of treatment. As such, we can presume that resistant H. pylori strains may be the cause of this phenomenon. In Romania, only a few hospitals have specialized pediatric gastroenterologists and even fewer pediatric endoscopists. Consequently, major difficulties in diagnosing and treating H. pylori infection are frequently encountered. The limitations of this study are mainly the low number of participants within a single geographical area—northeastern Romania—and that it investigates a limited number of cases, as it is a single-centre study. The patient enrolment was conducted partially during the COVID-19 pandemic when the number of upper digestive endoscopies performed routinely or for mild digestive symptoms was limited. In addition, the study was limited to the evaluation of patients with digestive symptoms who presented in a tertiary unit; the general pediatric population was sampled. According to present literature, in Romania, there is a high prevalence of H. pylori infection and related disorders [19] and there are limited research studies published on this topic and there is a lack of epidemiological data available. As far as our knowledge goes, this is the first study describing risk factors and treatment compliance in Romanian children. In addition, due to the COVID-19 pandemic onset during the study, we faced a limitation of the possibility to test antimicrobial resistance. Our hospital was equipped with high-performance PCR equipment but it has been used for a long time only for SARS-CoV-2 testing, and we have been able to use it for non-COVID testing several months after the end of this study period. Prospective country-wide studies are needed, since Romania is a leading country in empirical antibiotic consumption, and antibiotic resistance of H. pylori in our country is still unknown. Our ongoing research includes eradication rates and antibiotic resistance. 5. Conclusions Pediatric H. pylori infection has particular epidemiology, clinical features, associated disease, diagnosis and treatment strategies. Romania, with the highest incidence of rural poverty among EU countries, has particular risk factors for pediatric H. pylori infection such as living in rural areas, improper sanitary facilities in schools and homes and overcrowded housing. The lack of specialized pediatric gastroenterologists and endoscopists lead to major difficulties in diagnosis and treatment of this infection. Even if treatment compliance is satisfactory, antibiotic resistance may be a leading cause for eradication failure, which is not yet well investigated in Romanian children and which is the subject of our ongoing research. Author Contributions Conceptualization, O.-M.R. and S.D.; methodology, N.G. and G.S.; resources, G.P. and E.T.; writing—original draft preparation, O.-M.R. and G.G.B.; writing—review and editing, O.-M.R. and C.A.; visualization, E.T. and C.A.; supervision, S.D.; project administration, N.G., S.D. and G.S. 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 “ST. MARY” EMERGENCY CHILDREN’S HOSPITAL (no. 4363/20 February 2019). 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 Age distribution of H. pylori-positive children. jcm-11-02432-t001_Table 1 Table 1 Study population characteristics. Study Population n (%) H. pylori + n (%) H. pylori − n (%) p-Value * Total number 185 (100%) 116 (62.7%) 69 (37.3%) Age range (years) 6–17 years 6–17 years 6–17 years 0.79 Mean ± SD M = 13.12; SD = 3.27 M = 13.10, SD = 3.33 M = 13.15, SD = 3.19 Age groups years, n (%)   6–9 32 (17.29%) 21 (18.1%) 11 (15.9%) 0.74   10–14 71 (38.39%) 41 (35.3%) 30 (43.5%) 0.17   15–17 82 (44.32%) 54 (46.6%) 28 (40.6%) 0.85 Sex, n (%) <0.001   Female 126 (68.10%) 76 (65.5%) 50 (72.5%) 0.02   Male 59 (31.90%) 40 (34.5%) 19 (27.5%) 0.09 Place of residence, n (%) <0.001   Urban 69 (37.30%) 39 (33.6%) 30 (43.5%) 0.33   Rural 116 (62.70%) 77 (66.4%) 39 (56.5%) 0.001 Breastfeeding <0.001   >6 months 71 (38.38%) 67 (57.8%) 47 (68.1%) 0.07   <6 months 114 (61.62%) 49 (42.2%) 22 (31.9%) 0.02 * Between H. pylori-positive and H. pylori-negative groups. jcm-11-02432-t002_Table 2 Table 2 Risk factors associated with H. pylori infection. Study Population n (%) H. pylori + n (%) H. pylori − n (%) p-Value * Persons living in a home <0.001   1 pers/room 51 (27.6%) 26 (22.4%) 25 (36.2%) 1.00   2 pers/room 108 (58.4%) 73 (62.9%) 35 (50.7%) <0.001   >3 pers/room 26 (14.1%) 17 (14.7%) 9 (13%) 0.16 Type of drinking water 0.30   Bottled water 55 (29.7%) 33 (28.4%) 22 (31.9%) 0.17   Sink water 50 (27.0%) 28 (24.1%) 22 (31.9%) 0.48   Fountain water 80 (43.2%) 55 (47.4%) 25 (36.2%) 0.001 Pets 0.18   Cat 20 (10.8%) 14 (12.1%) 6 (8.7%) 0.11   Dog 15 (8.1%) 11 (9.5%) 4 (5.8%) 0.11   Other 5 (2.7%) 5 (4.3%) 0 (0%) 0.06   None 145 (78.4%) 86 (74.1%) 59 (85.5%) 0.03 Respiratory infection 0.57   1–2/year 141 (76.2%) 90 (77.5%) 51 (73.9%) <0.001   3–4/year 44 (23.8%) 26 (22.4%) 18 (26.1%) 0.29   >5/year 0 (0%) 0 (0%) 0 (0%) - History of antibiotic therapy 0.34   CLR 67 (36.2%) 38 (32.7%) 29 (42.0%) 0.32   AMX 1 (0.5%) 0 (0%) 1 (1.45%) -   AMC 14 (7.6%) 8 (6.9%) 6 (8.7%) -   Other 2 (1.08%) 2 (1.72%) 0 (0%) 0.50   Can’t remember 12 (6.5%) 7 (6.03%) 5 (7.2%) 0.77   CLR + AMX 5 (2.7%) 2 (1.72%) 3 (4.3%) 0.50   CLR + AMC 67 (36.2%) 48 (41.3%) 19 (27.5%) 0.001   CLR + MTZ 2 (1.1%) 2 (1.7%) 0 (0%) 0.50   CLR + OTHER 2 (1.1%) 2 (1.7%) 0 (0%) 0.50   AMC + OTHER 1 (0.5%) 1 (0.9%) 0 (0%) -   CLR + AMX + AMC 3 (1.62%) 2 (1.72%) 1 (1.4%) 1.00   CLR + AMX + OTHER 8 (4.3%) 3 (2.6%) 5 (7.2%) 0.72   CLR + AMX + AMC + MTZ 1 (0.5%) 1 (0.9%) 0 (0%) - Familial history of upper digestive pathology 0.32   Yes 31 (16.8%) 17 (14.7%) 14 (20.3%) 0.72   No 154 (83.2%) 99 (85.3%) 55 (79.7%) <0.001 AMX: amoxicillin; AMC: amoxicillin and clavulanic acid; CLR: clarithromycin; MTZ: metronidazole. * Between H. pylori-positive and H. pylori-negative groups. jcm-11-02432-t003_Table 3 Table 3 Clinical presentation symptoms and endoscopic patterns. Study Population n (%) H. pylori + n (%) H. pylori − n (%) p-Value * Clinic p = 0.37   Epigastric pain 105 (56.8%) 66 (56.9%) 39 (56.5%) 0.008   Epigastric + recurrent abdominal pain 3 (1.6%) 2 (1.7%) 1 (1.4%) 0.56   Epigastric pain + vomiting 10 (5.4%) 16 (13.8%) 8 (11.6%) 0.10   Recurrent abdominal pain 27 (14.6%) 18 (15.5%) 9 (13.0%) 0.08   Recurrent abdominal pain + vomiting 24 (12.9%) 3 (2.6%) 7 (10.1%) 0.20   Vomiting 3 (1.6%) 2 (1.7%) 1 (1.4%) 0.56   Refractory anemia 4 (2.2%) 4 (3.4%) 0 (0%) -   Other symptoms 9 (4.9%) 5 (4.3%) 4 (5.8%) 0.73 Endoscopic pattern <0.001   Nodular 38 (20.5%) 26 (22.4%) 12 (17.4%) 0.02   Nodular + hyperemic 36 (19.4%) 36 (31.0%) -   Nodular + hyperemic + snakeskin 2 (1.1%) 1 (0.9%) 1 (1.4%) 1.00   Nodular + erosive 1 (0.5%) 1 (0.9%) 0 (0%) -   Nodular + snakeskin 1 (0.5%) 0 (0%) 1 (1.4%) -   Erosive 6 (3.2%) 3 (2.6%) 3 (4.3%) -   Hyperemic 70 (37.8%) 25 (21.6%) 45 (65.2%) 1.00   Erosive + hyperemic 1 (0.5%) 0 (0%) 1 (1.4%) 0.01   Hyperemic + snakeskin 4 (2.1%) 2 (1,72%) 2 (2.9%) 1.00   Atrophic 26 (14.1%) 22 (19%) 4 (5.8%) 0.001 * Between H. pylori-positive and H. pylori-negative groups. jcm-11-02432-t004_Table 4 Table 4 The relationship between chronic inflammation and H. pylori density. Chronic Inflammation 1 (n = 116) p-Value Mild (n = 9) Moderate (n = 75) Severe (n = 32) H. pylori2, n (%) 0.002   Mild 5 (55.5%) 41 (54.7%) 9 (28.1%)   Moderate 1 (11.1%) 25 (33.3%) 17 (53.1%)   Severe 3 (33.4%) 9 (12.0%) 6 (18.8%) 1 Shows the intensity of lymphocytes and plasma cells in lamina propria according to the Sydney System. 2 Refers to the density of H. pylori in gastric mucosa. jcm-11-02432-t005_Table 5 Table 5 Eradication scheme and therapy compliance in H. pylori-positive patients. H. pylori + (n = 116) Treatment   PPI + AMX + CLR * 49 (42.2%)   PPI + AMX + MTZ 62 (53.4%)   PPI + AMC + MTZ 5 (4.3%) Duration of treatment   14 days 116 (100.0%) Discontinuation of treatment   Yes 16 (13.8%)   No 100 (86.2%) Cause   Treatment cost 0 (0%)   Side effects 5 (4.3%)   Misunderstanding of the treatment protocol 11 (9.5%) Side effects   Yes 34 (29.3%)   No 82 (70.6%) Persistence of symptoms   Yes 32 (27.5%)   No 84 (72.4%) * PPI: proton pomp inhibitor; AMX: amoxicillin; CLR: clarithromycin; MTZ: metronidazole. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Helaly G. El-Afandy N. Hassan A. Dowidar N. Sharaf S. Diagnostic value of housekeeping (glmM) gene expression in antral biopsies in comparison to rapid urease test and histological detection of Helicobacter pylori infection Egypt. J. Med. Microbiol. 2009 18 118 130 2. Yuan C. Adeloye D. Luk T.T. Huang L. He Y. Xu Y. Ye X. 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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/ijerph19095564 ijerph-19-05564 Review Inspiratory Muscle Training in Patients with Chronic Obstructive Pulmonary Disease (COPD) as Part of a Respiratory Rehabilitation Program Implementation of Mechanical Devices: A Systematic Review https://orcid.org/0000-0003-3641-1592 Vázquez-Gandullo Eva 1* Hidalgo-Molina Antonio 1 Montoro-Ballesteros Francisca 1 Morales-González María 2 Muñoz-Ramírez Isabel 1 https://orcid.org/0000-0002-2267-057X Arnedillo-Muñoz Aurelio 1* Clini Enrico M. Academic Editor 1 Pneumology, Allergology and Thoracic Surgery Department, University Hospital Puerta del Mar, 11009 Cádiz, Spain; antoniohmolina@hotmail.com (A.H.-M.); paquimb_88@hotmail.com (F.M.-B.); isabel.murami@gmail.com (I.M.-R.) 2 Pneumology Department, Hospital Punta Europa, 11207 Algeciras, Cádiz, Spain; moralesgonzalez.maria@gmail.com * Correspondence: evavgandullo@gmail.com (E.V.-G.); aurelioarnedillo@neumosur.net (A.A.-M.) 03 5 2022 5 2022 19 9 556407 3 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/). Chronic Obstructive Pulmonary Disease (COPD) is a complex and heterogeneous disease, with pulmonary and extrapulmonary manifestations, which leads to the need to personalize the assessment and treatment of these patients. The latest updates of national and international guidelines for the management of COPD reveal the importance of respiratory rehabilitation (RR) and its role in improving symptoms, quality of life, and psychosocial sphere of patients. Within RR, the inspiratory muscle training (IMT) has received special interest, showing benefits in maximum inspiratory pressure, perception of well-being, and health status in patients with chronic heart disease, respiratory diseases, and dyspnea during exercise. The aim of this review is to assess the efficacy of IMT in COPD patients through the use of inspiratory muscle training devices, compared with respiratory rehabilitation programs without inspiratory muscle training. In the last years, many mechanical devices focused on inspiratory muscle training have been developed, some of them, such as the AirOFit PRO™, PowerBreath®, or FeelBreathe®, have shown clear benefits. The active search for candidate patients to undergo the RR program with inspiratory muscle training using this type of device in COPD patients represents an advance in the treatment of this disease, with direct benefits on the quality of life of the patients. In this article, we review the available evidence on IMT in these patients and describe the different devices used for it. inspiratory muscle training inspiratory restriction device chronic obstructive pulmonary disease respiratory rehabilitation quality of life This research received no external funding. ==== Body pmc1. Introduction and Objectives Chronic Obstructive Pulmonary Disease (COPD) is a preventable and treatable disease, characterized by the presence of persistent respiratory symptoms and airflow obstruction [1]. Currently, this disease is one of the first causes of worldwide morbimortality [2]. The best known risk factor is exposure to tobacco smoke, although other factors such as environmental pollution or exposure to biomass combustion, together with individual predisposition, have also been correlated [1]. It is a complex and heterogeneous disease, with pulmonary and extrapulmonary manifestations, which leads to the need for a comprehensive approach to it [3,4]. The variability between individuals and within the same individual is ostensible, the cardinal symptom being dyspnea, frequently accompanied by cough and expectoration [5]. These symptoms are related not only to bronchial obstruction, but also to deconditioning, which leads to a decrease in physical activity. The air trapping and dynamic hyperinflation present in these patients are associated with an overload at the muscular level, which ends up conditioning a vicious circle that is difficult to break [6]. The guidelines for the management of COPD highlight the importance of respiratory rehabilitation (RR) and its role in improving symptoms, quality of life, and in the psychosocial sphere. Understanding this intervention is akin to a global evaluation of health status, followed by therapies adjusted to individual needs, including exercise training, education, and behavioral therapy [1,7,8]. RR is postulated as being the most cost-effective treatment strategy [8]. The implementation of respiratory rehabilitation in patients with COPD is widely accepted, demonstrating a reduction in hospital admissions and mortality in patients with frequent exacerbations [9]. Inspiratory muscle training (IMT) has received special interest as part of RR. In the 1970s and 1980s, Rochester [10] and Chen [11] highlighted inspiratory muscle weakness in COPD patients and the potential benefits of targeted training. Posterior studies have confirmed the efficacy of implementing IMT as part of a RR program in a certain profile of patients with COPD, showing improvements in maximum inspiratory pressure, perception of well-being, and health status in patients with chronic heart disease, other respiratory diseases, and dyspnea during exercise [12,13,14]. The aim of this review is to explain inspiratory muscle training, what devices can be used for its implementation, and the studies that support its use in COPD patients. We evaluated the efficacy of IMT in COPD patients with and without inspiratory muscle weakness in a RR program, and finally the usefulness of implementation of inspiratory restriction devices in domiciliary programs. 2. Material and Methods A systematic review has been carried out following PRISMA recommendations [15] for descriptive and systematic reviews. To carry out a structured search, in addition to following PRISMA recommendations, we raised the clinical question to be answered using the PICO (patient, intervention, comparison, outcome) methodology. According to this, we considered: patients with COPD; intervention was assessed as IMT to improve the quality of life, as well as peak inspiratory pressure and breathlessness on exertion; we compared inspiratory muscle training with mechanical devices included in a respiratory rehabilitation program versus a standard respiratory rehabilitation program; the results were measured as improvement in quality of life, as well as other variables like decreased dyspnea during exertion, meters walked in the 6MWT and improvement in inspiratory capacity. The authors assessed PubMed and EMBASE from 1 to 28 February, independently, carrying out the literature search in a stepwise manner, based on title and abstract The search engines were selected by the authors for accessibility and reproducibility. Finally, it was decided to continue with satisfactory results, although without overlooking the limitation that this search strategy entails. The following keywords were included in the search, alone or in combination: “inspiratory muscle training”, “inspiratory restriction device”, “chronic obstructive pulmonary disease”, “respiratory rehabilitation”, and “quality of life”. The main search yielded a result of 413 posts. Studies were included according to the following criteria: (a) systematic review, meta-analysis, and original articles; (b) published in the last 10 years; (c) efficacy of the inspiratory muscle devices; (d) studies evaluating the effects of inspiratory muscle training with a threshold device in stable or experiencing acute exacerbation COPD patients. Articles meeting exclusion criteria, e.g., do not specifically deal with IMT, low methodological quality, duplicate studies, lung diseases other than COPD, and studies carried out in active athletes in competition, were eliminated. Finally, 16 documents were considered eligible to evaluate IMT devices (Figure 1). To find other relevant articles, we also assessed the reference list of the collected papers. Two of the biases of the search strategy would be (1) it was carried out independently among the authors, and (2) the use of only two search engines. Nonetheless, the results allow us to answer the established PICO question. Table 1 shows the analyzed studies for the IMT devices. 3. Results Sixteen articles met the search criteria indicated above and were included. Of the initial 416 found by the search engine, 286 were excluded because they did not perform an IMT intervention, 35 studies did not have the required methodological quality, 23 were duplicate records and other reasons to exclude reports were: other non-COPD lung diseases, and studies in competitive athletes. 3.1. Profile of COPD Patients Who Are Candidates for IMT What Is a RR Program with IMT? COPD patients present a limitation in their activity due to peripheral muscle dysfunction, which, joined to functional alterations in ventilation and gas exchange, produce an increase in dyspnea and fatigue on exertion. As a consequence, they tend to have a sedentary lifestyle and decreased mobility, which further contributes to muscle dysfunction and physical deconditioning, increasing morbidity and mortality in these patients, compared to healthy adults [16]. Dyspnea is the main symptom in COPD patients, which origin may be multifactorial, involving physiological, psychosocial, and environmental spheres, which complicates its approach because the treatment of these symptoms may vary depending on the mechanism that originates it [16]. In addition, the intensity of the symptom does not correlate with the severity of the bronchial obstruction, although it is related to disease progression in cases of severe dyspnea and is usually associated with a decrease in the quality of life and survival at 5 years [17]. Within the pathophysiology related to dyspnea in COPD patients, it has been observed that during intense exercise, the respiratory muscles can consume up to 16% of oxygen, mainly for the skeletal muscles [18,19]. Therefore, if the respiratory muscles’ need for oxygen is very high, a competitive demand will be generated with respect to the active skeletal muscles, which could limit their oxygen supply. In the long run, this situation leads to an increase in the respiratory rate, with a decrease in expiratory time and air trapping, which implies a decrease in inspiratory capacity carrying to a greater sensation of dyspnea, regardless of the expiratory limitation at flow. This sustained situation favours respiratory muscle fatigue, which could alter the optimal ventilation required [6,20], and limit physical performance. McConnelly and Sharpe [21] in their research on healthy subjects concluded that respiratory muscles are resistant to fatigue in non-pathological conditions and at rest, but during intense and prolonged exercise it is possible to reach fatigue of the respiratory muscles. This study reveals that the main respiratory factors limiting physical exercise are the energetic compromise of the respiratory muscles with respect to the active skeletal muscles and the fatigue, so it is reasonable to believe that there may be improvements derived from training respiratory muscles. Taking into account all of the above, the implementation of an IMT program as part of RR may be indicated in patients with COPD and inspiratory muscle weakness with the aim of improving symptoms, especially dyspnea, and quality of life, although the mechanisms by which this improvement is achieved are unclear [14,22]. Among the authors who have confirmed the beneficial effects of an IMT program joined to RR, Gosselink et al. [13] observed benefits in exercise capacity, including patients with low PaO2 or high PaCO2, improving in both cases after the training of the inspiratory muscles. In the IMTCO study, published by Charususuin, they observed an improvement in the 6 min walking test (6MWT), the primary objective, with the use of the POWERbreathe KH1 device for the IMT. In addition to this, they found an improvement in inspiratory muscle function, health-related quality of life, and daily physical activity in patients undergoing this type of training [22]. Weiner et al. published that inspiratory threshold loading training, added to general exercise reconditioning, markedly improved inspiratory muscle strength and endurance, as well as exercise tolerance, in patients with COPD, and that the improvement in this group of patients was significantly greater than that achieved with general exercise reconditioning alone [23]. In this direction, Petrovic et al. [12], showed the benefits of IMT in patients with dynamic hyperinsuflation, as it produces an increased end-expiratory lung volume that may result in a greater weakness of the inspiratory muscles. They found an increase in exercise capacity and significant reduction in dynamic hyperinflation. In the same way, in 2018, a study was published that demonstrated a positive association between a 8 weeks IMT program with an increased capacity to sustain high ventilation for a longer duration, accompanied by consistent improvements in diaphragmatic strength [24]. This program also consisted of strength exercises followed by endurance ones. 3.2. What Is a Respiratory Rehabilitation Program with Inspiratory Muscle Training? Prior to start a rehabilitation program, it is advisable to demonstrate the existence of inspiratory muscle weakness (PImax), and thus add specific exercises for IMT, aimed at improving physical exercise performance, through repeated resistance exercises [25], which causes an improvement in lactate clearance kinetics and a decrease in the perception of the effort made [26]. To carry out this type of training, devices have been designed and are commonly used in rehabilitation programs, improving respiratory muscle strength and endurance, resulting in a decrease in dyspneic sensation and an increase in exercise tolerance [27]. Three types of devices are available for inspiratory muscle training: threshold devices, resistive load devices, and voluntary isocapnic hyperpnea devices [28]. Threshold device: training with this type of device is obtained with a hand-held device that allows airflow during inspiration after reaching an inspiratory pressure. The effort required by the inspiratory muscles can be adjusted by the tension of a spring; this tension determines the opening of the valve; Resistive loading device: this is one of the most commonly used categories. In this category we have different devices. The PFLEX resistive Trainer device (Respironics HealthScan Inc., Cedar Grove, NJ, USA), consists of a mouthpiece and a circular dial. Turning the dial varies the size of the opening through which the patient breathes. The smaller the opening, the greater the resistance to inspiration. It has 6 diameter sizes. The objective of this exercise is to increase the load on the inspiratory muscles progressively. Many studies have used this device for IMT [25,29]. The PowerBreathe® device also stands out for its widespread use [30]. The Feelbreathe® device also behaves like a resistive load device, but in this case it is nasal and not buccal. It is a nasal ventilatory flow restriction device composed by a strip of hypoallergenic material that is placed and adhered under the nostrils, provoking resistance to flow. Depending on the size and porosity of the device material, the inspiratory process is more or less difficult. This device has the possibility of using it not only in a static situation but also dynamically during exercise [31]; Voluntary isocapnic hyperpnea device: consisting of a device that increases the ventilation level of the subject to a predetermined level. The increase in ventilation causes an increase in respiratory rate, which can reach 50–60 rpm. This type of respiratory muscle training requires the patient to perform prolonged periods of hyperpnea, lasting up to 15 min and with a frequency of twice a day, 3 times a week, for 4–5 weeks [32]. To avoid hypocapnia, exercise should be performed on an isocapnic circuit, which maintains stable CO2 levels. One device using this method is the SpiroTiger® (Ideag Lab, Ziirich, Switzerland). Respiratory rehabilitation and IMT programs that complete the recommended time of 6 to 12 weeks have shown, as mentioned above, benefits in health-related quality of life, improvement of dyspnea and exercise tolerance [32]. The main objective is to achieve a change in the patient’s lifestyle habits, avoiding sedentarism, and incorporation to physical activity. Regarding the duration of the training program, it should be taken into account that a short intervention implies an increase in inspiratory muscle strength while a longer intervention increases functional capacity. The benefits last approximately 12–18 months if habitual activity is abandoned, returning the patient to his or her previous situation before starting respiratory rehabilitation. 4. Inspiratory Muscle Training Programs Based on the Use of Mechanical Devices Mechanical devices have shown to improve muscle strength and endurance in patients with COPD, leading to an improvement in the quality of life of these patients [13,33]. However, it has not been demonstrated that there is any additional benefit to an isolated pulmonary rehabilitation program without inspiratory muscle training [8,33,34]. In fact, its implementation in RR programs in COPD patients in general is not recommended by the British Thoracic Society (BTS) or by the Spanish Society of Pneumology and Thoracic Surgery (SEPAR), although the latter recommends adding IMT for patients with inspiratory muscle weakness, defined as a maximal inspiratory pressure of less than 60 cmH2O [35,36]. This variety of training usually employs small devices that are easily manipulated by the patient. Interest in this subject has been progressing over the last half century, reflecting the increase in the number of publications, which may be related to technological advances. These studies use simple devices, which generally increase inspiratory resistance by gradually decreasing the inspiratory orifice, showing a benefit for inspiratory muscle training in patients with COPD. As a main limitation of these studies, the sample size included is small [37,38,39]. Dekhuijzen et al. [40] compared a respiratory rehabilitation program to which they associated IMT with a flow resistance device, versus RR, observing an improvement in physical exercise capacity measured by the distance covered in a 6MWT and the maximal oxygen consumption (VO2max), in those patients in whom they followed a muscular inspiratory training program associated with the RR program. Some IMT devices are currently available and are described below (Figure 2). 4.1. Respifit STM Respifit STM is a threshold type device for IMT that is portable, small, and easy to use. It features a “Y” shape, mouthpiece, nasal closure clip, and a display that shows results and facilitates therapy monitoring. The mode of use consists of initially performing normal inhalations and exhalations, after which the subject should inhale and exhale slowly and deeply, without hyperventilating. The subject then makes slow turns of the head to one side and inhales and exhales, and then to the other side, repeating breaths, for one minute. The next minute, he performs the same procedure but with up and down movements of the head. Finally, the subject will lean forward to touch their toes while breathing in and out. Finally, the subject will return to normal inhalation and exhalation. This device has been studied by Petrovic et al. [12], aiming to analyze the effects of IMT on exercise capacity, dyspnea, and inspiratory fraction during exercise in patients with COPD. A total of 20 patients were included and divided into two groups. Patients in the treatment group performed an inspiratory muscle training program using the Respifit STM device daily for 8 weeks, with the other group serving as a control. Assessment of exercise capacity was measured by cardiopulmonary exercise test prior to the start of training and one week after the end of training. Improvements in respiratory muscle function, exercise capacity and quality of life were observed, as well as a decrease in dyspnea. 4.2. PowerBreathe® PowerBreathe® is an electronic resistive loading device that is small and light with a mouthpiece at the top and a display on which different parameters such as maximal inspiratory pressure (cmH2O), maximum inspiratory flow (l/s), training load (cmH2O), power (watts), average inhaled volume (l), and T-index (training intensity index) can be observed. Inside the device there is a quick response valve with electronic control to generate inhalation resistance. The patient should inhale and exhale through the mouthpiece 30 times. This regimen is recommended to be repeated twice a day. When inhaling, the patient will notice a resistance that varies in relation to the volume of air. The training resistance is maximal at the beginning of the inhalation (RV—residual volume) and gradually decreases to values close to zero at the end of the inhalation (TLC—total lung capacity). This resistance is designed to match the length-tension relationship of the inspiratory muscles, providing a constant relative training intensity at all lung volumes. This training method ensures optimal stimulation throughout the entire range of motion of the inspiratory muscles. The training load is introduced gradually over the first five breaths of a training session. The first two breaths are performed without load. During these breaths, inhaled volume and flow are measured and used to establish an appropriate training load. The training load is then gradually introduced during breaths three and four times until the full load is reached in the following breaths. The training load is adjustable and should be set at a level appropriate for the patient to effectively train the inspiratory muscles. Research has shown that inspiratory muscle training loads should exceed 30% of the maximal inspiratory muscle pressure (force) to be effective. Magadle et al. [23], analyzed the effect of adding IMT in patients with severe COPD (FEV1 < 50%) without respiratory failure, who were already included in a rehabilitation program, assessing lung function, inspiratory muscle strength, perception of dyspnea, exercise performance, and quality of life. All patients participated in a rehabilitation program for 12 weeks, after which they were randomized into two groups: one group was given IMT with PowerBreathe® and the other was given a sham inspiratory training device (control group). Statistically significant differences were observed in inspiratory strength and in the perception of dyspnea, however, there were no differences between the two groups with respect to FEV1 or 6MWT. The following study also aims to evaluate the added effect of IMT together with full body resistance training. For this purpose, it divides the patients into an experimental group (IMT using the PowerBreathe® device together with full body training) and a control group (full body training alone). After the training period an improvement in the Berg Balance Scale (BBS) was demonstrated and statistically significant differences were also found in inspiratory muscle strength, increasing up to 37% in the experimental group. However, no differences were found between both groups in the 6MWT [41]. Following the same line, Charususin et al. [42] conducted a study with the aim of evaluating the added benefits of IMT to a rehabilitation program in COPD patients with inspiratory muscle weakness. Although a statistically significant improvement in inspiratory muscle strength and endurance was established, this was not reflected in the 6MWT, where no differences were found. An advantage of the PowerBreathe® device is that it allows unsupervised training. Langer et al. [43] compared the efficacy of a mechanical loading threshold device versus an electronic device for home use, the PowerBreathe®. They note that the use of the electronic device with a home training program requires less time investment for the health services, and there is an improvement in inspiratory muscle capacity. In addition, study participants in the electronic device group tolerated higher training intensities and achieved significantly greater improvements in inspiratory muscle function [44]. 4.3. Threshold IMT® Threshold IMT® is a small and light threshold type device that is cylindrical in shape, with a nozzle at one end. This device incorporates a unidirectional valve independent of the flow, which ensures constant resistance and allows pressure adjustment (in cmH2O). This valve provides a resistance to the air flow, which forces the subject to make a greater effort to overcome the pressure [45]. The subject must repeat inspiration and expiration manoeuvres through the mouthpiece, perceiving a variable resistance only in inspiration. A use of about 10–15 min twice a day is recommended. According to the existing literature, the benefits derived from IMT with mechanical devices are greater in COPD patients with a maximal inspiratory pressure of less than 60 cmH2O (13), but there are studies that aim to demonstrate the efficacy of the use of these devices in patients with a maximal inspiratory pressure above 60 cmH2O. Beaumont et al. [46], with the IMT Threshold IMT® device, found no statistically significant differences in terms of improvement in dyspnea or functional parameters. No benefits were observed in a study in which two groups were compared: training with cycloergometer plus IMT with Threshold IMTR; versus training with cycloergometer alone. It was observed that combined training improves inspiratory strength versus isolated cycloergometer training; however, no differences were observed with regard to improved physical performance or dyspnea. Another interesting aspect of this study is that an analysis was performed in a subgroup of patients with inspiratory muscle weakness, defined as a maximal inspiratory pressure of less than 60 cmH2O, without noticing the benefits of combined training in this subgroup [47]. 4.4. PrO2Fit TM® PrO2Fit TM® is a small, lightweight, and portable resistive load device with a nozzle on the end. It is connected to a mobile application, which provides the user with a graphic representation of the effort made. For its use, the patient must repeatedly inhale and exhale through the mouthpiece, following the indications of the mobile application. This device allows us to evaluate the inspiratory musculature by means of an incremental respiratory endurance test, known as TIRE (Test of Incremental Respiratory Endurance). In this way, the maximum inspiratory pressure is measured over time, obtaining the maximum sustained inspiratory pressure. This device was developed for inspiratory muscle training in athletes and is of interest in patients with respiratory pathology; however, there are few studies that evaluate its efficacy in patients with COPD. One such study, by Formiga et al. [48], evaluates the reliability of such a device for measuring inspiratory muscle strength and endurance, but is not designed to test its efficacy as an inspiratory muscle training device. Although not focused on COPD patients, McCreery et al. [49] evaluated the effect of inspiratory muscle training using the PrO2 Fit device in patients with bronchiectasis, concluding that there is an increase in inspiratory muscle strength and endurance in these patients. The protocol of a randomized clinical trial comparing a home training program based on an incremental breathing endurance test (TIRE), using the PrO2 device, versus a traditional inspiratory muscle training program using the Threshold IMTR has recently been carried out. The results of this study are not yet published [50]. 4.5. Aerosure Medic® Resistive charging device designed to provide resistance on inspiration. It consists of a rectangular device with a mouthpiece and a charger. It has two modes, one for muscle training in which the patient must repeatedly inhale and exhale through the mouthpiece and a second mode with a mucolytic effect on the airway. In the study carried out by Daynes et al. [51], such a device is evaluated. Patients were included in a training program with Aerosure Medic®, to be used 3 times a day for a total of 8 weeks. A statistically significant improvement in dyspnea and in maximal inspiratory pressure (PImax) and maximal expiratory pressure (PImax) was observed, with the improvement in PImax being greater in the subgroup of patients with inspiratory muscle weakness, also defined in this study as a PImax of less than 60 cmH2O. 4.6. AeroFit IMT® AeroFit IMT® is a resistive loading device for IMT, currently under study. It consists of a small, portable, lightweight oral pressure manometer with a rubber rimmed mouthpiece. It contains resistance wheels that provide adjustable airflow. This resistance causes fatigue in the respiratory muscles, which is then compensated by increased muscle mass, making these muscles stronger, faster, and more efficient. The device is connected via an app to the cell phone where the subject can choose the desired training program and observe the progress achieved through training. It has been studied in athletes, demonstrating an increase in maximal respiratory strength without reporting dyspnea or respiratory fatigue after use. These results suggest its future application in patients with respiratory diseases such as COPD within an IMT. A clinical trial is currently under development in which the ability of AeroFit IMTR to improve inspiratory muscle strength in COPD patients is being evaluated. The results are not yet published [52]. 4.7. MicroRPM MicroRPM is a resistive loading device that is small, portable, lightweight, and noninvasive, containing a mouth-pressure manometer with a rubber flanged mouthpiece. It displays the test results in a device monitor, uses software and calculates the maximal inspiratory pressure and maximal expiratory pressure values (in cmH2O), from the one-second average maximum pressure. The MicroRPM needs a different adapter to be adjusted for inhalation and exhalation, without the need for special preparation in terms of cleaning and disinfecting the device by simply adapting the respective inhaler and exhaler adapter and the removable mouthpiece. Stavrou et al. did not find differences between two devices (MicroPRM vs. AirOFit PRO™); the comparison showed no differences in the maximal inspiratory pressure and maximal expiratory pressure variables, but statistically significant differences were observed between the devices in the parameter ease of use and information during the trials [52]. 4.8. SpiroTiger® This is a voluntary isocapnic hyperpnea device. It consists of a tube that connects to a breathing bag with a mouthpiece at a 90° angle. Between these components there is a side port with an opening that allows inspiration and expiration into the ambient air. It also has a monitor that shows and assists the patient by providing auditory and visual feedback. When the patient exhales, the bag fills with air, with higher concentrations of carbon dioxide. When the bag is full, the side valve opens and allows the remaining exhaled air to escape. Once expiration is complete, the valve closes and gives way to inspiration. During inspiration, the bag is first emptied completely and then the side valve is opened. A review conducted in 2015 evaluated five articles analyzing the SpiroTiger® device, one of them in patients with COPD and the rest in patients with cystic fibrosis. Finally, they conclude that this device presents an improvement in physical condition, measured in the different studies using the 6MWT and in VO2max, as well as an improvement in the quality of life. However, the improvement in FEV1 is not conclusive, as it is present in only two of the studies evaluated in the review, and therefore more studies are required [53]. There is a study evaluating the efficacy of SpiroTiger® training for four weeks in patients with COPD. Maximum inspiratory pressure, 6MWT distance, and quality of life were measured using the St George Respiratory Questionnaire for subjects with COPD, and an increase in maximum inspiratory pressure, 6MWT distance, and quality of life were observed [54]. 4.9. FeelBreathe® So far, the aforementioned devices must be used in a static position and breathing through the mouth, which is not considered physiological. Recently a device for inspiratory muscle training called FeelBreathe® has been designed. It is a nasal ventilatory flow restriction device consisting of a strip of hypoallergenic material that is placed and adhered under the nostrils, producing resistance to flow. Depending on the size and/or porosity of the device material, the inspiratory process is more or less difficult. The advantage of this device with respect to those mentioned above is, on the one hand, the fact that it is a nasal device, so breathing is more physiological and, on the other hand, it allows for use in dynamic situations, so we can use it while the patient is exercising. This device has been shown to be effective in improving ventilatory and cardiac efficiency in healthy patients, and in patients with COPD it has also demonstrated less dynamic hyperinflation with better ventilatory efficiency [50]. This ability of the device to be used in motion allows it to be implemented in pulmonary rehabilitation programs by using it during different exercises, and hence the hypothesis that the FeelBreathe® device brings added benefits to respiratory rehabilitation. Gonzalez-Montesinos et al. studied this circumstance and observed that patients who have used FeelBreathe® together with a pulmonary rehabilitation program show an improvement in quality of life, dyspnea, exercise capacity, and inspiratory muscle strength. However, the main limitation of these studies is the small number of patients, so more studies are needed to reach a definitive conclusion on the addition of FeelBreathe® in a pulmonary rehabilitation program [31,55,56]. 5. Conclusions The bibliography supports the use of IMT devices, despite the presented limitations: the sample size is low in most of the studies; the compared groups are not clearly standardized—therefore in some of them they may not be comparable, and the follow-up is different in all the studies. Despite the heterogeneity of the studies included in this review limiting the extrapolation of results, a wide benefit in terms of quality of life due to the use of inspiratory muscle training devices has been stated. One limitation of the review process was that the authors undertook an independent review, sharing data afterwards. Another limitation could be the use of just two search engines. All things considered; it can be concluded that COPD is a heterogeneous disease that requires a multidisciplinary approach for its control. Respiratory rehabilitation is postulated as an important part of non-pharmacological therapeutic options, with IMT taking special interest in recent decades as a part of the rehabilitation program. The IMT has been favoured by the development of different mechanical devices that help both in programs with direct supervision, as well as in others controlled by remote monitoring. Some of the devices that stand out in the chronic obstructive profile patients and present criteria of easier use, accessibility, and good results have been the AirOFit PRO ™, PowerBreathe®, or FeelBreathe®. This last device has the added value that it is a nasal device, favouring a more physiological breathing, and it also allows its use in dynamic situations, therefore it could be used when the patient is exercising. The active search for candidate subjects to carry out a PR program with training of the inspiratory muscles using this type of device in patients with COPD represents an advance in the treatment of this disease, with direct benefits on the quality of life of these patients. Nonetheless, further studies are needed to reach consensus regarding its standardization in clinical use. Acknowledgments Special thanks are due to the University Hospital Puerta del Mar, Cádiz (Spain) and María Romero Barrero for her contribution to the editing and revising of the manuscript. Author Contributions All authors (E.V.-G., A.H.-M., F.M.-B., M.M.-G., I.M.-R. and A.A.-M.) played a role in the content and writing of the manuscript. All authors have read and is responsible for any of the aspects included in 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. Conflicts of Interest The authors declare no conflict of interest. Abbreviations COPD Chronic Obstructive Pulmonary Disease RM Respiratory muscles RR Respiratory rehabilitation IMT Inspiratory muscle training T.lim Endurance capacity of inspiratory muscles 6MWT 6 min walking test SGRQ St. George’s Respiratory Questionnaire BBS Berg Balance Scale ABC Activity specific Balance Confidence scale VO2 Oxygen uptake VCO2 Carbon dioxide output FVC Forced vital capacity FEV1 Forced expiratory volume in first second MIP Maximal inspiratory pressure ID Inspiratory duration SMIP Sustained maximal inspiratory pressure mMRC Modified Medical Research Council PImax Maximum inspiratory pressure PEmax Maximum expiratory pressure ISWT Incremental shuttle walk test ESWT Endurance shuttle walk test PSQI Pittsburgh Sleep Quality Index Figure 1 PRISMA 2020 flow diagram. Figure 2 IMT devices used in respiratory rehabilitation. (a) Respifit STM; (b) PowerBreathe®; (c) Threshold IMT®; (d) PrO2Fit TM®; (e) Aerosure Medic®; (f) AeroFit IMT®; (g) MicroRPM; (h) SpiroTiger®; (i) FeelBreathe®. ijerph-19-05564-t001_Table 1 Table 1 Bibliography search of IMT devices. Author Publication Date Device Type of Devices Subject Study Duration Method Results Petrovic et al. 2012 Respifit STM Threshold 20 COPD 8 weeks Direct by cardiopulmonary and stress test Enhances inspiratory muscle function, dyspnea, and quality of life. Magadle et al. 2007 PowerBreathe® Resistive load and 34 COPD 12 weeks 6MWT, SGRQ Enhances inspiratory muscle function and dyspnea perception. Tounsi et al. 2021 PowerBreathe® Resistive load and 32 COPD 8 weeks BBS, ABC, 6MWT Enhances inspiratory muscle function and functional balance according to BBS and ABC. Charususin et al. 2018 PowerBreathe® Resistive load and 219 COPD 5–8 weeks 6MWT. No differences in 6MWT. Gains in respiratory muscle function and also endurance exercise capacity. Langer et al. 2018 PowerBreathe® Resistive load and 20 COPD 8 weeks PImax, T.lim Improvments in Pi,max and T,lim. Telemonitorization. Beaumont et al. 2015 Threshold IMT® Threshold 23 COPD 3 weeks Borg scale, 6MWT, PImax. Cycle ergometer Subgroup of patients with FEV1 < 50% pred., dyspnea was significantly improved. McCreery et al. 2021 PrO2 Fit Resistive load 10 BQ 8 weeks VO2, VCO2 and pulmonary function (FVC, FEV1) Increased inspiratory muscle strength and endurance. Telemonitorization. Formiga et al. 2018 PrO2 Fit Resistive load 81 COPD 1 day FEV1, FVC, 6MWT, MIP, ID, SMIP. Increased inspiratory muscle strength and endurance Formiga et al. 2020 PrO2 Fit Resistive load On going 8 weeks mMRC, FEV1, FVC, 6MWT. Test of incremental respiratory endurance training method has the potential to provide additional clinical benefits in COPD. Daynes et al. 2018 Aerosure Medic® Resistive load 23 COPD 8 weeks mMRC, PImax, PEmax. ISWT, ESWT Improvmente PI max, PE max, and reducing dyspnoea. Stavrou et al. 2021 AeroFit IMT® MicroRPM Resistive load 21 athletes 1 day PSQI, pulmonary function test, ergospirometry Compare both not differences between devices. AirOFitPRO™ is easier to operate as a device and provides more information. Bernardi et al. 2015 SpiroTiger® Resistive load 20 COPD 4 weeks Spirometry 6MWT, VO2max, SGRQ Increased inspiratory muscle and quality of life. Włodarczyk et al. 2015 SpiroTiger® Voluntary isocapnic hyperpnea - - 6MWT Improve quality of life and distance in 6MWT Gonzalez-Montesinos et al. 2020 FeelBreathe® Nasal restriction 18 COPD 8 weeks PI max y VO2max Positive effects in dynamic hyperinflation, breathing pattern, and breathing efficiency, with higher expiratory and inspiratory time. Arnedillo et al. 2020 FeelBreathe® Nasal restriction 16 COPD 8 weeks Inspiratory muscle strength (PImax), dyspnea (mMRC), quality of life (CAT) and exercise capacity (6MWT) Improvements in quality of life, dyspnea, exercise capacity, and inspiratory muscle strength Gonzalez-Montesinos et al. 2021 FeelBreathe® Nasal restriction 20 COPD 8 weeks VO2, VCO2, respiratory rate FB added to a pulmonary rehabilitation program in COPD patients could improve tolerance in the incremental exercise test and energy efficiency COPD: Chronic Obstructive Pulmonary Disease. SGRQ: St. George Respiratory Questionnaire score. BBS: Berg Balance Scale. ABC: activity specific Balance Confidence scale. 6MWT: 6 min walking test. PImax: maximal inspiratory mouth pressure. T,lim: endurance capacity of inspiratory muscles. BQ: Bronchiectasis. FEV1: forced expiratory volume in the first second. FVC: forced vital capacity. PImax: maximal inspiratory pressure, PEmax: maximal expiratory pressure. ID: inspiratory duration. SMIP: sustained maximal inspiratory pressure. mMRC: modified Medical Research Council. ISWT: incremental shuttle walk test. ESWT: endurance shuttle walk test. PSQI: Pittsburgh Sleep Quality Index. RR: respiratory rate, VO2: oxygen consumption, VCO2: carbon dioxide production. FB: FeelBreathe®. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Global Strategy for Diagnosis, Management, and Prevention of COPD 2022 Available online: https://goldcopd.org/2022-gold-reports/ (accessed on 1 February 2022) 2. Rabe K.F. Watz H. Chronic obstructive pulmonary disease Lancet 2017 389 1931 1940 10.1016/S0140-6736(17)31222-9 28513453 3. Agustí A. Sobradillo P. Celli B. Addressing the complexity of chronic obstructive pulmonary disease: From phenotypes and biomarkers to scale-free networks, systems biology, and P4 medicine Am. J. Respir. Crit. 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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/ijerph19095604 ijerph-19-05604 Review Parental Feeding Practices in Families Experiencing Food Insecurity: A Scoping Review https://orcid.org/0000-0001-5180-1455 Baxter Kimberley A. 1* https://orcid.org/0000-0002-0626-1119 Nambiar Smita 12 https://orcid.org/0000-0003-0516-9609 So Tsz Hei Jeffrey 1 Gallegos Danielle 1 https://orcid.org/0000-0002-0096-3320 Byrne Rebecca 12 Tchounwou Paul B. Academic Editor 1 Woolworths Centre for Childhood Nutrition Research, Faculty of Health, Queensland University of Technology, Graham St, South Brisbane 4101, Australia; smita.nambiar@qut.edu.au (S.N.); jeffrey.so@hdr.qut.edu.au (T.H.J.S.); danielle.gallegos@qut.edu.au (D.G.); ra.byrne@qut.edu.au (R.B.) 2 School of Exercise and Nutrition Sciences, Faculty of Health, Queensland University of Technology, Victoria Park Rd, Kelvin Grove 4059, Australia * Correspondence: kimberley.baxter@qut.edu.au 05 5 2022 5 2022 19 9 560428 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/). Parental feeding practices and styles influence child diet quality and growth. The extent to which these factors have been assessed in the context of disadvantage, particularly household food insecurity (HFI), is unknown. This is important, as interventions designed to increase responsive practices and styles may not consider the unique needs of families with HFI. To address this gap, a scoping review of studies published from 1990 to July 2021 in three electronic databases was conducted. A priori inclusion criteria were, population: families with children aged 0–5 years experiencing food insecurity and/or disadvantage; concept: parental feeding practices/behaviours/style; and context: high income countries. The search identified 12,950 unique papers, 504 full-text articles were screened and 131 met the inclusion criteria. Almost all the studies (91%) were conducted in the United States with recruitment via existing programs for families on low incomes. Only 27 papers assessed feeding practices or styles in the context of HFI. Of the eleven interventions identified, two assessed the proportion of participants who were food insecure. More research is required in families outside of the United States, with an emphasis on comprehensive and valid measures of HFI and feeding practices. Intervention design should be sensitive to factors associated with poverty, including food insecurity. feeding practices food insecurity infant feeding responsive feeding parents scoping review Children’s Hospital FoundationWCCNR03 KB is supported by a grant from the Children’s Hospital Foundation (Reference number WCCNR03) under the auspices of the Woolworths Centre for Childhood Nutrition Research (WCCNR). JS receives a PhD scholarship from the WCCNR. ==== Body pmc1. Introduction Parental feeding practices and styles play an important role in the development of child diet quality, eating behaviours and healthy growth [1]. Children are born with an innate ability to self-regulate their energy intake, which allows them to follow their own hunger and satiety cues [2]. This can be easily overridden by parental practices such as pressure to eat or the use of rewards for eating. These parent behaviours, referred to as ‘coercive control’ or non-responsive feeding practices, “teach” children to eat for reasons other than hunger [3]. Conversely, responsive feeding refers to prompt, emotionally supportive, contingent, and developmentally appropriate reciprocity between the child and their caregiver in relation to feeding and food intake [4]. Responsive practices fall broadly under the higher-order constructs of ‘structure’ and ‘autonomy support or promotion’ [3], whereby parents provide safe, nutritious, and developmentally appropriate foods and the child decides how much is eaten [1,5]. While practices are the specific goal-oriented actions a parent takes in relation to child feeding and eating, these sit within a broader construct known as feeding styles. Feeding style refers to the general way that parents interact with a child during meal and snack times [6]. An authoritative style is considered most appropriate, characterized by high levels of warmth and responsiveness to a child’s needs, along with high levels of age-appropriate reasoning and structure [7]. Over the last three decades, the global rise in the prevalence of childhood overweight and obesity prompted extensive research into the associations between parental feeding practices and styles with child outcomes. Responsive feeding practices are considered a protective factor in the prevention of excess weight and obesity [8,9], via the impact on a child’s ability to self-regulate their appetite and intake. Feeding practices also influence diet quality, for example, a pressure to eat has largely been associated with poorer quality diets in children, while parental modelling and encouragement are associated with improved diet quality, such as increased vegetable intake [10]. Such findings have led to the development of interventions aimed to modify feeding practices. Indeed, systematic reviews of randomized controlled trials of interventions found that promotion of responsive feeding is the most promising avenue for obesity prevention for children under two years [11,12]. However, exactly what components of interventions are most effective, and what components are most appropriate for different populations remains unclear [13]. This is particularly true for families experiencing socioeconomic disadvantage, who are disproportionally impacted by poor diet, suboptimal nutrition, and poor growth, including obesity [14]. Disadvantage, which includes financial and material hardship (low income, poor living conditions) and/or social isolation [15] has been strongly linked to poorer physical, cognitive, and social development in children [16]. The environmental conditions and adversity children experience during critical periods is known to impact on both immediate and long-term health. This has led to the nurturing framework linked to the sustainable development goals that posits that early child development is supported by seven key dimensions: good health, adequate nutrition, safety and security, responsive caregiving and learning and stimulation [17]. Within the context of responsive feeding, the nurturing framework is relevant; however, two circumstances may have particular significance for families living with disadvantage, that is, food insecurity and household chaos. Food insecurity is defined as the limited financial, physical, and social access to food of sufficient quality and quantity for a healthy and active life [18] and has been linked to poor child outcomes [19]. Food insecurity has a prevalence of around 12% at a population level in high income countries [20], with much higher rates in more disadvantaged communities. For example, in the USA 35.3% of households with incomes below the Federal poverty level were food insecure in 2020 [21], and in Australia up to 25% of households in low-income areas are affected [22,23]. A recent review of the literature by Gallegos et al. (2021) found that both persistent and transient household food insecurity were associated with sub-optimal child development outcomes [24]. Chaotic households that are prone to high noise and crowding, with low levels of routine, organisation and overall stability have been linked to poorer child development, overweight and obesity and food insecurity [25]. Household chaos and a lack of meal planning are potential mediating factors in food insecurity [26]. In contrast, responsive feeding is contingent on environments being pleasant, structured and without distractions, such that parents can recognize and respond to child cues in a prompt, developmentally appropriate way [4]. A narrative review by Arlinghaus and Laksa (2021) [27] argued that there are considerable structural constraints, such as the ability to access food and the cost of food, which influence how parents experiencing food insecurity feed their children. Those experiencing food insecurity have significantly more time constraints, particularly if they are single parents [27]. One of the benefits of responsive feeding, is that it promotes the development of healthy food preferences. Often, repeated exposure to novel foods is required before the child gains acceptance of a new food, but parents who are food insecure, may not offer foods that are not accepted immediately, particularly if they are expensive. The authors noted that low fruit and vegetable consumption may be the result of trying to prevent food wastage and the higher cost of such foods. Food insecurity can also be experienced intergenerationally, where chronic food insecurity shapes the way in which children learn about, acquire, and prepare food. There may be an emphasis on consuming foods with a high satiety value (that is, energy dense) over foods that are of higher quality (nutrient dense). Thus, interventions designed to support responsive feeding in households experiencing food insecurity, who may also have high levels of chaos, may require a different approach to commonly promoted strategies, such as repeated exposure to foods [28]. Therefore, the aim was to undertake a scoping review of the evidence related to parental feeding practices in families experiencing socioeconomic disadvantage—and food insecurity—in high income countries. The scoping review methodology was deemed appropriate to map the evidence and synthesise the key concepts given this diverse topic [29]. The objectives were to describe what and how parental feeding practices and styles have been assessed amongst families experiencing disadvantage, understand the characteristics of studies examining parent feeding practices in families with household food insecurity (HFI); and to identify and describe the key components of interventions that aim to modify feeding practices in families living with disadvantage and/or HFI. 2. Materials and Methods This review was compliant with the PRISMA checklist for scoping reviews [30] and the Joanna Briggs Institute (JBI) approach to scoping reviews [31]. The protocol was registered with the Open Science Framework (OSF) (doi:10.17605/OSF.IO/Q47VP) (created on 9 June 2021). 2.1. Inclusion and Exclusion Criteria A priori eligibility inclusion and exclusion criteria were developed as follows:Population: families with children aged 0–5 years experiencing HFI or disadvantage. Disadvantage could include a measure of HFI, poverty, low income, low education attainment, receiving welfare/food assistance or other indicators of socioeconomic disadvantage. Concept: Parental feeding practices or styles. Papers were included if a measure of parental feeding practices and/or styles was used or identified as a theme in qualitative research. Context: high income countries according to the World Bank definition [32]. Full-text, peer-reviewed articles that were published in English were included in this scoping review according to the above criteria between the years 1990 and 2021 (database searches conducted on 2 September 2020 and updated 12 July 2021). Articles were excluded if the population group had a diagnosed illness/disorder that would impact feeding (e.g., cystic fibrosis, premature birth), or the focus was on infant feeding practices exclusively (i.e., breastfeeding, use of formula, age of introduction of solid foods). Opinion pieces, editorials, reviews, conference abstracts or protocol papers were also excluded. 2.2. Search Strategy A search strategy was developed by KB and SNM in consultation with an experienced academic librarian. The search was run in three electronic bibliographic databases by KB (CINAHL, Medline and PsycInfo). Key words for the search strategy used in each database are shown in Appendix A. Citations were exported into EndNote and then imported into Covidence; a web based systematic review production tool [33]. The reference lists of included sources and relevant reviews were also checked. 2.3. Selection of Included Articles The title and abstract of each article were screened in Covidence using a priori eligibility criteria. All authors were involved in the screening process. Two authors screened citations for inclusion independently, with inter-rater conflicts resolved by another reviewer, and this task was shared across authors (KB, SNM, RB, DG, JS). This process was repeated to screen full-text articles. The final list of included articles can be found in Appendix B. 2.4. Data Extraction Data extraction was completed in Covidence using a modified version of their data extraction form. Extraction was done by one author and checked by a second author for completeness. 2.5. Data Synthesis and Analysis Descriptive statistics were used to describe the characteristics of included papers, namely, those that directly measured and reported household food insecurity (HFI) using a specific tool and those that did not, country of origin, study design, and assessment of feeding styles or practices. The number of different feeding practices assessed across all papers were tallied, using the Vaughn content map of food parenting practices [3] as a guide and a count made of the most frequently used tools to assess styles and practices. Data from those papers that measured HFI were described in more detail including study design, primary objective, country of origin, sample characteristics (age, gender, recruitment details), measures and tools used and key findings. Similarly, a table describing intervention studies designed to modify feeding practices amongst families experiencing food insecurity was included. Given the search identified only two intervention studies with families that reported HFI, this table was expanded beyond the original objective, to also include interventions for families experiencing disadvantage. Findings were also synthesised descriptively to map the relevant aspects of the literature as related to our research question. Results of the review are presented in narrative form. Quality appraisal was not conducted as this was not deemed necessary to meet the objectives of the review. 3. Results Searches identified 12,950 unique records (Figure 1). After screening, 131 met the inclusion criteria, with 27 studies (21%) assessing HFI within their population of interest (Table 1). Almost all studies were conducted in the United States (119/131, 91%) with the next most frequent location being Australia (6/131, 5%). One hundred and six papers examined feeding practices (81%). There was considerable heterogeneity in the types of practices assessed (Figure 2) and the tools used to assess these. Practices were categorised under the three higher-order food parenting constructs defined by Vaughn et al. (2016)—coercive control, structure, and autonomy support [3]. ‘Other’ practices included feeding practices that do not fall within the above known classification systems, such as laboratory eating protocols and food exposure practices. Practices representative of coercive control such as a pressure to eat and restriction were most often assessed, in 46% and 42% of papers, respectively. Meal and snack routines were the most frequently assessed practice under the construct of ‘structure’ at 28% of studies, followed by the practice of modelling. Practices that aligned with ‘autonomy support and promotion’ were assessed least often. Another 29 studies (27%) were classified as other, representing a disparate set of practices that parents used to influence child intake or eating behaviour, but could not be easily categorised within the Vaughn framework. More than thirty different questionnaires were used to assess feeding practices within the studies included in this review, the most frequent being the Child Feeding Questionnaire (n = 26 studies) [34], followed by the Comprehensive Feeding Practice Questionnaire (n = 7) [35] and the Feeding Practices and Structure Questionnaire (n = 5) [36]. Forty papers assessed feeding styles within a population experiencing disadvantage, with the most used questionnaire being the Caregiver Feeding Style Questionnaire (CFSQ) [7] in 25 papers, while another 10 papers used the Infant Feeding Style Questionnaire (IFSQ) [37]. Validation studies identified in this review provide evidence that the psychometric properties of the Child Feeding Questionnaire (CFQ), Caregiver’s Feeding Practices Questionnaire (CFPQ) and the Infant Feeding Style Questionnaire (IFSQ) have been assessed in disadvantaged populations in the United States, in particular Hispanic and African American populations; however, no specific methodological studies assessing the use of tools outside of the US were found. Figure 1 PRISMA diagram [38]. 3.1. Studies Examining Household Food Insecurity and Parental Feeding Practices/Styles The 27 papers identified are described in detail in Table 2. Twenty-three were conducted in the United States while the remaining four were in Australia. 3.1.1. Household Food Insecurity In those studies that reported HFI (n = 27), a variety of tools were used to define HFI in their participant cohorts. Most studies (17/27, 63%) used a variation of the USDA Household Food Security Survey Module (HFSSM), namely, either the 6-item [39,40,41,42,43,44], 10-item [45,46,47], or 18-item measure [48,49,50,51,52,53,54,55]; followed by a 2-item measure by Hager et al. (2010) (3/27, 11%) [56,57,58] and a 1-item question from the Australian Health Survey (3/27, 11%) [59,60,61]. The Radimer/Cornell Scale was also used in one paper [62], along with the Household Food Insecurity Access Scale (HFIAS) in another one paper [63]. Lastly, the remaining two papers used less rigorous methods with one paper using a study specific question, ‘Do you ever feel that you don’t have enough food for your family?’ (no evidence of validity or reliability provided) [64] and one paper describing food insecurity as a theme from focus group discussions with low-income parents [65]. There was wide variation in the reported proportion of HFI experienced between the groups described in each of the papers, ranging between 0–80%. 3.1.2. Feeding Practices and/or Styles The relationship between feeding practices and/or styles was most often examined within the context of child weight and obesity prevention [40,41,44,49,50,54,62,64]. The relationship between HFI and practices varied with HFI being associated with non-responsive practices in twelve [39,40,44,46,49,50,51,54,56,57,62,64] and non-responsive feeding styles in three [45,48,55] studies, respectively, with null findings in two others [41,64]. Interestingly, Kamdar et al. (2019), who found no relationship between feeding practices and styles, concluded that food insecurity may have a protective effect on dietary quality due to the adoption of coping mechanisms by mothers and grandmothers [41]. 3.2. Intervention Studies to Modify Feeding Practices in Families Living with Disadvantage and/or HFI Twelve studies described an intervention study that sought to modify early feeding practices amongst families who were categorised as low income, experiencing disadvantage and/or food insecure, these are summarised in Table 3. Only two of the interventions sought to assess and report the proportion of participants who were food insecure [50,58]. All the intervention studies identified originated from the US. Most of these research studies recruited participants via established programs for families on low incomes such as Head Start, Early Head Start or the Supplemental Nutrition Assistance Program (SNAP), with many research groups then utilising these existing programs and infrastructure to deliver the intervention. Length of the interventions ranged from a one-off video to three years (although the paper describing the 3-year intervention reported early outcomes at 10 months [50]). Interventions were largely aimed at mothers (10/12, 83% exclusively targeted mothers). Within one paper that included both mothers and fathers as participants, 92% were mothers [66] while the other paper reported participants as ‘parents’ and did not report the split of mothers to fathers [67]. Mode of delivery ranged from intensive multiple face-to-face appointments to remotely provided content via mail or phone and a computer tablet-based intervention in one case. Visual media content was a commonly used mode to deliver messaging in the interventions, with video described in several studies (n = 6, 50%) [58,68,69,70,71,72] as well as picture-based messaging [50]. In those papers using videos, these were described as short, curriculum-based videos, which included animation [72], real footage of mothers feeding their children in a home environment [68] and were tailored for the ethnicity of the target audience [68,69,70,72]. With the exception of Horodynski et al. 2005 [66], all the interventions described positive impacts on the intervention group in terms of the target feeding practices. Interventions largely targeted parental behaviours (feeding practices/styles), although Fisher et al. (2019) primary outcome was a reduction in calories from solid fat and added sugars (which was reduced by 23% at 12 weeks). Although many interventions had the underlying intention to prevent unhealthy weight gain among children, only Hughes et al. (2021) reported reduced child overweight/obesity compared to the control group [70]. Sun et al. (2017) showed a reduction in BMI among mothers in the intervention group compared with the control [72]. Of the two intervention papers that reported HFI, Fiks et al. (2017) found that HFI was significantly different at baseline between the intervention (HFI = 26%) and the control group (HFI = 60%) and, therefore, HFI was tested as a factor in their intention-to-treat analysis for health outcomes, with unchanged results. Messito et al. (2020) also reported the HFI rate of the participant cohort with 30.2% in the intervention and 34.5% in the control, which was found to be not significantly different at baseline. Messito et al. (2020) described tailoring content in the intervention to be sensitive to factors associated with poverty, including food insecurity [50]. ijerph-19-05604-t002_Table 2 Table 2 Details of studies examining feeding practices in families experiencing food insecurity (n = 27). First Author, Date Primary Objective Country Primary Recruitment Source Child Details (Sample Size; Age Mean (SD) or Range; Sex; Weight Measure If Available) Caregiver Details (Sample Size, Age Mean (SD); Relationship to Child; Ethnicity) Degree of HFI HFI Tool Used Feeding Practice Tool Key Outcome Quantitative Armstrong, et al. 2020 [39] To test associations among HFI, maternal restrained eating, and child feeding practices in low-income mothers of toddlers. United States SNAP for WIC and an urban paediatric clinic. N = 277 20.11 (5.5) months 53% male BMI z-score 0.54 (SD1.13) N = 277 27.28 (6.17) years Mothers African American (70%) Non-Hispanic White (8%) 40% food insecure 6-item USDA HFSSM [73] TFBQ [74] Relative increases in HFI were indirectly related to increases in restrictive and decreases in responsive child feeding practices, mediated through increases in mothers’ own restrained eating. Barroso et al. 2016 [40] To determine the association between measures of HFI, maternal feeding practices, maternal weight, and child weight-for-length in low-income Mexican Americans. United States WIC Clinics N = 240 17 (4.17) months 51.7% male, 48.3% female healthy weight 47.1%, 52.9% overweight N = 240 26.2 (5.81) years Mothers Hispanic (100%) 33% food insecure; 42% received SNAP 6-item USDA HFSSM [73] CFQ [34] + study specific items Children who were food insecure (SNAP recipients) were more likely to have a higher weight-for-length measurement. Berg et al. 2013 [63] To understand the relationships between parental perceptions about their child’s weight, feeding behaviours, acculturation, and HFI and obesity in childhood, in a low-income Hispanic population United States Three health fairs in a low-income Spanish speaking population N = 85 3.24 (0.99) years underweight, 15.4%; healthy 41.7%; overweight, 21.4% obese, 21.4% N = 85 30.91 years SD = 6.31 100% Hispanic 20% food insecure The Household Food Insecurity Access Scale (HFIAS)—9 items [75] CFQ [34] Parents’ weight, perceptions of child’s weight, adherence to the Hispanic culture, and food insecurity appear to impact parental concerns and behaviours, particularly restrictive and pressure-to-eat behaviours. Fiks et al. 2017 [58] To examine the feasibility and acceptability of Grow2Gether (a peer group intervention delivered through Facebook) and to test the impact on behaviours United States Two high-volume, obstetric clinics (Medicaid insured) 9 months N = 85 26.5 (5.4) years mothers 88% were black 42% food insecure 2-item household food security screener [76] IFSQ—10 items [37] A social media intervention resulted in high engagement and modestly improved feeding behaviours. Intervention reported significantly healthier feeding behaviours. Gross et al. 2018 [45] To determine the differential and additive impacts of HFI during the prenatal and infancy periods on obesity-promoting maternal infant feeding styles and practices at infant age 10 months. United States Secondary longitudinal analysis Details of recruitment NR N = 412 10 months N = 412 28.1 years mothers 100% Hispanics 39% food insecure 10-item USDA HFSSM [77] IFSQ [37] Prolonged HFI was associated with greater pressuring, indulgent and laissez-faire styles. Prenatal food insecurity was associated with less vegetable and more juice intake. Harris et al. 2018 [59] To examine the role of parent concern in explaining nonresponsive feeding practices in response to child fussy eating in socioeconomically disadvantaged families. Australia Socioeconomicaly disadvantaged urban community N = 208 3.6 (1.0) years 50% female BMI-z score 0.67 (1.33) N = 416 (i.e., 208 mother and father pairs) Mothers: 33.4 (5.3) years. Fathers 35.9 (6.6) years. ATSI (mother 4.8%, father 3.8%) 8% food insecure 1-item from Australian Health Survey [78] FPSQ-28 [36] In socioeconomically disadvantaged families, when parents are concordant in avoiding nonresponsive feeding practices, less child “food fussiness” is reported. Harris et al. 2019 [60] To examine if HFI modifies the relationship between child fussy eating and parents’ food provision and feeding with respect to exposure to a variety of healthy foods. Australia Socioeconomically disadvantaged urban community N = 260 3.6 (1.1) years female 51% BMI z score 0.7 (1.3) N = 260 33 (6) years mothers ATSI 5% 11% food insecure 1-item from Australian Health Survey [78] FPSQ—1 item (36) + Food exposure practices [79] Children’s fussy eating was associated with alternative meals in food insecure families. The availability of fruit was lower with HFI. Mothers’ food exposure practices may be contingent on the resources available. Horodynski et al. 2018 [48] To test the interactive effects of caregiver feeding style (CFS) and familial psychosocial risk in the association BMI-score in pre-schoolers from low-income families United States Head Start preschools N = 626 48.99 months (6.13) girls (51%) BMI z-score Mean 0.62 (SD1.16) N = 626 29.52 years (6.72) Primary caregivers non-Hispanic white (62%) and African American (30%) 37% food insecure 18-item USDA HFSSM [77] CFSQ [7] HFI was correlated with caregiver depressive symptoms and dysfunctional parenting. Uninvolved feeding styles intensified the risk, and an authoritative feeding style muted the risk conferred by living in a poor, food insecure and depressed family. Kamdar et al. 2019 [41] To investigate whether HFI affects child BMI through parental feeding demandingness and/or responsiveness and dietary quality 18 months later among low-income Hispanic pre-schoolers United States Head Start centres N = 137 time point 1: 4.8 years; time point 2: 6.3 years 47.8% female normal 48.9%, overweight 21.2%, obese 29.2% N = 137 dyads mothers, 2 grandmothers 46% food insecure 6-item USDA HFSSM [73] CFSQ [7] HFI had no influence on child BMI through feeding demandingness/responsiveness and/or child dietary quality. HFI was found to have a protective effect on dietary quality, this suggests the adoption of coping mechanisms McCurdy et al. 2014 [49] To examine why variation exists among child overweight in poor families with a focus on family food behaviours that are associated with income and maternal depression. United States Day care centres and a SNAP outreach project N = 164 51.4 (10.1) months 55.5% male overweight (17.1%) obese (15.9%) N = 164 30.1 (7.2) years mothers Hispanic (55%) 43% food insecure 18-item USDA HFSSM [77] 20 item FFBS [80] Higher food resource management skills and greater maternal presence when the child ate was significantly associated with lower child BMI z-scores Melgar-Quiñonez et al. 2004 [62] To examine the relationship of child-feeding practices and other factors to overweight in low-income Mexican American preschool-aged children United States HeadStart; Healthy Start; SNAP; and migrant education programs. N = 204 4.4 (0.8) years 51% female BMI: 17.0 (2.3) N = 204 Age NR 50% mothers and 50% fathers Latino, Mexican American, Mexican, or Hispanic 80% food insecure Radimer/Cornell scale (Spanish version) [81] Control and autonomy support Survey (study specific items) Variables positively associated with child overweight were income, mother’s BMI, child birth weight and juice intake. Biological and socioeconomic factors are more associated with overweight than self-reported child-feeding strategies. Messito et al. 2020 [50] To determine the impact of a primary care-based child obesity prevention intervention (StEP) beginning in pregnancy on maternal-infant feeding practices, knowledge, and styles at 10 months. United States Large urban public hospitals and affiliated health centres N = 412 10.6 (0.7) month 48.5% male intervention 49.5% male control grp N = 412 control: 28.8 (8.5) years intervention 28.9 (5.9) years mothers 100% female Hispanic Control 70% food insecure Intervention 60% food insecure 18-item USDA HFSSM [77] IFSQ 13 subscales [37] StEP reduced obesity-promoting feeding practices and styles, and increased knowledge at 10 months. Integration into primary health care helped to reach high-risk families. Na et al. 2021 [51] To explore relationships between HFI, food resource management skills (FRM) and child feeding practices of low-income parents. United States Head Start preschools N = 304 N = 304 32.2 (9.3) Non-Hispanic white (93.8%) 90% parent 95.4% Female 38% food insecure 18-item USDA HFSSM [77] CFPQ [35] Suboptimal child feeding is evident in low-income caregivers with low FRM skills,. Positive feeding practices were used by parents with high FRM skills regardless of HFI status. Orr et al. 2019 [56] To examine if caregiver feeding practices differed by household food security status in a diverse sample of infants. United States Paediatric clinics in academic teaching hospitals N = 842 2.3 (0.4) months 51% female N = 842 96% mothers, 4% father 28% black (non-Hispanic),18% white, 50% Hispanic, and 4% other. 43% food insecure. 2-item household food security screener [76] IFSQ—15 items [37] Feeding practices differed by HFI status. Food-insecure households had increased odds of agreeing with some obesity promoting practices such as immediately feeding a baby when they cry. Orr et al. 2020 [57] To examine associations between HFI status and parental feeding behaviour, weight perception, and child weight status in a diverse sample of young children United States Primary care paediatric residency training sites N = 503 25 (1.3) months 49% Male, 51% Female N = 503 52% Latino, 29% Black, 15% White, and 4% other. 37% food insecure 2-item household food security screener [76] CFQ—31 items [34] Parents with HFI reported more pressuring feeding behaviours and were more concerned about children becoming overweight. Perez et al. 2018 [52] To examine measurement equivalence of the CFQ and CEBQ across key contextual factors that influence paediatric obesity (gender, ethnicity, food security). United States paediatrician offices, day care centres, preschools, local shops or businesses frequented by families N = 243 4.8 (0.85) years 51% male healthy 66.7%, overweight 23.8%, obese 9.5% N = 243 70% mothers 33.6% Latino 30% food insecure 18-item USDA HFSSM [77] CFQ 28 [34] Both measures need continued psychometric work; group comparisons using some subscales should be interpreted cautiously. Subscales such as food responsiveness and restriction may be assessing behaviours that are less applicable in the context of HFI. Pesch et al. 2016 [53] To determine the association of child weight status with maternal pressuring or restricting eating prompts with four different types of food. United States Head Start N = 222 70.9 months (8.53) 49.1% male normal weight 57.66%; overweight 22.07%, obese 20.27% N = 222 White Non-Hispanic 73.42% mothers, or grandmothers 32% food insecure 18-item USDA HFSSM [77] Structured eating protocol with BATMAN coding schema [82] Mothers of children with obesity may alter their feeding behaviour differentially based on food type. Searle et al. 2020 [61] To examine associations between child temperament and parents’ structure-related feeding practices in a socioeconomically disadvantaged community. Australia Childcare centres, health clinic, family fun day, social media, newspaper N = 205 3.6 years (1.0) 2–5 years 51% male 205 mother-father pairs ATSI 5%. 50% female 50% male 13% food insecure 1-item from Australian Health Survey [78] FPSQ (three subscales) [36] Perceptions of child food fussiness may explain why parents use less structure at mealtimes with children who have more difficult temperaments. Trappmann 2015 [64] To examine the relationship between HFI, childhood overweight, feeding behaviours, and use of federal public assistance programs among Head Start children from rural Hispanic and American Indian community. United States Head Start Centres N = 374 47.71 months 97.73) 51% male BMI percentile 64.42 (26.91) N = 374 77% mothers, 10% fathers, and 13% other caregivers Hispanic and Native American 21% food insecure 1 Item uncited question: Do you ever feel that you don’t have enough food for your family? Control/pressure Study specific items No significant relationships emerged between HFI and child overweight/obesity, certain feeding behaviours, or public food assistance utilisation. Further research is needed to understand these relationships. Zhou et al. 2020 [54] To test controlling parental feeding practices as mediating mechanisms by which child appetitive traits are linked to weight in an economically and ethnically diverse sample of children. United States Paediatricians’ offices, day care centres, preschools, local businesses. N = 139 4.77 (0.84) years 51.8% male mean BMI: 16.47 (2.06) N = 139 mothers 38.1% at or below the poverty line Hispanic 43.9%, European American 33.1%, African American 20.1%, Asian American 2.9%. 0% food insecure 18-item USDA HFSSM [77] CFQ (pressure to eat and restriction subscales) [34] Child appetitive traits are linked to child BMI through restrictive feeding or pressure to eat. Parents living in poverty endorsed higher levels of pressure to eat than those not in poverty. Qualitative Blaine et al. 2016 [42] To describe low-income pre-schoolers’ snacking and TV viewing habits, including social/physical snacking contexts, types of snacks and caregiver rationales for offering snacks. United States SNAP for WIC offices, playgrounds, Head Start centres and online Target age = 3–5 years characteristics of children NR N = 47 31.2(9.2) years 89% mothers 6% fathers 34% white, 34% African American, 32% Hispanic/Latino 47% food insecure 6-item USDA HFSSM [73] Pressure; structure semi-structured interview TV viewing and child snacking themes were consistent across racial groups. Caregivers facilitate snacking and TV viewing, which are described as routine, positive and useful. Davison et al. 2015 [55] To examine food parenting practices specific to child snacking among low-income caregivers. United States SNAP for WIC and online community listings such as craigslist Target age = 3–5 years characteristics of children NR N = 60 31.2 years (8.4) 92% mother, 5% father 30% non-Hispanic white, 37% African American, 33% Hispanic 43% food insecure 18-item USDA HFSSM [77] control, structure, autonomy support, permissiveness. Semi-structured interview Permissive feeding was added to the model. The conceptual model includes 4 feeding dimensions including autonomy support, coercive control, structure and permissiveness. Fisher et al. 2015 [43] To qualitatively describe low-income, urban mothers’ perceptions of feeding snacks to their preschool-aged children. United States SNAP for women, infants, and children (WIC) 51 months (37–66 months) female 47% N = 32 27.5 years (20–41) mothers 91 % Black, 9% other, non-white 22% food insecure 6-item USDA HFSSM [73] Structure and control Focus group Mothers may perceive snacks as more important in managing children’s behaviour than providing nutrition. Snacks have a powerful hedonic appeal for mother and child. Gross et al. 2019 [46] To learn more about the financial pressures and perceived effects on infant and toddler feeding amongst low-income Hispanic mothers with children in infancy and toddlerhood. United States Large urban public hospital N = 100 3 - 24 months old N = 100 30 (6) years mothers 87% born outside of US 87% Spanish speaking 91% WIC participants 67% food insecure 10-item USDA HFSSM [77] Restriction Semi-structured interview HFI was frequently experienced, dynamic, complex and contributed to feeding beliefs, styles, and practices. Potential strategies—addressing misconceptions about maternal diet and breast milk, stress management, building social support, and connecting to assistance. Gross et al. 2021 [47] To understand how maternal stress, sadness, and isolation are perceived to affect feeding, to inform modifiable targets of interventions. United States large urban public hospital N = 32 5.1 months (1.4) (3–7 months) N = 32 29.3 years (6.6) Hispanic mothers 25% food insecure 10-item USDA HFSSM [77] maternal-infant feeding interactions, laissez-faire, pressure to eat, infant emotions Interview Maternal stress was perceived to negatively affect infant feeding. Mothers reported disrupting healthy feeding to avoid infant exposure to stress (including reduced breastfeeding). Herman et al. 2012 [44] To understand the contextual factors that influence how low-income mothers felt about addressing behavioural targets and mothers’ aspirations in child feeding. United States SNAP for WIC N = 32 50.9 (36.9–65.9 months)47% female N = 32 27.5 (20–41) years mothers 91% Black, 9% non-white 22% food insecure. 6-item USDA HFSSM [73] Structure Focus group Mothers’ aspirations in feeding were compatible with obesity prevention strategies to limit portion size and intake of fats/sugars. Mothers faced many feeding challenges. Tartaglia et al. 2021 [65] To explore parents’ experiences of feeding 0–5-year-old children and food literacy behaviours. Australia Parent-focused organisations in disadvantaged areas N = 87 59.4% ≤ 2 years, 40.5% 3–5 years N = 67 34 years (median) 92.5% parent, 4.5% grandparent, 3% guardian 92.5% female 22.4% ATSI NR HFI theme emerged from focus group discussion Structure Focus group Ten themes emerged and aligned with domains of relatedness, autonomy, and competence within self-determination theory. Parents were motivated to provide nutritious foods but faced many challenges. NR = not reported; HFI = household food insecurity/insecure; FS = food security/secure; USDA HFSSM = United States Department of Agriculture Household Food Security Survey Module; SNAP = Special Supplemental Nutrition Program; BMI = body mass index; CEBQ = child eating behaviour questionnaire; WIC = women, infants, children. Feeding practice measurement tools: ATSI = Aboriginal or Torres Strait Islander; CFSQ = Caregiver’s Feeding Style Questionnaire; IFSQ = Infant Feeding Style Questionnaire; CFQ = Child Feeding Questionnaire; TFBQ = Toddler Feeding Behaviour Questionnaire; FPSQ = Feeding Practices and Structure Questionnaire; FFBS = Family Food Behaviour Survey; CFPQ = Comprehensive Feeding Practice Questionnaire. ijerph-19-05604-t003_Table 3 Table 3 Studies describing an intervention to modify feeding practices amongst families living with HFI, low income or disadvantage (n = 12). First Author, Date Name of INV Study Design Description of Intervention Length of INV Mode of Delivery Target Audience Primary Outcome Measure/s Tool Used Results Key Components Black, 1997 [68] “Feeding Your Baby with Love” RCT A video including messages, title, music, and setting were designed by an advisory group of 6 African American adolescent mothers who were filmed feeding their infants in their homes. 2 weeks 1 × 15-min video provided to participants to take home N = 59 (INV = 26; Ctrl = 33) low-income, mothers 16.9 (1.3) years infants < 13 months 97% still in school 85% receive WIC African American Attitudes toward feeding Maternal communication during mealtime At 2 weeks About Your Child’s Eating (52-item questionnaire) [83] Parent–child interaction assessment [84] INV mothers were more involved with their infant and reported more favourable attitudes toward feeding and communication Culturally sensitive; adolescent mothers developed the vignettes and messages themselves, health professionals supported; realistic Fiks, 2017 [58] “Grow2Gether” RCT Private Facebook group INV commenced at 2 months prenatal until infant 9 months; video-based curriculum; foster behaviours promoting healthy parenting and infant growth. Moderated by a psychologist 11 months Online social media group with short video curriculum posted weekly. Groups of 9–13 women N = 87 (INV = 43; Ctrl = 44) low-income mothers 26.5 (5.4) years recruited when pregnant 42% food insecure Medicaid insured 80% African American Maternal-infant feeding practices At 11 months IFSQ—10 items [37] INV reported significantly healthier infant feeding behaviours. INV mothers had higher healthy feeding behaviour scores; were less likely to pressure child to finish food. No differences in infant feeding beliefs or the timing of solids introduction. Peer-group approach favoured by participants; high engagement (participants posted 30 times per group per week on average) Fisher, 2019 [85] “Food, Fun, and Families (FFF)” RCT Parenting INV aimed to reduce child consumption of empty calories from solid fat and added sugar (SoFAS). Content guided by authoritative food parenting theory; emphasised structure and autonomy support in feeding 12 weeks 12 in-person group sessions (60 min) of 8–12 mothers over 12 weeks Used behavioural change techniques e.g., goal setting and planning N = 119 (INV = 59; Ctrl = 60) low-income mothers 29.8 (7.1) years children aged 3–5 years income qualified to receive SNAP 91% African American Child measures: daily energy intake SoFAS post-test Authoritative food parenting practices At 12 weeks 24 h food recall Meal observations in a lab setting (study specific protocol) FFF children consumed ~23% less daily energy from SoFAS than control group, adjusting for baseline levels. FFF mothers displayed a greater number of authoritative parenting practices when observed post-intervention. FFF sessions were pilot tested with 9 women from a similar background. Horodynski, 2005 [86] “Nutrition Education aimed at Toddlers (NEAT)” Quasi-experimental Caregiver INV designed to improve caregiver-toddler mealtime interactions by empowering adults to become responsive to the child’s verbal and non-verbal behaviours 6 months 4 in-person group nutrition lessons (90 min) + 18 individual sessions (delivered by an EHS home visitor) N = 135 (43 INV, 53 control) mean age 26 years (17–45), low-income mothers (92%); Caucasian (84%) Child and parent mealtime behaviours At 6 months Adapted child eating behaviour Inventory [87] The feeding self-efficacy questionnaire (8 items) (uncited) INV showed higher knowledge scores. No statistically significant differences were found for measures of child and parent meal behaviours. Suggests looking at other avenues to enhance parents’ feeding practices. After group sessions toddlers joined caregivers in food tasting, simple food preparation and family eating time. Hughes, 2020 [69] “Strategies for Effective Eating Development (SEEDS)” RCT Post Test Results Multicomponent family-based obesity prevention INV. Promotes self-regulation and healthy food preferences in low-income Hispanic children. Included parental strategies to promote appropriate portion sizes, structure, and routines, and dealing with outside influences on child eating. Curriculum informed by self-determination theory 7 weeks 7 in-person group lessons over 7 weeks. 8-10 mother–child dyads in each group. Videos and experiential learning activities reinforce the information. N = 255 (136 INV and 119 control) 32.9 (6.8)–33.8 (7.3) years mothers children aged 3–5 years, children attending Head Start childcare Hispanic Feeding knowledge/practices/styles (parent) BMI, eating self-regulation, trying new foods, fruit/vegetable consumption (child) Parent: feeding knowledge survey, FPI [88], CFSQ [7] Child: compensation trials [89]; EAH [90], CEBQ [91]; willingness to try new foods (observation) [92,93] FPQ [94] weight (BMI) Short-term post test results showed change in maternal feeding behaviours and knowledge, understanding feeding misconceptions and child roles in eating, and achieving feeding efficacy. Effects on child eating behaviour were minimal. Experiential approach led to significant changes in behaviours; engagement was high, almost three quarters attended 5, 6, or all 7 of the lessons. Hughes, 2021 [70] “Strategies for Effective Eating Development (SEEDS)” RCT 6- and 12-month results As above 7 weeks As above As above As above   As above INV had significant improvements in repeated exposure of new foods, measured portion sizes, child involvement in food prep, feeding responsiveness, knowledge of best feeding practices, and feeding efficacy, reduced feeding misconceptions and uninvolved feeding. Effects on child eating behaviour were minimal. At 12 months, children were less likely to be overweight/obese. Outcome data at 6 and 12 months showed maintained improvement in key outcomes. Facilitators promoted a learner-based approach rather than a didactic one. Group session were pilot tested. Videos showed diversity Kugler, 2016 [95] Fractional factorial design Evaluation utilised multiphase optimisation strategy (MOST) to assess feasibility of a responsive parenting INV to prevent child obesity in low-income mothers with/without depression. Participants were randomised to 1 of 16 conditions using a factorial design with 8 components: responsive feeding (RF) (all participants), parenting, portion size, obesogenic risk assessment, mealtime routines, RF counselling, goal setting, mobile messaging, and social support Length varied based on allocation Up to 4 weeks INV was remotely delivered. RF and parenting curriculum (mail); portion size guidance (mail); obesogenic risk assessment (phone); personalised mealtime routine (phone); RF counselling (phone); social support (phone); mobile texts + videoes; Goal setting: (mail + phone) N = 107 (n = 45) with and without (n = 62) depressive symptoms low-income mothers 29.2 years child aged 12 to 42 months participating in WIC 85% white, 8% Black, 5% Hispanic Feasibility and acceptability of the intervention components and feasibility of implementing a factorial study design as part of a pilot study Completion rates for each INV component; participant feedback on components (post-test interview) Completion rates were high (85%) and did not statistically differ by depressive symptoms. All INV components were feasible to implement except for social support. Most participants reported the INV increased awareness of what, when, and how to feed their children. MOST provided an efficient way to assess the feasibility of components prior to testing with a fully powered experiment. 20% of participants receiving texts could not open the video messages sent INV primarily delivered by one research staff trained in health education Maher, 2010 [67] “Family Lifestyle Assessment of Initial Risk (FLAIR)” Qualitative study- content analysis A primary care obesity prevention INV targeting low-income minority parents. Identified family health risks and habits. Clinicians were trained in a patient-centred approach to deliver targeted brief behaviour change messages and set goals aligned with parents’ concerns. NR INV was delivered face to face alongside routine visits for paediatric patients. Supported by access to a health educator who provided brief behaviour change lifestyle counselling. N = 83 low-income minority parents % mothers NR 92% Medicaid recipients child aged 24–59 months 26% of children were overweight/obese 80% Hispanic; 17% African American Barriers to behaviour change experienced by families Strategies were to empower families to engage in healthy behaviour change. Content analysis of health educator documents (FLAIR goal setting forms + action plans; clinical notes) Themes were poor parenting skills (picky eating, food tantrums, bottle feeding, submitting to food requests), poor knowledge and skills regarding healthy eating, psychosocial issues (housing issues, parental unemployment, and intergenerational conflict regarding food choices). A skilled, culturally competent, health educator is essential. Family focused approach. INVs need to be prepared for the degree of psychosocial difficulty that families face Messito, 2020 [50] “Starting Early Program (StEP)” RCT A primary care child obesity prevention INV for low-income, Hispanic families beginning in pregnancy through to child aged 3 years. Addressed feeding, activity, and general parenting. 3 years This paper reports at 10 months Face-to-face individual nutrition counselling + nutrition and parent support groups coordinated with primary care visits. Content was developed for low health literacy, used picture-based messaging N = 412 Low-income mothers control: 28.8 (8.5) years; INV: 28.9 (5.9) years food insecure 30% in INV; 34.5% Ctrl recruited in third trimester Hispanic families Feeding styles Feeding practices (breastfeeding, introduction of cereal, water, and juice in the bottle and juice intake, self-feeding) At 10 months IFSQ [37], Infant feeding practices study II [96] INV showed greater breastfeeding, reduced juice and cereal in the bottle, and increased family meals than controls. INV had higher knowledge and lower nonresponsive feeding styles. High attendance at sessions. Utilising primary care provided access to high-risk families; built on-existing provider relationships; reduced costs; saved time Moore, 2018 [71] Non-experimental pre-test post-test design A novel home-based motivational interviewing intervention to improve food parenting practices of low-income mothers with preschool-aged children. 5 food parenting practices: ‘pressure to eat’, ‘food as a reward’, ‘involvement’, ‘environment’, and ‘modelling’ were targeted 6 weeks 3 home face-to-face sessions approx. 2 weeks apart. At session 1 a family mealtime was videoed. Session 2 mothers watched segments of the video that included the targeted feeding practices to discuss and plan to improve these practices. N = 15 mothers 32.3 (4.6) years child mean age = 3.2 years (0.9) low income Participate in WIC 86.7% white (mothers) 66.7% white (child) Food parenting practices 5 subscales from the CFPQ [35] The Family Mealtime Coding System (video recorded meal) [97] Mothers reported improvements in food parenting practices following the INV. INV had a decrease in controlling practices, ‘pressure to eat’ and ‘food as a reward’ and an increase in supportive practices, ‘involvement’, ‘environment’ and ‘modelling’. 93% of mothers ‘strongly agreed’ it was worth their effort to participate. Most mothers found that watching themselves on video was informative and applicable to their own lives. Childcare was provided; INV conducted at times convenient to the mother Nix, 2021 [98] “Recipe 4 Success” RCT A preventive INV featuring structured food preparation lessons, designed to improve 4 protective factors related to overweight among families living in poverty: toddlers eating habits, toddlers’ self-regulation, parents responsive feeding practices, and parents sensitive scaffolding 10 weeks 10 face-to-face weekly home lessons as part of usual EHS visits. Lessons took ~45 mins. Focused on active coaching with structured food preparation activities using 3–6 ingredients. Toddlers could participate N = 73 mothers child aged 30.72 months (6.96) months low-income families enrolled in Early Head Start 78% SNAP recipients 48% non-Hispanic white; 29% Black; and 23% Hispanic/Latino Child: healthy eating habits; self-regulation Mother: responsive feeding practices [9] and sensitive scaffolding [99] Child: 24-h food recall; snack delay task [100]; infant behaviour record [101]; infant-toddler social and emotional assessment [102] Video recordings of (1) parent introducing new foods and (2) 3 × 3 min interaction tasks INV toddlers consumed healthier meals/snacks and displayed better self-regulation. INV parents were more responsive and were better able to sensitively scaffold their toddlers’ learning and development. Showed medium to large INV effects on the 4 protective factors that are often compromised by living in poverty. Cocreated by administrators and home visitors from EHS. Used the pre-existing infrastructure of EHS for INV dissemination. Ingredients for the food preparation supplied Sun, 2017 [72] RCT pilot A family-centred, technology-based INV to improve health behaviours of low-income, overweight/obese Chinese mothers and their children. Guided by the Information Motivation Behavioural Skills Model. The INV used images, food items, and sample menus familiar to the Chinese culture. 8 weeks 8 weekly 30-min, interactive, Cantonese sessions accessed via table computers. 6 lessons were10 to 15-min animated videos; 2 lessons were a talk show format hosted by a bicultural dietitian with Cantonese speaking mothers N = 32 low-income Chinese mothers with low acculturation; basic computer/internet skills Head start participants 36 (4.9) years child aged 4.31 (0.69) years Chinese Maternal outcomes: self-efficacy, eating behaviours, physical activity, child-feeding practices, and BMI At 3 and 6 months CFQ-28 [34] The Family Eating and Activity Habits Questionnaire [103] Maternal Self-Efficacy 12-item scale (uncited) The INV was feasible. Significantly more INV mothers decreased BMI and increased their confidence for promoting healthful eating at home compared to control. Other outcomes saw small to medium improvement. There was no difference in child BMI. Tailored content. INV was adapted from previous research. Tablet provided by the INV INV created a theme song with key messages that mothers could sing to their child INV = intervention; RCT = randomised controlled trial; HFI = household food insecurity; CI = confidence interval; EHS = Early Head Start. Tools/measures: CFQ = Child Feeding Questionnaire; CFPQ = Caregiver’s Feeding Practices Questionnaire; IFSQ = Infant Feeding Style Questionnaire; CFSQ = Caregivers Feeding Styles Questionnaire; CEBQ = Children’s Eating Behaviour Questionnaire; FKQ = Feeding Knowledge Questionnaire; FPI = Food Parenting Inventory; FPQ = Food Preferences Questionnaire; EAH = eating in the absence of hunger protocol. 4. Discussion This scoping review examined the evidence related to parental feeding practices and styles in families with a young child (aged 0–5 years) experiencing socioeconomic disadvantage (with and without food insecurity)—in high income countries. After using broad search terms of socioeconomic disadvantage, of the 131 papers identified, only 27 (21%) papers were found to address the issue of household food insecurity (HFI), and only two of these papers described an intervention to support responsive feeding in families experiencing HFI. Whilst the evidence on the direct impact of food insecurity on parental feeding practices is scant, the literature suggests that it does likely influence how and what parents feed their children. Parental feeding practices are sensitive to factors which influence the feeding environment such as food insecurity and, therefore, such factors are important to consider in parental feeding practice research and intervention design. This review identified the most common measures used to assess feeding practices and styles, though there was little evidence that the validity and reliability of these tools have been assessed amongst families experiencing HFI. The practices most frequently assessed—pressure to eat and restriction—fall within the higher order construct known as ‘coercive control’, while fewer studies assessed ‘structure’ related feeding practices. In the future, studies could assess the aspects of structure to better elucidate the relationship between HFI, household chaos and a family’s ability to implement responsive feeding practices. Very few papers examined practices related to ‘autonomy support or promotion’. While the reasons for this cannot be determined from the review, it may be that practices such as educating children about the benefits of healthy eating or child involvement in meal planning and preparation may be considered less applicable in children under the age of five years. Variation in the tools used to measure HFI makes describing and comparing HFI amongst populations challenging and there are calls for greater consistency in measuring food insecurity [24,104]. This was reflected in this review, which found significant variation in the measures used to describe HFI. Several studies used short 1- or 2- item measures (7/27, 36%). Whilst these measures provide an indication of HFI levels, they may be less reliable and may also underestimate HFI by 5–8% points when compared to more rigorous, multi-item tools [104,105]. The most used HFI measure was the 18-item United States Department of Agriculture Household Food Security Survey Module (USDA HFSSM), which was the predominant tool cited in the literature [105,106]. The 18-item USDA HFSSM includes eight child-related items and therefore may be the most relevant in the context of parental feeding practices and HFI research which focuses on child-related outcomes. In this review 8/27, 30% of the papers used the 18-item USDA HFSSM which includes the child specific items. The short form (6-item) and 10-item form USDA HFSSM were also found to be used among 9/27 (33%) of the included papers. Studies balance the burden of administering tools and surveys to their participant group and therefore may opt for shorter measures of HFI; however, choosing measures that account for HFI severity and allow for child specific measures may be advantageous in parenting feeding practice research, especially in the context of socioeconomic disadvantage where the prevalence of HFI is likely to be high. In addition, the degree of severity of HFI may influence the type and frequency of feeding practices used at any given time. Another strong feature of the parental feeding practices and socioeconomic disadvantage/HFI literature summarised here is the heavy representation of US populations, which commonly draw on Head Start/Early Head Start and SNAP programs for recruitment. Studies conducted in the United States also tend to have a high proportion of Hispanic, Latina and/or African American participants. Perceptions of ideal body size, appropriate meal-time practices and family traditions vary across culture, and conceptualisations of “ideal” feeding practices in the scientific literature may clash with culture and community [107]. This may reduce the applicability of research findings to other countries or social and government assistance contexts outside of the US. Given that high-income countries, outside of the US, have evidence of significant HFI among their population, particularly in disadvantaged groups, this is of note and indicates the need for further research into HFI in other high-income countries. Whereas the US has readily identifiable groups among their population to recruit for research purposes (e.g., SNAP and Head Start), recruitment for such studies can be challenging in other countries due to the difficulty in identifying and successfully recruiting socioeconomically disadvantaged groups. In addition, food insecurity is monitored annually in the USA and has been identified as a significant public health issue, thus potentially highlighting it as an area of concern [108]. Further research may therefore also be warranted identifying successful avenues to recruit disadvantaged and HFI groups, which may also facilitate further research in this area. A recent narrative review of parent feeding practices in the context of food insecurity identified no existing interventions that target parent feeding practices specifically addressing the context of food insecurity [27]. Our scoping review of the literature supports this finding and whilst two interventions were identified which reported HFI, only one of those appeared to take into account the poverty related challenges of food insecurity [50]. This review adds to the evidence by identifying some of the key features and characteristics of interventions targeting feeding practices in disadvantaged groups. The intervention studies identified in this review showed largely positive improvements in the parent and child outcomes measured subsequent to participation in the intervention. A key feature identified in the interventions summarised was the high use of visual media content. Video and/or images are often used to convey messages to low health literacy groups. A systematic review has identified that pictorial information improves understanding and recall and is most impactful in the lowest health literacy groups [109]. Black and Teti (1997) developed a video which featured mothers from their target population, i.e., low-income adolescent African American mothers [68]. The video content, messaging and music was developed by an advisory panel of six African American adolescent mothers who were featured in the footage in their own homes feeding their babies. This culturally sensitive approach enhances the relatability of the messages. Other studies also adapted intervention content for their specific audience, including Sun et al. (2017) who developed an intervention for Chinese immigrant mothers and included videos in Cantonese featuring Chinese mothers with their children, including images, sample menus and foods which were also tailored to the Chinese culture [72]. Hughes et al. (2021) reporting on the intervention, ‘Strategies for Effective Eating Development (SEEDS)’, also utilised short videos in their face-to-face group sessions [70]. Videos can also be used in interventions to moderate the content and direct the conversation to targeted positive parent behaviours, such as in the ‘Grow2Gether’ intervention by Fiks et al. (2017)—an online social media group-based intervention that encouraged participation and discussion among peer mothers [58]. Videos were posted on closed social media groups, which acted to deliver positive feeding messages as well as to be a catalyst for productive discussion among participants around the content. Short, realistic, and relatable videos and media may be a successful feature to incorporate into interventions targeting parents from low income, disadvantaged backgrounds. The summarised interventions also demonstrated that a range of modes of delivery can be successful in this group, including traditional approaches of intensive face-to-face individual or group delivery of nutrition-based information, to remote modes of intervention delivery (i.e., video, mailed content, social media, and technology-based interventions). This is important given the context of COVID-19 impacting health service delivery and the engagement with families of young children [110]. Traditional, intensive, face-to-face interventions may not be practical or feasible in a post-COVID-19 environment and it may take some time until families are willing or able to attend such intensive face-to-face interventions. It is also important to note that the one intervention that showed no positive impact on parent behavior, Horodynski et al. (2005), was the most intensive of the interventions described with 4 group sessions and 18 individual home visits over 6 months [66]. This suggests that interventions need to move beyond intensive face-to-face sessions and instead implement multi-modal strategies to engage families. This scoping review also identified aspects from the summarised papers that reported HFI (n = 27) that may be potential areas to explore or target in interventions. Some of the studies highlighted different strengths within families that could potentially protect parental feeding practices from the negative impact of HFI. Food resource management (FRM) skills is one area that could be further explored. McCurdy et al. (2014) showed that better FRM skills and parental presence at meals was associated with healthier weight among 2–5-year-old children in low-income families. The potential pathway between FRM skills and healthier child weight needs to be further elucidated, but the mechanisms suggested by McCurdy et al. (2014) may reduce takeaway consumption due to more home cooking, parent modelling of healthy eating, as well as an increased structure in feeding practices, e.g., more family meals and parent presence at mealtimes. The potential role of FRM skills was also described in Na et al. (2021), which reported that low FRM skills were associated with suboptimal child feeding with and without HFI. In this paper, parents in food insecure households who had high FRM skills used similarly positive feeding practices as parents from food secure households with high FRM skills [51]. Kamdar et al. (2019) also suggests that families may use coping strategies which may mitigate the negative consequences of HFI. This paper found that dietary quality improved over 18 months in HFI families which was unexpected and needs further research but may indicate the adoption of coping strategies among families [41]. These findings, although requiring further exploration and research, may suggest how interventions can be designed to incorporate the strategies and coping mechanisms families who are at high risk of HFI already use to mitigate the negative impact of HFI on their feeding practice. It is also important to note that all the interventions identified within this review focused on individual behaviour change strategies, particularly that of mothers. This approach has been criticised for placing the responsibility for a child’s health solely on the mother and failing to advocate for structural interventions (e.g., policy change) to support parent feeding practices [111]. Researchers and practitioners are encouraged to utilise a socioecological model to intervene across systems for maximum impact [24]. This review has several strengths. It followed best practice guidelines using an a priori protocol. Due to the inconsistency of terminology used in the literature to describe feeding practices and styles, a deliberate decision was made to use broad search terms to identify as many papers as possible; however, given that some included studies (e.g., qualitative studies employing interview or focus group methodologies) did not set out to assess or describe HFI and feeding practices or styles, but these issues were raised by participants and reported in the results, it is possible that similar papers were not identified and included. This should be considered as a limitation. 5. Conclusions This scoping review highlights the lack of research at the crossover of parental feeding practices and food insecurity, especially in terms of interventions that target feeding practices among groups likely to have a high prevalence of food insecurity. More research is needed outside of the United States, with an emphasis on comprehensive and valid measures of HFI and feeding practices. Intervention design should be sensitive to factors associated with poverty, including food insecurity. Acknowledgments The assistance of Peter Sondergeld, Liaison Librarian for the School of Exercise of Nutrition Sciences at the Queensland University of Technology is greatly appreciated. Author Contributions Conceptualisation and methodology, all authors; literature search, K.A.B. and S.N.; title and abstract, and full-text screening, all authors; data extraction, K.A.B., S.N., T.H.J.S. and R.B.; writing—original draft preparation, K.A.B., S.N. and R.B.; writing—review and editing, K.A.B., S.N., T.H.J.S. and D.G.; funding acquisition, R.B., S.N. and D.G. 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 WCCNR is funded by Woolworths through the Children’s Hospital Foundation. Woolworths has not been involved in the design or conduct of the research or in the evaluation of the scientific quality of the research projects or in the establishment of the Centre governance. Appendix A ijerph-19-05604-t0A1_Table A1 Table A1 Key words for the search strategy used in each database. Database/ Platform Term 1 Parent/Child Term 2 Feeding Term 3 Food Insecurity Medline (via EBSCOhost) Keyword: Parent * Mother * maternal caregiver * father * Child * Infant * baby MeSH: child father-child relations father mother-child relations parents mothers maternal behaviour parent-child Relations Keyword: Feeding “Complementary feeding” weaning “eating behaviour” “food preferences” MeSH: feeding methods infant food eating weaning food preferences Keyword: “Food insecur *” “Food secur *” “Food shortage” “Food scarcity” “Food supply” Hunger “low income” poverty disadvantage * “food insufficiency” “low resource household” MeSH: Food Assistance Social security Food deprivation Working poor Health equity poverty PsychInfo Keyword: As above PsychInfo Thesaurus: Mothers Mother Child Communication Family Relations Father Child relations Father child communication Mother child relations Parent child relations Parental role Parents parental attitudes Parental characteristics Keyword: As above PsychInfo Thesaurus: Food Eating behavior Weaning Mealtimes Food Intake Food preferences Keyword: As above PsychInfo Thesaurus: Disadvantaged Economic Disadvantage Food Insecurity socioeconomic factors economic inequality poverty lower income level Hunger social issues social disadvantage socioeconomic status Family socioeconomic level economic resources food deprivation CINAHL Keyword: Parent * mother * Maternal Caregiver * Father * Child * Infant * baby CINAHL Terms: child father-child relations father+ mother-child relations parents+ mothers+ maternal behaviour parent-child Relations+ MM Infant Father-infant relations Mother-infant relations Parent-infant relations Keyword: Feeding “Complementary feeding” weaning “eating behaviour” “food preferences” CINAHL Terms: MM feeding methods infant food eating weaning food preferences Child Nutritional Physiology Infant Nutritional Physiology infant feeding eating behavior Keyword: “Food insecur *” “Food secur *” “Food shortage” “Food scarcity” “Food supply” Hunger “low income” poverty disadvantage * “food insufficiency” “low resource household” “working poor” CINAHL Terms: Food Assistance Food Security Economic and Social Security Poverty Poverty areas Appendix B. List of Included Papers in the Scoping Review Agrawal T, Farrell TJ, Wethington E, Devine CM. “Doing our best to keep a routine:” How low-income mothers manage child feeding with unpredictable work and family schedules. Appetite. 2018;120:57–66. Anderson CB, Hughes SO, Fisher JO, Nicklas TA. Cross-cultural equivalence of feeding beliefs and practices: the psychometric properties of the child feeding questionnaire among Blacks and Hispanics. Preventive medicine. 2005;41(2):521–531. Arlinghaus KR, Hernandez DC, Eagleton SG, Chen T-A, Power TG, Hughes SO. Exploratory factor analysis of The Comprehensive Feeding Practices Questionnaire (CFPQ) in a low-income hispanic sample of preschool aged children. Appetite. 2019;136:N.PAG-N.PAG. Arlinghaus KR, Vollrath K, Hernandez DC, Momin SR, O’Connor TM, Power TG, et al. Authoritative parent feeding style is associated with better child dietary quality at dinner among low-income minority families. The American journal of clinical nutrition. 2018;108(4):730–736. Armstrong B, Hepworth AD, Black MM. Hunger in the household: Food insecurity and associations with maternal eating and toddler feeding. Pediatric obesity. 2020:e12637. Barrett KJ, Thompson AL, Bentley ME. The influence of maternal psychosocial characteristics on infant feeding styles. Appetite. 2016;103:396–402. Barroso CS, Roncancio A, Moramarco MW, Hinojosa MB, Davila YR, Mendias E, et al. Food security, maternal feeding practices and child weight-for-length. Applied nursing research: ANR. 2016;29:31–36. Bauer KW, Haines J, Miller AL, Rosenblum K, Appugliese DP, Lumeng JC, et al. Maternal restrictive feeding and eating in the absence of hunger among toddlers: a cohort study. The international journal of behavioral nutrition and physical activity. 2017;14(1):172. Baughcum AE, Burklow KA, Deeks CM, Powers SW, Whitaker RC. Maternal feeding practices and childhood obesity: a focus group study of low-income mothers. Archives of pediatrics & adolescent medicine. 1998;152(10):1010–1014. Baughcum AE, Powers SW, Johnson SB, Chamberlin LA, Deeks CM, Jain A, et al. Maternal feeding practices and beliefs and their relationships to overweight in early childhood. Journal of developmental and behavioral pediatrics: JDBP. 2001;22(6):391–408. Beck AL, Hoeft KS, Takayama JI, Barker JC. Beliefs and practices regarding solid food introduction among Latino parents in Northern California. Appetite. 2018;120:381–387. Bekelman TA, Bellows LL, Clark L, Thompson DA, Kemper G, McCloskey ML, et al. An Ecocultural Perspective on Eating-Related Routines Among Low-Income Families With Preschool-Aged Children. Qualitative health research. 2019;29(9):1345–57. Berg J, Tiso S, Grasska M, Tan E, Chowdhury Y, Zender R, et al. Obesity, Parent Perceptions, Child Feeding, and Food Security in First Generation Hispanic Families. Californian Journal of Health Promotion. 2013;11(3):86–92. Berge JM, Miller J, Veblen-Mortenson S, Kunin-Batson A, Sherwood NE, French SA. A Bidirectional Analysis of Feeding Practices and Eating Behaviors in Parent/Child Dyads from Low-Income and Minority Households. The Journal of pediatrics. 2020;221:93. Black MM, Teti LO. Promoting mealtime communication between adolescent mothers and their infants through videotape. Pediatrics. 1997;99(3):432–437. Blaine RE, Fisher JO, Blake CE, Orloski A, Younginer N, Bruton Y, et al. Conditioned to eat while watching television? Low-income caregivers’ perspectives on the role of snacking and television viewing among pre-schoolers. Public health nutrition. 2016;19(9):1598–1605. Branscum P, Lora KR. Development and Validation of an Instrument Measuring Theory-Based Determinants of Monitoring Obesogenic Behaviors of Pre-Schoolers among Hispanic Mothers. International journal of environmental research and public health. 2016;13(6). Cartagena D, McGrath JM, Linares AM. Associations between Introduction of Age-Inappropriate Foods and Early Eating Environments in Low-Socioeconomic Hispanic Infants. Journal of pediatric health care: official publication of National Association of Pediatric Nurse Associates & Practitioners. 32(2):e27–e36. Corbett KS. Explaining infant feeding style of low-income black women. Journal of pediatric nursing. 2000;15(2):73–81. Cross MB, Hallett AM, Ledoux TA, O’Connor DP, Hughes SO. Effects of children’s self-regulation of eating on parental feeding practices and child weight. Appetite. 2014;81:76–83. Davison KK, Blake CE, Blaine RE, Younginer NA, Orloski A, Hamtil HA, et al. Parenting around child snacking: development of a theoretically-guided, empirically informed conceptual model. The international journal of behavioral nutrition and physical activity. 2015;12:109. Elias CV, Power TG, Beck AE, Goodell LS, Johnson SL, Papaioannou MA, et al. Depressive Symptoms and Perceptions of Child Difficulty Are Associated with Less Responsive Feeding Behaviors in an Observational Study of Low-Income Mothers. Childhood obesity (Print). 2016;12(6):418–425. Fiks AG, Gruver RS, Bishop-Gilyard CT, Shults J, Virudachalam S, Suh AW, et al. A Social Media Peer Group for Mothers To Prevent Obesity from Infancy: The Grow2Gether Randomized Trial. Childhood obesity (Print). 2017;13(5):356–368. Fisher JO, Serrano EL, Foster GD, Hart CN, Davey A, Bruton YP, et al. Title: efficacy of a food parenting intervention for mothers with low income to reduce preschooler’s solid fat and added sugar intakes: a randomized controlled trial. The international journal of behavioral nutrition and physical activity. 2019;16(1):6. Fisher JO, Wright G, Herman AN, Malhotra K, Serrano EL, Foster GD, et al. “Snacks are not food”. Low-income, urban mothers’ perceptions of feeding snacks to their preschool-aged children. Appetite. 2015;84:61–67. Galindo L, Power TG, Beck AD, Fisher JO, O’Connor TM, Hughes SO. Predicting preschool children’s eating in the absence of hunger from maternal pressure to eat: A longitudinal study of low-income, Latina mothers. Appetite. 2018;120:281–286. Goldthorpe J, Ali N, Calam R. Providing healthy diets for young children: the experience of parents in a UK inner city. International journal of qualitative studies on health and well-being. 2018;13(1):1490623. Gomel JN, Zamora A. English- and Spanish-speaking Latina mothers’ beliefs about food, health, and mothering. Journal of immigrant and minority health. 2007;9(4):359–367. Goodell LS, Johnson SL, Antono AC, Power TG, Hughes SO. Strategies Low-Income Parents Use to Overcome Their Children’s Food Refusal. Maternal and child health journal. 2017;21(1):68–76. Gross RS, Brown NM, Mendelsohn AL, Katzow MW, Arana MM, Messito MJ. Maternal Stress and Infant Feeding in Hispanic Families Experiencing Poverty. Academic Pediatrics. 2021. Gross RS, Mendelsohn AL, Arana MM, Messito MJ. Food Insecurity During Pregnancy and Breastfeeding by Low-Income Hispanic Mothers. Pediatrics. 2019;143(6). Gross RS, Mendelsohn AL, Fierman AH, Hauser NR, Messito MJ. Maternal infant feeding behaviors and disparities in early child obesity. Childhood obesity (Print). 2014;10(2):145–152. Gross RS, Mendelsohn AL, Messito MJ. Additive effects of household food insecurity during pregnancy and infancy on maternal infant feeding styles and practices. Appetite. 2018;130:20–28. Gross RS, Velazco NK, Briggs RD, Racine AD. Maternal depressive symptoms and child obesity in low-income urban families. Academic pediatrics. 2013;13(4):356–363. Harden J, Dickson A. Low-income mothers’ food practices with young children: A qualitative longitudinal study. Health Education Journal. 2015;74(4):381–391. Harris HA, Jansen E, Mallan KM, Daniels L, Thorpe K. Concern Explaining Nonresponsive Feeding: A Study of Mothers’ and Fathers’ Response to Their Child’s Fussy Eating. Journal of nutrition education and behavior. 2018;50(8):757–764. Harris HA, Jansen E, Mallan KM, Daniels L, Thorpe K. Do Dads Make a Difference? Family Feeding Dynamics and Child Fussy Eating. Journal of developmental and behavioral pediatrics: JDBP. 2018;39(5):415–423. Harris HA, Staton S, Morawska A, Gallegos D, Oakes C, Thorpe K. A comparison of maternal feeding responses to child fussy eating in low-income food secure and food insecure households. Appetite. 2019;137:259–266. Heinig MJ, Follett JR, Ishii KD, Kavanagh-Prochaska K, Cohen R, Panchula J. Barriers to compliance with infant-feeding recommendations among low-income women. Journal of human lactation: official journal of International Lactation Consultant Association. 2006;22(1):27–38. Herman AN, Malhotra K, Wright G, Fisher JO, Whitaker RC. A qualitative study of the aspirations and challenges of low-income mothers in feeding their preschool-aged children. The international journal of behavioral nutrition and physical activity. 2012;9:132. Hidalgo-Mendez J, Power TG, Fisher JO, O’Connor TM, Hughes SO. Child weight status and accuracy of perceived child weight status as predictors of Latina mothers’ feeding practices and styles. Appetite. 2019;142:104387. Hodges EA, Wasser HM, Colgan BK, Bentley ME. Development of FEEDING CUES During Infancy and Toddlerhood. MCN: The American Journal of Maternal Child Nursing. 2016;41(4):244-251. Hoerr SL, Hughes SO, Fisher JO, Nicklas TA, Liu Y, Shewchuk RM. Associations among parental feeding styles and children’s food intake in families with limited incomes. The International Journal of Behavioral Nutrition and Physical Activity. 2009;6. Horodynski MA, Arndt MJ. ‘Eating-together’ mealtimes with African-American fathers and their toddlers. Applied Nursing Research. 2005;18(2):106–109. Horodynski MA, Brophy-Herb H, Henry M, Smith KA, Weatherspoon L. Toddler feeding: expectations and experiences of low-income African American mothers. Health Education Journal. 2009;68(1):14–25. Horodynski MA, Brophy-Herb HE, Martoccio TL, Contreras D, Peterson K, Shattuck M, et al. Familial psychosocial risk classes and preschooler body mass index: The moderating effect of caregiver feeding style. Appetite. 2018;123:216–224. Horodynski MA, Stommel M. Nutrition education aimed at toddlers: an intervention study. Pediatric nursing. 2005;31(5):364. Horodynski MA, Stommel M, Brophy-Herb H, Xie Y, Weatherspoon L. Low-income African American and non-Hispanic White mothers’ self-efficacy, “picky eater” perception, and toddler fruit and vegetable consumption. Public health nursing (Boston, Mass). 2010;27(5):408–417. Hughes CC, Sherman SN, Whitaker RC. How low-income mothers with overweight preschool children make sense of obesity. Qualitative health research. 2010;20(4):465–478. 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Figure 2 Proportion of studies measuring feeding practices (n = 106). * Representing a variety of disparate practices which do not fit strictly within the Vaughn framework. ijerph-19-05604-t001_Table 1 Table 1 Summary of studies examining feeding practices and/or styles amongst families experiencing disadvantage, including food insecurity (N = 131). Study Characteristic % (N) Target population- Food Insecure - Low income/other measure of disadvantage   21% (27) 79% (104) Country of Origin- United States of America - Australia - United Kingdom - Germany - Chile   91% (119) 5% (6) 3% (4) 1% (1) 1% (1) Feeding style examined 31% (40) Feeding practices examined 81% (106) Type of Study Design Quantitative Cross sectional * Longitudinal Intervention Validation 43% (56) 11% (15) 8% (11) 7% (9) Qualitative Interview Focus Group Discussion Content Analysis of an Intervention Longitudinal 11% (14) 12% (16) 1% (1) 1% (1) Mixed Methods Design 6% (8) * Includes studies using direct observation of parent–child dyads, using a coding schema to quantify practices. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Satter E.M. The feeding relationship J. Am. Diet Assoc. 1986 86 352 356 10.1016/S0002-8223(21)03940-7 3950279 2. Frankel L.A. Hughes S.O. 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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/ijerph19095178 ijerph-19-05178 Article A Cross-Sectional Study on the Relationship between Oral Function and Sarcopenia in Japanese Patients with Regular Dental Maintenance Shirahase Ryuichi 12 https://orcid.org/0000-0002-4983-2399 Watanabe Yutaka 1* Saito Tohru 2 Sunakawa Yusuke 12 Matsushita Yuya 12 Tsugayasu Hideki 2 Yamazaki Yutaka 1 Rappelli Giorgio Academic Editor Tchounwou Paul B. Academic Editor 1 Gerodontology, Department of Oral Health Science, Faculty of Dental Medicine, Hokkaido University, Sapporo 060-8586, Japan; white.wave.ryu@gmail.com (R.S.); sunakawayuusuke@gmail.com (Y.S.); hpnijjq@yahoo.co.jp (Y.M.); yutaka8@den.hokudai.ac.jp (Y.Y.) 2 Medical Corporation Shuwa-Kai Tsugayasu Dental Clinic, Obihiro 080-0020, Japan; tohru_saito820@yahoo.co.jp (T.S.); sougou@tsugayasu-sika.jp (H.T.) * Correspondence: ywata@den.hokudai.ac.jp; Tel.: +81-01-1706-4582 24 4 2022 5 2022 19 9 517803 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/). We aimed to clarify the relationship between oral function assessments regarding oral hypofunction and sarcopenia in patients who had completed treatment for organic dental problems, including oral pain, removable denture fit, and tooth loss. This cross-sectional study included 269 patients aged ≥65 years (mean age 74.9 ± 6.50 years, 133 men, 136 women) who visited a dental clinic between June 2019 and March 2021. We evaluated oral function and sarcopenia and analyzed their relationship using the Jonckheere–Terpstra test, Mantel–Haenszel trend test, and Poisson regression analysis. We diagnosed 132 (49.07%) patients with oral hypofunction, 30 (11.2%) with sarcopenia, and 24 (8.9%) with severe sarcopenia. The number of oral hypofunction items (prevalence rate ratio [PRR] = 1.39, 95%Wald = 0.11 to 0.56) was significantly associated with sarcopenia. For each of the items, tongue-lip motor function [ta] (PRR = 0.80, 95%Wald = −0.44 to −0.02)] [ka] (PRR = 0.76, 95%Wald = −0.53 to −0.03) and tongue pressure (PRR = 0.95, 95%Wald = −0.09 to −0.02) showed a significant association with sarcopenia. However, no significant association was found for other variables. Dentists should not only treat organic dental problems but also consider the relationship between oral function and sarcopenia. oral hypofunction sarcopenia super-aged society organic dental problems mobility-impaired dental problems ==== Body pmc1. Introduction Oral health is well known to be related to general health and quality of life [1]. In recent years, attention has been focused on the decline in oral functions associated with aging [2]. A 2011 cohort study based on community-dwelling older people in Japan reported that poor oral function is a predictor of physical frailty, sarcopenia, disability, and death [3]. In a super-aged society, a society wherein the percentage of the population aged ≥65 exceeds 21% of the total population [4], dentistry in Japan needs to shift from “treatment-oriented” medicine, which mainly restores the form of teeth, to “treatment, management, and coordination-oriented” medicine, that aims to maintain and restore oral functions based on the patient’s life stage [4]. Oral hypofunction is defined as the development of the following seven signs and symptoms: poor oral hygiene, oral dryness, reduced occlusal force, decreased tongue-lip motor function, decreased tongue pressure, decreased masticatory function, and decreased swallowing function; additionally, oral hypofunction is diagnosed when three or more of these symptoms are present [5]. It has been included in the Japanese medical insurance system as a new disease name to promote this shift. Previous studies have shown that people with reduced oral function tend to avoid foods that are difficult to chew and are, thus, more susceptible to malnutrition [6]. It has also been reported that as oral function declines, opportunities for exercise decrease [7]. Poor nutrition and inadequate exercise are both causes of sarcopenia, and early detection and intervention are important for improving prognosis [8]. Sarcopenia is defined as “age-related loss of skeletal muscle mass, muscle strength, and/or physical performance” [9]. It is a risk factor for disability, hospitalization, death, and dementia [9]. Some previous studies have investigated the relationship between oral function and sarcopenia [10,11,12,13]. However, most of them are single oral function assessments, and only a few have investigated the relationship between poor oral function and sarcopenia using all the items of the oral hypofunction test [14,15]. Oral pain, prosthetic status for missing teeth, or the fit of removable dentures may also affect oral function assessment. However, previous studies have not considered dental diseases, such as dental caries, missing teeth, or poor fit of removable dentures in participants [3,10,11,12,13,14,15]. Kikutani defined organic masticatory disorder as a masticatory disorder caused by loss of masticatory organs due to pain in the mouth, progression of periodontal disease, and others, and mobility-impaired impaired masticatory disorder as a masticatory disorder caused by loss of oral function due to aging or disease [16]. According to him, oral problems can be broadly divided into organic problems and mobility-impaired problems. We believe that investigating the association between oral hypofunction and sarcopenia after excluding the effects of organic dental problems will further clarify that functional decline due to mobility-impaired dental problems is associated with sarcopenia. It will strengthen the evidence that declining oral function is related to general health. It also demonstrates the possibility that dental treatment aimed at maintaining and restoring oral function can contribute to general health. We hypothesized that oral hypofunction is associated with sarcopenia even in participants who are treated with restorative or prosthetic treatment for dental problems and are less affected by organic dental problems. Therefore, this study aimed to clarify the relationship between oral function assessment for oral hypofunction and sarcopenia in patients who had completed treatment for organic dental problems. 2. Materials and Methods 2.1. Design and Participants This cross-sectional study included outpatients aged ≥65 years who visited community dental clinics in a major city in northern Japan from June 2019 to March 2021. The study participants were recruited from patients who visited the clinic for regular dental maintenance every 1–3 months or who transitioned to regular maintenance after completing treatment. Treatment completion was defined as the absence of untreated caries, completion of initial periodontal treatment, occlusal support on both molars by natural or prosthetic teeth, and no complaints of difficulty in chewing. If patients complained of dental problems during regular dental maintenance, problem resolution was a priority. Patients were included in the study after satisfying the defining criterion of treatment completion. Those with impaired physical function due to comorbidities or injuries, pacemakers, and a history of head and neck cancer were excluded from the study. The contents of the study were explained to the patients verbally and in writing before written consent was obtained. The age, sex, height, weight, and comorbidities of the patients were assessed and recorded. The study included a total of 294 patients who consented to participate. However, 25 patients were excluded: 12 had difficulty walking independently, one had a pacemaker, two had difficulty measuring grip strength due to hand injury, and ten had missing data. The remaining 269 patients (mean age 74.9 ± 6.50 years, 133 men and 136 women) were considered study participants. The adjustment variables were selected in advance using a directed acyclic graph (Figure 1). This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethical Review Committee for Clinical and Epidemiological Research, Hokkaido University School of Dentistry (Approval No. 2019-4). 2.2. Survey Items Oral examination (number of functioning teeth, use of removable dentures, and oral function assessment), gait speed, grip strength, and body composition were measured. 2.3. Oral Assessment Surveys on the number of functional teeth and the use of removable dentures and oral function assessments were conducted by seven dental hygienists from clinics that had undergone prior training and standardization. The number of functional teeth was defined as the sum of the number of remaining teeth and the number of pontics in the bridge, the number of dental implants, and the number of artificial teeth in removable dentures. Teeth with only the root remaining and tooth mobility degree III were excluded from the number of functional teeth [17]. It was also confirmed that the patient had not eaten, drunk, brushed, or gargled within one hour prior to the assessment. 2.3.1. Oral Hygiene Oral hygiene was evaluated by visual examination using the tongue coating index (TCI) [18], which is an index of the degree of tongue coating. This index divides the surface of the tongue into nine areas, evaluates the degree of tongue coating in each area based on a three-point scale (score 0, 1, 2), and calculates the total score. Participants with a TCI of 50% or more (a total score of 9 or more) were defined as having poor oral hygiene. 2.3.2. Oral Dryness Oral dryness was evaluated based on the degree of oral mucosal wetness at the center of the tongue, approximately 10 mm from the tongue tip, using an oral moisture meter (Mucus, Life, Saitama, Japan) [19]. Measurements were obtained three times, and the median value was used as the measurement value. A value of less than 27.0 indicated oral dryness. 2.3.3. Occlusal Force The occlusal force was evaluated according to the number of remaining teeth. Teeth with only the roots remaining, tooth mobility degree III, bridge pontics, and dental implants were excluded from the number of remaining teeth. A decreased occlusal force was defined as less than 20 remaining teeth [5]. 2.3.4. Tongue-Lip Motor Function Participants were required to repeat the syllables [pa], [ta], and [ka] as quickly as possible within 5 s and the number of times each syllable was pronounced in 1 s was measured using an automatic measuring device (Kenko-kun Handy, Takei Kiki Kogyo, Niigata, Japan) [20]. Participants who pronounced any of the syllables less than six times were defined as having decreased tongue-lip motor function. 2.3.5. Tongue Pressure Tongue pressure was evaluated using an appropriate device (JMS Tongue Pressure Measuring Device, JMS, Hiroshima, Japan) [21]. Participants were instructed to position the hard ring part of the tongue pressure probe between the maxillary central incisors and push the pressure-receiving part (balloon) up to the palate using the tongue at the maximum force with their lips closed. For those with removable dentures, measurements were taken with their dentures inserted. Measurements were obtained three times, and the average value was used as the measurement value. A value of less than 30 kPa indicated low tongue pressure. 2.3.6. Masticatory Function Participants were required to freely chew 2 g of gummy jelly (Glucolum, G.C., Tokyo, Japan) for 20 s. They were subsequently required to rinse their mouths with 10 mL of water, and the gummies and water were spat out into a filtration mesh. The amount of glucose eluted in the solution that passed through the mesh was measured using the masticatory ability test system (Glucosensor GS-II, G.C., Tokyo, Japan) [22] to determine the concentration of eluted glucose. A glucose concentration of less than 100 mg/dL was defined as a decrease in masticatory ability. 2.3.7. Swallowing Function Swallowing function was assessed using the Seirei dysphagia screening questionnaire [23], which included 15 items. A minimum of one “A” response was defined as having decreased swallowing function. All the tests (Section 2.3.1, Section 2.3.2, Section 2.3.3, Section 2.3.4, Section 2.3.5, Section 2.3.6 and Section 2.3.7) were performed, and patients who had decreased oral function in three or more tests were diagnosed with oral hypofunction. 2.4. Sarcopenia Assessment Sarcopenia was assessed by three trained registered dietitians from the clinic, and all tests were standardized in advance. 2.4.1. Muscle Strength A Smedley grip strength meter (electronic hand dynamometer, SODIAL(R), Shenzhen, China) was used to measure the grip strength of the patients’ dominant hand. The measurements were taken twice, and the maximum value was recorded. Low muscle strength was defined as less than 28 kg for men and less than 18 kg for women. 2.4.2. Physical Performance The time required to pass a 6-m straight walking path was measured while participants were walking at a normal pace. A 1-m running section was provided before and after the measurement area. Gait speed was calculated from the measured values, and a speed of less than 1 m/s was defined as a decline in physical function. 2.4.3. Appendicular Skeletal Muscle Mass Appendicular skeletal muscle mass was measured using a body composition analyzer, InBody470 (InBody Japan, Tokyo, Japan). Skeletal muscle mass loss was defined as less than 7.0 kg/m2 in men and less than 5.7 kg/m2 in women. Based on the results from Section 2.4.1, Section 2.4.2 and Section 2.4.3, the participants were classified into three groups, including the normal, sarcopenia, and severe sarcopenia groups, according to the Asian Working Group for Sarcopenia 2019 (AWGS2019) criteria [8] (Figure 2). 2.5. Statistical Analysis The appropriate sample size was calculated using G*Power 3.1.9.7 software (Kiel University, Kiel, Germany). The effect size was set to medium, with an α error of 0.05, power of 0.80, and N2/N1 of 0.164 based on a previous study [14] that reported the prevalence of sarcopenia to be 16.4%. The required number of participants was 206. IBM SPSS Statistics 27 (IBM, New York, NY, USA) was used for statistical analyses, and the statistical significance level was set at p < 0.05 and 95%Wald, not including 1. The Kolmogorov–Smirnov normality test was performed. Kendall’s Tau-b test was conducted to evaluate the correlation between each test item in the oral function assessment. The Jonckheere–Terpstra and Mantel–Haenszel trend tests were used to investigate trends among participants in the normal, sarcopenia, and severe sarcopenia groups. The association of general health conditions (age, sex, body mass index [BMI], hypertension, diabetes mellitus, hyperlipidemia, cerebrovascular disease, malignancy, and cardiovascular disease) [3,24,25,26] with sarcopenia was investigated using Poisson regression analysis. To investigate the relationship between sarcopenia and oral hypofunction, two Poisson regression models were constructed: Model 1 was a series of univariate models with the presence or absence of sarcopenia (two groups: normal sarcopenia and severe sarcopenia) as the dependent variable, while the nine oral function assessments, diagnosis of oral hypofunction, number of oral hypofunction items, and removable denture use were used as the independent variables. In contrast, Model 2 was a multivariate model adjusted with the significant variables found in the univariate models. 3. Results According to the results presented in Table 1, which shows the number and percentage of patients for each test item, the minimum number of participants for each test item was 21 (7.8%) for masticatory function, and the maximum number was 170 (63.2%) for tongue-lip motor function. Of the 269 participants, 132 (49.07%) were diagnosed with oral hypofunction, 30 (11.2%) with sarcopenia, and 24 (8.9%) with severe sarcopenia. Table 2 shows trends in participant characteristics among the three groups. The highest incidence of oral hypofunction diagnosis and number of oral hypofunction items were observed in the severe sarcopenia group, followed by the sarcopenia group and then the normal group. Oral function tended to decrease with increasing sarcopenia severity compared to that in the normal group. Significant differences were observed in the number of remaining teeth, tongue-lip motor function [pa][ta][ka], tongue pressure, masticatory function, and swallowing function. Table 3 shows the results of the Poisson regression analysis of the association between sarcopenia and age, sex, and medical history. Significant associations were observed between age and BMI. Table 4 shows the relationship between sarcopenia and each oral function. In univariate analyses, there was a significant association between sarcopenia and the number of remaining teeth, tongue-lip motor function [pa][ta][ka], tongue pressure, masticatory function, and the number of oral hypofunction items. In the second column, Model 2, age, gender, presence of diabetes mellitus, and the presence of cerebrovascular disease were used as covariates. After selection variables were applied with the covariates, tongue-lip motor function [pa] (prevalence rate ratio [PRR] = 0.80, 95%Wald = −0.44 to −0.02) [ka] (PRR = 0.76, 95%Wald = −0.53 to −0.03), tongue pressure (PRR = 0.95, 95%Wald = −0.09 to −0.02), and number of oral hypofunction items (PRR = 1.39, 95%Wald = 0.11 to 0.56) were significantly associated with sarcopenia. 4. Discussion This study showed that the prevalence of sarcopenia was significantly higher as the number of oral hypofunction items increased in outpatients who had completed treatment for organic dental problems. This indicates an association between sarcopenia and poor oral function even in patients who receive appropriate dental treatment for organic dental problems and do not have oral pain or occlusal support deficits. Previous studies suggested an association between oral function and sarcopenia [14,15]. Kugimiya et al. conducted a study that investigated all items of oral function assessments on older people living in a community, and a significant association was observed between oral hypofunction and sarcopenia [15]. Our results support those of previous studies; however, Nakamura et al. found no significant association between oral hypofunction and sarcopenia in a study of older people living in a community [14]. In that study, subjective evaluation of masticatory ability was conducted using a questionnaire; however, it was reported that subjective and objective evaluations of masticatory ability do not always coincide [27]. In addition, these previous studies were conducted on older people living in the community and did not consider the status of dental problems, such as dental caries, missing teeth, and ill-fitting removable dentures, which may have been affected by oral pain and loss of occlusal support. To our knowledge, this is the first study showing the relationship between oral function and sarcopenia by conducting a full assessment of oral hypofunction in patients who had completed treatment for dental diseases and were less affected by organic dental problems. Ikebe et al. reported that oral hypofunction is present in 40–50% of older community residents [28]; the present study results were similar (49.1%). Regarding sarcopenia, a study conducted using the AWGS2019 in older people living in the community reported that 14.4% had sarcopenia, and 4.2% had severe sarcopenia [15]. Although this study had a biased population as it included patients from a single dental clinic, the prevalence of oral hypofunction and sarcopenia was comparable to that of previous studies. In addition, the oral problems of the present study participants were treated following a consistent policy. Conservative treatment was performed for defective tooth structure and prosthodontic treatment for tooth loss. Oral hygiene was also managed by dental hygienists who had received the same in-office training. The number of functional teeth was 27.53 ± 1.01. When compared to a previous study of older people living in the community [29], the present study showed that the number of functional teeth was close to the mean but with a smaller standard deviation. In this study, only 7.8% of patients had decreased masticatory function, a proportion which is small compared to those observed in a previous study [28]. Therefore, we believe that the present study participants were less affected by organic dental problems than those in previous studies [14,15], and this is a characteristic of this study. Focusing on each item of oral function assessment, the tongue-lip motor function and tongue pressure were significantly related to sarcopenia. The relationship between tongue-lip motor function and sarcopenia, and between tongue pressure and sarcopenia have already been reported in a previous study [11], consistent with our results. In this study, oral hygiene, oral dryness, number of remaining teeth, masticatory function, and swallowing function were not significantly associated with sarcopenia. Specifically, oral hygiene was not significantly associated with sarcopenia because the participants in this study received oral hygiene instructions from a dental hygienist as part of their dental care. We did not find any reports of an association between oral dryness and sarcopenia. The number of remaining teeth was found to be significantly associated with sarcopenia in a previous study of older people living in the community [10,13,30]. Since the participants in this study included those with restored occlusal support, we considered that the association between the number of remaining teeth and sarcopenia was weakened. The relationship between sarcopenia and masticatory function had already been reported to be significant in previous studies [10]. In this study, only 7.8% of the patients had decreased masticatory function, which is less than that observed in previous studies [10,28] and may be attributed to the fact that this study was conducted on a population with restored occlusal support. Therefore, the small number of patients with decreased masticatory function may be the reason for the inconsistency in the results. Swallowing function was significantly associated with sarcopenia in a previous study of community-dwelling older women [31] and a previous study of hospitalized patients [32]. The study of community-dwelling older women [31] comprised a population with a high mean age of 82.3 ± 6.9 years. The study of hospital inpatients [32] showed a higher prevalence of sarcopenia than that observed in this study. These differences in age and sarcopenia prevalence may have influenced the association between swallowing function and sarcopenia. Appropriate dental treatment for dental caries, periodontal disease, and tooth loss to resolve organic oral problems has been reported to be effective in preventing malnutrition, a risk factor for sarcopenia [33]. However, the prevalence of sarcopenia was higher in those with reduced oral function, despite having completed treatment for oral problems. This result indicates that restoration of tooth shape alone is not sufficient to maintain the health of older people against oral problems. The results suggest that treatment aimed at maintaining and improving oral functions, such as oral function training [34] and nutritional guidance [35], is also necessary for mobility-impaired dental problems to prevent sarcopenia. In contrast, the presence of sarcopenia may have affected the decline in oral function. If oral function decline persists after treatment for organic dental problems, the presence of sarcopenia should be suspected, and skeletal muscle mass, muscle strength, and physical function assessments should be considered, as well as dietary and exercise therapy [36]. This study had some limitations. First, since this was a cross-sectional study, we could not determine the causal relationship between oral hypofunction and sarcopenia. To verify their causal relationship, it is necessary to conduct an intervention study wherein patients with oral function decline are classified into oral function training and non-training groups. However, we conducted a cross-sectional study because we thought it was necessary to first understand the actual situation. Second, the number of participants in this study was limited because it only included patients who completed treatment at a single dental clinic in a specific area; hence, bias exists because the response to organic dental disorders is based on the treatment guidelines of a single dental institution. Therefore, the sample size of this study was small compared to that of previous studies [14,15], and the independent variables were limited. Third, we did not investigate lifestyle habits, such as alcohol consumption, smoking, or exercise habits, which are reportedly associated with sarcopenia or the presence or absence of a cohabitant [37,38,39,40]. The possibility that these factors may have affected the results should not be ruled out. Fourth, prosthetic analysis was not performed in this study because it was difficult to categorize the results due to the variation in tooth loss sites and ranges. Fifth, this study included participants with fewer than 20 remaining teeth. To completely exclude the effects of organic dental problems, only those with more than 20 teeth should be included in the study. However, approximately half of the older population in Japan has fewer than 20 teeth [28]. If participants with less than 20 remaining teeth were excluded, the results would deviate greatly from the actual situation; therefore, those with less than 20 remaining teeth were included in the study. Finally, although the study participants had completed initial periodontal treatment, we did not investigate their detailed periodontal status. Although there is no unified view on the relationship between periodontal disease and sarcopenia, previous studies have reported on the relationship between systemic inflammation and sarcopenia [41], which may have influenced the results. We believe that additional research on these factors using a larger sample size is necessary to strengthen our findings. 5. Conclusions There is a significant association between poor oral function and sarcopenia, even in older people whose treatment of organic dental problems has been completed and have no ongoing dental complaints such as pain. Japan is in the midst of a super-aged society, wherein the structure of dental diseases is also changing along with the alterations in population structure. Dental treatment in a super-aged society should not be limited to organic treatment but should also consider the relationship between mobility-impaired dental problems and sarcopenia. Acknowledgments We would like to express our deepest gratitude to the staff of the Medical Corporation Shuwa-kai Tsugayasu Dental Clinic and the Gerodontology, Department of Oral Health Science, Faculty of Dental Medicine, Hokkaido University. Author Contributions Conceptualization, R.S. and Y.W.; methodology, Y.W., T.S. and Y.Y.; formal analysis, R.S.; investigation, R.S., Y.S. and Y.M.; resources, H.T.; data curation, R.S. and Y.M.; writing—original draft preparation, R.S.; writing—review and editing, Y.W. and Y.Y.; visualization, R.S.; supervision, T.S., Y.W. and Y.Y; project administration, H.T. and Y.Y.; 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 was approved by the Ethical Review Committee for Clinical and Epidemiological Research, Hokkaido University School of Dentistry (Approval No. 2019-4). 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 Selection of adjustment variables by directed acyclic graph. Figure 2 AWGS2019 criteria for the diagnosis of sarcopenia. ijerph-19-05178-t001_Table 1 Table 1 Items for oral function assessment and the number and percentage of patients with oral hypofunction. Clinical Signs Measurement Number % Poor oral hygiene Tongue coating index ≥ 50% 52 19.33 Oral dryness The measured value obtained by a recommended moisture checker is less than 27.0. 115 42.75 Reduced occlusal force The number of remaining teeth is less than 20. 131 48.70 Decreased tongue-lip motor function The number of /pa/, /ta/ or /ka/ pronunciations per second is less than 6. 170 63.20 Decreased tongue pressure The maximum tongue pressure is less than 30 kPa. 130 48.33 Decreased masticatory function The glucose concentration obtained by chewing gelatin gummies is less than 100 mg/dL. 21 7.80 Decreased swallowing function The A items on the Seirei dysphagia screening questionnaire more than 1. 68 25.30 ijerph-19-05178-t002_Table 2 Table 2 Trends in participant characteristics among the study groups. All Normal Sarcopenia Severe Sarcopenia p-Value Analysis Variables (n = 269) (n = 215) (n = 30) (n = 24) Characteristics Age 74.93 ± 6.50 73.94 ± 6.03 77.17 ± 6.64 80.96 ± 6.62 <0.001 *** a Sex (%, male) 49.44 46.05 56.67 70.83 0.016 * b Height (cm) 157.22 ± 8.79 158.01 ± 8.77 152.45 ± 7.22 155.41 ± 8.83 0.005 ** a Weight (kg) 59.05 ± 10.61 60.58 ± 9.76 52.04 ± 12.45 54.10 ± 10.91 <0.001 *** a BMI (kg/m2) 23.59 ± 3.29 24.14 ± 3.22 21.52 ± 3.03 21.25 ± 1.97 <0.001 *** a Variables of sarcopenia Grip strength (kg) 28.13 ± 11.96 29.44 ± 11.89 25.83 ± 13.01 19.31 ± 5.80 <0.001 *** a Gait speed (m/s) 1.06 ± 0.27 1.10 ± 0.26 1.02 ± 0.23 0.78 ± 0.23 <0.001 *** a SMI (kg/m2) 6.67 ± 0.96 6.85 ± 0.92 5.85 ± 0.80 5.99 ± 0.66 <0.001 *** a Variables of oral hypofunction and oral health status Oral hygiene (%) 32.48 ± 17.26 32.36 ± 16.87 32.15 ± 21.36 34.03 ± 15.66 0.844 a Oral dryness 26.91 ± 3.09 27.03 ± 3.09 26.87 ± 2.80 25.94 ± 3.43 0.136 a Number of remaining teeth 17.25 ± 8.81 17.99 ± 8.41 14.13 ± 9.83 14.63 ± 9.96 0.016 * a Tongue-lip motor function/pa/ (times/s) 6.09 ± 0.96 6.23 ± 0.83 5.75 ± 0.99 5.36 ± 1.51 <0.001 *** a /ta/ (times/s) 6.04 ± 0.93 6.15 ± 0.86 5.68 ± 0.83 5.48 ± 1.34 <0.001 *** a /ka/ (times/s) 5.92 ± 0.95 5.75 ± 0.85 5.17 ± 0.95 4.98 ± 1.32 <0.001 *** a Tongue pressure (KPa) 30.27 ± 8.27 31.50 ± 7.88 27.65 ± 8.56 22.51 ± 6.40 <0.001 *** a Masticatory function (mg/dL) 182.87 ± 59.53 187.37 ± 59.88 161.30 ± 39.30 169.50 ± 70.74 0.013 * a Swallowing function (%) † 25.29 21.40 30.00 54.17 0.001 ** b Number of oral hypofunction items 2.55 ± 1.31 2.34 ± 1.21 3.03 ± 1.19 3.75 ± 1.51 <0.001 *** a Diagnosis of oral hypofunction (%) 49.07 43.72 64.52 75.00 0.001 ** b Number of functional teeth 27.53 ± 1.01 27.56 ± 0.96 27.50 ± 1.22 27.29 ± 1.16 0.698 a Removable denture use (%) 64.68 64.65 64.52 62.50 0.926 b Medical history Hypertension (%) 26.77 27.91 16.13 29.17 0.677 b Diabetes mellitus (%) 12.27 9.30 16.13 33.33 0.001 ** b Hyperlipidemia (%) 12.27 12.56 9.68 12.50 0.865 b Cerebrovascular disease (%) 6.32 4.65 9.68 16,67 0.014 * b Cardiovascular disease (%) 11.15 11.63 6.45 12.50 0.269 b Cancer (%) ‡ 5.95 6.05 9.68 0.00 0.498 b BMI, body mass index; SMI, skeletal muscle mass index. a. Jonckheere–Terpstra trend test. b. Mantel–Haenszel trend test. * p < 0.05, ** p < 0.01, *** p < 0.001. † Percentage of patients with reduced swallowing function. ‡ Exclude head and neck cancer. ijerph-19-05178-t003_Table 3 Table 3 Relationship between sarcopenia and age, BMI, sex, and medical history. Variables PPR 95%Wald p-Value Lower Limit Upper Limit Age 1.09 0.05 0.12 <0.001 *** BMI 0.81 −0.30 −0.13 <0.001 *** Sex 1.73 −0.01 1.10 0.053 Hypertension 0.78 −0.89 0.39 0.443 Diabetes mellitus 2.34 0.23 1.47 0.008 ** Hyperlipidemia 0.89 −0.97 0.73 0.788 Cerebrovascular disease 2.20 −0.01 1.58 0.052 Cancer 0.93 −1.24 1.09 0.898 Cardiovascular disease 0.81 −1.13 0.71 0.653 ** p < 0.01, *** p < 0.001. Poisson regression analysis was performed. Dependent variable: two sarcopenia groups. Independent variables: age, BMI, sex, hypertension, diabetes, dyslipidemia, cerebrovascular disease, cancer, and cardiovascular disease. PRR. prevalence rate ratio. ijerph-19-05178-t004_Table 4 Table 4 Relationship between sarcopenia and oral function assessment, removable denture use, number of functional teeth, diagnosis of oral hypofunction, and number of oral hypofunction items. Variables Model 1 Model 2 95% Wald 95% Wald PRR Lower Limit Upper Limit p-Value PRR Lower Limit Upper Limit p-Value Oral hygiene 1.00 −0.01 0.02 0.816 1.00 −0.02 0.02 0.861 Oral dryness 0.96 −0.12 0.04 0.281 0.97 −0.11 0.05 0.404 Number of remaining teeth 0.97 −0.06 −0.07 0.017 * 0.99 −0.05 0.02 0.359 Tongue-lip motor function /pa/ 0.69 −0.56 −0.19 <0.001 *** 0.80 −0.44 −0.02 0.035 *              /ta/ 0.68 −0.61 −0.17 <0.001 *** 0.80 −0.48 0.02 0.070             /ka/ 0.64 −0.65 −0.23 <0.001 *** 0.76 −0.53 −0.03 0.029 * Tongue pressure 0.93 −0.10 −0.04 <0.001 *** 0.95 −0.09 −0.02 0.003 ** Masticatory function 1.00 −0.01 −0.00 0.027 * 1.00 −0.01 0.00 0.207 Swallowing function 2.02 0.16 1.25 0.011 * 1.60 −0.10 1.04 0.108 Removable denture use 1.01 −0.55 0.57 0.968 0.81 −0.79 0.36 0.467 Number of functional teeth 0.90 −0.33 0.13 0.374 0.89 −0.34 0.10 0.296 Diagnosis of oral hypofunction 2.45 0.31 1.48 0.003 ** 1.63 −0.14 1.12 0.127 Number of oral hypofunction items 1.57 0.25 0.65 <0.001 *** 1.39 0.11 0.56 0.004 ** Model 1. 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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091172 animals-12-01172 Article Novel Quantitative PCR for Rhodococcus equi and Macrolide Resistance Detection in Equine Respiratory Samples https://orcid.org/0000-0002-5353-2081 Narváez Sonsiray Álvarez 1* Fernández Ingrid 2 Patel Nikita V. 2 Sánchez Susan 2 Cywinska Anna Academic Editor Witkowski Lucjan Academic Editor 1 Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA 2 Athens Veterinary Diagnostic Laboratory, Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA; ingridf@uga.edu (I.F.); nikita.patel2@uga.edu (N.V.P.); ssanchez@uga.edu (S.S.) * Correspondence: sonsiray.alvarez@uga.edu 03 5 2022 5 2022 12 9 117218 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/). Simple Summary Multidrug-resistant (MDR) Rhodococcus equi (R. equi) is rapidly spreading across the US in equine breeding farms, causing devastating untreatable disease in foals. There is a critical need for new diagnostic tools that can identify R. equi and its antibiotic resistance profile accurately and fast. This project aimed to develop and standardize a novel multiplex quantitative real-time PCR (qPCR) to detect R. equi and its most clinically relevant antimicrobial resistance genes directly from equine respiratory samples. We have designed three pairs of oligos (a.k.a primers or oligonucleotides) to identify R. equi and MLSB (macrolide, lincosamide, streptogramin B) resistance genes erm(46) and erm(51) that can be used in single-plex and multiplex qPCR assays. Furthermore, our new qPCR shows high sensitivity and specificity in in-silico analysis and when tested in mock equine respiratory samples. Therefore, we believe it can be used for a fast-preliminary diagnosis of R. equi and the simultaneous prediction of its most critical resistant profile. The new molecular diagnostic tool presented here will shorten the waiting time from the moment the practitioner sees the equid patient until it is diagnosed and appropriately treated. Abstract R. equi is an important veterinary pathogen that takes the lives of many foals every year. With the emergence and spread of MDR R. equi to current antimicrobial treatment, new tools that can provide a fast and accurate diagnosis of the disease and antimicrobial resistance profile are needed. Here, we have developed and analytically validated a multiplex qPCR for the simultaneous detection of R. equi and related macrolide resistance genes in equine respiratory samples. The three sets of oligos designed in this study to identify R. equi housekeeping gene choE and macrolide resistance genes erm(46) and erm(51) showed high analytic sensitivity with a limit of detection (LOD) individually and in combination below 12 complete genome copies per PCR reaction, and an amplification efficiency between 90% and 147%. Additionally, our multiplex qPCR shows high specificity in in-silico analysis. Furthermore, it did not present any cross-reaction with normal flora from the equine respiratory tract, nor commonly encountered respiratory pathogens in horses or other genetically close organisms. Our new quantitative PCR is a trustable tool that will improve the speed of R. equi infection diagnosis, as well as helping in treatment selection. Rhodococcus equi qPCR diagnosis macrolide resistance erm(46) erm(51) the U.S. Department of Agriculture1U18FD006157-04 This work was supported by grant 1U18FD006157-04 from the U.S. Department of Agriculture. ==== Body pmc1. Introduction R. equi is an animal and human pathogen, well known in veterinary medicine as the leading cause of severe bronchopneumonia in foals [1]. The emergence and spread of MDR R. equi represent a significant threat to the equine industry due to the economic impact associated with this disease, related to animal long-term treatment costs, veterinary and nursing care costs, and lost income from animal mortality. MDR R. equi is also a concern to public health as the antibiotic therapy of choice to treat R. equi infections in horses (a macrolide in combination with rifampin) is also routinely used to treat bacterial infections in humans [2,3]. Our previous investigation determined that in the US, R. equi resistant to macrolides and rifampin mainly cluster in three clonal populations: clone 2287, clone G2016, and clone G2017 [4,5,6]. Clones 2287 and G2016 carry the MLSB resistance gene erm(46) as a part of transposon tnRErm46, and a different rifampin resistance based on point mutations in the rpoB gene at position 531 [4,7]. R. equi clone G2017 carries a different MLSB resistance gene, erm(51) in transposon tnRErm51 [6], and a rpoB mutation in position 531, which confers rifampin resistance [6]. Due to the insidious progression of infection to severe clinical signs, early and accurate diagnosis of foals with R. equi pneumonia is essential. We present a new qPCR approach to quickly and efficiently identify macrolide-resistant R. equi directly from equine respiratory samples. 2. Materials and Methods 2.1. Bacterial Genomes The 202 R. equi genomes included in our analysis were randomly selected Illumina whole-genome assemblies from isolates characterized in previous studies (see GeneBank accession numbers in Table S1): 105 environmental genomes (n = 35 macrolide susceptible and n = 70 macrolide resistant) from Huber et al., 2020 [6]; 62 clinical isolates (n = 19 macrolide susceptible and n = 43 macrolide resistant) from Álvarez-Narváez et al., 2019 [7]; and 2021 [5]; and 35 macrolide susceptible strains representative of the global genomic diversity of R. equi [8]. The 25 non-R. equi reference genomes were selected based on genetic similarity with R. equi and previous literature [9,10]. 2.2. Oligo and Probe Design and In-Silico Validation Genes choE, erm(46), and erm(51) were extracted from the genomes of R. equi 103S (NCBI accession number NC_014659.1), R. equi PAM2287 (NCBI accession number ASM209440v1), and R. equi lh_50 (NCBI accession number ASM1687895v1) using Artemis software (v18.1.0) [11]. Oligos and probes were designed using the function “find primers” from ApE-A plasmid Editor (v2.0.61, [12]). Geneious mapper (Version 6.0.3, [13]), set up with a high sensitivity method and fine-tuned with up to five iterations, was used to map 202 R. equi genomes (Table S1) and 25 non-R. equi reference genomes (plasmids and chromosomes) to the three sets of oligos and probes designed in this study. Single nucleotide polymorphisms (SNPs) between the oligo sets and the tested sequences were quantified by hand from the sequence alignment. The expected amplification detection was calculated based on QuantiNova DNA polymerase processivity (Taq DNA Polymerase 2–4 kb/min) and PCR elongation time (30 s). This way, amplification would only be detected if the forward and reverse primers are in <2 kb proximity and the corresponding probe is inside that <2 kb DNA fragment. 2.3. Bacterial Strains and Culture Conditions Three R. equi strains were used in this study: R. equi PAM2287 (NCBI accession number ASM209440v1), a macrolide and rifampin-resistant clinical isolate that carries the virulence plasmid pVAPA, the macrolide resistance gene erm(46), and the rifampin mutation rpoBS53F [7]; R. equi 103-ApraR is a plasmidless derivative strain of R. equi 103 containing the aac(3)IV apramycin resistance cassette integrated into the chromosome [14]; and R. equi lh_50 (NCBI accession number ASM1687895v1) is a macrolide and rifampin-resistant environmental isolate carrying the macrolide resistance gene erm(51), and the rifampin mutation rpoBS531Y [6]. All R. equi strains were routinely cultured in a brain–heart infusion medium (BHI; Difco Laboratories-BD) at 37 °C and 200 RPMs unless otherwise stated. Agar media were prepared by adding 1.6% of bacteriological agar (Oxoid). When required, media was supplemented with antibiotics (erythromycin, 8 µg/mL; and rifampin, 25 µg/mL; Sigma- Aldrich, St. Louis, MO, US). Additionally, qPCR specificity was tested on 12 wildtype R. equi (Table S3) and five clinical isolates frequently isolated from the respiratory tract of healthy and sick horses (Corynebacterium pseudotuberculosis, Streptococcus equi subsp. equi, Streptococcus equi subsp. zooepidemicus, Nocardia asteroides, and Mycobacterium avium subsp. paratuberculosis) from the Athens Veterinary Diagnostic Laboratory (Athens, GA, USA) collection, extracting DNA directly from frozen stocks. 2.4. DNA Extraction and Real-Time qPCR Assay DNA was extracted from frozen stocks, isolated colonies, and equine nasal swabs using IndiSpin® Pathogen Kit (Indical Bioscience, Orlando, FL, US) following manufacturer’s instructions. qPCRs were carried out using the QuantiNova Pathogen +IC Kit (Qiagen, Germantown, MD, US) in a 7500 Real-Time PCR System thermocycler (Applied Biosystems, Bedford, MA, US). For single qPCRs, a master mix volume of 20 μL per reaction was used mixing 5 μL of DNA template, 5 μL of Quantinova Mix, 0.1 μL of Quantinova Rox, 2 μL of each forward and reverse 10 μM primers (Table 1), 1 μL of corresponding 6 μM probe (Table 1), and 4.90 μL of molecular grade water (Fisher). For multiplex qPCR, a master mix volume of 20 μL per reaction was used mixing 5 μL of DNA template, 5 μL of Quantinova Mix, 0.1 μL of Quantinova Rox, 1 μL of each forward and reverse 10 μM primer combination (n = 6 primers) (Table 1), and 1 μL of each of the three 6 μM probes. PCR reactions were performed in triplicate. The thermocycler conditions used for both singleplex and multiplex were 5 min at 95 °C of initial denaturation, and 40 cycles of amplification with 5 s at 95 °C of denaturation, followed by 30 s of oligonucleotide hybridization at 60 °C, and 30 s of elongation at 68 °C. CT (cycle threshold) values were estimated automatically by QuantStudioTM Design and Analysis Software (v 1.5.1, Applied Biosystems, Bedford, MA, US). CT cut off for all our qPCRs was set at 40 cycles, and CT values below 35 were call positive; CT values between 35 and 40 were called suspect; and Ct values after 40 were considered negative. Cut offs were estimated based on limits of detection (LOD) results. DNA from R. equi 2287, R. equi 103-ApraR, and R. equi lh_50 was used as a positive control for the Rhodo_Dlab set of oligos. R. equi 2287 DNA was used as a positive control for the Erm46_Dlab set and R. equi lh_50 was used as a positive control for the Erm51_Dlab set. The genomes of the three strains have been fully sequenced and are publicly available in NCBI. Water (instead of bacterial DNA) was used as a universal negative control in all assays, and DNA extracted from nasal swabs of healthy horses was additionally used as an extra negative control in the multiplex qPCR in mocking samples. 2.5. Standard Curve Construction R. equi DNA concentration was measured with a Qubit Fluorometer (ThermoFisher, Waltham, MA, US) and Qubit dsDNA BR Assay Kits (ThermoFisher, Waltham, MA, US) and adjusted to 10–15 ng/μL. Ten-fold serial dilutions were made with R. equi extracted DNA in molecular grade water (Fisher Scientific, Pittsburgh, PA, US). The qPCR assay stated above was used to determine the CT values for each dilution. A standard regression curve was constructed with QuantStudioTM Design and Analysis Software (v 1.5.1, Applied Biosystems, Bedford, MA, US) using linear regression analysis of the log10 sample quantity and the corresponding CT values. Slope and regression equations were calculated for all primer sets individually and in combination. The percentage of efficiency of the qPCR reaction was calculated using the following formula: Efficiency% = (−1 + 10(−1/slope)) × 100. 2.6. Limit of Detection (LOD) Calculation LOD is presented as the minimum number of target copies in a sample that can be measured accurately [15]. The LOD was calculated with The Rhode Island Genomics and Sequencing Center online calculator (https://cels.uri.edu/gsc/cndna.html, accessed on 22 April 2022, Andrew Staroscik, Kingston, RI, US). This calculator requires the user to input the minimum amount of template detected (MAT) in ng and the length of the template (LT) in bp. With this information the number of copies is calculated with the following formula: number of copies = (MATng × 6.022 × 1023 molecules/mole)/(LTbp × 1 × 109 ng/g × 650 g/mole of bp). MAT was calculated with the following formula: MAT = DNA concentration of template (ng/µL) × last fold dilution detected × vol. template. R. equi genome size (~5.2 Mbp) was used as LT in all LOD calculations. 3. Results 3.1. Oligo Set Design and In-silico Validation We designed for this study a total of three oligo pairs and their corresponding probes (Table 1) targeting R. equi housekeeping gene choE (Rhodo_Dlab set), and macrolide resistance genes erm(46) (Erm46_Dlab set) and erm(51) (Erm51_Dlab set). We performed a preliminary in-silico validation of the oligos and probes to test their specificity following the inclusivity and exclusivity criteria [16]. We checked in-silico inclusivity by mapping the three primer sets and probes to the whole genome sequences of 202 R. equi (Table S1) isolated from different animal species and presenting multiple susceptibility profiles (Table 2). The Rhodo_Dlab set mapped with the chromosomes of all the 202 R. equi tested at the targeted place. However, three R. equi genomes showed >1 SNP difference with the Rhodo_Dlab set, and to be conservative, we predicted PCR products in 199 out of 202 reactions (98.5%) (Table 2). Erm46_Dlab and Erm51_Dlab sets had perfect matches (zero SNPs) with the genomes of all erm(46)-positive (n = 85) and erm(51)-positive (n = 29) R. equi, respectively, and PCR products were predicted for all reactions (Table 2). Although we observed that the three oligo sets had matches with non-targeted R. equi sequences, amplification was never expected as the combination of the two oligos and corresponding probe was never found in enough proximity to generate a PCR product (Table 2). Additionally, all non-target matches were full of SNPs (data not shown) and that would most probably hamper the alignment between the oligos/probe and the R. equi genome. We tested the in-silico exclusivity by mapping the three primer sets and probes to the whole genome sequences of 25 non-R. equi reference genomes (plasmids and chromosomes) of bacteria species in close genetic proximity with R. equi and other common respiratory pathogens. Similar to the observations made on the non-targeted R. equi sequences, occasionally, one of the oligos or the probe would align with non-R. equi genomes. (Table S2). Still, detection of amplification was never expected as none of the two primers and corresponding probes align in the same genome simultaneously. (Table 2 and Table S2). 3.2. Testing Oligos and Probes in Singleplex and Multiplex qPCR Assays We first explored the optimal hybridization temperature for each pair of oligos in a conventional singleplex PCR with a temperature gradient between 55 °C and 70 °C (Figure 1). We observed that the three oligo pairs produced the desired band size (~200 bp) regardless of the hybridization temperature used. Still, their performance was better between 60–70 °C. Most of the qPCR diagnostic tests run in our laboratory use 60 °C as a hybridization temperature. Hence, we decided to use 60 °C as a hybridization temperature in this assay for convenience. Then we tested the qPCR efficiency and analytic sensitivity (expressed as the limit of detection [LOD]) for each oligo set individually. Macrolide resistant R. equi 2287 was used as a template to characterize the Rhodo_Dlab set and the Erm46_Dlab set, while R. equi lh_50 was used with the Erm51_Dlab group. PCR efficiencies ranged between 104 and 121%, with coefficients of determination (R2) above 0.99 (Table 3. The qPCR detected R. equi (gene choE) even when just as little as 6 × 10−5 ng of R. equi DNA was present in the sample (Figure 2 and Figure S1), and the LOD for the Rhodo_Dlab set was estimated to be 10.7 complete genome copies per PCR reaction (Table 3). Similarly, the oligo sets designed to identify macrolide resistance genes erm(46) and erm(51) detected the corresponding targets, even when a small load of R. equi DNA was present in the sample (~6 × 10−6 ng, Figure 2 and Figure S1). The LOD for the Erm46_Dlab and Erm51_Dlab oligo sets was estimated to be 1.18 and 1.07 complete genome copies per PCR reaction, respectively (Table 3). Finally, we tested the performance of each oligo pair when working together in a multiplex qPCR assay. This time, we decided to use a pool of the three R. equi strains mentioned above (ratio 1:1:1) as a DNA template. We observed that the qPCR efficiency and R2 value decreased for all primers sets (Table 3). No changes in efficiency and sensitivity were observed for the Rhodo_Dlab pair (Table 3). Similarly, a 10-fold decrease in LOD was observed for Erm46_Dlab and Erm51_Dlab oligo sets, and no changes were observed for the Rhodo_Dlab set. 3.3. Testing the Analytic Sensitivity and Specificity in Mocking Equine Respiratory Samples We extracted and pooled the microbial DNA content of 13 nasopharyngeal swabs from 13 healthy horses (one swab per animal). We used that as representative DNA of the normal equine respiratory flora. We used this DNA extract to dilute R. equi DNA (pool of the three R. equi isolates mentioned above) in 10-fold serial dilutions to have a “mock” respiratory sample containing decreasing amounts of R. equi DNA, and we recalculated the multiplex qPCR efficiency and analytic sensitivity (LOD) (Table 3). We observed that no CT values were recorded for the respiratory microbial DNA when R. equi DNA was not present (Figure 3), demonstrating that our multiplex qPCR is not reactive to normal bacterial communities present in the respiratory tract of horses. Although we found that the LOD slightly decreased in this assay compared to the multiplex qPCR performed on clean R. equi DNA, the amplification efficiency did not significantly change (Table 3). Additionally, we determined the analytic specificity of the multiplex qPCR by testing its inclusivity, or the ability to detect a wide range of R. equi isolates of the ADVL collection (n = 12, Table S3), and its exclusivity, or lack of interference from three genetically similar organisms C. pseudotuberculosis, N. asteroids, and M. avium subsp. paratuberculosis, and two common equine respiratory pathogens, S. equi subsp. equi, S. equi subsp. zooepidermicus (Figure 3). The multiplex qPCR detected all the R. equi isolates (Table S3). At the same time, no signal (CT values) was observed for the non-R. equi species for any oligo pairs (Figure 3), proving that our strategy is specific for R. equi and not reactive to non-target DNA. All wildtype clinically obtained R. equi tested in this assay were susceptible to macrolides. No signal was detected for the Erm46_Dlab and Erm51_Dlab oligo sets (Table S3), further demonstrating specificity. 4. Discussion The current diagnosis for R. equi pneumonia in foals generally involves a cytology report describing the presence of pleomorphic rods in respiratory fluids, a preliminary qPCR detecting R. equi directly from the respiratory sample, and subsequent bacteria isolation and antimicrobial susceptibility profiling [17]. Cytology and PCR results are usually available to the clinician in the first 12 h. However, R. equi isolation and corresponding antimicrobial susceptibility testing can take up to 72 h. Due to the insidious nature of this disease [1], fast action is crucial, and clinicians generally start treatment with a macrolide (clarithromycin) and rifampin before the susceptibility profiles are available. This strategy has been effective so far as resistance to macrolides and rifampin was below 5% of all R. equi cases recorded in some studies [5,18]. However, over the last 15 years, the number of resistant isolates has significantly increased, to the point that resistant R. equi to all macrolides and rifampin is being cultured from up to 40% of foals at a farm in Kentucky [19]. The increasing prevalence of MDR R. equi in the US has been recently evidenced by epidemiological studies such as Dr. Huber’s et al. in Kentucky [18,20], and requires the development of new diagnostic tools like the qPCR described here, that account for bacterial detection and clinically relevant resistance identification directly from respiratory samples, fast and accurately. The dual antimicrobial therapy to treat R. equi infections in horses mentioned above has been used for over 30 years [18,21,22,23]. In the US, resistant R. equi are mainly grouped in three clonal populations with entirely different genetic backgrounds, although they share similar antimicrobial resistance mechanisms [4,5,6]. All resistant clones present a rifampin resistance point mutation at position 531 of the rpoB gene, and they all carry an MLSB resistance erm gene inserted in a transposon [4,5,6]. So far, two different erm genes have been identified in R. equi, erm(46) primarily found in clinical isolates (clones 2287 and G2016) [4,24], and erm(51) mainly associated with environmental samples [6]. Although erm(46) and erm(51) appear to be part of mobilizable elements that could mobilize into other bacteria through horizontal gene transfer [6,7,25], these genes have only been observed in the genomes of R. equi. Additionally, genetic analysis showed that erm(46) and erm(51) share low similarity with each other (~50% at nucleotide level [6]) and with other known erm genes (<68% nucleotide sequence identity to erm(38), erm(39) and erm(40) found in Mycobacterium spp.) [6]. Our multiplex qPCR targets these two erm genes and not the rifampin resistance as punctual mutations are challenging to identify by qPCR, and as epidemiology evidence shows, if an isolate is identified as R. equi and carries an erm gene, it most probably also contains a rifampin resistance mutation [4,5,6]. Like previous approaches, our qPCR strategy targets the R. equi housekeeping gene choE to identify R. equi [10,26,27,28]. Still, we are using a new oligo combination that allows the assay to be run in multiplex with two more sets of primers to detect erm(46) and erm(51) genes. We decided not to target the virulence gene vapA as some did previously [10,26,29,30,31] as vapA is part of a plasmid, and there is a slight chance that this virulence gene is not present in equine R. equi isolates [28,32]. We first performed an in-silico validation of our assay to have preliminary data supporting the specificity of our primers and probes. In-silico validations of molecular-based detection methods are gaining popularity [33,34,35]. However, to our knowledge, this is the first time this approach has been used to develop a qPCR to detect R. equi. The Rhodo_Dlab set showed high in-silico specificity as it mapped with all the chromosomes of the 202 R. equi tested and did not show significant matches with any of the non-R. equi genomes (Table S2). Still, a small proportion of R. equi genomes (22/202) showed SNPs with the Rhodo_Dlab oligo set: 19 genomes presented only one SNP difference with the Rhodo_Dlab set and three R. equi genomes showed >1 SNP (Table 2). SNPs in primer and probe binding sites can destabilize oligonucleotide binding and reduce target specificity [36]. Yet, PCR performance studies showed that a single SNP does not prevent amplification [37]. Hence, we estimated that the in-silico inclusivity of the Rhodo_Dlab set is 98.5%, and its exclusivity is 100%. Erm46_Dlab and Erm51_Dlab sets only had perfect matches (zero SNPs difference) with the genomes of macrolide-resistant erm(46)-positive and erm(51)-positive R. equi, respectively. They were predicted to have 100% inclusivity and exclusivity (Table 2). Overall, the in-silico validation of the three primer sets designed in this study showed that they are highly specific to R. equi in the case of the Rhodo_DLab set and macrolide resistance genes erm(46) and erm(51) (Erm46_Dlab and Erm51_Dlab oligo sets, respectively). This encourages us to continue testing our qPCR assay in-vitro. The LOD and amplification efficiency of our choE oligo set (Rhodo_DLab) in singleplex and multiplex assays are comparable to what was previously published [26], and the three oligo sets used in this study showed LODs and amplification efficiencies above what considered an optimal performance. Additionally, we proved the high analytic specificity of this new R. equi multiplex qPCR by testing its inclusivity and exclusivity [16]. In total, 100% of the R. equi strains tested were identified, while none of the non-target species gave a signal in the multiplex. Furthermore, our multiplex qPCR showed not to be reactive to normal bacterial communities present in the respiratory tract of horses, further demonstrating the utility of our assay as a crucial R. equi diagnostic tool. Unfortunately, all the R. equi clinical isolates of the AVDL collection were susceptible to macrolides, so we could not test inclusivity. Future work will focus on validating this qPCR with respiratory samples from horses diagnosed with pneumonia caused by R. equi susceptible and resistant to macrolides and rifampin. Additionally, new resistances to macrolides and rifampin that our test does not detect may develop. Hence, although our qPCR strategy is an excellent tool to provide a fast answer to clinicians, verification based on bacterial culture and susceptibility testing for all samples is paramount, even if tested by this method. 5. Conclusions This manuscript describes a new multiplex qPCR assay for the simultaneous identification of R. equi and its two most clinically relevant macrolide resistance genes, erm(46) and erm(51). Our qPCR approach is highly specific and sensitive, even when performed directly from equine respiratory samples. Acknowledgments We thank L. Berghaus, K. Hart and the Large Animal Medicine Department from the University of Georgia for facilitating the R. equi strains PAM2287 and 103-ApraR and Laura Huber from the Department of Pathobiology, College of Veterinary Medicine at Auburn University for facilitating R. equi strain lh_50. We also want to thank Noah Cohen from Texas A&M University for advising us about the standard procedures to treat foals with R. equi pneumonia in the clinical setting. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ani12091172/s1, Figure S1: Standard curves for qPCR in mocking communities; Table S1: List of R. equi genomes included in the in-silico validation, Table S2: In the in-silico validation of oligos and probes in 25 non-R.equi bacterial genomes (chromosomes and plasmids), Table S3: R. equi clinical isolates tested in this study Click here for additional data file. Author Contributions Conceptualization, S.Á.N. and S.S.; methodology, S.Á.N., S.S. and I.F.; software, I.F.; validation, I.F. and N.V.P.; formal analysis, S.Á.N., I.F. and S.S.; investigation, S.Á.N.; resources, S.S.; data curation, S.S.; writing—original draft preparation, S.Á.N.; writing—review and editing, S.Á.N. and S.S.; visualization, S.Á.N. and I.F.; supervision, S.S.; project administration, S.Á.N. and S.S.; funding acquisition, S.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 The datasets analyzed for this study can be found in GenBank (https://www.ncbi.nlm.nih.gov/genbank/, accessed on 22 April 2022). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Conventional PCR with temperature gradient for oligo sets Rhodo_Dlab, Erm46_Dlab, and Erm51_Dlab. Expected band of ~200 bp size. Figure 2 Testing the analytic sensitivity of Rhodo_Dlab, Erm46_Dlab, and Erm51_Dlab sets in singleplex. qPCR curves for the three oligo sets in singleplex assays. In the Y-exe ΔRn, or fluorescence signal. In the X-exe, PCR amplification cycle. Colors indicate different 10-fold dilution of R.equi DNA (ng/µL). Figure 3 Testing the analytic specificity of Rhodo_Dlab, Erm46_Dlab, and Erm51_Dlab sets in the multiplex. qPCR curves for the three oligo sets in multiplex assays. In the Y-exe ΔRn, or fluorescence signal. In the X-exe, PCR amplification cycle. Colors indicate different bacteria species and PCR controls: pink- R.equi mix DNA (R.e); purple- nasal swab DNA (matrix); dark blue, M. avium subsp. paratuberculosis (M.a.p); light blue- N. asteorides (N.a); dark green-S. equi subsp. zooepidermicus (S.e.z); light green-S. equi subsp. equi (S.e.e); yellow- C. pseudotuberculosis (C.p); red negative control (no DNA, Mmix). animals-12-01172-t001_Table 1 Table 1 Oligos and probes. Name SEQUENCE 5’-3’ Product Size Purpose Rhodo_Dlab_F TGTCAACAACATCGACCAGGC 200 bp Amplifies choE gene, chromosomal marker in R. equi Rhodo_Dlab_R GCGTTGTTGCCGTAGATGAC Rhodo_Dlab_P /56-FAM/CCGCCCAAC/ZEN/GTTCGGGTTTCACAACCGCTT/3IABkFQ/ * Erm46_Dlab_F GTGGCGCAACGATGATGACT 192 bp Amplifies macrolide resistance gene erm46 Erm46_Dlab_R TGAAGACGGTGTGGACGAAG Erm46_Dlab_P /5HEX/CCGCATCGG/ZEN/CGTTCACACCACGGC/3IABkFQ/ * Erm51_Dlab_F CTGCCGTTTCACCTGACCAC 198 bp Amplifies macrolide resistance gene erm51 Erm51_Dlab_R GGGACGGAAATGTGTGGATG Erm51_Dlab_P /5Cy5/GCCGGCGTC/TAO/GGTGGTGCCACGATGATGA/3IAbRQSp/ * * /56-FAM/-excitation 495 emission 520;/5HEX/- excitation 538 emission 555; 5Cy5/-excitation 648 emission 668. animals-12-01172-t002_Table 2 Table 2 In-silico validation of the oligos and probes. Match with Rhodo_Dlab Set Match with Erm46_Dlab Set Match with Erm51_Dlab Set FW RV Probe PCR Products FW RV Probe PCR Products FW RV Probe PCR Products Macrolide Susceptible [n = 88] 88 88 88 87 1 88 1 0 1 0 88 0 Macrolide Resistant erm(46)-positive [n = 85] 85 85 85 83 85 85 85 85 2 1 85 0 Macrolide Resistant erm(51)-positive [n = 29] 29 29 29 29 0 29 14 0 29 29 29 29 Non- R. equi species [n = 24] 2 6 2 0 4 6 3 0 1 0 10 0 In hard brackets is the number of strains in each resistant genotype category. FW refers to the number of genomes that had a match with the forward oligo of the set. RV refers to the number of genomes that had a match with the reverse oligo of the set. Probe refers to the number of genomes that had a match with the probe of the set. PCR product indicates the number of genomes, in which the PCR set would produce a detectable PCR product (forward and reverse primers are in <2 kb proximity and corresponding probe is inside that <2 kb DNA fragment). This was calculated based on QuantiNova DNA polymerase processivity (Taq DNA Polymerase 2–4 kb/min) and PCR elongation time (30 s). animals-12-01172-t003_Table 3 Table 3 Efficiency, coefficient of determination (R2) and limit of determination (LOD) for each primer set in singleplex and multiplex assays. Efficiency (%) R2 LOD Singleplex Multiplex Multiplex Mocking * Singleplex Multiplex Multiplex Mocking * Singleplex Multiplex Multiplex Mocking * Rhodo_Dlab 121.1 112.8 115.5 0.9976 0.9987 0.9904 10.7 11 10.7 Erm46_Dlab 104.7 105.5 102.8 0.9999 0.9994 0.9976 1.18 11.8 10.7 Erm51_Dlab 120.5 105.4 90.2 0.9993 0.9971 0.9917 1.07 10.7 106.9 LOD expressed as the minimal number of complete genome copies detected per PCR reaction. * Multiplex qPCR performed in the mocking equine respiratory samples spiked with R. equi DNA. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Giguère S. Cohen N. 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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091133 plants-11-01133 Review Molecular Biology, Composition and Physiological Functions of Cuticle Lipids in Fleshy Fruits https://orcid.org/0000-0002-7418-8718 García-Coronado Heriberto 1 https://orcid.org/0000-0001-5225-8028 Tafolla-Arellano Julio César 2 https://orcid.org/0000-0001-5857-2608 Hernández-Oñate Miguel Ángel 3 https://orcid.org/0000-0003-3461-0029 Burgara-Estrella Alexel Jesús 4 Robles-Parra Jesús Martín 5 https://orcid.org/0000-0002-2612-9000 Tiznado-Hernández Martín Ernesto 1* Kim Hyun Uk Academic Editor Kumar Manu Academic Editor Singh Kesawat Mahipal Academic Editor 1 Coordinación de Tecnología de Alimentos de Origen Vegetal, Centro de Investigación en Alimentación y Desarrollo A.C., Carretera Gustavo Enrique Astiazarán Rosas 46, Hermosillo 83304, Sonora, Mexico; heriberto.garcia.dc19@estudiantes.ciad.mx 2 Laboratorio de Biotecnología y Biología Molecular, Departamento de Ciencias Básicas, Universidad Autónoma Agraria Antonio Narro, Calzada Antonio Narro 1923, Buenavista, Saltillo 25315, Coahuila, Mexico; jtafare@uaaan.edu.mx 3 CONACYT-Coordinación de Tecnología de Alimentos de Origen Vegetal, Centro de Investigación en Alimentación y Desarrollo A.C., Carretera Gustavo Enrique Astiazarán Rosas 46, Hermosillo 83304, Sonora, Mexico; miguel.hernandez@ciad.mx 4 Departamento de Investigación en Física, Universidad de Sonora, Blvd. Luis Encinas y Rosales S/N, Hermosillo 83000, Sonora, Mexico; alexel.burgara@unison.mx 5 Coordinación de Desarrollo Regional, Centro de Investigación en Alimentación y Desarrollo A.C., Carretera Gustavo Enrique Astiazarán Rosas 46, Hermosillo 83304, Sonora, Mexico; jrobles@ciad.mx * Correspondence: tiznado@ciad.mx 22 4 2022 5 2022 11 9 113324 3 2022 12 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/). Fleshy fruits represent a valuable resource of economic and nutritional relevance for humanity. The plant cuticle is the external lipid layer covering the nonwoody aerial organs of land plants, and it is the first contact between fruits and the environment. It has been hypothesized that the cuticle plays a role in the development, ripening, quality, resistance to pathogen attack and postharvest shelf life of fleshy fruits. The cuticle’s structure and composition change in response to the fruit’s developmental stage, fruit physiology and different postharvest treatments. This review summarizes current information on the physiology and molecular mechanism of cuticle biosynthesis and composition changes during the development, ripening and postharvest stages of fleshy fruits. A discussion and analysis of studies regarding the relationship between cuticle composition, water loss reduction and maintaining fleshy fruits’ postharvest quality are presented. An overview of the molecular mechanism of cuticle biosynthesis and efforts to elucidate it in fleshy fruits is included. Enhancing our knowledge about cuticle biosynthesis mechanisms and identifying specific transcripts, proteins and lipids related to quality traits in fleshy fruits could contribute to the design of biotechnological strategies to improve the quality and postharvest shelf life of these important fruit crops. fruit cuticle cutin wax plant lipids genes cuticle composition cuticle biosynthesis ==== Body pmc1. Introduction Fleshy fruits are horticultural commodities with an edible and thick mesocarp or another tissue that are rich in water, sugars, fiber, minerals, vitamins, and antioxidant compounds. That is why fleshy fruits are a valuable source of nutrients for humanity—especially for lesser developed countries, where they are relatively accessible—and their production represents an important economic resource [1]. It has been predicted that global climate change will increase droughts in the following decades, reducing available water for agriculture [2]. In this scenario, it is necessary to develop biotechnological and agronomical strategies to develop and grow plants that are adapted to grow under conditions of limited water supply without affecting fruit productivity and quality. Because of that, it is necessary to carry out efforts to elucidate the molecular mechanism of drought adaptation and water loss avoidance in fleshy fruit-producing plants [2]. Despite fleshy fruits’ physical characteristics and the ontogeny among plant species being very diverse, the development and ripening of fleshy fruits occur through coordinated biochemical and molecular mechanisms, which appear to be evolutionarily conserved [3]. During fruit’s ripening, an increase in the production of antioxidant pigments, volatile compounds and sugars, accompanied by cell wall depolymerization and cuticle modification, occurs. Once the fruit has ripened and during postharvest, these changes increase the softening, water loss and susceptibility to pathogen infections [4], representing a major challenge for fleshy fruit commercialization and export. The plant cuticle is the external lipidic layer covering land plants’ nonwoody aerial organs. The first land colonizer plants developed the ability to synthesize cuticles as a protection against desiccation, UV light exposure and extreme temperatures [5,6]. Because of this feature, distant evolutionary plants share some genes that play a role in fruit cuticle biosynthesis [7]. It is the first interaction between fruits and their surrounding environment and plays several roles in plant development, physiology and protection against biotic and abiotic stresses. One of its main functions is to protect the plant against water loss, acting as a transpiration barrier [8]. Thus, the cuticle has a relevant role in the development, ripening and postharvest shelf life of fleshy fruits [9,10]. Two main layers form the plant cuticle. The most internal layer, cutin, is covalently linked to the cell wall. It is formed mainly by long-chain fatty acids (LCFA) of 16 and 18 carbons and their oxygenated derivatives [5]. The most external layer, named cuticular wax, can be deposited over the cutin (epicuticular wax) or intercalated between the cutin components (intracuticular wax). Cuticular wax is formed by very long chain fatty acids (VLCFA) with 20 or more carbons in the main chain, and their derivatives, such as alkanes, alkenes, primary and secondary alcohols, aldehydes, ketones and esters, together with triterpenoids, steroids and phenolic compounds [11]. Generally, during organ growth, the cuticle increases in thickness. Nevertheless, specific cuticle deposition patterns, compositions and structures depend on plant species, organs, fruit cultivars, developmental stages and environmental conditions [6]. In fleshy fruits, as in other plant organs, cuticle composition is a dynamic characteristic that changes in response to developmental stages and environmental conditions [6]. Maintaining water content is essential for fleshy fruit development, and consequently, it has been hypothesized that the cuticle has a relevant function in developing and maintaining quality parameters during fruit development on plants [10]. Cuticle composition analysis during fruit development on plants and in postharvest conditions allows the elucidation of the association between the cuticle composition, quality parameters and longer shelf life of fleshy fruits. Several studies have been carried out that together suggest that the fleshy fruit cuticle plays a pivotal role in maintaining quality in postharvest shelf life, mainly by avoiding the fruit softening caused by water loss [8,12]. Due to the considerable importance of cuticles in plant physiology, development and defense against biotic and abiotic stress, efforts to elucidate the molecular pathway of cuticle biosynthesis have been carried out in plants—mainly in model plants such as Arabidopsis [13], tomato (Solanum lycopersicum) [14] and relevant crop plants [15]. Furthermore, it has been possible to identify orthologous genes and proteins playing a role in cuticle biosynthesis in other fruits through transcriptomic and proteomic tests. Excellent reviews have been published regarding the biosynthesis pathway and chemical composition of cuticles in plants [5,11] and fruits [16], their physiological functions [6] and their association with crop improvement [10,17]. This review describes the current information about cuticle biosynthesis and composition dynamics during growth, development and ripening and in the postharvest environment in fleshy fruits. An overview of studies regarding cuticle biosynthesis and composition in fleshy fruits and its relationship with water loss reduction and other relevant postharvest issues is presented. Gene expression analyses to identify transcripts and proteins playing a role in fleshy fruit cuticle biosynthesis are included and discussed. All this knowledge about the cuticle biosynthesis mechanism and identifying specific transcripts, proteins and metabolites related to quality traits in fleshy fruit-producing plants could contribute to developing biotechnological strategies to improve plant drought adaptation and reduce water loss for these economically and nutritionally important horticultural commodities. 2. Fleshy Fruit Cuticle Composition Most studies carried out to analyze cuticle composition are based on chromatographic methods such as gas chromatography coupled to mass spectrometry (GC-MS), together with Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopy [16]. These tools provide valuable data to accurately compare tissues, species or developmental stages. Table 1 shows the main components of the cutin, intracuticular and epicuticular waxes of the cuticle from different fruit species. Generally, a high proportion of alkanes and triterpenoids, followed by other very-long chain (VLC) aliphatic compounds, are found in the cuticular wax of fruits such as tomato, apple, sweet cherry, peach, pear, pepper and pitahaya [6]. Triterpenoids are the most prominent wax compounds in grape, olive and blueberries, whereas VLC aliphatics are in minor proportions [6]. In fruits such as orange, mandarin, lemon and jujube, VLC aliphatic waxes are found in significantly greater amounts than triterpenoids. 9(10),16-dihydroxy hexadecanoic acid is the main cutin component of tomato, apple, sweet cherry, drupe fruit, pepper, olive, guava and pitahaya. In fact, except for citrus fruits, 9(10),16-dihydroxy hexadecanoic acid is one of the most prevalent constituents of cutin in fleshy fruits. Nevertheless, the proportions of fruit cuticle components are very dynamic, and they vary during fruit development and ripening. 2.1. Changes in Cuticle Composition during Fleshy Fruit Development and Ripening Even though patterns of development and growing vary significantly among different types of fleshy fruits, they present a similar development and growing phenomena in which the first phase is characterized by many cycles of cell division and differentiation, with a low growth rate [4]. Subsequently, a phase of cell expansion begins, leading to a significant increase in fruit volume and mass during fruits’ development, which is characterized by the accumulation mainly of water and soluble solids [52,53]. Physiological maturity is attained when the fruit has reached its maximum size. After that state, the fruit ripening phenomenon is initiated [4]. The function of fleshy fruits is to protect the seed when the embryo has not been fully developed and promote fruit consumption and the dispersal of the seed once the embryo has been developed, so it is mature and ready to germinate and grow [1]. The depolymerization of the cell wall and changes in cuticle composition occur during fruit ripening. Once the fruit has ripened and during postharvest, these changes could increase softening, water loss and susceptibility to pathogen infections. Table 2 summarizes the cuticle composition changes recorded during fleshy fruit development phenomena. Next, studies carried out in mature fruits, during fruit development and ripening are summarized and discussed. 2.1.1. Tomato In the case of the tomato fruit (S. lycopersicum) “Ailsa Craig” variety, the amount of wax of VLC aliphatic compounds increases continually throughout its development. During the developmental phenomena, the main components of cuticular waxes are alkanes and triterpenoids, but alkanes show the most significant increase. When compared with other species, an apparent particularity of tomato fruit waxes is the presence of large amounts of VLC unsaturated compounds (i.e., alkenes and alken-1-ols), which increase throughout fruit development and ripening [18]. Tomato fruit cuticle is mainly composed of cutin [20]. Tomato epicuticular and intracuticular waxes are mainly formed by VLC aliphatic compounds and pentacyclic triterpenoids, respectively [19]. Like waxes, cutin monomers increase throughout tomato fruit “Ailsa Craig” development and ripening. C16 fatty acids, including a large amount of 9(10),16-dihydroxy hexadecanoic acid, are the principal constituents (86–88%) of total cutin, whereas C18 fatty acids, with a large amount of 18-hydroxy octadecanoic acid, are the minor constituents (10–12%) [18]. The chemical composition of tomato fruit cuticle in relative wild-tomato species is very diverse and mainly varies in the occurrence of triterpenoid isomers and wax esters [20]. Like S. lycopersicum [18], the most prominent cutin constituent of tomato wild species S. pimpinellifolium, S. cheesmaniae, S. chmielewskii, S. neorickii, S. habrochaites and S. pennellii is 10,16-dihydroxy hexadecanoic acid. However, a notably significant amount of 9,10,18-trihydroxy octadecanoic acid is present in S. chmielewskii, S. habrochaites and S. pennellii species [20]. The main constituent of cuticular wax of all seven Solanum species IS alkanes, including as the most common and abundant nonacosane (C29) and hentriacontane (C31), but the total wax coverage of all the six wild species is higher compared with S. lycopersicum. The main non-aliphatic constituents identified were the pentacyclic triterpenoids amyrins. Nevertheless, triterpenoids represent a significant proportion of total wax composition only in S. lycopersicum, S. pimpinellifolium and S. cheesmaniae [20]. The tomato fruit mutants ripening inhibitor (rin), non-ripening (nor) and the landrace “Alcobaca”, which are characterized AS having a delayed or absent ripening process and substantially less softening, have higher amounts of wax and cutin than the typical tomato fruit ripening “Ailsa Craig”. A higher relative proportion of C18 monomers than C16 is shown in rin, nor and “Alcobaca” during development than in “Ailsa Craig”. It has been hypothesized that cutin with a large amount of C16 oxygenated fatty acids has a more rigid cuticle than cuticles constituted by an equal mixture of C16 and C18 oxygenated fatty acids in the cutin, which are more elastic. Furthermore, cuticle elasticity has been attributed to higher trihydroxy fatty acid content in cutin. Nevertheless, this hypothesis needs the support of more experimental data [18]. 2.1.2. Citrus Very long chain fatty acids, alkanes and primary alcohols are the main constituents of the sweet orange cuticle (Citrus sinensis [L.] Osbeck) cultivar “Navelate” [22]. The epicuticular wax of the sweet orange fruit (C. sinensis) cutivar “Bingtang” is mainly composed of fatty acids, followed by alkanes. Intracuticular waxes are mainly composed of fatty acids, triterpenoids and alcohols. For cutin, the predominant constituents are cis-9-hexadecenoic acid and cinnamic acid [23]. In “Navelate” sweet orange, cuticle thickness slightly decreases during development. The total epicuticular wax load significantly increases only at the breaker (Bk) stage but remains unchanged at mature green (MG), colored (C) and full-colored (FC) stages. During sweet orange fruit development, VLC alkanes increase, whereas VLC fatty acids and VLC aldehyde proportion decrease [22]. Epicuticular waxes of the navel orange (C. sinensis [L.] Osbeck) cultivar “Newhall” are mainly composed of fatty acids, followed by alkanes and primary alcohols, whereas terpenoids are only present in low amounts. In contrast, intracuticular waxes are mainly composed of cyclic wax compounds, such as the triterpenoids, whereas aliphatic compounds are in low concentrations. In early navel orange fruit development stages, a low variety of epicuticular wax components is observed, but compound variety increases in the late stages. The main fatty acid constituents increase with further development [21]. The “Glossy Newhall” mutant displays a glossier peel than its wild-type navel orange (C. sinensis [L.] Osbeck cv. “Newhall”). During development, the total cuticular wax increases in navel orange and “glossy Newhall” with the same deposition pattern; nevertheless, “Glossy Newhall” presents a significantly lower wax load [56]. The main cuticular constituents of both navel orange and “Glossy Newhall” mature fruits are triterpenoids, followed by aldehydes, alkanes and fatty acids, but in “Glossy Newhall” mutant, aldehydes and alkanes are present in a lower amount [56]. During wild-type navel orange development, the total epicuticular wax increases from 60 to 120 days after flowering (DAF), decreases from 120 to 150 DAF and increases from 150 to 210 DAF. In contrast, in the “Glossy Newhall” mutant, the increase from 150 to 210 DAF does not occur [21]. These differences are consistent with the loss of wax crystals phenotype observed in “Glossy Newhall”, which have been associated with a decrease in the aldehydes and alkanes components of navel orange cuticle [21,56]. It has been suggested that cuticular crystals are mainly composed of VLC aliphatic constituents, especially by alkanes. Similar to navel orange “Newhall” [56], the cuticular wax of mandarin (Citrus unshiu) “Satsuma” mature fruit is mainly composed of aldehydes, alkanes, fatty acids and primary alcohols. Nevertheless, navel orange “Newhall” has a higher total cuticular wax and epicuticular wax amount than mandarin “Satsuma”. Furthermore, in cultivar “Newhall”, a significantly high amount of hentriacontane (C31), C24 and C26 chain length fatty acids and aldehydes are observed. In the case of terpenes, wax constituents, farnesol and squalene are only observed in navel oranges but not in mandarin fruit [24]. The main components in mandarin “Satsuma” fruit (C. unshiu) epicuticular wax are fatty acids, followed by alkanes and terpenoids. For intracuticular wax, the predominant constituents are terpenoids, followed by alkanes and fatty acids. The main constituents of cutin are cinnamic acids, followed by hexadecanedioic acid (C16) and hexadecanoic acid (C16) [25]. In mature green lemon fruits (Citrus limon Burm. f. Eureka), the main components of epicuticular wax are alkanes (C23-C33), with hentriacontane (C31) as the major component [26]. 2.1.3. Apple At the completely ripe stage, the cuticular waxes of apple fruit (Malus domestica Borkh.) late-season “Florina” and early-season “Prima” cultivars are mainly composed of triterpenoids, which represent 70% and 83% of the total wax contents, respectively, of which ursolic acid and oleanolic acid are the most prominent. In “Florina”, the principal VLC aliphatic compounds are primary alcohols, whereas in “Prima”, these are secondary alcohols, fatty acids and alkanes. A slight but not significant difference in total wax amounts between the two cultivars is observed. Nevertheless, “Florina” presents a higher number of fatty acids, esters, primary alcohols and aldehydes than “Prima” cultivar fruits [29]. Cutins of “Florina” and “Prima” cultivars are mainly composed of hydroxylated hexadecanoic (C16) and octadecanoic (C18) acid monomers, of which 9(10),16-dihydroxy hexadecenoic acid is the most prominent, representing 34% of the total cutin content [29]. In both “Golden Delicious” and “Red Delicious” varieties, the main components of cutin are the fatty acids 9,10,18-trihydroxy octadecanoic (C18), 10,20-dihydroxycosanoic (C20), 10,16-dihydroxy hexadecanoic (C16), 9,10-epoxy-12-octadecenoic (C18:1) and 9,10-epoxy-18-hydroxy-12-octadecenoic acid (C18:1) [57]. In contrast to “Florina” and “Prima” cultivars, the main constituents of the cuticular wax of apple (M. domestica Borkh) cultivars “Red Delicious”, “Royal Gala”, “Granny Smith” and “Cripps Pink” are fatty acids, followed by alkanes and triterpenoids, with nonacosane (C29) and ursolic acid the main alkanes and triterpenoids compounds, respectively [58]. The main constituents of cuticular wax of the apple fruit (M. domestica Borkh.) cultivar “Starkrimson” at commercial maturity are fatty acids, primary alcohols and alkanes. Docosanoic (C22) and octacosanoic (C28) acids are the most prominent fatty acids, whereas pentacosanol (C25) and octacosanol (C28) are the most prominent primary alcohols [28]. The main components of “Red Fuji” apple (M. domestica Borkh.) cuticular wax are hydrocarbons, fatty acids, nonacosan-10-one and nonacosan-10-ol. Even-numbered straight-chains are the most prevalent fatty acids, whereas nonacosane (C29) is the major alkane compound. Both nonacosane (C29), and heptacosane (C27) amounts increase during “Red Fuji” apple fruit development [27]. For the apple cultivars “Stark”, “Golden”, “Mutsu”, “Golden Delicious”, “Camachi”, “Huahong”, “Jona Gold”, “Red Star”, “Ralls” and “Mashima Fuji”, the main wax constituents at harvest are alkanes, followed by fatty acids and primary alcohols. Terpenoids and aldehydes were only observed in the “Red Star” cultivar. Nevertheless, after 49 days of postharvest storage at room temperature and 90% relative humidity, terpenoids and aldehydes were found to be present in the 10 cultivars [59]. These analyses show that, like orange fruit, apples belonging to different cultivars can exhibit marked differences in cuticle composition at harvest and during the postharvest storage of apples. 2.1.4. Prunus spp. The main constituents of the cuticular wax of mature sweet cherry fruits (Prunus avium) cultivars “Rainier”, “Bing”, “Lapins”, “Kordia” and “Regina” are triterpenes, alkanes and alcohols with 76%, 19% and 1% of the total wax, respectively. Further, nonacosane (C29) is the most prominent alkane in all five cultivars [60]. Ursolic acid is the most abundant triterpene, accounting for 60% of total triterpenes. For alcohols, the secondary alcohol nonacosan-10-ol is the most abundant. As reported for tomato [18], mature sweet cherry fruit cutin is mainly composed of C16 monomers. Out of those, the most abundant is 9(10),16-dihydroxy hexadecanoic acid [30]. Wax and cutin accumulation increase during the first stages of development, but they markedly decrease at the latest developmental stages. During development, triterpenes decrease, but alkanes and alcohols remain practically unchanged. In the case of cutin, a decrease in the total mass of cutin during sweet cherry development due to a low deposition of the main cutin constituents was observed [30]. Cuticular waxes of cherry fruit (P. avium L.) cultivars “Celeste” and “Somerset” are mainly composed of ursolic acid, nonacosane (C29), linoleic acid and beta-sitosterol [61]. Unlike “Rainier”, “Bing”, “Lapins”, “Kordia” and “Regina” cultivars [30], cutin composition in “Celeste” and “Somerset” is mainly composed of C18 monomers. At commercial harvest, “Somerset” cherries are firmer, juicer, have higher quality indicators and have higher yields of cuticle than “Celeste” cherries. “Somerset” cuticles have large amounts of the cuticular wax phytosterols and alkanes, with sizes between C27 to C31 of chain length, and higher amounts of cutin than “Celeste”. Altogether, the above-mentioned data strongly suggest an association between cuticle yields and composition in maintaining fruit quality at harvest [61]. Nectarine (Prunus persica L. Batsch) cuticular waxes of “Summergrand” and “Zéphir” varieties are mainly composed of the triterpenoids oleanolic and ursolic acids. Minor compounds in nectarine wax are VLC aliphatics, mainly composed of alkanes, alcohols and fatty acids. Total waxes are low at the first stage of nectarine development, accumulate strongly at the middle stage, decrease at the end of the middle stage and slightly increase again near ripening. An early active cuticle accumulation process is observed during the first growth period, mainly due to triterpenoid deposition and cutin formation. On the other hand, the increase in waxes close to the final development and ripening stage consists mainly in alkane accumulation [32]. In mature peach fruits (P. persica L. Batsch.), the main wax constituents are the alkanes tricosane (C23) and pentacosane (C25) and the triterpenoids ursolic and oleanolic acids, while the main cutin constituents are the mono-unsaturated 18-hydroxyoleic acids (C18:1). For the “October Sun” cultivar, triterpenes, alkanes and fatty acids comprise 51.91%, 16.51%, and 8.27% of total wax constituents, respectively; whereas for the “Jesca” cultivar, these comprise 44.05%, 29.40% and 10.22% of total wax constituents, respectively. In “October Sun” and “Jesca” cultivars, C18 monomers represent 54.7 and 57.1% of total cutin constituents, respectively [31]. In agreement with that reported in other fruits of the genus Prunus [30,32,60], cuticular waxes of drupe fruit (Prunus laurocerasus L.) are mainly composed of pentacyclic triterpenoids, which account for 87% of total waxes, with ursolic acid the most prominent component. The aliphatic wax compounds are mainly composed of fatty acids, alkanes and primary alcohols, with about 10% of total wax. Nonacosane (C29) and triacontanoic acid (C30) are the main aliphatic compounds during drupe fruit development. The cutin is mainly made of 9(10),-dihydroxy hexadecanoic acid, 9,10-epoxy-18-hydroxy octadecanoic acid and 9,10,18-trihydroxy octadecanoic acid, comprising more than 70% of the total cutin monomers. At later stages of development, drupe shows higher amounts of total cutin and triterpenoids and a higher abundance of 3,4-dihydroxy cinnamic acid than at earlier stages [33]. 2.1.5. Pear The epicuticular wax of mature pear (Pyrus spp.) fruits from the species P. communis Linn., P. ussuriensis Maxim., P. sinkiangensis Yü., P. bretschneideri Rehd. and P. pyrifolia Burm Nakai is mainly composed of alkanes, primary alcohols and terpenoids, with 40.72%, 24.47% and 11.8% of the total content, respectively. Alkanes of 28 to 31 carbon chain lengths are the most abundant, while the alcohol triacontanol (C30) is the most abundant [37]. The cuticular wax of Asian pear cultivars “Kuerle”, “Xuehua” and “Yuluxiang” are very similar and are mainly composed of alkanes and primary alcohols. The “Kuerle” cultivar shows a higher cuticular wax amount than “Xuehua” and “Yuluxiang”, with “Xuehua” the cultivar with the lowest amount. The most abundant wax fractions of “Kuerle” and “Yuluxiang” are alkanes and primary alcohols, whereas in the case of “Xuehua”, these are primary alcohols and terpenoids [36]. The cuticular wax of wild-type “Dangshansuli” pear fruit (Pyrus bretschneideri) and its russet skin mutant “Xiusu” is mainly composed of alkanes, alkenes, fatty acids, alcohols and terpenes. Alkanes are the main compounds during pear fruit growth and development, with nanocosane (C29) as the major component. There was no difference between alkane content in both “Dangshansuli” and “Xiusu” cultivars at early stages of development. Nevertheless, a higher content of alkanes is synthesized in “Dangshansuli” fruits during growth. Nonacosane (C29) content increases significantly in “Dangshansuli” fruits during ripening, becoming the most abundant alkane compound during “Dangshansuli” pear development [35]. Fatty acid content, mainly composed of hexadecanoic and octadecanoic acid, is higher during the early stages of “Dangshansuli” and “Xiusu” pear fruit development, decreasing in the middle and late stages. In contrast, for triterpenoids, mainly composed of alpha-glycosidal and beta-glycosidal, a continuous increase in relative content is shown during all development stages of both cultivars. Fatty alcohol content is higher in “Xiusu” pear than in “Dangshansuli”, and this difference is more obvious during the latest stage of the ripening phenomena. A gradual increase in cuticle thickness is present in “Dangshansuli” fruit, whereas no clear deposition pattern is observed for “Xiusu” fruit [35]. Similarly, the main constituents of cuticular wax of Asian pear fruit (P. bretchneideri Rehd) cultivar “Pingguoli” are alkanes, fatty acids and triterpenoids, accounting for 25.9%, 27.8% and 33.6% of the total waxes, respectively. Straight-chain odd-numbered compounds are the main alkane components, and out of these, nonacosane (C29) and heptacosane (C27) are the most prominent. Fatty acids include saturated and unsaturated straight-chain odd and even-numbered compounds. In contrast, for triterpenoids, alpha-amyrin is the most abundant [34]. Changes in total wax content, relative amount and carbon chain length have been observed during “Pingguoli” pear fruit development. In earlier stages, alkanes and fatty acids are the main wax compounds, whereas alkanes and triterpenoids predominate in later stages. Total wax content increases abruptly in later stages of development, while a reduction in alkane proportion is shown during development [62]. 2.1.6. Berries (Vaccinium spp.) At the ripe stage, the cuticular wax of berries of the Vaccinium genus is mainly composed of triterpenoids, but significant variations in composition have been shown between berries belonging to different species [63] and among cultivars [38]. Through the analysis of nine blueberry cultivars belonging to the species Vaccinium corymbosum (cv. “Misty”, “O’Neal”, “Sharpblue”, “Brigitta”, “Darrow” and “Legacy”) and V. ashei (cv. “Britewell”, “Premier” and “Powderblue”), it was shown that their cuticular waxes are mainly composed of triterpenoids and beta-diketones, accounting for 64.2% and 16.4% of the total wax, respectively. Nevertheless, the total wax composition differs considerably between cultivars. Hentriacontan-10,12-dione was only detected in V. corymbosum, whereas tritriacontan-12,14-dione was only detected in V. ashei. Except for beta-diketones, VLC aliphatic compounds are minor constituents of cuticular wax. For aldehydes, fatty acids and primary alcohols, the main constituents are C28 and C30 compounds, whereas for alkanes, the main constituent is C29 [39]. The cuticular wax of blueberry cultivars “Legacy” (V. corymbosum) and “Brightwell” (V. ashei) is composed mainly of oleanolic and ursolic acid, followed by hentriacontane-10,12-dione and tritriacontane-12,14-dione, respectively. During ripening, the total wax amount and the triterpenoid content increase continuously for both cultivars; nevertheless, “Brightwell” shows a higher wax content than “Legacy”. A decrease in the relative content of diketones occurs during the ripening of both blueberry cultivars with an increase in VLC aldehydes, primary alcohols, fatty acids and alkanes [40]. At ripening stages, the triterpenoid wax fraction of blueberry (V. corymbosum L.) cultivars “Brigitta” and “Duke” is mainly composed of lupeol, oleanolic acid and ursolic acid, whereas alpha-amyrin is only observed in the “Brigitta” cultivar [38]. Altogether, these studies showed a cultivar-dependent cuticular wax deposition and composition for blueberry fruits. The most prominent components of lingonberry (V. vitis-idaea L.) and bog bilberry (V. uliginosum L.) waxes are triterpenoids and fatty acids, respectively, representing more than 50% of the total wax. In contrast, for bilberry (V. myrtillus L.), the triterpenoids and fatty acids mixture comprises more than 70% of the cuticular wax composition [41]. In the first stages of development, when berries are in stages of intensive growth, steroids are in very low amounts in the cuticle, but they increase during the stage of maturation once the berries have reached their final size. A species-specific pattern of wax composition has been observed during berries’ fruit development, with similarities among phylogenetically related species [64]. Both wild-type bilberry (V. myrtillus) and its “glossy mutant” GT have similar patterns of cuticular wax deposition and composition through development, consisting of a decrease in triterpenes and an increase in aliphatic compounds. The dominant compounds during bilberries’ development are triterpenoids and fatty acids. Despite no significant differences in total wax amount being detected between wild-type and GT during development, the glaucous phenotype could be due to a higher proportion of triterpenes and a lower proportion of fatty acids and ketones present in bilberry GT [54]. 2.1.7. Grape Cuticular waxes of grapes (Vitis vinifera L.) varieties “Müller Thurgau” and “Blauer Spätburgunder” are mainly composed of oleanolic acid, but this compound is absent in epicuticular wax. Triterpenoid deposition begins and increases early in grapevine fruit development and decreases during ripening. Except for alkyl esters and fatty acids, whose deposition does not decrease during ripening, VLC aliphatic compounds have the same pattern of deposition to triterpenoids, but they are present in much smaller amounts [42]. Like oranges [21,56], the epicuticular wax crystals of grapevine fruit are formed apparently only by VLC aliphatic compounds. The main components of epicuticular wax are alcohols, which are present in higher amounts in the first stages of development and decrease gradually during grapevine development. In contrast, alkyl esters and fatty acids are in much smaller amounts in the first stages, but they increase in the last stage of development [42]. The triterpenoid wax composition of the eight grape (V. vinifera) cultivars “Chasselas”, “Gewurztraminer”, “Muscat d’Alsace”, “Pinot auxerrois”, “Pinot gris”, “Pinot noir”, “Riesling” and “Sylvaner” are quite similar. Nevertheless, they exhibit differences during the grapefruit ripening phenomena. Oleanolic acid and oleanolic aldehyde are the most prominent constituents of the grape cuticle triterpenoid fraction for all eight cultivars. In earlier stages of ripening, a high level of total triterpenoids is observed, with a gradual decrease with the progression in development. “Gewurztraminer” shows an exceptionally higher amount of sitosterol than other cultivars, whereas 3,12-oleandione was only present in the “Muscat d’Alsace” cultivar [43]. The total aliphatic amount is highest at the early stages and slightly decreases at the end of grape berry “Gewürztraminer” cultivar development. Total triterpenoids, VLC aldehydes and VLC primary alcohols show a similar pattern of deposition to the total aliphatic amount, but their decrease is more obvious at the end of development. In contrast, VLC fatty acids and VLC esters increase during development. Alkanes are minor constituents of the cuticular wax of berries and show no significant changes during grape berry development [44]. Both total cuticular wax and epicuticular wax of mature grape berry (V. vinifera) cultivars “Kyoho”, “Muscat Hamburg”, “Redglobe” and “Zuijinxiang” are mainly composed of terpenoids, alcohols, fatty acids and esters. In agreement with the findings reported for other grape cultivars [42,43], the most abundant terpenoid among the four cultivars analyzed in this study is oleanolic acid. Grape berry cuticular terpenoids are mainly present in intracuticular wax, fatty acids are mainly present in epicuticular wax, whereas hydrocarbons are equally distributed in intra and epicuticular wax [45]. 2.1.8. Pepper A study carried out in 50 diverse pepper (Capsicum spp.) accessions, including the genera C. annuum, C. chinense, C. baccatum, C. pubescens and C. frutescens, recorded that the main wax constituents are alkanes and nonaliphatic compounds including triterpenoids and phytosterols. The amount of alkanes ranges from 13% to 74% of the total waxes, with nonacosane (C29) and hentriacontane (C31) the most abundant alkanes. Nonaliphatic compounds range from 10% to 76%, with the main components being alpha and beta-amyrin, glutinol and lupeol. Pepper cutin comprises C16 and C18 fatty acids and their oxygenated derivatives, p-coumaric and m-coumaric acids. Similar to as observed for tomato [18] and sweet cherry [30], the main cutin constituents of pepper fruit are C16 monomers, ranging from 54% to 87%. Among those, the most important is 9(10),16-dihydroxy hexadecanoic acid, ranging from 50% to 82% of total cutin [46,65]. 2.1.9. Olive The cuticular wax of the olive (Olea europaea) cultivar “Arbequina” is mainly composed of triterpenoids (74–62%), followed by primary alcohols (9–11%) and fatty acids (8–9%). Further, among the most abundant components are oleanolic acid, hexacosanol (C26) and hexacosanoic acid (C26), respectively. No changes have been observed in total wax content and triterpenoid content during olive development; nevertheless, the VLC acyclic compounds increase. Despite no differences in total cutin amount being observed between the developmental stages of olive fruit, fatty acids, ω-hydroxy fatty acids and ω-hydroxy fatty acids with mid-chain hydroxy groups increased. Out of these, the predominant cutin monomers are 9(10),16-dihydroxy hexadecanoic, 9,10,18-trihydroxy octadecenoic and 9,10,18-trihydroxy octadecanoic acid [47]. 2.1.10. Guava The cuticular wax of the physiologically mature guava fruit (Psidium guajava L.) cultivar “Pearl” is mainly composed of fatty acids, primary alcohols and triterpenoids, such as uvaol, ursolic and maslinic acid, which are the most abundant. Octacosanoic acid (C28) and triacontanol (C30) are the most prominent constituents of fatty acids and primary alcohols, respectively. In cutin, the principal constituents are the monomers 9(10),16-dihydroxy hexadecanoic acid and 9,10-epoxy-18–hydroxy octadecanoic acid [48]. 2.1.11. Pitahaya At the mature stage, the wax of the pitahaya fruit (Hylocereus polyrhizus) cultivar “Hongshuijing” mainly comprises triterpenoids, followed by alkanes and fatty acids. Alkanes range from C20 to C35 of chain length, dominated by hentriacontane (C31) and tritiacontane (C33), whereas the most prominent triterpenoids are uvaol, lupenon, beta-amyrinon and beta-amyrin. Cutin comprises 9(10),16-dihydroxy hexadecanoic acid and 9,10-epoxy-18-hydroxy octadecanoic acid. The cuticle of pitahaya presents a wax/cutin ratio of 0.6 and compounds with an average chain length (ACL) of 30.5. Authors argue that ACL is higher than that reported for other petal and fruit cuticles and similar to that reported for leaf cuticles of other species [49]. One of the most abundant components of fleshy fruits is water, which is essential for fruit metabolism, fruit development and size increase [53]. In fleshy fruits, most water loss occurs through transpiration through the fruit surface [53], which is covered by the cuticle. It has been suggested that high wax/cutin ratios and compounds with high ACL could be a physiological adaptation to enhance the transpiration barrier of the fruit cuticle to withstand arid environments [49]. In addition, a high triterpenoids content could strengthen the mechanical support and plasticity of the cuticular membrane, protecting the fruit cuticle from the harmful effects of high-temperature stress [49]. In the next section of this review, studies regarding the physiological function of cuticles at harvest and during postharvest in fleshy fruits are described and discussed, mainly regarding fruit quality maintenance and water loss reduction. 3. Physiological Function of Fleshy Fruit Cuticle 3.1. Water Loss The loss-of-function mutation of beta-ketoacyl-CoA synthase (KCS) in tomato fruit, designated as SlCER6 mutant, causes a decrease of alkanes and aldehydes longer than C30 and an increase of intracuticular triterpenoids in the cuticle. An increase in permeability has been observed due to the reduction of the intracuticular VLC aliphatic compounds. The authors suggest that the transpiration barrier is mainly determined by the proportions of VLC aliphatic constituents and triterpenoids of the intracuticular waxes rather than epicuticular wax’s VLC aliphatic composition [19]. During tomato fruit development, SlCER6 shows a higher cuticle amount than wild type “MicroTom”. Nevertheless, a reduction in VLC alkanes and an increase in cyclic triterpenoids, together with an increase in water loss, are shown in waxes of SlCER6 [66]. Positional sterile (ps) mutant of tomato exhibits a similar phenotype to SlCER6, which is defective in the elongation of VLC fatty acids (VLCFA). No difference in cutin composition, cutin accumulation and cuticular wax accumulation between the mutant ps and its wild type is observed. Nevertheless, the wild type exhibits a remarkably higher level of alkanes and aldehydes in cuticular waxes and a remarkably lower level of esters and triterpenoids than ps fruits, with hentriacontane (C31) the most prominent alkane constituent in wild-type tomato waxes. Furthermore, a reduction in growth and weight and an increase in water loss are observed in ps fruits [67]. Studies with tomato fruit strongly support the statements that (i) cuticle rather than cell wall modifications could have a significant role in the reduction of the softening rate in fleshy fruits [12], (ii) waxes are the main cuticular structures that regulate the permeability in fleshy fruit peels [19,66], and that (iii) a specific change in cuticle wax composition rather than an increase in thickness or the total amount of cuticle has a more significant effect on the properties of fleshy fruits [19,66], especially for the reduction of water rate loss. Furthermore, several studies showed that epicuticular waxes, rather than intracuticular waxes, have a significant effect on fleshy fruit cuticle permeability [45], although other studies have shown opposite results [19]. Therefore, more experimental evidence is needed to fully elucidate the role of epicuticular and intracuticular waxes in the permeability properties of the cuticle. In “Navelate” sweet orange, the total epicuticular wax load significantly increases in the earlier stage of development, breaker (Bk), but remains unchanged in the later stages, namely mature green (MG), colored (C) and full-colored (FC). Terpenoids are mainly present in the Bk stage, and a notorious increase of hentriacontane (C31) happens in this stage. Cuticle transpiration and permeability are lower in the first two stages of development (Bk and MG), suggesting that alkanes and triterpenoids have a relevant function in controlling cuticle permeability during sweet orange fruit development [22]. It had been suggested that the early rise of epicuticular crystals, alcohols and triterpenoids observed at the beginning of the development of grapevine fruit could be due to a mechanism to protect the underlying cuticle from the exponential increase in volume and rapid surface expansion [42]. Like sweet orange [22] and grapevine [42], during nectarine development, an early active cuticle accumulation process is observed during the first growth period, mainly by triterpenoid deposition and cutin formation. Authors suggest that the increase in wax accumulation during the early stages of development allows the fruit to reduce water loss at harvest and during postharvest conditions [32]. The removal of epicuticular waxes in grape berry induces higher water loss and softening, indicating that epicuticular waxes could play a pivotal role in the postharvest quality of grape berry by reducing the water loss rate [45]. During postharvest storage, alkanes and aldehydes of Korla pear fruit cuticular waxes negatively correlate with weight loss, whereas fatty acids and alcohols have a positive correlation. The composition and morphological analysis of the Korla pear cuticle suggests that alkanes and aldehydes could contribute to wax crystal formation and consequently fruit water retention in Korla pear during postharvest storage [68]. Water deficit induces total aliphatic waxes accumulation at the end of grape berry development, accompanied by an obvious increase of VLC esters. This increase in cuticular VLC esters could be due to an adaptation to low water availability in grape berries. Nevertheless, these changes of composition do not cause a significant change in the berry transpiration rate [44]. On the other hand, it has been observed that water deficit leads to a lower triterpenoids/total aliphatic wax ratio in green and red berries. The apple fruit (M. domestica) cultivar “Florina” shows higher amounts of fatty acids, esters, primary alcohols and aldehydes than the “Prima” cultivar. However, it was not possible to establish a relationship between water permeability and cuticle composition for both cultivars [29]. It has been reported that the cuticle of physiologically mature guava fruit (P. guajava L.) has a large abundance of cyclic components, epoxy, hydroxy and carboxyl functional groups, and a relatively smaller amount of ACL of acyclic components than cuticles of other species and organs, which has been related with the low ability to reduce the transpiration of guava fruit cuticle [48]. In agreement, the cuticle of mature pitahaya fruit (H. polyrhizus) presents a wax/cutin ratio of 0.6 and an ACL of 30.5. Authors argue that the ACL is higher than that reported for other petal and fruit cuticles, similar to that reported for leaf cuticles of other plant species. They attribute these changes to the enhancement of the transpiration barrier of the pitahaya cuticle to withstand arid environments [49]. Cuticle composition analyses of pepper species C. annuum and C. chinense, which have high and low postharvest water loss rates, respectively, showed that postharvest fruit water loss is associated with the cuticle composition and the ratio of the wax constituents rather than the total wax amount. It has been shown that an increase in the total amounts of triterpenoid and sterols in the cuticular waxes of pepper fruits could increase postharvest water loss, while an increase in the amounts of primary alcohols and alkanes could reduce it—specifically, an increase of C29 and C31 alkanes [46]. In the case of cutin, it has been shown that water loss has a negative association with the C16/C18 ratio. The increase of total C16 monomers and 9(10),16-dihydroxy hexadecenoic acid in the cutin appears to induce postharvest fruit water loss in pepper fruits [46]. During olive development, a slight increase in the ACL of VLC acyclic compounds was observed, with a slight reduction of the C16/C18 ratio of cutin monomers; nevertheless, no differences were observed in cuticular permeability and water loss during olive fruit development [47]. The tomato cultivar “Delayed Fruit Deterioration” (DFD) exhibits a remarkable delayed softening at postharvest and remains firm for at least six months at fully ripe stages, but it otherwise undergoes a normal ripening process. No significant differences were found in the patterns of wall polysaccharide modification and the expression of genes related to wall degradation between DFD and the normal softening AC cultivar. However, DFD showed a lower transpiration rate, lower water loss, higher cellular turgor, higher firmness and a thicker and more swelled pericarp at ripening stages than AC [12]. Although DFD and AC have similar cuticle anatomies, DFD shows a stronger cuticle and a higher total wax amount. Besides, a significant increase in alkadienes in red ripe fruits is shown in DFD, but not in AC. Based on these data, the authors suggested that the delay of the softening phenotype could be due to the significant increase in alkadienes and the absence of naringenin in the cuticular wax of DFD, which has been associated with both mechanical support and turgor maintenance through water loss reduction [12]. In agreement, it has been shown that water stress increases fruit firmness and total cuticle, total wax and triterpenoids amounts, whereas it decreases cuticle permeability, transpiration rate and the relative amount of VLC alkanes in AC tomato fruits, which suggests an association between cuticle characteristics, transpiration and fruit firmness. In addition, an increase in total cutin amounts and 9(10),16-dihydroxy hexadecenoic acid was shown in AC [9]. Water stress does not affect cuticle permeability and thickness in DFD but induces an increase in both characteristics in AC tomato fruits. Actually, after water stress, the cuticle of AC shows similar characteristics to that of DFD, which suggests a change in cuticle metabolism in response to low water availability conditions in tomato [9]. It has been suggested that high amounts of alkanes and low amounts of triterpenoids in cuticles reduce the transpiration of fruit surfaces in fleshy fruits [46,66,67]. This study showed that cuticle permeability was positive and negatively correlated with the total cutin amount and the proportion of VLC alkanes in AC fruits, respectively. Besides, the levels of cyclic triterpenoids were positively correlated with the water loss rate [9]. The cuticles of mango cultivars “Kent”, “Tommy Atkins”, “Manila”, “Ataulfo”, “Criollo” and “Manila” exhibit different epicuticular wax deposition patterns, architectures and cutin compositions at the mature-green stage and during postharvest, accompanied by different water transpiration rates, firmness and fruit quality appearance. During postharvest, the mango “Tommy” cultivar has a higher wax deposition and cuticle thickness and exhibits a lower percentage of weight loss and less visual deterioration than the “Criollo” cultivar. Authors suggest that cuticle characteristics observed in premium cultivars such as “Tommy” are potential factors that could be associated with fruit quality preservation during postharvest storage [69]. 3.2. Postharvest Storage The amounts of both epi- and intracuticular waxes of mandarin “Satsuma” fruit (C. unshiu) increase after 20 days of room temperature (25 °C) storage, but they decrease after 40 days. A decrease in terpenoids and fatty acids and an increase in the proportion of alkanes is shown after 40 days of storage. Further, the total cutin amount decreases during postharvest storage, but the proportion of almost all cutin components remains stable [25]. The navel orange cultivar “Newhall” has a higher total cuticular wax and epicuticular wax amount than mandarin “Satsuma”. Notably, a significantly higher amount of hentriacontane (C31), and C24 and C26 chain length fatty acids and aldehydes is observed. During seven days at 25 °C and 40–50% relative humidity of postharvest conditions, navel orange exhibited a lower weight loss than mandarin [24], which could be due to the difference in the epicuticular wax content and composition observed. During postharvest, the peach melting cultivar “October Sun” shows a more dramatic firmness loss and weight loss than the non-melting cultivar “Jesca”. At harvest, wax percentages are similar in both cultivars, whereas cutin percentages are significantly higher in “October Sun” than in “Jesca”. Five days after harvest, the total wax and cutin yields remain unchanged in “October Sun”, whereas in the “Jesca” cultivar, both wax and cutin significantly increase. At commercial harvest, the ratio of alkanes to triterpenoids and sterols is 0.31 in “October Sun” and 0.65 in “Jesca”. These data strongly suggest that the increasing alkanes play a role in maintaining the firmness and reducing weight loss in non-melting “Jesca” cultivars [31]. The total wax content of Korla pear fruit increases during 30 days of postharvest storage, but it decreases at day 90. Furthermore, alkanes and aldehydes show a negative correlation with weight loss of Korla pear during postharvest, whereas fatty acids and alcohols have a positive correlation [68], suggesting that alkanes play an important role in reducing water loss. In apple cultivars “Stark”, “Golden”, “Mutsu”, “Golden Delicious”, “Camachi”, “Huahong”, “Jona Gold”, “Red Star”, “Ralls” and “Mashima Fuji”, a decrease in total cuticular wax amount is observed after 49 days of postharvest storage, with a decrease in alkanes and primary alcohols and an increase in fatty acids proportion. A relationship between weight loss rate and total wax, total alkanes and C54 alkanes is shown in all the 10 cultivars, suggesting that alkane biosynthesis is essential for reducing weight loss during postharvest storage in apples [59]. Through the cuticle wax analysis of 35 cultivars of pear (Pyrus spp.) mature fruits, it has been shown that the cultivar with the longest postharvest storage period also showed a higher wax concentration [37]. In berries, lingonberry fruit (V. vitis-idaea), which is characterized as having a longer shelf-life than honeysuckle (Lonicera caerulea), and strawberry tree (Arbutus unedo), a higher content of triterpenoid acids in the cuticle was recorded. It has been suggested that triterpenoid acids might be related to lingonberry surface firmness and durability, probably due to the mechanical properties that they provide and the antimicrobial effect [64]. The main quality preservation strategies used to maintain the fruit quality at postharvest are based on temperature regulation such as cold storage and the application of ethylene regulators such as 1-methyl cyclopropane (1-MCP). Furthermore, controlled atmospheres are utilized with the same goal [70]. Nevertheless, during development and postharvest, fleshy fruits are susceptible to phytopathogen attack and the development of physiological disorders, such as cracking, russeting and chilling injury [70]. In Table 3, cuticle composition changes observed in response to postharvest storage conditions in fruits are shown. It has been reported that cuticle composition could have a relevant function regarding phytopathogens and the susceptibility to physical disorders. In the next section, the effect of postharvest treatments on cuticle composition and the relationship between cuticle composition, phytopathogen attack and physical disorders susceptibility are described. 3.3. Cold Storage Different patterns of changes in response to cold storage have been shown among apple cultivars. The main constituents of the cuticular wax of apple “Maxi Gala” fruit after nine months of cold storage are alkanes and fatty acids, with nonacosane (C29) and cis-13,16-docosadienoic acid (C22:2) the main compounds of these two fractions, respectively [72]. The amounts of total cuticular wax and the main alkane constituents nonacosane (C29) and heptacosane (C27) decrease during seven months of postharvest storage at 0 °C in “Red Fuji” apple fruit [27]. During 140 days of cold storage, the total wax content of apple fruit cultivar “Starkrimson” increases from day 0 to day 80, then decreases at day 140 [28]. The total epicuticular wax content of sweet orange fruit increases after 30 days of postharvest cold storage (4 °C), then decreases at day 40, whereas at 25 °C, a continuous increase occurs during 40 days of storage. At 4 °C, the total cutin amount decreases continuously, whereas at 25 °C, an increase is observed at 20 and 40 days of storage. At 4 °C, triterpenoids increase continuously during 20 days and then decrease after 40 days of storage. At the same time, a continuous increase in triterpenoids and a decrease in fatty acid is observed during 40 days of storage at 25 °C. At 4 °C, alkane composition remains stable, whereas at 25 °C, the alkane fraction increases. Moreover, nonacosane (C29) becomes the main alkane after 40 days of storage at 25 °C [23]. Changes in cuticle amounts and composition have been observed in response to postharvest at 20 °C and 0 °C for both “Somerset” and “Celeste” sweet cherry fruit cultivars, with a general increase in cuticle amount in response to cold storage [61]. Ursolic acid content has been positively associated with weight loss and softening of blueberry fruit at postharvest cold storage, whereas a negative association has been reported for oleanolic acid. During 45 days of postharvest storage at 0 °C, blueberry “Duke” was more prone to softening and dehydration than the “Brigitta” variety, which was highly correlated with the higher ursolic acid content in the triterpenoid wax fraction of “Duke” blueberry [38]. Cold storage at 4 °C for 30 days reduces the total wax content of both “Legacy” (V. corymbosum) and “Brightwell” (V. ashei) blueberry varieties, but differences in wax composition between both cultivars in response to cold storage have been reported. For the “Legacy” cultivar, diketones are the only VLC compound that decrease during the storage at 4 °C, whereas for “Brightwell”, a decrease in the content of all aliphatic VLC compounds was observed [40]. 3.4. Heat and UV Light The quality of fruits is affected by excessive exposure to heat and UV light, mainly due to the oxidation of proteins and enzymes. One of the physiological functions of fruit cuticles is protecting against UV light exposure and extreme temperatures [5,6]. An increase in thickness, cinnamic acid derivatives and chalconaringenin compounds of cuticle appears to play a pivotal role in modulating UV radiation exposure in tomato fruit [73]. Furthermore, conformational changes leading to the glass transition of the cuticle membrane could serve as an adaptation mechanism in response to a change in environmental conditions [73]. It has been shown that the heat capacity of cuticle depends on the developmental stages of tomato fruit and that the thermal properties of fruit cuticle could be regulated by phenolic compounds [73]. Heat treatment increases the wax contents amount of “October Sun” peach fruits, whereas the effect of heat on cutin is less clear [74]. After a room temperature storage period, peach subjected to heat treatment and cold storage showed a reduction of cutin amount. Furthermore, it has been shown that heat treatment reduces the acyclic/cyclic compounds ratio of peach fruits [74], which strongly suggests a major role of wax cyclic compounds in response to heat. 3.5. Ethylene Regulators and Controlled Atmosphere A controlled atmosphere (CA), dynamic controlled atmosphere (DCA) based on chlorophyll fluorescence (DCA-CF), DCA respiratory quotient (DCA-RQ) and 1-MCP application to apple fruits “Maxi Gala” do not affect the total cuticular wax content during cold storage conditions. Nevertheless, these treatments induce a change in the composition or concentration of specific wax constituents. DCA-CF leads to a higher concentration of nonacosane (C29) and a reduction of mass loss, whereas 1-MCP reduces the concentration of nonacosan-10-ol and specific fatty acid constituents [72]. Storage of mature apple “Cripps Pink” under CA, DCA-CF and DCA-RQ treatments increases the wax concentration from day 7 to 14 of shelf life at 20 °C. Besides, all treatments led to a general increase of unsaturated fatty acids. Particularly, an increase in cis-11,14-eicosadienoic acid (C20:2), nonacosane (C29) and tetracosanal (C24) was observed. A controlled atmosphere leads to an increase in ursolic and oleanolic acids, whereas DCA-RQ leads to an increase in 10-nonacosanol (C29) [71]. In apple fruit cv. “Starkrimson”, the combination of ethephon treatment and storage at 0 °C accelerates total wax and VLC aliphatic deposition, whereas 1-MCP causes the opposite effect. One of the most obvious effects of ethephon and 1-MCP treatments was the increasing and decreasing of octacosanoic acid content, respectively [28]. In “Red Fuji” apple fruit, the total cuticular wax, nonacosane and heptacosane amounts decrease during seven months of postharvest storage at 0 °C, but 1-MCP treatment slightly suppresses this reduction [27]. Like “Starkrimson” apple [28], in “Red Fuji” apple, nonacosan-10-ol, nonacosan-10-one and hexadecanoic acid amounts increased after seven months of cold storage, but when fruits were treated with 1-MCP, their amounts were reduced [27]. Altogether, these findings support the relevant role of ethylene on the regulation of cuticular wax biosynthesis during the postharvest storage of fleshy fruits. 3.6. Physiological Disorders The specific aliphatic composition of cutin influences the mechanical properties of apple fruit cuticles. It has been proposed that microcrack formation is due to low elastic cutin properties due to the low presence of phenolic compounds [57]. Sweet cherry varieties with a higher amount of nonacosane (C29) are more tolerant to cracking than those with lower levels, suggesting that this wax component could protect sweet cherry from cracking [60]. There were no differences between alkane contents in both wild-type “Dangshansuli” pear fruit and its russet mutant “Xiusu” at early stages of development. Nevertheless, as the fruit grows, a higher content of alkanes is synthesized in “Dangshansuli” fruits. These differences in wax deposition and composition during pear development could contribute to russeting formation observed in the “Xiusu” fruit [35]. The cuticular waxes of jujube fruit (Ziziphus jujuba Mill.) cultivars “Popozao”, “Banzao” and “Hupingzao” are mainly composed of fatty acids, primary alcohols and alkanes. No significant differences were observed in the mass of cuticle or cutin between the cracking-resistant cultivar “Popozao” and the cracking-susceptible cultivar “Hupingzao”. Nevertheless, in the coloring stage of jujube development, “Popozao” shows a higher level of total wax than “Hupingzao”. It has been suggested that the severity of microcracks during fruit development could be related to a lower level of cuticular wax. Furthermore, during the coloring period, “Popozao” cuticular wax contains fewer fatty acids but more alkanes and aldehydes with a chain length greater than 20 carbon atoms than cultivars “Banzao” and “Hupingzao”. Based on the above-mentioned factors, it seems that alkanes and aldehydes with longer chain lengths could contribute to protecting against microcracking during the coloring period of jujube fruit enlargement [50]. No difference in thickness and total content of epicuticular wax is shown in oleocellosis-damaged lemon fruits, but a significant increase of alkanes (especially C29) and a decrease of the amount of aldehydes (especially C32) are shown, suggesting that oleocellosis can be related to the transformation of VLC aldehydes to VLC alkanes [26]. In Table 4, a summary of changes in cuticle composition reported in response to the appearance of skin disorders in fleshy fruits is shown. 3.7. Pathogen Infection In Asian pear, a negative association between cuticular wax concentration and the development of Alternaria rot has been shown, with a difference in resistance to Alternaria rot between cultivars [36]. Cuticular waxes of mature goji berry fruit (L. barbarum L.) are mainly composed of fatty acids, alkanes and primary alcohols, accounting for 47.09%, 21.66% and 11.98% of the total content, respectively. Despite the lower amount of terpenoids present (1.29%), experimental evidence shows an association between their presence and Alternaria alternata infection resistance in goji berry fruit [51]. It has been proposed that triterpenoids of cuticular waxes have a potential role in maintaining fruit integrity and postharvest quality and extending shelf-life because they provide mechanical toughness and protection against pathogen infections in lingonberry fruit (V. vitis-idaea) [64]. In agreement, the cuticular wax fraction of pear fruits, mainly composed of triterpenoids, inhibits A. alternata germination and growth in vitro, indicating that these compounds might contribute to antifungal protection against fungal pathogens in pear fruit [34]. It has been suggested that the increase in wax accumulation in the early stages of nectarine development could play a role in the resistance to fungus infection and water loss at harvest and during postharvest conditions, apparently due to the presence of triterpenoids. Oleanolic and ursolic acids appear to contribute to nectarines’ fruit resistance to brown rot caused by Monilinia laxa in the middle stages of development, but this resistance is not observed at the maturity stage. Authors argue that the lack of resistance showed at the mature stage could be due to the presence of microcracks in the fruit epidermis, which affect cuticle integrity, and a higher level of alkanes in the cuticle, which could serve as a carbon source favoring the growth of fungus [32]. The analysis of epicuticular wax components of mandarin “Satsuma” fruit (C. unshiu) showed that they could promote mycelial growth of Penicillium digitatum, whereas cutin components could inhibit conidial germination at different storage periods [25]. Furthermore, the tomato mutant DFD exhibits resistance to microbial pathogens even when the cuticular wax has been removed, which suggests a possible role of the cutin structure in the resistance to microbial pathogens in tomato fruit [12]. The studies mentioned above show that triterpenoids and cutin components, rather than VLC aliphatics, appear to have a more relevant function during the fruit defense to pathogen infection. The biochemical metabolism of fleshy fruit during development and postharvest has been widely studied. Although several studies showed the pivotal role of cuticle biosynthesis in fleshy fruit quality [9,10], studies using genes and proteins to enhance fruit quality through cuticle modification are still scarce. These studies have allowed the identification of genes and proteins that can be modified to extend fleshy fruits’ shelf life [3,75]. Furthermore, this knowledge can contribute to generating technologies to improve fruit quality by increasing postharvest shelf-life, enhancing pathogen resistance, reducing physical disorders and reducing softening and water loss rates. Below, studies regarding the molecular pathway of cuticle biosynthesis in fleshy fruits and its relationship with softening, water loss and fruit quality are described. 4. The Molecular Pathway of Cuticle Biosynthesis Cuticle composition is the phenotypic result of the activation of a specific biochemical pathway, which includes the participation of specific transcription factors, enzymes, transporters and RNA regulators in response to a stimulus [8,16]. Due to the considerable importance of cuticles in plant physiology, development and defense against biotic and abiotic stress, efforts to elucidate the molecular pathway of cuticle biosynthesis have been carried out, mainly in model plants such as Arabidopsis [13] and relevant crop plants such as wheat (Triticum astivum), rice (Oryza sativa), barley (Hordeum vulgare) and maize (Zea mays) [15]. In the case of fruits, most studies have been carried out in the model plant tomato (S. lycopersicum) [8,14,76]. Furthermore, by using massive RNA sequencing (RNAseq) and bioinformatic analysis, it has been possible to identify orthologous genes and proteins playing a role in cuticle biosynthesis in other fruits. However, some aspects of their regulation, the transport of their monomers across the cell wall and their macromolecular structure have not been clarified yet [5,16,77]. Both cutin and cuticular wax biosynthesis begin with C16 and C18 fatty acid (FA) precursors. Cutin biosynthesis involves the (i) synthesis of FA, (ii) FA oxidation, (iii) the export of the cutin monomers and (iv) their assembly [5]. Cuticular wax biosynthesis involves (i) FA elongation, (ii) functional groups modification (including primary alcohols and alkanes pathways) and iii) transport [11]. The mevalonic acid pathway synthesizes triterpenoid and sterol waxes [78]. In the next section of the review, genes and proteins involved in each of these processes are described, emphasizing discoveries carried out in fruits. 4.1. Cutin Biosynthesis The precursors C16 and C18 FA are synthesized in plastids, where they are bonded to an acyl carrier protein (ACP) forming a fatty acyl-ACP complex. In plastids, the enzyme ketoacyl ACP-synthase (KASIII) can synthesize C18 FA from C16 FA through the condensation of a malonyl-coenzyme A (malonyl-CoA) molecule. Fatty acyl-ACP thioesterase A (FATA) and B (FATB) release C16 and C18 FA from ACP [79]. After, they are exported to the cytoplasm, where long-chain acyl-CoA synthetase (LACS) esterifies the FA to a coenzyme A (CoA) molecule [80,81]. Fatty acyl-CoA (C16 and C18) are then transported to the endoplasmic reticulum (ER) where FA oxidation occurs [5]. Protein members of the cytochrome 450 family such as CYP86A carry out the terminal (ω) oxidation of FA [82]. Then, CYP77A carries out the mid-chain oxidation [83]. It has been demonstrated that CYP77A19 and CYP77A20 from Solanum tuberosum oxidize fatty acids in vitro. Besides this, it was proved that CYP77A19 and CYP77A20 expression partially restored the wild phenotype in an Arabidopsis cutin mutant [83]. Altogether, these reactions can lead to the synthesis of saturated and unsaturated ω-hydroxy FA, ω-midchain-dihydroxy FA, ω-9,10-trihydroxy FA and 9,10-epoxy ω-hydroxy FA [84]. In addition, the oxidation of the ω-hydroxyl group could be carried out, leading to the synthesis of α-ω-dicarboxylic FA. It has been suggested that a CYP86B carries out this reaction, but this has not been confirmed yet [5]. In vitro analysis has demonstrated that SlCYP86A69 plays a role in the ω-hydroxylation of octadecenoic acid in tomato fruits [85]. The mutation of the gen SlCYP86A69 causes a deficient cutin and altered fruit surface structure [86]. Glycerol-3-phosphate acyltransferase (GPAT) transfers the acyl group from acyl-CoA to a glycerol-3-phosphate molecule, leading to the synthesis of 2-monoacylglycerol (MAG) cutin monomers [87,88]. The heterologous expression in yeast of EgGPAT1 from Echium pitardii, homologous to AtGPAT4/AtGPAT8 from Arabidopsis, shows acyltransferase activity. Furthermore, the ectopic expression of EgGPAT1 leads to an increase in the synthesis of cutin monomers in leaves of tobacco [87]. Besides this, it has been reported that PpGPAT2 and PpGPAT4 from Physcomitrella patens play a role in cuticle biosynthesis. A mutation in the gen Slgpat6-a abolishes the enzymatic activity of GPAT6 and leads to the alteration of the cuticle thickness, composition and properties of tomato, which suggests that this protein plays a central function in fruit cutin biosynthesis [89]. It has been hypothesized that MAGs are exported from the endoplasmic reticulum (ER) across the plasma membrane and cell wall through the activity of ATP Binding Cassette subfamily G (ABCG/WBC) and Glycosylphosphatidylinositol-Anchored Lipid Transfer Protein (LTPG) transporters, respectively [11]. It has been demonstrated that the ATP Binding Cassette transporters (ABCG), AtABCG32 from Arabidopsis and SlABCG42 from tomato can export 10,16-dihydroxy hexadecanoyl-2-glycerol, and the free fatty acids can export omega-hydroxy hexadecanoic acid and hexadecanedioic acid in vivo [90]. LTPG1 is required for the export of lipids in Arabidopsis, and it has been reported that LTPG2 is targeted to the plasma membrane, suggesting that it has an overlapping role with LTPG1 in cuticular wax deposition [91,92]. Nevertheless, the mechanism through which cutin monomers move across the cell wall is still unclear [77]. Once in the surface of epidermal cells, proteins belonging to the GDSL-motif lipase/esterase (GDSL) superfamily and cutin synthases (CUS) incorporate MAG into the cuticle matrix through esterification [5]. In tomato fruit, it was demonstrated that GDSL1 plays a role in the extracellular accumulation of cutin polyester. By immunolabeling experiments, it was shown that GDSL1 is trapped in the cuticle of tomato fruit. Further, the silencing of GDSL1 leads to a reduction in ester bond cross-links in cutin [93]. Cutin monomers are esterified to form self-assembled particles named cutinsomes. CUS1 is an acyltransferase associated with the outer epidermal wall, which bonds cutin monomers contributing to cutin deposition in tomato fruit surface [94,95]. It has been hypothesized that cutin monomers are linked to the hydroxyl groups of the cell wall components by covalent ester and/or ether bonds [5]. However, the sites of deposition of the cutin polyesters on the outer faces of the cell wall are still unknown [77]. In Figure 1, the chemical structure of the main cutin components found in fleshy fruit cuticles and the main enzymes that could carry out the synthesis of these components are shown. 4.2. Cuticular Wax Biosynthesis 4.2.1. Fatty Acids Elongation Cuticular wax biosynthesis is carried out in the ER and includes FA elongation, functional group modification and wax transport. Like cutin monomers, wax biosynthesis uses the precursors FA-CoA (C16 and C18) and malonyl-CoA, generated by LACS, and acetyl-CoA carboxylase (ACCase), respectively [11]. A process of elongation is carried out in the ER membrane by proteins belonging to the fatty acid elongase (FAE) multienzyme complex. Each elongation cycle involves four consecutive reactions that perform the addition of two-carbon atoms to the acyl chain [11]. These reactions consist of (i) the condensation of malonyl-CoA to the FA-CoA molecule by the enzymes beta-ketoacyl-CoA synthases (KCS) [97], (ii) reduction of the beta-ketoacyl-CoA by beta-ketoacyl-CoA reductase (KCR), synthesis of enoyl-CoA by beta-hydroxyacyl-CoA dehydratase (HCD) and reduction of enoyl-CoA by enoyl-CoA reductase (ECR) [98]. Thereby, VLCFAs with 20 or more carbon atoms are synthesized from FA-CoA C16 and C18 monomers [99]. The Arabidopsis genome includes 21 genes predictively encoding KCS, from which ECERIFERUM6 (CER6/KCS6) carries out the most important role in wax biosynthesis [8]. Furthermore, it was demonstrated that CER6 (KCS6) is essential for the synthesis of VLCFA longer than C28 in tomato and appears to be involved in the generation of branched VLCFA [100]. It was shown that MdKCS2 from apple is located at the ER and its gene has a higher expression in apple pericarp. Besides, it was proved through ectopic expression that MdKCS2 increases wax content in Arabidopsis [101]. Through the analysis of Citrinae species, including the cultivated citrus C. clementina and C. sinensis, 96 genes encoding KCS have been identified, from which CsKCS2 and CsKCS11 proteins are located in the ER, and their genes increase their expression in fruits at the ripening stage, suggesting that they are involved in the accumulation of fruit cuticular wax during the ripening of citrus [102]. Once the FAs have been elongated, both VLC alcohols and VLC aldehydes can be generated through the reduction of VLCFA by fatty acyl-CoA reductases (FAR) enzymes, through the primary alcohols and alkanes pathways, respectively [8]. 4.2.2. Primary Alcohols Pathway The acyl-reduction pathway, also known as the primary alcohols pathway, carries out the reduction of the carboxylic group from VLCFA to form primary alcohols [8]. In agreement with that previously reported for plants [11], wax composition analysis in fleshy fruits shows that this pathway predominantly synthesizes primary alcohols in even-numbers carbon atom wax compounds. This reaction is mainly catalyzed by the alcohol-forming fatty acyl-CoA reductase named CER4 [103]. The expression of CsCER4, homologous to AtCER4 from Arabidopsis, changes during cucumber fruit development. The different expression level of CsCER4 between glossy type and waxy type cucumber suggests its role in wax biosynthesis in this fruit [104]. In the primary alcohols pathway, primary alcohols are used to synthesize esters through esterification to FA by wax synthetases (WS) enzymes. Wax synthase/diacylglycerol acyltransferase 1 (WSD1) is a WS located at the ER that catalyzes the synthesis of wax esters using mainly C16 acyl-CoA as precursors [105]. Further, it was suggested that CER17 can perform the desaturation of VLC acyl-CoA leading to the synthesis of unsaturated primary alcohols [106]. Thereby, the primary alcohols pathway leads to the generation of saturated and unsaturated VLC primary alcohols and wax esters [11]. 4.2.3. Alkanes Pathway The alkanes pathway uses as precursors the aldehydes generated by the reduction of the carboxylic group from VLCFA. In accordance with that previously reported for plants [11], wax composition analysis in fleshy fruits shows that this pathway predominantly synthesizes alkanes in odd-numbers carbon atom wax compounds. A decarbonylation of aldehydes is carried out to form alkanes by the enzymatic complex CER1-CER3/WAX2, leading to the elimination of one carbon atom in the carbon chain [107]. It has been proved that the gene CsWAX2 located at the ER from cucumber (Cucumis sativus L.), which is homologous to AtWAX2 from Arabidopsis, is highly expressed in the epidermis and is involved in wax biosynthesis and plant response to abiotic and biotic stress [108]. Cucumber fruits with a waxy phenotype have a higher expression of the gene CsCER1. The CsCER1 protein is located at the ER, and its gene is specifically expressed in the fruit epidermis. Drought, low temperature and abscisic acid induce the expression of CsCER1. Furthermore, abnormal expressions of CsCER1 induce alterations of cuticle permeance, drought resistance and VLC alkanes biosynthesis, suggesting that it can carry out a pivotal role in VLC alkanes synthesis, especially in response to abiotic stress [109]. In the alkanes pathway, the midchain oxidation of alkanes can be carried out by the cytochrome P450 enzyme (CYP96A15) mid-chain alkane hydroxylase (MAH1) to generate secondary alcohols and subsequently ketones [110]. Thereby, alkanes, aldehydes, secondary alcohols and ketones can be generated by this pathway [11]. 4.2.4. Triterpenoid Wax Biosynthesis The mevalonic acid pathway synthesizes triterpenoid and sterol waxes. The cyclization of 2,3-oxidosqualene leads to the synthesis of triterpenoids by the activity of oxidosqualene cyclase (OSC) enzymes [78]. Beta-amyrin synthase (BAS) activity leads to the synthesis of lupeol, alpha and beta-amyrin [111]—one of the most prevalent terpenoid compounds in fleshy fruit cuticles. In tomato fruits, triterpene synthase 1 (SlTTS1) and 2 (SlTT2) catalyze the synthesis of alpha and beta-amyrins [112]. Then, a carboxylic functional group is introduced to beta and alpha-amyrin by proteins of the cytochrome 450 family CYP716A, leading to the synthesis of oleanolic and ursolic acid, respectively [78,111]. Regarding cuticle biosynthesis, the introduction of carboxylic groups could pave the way for further polymerization by enzymes such as acyltransferases. It has been shown that CYP716A46 and CYP716A44 from tomato can synthesize oleanolic and ursolic acid by the C-28 oxidation of beta and alpha-amyrins, respectively [111]. 4.3. Transport of Cuticle Components It has been hypothesized that waxes are transported from the ER to the plasma membrane (PM) through Golgi vesicles, then exported to the apoplast by the activity of ABCG and LTPG transporters [16]. Like cutin precursors, it has been suggested that the transporters from the ABCG subfamily AtABCG11/CER5, AtABCG12, AtABCG13 and AtABCG32 are required for wax export in Arabidopsis [8]. It has been suggested that cuticular components are secreted through vesicles derived from the trans-Golgi networks that fuse with the PM. Further, other hypotheses suggest that waxes can be transported directly from the ER through ER-PM contact sites [11]. More recently, a passive mechanism of cuticular component transport involving a phase-separation process have been proposed [77]. This hypothesis suggests that the highly hydrophobic waxes could cross the cell wall through association with an aggregate of amphiphilic cutin monomers [77]. Nevertheless, the mechanism of transport and the molecular organization between cutin, waxes and the cell wall components have not been elucidated yet. Omics sciences facilitate the identification of transcripts and proteins involved in relevant biochemical pathways in fruits. Recently, efforts to identify genes and proteins involved in cuticle biosynthesis and transport in fleshy fruits have been carried out. In Figure 2, the structure of the main cuticular wax components found in fleshy fruit cuticles and enzymes that could carry out their synthesis are shown. In the next section of the review, a transcriptomic and proteomic analysis complemented with differential gene expression analysis such as qRT-PCR, contributing to the elucidation of the molecular pathway of cuticle biosynthesis, regulation, transport and its association with fruit quality, is described. 5. An Overview of the Current Status in the Elucidation of Molecular Mechanism of Cuticle Biosynthesis in Fleshy Fruits, Its Regulation, and Physiological Function Through laser microdissection (LMD), transcriptomic analysis and differential expression gene protocols, it has been possible to identify genes that express in peel and epidermis, playing a role in cuticle biosynthesis and stress response in fruits [113]. An increase in the expression of SlCER6, GDSL, LTP and MD-2-related lipid recognition domain-containing (ML) protein (MD2) correlates with the stages of major cuticle deposition during tomato fruit development [114]. Furthermore, by pyrosequencing and LMD, epidermal-specific transcripts related to cuticle biosynthesis in tomato fruit epidermis were identified, including CYP450, AtCER10, LACS, KCS6, CER2, CER6, CER1 and LTP, and the transcriptional factors SHINE1/WAX INDUCER 1 (SHN1/WIN1), zinc finger (ZNF), cutin deficient 2 (CD2) and MYB [76]. Thirteen genes specific to the exocarp and correlating with the cuticle deposition pattern of sweet cherry fruits (P. avium) were identified, including PaLipase, PaLTPG1, the CYP450 aberrant induction of type three genes 1 (PaATT1), LACERATA (PaLCR), PaGPAT4/8, PaLACS2, PaLACS1 and PaCER1 and the transcriptional factors PaWINA and PaWINB [115]. The major deposition of cuticle in sweet cherry fruits and the major expression of the genes PaLIPASE, PaFATB, PaLACS9, PaLTPG1, PaWBC11, PaWINA and PaWINB occurs at the earlier stages of development, strongly suggesting their participation in cuticle biosynthesis in cherry fruits. Nevertheless, the expression of PaCER5, PaLACS9, PaLTPG1 and PaWBC11 increases at later stages, despite the lack of a significant increase in cuticle deposition [116]. Through the transcriptomic analysis of mango peel during fruit development, transcripts orthologous to the transcriptional factors MiSHN1 and MiCD2, the enzymes MiCER1, MiCER2, MiCER3, MiKCS2, MiKCS6, MiCUS1 and MiCUS2 and the transporters MiWBC11, MiLTP1, MiLTP2, MiLTP3 and MiLTPG1 related to cuticle biosynthesis were identified. The higher expression of transcripts related to cuticle biosynthesis was shown at 153 DAF in ripening stages, and it was shown to correlate with the major cuticle deposition through mango development [117]. Through metabolomic and transcriptomic analysis, 27 genes related to cuticular wax biosynthesis and regulation from “Yuluxiang” pear fruit were identified, including PbrLACS1, PbrMAH1, PbrLTP3, PbrDGAT1, PbrWIN1, PbrKCS2, PbrKCS4, PbrKCS6, PbrKCS10, PbrECR, PbrCER9 and PbrKCR1. Furthermore, 12 genes coding for transcriptional factors and a new gene tentatively coding for a beta-amyrin synthase were identified. Deposition patterns during pear development positively correlate with the expression of these cuticle-related genes. These findings allowed the identification of the cuticle biosynthesis pathway in pear fruit [118]. At the green expanding stage in mandarin epidermis (C. clementina), the most expressed genes are related to cuticle biosynthesis, flavonoid biosynthesis and defense response [119]. During “Newhall” navel orange development, the expression of genes involved in cutin and wax biosynthesis significantly increases in later development stages. Out of these, a transcription factor MYB (GL1-Like) appears to regulate the wax synthesis by controlling the expression of CER, KCS, and LACS genes [119]. The analysis of “Navelate” sweet orange fruits and its abscisic acid (ABA) biosynthesis-impaired mutant “Pinalate” suggest that ABA could regulate wax biosynthesis genes. The expression levels of the genes analyzed in this study were consistent with the amounts of VLC aliphatics and terpenoids, which enhance the cuticle metabolism pathway for sweet orange [22]. It was shown through the transcriptomic and metabolomic analysis of “Newhall” navel orange and its glossy mutant “Gannan No. 1′ that the down-regulation of the genes FATB, LACS1, LACS2, KCS, FAR2 and CER3 and the transcription factor coding gene MYB16 was associated with a decrease in VLC aliphatic [120]. RNAseq analyses of “Newhall” navel orange peel and its glossy mutant “Ganqi 3’ suggest that the glossy phenotype could be due to the decrease in the expression of CsACC1, CsCAC3, CsKASI, four CsLACS, six CsKCS, three alkane-forming pathway genes (CsCER1-LIKE and CsCER3), five alcohol-forming pathway genes (CsCER4-LIKE and CsFAR2-LIKE) and fourteen ABCG transporters genes, including CsABCG11-LIKE, CsABCG15, and CsABCG32 [121]. Analysis by qRT-PCR showed that genes encoding cuticle biosynthesis enzymes and the transcriptional factors encoding genes CsMYB16, CsMYB94 and CsMYB96 have a low expression at 60 days after flowering (DAF), increase at 150 DAF and then decrease at 210 DAF in both “Newhall” navel orange and “Ganqi 3”. In contrast, the expression of CsLACS9, CsKCS2-LIKE1, CsKCS2-LIKE2, CsFAR2-LIKE2 and CsCER7 increased continuously during development. Nevertheless, at 150 and 210 DAF, “Ganqi 3’ exhibited a low expression of almost all cuticle-related genes analyzed [122]. Like “Ganqi 3’, the navel orange glossy mutant “glossy Newhall” exhibits a decrease in the expression of genes related to wax biosynthesis and export. Besides, a loss of epicuticular wax crystals is shown in “glossy Newhall” [21]. Authors suggest that the glossy phenotype in “Ganqi 3’ and “glossy Newhall” is due to a reduction in the VLC aliphatic compounds due to the decrease in the expression of wax-related genes observed [21,121]. Transcripts putatively involved in cuticle biosynthesis and with tissue-specific expression were identified in apple fruit “Florina” and “Prima”, including LACS2, KCS7/2, FIDDLEHEAD (FDH), HCD/PASTICCINO2 (PAS2), CER10, CER1, CER4, LCR, WBC11, LTPG1 and WIN1. A higher expression in the peel than in pulp was confirmed, and differences were observed between “Florina” and “Prima” cultivars. With these data, it was suggested that they can be associated with the known difference in wax composition between “Florina” and “Prima” cultivars [122]. The metabolomic and transcriptomic profiling of habanero peppers (Capsicum chinense Jacq.) genotypes PI 224448 and PI 257145, which exhibit low and high levels of cutin amounts, respectively, show that GDSL lipase, GPAT6, CYP86A, CYP77A and the transcription factors SHN1, ANTHOCYANINLESS2 (ANL2) and homeodomain GLABROUS 1 (HDG1) could be contributing to this phenotype [65]. Seventy-nine genes potentially related to wax biosynthesis were identified through transcriptomic analysis of blueberries. Differential expression analyses between waxy and non-waxy blueberries led to the identification of a FATB gene tentatively associated with the waxy coating phenotype [123]. Analysis of the glossy type of bilberry suggests that the contents of fatty acids and ketones in cuticle composition affect the amounts of crystals and the glaucous phenotype in this fruit. Furthermore, the specific expression of the genes CER26-like, FAR2, CER3-like, LTP, MIXTA and BAS suggest their role in wax biosynthesis and the glaucous phenotype’s appearance in the bilberry skin [54]. Transcripts coding for the transcriptional factors MYB42, MYB52 and MYB93, the enzymes LACS1, CYP86A, GPAT6, KCS4, KCS2, KCS10, CER1, CER3, CER6 and FAR and the transporters ABC, WSD and WBC11, related to cuticle biosynthesis, have been identified in the epidermis of apple fruit cultivar “Cox Orange Pippin”. A decrease in cuticular waxes, ursolic and oleanolic acid, along with low expression of LACS1/CER8, LCR, GPAT6, KCS2, 6 and 10 is shown on the russeted patches of the semi-russeted apple variety “Cox Orange Pippin” [124], suggesting a relationship between the expression of genes related to wax biosynthesis and the russeting development in fruits. Consistent with the changes shown in cuticle composition, genes involved in the synthesis of C16 and C18 FA and CER1 are induced by oleocellosis in lemon fruit, suggesting that the increase in the deposition of fatty acids and the content of VLC alkanes in cuticles is associated with the appearance of oleocellosis [26]. “Kordia” sweet cherry cultivar, which shows a cracking resistance phenotype, has a higher expression of PaWINB, WS and PaKCS6 during the fruit setting stage than the cracking susceptible “Bing” cultivar. Authors suggest that the cuticle deposition function of these genes could be involved in the tolerance to cracking observed in the “Kordia” cultivar [125]. Cold storage at 0 °C decreases the expression of the genes PpCER1, PpLACS1 and PpLipase in “October Sun” peach fruit, but after five days of room temperature storage, the expression levels of PpLACS1 and PpLipase increase. In addition, CO2 and heat treatment restored the expression of PpLACS1 of cold-stored fruits to similar levels to those of harvest conditions [74], suggesting a regulation of cuticle metabolism in response to CO2, heat and cold storage conditions. At postharvest, cold storage and 1-MCP treatment decreased the cuticular wax density, delayed wax crystal melting and senescence and reduced the expression of the genes MdCER6, MdCER4 and MdWSD1 in apple “Starkrimson” fruits, whereas ethephon induced the opposite effect. Authors suggest an effect of ethylene in cuticular wax composition and crystal morphology through the regulation of MdCER6 and the alcohol forming pathway in apple fruit during postharvest cold storage [126]. During tomato fruit development, the genes related to cuticle biosynthesis CUS1, GPAT4, CER6, triterpene synthase 2 (TTS2) and cutin deficient 3 (CD3) were expressed at higher levels during mature green than during red ripe stages. At standard conditions, AC tomato fruits have a lower expression of these genes than DFD; nevertheless, water stress treatment significantly increases their expression in AC, but not in DFD [9]. Water deficit increases the total wax and esters amount and the expression of the genes WSD1, CER1, CER2, CER3, CER4 and CER10 in grape berry fruits. Additionally, an increase in the wax compound with a chain length from C40 to C50 is shown. However, despite the change in cuticle composition observed, no significant difference in fruit transpiration was shown [44]. The expression of MIXTA, which codes for transcription factor type MYB, occurs predominantly in epidermal cells of tomato fruit. It has been shown that MIXTA silencing leads to a thinner cuticle, an increased susceptibility to pathogens and water loss, accompanied by a decrease in the expression of the genes CYP77A, CYP86A, LACS2, GPAT4, ABCG11, ABCG32, GDSL, KCS3 and SHN3, suggesting that MIXTA regulates wax biosynthesis and could modulate the integrity of tomato fruit during postharvest [127]. It was reported that the gene MdKCS2 shows a large expression in apple pericarp. Besides this, it was proved through ectopic expression that MdKCS2 improved drought resistance in Arabidopsis by changing epidermal permeability and increasing wax deposition. In agreement with these findings, it was shown that drought and salt stress induce the expression of MdKCS2 [101]. In pepper fruit, two linked quantitative trait loci (QTL) associated with reduced post-harvest water loss traits have been identified. Transcriptomic analysis showed that a higher expression of the genes CER1, CER3, LTP, FAR and CYP96A/MAH1, along with a decrease in FA and an increase in the amount of iso-alkanes in the cuticle, could be related to post-harvest water loss in pepper. Besides, a relationship between post-harvest water loss, a delayed over-ripening on the plant and reduced fruit softening after storage is suggested [128]. Efforts to elucidate the molecular pathway of fleshy fruits and the regulation and molecular response during fruit developmental stages in response to environmental conditions and treatments on plant or during postharvest conditions will contribute to the design of biotechnological strategies to develop plants adapted to grow and produce fleshy fruits under conditions of limited water supply, without affecting fruit productivity and quality. 6. Concluding Remarks The cuticle composition, amount and biosynthesis pattern during fruit development are clearly different among various fruits, suggesting a role of fruit adaptation to the different environments in which the different fruit species evolved. This composition has been correlated with the physiology of fruit phenotypes in different studies. The data generated by the analysis of genes playing a role in cuticle biosynthesis further support the involvement of cuticle-specific components with a given fruit phenotype. This also has allowed us to move towards the elucidation of the molecular mechanism of cuticle biosynthesis. The study of the genes involved in cuticle biosynthesis in different fruits seems to suggest that there is a universal molecular mechanism of fruit cuticle biosynthesis that is active in the different fruit species. The physiology of fruit cuticles is broad and includes responses to pathogen attack, biotic and abiotic stress, fruit quality and a role in development of physiological disorders. With all these data available along with those that are currently being generated, in the future, it will be possible to design fruits with stronger resistance to pathogen attack, that are less prone to develop physiological disorders, that have a low rate of weight loss and softening and that have a longer shelf life. This in turn will boost the sales of fruits to international markets, which is an important economic activity for developing countries such as Mexico. Funding This research was funded by the Mexican National Council of Science and Technology (CONACYT), PhD. Scholarship. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Biosynthesis pathway and chemical structure of common cutin monomers found in the fleshy fruit cuticle. Only the gene subfamily’s main name is included for reactions involving multiple paralogs. 9-hydroxy fatty acid structures are used to represent both 9 and 10 hydroxy fatty acid monomers. The main C16 and C18 monomers are used to exemplify the structure of 2-monoacylglycerol monomers. Abbreviations: Cytochrome P450 subfamily 86A, 86B and 77A (CYP86A, CYP86B and CYP77A, respectively); StearoyI-ACP desaturase (SAD); Glycerol-3-phosphate acyltransferase (GPAT). The figure was built based on the literature [5,8,16,82,83,84,85,86,87,88,89]. Chemical structures were drawn with the JSME Molecular Editor [96]. Figure 2 The biosynthesis pathway and chemical structure of common cuticular wax compounds found in the cuticle of fleshy fruits. Only the gene subfamily’s main name is included for reactions involving multiple paralogs. Twenty-four chain length carbon atoms are used to exemplify the main very long chain (VLC) wax compounds synthesized by the primary alcohols pathway. Twenty-three chain length carbon atoms are used to exemplify the main VLC wax compounds synthesized by the alkane pathway. Abbreviations: long-chain (LC); fatty acid elongase multienzyme complex (FAE); beta-ketoacyl-CoA synthase (KCS); beta-ketoacyl-CoA reductase (KCR); beta-hydroxyacyl-CoA dehydratase (HCD); Enoyl-CoA reductase (ECR); Fatty acyl-CoA reductase/ECERIFERUM1, 3, 4 and 17 (CER1, CER3, CER4 and CER17, respectively); Wax synthase/diacylglycerol acyltransferase 1 (WSD1); Mid-chain alkane hydroxylase (MAH1); Oxidosqualene cyclase (OSC); Cytochrome P450 subfamily 716A44 and 716A46 (CYP716A44 and CYP716A46, respectively). The figure was built based on the literature [6,8,11,13,16,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111]. Chemical structures were drawn with the JSME Molecular Editor [96]. plants-11-01133-t001_Table 1 Table 1 The main cuticle components present in fleshy fruits of different species. Fruit Layer Main Components References Tomato (Solanum lycopersicum) Cuticular wax Alkanes (C29 and C31) and triterpenoids (amyrins) [18,19,20] Epicuticular VLC aliphatic compounds Intracuticular Pentacyclic triterpenoids Cutin 9(10),16-dihydroxy hexadecanoic acid Orange (Citrus sinensis) Cuticular wax Fatty acids (C26), alkanes (C31), primary alcohols, aldehydes and triterpenoids [21,22,23] Epicuticular Fatty acids and alkanes Intracuticular Fatty acids, triterpenoids and primary alcohols Cutin cis-9-hexadecenoic acid and cinnamic acid Mandarin (Citrus unshiu) Cuticular wax Aldehydes, alkanes, fatty acids and primary alcohols [24,25] Epicuticular Fatty acids, followed by alkanes and terpenoids Intracuticular Terpenoids, followed by alkanes and fatty acids Cutin Cinnamic acids, hexadecanedioic acid (C16) and hexadecanoic acid (C16) Lemon (Citrus limon) Epicuticular Alkanes (C31), aldehydes, alcohols and fatty acids [26] Apple (Malus domestica) Cuticular wax Fatty acids, alkanes (C29), triterpenoids (ursolic acid) and primary alcohols [27,28,29] Cutin 9(10),16-dihydroxy hexadecenoic acid Sweet cherry (Prunus avium) Cuticular wax Triterpenes (ursolic acid), alkanes (C29) and alcohols [30] Cutin 9(10),16-dihydroxy-hexadecanoic acid Monocarboxylic, dicarboxylic and ω-hydroxylated octadecanoic acids. Nectarine/Peach (Prunus persica) Cuticular wax Triterpenoids (oleanolic and ursolic acid), alkanes (C23 and C25) and fatty acids [31,32] Cutin Mono-carboxylic, α,ω-dicarboxylic and ω-hydroxylated fatty acids 18-hydroxyoleic acid Drupe fruit (Prunus laurocerasus) Cuticular wax Triterpenoids (ursolic acid), fatty acids, alkanes and primary alcohols [33] Cutin 9(10),-dihydroxy hexadecanoic acid, 9,10-epoxy 18-hydroxy octadecanoic acid and 9,10,18-trihydroxy octadecanoic acid Pear (Pyrus spp.) Cuticular wax Alkanes (C29), primary alcohol (C30), terpenoids and fatty acids [34,35,36,37] Berries (Vaccinium spp.) Cuticular wax Triterpenoids (oleanolic and ursolic acid), beta-diketones and fatty acids [38,39,40,41] Grape (Vitis vinifera) Cuticular wax Triterpenoid (oleanolic acid), primary alcohols, fatty acids and esters. [42,43,44,45] Epicuticular Primary alcohols, fatty acid, esters and terpenoids Intracuticular Triterpenoid (oleanolic acid) Pepper (Capsicum spp.) Cuticular wax Alkanes (C29 and C30), triterpenoids (amyrins), phytosterols, fatty acids and primary alcohols [46] Cutin 9(10),16- dihydroxy hexadecanoic acid Olive (Olea europaea) Cuticular wax Triterpenoids (oleanolic acid), primary alcohols (C26) and fatty acids (C26) [47] Cutin 9(10),16-dihydroxy hexadecanoic, 9,10,18-trihydroxy octadecenoic and 9,10,18-trihydroxy octadecanoic acids Guava (Psidium guajava) Cuticular wax Fatty acids (C28), primary alcohols (C30) and terpenoids (uvaol, ursolic acid and maslinic acid) [48] Cutin 9(10),16-dihydroxy hexadecanoic acid and 9,10-epoxy-18–hydroxy octadecanoic acid Pitahaya (Hylocereus polyrhizus) Cuticular wax Triterpenoids, alkanes (C31 and C33) and fatty acids [49] Cutin 9(10),16-dihydroxy hexadecanoic acid and 9,10-epoxy-18-hydroxy octadecanoic acid Jujube (Ziziphus jujuba) Cuticular wax Fatty acids, primary alcohols and alkanes [50] Goji berry (Lycium barbarum) Cuticular wax Fatty acids, alkanes and primary alcohols [51] plants-11-01133-t002_Table 2 Table 2 Cuticle composition changes recorded during fleshy fruits development. Fruit Scientific Name Observation References Tomato Solanum lycopersicum L. Continuous increase of alkanes, triterpenoids, and cutin. [18] Orange Citrus sinensis L. Osbeck Increasing alkanes amount. Decreasing fatty acids and aldehydes amount. Increasing epicuticular wax, terpenoid and hentriacontane amounts at the earlier stage. [22] Apple Malus domestica Increasing cuticular wax, nonacosane and heptacosane amounts. [27] Sweet cherry Prunus avium L. Decreasing of triterpenes and cutin amount. [30] Nectarine Prunus persica L. Batsch Increasing triterpenoids and cutin amounts at earlier stages, then they decrease until maturity. Increase in alkanes amount at the later stages. [32] Drupe fruit Prunus laurocerasus L. Increasing cutin, triterpenoids and cinnamic acid amounts at later stages. [33] Pear Pyrus bretschneideri Increasing fatty acids amount at earlier stages and then decreases. Continuous increase of triterpenoids amount. [35] Blueberry Vaccinium corymbosum and V. ashei Continuous increase of total wax and triterpenoids amounts at ripening. Decrease in the relative content of diketones. Increase in the relative content of aldehydes, primary alcohols, fatty acids and alkanes. [40] Bilberry Vaccinium myrtillus Decrease in triterpenes amount. Increase in aliphatic compounds amounts. [54] Grape Vitis vinifera Increasing triterpenoid, primary alcohols and aldehydes amounts at early stages and decreasing at ripening. Increase alkyl esters and fatty acids amount at later stages. [42,43,44] Olive Olea europaea Increasing in very long chain of acyclic, ω- hydroxy fatty acids and ω- mid-chain dihydroxy fatty acids amounts. Increasing in average chain length of the compounds. Decreasing of C16/C18 ratio of cutin monomers. [47] Mango Mangifera indica L. Increasing epicuticular wax and cutin amounts. [55] plants-11-01133-t003_Table 3 Table 3 Cuticle composition changes in response to different postharvest storage conditions of fleshy fruits. Fruit Conditions Observations Ref. Room temperature storage Peach (P. persica L. Batsch.) 5 days (20 °C). Increasing of wax and cutin amount. [31] Sweet orange (C. sinensis) 40 days (25 °C). Continuous increasing of epicuticular wax, triterpenoids and nonacosane amounts Increasing of cutin at 20 and 40 days. Decreasing of fatty acids amount. [23] Mandarin (C. unshiu) 40 days (25 °C) Increasing epi- and intracuticular waxes amounts after 20 days, but decreasing after 40 days. Decreasing of terpenoids, fatty acids, and cutin amounts. Increasing of alkanes amount. [25] Apple (M. domestica) 49 days (25 °C) Decreasing of wax, alkanes and primary alcohols amounts. Increasing in fatty acid proportion. [59] Apple (M. domestica) 8 months in CA, DCA-CF, and DCA-RQ (20 °C) Increasing wax concentration from 7 to 14 days. Increasing of unsaturated fatty acids, cis-11,14-eicosadienoic acid, nonacosane and tetracosanal amounts. [71] Cold storage Sweetcherry  (P. avium L.) 5 days (0 °C) Increase in cuticle amount. [61] Blueberry (V. corymbosum and V. ashei) 30 days (4 °C) Decreasing of total wax content. [40] Sweet orange (C. sinensis) 40 days (4 °C). Epicuticular wax amount increases at 30 days then decreases at 40 days. Cutin amount decreases continuously. Triterpenoids amount increase continuously at 20 days and then decrease at 40 days. [23] Korla pear (Pyresbretschnei deli) 90 days (0 °C) Increasing of wax content during 30 days, but decreasing at day 90. [68] Apple (M. domestica) 140 days (0 °C) Increasing total wax content from day 0 to day 80, then decreases at day 140. [28] Apple (M. domestica) 7 months (0 °C) Decreasing of total cuticular wax, nonacosane (C29) and heptacosane (C27) amounts. Increasing of nonacosan-10-ol, nonacosan-10-one and hexadecanoic acid amounts. [27] Asian pear (P. sinkiangensis and P. bretschneideri) 7 months (3 °C) Decreasing of total wax and variety of wax compounds. Decreasing primary alcohols amounts. Increasing alkanes amount. [36] Treatments with Ethylene and inhibitors of ethylene action Apple (M. domestica) 140 days with ethephon (0 °C) Accelerating of total wax and VLC aliphatic deposition. Increasing octacosanoic acid. [28] Apple (M. domestica) 140 days with 1-MCP (0 °C) Delaying of total wax and VLC aliphatic deposition. Decreasing of octacosanoic acid. [28] Apple  (M. domestica) 7 months (0 °C) with 1-MCP Decreasing of nonacosan-10-ol, nonacosan-10-one and hexadecanoic acid. [27] Abbreviations: Controlled atmosphere (CA); Dynamic controlled atmosphere by Chlorophyll Fluorescence (DCA-CF); Dynamic controlled atmosphere by Respiratory Quotient (DCA-RQ); 1-methylcyclopropane (1-MCP). plants-11-01133-t004_Table 4 Table 4 Cuticle composition associated with physical skin disorders of fleshy fruits. Fruit Physical Phenotype Observation References Glossy phenotype Orange “Newhall” (C. sinensis) Glossy mutant “Glossy Newhall” Low amounts of aldehydes, alkanes, and wax crystals during fruit development. Less amount of epicuticular wax at later stages of development. [21,56] Bilberry (V. myrtillus) Bilberry “Glossy Mutant” A high proportion of triterpenes, and a lower proportion of fatty acids and ketones. [54] Physical disorder Pear “Dangshansuli” (P. bretschneideri) Russet mutant “Xiusu” Low content of alkanes and high content of alcohols during development and ripening. [35] Jujube “Popozao” (Z. jujuba Mill.) Cracking-susceptible “Hupingzao” Low amount of total wax, alkanes, and aldehydes with a chain length greater than C20, and high amount of fatty acids. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095085 ijms-23-05085 Article Machine Learning and Pathway Analysis-Based Discovery of Metabolomic Markers Relating to Chronic Pain Phenotypes https://orcid.org/0000-0003-3504-4663 Miettinen Teemu 1 https://orcid.org/0000-0001-8999-6040 Nieminen Anni I. 2 Mäntyselkä Pekka 3 https://orcid.org/0000-0002-4899-605X Kalso Eija 1† https://orcid.org/0000-0002-5818-6958 Lötsch Jörn 45*† Helyes Zsuzsanna Academic Editor 1 Pain Clinic, Department of Perioperative Medicine, Intensive Care and Pain Medicine, Helsinki University Hospital and SleepWell Research Programme, University of Helsinki, 00014 Helsinki, Finland; teemu.miettinen@helsinki.fi (T.M.); eija.kalso@helsinki.fi (E.K.) 2 Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, 00014 Helsinki, Finland; anni.nieminen@helsinki.fi 3 Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio Finland, and Primary Health Care Unit, Kuopio University Hospital, 70211 Kuopio, Finland; pekka.mantyselka@uef.fi 4 Institute of Clinical Pharmacology, Goethe—University, Theodor—Stern—Kai 7, 60590 Frankfurt am Main, Germany 5 Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany * Correspondence: j.loetsch@em.uni-frankfurt.de; Tel.: +49-69-6301-4589; Fax: +49-69-6301-4354 † These authors contributed equally to this work. 03 5 2022 5 2022 23 9 508521 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/). Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabolomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, sleep, and obesity in 71 men and 122 women undergoing tertiary pain care. They were examined for patterns in d = 97 metabolomic markers that segregated patients with a relatively benign pain phenotype (low and little bothersome pain) from those with more severe clinical symptoms (high pain intensity, more bothersome pain, and co-occurring problems such as sleep disturbance). Two independent lines of data analysis were pursued. First, a data-driven supervised machine learning-based approach was used to identify the most informative metabolic markers for complex phenotype assignment. This pointed primarily at adenosine monophosphate (AMP), asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine, and secondarily at cysteine and nicotinamide adenine dinucleotide (NAD) as informative for assigning patients to clinical pain phenotypes. After this, a hypothesis-driven analysis of metabolic pathways was performed, including sleep and obesity. In both the first and second line of analysis, three metabolic markers (NAD, AMP, and cysteine) were found to be relevant, including metabolic pathway analysis in obesity, associated with changes in amino acid metabolism, and sleep problems, associated with downregulated methionine metabolism. Taken together, present findings provide evidence that metabolomic changes associated with co-occurring problems may play a role in the development of severe pain. Co-occurring problems may influence each other at the metabolomic level. Because the methionine and glutathione metabolic pathways are physiologically linked, sleep problems appear to be associated with the first metabolic pathway, whereas obesity may be associated with the second. chronic pain phenotypes sleep disorders obesity metabolic markers metabolic pathways supervised machine Governmental Research FundingTYH2014214 Landesoffensive zur Entwicklung wissenschaftlich−ökonomischer Exzellenz (LOEWE), Zentrum: Translational Medicine and Pharmacology (JL)The work has been supported by the Governmental Research Funding (TYH2014214) (EK), and Landesoffensive zur Entwicklung wissenschaftlich−ökonomischer Exzellenz (LOEWE), Zentrum: Translational Medicine and Pharmacology (JL). JL was also supported by the Deutsche Forschungsgemeinschaft (DFG LO 612/16−1). The funders had no influence on the analytical method design, data selection and analysis, decision to publish, or preparation of the manuscript. FIMM metabolomics unit was supported by HiLIFE and Biocenter Finland. ==== Body pmc1. Introduction Recent advances in knowledge of the biochemical basis of the pathophysiological processes involved in pain have involved metabolic processes in the production or degradation of active endogenous or exogenous molecules relevant to pain modulation [1]. Metabolic markers have been associated with various pain etiologies, such as rheumatoid arthritis [2,3], interstitial cystitis [4], or fibromyalgia [5,6]. For example, processes related to energy metabolism or biochemical changes in lipids and amino acids have been shown to differ in fibromyalgia patients from healthy controls [7]. In addition, metabolomic markers have been associated with specific clinical presentations of pain, examples being choline, phosphocholine, alanine, and taurine levels with the presence of nociceptive or neuropathic pain [8], ornithine levels with the characteristics of musculoskeletal pain [9], or epiandrosterone sulfate levels with widespread pain [10,11]. Glutamate levels may also be associated with nociception for various pain conditions [12]. The interplay between pain and metabolomics is likely complex, as persistent pain is often accompanied by a host of co-occurring problems which may also manifest at the metabolomics level. In a recent study of a cohort of 277 patients undergoing tertiary care for persistent pain, six different pain phenotype parameters yielded a subgroup structure based primarily on affective pain interference and number of pain areas [13]. Interestingly, among the 54 non-pain-related parameters, sleep problems proved most relevant for assigning a patient to the pain phenotype subgroup. A high number of chronic pain patients suffer from sleep problems. The prevalence for insomnia was 39.8% among those with fibromyalgia and 25.1% among those with musculoskeletal disorders [14]. Patients who have higher pain intensity, more widespread pain, and longer lasting pain report more sleep problems [15,16]. Studies regarding insomnia, obstructive sleep apnea (OSA), and experimental sleep deprivation and fragmentation have all suggested alterations at the metabolomics level. These include elevated levels of branched-chain amino acids (BCAAs) and altered glucose metabolism [17]. Obesity is another problem co-occurring with more severe pain [18]. It is associated with many metabolomic changes, such as elevated levels of BCAAs and aromatic amino acids (AAAs), and changes in acylcarnitines, fatty acids (such as phospholipids), and carbohydrates (such as glucose and mannose) [19]. In the present study, 110 polar metabolite serum markers covering 24 metabolite classes [20] were acquired from a cohort of patients analyzed previously for pain phenotype subgroup structure. We examined the associations of these markers with the identified subgroups (lower pain intensity and less interfering pain vs. higher pain intensity, more interfering pain, and more co-occurring problems) [13] in a data-driven approach using machine learning algorithms [21] and related feature selection techniques [22]. To further explore the complex reciprocal interactions between pain and co-occurring problems, we investigated metabolic pathways in relation to obesity and sleep problems, expecting to find alterations in, for example, amino acid metabolism [17,19]. Finally, we were interested whether these three analyses would suggest some common metabolomic markers or interacting mechanisms for those with more severe pain, and co-occurring obesity and sleep problems. 2. Results Of the n = 320 patients with persistent pain treated in tertiary care, n = 277 patients had the necessary information about pain to be included in the previous analysis (Figure 1). This had established a patient subgroup structure based on relevant pain-related and other clinical symptoms [13]. Since in 84 of these patients the metabolomics had not been analyzed (due to patient non-compliance), the cohort analyzed comprised 71 men and 122 women. Descriptive statistical parameters relating to patient demographics, living situation, other pains, treatment experiences, comorbidities, and lifestyle are shown in Table 1. The raw data from the metabolomic markers are shown in Supplementary Figure S1. 2.1. Metabolomic Markers Informative for Pain Phenotype Assignment Of the analyzed patients, 57 belonged to the subgroup characterized by lower pain intensity and less pain interference. Sex and age distributions were equal across the subgroups (sex: χ2 = 0.23101, df (degrees of freedom) = 1, p = 0.6308, age: t = −0.16011, df = 86.444, p = 0.8732); however, BMI was lower in the patients belonging to the group with lower pain intensity and less pain interference (26.3 ± 5.15 kg/m2) than in the other patients (29.2 ± 6.1 kg/m2; t = −3.7273, df = 121.11, p = 0.0002956). The Boruta feature selection analysis identified five metabolomic markers definitely important (AMP, asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine), two others as tentatively important (cysteine and nicotinamide adenine dinucleotide, NAD), while 90 markers were classified as unimportant and excluded from further analyses (Figure 2). Of note, none of these markers was found when running the same algorithm on permuted metabolomic data. Because the five confirmed metabolomic markers were insufficient in subsequent validation to successfully train a random forest or other classifier, all seven above-mentioned markers were treated as important for the pain-related subgroup structure of this cohort. When training random forest classifiers with these markers (Table 2), balanced classification accuracy was better than random assignment, and AUC-ROC was 70% (66.3–72.2%). Balanced classification accuracy was also better than random assignment for the other machine-learning algorithms used to validate the selected set of metabolomic markers. Of note, statistical comparisons of markers between patient subgroups using Wilcoxon–Mann–Whitney U tests (Figure 3) showed significant effects for two of the selected markers, AMP (W = 3057, p = 0.0208) and glucuronic acid (W = 3163, p = 0. 04415), both of which were lower in the low-pain subjects, while, for two others, group differences showed a tendency toward statistical significance (p < 0.1: asparagine, propionylcarnitine); however, none of these effects would pass a Bonferroni α correction. 2.2. Metabolomic Markers Relevant to Obesity and Sleep Examination of the effects of obesity and sleep problems on metabolomics continued with univariate statistical analysis (t-test and fold change) and metabolite pathway analyses. The volcano plot analysis (Table 3), used to visualize the data, showed metabolomic markers with statistically significant differences when patients with obesity were compared to those without: 11 amino acids (glutamate, asparagine, glycine, tyrosine, valine, alanine, isoleucine, symmetric dimethylarginine, creatinine, creatine, citrulline), three acyl-carnitines (isovalerylcarnitine, propionylcarnitine, hexanoylcarnitine), two alkyl-phenylketones (hydroxykynurenine, kynurenine), sugar acid (glucuronic acid), three purine nucleosides (inosine, adenosine, guanosine), a bile acid (chenodeoxycholic acid), a (5′->5′)-dinucleotide (NAD), and a pyrimidine nucleoside (cytidine). In the pathway analysis (Figure 4), the top 10 enriched metabolic routes were related to amino acid metabolism and energy production, among others. Further detailed results are provided in Supplementary Table S1. In the t-test analysis (Table 3), seven metabolomic markers differed statistically significantly when those having recurring sleep problems were compared to those sleeping normally or having only mild sleep problems: six amino acids (serine, symmetric dimethylarginine, homocysteine, dimethylglycine, GABA, asymmetric dimethylarginine) and choline. In pathway analysis (Figure 4), the top enriched metabolic routes related to phospholipid synthesis and methionine metabolism, among others. 2.3. Convergences in the Findings between the Machine-Learning Approach and Pathway Analyses Contrasting the findings from the machine learning approach with pathway analyses it showed that four metabolites appeared both in the machine-learning-derived algorithm and in the top 25 metabolic pathways in relation to obesity: NAD (in 18 pathways), AMP (11), cysteine (4), and asparagine (2). For sleep problems, three of the same metabolites appeared in the machine-learning-derived algorithm and in the top 25 metabolic pathways: NAD (in 17 pathways), AMP (4), and cysteine (2). Therefore, markers appearing in all these analyses were AMP, NAD, and cysteine. 3. Discussion This study sought first to elucidate metabolomic markers that were associated with having either a less severe pain phenotype (lower and less interfering pain) or a more difficult one (higher pain, more interfering pain, and more co-occurring problems). A data-driven machine-learning-based approach picked seven markers: AMP, asparagine, deoxycytidine, glucuronic acid, propionylcarnitine, cysteine, and NAD. Analysis of two common problems that associate with more difficult pain, i.e., obesity and sleep problems, implicated several metabolomic markers and pathways which may have an effect on pain. Further, three markers (NAD, AMP, and cysteine) appeared across the results from the machine learning and pathway analyses. As described in the methods section, supervised machine learning classification algorithms were used for knowledge discovery rather than biomarker generation. The latter was not pursued for two reasons. First, the pain-related phenotype is a complex human phenotype that includes elements of both pain and sleep problems. This phenotype was based on a previous report of ours that suggested that sleep is a key factor in persistent pain [13]. The current study aimed to analyze metabolomic factors that may be involved in the process of pain chronification, not to identify biomarkers for e.g., diagnostic purposes. Second, understanding the involvement of metabolomic regulation in persistent pain is a new field of research and previous findings have so far not been able to formulate specific hypotheses-based metabolomics-derived data. Therefore, the present study aimed to gain further insight into the role of metabolomic regulation in human persistent pain with a special focus on the comorbidity of sleep. Obesity is associated with more severe pain [18] and several mechanisms may explain this: e.g., heavier weight on joints and spine, depression, or low-grade chronic inflammatory state [29,30]. However, effects from differential metabolomics levels may emerge as well. As expected, alterations in amino acid metabolism pathways also appeared in this study [19]. A metabolomic profile, observed here too, of increased levels of BCAAs valine and isoleucine, and glutamate and alanine, has been hypothesized to reflect an overload of BCAA catabolism [31]. This may contribute to the development of glucose intolerance or affect neurotransmitter production, while increased levels of BCAAs may also be associated with increased inflammation, possibly leading to more pain [32,33]. Elevated glutamate, as excitatory neurotransmitter related to pain sensation, has been associated with greater pain in several studies [12]. Another interesting finding was that the metabolomic marker glucuronic acid appeared in both the machine-learning algorithm and the obesity-associated pathway analysis. Glucuronic acid has been shown to activate Toll-Like Receptor 4, leading to enhanced nociception possibly through the release of cytokines [34]. Sleep problems were associated with decreased levels in four metabolites (choline, homocysteine, dimethylglycine, and serine) in the methionine pathway. Experimental sleep deprivation in animals and humans reduces levels of cysteine [35] and homocysteine [36]. In response to simulated night shifts in humans, choline levels and those of two other metabolites in the methionine pathway decreased [37]. Homocysteine has been of much interest in research as elevated homocysteine levels have appeared as a risk factor for several diseases, including cardiovascular disease and dementia, and sleep problems have been proposed to play a part in this process [38]. However, sleep problems occur in various forms, and it may be that only obstructive sleep apnea (OSA) or severely reduced sleep durations (<5 h) link to elevated homocysteine [39,40]. OSA may induce more pain through chronic headaches [41] and metabolomic level alterations in OSA, such as disruptions in amino acid, fatty acid, carbohydrate, bilirubin, and xanthine metabolism, have been found [17,42]. Associations with metabolomics are often nonlinear and highly complex, as different pathways interact with one another. For pain relief, stimulating the methionine pathway has been studied in relation to chronic pancreatitis, hypothesizing that the effects would be mediated through reduced oxidative stress [43]. As pain, obesity, and sleep problems are showing to have reciprocal relationships, we were interested in the possible interactions across the metabolomic findings. One marker appearing in all three analyses was cysteine, a product of the methionine pathway, which is needed for glutathione synthesis [44]. Our results suggested that the methionine pathway is downregulated with sleep problems, while obesity associated with an altered glutathione pathway. If obesity affected glutathione metabolism through elevated glutamate or decreased glycine availability [45], could co-occurring sleep problems take the imbalance further through reduced cysteine availability? Glutathione plays an important role as an antioxidant defense and its deficit has been studied in relation to several diseases. NAD, another common marker in the analyses, appeared in most pathways that both obesity and sleep problem analyses highlighted. Obesity is associated with decreased NAD levels and increased inflammatory cytokines are proposed as one possible mechanism for this [46]. Alterations of NAD levels may influence many processes as it has multiple functions, one of which is to do with the internal circadian clock, which then may play a part in sleep regulation [47]. Finally, increased AMP levels have been linked to obesity and diabetes [48]. AMP may also have direct effects on pain [49]. AMP is a hydrolysis product from ATP, a molecule which cells increasingly release in inflammation, tissue damage, or nerve injury. AMP is itself hydrolyzed to adenosine, which exhibits antihyperalgesic and antiallodynic effects. However, persistently elevated adenosine levels are associated with mechanical and thermal hypersensitivity, suggesting a possible role in chronic pain [50]. In our study, the serum level of AMP was higher in those with more pain and pain interference, suggesting that AMP hydrolysis might be affected in a variety of pain conditions, contributing to increased severe pain. Strengths and Limitations This study analyzed metabolomics in pain patients with two complementary approaches. Data-driven methods may produce subgroup allocations that are more valid in the real world than those corresponding to some individual pain-related factor. Using machine learning to search for important combinations of metabolomic markers in pain subgroups and comparing these results to findings about two significant problems, obesity and sleep, among pain patients is a way to assess the validity of these results. Thus, combining different analysis strategies can be considered a strength of this study. In addition, the presented set of metabolic markers derived from the data-driven part of the analysis has undergone several procedures to validate it and can therefore be considered as an internally validated result. In particular, (i) none of the markers emerged when feature selection was performed on permuted data. Moreover, (ii) algorithms other than random forests could be trained with these metabolic markers to assign cases to the correct phenotype group with a balanced accuracy that was better than guessing, whereas (iii) this was unsuccessful when training the algorithms with permuted data indicating that overfitting was unlikely. In addition, (iv) training the algorithms failed with markers that were significant in one-dimensional statistical analyses of group differences, suggesting a rejection of these markers found by simple statistics in favor of the markers found by the more complex approach pursued here, as discussed in the next section. Only some, but not all, of the identified metabolomic markers that were instrumental for the assignment of pain phenotypes by different machine algorithms differed statistically significantly between the two phenotype groups (Figure 3). At first glance, this might call the present results into question. However, a rejection of the presented relevant metabolomic markers as predictors of pain phenotype due to lack of significance fails to recognize the high dimensionality of the data set and inadequately reduces it to a multiple unidimensional problem. In contrast, it has recently been shown that higher significance does not automatically mean stronger predictive power and variables with strong predictive power may be sometimes not significant [51]. As the authors of the report state, “the main difference between finding a subset of variables to be highly significant and finding them to be highly predictive is that the former involves making assumptions about the exact distribution of the variables but not knowing it, whereas the latter requires knowing the distribution of the variables in the classes under study”. Nevertheless, considering that some of the selected metabolomic markers were different from those that showed statistically significant differences between subgroups, we repeated the classification step of the data analysis using only the statistically significant metabolomic markers for algorithm training. In this case, classification performance fell back to the level of guessing. The final set of metabolomic markers was found using a feature selection technique based on random forests, which is an established approach [24,52]. However, several additional analyses were performed to validate the final set of metabolomics markers. These included first classification algorithms other than random forests to ensure that the results were not due to properties of the random forests algorithm. In fact, SVM with the selected features provided even better classification performance than random forests. Second, training the algorithms with permuted metabolomics information resulted in their inability to assign patients to the correct cluster, demonstrating that the presented result was not due to overfitting or random selection. Finally, as an alternative to the Boruta approach based on random forests, the method of least absolute shrinkage and selection operators (LASSO [53]) as a regression-based method was used as an alternative feature selection technique. LASSO identified alanine, GABA, serine, proline, betaine, valine, isoleucine, asparagine, creatine, hypoxanthine, glutamine, glutamate, citrulline, AMP, sorbitol, gamma glutamyl cysteine, guanosine, chenodeoxycholic acid, taurochenodeoxycholic acid, isobutyryl carnitine, and cysteine as informative. However, training random forests with this marker set resulted in poor balanced accuracy of only 51.5% (interquartile range of 49.3–53.1), and other algorithms did not provide support that this feature set as informative for subgroup assignment. Based on these observations, the present feature set seems to be sufficiently validated. Nevertheless, the small sample size is a limitation that must be considered when generalizing the present results. 4. Material and Methods 4.1. Subjects and Study Design The cohort originally comprised n = 320 patients undergoing multidisciplinary therapy in tertiary pain care, enrolled between September 2013 and November 2016. The Coordinating Ethics Committee of Helsinki and Uusimaa Hospital District approved the study protocol (29.13.03.00/12). Informed written consent was obtained from all participants. The only exclusion criteria were active cancer or inability to answer questionnaires in Finnish. As described previously (see Table 1 in [13]), a total of d = 59 parameters in seven different categories, namely (i) pain phenotype-related features, (ii) pain etiology-related information, (iii) psychological parameters, (iv) demographic parameters, (v) lifestyle-related parameters, (vi) information about previous treatments, and (vii) information about comorbidities, had been acquired from the present cohort. Five of the pain-related parameters were used for pain-related clustering [13]; the other 54 parameters were not directly included in this cluster analysis but were used for later interpretation of the pain phenotype-derived clusters. Only the acquisition of information directly relevant to the present analysis, i.e., parameters related to pain, sleep, obesity, and metabolomics, are described below, while other details of the complete study have been described separately [13]. 4.2. Pain-Related Phenotypes As previously described [13,18], five pain-related parameters had been acquired from the patients, namely (i) pain intensity, (ii) activity pain interference, (iii) affective pain interference (assessed with the Brief Pain Inventory (BPI) [54]), (iv) the number of pain areas (from the pre-treatment health questionnaire, using an image of the human body on which the patient had marked areas with pain), and (v) the duration of pain. Based on the patterns found with these parameters [13], a subgroup of 81 patients characterized by a relatively smaller number of pain areas and a lower level of affective pain interference was distinguished at the top level of the cluster dendrogram from the other patients. In interpreting this pain-related cluster structure with the 54 predominantly non-pain-related parameters mentioned above, using explainable artificial intelligence (XAI) type algorithms (i.e., which make cluster assignment transparent and understandable to non-informaticians (see [55] for another example of XAI in pain research)), sleep problems were consistently at the top of the rule hierarchy. This indicated that sleep provided the most relevant information for subgroup assignment, besides the pain-related parameters that had been used for cluster building. This provided the basis for identifying sleep as a central factor in chronic pain in the present cohort and provided a mixed pain- and sleep-related phenotype suitable for the aim of the present study to analyze the role of metabolomics at the interface of pain and sleep problems. Obesity is another major comorbidity with both pain and sleep problems and has clear metabolic implications [19] and was therefore chosen as one of the parameters to be studied in the metabolomic analyses. Those with obesity are more likely to suffer from various chronic pain conditions (for example chronic headaches, fibromyalgia, and joint pain) and population studies have suggested obesity as a risk factor for developing chronic pain. Research on potential biochemical mechanisms linking obesity with pain is rapidly growing [29]. 4.3. Sleep and Obesity Parameters Sleep problems were assessed using the previous criteria [56]. Briefly, subjective sleep difficulties were first queried using the sleep item from the 15D Health-Related Quality of Life (HRQoL) questionnaire [57]. In the 15D sleep item, respondents indicate whether they have normal sleep or mild, marked, great, or extreme sleep problems. Patients who reported normal sleep were classified under this category. Patients who reported at least marked sleep problems were assessed for recurrence of the problems, using the Basic Nordic Sleep Questionnaire (BNSQ) [58]. This a standardized questionnaire assessing sleep disturbances that asks about various symptoms in the past three months on a scale of 1 to 5 (1 = never or less than once a month; 2 = less than once a week; 3 = 1–2 nights a week; 4 = 3–5 nights a week; 5 = every night or almost every night). Patients were classified as having “recurrent sleep problems” if they reported at least one of the following problems: 1 = difficulty falling asleep at least three times per week; 2 = night-time awakenings at least three times per night, on at least three nights per week; 3 = feeling extremely tired after waking up in the morning at least three times per week. Additionally, daytime sleepiness also had to be reported at least three times per week. The remaining patients who neither reported sleeping normally nor met the criteria for recurrent sleep problems were classified as having “mild or infrequent sleep problems.” A patient was assigned as obese if the body mass index (BMI) was 30 or higher. The height and weight information used to calculate BMI were taken by a nurse while the patient visited the pain clinic for examination. 4.4. Serum Metabolomic Markers Metabolomics were performed at the Finnish Institute of Molecular Medicine, using previously published methods [20]. Ten microliters of labelled internal standard mixture were added to 100 µL of biofluid sample and allowed to equilibrate. A total of 400 µL of extraction solvent (1% formic acid in acetonitrile) was added for protein precipitation. The samples were then centrifuged (14,000 rpm; 4 °C; 15 min); supernatants were collected and dispensed into phospholipid removal plate (OstroTM, Waters Corporation, Milford, MA, USA), and then vacuum filtered (pressure differential 300–400 mbar; 2.5 min) on a Hamilton robot vacuum station. A total of 5 μL of filtered sample extract was injected into an ACQUITY UPLC system coupled to a Xevo® TQ−S triple quadrupole mass spectrometer (Waters Corporation). Chromatographic separation was carried out with a 2.1 × 100 mm ACQUITY 1.7 µm BEH amide HILIC column (Waters Corporation) (temperature maintained at 45 °C). The total run time was 14.5 min including 2.5 min of equilibration step at a flow rate of 600 µL/min and subsequently, the gradient was created with mobile phase B (ACN/H2O, 90/10 (v/v), 20 mM ammonium formate, pH at 3) and mobile phase A (ACN/H2O, 50/50, ammonium formate, pH at 3) according to Nandania et al. [20]. About 5 µL of sample extract was injected with two cycles of washes, seal wash and partial loop. The detection system, a Xevo® TQ−S MS (Waters Corporation), was operated with polarity switching electro spray ionization (ESI) having capillary voltage at 0.6 KV in both polarities. Throughout the experiment the following settings were used: the source temperature (120 °C), desolvation temperature (650 °C), high pure nitrogen and argon gas used as desolvation gas (600 L/hr) and collision gas (0.15 mL/min), respectively. Multiple reaction monitoring (MRM) acquisition mode was selected for quantification of metabolites (span time of 0.1 sec). MassLynx 4.1 software (Waters Corporation) was used for data acquisition, data handling, and instrument control. Data processing was done using TargetLynx software (Waters Corporation) and metabolites were quantified by using labeled internal standards and external calibration curves. 4.5. Data Analysis 4.5.1. Data and Analysis Strategy Data analysis was in two main parts (Figure 1). First, a data-science-based approach, using machine-learning-based feature selection methods [21,22] was pursued to identify metabolomic markers that could provide relevant information for assigning a patient to the correct pain phenotype subgroup. This approach was unbiased with respect to metabolomic markers or pathways potentially involved in the segregation of pain phenotype subgroups, analogously to the approach taken previously in a comparable “omics”-focused assessment [59]. Second, a metabolic pathway-based, hypothesis-driven approach, using metabolite set enrichment analysis (MSEA), was pursued to examine biologically meaningful patterns that are significantly enriched in the quantitative metabolomics data related to pathways relevant to sleep problems or obesity. The two lines of data analysis were performed independently by two researchers, resulting in differences in some details of the analyses, mainly due to the different software tools used and their default settings. The two parts were conducted independently to avoid mutual influence of the results, i.e., the characteristics selected in the first part were not considered in the second part and vice versa, which also allowed internal validation to a certain extent. Full details are provided below. The data space in both lines of analysis had the form D=xi,yi|xi∈ X, yi∈Y, i=1…n that consisted of a so-called input space X with the metabolomic markers collected from 193 patients. In addition, the so-called output space Y was included, which, in the first line of the analysis, consisted of class or subgroup information on the assignment of patients to the two pain phenotypes described above, and, in the second line of assignment, to the recurring sleep problems or obesity subgroups. Losses from the original 320 patients are due to (i) missing phenotypic information, resulting in only 277 patients being analyzed in the previous analysis [13], and (ii) metabolic information not available from 84 patients. Basic descriptive statistics were calculated, and group comparisons were performed using Wilcoxon-Mann-Whitney-U tests [60,61] or χ2 tests [62], with an α level set at 0.05 and corrected for multiple testing, according to the proposal of Bonferroni [63]. The main analyses were conducted independently by two researchers and are described below. 4.5.2. Data-Driven Association of Metabolomic Markers and Pain Phenotypes The programming work required for this part of the analyses was carried out in the R language [64] using the R software package [23], version 4.0.2 for Linux, which is available free of charge in the Comprehensive R Archive Network (CRAN) at https://CRAN.R−project.org/. Analyses were performed on an Intel Core i7−10510U (Intel Corporation, Santa Clara, CA, USA) notebook computer running Ubuntu Linux 20.04.1 LTS 64−bit (Canonical, London, UK)). Data Preprocessing and Transformation For the machine learning-based analyses, the data were preprocessed as follows. Subjects and variables with >20% missing values in the metabolomics information were eliminated, since for the machine-learning-based analyses, this had been defined as the limit for imputation, as used previously [13]. Therefore, only 97 metabolomic markers were included in these analyses. A transformation of the metabolomics data best suited for their association with the pre-established cluster structure (see above) was identified by means of PC−corr analysis [65]. This is an algorithm that complements principal component analysis (PCA) [66,67]. PC−corr attempts various transformations of the data for optimal segregation of the cohorts along a PC, which is evaluated by quantitative measures expressed as p-value, area under the receiver−operator characteristic (AUC−ROC), and area under the precision−recall curve (AUPR). Since the first principal component (PC) captures the largest possible variance in the data, optimum cluster segregation along this component was searched. This analysis was performed using an R-script provided with the description of the PC−corr analysis (pccorrv2.R, https://github.com/biomedical−cybernetics/PC−corr_net [65]). The analysis resulted in a recommendation for log transformation of the data as best suited to observe cluster segregation along the first PC. Missing values were replaced by non-parametric imputation by random forests [68,69], as implemented in the R library “missForest” (https://cran.r−project.org/package=missForest [70]). Selection of Metabolomic Markers Informative for Pain−Phenotype Assignment Metabolomic markers that provided relevant information for patient subgroup assignment were identified using supervised feature selection and machine learning. Feature selection [22] was implemented with the “Boruta” approach [24], which is based on the random-forests algorithm [68,69] as a generally well-performing classifier using a tree-based structure. The Boruta method provides a clear decision on whether a variable is important or not, derived from a 100-fold cross-validation approach and a statistical evaluation with p-values defaulting to 0.01 [24]. These calculations were performed with the R package “Boruta” (https://cran.r−project.org/package=Boruta [24]) with the default hyperparameter settings. It should be mentioned that it would be a problem to mix different types of feature selection algorithms. However, the analyses reported in Section 4.5.2 and Section 2.2 of this paper basically included only a one-dimensional feature analysis. This means that the relationships between feature dimensions, whether linear or more complex, are not considered. To further circumvent possible circularity, the Boruta method-based feature selection was performed again with permuted metabolome data, with the expectation that the validity of the selected features would be supported if they were not also selected from permuted data. Validation of Metabolomic Markers Informative for Pain Phenotype Assignment To assess whether the selected metabolomic markers indeed provided relevant information for subgroup assignment, various machine learning classification algorithms were trained to perform the task of assigning a patient to the correct subgroup, based on the information provided by the metabolomics data. This was performed with machine learning for knowledge discovery. The approach assumes that if a classifier can be trained to assign a patient to the correct class better than by guessing, the features (the metabolomic markers in the dataset needed by the classifier to accomplish this task) contain relevant information about the addressed class structure. In this way, the most informative markers can be identified. Thus, feature selection takes precedence over classifier performance whereas creating a powerful classifier to identify a biomarker is not the goal. This means that the analysis can be considered as successful if the class assignment is better than guessing and the variables needed for this assignment have been identified. In order to assess whether the feature selection procedure identified a set of variables that provides enough information for class separation, several different machine-learning algorithms were trained with both full and reduced feature sets. A 100-fold cross validation scenario was run on disjoint training (2/3 of the cases) and test (1/3 of the cases) data subsets, randomly drawn from the original data set using Monte Carlo resampling [71] as implemented in the R library “sampling” (https://cran.r−project.org/package=sampling [72]). Classification performance was evaluated using standard measures comprising first balanced accuracy [73] as the main criterion, and then the AUC−ROC [74], sensitivity, specificity, precision, recall, positive and negative predictive value [75,76], and the F1 measure [77,78]. These calculations were performed with the R libraries “caret” (https://cran.r−project.org/package=caret [26]) and “pROC” (https://cran.r−project.org/package=pROC [27]). To address possible circularity arising from feature selection and validation with random forests only, algorithms of supervised machine learning were selected to cover different types of classifiers, including methods previously applied to pain-related data [79] and included (i) random forests [68,69] as the algorithm used for feature selection, (ii) support vector machines (SVM) [80]), (iii) adaptive boosting [81], (iv) k-nearest neighbors (kNN) [82], (v) conditional inference trees (CTREE) [83], (vi) classification and regression trees (CART) [84], (vii) the hierarchical tree−based C5.0 classifier [85], and (viii) the non-hierarchical rules-generating partial decision trees classifier (PART) [86]. The R libraries used for these calculations comprised, in the above order of algorithms, “randomForest” (https://cran.r−project.org/package=randomForest [87]), “kernlab” (https://cran.r−project.org/package=kernlab [88]), “xgboost” (https://cran.r−project.org/package=xgboost [89]), “caret”, “party” (https://cran.r−project.org/package=party [83]), “rpart” (https://cran.r−project.org/package=rpart [90]), “C5.0” (https://CRAN.R−project.org/package=C50 [91], and “RWeka” (https://cran.r−project.org/package=RWeka [92]). Hyperparameters were tuned during grid searches (as performed previously [55]). For example, random forests were built with 500 trees and three features per tree, while the kNNs were used with the Euclidean distance and the value of k could be selected, based on an actual grid search performed on each run. SVM was executed with a radial-based Gaussian kernel, while CART was implemented with a minimum limit of five cases per split and a maximum tree depth of five decisions. To control possible overfitting, all machine-learning algorithms were additionally trained with randomly permuted features. The classifier trained with these data should not perform better than guessing, i.e., should give a balanced accuracy and an AUC−ROC equal or close to 50%. For examples of R code used for the best-performing classifiers random forest and SVM, see Box 1. Box 1 R code details for the best—performing classifiers random forest and SVM. SVM = {ActualClassifierObject <− ksvm(as.factor(Clusters) ~ ., data=TrainData, kernel=“rbfdot”, prob.model=TRUE, type = “nu−svc”)} Defaults of the ksvm support vector machines method (for full details, see https://cran.r−project.org/web/packages/kernlab/kernlab.pdf): ksvm(x, y = NULL, scaled = TRUE, type = NULL, kernel =“rbfdot”, kpar = “automatic”,C = 1, nu = 0.2, epsilon = 0.1, prob.model = FALSE, class.weights = NULL, cross = 0, fit = TRUE, cache = 40, tol = 0.001, shrinking = TRUE, ..., subset, na.action = na.omit) RF = {ActualClassifierObject <− randomForest(as.factor(Clusters) ~ ., data = TrainData, mtry=3, ntree=500, na.action = na.roughfix)} Defaults of the randomForest method (for full details, see https://cran.r−project.org/web/packages/randomForest/randomForest.pdf): randomForest(x, y=NULL, xtest=NULL, ytest=NULL, ntree=500, mtry=if (!is.null(y) && !is.factor(y)) max(floor(ncol(x)/3), 1) else floor(sqrt(ncol(x))), weights=NULL, replace=TRUE, classwt=NULL, cutoff, strata, sampsize = if (replace) nrow(x) else ceiling(.632*nrow(x)), nodesize = if (!is.null(y) && !is.factor(y)) 5 else 1, maxnodes = NULL, importance=FALSE, localImp=FALSE, nPerm=1, proximity, oob.prox=proximity, norm.votes=TRUE, do.trace=FALSE, keep.forest=!is.null(y) && is.null(xtest), corr.bias=FALSE, keep.inbag=FALSE, ...) 4.5.3. Pathway-Based Assessment of Metabolomic Markers Relevant to Sleep and Obesity Pathway-based analyses were performed using prepackaged software tools available as a web-based comprehensive metabolomics data processing tool MetaboAnalyst (version 5.0, https://www.metaboanalyst.ca/home.xhtml; accessed on 1 September 2021, [28,93]. Metabolites were removed at a threshold of 20% missing values [94]. Log transformation and autoscaling were used to normalize the data. Missing values were imputed with k-nearest neighbors algorithm [82] based on similar samples. For univariate analysis, volcano plot analysis was performed using FC = 1 and p-value < 0.05. Pathway enrichment analyses were performed using the quantitative metabolite enrichment analysis (MSEA) algorithms in Metaboanalyst [95]. MSEA uses similar algorithms to those originally developed for Gene Set Enrichment Analysis (GSEA) [96]. KEGG metabolite IDs and a metabolic pathway-based SMPDB database (containing 99 metabolite sets to normal human metabolic pathways) were used. Metabolite sets containing at least two entries were used as cut off. Enrichment ratio was computed by hits/expected. 5. Conclusions The results of this study suggest several metabolomic markers and pathways that may play a part in pain becoming more severe for some patients. Some effects may be more direct, such as our findings about AMP and the hypothesis that this might alter adenosine metabolism, leading to increased pain sensitivity. However, there may also be many indirect effects. For example, we found that NAD levels were altered in obesity: NAD appears in many metabolomic pathways and is associated with many functions, such as circadian rhythms, which may then influence sleep regulation. Then, as research has suggested, disturbed sleep may lead to greater pain through several processes. Our findings also raise the possibility that several problems co-occurring with pain may disturb metabolomic processes in an additive way: if sleep problems are associated with downregulating the methionine pathway and obesity with alterations in glutathione metabolism, what effects might occur when these two problems combine, given the known links between these pathways? Metabolomics is a promising new approach to gain understanding of processes in chronic pain, and clearly warrants further research. Acknowledgments We thank Les Hearn for proofreading the manuscript, the physicians and nurses of the participating pain clinics for their contributions to data collection, and Minna Kymäläinen RN for her work on data management. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23095085/s1. Click here for additional data file. Author Contributions Supervised the project and acquired funding: E.K.; designed the clinical experiments: E.K., T.M., P.M.; analyzed the data: J.L. (data-driven part), A.I.N. (pathway analyses); interpretation of the results: T.M., E.K., J.L., A.I.N., P.M.; wrote the paper: T.M., J.L., E.K., A.I.N., P.M.; critical evaluation of the study results: E.K., J.L., T.M., A.I.N.; All authors discussed the results and commented on the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The Coordinating Ethics Committee of Helsinki and Uusimaa Hospital District approved the study protocol (29.13.03.00/12). Informed Consent Statement Informed written consent was obtained from all participants. Data Availability Statement Data cannot be shared publicly because of ethical restrictions permitting only the release of group level data to protect patient privacy. Requests for subject level data may be made by submitting an application to the coordinating ethics committee of the Helsinki and Uusimaa Hospital District (please see https://www.hus.fi/en/researchers/Research_policy_and_procedure/Pages/default.aspx; secretary for the ethics committee tel. +358504286400, email eettiset.toimikunnat@hus.fi) and contacting the principal investigator for this study, Dr. Eija Kalso, via email (eija.kalso@helsinki.fi). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flowchart showing number of patients and steps of data analysis. The data analysis followed two main lines: (i) A data-driven, unbiased approach to identify the most informative metabolomic markers for segregating patient subgroups in relation to the pain- and sleep-related phenotypes previously identified in the same cohort [13]; and (ii) a hypothesis-driven enrichment analysis examining metabolomic markers involved in sleep problems and obesity as main features of the patients’ clinical picture. The figure was created using Microsoft PowerPoint® (Redmond, WA, USA) on Microsoft Windows 11 running in a virtual machine powered by VirtualBox 6.1 (Oracle Corporation, Austin, TX, USA). Figure 2 Identification and validation of metabolomic markers relevant for the assignment of patients to the correct pain phenotype subgroups. (A): Results of the variable selection procedure performed as random forest-based Boruta analysis, which assesses the measure of importance of a variable based on the decrease in classification accuracy due to random permutation of values in a 100-fold cross-validated approach. The importance measure is calculated separately for all trees in the forest that use the respective feature for classification. Then the mean value and the standard deviation of the loss of accuracy are calculated and the z-score is used in comparison to an external reference, the so-called “shadow” features (empty boxes), obtained by permuting the values of the original feature. Green and yellow boxes represent “confirmed” or tentatively significant features, respectively, i.e., features that contribute to the classification success and were selected for the validation analyses shown in the lower line of panels. The red boxes are confirmed as non-informative variables and excluded from further analysis. The boxes were constructed using the minimum, quartiles, median (solid line inside the box), and maximum of these values. The whiskers add 1.5 times the interquartile range (IQR) to the 75th percentile or subtract 1.5 times the IQR from the 25th percentile. The black circles indicate outliers from this interval. (B): Results of the Boruta feature selection analysis when instead of the original data, randomly permuted metabolic marker concentrations were used. The figure was created using the R software package (version 4.0.2 for Linux; https://CRAN.R-project.org/ [23]) and the R libraries “Boruta” (https://cran.r-project.org/package=Boruta [24]) and “ggplot2” (https://cran.r-project.org/package=ggplot2 [25]). Figure 3 Raw data of the selected metabolomics features presented separately for the two pain and sleep-related subgroups. The transformed values (log10(x + 1)) are shown; for untransformed values of all metabolomic markers see Supplementary Figure S1. Individual data points are presented as dots on violin plots showing the probability density distribution of the variables, overlaid with box plots where the boxes were constructed using the minimum, quartiles, median (solid line inside the box), and maximum of these values. The whiskers add 1.5 times the interquartile range (IQR) to the 75th percentile or subtract 1.5 times the IQR from the 25th percentile. Statistical significances are shown at the top of each panel. The figure was created using the R software package (version 4.0.2 for Linux; https://CRAN.R-project.org/ [23]) and the R libraries “Boruta” (https://cran.r-project.org/package=Boruta [24]) and “ggplot2” (https://cran.r-project.org/package=ggplot2 [25]). Figure 4 (A): Volcano plot showing the results for elucidating discerning markers between obese (BMI > 30) and non-obese patients, and those with recurring sleep problems, and those with normal sleep or only mild sleep problems. FC = 1, p-value < 0.05, BMI > 30/BMI < 30 and recuring/normal and mild sleep problems. FC = 1, p-value < 0.05 (B): Top 25 metabolic pathways that pathway enrichment analysis using SMPDB database suggested as having the most alterations, on the left in relation to obesity, and on the right in relation to sleep problems. The figure has been created using the MetaboAnalyst software (version 5.0, https://www.metaboanalyst.ca/home.xhtml [28]. (C): Mechanistic model illustrating how problems co-occurring with chronic pain may link at the metabolomic level. On the partial description of methionine metabolism (right), the blue arrows show the four metabolomic markers that are decreased in the recurring sleep problems subgroup in statistical analysis, suggesting downregulated methionine metabolism in this subgroup. Methionine metabolism is an important source of cysteine, needed for glutathione metabolism (left), and which appeared altered with obesity. The figure was created using Microsoft PowerPoint® (Redmond, WA, USA) on Microsoft Windows 11. ijms-23-05085-t001_Table 1 Table 1 Basic descriptive statistics of information in 53 parameters not primarily used for pain phenotype clustering [13], collected from the 193 patients included in the present analyses: patients’ demographics, living situation, other pains, medical treatment experiences and comorbidities, and lifestyle-related parameters. For ordinal and interval-scaled variables, medians with IQRs are reported; for categorical variables, the categories are shown with the counts of patients belonging to each. Raw non-imputed data are shown; counts < 193 indicate missing data for some patients. Category Variable n Median Interquartile Range Categories and n Per Category Demographics Age 193 48 38–56 - Sex 193 - - Men = 71 Women = 122 Living situation No. of children 193 2 0–2 - Civil status 192 - - Married = 75 Registered relationship = 0 Cohabiting = 38 Unmarried = 49 Separated = 25 Widow = 5 Education in years 188 13 11–15.13 - Type of work 193 - - Agriculture = 2 Manual work = 15 Office work = 94 Studying or at school = 9 Housewife = 2 Pensioner = 40 Unemployed = 31 Household income 184 4 3–6 - Missed workdays within previous 12 mo 173 39 2–180 - Pain related No. of pain areas 193 3 2–5 - Duration of pain 193 - - <1 mo = 0 1–3 mo = 2 3–6 mo = 5 6–12 mo = 23 1–2 y = 30 >2 y = 123 Pain intensity 193 6 5–6.75 - Affective pain interference 193 7 4.75–8.25 - Activity pain interference 193 6.67 5.67–8 - Any neuropathic pain 188 - - No = 117, yes = 71 Low back pain 188 - - No = 132, yes = 56 Musculoskeletal pain other than back pain 188 - - No = 145, yes = 43 Facial pain 188 - - No = 178, yes = 10 Abdominal pain 188 - - No = 181, yes = 7 Complex regional pain syndrome 188 - - No = 177, yes = 11 Headache 188 - - No = 184, 1 = 4 Phantom pain 188 - - No = 188 Fibromyalgia 188 - - No = 170, yes = 18 Chronic pain syndrome 188 - - No = 184, yes = 4 Other pain diagnosis 188 - - No = 168, yes = 20 Previous treatments Negative treatment experiences 193 3 1–4 - Positive treatment experiences 193 4 2–6 - Physician visits within previous 12 mo 181 10 5–14 - Comorbidities Hypertension 192 - - No = 135, Yes = 57 Heart failure 192 - - No = 187, Yes = 5 Angina pectoris 192 - - No = 180, Yes = 12 Diabetes 191 - - No = 175, Yes = 16 Asthma 192 - - No = 160, Yes = 32 Chronic obstructive pulmonary disease 192 - - No = 186, Yes = 6 Rheumatoid arthritis 192 - - No = 190, Yes = 2 Joint disease other than rheumatoid arthritis 192 - - No = 141, Yes = 51 Low back pain 192 - - No = 91, Yes = 101 Depression 190 - - No = 135, Yes = 55 Psychiatric disorder other than depression 192 - - No = 181, Yes = 11 Hypercholesterolemia ever in life 166 - - No = 94, Yes = 72 Using cholesterol medication 168 - - No = 143, Yes = 25 High blood pressure ever in life 190 - - No = 107, Yes = 83 Blood pressure medication use ever in life 85 - - No = 28, Yes = 57 Diabetes type 159 - - No = 130 No, but elevated blood sugar = 7 Yes, type 1 diabetes = 4 Yes, type 2 diabetes = 14 Yes, but don’t know type = 1 Yes, diabetes during pregnancy = 3 Lifestyle Smoking currently 193 - - No = 118, yes = 75 Exercise periods of >20 min per week 190 2 0–3 - Hours spent sitting per day 185 6 3.5–9.5 - Sleep problems index 190 17 14–20 - Nutritional index 135 1 1–2 - Drug abuse 135 0 0–0 No = 124 Has used = 10 Dependent = 1 Alcohol consumption frequency 126 - - Never = 19 Once a month or less = 43 2–4 times a month = 40 2–3 times a week = 20 4 times a week or more = 4 Body mass index 192 27.82 24.23–32.71 - Systolic blood pressure, mm Hg 193 135 124–150 - Diastolic blood pressure, mm Hg 193 86 80–94 - Waist circumference 192 95.25 84.5–106.25 - ijms-23-05085-t002_Table 2 Table 2 Performance measures for assigning subjects to the two clusters previously found in the pain patients [13], of which cluster #1 includes patients with comparatively few body areas in pain, low interference, little sleep disturbance, and low blood pressure. The performance of machine-learning-based random forest classifiers is given; for further algorithms, the selected main performance criterion (balanced accuracy) is shown in Supplementary Figure S2. Classification performance was measured (i) with the original data, (ii) with data sets designed to provide negative control by permutation of the original metabolomic parameters, and then with original or permuted data of those seven metabolomic markers found relevant to the patient subgrouping after feature selection (Figure 3). Results represent the medians (IQRs in parentheses) of the test performance measures from 1000 model runs using Monte Carlo resampling. The parameters correspond to the performance marker set implemented in the R libraries “caret” (https://cran.r-project.org/package=caret [26]) and “pROC” (https://cran.r-project.org/package=pROC [27]). Parameter Full Feature Set Reduced Feature Set Feature set Original Permuted Original Permuted Sensitivity, recall 0 (0–0) 0 (0–0) 31.6 (26.3–36.8) 10.5 (5.3–15.8) Specificity 100 (97.8–100) 100 (100–100) 88.9 (84.4–91.1) 91.1 (86.7–93.3) Positive predictive value, precision 0 (0–50) 50 (0–100) 53.6 (45.5–60) 33.3 (22.2–45.5) Negative predictive value 70.3 (70.3–70.3) 70.3 (70.3–70.3) 75 (73.7–76.9) 70.5 (69.4–71.9) F1 10 (9.5–10) 10 (10–10) 38.8 (33–45.2) 16.7 (14.3–25) Balanced Accuracy 50 (49.9–50) 50 (50–50) 59.1 (57.1–62.9) 50.4 (47.8–53.5) ROC-AUC 50.7 (46.5–56.1) 51.3 (46.7–55.1) 70 (66.3–75.2) 56.1 (49.3–61.6) ijms-23-05085-t003_Table 3 Table 3 Statistical analysis (fold change and t-test) used in volcano plot for elucidating discerning markers between obese (BMI > 30) and non-obese patients, and those with recurring sleep problems and those with normal sleep or only mild sleep problems. Metabolomic Marker FC log2(FC) Raw.Pval −log10(p) Obesity Glutamate 1.1076 0.14741 7.385 × 10−5 4.1317 Asparagine 0.97389 −0.038168 0.00060007 3.2218 Glycine 0.96871 −0.045858 0.0013494 2.8698 Tyrosine 1.0282 0.040139 0.0018034 2.7439 Valine 1.0209 0.029846 0.0019009 2.721 Alanine 1.0211 0.030172 0.0030191 2.5201 Isovalerylcarnitine 1.155 0.2079 0.0053701 2.27 Isoleucine 1.0301 0.042839 0.0061138 2.2137 Symmetric dimethylargininee 0.88753 −0.17213 0.0066633 2.1763 Propionylcarnitine 1.1127 0.15403 0.0097422 2.0113 Hydroxykynurenine 1.2256 0.29344 0.009839 2.007 Glucuronic acid 1.1245 0.16928 0.011138 1.9532 Creatinine 0.98053 −0.028359 0.012257 1.9116 Creatine 1.0483 0.068066 0.013068 1.8838 Hexanoylcarnitine 1.1638 0.21882 0.020064 1.6976 Citrulline 1.0376 0.053191 0.02039 1.6906 Inosine 1.2492 0.32101 0.02406 1.6187 Chenodeoxycholic Acid 1.0856 0.11852 0.024663 1.6079 Adenosine 1.2961 0.37413 0.032691 1.4856 Kynurenine 1.0443 0.062527 0.034 1.4685 NAD 0.73752 −0.43924 0.036641 1.436 Cytidine 1.0567 0.079523 0.047004 1.3279 Guanosine 1.4269 0.51284 0.047952 1.3192 Sleep problems Serine 0.98126 −0.027298 0.017081 1.7675 Symmetric dimethylarginine 0.91811 −0.12326 0.021126 1.6752 Homocysteine 0.85203 −0.23103 0.021403 1.6695 Dimethylglycine 0.9218 −0.11747 0.028466 1.5457 GABA 0.87712 −0.18915 0.03143 1.5027 Asymmetric dimethylarginine 0.91048 −0.1353 0.031587 1.5005 Choline 0.96778 −0.047256 0.049881 1.3021 FC = fold change. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094553 ijms-23-04553 Article Tracking Changes in the Spring Barley Gene Pool in Poland during 120 Years of Breeding Dziurdziak Joanna 1 Podyma Wiesław 1 https://orcid.org/0000-0001-8095-2105 Bujak Henryk 23 https://orcid.org/0000-0001-8691-410X Boczkowska Maja 1* Lan Xiu-Jin Academic Editor 1 Plant Breeding and Acclimatization Institute-National Research Institute, Radzików, 05-870 Błonie, Poland; j.dziurdziak@ihar.edu.pl (J.D.); w.podyma@ihar.edu.pl (W.P.) 2 Department of Genetics, Plant Breeding and Seed Production, Wrocław University of Environmental and Life Sciences, Grunwaldzki 24A, 53-363 Wrocław, Poland; henryk.bujak@upwr.edu.pl 3 Research Center for Cultivar Testing (COBORU), 63-022 Słupia Wielka, Poland * Correspondence: m.boczkowska@ihar.edu.pl 20 4 2022 5 2022 23 9 455319 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/). This study was undertaken to investigate the diversity and population structure of 83 spring barley (Hordeum vulgare L.) cultivars, which corresponded to 120 years of this crop’s breeding in Poland. The analysis was based on 11,655 DArTseq-derived SNPs evenly distributed across seven barley chromosomes. Five groups were assigned in the studied cultivars according to the period of their breeding. A decrease in observed heterozygosity within the groups was noted along with the progress in breeding, with a simultaneous increase in the inbreeding coefficient value. As a result of breeding, some of the unique allelic variation present in old cultivars was lost, but crosses with foreign materials also provided new alleles to the barley gene pool. It is important to mention that the above changes affected different chromosomes to varying degrees. The internal variability of the cultivars ranged from 0.011 to 0.236. Internal uniformity was lowest among the oldest cultivars, although some highly homogeneous ones were found among them. This is probably an effect of genetic drift or selection during their multiplications and regenerations in the period from breeding to the time of analysis. The population genetic structure of the studied group of cultivars appears to be quite complex. It was shown that their genetic makeup consists of as many as eleven distinct gene pools. The analysis also showed traces of directed selection on chromosomes 3H and 5H. Detailed data analysis confirmed the presence of duplicates for 11 cultivars. The performed research will allow both improvement of the management of barley genetic resources in the gene bank and the reuse of this rich and forgotten variability in breeding programs and research. barley DArTseq SNP diversity cultivars breeding ==== Body pmc1. Introduction The International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA) in 2001 defined cultivar as “a plant grouping, within a single botanical taxon of the lowest known rank, defined by the reproducible expression of its distinguishing and other genetic characteristics” [1]. The advances in plant breeding achieved in the 20th century have had a tremendous impact on the agricultural landscape and have contributed to improving global food security through significant increases in crop productivity [2,3]. A milestone was the Green Revolution of the 1960s and 1970s [4]. However, it is believed that this was a major trigger for the genetic erosion of crop species, and constant selection based on crosses between genetically closely related cultivars has significantly narrowed the crops’ gene pools [5,6]. Barley breeding has focused on improving yield and biotic and abiotic stress tolerance. Malting quality is also important due to barley’s use in the brewing industry. Various traditional breeding methods have been employed, i.e., selection (mass, pure line, pedigree or bulk), haploid and doubled haploid production, mutation, single-seed descent (SSD), compound crosses, backcrossing, interspecific and intergeneric crosses. Male sterile-facilitated recurrent selection (MSFRS) and diallel selective mating system (DSMS) have also been used, which facilitate breakage of existing linkage blocks and expansion of the gene pool by providing large amounts of genetic diversity into barley cultivars [7]. Due to the increasing dynamics of changes in market demands and needs, due to climate change and the emergence of new pathogen races, the most traditional methods, requiring a long-term breeding program, have needed support. Molecular biology and genetic engineering tools have provided a significant shortening of the breeding process [8,9]. Molecular markers, Quantitative Trait Loci (QTL) mapping and finally whole-genome sequencing, as well as genetic modification and genome editing have facilitated early generation and targeted selection and thus overcome the disadvantages of traditional breeding [8]. Using molecular biology tools in breeding has significantly facilitated and accelerated the identification of genotypes that determine a specific and desired phenotype. The molecular characterization of preserved collections performed in gene banks helps in the preliminary identification of germplasm potentially applicable to current breeding programs. This is crucial, especially where there is a fragmented structure of the breeding companies producing cultivars for the local market, which usually do not have the financial resources and laboratory infrastructure to perform their own rapid screening of gene bank collections to identify components for crossbreeding. However, it is essential to provide open access to genetic data. The beginning of spring barley breeding on Polish territory dates back to the end of the 19th century. Beginning in 1870, breeding stations and companies were established in the partitioned Polish territory. Initially, breeding was dominated by cultivars selected from elite materials imported from abroad, landraces and ecotypes. Barley breeding in Wielkopolska, which at that time was part of the Prussian partitioning, was carried out by Hildebrand, Kirhoff and Stiegler. Their cultivars were widely grown on Polish lands and used in further breeding work. At the beginning of the 20th century, Polish breeders started to work on components and cultivars from Moravia (now the Czech Republic) [10]. As early as in 1902, Antoni Sempołowski, who is considered the pioneer of Polish breeding, distinguished four ways of cereal improvement, i.e., improvement by selection, breeding of new cultivars by searching and consolidation of new types, breeding of new cultivars by crossing, and acclimatization [11]. In the interwar period, barley breeders began crossing indigenous landraces with German cultivars, including the most valued cultivar, ‘Isaria’ [12]. In later periods well yielding, popular in the cultivation of foreign cultivars and Polish parental components, was used for further crossbreeding [10]. Old cultivars can be a valuable source of variability that has been lost due to the focus on high yield [13]. They may contain genes determining resistance to biotic and abiotic stresses, as well as parameters determining, quality oriented towards health-promoting properties [14,15,16]. Therefore, old cultivars and landraces are a source of genetic information for direct use or as parental lines in breeding programs for better adaptation of new cultivars [17,18,19]. However, it should also be considered that the general profile of agrotechnical traits will be significantly worse in the case of old cultivars compared to modern ones [20]. Here, emphasis was placed on investigating changes in the gene pool of the Polish spring barley cultivars collection during 120 years of breeding based on the analysis of DArTseq-derived SNPs. For five breeding periods, both the size of gene pools, their structure and internal level of diversity were assessed. Traces of targeted breeding were examined along the chromosomes. The level of heterogeneity within the studied cultivars was also estimated. The analysis presented here also provided an opportunity to verify and identify duplicates in the germplasm collection. The DArTseq results also enabled the core collection to be selected. Therefore, the results will improve the efficiency of collection management and its use in research and breeding. 2. Results 2.1. Data Quality Analysis Sequencing yielded over 75,000 SNP loci, from which loci with low reproducibility (RepAvg ≤ 0.95), low call rate (CallRate ≤ 0.95), and low minor allele frequency (MAF < 0.01) were removed. As a result, approximately 85% of the loci obtained were removed, and loci, 11,655 in number, that met all quality parameters were used for analysis. The distribution of loci on chromosomes before and after filtering was also checked. Filtering did not affect the uniform distribution on chromosomes, which ranged from 10 to 15%. However, the proportion of loci with unknown chromosomal location decreased by 2% compared to the raw data. The highest number of loci analyzed was located on chromosome 2H (1695) and the lowest on 1H (1150). On average, 1 bp per 470 Kbp in the genome was analyzed. Loci distribution along each chromosome showed a similar pattern, i.e., the number of studied loci was higher at the ends of chromosomes and decreased towards centromere (Table 1, Figure 1). The frequencies of transitions (A > G, G > A, C > T, and T > C) and transversions (other variants) among SNPs were 60.2% and 39.8%, respectively. On chromosome 3H there were significantly less purine transitions and significantly more pyrimidine transitions compared to the other chromosomes. Among the transversions, their significantly decreased frequency was observed on 1H (A > C) and 3H (A < T), and a simultaneously increased frequency on 7H (C > A) (Table 2). The polymorphism information content (PIC) ranged from 0.02 to 0.49 with mean 0.19 and median 0.13. Over 40% of loci had PIC below 0.1 (Figure 2b). Between 34% (5H) and 52% (1H) of low PIC loci were present on individual chromosomes. In total, about 18% of loci were highly informative, i.e., had a PIC above 0.4. Their proportion on chromosomes ranged from 0.12 (1H) to 0.22 (3H). The mean PIC value for each chromosome showed significant. differences. The lowest value was observed for 1H and the highest values for 3H and 5H (Figure 2b). 2.2. Genetic Diversity The coefficients of variation such as observed heterozygosity (uHo), expected heterozygosity (uHe) and fixation factor (F) were calculated for the studied material. The mean values of these were 0.058, 0.197 and 0.706, respectively. The mean uHo for 3H, 5H and 6H (~0.06) was significantly higher than for the other chromosomes (~0.05) (Figure 3). The mean uHe was 0.155–0.216 for 1H and 5H, respectively. F-values for individual chromosomes also showed significant differences. The lowest value was observed for 1H (0.671) and the highest for 4H (0.757). Heterozygous state was not observed in approximately 23% of loci. Chromosome 5H had the highest proportion of heterozygous loci, while 2H had the lowest (Table 2). The analysis of diversity coefficients (uHo, uHe and F) in groups of cultivars, assigned based on the period of breeding, showed the presence of significant differences (Figure 4). Heterozygosity observed decreased progressively with time, while the level of inbreeding increased. The pattern of uHe values was a little more complicated, i.e., it tended to alternately decrease and increase in consecutive periods. Its values were highest in the group of the newest and the oldest cultivars and lowest in the group from the period 1990–1999. Allelic richness (AR) also showed fluctuations over time, being highest in the period 1990–1999 and lowest in cultivars bred after 2000. Analysis of the diversity coefficients in relation to the period of breeding and chromosome showed that the pattern of changes in the level of uHo was in most cases consistent with the main pattern (Figure 5). The divergence occurred on chromosomes 1H and 5H, where an increase in heterogeneity of cultivars bred in 1970–1989 was observed. uHo showed a variable behavior over time depending on the chromosome. For 1H, 3H, 4H and 5H uHe initially increased and then decreased, although the increasing trend interruption occurred either in the period 1970–1989 or in 1990–1999. For 6H uHe decreased with time and for 2H and 7H it fluctuated. The inbreeding level showed a similar change pattern as uHo, but in the opposite direction. Because DArTseq analysis was conducted on pooled samples, where each cultivar was represented by eight seedlings, it was possible to estimate the level of intrinsic heterogeneity of the cultivars studied. Barley is a self-pollinating species; therefore, heterozygous loci are due to the presence of different genotypes in the sample. Thus, it can be assumed that the heterozygosity observed reflects the heterogeneity of the cultivar. Within 83 tested cultivars Ho ranged from 0.011 (‘Kazimierski’) to 0.236 (‘Cesarski Stieglera’) (Figure 6). In the group of the oldest cultivars, i.e., those bred before 1945, which included also cultivars bred at the end of the 19th century, the level of heterogeneity ranged from 0.012 (‘Przeworski’) to 0.236 (‘Cesarski Stieglera’). Eight cultivars showed a relatively high level of homogeneity, while the remaining five were significantly internally differentiated. In cultivars bred between 1945 and 1969, heterogeneity ranged from 0.011 (‘Kazimierski’) to 0.176 (‘Antoniński Browarny’). In cultivars bred between 1945 and 1969, heterogeneity ranged from 0.011 (‘Kazimierski’) to 0.176 (‘Antoniński Browarny’). This group included two pairs of accessions whose passport data indicate that they may be duplicates. According to the EGISET database, accessions numbered PL42124 and PL43614 are duplicates of ‘Damazy’ cultivar and PL40940 and PL42363 of ‘Jarek’ cultivar. These accessions are characterized by a high level of homogeneity, although in the case of ‘Damazy’, there is a difference between the two samples, i.e., 0.013 vs. 0.024. Among 18 accessions representing cultivars bred in the period 1970–1989, only four showed an increased level of heterogeneity (>0.1), i.e., ‘Lot’ (0.205), ‘Polon’ (0.190), ‘Lubuski’ (0.174) and ‘Dema’ (0.127). In this group, there were as many as six pairs of accessions that may represent duplicates (Table 1). For two pairs, i.e., PL43033 and PL43416 (‘Dema’) and PL43032 and PL43421 (‘Lot’), there were significant differences in the level of heterogeneity. In the fourth and most numerous group of cultivars, which were bred in the late 20th century, the level of heterogeneity was quite even and noticeably low (generally below 0.09). Accession number PL43812 is an exception; according to passport data, it is one of three accessions representing the ‘Bryl’ cultivar. However, the level of heterogeneity of this accession (0.189) is considerably higher than that of the other two accessions, for which Ho is about 0.035. A value above 0.1 in this group was also found in the sample representing the ‘Rataj’ cultivar. The fifth group consisted of modern cultivars, among which there were seven of Polish origin and five of foreign origin, i.e., from Germany and France. All cultivars were characterized by a very high level of homogeneity. The highest Ho value was found in the ‘Granal’ cultivar (0.083), the lowest in ‘Runner’ and ‘RGT Planet’ (0.013). 2.3. Unique Alleles The number of unique alleles was also compared among the groups (Figure 7). As a threshold level, the frequency of a unique variant higher or equal to 0.25 in a given group of cultivars was assumed. In this way, the dynamics of changes in the genome of the presence of unique variants occurring quite commonly in the studied groups was observed. Data considering rare alleles, i.e., >0.05, are presented in Table S1. In the oldest cultivars, 78 loci contained variants that were not transferred to the group of cultivars bred in the subsequent period. However, in the group of cultivars bred between 1945 and 1969, there were 125 loci in which new variants were present. Thus, changes affected about 1.74% of all investigated loci. The highest proportion of changes of unique alleles was observed between the groups of cultivars bred in 1990–1999 and modern ones, and they were related to 4.53% of analyzed loci. On the other hand, the smallest changes were observed between the groups from the middle breeding period, i.e., between 1970–1989 and 1990–1999 (0.94% of loci). Changes in allele frequency, i.e., the disappearance of ‘old’ alleles and appearance of ‘new’ ones, are related to the constant evolution of the breeding direction and to the appearance of new objectives, apart from yield increase. From the perspective of individual chromosomes, the greatest magnitude of change was in chromosome 5H (Table 3). During the surveyed breeding period, 125 unique allelic variants were lost while 138 new variants were introduced. The smallest changes affected 1H and 6H; however, on 1H almost twice as many new allelic variants appeared as were lost, while on 6H only the removal of variation associated with unique alleles took place. Comparing the different consecutive periods, it is clear that the dynamics of change varied at different times for different chromosomes. However, two points at which “old” variation was replaced by “new” variation can be clearly seen, i.e., 1970–1989 and recently. 2.4. Genetic Distance and Principal Coordinate Analysis An analysis of genetic distance showed that the lowest distance occurred between the two accessions representing the “Klimek” cultivar, and the highest between ‘Mazowiecki’ and ‘Stratus’ (Table 4). Low distance values, i.e., below 0.05, were also observed for nine successive pairs of accessions. This similarity will be discussed in detail in the following section, dealing with duplicates. Maximal genetic distance between accessions in the five groups had the lowest value for modern cultivars, and the highest for cultivars bred in the period 1945–1969. Thus, it can be concluded that, among the studied groups of cultivars, those bred most recently have the narrowest gene pool, while the widest gene pool was recorded for cultivars bred after World War II. Principal coordinate analysis (PCoA) performed for 83 spring barley cultivars indicated that the first three axes account for 32.69%, i.e., 13.81%, 10.69% and 8.19% of the variation, respectively (Figure 8). Graphical visualization of the results in a 3D plot of the first three coordinates showed that cultivars bred in the first four periods were arranged sequentially along the PCo1 axis. There is no clear demarcation between the groups of cultivars, and the gene pools in the subsequent periods partly overlap and intermingle. The PCo3 axis allowed us to distinguish the group of the newest cultivars. Several cultivars bred in the period 1990–1999 (‘Orlik’(51,52), ‘Mobek’ and ‘Gwarek’) exhibit greater similarity to the group of recent cultivars than to cultivars bred in the same period. Among the most recent cultivars, those bred in Poland display a link to historical domestic materials. Foreign cultivars, on the other hand, show some distinctness. Polish cultivar ‘Podarek’ is the most genetically similar to foreign cultivars, especially to ‘Alianz’ and ‘RGT Planet’. The 3D plot also clearly shows the distinctiveness of the five accessions. Among them, the outermost, i.e., ‘Klimek’(35,36) and ‘Mazowiecki’, are multi-row. The other two are ‘Polo’ and ‘Start’. Both are two-row, like the rest of the tested cultivars, but they originated from crosses of foreign cultivars. 2.5. Population Structure Analysis of Molecular Variance (AMOVA) performed for 83 spring barley cultivars assigned to five breeding periods showed that most of the variation occurred within the groups (91%), and only 9% was inter-group variation. The admixture model in the STRUCTURE software [22] was implemented to investigate the population structure in the studied set of cultivars. Based on ad hoc statistic ΔK, the true number of clusters in the current study was identified at the level of 11 (Figure S2). Cultivars were assigned into clusters based on an 80% membership threshold. Only 28 cultivars were classified into nine clusters, i.e., gene pools, and the rest showed varying levels of admixture (Figure 9). Most cultivars were assigned to pools 11 (nine cultivars) and 9 (seven cultivars). None of the studied accessions were assigned to pools 1 and 4 (Figure 10). The group of cultivars bred before 1945 was dominated by pool 7, as in the following period (Figure 10). However, it should be noted that the percentage of this cluster decreased from 60.7% to 37.9% in the following periods. What is more, in the group of the oldest cultivars, five were considered pure, i.e., four were assigned to cluster 7 and one to cluster 8. The share of cluster 8 in the later periods of breeding is negligible and practically does not occur in cultivars bred after 1969. About 20% of this group was also represented by cluster 1. Its highest admixture was observed in the cultivar ‘Kujawski’. The participation of the remaining gene pools did not exceed several percent. In the group of cultivars bred in the period 1945–1969, only two cultivars were recognized as belonging to cluster 2. In both cases, this was ‘Damazy’. It is worth noticing that this cluster appears as an admixture in several more cultivars, but its contribution does not exceed 40%. In this group, the proportion of gene pool 1 increases slightly (21.4%). This pool constitutes about 57% of the genetic makeup in the cultivar ‘Jarek’, represented by two accessions. In the remaining cultivars, its content ranged from 0 to 37%. In the next two periods, in total, from 1970 to 1999, pool 11 was dominant and its participation increased with time from 37.3% to 43.7%. Among the cultivars bred in the initial period (1970–1989), only four were classified as pure. Two accessions representing ‘Klimek’ cultivar were assigned to gene pool 6, and two representing ‘Bielik’ cultivar to pool 11. Interestingly, gene pool 6 was practically absent in the remaining cultivars. In the group of cultivars from a later period (1990–1999), 10 cultivars were considered pure. They represent cluster 11 (6 accessions), 10 (two accessions) and 3 and 5 (one accession each). At the same time, the share of cluster 1 decreased with time in these two groups. The proportion of cluster 10 remained constant at about 15%, while an increase from 8.5% to 13.5% was observed for cluster 9 in these two groups. Whereas for the previous four periods of breeding, continuity of changes in population structure was observed, in the group of contemporary cultivars there was a rapid increase in the contribution of cluster 9, to 69.4%, and marginalization of other clusters. Seven cultivars from this period were assigned as pure to cluster 9, while in the rest its participation ranged from 23.8–69.4%. It should be noted that five cultivars with the highest proportion of cluster 9 were of foreign origin. An additional contribution of clusters 10 and 11 was observed in Polish cultivars. An exception was ‘Podarek’ cultivar, whose genetic makeup does not differ significantly from Western European cultivars. 2.6. Traces of Targeted Selection Genomic regions involved in differentiation of cultivars bred before 1945 and after 2000 were revealed by plotting FST values for all loci with known locations in the genome (Figure 11). Regions with high FST values that indicate fixation of different alleles in both groups were observed on chromosomes 5H and 3H. The majority of regions with high FST were identified on 5H. It is noteworthy that these regions were found in both distal (especially in the short arm) and pericentromeric parts. On 3H, high FST was observed on the short arm and these loci were located in the middle part of the arm. For comparison, the analysis of PIC distribution in the two groups of cultivars was also performed. It showed that in the majority the PIC profile remained unchanged. Importantly, regions of low polymorphism were found in centromeric and pericentromeric regions in both groups at 1H, 2H, 4H and 7H. A remarkable change in the PIC profile was detected at 5H; in the region with high FST, the average PIC value increased in the group of the most recent cultivars. The alleles not present in the oldest cultivars also appeared there. 2.7. Identification and Verification of Duplicates In the studied set of 83 spring barley cultivars, as many as 31 accessions had passport data indicating that they appeared to be duplicates or even triplicates of cultivars. These accessions were submitted to the gene bank in different years. One of the aims of this study was to verify whether these accessions were indeed duplicates. For final verification, an identity by descent (IBD) analysis was performed (Figure 12) and its results were compared with those obtained in previously described analyses (Table 5). In this way, using different analytical approaches, it was possible to determine that duplicates occur for 10 varieties in the gene bank collection. An additional triplicate was identified for the cultivar Ars. The cultivar Mago showed a very high level of genetic similarity to both accessions of ‘Ars’ cultivar. However, in the case of three ‘Bryl ‘accessions, DArTseq analysis revealed genetic distinctness of accession PL 43812. It should therefore be assumed that this accession does not represent the ‘Bryl’ cultivar because the seed sample was contaminated with another cultivar, as indicated by its exceptionally high heterogeneity. Accessions representing cultivars such as ‘Dema’, ‘Lot’, ’Polo’ and ‘Rhodes’ according to passport data cannot be considered duplicates. Especially in the case of ‘Polo’, we are dealing with completely different genetic makeup. According to the population structure analysis, accession PL 43368 is the only one in the studied set of cultivars that represents the third gene pool and is therefore a valuable source of the collection diversity. 2.8. Core Collection An advanced maximization strategy through a modified heuristic algorithm (A*), which is complete and optimal, i.e., it finds a path if only one exists, and the shortest path, was used to identify the minimum group of cultivars representing the full diversity. Out of the studied 83 cultivars, a set of 50 that should form the core collection was extracted. The cultivars are marked in Table 6. 3. Discussion Described in this paper, the analysis of 83 spring barley cultivars representing 120 years of Polish breeding is the next step towards a molecular characterization of the collection conserved at NCPGR using high-resolution and genome-wide genotyping via the DArTseq method. This is a direct continuation of the study by Dziurdziak et al. [25,26] in which barley landraces were characterized. So far, a large number of articles have been published on the analysis of barley genetic diversity. In spite of this, the topic is still of interest to researchers from all over the world, which may indicate its relevance. In the last two years only, a number of publications on this subject have appeared [27,28,29,30,31,32,33,34,35]. A detailed description of genetic diversity is a prerequisite for effective conservation and utilization of genetic resources and progress in crop breeding programs. 3.1. SNP Abundance and Analysis of Base Changes The analyzed loci, relatively uniform, represented all barley chromosomes, and their proportion and density was consistent with previous results obtained by DArTseq for barley [25]. At the same time, the analysis provided significantly more uniform and above 3.5 times denser data than the results obtained for wheat based on 65,560 loci derived from genotyping-by-sequencing (GBS), of which over 77% SNPs had unknown chromosome location [36]. The distribution of the analyzed loci along chromosomes, i.e., their high frequency in the distal parts of chromosomes and low or complete absence in the centromeric and pericentromeric regions, was also observed in previous studies on barley, durum wheat, and soybean [21,25,37,38]. This is also consistent with the distribution of protein-coding genes on barley chromosomes and the recombination rate [21]. A characteristic feature of Triticeae, including barley, is a significantly reduced level of meiotic recombination in the centromeric and pericentromeric regions [39,40,41]. A high recombination rate in distal chromosome fragments is associated with barley domestication. In wild barley, high recombination rates have been found in more interstitial chromosomes’ regions [42]. The analysis showed the presence of all possible SNP types in the studied cultivar set. The number of transition-type SNPs was 1.5 times higher than the transversion-type. An excess of transversions was also observed in previous studies involving NGS technology for cowpea, wheat, rice, barley, and common bean, among others [25,36,43,44,45]. The higher frequency of transition SNPs over transversion SNPs is due to their higher probability of preserving protein structure and function [44,46]. The most abundant SNP was A > G followed by C > T which may reflect the frequency of methylation/demethylation related mutations and was also common in the above cited studies. It is noteworthy that the DArT-seq analysis also revealed an increased relative abundance of C > G SNPs compared to the other transversions. Similar results were previously obtained by Duran et al. [47] for barley, Lai et al. [48] and Alipour et al. [36] for wheat, but this phenomenon has not been explained so far. Polymorphism of the examined loci, determined by the PIC coefficient, was slightly lower in the cultivars than in the landraces previously studied [25]. However, differences occurred at the chromosome level. For landraces, the lowest mean PIC value was observed for 2H and for cultivars for 1H. This may indicate increased selection within 1H during breeding. 3.2. Genetic Diversity For thousands of years, since their domestication, crops have been cultivated as populations with a complex genetic structure. Selection occurred on farms either as a result of human efforts or as a result of pressure from local ecogeographic conditions. This resulted in a differentiation between populations and the formation of landraces [49,50]. The 20th century brought progress in breeding and the displacement of landraces by cultivars tending towards homogeneity. To be released, cultivars had to go through evaluation for distinctness, uniformity, and stability [51]. Looking ove4 120 years of barley breeding in Poland it is clearly visible that the average variability within old cultivars is almost three times higher than in the group of modern cultivars, which are very uniform. Breeding-related selection is even more pronounced when the results obtained here are compared with the previous ones for landraces. Even the most internally differentiated cultivar, i.e., ‘Cesarski Sieglera’ (Ho = 0.236), is almost twice as less heterogeneous than the Polish landrace PL503844 (0.422) [25]. Thus, it can be clearly seen how breeding progress leads to genetic uniformity of individuals within a cultivar. Obviously, among the old cultivars studied here, there were also some with low heterogeneity, comparable even to modern cultivars, e.g., ‘Danubia Ciolkowski’ or ‘Kujawski’. However, it should be considered that a time lapse took place from the breeding of the oldest cultivars to their acquisition by the gene bank and finally to the time of the genetic analysis presented here. The oldest cultivars in the studied set come from the turn of the 19th and 20th century. Thus, they must have survived one or sometimes two world wars, during which part of their original variability may have been lost. Before these cultivars were acquired for the gene bank, they were maintained in the collections of breeders, universities or scientific institutes. Improper conservation breeding, repeated propagation or even lack of sufficiently frequent seed regeneration may have led to the degeneration of cultivars by further loss of variability. The breeders’ habit is to remove individuals diverging from the remaining plants from the cultivar, so that the cultivar fulfils the condition of uniformity. However, in the case of old cultivars, this may have exacerbated the loss of genetic variation. In the period prior to preservation in the seed bank, situations could also arise in which an old cultivar was deliberately over-selected for use in a breeding program, but this information was not provided to the gene bank. The low heterogeneity of some old cultivars may also be the result of genetic drift that occurred during seed reproduction for the gene bank, i.e., when the initial seed sample was too small and did not fully represent the original variability of the cultivar. Of course, at each of the stages the selection pressure of the environment may have also acted to remove some of the genotypes from the population, thus depleting its gene pool. At this point, from the point of view of the gene bank, it is irrelevant either where or for what reason the reduction in variation occurred. However, the information about the low level of heterogeneity attached to the description of the accessions in the gene bank database is important mainly for the end users, i.e., breeders and scientists, and sometimes also for farmers. Therefore, it cannot be generalized that old cultivars are always highly heterogeneous. It is worth noticing, that among old oat cultivars stored in NCPGR, and coming from the same breeding period, not so significant differences in the level of heterogeneity were observed [52]. However, the same trend was observed, i.e., that as breeding progressed in the 20th century, the genetic uniformity of individuals within a cultivar clearly increased [53]. However, the increase in genetic uniformity of the studied cultivars was not accompanied by a decrease in overall genetic diversity. Over the 120 years of breeding, fluctuations in the level of uHe, AR and maximum genetic distance were observed in the studied cultivar groups. Thus, no loss of genetic variation was observed as a result of breeding progress, as was implied by Gepts et al. [5] or Russell et al. [54]. The results of the analyses presented here are consistent with the meta-analysis of changes in genetic variation in crop cultivars conducted by van der Wouw et al. [55]. Based on the results obtained, no loss of genetic diversity was observed between the oldest and the newest cultivars studied. However, a detailed analysis of changes in allele frequency clearly indicated genetic erosion. In the course of breeding, about 600 alleles were lost from the gene pool of barley cultivars over the years. They have been preserved only thanks to the activity of the gene bank. Gradually, during breeding, ’old’ unique alleles were driven out from Polish cultivars and replaced by new allelic variation. As many as 11% of the 11,655 loci examined have completely different alleles in the group of the oldest and the newest cultivars. On the basis of the few pedigree data, we can state that alleles representing the native gene pool from landraces occurring in Poland and the Czech Republic were almost completely suppressed in breeding programs. This result also indicates that researchers should be very cautious about the results of the analysis of genetic diversity in the context of changes over time. 3.3. Evidence of Targeted Selection Genome-wide DArTseq analysis provided an opportunity to evaluate changes in the genetic structure of spring barley cultivars bred in Poland. Both PCoA and STRUCTURE showed the merging of consecutive groups of gene pools. Breeding in Poland follows European trends, so it may be assumed that changes in population structure reflect a breeding focus on increasing yield and, in recent years, also on increasing resistance to pathogens. A gradient of variation and gradual targeted shifts were also observed in earlier studies on barley [56,57,58]. Thanks to the knowledge of the barley genome sequence and the mapping of DArTseq data to it, it was possible to determine the chromosomal localization of the analyzed loci. This allowed observation not only of the changes in genetic diversity in time, but also to what extent this affected individual chromosomes. In general, for most chromosomes there was the same pattern of change over time, i.e., a decrease in observed heterozygosity and an increase in inbreeding along with breeding progress. Comparison of the polymorphism level of loci along chromosomes in cultivars representing extreme breeding periods allowed detection of regions showing a lack of variation. These regions did not change during 120 years of breeding and were located in the centromeric and pericentromeric fragments of chromosomes 1H, 2H, 4H and 7H. Interestingly, in landraces of spring barley, such “empty” regions were observed at 1H, 2H and 4H [25] and, in the study of Tondelli et al. [58], at 1H, 2H and 7H. This means that landraces contain variability within 7H, and European modern cultivars within 4H, which is not present in Polish cultivars. The 4H centromeric region contains the QTL of net form net blotch (NFNB) resistance and Mlg, a powdery mildew resistance gene in the gene-dense pericentromeric region [59,60], while the 7H centromeric region contains QTLs related to heading date, yield and yield-forming traits such as plant height and root length [61,62,63,64,65,66]. FST analysis enabled identification of regions in which, during breeding, different alleles were fixed compared to the oldest cultivars. These regions occurred mainly on 5H. Their presence in the pericentromeric region was also found in modern European cultivars [58]. The fixation of “new” alleles in the pericentromeric region may be related to resistance breeding programs. In this region, several loci for resistance to leaf rust were found, including Rph2 [58,67]. The VRN-1 gene encoding the MADS-box transcription factor is located in close proximity to the high-fixation region found on 5HL. Its involvement in the regulation of genes related to reproductive organs and flowering of plants is well known [68]. Wild-type VRN-1 determines the need for vernalization, i.e., prolonged exposure to cold as a prerequisite for flowering in most winter cereals [69]. Deletion in the first intron allows spring-sown plants to flower without prior vernalization [70]. It was proved that a genetic variation of VRN-1 correlates with flowering time in spring forms of barley [71]. According to the Voss-Fels et al. [72] study, VRN-1 is also associated with root system morphology. In addition, variation in this gene also affects final biomass and yield, especially under drought and salinity stress [73,74]. The high FST region on 3H may be associated with selection for reduced plant height and increased lodging resistance. Numerous genes and QTLs related to plant height have been mapped on chromosome 3H [58,75,76,77,78]. 3.4. Improving the Management of the Germplasm Collection DArTseq analysis will also enable improved management of the germ plasm collection. On the one hand, verification or identification of duplicate accessions was performed, and on the other, a core collection was selected. In a group of 74 cultivars stored in the Polish gene bank, for 15 cultivars, there were two or even three separate accessions. Duplicates in gene banks arise when, by mistake, a cultivar or other type of accession becomes added to a collection multiple times [79]. Here, duplicates were most often created as a result of inclusion of accessions into the collection before their official registration as a cultivar and subsequent incorporation of an already registered cultivar. Accessions with identical passport data and genetic makeup will be combined as separate subsamples under a common accession number. In contrast, accession PL43812 ‘Bryl’ will have its passport data corrected. Due to the genetic distinctiveness of this accession from the other cultivars, it will be submitted to the curator for characterization and evaluation. Improved barley collection management will also be provided by the selected core collection. The idea behind the establishment of core collections is to facilitate scientists and breeders in using the genetic resources stored in germplasm collections [80]. This also facilitates the maintenance of germplasm collections in gene banks, which can thus reduce the number of accessions held in active collections and provide access to the full range of diversity. 4. Materials and Methods 4.1. Plant Material From the spring barley collection held at the National Center for Plant Genetic Resources (NCPGR), 74 accessions classified as advanced/improved cultivars were selected and analyzed. In addition, nine cultivars that are currently cultivated and have not yet been accessioned into the gene bank collection were included in the analysis (Table 6). For each investigated cultivar, information about the period and place of its breeding and the time of its entry and presence in the official register of cultivated varieties, maintained by the Research Centre for Cultivar Testing (RCCT), was collected. Data for historical cultivars were obtained from Arseniuk et al. [10] and for more contemporary cultivars directly from RCCT. Based on these data, the cultivars were divided into five groups i.e., bred before 1945, 1945–1969, 1970–1989, 1990–1999 and after 2000. ijms-23-04553-t006_Table 6 Table 6 The list of spring barley cultivars analyzed by DArTseq. No. Accession Number Cultivar Name BREEDING SITE Country Year/Period of Registration Year/Period of Deregistration Core Collection 1 PL41572 Antoniński Browarny Antoniny POL 1930 1939 yes 2 PL41323 Cesarski Stieglera Sobótka POL after 1918 1929 yes 3 PL42125 Danubia Ciołkowski (Danubia Ciślikowski) Ciołkowo POL 1930 1940 yes 4 PL40306 Elka Hilderanda Kleszczewo POL 1930 1939 no 5 PL41691 Hanna Borzymowicki Borzymie POL 1930 1939 yes 6 PL41692 Hanna Gambrinus; Hanna Gambrvnus Sielce POL 1918–1939 1957 yes 7 PL41695 Hanna Skrzeszowicki Polanowice POL 1918–1939 1971 yes 8 PL43217 Kujawski Rusewko POL after 1918 1929 yes 9 PL41475 Kutnowski Kutno POL 1900 1918–1939 yes 10 PL42060 Puławski Browarny Puławy POL 1918–1939 1939 yes 11 PL41905 Przeworski Dolne POL 1918–1939 1939 yes 12 PL42129 Putza Rusewko POL 1930 1940 yes 13 PL40460 Teresa Rusewko POL 1930 1940 yes 14 PL41570 Antałek Tulce POL 1956 1971 yes 15 PL42034 Boryna Szelejewo POL 1955 1958 yes 16 PL42042 Browarny PZHR Strzelce POL 1946 1969 no 17 PL42124 Damazy Polanowice POL 1969 1975 yes 18 PL43614 Damazy Polanowice POL 1969 1975 no 19 PL40940 Jarek Bąków POL 1963 1970 no 20 PL42363 Jarek Bąków POL 1963 1970 no 21 PL41740 Kazimierski Brzezie POL 1955 1967 yes 22 PL44075 Kos Leszno POL 1946 1958 yes 23 PL42127 Mazowiecki Młochów, Dłużew POL 1946 1959 yes 24 PL41916 Refleks Sobótka POL 1955 1960 yes 25 PL41924 Sandomierski Jasice POL 1955 1960 no 26 PL41940 Skrzeszowicki Polanowice POL 1955 1972 no 27 PL41233 Wanda Celbowo POL 1965 1970 no 28 PL41419 Ars Gorzów Wlkp. POL 1983 1996 yes 29 PL43646 Ars Gorzów Wlkp. POL 1983 1996 no 30 PL43423 Bielik Modzurów POL 1984 1994 no 31 PL41415 Bielik Modzurów POL 1984 1994 yes 32 PL43033 Dema Łagiewniki POL 1987 1998 no 33 PL43416 Dema Łagiewniki POL 1987 1998 no 34 PL41328 Gryf Gorzów Wlkp. POL 1971 1980 no 35 PL43086 Klimek Strzelce POL 1989 1996 no 36 PL43414 Klimek Strzelce POL 1989 1996 yes 37 PL41329 Kosmos Bąków POL 1974 1978 yes 38 PL43032 Lot Małyszyn, Gorzów Wlkp. POL 1987 2007 yes 39 PL43421 Lot Małyszyn, Gorzów Wlkp. POL 1987 2007 no 40 PL41769 Lubuski Strzelce, Borów POL 1970 1975 no 41 PL41418 Mago na POL na na no 42 PL41886 Piast Polanowice POL na 1970 no 43 PL40556 Polon Małyszyn POL 1977 1989 yes 44 PL43056 Rudzik Modzurów POL 1987 2008 yes 45 PL43423 Rudzik Modzurów POL 1987 2008 no 46 PL44045 Atol Strzelce POL 1997 2007 no 47 PL44030 Bies Modzurów POL 1996 2010 yes 48 PL43637 Boss Bąków POL 1994 2020 yes 49 PL44031 Gwarek Polanowice POL 1999 2011 no 50 PL43424 Mobek Modzurów POL 1993 2001 yes 51 PL43335 Orlik Bąków POL 1990 2000 yes 52 PL43417 Orlik Bąków POL 1990 2000 no 53 PL43368 Polo Strzelce POL 1992 2003 yes 54 PL43411 Polo Strzelce POL 1992 2003 yes 55 PL43867 Rastik Radzików POL 1999 2010 yes 56 PL43749 Rodion Radzików POL 1996 2021 no 57 PL35393 Start Polanowice POL 1995 2010 yes 58 PL43868 Stratus Strzelce POL 1999 2020 yes 59 PL500074 Bryl Bąków POL 1998 2021 no 60 PL43949 Bryl Bąków POL 1998 2021 yes 61 PL43812 Bryl Bąków POL 1998 2021 no 62 PL500070 Edgar Bąków POL 1992 2004 no 63 PL500666 Edgar Bąków POL 1992 2004 no 64 PL43419 Nagrad Nagradowice POL 1990 na no 65 PL43379 Nagrad Nagradowice POL 1990 na yes 66 PL43750 Rabel Radzików POL 1996 2010 yes 67 PL500667 Rambo Radzików POL 1993 2003 yes 68 PL43747 Rambo Radzików POL 1993 2003 no 69 PL43748 Rataj Radzików POL 1996 2010 yes 70 PL43369 Rodos Strzelce POL 1992 2010 yes 71 PL43412 Rodos Strzelce POL 1992 2010 yes 72 PL503817 Granal Nagradowice POL 2001 2021 no 73 PL503818 Nadek Nagradowice POL 2004 2014 yes 74 PL44032 Sezam Szelejewo, Modzurów POL 2000 2010 no 75 ni Runner na GER 2018 up now no 76 ni Atico Kraków POL 2009 up now yes 77 ni Podarek Strzelce POL 2014 up now yes 78 ni Allianz na FRA 2016 up now no 79 ni Rubaszek Smolice POL 2014 up now yes 80 ni Soldo na GER 2013 up now yes 81 ni Ella na FRA 2012 up now yes 82 ni Rezus Smolice POL 2018 up now yes 83 ni RGT Planet na FRA 2016 up now yes na—data not available; ni—not included in the gene bank collection; FRA—France; GER—Germany; POL—Poland. 4.2. DArTseq Genotyping Seeds, were obtained from long term storage of NCPGR or directly from breeding stations, were sown in a greenhouse in a substrate dedicated to planting seeds. From eight, random seedlings in the second leaf stage, the middle part of the second leaf about 10 mm long was collected. A modified CTAB protocol [81,82] was used to isolate total genomic DNA. The DNA quantity and quality were assessed by spectrophotometric analysis using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Willmington, DA, USA) followed by agarose gel electrophoresis (1.5% agarose). The obtained DNA isolates were mixed in equal proportions to form a pooled sample representing the tested cultivar. All bulk samples were diluted to a final concentration of 75 ng/µL and shipped to the Diversity Arrays Technology Pty Ltd., Canberra, Australia for DArTseq genotyping. The resulting sequences were aligned to the barley Morex genome assembly [21]. 4.3. Data Analysis DArTseq results in a form of a table containing codominant single nucleotide polymorphisms (SNPs) were transformed into a binary matrix. Each locus was recorded as two lines where homozygotes were denoted as 1/1 or 0/0 and heterozygotes as 1/0. In the first step the array was filtered according to reproducibility (RepAvg ≥ 0.95), call rate (CallRate ≥ 0.95), and the minor allele frequency (MAF > 0.01). Further preliminary analysis included determination of the proportion of polymorphic loci and calculation of polymorphic information content (PIC), observed (Ho) and expected heterozygosity (He), and inbreeding coefficient (F) according to the formulas published in Dziurdziak et al. [25]. The distribution of the investigated loci on the chromosomes and PIC, Ho and F along the chromosomes were also assessed using the sliding window method with 500 kb intervals at 250 positions for each chromosome. Values of variation coefficients were calculated for groups of cultivars using a formula excluding the effect of sample size. Analysis of variance ANOVA and Tukey’s post hoc test were used to compare the degree of variation. The level of allelic richness (AR) was assessed based on rarefaction method. Analysis of molecular variance AMOVA was also performed. The Wright’s FST parameter was used to estimate genome wide group differentiation, and to increase plot resolution transformation by rising FST to the 10th power (FST10) was performed [58]. The genetic distance between the sites was calculated using the Jaccard coefficient and then principal coordinate analysis (PCoA) was performed. Moreover, the identity by descent (IBD) was estimated for all pairwise comparisons among the accessions. Duplicates were defined as having IBD > 0.95 among accessions. The final step of the analysis was to perform clustering based on the Bayesian model to analyze the genetic structure of examined accessions. In order to obtain the most probable value of K, a search was conducted in the range from 1 to 16 with six independent repetitions per K for cultivars analysis, whereas analysis of the compiled cultivars and preexisting landraces results was performed for K up to 11 with six independent runs/K. A LINUX cluster hosted by the Interdisciplinary Centre for Mathematical and Computational Modelling at the Warsaw University was used to run the analysis of batch files. The number of clusters was determined based on the posteriori data probability for a given K and ΔK [23] and the full search algorithm was used to find the best match for replicated cluster analysis results. A cutoff value of 0.8 was set as the probability of assigning accession to the group. A core collection was extracted using the advanced M strategy implemented through a modified heuristic algorithm (A*). The above mentioned analyses were performed using Microsoft Excel 2016, XLSTAT Ecology (Addinsoft, Inc., Brooklyn, NY, USA), GenAlEx 6.501 [22], HP-RARE 1.1 [83], PLINK [84], STRUCTURE v2.3.4 [85], CLUMPP [24], PowerCore [86]. The following packages in R were used to visualize the results: igraph [87], circlize [88]. The population structure analyses were performed in the framework of Computational Grant (G72-19) from the Interdisciplinary Center for Mathematical and Computer Modeling at the University of Warsaw, Poland (ICM UW). 5. Conclusions This study showed that the gene pool structure of spring barley cultivars has changed significantly during 120 years of breeding in Poland. Many alleles have been displaced and replaced by new ones. These changes were associated with breeding priority evolution over time. Traces of directed selection are particularly visible on chromosomes 3H and 5H. The genetic uniformity of the cultivars increased with the progress of breeding. In contrast, the low variation within some of the old cultivars is the result of selection that probably occurred before they were obtained by the gene bank. A side effect of the analysis was the identification and verification of duplicates and the establishment of a core collection and thus DArTseq analysis will contribute to more efficient management of the barley collection in the gene bank. Analysis of changes in the level of genetic diversity over time may not reflect changes in genetic structure, so its results should be treated with caution. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094553/s1. Click here for additional data file. Author Contributions Conceptualization, J.D. and M.B.; methodology, J.D. and M.B.; formal analysis, M.B.; investigation, J.D.; resources, H.B. and W.P.; data curation, J.D. and M.B.; writing—original draft preparation, J.D.; writing—review and editing, M.B., H.B. and W.P.; visualization, J.D. and M.B.; supervision, M.B.; project administration, W.P. and M.B.; funding acquisition, W.P. and H.B. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by the multi-annual program: 2015–2020 “Establishment of a scientific basis for biological progress and preservation of plant genetic resources as a source of innovation to support sustainable agriculture and food security of the country” coordinated by Plant Breeding and Acclimatization Institute-National Research Institute and financed by the Ministry of Agriculture and Rural Development of Poland. The calculations were performed at the Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw (ICM UW) within the framework of Computational Grant No. G72–19. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The raw data of DArTseq SNP used in this study are openly available on the platform Center for Open Science at https://osf.io/v4m5s/ (accessed on 17 April 2022). 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 Circular overview of seven H. vulgare chromosomes based on DArTseq data acquired for 83 spring cultivars. (a) DArTseq loci distribution; (b) Average polymorphism information content (PIC) distribution; (c) Average observed heterozygosity (Ho) distribution. A sliding window approach with 500 kb windows, printed for 250 positions along the full length of barley chromosomes based on the genome assembly: IBSC_v2 [21] was applied. Figure 2 Summary of polymorphism information content (PIC) values. (a) Range of relative frequencies for all analyzed DArTseq loci in 83 spring barley cultivars; (b) Mean PIC value including chromosomal location of studied DArTseq loci. Letters above the bars in the graph indicate homogeneous groups determined by Tukey’s post hoc test. Figure 3 Summary of the diversity coefficient values across barley chromosomes for 83 cultivars based on DArTseq data. Letters above the bars in the graph indicate homogeneous groups determined by Tukey’s post hoc test. Figure 4 Summary of the diversity coefficient values for cultivar groups assigned based on the breeding date. Letters above the bars in the graph indicate homogeneous groups determined by Tukey’s post hoc test. Figure 5 Summary of the diversity coefficients values for cultivar groups, assigned based on the breeding date considering chromosome localization. Letters above the bars in the graph indicate homogeneous groups determined by Tukey’s post hoc test. (a) observed heterozygosity (uHo); (b) expected heterozygosity (uHe); (c) inbreeding coefficient (F). Figure 6 Heterogeneity level of 83 spring barley cultivars expressed by observed heterozygosity value based on SNPs derived from DArTseq analysis. Figure 7 Summary of changes in the number of unique alleles during more than 120 years of breeding and cultivation of spring barley in Poland. Colors indicate groups and dashed lines connect compared periods. Above the axis, information about the new breeding objectives is placed. Figure 8 Graphical presentation of the Principal Coordinate Analysis results for DArTseq data of 83 spring barley cultivars. Results in the first three coordinates’ system. Each point denotes one tested cultivar. Numbering according to Table 6. Rotable 3D figure can be found in the supplementary materials (Figure S1). Figure 9 The results of 100,000 iterations of STRUCTURE software [22] for 83 spring barley cultivars based on DArTseq-derived SNPs data with K values K = 11 based on ad hoc measure ∆K [23,24], where K is the number of ad hoc clusters; each vertical bar represents one cultivar that is marked by order number according to Table 6. The length of the colored segment shows the estimated proportion of membership of each gene pool in the cultivar genetic makeup. Figure 10 Proportion of 11 gene pools in five breeding periods of spring barley based on population structure analysis. (a) Cultivars bred before 1945; (b) cultivars bred between 1945 and 1969; (c) cultivars bred between 1970 and 1989; (d) cultivars bred between 1990 and 1999; (e) cultivars bred after 2000. Figure 11 Circular overview of seven H. vulgare chromosomes. (a) Transformed FST10 for cultivars bred before 1945 and after 2000; (b) Average polymorphism information content (PIC) distribution in cultivars bred before 1945; (c) Average polymorphism information content (PIC) Distribution in cultivars bred after 2000; (d) Number of unique SNPs in cultivars bred before 1945; (e) Number of unique SNPs in cultivars bred after 2000. A sliding window approach with 500 kb windows, printed for 250 positions along the full length of barley chromosomes based on the genome assembly: IBSC_v2 [21]. Figure 12 Identity by descent (IBD) based clustering of spring barley cultivars with cutoff at 0.95. Accession numbers according to Table 6. ijms-23-04553-t001_Table 1 Table 1 Summary of DArTseq loci distribution on chromosomes for 83 spring barley cultivars. Chromosome lengths according to barley Morex genome assembly [21]. Chromosome Length (Mbp) Number of Loci Mean Distance (Mbp) Percentage of Loci Percentage of Homozygous Loci/Chromosome 1H 558.54 1150 0.49 10% 25% 2H 768.08 1695 0.45 15% 32% 3H 699.71 1541 0.45 13% 19% 4H 647.06 1109 0.58 10% 30% 5H 670.03 1574 0.43 14% 15% 6H 583.38 1158 0.50 10% 20% 7H 657.22 1571 0.42 13% 23% Unknown na 1857 na 16% 22% ijms-23-04553-t002_Table 2 Table 2 Summary of point mutation abundance at the studied loci by chromosome based on DArTseq analysis of 83 spring barley cultivars. Total Abundance on Chromosomes Unknown 1H 2H 3H 4H 5H 6H 7H Transitions (Ts) Purines A > G 1910 186 263 235 206 278 183 245 314 G > A 1752 178 254 211 168 249 193 228 271 Pyrimidines C > T 1754 184 248 252 165 240 169 243 253 T > C 1604 160 222 244 145 207 151 237 238 Transversion (Tv) Purines > Pyrimidines A > C 522 33 70 75 47 70 56 70 101 A > T 292 37 44 24 34 45 33 32 43 G > C 890 101 119 107 90 116 80 125 152 G > T 525 56 95 65 45 72 52 72 68 Pyrimidines > Purines C > A 533 45 79 67 44 72 47 91 88 C > G 1027 89 170 146 86 118 103 128 187 T > A 291 28 45 39 23 48 32 36 40 T > G 555 53 86 76 56 59 59 64 102 % Ts 60.2% 61.6% 58.2% 61.1% 61.7% 61.9% 60.1% 60.7% 57.9% % Tv 39.8% 38.4% 41.8% 38.9% 38.3% 38.1% 39.9% 39.3% 42.1% Ts/Tv ratio 1.51 1.60 1.39 1.57 1.61 1.62 1.51 1.54 1.38 ijms-23-04553-t003_Table 3 Table 3 Change in the number of unique alleles in consecutive breeding periods considering chromosome allocation. Results based on DArTseq analysis for 83 spring barley cultivars. Groups Before 1945 vs. 1945–1969 1945–1969 vs. 1970–1989 1970–1989 vs. 1990–1999 1990–1999 vs. After 2000 Chromosomes 1H 0 1 3 21 3 0 23 26 2H 36 2 10 23 2 4 21 68 3H 12 18 25 16 2 0 33 3 4H 1 24 9 6 2 24 55 9 5H 3 43 30 32 33 9 59 54 6H 13 2 44 2 0 3 13 3 7H 6 18 8 8 2 8 13 59 Unknown 7 17 24 17 10 7 35 54 ijms-23-04553-t004_Table 4 Table 4 Summary of Jaccard genetic distance analysis for 83 spring barley cultivars based on DArTseq-derived SNPs. Minimum Maximum Genetic Distance Cultivars Genetic Distance Cultivars Before 1945 0.162 Danubia Ciołkowski–Hanna Borzymowski 0.462 Cesarski Stieglera–Puławski Browarny 1945–1969 0.015 Jarek–Jarek 0.667 Kos–Mazowiecki 1970–1989 0.014 Klimek–Klimek 0.632 Klimek(36)–Polon 1990–1999 0.021 Rambo–Rambo 0.649 Start–Bryl(59) after 2000 0.249 Granal–Sezam 0.450 Atico–Ella total 0.014 Klimek–Klimek 0.677 Mazowiecki–Stratus The number in parentheses is according to Table 6. ijms-23-04553-t005_Table 5 Table 5 List of duplicate accessions verified from passport data and DArTseq analysis results. No. Accession Number Cultivar Name Passport Data Genetic Distance Population Structure Identity by Descent 17 PL42124 Damazy yes yes yes yes 18 PL43614 Damazy 19 PL40940 Jarek yes yes yes yes 20 PL42363 Jarek 28 PL41419 Ars yes no yes yes 29 PL43646 Ars 41 PL41418 Mago no 30 PL43423 Bielik yes yes yes yes 31 PL41415 Bielik 32 PL43033 Dema yes no no no 33 PL43416 Dema 35 PL43086 Klimek yes yes yes yes 36 PL43414 Klimek 38 PL43032 Lot yes no no no 39 PL43421 Lot 44 PL43056 Rudzik yes yes yes yes 45 PL43423 Rudzik 51 PL43335 Orlik yes yes yes yes 52 PL43417 Orlik 53 PL43368 Polo yes no no no 54 PL43411 Polo 59 PL500074 Bryl yes yes yes yes 60 PL43949 Bryl 61 PL43812 Bryl no no no 62 PL500070 Edgar yes yes yes yes 63 PL500666 Edgar 64 PL43419 Nagrad yes yes yes yes 65 PL43379 Nagrad 67 PL500667 Rambo yes yes yes yes 68 PL43747 Rambo 70 PL43369 Rodos yes no no no 71 PL43412 Rodos Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Polymers (Basel) Polymers (Basel) polymers Polymers 2073-4360 MDPI 10.3390/polym14091694 polymers-14-01694 Article Design for 3D Printed Tools: Mechanical Material Properties for Direct Polymer Additive Tooling https://orcid.org/0000-0003-0896-7083 Frohn-Sörensen Peter 1* https://orcid.org/0000-0001-5132-9779 Geueke Michael 1 https://orcid.org/0000-0002-7497-4786 Engel Bernd 1 https://orcid.org/0000-0001-8876-2242 Löffler Bernd 2* Bickendorf Philipp 2 https://orcid.org/0000-0001-5365-0726 Asimi Arian 2 https://orcid.org/0000-0001-7140-0405 Bergweiler Georg 2 Schuh Günther 2 Gómez-Gras Giovanni Academic Editor Pérez Marco A. Academic Editor 1 Forming Technology, Institute of Production Technologies, University of Siegen, 57076 Siegen, Germany; michael.geueke@uni-siegen.de (M.G.); bernd.engel@uni-siegen.de (B.E.) 2 Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, 52074 Aachen, Germany; p.bickendorf@wzl.rwth-aachen.de (P.B.); arian.asimi@rwth-aachen.de (A.A.); g.bergweiler@wzl.rwth-aachen.de (G.B.); g.schuh@wzl.rwth-aachen.de (G.S.) * Correspondence: peter.frohn@uni-siegen.de (P.F.-S.); b.loeffler@wzl.rwth-aachen.de (B.L.); Tel.: +49-271-740-4666 (P.F.-S.); +49-175-6425208 (B.L.) 21 4 2022 5 2022 14 9 169428 3 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/). In relation to the fourth industrial revolution, traditional manufacturing methods cannot serve the flexibility demands related to mass customization and small series production. Rapid tooling provided by generative manufacturing has been suggested recently in the context of metal forming. Due to the high loads applied during processes to such tooling, a purposeful mechanical description of the additively manufactured (AM) materials is crucial. Until now, a comprehensive characterization approach for AM polymers is required to allow a sophisticated layout of rapid tooling. In detail, information on compressive and flexural mechanical properties of solid infilled materials made by additive manufacturing are sparsely available. These elementary mechanical properties are evaluated in the present study. They result from material specimens additively manufactured in the fused filament fabrication (FFF) process. The design of the experiments reveals significant influences of the polymer and the layer height on the resulting flexural and compressive strength and modulus as well as density, hardness, and surface roughness. As a case study, these findings are applied to a cup drawing operation based on the strongest and weakest material and parameter combination. The obtained data and results are intended to guide future applications of direct polymer additive tooling. The presented case study illustrates such an application and shows the range of manufacturing quality achievable within the materials and user settings for 3D printing. additive tooling rapid tooling additive manufacturing FFF FDM polymers flexibility metal forming mass customization ==== Body pmc1. Introduction Due to the transformation from mass production to mass personalized production in the last decades, this paradigm shift requires alternative production techniques and manufacturing processes to fulfil the individualized consumer demand [1]. Mass personalized product individualization, shortened product lifecycles and lead times, as well as increased product derivatives, necessitate economic alternatives for traditional production techniques, and manufacturing processes typically implemented for great lot sizes [2,3,4]. Steadily tightening political and environmental regulations paired with globalization and price competition forces manufacturers to reconsider their strategies on the distribution markets [5]. When it comes to cost and time consumption in large-scale industrial production, alternative approaches are inevitable to ensure transformation from mass production to mass personalized production. Sheet metal forming, as one of the common metal forming techniques, is an omnipresent production process for automotive, naval, and aerospace, as well as household appliance, typically aiming for great lot size production due to cost intensive tool investments and a high level of automation [6]. On the other hand, mass personalized production requires agile reconfigurability to ensure a fast, individualized, and economic process for small lot size, shape complexity, and physical parameter variation [7]. Since there are no suitable and economically approved techniques to ensure individualized and flexible small batch size production in deep drawing, further approaches are required to fulfil these agile demands [2]. Additive manufacturing (AM) may empower an affordable alternative to tackle high complexity in reconfigurable production systems, since it enables a flexible production for individualized products, neglecting cost penalties in manufacturing [8]. In AM, 3D data is transformed directly into physical parts without further tooling. Disregarding the comparable high production time of AM processes as an ongoing technological hard and software improvement, most of the AM processes are material-saving. The AM process generates objects layer-wise on demand, whereas traditional manufacturing like grinding or milling are subtractive processes. Therefore, direct polymer additive tooling (DPAT) is a promising tooling method that may be used in sheet metal forming for small batch size production and prototyping [9]. This work aims to study the mechanical performance of four FFF materials, namely polylactic acid (PLA), polycarbonate (PC), polyamide (PA), and polyethylene terephthalate glycol modified (PETG). Flexural and compression tests are performed in a full-factorial design of experiments. Subsequently, to investigate the performance of DPAT for deep drawing, the weakest and the strongest parameter results are applied to a cup drawing experiment using tooling made by the FFF process. Background and Related Work Equipment for conventional production technologies can be manufactured with AM to enable small to medium-sized series in the original material. The production of components and tools with short lead time by means of additive manufacturing is characterized by a variety of terms. The most used terms are rapid tooling, rapid prototyping, and rapid manufacturing. With respect to AM and the production of manufacturing tools, these terms can also be summarized as additive tooling (AT). AT enables direct manufacturing of tools with close to final product quality [10]. Applications for AT as a production technology range from casting and injection molds to cutting and forming tools. Shorter lead times are a decisive advantage of AT and enable economical production of tools for small batches [11]. Particularly in the highly competitive automotive industry, it is possible to benefit from this advantage and achieve a shorter time-to-market [12]. In this context, forming tools manufactured by AT to produce car body parts have the potential to meet the requirements in terms of flexibility and ever shorter lead times. The production of three-dimensional sheet metal workpieces, such as those used in the car body, is usually carried out by deep drawing. Corresponding DPAT tools can achieve similar results to traditional sheet metal forming tools with limitations in the aspect of fatigue life [13]. In the deep drawing process, a sheet blank is restrained peripherally by one or multiple blank holder units. Afterwards, a punch draws the material radially into a forming die. This enables complex open hollow bodies, like cup or box contours, in single- or multiple-step iterations. Compared to stretch forming, where a considerable change of the sheet thickness is achieved, deep drawing allows the material to flow with the aid of a blank holder and, therefore, ideally aims for constant material thickness [14]. Since deep drawing applications usually aim for mass size production, grey casting accompanied by post-milling is the established way of tool manufacturing [15]. The application area of deep drawing tools is an important field of research due to the complex load conditions that push the tools and the sheet metal material to their limits [16]. Even though DPAT is widely used in embossing and bending operations as well as injection mold tooling, this application has only been used occasionally in sheet metal forming so far [17]. On the other hand, metal based additive tooling approaches have been studied more extensively. However, compared to conventional subtractive tooling methods, these techniques require high pre-investments and precise machinery, usually exceeding tool costs for small batch size and try-outs. Some DPAT approaches for sheet metal forming have been studied by several authors. While [9,10,18] stated general insights, limitations, and design recommendations for DPAT, other researchers focused explicitly on practical try outs and feasibility approaches. Durgun [19] investigated a V-shaped tailgate forming tool made from polycarbonate for 101 forming operations on DC04 (0.8 mm) and S355MC (0.8 mm) sheet metal. For DC04, the tools showed good dimensional accuracy over the whole batch, whereas S355MC showed dimensional stability up to the 50th part. Prior to a feasibility study existing for two different drawing tools, Schuh et al. investigated the forming behavior of AM parts via cupping tests and structural infill optimization. In addition, they included a simulation approach and optical measurements of the forming tools to determine the deformation behavior up to 23 forming operations [16]. Nakamura et al. [20] examined the forming behavior of a V-bent and a deep drawn cylindrical cup for three different sheet metals. Besides the geometrical accuracy, they investigated the surface roughness after the forming operation. In addition, stiffening metal elements were inserted into the AM tool structures and therefore enhance their performance. Schuh et al. assessed the geometric accuracy of DPAT for PLA material on different geometry features in a deep drawing process. They tested a demonstrator for 27 drawing iterations, where they stated a stable tolerance of ±0.5 mm for a DC04 sheet metal part (1 mm) in four out of five geometry features [21].Aksenov and Kononov [22] studied the performance of DPAT on thin aluminum sheets via multiple V-bent operations of 2–4 mm height without a noticeable wear behavior on the polyethylene terephthalate (PET) tool after a few dozen forming operations. Frohn-Sörensen et al. [23] examined the performance and geometrical stability for DPAT on a rubber pad forming process for DC04 (0.7 mm) up to 64 parts. The results showed that the PLA dies could be used to draw conventional sheet metal with a stabilized performance after the 32nd forming operation. Geueke et al. [24] extended this approach and performed a topology optimization on the forming dies, where they reduced the AM material up to 30% with negligible geometrical forming deviations compared to the rigid die from the previous study. Bergweiler et al. [17] investigated the dimensional precision of deep drawn cups using DPAT with lot sizes up to 20 DC04 (1 mm) parts, where they stated a geometrical deviation of ±0.5 mm on the forming tools. Löffler et al. [25] examined deep drawing using DPAT and PLA material on DC04, aiming for reduction of tooling costs. They stated a general feasibility with geometrical deviations up to −0.93 mm on the tool set with cost reduction of 93% compared to conventional tooling. Prior to DPAT, several authors conducted mechanical performance tests for different polymers and load types via AM. Since the geometries for tensile und flexural tests are clearly specified in the standards DIN EN ISO 527 and ISO 178, respectively, the compression test geometry according to EN ISO 604 refers to an inequation for different specimen shapes of pipes, cylinders, or prisms. This inconsistency leads to the issue of authors using non-uniform specimen contours. For example, Wang et al. [26] used a 36 mm cube of pure filler structure, whereas ref. [20] used a cylinder with 25 mm diameter and 30 mm height, which makes the test results hard to compare. Besides that, the compression tests by refs. [20,27] revealed different values for PLA material. Nakamura et al. [20] achieved 30 MPa, whereas ref. [27] gained a compression strength of 59.78 MPa for PLA specimen. A similar discrepancy can also be stated by the investigations of refs. [28,29], as they gained higher mechanical strength for polymer-based AM tensile specimen with higher layer thickness (0.3 mm), while ref. [30] obtained a better performance for smaller layer thickness (0.05 mm). This inconsistency can be further confirmed for compression test results with respect to layer thickness. Sood et al. [31] found out that higher layer thickness (0.254 mm) improved the mechanical performance, even though ref. [32] gained contrary results, as they improved the performance with smaller layer heights (0.14 mm). For flexural testing, this discrepancy revealed contrary test results. Sood et al. [33] could improve the performance with higher layer height (0.254 mm), although ref. [34] revealed better results for lower layer height (0.1 mm). In general, a comparison between the aforementioned outcomes should be viewed with caution since the AM filaments and printing parameters were not used consistently and uniformly. Due to the partly inconsistent and contradictory mechanical test results for identical polymers, further investigations are necessary to predict and apply DPAT in sheet metal forming and the production sector in general. Even though literature reveals a large amount of tensile test data, fewer flexural and compression data are available. To ensure a performant application of DPAT in sheet metal forming, this study can contribute to this field of research [35]. 2. Materials and Methods 2.1. Parameters and Properties for Additive Tooling In the following, the essential properties and slicing parameters for additive tooling (AT) for forming technologies are derived, justified, and described. Subsequently, they are used to determine a suitable test setup for material characterization. The results are used to assess the process suitability as a forming tool material. Different forming technologies are distinguished according to their main stress type in the technical standards DIN 8582 (cf. Figure 1), Schuler GmbH [36] (p. 7), and DIN 8585-1 (p. 3; cf. Appendix A). This results from the introduced stresses, which are the outcome of the corresponding relative movements between the workpiece and the tool, cf. ref. [36] (pp. 6–18). In production technology, deep drawing, stamping, and bending are of particular importance. Deep drawing is characterized by a combination of tensile and compressive stresses. In addition, shear stress results from the material flow of the sheet metal flowing downstream. The general stress spectrum is depicted in DIN 8585-4 (p. 3, see Appendix A). In contrast to deep drawing, stamping is dominated by tensile forming. In the following, an idealized cup geometry is considered for a deep drawing process (cf. Figure 2), see [37] (p. 16) and [14] (p. 262). While uniaxial tensile stress dominates in the punch edge rounding at the sheet metal component, the bottom of the cup experiences a tensile–tensile stress. In the flange area, tensile stress is combined with compressive stress due to the often rotationally symmetrical shape of formed components. Polymer-based additively manufactured tools exhibit an elastic–plastic deformation behavior and are more suitable for use areas with limited load/pressure due to their reduced mechanical properties and higher wear. They are more sensitive to stresses during deep drawing (cf. Figure 2) than conventional tools due to their lower strength and greater susceptibility to wear. Deep drawing tools are typically made of metal (especially free-cutting steel and aluminum), which are assumed to be quasi-static and exhibit low wear due to the use of lubricants. Thus, it is particularly important to adapt the design of the additive manufacturing process to the load cases of forming technologies in order to ensure a sufficient service life, cf. [21] (p. 4). The stability of additively manufactured components depends in particular on the infill density. As a result of a higher infill density, an increase in compressive strength is observed. The infill pattern should determine the volume filling of the component as efficiently as possible, which can optimize material efficiency, production time, and costs, cf. [38] (pp. 16–18). The infill is based on a fully computer-generated and repetitive pattern. The diameter of the selected nozzle defines the range in which the layer height is adjusted in the slicing software. The thickness, as well as the number of wall lines, which is prioritized in most slicers, also influences the internal stability and strength of additively manufactured components. Therefore, the number of walls (perimeters) must be determined to gain a clean mapping of the contours. The temperature of the nozzle and the printing platform affect the strength of the connection between the material strand and the underlying layers. Usually, a material comes along with its individual data sheet, which is based on empirical try-out parameters for the appropriate system technology to produce a satisfactory print result. A high degree of overlap between the layers increases the internal stability of additively manufactured components, although the resulting over-extrusion may cause geometric deviations. The higher the printing speed, the faster and more favorably the manufacturing process can be designed. However, if the printing speed is too high, the layer adhesion is not sufficiently pronounced, so that the internal strength is reduced. Further on, higher printing speed comes along with higher acceleration and deceleration of the printing heads, which may influence the mechanical performance and lifespan of the printer. Additionally, the printing direction affects the performance of additively manufactured forming tools. Here, it is important that the layer-wise building direction lines up with the direction of the main load during the forming process. Otherwise, the probability of interlayer delamination increases. Material parameters, which are decisive for the suitability as a tool material, are related in particular to conventional mechanical parameters. These are given in the technical datasheets (TDS) of the filament manufacturers. Unfortunately, they do not include the influence of the slicing parameters on the AM processes and machines. Often these values are determined according to DIN EN ISO 527(pp. 1–34, see Appendix A) with various assumptions (e.g., regarding the printing speed, filament overlay, infill density). The most important mechanical parameters considered in the application case of forming technology are the following:Modulus of elasticity or tensile modulus (given in most TDS) of additively manufactured specimen (in GPa); Tensile strength printed specimen (specified in most TDS) in one or more printing directions (in MPa); Compressive stress or compressive yield stress at 5% compression (not specified in TDS) (in MPa); Density of specimen (specified in most TDS) (in g/mm3); D-Shore-hardness of specimen (not specified in TDS). The economic efficiency and service life of a tooling system is significantly influenced by the choice of the tool material and its pairing with the corresponding sheet metal. To confirm the suitability of these materials for the use as inserts in forming tools, it is necessary to investigate the strength properties in particular. In addition to various slicing parameters, batch variations in the filament production also have an influence. To reduce the probability of these effects occurring, all materials are requested from the same manufacturer at the same time. Following the delivery (vacuum packed), all material is used up for printing within a few working days. This minimizes the influence of atmosphere and ageing effects. In the following, standardized compression and bending tests as well as operating tests with cup geometries will be conducted under variation of tool material and slicing parameters. The obtained data from material characterization are then applied to a suitability assessment for sheet metal forming tools. Flexural and compressive strength and modulus, as well as density, hardness, and surface roughness, are common material performance test values that are all considered relevant for the specific application of direct polymer additive tooling. 2.2. Material Characterization The material properties identified as relevant for additively manufactured tooling from polymers are evaluated for four relevant materials. Polylactide (PLA), as a standard, stiff 3D printing material, is chosen due to its former application for additive tooling [9,23]; Polycarbonate (PC) is supposed to have strong material characteristics and was applied successfully in industrial sized additive tooling applications by [19]; Polyamide (PA), a.k.a. Nylon, is a softer material but interesting for application in additive tooling due to its lower friction coefficients; PETG is included in the study as it is a good compromise of mechanical properties, availability, processability in AM, and recyclability. ABS is a commonly used polymer in FFF. Due to its weak mechanical properties [23], it is excluded from this study and is therefore considered unsuitable for application in additive tooling. High performance polymers, such as polyether ether ketone (PEEK), are disregarded, as their material cost might sharply narrow the economic niche of additive tooling compared to conventional subtractive steel tool manufacturing practices and should be addressed in separate studies. With regard to the tool manufacturing application, compressive and flexural properties are tested instead of standard tensile tests. In particular, these data are scarcely available in literature compared to tensile properties. Compressive and flexural material specimens are printed according to the technical standards EN ISO 604 and ISO 178 (also see Appendix A), respectively. For compression, cylindrical geometries with a diameter of 30 mm and a height of 20 mm are selected, whereas bars with a length of 100 mm and a cross section of 4 mm by 8 mm are manufactured for bending tests. As mentioned in the introduction, the mechanical parameters of a given polymer filament might significantly vary between manufacturers, and also between the used 3D printer. For this reason, the filament manufacturer and printer are kept constant in this study. Moreover, the processing parameters with regard to speeds and temperatures might influence the mechanical behavior of the material. However, they strongly relate to the overall construction of individual printers, e.g., hot end, heating, axis setup, etc. In the present study, they are kept to the manufacturer recommendations. The slicing parameters, layer thickness, as well as perimeters are varied as they have to be defined by the user. They influence the mechanical stability and the surface quality of an additively manufactured object. Considering common FFF printing setups, the layer thickness is varied in between 0.1 and 0.3 mm, while the number of walls is set between 1 and 5. The corresponding specimens for are additively manufactured by FFF on Ultimaker “S5 Pro Bundle” machines using a 0.4 mm nozzle and the parameters summarized in Table 1. A solid (100%) infill was chosen, as the purpose of the study is to deliver mechanical material properties with maximized strength for tool applications. The printing orientation is perpendicular to the load because, from an application point of view, this orientation agrees to the manufacture of forming tools. The other printing parameters (i.e., nozzle temperature, bed temperature, and printing speed) are kept to the manufacturers’ suggestions in order to allow stable and comparable printing conditions. In the case of bed heating, the adjusted temperature of 80 degrees Celsius lies within the feasible ranges of all materials. Before destructive mechanical testing, the specimens are evaluated for their surface roughness, using a Mahr Marsurf LD260, to obtain the surface roughness parameters Rz and Ra. In addition, hardness (Shore-D grade) was evaluated from the compression test cylinders by a digital indentation gauge with three repetitions each. On a universal tensile testing machine type Zwick/Roell Z250, test assemblies for three-point bending and uniaxial compression are equipped. The compression and bending forces resulting from the experiments are continuously evaluated from the machine’s GTM load cell (series K, accuracy class 0.02%). For the compression tests, hysteresis loops are driven during the evaluation of compressive elastic modulus to eliminate settlements, gaps, and specimen surface unevenness. During elastic deformation, compression rates of 0.05 mm/s were achieved. Subsequently, the experiments run until compressive strain reaches 10%, cf. Figure 3. The obtained force over travel signals is compensated by a combined machine/assembly stiffness of 99.056 N/mm, which was evaluated prior by loading without specimen. For three-point bending, two supports are set into a lateral distance of 68 mm regarding their contact points towards the bar-shaped bending specimens. In between these supports, a wedge-shaped tool vertically applies the bending force. All material test raw data are provisioned in a data repository [39]. 3. Material Test Results The mechanical properties of specimens made by additive manufacturing with solid infill are evaluated with respect to compression and flexion with the intention to be applied as a tooling technique. Hence, material properties with the highest possible resilience are of interest. Looking at the results, the achieved strength values from all material and parameter variations are considered first, cf. Figure 4. The strongest combination with respect to both loading conditions is obtained by PLA with the finest layer resolution. Polycarbonate (PC) reaches similar strength but reveals no sensitivity against layer thickness. This observation could be interpreted as beneficial by means of production time, which generally decreases sharply with thicker layer heights. Likewise, PETG has shown a minor influence of layer height on strength, while nylon (PA) is strongly weakened by increasing layer height. At 0.3 mm layer height, PA delivers the weakest combination with respect to both bending and compression load situation. For additive tooling, the elastic constants are of key interest to quantify local displacements of the tools under load and, thus, manufacturing precision. With regard to both loading conditions, bending and compression, the elastic moduli are evaluated from the tests during the initial loading phases and summarized in Figure 4. During compression tests, hysteresis loops are conducted, where compression is initially increased up to 75% of the material’s compression strength. Subsequently, force is decreased until 10% compression strength. From this point, the test is continuously performed up to 10% compression. From the slope of reloading the specimens within the loop, the elastic compression modulus Ec is evaluated where a linear regression behavior is assured by a coefficient of determination R2 > 0.9998 (also see Figure 3). The achieved elastic material constants under flexural and compressive load are displayed for all material and parameter combinations in Figure 5. Corresponding to strength, the highest elastic constants are seen from the results of PLA, while PA delivers the weakest combination. Interestingly, the elastic moduli are influenced in a much lesser way by layer thickness, compared to the results on strength. Only PA shows a significant sensitivity with decreasing elastic moduli towards thicker layers. Similar to the strength tests, the results from PC show the second highest values. Apart from these major results, the surface roughness (with regard to Rz) sharply increases towards thicker layers for PC (26 µm up to 125 µm for 0.1 mm to 0.3 mm layers) and PA (13 µm up to 63 µm), while PLA and PETG stay on comparatively smooth averages (22 µm and 28 µm, respectively). Surface hardness on the Shore-D scale could only be related with moderate correlation towards the results presented above. A weak influence of layer height and number of walls is obtained, except for PA, at the highest layers. Two groups of hardness are obtained with respect to the materials, with PLA and PC showing 81 degrees and 82 degrees of Shore-D hardness, respectively, on average, and PA and PETG revealing 76 degrees and 78 degrees, respectively, on average. For PA at 0.3 mm layers, a sharp drop of hardness towards 70 degrees is obtained. Lastly, density ρ was evaluated from the 3D-printed compression test specimens because they show a higher volume to surface ratio than the bending bars. For all parameters adjusted, an average density of 1179 kg/m3 is obtained from the PC specimens. PETG weighs on average 1235 kg/m3, making it the densest material tested. The lowest density is obtained from the PA specimens having 1002 kg/m3 on average for 0.3 mm layer thickness and 1105 kg/m3 for the other parameter adjustments. Evidently, this sudden drop of density over layer height explains the weak material properties observed and might be related to a large number of voids resulting from this processing setup. As 0.4 mm nozzles were used throughout this study, the sudden drop in density and mechanical material properties over layer height might relate to the nozzle diameter. For PLA, a finely defined density variation is seen when varying layer thickness ranging from 1166 kg/m3 up to 1228 kg/m3 over decreasing layer height from 0.3 mm to 0.1 mm. PETG shows a disadvantageous balance of density ratio to its elastic constants and strength compared to the other materials. All numerical results obtained from the material tests are summarized in Table 2. The experimental history of all material tests is documented in a data repository [39]. In the subsequent cup-type drawing test, the strongest and weakest materials and parameter combinations are selected primarily according to compressive strength and modulus. Apart from the herein regarded deep drawing process, DPAT was successfully applied to a number of other forming processes, such as bending. Depending on the application case, the tested mechanical properties under bending load need to be taken into account to layout such tooling. Moreover, surface roughness is presented in Table 2 to assure a smooth surface of additively manufactured tools avoiding surface marks on the product. In the case of PC at a layer thickness of 0.3 mm, surface defects might occur depending on the sheet metal thickness of the product. Hardness and density are tested primarily for argumentative purpose, as weak mechanical properties might relate to a significantly low density, as in the case of PA at 0.3 mm. It is observed that the tested hardness shows mediocre correlation to the materials’ mechanical performance. 4. Use Case—Deep Drawing Deep drawing is used as a forming process to apply the finding of the previous chapter to a real application tooling scenario. The wide application and the generally high tool loads make deep drawing a suitable use case for AT. Two different materials and their underlying parameter sets are used, showing the maximum span in compression strength of all tested material configurations: PLA (0.1 mm layer height and 1 wall) and PA (0.3 mm layer height and 5 walls). With respect to the properties’ flexural strength, surface roughness, compression modulus, and flexural modulus, the selected materials show the best and least performing configuration of all tested material configurations if minor variations that are caused by the change of wall numbers are neglected (cf. Figure 4 and Figure 5). The cup test, which is a commonly used deep drawing experiment, is implemented for the use case scenario. Similar to Bergweiler et al., the deep drawing specifications are set in such a way that the tools experience significant loads that are typical for deep drawing [17]. This can be achieved, for example, by setting the drawing ratio to the limit and by using a small die corner and punch nose radius. Table 3 summarizes all relevant deep drawing specifications for this use case. The sheet metal material DC04, which is used for the experiments, is a cold rolled steel according to DIN EN 10130. The mechanical properties are listed in Table 4. The experiments are executed using a three-part deep drawing toolset, consisting of a stamp, a die, and a blank holder. All three tools are printed for each material configuration with the same specifications. Shrinkage corrections are incorporated into the CAD geometry to enhance the initial accuracy of the printed parts. This iteration assures that identical geometrical prerequisites prevail in both cases of tooling material so that the influence of the tooling material configuration is analyzed exclusively from the results. In detail, the die diameter is increased by 0.2 mm for PLA, and by 0.5 mm for PA, respectively. Furthermore, the stamp is scaled-up by 0.5% in the direction of x and y and by 0.2% in z-direction, identically for both materials. Since the bank holder is a thin part with little material agglomeration, no shrinkage corrections are set for both materials. The knowledge of these shrinkage corrections comes from previous work and is not further detailed in the present study. Surface measurements of the initial tool geometries confirm the preset shrinkage corrections since the accuracy of the parts lays close to the respective layer height. Because PA material is printed with a layer height of 0.3 mm, whereas PLA is printed with a value of 0.1 mm, PA tools show slightly less accuracy, resulting in a maximum deviation span of −0.21 mm on the top surface of the stamp between those two materials. The deep drawing experiments are carried out using a four-pillar die set, which is mounted on a single stroke press, having the specifications as described in [17]. A test series of 30 cups are drawn from each material configuration and subsequently measured using a GOM optical measurement device as described in [23]. The stamp and die surfaces of each material configuration are measured as well, using enlarging interval steps. The measuring points that are marked on the cup and tool of each graph of Figure 6, Figure 7, Figure 8 and Figure 9 are averaged around the circumference. In order to compare the performance of both material configurations for the application scenario, two major key indicators come into play. The first one is the accuracy of the first drawn cup compared to the desired CAD geometry, which can be extracted from a surface comparison of the scanned part. This comparison gives an impression of the tolerances that can be potentially achieved by the underlying tooling configuration. The second indicator stands for the durability of the tools that is also linked to the accuracy of the drawn part or the wear on the tools over the course of a series. In the following context the term wear is used for the deviation change of the tool surface, which predominantly consists of plastic deformation. An analysis of different types of wear e.g., adhesive, abrasive, or erosive wear, are not further investigated and thus not part of the study. In forming tools, wear is caused by permanent frictional stress between the forming tool and the workpiece. According to the SOCIETY OF TRIBOLOGY, “wear is the progressive loss of material from the surface of a solid body caused by mechanical causes, i.e., contact and relative movement of a solid, liquid or gaseous mating body.” [40] (p. 108). Figure 6 illustrates the accuracy of the first drawn cup and the repeatability of the drawn cups over the course of 30 drawing operations manufactured from the PA toolset. The left color map of Figure 6 shows the surface comparison of the first drawn cup to the desired CAD geometry. The global maximum and minimum deviation values are 0.88 mm and −1.48 mm, respectively. The color map in the middle of Figure 6 illustrates the surface comparison of the 30th drawn cup to the first drawn cup. Over the course of 30 drawing operations, the deviation values gradually increase, which can be seen in the graph of Figure 6, and reach a maximum span from −0.79 mm to 0.60 mm. Figure 7 is structured in the same way as Figure 6 and shows the deviation values of the cups drawn from the PLA toolset. The first cup drawn from the PLA toolset is more accurate than the cup drawn from the PA toolset, reaching a global maximum and minimum deviation value of 0.36 mm to −0.87 mm, respectively. In addition, the test series shows a better reproducibility over the course of 30 drawing operations. A marginal decrease in precision can be noticed at a drawing step of around 18, leading to a maximum deviation span of −0.23 mm to 0.25 mm. The majority of the increased deviation span can be traced back to alignment errors during the surface analysis. The color map of Figure 8 illustrates the surface comparison of the PA stamp after the 30th drawing operation compared to the initial stamp geometry right after printing. The deviation values can be interpreted as wear on the tool. The maximum and minimum deviation values can be seen around the punch nose radius. They are set between 0.20 mm and −0.45 mm, respectively, for the PA material. The change of tool wear is shown in the graphs for different measuring points for both material configurations. Deviation values increase for PA gradually until the 20th drawing operation and increase stronger until the end of the series. In contrast, the wear on the PLA stamp is much lower over the course of the series and lays in the range of alignment errors, thus it can be neglected. The graphs and the color map of Figure 9 are structured in the same way as shown in Figure 8. However, the wear on the die is illustrated instead. The deviation values of the PA die are a bit less than on the PA stamp, ranging from −0.33 mm to 0.19 mm over the course of 30 drawing operations. In contrast, the wear on the corner radius of the PLA die is higher compared to the wear on the stamp, but still less than the wear on the PA die. 5. Discussion Four polymers commonly used in FFF, namely PC, PLA, PA, and PETG, are considered for their use in direct polymer additive tooling (DPAT) in the present study. During additive fabrication of specimens intended for mechanical testing, the machining parameters are used according to the material manufacturers recommendations. Large differences between the mechanical parameters of these materials are observed with particular respect to compressive stiffness and strength. Initially, however, this study points out in a literature review that mechanical constants strongly vary across the different manufacturers. Therefore, the herein provided parameters are therefore intended to highlight the relative differences between the polymers rather than the absolute values, which might differ even more between the providers of a certain material than among different polymers of an identical provider. Next to different polymers, the user-related FFF parameters, namely layer height and number of walls (or perimeters), are focused on the experimental design of this paper while the fabrication parameters relating to temperatures and speeds are kept constant. PLA and PA reveal a strong sensitivity to compression and bending related mechanical properties, while the properties of PETG are less affected. Considering the initially mentioned strong dependency of mechanical parameters from the manufacturer, a general recommendation towards thinner layers results. Compared with what is known from the literature on tensile, compression, or bending tests, the presented trend of increasing mechanical strength by lowering the layer thickness agrees with [30,32,34], for PLA. Interestingly, the mechanical integrity of PC is not degraded by raising the layer thickness, which might open up an economical gap as layer thickness directly influences the manufacturing time. Despite the large difference in mechanical parameters observed in the material test section, a low correlation of surface hardness is seen from the tests. Due to the discontinuous nature of additive manufacture, the testing needle of the Shore-D hardness measuring gauge might either penetrate on a tool path of the FFF process or in between two paths, which might be the reason for said lack of correlation. Clearly, this issue should be addressed and investigated in future research. The mechanical parameters, with respect to bending and compression load tested in the first part of this study, are intended to relate to the quality which is expected from sheet metal drawing in DPAT. Consequently, the best and the worst material and layer thickness combination is applied to a use case in the second part of the paper to illustrate the span of manufacturing quality in a deep drawing operation. In addition to the corresponding fabrication parameters, which were also used for the mechanical testing specimens, a shrinkage compensation is conducted for the forming tools from PLA and PA. Resulting from the cup drawing experiments, a large difference between both tool materials is seen from the surface scans. The PA tools show higher product shape deviations and a considerable tool degradation after 30 strokes, while the shape deviation of the cups drawn on the PLA toolset lies within the margin of alignment errors during the drawing series. In addition, minor tool degradation was observed. Considering the mild drawing steel sheet material, DPAT shows suitability for sheet metal drawing of industrial products when using the herein recommended optimal parameters for strong polymer materials such as PLA. The findings of the parameter study can help the tool designer to manufacture stronger tools, which is mainly beneficial in two ways. First, an improved tool stiffness leads to sheet metal parts that are more accurate due to less elastic tool deformation. In addition, stronger tools are less prone to wear, which helps to manufacture more quantities that are acceptable in terms of part accuracy. Both advantages can lead to a wider range of application in industry for this tooling technique. Especially for prototypes and parts in small quantities, DPAT can be an economic way to manufacture sheet metal parts. Forming of more complex geometries might result in higher local surface pressures on the tool surfaces and lead to higher permanent plastic surface deviations. In addition, high strength steels and higher sheet thickness could exceed the manufacturing capabilities of DPAT when using conventional polymers and might require stronger materials, e.g., polyether ether ketone (PEEK), fiber-reinforced polymers, or polymers with filler materials. 6. Conclusions Utilizing direct polymer additive tooling (DPAT) in molding and sheet metal forming processes has been studied recently for the economical fabrication of small batch series. Up until now, exemplary materials have been tried out to demonstrate the feasibility of DPAT in particular for sheet metal forming, or tool running-in and degradation effects were investigated over production of various small series. However, a comprehensive comparison of materials and key parameters for DPAT is missing, as in comparison to the application range of additive manufacturing in general, DPAT materials need to be as strong as possible and are mostly made with solid infill. In the present study, the mechanical properties from PC, PLA, PA, and PETG are evaluated under compression and bending, as these load cases are postulated as most relevant for tool manufacture. Moreover, density, hardness, and surface roughness are tested. Collectively, these parameters are considered relevant for the specific application of direct polymer additive tooling. While there is evidently a large difference in between the tested polymers results, literature indicates an almost as high dependency of material properties in between varying manufacturers for a given material. Therefore, the presented comparison aims for showing tendencies between polymers while keeping to a single material provider. An important aspect of the presented results is the dependency of the user-related manufacturing parameters in fused filament fabrication (FFF), namely layer thickness and number of walls. For layer thickness, the considered materials have shown a strong dependency towards increasing strength with thinner layers except for PC which revealed constant strength parameters. The number of walls was identified to be of subordinary relevance for material strength. From the material tests, the best and worst case, PLA at 0.1 mm layer thickness and PA (Nylon) at 0.3 mm thickness, respectively, where applied to DPAT of a deep drawing tool set. A small series of 30 cups was formed on each tooling and subsequently evaluated by digital image correlation (DIC). A high influence of the tooling material results corresponds to the material properties evaluated in the preceding material test series. While the shape deviations of the cups formed on the PLA tooling lie between 0.36 mm and −0.87 mm, the tool degradation over the small batch series of 30 pieces lies within the margin of alignment errors of the DIC. For PA, the cups show deviations in between 0.88 mm and −1.48 mm. In addition, a considerable degradation of the PA tooling was observed from the small batch of 30 pieces, leading to an additional deviation of 0.8 mm. The shape deviations of the cup series are primarily linked to the considerably higher elastic modulus of PLA than PA as the stiffer tool material experiences less elastic displacement under the same load. The observed tool degradation relates to the differences in strength of both materials because higher strength leads to fewer local plastic deformations of the tooling, e.g., the fillet radius. By the presented results, design, and layout, recommendations for DPAT are provided for sheet metal drawing operations. In particular, for small batch series, DPAT opens up economical chances compared to conventional tooling from steel. The results imply a tradeoff situation between a fast and economical tool manufacture by means of thicker layers and the strongest and most accurate combination given by thin layers, which results in longer production times. Author Contributions Conceptualization, P.F.-S., M.G., B.L. and P.B.; investigation, methodology and formal analysis, P.F.-S., M.G., B.L., A.A. and P.B.; validation, B.L. and P.F.-S.; writing—original draft preparation, P.F.-S., M.G., B.L., A.A. and P.B.; writing—review and editing, G.B. and B.E.; supervision, B.E. and G.S.; project administration, P.F.-S. and B.L. All authors have read and agreed to the published version of the manuscript. Funding The project has been financed by the Central Innovation Program for SMEs (ZIM) of the Federal Ministry for Economic Affairs and Energy under the grant number KK5057110KL1. This research was funded by the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) within the project “CONVertER for Trucks” (ConverT), grant number 16EM4009-2. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The experimental history of all material tests is documented in a data repository: Frohn-Sörensen, P., Geueke, M., Löffler, B., Bickendorf, P. and Asimi, A. (2022), “Measurements of mechanical material properties under compressive and bending load of additive manufactured polymers”, Harvard Dataverse, 10 February, accessed on 31 March 2022, available at: https://doi.org/10.7910/DVN/1ARRM2. 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. Appendix A. Technical Standards DIN EN 10130:2007. Cold rolled low carbon steel flat products for cold forming—Technical delivery conditions. DIN EN ISO 527:2019. Plastics—Determination of tensile properties—Part 1: General principles. ISO 178:2019. Plastics—Determination of flexural properties. ISO 604:2002. Plastics—Determination of compressive properties. DIN 8582:2003. Manufacturing processes forming—Classification; Subdivision, terms and definitions, alphabetical index. DIN 8585-1:2003. Manufacturing processes forming under tensile conditions—Part 1: General; Classification, subdivision, terms, and definitions. DIN 8585-4:2003. Manufacturing processes forming under tensile conditions—Part 4: Stretch forming; Classification, subdivision, terms, and definitions. Figure 1 Classification of forming production processes according to DIN 8582, DIN 8585-1, adapted from Schuler GmbH [36] (p. 7). Figure 2 Stress ratios during deep drawing of a cup according to Doege (adapted from Kästle [37] (p. 16), Doege et Behrens [14] (p. 262)). Figure 3 Machine stiffness compensated force-displacement curve of a compression test of a 3D printed solid cylinder from polycarbonate with a layer height of 0.2 mm and a single wall perimeter. A hysteresis loop is driven to eliminate any secondary influences, e.g., clearances. Indication of relevant areas for evaluation of mechanical material properties. Figure 4 Resulting mechanical properties from the variation of materials and 3D-printing parameters. (a) Compression strength σc and (b) ultimate flexural strength σf results. A large influence of material and layer thickness is obtained, while the number of walls plays a subordinate role. Figure 5 Elastic moduli resulting from the variation of materials and 3D-printing parameters. (a) Compression modulus Ec and (b) flexural modulus Ef. A large material influence on elastic constants is obtained while the number of walls is of minor relevance. Only the elastic coefficients of PA are influenced significantly by layer thickness. Figure 6 Color map and deviation values of different points of cups drawn from the PA tool: (left) first drawn cup compared to the CAD geometry; (middle) 30th drawn cup compared to the first drawn cup; (right) deviation values of different measuring points of each cup compared to the first cup over the course of 30 drawing operations. The drawing inside the diagram indicates the location of the measuring points on the cup surface. Figure 7 Color map and deviation values of different points of cups drawn from the PLA tool: (left) first drawn cup compared to the CAD geometry; (middle) 30th drawn cup compared to the first drawn cup; (right) deviation values of different measuring points of each cup compared to the first cup over the course of 30 drawing operations. The drawing inside the diagram indicates the location of the measuring points on the cup surface. Figure 8 Deviation values (wear) of different measuring points on the stamp surface compared to the initial stamp geometry of both material configurations: (left) selected measuring points; (middle) deviation values of PA stamp over the course of 30 drawing operations; (right) deviation values of PLA stamp over the course of 30 drawing operations. The drawing inside the diagram indicates the location of the measuring points on the punch surface. Figure 9 Deviation values (wear) of different measuring points on the die surface compared to the initial die geometry of both material configurations: (left) selected measuring points; (middle) deviation values of PA die over the course of 30 drawing operations; (right) deviation values of PLA die over the course of 30 drawing operations. The drawing inside the diagram indicates the location of the measuring points on the die surface. polymers-14-01694-t001_Table 1 Table 1 3D printing parameters, applied to both specimen geometries (bending bar, cylindrical compression test spec.). Five repetitions were printed for each setup. While variations of layer thickness and number of walls are the main objective of this paper, nozzle and bed temperatures as well as printing speed are kept to the material manufacturers’ recommendations. Material Layer Thickness Number of Walls Nozzle Temperature Bed Temperature Printing Speed [mm] [-] [°C] [°C] [mm/s] PLA 0.1, 0.2, 0.3 1, 3, 5 205 80 45 PC 270 PETG 235 PA 245 polymers-14-01694-t002_Table 2 Table 2 Average mechanical material parameters over FFF layer thickness. Main results of testing elastic bending modulus Ef, ultimate bending strength σf, elastic compression modulus after hysteresis Ec, and compression strength σc. Moreover, surface roughness Rz, surface hardness on Shore-D scale, and densities ρ were evaluated from the cylindrical specimens prior to compression tests. Material PC PLA PA PETG Layer [mm] 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 Ef [GPa] 1.92 1.92 1.93 3.37 3.28 3.12 1.34 1.32 0.75 1.93 1.81 1.79 σf [MPa] 92 93 92 111 105 98 82 79 49 82 79 76 Ec [GPa] 2.23 2.30 2.12 2.63 2.67 2.44 1.84 1.71 0.92 1.38 1.46 1.39 σc [MPa] 79 78 79 90 78 71 79 72 44 56 54 48 Rz [µm] 26 60 125 14 26 26 13 23 63 15 26 30 Hardness (Shore-D) 82 82 82 84 80 81 79 77 71 79 78 78 ρ [kg/m3] 1186 1178 1172 1228 1202 1166 1114 1095 1002 1252 1239 1213 polymers-14-01694-t003_Table 3 Table 3 Deep drawing specification for the use case. No. Feature Symbol Value (mm) 1 Blank diameter D 53.1 2 Drawing ratio β 2.125 (no unit) 3 Blank thickness S o 1 4 Drawing depth h o 15.77 5 Clearance C 1.69 6 Die diameter D p 28.38 7 Punch diameter D i 25 8 Die corner radius R p 2.5 9 Punch nose radius R i 5 polymers-14-01694-t004_Table 4 Table 4 Mechanical properties of DC04 as given in DIN EN 10130. Material Yield Strength Ultimate Strength Elongation at Break DC04 210 MPa 270–350 MPa 38% Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Wang Y. Ma H.-S. Yang J.-H. Wang K.-S. Industry 4.0: A Way from Mass Customization to Mass Personalization Production Adv. Manuf. 2017 5 311 320 10.1007/s40436-017-0204-7 2. Schuh G. Bergweiler G. Fiedler F. Bickendorf P. Colag C. 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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/ijerph19094999 ijerph-19-04999 Article Weekday and Weekend Physical Activity of Preschool Children in Relation to Selected Socioeconomic Indicators https://orcid.org/0000-0003-0434-6263 Herbert Jarosław 1* https://orcid.org/0000-0002-7388-5722 Matłosz Piotr 1 https://orcid.org/0000-0002-7499-1471 Martínez-Rodríguez Alejandro 2 https://orcid.org/0000-0002-2128-4116 Przednowek Krzysztof 1 https://orcid.org/0000-0002-4406-7755 Asif Muhammad 3 https://orcid.org/0000-0002-5786-6214 Wyszyńska Justyna 4 Mazur Joanna Academic Editor 1 Institute of Physical Culture Sciences, Medical College, University of Rzeszów, 35-959 Rzeszów, Poland; pmatlosz@ur.edu.pl (P.M.); krzprz@ur.edu.pl (K.P.) 2 Department of Analytical Chemistry, Nutrition and Food Science, Faculty of Sciences, University of Alicante, 03690 Alicante, Spain; amartinezrodriguez@ua.es 3 Govt. Associate College Qadir Pur Raan, Multan 60000, Pakistan; asifmalik722@gmail.com 4 Institute of Health Sciences, Medical College, University of Rzeszów, 35-959 Rzeszów, Poland; jwyszynska@ur.edu.pl * Correspondence: jherbert@ur.edu.pl; Tel.: +48-178721861 20 4 2022 5 2022 19 9 499926 12 2021 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/). Physical activity (PA) is as vital for improving the health of young children as it is positively associated with a broad range of psychological, cognitive, and cardio-metabolic outcomes. The aims of this study were to: (1) to assess the level of PA and meeting the WHO recommendations: moderate-to-vigorous physical activity (MVPA) and the number of steps in Polish preschool boys and girls on weekdays and on weekends; (2) to investigate the relationship between selected socioeconomic indicators (self-reported by parents) and PA, including meeting the WHO recommendation for daily MVPA and the number of steps on weekdays and on weekends among Polish preschoolers. Data were collected in the 2017/2018 school year. The study included a total of 522 boys and girls both aged between 5 and 6 years. The ActiGraph GT3X-BT tri-axial accelerometer was used to measure PA. Selected socioeconomic indicators as well as parental body weight and body height were self-reported by parents/caregivers using a questionnaire. In most of the PA indicators analyzed for girls (moderate, vigorous, total MVPA, and steps/day), the averages were higher during the week than during the weekend. Moreover, significantly more boys met the criteria of MVPA, both on weekdays and over the weekend (32.3% boys and 19.2% girls on weekdays and 31.1% boys and 18.1% girls on weekends). Additionally, more boys met the step recommendations, but only on weekends (15.5% boys and 6.6% girls). It was found that if there were two people in a household, there was an almost a three-fold greater chance (adj. OR = 2.94, p = 0.032) of meeting the MVPA criterion with an even stronger association (over fivefold greater chance) in meeting the step recommendation (adj. OR = 5.56, p = 0.033). The differences in the day schedule may potentially contribute with the level of PA in girls. Among the analyzed selected socioeconomic indicators, only the number of people in a household had a significant association on PA. accelerometry objective monitoring young children physical activity preschool ==== Body pmc1. Introduction Physical activity (PA) during the preschool years is crucial for child development and health as well as well-being [1,2]. Regular PA during the preschool age protects against the accumulation of excess body fat [3], whereas high amounts of sedentary behavior (SB) are associated with an increased risk of being overweight or obese [4]. Furthermore, regular PA helps the motor, musculoskeletal, social, and psychological development of preschool children [5]. Therefore, it is important to increase PA in early childhood [6,7], and increases in PA intensity allow for new motor experiences during the preschool years [8]. Moreover, PA may have positive correlations regarding brain function, cognitive development, and school performance among young children [9,10,11]. Furthermore, the consolidation of strong PA habits during childhood has positive long-term effects on lifestyle throughout adulthood [12], and the results of a recent systematic review and meta-analysis of longitudinal studies showed that PA is beginning to decline in childhood compared to previous scientific reports [13]. Currently, public health guidelines on PA place considerable emphasis on the population of children aged 6 to 11 years [14]. These guidelines typically address the frequency, timing, and intensity of PA. The World Health Organization (WHO) and public health authorities around the world recommend that children aged 5–17 years should perform moderate-to-vigorous PA (MVPA) for at least 60 min daily for optimal health benefits [14]. In contrast, the Canadian PA guideline for preschool children suggests children aged 3–6 years should participate in at least 180 min of PA to achieve health benefits [15]. However, it is important to remember that all levels of PA, LPA (light-intensity PA), MPA (moderate-intensity PA), and VPA (vigorous-intensity PA) are important [16]. Studies have shown that preschool children spend most of their day on SB and a small proportion of their day on moderate- or vigorous-intensity PA (MVPA) (<15%) [17,18]. The most commonly used measure for PA analyses is MVPA. Moderate-to-vigorous PA has been shown to be essential for health promotion and disease prevention [16,19] and a large proportion of children do not meet the guidelines for minimum time spent on MVPA [20,21,22,23], and the situation worsens with age [24]. Martínez-Bello and Estevan [25], based on an analysis of the latest literature, confirmed factors that impact PA and motor competence are not only present in primary education but are already manifested in early childhood. Preschool children typically spend a large amount of time with their parents, who can have a strong influence on their behavior, including PA. Research has shown that PA in early childhood is associated with parental practices that encourage or discourage engagement in PA [26,27,28,29]. Additionally, there are inconsistent findings on the association between parents, educational level, and children’s PA [30,31]. Physical activity is influenced by psychological, social, environmental, and demographic variables [32], and analyses of non-modifiable socio-demographic variables such as age and sex influence lower levels of PA in children [33,34]. In addition, Bassul et al. [35] reported that most parents have positive perceptions and high satisfaction with all aspects of their neighboring environment, such as it being perceived as pleasant and safe for walking and cycling, the number of PA facilities, and the quality and availability of local restaurants and food shops. Selected socioeconomic status (SES, which commonly refers to educational level, social class, and/or income) have direct or indirect links to various health indicators [36]. Low education and/or the professional skills of parents are one of the most important risk factors for children internalizing (emotional) and externalizing (behavioral) problems [37]. Low SES is associated with low PA [38], and it is also a factor that strongly influences PA [39]. Studies report that youth who are considered to be lower SES participate in less PA than their more advantaged counterparts [40,41]. Additionally, children in lower SES households in the US and other developed countries are more likely to be overweight or obese [42]. Children with lower SES may experience greater barriers to being or becoming physically active. For example, factors of lower household income would affect participation in PA, as those less financially well off cannot afford to participate, resulting in lower average daily PA than children in the high SES group. For this reason, it is important to consider the various causes and factors that may affect children’s PA levels. A study by Hesketh et al., 2006, showed an association between PA and household income in preschool children [43]. However, systematic reviews showed no relationships between selected socioeconomic indicators and the level of PA in preschool children [44,45]. Among other factors, focusing on an analysis of parent–child relationships in preschool children is the key to understanding the factors that are important in shaping a child’s active lifestyle [12,46]. Nonetheless, PA studies using objective methods are in the minority, and there is currently a lack of valuable studies of objective measurements of parent–child PA in the context of material conditions and other selected factors (e.g., the number of people in the family). A variety of mechanisms, including encouragement, beliefs, and attitudes towards PA, role modeling, and involvement can help to shape important attitudes and behaviors associated with PA in children [47]. Family members and parents have a strong influence on PA [48], which can take many forms, such as modeling and encouragement [49], rules and restrictions [50], participation [51], and in watching or supervising [52]. In addition, researchers report conflicting findings regarding children’s PA on weekends and weekdays. The day of the week is an important determinant of MVPA, as young children are more sedentary and less physically active [44,53]. Brooke et al. [54], Lee et al. [55], and Gråstén et al. [56] reported in their works that children are more engaged in MVPA on weekdays than during weekends. In contrast, Nupponen et al. [57], Hinkley et al. [45], and Van Cauwenberghe et al. [58] indicated that children were more often physically active on weekends rather than on weekdays. Children’s PA levels on weekends are important because children may have more time to engage in outdoor play and recreational activities compared to weekdays when they spend many of their hours in a seated position. Therefore, it is necessary to study children’s PA during both weekends and weekdays to better understand behaviors and to promote children’s PA. Taking into account the fact that there is a lack of current and wide-ranging studies among Polish preschoolers that compare socioeconomic indicators with objectively measured PA, the present study focuses on the assessment of these relationships. To the best of our knowledge, this is the first study to examine the associations between a device-based measure of PA, the number of steps and meeting recommendations for MVPA, and selected socioeconomic indicators on weekdays and on weekends. Therefore, the outcomes of present study may be used in the development of preventive programs addressed to the pediatric population. The aims of this study were: (1) to assess the level of PA and meeting the WHO recommendations (MVPA and the number of steps) in Polish preschool boys and girls on weekdays and on weekends; (2) to investigate the relationship between the selected socioeconomic indicators (self-reported by parents) and PA, including meeting the WHO recommendation for daily MVPA and the number of steps on weekdays and on the weekends among Polish preschoolers. We hypothesize that there is a difference in PA level and meeting the WHO recommendation for daily MVPA and the number of steps on weekdays and weekends among Polish children in kindergartens. We also assume that in this group there is an association between selected socioeconomic indicators and the abovementioned variables related to PA. 2. Materials and Methods This study was approved by the Bioethics Committee of the University of Rzeszów (no. 2017/01/05) and was conducted in accordance with the ethical standards stated in the relevant version of the Declaration of Helsinki. Before the study was initiated, written consent for participation was obtained from the children’s parents. 2.1. Procedures Based on data published by the Polish Central Statistical Office, there were approximately 6800 preschoolers between 2017 and 2018 in Rzeszów, Poland. Assuming a confidence level of 95% and a 5% margin of error, the required sample size should include at least 364 participants. The invitation to participate in the study was sent by researchers to all kindergartens in Rzeszów. The consent of 41 kindergarten principals were obtained for participation in this study. Based on data from Rzeszów City Hall, the average number of preschoolers attending each kindergarten is approximately 70. Considering an estimate that approximately 30% of parents would agree for child participation in the study, and possible complications during examinations (missing data in surveys, failure to meet valid days when measuring PA with accelerometers, absence of children on the day of the test, etc.), we decided to randomly select 22 kindergartens for participation (kindergartens were selected using STATISTICA software—sampling without replacement). The consent form, the questionnaires, and detailed guidelines were delivered to parents of all children attending to selected kindergartens through kindergarten staff. The parents were instructed to discuss and complete the questionnaire together. In case of two or more children from one family, each child received their own code, and the parents were instructed to complete separate questionnaires for each one. The signed consents and filled questionnaires (n = 565) were collected by kindergarten staff. With the help of tutors/teachers, all participants received comprehensive information about the study. Anthropometric measurements were carried out in kindergartens, in a separate room. All the measurements were taken between 8:00 a.m. and 10:00 a.m. 2.2. Participants The inclusion criteria consisted of children (1) who were 5 to 6 years old, (2) whose parents or caregivers provided written parental consent and child assent prior to data collection, and (3) attending preschool in Rzeszów. Exclusions criteria were: (1) any conditions that may affect the assessment of PA. During the data collection stage, 43 subjects were excluded from the study for the following reasons: strong anxiety of examination (n = 5), failure to return or complete the survey (n = 20), and a lack of valid accelerometer data (n = 18). Therefore, to the final analysis, 522 children were included (Figure 1). The final sample consisted of 522 preschoolers (271 girls) aged 5–6 years (5.4 ± 0.6). 2.3. Anthropometric Measurements Body height was measured to an accuracy of 0.1 cm using a portable stadiometer (Tanita HR-200, Tokyo, Japan). This measurement was taken in a vertical position, barefoot. Bodyweight was assessed with an accuracy of 0.1 kg using a body composition analyzer (BC-420 MA, Tanita, Tokyo, Japan) [59]. Body mass index (BMI) was calculated as body weight (in kg) divided by height in meters squared (kg/m2). Based on the BMI values, BMI percentiles were calculated by referencing Polish centile charts [60]. Based on the BMI percentile values, categories of participant body mass were determined as follows: underweight (<5th percentile), healthy body mass (between 5th and 85th percentile), overweight (BMI ≥ 85th percentile and <95th percentile), or obese (≥95th percentile) [61]. 2.4. Physical Activity The ActiGraph GT3X-BT tri-axial accelerometer (ActiGraph, Pensacola, FL, USA) was used to measure PA. Currently, accelerometers are used in many studies on the level of PA [62]. Actigraphy is a valid method to objectively measure PA level in preschool children [63]. The accelerometer was worn at the participant’s right hip. After the end of the recording, the sensor was connected to a computer via a mini-USB for data transfer. The participants were instructed to wear the accelerometer for seven consecutive days, 24 h a day, five days a week, and during the two days of the weekend. The data were collected in 5-s epochs [64]. Non-wear time was defined as 60 min of consecutive zeros, allowing for 2 min of non-zero interruptions [65]. Wear time of ≥500 min/day was used as the criterion for a valid day, and ≥4 days were used as the criteria for a valid 7-day period of accumulated data [58]. ActiGraph data were analyzed with Actilife 6.13. (ActiGraph LLC, Pensacola, FL, USA). The cut-off points from Evenson et al. were selected to determine the time spent on MVPA level (>2296 counts per minute—CPM). The cut-off points were: Sedentary: 0–100 CPM, Light: 101–2295 CPM, Moderate: 2296–4011 CPM, Vigorous: 4012–∞ CPM [66]. The participants complying with the minimum 60 min of MVPA per day requirement met the guidelines, while the participants who did not meet this number (<60 min) were regarded as inactive [67]. Physical activity values were compared with the established recommendations of ≥60 min of MVPA or ≥180 min of PA [68] at any intensity to evaluate the proportion of participants meeting these recommendations. Daily step count was calculated as the mean daily step count from all valid days. All step counts below 1000 and above 30,000 steps per day were deleted and treated as missing data according to the rules of Rowe et al. [69]. Participants with at least 12,000 steps per day were considered to be sufficiently physically active [70]. 2.5. Selected Socioeconomic Indicators The parents of the participating children were given a questionnaire that they were asked to complete to provide relevant information, including their education level and family structure. Selected socioeconomic indicators and socio-demographic characteristics (children’s sex and date of birth, place of residence, number of people in household, and parents’ education), as well as parental body weight and body height, were self-reported by the parents/caregivers using a questionnaire. Based on parents’ answers in the questionnaire, household income factors were defined as low, middle, or high. Parental BMI was calculated as underweight (BMI < 18.5), normal (BMI 18.5–24.9), overweight (BMI 25–29.9), and obese (BMI ≥ 30) [71]. 2.6. Statistical Analysis Statistical analysis was performed using SPSS 20 software (IBM, North Harbour, UK). The data were presented as the mean ± standard deviation (SD) and percentage (%) for continuous and categorical variables, respectively. Univariate and multivariate logistic regression analysis was performed to assess the significant determinants of meeting the MVPA criterion (>60 min/day) according to BMI percentiles and socioeconomic factors. The covariates included sex, various indicators of PA (np. MVPA), and the number of steps. The McNemar test was used to determine the significance of differences in MVPA and steps per day on weekdays vs. weekends. The Wilcoxon signed rank test was used to compare the two measurement variables. The normality of the distribution was applied, and the non-parametric Wilcoxon test was used. The level of statistical significance was set at p < 0.05. For measuring the effect size, the value of eta square (η2) was calculated and interpreted using the following criteria: no effect (η2 < 0.01), small effect (0.01 ≤ η2 < 0.06), moderate effect (0.06 ≤ η2 < 0.14), strong effect (η2 ≤ 0.14) [72]. 3. Results The final sample consisted of 522 preschoolers (271 girls) aged 5–6 years (5.4 ± 0.6). The average height was 116.3 ± 6.0 cm, and the average weight was 21.2 ± 3.6 kg. All participating children were white Caucasian, which is representative of the ethnic demographics of Poland. Table 1 shows that the overall prevalence of overweight and obesity, defined by BMI, was 6.5% and 3.4%, respectively. Based on BMI in boys, 5.2% were overweight and 3.6% were obese. Similarly, in girls, 7.7% were overweight and 3.3% were obese. There were no significant differences in the occurrence of individual body mass categories between boys and girls. The place of residence (95% of the respondents live in a city), father’s and mother’s education, were accessed. Differences were found in the mother’s education as a parent of five- and six-year-olds (p < 0.037). A higher percentage of mothers declared higher education than fathers. Significant differences were also found between five- and six-year-olds regarding the number of persons in the household (p < 0.021). Significantly more six-year-olds (6.9%) were in a two-person family compared to five-year-olds (1.5%). Most parents declared a high household income (92.3%). There were no significant differences between sex. Table 2 shows the individual levels of PA during weekdays vs. weekends, analyzed separately for groups of girls and boys, and in the total sample. In most of the PA indicators analyzed in girls (moderate, vigorous, total MVPA and steps/day), averages were higher during the week than during the weekend. However, no size effects were observed. Table 3 shows the distribution of selected parameters relating to PA. The data are presented with regard to age and sex. On both weekdays and weekends, most indicators of PA (light, moderate, MVPA, and steps/day) were higher in boys than girls (p < 0.05). Moreover, significantly more boys compared to girls met the criteria of MVPA and steps over the weekend (31.1% vs. 18.1% and 15.5% vs. 6.6%, respectively). Moreover, more boys meet steps recommendations, but only on weekends. Table 4 compares the results related to meeting the recommendation for PA level on the weekend vs. weekday. Results shows that 45.3% of girls and 55.4% of boys met MVPA recommendations on both weekend and weekdays. The criterion of 12,000 steps at the weekend and on weekday was met by 44.4% boys and girls. Table 5 presents univariate and multivariate logistic regression analysis assessing the relationship between meeting the MVPA recommendation (≥60 min/day) and selected socioeconomic indicators. It was found that if there were two people in household, there was an almost a three-fold greater chance (adj. OR = 2.94, p = 0.032) of meeting the MVPA criterion (≥60 min/day). A similar situation is found in Table 6, where the univariate and multivariate logistic regression analysis was conducted to assess the significant determinants of meeting the number of steps criterion (≥12,000) depending on selected socioeconomic indicators. It was found that if there were two people in a household, there was more than a fivefold chance (adj. OR = 5.56, p = 0.033) of meeting the criteria of steps (≥12,000). 4. Discussion The aim of this study was to analyze children’s PA on both weekends and weekdays to better understand behavior and promote the PA of children, and to analyze the relationship between selected socioeconomic indicators and PA. The results confirmed the hypothesis that Polish preschoolers are potentially more active on weekdays than on weekends. Only 8.4% of participants during the week and 10.9% of participants on the weekend met international guidelines for daily steps. The MVPA score was much better, where the guidelines were met by 25.5% of the participants during the week and 24.3% of the participants over the weekend. Based on the analysis of the self-reported results, boys were more active than girls. During the week, boys showed significantly higher values of PA parameters (MVPA in boys 50.1 ± 22.4 vs. girls 42.4 ± 20.1). During the weekend, boys also showed significantly higher values of PA parameters (MVPA in boys 48.6 ± 29.6 vs. girls 38.62 ± 21.96). Our findings are therefore consistent with the literature that preschool boys are more active than their female counterparts [73,74]. The results of this analysis show that boys and girls accumulate more MVPA on weekdays compared to weekend days. Similar values were obtained by other researchers [75,76,77]. Despite the fact that only 8.4% of participants on weekdays and 10.9% over the weekend met the recommendation of 12,000 steps per day, the results of our study are not significantly different from those of other authors. Considering the number of steps (weekday 8869.97 ± 2174.43; weekend 8587.43 ± 3017.55), our participants are at an average level compared to other results [78,79]. The results of this analysis show that boys and girls accumulate a higher number of steps on weekdays compared to weekend days. Given the differences in favor of activity during weekdays, many analyses confirm this result [78,80,81]. Our results also show sex differences, with boys being at the forefront of daily number of steps (boys 9109.99 ± 2151.98 vs. girls 8647.67 ± 2175.43). This is also evident in other analyses [82,83]. Possible explanations for significant differences between weekday PA and weekend PA may include participation in more physical activities during weekdays (e.g., PE class), or compulsory class activities in which participation in the curriculum activities are deemed compulsory by the kindergarten. However, the influence of segmented activities during kindergarten hours on step counts and other PA indicators are not conclusive because we were unable to provide relevant evidence [77]. Other authors offer an explanation of the difference in meeting recommendations of PA in weekdays and weekends by differences in sleep duration, family activities or parental support [75,76]. Selected socioeconomic indicators are a complex and multifactorial construct with the most common indicators being education level and income level, among others. One of the most important indicators is the level of education because it reflects not only economic factors, but also general and health knowledge, which may be more important for children’s health behavior than, e.g., income or place of residence. Families with higher incomes can afford to use cars to take the child to kindergarten instead of walking or using public transport. This reflects consistency with a recent study that found that children with higher parental income (as one of the strongest demographic factors) favored participation in organized PA, which could possibly be explained by parental support for such activities [84]. The results in Malmo et al. [31] point towards no significant relationship between preschool children’s activity levels at leisure and their parents’ education level. Subjects, whose parents reported household income factors, met the recommendations of the MVPA (94.9%) and daily steps (100%). On the other hand, there were more normal weight children who met the MVPA recommendations (80.8%) compared to their parents declaring no obesity (87.9%) and more normal weight children who met the daily steps recommendations (84.6%) compared to their parents declaring no obesity (88.95%). Adult obesity is most often caused by low PA levels, so it is most likely that children with low PA levels drew patterns from low-activity parents [26,85]. It is also interesting to note that every second child who met the MVPA and daily steps recommendations lived in a family of four (MVPA—45.5%) and daily steps (53.8%). The results partly support the hypothesis that the selected socioeconomic indicators were associated with higher PA. The findings of this study suggest that the number of people living together in the same house has a great influence on the fulfillment of the PA criteria. If there were two people in the household, the chance of meeting the MVPA criterion was almost three times higher (OR = 2.94). On the other hand, when there were two people in the household, the chance of meeting the steps/day criterion was more than five times higher (adj. OR = 5.56). One possible explanation of this association could be that single parents may put greater attention and spent more time being physically active with a child. It is likely that parents/parent are role models for a child’s extracurricular PA. When children find that their parents are actively involved and value PA, they can adopt the values and behaviors themselves. Physically active parents can provide more support and encouragement to their children to be active and influence their children’s level of activity in this way. There may be a genetic predisposition to PA. For example, in a review, Beunen and Thomis found that heritability rates for practicing PA ranged from 0.35 to 0.83, and children whose parents were active in PA were 1.2–5.8 times more likely to participate in PA than children whose parents were not active in PA [86]. It is important to remember that parents play an important role in promoting healthy and active lifestyles in their children [87,88]. In the case of other selected socioeconomic indicators, the scale of the differences was insignificant. Parents that attain higher education can take advantage of parenting practices that encourage PA, as they are more aware of the health benefits of PA. To meet the minimum recommendations of PA, among others, one should: increase activity (walking) over short distances, refrain from installing screens/TV in children’s bedrooms, promote non-competitive PA, improve infrastructure in playgrounds offering more physical games, encourage children to be active, and reduce sedentary time in kindergarten and at home. Nevertheless, some limitations of the study should be mentioned. The data are cross-sectional and do not allow for an analysis of cause-and-effect relationships. Consequently, we do not know the direction of the relationships found. To the best of our knowledge, this is the first study in Poland to examine the complex associations between a device-based measure of PA, meeting recommendations for MVPA (≥60 min/day) and the number of steps (≥12,000) and selected socioeconomic indicators on weekdays and on weekends. The study covered a relatively large sample of preschoolers. One of the strengths of this study is the provision of objective data on children’s PA. The cross-sectional nature of the methodology applied in the present study and a statistical analysis which does not include the causality and generalizability models should be recognized as important limitations, and therefore our outcomes should be treated with caution. Present research was based mainly on analyzes of PA and selected socioeconomic indicators (including household income factors). Therefore, future research should focus on the full analysis of SES versus PA and sedentary behaviors of children and their parents, both at the weekdays and the weekend. Moreover, the questionnaire used in the study should be considered as a limitation of the study, as it has not been validated. Therefore, results related to the use of this questionnaire should be treated with caution. Another limitation of this study could be that the 7.6% of participants who meet the inclusion criteria were excluded from the analysis due to a strong anxiety about examination, a failure to return or complete the survey, and a lack of valid accelerometer data. The results may be limited to some extent because all kindergartens were located in one metropolitan area. In addition, the research sample was not an ideal representation of the population of children attending kindergarten. It did not include children from rural areas or other towns. However, it is worth noting that there were no interventions in the children’s PA during the study. Future research should target cause-effect relationships and analyze PA more closely during the day, divided between kindergarten attendance and staying at home. In summary, this study demonstrated that preschools are a strong predictor of PA levels, which supports the importance of the preschool setting for healthy PA behaviors and development. While some of the observed correlates were non-modifiable (e.g., selected socioeconomic indicators), these findings may be helpful in identifying families who are at higher-risk of promoting an inactive lifestyle to their young children (e.g., number of people in household). This study suggests that future interventions should be aimed at increasing PA in young children by promoting PA and its benefits to parents. 5. Conclusions Approximately one third of boys and one fifth of girls meet the WHO recommendations according to MVPA and steps. Boys were more physically active than girls both during weekdays and on weekends. The differences in the day schedule may potentially contribute with the level of PA in girls. Among the analyzed selected socioeconomic indicators, only the number of people in household had a significant association on PA. The present findings may help to promote future interventions that focus on increasing PA (including MVPA and daily steps) on both weekday and weekends to improve physical development and maintenance of healthy weight in preschool children. Further research is needed to define modifiable determinants of PA in children attending kindergarten. Author Contributions Conceptualization, J.H. and J.W.; methodology, J.H., J.W. and P.M.; software, K.P. and M.A.; formal analysis, J.H.; investigation, J.H., J.W., P.M., K.P., M.A. and A.M.-R.; resources, J.H., P.M. and M.A.; data curation, J.H.; writing—original draft preparation, J.H. and P.M; writing—review and editing, A.M.-R.; supervision, J.W., P.M. and A.M.-R. 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 (or Ethics Committee) of Bioethics Committee of the University of Rzeszów (no. 2017/01/05) for studies involving humans. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data is available at the link: https://repozytorium.ur.edu.pl/handle/item/7423 (accessed on 1 July 2021). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flow diagram for participant recruitment. ijerph-19-04999-t001_Table 1 Table 1 Characteristics of the population by age and sex. Variables Age (Years) Sex Total Sample (n = 522) 5 (n = 261) 6 (n = 261) p a Boys (n = 251) Girls (n = 271) p b Body height (cm) † 116.4 ± 6.1 116.2 ± 5.8 0.761 116.8 ± 6.0 115.8 ± 5.9 0.067 116.3 ± 6.0 Weight (kg) † 21.8 ± 3.6 21.2 ± 3.6 0.859 21.3 ± 3.6 21.0 ± 3.6 0.448 21.2 ± 3.6 BMI (kg/m2) † 15.5 ± 1.4 15.6 ± 1.7 0.488 15.5 ± 1.7 15.6 ± 1.6 0.570 15.6 ± 1.6 Body mass classification (according to BMI percentiles) *  Underweight 22 (8.4) 23 (8.8) 0.809 18 (7.2) 27 (10.0) 0.401 45 (8.)  Normal 215 (82.4) 210 (80.5) 211 (84.1) 214 (79.0) 425 (81.4)  Overweight 17 (6.5) 17 (6.5) 13 (5.2) 21 (7.7) 34 (6.5)  Obesity 7 (2.7) 11 (4.2) 9 (3.6) 9 (3.3) 18 (3.4) Place of residence *  Urban 244 (93.5) 252 (96.6) 0.108 243 (96.8) 253 (93.4) 0.074 496 (95.0)  Rural 17 (6.5) 9 (3.4) 8 (3.2) 18 (6.6) 26 (5.0) Mother’s education *  Middle school or lower 50 (19.2) 70 (26.8) 0.037 60 (23.9) 60 (22.1) 0.632 120 (23.0)  High school/University 211 (80.8) 191 (73.2) 191 (76.1) 211 (77.9) 402 (77.0) Father’s education *  Middle school or lower 108 (41.4) 119 (45.6) 0.331 110 (43.8) 117 (43.2) 0.881 227 (43.5)  High school/University 153 (58.6) 142 (54.4) 141 (56.2) 154 (56.8) 295 (56.5) Number of people in household *  2 4 (1.5) 18 (6.9) 0.021 8 3(3.2) 14 (5.2) 0.662 22 (4.2)  3 64 (24.5) 72 (27.6) 67 (26.7) 69 (25.5) 136 (26.1)  4 142 (54.5) 116 (44.4) 129 (51.4) 129 (47.6) 258 (49.4)  5 35 (13.4) 42 (16.1) 35 (13.9) 42 (15.5) 77 (14.8)  More 16 (6.1) 13 (5.0) 12 (4.8) 17 (6.3) 29 (5.6) Household income *  High 241 (92.3) 241 (92.3) 1.00 230 (91.6) 252 (93.0) 0.561 482 (92.3)  Middle or low 20 (7.7) 20 (7.7) 21 (8.4) 19 (7.0) 40 (7.7) Parental obesity *  None 224 (85.8) 223 (85.4) 0.126 210 (83.7) 237 (87.5) 0.117 447 (85.6)  Father 11 (4.2) 19 (7.3) 13 (5.2) 17 (6.2) 30 (5.7)  Mother 13 (5.0) 14 (5.4) 19 (7.6) 8 (3.0) 27 (5.2)  Both parents 13 (5.0) 5 (1.9) 9 (3.6) 9 (3.3) 18 (3.4) Data are expressed as: * n (%); † mean ± SD; p a—the assessment of significance of differences between 5 and 6 years old; p b—the assessment of significance of differences between boys and girls; BMI—body mass index; significant associations are highlighted in bold. ijerph-19-04999-t002_Table 2 Table 2 Levels of physical activity in weekday and weekends. Total (n = 522) Girls (n = 271) Boys (n = 251) Average Physical Activity (min/Day) Mean ± SD p η2 p η2 Mean ± SD p η2 Light weekday 464.0 ± 710 456 ± 97.8 37.9 ± 17.2 35.5 ± 20.5 8.3 ± 6 7.9 ± 8.7 46.2 ± 21.6 43.4 ± 26.3 8873.4 ± 2183.8 8596.0 ± 3016.2 0.241 0.002 455.5 ± 72.5 451.6 ± 92.6 34 ± 15.3 31.2 ± 16.4 8.4 ± 6.2 7.3 ± 8 42.4 ± 20.1 38.5 ± 21.9 8634.9 ± 2182.3 8286.9 ± 2639.4 0.676 0.001 473.3 ± 68.3 460.8 ± 103.2 42 ± 18.1 40.1 ± 23.3 8.2 ± 5.7 8.5 ± 9.4 50.3 ± 22.5 48.6 ± 29.5 9130.7 ± 2160.3 8929.6 ± 3349.5 0.239 0.005 weekend Moderate weekday 0.001 0.004 0.002 0.008 0.050 0.002 weekend Vigorous weekday 0.001 0.001 0.001 0.005 0.150 0.001 weekend Total MVPA weekday 0.001 0.003 0.001 0.008 0.127 0.001 weekend Steps/day weekday 0.004 0.003 0.011 0.005 0.148 0.001 weekend η2: eta square-effect size; MVPA—moderate to vigorous physical activity; significant associations are highlighted in bold. ijerph-19-04999-t003_Table 3 Table 3 Physical activity levels on weekdays and during weekends by age and sex. Variables Age (Years) Sex Total Sample (n = 522) 5 (n = 261) 6 (n = 261) p a Boys (n = 251) Girls (n = 271) p b Weekdays Average physical activity on weekday (min/day) †  Light 463.9 ± 621.1 464.7 ± 78.4 0.908 473.1 ± 68.5 456.1 ± 71.7 0.006 464.3 ± 70.6  Moderate 37.0 ± 16.4 38.6 ± 17.8 0.290 41.9 ± 18.0 34.1 ± 15.3 0.001 37.8 ± 17.1  Vigorous 8.0 ± 5.7 8.5 ± 6.3 0.391 8.2 ± 5.7 8.3 ± 6.3 0.720 8.3 ± 6.04  MVPA 45.1 ± 20.6 47.1 ± 22.4 0.279 50.1 ± 22.4 42.4 ± 20.1 0.001 46.1 ± 21.5  Steps/day 8905.4 ± 2071.9 8834.5 ± 2276.4 0.710 9109.9 ± 2151.9 8647.6 ± 2175.4 0.001 8869.9 ± 2174.4 Meeting criteria of MVPA (≥60 min/day) on weekday *  Yes 63 (24.1) 70 (26.8) 0.482 81 (32.3) 52 (19.2) 0.001 133 (25.5)  No 198 (75.9) 191 (73.2) 170 (67.7) 219 (80.8) 389 (74.5) Meeting criteria of steps (≥12000) on weekday *  Yes 22 (8.4) 22 (8.4) 0.999 26 (10.4) 18 (6.6) 0.127 44 (8.4)  No 239 (91.6) 239 (91.6) 225 (89.6) 253 (93.4) 478 (91.6) Weekend Average physical activity on weekend (min/day) †  Light 459.8 ± 871.6 452.6 ± 106.9 0.399 460.9 ± 103.4 451.9± 92 0.292 456.2 ± 97.7  Moderate 34.4 ± 18.2 36.5 ± 22.6 0.256 40.0 ± 23.4 31.2 ± 16.4 0.001 35.4 ± 20.5  Vigorous 7.7 ± 8.4 8.1 ± 9.1 0.565 8.5 ± 9.4 7.3± 8 0.103 7.9 ± 8.7  MVPA 42.1 ± 23.7 44.6 ± 28.7 0.282 48.6 ± 29.6 38.6 ± 21.9 0.001 43.3 ± 26.4  Steps/day 8731.0 ± 2781.4 8443.8 ± 3235.4 0.277 8907.6 ± 3352.3 8290.8 ± 2642.2 0.020 8587.4 ± 3017.5 Meeting criteria of MVPA (≥60 min/day) on weekend *  Yes 59 (22.60) 68 (26.10) 0.359 78 (31.1) 49 (18.1) 0.001 127 (24.3)  No 202 (77.40) 193 (73.90) 173 (68.9) 222 (81.9) 395 (75.7) Meeting criteria of steps (≥12000) on weekend *  Yes 29 (11.1) 28 (10.7%) 0.888 39 (15.5) 18 (6.6) 0.001 57 (10.9)  No 232 (88.8) 233 (89.) 212 (84.5) 253 (93.4) 465 (89.1) Total (weekday and weekends) Average physical activity in total (min/day) †  Light 3314.2 ± 553.7 3268.2 ± 457.3 0.302 3279.4 ± 474 3302.2 ± 537.9 0.608 0.022 0.026 0.014 0.039 3291.2 ± 507.8  Moderate 256.4 ± 117.3 269.4 ± 113.4 0.198 275.0 ± 116.2 251.8 ± 113.8 262.9 ± 115.4  Vigorous 52.6 ± 36.5 63.0 ± 45.1 0.004 62.0 ± 41.7 53.9 ± 40.7 57.8 ± 41.3  MVPA 309.1 ± 143.8 332.4 ± 145.7 0.067 337.0 ± 146.1 305.8 ± 142.8 320.8 ± 145.1 Steps/day 60258.4 ± 14739 64596.8 ± 1482.8 0.001 63829.3 ± 14856.1 61129.3 ± 14904.5 62427.6 ± 14928.1 Meeting criteria of MVPA (≥60 min/day) in total *  Yes 37 (14.2) 62 (23.8) 0.005 59 (23.5) 40 (14.8) 0.011 99 (19.0)  No 224 (85.8) 199 (76.2) 192 (76.5) 231 (85.2) 423 (81.0) Meeting criteria of steps (≥12000) in total *  Yes 5 (1.9) 21 (8.0) 0.001 15 (6.0) 11 (4.1) 0.314 26 (5.0)  No 256 (98.1) 240 (92.0) 236 (94.0) 260 (95.9) 496 (95.0) Data are expressed as: * n (%); † mean ± SD; p a—the assessment of significance of differences between 5 and 6 year olds; p b—the assessment of significance of differences between boys and girls; MVPA—moderate to vigorous physical activity; significant associations are highlighted in bold. ijerph-19-04999-t004_Table 4 Table 4 Meeting physical activity criteria at weekends vs. weekday. Total (n = 522) Girls (n = 271) Boys (n = 251) (Weekday) Meeting Criteria of MVPA (≥60 min/Day) Total (Weekday) Meeting Criteria of MVPA (≥60 min/Day) Total (Weekday) Meeting Criteria of MVPA (≥60 min/Day) Total No Yes No Yes No Yes (weekend) Meeting criteria of MVPA (≥60 min/day) No n 330 65 395 194 28 222 136 37 173 % 85.4 48.5 75.9 88.6 54.7 82.1 81.2 44.6 69.2 Yes n 57 70 127 26 22 48 31 48 79 % 14.6 51.5 24.1 11.4 45.3 17.9 18.8 55.4 30.8 p 0.470 0.683 0.630 (weekday) Meeting criteria of steps (≥12,000) Total (weekday) Meeting criteria of steps (≥12,000) Total (weekday) Meeting criteria of steps (≥12,000) Total No Yes No Yes No Yes (weekend) Meeting criteria of steps (≥12,000) No n 441 25 466 244 10 254 197 15 212 % 92.1 55.6 89.0 96.1 55.6 93.4 87.6 55.6 84.2 Yes n 36 20 56 9 8 17 27 12 39 % 7.9 44.4 11.0 3.9 44.4 6.6 12.4 44.4 15.8 p 0.129 1.000 0.066 MVPA—moderate to vigorous physical activity. ijerph-19-04999-t005_Table 5 Table 5 Linking MVPA criterion fulfilment parameters (≥60 min/day) to socioeconomic factors. Variables Meeting Criteria of MVPA (≥60 min/Day) Yes (n = 99) n (%) No (n = 423) n (%) Unadjusted OR (95% CI) p Adjusted OR a (95% CI) p Place of residence Urban 95 (19.2) 401 (80.8) REF REF Rural 4 (15.4) 22 (84.6) 0.76 (0.25–2.28) 0.634 0.85 a (0.28–2.55) 0.774 Mother’s education High school/University 72 (17.9) 330 (82.1) REF REF Middle school or lower 27 (22.5) 93 (77.5) 1.33 (0.81–2.19) 0.261 1.32 a (0.80–2.17) 0.283 Father’s education High school/University 49 (16.6) 246 (83.4) REF REF Middle school or lower 50 (22.0) 177 (78.0) 1.42 (0.914–2.201) 0.119 1.42 a (0.91–2.21) 0.125 Number of people in household 2 8 (36.4) 14 (63.6) 2.67 (1.00–7.06) 0.048 2.94 (1.10–7.90) 0.032 3 24 (17.6) 112 (82.4) REF REF 4 45 (17.4) 213 (82.6) 0.99 (0.57–1.70) 0.950 0.98 (0.57–1.70) 0.946 5 16 (20.8) 61 (79.2) 1.22 (0.60–2.48) 0.574 0.700 1.26 (0.62–2.56) 1.28 (0.47–3.52) 0.528 more 6 (20.7) 23 (79.3) 1.21 (0.45–3.31) 0.629 Household income High 94 (19.5) 388 (80.5) REF REF Middle or low 5 (12.5) 35 (87.5) 0.59 (0.22–1.54) 0.283 0.57 a (0.22–1.50) 0.265 Parental obesity None 87 (19.5) 360 (80.5) REF REF Father 4 (13.3) 26 (86.7) 0.64 (0.217–1.87) 0.412 0.65 (0.22–1.91) 0.265 Mother 5 (18.5) 22 (81.5) 0.94 (0.34–2.55) 0.904 0.82 (0.30–2.26) 0.715 Both parents 3 (16.7) 15 (83.3) 0.83 (0.23–2.92) 0.769 0.81 (0.23–2.87) 0.755 OR (95% CI)—odds ratio with a 95% confidence interval; REF—reference category; a—the model adjusted for sex; MVPA—moderate to vigorous physical activity; significant associations are highlighted in bold. ijerph-19-04999-t006_Table 6 Table 6 Linking the parameters of meeting the steps/day criterion (≥12,000) to socioeconomic factors. Variables Meeting Criteria of Steps (≥12,000) Yes (n = 26) n (%) No (n = 496) n (%) Unadjusted OR (95% CI) p Adjusted OR a (95% CI) p Place of residence Urban 26 (5.2) 470 (94.8) REF REF Rural 0 (0.0) 26 (100.0) 0.00 (0.00–0.00) 0.998 0.00 (0.00–0.00) 0.998 Mother’s education High school/University 16 (4.0) 388 (96.0) REF REF Middle school or lower 10 (8.3) 110 (91.7) 2.19 (0.97–4.97) 0.060 2.18 (0.96–4.93) 0.063 Father’s education High school/University 12 (4.1) 283 (95.9) REF REF Middle school or lower 14 (6.2) 213 (93.8) 1.55 (0.70–3.42) 0.285 1.55 (0.70–3.42) 0.280 Number of people in household 2 3 (13.6) 19 (86.4) 5.21 (1.08–25.10) 0.040 5.56 (1.14–26.99) 0.033 3 4 (2.9) 132 (97.1) REF REF 4 14 (5.4) 244 (94.6) 1.89 (0.61–5.87) 0.269 1.89 (0.61–5.86) 0.271 5 4 (5.2) 73 (94.8) 1.81 (0.44–7.44) 0.412 1.84 (0.45–7.59) 0.398 more 1 (3.4) 28 (96.6) 1.18 (0.13–10.95) 0.885 1.22 (0.13–11.38) 0.860 Household income High 26 (5.4) 456 (94.6) REF REF Middle or low 0 (0) 40 (100.0) 0.00 (0.00–0.00) 0.998 0.00 (0.00–0.00) 0.998 Parental obesity None 23 (5.1) 424 (94.9) REF REF Father 1 (3.3) 29 (96.7) 0.64 (0.08–4.87) 0.664 0.64 (0.08–4.95) 0.673 Mother 1 (3.7) 26 (96.3) 0.71 (0.09–5.46) 0.741 0.64 (0.08–5.00) 0.675 Both parents 1 (5.6) 17 (94.4) 1.08 (0.14–8.51) 0.941 1.07 (0.14–8.42) 0.948 OR (95% CI)—odds ratio with a 95% confidence interval; REF—reference category; a—the model adjusted for sex; MVPA—moderate to vigorous physical activity; significant associations are highlighted in bold. 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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/ijerph19095494 ijerph-19-05494 Article The Feasibility of Maintaining Biological Phosphorus Removal in A-Stage via the Short Sludge Retention Time Approach: System Performance, Functional Genus Abundance, and Methanogenic Potential Luo Haichao 1 Guo Wanqian 1* Xing Chuanming 1 Yan Bo 1 Zhao Qi 1 Ren Nanqi 2 Sun Bo Academic Editor Dong Hongyu Academic Editor Du Juanshan Academic Editor 1 State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China; lhcdxw_2010@163.com (H.L.); ab1529902467@163.com (C.X.); yanbo1968@163.com (B.Y.); zqhit@outlook.com (Q.Z.) 2 School of Environment, Harbin Institute of Technology, Harbin 150090, China; rnq@hit.edu.cn * Correspondence: guowanqian@126.com; Tel.: +86-451-8628-3008 01 5 2022 5 2022 19 9 549423 1 2022 11 3 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 increasing concerns on resource and energy recovery call for the modification of the current wastewater treatment strategy. This study synthetically evaluates the feasibility of the short sludge retention time approach to improve the energy recovery potential, but keeping steady biological phosphorus removal and system stability simultaneously. SBRS-SRT and SBRcontrol that simulated the short sludge retention time and conventional biological phosphorus removal processes, respectively, were set up to treat real domestic sewage for 120 d. SBRS-SRT achieved an efficient COD (91.5 ± 3.5%), PO43−-P (95.4 ± 3.8%), and TP (93.5 ± 3.7%) removal and maintained the settling volume index around 50 mL/gSS when the sludge retention time was 3 d, indicating steady operational stability. The poor ammonia removal performance (15.7 ± 7.7%) and a few sequences detected in samples collected in SBRS-SRT indicated the washout of nitrifiers. The dominant phosphorus accumulating organisms Tetrasphaera and Hydrogenophaga, which were enriched with the shortened sludge retention time, was in line with the excellent phosphorus performance of SBRS-SRT. The calculated methanogenic efficiency of SBRS-SRT increased significantly, which was in line with the higher sludge yield. This study proved that the short sludge retention time is a promising and practical approach to integrate biological phosphorus removal in A-stage when re-engineering a biological nutrient removal process. short sludge retention time biological phosphorus removal A-stage operational stability functional microbial abundance long-term methanogenic efficiency National Key R & D Program of China2019YFC1906600 National Natural Science Foundation of China51978201 State Key Laboratory of Urban Water Resource and Environment2020DX08 This work was financially supported by the National Key R & D Program of China (NO. 2019YFC1906600), the National Natural Science Foundation of China (NO. 51978201), and the State Key Laboratory of Urban Water Resource and Environment (2020DX08). ==== Body pmc1. Introduction The vast amounts of energy and material consumption caused by the huge scale and number of constructed wastewater treatment plants (WWTPs) has attracted society’s concerns. Thus, technologies that focused on energy saving or recovery [1,2], resource recovery or utilization [3,4], and meeting the strict effluent discharge standards [5] were developed. The certification of “energy neutral” was achieved in the Strass Wastewater Treatment plant that operated an A-B stage process, in Austria, Leading to the reconsideration of the A-B process to modify current WWTPs. Generally, the first stage is the extremely high load biosorption of the biological concentration of sewage with minimum organic oxidation degradation. The concentrated sludge is anaerobically digested for the recovery of energy content from sewage organics. Subsequently, a low load biological stage follows the first stage, operated to ensure the removal of dissolved organics and ammonia. This is the so-called A-B process due to the two-stage operation model [6]. Thus, biological phosphorus removal is limited in a typical A-B process. Additionally, low available organic carbon in the B stage limits nitrogen removal. To meet the strict discharge standards, enhanced biological phosphorus removal (EBPR) processes, such as anaerobic/anoxic–oxic (AO), anaerobic–anoxic–oxic (AAO), or their modified operation mode, are widely applied in WWTPs [7]. Generally, sequencing anaerobic and aerobic conditions is necessary to achieve efficient biological phosphorus removal [8]. However, the competition for insufficient organic carbon sources between polyphosphate accumulating organisms (PAOs) and denitrifying bacteria inevitably occurs in the anaerobic phase of WWTPs [9]. This unavoidable drawback would be overcome if biological phosphorus removal was separated from nitrogen removal when re-engineering a typical EBPR process. Based on the multiple autotrophic nitrogen removal technologies development and investigationin recent decades [10,11], modifying the classical A-B stage process into an A-stage for C and P removal, with the B-stage for autotrophic nitrogen removal, is a promising approach. The high-rate activated sludge technology (sludge retention time, SRT 0.5–2 d) was employed as an A-stage for partial organic carbon capture, mainly based on bio-sorption in the typical A-B stage process [6]. However, the high-rate activated sludge technology lost sight of phosphorus removal, and chemical phosphorus removal was required to compensate for this deficiency. Integrating biological phosphorus removal into the A-stage might be an applicable and promising exploration when reengineering one EBPR process into the A-B stage. Furthermore, it would be really unfortunate if biological phosphorus removal was abandoned when reengineering one EBPR process into the A-B stage. Thus, researchers investigated the feasibility of efficient biological removal under short or ultra-short SRT [12,13]. Chan et al. operated sequencing batch reactors (SBRs) to treat synthetic sewage, reporting that phosphorus removal and system stability deteriorated when SRT was shorter than 3 d [14]. Shao et al. [15] explored the dynamics of organic carbon and phosphorus removal in an ultra-short SRT SBR system treating real domestic sewage. However, the sludge volume index (SVI) of the SBR system with SRT at 3 d was above 150 mL/g, indicating the system was at the edge of instability. The studies were mainly concerned with the removal of COD and PO43−-P. However, TP removal and the ammonia preservation in A-stage determine the necessity of a chemical phosphorus removal section and the applicability of autotrophic nitrogen removal, respectively. The attentions should be paid to the removal of total phosphorus (TP) and the preservation of ammonia when performance in real domestic sewage treatment. Additionally, the study evaluated the integration of short SRT EBPR in the A-stage, with sludge yield rate (Y or Yobs) or the ratio of the mixed liquor volatile suspended solids (MLVSS) and the mixed liquor suspended solids (MLSSs) [14,16]. Generally, waste activated sludge (WAS) anaerobic digestion (AD) is applied for energy recovery via biogas production in WWTPs [17], and the main objective of the A-B stage is energy and resource recovery. However, a few investigations evaluated the methanogenic efficiency of WAS from the S-SRT system by a long-term AD process. The main objects of this study are to investigate the stability and the methane production potential of short-SRT EBPR systems acting as the A-stage. Two sequencing batch reactors (SBRcontrol and SBRS-SRT) are set up and operated for 120d. The oxic phase duration of SBRcontrol is adjusted (from 1.5 h to 2.5 h) to achieve efficient phosphorus and ammonia removal, while the SRT of SBRS-SRT is adjusted from 5 d to 3 d. The overall COD, phosphorus removal efficiencies, and operational stabilities of the two SBR systems are studied; the microbial community and structures are measured to analyze the primary driving force corresponding to the reactors’ operations. Two AnSBR are also set up to anaerobically digest WAS from the two SBR systems treating sewage. This study proves the feasibility of short-time EBPR as a practical tool for the modification of conventional biological phosphorus removal processes into the A-stage towards improving the energy recovery potential. 2. Materials and Methods 2.1. Domestic Sewage and Reactors Domestic sewage was sampled from a sewer every day in the time period of 16:00–17:00. The sewage was collected from the second campus of the Harbin Institute of Technology and the residential quarters near the campus. A total of 40 L sampled sewage was passed through a 40 mesh sieve and stored in a 60 L influent tank. The main characteristics of the sewage sample are shown in Table 1. Two SBR reactors with a working volume of 9 L were set up in this study. The schematic diagram is shown in Figure 1. Two anaerobic SBR (AnSBR) were also set up to investigate the methanogen efficiency of WAS from the aforementioned SBRs. The working volume of the two AnSBRs were both 2 L. 2.2. Reactor Operation Two SBR reactors were operated for four cycles per day. In each cycle, the incoming influent and discharge of effluent were both 4.5 L (half of the working volume) to maintain the hydraulic retention time as 12 h. The SRT of the SBRcontrol was 10 d by discharging 0.9 L mixture sludge at the end of the oxidation phase each day, but the discharging volume of the SBRS-SRT reactors varied according to the pre-set SRT of each operation stage. Each cycle of SBRS-SRT consisted of 15 min inflow at the first 15 min of the anaerobic phase, 2.5 h anaerobic, 1.5 h oxidation, 30 min settling, 15 min discharging, and 75 min idle. The SBRcontrol operated with the same durations of inflow, settling, discharging, and idle phase, but the duration of the anaerobic and oxidation phases varied. The biomass inoculum for the two experimental SBRs was collected from the second settling tank of the Wenchang Wastewater treatment plant (Harbin, China). The collected sludge was passed through 20 mesh sieves to remove large particles and then, the MLSSs were measured. Certain volumes of sludge were inoculated to maintain the initial MLSS concentrations of the two experimental SBRs as 4.0 g/L. Mechanical stirring was employed to maintain the suspension of the mixed liquor. Two air diffusers were set at the bottom of each SBR and connected with a glass rotameter to control the aeration intensity at 0.8 L/min. The oxygen concentration was measured daily. Additionally, the dissolved oxygen concentration of the two experimental SBRs was maintained above 3.0 mg/L. Each SBR was equipped with an air pump. All phases of each SBR were managed by time controllers. The detailed operational strategies of the two SBRs are shown in Table 2. The operation SRT and temperature of the two AnSBRs were 20 d and 37.0 °C, respectively. The detailed operation parameters of the two AnSBR are shown in the Supplementary Material Text S1 (Figure S1). 2.3. Analytical Methods High-Throughput Sequencing Analysis Sludge samples (100 mL) were collected from the two SBRs on the last day of each operation stage, and the inoculum WAS was sampled as a control. Metagenomic DNAs were extracted by using the 3S DNA isolation kit for Environmental Samples (Shanghai Majorbio Bioscience & Technology, Shanghai, China) following the manufacturer’s instructions. The primers 338F (ACTCCTACGGGAGGCAGCA) and 806R (GGACTACHVGGGTWTCTAAT) were employed for PCR performances, executed in TransStart Fastpfu DNA Polymerase 20 μL reaction systems through 27 time cycles. The high-throughput sequencing analysis of DNA samples was carried out by a commercial service and conducted based on the online data processing developed by the Shanghai Major Biomedical Science and Technology Ltd. (Shanghai, China) (http://www.majorbio.com/) on 1 December 2021. COD, NH4+-N, PO43−-P, total phosphorus (TP), MLSS, MLVSS, and SVI were measured daily, according to the standard methods (APHA 2012). The indexes of influent were measured without pre-filtration by 0.45 μm polyethersulfone filter. The generated biogas from the AnSBR was collected by a 2 L gas bag. The methane contents were measured by gas chromatography (Agilent 7890, Agilent Co., Ltd., City of Santa Clara, CA, USA) that was equipped with a flame ionization detector and a thermal conductivity detector. As the energy or resource recovery is mainly based on the collected WAS, the accumulated WAS discharge per unit of COD (Yobs) was calculated by Equation (1) in this study. (1) Yobs=∑(Vdischarge×St)∑Vinf×(CODinf−CODeff) where Vdischarge (L) is the volume of discharged WAS; St (g/L) is the concentration of MLSS or MLVSS in SBRs at time t; Vinf (L) is the volume of influent sewage per day; CODinf (mg/L) and CODeff (mg/L) are the concentrations of COD in influents and effluents of SBRs. The methanogenic efficiency (MP) of WAS and total methane recovery potential (MPtotal) of the two experimental SBRs were calculated according to Equations (2) and (3) as follows:(2) MP=Vbiogas×RmethaneSWAS (3) MPtotal=MPaverage×Yobs×RCOD where Vbiogas is the total volume of generated biogas at time t; Rmethane is the volume ratio of methane in generated biogas; SWAS is the concentration of inflow WAS corresponded to biogas production; and MPaverage is the average methanogenic efficiency of specified operation duration. Yobs of the same specified operation duration was calculated according to Equation (1), and RCOD is the average COD removal efficiency. 3. Results and Discussion 3.1. Operational Stability of Two SBRs under Different Stages The operational stability was assessed by the measurements of MLSS, MLVSS, SVI, and Yobs as shown in Figure 2. The average MLSS, MLVSS, SVI, MLVSS/MLSS, and the p-value (t-test) of the two SBRs during each stage are shown in Table S1. The average concentrations of MLSS in SBRS-SRT decreased with the decrease in SRT, as shown in Figure 2a. The average ratios of MLVSS/MLSS decreased from 60.2 ± 6.1% to 54.0 ± 8.0% with the SRT shortening from 4 d to 3 d in SBRS-SRT, which was not consistent with the study in [15]. As shown in Table S1, the average MLVSS/MLSS ratios of SBRS-SRT remain slightly higher than SBRcontrol (54.0 ± 8.0% vs. 51.2 ± 6.3%, p = 0.10). This phenomenon might be caused by the difference and instability of sewage quality. However, a higher MLVSS/MLSS was beneficial to the sequential AD treatment of WAS [18]. The SV30 and SVI were measured to assess the sedimentation performance of the activated sludge in the experimental reactors and the results are shown in Figure 2c,d. The SV30 of SBRcontrol significantly decreased when the duration of the oxic phase was extended from 2 h to 2.5 h, while the SV30 remained relatively stable with the shortening of SRT in SBRS-SRT. The SVI of both experimental SBRs remained around 50 mL/g, indicating the excellent sedimentation capacity of the activated sludge in this study. It was notable that the SVI of SBRS-SRT was higher than SBRcontrol during operation stage III. It might be due to the high organic substance content and also indicated the higher metabolic activity of the activated sludge in SBRS-SRT. The accumulated WAS discharged from SBRcontrol and SBRS-SRT is demonstrated in Figure 2e,f. The corresponding Yobs of MLSS and MLVSS were calculated by Equation (1), and the effluent MLSS or MLVSS was not included to represent the total feedstock of the subsequent WAS disposal processes realistically in this study. The extension of the oxidation duration slightly affected the Yobs of the SBRcontrol, which were 0.4257 g/gCOD (Yobs-MLSS-2.5h) and 0.3808 g/gCOD (Yobs-MLSS-2h) when the oxic phase durations were 2 h and 2.5 h, respectively. The shortening of SRT from 4 d to 3 d increased the Yobs from 0.4223 g/gCOD (Yobs-MLSS-4d) to 0.4849 g/gCOD (Yobs-MLSS-3d). The Yobs-MLSS-3d of SBRS-SRT was 27.3% higher than the Yobs-MLSS-2h of the SBRcontrol and the Yobs-MLVSS-3d was 35.2% higher than Yobs-MLVSS-2.5h, indicating that more removed COD was converted into WAS. The high accumulation of WAS production of SBRS-SRT at SRT 3 d indicates the outstanding COD capture capacity of SBRS-SRT. It was beneficial to increase the energy recovery potential of the subsequent WAS AD process. 3.2. Sewage Nutrient Removal Efficiencies of the Two SBR Systems The SRT of the SBRS-SRT and SBRcontrol was 5 d and 10 d, respectively, during the initial 21 d to accumulate PAOs and to acclimate to the operation mode for the start-up. The nutrient removal efficiencies of SBRS-SRT and SBRcontrol EBPR reactors were shown in Figure 3. The average nutrient removal efficiencies were shown in Table S2. The average COD removal efficiencies of SBRS-SRT and SBRcontrol under each stage were 90.0 ± 3.9% and 90.7 ± 5.4%, 91.1 ± 3.2% and 90.7 ± 3.5%, 92.0 ± 3.8% and 91.5 ± 3.5%, respectively (p > 0.05), as shown in Table S2. The shortening of the SRT affected the COD removal performance of SBRS-SRT negligibly, while the extension of the oxic phase duration slightly enhanced the COD removal efficiency of SBRcontrol, as shown in Figure 3a. COD was mainly removed by the adsorption of sludge flocs and the metabolism of activated organisms. The previous studies confirmed that short SRT enhanced the adsorption of sludge flocs and accelerated the microorganism activities [15], which accounted for the steady and excellent COD removal efficiency of SBRS-SRT. Ammonia removal was the premise step that supplied NOx−-N for denitrification to achieve nitrogen removal in conventional WWTPs. The oxic phase duration of the SBRcontrol was adjusted and extended to achieve efficient ammonia removal. The ammonia removal performances of the two experimental SBRs are shown in Figure 3b. The ammonia removal efficiency increased from 35.2 ± 19.9% to 88.9 ± 5.4% with the increase in the oxic phase duration from 1.5 h to 2.5 h, as shown in Table S2. However, the ammonia removal efficiencies decreased from 25.9 ± 18.5% to 15.7 ± 7.7% (p < 0.05, Table S2) with the SRT shortening from 5 d to 3 d indicating that only a limited amount of NH4+-N was removed in SBRS-SRT. An SRT around 4.3 d and a low dissolved oxygen were beneficial for the nitrification and the accumulation of AOBs [19]. The short duration of the oxic phase in SBRS-SRT accounted for the inefficient ammonia removal. The activity of the AOBs was inhibited when the SRT of the SBR system was 3.5 d [13]. The nitrification was even undetectable in a continuous A/O process when the SRT was 4 d [17]. However, the SBRS-SRT offered a lower ammonia removal efficiency, which was mainly by microbial assimilation. Both the SBRcontrol and the SBRS-SRT removed PO43−-P efficiently, as shown in Figure 3c. The average PO43−-P removal efficiency of SBRS-SRT was above 95% under both SRT 4 d and 3 d, as shown in Table S2. It was comparable with the S-SRT or traditional EBPR processes of previous studies [17,20]. However, the evident value difference between the PO43−-P and TP content in sewage indicated the necessity to pay attention to the TP removal performance of the SBRS-SRT and the SBRcontrol. Furthermore, TP was the control target specified in effluent discharge standards. The average TP removal efficiencies of the SBRS-SRT were 93.8 ± 3.9% and 93.5 ± 3.47% at SRT 4 d and 3 d, respectively, as shown in Figure 3d. The corresponding TP concentrations in the effluent were 0.32 ± 0.21 mg/L and 0.32 ± 0.16 mg/L, respectively, which met the first A class of Chinese standards (GB, 18918-2002, <0.5 mg/L). The TP in sewage consisted of both inorganic phosphorus (mainly PO43−-P) and organic phosphorus. Organic phosphorus was removed by biodegradation and biosorption. The different removal pathways of organic phosphorus and PO43−-P might account for the lower TP removal efficiency than that of PO43−-P. However, the chemically enhanced phosphorus removal section was non-essential in the subsequent B-stage. In conclusion, the low COD concentrations, high ammonia retained ratios, and excellent phosphorus removal confirmed that the effluent from the SBRS-SRT was adapted to the autotrophic nitrogen removal processes and the additional chemical phosphorus removal section was non-essential. 3.3. Abundance Variation of Functional Microbes Related to System Stability and Phosphorus Removal Sludge was sampled on day 0 (inoculum), day 21 (SRT10d1 and SRT5d), day 84 (SRT10d2 and SRT4d), and day 120 (SRT10d3 and SRT3d) from two operated experimental SBRs for high-throughput sequencing analysis, and the average length of OTU was 416 with a coverage above 99% in this study. The analysis of microbial diversity and community structure was conducted after data extraction flat. The indexes that reflected microbial diversity are shown in Table S3. Microbial diversity reduced compared with the WAS, indicating the reconstruction of microbial communities. The abundance of functional bacteria related to phosphorus removal and system stability is shown in Table 3 and the details of the bacteria with abundance higher than 1% are shown in Figure S2. The detected sequence numbers of the microbial related to nitrification are shown in Table S4. The key to maintaining the stability of an activated sludge process is to avoid sludge bulking. The enrichment of the filamentous bacteria was one of the most significant factors that caused sludge bulking. The excessive growth of Thiothrix, which is a typical filamentous bacterium, results in bulking the sludge in conventional activated sludge systems [21]. Thiothrix was detected in the short-sludge-age or ultra-short SRT EBPR systems reported by [13,15]. The abundance of Thiothrix was increased to 1.86% in SBRS-SRT after 120 d operation due to the shortening of SRT, but it remained stable and lower than 1% in the SBRcontrol. The disagreement between the enrichment of filamentous bacteria and the good settling ability of sludge in SBRS-SRT was mainly due to the relatively low abundance of Thiothrix (ranged as the twelfth most abundant bacteria in the sample SRT3d) and the quality of the influent. However, the results suggest that the SBRS-SRT had the risk of sludge bulking. Only a few sequences were detected and the sequence numbers of Nitrospira and norank_Nitrosomonadaceae were both zero in the samples SRT4d and SRT3d, as shown in Table S4. These dates suggest that the nitrifying bacteria were washed out from the SBRS-SRT completely, which is in agreement with the poor ammonia removal performance of SBRS-SRT. Tetrasphaera is an important PAO [22] and has a comparable contribution to phosphorus removal to Candidatus_Accumulibacter in the EBPR process [23]. Tetrasphaera was the dominant PAO in both the SBRS-SRT and SBRcontrol, while the abundances of Candidatus_Accumulibacter and Dechlorimonas [24] were lower than 0.5% in the collected samples. The abundance of Tetrasphaera in the sample collected from SBRS-SRT at SRT 3 d was almost seven times higher than the inoculum (6.29% vs. 0.81%). The shortening of SRT was beneficial for the enrichment of Tetrasphaera. The abundance of Tetrasphaera in the samples collected from the SBRcontrol decreased from 12.22% to 3.56% when the duration of the oxic phase extended from 2 h to 2.5 h. The extension of the oxic phase improved the ammonia removal that resulted in the enhanced competition of the carbon source between denitrification and phosphorus release in the anaerobic phase. This might cause the reduction in PAO Tetrasphaera. Hydrogenophaga [25,26] and Flavobacterium [27] were reported to have the function of phosphorus removal and were enriched in SBRS-SRT and SBRcontrol, respectively. The abundance of the main glycogen accumulating organisms (GAO) Candidatus_Competibacter [17] increased from 1.35% to 3.26% when the SRT was shortened from 4 d to 3 d. The wash-out of the nitrifying bacteria in the SBRS-SRT eliminated the competition between denitrification and phosphorus release processes in the anaerobic phase, which left a surplus carbon source that accelerated the enrichment of both GAOs and PAOs. However, the abundance of the PAOs was still significantly higher than the GAOs, which was in line with the excellent phosphorus removal performance of SBRS-SRT. 3.4. Methanogenic Efficiency of WAS from the Two SBRs The methane production and methanogenic efficiency of two AnSBRs (AnSBRcontrol and AnSBRS-SRT) treated WAS from the corresponding two SBR is demonstrated in Figure 4. The methanogenic efficiency of the AnSBRS-SRT treated WAS was significantly higher than the AnSBRcontrol. The WAS average methanogenic efficiency decreased from 166.7 ± 54.7 mL CH4/gSS to 136.0 ± 53.2 mL CH4/gSS when the SRT of SBRS-SRT shortened from 4 d to 3 d. This result was consistent with the decrease in MLVSS/MLSS ratios (from 60.2% to 54.0%), as previously discussed. However, the average methanogenic efficiency of the WAS collected from the SBRS-SRT (SRT 3 d) was 54.1% higher than the methanogenic efficiency of the WAS collected from the SBRcontrol (the oxic phase duration as 2.5 h), as shown in Table S5. As discussed above, the two SBRS achieved equivalent COD removal efficiency. Taking the increase in Yobs and comparable COD removal efficiency into an account, the methane recovery potential of SBRS-SRT at SRT 3 d was 95.1% higher than the SBRcontrol with the oxic phase duration as 2.5 h, according to Equations (2) and (3). The S-SRT approach was an effective and promising selection for the enhancement of energy recovery. 4. Conclusions Two EBPR SBR systems were set up to treat real domestic sewage and two AnSBRs were conducted to compare the methanogenic efficiencies of the generated (or collected) WAS from the two systems. A T-test was employed to evaluate the significant difference between the two SBRs at each stage. The SBRS-SRT achieved efficient and comparable COD, PO43−-P, and TP removal (p > 0.05) and the removal efficiencies were 91.5 ± 3.5%, 95.4 ± 3.8%, and 93.5 ± 3.7%, respectively, at a SRT of 3 d. The SBRS-SRT remained steady sludge settleability, which was comparable with the SBRcontrol (p > 0.05). The ammonia in sewage was retained with an ammonia removal efficiency of 15.7 ± 7.7% indicated the wash-out of nitrifiers in SBRS-SRT when the SRT was shorter than T4 d. The enrichment of Tetrasphaera and the stable abundance of filamentous bacteria were the source force that maintained the stability of the SBRS-SRT. The methanogenic efficiency increased by 95% when the SRT of SBRS-SRT was 3 d compared with SBRcontrol as its oxic phase duration was 2.5 h. This study proved that the S-SRT EBPR was a promising and practical A-stage selection that maximally utilized the biological phosphorus removal function when shifting a conventional WWTP into a “source and energy recovery factory” operated as an A-B stage process. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095494/s1. Text S1: Anaerobic sequential batch reactor (AnSBR) set-up and operation, Figure S1: schematic of the two experimental AnSBR, Figure S2: percent of microbial abundance on Genus level (abundance > 1%), Table S1: the average value of the indexes related to the sludge in the two experimental SBRs, Table S2: the average nutrients removal efficiencies of the two experimental SBRs, Table S3: variation of index related to the microbial diversity, Table S4: sequence number of microbial related to the nitrification process without data extrac-tion flat, Table S5: the average methane production and methanogenic efficiencies of the two experi-mental AnSBR. Click here for additional data file. Author Contributions Methodology, H.L. and B.Y.; formal analysis, H.L.; investigation, H.L. and C.X.; resources, W.G.; writing—original draft preparation, H.L.; writing—review and editing, W.G. and Q.Z.; project administration, W.G. and N.R.; funding acquisition, W.G. All authors have read and agreed to the published version of the manuscript. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Abbreviations Short sludge retention time S-SRT Anaerobic digestion AD Sequencing batch reactors SBR Mixed liquor volatile suspended solids MLVSS Wastewater treatment plants WWTPs Mixed liquor suspended solids MLSS Enhanced biological phosphorus removal EBPR Anaerobic SBR AnSBR Anaerobic/anoxic–oxic AO Polyethersulfone PES Anaerobic–anoxic–oxic AAO Methanogenic efficiency MP Polyphosphate accumulating organisms PAOs Total methane recovery potential MPtotal Sludge volume index SVI Ammonia oxide bacterial AOB Total phosphorus TP Glycogen accumulating organisms GAO Waste activated sludge WAS Figure 1 Schematic of the experimental SBR. Figure 2 Variations of the sludge (a) MLSS and (b) MLVSS concentrations, (c) SV30 and (d) SVI in the two experimental SBRs and the accumulated WAS discharge of (e) SBRcontrol and (f) SBRS-SRT. Figure 3 Performances of the two experimental SBRs on (a) COD, (b) NH4+-N, (c) PO43− -P, and (d) TP removal. Figure 4 The anaerobic digestion performance of the two experimental AnSBRs (a). methane production, (b) methanogenic efficiency. ijerph-19-05494-t001_Table 1 Table 1 Characteristics of the sewage used in this study. Characters COD mg/L NH4+-N mg/L PO43−-P mg/L TP mg/L pH Ranges 213.3–773.3 39.2–84.9 2.9–6.2 3.7–6.7 7.1–7.5 Average values 477.8 ± 124.4 59.6 ± 7.1 4.1 ± 0.6 5.1 ± 0.8 7.2 ± 0.2 ijerph-19-05494-t002_Table 2 Table 2 Operation strategies of the two experimental SBRs. Reactor Parameters Stage I (0–21 d) Stage II (22–84 d) Stage III (85–120 d) SBRcontrol Anaerobic (h) 2.5 2.5 2.0 Oxic (h) 1.5 1.5 2.0 SRT (d) 10 10 10 Aeration (L/min) 0.8 0.8 0.8 SBRS-SRT Anaerobic (h) 2.5 2.5 2.5 Oxic (h) 1.5 1.5 1.5 SRT (d) 5 4 3 Aeration (L/min) 0.8 0.8 0.8 ijerph-19-05494-t003_Table 3 Table 3 Functional genera related to phosphorus removal and system stability. Genera Inoculum SRT 10 d1 SRT 10 d2 SRT 10 d3 SRT 5 d SRT 4 d SRT 3 d PAOs Tetrasphaera 0.81 4.28 12.22 3.56 3.43 4.60 6.29 Flavobacterium 0.27 0.45 1.5 1.76 0.54 0.06 0.16 Hydrogenophaga 0.02 0.02 - 0.01 1.65 0.79 1.55 Dechloromonas 0.21 0.22 0.05 0.11 0.02 0.03 0.04 Candidatus_ Accumulibacter - 0.01 0.09 0.04 0.06 0.04 0.04 GAOs Candidatus_ Competibacter 0.42 1.28 4.97 4.23 3.49 1.35 3.26 Filamentous bacteria Thiothrix 0.03 0.04 0.07 0.05 0.08 0.79 1.86 Relative abundance of the functional genera, percent. 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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092105 cancers-14-02105 Review Overcoming Therapy Resistance in Colon Cancer by Drug Repurposing https://orcid.org/0000-0002-4507-2396 El Zarif Talal 1† Yibirin Marcel 2† De Oliveira-Gomes Diana 3 Machaalani Marc 1 https://orcid.org/0000-0001-5428-5660 Nawfal Rashad 1 https://orcid.org/0000-0001-5343-9015 Bittar Gianfranco 4 Bahmad Hisham F. 5* Bitar Nizar 67 Sterpetti Antonio V. Academic Editor 1 Faculty of Medicine, Lebanese University, Beirut 1003, Lebanon; talalelzarif@gmail.com (T.E.Z.); m.machaalani@st.ul.edu.lb (M.M.); rn107@aub.edu.lb (R.N.) 2 Internal Medicine Residency Program, Department of Medicine, Boston University Medical Center, Boston, MA 02218, USA; marcel.yibirinwakim@bmc.org 3 Department of Research, Foundation for Clinic, Public Health, and Epidemiological Research of Venezuela (FISPEVEN), Caracas 1050, Venezuela; dianacdeoliveirag@gmail.com 4 Baylor St. Luke’s Medical Center, Houston, TX 770030, USA; gianfrancobittar@gmail.com 5 The Arkadi M. Rywlin M.D. Department of Pathology and Laboratory Medicine, Mount Sinai Medical Center, Miami Beach, FL 33140, USA 6 Head of Hematology-Oncology Division, Sahel General Hospital, Beirut 1002, Lebanon; nbitar@sahelhospital.com.lb 7 President of the Lebanese Society of Medical Oncology (LSMO), Beirut 1003, Lebanon * Correspondence: hisham.bahmad@msmc.com; Tel.: +1-786-961-0216 † These authors contributed equally to this work. 23 4 2022 5 2022 14 9 210516 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/). Simple Summary Despite improvements in standardized screening methods and the development of promising therapies for colorectal cancer (CRC), survival rates are still low. Drug repurposing offers an affordable solution to achieve new indications for previously approved drugs that could play a protagonist or adjuvant role in the treatment of CRC. In this review, we summarize the current data supporting drug repurposing as a feasible option for patients with CRC. Abstract Colorectal cancer (CRC) is the third most common cancer in the world. Despite improvement in standardized screening methods and the development of promising therapies, the 5-year survival rates are as low as 10% in the metastatic setting. The increasing life expectancy of the general population, higher rates of obesity, poor diet, and comorbidities contribute to the increasing trends in incidence. Drug repurposing offers an affordable solution to achieve new indications for previously approved drugs that could play a protagonist or adjuvant role in the treatment of CRC with the advantage of treating underlying comorbidities and decreasing chemotherapy toxicity. This review elaborates on the current data that supports drug repurposing as a feasible option for patients with CRC with a focus on the evidence and mechanism of action promising repurposed candidates that are widely used, including but not limited to anti-malarial, anti-helminthic, anti-inflammatory, anti-hypertensive, anti-hyperlipidemic, and anti-diabetic agents. colorectal cancer therapy resistance drug repurposing in silico drug screens ==== Body pmc1. Introduction Colorectal cancer (CRC) is the third most prevalent cancer in the world, with more than 100,000 new cases and 50,000 deaths occurring in the United States during 2021 [1]. It is the third most common cancer in both sexes and the second most common cancer-related mortality cause [2]. It is projected that there will be an overall doubling of CRC cases in the following decades [3], with an estimated worldwide increase to 2.5 million new cases in 2035 [4]. In countries with a high human development index, the incidence and mortality rates of CRC have decreased predominantly in older adults, while in lower- and middle-income countries, mortality is increasing [2]. There is a growing incidence of CRC in younger groups, likely attributed to a high prevalence of certain risk factors such as poor diet, low physical activity, and higher rates of obesity [2]. Most CRCs arise from neoplastic polyps as stem cells progressively acquire genetic and epigenetic alterations [4]. Chromosomal instability, mismatch repair deficiency, and CpG hypermethylation underline the pathogenesis of CRC [5]. Significant molecular heterogeneity with altered mismatch repair mechanisms leading to microsatellite instability in BRAF-mutated sessile serrated adenomatous polyps and adenocarcinomas increase after 85 years of age [6]. Sporadic CRC accounts for 70% of new cases, usually following a specific succession of mutations in the adenomatous polyposis coli (APC) gene, followed by KRAS, TP53, and DCC mutations [7]. Familial cases correspond to approximately 25% of cases, and 5% occur in well-defined hereditary CRC syndromes such as familial adenomatous polyposis and Lynch syndrome [7]. The stage of the CRC at the time of diagnosis is crucial in determining survival. While the 5-year survival is approximately 90% for patients with stage I disease, in stage IV it decreases to less than 10%, highlighting the importance of early detection [8]. For localized early-stage CRC, surgery is the standard therapy [5]. In patients with stage II CRC with a high risk of recurrence after surgery or stage III disease (lymph node metastases), adjuvant chemotherapy using oxaliplatin and irinotecan in addition to 5-fluorouracil (5FU) or Capecitabine is used [9]. Targeted therapies, including monocolonal antibodies against VEGF (bevacizumab) or EGFR (cetuximab or panitumumab) are used in the metastatic setting in combination with chemotherapy depending on RAS mutational status and tumor location (left vs. right) [9,10]. In addition, immunotherapy has proven to be an effective treatment modality in the setting of microsatellite instability (MSI) high CRC [10]. For patients with unresectable lesions, treatment is a combination of maximum tumoral cytoreduction and chemotherapy [11]. Despite the advances in treatment, advanced disease remains to be associated with poor survival and resistance to cytotoxic and targeted chemotherapies is still occurring [12]. 2. Repurposing Approved Drugs in Colon Cancer Drug repurposing or repositioning involves using approved drugs for conditions different from their original indication [13,14,15]. Several drugs have acquired additional use in the past years and have been reintroduced into practice fueled by this phenomenon. For instance, thalidomide, discontinued from its original use as an antiemetic, is currently used for multiple myeloma [16] and moderate to severe erythema nodosum leprosum [17]. Another example is Sildenafil which preserves both its primary indication for erectile dysfunction [18] and repurposed indication as a treatment option for idiopathic pulmonary hypertension [19]. Drug repurposing has regained a significant role as a convenient, fast, and relatively safe drug development strategy. New drug development usually takes around 10–15 years on average [20], with a success rate reported from 2 to 10% [21,22]. According to the U.S. Food and Drug Administration (FDA), as of 2018, the compound percentage of drugs reaching stage 4 clinical trials was around 6% [23]. Drug repurposing offers significantly shorter development times and lower investments described as 160 million times lower, particularly costs regarding safety testing, molecular characterization, safety profiling, and initial marketing. It leverages known genetic, pharmacodynamic, pharmacokinetic, and adverse effect profiles, usually bypassing stage 1 clinical trials [24]. Therefore, this approach represents a more cost-efficient, expedited, and less risky strategy than traditional drug development [21]. Many successful reintroductions and alternative indications second repurposing as a feasible option in many areas of medicine. Aspirin, for example, has acquired a wide range of indications, ranging from acutely therapeutic to prolonged preventative ones [14,25]. The cardiovascular field further illustrates this diversity with the recent supportive evidence of SGLT-2 inhibitors, initially approved for hyperglycemia management, for heart failure management regardless of the patients’ ejection fraction and notwithstanding their diabetes status [26,27,28,29]. Therapeutics for Alzheimer’s disease have been highly reliant on this strategy. Since memantine in 2003, no new drugs had been approved until the FDA granted the recent fast track concession for aducanumab in 2021 [14,30]. As of 2017, approximately 27 FDA-approved drugs were being evaluated for Alzheimer’s disease in stages 1–3 clinical trials [14]. Oncology has also gained benefits from drug repurposing. Estimation is that 5% of the anticancer drugs entering phase 1 clinical trials are eventually approved [31]. Certain calcium channels blockers such as felodipine and amlodipine besylate undermine filopodia stability in cancer cells, decreasing the likelihood of progression, invasion, and metastasis [32]. Metformin, classically an antidiabetic drug, has been described to decrease tumor growth. Although metabolic reprogramming halting oxidative phosphorylation and multi-targeted mTOR inhibition have hypothesized metformin’s antitumoral activity, precise mechanisms remain obscure [21,33,34]. The benefits of drug repurposing are evident after their serendipitous discovery and raise interest in predictive tools to optimize outcomes. Many approaches group together into either experimental or computational models [24,35]. The former usually involves either in vitro analysis measuring affinity and interaction stability, also called binding assays, or combined in vitro/in vivo models using compound libraries to test for cellular lineage changes, known as the phenotypic model. The phenotypic approach aims to reproduce diseases in an experimental cellular environment and relies on known compound libraries to test and characterize cellular responses [24]. Alternatively, known compounds have been assessed using in silico models stemming from structure-based principles: direct molecular docking, inverse molecular docking, and receptor-based pharmacophore searching [36]. Drug-based strategies use established drug information such as pharmacodynamics, biochemical, adverse effect profiles, and genomic data to determine potential alternative uses. Transcriptomics data are especially valuable to depict deviant cellular responses to diverse pathologic states, notably those with solid genetic pathomechanisms. Conversely, knowledge-based strategies use well-characterized molecular disease mechanisms to depict candidates for drug repurposing [35]. Large genetic and disease datasets are becoming publicly available, and computational tools for processing massive data are evolving accordingly. Computational-based drug repurposing uses data mining, machine learning, and network analysis to distill large datasets involving disease-specific transcriptomics, proteomics, drug efficacy, responses, and even clinical variables [35]. This information provides insight into complex biologic processes such as epigenetic regulation in cancer cells. Furthermore, drug repurposing approaches may be used for epigenetic reprogramming of cancer cells to increase susceptibility via differential transcriptome expressions. A study characterized 45 FDA-approved drugs yielding synergistic activity with histone deacetylating agents and methylation inhibitors. Additionally, they characterized 85 FDA-approved medications that antagonized the action of these drug families, thwarting favorable responses in colon cancer cells. Altogether, these findings illustrate the benefits and complexity of drug repurposing to design personalized and highly effective treatment plans that account for previously unknown drug interactions [37] (Table 1). 2.1. Anti-Hypertensives and Anti-Arrhythmic Drugs Angiotensin I converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are commonly used drugs that have life-prolonging effects on patients treated for several diseases including but not limited to hypertension and heart failure [90]. An in vivo study by Kubota et al. suggested that both ACEIs and ARBs suppress colitis-induced CRC by decreasing chronic inflammation and oxidative stress in obese mice [38]. In another study by Kedika et al., patients who had one or more histologically confirmed adenomatous polyps on an index colonoscopy and received lisinopril—an ACEI—had a 41% reduction in the risk of developing similar polyps over the next 3–5 years [39]. Beta blockers (BB) are class II antiarrhythmic drugs used primarily to treat cardiovascular diseases and many other conditions [91]. In a study by Tapioles et al., Nebivolol was shown to selectively inhibit mitochondrial respiration in an HCT-116 colon cancer cell line by decreasing the activity of complex I of the respiratory chain and restraining the growth of colon cancer cells, hinting towards a repurposing potential for this drug in colon cancer [40]. Furthermore, Engineer et al. demonstrated that the combination of ACEI/ARB with BB was associated with increased survival, decreased hospitalization, and decreased tumor progression in advanced CRC [92]. 2.2. Nonsteroidal Anti-Inflammatory Drugs Nonsteroidal anti-inflammatory drugs (NSAIDs) employ their anti-inflammatory, analgesic, and antipyretic properties by inhibiting the cyclooxygenase (COX) enzymes [93]. COX-2 overexpression is a major risk factor for the development of CRC [94]. The therapeutic effect of aspirin in CRC can be explained by inhibition of COX-2 as well as the c-MYC transcription factor [41,42]. Furthermore, aspirin blocks platelet activity which is implicated in cancer metastasis and immune evasion [43]. However, Chan et al. argued that aspirin must be used for more than 10 years to achieve a statistically significant reduction in COX-2 positive cancer [44]. Celecoxib works by selectively and reversibly inhibiting COX-2, and thus acts to decrease inflammation and pain without affecting platelets [95]. Many studies concluded that celecoxib increases radiosensitization of CRC cells [96,97]. Celecoxib also affects p53 by regulating the expression of p21 and CyclinD1 in a COX-2-independent manner, by upregulating BCCIP, increasing radiosensitivity in the HCT116 CRC cell line [45]. A randomized controlled trial by Bertagnolli et al. showed that celecoxib was effective for the secondary prevention of colorectal adenomas and decreased the cumulative incidence of adenomas after 3 years from 60.7% in the placebo arm to 43.2% in patients receiving 200 mg of celecoxib twice daily [46]. 2.3. Anti-Hyperlipidemic Drugs Statins markedly inhibit HMG-CoA reductase, the enzyme that controls the rate-limiting step in the cholesterol synthesis pathway in the liver [98]. Remarkably, in a large study including 1953 patients with CRC and 2015 controls, the use of statins for at least 5 years was associated with a significantly reduced relative risk of developing CRC (odds ratio (OR) = 0.50; 95% confidence interval (CI), 0.40–0.63) [99]. In vivo, lovastatin was shown to restrict cancer progression and metastasis formation by inhibiting MACC1 [47]. In a large meta-analysis including a total of 31 studies and involving more than 1.6 million subjects, statins were shown to have a moderate protective effect against developing CRC [48]. 2.4. Anti-Diabetic Drugs Metformin, an oral anti-diabetic medication used for type 2 diabetes mellitus, is a biguanide drug that increases insulin sensitivity, decreases intestinal absorption of glucose, and decreases its production by the liver [100]. Previous studies have shown a protective effect of metformin in CRC risk and prognosis [101,102]. The current understanding is that metformin inhibits the mammalian target of rapamycin (mTOR) pathway which plays a central role in CRC cell growth and proliferation [49]. Furthermore, metformin downregulates IGF receptor activation through decreasing insulin and insulin growth factor, resulting in decreased proliferation in colorectal neoplasia [103,104]. Inhibition of mTOR is achieved through inhibition of mitochondrial mammalian respiratory chain complex I followed by activation of liver kinase B1 and downstream target Adenosine monophosphate-activated protein kinase (AMPK) [50,51]. Other research has shown that metformin, through modulation of oxidative stress and nuclear factor-κB (NF-κB) inflammatory responses would induce apoptosis in CRC cell lines [52,53]. Metformin may also increase sensitivity of cancer cell lines to chemotherapeutic agents such as 5-Fluorouracil, irinotecan, and paclitaxel [105,106,107]. Dapagliflozin, another oral antihyperglycemic medication used for type 2 diabetes mellitus works by inhibiting the sodium/glucose cotransporter 2 (SGLT2) in the proximal tubules of the kidney [108]. Dapagliflozin decreases the adhesion of CRC cells by affecting cellular interaction with Collagen types I and IV through activating ADAM10, which subsequently causes a loss in the full-length DDR1 [54]. DDR1 binding to Collagens I and IV is necessary to stimulate cell–collagen interactions [109]. Dapagliflozin also decreases colon cell proliferation by increasing Erk phosphorylation in the HCT116 human colon cancer cell line [55]. In a case report by Okada et al., SGLT2 inhibition in combination with the EGFR inhibitor, cetuximab, reduced both tumor size and carcinoembryonic antigen (CEA) levels in CRC with liver metastasis [110]. 2.5. Anti-Helminthic Drugs Mebendazole is a broad spectrum benzimidazole that inhibits microtubule synthesis by blocking tubulin polymerization [111]. Mebendazole has cytotoxic activity against different CRC cell lines such as HCT-116, RKO, HT-29, HT-8, and SW626 [56,112]. Nygren and Larsson reported that mebendazole induced remission of metastatic lesions in a patient with refractory metastatic CRC [113]. Another study carried out on mice with a constitutional mutation in the Adenomatous polyposis coli (APC) gene showed that the combination of mebendazole and sulindac (an NSAID) decreased both the number and size of intestinal microadenomas by inhibiting MYC and COX-2 pathways, angiogenesis, and the release of pro-tumorigenic cytokines [57]. Niclosamide is a salicylamide derivative that acts by uncoupling oxidative phosphorylation and regulating different signaling pathways [114]. Niclosamide downregulated the Wnt/β-catenin cascade, which is aberrantly activated in 80% of sporadic CRC [115], in both in vitro and in vivo studies [58] and resulted in decreased proliferation in multiple human CRC cell lines such as HCT-116, Caco2, and HT-29 [59], possibly via the induction of autophagy [116]. Furthermore, a recent study by Kang et al. demonstrated that niclosamide could be combined with metformin to synergistically inhibit APC-mutant CRC by suppressing Wnt and YAP [117]. 2.6. Anti-Retroviral Drugs Tenofovir is a nucleoside antiretroviral drug that acts by inhibiting the reverse transcriptase enzyme [118]. Tenofovir also inhibits the activity of human telomerase [119], a crucial enzyme for tumorigenesis and cancer proliferation, whose inhibition represents a promising therapeutic strategy in cancer treatment [120,121]. Sherif et al. demonstrated that rats receiving tenofovir at a dose of 50 mg/kg for 24 weeks had diminished colorectal cell proliferation attributed to decreased Bcl-2 and cyclin D1 expression [60]. Zidovudine, also known as azidothymidine, is another nucleoside reverse transcriptase inhibitor (NRTI) used in the treatment of human immunodeficiency virus (HIV) [122]. Brown et al. demonstrated Zidovudine’s telomerase inhibition activity in the HT-29 colon cancer cell line [61]. Furthermore, Fang et al. showed that the antitumor activity of zidovudine in colon cancer cells is mediated by increased expression of the p53-Puma/Bax/Noxa pathways favoring apoptosis, and activation of the p53-p21 pathway promoting cell cycle arrest [62]. Efavirenz is a non-nucleoside reverse transcriptase inhibitor (NNRTI) used in the treatment of HIV that is selectively cytotoxic to different tumor cell lines, including colorectal carcinoma, by activating the phosphorylation of p53 [63]. Protease inhibitors (PI) are also drugs that suppress the action of HIV proteases to inhibit viral growth, infectivity, and replication [123]. Indinavir and Saquinavir are PI that suppress the growth of human tumor cells by blocking angiogenesis and matrix metalloproteinases to inhibit tumor invasion and progression. [64]. Furthermore, Mühl et al. reported that Ritonavir synergizes with butyrate to induce apoptosis of CRC cells [66]. The anticancer effect of Ritonavir is most likely due to the inhibition of proteolytic degradation, which causes the accumulation of p21 [68], the decreased production of TNF-α, IL-6, IL-8, and VEGF [67], and the increased expression of anti-inflammatory heme oxygenase-1 [66]. Integrase inhibitors are the latest class of antiretroviral drugs which were approved for HIV therapy due to their efficacy, tolerability, and safety [124]. Raltegravir is an integrase inhibitor that inhibits the Fascin-1-dependent invasion of colorectal tumor cells in vitro and in vivo [69]. Fascin-1 is an actin cross-linking protein whose elevated expression is associated with aggressive clinical progression, dismal prognosis, increased recurrence, and worse survival outcomes in patients with CRC [125,126]. 2.7. Anti-Microbials Other anti-microbial drugs have been investigated for repurposing in colon cancer treatment including doxycycline, a semi-synthetic antibiotic derivative of tetracycline used in the treatment of a wide variety of infections [127]. Doxycycline has also been shown to inhibit matrix metalloproteinases [128]. Onoda et al. demonstrated that a combination therapy consisting of doxycycline and a COX-2 inhibitor suppressed colon cancer cell proliferation and invasion [71]. Doxycycline reportedly induced apoptosis in a dose-dependent manner through activation of caspases, release of cytochrome C, and translocation of Bax [70]. Another antibiotic with potential in cancer therapeutics is clarithromycin. Clarithromycin is a potent inhibitor of tumor-induced angiogenesis [73] showing increased efficacy when combined with approved anticancer drugs [72,75,129]. It is also implicated in attenuating autophagy in myeloma cells [130]. Targeting autophagy is considered a promising strategy for colon cancer therapy [131,132]. In a study by Petroni et al., clarithromycin was indeed shown to modulate autophagy in human CRC cells and inhibited the growth of tumors by targeting hERG1 [74]. The inhibition of autophagy as a mechanism of anticancer activity is also shared by azithromycin, another macrolide antibiotic [76,77]. Qiao et al. demonstrated that azithromycin had a synergistic antitumor activity with the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in colon cancer cells. Azithromycin may also suppress autophagy by upregulating the expression of p62 and LC-3B to ultimately induce colon cancer cell death [78]. Gemifloxacin is a fluoroquinolone used in the setting of community-acquired pneumonia and acute exacerbations of chronic bronchitis [133]. Kan et al. demonstrated that gemifloxacin inhibits the migration and invasion of SW620 and LoVol colon cancer cells and downregulates Snail to reduce epithelial-to-mesenchymal transition (EMT). Gemifloxacin also suppresses the NF-κB pathway and cytokine-mediated cell migration and invasion as shown by decreased levels of tumor necrosis factor alpha (TNF-alpha), interleukin 6 (IL-6), IL-8, and vascular endothelial growth factor (VEGF) [79]. Antimalarials are also being considered for the treatment of colon cancer. Artesunate is an antimalarial agent recommended for the treatment of patients with severe Plasmodium falciparum malaria [134]. In a preclinical model of CRC, artesunate was found to suppress inflammation and oxidative stress [81]. Efferth et al. demonstrated a cytotoxic action of artesunate on tumor cells via both p53-dependent and -independent pathways [135] implicated in downregulation of β-catenin [80]. Mefloquine, another antimalarial drug, was found to induce growth arrest and apoptosis of CRC cells in mice via inhibition of the tumor NF-κB signaling pathway [82]. 2.8. Others Drugs used for neurological conditions are increasingly being considered as therapeutic options in cancer patients [136,137]. Friedmann et al. demonstrated that valproate, a histone deacetylase inhibitor (HDACi), dose-dependently reduced the viability of adenocarcinoma cell lines, particularly when combined with mitomycin C [138]. Additionally, in a study by Mologni et al., valproate was found to enhance bosutinib cytotoxicity in colon cancer cells [139]. This may be explained by increasing histone hyperacetylation of H3 and H4 to enhance antitumor activity and by relieving HDAC-driven transcriptional repression [83,140]. Fluoxetine is a selective serotonin reuptake inhibitor (SSRI) that is used in the treatment of major depressive disorder [141]. In a study examining murine colitis-associated colon cancer, fluoxetine was found to inhibit NF-κB activation and decrease TNF-α-mediated IκB kinase (IKK) and IκBα phosphorylation; thus suppressing dextran sulfate sodium (DSS)-induced colitis and colitis-associated tumorigenesis [84]. Furthermore, Kannen et al. studied the antiproliferative effects of fluoxetine on HT29 colon cancer cells. Fluoxetine increased the percentage of HT29 cells in the G0/G1 phase of the cell cycle and enhanced the expression of p27 protein. Fluoxetine also suppressed the development of dysplasia and vascularization-related dysplasia in colon tissue, and reduced VEGF expression and the number of cells with angiogenic potential, such as CD133, CD34, and CD31-positive cell clusters [85]. Sirolimus, also known as Rapamycin, is an FDA-approved mTOR inhibitor used in the prophylaxis of renal graft rejection [142]. Mussin et al. demonstrated that a combination of sirolimus and metformin synergistically inhibits colon tumor growth both in vitro and in vivo [86]. He et al. revealed that mTOR inhibitors induce apoptosis in colon cancer cells via CHOP-dependent DR5 induction of 4E-BP1 dephosphorylation resulting in decreased tumor proliferation, angiogenesis, and invasion [88]. In addition, Wang et al. demonstrated that sirolimus suppresses the FBXW7-loss-driven EMT through its mTOR inhibition activity, thereby decreasing CRC cell migration and invasion [87]. Finally, it is worth noting that probiotics have also been considered for the treatment of CRC. For instance, Hu et al. found that butyrate decreased the transcription of the pro-proliferative miR-92a in human CRC cells [89]. Furthermore, butyrate can also induce apoptosis of DLD-1 colon cancer cells by synergizing with ritonavir [66]. 3. Clinical Trials on Drug Repurposing in Colon Cancer Despite the heterogeneity of potential drugs that can be repurposed, only a few collectively form the most promising treatments for CRC and have been incorporated in clinical trials. A brief overview of the mechanism of action of these drugs is summarized in Figure 1. Aspirin is the most represented drug in current clinical trials investigating candidate drugs for repurposing in the treatment of CRC (Table 2). One phase 3 clinical trial involves the use of aspirin as an adjuvant component in stages II and III PIK3CA-mutated colon cancer patients. The trial aims to determine whether the daily consumption of 100 mg of aspirin is effective in reducing recurrence and improving survival compared to placebo (ClinicalTrials.gov; NCT02467582). Two similar phase 3 clinical trials aim to determine the effect of 80 mg daily adjuvant aspirin on survival in stages II and III colon cancer patients compared to placebo (ClinicalTrials.gov; NCT02301286 and NCT03464305). ASPIK French is another phase 3 clinical trial whose goal is to determine local or distant recurrence or second CRC or death from any cause, whichever occurs first, in patients with surgically resected PI3K-mutated colon cancer taking 100 mg of daily aspirin as compared to placebo (ClinicalTrials.gov; NCT02945033). Finally, the ASCOLT phase 3 clinical trial is studying the 5-year disease-free and overall survival in patients with Dukes C or high-risk Dukes B CRC taking 200 mg daily aspirin for 3 years (ClinicalTrials.gov; NCT00565708). NSAIDs are also among the drugs currently under study for repurposing in CRC therapeutics. For instance, the NICHE phase 2 clinical trial involves the administration of celecoxib along with nivolumab and ipilimumab for stages I to III colon cancer in the neoadjuvant setting. The adverse effects will be assessed to determine the regimen’s safety (ClinicalTrials.gov; NCT03026140). Mebendazole, an anti-helminthic drug, is being tested in a phase 3 clinical trial for its use as an adjuvant component to FOLFOX with Bevacizumab in stage IV CRC patients (ClinicalTrials.gov; NCT03925662). Furthermore, MECORA is a phase 2 clinical trial which aims to examine the effect of metformin in non-diabetic patients with colon cancer where metformin will be administered before and after colon cancer surgery (ClinicalTrials.gov; NCT03359681). A phase IB clinical trial aims to assess the safety of the antimalarial hydroxychloroquine along with Axitinib and hepatic chemoembolization in subjects with liver dominant metastatic CRC (ClinicalTrials.gov; NCT04873895). Finally, a dose-finding phase 1/2 clinical trial is studying the safety and recommended phase 2 dose (RP2D) of the combination of neratinib and sodium valproate in patients with advanced solid tumors, including RAS-mutated CRC patients (ClinicalTrials.gov; NCT03919292). 4. Conclusions and Future Directions Despite the advances in oncology, cancer continues to be one of the leading causes of morbidity and mortality worldwide. CRC has the third highest mortality rate of all cancers, with poor survival rates in many groups. Moreover, CRC cases are expected to increase dramatically in the following decades [3]; this is why finding effective treatments for these patients is crucial. Developing new drugs and translating them into clinical practice from phases 1 to 3 is very long and expensive, with only 5% of oncology drugs resulting in FDA approval [33]. For this reason, drug repurposing has gained more interest as a fast and safe way to achieve better outcomes since the pharmacokinetic, pharmacodynamic, and toxicity profiles of these drugs are already established. The investigation of previously approved drugs with other indications for CRC treatment should identify new effective therapies with lower costs and shorter timelines. Many FDA-approved drugs for infectious, cardiovascular, metabolic, and other diseases are currently studied as possible cancer therapies. It is important to highlight that the heterogeneity of cancer physiology and response to therapy and the multiple resistance mechanisms these cells develop represent an enormous challenge in oncology. The combination of computational frameworks (translational bioinformatics, computational intelligence, and methodological and systems biology) in multidisciplinary teams has successfully sped up clinical trials for repurposing drugs [143]. The emergence of new technologies in this field, such as large-scale multi-omics sequencing, genome-wide positioning systems network (GPSnet) algorithms, and other artificial intelligence algorithms, has helped identify new targets for older drugs [144]. The tools have matured, and novel technological advancements have enabled the identification of drugs that are suitable for repurposing. Pushpakom et al. elegantly highlighted the recent ongoing drug repurposing strategies [145]. In the era of big data, computational-based approaches will be a driving force in this field. These strategies range from mapping drug-binding sites and implicated downstream pathways to developing correlative signatures of transcriptomic and genetic data and their integration with clinical databases [145]. These approaches can help narrow down the list of candidate drugs that can be used for repurposing [146]. Nevertheless, experimental strategies relying on large-scale drug testing using in vitro and in vivo models remain to be an essential bridge to early phase clinical trials [145,147]. However, there are several limitations that might have rendered efforts in drug repurposing unsuccessful. Currently available drugs are approved at specific dosages to treat specific conditions. It is unknown whether these drugs are effective in treating other conditions such as CRC and whether different pharmacodynamic and pharmacokinetic properties are required for their activity in this setting [148]. Clinical trials are crucial to answer these questions; however, funding efforts have remained to be important obstacles as well as regulatory and organizational hurdles [149]. Despite that, not all trials translate into a clinical benefit which has recently been observed during the COVID-19 pandemic where a lot of negative trials have been reported [150]. This may be due to poorly designed trials or due to the fact that in vitro effects observed are simply not always translated into clinical benefit in larger groups of patients [150,151]. In conclusion, the overall impact of repurposing drugs must be studied in terms of survival and other aspects such as toxicity and side effects. Although the success rate is not so high, this is a promising strategy that must be deeply studied to provide new therapies for patients with CRC. Drugs that are currently being tested in clinical trials including but not limited to metformin, mebendazole, aspirin, celecoxib, and valproic acid are promising candidate drugs that might have substantial benefit in the CRC clinic. Acknowledgments Figures were created with BioRender.com accessed on 15 April 2022. Author Contributions Conceptualization, T.E.Z., M.Y., H.F.B. and N.B.; methodology, T.E.Z., M.Y., D.D.O.-G., M.M., R.N., G.B., H.F.B. and N.B.; validation, H.F.B. and N.B.; data curation, T.E.Z., M.Y., D.D.O.-G., M.M., R.N., G.B. and H.F.B.; writing—original draft preparation, T.E.Z., M.Y., D.D.O.-G., M.M., R.N., G.B. and H.F.B.; writing—review and editing, T.E.Z., H.F.B. and N.B.; visualization, N.B.; supervision, N.B.; project administration, H.F.B.; funding acquisition, H.F.B. 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 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 Mode of action of candidate repurposed drugs being tested in clinical trials for patients with CRC. HDAC: Histone Deacetylase; TNIK: TRAF2 And NCK Interacting Kinase; COX: Cyclo-oxygenase; mTOR: mammalian Target of Rapamycin. Adapted from “Round-Cell Background”, by BioRender.com (2022). Retrieved from https://app.biorender.com/biorender-templates accessed on 15 April 2022. cancers-14-02105-t001_Table 1 Table 1 Summary table of the drugs that have been repurposed to be used in colon cancer. Reference Drug Original Indication Possible Mode(s) of Action Effect(s) [38,39] ACEIs/ARBs Hypertension Decreased chronic inflammation and oxidative stress Reduced risk of adenomatous colon polyps [40] Nebivolol Hypertension and other indications Inhibition of mitochondrial respiration by decreasing the activity of Complex I of the respiratory chain Suppressed the growth of colon cancer cells [41,42,43,44] Aspirin Antiplatelet Inhibition of COX-2, c-MYC transcription factor, and the antiplatelet mechanism of action Decreased cancer metastasis and immune evasion [45,46] Celecoxib Anti-inflammatory Effect on p53 by regulating the expression of p21 and CyclinD1 in a COX-2-independent manner Upregulation of BCCIP Increased radiosensitivity in HCT116 cell line Decreased incidence of adenomatous polyps. [47,48] Lovastatin Antilipidemic Inhibition of MACC1 Restricted cancer progression and metastasis formation [49,50,51,52,53] Metformin Antihyperglycemic Inhibition of mTOR Modulation of oxidative stress and nuclear factor-κB inflammatory responses Apoptosis in CRC cell lines [54,55] Dapagliflozin Antihyperglycemic Effect on cellular interaction with Collagen types I and IV Increased Erk phosphorylation Decreased adhesion and proliferation of colon cancer cells [56,57] Mebendazole Anti-helminthic Inhibition of MYC Cytotoxic activity against different colon cancer cell lines [58,59] Niclosamide Anti-helminthic Downregulation of the Wnt/β-catenin cascade Decreased proliferation in multiple human CRC cell lines [60] Tenofovir Anti-retroviral (anti-HIV drug) Decreased Bcl-2 and cyclin D1 expression Inhibition of proliferation, oxidative stress, and inflammation [61,62] Zidovudine Anti-retroviral (anti-HIV drug) Increased expression of the p53-Puma/Bax/Noxa pathways Activation of the p53-p21 pathway Apoptosis Cell cycle arrest [63] Efavirenz Anti-retroviral (anti-HIV drug) Activation of the phosphorylation of p53 Cytotoxic activity against different colon cancer cell lines [64] Indinavir Anti-retroviral (anti-HIV drug) Proteasome-independent block of angiogenesis and matrix metalloproteinases Suppressed growth [64,65] Saquinavir Anti-retroviral (anti-HIV drug) Proteasome-independent block of angiogenesis and matrix metalloproteinases Inhibition of proteolytic degradation and accumulation of p21 Apoptosis Suppressed growth [66,67,68] Ritonavir Anti-retroviral (anti-HIV drug) Inhibition proteolytic degradation and accumulation of p21 Decreased production of TNF-α, IL-6, IL-8, and VEGF Increased expression of heme oxygenase-1 Apoptosis Suppressed angiogenesis [69] Raltegravir Anti-retroviral (anti-HIV drug) Blockage of fascin-1 Suppressed invasion [70,71] Doxycycline Antibiotic Inhibition of matrix metalloproteinases Activation of caspase-3, -8, and -9 Release of cytochrome c and Bax translocation Apoptosis Suppressed proliferation and invasive potential [72,73,74,75] Clarithromycin Antibiotic Inhibition of autophagy by targeting hERG1 Suppressed angiogenesis Suppressed growth of colon cancer cells [76,77,78] Azithromycin Antibiotic Inhibition of autophagy by upregulating p62 and LC-3B Apoptosis [79] Gemifloxacin Antibiotic Inhibition of NF-κB activation Inhibition of TNF-α, IL-6, IL-8, and VEGF Suppressed cell migration and invasion [80,81] Artesunate Antimalarial Downregulation of β-catenin Apoptosis Cytotoxicity [82] Mefloquine Antimalarial Inhibition of NF-κB activation Apoptosis Growth arrest [83] Valproate Antipsychotic Histone hyperacetylation Relief of HDAC-mediated transcriptional repression Reduced viability Enhanced cytotoxicity [84,85] Fluoxetine Antidepressant Inhibition of NF-κB activation and IKK phosphorylation Cell-cycle arrest at G0/G1 Enhanced p27 expression Reduced VEGF expression Suppressed colitis-associated tumorigenesis Suppressed dysplasia and angiogenesis [86,87,88] Sirolimus Prevention of kidney transplant rejection CHOP-dependent DR5 induction on 4E-BP1 dephosphorylation Suppressed FBXW7 loss-driven EMT Apoptosis Decreased angiogenesis Suppressed proliferation and invasion of colon cancer cells [89] Butyrate Probiotic Inhibition of miR-92a Suppressed proliferation of colon cancer cells cancers-14-02105-t002_Table 2 Table 2 Examples of some repurposed drugs currently being clinically investigated for the treatment of colon cancer. Clinical Trial Number Phase Status Estimated Completion Date Intervention/Treatment Patient Population Patients Enrolled Primary Outcome Measures Secondary Outcome Measures NCT02467582 3 Active, not recruiting June 2029 Aspirin Stages II and III PIK3CA-mutated CRC previously treated with surgery 185 DFS after 6 years Time to recurrenceOS Cancer-specific survival Adverse events NCT02301286 3 Recruiting September 2022 Aspirin Stages II and III CRC 1588 OS DFS TTF NCT03464305 3 Recruiting December 2026 Aspirin Stages II and III CRC 400 5-year OS DFS TTF NCT02945033 3 Recruiting July 2024 Aspirin PI3K-mutated CRC 246 Recurrence or second CRC or death, whichever occurs first 5-year OS Adverse events NCT00565708 3 Active, not recruiting June 2026 Aspirin Dukes C and high-risk Dukes B CRCs 1587 DFS OS NCT03026140 2 Recruiting January 2022 Nivolumab + Ipilimumab with or without Celecoxib Stages I to III CRC 60 Incidence of adverse events Immune activating capacity of immunotherapyRelapse-free survival NCT03925662 3 Recruiting December 2028 FOLFOX + bevacizumab with or without mebendazole Stage IV CRC 40 ORR - NCT03359681 2 Recruiting January 2022 Metformin CRC 48 Ki67 expression on tumor samples Cleaved Caspase-3 expression Immunoscore Immunological changes in blood samples In vitro cell growth NCT04873895 1 Recruiting November 2023 Axitinib + hydroxychloroquine Liver-dominant metastatic CRC 25 Serious adverse events ORR in setting of liver metastasis PFS OS NCT03919292 1/2 Recruiting January 2024 Neratinib + valproate Advanced solid tumors including CRC 113 Recommended phase 2 dose Adverse events Antitumor effects PFS Abbreviations: CRC: colorectal cancer; DFS: disease-free survival; ORR: objective response rate; OS: overall survival; PFS: progression-free survival; TTF: time-to-treatment-failure; FOLFOX: folinic acid + fluorouracil + oxaliplatin. 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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092610 molecules-27-02610 Article Anti-Inflammatory Effects of Cycloheterophyllin on Dinitrochlorobenzene-Induced Atopic Dermatitis in HaCaT Cells and BALB/c Mice Wang Chia-Chen 12 Hsiao Chien-Yu 34 Hsu Yu-Jou 5 Ko Horng-Huey 6 Chang Der-Chen 7 https://orcid.org/0000-0003-3478-5451 Hung Chi-Feng 156* Pae Hyun-Ock Academic Editor 1 School of Medicine, Fu Jen Catholic University, New Taipei City 24205, Taiwan; jamiewang@tma.tw 2 Department of Dermatology, Cardinal Tien Hospital, New Taipei City 23148, Taiwan 3 Department of Nutrition and Health Science, Chang Guang University of Science and Technology, Taoyuan 33303, Taiwan; mozart@gw.cgust.edu.tw 4 Research Center for Food and Cosmetic Safety and Research Center for Chinese Herbal Medicine, Chang Gung University of Science and Technology, Taoyuan 33303, Taiwan 5 PhD Program in Pharmaceutical Biotechnology, Fu Jen Catholic University, New Taipei City 24205, Taiwan; s16179263@gmail.com 6 School of Pharmacy, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; hhko@kmu.edu.tw 7 Department of Mathematics and Statistics and Department of Computer Science, Georgetown University, Washington, DC 20057, USA; chang@georgetown.edu * Correspondence: skin@mail.fju.edu.tw; Tel.: +886-2-29053911 19 4 2022 5 2022 27 9 261013 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/). Atopic dermatitis (eczema) is a condition that makes skin red and itchy. Though common in children, the condition can occur at any age. Atopic dermatitis is persistent (chronic) and tends to recur periodically. It may be accompanied by asthma or hay fever. No cure has been found for eczema. Therefore, it is very important to develop ingredients that aid the prevention and treatment of atopic dermatitis. Cycloheterophyllin is derived from Artocarpus heterophyllus and has antioxidant and anti-inflammatory activities. However, it still is not understood whether cycloheterophyllin is an anti-atopic dermatitis agent. Keratinocytes (HaCaT cells) and BALB/c mice for inducing AD-like cutaneous lesions were used to evaluate the potential of cycloheterophyllin as an anti-atopic dermatitis agent. The release of pro-inflammatory cytokines induced by treatment of TNF-α/IFN-γ was reduced after pretreatment with cycloheterophyllin. The inhibitory effects could be a contribution from the effect of the MAP kinases pathway. Moreover, the symptoms of atopic dermatitis (such as red skin and itching) were attenuated by pretreatment with cycloheterophyllin. Epidermal hyperplasia and mast cell infiltration were decreased in the histological section. Finally, damage to the skin barrier was also found to recover through assessment of transepidermal water loss. Taken together, prenylflavone-cycloheterophyllin from Artocarpus heterophyllus is a potential anti-atopic dermatitis ingredient that can be used in preventing or treating the condition. Artocarpus natural product cycloheterophyllin flavone atopic dermatitis keratinocytes DNCB ==== Body pmc1. Introduction Nearly 10% of people have been troubled by atopic dermatitis. Lubricants and steroids are among the first-line approaches for relieving the troubles caused by atopic dermatitis [1]. In severe cases, phototherapy can be used. These disturbing symptoms are often not eradicated by these treatments. Further, in many studies, new drugs such as PD4 inhibitors or those that block IL-4 and IL-13 receptors have been shown to be very effective [2]. However, the prices of such drugs are high. They are not affordable to the general public. Because of this factor, most people can only cope with symptoms for a short period of time. In disease treatments, people seek long-term benefits in addition to short-term relief of disease symptoms. Many traditional herbal components are ingredients in medicines that treat diseases. Despite their beneficial effects, scientific evidence for their mechanisms of action and effectiveness is often lacking. Therefore, it is necessary to fill such gaps in knowledge of medicinal plants during the drug development process [3]. A variety of tropical fruit trees growing all year round produce edible fruits used by local communities in their traditional medicine. Such fruits are rich in nutrients, but their medicinal properties remain to be studied. Therefore, research on the phytochemicals of these fruit trees is necessary to promote their medical use. Artocarpus heterophyllus and Artocarpus altilis are tropical fruit trees, both of which are Artocarpus plants and produce edible fruits rich in protein and fiber [4] that are also very good superfood candidates [5]. In addition, the flower, heartwood, and leaves of these trees have also been found to be rich in many biologically active ingredients [4,6,7]. Among them, cycloheterophyllin is one of the ingredients with very good anti-inflammatory and antioxidant effects [8]. In past research, it was found that it has a good anti-ultraviolet damage effect and has a whitening effect by inhibiting the action of tyrosinase [8,9]. In addition, nerve research has also found that cycloheterophyllin inhibits the release of glutamate and induces anti-epileptic activity [10]. Therefore, we speculate that its anti-inflammatory and anti-allergic effects should have considerable antagonistic activity in other skin diseases, such as atopic dermatitis and psoriasis. Therefore, in this study, we preliminarily verified cycloheterophyllin’s future development potential in atopic dermatitis of the skin. We demonstrate its anti-inflammatory and anti-allergic effects using skin keratinocytes in vitro. Further, the use of DNCB-induced skin inflammation was used to test its anti-atopic dermatitis symptoms. The results show that cycloheterophyllin has good potential for future application in inflammatory skin diseases. 2. Results 2.1. The Effect of Cycloheterophyllin on Skin Cell Viability First, we examined whether cycloheterophyllin has any effect on skin keratinocyte (HaCaT cell) viability. In past studies, it has been shown that cycloheterophyllin has some anti-photoaging activity on skin fibroblasts without any toxicity [8]. In order to further understand its role in keratinocytes, we first treated HaCaT cells with cychohetrophyllin from 1 to 30 μM for 1 h or 24 h. We found that cycloheterophyllin had no significant effect on the cell viability of HaCaT cells at concentrations of 1–30 μM (Figure 1). Therefore, the following experiments related to pharmacological mechanisms were mainly conducted at concentrations of 1, 3, and 10 μM. 2.2. The Anti-Inflammatory Potential of Cycloheterophyllin in Tumor Necrosis Factor-α (TNF-α)/Interferon-γ (IFN-γ)-Induced Inflammatory Response in HaCaT Cells Upregulation of proinflammatory cytokines plays a key role in the etiology of atopic dermatitis [11]. Several studies have shown that cytokines such as interferon-γ (IFN-γ) and tumor necrosis factor-α (TNF-α) stimulate epidermal keratinocytes to activate signaling pathways involved in pro-inflammatory responses. Therefore, this model is often used as an in vitro testing method for anti-inflammatory skin treatments [12]. Stimulation of keratinocytes with TNF-α and IFN-γ results in the mRNA expression of pro-inflammatory cytokines such as IL-6, IL-1, and IL-8 (Figure 2). Cycloheterophyllin pretreatment (1, 3, and 10 μM) for 1 h significantly (p < 0.05) diminished the TNF-α/IFN-γ-induced mRNA expression of IL-1β, IL-6, and IL-8 (Figure 1, left panel). These results clearly demonstrate that exposure of HaCaT cells to cycloheterophyllin has a significant protective effect against inflammatory cytokines. We further performed similar experiments using primary cultured keratinocytes to confirm that this effect can also be produced in primary human skin keratinocytes. The results show that cycloheterophyllin does have the same effect on primary human keratinocytes (Figure 2, right panel). 2.3. The Effect of Cycloheterophyllin on the TNF-α/IFN-γ-Induced Activation of MAP Kinases in HaCaT Cells A major pathway of MAP kinase phosphorylation is the activation of inflammatory transcription factors that act as downstream substrates of kinases to promote the secretion of inflammatory cytokines such as IL-6, IL-8, and IL-1β [12,13]. Therefore, we did find that TNF-α/IFN-γ (10 ng/mL) significantly increased the phosphorylation of P38 ERK and JNK1/2 (p < 0.01). The pretreatment of cycloheterophyllin (1, 3, and 10 μM) decreased the TNF-α/IFN-γ-induced phosphorylation of P38, ERK, and JNK in a dose-dependent manner (Figure 3). Furthermore, after pretreatment with the MAPK inhibitor, PD98059, we did not find that cycloheterophyllin could further inhibit the expression of proinflammatory cytokine mRNA (Figure 4). These experiments demonstrate that cycloheterophyllin reduces proinflammatory cytokine expression by inhibiting the phosphorylation of MAPK’s signal pathway. 2.4. Effects of Cycloheterophyllin on Atopic Dermatitis (AD)-like Skin Lesion in BALB/c Mice To investigate the anti-inflammatory effect of cycloheterophyllin on AD, a BALB/c AD model was set up by applying DNCB on the mice for fifteen days. By repeatedly exposing the dorsal skin and ear areas of mice to DNCB, AD-like skin damage was induced. During the experiment, we recorded the changes in the appearance of the skin on the backs and ears of the mice. The results show that the dorsal skin of the mice in the DNCB-induced group had serious redness, inflammation, and desquamation, while the mice in the cycloheterophyllin treatment group (10, 30 mg/kg) had reduced redness and inflammation (Figure 5, left panel). In addition, DNCB-induced ear inflammation and swelling were clearly suppressed in the cycloheterophyllin-treated group (Figure 5, middle and right panel). Observing changes in the appearance of the skin in mice, we did demonstrate that cycloheterophyllin has an anti-atopic dermatitis effect. 2.5. Effects of Cycloheterophyllin on Skin TEWL and Hydration in BALB/c Mice Transepidermal water loss (TEWL) is the amount of water that passively evaporates to the external environment due to the water vapor pressure gradient on both sides of the skin barrier through the skin, and is used to characterize skin barrier function [14]. From the appearance of the skin of the mice that were damaged by the administration of DNCB (Figure 5), it can be seen that the damage to the skin barrier is severe: TEWL increased significantly on the fifth day. This phenomenon was continued until the DNCB was discontinued. Therefore, the skin barrier was no longer able to maintain skin moisture after the fifth day (Figure 6A). Further, we also measured that the water content of the stratum corneum reduced substantially on fifth day (Figure 6B). In the group that received cycloheterophyllin pretreatment, we did find that the reduction in TEWL and skin hydration caused by DNCB was significantly restored by day 15 (Figure 6A,B). 2.6. Effects of Cycloheterophyllin on DNCB-Induced Scratching Behavior and Enlarged Spleen in BALB/c Mice Atopic dermatitis (AD) is a chronic, relapsing pruritic inflammatory skin disease. In our experiments, we also found a significant increase in the frequency of scratching in a DNCB-induced mouse model of atopic dermatitis (Figure 7A). The increased frequency of scratching was reduced by the administration of cycloheterophyllin (10 mg/kg and 30 mg/kg) (Figure 7A). Further, we also found that the weight of the spleen after treatment of DNCB was also reduced due to the pretreatment of cycloheterophyllin (Figure 7B). 2.7. Effects of Cycloheterophyllin on Epidermal Thickness and Mast Cell infiltration in DNCB-Induced Atopic Mice Finally, we used hematoxylin and eosin (H&E) staining and toluidine blue staining to detect epidermal hyperplasia and mast cell infiltration. As shown in Figure 8A, we can observe that DNCB does indeed cause a very serious epidermal hyperplasia. This hyperplasia is suppressed with the increase of the drug concentration (10 and 30 mg/kg). Further, we found that the infiltration of mast cells in the epidermis due to inflammation was also inhibited by the pretreatment of cycloheterophyllin (Figure 8B). 3. Discussion The results of this study show that cyclohetrophyllin, a component isolated from tropical fruit trees, has not only anti-photoaging [8] and whitening effects [9], but also great potential in the future of inflammatory skin disease treatments. The experimental results showed that cyclohetrophyllin has not only a good antioxidant effect, but also an anti-inflammatory effect. Oxidation and inflammation are known to play very important roles in many diseases. Therefore, we infer that cycloheterophyllin also has very good development potential for other diseases caused by excessive oxidation and inflammation. We found that cycloheterophyllin inhibited TNF-α/IFN-γ-induced IL-1β, IL-6, and IL8 expression in HaCaT. Epidermal keratinocytes are the main cellular component of the epidermis and may contribute to the pathogenesis of AD by producing pro-inflammatory genes [15]. Many studies have shown that keratinocytes produce TNF-α, IFN-γ, and IL-6, which are considered to be key to the inflammation medium [16,17]. Furthermore, the overproduction of cytokines by keratinocytes in AD skin lesions plays an important role in inflammation associated with atopic diseases [17,18]. Our findings show that cycloheterophyllin can effectively inhibit the expression of IL-6, IL-1β, and IL-8 in human keratinocytes, suggesting its therapeutic potential as an anti-AD agent. As for whether cycloheterophyllin has any effect on the expression of other cytokines and chemokines, this will be further studied in the future. Various fruit trees have traditionally been used as folk medicines across civilizations [19]. The plant parts that are used in these traditional medicines include fruits, bark, leaves, stems, roots, branches, and sap [20]. They are widely used as a folk medicine for respiratory, digestive tract, and skin diseases [21]. In modern medicine, extracts from different parts of plants have been used for various therapeutic purposes. Most bioactive compounds found in plant extracts are prime candidates for their medicinal properties [22]. The phytochemicals of tropical fruit trees fall into three main groups: (1) phenolics, (2) carotenoids, and (3) terpenes and terpenoids [22]. The Artocarpus genus of the family Moraceae is a rich source of prenylated flavonoids and derivatives that have been studied phytochemically and biologically [23]. The fruit, root bark, and heartwood of Artocarpus heterophyllus have been isolated and found to contain many phenolic compounds with antioxidant and anti-inflammatory activities [23,24,25,26]. Previous phytochemical studies on Artocarpus heterophyllus have shown that flavonoids and 2-arylbenzofurans are present with cytotoxic, tyrosinase inhibitory, anti-inflammatory, and anti-respiratory burst activities [24,25,26,27,28,29]. Structurally, cycloheterophyllin is a flavone belonging to the flavonoid family and is a prenylflavone compound. In our study, cycloheterophyllin potently reduces the mRNA expression of proinflammatory cytokines caused by cytokines TNF-α and IFN-γ. A major consequence of MAPK phosphorylation is the activation of inflammatory transcription factors that act as downstream substrates of kinases to promote the secretion of inflammatory cytokines [11,13]. Previous studies have shown that phenolic compounds 11 and 30 from Artocarpus heterophyllus wood have anticancer potential through the MAPK pathway [25]. Therefore, the inhibition of proinflammatory cytokine expression by cycloheterophyllin may also reduce the expression of related cytokines through its effect on MAPK. As for which map kinase (ERK, JNK, or p38) contribution is relatively important, this needs to be investigated with related MAP kinase inhibitors in the future. Our in vivo studies were performed in BALB/c mice with AD-like skin lesions treated topically with DNCB [11,14]. Histopathological analysis confirmed that cycloheterophyllin treatment reduced mast cell infiltration and DNCB-induced epidermal thickening, thereby alleviating DNCB-induced atopic skin symptoms in mice. It has been proposed that oxidative stress is involved in the pathogenesis of AD, which triggers skin inflammation by inducing epidermal keratinocytes to release pro-inflammatory cytokines and impair skin barrier function [30,31]. Therefore, antioxidants are believed to be beneficial in the prevention and/or treatment of AD. In our previous study, it was proven that cycloheterophyllin can resist the oxidative damage caused by hydrogen peroxide and UVA in skin fibroblasts. It can be understood that cycloheterophyllin has a very anti-oxidative effect in skin cells [8]. Our experimental results show that the ability of cycloheterophyllin to inhibit the release of cytokines and prevent epidermal water loss may also be closely related to the antioxidant properties of cycloheterophyllin. Mast cells play an important role in the pathogenesis of AD. Mast cells regulate inflammation and eosinophil activation by secreting multiple mediators [32]. Mast cell-derived histamine and other inflammatory mediators contribute to itch and inflammation in AD [33]. Further, our experimental results show that cycloheterophyllin can inhibit the scratching behavior caused by DNCB, and we also found that the infiltration of mast cells was significantly inhibited in the staining of tissue sections. Therefore, it is inferred that the effect on mast cells may also contribute to itching caused by anti-DNCB. Topical administration has a faster effect on the administration site, but the dose is difficult to control. For AD animal studies, oral administration is more convenient and easier to control than topical administration [34,35]. Because AD symptoms are systemic and not limited to the skin, oral administration was chosen for this study. The results of our research show that cycloheterophyllin can achieve an anti-atopic dermatitis effect after oral administration. This shows that cycloheterophyllin can be developed not only for local administration but also for systemic treatment. 4. Materials and Methods 4.1. Materials Cycloheterophyllin was isolated from the plant Artocarpus heterophyllus Lam. and dissolved in DMSO as previously described [26]. Sigma Chemical Co. (St Louis, MO, USA) was the source used to obtain 3-(4,5-Dimethylthiazol-2-yl)-2ami,5-diphenyltetrazolium bromide (MTT). Primary antibodies anti-p38, anti-ERK1/2, anti-JNK, anti-phospho-ERK1/2, anti-phospho-p38, and anti-phospho-JNK were purchased from Cell Signaling Technology (Beverly, MA, USA). The secondary antibodies were also purchased from Cell Signaling Technology. A Total RNA Isolation Kit (GeneDireX®, Vegas, NV, USA), an iScript™ cDNA Synthesis Kit (BIO-RAD, Hercules, CA, USA), and PowerUp™ SYBR™ Green Master Mix (Applied Biosystems™, Waltham, MA, USA) were used for Quantitative Polymer Chain Reaction (PCR) testing. A Pierce Protein Assay Kit (Pierce, Rockford, IL, USA) was used for a Western Blot Assay. 4.2. Methods 4.2.1. Cell Culture and MTT Assay Human immortalized keratinocytes (HaCaT cells) were a gift from Dr. Yih-Jing Lee of Fu Jen Catholic University. HaCaT cells were carefully cultured at 37 °C in DMEM containing 10% (v/v) FBS and 100 µg/mL antibiotics. Primary keratinocytes were isolated from human foreskin tissue and grown in Keratinocyte-SFM (Gibco BRL/Invitrogen, Carlsbad, CA, USA). In this study, primary keratinocytes were used between passages 2 and 4. Cell viability was assessed using the MTT assay. HaCaT cells (1 × 105 cells/well) were seeded into 24-well plates and maintained at 37 °C in 5% CO2. After 24 h of culture, the cell culture medium was changed to a serum-free medium containing different concentrations of cycloheterophyllin for 1 h or 24 h. Then, MTT dye was added, and the dishes were incubated at 37 °C for an additional 3 h. The supernatant was then carefully removed, and the insoluble formazan crystals were dissolved in DMSO. Absorbance was measured at 540 nm using a spectrophotometer (Tecan Sunrise Basic Microplate Reader). DMEM, FBS, and antibiotics were purchased from Gibco-BRL (Grand Island, NY, USA). 4.2.2. Quantitative Polymer Chain Reaction (PCR) HaCaT cells were seeded in 3.5 cm dishes. Cells can reach 90% confluence after 24 h of quiescent growth. Cells were pretreated with cycloheterophyllin for 1 h and then stimulated with TNF-α/IFN-γ for 1 h, respectively. The cells were then scraped and centrifuged (16,000× g, 10 min, 4 °C) and the supernatant was removed. RNA was purified using the Total RNA Isolation Kit. According to the operation procedure of iScript™ cDNA Synthesis Kit, reagents were added one by one and operated under the specified conditions to convert RNA into cDNA. Additionally, PowerUp™ SYBR™ Green Master Mix was used. A total of 7.5 μL ddH2O, 2 μL cDNA, 0.25 μL forward and reverse primers, and 10 μL SYBR GREEN were added and mixed well. The primer sequences are shown in Table 1. RNA was then quantified using the ABI StepOnePlus™ Real-Time PCR System. 4.2.3. Western Blot Assay Western blots were used to analyze changes in various proteins in cells. HaCaT cells were seeded in 3.5 cm dishes. After cells reached 90% confluence and were starved for 24 h, they were pretreated with cycloheterophyllin for 1 h and then stimulated with TNF-α/IFN-γ for 1 h, respectively. After scraping, cells were crushed by sonication and centrifuged (13,200 rpm, 10 min, 4 °C). After centrifugation, the supernatant was taken, and protein was quantified using the Pierce Protein Assay Kit. Approximately 20–40 μg of protein was electrophoresed on a 10% SDS-polyacrylamide gel, followed by electroporation with PVDF membranes. After the transfer, the PVDF membrane was placed in a TBS-T solution (Tris-buffered salt/0.05% tween 20) containing 5% nonfat dry milk for 1 h with continuous shaking to avoid nonspecific binding. Then, the PVDF membrane was washed 3 times with TBS-T (30 min in total). After that, the primary antibody was added (diluted 1:1000). PVDF membranes were left overnight at 4 °C and then washed 3 times with TBS-T for 10 min each. Finally, after adding the secondary antibody for 1 h (diluted to 1:1000), the PVDF membrane was washed 3 times with TBS-T, then the developing solution was added, and the membrane was put into the chemiluminescence extraction system (BIOSTEP Celvin®) for photography. 4.2.4. DNCB-Induced Atopic-Dermatitis-Like Skin Inflammation in Mice Male BALB/c mice (8 weeks old) were purchased from the National Laboratory Animal Center of Taiwan. Mice were housed in a standard laboratory, and the temperature and humidity were controlled at 21 ± 2 °C and 50 ± 20%, respectively. Mice were housed in an animal center with filtered laminar airflow control and a 12-h light/dark cycle at Fu Jen Catholic University, New Taipei City, Taiwan. Mice were allowed to take water and food ad libitum. Experiments were performed with the approval of the Institutional Animal Care and Use Committee of Fu Jen Catholic University (Approval No. A10703). First, mice were divided into four groups: control group, DNCB group, and cycloheterophyllin (10 mg/kg and 30 mg/kg) plus DNCB group. In this in vivo experiment, cycloheterophyllin was dissolved in DMSO by ultrasonic shock, while DNCB was dissolved in 75% ethanol. The former was administered orally, while 100 μL and 20 μL of the latter were applied to the skin of the back and right ear, respectively. Three days before the experiment, mice were anesthetized, dorsal hair was removed, and a small measuring magnet (SCT-MAG-TF) was embedded in the back of each mouse’s hind foot. After standing for three days, it was confirmed that the mice were in good physical condition and had normal skin in the hair removal area on the back. Then the experiment was started. Relevant physiological values of mouse skin parameters, including TEWL, erythema, skin moisture, blood flow, ear thickness and number of scratches, were measured before the experiment. During the experiment, photographs were taken to document changes in the appearance of the skin and ears. Since the temperature and humidity in the environment could have had a great influence on the parameters to be measured on the skin surface, when evaluating the physiological parameters of the skin, the whole process was carried out in a room with constant temperature and humidity. The first stage (days 1–4) is the period of allergic atopic dermatitis. After measuring the basic physiological values of mice, 1% DNCB was evenly applied to the skin of the back and right ear. On the fifth day, oral cycloheterophyllin was started. The second stage (days 5 to 14) involved re-induction of atopic dermatitis. We evenly applied 0.5% DNCB to the skin of the back and right ear of mice in the three experimental groups. The next day, we tested and recorded the physiological values of the skin and took pictures. After completing all tests on day 15, the mice were euthanized with carbon dioxide (CO2), and the dorsal skin tissue and spleen were removed for subsequent experimental analysis (Figure 9). Scratching behavior was tested by placing the animals in an observation cage (11 cm in diameter, MicroAct, Neuroscience, Tokyo, Japan). The scratching behavior of mice was automatically and objectively detected and assessed. Scratch behavior was measured for a total of 60 min. MicroAct uses the following analysis parameters to detect waves corresponding to continuous scratching behavior in mice: threshold, 0.05 V; interval between events, 0.05 s; minimum duration, 0.25 s; maximum frequency, 30 Hz; minimum frequency, 5 Hz. 4.2.5. Statistical Analysis Sigma-Plot software (version 10.0) was used for all statistical analyses of the data. All data are presented as mean ± SEM. Statistical significance was assessed by unpaired two-tailed Student’s t-test. Scientifically significant differences are indicated by p-values of less than 0.05 and 0.01. A single asterisk (*) indicates p-values of less than 0.05. Two asterisks (**) or two number signs (##) are indicated by p-values of less than 0.01 are indicated by. 5. Conclusions From the above results and descriptions, we have demonstrated that cycloheterophyllin in Artocarpus heterophyllus has very good anti-inflammatory and antioxidant effects. These effects can contribute to the development of therapeutic drugs and combating AD. Acknowledgments We thank Tzy-Ming Lu from Tajen University for providing of cycloheterophyllin. Author Contributions Conceptualization, C.-C.W. and H.-H.K.; Data curation, Y.-J.H., D.-C.C. and C.-F.H.; Formal analysis, C.-F.H.; Investigation, C.-Y.H. and Y.-J.H.; Methodology, C.-Y.H. and Y.-J.H.; Project administration, C.-C.W. and C.-F.H.; Resources, C.-Y.H., H.-H.K. and C.-F.H.; Writing—original draft, C.-C.W., D.-C.C. and C.-F.H.; Writing—review and editing, D.-C.C. and C.-F.H. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by research grants from the Ministry of Science and Technology (MOST110-2320-B-030 -004 -MY3), the Cardinal Tien Hospital (CTH-110A-FJU-2228; CTH111A-FJU-2226), and Chang Gung Memorial Hospital (CMRPF1J0042) in Taiwan. Institutional Review Board Statement All animal experiments in this study were approved by the Institutional Animal Care and Use Committee of Fu Jen Catholic University (approval #A10367). The principles of the 3Rs (Replacement, Reduction, and Refinement) were followed to optimize the experimental design. The foreskin was provided after institutional review board approval (#18MMHIS039e) at Mackay Memorial Hospital. Experiments were carried out in accordance with relevant guidelines and regulations. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study is available in article. Conflicts of Interest The authors declare no conflict of interest. Sample Availability Samples are not available from the authors. Figure 1 The effect of cycloheterophyllin on HaCaT cell viability. HaCaT cells were given different concentrations (1–30 μM) of cycloheterophyllin for 1 h or 24 h. The left panel shows the results for 1 h. The right panel shows the results for 24 h. Figure 2 The anti-inflammatory potential of cycloheterophyllin in the TNF-α/IFN-γ-induced inflammatory response in HaCaT cells (left panel) and human epidermal keratinocytes (right panel). HaCaT cells were pretreated with different concentrations of cycloheterophyllin (1, 3, and 10 μM) for 1 h, then cells were treated with TNF-α/IFN-γ (10 ng/mL) for 1 h. Total RNA was isolated and mRNA expression levels of (A) IL-1β, (B) IL-6, and (C) IL-8 were determined using qPCR. Values represent mean ± SEM from three independent experiments. ## p < 0.01 compared to untreated conditions; * p < 0.05 and ** p < 0.01 compared to TNF-α/IFN-γ treated conditions. Figure 3 The effect of cycloheterophyllin on the TNF-α/IFN-γ-induced activation of MAP kinases in HaCaT cells. Cycloheterophyllin reduces TNF-α/IFN-γ-induced activation of p38 (A), JNK (B), and ERK (C) in human keratinocyte (HaCaT) cells. HaCaT cells were pretreated with various concentrations of cycloheterophyllin (1, 3, and 10 μM) for 1 h, and then cells were treated with TNF-α/IFN-γ (10 ng/mL) for 30 min. Quantitative analysis of Western blots was performed. Values represent mean ± SEM from three independent experiments. ## p < 0.01 compared to untreated conditions; * p < 0.05 and ** p < 0.01 compared to TNF-α/IFN-γ treated conditions. Figure 4 The anti-inflammatory effects of cycloheterophyllin on the TNF-α/IFN-γ-induced inflammatory response with/without pretreatment of MAPK inhibitor, PD98059, in HaCaT cells. HaCaT cells were pretreated with PD98059 (50 μM), cycloheterophyllin (10 μM), or their combinations for 1 h, and then cells were treated with TNF-α/IFN-γ (10 ng/mL) for 30 min. Total RNA was isolated and mRNA expression levels of (A) IL-1β, (B) IL-6, and (C) IL-8 were determined using qPCR. Values represent mean ± SEM from three independent experiments. ## p < 0.01 compared to untreated conditions; * p < 0.05 compared to TNF-α/IFN-γ treated conditions. Figure 5 The effect of cycloheterophyllin on DNCB-induced inflammatory response to changes in skin appearance in mice. (Left panel) shows the effect of the skin changes on the dorsal skin. (Middle panel) shows the inhibitory effect of the inflammatory response on the ear. (Right panel) shows statistical results of ear inflammation thickness. On the first day, 1% DNCB was administered to the dorsal skin. Then, 0.5% DNCB was administered on the 8th day, the 11th day, and the 14th day to induce skin inflammation. The dorsal skin was given 100 μL DNCB and the ear was given 20 μL DNCB. ## p < 0.01 compared to untreated conditions; * p < 0.05 compared to DNCB-induced group. Figure 6 Changes in DNCB-induced skin physiological parameters of BALB/c mice after cycloheterophyllin pretreatment. Analysis of the effects of changes in transepidermal water loss (A) and hydration (B) in an atopic dermatitis-like phenotype in BALB/c mice. Values represent mean ± SEM from at least three independent experiments. ## p < 0.01 compared to untreated conditions; ** p < 0.01 compared to DNCB-induced group. Figure 7 Effects of cycloheterophyllin on scratching and spleen enlargement in mice. (A) Analysis of changes in the number of scratches in BALB/c mice with atopic dermatitis-like appearance. (B) The effect of cycloheterophyllin on spleen weight. Values represent mean ± SEM from at least three independent experiments. ## p < 0.01 vs. untreated condition; * p < 0.05 vs. DNCB-induced group. Figure 8 Effects of cycloheterophyllin on epidermal hyperplasia and mast cell infiltration. (A) Upper panel: histopathological variation due to DNCB induction was evaluated using hematoxylin–eosin staining (scale bar, 50 μm). Lower panel: quantitative analysis of epidermal thickness. (B) Toluidine blue staining; scale bar: 20 μm. Arrows indicate mast cells. Lower panel: number of mast cells. Values represent the mean ± SEM from at least three independent experiments. ## p < 0.01 compared with the no-treatment condition; * p < 0.05 and ** p < 0.01 compared with the DNCB-induced group. Figure 9 Experimental design of a mouse model of atopic dermatitis (AD)-like skin injury. molecules-27-02610-t001_Table 1 Table 1 Primer sequences for RT-qPCR. Genes Primers Sequence (5′-3′) IL-1β Forward CTC TCA CCT CTC CTA CTC ACT Reverse ATC AGA ATG TGG GAG CGA AT IL-6 Forward ATC AGA ATG TGG GAG CGA AT Reverse GGA CCG AAG GCG CTT GTG GAG IL-8 Forward ACT GAG AGT GAT TGA GAG TGG AC Reverse AAC CCT CTG CAC CCA GTT TTC GAPDH Forward CTG CTC CTG TTC GAC AGT Reverse CCG TTG ACT CCG ACC TTC AC Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Eichenfield L.F. Tom W.L. Berger T.G. Krol A. 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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/ijerph19094930 ijerph-19-04930 Brief Report Properties of the Omicron Variant of SARS-CoV-2 Affect Public Health Measure Effectiveness in the COVID-19 Epidemic https://orcid.org/0000-0002-4663-6069 Furuse Yuki 12 Van Winkle Lon Jeffrey Academic Editor 1 Nagasaki University Graduate School of Biomedical Sciences, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan; furusey.nagasaki@gmail.com 2 Medical Education Development Center, Nagasaki University Hospital, 1-7-1 Sakamoto, Nagasaki 852-8501, Japan 19 4 2022 5 2022 19 9 493024 3 2022 17 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/). Nonpharmaceutical and pharmaceutical public health interventions are important to mitigate the coronavirus disease 2019 (COVID-19) epidemic. However, it is still unclear how the effectiveness of these interventions changes with the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) novel variants. This simulation study utilized data from Japan and investigated how the characteristic properties of the Omicron variant, which emerged in late 2021, influence the effectiveness of public health interventions, including vaccination, the reduction of interpersonal contact, and the early isolation of infectious people. Although the short generation time of the Omicron variant increases the effectiveness of vaccination and the reduction of interpersonal contact, it decreases the effectiveness of early isolation. The latter feature may make the containment of case clusters difficult. The increase of infected children during the Omicron-dominant epidemic diminishes the effects of previously adult-targeted interventions. These findings underscore the importance of monitoring viral evolution and consequent changes in epidemiological characteristics. An assessment and adaptation of public health measures against COVID-19 are required as SARS-CoV-2 novel variants continue to emerge. COVID-19 SARS-CoV-2 variant public health nonpharmaceutical intervention ==== Body pmc1. Introduction Various public health interventions against the coronavirus disease 2019 (COVID-19) have been implemented around the world since its emergence. Nonpharmaceutical interventions still play a significant role in controlling the COVID-19 epidemic, although effective vaccines have been developed and widely used. Reducing interpersonal contact is a mainstay of such interventions. Limiting social activities by implementing lockdowns, canceling mass-gathering events, closing restaurants and bars, encouraging work from home, and closing schools can prevent the spread of the disease [1,2]. Test-trace-isolate (TTI) is another strategy to hinder viral transmission from infected persons. The TTI strategy finds infected people effectively to isolate them through extensive testing and contact tracing [3]. A cluster-based approach to identifying superspreading events also aims to detect infected people and their contacts for early isolation and quarantine [4,5]. Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can prevent hospitalization and death by COVID-19 [6]. Vaccination is especially important for people at high risk of developing severe illnesses, to alleviate the burden on the healthcare system. Furthermore, vaccination can prevent viral infection itself [6]. Hence, increasing vaccination coverage forms a herd immunity that helps control the infection spread. Even if the vaccine effectiveness to prevent viral infection is not 100%, an effective reproduction number can go down in a population with a high proportion of immune people [7]. Novel variants of SARS-CoV-2 continue to emerge, imposing additional risks on public health. Some variants increase the transmissibility of the virus (e.g., Alpha and Delta), while others alter the antigenicity of the virus to escape the immunity generated by vaccination or prior infection (e.g., Beta and Gamma) [8]. The advent of the latest variant of concern, Omicron, was first reported in Botswana and South Africa in late 2021 [9]. The variant has caused a surge of cases around the world. This novel variant spreads rapidly owing to a short generation time for transmission and a substantial antigenic change [10,11,12]. Interestingly, the number of COVID-19 cases in an epidemic wave caused by the Omicron variant dramatically declined in a short period in some countries, whereas other countries continue to face issues in controlling the epidemic, as of March 2022 [13]. To understand how the properties of the Omicron variant influence the effectiveness of public health measures, this study analyzed a simulation model that reflected the COVID-19 situation in Japan with virtual scenarios of viral characteristics and public health interventions. The findings could imply the need to adapt public health measures to the novel variant. 2. Materials and Methods 2.1. Simulation Model A deterministic compartment model was developed for the simulation in the present study, as shown in Figure 1. The compartment model comprises S, susceptible; I, infectious; T, infectious who will be isolated earlier by TTI; and R, removed. Each compartment is layered into four age groups: 0–19 years old, 20–39 years old, 40–59 years old, and ≥60 years old. The population number in each group was determined according to a demographic census in Japan [14]. S people get an infection from I and T people by the effective contact rate β. ε% of I people become isolated and lose transmissibility due to TTI at a rate α, and the rest (1 − ε)% of I people become R at a rate γ. 2.2. Infection Spread The effective contact rate β was subject to change for each scenario according to the other parameters so that the total number of newly infected people increases from ~1000 to ~20,000 in 30 days in the simulation. This situation corresponds to the number of COVID-19 cases in the growing phase of the 5th and 6th epidemic waves in Japan, which were caused by the Delta variant in July–August 2021 and the Omicron variant in January–February 2022, respectively [15]. The transmission matrix among the age groups was determined according to a previous study [7]. Briefly, transmission within the same age group is four times more frequent than across different age groups, and people aged 20–59 years are four times more infectious than the other age groups (Figure S1A). The proportion of people under the age of 20 (hereafter, the age group is regarded as children) accounts for 20% of all infected people in the simulation under the transmission matrix, which is equivalent to the observation data during the Delta-dominant 5th wave of the COVID-19 epidemic in Japan [15]. 2.3. Properties of the Omicron Variant Three characteristic properties of the Omicron variant were explored. Firstly, the generation time of the Omicron variant is shorter than that of the Delta variant [11,12]. In the simulation model, the generation times of the Delta and Omicron variants were set as 5 and 3 days, respectively. Secondly, the transmission matrix differs between the Delta and Omicron variants. During the Omicron-dominant 6th epidemic wave in Japan, the proportion of children among COVID-19 patients increased to ~30% [15]. This can be attributed to the efficient viral growth in the upper airway seen in this variant and a larger proportion of susceptible people in children compared to adults [7,16,17,18]. The assumption that children are 1.2 times more susceptible than adults (Figure S1A) reproduced a similar situation in the simulation model. Thirdly, vaccination effectiveness declines for the Omicron variant [19,20]. In the simulation, it was assumed that vaccination effectiveness to prevent infection decreases by half for the Omicron variant compared with the Delta variant. 2.4. Interventions Three public health interventions were investigated in the study: early isolation, the reduction of interpersonal contact, and vaccination. Early isolation by TTI increases ε in the simulation model (Figure 1). This increases the proportion of T, which has a shorter infectious period than I. The reduction of interpersonal contact decreases the effective contact rate β in the simulation model (Figure 1). Two scenarios for contact reduction were tested: “adult-focused” and “adults and children” (Figure S1B). The intervention was assumed to work more effectively for pairs within a close age range, but little for child–adult pairs because most contact between children and adults must occur in the household [5,21]. Public health interventions on social activities seem to hardly prevent such household transmissions [21,22]. Vaccination removes a part of S people from the population (Figure 1). “Adult-targeted” vaccination reduces only S people aged ≥20, whereas “adults and children” vaccination removes the same proportion of S people across all age groups. These interventions are implemented on day 30 in the simulation. The intensity of each intervention was set so that the number of newly infected people decreases to ~10,000 on day 60 in the simulation for the Delta variant. The same interventions are applied for viruses with characteristic properties of the Omicron variant in order to see the changes in the effectiveness of the interventions. 2.5. Data Availability The computer script for the simulation was written in R. The model description and detailed parameter settings are available on the Github website (https://github.com/yukifuruse1217/omicron_and_measures/blob/main/SIR_japan_omicron_measures_forGit.R (accessed on 23 March 2022)). 3. Results The COVID-19 infection spread and its control via public health interventions were simulated for the Delta variant (a black broken line in each panel of Figure 2). Additionally, the way each property of the Omicron variant influences the effectiveness of the interventions was investigated (the colored lines in Figure 2). The results showed that the effect of early isolation by TTI is reduced for the Omicron variant due to its short generation time (Figure 2A). On the other hand, the short generation time of the Omicron variant intensifies the effect of reducing interpersonal contact. The introduction of the short generation time rapidly decreases the number of COVID-19 cases by reducing interpersonal contact compared to the Delta variant (Figure 2B,C). However, the effect of reducing contact diminishes for the Omicron variant when the intervention focuses only on interpersonal contact among adults (Figure 2B). This occurs because transmission among children contributes more to the infection spread for the Omicron variant. Conversely, the effect of reducing interpersonal contact among children (e.g., by school closure) in addition to adult-focused intervention is more evident for the Omicron variant than for the Delta variant (Figure 2C). The short generation time enhances the effect of vaccination in suppressing infection spread (Figure 2D,E). Yet, an increase in the proportion of infected children diminishes the effect of vaccination when vaccination targets only adults (Figure 2D). Vaccination for children has been approved and recently administered in some countries [23,24,25]. Child vaccination cancels the influence of the increase of infected children on vaccination effectiveness (seen by comparing the green lines in Figure 2D,E). Still, the integrative properties of the Omicron variant, including an immune-escaping ability, decrease the effect of vaccination compared to the Delta variant (Figure 2E). As already observed, the effects of early isolation, adult-focused reduction of interpersonal contact, and vaccination targeting adults decline substantially for the Omicron variant (Figure 2). However, because those interventions have different sites of action in infection spread dynamics (Figure 1), their combination can work synergistically. Implementing all the interventions has a synergistic effect on controlling the COVID-19 epidemic, even if the impact of each intervention is moderate (Figure 3). Additional public health measures for children could further help the mitigation. 4. Discussion This study showed how the characteristic properties of the Omicron variant influence the effectiveness of public health interventions. Its short generation time enhances the effect of reducing interpersonal contact (e.g., by limiting social activities) and decreasing susceptible people (e.g., by vaccination). In contrast, the short generation time of the Omicron variant diminishes the effect of early isolation by TTI. The reduced impact of early isolation could cause failure in the early containment of case clusters. In fact, case clusters in preschools, schools, and nursing homes have been increasingly reported in the Omicron-dominant 6th wave of the COVID-19 epidemic in Japan [15]. Public health measures for limiting interpersonal contact are usually focused on social activities among adults. For example, closing restaurants and bars, restricting mass-gathering events, and working from home were advised during a state of emergency for COVID-19 in Japan [21,26]. Additionally, adults represent the main population for vaccine administration so far [18], as evidence regarding vaccination efficacy and safety for children was previously unavailable [27]. The proportion of infected children increased in the Omicron-dominant epidemic, possibly due to efficient viral transmission and a large proportion of non-immune people [7,16,17,18]. The effectiveness of adult-focused public health measures was shown to decline in the Omicron-dominant epidemic in this simulation study. An implementation of child-targeted public health measures, such as school closure and mass vaccination for children, might also be worth considering. However, we should prudentially discuss the pros and cons of such actions [28,29]. The model developed in this study referred to the COVID-19 situation in Japan. Still, the properties of the Omicron variant, such as the short generation time and immune-escape ability, are not unique to the country. Therefore, the reduced impact of public health interventions upon Omicron must be the case for other countries as well. This study was not designed to measure or compare the effects of different interventions. Rather, it investigated whether the properties of the Omicron variant had a positive or negative influence on the effectiveness of public health interventions compared to the Delta variant. Models considering complex details, such as the waning of immunity, network structures, and people’s mobility, should be built to quantify the absolute impact of each public health intervention or predict the future course of the epidemic [30,31,32]. In the present simulation analysis, a single intervention with the same intensity was implemented for Delta-dominant and Omicron-dominant epidemics, and the properties of Omicron were tested one by one. Because those situations never happen in the real world, the fitness of the model cannot be discussed. 5. Conclusions This study concludes that the effectiveness of public health interventions depends not only on their intensity but also on the epidemiological characteristics determined by a circulating virus. Recently, different sublineages of the Omicron variant and recombinant viral strains have emerged, and their risk assessment is underway [33]. We should keep monitoring viral evolution and consequent changes in transmission dynamics. Continuing evaluation of public health measures is important, possibly helping strategy optimization to mitigate the COVID-19 epidemic. Acknowledgments I thank Koji Maemura, Kayoko Matsushima, Hisayuki Hamada, and Noriyuki Nishida for their support. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19094930/s1, Figure S1: Transmission matrix among the age groups. Click here for additional data file. Funding This study was funded in part by the Research Program on Emerging and Re-emerging Infectious Diseases (grant number 20fk0108451s0301) from the Japan Agency for Medical Research, by the Grant-in-Aid for Scientific Research on Promotion of Joint International Research (JP19KK0204) from the Japan Society for the Promotion of Science, and by the Nagasaki University State of the Art Research program (grant number not available) from Nagasaki University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The computer script for the simulation in this study is available on the Github website (https://github.com/yukifuruse1217/omicron_and_measures/blob/main/SIR_japan_omicron_measures_forGit.R (accessed on 23 March 2022)). Conflicts of Interest The author declares no conflict of interest. Figure 1 Scheme of the simulation model. The figure depicts the compartment model developed for the simulation in this study. Figure 2 Influence of the properties of the Omicron variant on the effectiveness of public health interventions. The number of newly infected people in the 60-day simulation is shown in the figure. The infection spreads are adjusted to reproduce a similar situation for all scenarios by day 30. Thereafter, each intervention is implemented to reduce the number of new cases to the same degree for the Delta variant (black broken lines). Colored solid lines represent the number of new cases when a circulating virus acquires different properties of the Omicron variant. Analyzed interventions are (A) early isolation, (B) “adult-focused” reduction of contact, (C) “adults and children” reduction of contact, (D) “adult-targeted” vaccination, and (E) “adults and children” vaccination. Figure 3 Synergistic effect of public health interventions to control the spread of the Omicron variant. Simulated epidemic curves for the Omicron variant with implementing a single public health intervention or their combination on day 30 are shown. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Haug N. Geyrhofer L. Londei A. Dervic E. Desvars-Larrive A. Loreto V. Pinior B. Thurner S. Klimek P. Ranking the effectiveness of worldwide COVID-19 government interventions Nat. Hum. Behav. 2020 4 1303 1312 10.1038/s41562-020-01009-0 33199859 2. Sharma M. Mindermann S. Rogers-Smith C. Leech G. Snodin B. Ahuja J. Sandbrink J.B. Monrad J.T. Altman G. Dhaliwal G. Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe Nat. Commun. 2021 12 5820 10.1038/s41467-021-26013-4 34611158 3. Contreras S. Dehning J. Loidolt M. Zierenberg J. Spitzner F.P. 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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091128 plants-11-01128 Article The Biodiversity of Grapevine Bacterial Endophytes of Vitis amurensis Rupr. https://orcid.org/0000-0002-2549-8568 Aleynova Olga A. * Nityagovsky Nikolay N. https://orcid.org/0000-0002-0516-6144 Dubrovina Alexandra S. Kiselev Konstantin V. Hirel Bertrand Academic Editor Laboratory of Biotechnology, Federal Scientific Center of the East Asia Terrestrial Biodiversity, Far Eastern Branch of the Russian Academy of Sciences, Vladivostok 690022, Russia; niknit1996@gmail.com (N.N.N.); dubrovina@biosoil.ru (A.S.D.); kiselev@biosoil.ru (K.V.K.) * Correspondence: aleynova@biosoil.ru; Tel.: +7-4232-310718; Fax: +7-4232-310193 21 4 2022 5 2022 11 9 112818 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/). In this paper, the composition profiles of bacterial endophytes in wild-growing Amur grape Vitis amurensis Rupr. grown in the south of the Russian Far East were analyzed using both a cultivation-dependent (sowing bacteria) and a cultivation-independent (next generation sequencing, NGS) approach. Both methods revealed the prevalent endophytes in V. amurensis were represented by Gammaproteobacteria—40.3–75.8%, Alphaproteobacteria—8.6–18.7%, Actinobacteria—9.2–15.4%, and Bacilli—6.1–6.6%. NGS also showed a large proportion of Bacteroidia (12.2%) and a small proportion of other classes (less than 5.7%). In general, NGS revealed a greater variety of classes and genera in the endophytic bacterial community due to a high number of reads (574,207) in comparison with the number of colonies (933) obtained after the cultivation-dependent method. A comparative analysis performed in this study showed that both wild grape V. amurensis from Russia and domesticated cultivars of V. vinifera from Germany and California (USA) exhibit the same basic composition of endophytic bacteria, while the percentages of major taxa and minor taxa showed some differences depending on the plant organ, grape individuals, environmental conditions, and sampling time. Furthermore, the obtained data revealed that lower temperatures and increased precipitation favored the number and diversity of endophytic bacteria in the wild Amur grape. Thus, this study firstly described and analyzed the biodiversity of endophytic bacteria in wild grapevine V. amurensis. bacteria endophytes grape microbiome Vitis amurensis ==== Body pmc1. Introduction Grapes from the genus Vitis have been widely recognized as economically important fruit crops used for grape, wine, raisins, and juice production [1]. The Vitaceae family includes about 15 genera and ca. 900 species mostly in pantropical regions of Asia, Africa, Australia and the Pacific islands, with a few genera in temperate regions of the Northern Hemisphere [2]. It is well known that grape yield and fruit quality depend highly on external factors, such as the vineyard location, weather conditions, agricultural practices, and various biotic factors, such as microbial pathogens and endophytic microbiome [3]. Plant endophytes include bacteria, archaea, fungi, and protists that colonize the plant interior regardless of the outcome of the association [4]. Some endophytes are known to confer mutually beneficial effects to the host plant [3]. Some endophytes promote plant growth via nitrogen fixation, phytohormone production, or nutrient acquisition, and are also known to confer tolerance to abiotic and biotic stresses [5]. Endophytes possess considerable potential for application in agriculture as natural agents for biological control, plant growth promotion, crop yield improvement, and environmental stress control. In the last decade, researchers have been actively studying the microbiome assemblage in grape species. Both general composition of endophytic communities and the endophyte biodiversity in healthy vs. diseased grapevine cultivars were studied to isolate microorganisms capable of grapevine pathogen biocontrol and fruit yield improvement. The main body of research on the biodiversity of grapevine endophytic bacteria has been devoted to the European wine grape (Vitis vinifera) [6,7,8,9,10,11]. Most available studies show Gammaproteobacteria represent the dominant class of endophytic bacteria in V. vinifera [6,8]. It has been shown that the main bacteria included Bacillus spp., Pseudomonas spp., Erwinia spp., Pantoea spp., and Curtobacterium spp. In addition, there were studies on the endophytic bacterial communities of the grapevine varieties grown across the North American continent [12,13]. Proteobacteria were reported as the main representative of the bacterial community in American grape [12]. According to Deyett and Rolshausen [12], the core microbiome of grapevine sap from California was primarily composed of seven bacterial taxa (Streptococcus, Micrococcus, Pseudomonas, Bacteroides, Massilia, Acinetobacter and Bacillus) that were present throughout the growing season [13]. Moreover, Campisano et al. [14] conducted a comparative analysis of bacterial endophytes detected in wild and domesticated European grapevine V. vinifera. According to the study, wild grapevines were inhabited by a much more diverse endophytic bacterial community than domesticated counterparts. Thus, studying the bacterial microbiome of wild grapes represents an important area of research with a potential to detect new bacteriome variations that are not typical to cultivated varieties. Currently, little is known about the microbiome of grapes growing in the Far East of Russia. The main representative of the Far Eastern wild grapes is the Amur grape Vitis amurensis Rupr. This species of grape exhibits a high resistance to low temperatures and microbial diseases, such as powdery mildew, grape white rot and anthracnose [15,16,17]. Furthermore, V. amurensis is used as rootstock to generate grape varieties with a high resistance to biotic and abiotic stress. Moreover, this species contains a high number of bioactive compounds (i.e., resveratrol and other stilbenes) with beneficial effects to human health [18]. It has been shown that stilbenes found in the stem of V. amurensis are capable of suppressing pathogenic bacteria such as Pseudomonas aeruginosa, Xanthomonas axonopodis, Streptococcus mutans and Streptococcus sanguis [19,20,21]. In addition, there are many examples where endophytic bacteria from wild relatives of crops, such as olive, rice, maize, barley and others, have been used to increase crop yields and resistance to environmental stresses. For example, bacterial endophytes from wild maize suppressed Fusarium graminearum and Sclerotinia homoeocarpa in cultivated maize and inhibited mycotoxin accumulation [22,23]. Moreover, endophytic bacteria from wild rice (Oryza meridionalis) bear considerable potential for promoting plant growth and degradation of phthalates [24,25]. Therefore, studying endophytic bacteriome of wild grape V. amurensis could contribute to the production of natural endophyte-containing agents that can be used to increase grapevine stress resistance and to improve the quality of grape-derived products. In this study, we aimed to analyze the biodiversity of endophytic bacteria in V. amurensis growing in natural population. The composition of bacterial endophytic community in V. amurensis was determined using bacterial sowing and NGS. This paper presents data on the biodiversity of bacterial endophytes in V. amurensis depending on the sample collection times, individual grape varieties, and different grapevine organs. 2. Results 2.1. The General Composition of Endophytic Bacterial Community in Different Organ of V. amurensis We selected and identified the main representatives of the V. amurensis bacteriome. V. amurensis tissues were collected from two different plants in July and September for four years from 2018 to 2021. Then, a cultivation-dependent approach (bacterial seeding) was employed to analyze the endophytic bacteriome of V. amurensis using surface-sterilized plant tissues. We analyzed a total of 933 bacterial strains obtained as a result of the microbiological seeding procedure performed over the 4-year period. These strains were divided into four classes of bacteria. Gammaproteobacteria was the dominant class—76%. In addition, we detected Actinobacteria—9.2%, Alphaproteobacteria—8.6%, Bacilli—6.1%, and Bacteroidia less than 1% (Figure 1a). Moreover, we used surface-sterilized tissues of the same two wild V. amurensis plants collected in July and September 2021 for NGS analysis of the endophytic bacterial community. We obtained 3,108,452 paired reads of 16s rRNA gene. A total of 574,207 amplicon sequence variants (ASVs) were obtained after pre-processing for further analysis (Figure 1b). According to the analysis, 17 taxa were presented in different grapevine organs (stem, leaf, berry, seed) with the relative representation above 0.1%. Among the 17 taxa, ASVs belonging to 5 classes were the most represented: Gammaproteobacteria—40.3%, Alphaproteobacteria—18.7%, Actinobacteria—15.4%, Bacteroidia—12.2% and Bacilli—6.6% (Figure 1b). Thus, the metagenomic analysis generally confirmed the data of the cultivation-dependent approach. Notably, a total of 22 common genera of endophytic bacteria were detected by both cultivation-dependent and cultivation-independent approaches, while 18 unique genera were detected by the cultivation-dependent method and 59 unique genera–by NGS (Supporting Information S1). According to the cultivation-dependent method, the predominant bacterial genera were Pantoae—29.5% and Erwinia—25%, while these bacterial genera were either not present or detected in trace amounts (less than 1%) in the metagenomics study (Figure 2). The top five taxa in NGS-analysis included Comamonadaceae (12%), Methylobacterium (8%), Hymenobacter (8%), Sphingomonas (5%) and Cutibacretium (5%). The Comamonadaceae, Hymenobacter, and Cutibacterium taxa accounted for 12%, 8%, and 4.6%, respectively, for all analyzed ASVs according to the cultivation-independent method, while they were not detected after bacterial seeding (Figure 2). The analysis of endophytic bacteriome of the different V. amurensis organs revealed that the highest number of strains and obtained ASVs were detected in the leaves and stems, while the seeds showed much lower diversity of endophytic bacteria (Figure 1c,d). The Gammaproteobacteria class was dominant in the seeds, while the Alphaproteobacteria and Bacilli classes were less represented. The leaves of V. amurensis were predominantly colonized by the Bacteroidia and Myxococcia compared to other plant organs. ASVs were represented by 128 taxa in the samples of plant organs. Among them, 63 taxa were found in all analyzed grapevine organs (Figure 1d and Supporting Information S2). The beta diversity data showed diffuse clustering and no significant difference between organ samples performed by PERMANOVA test (R2: 13.6%, p = 0.521) (Supporting Information S3). The most common taxa for the leaves of V. amurensis were Hymenobacter (16%), Methylobacterium-Methylorubrum (9%), and Comamonadaceae (8%), while the most common taxa for the stem were represented by Sphingomonas (6.6%), Methylobacterium-Methylorubrum (8.5%), and Comamonadaceae (7.2%) (Figure 3). The largest number of ASVs in grape berries and seeds belonged to the taxa Comamonadaceae (17.5% and 43%, respectively). Moreover, genera Cutibacterium (5.8%) and Dechloromonas (6.7%) were most often found in grape seeds (Figure 3). 2.2. Differences in the Composition of Endophytic Bacterial Community in V. amurensis Depending on the Year of Tissue Collection We used the cultivation-dependent approach to isolate individual endophytic bacteria from the tissues of two V. amurensis plants collected every year from 2018 to 2021. In 2018, we isolated and identified 242 strains of endophytic bacteria, in 2019–173 strains, in 2020–363 strains and in 2021–155 strains (Figure 4a). Most strains of endophytic bacteria (71.5–79.4%) collected each year belonged to Gammaproteobacteria. The distribution among other classes of endophytic bacteria varied depending on the year of sampling. In 2018 and 2020, the percentage ratio of the endophytic bacteria classes were similar. In 2020, Bacteroidia class were detected (0.55%), while in 2018 this class was not present. The incidence of the Actinobacteria class in 2019 decreased by half and reached 6% compared to 2018 and 2020, respectively, and dropped to less than 1.3% in 2021. The incidence of Bacilli was 2% in 2018 and 2020, while it increased to 8% and 19% in 2019 and 2021, respectively (Figure 4a). The generic biodiversity was the richest in 2019 and 2020 (23 and 22 genera), and there were 9 and 10 unique genera for 2019 and 2020, respectively (Figure 4b). Common genera that were detected every year of the bacterial seeding were Bacillus, Erwinia, Pantoea, Pseudomonas and Sphingomonas (Supporting Information S4). 2.3. Seasonal Variations in the Composition of Endophytic Bacteriome in V. amurensis We also analyzed the biodiversity profile of endophytic bacteria in V. amurensis depending on the collection season. The leaves and stems of V. amurensis were collected in the first half of July and in the second half of September. The cultivation-dependent approach resulted in a greater number of strains sown in autumn (555) than in summer–(378) (Figure 5a). In total, 14 genera of bacteria were common for summer and autumn, while 9 genera were unique for summer and 15 for autumn (Figure 5c and Supporting Information S5). A total of 257,016 ASVs were obtained in the autumn of 2021 and 317,191 ASVs in the summer of 2021 using the cultivation-independent approach. The percentage of Alphaproteobacteria increased two-fold in the autumn, while the percentage of Bacilli decreased four-fold (Figure 5b). A total of 6 genera were identified as unique for the summer, and 3 genera were unique for the autumn (Figure 5d and Supporting Information S6). PERMANOVA test showed no significant difference between summer and autumn samples (R2: 8.8%, p = 0.068) (Supporting Information S3). 2.4. The Composition of Endophytic Bacterial Community in Different Representatives of V. amurensis Grapevine In addition, we compared the percentage of the community of endophytic bacteria in individual plants of V. amurensis. The two representative V. amurensis plants differed only in their place of growth, while their approximate ages were the same. We detected no significant differences in beta diversity between samples collected from plant A and plant B (R2: 8.9%, p = 0.064) (Supporting Information S3). The incidence of Bacteroidia was 2-fold higher in plant A than in plant B (Figure 6a). There were only two unique taxa in plant B belonging to Gammaproteobacteria and Intrasporangiaceae and one unique genus Frondihabitans in plant A (Figure 7d and Supporting Information S7). 2.5. Comparative Analysis of Endophytic Bacteria Biodiversity in V. amurensis and V. vinifera We conducted a comparative analysis of the bacteriomes of V. amurensis obtained in this study with the previously studied bacteriomes of V. vinifera grapevines growing in Germany [26] and California, USA [12] (Supporting Information S8). We analyzed the amplicon data of each sample site with respect to the location. The results for alpha and beta diversity analysis are shown in Figure 7a,b, respectively. The grape samples collected in Russia (Vladivostok) and USA (California) were similar in alpha diversity. The Germany samples exhibit reduced alpha diversity compared to Russia (Vladivostok) (p < 0.001) and to USA (California) (p < 0.001). (Figure 7a and Supporting Information S9). The beta diversity results are presented in the nonmetric multidimensional scaling (NMDS) ordination (Figure 7b). NMDS ordination showed that samples from Russia (Vladivostok), USA (California) and Germany were located in separate clusters (Figure 7b). The PERMANOVA test demonstrated that the samples collected in Vladivostok and California were more similar (R2: 1,4%, p = 0.473) based on beta diversity than samples from California and Germany (R2: 4,9%, p = 0.002), while the samples from Russia and Germany were most diverse (R2: 11,8%, p = 0.001) (Supporting Information S10). These results were also supplemented by UpSet intersection diagrams. Samples collected in Vladivostok and California displayed 47 intersection genera, California and Germany had 21, and Vladivostok and Germany had only 5 (Figure 7d and Supporting Information S11). According to the analysis, the grape bacteriome is represented by 23 main classes of bacteria (Figure 7c). The classes Gammaproteobacteria, Alphaproteobacteria, Actinobacteria, Bacteroidia and Bacilli dominated over other classes in all bacteriomes included in the analysis. Gammaproteobacteria was the dominant class in all grapevine samples (40–50%), with Pseudomonas as the most represented genus in California and Germany samples (Figure 8). The most abundant taxa in the samples collected in Russia (Vladivostok) was Comamonadaceae (Betaproteobacteria). There were 67 genera common to all regions of the material collection. The analysis also revealed 22 unique genera for USA (California), 13—for Russia (Vladivostok) and 5—for Germany (Figure 7d and Supporting Information S11). For the wild grape V. amurensis, the unique genera were Alcaligenes, Ampullimonas, Anaerobacillus, Aquabacterium, Curvibacter, Cutibacterium, Dermacoccus, Erwinia, Fibrella, Frondihabitans, Heliimonas, Neochlamydia and Nitrospirillum (Figure 8 and Supporting Information S11). 3. Discussion The microbiota of grapes are highly variable, mostly due to the influence of external factors, such as environmental cues, geographical location, or individual characteristics of grape varieties [8]. This study focused on the bacterial endophytes from wild V. amurensis growing in natural conditions. A comparative analysis of findings from the cultivation-dependent (bacteriological seeding in 2018–2021) and cultivation-independent (NGS) approaches revealed that Gammaproteobacteria, Alphaproteobacteria, Actinobacteria, Bacteroidia and Bacilli were the dominant classes in the endophytic bacteriome of the wild grape. However, the ratio between the genera of endophytic bacteria considerably varied according to the two methods. This can be explained by the fact that we sowed bacterial strains over the 4-year period, while NGS was performed only for probes collected in the summer and autumn of 2021. Weather conditions varied considerably each year. In addition, the lower sensitivity of the culture-dependent approach contributed to the difference between the results. In our opinion, these two conditions led to the observed differences in the percentages of endophytic bacterial genera. Therefore, it is necessary to apply both a cultivation-dependent and a cultivation-independent approach over a time period of several years in order to obtain a more comprehensive picture of endophytic bacteria assemblage in the same plant. The cultivation-dependent method demonstrated that 10 bacterial genera prevailed in the V. amurensis endophytic community (Pantoea, Erwinia, Pseudomonas, Bacillus, Curtobacterium, Rhizobium (sphaerophysae group), Frigoribacterium, Sphingomonas, Xantomonas, and Buttiauxella) (Figure 2). The data obtained on the main genera of endophytic bacteria present in V. amurensis were similar to the previously published data on bacterial community composition in V. vinifera from Australia and Italy [6,7,8,9,27]. While studying the endophytic bacteria distribution over several years (2018, 2019, 2020 and 2021), we discovered an interesting relationship between the weather conditions and bacterial biodiversity: a minimal number of endophytic bacteria (only 155 strains) were detected under hot and dry weather conditions in the Primorsky Territory of Russia (2021 year) (Figure 4a and Table 1). On the contrary, we isolated the maximum number of endophytic bacteria (363 strains) under cold and damp conditions in 2020 using the same methods (Figure 4a and Table 1). Thus, an average temperature of 15 °C and a large amount of precipitation contribute to both quantitative and qualitative biodiversity of endophytic bacteria of V. amurensis. Similar to the results obtained by Baldan et al. [11], the bacterial composition changed depending on the season of sampling. We showed that the composition of bacterial endophytes was richer in autumn than in summer. This was probably due to the gradual colonization of endophytic bacteria during growth and development of the aboveground grapevine organs, e.g., leaves. In addition, there were some unique genera of bacteria in wild grape V. amurensis either in the summer or in the autumn periods. This indicates a special influence of various environmental physical parameters (air temperature, precipitation, illumination, etc.), on the percentage ratio between different classes of bacteria present in the intercellular space of grapevine tissues. The analysis of the bacteriological community in different organs of V. amurensis showed that most endophytic bacteria inhabited stems and leaves. This conclusion confirmed previously known information that the endophytes of grapes travel from the root system through conducting vessels into the stem and then move into the leaves [12]. Moreover, we noted that number of endophytic bacterial strains and the amount of ASVs were significantly lower in summer leaves than in autumn ones. The data indicate that the bacteria had not arrived in time to settle in the leaves at the beginning of the summer season compared to the autumn. A similar situation was also observed in the case of berries and seeds: the number of ASVs detected and the number of isolated strains of endophytic bacteria were 3–12 and 2.2–8.9 times lower in the berries than in the stems and leaves, respectively (Figure 1). This effect was most likely due to the fact that the berries developed later than the leaves and contained more phenolic compounds, which prevented active endophyte accumulation. The lowest biodiversity of endophytic bacteria was found in the grape seeds, which can be explained by the better protection of seeds by the berry pulp. Interestingly, the metagenomic analysis revealed two genera of endophytic bacteria unique to the grape seeds, i.e., the genera Amycolatopsis and Pseudoalteromonas (Figure 1 and Supporting Information S2). It is known that bacteria of the genus Amycolatopsis are able to produce antibiotics [28], while bacteria of the genus Pseudoalteromonas are usually found in marine eukaryotes and are capable of producing bioactive compounds [29]. Therefore, it is possible that symbiosis of the seed-associated bacteria with the plant could contribute to seed protection. Next, we compared the data on endophytic microbial assemblage in V. amurensis with the previously studied endophytic bacteria communities in grapevines from other regions of the world, including Germany [26] and USA (California) [12]. Nonmetric multidimensional scaling showed that samples from Russia (Vladivostok), USA (California), and Germany were located in separate clusters. The bacteriome of grapes was represented by 23 main classes of bacteria. The prevalent classes were Gammaproteobacteria, Alphaproteobacteria, Actinobacteria, Bacteroidia and Bacilli for all grapes. Gammaproteobacteria was the dominant class in all samples (40–50%), with Pseudomonas as the most represented genus in USA and Germany, and Comamonadaceae (Betaproteobacteria)–in Russia. There were 46 genera common to all regions of material collection. We also detected a number of unique genera for USA (14 genera), Russia (11 genera), and Germany (4 genera). The differences between the endophytic bacteriome compositions in the grapevines show that the place of growth also affects the percentage ratio between classes of endophytic bacteria. However, this issue needs further investigation with additional RNA-seq libraries from other cultivars. In order to present a more complete picture of grapevine microbiota, it is necessary to expand the studies on biodiversity of bacterial endophytes to a higher number of cultivars and individuals from the wild and cultivated Vitis species growing globally. The data obtained in this investigation are interesting for practical application in agriculture. Knowledge about the biological diversity of endophytic bacteria in wild grapes, including V. amurensis, could prove useful for the development of new approaches to increase the stress resistance of cultivated grapes, yield, and fruit quality. For example, it has been shown that some endophytic bacterial isolates from domesticated and wild V. vinifera grapevines were highly active against Botrytis cinerea, Neofusicoccum parvum, Botryosphaeria dothidea, Botryosphaeria obtuse, Pochonia chlamydospora, Plasmopara viticola, and Rhizobium vitis in vitro [9,14,30]. Bacillus and Pantoea exhibited the most prominent antimicrobial activities. Moreover, bacterial endophyte Bacillus licheniformis isolated from V. vinifera has been shown to stimulate the production of secondary metabolites, such as monoterpenes, exhibiting antioxidant activity, and sesquiterpenes, exhibiting antibacterial effects [31]. Moreover, B. licheniformis produced carotenoids, which can act as antioxidants useful for plant stress protection [32]. It has been shown that bacterial endophytes B. licheniformis and Pseudomonas fluorescens can modulate ABA metabolism in inoculated grape plants, which gives them an advantage over uninfected plants in drought conditions [31,33]. Grape endophytic bacteria have previously been shown to favorably affect the quality of grape fruit. For example, grapevine inoculation with endophytic Acinetobacter lwoffii, Bacillus subtilis, and Pseudomonas fluorescens was effective against Botrytis cinerea and led to the accumulation of host-synthesized phytoalexins, especially trans-resveratrol (3,5,4′-tryhydroxystilbene) and its oligomer, trans-ε-viniferin, which could contribute to the grape fruit metabolite composition [34]. Interestingly, native endophytes and products based on endophytes from the wild grape V. amurensis can stimulate stilbene production in grape cell suspensions, which could further contribute to the development of a new stimulators of stilbene biosynthesis in grapevine or grape cell cultures [35,36]. Taken together, these obtained data can be employed to create endophyte-based preparations for plant pathogen protection. Thus, future studies on the biochemical properties (e.g., the ability to secrete phytohormones or biologically active substances) or biological functions (e.g., plant disease protection) of isolated endophytic bacteria can greatly contribute to crop protection and plant functional studies. 4. Materials and Methods 4.1. Plant Material For both cultivation-dependent and cultivation-independent approaches, we used tissues of two healthy 10–15-year-old vines of V. amurensis located at a distance of 1 km from each other in a nonprotected natural population near Vladivostok, Russia (the southern Primorsky Territory of the Russian Far East, longitude 43.2242327 and latitude 131.99112300). Shoots, leaves (young stems 7–8 cm long with three healthy leaves), berries (green and mature), and seeds were collected at 10–11 a.m. on low-cloud days without precipitation, the air temperature was 17–20 °C. The values of the average temperatures and precipitation in 2018–2021 in Vladivostok (Primorsky Territory of Russia) are shown in the Table 1. Each plant material specimen was delivered to the laboratory within 30 min. For the cultivation-dependent approach (bacterial sowing), plant materials were selected in July and September from 2018 to 2021. Two biological replicates (two individual vines) were collected in July, and two biological replicates–in September. Thus, there were 4 biological replicates per year. In total, 16 biological replicates were collected and analyzed by the cultivation-dependent approach from 2018 to 2021. For the cultivation-independent approach (NGS) we used grapevine material collected in July and September of 2021 (a total of 4 biological replicates) and applied 2 technical replications per biological replicate. 4.2. Isolation and Identification of the Endophytic Bacteria The grapevine tissues (1.5 g) were washed under running water with soap and washed sequentially under sterile conditions in 75% ethanol for 2 min, 10% hydrogen peroxide for 1 min, and five times in sterile water. To check the efficacy of this method of surface sterilization, 100 µL of the last wash water was incubated on the R2A medium [37]. No microorganism growth was observed 3 days after the last portion of washing water had been plated in the Petri plates containing the growth media. This validated the quality of the performed superficial sterilization of the grape tissues. The surface-sterilized tissue of V. amurensis was ground to a homogeneous mass in a sterile mortar; the resulting juice was squeezed, and a 100 μL aliquot was transferred to R2A media in Petri plates. After 3 days, the grown bacterial colonies were sampled and carefully transferred to a new sterile Petri plate for repeated cultivation. We isolated almost all the seeded colonies into separate strains, a total of 933 separate strains of endophytic bacteria were obtained over 4 years of biological sowing. DNA of the 933 bacteria strains was isolated by the hexadecyltrimethylammonium bromide (CTAB) method with modifications [38]. Bacterial 16S rRNA gene sequences were amplified using universal bacterial primers for the amplification of approximately 1500 bp 16S PCR products (8F, 5′AGA GTT TGA TCM TGG CTC AG and 1522R, 5′AAG GAG GTG ATC CAR CCG CA) [39]. PCR products were sequenced using an ABI 3130 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA) according to the manufacturer’s instructions as described [35,36]. The Basic Local Alignment Search Tool (BLAST) program was used for sequence analysis. Multiple sequence alignments were performed using the Clustal X program [40]. A sequence identity of ≥99% is considered as a sufficient threshold value for taxonomic identification bacteria genus. 4.3. DNA Extraction, PCR Condition, Library Preparation, and Sequencing DNA for NGS was isolated using two approaches. The first approach used the method employed in our laboratory [38] with small modifications. Namely, 50 mg of V. amurensis tissue was taken 800 µL CTAB-buffer with 2× content of NaCl (100 mM Tris pH 7.5, 1.4 M NaCl, 40 mM EDTA pH 7.5, 1% CTAB) was added, incubated for 1 h 60 °C in a Gnom thermostat (DNA-technology, Moscow, Russia). Then 300 µL of chloroform was added, gently mixed and centrifuged for 10 min at 4 °C and 13,200 rpm (Ependorf, Germany). Further, a supernatant (420 µL) was selected in separate test tubes with 950 µL of 96% ethanol and frozen at −20 °C overnight. Then, the DNA in ethanol was centrifuged for 10 min at 4 °C and 13,200 rpm, and then the supernatant was removed. The precipitate was dried until the ethanol completely evaporated at room temperature (30 min). The precipitate was dissolved in 100 µL of distilled water and then purified on Plasmid DNA purification columns Plasmid MiniPrep kit per manufacturer’s protocol (Evrogen, Moscow, Russia). As a result, the DNAs were eluted in 50 µL of elution buffer. According to the second approach, the DNA was extracted from 30 mg of V. amurensis tissue using the ZymoBIOMICS DNA miniprep kit per manufacturer’s protocol (Zymo Research, Irvine, CA, USA). DNA was assessed for quality and quantity using the NanoPhotometer P300 (IMPLEN, Munich, Germany). The DNA samples were sent to Evrogene (Moscow, Russia) for high-throughput sequencing using Illumina technology. The libraries were prepared for sequencing according to the protocol described in the manual “16S Meta-genomic Sequencing Library Preparation” (Part #15,044,223 Rev. B; Illumina, San Diego, CA, USA). Bacterial 16S rRNA regions were amplified from all samples using primers 515F (5′GGTAATACGKAGGKKGCDAGC) and 806R (5′RTGGACTACCAGGGTATCTAA) modified for Vitis sp. plants. After obtaining the amplicons, the libraries were purified and mixed equimolarly using the SequalPrep™ Normalization Plate Kit (Cat #A10510-01, ThermoFisher, Waltham, MA, USA). Quality control of the obtained library pools was performed using Fragment Analyzer and quantitative analysis was performed using qPCR. The library pool was sequenced on Illumina MiSeq (2 × 250 paired end) using MiSeq Reagent Kit v2 (500 cycles). The FASTQ files were obtained using bcl2fastq v 2.17.1.14 Conversion Software (Illumina, San Diego, CA, USA). The phage PhiX library was used to control sequencing parameters. Most of the reads pertaining to phage DNA were removed during demultiplexing. Bacterial sequences were deposited in NCBI under the accession number PRJNA813962 and in database of laboratory Biotechnology, Federal Scientific Center of the East Asia Terrestrial Biodiversity, Far Eastern Branch of the Russian Academy of Sciences, Russia (https://biosoil.ru/downloads/biotech/Vitis%20metagenom/2021-09=Vitis_amurensis_endophytes_16s), (accessed on 14 March 2022). 4.4. Computational Analysis For the comparative analysis of endophytic bacteriomes from V. amurensis and V. vinifera, we selected two studies from California (cv. ‘Syrah’) and Germany (cv. ‘Cabernet Dorsa’) where the biodiversity of endophytic bacteria was evaluated [12,26]. The main criteria for the selection of metagenomic studies were the presence of a bacterial film elimination step in the “Materials and Methods” section of research, different geographical location and the same 16s rRNA sequencing region (515F-806R). From the selected studies, we selected samples belonging to the above-ground parts of the plant and not subjected to any treatments or infections. The samples used in the comparative analysis are presented in Supporting Information S8. Raw readings of all samples were subjected to further bioinformatic analysis. NGS reads were preprocessed using QIIME 2 [41] and DADA2 programs [42]. The primers, remaining PhiX reads, and chimeric sequences were removed, and paired-end reads were merged and sorted. The authors of the DADA2 algorithm refer to the sequences as amplicon sequence variants (ASVs). This algorithm has the capacity to resolve sequences differences to a single nucleotide, allowing for more robust identification. Taxonomic identification of ASVs was performed using the QIIME 2 Scikit-learn algorithm [43] using the Silva 138 pre-trained classifier (99% OTUs from 515F/806R region of sequences) [44]. The obtained data were processed using the R language. The phyloseq library [45] and tidyverse package [46] were used in pre-filtering and data preparation. Taxa for bar plot, heatmap and UpSet diagram visualizations were filtered based on relative abundance of >0.1% for each biocompartment. We merged the taxonomic ranks in bar plots that were relative abundant <0.1% in each factor to one group called “other”. Shannon alpha diversity and Bray–Curtis beta diversity data were obtained using the Vegan package [47]. Bray–Curtis dissimilarity data were transformed to even sampling depth and converted to nonmetric multidimensional scaling (NMDS). A pairwise Wilcoxon rank sum test with Bonferroni correction was performed to analyze the alpha diversity data between groups. Statistical validation of beta diversity data was performed using the PERMANOVA test with 999 permutations [47]. The ggplot2 [46] and ComplexHeatmap [48] R libraries were used in the graphical representation of the results. 5. Conclusions In this study, we firstly described the biodiversity of endophytic bacteria in wild-growing grapevine V. amurensis. According to both the cultivation-dependent and cultivation-independent approaches, Gammaproteobacteria, Actinobacteria, Alphaproteobacteria, Bacilli and Bacteroidia represented the dominant classes of bacteria. The data indicated that the weather conditions significantly affected the number and biodiversity of endophytic bacteria in V. amurensis. Namely, lower temperatures (15–16 °C) and increased precipitation (140–280 mm in month) favored both the quantitative and qualitative diversity of endophytic bacteria inhabiting the intercellular space of V. amurensis tissues. The obtained data also show that the composition of bacterial endophytes was richer in autumn than in summer. Among the aboveground organs of grapes, the stems and leaves were the leaders in quantitative composition and biodiversity of endophytic community. In addition, this study showed that the community of endophytic bacteria of V. amurensis was closer to the endophytic community of V. vinifera growing in Germany. Thus, this paper presented and discussed various factors that affect the biodiversity of endophytic bacteria in wild grapevine V. amurensis. Considering that a high number of factors affects the biodiversity of endophytic bacteria in V. amurensis, this study should be expanded to include more individuals and geographic areas where this grapevine species is present. The knowledge about the biological diversity of endophytic bacteria in wild grapes V. amurensis will development of new approaches to increase grapevine stress resistance as well as the yield and quality of fruits. Supplementary Materials The following are available online at https://www.mdpi.com/article/10.3390/plants11091128/s1, Supporting Information S1. Intersections in our data (Data type); Supporting Information S2. Intersections in our metagenome data (Organ material)—Figure 1d; Supporting Information S3. NMDS ordination plots and PERMANOVA results in our data; Supporting Information S4. Intersections in data of cultivate-dependent method (Date)—Figure 4b; Supporting Information S5. Intersections in data of cultivate-dependent method (Season)—Figure 5c; Supporting Information S6. Intersections in our metagenome data (Season)—Figure 5d; Supporting Information S7. Intersections in our metagenome data (Plants)—Figure 6b; Supporting Information S8. Samples used in comparative analysis of the grape bacteriomes; Supporting Information S9. Alpha diversity results; Supporting Information S10. PERMANOVA results in comparative analysis of the bacterial biodiversity between grapes; Supporting Information S11; Intersections between Vitis metagenome data—Figure 7d. Click here for additional data file. Author Contributions O.A.A. and K.V.K. performed research design, data analysis, paper preparation, and the experimental process. O.A.A. and N.N.N. performed DNA isolation of microorganisms, PCR, and sequencing analysis. O.A.A. performed DNA isolation for NGS. N.N.N. performed bioinformatic analysis. A.S.D. performed paper preparation. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by a grant from the Russian Science Foundation (grant number 20–74–00002). Data Availability Statement The data presented in this study are available within the article and supplementary material. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Comparative analysis of the endophytic community composition in different organs of wild grape Vitis amurensis obtained by the cultivation-dependent (bacteriological sowing (Sow)) and cultivation-independent approach (the next generation of sequencing (NGS)). The composition of endophytic bacteria of grape V. amurensis depends on the plant organ: (a) Class-level taxonomical bar plots for the bacterial community of bacteriological sow in berry, leaf, seed, stem and the sum of data for all organs; (b) Class-level taxonomical bar plots for the bacterial community as a result of the next generation of sequencing (NGS) in berry, leaf, seed, stem and the sum of data for all organs; (c) Genus-level UpSet diagrams depicting overlapping taxa of bacteriological sow in berry, leaf, seed, stem and the sum of data for all organs; (d) Genus-level UpSet diagrams depicting overlapping taxa of NGS in berry, leaf, seed and stem. Taxa were filtered based on relative abundance of >0.1% for each biocompartment. Filtered taxa in bar plot placed in “other” category and removed from UpSet diagram. Number of colonies (for sow) or amplicon sequence variants (ASVs) located above taxonomical bar plots. Figure 2 Genus-level relative abundance heat maps of significant taxa obtained through the cultivation-independent method (next generation of sequencing (NGS)) and cultivation-dependent method (bacteriological sowing (Sow)). The top 10 most abundant taxa from each factor are displayed. White squares (NA) represent absence of taxa. Figure 3 Genus-level relative endophytic bacteria abundance heat maps of significant taxa the next generation of sequencing (NGS) in different grape organs (stem, leaf, berry and seed). The top 40 most abundant taxa from each factor are displayed. White squares (NA) represent absence of taxa. The intersection selection is made based on the Figure 1d. Figure 4 Composition of endophytic bacterial community in wild grape Vitis amurensis depending on the year of material collection. (a) Class-level taxonomical bar plots for the bacterial community composition in 2018–2021; (b) Genus-level UpSet diagrams depicting overlapping taxa of bacteriological sow and next-generation sequencing. Taxa were filtered based on relative abundance of >0.1% for each biocompartment. Number of colonies located above taxonomical bar plots. Figure 5 Composition of endophytic bacterial community in wild grape Vitis amurensis depends on the season of material collection: (a) Class-level taxonomical bar plots for the bacterial community of cultivation-dependent approach in summer and autumn; (b) Class-level taxonomical bar plots for the bacterial community as a result of cultivation-independent approach (next generation of sequencing (NGS)) in summer and autumn; (c) Genus-level UpSet diagrams depicting overlapping taxa of bacteriological sow in summer and fall; (d) Genus-level UpSet diagrams depicting overlapping taxa of NGS in autumn and summer. Taxa were filtered based on relative abundance of >0.1% for each biocompartment. Filtered taxa in bar plots placed in “other” category and removed from UpSet diagram. Number of colonies or amplicon sequence variants (ASVs) located above taxonomical bar plots. Figure 6 Composition of endophytic bacterial community in two different Vitis amurensis plants: (a) Class-level taxonomical bar plots for the bacterial community as a result cultivation-independent approach (the next generation of sequencing (NGS)) in Plant A and Plant B; (b) Genus-level UpSet diagrams depicting overlapping taxa of NGS in Plant A and Plant B. Taxa were filtered based on relative abundance of >0.1% for each biocompartment. Filtered taxa in bar plots placed in “other” category and removed from UpSet diagram. Number of amplicon sequence variants (ASVs) located above taxonomical bar plots. Figure 7 A comparison of endophytic bacterial communities in cultivated Vitis vinifera from USA (California) and Germany with the endophytic community in Vitis amurensis from the Russian Far East (Vladivostok) (a) Shannon’s alpha diversity boxplot; (b) Bray–Curtis beta diversity NMDS plot; (c) Class-level taxonomical bar plots for the bacterial community composition V. vinifera from USA (California), Germany, and V. amurensis from Russia (Vladivostok); (d) Genus-level UpSet diagrams depicting overlapping taxa of bacteriological sow and next-generation sequencing. Taxa were filtered based on relative abundance of >0.1% for each biocompartment. Filtered taxa in bar plot placed in “other” category and removed from UpSet diagram. Number of amplicon sequence variants (ASVs) located above taxonomical bar plots. Figure 8 Genus-level relative endophytic bacteria abundance heat maps of significant taxa of Vitis vinifera from USA (California), Germany, and Vitis amurensis from Russian Far East (Vladivostok). The top 20 most abundant taxa from each factor are displayed. White squares (NA) represent absence of taxa. The intersection selection is made based on the Figure 7d. plants-11-01128-t001_Table 1 Table 1 The values of the average temperature and amount of precipitation from 2018–2021 in Vladivostok, Primorsky Territory of Russia. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094784 ijms-23-04784 Article Targeting Cell Death Mechanism Specifically in Triple Negative Breast Cancer Cell Lines Pruteanu Lavinia-Lorena 123 https://orcid.org/0000-0002-3055-4747 Braicu Cornelia 4* https://orcid.org/0000-0001-9412-6867 Módos Dezső 1 Jurj Maria-Ancuţa 4 https://orcid.org/0000-0002-3926-5423 Raduly Lajos-Zsolt 4 Zănoagă Oana 4 Magdo Lorand 4 https://orcid.org/0000-0002-7450-9454 Cojocneanu Roxana 4 Paşca Sergiu 4 https://orcid.org/0000-0003-2927-4622 Moldovan Cristian 25 https://orcid.org/0000-0001-7159-6102 Moldovan Alin Iulian 25 https://orcid.org/0000-0001-9397-0791 Ţigu Adrian Bogdan 2 Gurzău Eugen 6 https://orcid.org/0000-0001-8524-743X Jäntschi Lorentz 78 Bender Andreas 1 https://orcid.org/0000-0001-5828-1325 Berindan-Neagoe Ioana 4 Kim Nam Deuk Academic Editor 1 Department of Chemistry, Centre for Molecular Science Informatics, University of Cambridge, Cambridge CB2 1EW, UK; pruteanulavinia@gmail.com (L.-L.P.); dr.dezso.modos@gmail.com (D.M.); ab454@cam.ac.uk (A.B.) 2 MedFuture Research Center for Advanced Medicine, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400377 Cluj-Napoca, Romania; moldovan.cristian1994@gmail.com (C.M.); alin.moldovan92@yahoo.ro (A.I.M.); adrianbogdantigu@gmail.com (A.B.Ț.) 3 Department of Chemistry and Biology, North University Center at Baia Mare, Technical University of Cluj-Napoca, 4800 Baia Mare, Romania 4 Research Center for Functional Genomics, Biomedicine and Translational Medicine, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400337 Cluj-Napoca, Romania; ancajurj15@gmail.com (M.-A.J.); raduly.lajos78@gmail.com (L.-Z.R.); zanoaga.oana@gmail.com (O.Z.); lorand.magdo@gmail.com (L.M.); cojocneanur@gmail.com (R.C.); pasca.sergiu123@gmail.com (S.P.); ioana.neagoe@umfcluj.ro (I.B.-N.) 5 Department of Pharmaceutical Physics-Biophysics, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania 6 Environmental Health Center, 400240 Cluj-Napoca, Romania; egurzau@ehc.ro 7 Institute for Doctoral Studies, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania; lorentz.jantschi@chem.utcluj.ro 8 Department of Physics and Chemistry, Technical University of Cluj-Napoca, 400641 Cluj-Napoca, Romania * Correspondence: cornelia.braicu@umfcluj.ro 26 4 2022 5 2022 23 9 478418 3 2022 15 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/). Triple negative breast cancer (TNBC) is currently associated with a lack of treatment options. Arsenic derivatives have shown antitumoral activity both in vitro and in vivo; however, their mode of action is not completely understood. In this work we evaluate the response to arsenate of the double positive MCF-7 breast cancer cell line as well as of two different TNBC cell lines, Hs578T and MDA-MB-231. Multimodal experiments were conducted to this end, using functional assays and microarrays. Arsenate was found to induce cytoskeletal alteration, autophagy and apoptosis in TNBC cells, and moderate effects in MCF-7 cells. Gene expression analysis showed that the TNBC cell lines’ response to arsenate was more prominent in the G2M checkpoint, autophagy and apoptosis compared to the Human Mammary Epithelial Cells (HMEC) and MCF-7 cell lines. We confirmed the downregulation of anti-apoptotic genes (MCL1, BCL2, TGFβ1 and CCND1) by qRT-PCR, and on the protein level, for TGFβ2, by ELISA. Insight into the mode of action of arsenate in TNBC cell lines it is provided, and we concluded that TNBC and non-TNBC cell lines reacted differently to arsenate treatment in this particular experimental setup. We suggest the future research of arsenate as a treatment strategy against TNBC. triple negative breast cancer breast cancer gene expression arsenate microarray mode of action UEFISCDICANCERTER-p53 This work was partially funded by UEFISCDI, projects entitled “Genomic mapping of the population from polluted area with radioactivity and heavy metals to increase national security and Advanced Innovative approaches for predictable regenerative medicine”, PNII project entitled “Modulation of pro/anticarcinogenic effect of toxic chemical agents in breast cancer multitargeted therapy” (CANCERTER-p53). ==== Body pmc1. Introduction Breast cancer is a common female malignancy, representing 11.6% of all cancer cases worldwide, Ref. [1] particularly in developing countries [2,3,4]. Among all breast cancer subtypes, triple negative breast cancer (TNBC) is differentiated from other types of breast cancer by not expressing three receptors, namely the Estrogen receptor, Progesterone receptor and the receptor tyrosine kinase Her2/neu [3,4,5]. TNBC occurs more often in younger women and it is more difficult to identify on a mammogram [2,3,4]. Furthermore, TNBC tends to grow faster than other types of cancer and it frequently recurs [3,6]. Standard therapy across breast cancer subtypes includes surgery, chemotherapy, and radiation. Non-selective chemotherapies are especially important for TNBC patients, because no targeted therapy is available. Also, for those patients who have developed metastases, surgery alone is not sufficient, and additional general chemotherapy is necessary [4,6,7,8,9,10,11]. Hence, treatment options for TNBC differ from other types of breast cancer, and they are generally more limited [3,5]. All of these factors necessitate potential novel chemotherapeutic agents, ideally with at least limited selectivity. Among non-specific cancer treatments, arsenic-derived compounds are commonly used [12,13,14]. In the human body, inorganic arsenic compounds are converted to arsenite (arsenic in the +3 oxidation state) and arsenate (arsenic in the +5 oxidation state). Arsenite is significantly more toxic than arsenate, which is related to both reactivity and transport [12,13,14]. Upon entering the cell, arsenate can be reduced to arsenite, leading to both chemical species being present depending on the redox state of the cell [15,16,17]. Arsenate is known to cause direct and indirect DNA damage through reactive oxygen species, [18] and can affect the DNA repair mechanism at low concentrations [19]. Increased inorganic phosphate transport observed in the MDA-MB-231 cell line may be associated with the higher energy demands linked to its metastatic phenotype and can increase the arsenate intake as well [20]. Arsenic has been studied more extensively on the transcriptomic level due to its clinical relevance, [21] however the same is not yet true for arsenate, which is the contribution of the current work [20]. On the mechanistic level, the activity of arsenate is largely unknown in breast cancer. Here we attempted to unravel the effects of arsenate on TNBC cells in comparison with one double positive breast cancer (DPBC) and one normal breast cell line. In particular, we used the normal breast cell line HMEC (Human Mammary Epithelial Cells), the DPBC cell line MCF-7, as well as the TNBC cell lines Hs578T and MDA-MB-231. HMEC and MCF-7 possess intact DNA repair mechanisms according to the COSMIC cell line encyclopedia, while the two TNBC cell lines are p53 mutants [22]. The purpose of this study was to investigate whether arsenate can be a selective chemotherapeutic agent against TNBC cell lines. For this, we examined the response to arsenate treatment in autophagy, apoptosis and cell proliferation via phenotypic and transcriptomics readouts. Firstly, we evaluated the effect of arsenate treatment on the cellular level. We performed functional tests, including colony assay formation, autophagy and apoptosis investigation using fluorescence microscopy, and measured cytoskeletal response by immunofluorescence staining followed by confocal microscopy evaluation and dark field microscopy for morphologic alteration. Then, after seeing that arsenate causes apoptosis specifically in the Hs578T and MDA-MB-231 cell lines, we investigated whether there is any mechanistic change in the transcriptome of the cell lines responding to the low arsenate concentration using cDNA microarrays and regularized discriminant analysis (RDA). Finally, findings from the gene expression analysis were validated by qRT-PCR, and at the protein level by ELISA and immunofluorescence confocal microscopy. 2. Results 2.1. Arsenate Exposure Decreases Colony Formation in Cancer Cell Lines We first assessed the effect of arsenate exposure on colony formation capacity, which is a widely used test to assess the sensitivity of tumor cell lines to therapeutic agents [23]. The test evaluates the clonogenic capacity, responding to much lower doses than the standard MTT test. The result (Figure 1A) shows that arsenate concentration of 50 nM (final concentration in the cell culture medium) has the capacity to attenuate the colony formation rate in all three breast cancer cell lines (for MCF-7, 0.76 fold; Hs578T 0.83 fold; MDA-MB-231 to 0.87 fold of control). The effect of arsenate treatment on the ability of forming colonies has been shown in previous studies, Ref. [24] and the current results are in agreement with that. (The HMEC cell line was unable to form colonies, since it is a non-tumorous cell line). 2.2. Effect of Arsenate on the Modulation of Apoptosis and Autophagy in MCF-7, Hs578T, and MDA-MB-231 Cells Given the decrease of colony formation ability described above, we next investigated its mechanistic background, focusing on apoptosis and autophagy. We stained the cells with monodansylcadaverine (MDC), a fluorescent marker for the acidic endosomes, lysosomes, and late-stage autophagosomes [25]. An increase of the MDC signal was observed in the case of treated cancer cell lines compared to untreated cells (Figure 1B), which generally labels later stages of the degradation processes, as opposed to being a specific marker for autophagy [25]. Arsenate treatment increased the number of autophagy vacuoles containing MCF-7 cells by a factor of 1.91 compared to control (p = 0.0004). However, the increase is not observed for arsenate treated vs. untreated HMEC cells (Figure 1B; p > 0.05 in a t-test). The number of autophagic cells in the Hs578T and MDA-MB-231 cell lines increased significantly (by a factor of 5.31 and 6.43, p = < 0.0001 and 0.0001 in a t-test, respectively). The cells were then simultaneously stained with Annexin-V and FITC/PI to visualize apoptosis. Only Annexin-V FITC staining visualizes early apoptosis, meanwhile both Annexin-V and FITC PI are markers for late apoptosis. An increased apoptotic rate was observed in the triple negative breast cancer cell lines as follows. In the Hs578T cell line, both the early and late apoptotic state was visible, while in case of the MDA-MB-231 cells, the majority of cells appeared in the late apoptotic phase (70–90%; Figure 1C). The number of apoptotic cells also increased in the DPBC MCF-7 cell line (by a factor of 2.82; p = 0.026 in a t-test), but not in the HMEC cell line (p > 0.05). These data suggest the involvement of apoptosis and likely autophagy as a response to arsenate exposure, which, based on the data shown here, is more pronounced in the TNBC cancer cell lines. Consistent with that, arsenic in oxidation state +3 has previously been found to interfere with intrinsic and extrinsic apoptosis and autophagy mechanisms in the breast cancer cell lines MCF-7 and MDA-MB-231 [26]. Arsenic trioxide was found to suppress cell growth, to stimulate apoptosis, and to be involved in retarded cell invasion by interfering with coding and non-coding gene regulation [27,28,29,30]. Autophagy has been presented in previous literature as a protective mechanism against arsenite induced oxidative stress, which causes genome damage [31]. Meanwhile, there is no literature information related to the modulation of autophagy by arsenate. Based on the current study, we can conclude that arsenate exposure likely activates autophagy (with some ambiguity from the MDC marker used as in our previous studies [32,33]) and (more certainly) apoptosis, and hence similar cellular mechanisms as arsenite. In our study the activation of autophagy observed by fluorescence microscopy is supported by microarray data. The idea of this study was to demonstrate how complex the mechanistic effects of arsenate are. On this occasion we did not focus on a single mechanism like the autophagy. Microarray data shows that arsenate’s effects are complex, emphasizing the crosstalk among the different signalling pathways. This observation was is confirmed as well in publications such as [34]. 2.3. Dark-Field Microscopic and Cytoskeletal Evaluation We next used dark field microscopy to assess cellular morphology, which allows for the assessment of cytoskeleton alterations and hence the actin and tubulin status of a cell. It can also resolve more discrete features such as membrane disorganization, blebbing and apoptotic bodies. In the case of HMEC cells, only a slight modification of morphology was observed (Figure 2). The cells appear slightly elongated in the arsenate treated group compared to the control. Nuclei have a normal round/elliptical shape with no signs of fragmentation. After arsenate exposure the cell membrane of TNBC cells became thick and fragmented (Figure 2F,H, green arrows). Cellular stress becomes visible through abnormal elongated cells for MCF-7 and Hs578T cells and irregular nuclei surrounded by sparse apoptotic bodies (Figure 2D,F). Numerous apoptotic bodies can be seen in the case of arsenate treated cells (Figure 2H), and the apical membrane (Figure 2F) shows signs of breakage and a higher degree of disorganization. Apoptopodia-like projections are prominent in the case of Hs578T cells (Figure 2F), which are less pronounced for MDA-MB-231 and MCF-7 and not present in the case of HMEC cells. In the case of Hs578T, the presence of cells with abnormally high nuclear displacement and the formation of tunneling nanotubes (Figure 2F) can be observed. All of this shows that HMEC cells are not going through the same strong apoptotic response that is observed for the tumor cells. To assess whether the morphological response of the cellular cytoskeleton to arsenate treatment is in accordance with the dark field microscopy images, we next stained the actin cytoskeleton with Phalloidin-FITC dye and the cell nuclei with DAPI staining, visualized in Figure 3. The response of HMEC cells (Figure 3AI,II) to arsenate exposure was reduced compared to the cancer cell lines, and it can be observed that the cells are now more compact and have a slightly elongated shape. Also, the nucleus and cytoplasm area of HMEC cells is reduced as a result of arsenate exposure. Some larger nuclei are still visible in the case of HMEC cells, which indicates a stress response; however, the nuclei are not fragmented. In contrast, in the case of breast cancer cells, the nuclear fragmentation is more pronounced in TNBC cells (Figure 3BII). Alteration of the cytoskeletal organization is overall more pronounced in breast cancer cells. Hs578T cells treated with arsenate do not present significant alterations to the cytoskeleton (Figure 3CII); however, irregular and fragmented nuclei are now present as an effect of arsenate treatment (indicated by red arrows). In the case of MDA-MB-231 untreated cells (Figure 3DI), we can observe normal morphology; meanwhile, those cells treated with arsenate (Figure 3DII) have giant multinucleated cells and the cytoskeleton staining is now stronger on the edges of the membrane. This is in agreement with previous work in that arsenic trioxide is a chemical agent recognized to produce cytoskeletal injury [35]. It has also been previously demonstrated in a separate study that arsenic trioxide affects the cytoskeleton, cell adhesion and epithelial mesenchymal transition- related genes [36]. What is novel in this work though is that arsenate’s therapeutic stress produces pro-apoptosis signals largely selectively in TNBC cells (based on dark-field microscopic and cytoskeletal evaluation). We then wanted to understand these changes at the transcriptomic level. 2.4. Mode-of-Action Analysis of Arsenate Treatment Based on Gene Expression Data We next investigated the mode-of-action of arsenate treatment in the four different cell lines based on gene expression data (see Figure 4A for the experimental workflow and methods section for experimental details). A Pearson correlation matrix analysis visualized as a heatmap (shown in Figure 4B) showed that the first differentiating factor between samples is the cell line, and only the second one is the arsenate treatment. This is in agreement with previous experiments in breast cancer cell lines and their response to chemotherapeutics [37]. We next used principal component analysis (PCA) to visualize differences between the different cell lines and treatment conditions further, the results of which are shown in Figure 4B. It can be seen, in agreement with the correlation analysis, that the four cell lines are located in rather distinct locations of PCA space. Arsenate treated cells, as a whole, are not distinct from untreated cells in a specific direction in the first three principal components; however, they generally differ from the non-treated cell lines (Figure 4B). We next evaluated gene expression on an individual gene and pathway level. First, we found the number of differentially expressed genes in the four arsenate-treated cell lines, which were 81 for HMEC, zero for MCF-7, 1231 for Hs578T and 275 for the MDA-MB-231 cell line (with a q-value < 0.1 in a Benjamini-Hochberg False Discovery Rate-corrected t-test and |log2 FC| > 1; see Table S3 for details in the Supplementary Materials). This seems to an extent surprising given the toxicity of arsenic [38], and one reason might be that the concentration of arsenate (50 nM) is relatively low. Furthermore, the two TNBC cell lines had a stronger response than the two other cell lines investigated here. However, these differentially expressed genes were not enriched in any gene ontology biological process, (FDR > 0.1) nor were they enriched by using the CAMERA method for gene-set enrichment analysis (FDR > 0.1). To distinguish the weak transcriptomics signal, we compared the response of the TNBC and DPBC and normal cell lines. 2.5. Arsenate Response in Triple Negative Cell Lines vs. Double Positive and Normal Cell Line We used regularized discriminant analysis (RDA) to differentiate the response to arsenate between the cell lines as follows. For this kind of comparison, we used the fold change values as input. We treated the two TNBC cell lines as one and the normal and DPBC cell line together as a second set of cell lines. This way we intended to investigate whether the RDA analysis will show transcriptomic changes according to the morphological results obtained. Indeed, we found enrichment in the apoptosis, the mTORC and the cell cycle hallmarks using the RDA value as input data (Figure 5). This suggests that even though the hallmarks are not changed at the individual cell line level after arsenate treatment, their response on the transcriptomic level is different when we compare the DPBC and TNBC cells. The mTORC signalling was differentiated between the TNBC and the DPBC/normal cell lines. The mTORC signalling was generally downregulated in the TNBC cell lines. This downregulation included various metabolic enzymes such as glucose-6-phosphate dehydrogenase (G6PD) or sorbitol dehydrogenase (SORD), amino acid transporters such as cystine/glutamate transporter (SLC7A11) and large neutral amino acid transporter small subunit 1 (SLC7A5). The mTORC is the master regulator of autophagy, inhibiting it in the case of adequate metabolic flux [39]. These results show the downregulation of the metabolic input after arsenate treatment, which can trigger autophagy through the mTORC complex in TNBC cell lines. However, all these responses on the transcriptome are weak, possibly due to the low concentration of the arsenate treatment used. Next we selected the key regulators of the various processes (autophagy, apoptosis, cell cycle) for further validation experiments to validate our results. The activation of apoptosis, autophagy and cell cycle arrest are the key outcomes of arsenate treatment as observable from the genes shown in Figure 5 in combination with autophagy and apoptosis assays (Figure 1) and microscopic images (Figure 2 and Figure 3). Given that apoptosis regulation is a complex process, we next used network visualization to gain further insights into the mode of action of arsenate treatment (Figure 6). The higher degree proteins tend to be differentially regulated in the TNBC cell lines, such as Lymphoid Enhancer Binding Factor 1 (LEF1) or the cyclin dependent kinase 2 (CDK2). We selected the main regulators of the apoptotic pathway and other proteins which are involved in different processes for further analysis, namely the apoptosis regulator BCL2, the BCL2 domain-containing protein Myeloid Cell Leukemia 1 (MCL1), transforming growth factor 2 (TGFβ2) and Cyclin D1 (CCND1). The genes were selected based on their function in apoptosis according to the network figure (Figure 6) and their involvement in other biological processes such as cell cycle—CCND1 and TGF pathway TGFB1. 2.6. qRT-PCR Validation of Transcriptomic Profiles Following microarray-based gene expression analysis, we selected four genes for qRT-PCR in order to validate our results, which have a central role in apoptosis (Figure 7) and which were negatively regulated from the microarray data as an effect of arsenate treatment. BCL2 is an apoptosis regulator which blocks BAX from releasing Cytochrome C out of the mitochondria. This represents the initiation step of the intrinsic apoptotic process and activates the caspase cascade [40]. MCL1 has a similar role as a BCL2 family apoptosis inhibitor protein [41], while TGFβ1 is a key cytokine involved in drug-resistance by regulating stemness, epithelial-mesenchymal transition (EMT) angiogenesis, and apoptosis [42,43] The fourth gene, cyclin D1, is one of the cell proliferation cyclins [44] and it has been selected for further analysis because of its prognostic significance in breast cancer patients [45,46]. It can be seen (Figure 7) that in the case of the Hs578T and MDA-MB-231 cell lines, we observed a downregulation of BCL2, MCL-1, TGFβ1 and CCND1 at 24 h post-treatment with arsenate when compared to the control group. No alteration of relative gene expression can be seen in the case of normal cell line HMEC and MCF-7 (Figure 7). The expression of antiapoptotic regulators (BCL2 and MCL-1) hence significantly decreased after arsenate exposure, which provides a mechanistic rationale for in apoptosis facilitation via the intrinsic apoptosis pathway [47]. CCND1 is an influential cell-cycle regulatory protein, and its overexpression is connected with cell proliferation, poor prognosis and recurrence in breast cancer, which has here shown to be downregulated as an effect of the arsenate exposure. Hence, decreased CCND1 expression can be related to decreased cell proliferation [48]. CCND1 provided to be a link between degradative autophagy and cell cycle regulation in hepatocarcinoma tumorigenesis [49]. Overall, we can see that arsenate regulates key genes involved in cell cycle regulation, signal transduction, autophagy [50] and apoptosis [8,51]. The alteration produced might in involve epigenetic components in addition to the transcriptomic level, [8] which, however, was outside the scope of the current study. 2.7. BCL2 Quantification by Fluorescence Confocal Microscopy and TGFβ2 Protein Quantification via ELISA We next quantified alteration at the protein level as a validation step for the alteration on the transcriptome level. The results from BCL2 protein quantification by confocal immunofluorescence are presented in Figure 8, revealing slightly reduced fluorescence intensity, thereby confirming the reduced expression level of BCL2 as an effect of arsenate exposure (Figure 8A). Finally, we quantified TGFβ2 and IL6 by an ELISA assay (at the protein level) after 24 h and 48 h from cultures of HMEC, MCF-7, Hs578T and MDA-MB-231 cells for treatment vs. control, the results of which are shown in Figure 8B. We observe a slightly decreased level of TGFβ2 after 48 h in TNBC cell lines. TGFβ2 is involved in the EMT involved in cell migration and angiogenesis, [42] and overexpression of TGFβ2 promotes tumor growth and invasion, therefore its inhibition by arsenate exposure might contribute favorably to treatment efficacy [52]. TGFβ also influences TNBC cancer stem cells through regulating stemness EMT and apoptosis [43]. Downregulating TGFβ2 with arsenate could in turn help to reduce such effects and make the TNBC cells more susceptible to conventional chemotherapy. In contrast to TGFβ2, IL6 had a very little downregulation after 48 h of arsenate treatment in the TNBC cell lines (p < 0.05 t-test, Figure 8B). IL6 is an activator of mTOR signalling, which is involved in metastasis formation of TNBC [53,54] as well as in drug resistance which is counteracted by the administration of arsenate [33]. 3. Discussion Arsenic derivatives showed antitumoral activity in the case of many types of cancer such as arsenic trioxide on head and neck tumors [55] or on epithelial ovarian cancer, Ref. [56] human neuroblastoma, Ref. [57] human liver cancer cells, Ref. [58] leukaemia, Ref. [59] renal cancer [60] and prostate cancer [61]. Arsenate and arsenite showed inhibition of proliferation of melanoma cells [62] and of human promyelocytic leukemia cells [63]; arsenite and arsenic acid induced apoptosis in the leukemia cells [64]; tetraarsenic hexoxide induced G2/M arrest, apoptosis, and autophagy in SW620 human colon cancer cells [65]. In the context of TNBC, arsenic derivatives have shown activity in in vitro experiments against several breast cancer cell lines like arsenate on MCF-7 cells [66]; arsenite on DPBC cells (MCF-7) and TNBC cells (MDA-MB-231, T-47D, BT-20 [7,8,9,10,11], and arsenic disulfide on MCF-7 and MDA-MB-231 breast cancer cells [26,67]. Arsenate derivatives have been researched extensively regarding their medical applicability as well as biological effects. Arsenate affects cancer progression through coding and non-coding genes related to a wide range of biological processes [68]. A particular application of arsenate derivatives is focused on miRNAs as promoters of apoptosis induced by arsenic trioxide, which is commonly used in the treatment of acute promyelocytic leukemia [68,69,70] The cross-talk among all of the literature and the current applicability of arsenate gives a niche for further investigations to fit the puzzle pieces together. Most of the studies that presented the biological effect of arsenic are related to the oxidation state +3 (arsenite); meanwhile for the oxidation state +5 (arsenate) there is much less information about its known mode of action. Despite the fact that arsenate efficacy in the treatment of breast cancer was demonstrated, Ref. [66] its antitumor mechanism has not been fully elucidated yet. In a wide range of cellular models [27,71,72,73], it has been shown before that arsenic treatment has the capacity to significantly reduce cell proliferation, invasion, and metastasis and to induce apoptosis. Our analysis now showed that arsenate’s effect is largely cell line specific to TNBC cell lines, absent in HMEC normal control cells, and present only to a much lesser effect in MCF-7 cells. Arsenic treatment has been demonstrated to specifically activate apoptosis in MCF-7 2D- and 3D-culture models [67]; however, arsenate has only a moderate effect on the MCF-7 cell line in the current study. The cause could be that cells were grown in clusters in our study, and darkfield microscopy showed apoptosis only at the edge of the clusters. The effect of arsenate treatment was more pronounced in the case of TNBC cells, as this could be observed by microscopy data and confirmed on the gene expression level. Arsenite showed the ability to induce S-phase arrest, autophagy and apoptosis on various tumors by modulating genes such as Forkhead box O3 (FOXO3a) and Cyclin D1 (CCND1) [74], or sustaining inhibition of mTORC1 [7], the latter of which was shown to be related to autophagy regulation. The mTOR pathway is activated through IL6 signaling, which is closely related to cell growth and metastasis in TNBC [53,54]. Other studies have shown that the blockade of IL6-associated inflammation positively correlates with the inhibition of tumor growth and EMT process, [53] which should be further explored in TNBC. The mTOR pathway is a frequently activated pathway in human cancers, representing an attractive target for anti-cancer drug development [75]. Furthermore, mTOR also negatively regulates autophagy [76]. The inhibition of mTOR signaling can decrease cellular proliferation and promotion of cell death including apoptosis and autophagy [76]. The current study proposes autophagy and apoptosis as a final cellular response of arsenate-inducing oxidative stress, where mTOR signaling has an essential role, as we observed in our study. It was demonstrated previously that the apoptotic and autophagic responses have very specific cross-talk [77]. Evidence in the literature suggests that in the case of the TNBC cells, arsenate could induce apoptosis through autophagy. In our experiments, we have seen both elevated autophagy and apoptosis in TNBC cell lines, but not in HMEC cells. MCL1 and BCL2 are the main effector proteins in regulating the antiapoptotic and anti-autophagy response, which were downregulated in TNBC cells validated by qRT-PCR. The apoptosis mechanism was activated in the case of breast cancer cells in this study as well. Similarly, in HT-29 colorectal cancer cells, activation of the intrinsic apoptosis pathway was demonstrated via upregulation of BAX and downregulation of BCL2 [78]. Although this effect was also observed in the present study, it was considerably smaller. Additionally, we have seen the capacities of BCL2 family proteins to regulate autophagy via the interaction with Beclin-1; caspases have been indicated to suppress autophagy via a mechanism mediated by the cleavage of autophagy-related proteins [79]. The analysis described in our paper shows that arsenate reduced cell proliferation as well as activation of autophagy and apoptosis in breast cancer cells. In this study the cytotoxic effect of arsenate was found to be largely cell type specific, as observed previously also in hepatocellular carcinoma cells [80]. Our study next investigated the cellular effects of arsenate further, based on functional tests in combination with transcriptomics experiments to elucidate its mode of action. Each cell line in this study responded to arsenate treatment differently (possibly depending on the mutations present, TNBC cell lines being known to be TP53 mutant [81]). In Figure 9 we emphasized the relevance of breast cancer’s molecular subclassification. While arsenate causes increased apoptosis and autophagy in TNBC cell lines, HMEC and MCF-7 cells have intact DNA repair pathways and are therefore better able to cope with this type of damage (Figure 9). In the case of Hs578T cells, we observed an alteration of chromatin pathways, DNA replication and telomere signaling pathways, and chromatin modification (a form of late apoptosis signals) correlating with microscopy data from previous studies [82,83]. Chromatin modifications are a frequent event observed during the repair of environmental exposure-induced DNA damage, including for arsenic exposure [84]. It has previously been demonstrated that arsenic affects chromatin silencing pathways in HeLa cells [85]. These alterations might be transient or can be accompanied by heritable epigenetic alterations at some specific sites of chronic arsenic exposure. These epigenetic changes and DNA damage might, in turn, be exploited as a therapeutic strategy for breast cancer by inducing apoptosis in TNBC cells. In the case of MDA-MB-231 cells the reduction of cell proliferation was related to the activation of cell death via the endoplasmic reticulum and mitochondrial axis, as confirmed by fluorescence microscopy and gene expression data, whereas in the case of microarray data we identified genes that regulate these processes, which is shown in Figure 6 (network showing the specific genes related to the intrinsic, mitochondrial axis of apoptosis via MCL1 and BCL2) [86]. Arsenic compounds activate an apoptosis-related mechanism via intrinsic and extrinsic caspase pathway activation [87]. Arsenate target genes involved epigenetic reprogramming [88], which lately affect cell fate through a direct or indirect way [8]. DNA damage caused by arsenic derivatives exposure was identified in multiple cancer models and was demonstrated to affect the response to chemotherapy [89]. In the current study, arsenate has shown a chromatin-modifying effect in all cell lines, which can be the marker of DNA damage, but the normal and DPBC cell lines can more readily cope with this effect, which resulted in a relatively decreased apoptotic rate compared to the TNBC cell lines with relatively higher apoptotic levels, leading to a degree of selective toxicity [82,83]. The mutated status of p53 in the two TNBC cell lines is possibly causally related behind the decreased DNA damage response [22]. In spite of the fact that we treated the cells with a very low concentration of arsenate at 50 nM, it had the capacity to interfere with cell proliferation checkpoints and apoptosis and thus suppress tumorigenesis. This has important relevance because DNA repair systems interact with other cellular components responsible for homeostasis and DNA metabolism [90]. Arsenic is presented in the literature not only as an apoptosis regulator but also as an autophagy regulator, which in agreement with our data, and also for the +5 oxidation state. Our data suggest the involvement of apoptosis and autophagy in the effects of arsenate exposure, which furthermore appears to be specific to cancer cell lines, based on the data generated here. In our in vitro experiments we have not distinguished whether arsenate or arsenite had the biological effect in the intracellular milieu. Nevertheless, the outcome of the apoptosis and autophagy assay suggest a cell line specific cytotoxic effect. Arsenic in oxidation state +3 has previously been found to interfere with intrinsic and extrinsic apoptosis and autophagy mechanisms in the breast cancer cell lines MCF-7 and MDA-MB-231 [26]. Arsenic trioxide was found to suppress cell growth, to stimulate apoptosis, and to be involved in retarded cell invasion by interfering [91] with coding and non-coding gene regulation [27,28,29,30]. We can conclude that in our case, the arsenate exposure activates two important mechanisms, autophagy and apoptosis regulating the cell death, and hence we consider arsenate as a promising candidate in cancer management. 4. Materials and Methods 4.1. Cell Lines and Treatment HMEC (human mammary epithelial cells, A10565 Life Technology, Carlsbad, CA, USA) were maintained in HMEC basal serum free medium (Life Technology, cat no. 12753018, Carlsbad, CA, USA) and HMEC supplement kit (Life Technology cat. No. 12755013, Carlsbad, CA, USA). The DPBC cell line MCF-7 (ATCC collection, Manassas, VA, USA) was cultured in MEM medium supplemented with 10% fetal bovine serum, 2 mM L-glutamine and 1% nonessential amino acids. The Hs578T cell line (ATCC collection) was maintained in MEM (Dulbecco’s Modified Eagle Medium, Gibco Life Technologies, Waltham, MA, USA) high glucose (4500 mg/mL glucose) supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 1% nonessential amino acids (Gibco Life Technologies, Waltham, MA, USA) and 0.01 mg/mL insulin. The MDA-MB-231 cell line (ATCC collection) was cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum and 2 mM L-glutamine. All cells were maintained in a humidified incubator at 37 °C with 5% CO2. We used the As5+ in solution directly because arsenate is internalized easily by phosphate carriers. [92] Hence, the normal and tumor breast cancer cells were treated with arsenic in the oxidation state +5 (As5+) presenting less direct cell toxicity than (As3+). [14] Arsenate was obtained in 1000 mg/L standard solution (As + 5HNO3 → H3AsO4 + 5NO2 + H2O) (produced by Merck KGaA, Darmstadt, Germany, Product Number 1197730100, Lot number HC55536773) and diluted to the required concentration. 4.2. Colony Assay Treated and untreated cells were seeded in six-well plates at a density of 250 cells/well/2 mL in triplicate. After 14 days, the cells were washed with PBS 1×, fixed with 1 mL of methanol 80% for 15 min, stained with 300 µL of Trypan Blue 0.2% and then washed with PBS 1×. The colonies were counted by a visual observer without the use of visual augmentation devices. Images of the plates have been taken with a c300 machine (Azure Biosystems, Dublin, CA, USA) using the white light and then they were counted directly from the plate (n = 3). A graphical representation and t-test results were shown. 4.3. Autophagy and Apoptosis Detection Both autophagy and apoptosis assessments were done using fluorescence microscopy on 10,000 pre-plated cells for 24 h in 96-well plates for each triplicate of control and arsenate treated samples. Fluorescence microscopy was performed on an Olympus I×71 microscope (Olympus, Tokyo, Japan) using a 20× objective for magnification. For autophagy detection, the cells were treated with an Autophagy/Cytotoxicity Dual Staining Kit (Abcam cat no. ab133075, Cambridge, MA, USA) that contains monodansylcadaverine (MDC) for autophagic vacuole detection in cultured cells and propidium iodide (PI) for necrotic cell detection. Staining was applied after 24 h of arsenate treatment. Apoptosis was detected by the Annexin V-FITC/PI Apoptosis Detection Kit (Abcam cat no. ab14155, Cambridge, MA, USA). The kit contains Annexin V-FITC that stains in green the apoptotic cells that translocated membrane phospholipid phosphatidylserine to the outer leaflet of the cellular membrane, while the PI part of the composition stains the nuclei. Late apoptotic cells are hence double stained with both PI and Annexin-V-FITC. The staining was performed according to the manufacturer’s protocol followed by fluorescence microscopy evaluation (20× magnification). On four different images the apoptotic and autophagic cells were counted in both, treated and untreated conditions. The average cell count of the untreated condition was set to 100% and changes in cell number were reported as multiples of this number. 4.4. Dark-Field Microscopy Dark-field microscopy was performed using an Olympus B × 43 microscope (Olympus, Tokyo, Japan) equipped with a CytoViva Enhanced Dark-Field Condenser (Cytoviva, Auburn, AL, USA), an UPlanFLN60×, NA = 1.2 oil immersion objective (Olympus, Tokyo, Japan) and a 6.4 µm/pixel CCD camera (QImaging, Surrey, BC, Canada). Images were calibrated for scale and annotated in ImageJ2.0 [93] and converted to 8-bit grayscale. Contrast enhancement was performed in the same software (0.3% saturated pixels; Normalized and Histogram equalized) followed by the application of an Unsharp Mask (Sigma value = 2–12 pixels; Mask Weight = 0.6). The magnification used for all images was 60×. 4.5. Cytoskeletal Evaluation The fluorescent staining protocol used DAPI (Abcam, Cambridge, UK) for the labelling of the nucleus and Phalloidin-FITC (Cytoskeleton Inc., Denver, CO, USA) for the cytoskeleton. After treatment, the cells were fixed in 4% paraformaldehyde followed by 0.5% Triton × permeabilization for 1 h. The cells were incubated at 37 °C and 5% CO2. Thereafter, 100 µL of 200 nM Phalloidin-FITC was added and the samples were incubated at room temperature under no illumination for 30 min. 200 µL of 100 nM DAPI was added over the coverslip for 30 s and washed with a phosphate saline buffer. The coverslips were mounted with 90% glycerol. Images were captured using a UPLSAPO40 × 2, NA:0.95 objective (Olympus, Tokyo, Japan) and excitation wavelengths/emission windows were automatically selected according to the fluorescence dye spectral information database inside the acquisition software (FW10-ASW, Olympus, Tokyo, Japan). 4.6. Microarrays For microarray experiments, cells from three serial passages were seeded in a six-well plate, using 0.3 million cells/well for each triplicate of control and arsenate treated cells. RNA extraction was performed using TriReagent, which was then purified using the RNeasy Mini kit (Qiagen, Hilden, Germany). The microarray samples were prepared according to the Agilent Low Input Quick Amp Labeling (5190–2305) protocol to synthesize equal quantities of 100 ng of total RNA, followed by purification of the hybridization products using the RNeasy Mini kit (Qiagen). A NanoDrop2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA) was used to perform probe quality control, with results showing that all the probes had a specific activity higher than 6 pmol/µL Cy3/µg cRNA (specific activity > 8 pmol Cy3/µg cRNA). Fragmentation and hybridization were performed based on the Agilent One-Color protocol (Agilent Technologies, Santa Clara, CA, USA). [94,95] The samples were hybridized for 17 h at 65 °C in a hybridization oven. This was followed by microarray slide scanning with a SureScan Microarray Scanner (1 × 60 k array slides with 61 × 21 mm size, resolution 3 µM) from Agilent, and image processing was undertaken with the Feature Extraction 11.0.1.1 software (Agilent 2016, Santa Clara, CA, USA). Gene expression values were determined using the Agilent G4851C microarray slides for the three arsenate treated samples and three controls across four cell lines (HMEC, MCF-7, Hs578T, and MDA-MB-231). Resulting data were analyzed using the limma [96] package in R [97], where the background was corrected with the “normexp” method and then quantile normalization [96] was performed, as we used in our previous work. [98] Probes transcribed and expressed in at least three samples in any conditions at a level higher than the 95th percentile were selected. This process resulted in a list of 29,874 probes. Next, probes were mapped to genes using the mean expression with the “avereps” function in R. The probe sets were translated using the annotation file of the microarray chip [97]. This resulted in a list of 18,849 genes which were used for subsequent analysis, following the standard procedure [96]. From the gene expression values, we conducted a Principal Component Analysis (PCA) using the “prcomp” function in R [97] for visualization purposes. Based on the experimentally determined gene expression profiles, we calculated the average log2 fold change value per gene for each cell line responding to arsenate in R, using the functions lmFit and eBayes [99]. Significantly differentially expressed genes (with Benjamini-Hochberg corrected p-value < 0.1 and |log2 FC| > 1) were tested in the Gorilla [100] tool for Gene Ontology Biological Process overrepresentation [101,102]. For gene set enrichment analysis we used the CAMERA method [103]. The calculation of log2 fold changes between each treatment and each non-treated sample resulted in nine fold-change values per cell line (three treated and three untreated replicates in each distinct cell lines). Next, Robust Regularized Discriminant Analysis (RDA) was performed on these fold changes using the R package RDA [104]. After a parameter search we chose to use as parameters α = 0.22 and δ = 0.33, because these values correctly classified all of our samples (see Table S1 for the confusion matrix). After optimizing parameters, we calculated a centroid value per gene, which indicates the extent to which the given gene is able to differentiate the two TNBC cell lines from the double positive and normal cell line. This centroid was the subject of the subsequent Gene Set Enrichment Analysis (GSEA) [105] using the Cellular Hallmarks from MolSigDB and the network analysis (see below) [106]. A high centroid-based differential expression value represents a larger response of the given gene in the TNBC cell lines. The cut-off for significantly differentially regulated hallmarks was set to an FDR of below 0.15. The GSEA was run using a gene set size cut-off larger than 10 genes, but smaller than 500. All other parameters were kept as default. 4.7. Apoptosis Network in Pathological Condition as Effect of Arsenate Treatment We next generated an apoptosis reference network by using the genes from the MolSigDB apoptosis pathway [106] and mapped them to UniProt gene identifiers through the UniProt mapping service [107]. We used the mapped UniProt identifiers as a searching seed in the SIGNOR database [108]. We kept the seeds and also their direct interaction partners if they interacted with at least two seed proteins. We then mapped the centroid values of each gene from the RDA analysis to the network, and we indicated that with a gradient. We calculated the degree—number of neighbours—of all nodes of the whole SIGNOR network. Degree was indicated by node size in the visualization. This method visualizes the most central regulators in the apoptosis specific regulatory network as a key anticancer mechanism. 4.8. qRT-PCR Evaluation Total RNA extraction was performed using TriReagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol. A NanoDrop-1100 (Thermo Fisher Scientific, Carlsbad, CA, USA) was used to evaluate RNA concentration and quality by measuring the absorbance of UV light. For gene expression evaluation, total RNA (1000 ng) was reversely transcribed into cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Carlsbad, CA, USA). We used the Assay Design Center from Roche for the primer design (Roche Inc. 2018, NJ, USA). The primers for each gene are listed in Table S2. SYBR Select Master Mix (Life Technologies, Carlsbad, CA, USA) was used for gene expression evaluation, and all amplifications and detections were carried out in the Applied Biosystems ViiA7 System (Thermo Fisher Scientific, Waltham, MA, USA) based on the manufacturers recommended protocol. 4.9. TGFβ2 and IL6 Quantification in Cell Culture Medium The expression level of TGFβ2 released in the cell culture medium was detected by ELISA using the Human TGF-beta 2 DuoSet ELISA (R&D System, cat no. DY302, Minneapolis, MN, USA), DuoSet Ancillary Reagent Kit 2 (5 plates, R&D Systems, cat no. DY008, Minneapolis, MN, USA) and Sample Activation Kit 1 (R&D Systems, cat no. DY010, Minneapolis, MN, USA). For IL6 quantification from cell culture, ELISA was performed using the IL6 DuoSet ELISA Kit (R&D System, cat no. DY206-05, Minneapolis, MN, USA) along with the DuoSet Ancillary Reagent Kit 2 (5 plates, R&D Systems, cat no. DY008, Minneapolis, MN, USA). 4.10. BCL2 Protein Evaluation by Confocal Microscopy For immunofluorescence staining, a Human/Mouse BCL2 Antibody (R&D Systems, cat no. AF810-SP, Minneapolis, MN, USA) was used. Incubation was done with 5 µg/mL overnight followed by washing steps and incubation for 2 h with secondary antibody Goat Anti-Rabbit Alexa Fluor® 488 (ab150077, 1:100 dilution). Laser scanning confocal microscopy was performed on an Olympus FV1200MPE microscope equipped with UPLSAPO40×2, NA:0.95 objective. 4.11. Statistical Evaluation For pairwise comparisons we used two-sided t-tests, our considered significance level was p < 0.05, and the statistical analyses were performed using GraphPad Prism software version 6 for Windows (GraphPad Software, San Diego, CA, USA). For microarray differential gene analysis, we used moderate t-statistics with a Benjamini-Hochberg correction and p < 0.05. For Gene-set enrichment analysis we used the Kolmogorov Smirnov test for p < 0.05 and FDR < 0.1. 5. Conclusions In this study we were able to demonstrate that arsenate induces a cell line specific morphological and transcriptomic alteration at low concentration. Arsenate induces the cytoskeletal alteration and cell death in TNBC cell lines through activating autophagy and apoptosis and reduces the clonogenic capacity. The novelty of this study stands in the fact that arsenate therapeutic stress produces pro-apoptosis signals largely selectively in TNBC cells (based on dark-field microscopic and cytoskeletal evaluation). In addition, arsenate showed no effects in HMEC cells and only moderate effects in MCF-7 cells. Regularized discriminant analysis showed that the low concentration of arsenate affected the G2M checkpoint, autophagy and apoptosis cell line specifically. The downregulation of anti-apoptotic genes (MCL1, BCL2, TGFβ1 and CCND1) was confirmed by qRT-PCR, and on the protein level, for TGFβ2, by ELISA, concluding that TNBC and non-TNBC cell lines in this particular experimental setup reacted differently to treatment. The alteration of gene expression levels demonstrates a crosstalk among autophagy, cell cycle and apoptosis as a potential mechanism of action of arsenate which must be investigated in future pharmacological interventions. This study is a step toward understanding arsenate TNBC-type specific effects which potentially correlates with active DNA repair pathways. However, further studies are necessitated to demonstrate arsenate metabolism and mechanism of action, considering the importance of intracellular reduction of the metalloids for biological effects. Nevertheless, this study makes the use of arsenate to be a potential selective chemotherapeutic drug treating triple negative breast cancer one step closer to reality. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094784/s1. Click here for additional data file. Author Contributions Conceptualization, L.-L.P. and C.B.; methodology, L.-L.P., C.B. and D.M.; software, A.B. and I.B.-N.; validation, M.-A.J. and L.-Z.R.; formal analysis, R.C.; investigation, C.M., A.I.M. and A.B.Ț.; resources, E.G.; data curation, L.M. and S.P.; writing—original draft preparation, L.-L.P., C.B. and D.M.; writing—review and editing, L.J. and A.B.; visualization, O.Z.; supervision, A.B. and I.B.-N.; project administration, L.-L.P.; funding acquisition, C.B. 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 generated or analyzed during this study are included in this published article (and its Supplementary Information files). Conflicts of Interest The authors declare that they have no conflict of interest. Figure 1 Evaluation of cellular effect of arsenate. (A) Arsenate treatment (50 nM) affects the ability of breast cancer cell lines to form colonies at 24 h after arsenate treatment. On the left side of the figure are representative images of the colony formation assays for each cell line, while on the right side boxplots for the number of colonies are shown. (* p < 0.05 two sided t-test treated vs. untreated cells n = 3). Arsenate significantly decreased the colony forming capacity of all cancer cell lines used in this study (while the normal HMEC cell line used as a control is not able to form colonies in any case). (B) Autophagy evaluation by fluorescence microscopy following exposure to 50 nM arsenate on different cell lines (20× magnification). This experiment emphasizes an increase of MDC-labeled vesicles as an effect of arsenate exposure in tumor cells, which is less profound in normal cells 24 h after treatment. Compared to control, the number of autophagic cells was significantly increased 24 h after arsenate treatment. (*** p < 0.001, **** p < 0.0001 two sided t-test, treated vs. untreated cells n = 3) (C) Apoptosis evaluation in the same experimental conditions at 24 h after arsenate treatment. Green fluorescence is Annexin V-FITC and red fluorescence is propidium iodide (PI). Annexin V-FITC around the membrane displays apoptotic cells, only red fluorescence in the nucleus displays the necrotic cells and double staining is specific for late apoptotic cells. Large numbers of fluorescent Annexin V-FITC and Annexin V-FITC/PI was observed in tumoral cells treated with arsenate; in contrast, few fluorescent cells were observed in the HMEC control cells. The number of cells were counted with the apoptotic markers and normalized with the untreated controls. (* p < 0.05, *** p < 0.001 two sided t-test, treated vs. untreated cells n = 3). Figure 2 Effect of arsenate treatment on four different cell lines visualized using dark field microscopy. Magnification of 15 μm. (A) HMEC untreated cells, (B) HMEC arsenate treated cells, (C) MCF-7 untreated cells, (D) MCF-7 arsenate treated cells, (E) Hs578T untreated cells, (F) Hs578T arsenate treated cells, (G) MDA-MD-231 untreated cells, (H) MDA-MD-231 arsenate treated cells. Red arrows (D) indicate apoptotic bodies; green arrows (F,H) indicate thickened and fragmented cell membranes. EC (orange—(F)) elongated cell, orange arrows (F) indicate apoptopodia-like projections, magenta arrows (F) indicate tunneling nanotubes, cyan arrows (H) show apoptotic bodies labeled AB. No important alterations can be seen for normal cell lines; meanwhile, in the case of tumor cells, the activation of apoptotic mechanisms can be observed (indicated by red arrows), which is more pronounced for TNBC cells. Figure 3 Changes in the cytoskeleton after arsenate exposure (II) with cytoskeleton staining by Phalloidin-FITC and nucleus staining by DAPI in comparison to control (I). Magnification of 50 μm. (A)—HMEC; (B)—MCF-7; (C)—Hs578T; (D)—MDA-MB-231. Note in (II) the completely disorganized actin cytoskeleton in the case of the MCF-7 cell line and the increased amount of actin filaments at the cell membrane of the MDA-MB-231 cell line affecting cytoskeletal organization. Red arrows point to irregular or fragmented nuclei and magenta arrows indicate cytoskeleton damage. Alterations are more prominent in all cancer cell lines compared to the HMEC cell line where the actin filaments are not affected and nuclear damage is insignificant. Figure 4 (A) Workflow of this study. First, we started with phenotypic readouts of different methods from the control (HMEC) and the three different breast cancer cell lines (MCF-7, Hs578T and MDA-MB-231) with and without arsenate treatment. Next, microarray data were collected from three replicates each of the four cell lines in each condition. Subsequently, we determined differentially expressed genes using fold change (FC) and the False Discovery Rate (FDR)-corrected t-test, CAMERA. The response to arsenate between the two TNBC and the DPBC and normal cell lines was compared by using Robust Regularized Discriminant Analysis. From the resulting centroid of data, GSEA (gene set enrichment analysis) was performed in order to identify the involved Gene Ontology Biological Processes (GO-BP) and pathways. Representative genes were selected to validate the differentially expressed genes by qRT-PCR, ELISA, and fluorescence microscopy. (B) Similarity of cell lines and treatment conditions based on Pearson correlation and principal component analysis (PCA). It can be seen that the cell type causes bigger differences in gene expression space than treatment conditions (panel A). In (panel B) the arsenate’s response has no specific direction compared to untreated samples; however, treated and untreated samples are generally distinguishable. Figure 5 Gene Set Enrichment Analysis. (A) Genes in TNBC vs. DPBC and normal cell lines are perturbed differently after arsenate treatment with respect to apoptosis, mTOR signaling and G2M checkpoint signaling (q < 0.15). (B) Lists of genes differentially expressed per cell line belonging to the above pathways are colored by their differential expression. It can be seen that apoptosis, mTOR signaling and G2M checkpoint regulating genes are downregulated in the TNBC cases after arsenate treatment, while they are upregulated or not changed in the DPBC and in HMEC cell lines. The full results can be seen in Table S4. Figure 6 The effect of arsenate treatment on the apoptosis network and its interactors according to the SIGNOR database. Node size is according to degree. The colours are according to centroids above towards the TNBC cell lines. Grey proteins have no centroid values. Green arrows are up-regulating interactions; red half circle-ended lines are downregulating interactions. The effect of grey lines is unknown. High degree yellow bordered proteins are chosen to validate. They are central members of the network in apoptosis. Many high degree proteins such as LEF1 and CDK2 also respond to treatment in TNBC cell lines. Figure 7 Validation of the effect of arsenate by qRT-PCR on selected genes related to apoptosis and cell proliferation. Relative gene expression levels are shown for MCL1, BCL2, TGFβ1, CCND1 (Cyclin D1) across cell lines and in arsenate treated and control group (untreated cells). The data were normalized to β-actin and B2M using the ΔΔct method for the HMEC, MCF-7, Hs578T and MDA-MB-231 cell lines compared to the arsenate treated group versus the control group. x is the mean and the line is the median in the boxplots (* p < 0.05). It can be seen that both apoptosis inhibitors (MCL1 and BCL2) are downregulated after arsenate treatment in TNBC cell lines when compared to untreated cells, but not in the normal and DPBC cell lines. Also, survival factor TGFβ1 and cell proliferation indicator CCND1 are downregulated in Hs578T and MDA-MB-231 cell lines compared to their expression in HMEC and MCF-7. Figure 8 (A) Microscopy visualization of BCL2 validation at the protein level. Protein expression of BCL2 marked by fluorescently tagged antibodies followed by confocal microscopy evaluation. It can be seen that the expression level of the BCL2 protein is slightly reduced in case of the arsenate treated group compared to control for the case of Hs578T and MDA-MB-231 at 48-h post-treatment, confirming the qRT-PCR and microarray data. (B) TGFβ2 and IL6 validation at the protein level. Protein expression of TGFβ2 and IL6 released in cell culture medium 24 h and 48 h for control and arsenate treated cells (HMEC, MCF-7, Hs578T and MDA-MB-231) evaluated by ELISA. x is the mean and median is the middle line in the boxplots. * p < 0.05 two-sided t-test. TGFβ2 is downregulated in protein level after 48 h of arsenate treated cells, but there is no change in the IL6 levels. 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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092806 molecules-27-02806 Article Dictyophora Polysaccharide Attenuates As-Mediated PINK1/Parkin Pathway-Induced Mitophagy in L-02 Cell through Scavenging ROS https://orcid.org/0000-0001-7042-1730 Hu Ting 123† Lu Ju 1† Wu Changyan 1† Duan Tianxiao 1 Luo Peng 1234* Ozeki Yasuhiro Academic Editor 1 School of Public Health, Guizhou Medical University, Guiyang 550025, China; hutinggmc@126.com (T.H.); luju3621luju@163.com (J.L.); wcy9409@163.com (C.W.); txduan2020@hotmail.com (T.D.) 2 Key Laboratory of Environmental Pollution Monitoring Control Ministry of Education, Guizhou Medical University, Guiyang 550025, China 3 Guizhou Engineering Research Center of Food Nutrition and Health, Guiyang 550025, China 4 State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang 550014, China * Correspondence: luopeng@gmc.edu.cn † These authors contributed equally to this work. 28 4 2022 5 2022 27 9 280626 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/). Arsenic (As) is common in the human living environment and a certain amount of exposure to As can lead to liver damage; this toxic effect has been proved to be closely related to intracellular PINK1/Parkin pathway-mediated mitophagy. Dictyophora is an edible fungus that extracts polysaccharides with antioxidant and hepatoprotective effects. In the present study, we demonstrated that As induced the onset of mitophagy in hepatocytes by stimulating cellular production of ROS to activate PINK1/Parkin, and the extent of damage increased with increased As-induced toxicity. Dictyophora polysaccharide (DIP) has the ability to scavenge intracellular ROS, which can inhibit oxidative stress injury and inhibit the PINK/Parkin pathway through its receptors or efficacious proteins, thus preventing mitochondrial autophagy and alleviating the hepatotoxicity of As. In conclusion, our results indicate that DIP can reduce As-induced PINK1/Parkin pathway-mediated hepatic mitophagy through scavenging ROS and exert hepatoprotective effects, providing experimental data and theoretical basis for the development of medicinal value of Dictyophora as a dual-use food and medicinal fungus. Dictyophora polysaccharide As PINK1/Parkin ROS National Natural Science Foundation of China82173642 Guizhou Provincial Science and Technology FoundationSupport plan [2021] General 134 Foundation of Guizhou Educational CommitteeKY [2021] 008 Guizhou Provincial Department of Education Youth Science and Technology Talents Growth ProjectKY [2022]218 This research was supported by the National Natural Science Foundation of China (No.82173642), Guizhou Provincial Science and Technology Foundation (No. Support plan [2021] General 134), Foundation of Guizhou Educational Committee (No. KY [2021] 008), and Guizhou Provincial Department of Education Youth Science and Technology Talents Growth Project (No. KY [2022]218). ==== Body pmc1. Introduction Arsenic (As) is a basic element for animals and is predominantly found in rocks, soils, and natural water [1]. Many studies have shown that oxidative stress, cell proliferation, and induction of cell death have been reported followed by arsenic exposure [2,3,4]. Long-term arsenic exposure can cause damage to multiple organs in the body, with the liver being one of the main target organs [5]. Normal activities of the liver are dependent on mitophagy in many liver diseases [6]. Mitophagy is a selective autophagy that specifically degrades dysfunctional or superfluous mitochondria and is one of the most important mitochondrial quality control mechanisms. This is essential for maintaining cellular homeostasis [7,8]. Our previous studies have found that arsenic accumulation in liver cells caused some amount of damage, and this toxic effect was mediated by the PINK1/Parkin signaling pathway [9], which is well-recognized for being one of the key pathways that mediated mitophagy [10]. Dictyophora is one of the most precious and important plant resource in China and is one of the highly valued mushroom in the world [11]. It is also regarded as the “queen of the mushrooms” [12] and has food and medicinal effects, i.e., antifatigue, hypoglycemic, immunomodulatory, antiaging, and hepato-protective effects [13]. Recently, our studies in rats exposed to sodium arsenite showed that Polysaccharides extracted from Dictyophora (DIP) could alleviate liver injury. It suggested that DIP has medicinal value in protecting liver injury [14]. However, the underlying mechanisms are still unclear. Whether the hepatoprotective effect of DIP is related to mitophagy needs to be further clarified. In our study, L-02 hepatocyte was treated with sodium arsenite to explore the effect of DIP in sodium arsenite-induced liver injury and the mediating role of mitophagy. The results of this study will lay a foundation for the development of nutrition and medicinal value of Dictyophora chinensis. 2. Materials and Methods 2.1. Materials Normal human liver cell line L-02 (Cell Bank of Chinese Academy of Sciences); Dictyophora was picked in Zhijin County (Bijie, Guizhou, China); Sodium arsenite, N-acetylcysteine (Sigma, New York, NY, USA); RPMI1640 medium, fetal bovine serum, pancreatin, (Gibco, Waltham, MA, USA); CCK-8 cell proliferation toxicity detection kit (Shanghai Dongren Chemical Technology Co., Ltd., Shanghai, China); reactive oxygen detection kit, BAC protein concentration determination kit (Beyotime, Shanghai, China); rapid reverse transcription kit, qPCR kit (Yishan Biotechnology, Shanghai, China); β-tublin primary antibody (Aibixin, Shanghai, China), LC3 II primary antibody, p62 primary antibody, PINK1, Parkin primary antibody (CST, Kansas City, MO, USA); CO2 incubator (INC108med, Memmert, Schwabach, Germany); high-speed refrigerated centrifuge (3K15, Sigma, USA); microplate reader (Multiskan FC, Thermo Fisher, Waltham, MA, USA); flow cytometer (NovoCyte, Agilent, Santa Clara, CA, USA); timing voltage stabilized steady flow electrophoresis instrument (PowerPac-Basic, Bio-Rad, Hercules, CA, USA); electrophoresis and transfer tank (MiniPROTEAN Tetra, Bio-Rad, Hercules, CA, USA); gel imaging system (Chemic+, Bio-Rad, Hercules, CA, USA). 2.2. Cell Culture L-02 cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum and 1% penicillin-streptomycin mixture and kept in a humidified incubator with 95% air and 5% CO2 at 37 °C. Cells in the normal control group were cultured normally and the treatment group was pretreated with NaAsO2 or DIP for 4 h and then exposed to 10 μM NaAsO2. DIP was extracted from the fruit body of Dictyophora purchased by us, and the specific extraction method was the same as in our study [15]. We have confirmed that DIP is mainly a polysaccharide composed of D-glucose, and the rest include D-mannose, L-rhamnose, D-galactose, D-xylose, L-fucose, etc. [16]. All experiments were performed 24 h after cell inoculation. 2.3. Cell Viability Assay The proliferation effect of NaAsO2 or DIP on L-02 cells was detected using an CCK-8 kit. According to the manufacturer’s instruction, cells were cultured in 96-well plates at approximately 1 × 104 cells per well. When the cells were adherent to the bottom of the cell, the cells were treated with different concentrations of NaAsO2 for 24 h or pretreated with different concentrations of DIP for 4 h and then exposed to 10 μM NaAsO2 for 24 h. Then, CCK-8 was added and incubated for 2–4 h at 37 °C. The absorbance at 490 nm was measured using a microplate reader. The data were calculated from the mean of six replicates; each experiment was conducted in triplicate. 2.4. Detection of ROS L-02 cells were treated with NaAsO2 (10 μM, 24 h), DIP (80 μg/mL, 4 h, then exposed to 10 μM NaAsO2 for 24 h), and NAC (5 mM, 1 h, then exposed to 10 μM NaAsO2 for 24 h). One set of L-02 cells without any treatment was kept as normal control. Furthermore, 1 mL of DCFH-DA with a final concentration of 10 μmol/L was added to each well. The solution was then incubated for 20 min at 37 °C, the serum-free culture solution was washed three times to wash out the excess of DCFH-DA, the cells were collected, and the solution was then centrifuged at 4 °C at 1000 g/min for 5 min. The cells were fixed for analysis in a flow cytometer. 2.5. Observe by Transmission Electron Microscopy After cells were treated as described above, the cells were trypsinized and collected, washed twice with pre-cooled PBS, and fixed in 2.5% glutaraldehyde at 4 °C for 24 h. Then, they were washed three times with 0.1 mol/L PBS for 15 min each time, fixed with 1% osmium acid at 4 °C for 2 h, washed three times with 0.1 mol/L PBS for 15 min each time, dehydrated in gradient (50%, 70%, 90%, 100%) acetone solution for 30 min, put in anhydrous acetone with a ratio of 1:1, infiltrated with resin for 12 h, and then put the pure resin at medium penetration for 12 h. The infiltrated samples were polymerized and embedded in the embedding box at 37 °C for 12 h, 45 °C for 12 h, and 60 °C for 12 h. After ultrathin sectioning and staining, the ultrastructure of cells was observed under a transmission electron microscopy. 2.6. RT-qPCR Total RNA was isolated from cells using the acid guanidinium thiocyanate-ephenol-echloroform method. A Qubit Reagent RNA concentration kit was used to determine the concentration. An appropriate amount of dissolved RNA was taken out and then reverse transcribed into cDNA. The reverse transcription product was mixed with SYBR Green, primers, and ddH2O according to the instructions and the reaction program was set up, and the expression of PINK1 and Parkin genes was tested on a computer. The primers were as follows: PINK1 forward, 5′-AGTCCATTGGTAAGGGCTGC-3′, and reverse, 5′-AAATCTGCGATCACCAGCCA-3′; Parkin forward, 5′-TAGCTTTGCACCTGATCGCA-3′, and reverse, 5′-GCGGCTCTTTCATCGACTCT-3′; β-actin forward, 5′-CCTGGCACCCAGCACAAT-3′, and reverse, 5′-GCCGATCCACACGGAGTA-3′; β-actin was used as a control. Relative expression levels were measured using the ∆∆Ct method. 2.7. Western Blot After L-02 cells were grouped and processed as described above, an appropriate amount of lysis solution was added, and the cells were collected by a cell scraper. After the cells were fully lysed on ice, the cells were centrifuged at 12,000× g for 15 min. After 12% SDS-PAGE electrophoresis and transfer membrane, 5% skimmed milk powder was blocked at room temperature for 2 h, and then the LC3 II/І, p62, PINK1, Parkin, and β-tubulin antibodies were 1:1000, 1:3000, and 1:1500, respectively. The cells were incubated overnight at 1:500 and 1:3000, then incubated with horseradish peroxidase (HRP)-labeled secondary antibody (1:10,000) at room temperature for 60 min, and developed with ECL luminescent solution. Image J software was used to analyze the gray value of the protein bands. 2.8. Statistical Analysis SPSS20.0 statistical software was used to analyze the data; one-way analysis of variance was used to compare the differences between groups. An LSD test was used when the variance was uniform, and Dunnett’s T3 test was used when the variance was uneven. p < 0.05 was considered statistically significant. 3. Results 3.1. Effect of As on the Viability of L-02 Cells L-02 cells at around 70% confluences were cultured in different concentrations (0, 1, 2, 4, 8, 16, 32, 64, and 128 μM) of sodium arsenite (NaAsO2) for 24 h. The CCK-8 kit was used to detect the effect of NaAsO2 on the viability of the L-02 cells. As shown in Figure 1A, the viability of the L-02 cells decreased in a dose-dependent manner (p < 0.05). It was determined that the IC50 of NaAsO2 in L-02 cells was 39.70 ± 3.59 μM; thus, we chose 1/2 IC50 (20 μM), 1/4 IC50 (10 μM), and 1/8 IC50 (5 μM) treated L-02 cells for 24 h as the treatment condition in the subsequent experiments. 3.2. As-Induces Mitophagy in L-02 Cells To determine the occurrence of mitophagy in L-02 cells treated with NaAsO2, L-02 cells were treated with 5 μM, 10 μM, and 20 μM NaAsO2 for 12 h, 24 h, and 48 h, and the mitophagy-related proteins PINK1, Parkin, p62 and LC3 II/І were examined. The results showed that with increasing NaAsO2 exposure time and concentration, the overall expression of PINK1, Parkin, p62, and LC3 II/І increased (p < 0.05, Figure 1B,C). After L-02 cells were exposed to 10 μM and 20 μM of NaAsO2, the difference was statistically significant (p < 0.05). After L-02 cells were exposed for 24 h and 48 h, the difference was statistically significant (p < 0.05). Based on these results, we chose a NaAsO2 exposure time at 24 h and a concentration at 10 μM as the conditions for the subsequent experiments. 3.3. DIP Inhibited NaAsO2-Induced ROS and Mitophagy in L-02 Cells To explore the effect of DIP against arsenic-induced mitophagy, L-02 cells were pretreated with 10 μg/mL, 20 μg/mL, 40 μg/mL, 80 μg/mL, and 160 μg/mL DIP for 4 h and then exposed to 10 μM NaAsO2 for 24 h. The altered activity of L-02 cells was detected by CCK8 assay. It was clear that pretreatment with 80 μg/mL DIP significantly enhanced the tolerance of L-02 cells to NaAsO2. Subsequent experiments chose 80 μg/mL as the DIP intervention concentration (Figure 2A). DIP has been reported to have antioxidant function by numerous studies [17,18]. Therefore, the DCFH-DA fluorescent probe method is used to detect intracellular reactive oxygen species (ROS). The results of the flowmetry analysis showed (Figure 2B) that DIP pretreatment reduced NaAsO2-induced intracellular ROS levels in L-02 cells compared with the control. The changes in cellular mitochondrial membrane potential were detected by JC-1 Mitochondrial Membrane Potential Assay Kit, and the results showed that the proportion of NaAsO2-induced elevated mitochondrial membrane potential depolarization was reduced in L-02 cells after DIP pretreatment (p < 0.05, Figure 2C). Meanwhile, DIP was shown to inhibit the protein expression of PINK1, Parkin, p62, and LC3 II/І by a Western blot assay (Figure 2D). These results suggest that DIP can inhibit mitophagy injury induced by NaAsO2 through the PINK1/Parkin pathway. 3.4. Effects of Scavenging ROS on NaAsO2-Induced Mitochondrial Structural Damage To clarify the mechanism of DIP protecting L-02 cells from mitophagy injury, we pretreated L-02 cells exposed to NaAsO2 with ROS-specific scavenger NAC. The results of CCK8 showed that after NaAsO2 treatment, the cell survival rate was significantly (p < 0.05) reduced; after pretreatment with NAC, the inhibition of NaAsO2 cell survival rate was alleviated (Figure 3A). The result showed that NaAsO2 triggered ROS generation and NAC can effectively eliminate the generation and accumulation of ROS induced by NaAsO2. As shown in Figure 3B,C, the results of the DHFH-DA fluorescent probe method showed that the intracellular ROS content of the As group was higher (p < 0.05) than that of the control group. After NAC pretreatment (p < 0.05), the intracellular ROS decreased significantly compared with the As group. Observation under a fluorescence microscope revealed that there were few green fluorescent cells in the control group and the NAC group. The green fluorescent cells in the As group increased while the green fluorescent cells decreased after NAC pretreatment. These results indicated that NaAsO2 can cause the accumulation of ROS in L-02 cells, while NAC obviously inhibits the accumulation of ROS in L-02 cells induced by NaAsO2. As shown in Figure 3D, the results of the transmission electron microscopy showed that the mitochondrial cristae were complete and clear. After exposure to 10 μM NaAsO2, the mitochondria in the cells were swollen and deformed, the mitochondrial cristae were broken or had disappeared, a vacuole-like structure appeared, and mitochondrial autophagosomes wrapped in a double membrane were visible; the damage to the mitochondria in the NAC + As group was significantly (p < 0.05) alleviated compared to the As group. 3.5. Effects of ROS Clearance on Mitophagy-Related Genes and Proteins in the PINK1/Prkin Pathway Intracellular RNA was extracted for RT-QPCR analysis, as shown in Figure 4A,B. After NaAsO2 treatment, the mRNA expressions of PINK1 and Parkin increased significantly, and the differences were statistically significant (p < 0.05). However, NAC pretreatment reduced the expression of PINK1 and Parkin mRNA, suggesting that ROS plays an important role in the up-regulation of PINK1or Parkin mRNA by NaAsO2 in L-02 cells. As shown in Figure 4B, Western blot results showed that the expression levels of p62, LC3 II/І, and PINK1 protein following exposure to the NaAsO2 increased (p < 0.05), and the expression of Parkin protein in the cytoplasm decreased (p < 0.05), indicating that NaAsO2 induced PINK1/Parkin-mediated mitophagy. In contrast, the expression levels of p62, LC3 II/І, PINK1, and Parkin protein were significantly (p < 0.05) reduced in the NAC+As group compared with the As group, indicating that ROS induced by NaAsO2 mediates the PINK1/Parkin pathway. 4. Discussion Dictyophora is a valuable dual-use fungus, rich in vitamins, proteins, polysaccharides, and other active substances [19]. DIP is extracted from Dictyophora and consists of a variety of monosaccharides that have been shown to have anti-inflammatory and immunomodulatory properties [20]. It has great exploitation value in medicine and food. Kanwal et al., using the Illumina MiSeq platform, found that DIP decreased endotoxemia (via lipopolysaccharide) and pro-inflammatory cytokine (TNF-α, IL-6, and IL-1β) levels and increased the expression of tight junction related proteins (claudin-1, occludin, and zonula occludens-1). This demonstrates the effect of DIP in reducing inflammation and lowering endotoxin levels [21]. Wang et al. used DIP to intervene in C57BL/6 mice with dextran sodium sulfate-induced colitis and showed that DIP could regulate macrophage polarization and restore intestinal barrier function, suggesting that DIP could be used as a functional food or nutritional agent to improve intestinal inflammation [22]. Guizhou province in China is a typical karst landscape, and some of the soils in the region are rich in the element As [3]. We previously used Bayesian reference dosing to analyze the possible maximum acceptable cumulative arsenic exposure level for liver damage caused by arsenic from coal burning in Guizhou province. For liver damage caused by arsenic from coal burning, the recommended maximum acceptable cumulative arsenic exposure level is 7120 mg. With the increase of cumulative exposure, liver injury was aggravated, resulting in significant changes in serum ALT, AST, and other indicators [23]. Our previous study has confirmed the protective effect of DIP against liver injury caused by arsenic through in vivo experiments in rats, but the mechanism is unclear [14]. In addition, we found that arsenic exposure can cause mitophagy in human liver cells (L-02 cells), thereby mediating apoptosis, and the PINK1/Parkin pathway plays an important role [9]. This is consistent with most studies. Jiang et al. found that lipocalin mediated mitophagy via the activation of the SIRT1-PINK1 signaling pathway, which is closely related to oxidative stress, inflammation, apoptosis, and mitochondrial dysfunction induced by lung ischemia-reperfusion injury in type 2 diabetic rats [24]. In addition, a study confirmed that probiotic pretreatment mediated PINK/ Parkin-induced autophagy and eliminated damaged mitochondria, thereby reducing induced apoptosis [25]. All of the above suggest a close relationship between autophagy and cell damage. Mitochondria are important functional organs that provide energy during normal life activities. Damage to mitochondria may lead to a variety of human diseases, including cancer, cardiovascular disease, neurodegenerative disease, and liver disease [26]. When mitochondria are damaged by starvation, oxidative stress, inflammation, ROS, or hypoxia, they will initiate mitophagy to protect themselves [27,28]. Mitophagy is a kind of selective autophagy, which is used to selectively remove damaged mitochondria or misfolded proteins in the cell. It plays a vital role in maintaining cell homeostasis and mitochondrial quality control [29]. Therefore, based on our previous evidence that DIP has a protective effect against As-induced liver injury, and that As can induce mitophagy and trigger cytotoxicity through the PINK1/Parkin pathway, our present study explored the mechanism of DIP protection against As-induced liver injury from the perspective of mitophagy to further enrich the pharmacological mechanism of Dictyophora. Our study showed that L-02 cell survival decreased after NaAsO2 treatment and that protein expression of p62 and LC3 II/І increased with increasing exposure concentration and time. LC3 and p62 are the main proteins involved in autophagy and are key indicators for detecting cellular autophagy, so it is suggested that NaAsO2 can induce autophagy. The PINK1/Parkin pathway is currently a pathway that has been studied in the mitophagy pathway [30]. PTEN-induced kinase 1 (PINK1) is a Ser/Thr kinase that is mainly located on the outer membrane of mitochondria. Parkin RBR E3 ubiquitin protein ligase (Parkin) is mainly located in the cytoplasm and plays a key role in mitochondrial motility and size [31,32]. In general, the small amount of PINK1 produced is easily degraded by the proteasome, so it cannot be detected or the amount detected is small; but when the membrane is depolarized or the mitochondrial complex is damaged, the PINK1 dimer is autophosphorylated, thereby activate kinase and bind to ubiquitinated Parkin. As PINK1 can quickly respond to changes in mitochondrial stressors, it can be used as a sensor of mitochondrial damage [33,34]. The results of this experiment showed that compared with the control group, the expression level of PINK1 protein increased in L-02 cells treated with NaAsO2, while the level of Parkin protein in the cytoplasm decreased, indicating that NaAsO2 induced PINK1/Parkin-mediated mitophagy. DIP has antioxidant capacity. Liu et al. found that DIP exhibited the strong reducing ability and scavenging activity of DPPH, superoxide and hydroxyl radicals in vitro antioxidant assays, indicating the potential of DIP as a natural antioxidant resource [35]. Our previous study also found that DIP unregulated the expression of Bax and caspase-3 genes and reduced Bcl-2/Bax heterodimer formation, regulated the HCC-LM3 cell cycle, and promoted the role of the cellular mitochondrial apoptotic pathway, suggesting that DIP has potential therapeutic value for liver injury [16]. In the organism, one of the main sources of ROS is the substrate end of the respiratory chain in the inner mitochondrial membrane, and mitochondrial damage leads to an increase in ROS, triggering increased activity of DPPH and oxidative and hydroxyl radicals [36]. Thus, does DIP inhibit arsenic-induced mitophagy in the liver, and is the mechanism of DIP protection of the liver related to ROS? We found that DIP had an inhibitory effect on NaAsO2-induced L-02 cytotoxicity by assaying the cellular activity after DIP pretreatment. Detection of intracellular ROS by DCFH-DA fluorescent probe assay revealed that NaAsO2 could induce intracellular ROS production, while DIP could scavenge excess ROS. It is known that increased ROS disrupts the mitochondrial membrane and alters the membrane permeability, reducing the concentration difference between ions inside and outside the membrane by free diffusion, which leads to a decrease in membrane potential [37]. Therefore, we used JC-1 probe staining to detect the proportion of mitochondrial membrane potential depolarization in cells and found that NaAsO2 induced an increase in the proportion of mitochondrial membrane potential depolarization, and this proportion decreased after DIP treatment. This shows that DIP has a protective effect on NaAsO2-induced mitochondrial damage; however, does DIP interfere with the mitochondria process? We further examined the expression of p62, LC3 II/І, PINK1, and Parkin proteins and found that pretreatment with DIP reduced the expression of these proteins compared to NaAsO2 exposure alone. The p62 protein, also known as the SQSTM1 protein, is involved in autophagy as a linker protein connecting LC3 and ubiquitinated substrates [38]. As an important autophagic bridging protein, p62 is responsible for the degradation of ubiquitinated proteins into autophagosomes and is a marker of autophagic flow, and reduced levels of p62 imply that autophagic flow is protected. In summary, we hypothesize that during NaAsO2-induced mitochondrial injury. DIP may reduce the proportion of mitochondrial membrane potential depolarization by clearing excess ROS scavenging, activating the PINK1/Parkin pathway to regulate p62 and LC3 II/І protein expression, and alleviating arsenite-induced mitophagy injury. Finally, we directly used a specific scavenger of ROS (N-Acetyl-L-cysteine. NAC) to verify our speculation, and the results were as we thought. Pretreatment of L-02 cells with NAC followed by arsenic exposure inhibited NaAsO2-induced mitophagy along with a decrease in intracellular ROS levels. LC3 II/І, p62 expression levels were also reduced. We further investigated the relationship between NaAsO2-induced production of ROS and mitophagy and the PINK1/Parkin pathway. The results showed that NaAsO2 treatment increased the expression level of PINK1 and Parkin, while NAC pretreatment alleviated this phenomenon. Moreover, we found by transmission electron microscopy results that more morphologically abnormal mitochondria were present in NaAsO2-treated cells compared with control cells, forming mitochondrial autophagosomes, while structural damage of mitochondria was significantly inhibited by NAC pretreatment. These results suggest that ROS scavenging plays an important role in the protective mechanism of DIP against NaAsO2-induced mitophagy in L-02 cells. This study provides new evidence for the hepatoprotective mechanism of Dictyophora and provides a reference for the study of the pharmacological mechanism of Dictyophora polysaccharide. However, there are limitations, because the molecular mechanism of mitophagy is complex; among the many mechanisms of mitophagy, we only studied the PINK1/Parkin pathway. In addition, Dictyophora polysaccharide has a variety of beneficial effects on the human body and may not have a single reason for its hepatoprotective effect, so further research is needed on the hepatoprotective mechanism of Dictyophora polysaccharide. 5. Conclusions In summary, mitophagy was found in hepatocytes induced by arsenic exposure, and DIP exerts a protective effect on hepatocyte by scavenging ROS, which could restrain arsenic-induced mitochondrial membrane potential depolarization and PINK1/Parkin pathway-mediated mitophagy to inhibit hepatocyte injury (Figure 5). Author Contributions Conceptualization, T.H. and C.W.; methodology, J.L. and T.H.; investigation, T.D. and C.W.; Writing—original draft preparation, T.H.; Writing—review and editing, P.L.; Funding acquisition, P.L. 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 All data and materials are contained and described within the manuscript. Conflicts of Interest The authors report no potential conflict of interest. Figure 1 As induces mitophagy in L-02 cells. (A) CCK8 assay was used to explore the most suitable exposure time and concentration for this experiment. (B) Western blotting was used to detect the effect of different concentrations of NaAsO2 on autophagy-related proteins under different exposure times. (C) Western blotting was used to detect the effects of different exposure times on autophagy-related proteins under different concentrations of NaAsO2. * p < 0.05 compared with the control group. Figure 2 DIP inhibited NaAsO2-induced mitophagy in L-02 cells. (A) CCK8 assay was used to determine the concentration of DIP with the best effect. (B) DCFH-DA fluorescent probe was used to detect intracellular ROS. (C) JC-1 mitochondrial membrane potential detection kit was used to detect mitochondrial membrane potential of cells. (D) Western blotting was used to detect the effect of DIP on autophagy-related proteins. * p < 0.05 compared with the control group. # p < 0.05 compared with the As group. Figure 3 Effects of scavenging ROS on NaAsO2-induced mitochondrial structural damage. (A) CCK8 assay was used to detect cell viability of NAC pretreatment. (B) Flow cytometry detection of NAC inhibits the accumulation of ROS in L-02 cells induced by NaAsO2. (C) The ROS detection kit fluorescently detects the effect of NAC on the ROS in L-02 cells induced by NaAsO2. Scale bar = 100 μm. (D) Transmission electron microscopy was used to detect the effect of NaAsO2 on intracellular mitochondria and the effect of NAC. In the figure, the yellow arrow points to normal or slightly damaged mitochondria, and the blue arrow indicates the appearance of mitochondria with disappeared mitochondrial cristae, swelling, and enlargement. * p < 0.05 compared with the control group. # p < 0.05 compared with the As group. Figure 4 Effects of ROS clearance on mitophagy-related genes and proteins in PINK1/Prkin pathway. (A) RT-qPCR was used to detect the changes of PINK1 and Parkin mRNA in mitophagy induced by NaAsO2 treated with NAC. (B) Western blotting was used to detect the expression of mitophagy-related proteins induced by NaAsO2 after NAC pretreatment. * p < 0.05, ** p < 0.01 compared with the control group. # p < 0.05, ## p < 0.01 compared with the As group. Figure 5 DIP attenuates PINK1/Parkin pathway-mediated mitophagy damage in L-02 cell through scavenging ROS. Mitophagy was found in hepatocytes induced by arsenic exposure, and DIP exerts a protective effect on hepatocyte by scavenging ROS, which could restrain arsenic-induced mitochondrial membrane potential depolarization and PINK1/Parkin pathway-mediated mitophagy to inhibit hepatocyte injury. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Shrestha A. Sharma S. Gerold J. Erismann S. Sagar S. Koju R. Schindler C. Odermatt P. Utzinger J. Cissé G. 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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091207 plants-11-01207 Review Advances in Understanding the Genetic Basis of Fatty Acids Biosynthesis in Perilla: An Update Bae Seon-Hwa 1 https://orcid.org/0000-0003-2781-0778 Zoclanclounon Yedomon Ange Bovys 2 https://orcid.org/0000-0003-3691-5838 Kumar Thamilarasan Senthil 2 https://orcid.org/0000-0003-1100-6953 Oh Jae-Hyeon 3 https://orcid.org/0000-0002-2029-5702 Lee Jundae 1 Kim Tae-Ho 2 https://orcid.org/0000-0003-2935-7612 Park Ki Young 4* Martínez-Force Enrique Academic Editor Martínez-Rivas José Manuel Academic Editor 1 Department of Horticulture, Institute of Agricultural Science & Technology, Jeonbuk National University, Jeonju 54896, Korea; cute1004bsh@naver.com (S.-H.B.); ajfall@jbnu.ac.kr (J.L.) 2 Genomics Division, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea; angez9914@gmail.com (Y.A.B.Z.); seninfobio@gmail.com (T.S.K.); thkim1961@korea.kr (T.-H.K.) 3 R&D Coordination Division, Rural Development Administration, Jeonju 54875, Korea; jhoh8288@korea.kr 4 Department of Practical Arts Education, Gongju National University of Education, Gonju 32553, Korea * Correspondence: kypark7502@gjue.ac.kr 29 4 2022 5 2022 11 9 120708 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/). Perilla, also termed as purple mint, Chinese basil, or Perilla mint, is a flavoring herb widely used in East Asia. Both crude oil and essential oil are employed for consumption as well as industrial purposes. Fatty acids (FAs) biosynthesis and oil body assemblies in Perilla have been extensively investigated over the last three decades. Recent advances have been made in order to reveal the enzymes involved in the fatty acid biosynthesis in Perilla. Among those fatty acids, alpha-linolenic acid retained the attention of scientists mainly due to its medicinal and nutraceutical properties. Lipids synthesis in Perilla exhibited similarities with Arabidopsis thaliana lipids’ pathway. The homologous coding genes for polyunsaturated fatty acid desaturases, transcription factors, and major acyl-related enzymes have been found in Perilla via de novo transcriptome profiling, genome-wide association study, and in silico whole-genome screening. The identified genes covered de novo fatty acid synthesis, acyl-CoA dependent Kennedy pathway, acyl-CoA independent pathway, Triacylglycerols (TAGs) assembly, and acyl editing of phosphatidylcholine. In addition to the enzymes, transcription factors including WRINKLED, FUSCA3, LEAFY COTYLEDON1, and ABSCISIC ACID INSENSITIVE3 have been suggested. Meanwhile, the epigenome aspect impacting the transcriptional regulation of FAs is still unclear and might require more attention from the scientific community. This review mainly outlines the identification of the key gene master players involved in Perilla FAs biosynthesis and TAGs assembly that have been identified in recent years. With the recent advances in genomics resources regarding this orphan crop, we provided an updated overview of the recent contributions into the comprehension of the genetic background of fatty acid biosynthesis. The provided resources can be useful for further usage in oil-bioengineering and the design of alpha-linolenic acid-boosted Perilla genotypes in the future. fatty acid biosynthesis Perilla transcription factor oil crop genomics fatty acid desaturase triacylglycerol biosynthesis transcriptomics This study received no external funding. ==== Body pmc1. Introduction Perilla frutescens var. frutescens is an oil crop from the mint family that is widely distributed in East Asia including India, Vietnam, China, and Korea [1]. The Perilla genetic resource encompasses the oil crop type P. frutescens var. frutescens, the weedy/wild type P. frutescens, and wild species Perilla setoyensis, Perilla hirtella, and Perilla citriodora [2]. While P. citriodora is known as one of the diploid progenitors [3] of tetraploid P. frutescens, the second diploid donor has not yet been elucidated. In Korean dietary habits, P. frutescens var. frutescens is used for its oil and as leafy vegetable. The fresh leaves can serve as a wrap for meat and boiled rice and are also prepared in a pickled form [2]. In China, where it originated [1,2], Perilla is used secularly as a traditional herbal medicine and fragrance [2]. The health-promoting properties of this plant are attributable to its wide panel of phytochemical compounds [4]. Among them, fatty acids including omega-3, -6, and -9 have been reported as anti-cancer agents [5,6,7], coronary heart-disease protectants [8], anti-diabetic agents [9], insulin-resistant [10], anti-cardiovascular disease agents [11], and anti-depressive agents [12,13,14]. In addition, preclinical tests revealed the positive effect of Perilla for mitigating moderate dementia [15]. However, further investigations are required to confirm its role before a recommendation for its use as an antioxidative complement for patients with dementia [4,15]. In addition, Perilla is also used as a supplement in animal feeding [16,17]. Due to the numerous applications of fatty acids from Perilla in the health industry, the oil industry, and for animal breeding, a comprehensive background underpins fatty acid biosynthesis as a fundamental prerequisite for proper utilization in the biomedical, bioengineering, and animal industries. Recently, Perilla entered into the genomics era with the sequencing of tetraploid P. frutescence and one diploid donor P. citriodora [3], laying a foundation for unraveling the genetic basis of its multiple health and nutraceutical benefits. In the present review, we will examine recent breakthroughs on the genetic basis of fatty acid biosynthesis in Perilla. 2. Earlier Identification and Cloning of Fatty Acid Encoding Gene in Perilla The genetic characterization interest for Perilla as an oil crop with numerous health beneficial attributes started as early as the 1900s. Several fatty acid genes have been cloned and functionally characterized. Lee et al. (https://www.ncbi.nlm.nih.gov/nuccore/U59477.1/, accessed on 12 February 2021) first characterized a ω-3 fatty acid desaturase PfrFAD7 (Genbank accession: U59477.1) extracted from a Korean cultivar “Okdong” seedling. Subsequently, a cloning of a second gene PrFAD3 was conducted by Chung et al. [18]. PrFAD3 exhibited a seed-specific expression when compared to other organs including the leaf, stem, and root, suggesting a preferential accumulation of alpha-linolenic acid (ALA) in the seed. Hwang et al. [19,20] also reported four 3-ketoacyl-acyl carrier protein synthases (KAS) encoding genes, PfKAS3a (KAS III) and PfKAS3b (KAS III), PfFAB1 (KAS I), and PfFAB24 (KAS II/IV), which were responsible in the high accumulation of alpha-linolenic synthesis in P. frutescens seeds. Another alpha-linolenic acid-related gene, the microsomal oleate 12-desaturase (PfFAD2) gene, was functionally characterized for the first time in P. frutescens var. frutescens seed [21] in later studies. In addition to the previously identified FAD3 and FAD7 type genes, Xue et al. [22] isolated two FAD8 alpha-linoleic-related genes (PrFAD8a and PrFADb) harboring two pyrimidine stretches. Interestingly, the expression of PrFAD8 genes was predominantly observed in the Perilla bud while its accumulation increased under injury, Methyl jasmonate (MeJA), Salicylic Acid (SA), and Abscisic acid (ABA) effects; highlighting their implications in plant defense, growth, and development. 3. Transcriptomics Sheds Lights into Key Master Player Enzymes of Perilla Fatty Acid Biosynthesis Although some genes have been investigated earlier, the fully resolved biosynthesis pathway of fatty acids in Perilla was still unclear. To fill this gap, the RNA sequencing approach has been extensively used because it helps in uncovering expressed genes related to a biological process. By deciphering the transcriptome of Perilla using diverse organs, scientists were able to identify key genes related to fatty acid biosynthesis via de novo transcripts assembly and functional gene prediction. Thus, extensive transcriptome studies have been initiated using different materials, including P. fruescens var. frutescens, Perilla frutescens var. crispa f. purpurea (red Perilla), and P. frutescens var. crispa f. viridis (green Perilla) [23,24,25,26]. The uncovered key genes involved in fatty acid biosynthesis in Perilla have been summarized in Figure 1. Briefly, based on Perilla’s fatty acid desaturase subcellular localization prediction [27] and the well-studied Arabidopsis fatty acid biosynthesis model [28], most fatty acids, including palmitic acid (C16:0), stearic acid (C18:0), and oleic acid (C18:1), were exclusively synthesized in plastids and conveyed into the cytoplasm where they entered into an acyl-CoA pool for the esterification process at sn-2 position resulting in phosphatidylcholine under the acyl-CoA:lysophosphatidylcholine acyltransferase (LPCAT) enzyme effect. Oleic acid was then desaturated in the endoplastic rediculum (ER) to become consecutively linoleic acid (LA) and alpha-linolenic acid (ALA) under FAD2 and FAD3 genes, respectively. The resulting polyunsaturated fatty acids were transacylated onto the sn-3 position of diacylglycerol by phospholipid:diacylglycerol acyltransferase (PDAT) or returned to the acyl-CoA pool via LPCAT to be incorporated into TAG through the Kennedy pathway, inducing the production of triacylglycerols (TAGs) [29]. Using Perilla as a plant model, numerous fatty acid-related genes have been identified. From a time-course seed transcriptome analysis, Kim et al. [25] identified 43 acyl-lipid related genes in P. frutescens var. frutescens cv. Dayudeulkkae (Table 1). The identified genes via Arabidopsis orthologs detection covered the de novo fatty acid biosynthetic key enzymes present in the plastid, endoplasmic reticulum desaturases, oil body proteins, acyl-CoA-, and phosphatidylcholine-mediated TAG synthesis. Transcriptome mining revealed five sub-unit genes (α-PDH, β-PDH, EMB3003, LTA2, and LPD1) of the precursor enzyme plastidial pyruvate dehydrogenase complex (PDHC) involved in the synthesis of acetyl-CoA from pyruvate. Afterward, acetyl-CoA carboxylase (ACCase) transformed acetyl-CoA ito malonyl-CoA [30]. The ACCase in Perilla encompassed two ACCases subunits alpha (α-CTa and α-CTb), one ACCase subunit beta (β-CT), two isoforms of biotin carboxyl-carrier protein (BCCP1 and BCCP2), and one biotin carboxylase (BC). Furthermore, the malonyl-CoA ACP transacylase, an acyl carrier protein transacylase, catalyzed malonyl-CoA to form malonyl-ACP, paving the way for fatty acid elongation under the action of acyl-chain enzymes, i.e., 3-keto-acyl-ACP synthase (KAS), 3-ketoacyl-ACP reductase (KAR), 3-hydroxylacyl-ACP dehydratase (HAD), and Trans-∆2-enoyl-ACP reductase (EAR), respectively [23,24,31]. It is worth mentioning that WR1 is well conserved in plant species. For instance, homologous genes have been identified in Brachypodium distachyon [32], Camelina sativa [33], Solanum tuberosum [34], Cocos nucifera [35], Brassica napus [36], Elaeis guineensis [37], and Jatropha curcas [38]. In A. thaliana, through the promoter binding element AW-box, WRI1 targets upstream genes encoding for malonyl-CoA:ACP malonyl transferase, enoyl-ACP reductase, pyruvate dehydrogenase, oleoyl-ACP thioesterase, biotin carboxyl carrier protein 2, ketoacyl-ACP synthase, and hydroxyacyl-ACP dehydrase [39,40,41,42,43,44,45,46]. The homologous sequence of WR1 has been demonstrated in augmentation from 10 to 40% of seed oil in transgenic maize [47] and Brassica napus [36], suggesting that Perilla’s WR1 gene might be a promising candidate for oil-oriented bioengineering in Perilla. Through carbon chain elongation, palmitoyl-ACP (C16:0) is converted into stearoyl-ACP (C18:0). The latter is transformed into oleic acid (C18:1)-ACP under the catalysis of stearoyl-acyl carrier protein desaturase (SAD). In Perilla, two SAD genes have been identified, including PfFAB2 and PfDES6 [25]. Using a red Perilla (Perilla frutescens var. crispa F. purpurea) seed transcriptome, Liao et al. [23] identified fatty acid desaturases PfFAD6 and PfFAD7/8 that act on the vector glycerolipid, i.e., monogalactosyldiacylglycerol (MGDG), in order to process (C18:1) into (C18:2) and (C18:2) to (C18:3), respectively (Figure 1). To terminate fatty acids synthesis in Perilla plastids, fatty acyl-ACP thioesterase (FATA), palmitoyl/stearoyl-acyl carrier protein thioesterase (FATB), and palmitoyl-CoA hydrolase (PCH) were solicitated. PCH specifically induced C18:1- and C18:2-synthesis, while FATA was a C18:1-exclusive catalyst. Meanwhile, FATB transformed only C16:0-ACP or C18:0-ACP to C16:0 or C18:0, respectively (Figure 1). Representative gene coding for these enzyme has been pinpointed by de novo transcriptome analysis and comparative transcripts with regard to the well characterized A. thaliana fatty acid-related gene [23,24]. Free FAs were then moved into the cytoplasm where they were esterified to form an Acyl-CoA pool under the action of long-chain acyl-COA synthesis (LACS). Liao et al. [23] reported the important expression of LACS genes in Perilla seeds ten days after flowering, indicating an initiation of TAGs synthesis pathway in the endoplasmic reticulum (ER). In the ER, esterified fatty acids are translated into phosphatidylcholines via lysophosphatidylcholine acyltransferase (LPCAT). Based on the Arabidopsis plant model, mainly two fatty acid desaturases have been identified in the ER: an FAD2 that converts PC-C18:1 into PC-18:2 and an FAD3 that catalyzes PC-C18:2 into PC-C18:3 [48,49,50]. Homologous sequences in Perilla seed (PfFAD2 and PfFAD3) transcriptome [23,24,25] have also been identified (Table 1). Recently, the transcriptome assessment of Chinese cultivar PF40 highlighted 33 candidate genes involved in TAG biosynthesis-covering transcription factors (Supplementary Table S1), and fatty acids were exported from plastid, acyl editing of phospatidylcholine, acyl-CoA dependent Kennedy pathway, acyl-CoA independent pathway, and TAGs assembly into oil bodies (Table 1). The identified genes corroborated with previous findings [23,24,25], except for the first identification of fatty export1 (FAX1) as an additional enzyme to long-chain acyl-CoA synthetase (LACS) that mediated plastid fatty acid export. In the absence of a whole genome representative resources, the detection of potential genes isoforms and the full FADs gene repertoire is difficult to predict, and diverse gene targets for functional validation and bio-engineering purposes are not provided. Due to the fact that Perilla has entered into the genomics era, the next section covers genomics-based advances in the detection of fatty acids in Perilla via genome-wide identification and genome-wide association study strategies. 4. Whole-Genome-Driven Fatty Acid Genes Discovery With the advent of long-reads and chromosome conformation capture technologies, a high-quality chromosome scale genome of tetraploid P. frutescens var. frutescens has recently been assembled [3]. The genome spanned 1.203 Gb, along with 20 chromosomes with an N50 of 62.64 Mb and a total of 38,941 predicted gene models. From a panel of 191 accessions, a genome-wide association study for seed alpha-linolenic acid content enabled the identification of an LPCAT encoding region located in chromosome 2. This finding corroborates previous observations, suggesting the role of LPCAT in FAs and TAGs synthesis in B. napus [51] and A. thaliana [52]. Interestingly, a deletion of this gene was noted in some individuals of the studied panel corresponding to a loss of around 6% of seed oil ALA content. This suggests that the transcriptional regulation of LPCAT might be responsible for ALA content variations in Perilla. Taking advantage of the PF40-generated high-quality genome, in silico genome-wide analysis identified a repertoire of 42 fatty acid desaturases clustered into five families including omega-3 desaturase, ∆7/∆9 desaturase, FAD4 desaturase, ∆12 desaturase, and front-end desaturase [27]. The heterologous validation of candidate fatty acid desaturase genes using A. thaliana revealed a positive impact (increase of 18–37% alpha-linolenic acid content) of the PfFAD3.1 gene. Furthermore, the upregulation of WRINKLED (WRI1), FUSCA3 (FUS3), LEAFY COTYLEDON1 (LEC1 and LCE2), and ABSCISIC ACID INSENSITIVE3 (ABI3) transcription factors was noted in PfFAD3.1 Arabidopsis transgenic lines [3] and Perilla seed expression profiles [23], suggesting their regulation roles in the Perilla FAs synthesis pathway. 5. Concluding Remarks and Outlook Fatty acids play an important role in the lipid supply of plants and have valuable medicinal properties for humans. Here, we summarized the breakthroughs that shed light into the genetic and molecular determinants of FA and TAG synthesis in Perilla. Transcriptomics and genomics studies revealed the key master player enzymes responsible for FAs synthesis in Perilla, including polyunsaturated fatty acids desaturases, acyl-related enzymes, and transcription factors. However, the evidence of their role is still elusive since strong functional validation has not yet been provided. The mechanism of the regulation of FA synthesis by TFs in Perilla is still elusive. Meanwhile, the recent work from Moreno-Perez et al. [53] suggested histone methylation (H3K4me3) implication into fatty acid biosynthesis in sunflowers with interactions with TFs. Moreover, acetyl-CoA, which is involved in fatty acid synthesis in plants, has been found to be correlated with histone acetylation and DNA methylation in A. thaliana through the beta-oxidation process [54]. Therefore, an in-depth investigation of identified TFs, such as ABI3, FUS3, LEC1, and LEC2, and the epigenome landmark of Perilla will pave a new avenue in deciphering the full landscape of fatty-acid biosynthesis in Perilla. Functional validation using Perilla as a material instead of A. thaliana would drastically shape the validation efficiency of the identified genes. For this purpose, Agrobacterium-based protocols [55,56] have been tested and can serve as further functional validation. Moreover, in the current era of gene and genome editing with applicable cases in plants [57,58,59,60], designing appropriate gene editing strategies that fit into the Perilla system will surely expedite the production of enriched alpha-linolenic acid-Perilla genotypes. Furthermore, considering the species diversity within the Perilla genus, systematic fatty acid content evaluation within the Perilla species will help reveal potential alpha-linolenic acid-enriched species donors and characterize their respective biosynthetic pathways. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants11091207/s1, Table S1: Identified transcription factors from Perilla through trancriptome, whole genome, and in silico co-expression analyses. Click here for additional data file. Author Contributions Conceptualization, S.-H.B.; methodology, S.-H.B. and Y.A.B.Z.; writing—original draft preparation, S.-H.B., Y.A.B.Z. and T.S.K.; writing—review and editing, S.-H.B., J.-H.O., J.L., T.-H.K. and K.Y.P.; visualization, Y.A.B.Z.; supervision, J.L., T.-H.K. and K.Y.P.; funding acquisition, K.Y.P. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data presented in this study are available in Table S1. Conflicts of Interest The authors declare no conflict of interest. Figure 1 A simplified putative diagram view of fatty acids biosynthetic pathway in Perilla and triacylglycerols (TAGs) assembly. The schematic view involved bio-chemical interactions occurring in plastid, cytoplasm, and endoplasmic reticulum, respectively. The resulting TAGs are indicated in yellow. Purple circles indicate transcription factors, including WRINKLED (WRI1), FUSCA3 (FUS3), LEAFY COTYLEDON1 (LEC1, LCE2), and ABSCISIC ACID INSENSITIVE3 (ABI3). The transcriptional regulation of FUS3, LCE1, LCE2, and ABI3 with PfFAD3.1 is not yet uncovered. PDHC: plastidial pyruvate dehydrogenase complex; ACCase: acetyl-CoA carboxylase; MCMT: malonyl-CoA ACP transacylase; KASIII: ketoacyl-ACP synthase type III; KAR: 3-ketoacyl-ACP reductase; HAD: 3-hydroxyacyl-ACP dyhydratase; EAR: 2-enoyl-ACP reductase; KASII: ketoacyl-ACP synthase type II; KASI: ketoacyl-ACP synthase type I; SAD: stearoyl-acyl carrier protein desaturase; FATB: acyl-ACP thioesterase B; FATA: acyl-ACP thioesterase A; MGDG: monogalactosyldiacylglycerol; PfFAD: Perilla frutescens fatty acid desaturase; PC Pool: phosphatidylcholines pool; PCH: palmitoyl-CoA hydrolase; LACS: long-chain acyl-CoA synthetase; PDCT: phosphatidylcholinediacylglycerol cholinephosphotransferase; FAX: fatty acid export; LPCAT: lysophosphatidylcholine acyltransferase; PDAT: phospholipid diacylglycerol acyltransferase; DGAT: diacylglycerolacyltransferase; GPAT: glycerol-3-phosphate acyltransferase; LPAT: 1-acylglycerol-3-phosphate acyltransferase; DHAP: dihydroxyacetone phosphate; PAH: phosphatidic acid phosphatase; OLEO: Oleosin. plants-11-01207-t001_Table 1 Table 1 Summary of Identified Major Genes Involved in Fatty Acid and Triacylglycerols Biosynthesis in Perilla. Enzyme ID Enzyme Name GeneID Homologous Pathways Involved Field of Study References PF40 * Dayudeulkkae ** PC *** A. Thaliana PDH(E1α) Pyruvate Dehydrogenase E1 Subunit Alpha 1 Locus_2112 AT1G01090.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] PDH(E1ß) Pyruvate Dehydrogenase E1 Subunit beta 1 Locus_25208 AT2G34590.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] EMB3003(E2) Pyruvate dehydrogenase e2 component (dihydrolipoamide acetyltransferase) Locus_33306 AT1G34430.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] LTA2 (E2) Plastid E2 Subunit of Pyruvate Decarboxylase, PLE2 Locus_5104 AT3G25860.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] LPD1 (E3) Lipoamide dehydrogenase Locus_7407 AT3G16950.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] α-CTa Alpha-carboxyltransferase Isoform a Locus_8492 AT2G38040.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] α-CTb Apha-carboxyltransferase Isoform b Locus_2178 AT2G38040.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] ß-CT Beta-carboxyltransferase Locus_53041 ATCG00500.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] BC Biotin carboxylase Locus_22078 AT5G35360.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] BCCP1 Biotin carboxyl carrier protein of acetyl-CoA carboxylase 1 Locus_29162 AT5G16390.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] BCCP2 Biotin carboxyl carrier protein of acetyl-CoA carboxylase 2 Locus_17340 AT5G15530.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] MCMT Malonyl-CoA ACP transacylase Locus_14579 AT2G30200.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] KASIII 3-Ketoacyl-ACP synthase Locus_10821 AT1G62640.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] KAR 3-ketoacyl-ACP reductase Locus_1445 AT1G24360.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] HAD 3-hydroxyacyl-ACP dyhydratase Locus_19332 AT5G10160.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] EAR 2-enoyl-ACP reductase Locus_25443 AT2G05990.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] FATA Fatty acyl-ACP thioesterase A Locus_29919 AT3G25110.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] FATB Fatty acyl-ACP thioesterase B Locus_6603 AT1G08510.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] FAB2 Fatty acid biosynthesis2 Locus_13564 AT2G43710.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] DES6 Stearoyl-acyl carrier protein desaturase Locus_9486 AT1G43800.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] KASI Ketoacyl-ACP Synthase I Locus_26341 AT5G46290.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] KASII Ketoacyl-ACP Synthase II Locus_1373 AT1G74960.1 FA de novo biosynthesis and export from plastid Transcriptomics [25] LACS8 Long-chain acyl-CoA synthetase 8 chr07_36292788_36299197 chr19_22302145_22308533 Locus_3838 chr06_37084362_37090768 AT2G04350.1 FA de novo biosynthesis and export from plastid Genome Assembly, Transcriptomics [3,25] LACS9 Long-chain acyl-CoA synthetase 9 chr03_70622879_70627324 chr09_58852417_58856892 chr01_02424545_02428997 Locus_23636 chr01_02424545_02428997 AT1G77590.1 FA de novo biosynthesis and export from plastid Genome Assembly, Transcriptomics [3,25] FAX1 Fatty acid export 1 chr05_24282740_24284950 chr01_71691539_71693779 chr02_42552603_42554830 FA de novo biosynthesis and export from plastid [25] FAX2 Fatty acid export 2 chr07_10626150_10628000 chr06_11381976_11383822 FA de novo biosynthesis and export from plastid [25] FAX3 Fatty acid export 3 chr04_00857340_00859552 chr03_67540865_67543081 FA de novo biosynthesis and export from plastid [25] FAX5 Fatty acid export 5 chr04_65527957_65529911 chr07_22534802_22537586 chr06_00746938_00748860 chr19_10735560_10738363 chr03_02347871_02349825 chr06_23562111_23564893 FA de novo biosynthesis and export from plastid [25] FAD2 Omega-6 fatty acid desaturase chr12_56933298_56934446 chr11_05592060_05593208 chr11_05575254_05576393 Locus_733 chr08_55538081_55539229 AT3G12120.1 Acyl editing of phospatidylcholine Genome Assembly, Transcriptomics [3,25] chr12_56948107_56949167 chr08_55558209_55559348 FAD3 Omega-3 fatty acid desaturase chr12_04645208_04647776 chr11_54194712_54197265 Locus_22029 chr08_04030082_04032640 AT2G29980.1 Acyl editing of phospatidylcholine Genome Assembly, Transcriptomics [3,25] FAD8 Omega-8 fatty acid desaturase Locus_5107 AT5G05580.2 Acyl editing of phospatidylcholine Transcriptomics [25] GPAT9 Glycerol-3-phosphate acyltransferase 9 chr12_33733527_33737891 chr11_26255533_26259881 Locus_10180 chr08_33038421_33042132 AT5G60620.1 Acyl-CoA-dependent TAG synthesis in Kennedy pathway Genome Assembly, Transcriptomics [3,25] LPAT2 1-acyl-sn-glycerol-3-phosphate acyltransferase 2 chr05_23583386_23588593 chr05_34400913_34404444 chr01_72114246_72119454 Locus_6587 chr02_43313059_43318262 chr02_32585727_32589258 AT3G57650.1 Acyl-CoA-dependent TAG synthesis in Kennedy pathway Genome Assembly, Transcriptomics [3,25] PAH1 Phenylalanine hydrolase 1 chr01_61567423_61570965 chr14_08597119_08602056 chr15_37103964_37108907 chr03_61656532_61661875 chr18_09154357_09159306 chr17_34575710_34580664 chr09_50343045_50349360 chr10_43830659_43835596 chr01_11516392_11522733 Acyl-CoA-dependent TAG synthesis in Kennedy pathway DGAT1 Diacylglycerol O-acyltransferase 1 chr01_09730655_09741367 chr01_48275733_48286173 Locus_14696 chr05_08797620_08808333 AT2G19450.1 Acyl-CoA-dependent TAG synthesis in Kennedy pathway Genome Assembly, Transcriptomics [3,25] DGAT2 Diacylglycerol O-acyltransferase 2 chr14_26782964_26787941 chr18_25811826_25816791 Locus_12629 chr10_25785382_25790335 AT3G51520.1 Acyl-CoA-dependent TAG synthesis in Kennedy pathway Genome Assembly, Transcriptomics [3,25] DGAT3 Diacylglycerol O-acyltransferase 3 Locus_1560 AT1G48300.1 Acyl-CoA-dependent TAG synthesis in Kennedy pathway Transcriptomics [25] LPCAT Lysophosphatidylcholine acyltransferase chr01_06996630_07001595 chr05_56678891_56685081 chr01_03079195_03084058 chr07_53028425_53034567 chr01_43224061_43229071 chr02_66141068_66147271 chr02_04634020_04638876 chr19_35211932_35217537 Locus_43749 PC00000058_00436672_00441634 chr02_10454190_10460391 chr05_03185967_03190829 chr06_54113419_54119561 AT1G12640.1 PC-mediated TAG synthesis Transcriptomics [3,25] CPT1 Diacylglycerol cholinephosphotransferase Locus_7821 AT1G13560.1 PC-mediated TAG synthesis Transcriptomics [25] CPT2 Diacylglycerol cholinephosphotransferase Locus_22567 AT3G25585.1 PC-mediated TAG synthesis Transcriptomics [25] PDAT1 Phospholipid:diacylglycerol acyltransferase 1 chr05_44104376_44108847 Locus_7255 chr02_22969948_22974420 AT5G13640.1 Acyl-CoA independent pathway Transcriptomics [3,25] chr03_00447151_00451507 PC00002899_00154872_00159184 chr02_52135886_52140327 chr09_00376677_00380564 PDAT2 Phospholipid:diacylglycerol acyltransferase 2 chr05_38922115_38924735 Locus_29208 chr02_28050267_28052887 AT3G44830.1 Acyl-CoA independent pathway Transcriptomics [3,25] chr02_45992086_45994691 PDCT Phosphatidylcholine:diacylglycerol cholinephosphotransferase chr03_46291224_46293449 chr09_37050943_37053194 Locus_15867 chr01_27228085_27230144 AT3G15820.1 Acyl-CoA independent pathway Genome Assembly, Transcriptomics [3,25] OLEO2 Oleosin2 chr15_52133834_52134256 Locus_31790 AT5G40420.1 TAG assembly Transcriptomics [3,25] chr17_50355018_50355440 chr09_02008310_02008732 OLEO Oleosin chr14_08347244_08347714 Locus_31788 chr10_44101965_44102435 AT3G18570.1 TAG assembly Transcriptomics [3,25] chr18_08871500_08871970 OLEO1 Oleosin1 chr05_05196095_05196523 Locus_29266 chr02_64426568_64426996 AT4G25140.1 TAG assembly Transcriptomics [3,25] chr01_30156121_30156549 OLEO5 Oleosin5 chr05_59989345_59989911 Locus_29276 AT3G01570.1 TAG assembly Transcriptomics [3,25] 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094550 ijms-23-04550 Review Physiological and Pathological Significance of Esophageal TRP Channels: Special Focus on TRPV4 in Esophageal Epithelial Cells https://orcid.org/0000-0002-5285-0221 Boudaka Ammar 12* Tominaga Makoto 234 Couvineau Alain Academic Editor 1 Department of Physiology, College of Medicine and Health Sciences, Sultan Qaboos University, Al-Khoud, P.O. Box 35, Muscat 123, Oman 2 Division of Cell Signaling, National Institute for Physiological Sciences, Okazaki 444-8787, Aichi, Japan; tominaga@nips.ac.jp 3 Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), Okazaki 444-8787, Aichi, Japan 4 Exploratory Research Center on Life and Living Systems, Thermal Biology Group, Okazaki 444-8787, Aichi, Japan * Correspondence: boudaka@squ.edu.om 20 4 2022 5 2022 23 9 455017 1 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/). Transient receptor potential vanilloid 4 (TRPV4) is a non-selective cation channel that is broadly expressed in different human tissues, including the digestive system, where it acts as a molecular sensor and a transducer that regulates a variety of functional activities. Despite the extensive research to determine the role of this channel in the physiology and pathophysiology of different organs, the unique morphological and functional features of TRPV4 in the esophagus remain largely unknown. Ten years ago, TRPV4 was shown to be highly expressed in esophageal epithelial cells where its activation induces Ca2+-dependent ATP release, which, in turn, mediates several functions, ranging from mechanosensation to wound healing. This review summarizes the research progress on TRPV4, and focuses on the functional expression of TRPV4 in esophageal epithelium and its possible role in different esophageal diseases that would support TRPV4 as a candidate target for future therapeutic approaches to treat patients with these conditions. ATP Ca2+ homeostasis esophageal cancer esophageal epithelial cells esophagus GERD ion transporters mechanosensation TRPV4 wound healing ==== Body pmc1. Introduction The main functions of the alimentary canal are the propulsion of food, mechanical and chemical digestion, secretion of enzymes, absorption, and protection against different pathogens and toxins, as well as formation and expulsion of fecal material. These functions are carried out on a daily basis and their regulation depends on a proper set of functional signals from a variety of sources ranging from the luminal contents to the nervous system [1]. Contents of ingested meals interact directly with the alimentary canal epithelium and indirectly with two subsets of nerve fibers, intrinsic and extrinsic, that innervate the gastrointestinal tract. The local nervous system, also termed the enteric nervous system, exists as an intricate neuronal mesh enclosed in the wall of the alimentary canal and is involved in detecting chemical, mechanical, and osmolarity changes, as well as in regulating gut secretory and motility functions. Both limbs of the enteric nervous system, the submucosal and myenteric plexuses, are, in turn, modulated by extrinsic vagal and spinal efferent nerve fibers as part of a reflex arc initiated by stimulation of extrinsic afferent nerves originating from jugular, nodose, and dorsal root ganglia. Such an arrangement provides the alimentary canal with a complex and elaborate set of molecular sensors that scrutinize the luminal contents, discern adverse conditions in the digestive tract wall and lumen, and modulate secretory activity [2]. The esophagus is part of the alimentary canal that extends from the mouth to the anus. Like other segments of the canal, the esophagus wall is composed of the same four basic layers, but the histological features of most of these layers do differ. For example, the outermost layer is adventitia rather than serosa. The esophagus muscularis externa contains striated muscle fibers in its proximal region, and distally, these striated fibers mix with smooth muscle fibers in variable proportions in a species-dependent manner. The submucosa of the esophagus contains connective tissue cells, blood and lymphatic vessels, nerves, and submucosal glands. Interestingly, esophagus tissue in pigs and humans has large numbers of submucosal glands, which are absent in rodent esophagus [3]. Submucosal glands are tubuloacinar glands that are dispersed throughout the submucosa. They are lined with epithelial cells and mainly secrete mucus, bicarbonate, and growth factors, and their primary function is to lubricate the esophagus and to protect the tissue from the damaging effects of acidic gastric refluxate [4]. Another unique feature of the esophageal wall structure is its mucosa, in which the epithelium has a stratified squamous type with varying thickness and degree of keratinization, which is dependent on the species under investigation. In the esophagus of rodents, squamous epithelial cells are organized in four to five layers and are usually keratinized. Meanwhile, in the thicker esophageal mucosa of humans and pigs, the squamous cells are arranged in up to 10–15 layers, and the epithelial surface is not keratinized [3]. Sentient responses to chemical, thermal, and mechanical stimuli occur in the esophagus and ion transporters mediate many of these responses. 2. TRP Channels in the Esophageal Wall Ion transporters play an important role in gastrointestinal physiology and pathophysiology. Several studies have been conducted to explore the physiological expression of different ion channels in the wall of the alimentary canal [5]. In the esophageal mucosa, epithelial cells, also known as esophageal keratinocytes, express a broad variety of receptors and ion channels such as calcium sensing receptors (CaSRs) [6], protease-activated receptor 2 (PAR2) [7], epithelial sodium channels (ENaCs) [8,9], acid-sensing ion channels (ASICs) [10], and members of the transient receptor potential channel family [11,12,13]. These channels and receptors work conjointly as multiple sensors for relevant chemical and physical stimuli. Transient receptor potential (TRP) channels are non-selective cation channels that mediate influx of Ca2+, Mg2+ and monovalent cations in different cell types [14]. The first mammalian thermosensitive TRP channel was cloned from sensory neurons by Professor David Julius and his team in 1997. This TRP channel was first called vanilloid receptor subtype 1 (VR1; now named TRPV1). VR1 was shown to be a heat-sensing calcium-permeable ion channel that is stimulated by capsaicin (the substance that provides the piquancy of hot red chili peppers), noxious heat, and low pH, suggesting its possible role as a pain transducer [15]. This discovery opened the doors for subsequent discovery of other members of the TRP channel superfamily that make substantial contributions to different physiological and pathological conditions in almost every organ of the human body. Professor Julius was recently awarded the 2021 Nobel Prize in Physiology or Medicine, which he shared with the molecular biologist and neuroscientist Professor Ardem Patapoutian. A functional TRP channel has a central cation-permeable hydrophilic pore encircled by four subunits, and each subunit has six transmembrane domains with cytoplasmic C and N termini [16]. To date, mammalian TRP channels are a large superfamily comprising 28 members that are categorized into six subfamilies based on their amino acid sequence: ankyrin (TRPA1), canonical (TRPC1-7), melastatin (TRPM1-8), mucolipin (TRPML1-3), polycystin (PC) (TRPP1-3), and vanilloid (TRPV1-6) [14,17,18]. Members of this family of ion channels are expressed in almost every cell in the body including the alimentary canal [13,19,20,21,22,23], where they play a pivotal role in the homeostasis and different diseases of the GI tract [24,25]. In the digestive tract, TRP channels are mainly expressed by primary afferent sensory neurons that emerge from enteric nervous system neurons, and vagal and dorsal root ganglia that jointly innervate the alimentary canal [25]. Nevertheless, several recent studies also revealed functional expression of TRP channels in non-neuronal cells of the gut such as esophageal epithelial cells, enterocytes, and enteroendocrine cells [12,26,27,28]. The TRPV1 channel, the most studied member of the TRP family, is extensively expressed in the alimentary canal, mostly by primary afferent sensory and enteric neurons, but it is also expressed by enteroendocrine cells and mucosal epithelial cells [29]. The TRPA1 channel is expressed by mucosal cells as well as ganglia and enteric primary neurons that project to the alimentary canal. The TRPA1 channel is considered as one of the most promising polymodal chemosensors in the gut as it can be stimulated by an array of dietary and noxious molecules, such as allicin and isothiocyanates, as well as by products of oxidative stress and exogenous irritants [25,30]. The TRPM5 and TRPM8 channels, two members of the melastatin subfamily, are widely expressed in the alimentary canal. The TRPM5 channel is expressed by lingual taste bud receptor cells and gut chemosensory cells [31,32], whereas the TRPM8 channel mostly localizes to primary afferent neurons where it functions as a cold chemosensor [33,34]. Different members of the TRP superfamily were shown to be expressed in the esophageal wall (Table 1). For instance, TRPA1-expressing vagal sensory neurons and afferent nerves were identified in guinea pig esophagus, where they mediate long-lasting mechanical hypersensitivity of vagal nodose and TRPV1-positive jugular afferent C fibers that is induced following mast cell activation [35]. Moreover, TRPA1 channel agonists preferentially stimulate vagal nodose nociceptive fibers, whereas jugular nerve fibers have a relatively weaker response to these agonists [36]. TRPA1-expressing vagal sensory neurons and afferent C-fiber subtypes are also sensitized by prolonged allergen challenge in guinea pig esophagus [37]. Although upregulation of mucosal TRPA1 channel expression was shown to mediate macroscopic and microscopic gastric mucosal injury in a rat model of gastritis [38], there is no current evidence to support a role for esophageal epithelial TRPA1 channel in mediating esophagitis or esophageal hypersensitivity in gastroesophageal reflux disease (GERD) patients. Likewise, TRPM8-expressing vagal C fibers of jugular, but not nodose, origin express TRPM8 mRNA and respond to TRPM8 channel agonists as evidenced by results from both patch clamp and calcium imaging techniques [39]. This finding suggests a putative role for these vagal jugular C fibers in esophageal sensation and nociception. This possibility is further supported by the ability of menthol (TRPM8 agonist) infusion to elicit cold sensations in the esophagi of healthy subjects compared to the heartburn evoked in GERD patients [40]. The TRPV1 channel is expressed in esophageal sensory neurons and afferent nerve fibers of different animal species [13], and mediates capsaicin-induced heartburn and esophageal sensitivity [41]. Upregulation of TRPV1 channel expression in mucosal, including intraepithelial, sensory fibers might contribute to symptoms experienced by patients with GERD [47,48]. Moreover, TRPV1 channel overexpression, at both the mRNA and protein level, was shown in the esophageal mucosa of patients with non-erosive reflux disease (NERD) and erosive reflux disease (ERD), suggesting that TRPV1 channel might contribute to NERD symptoms and possibly explain the esophageal hypersensitivity exhibited by these patients [11]. These observations were further supported by a recent study that revealed significantly increased expression of TRPV1 channel on superficial mucosal sensory nerves in NERD patients and concomitant, exclusively increased expression of ASIC3 channel on epithelial cells from patients with NERD and ERD, indicating a sensory role for esophageal epithelial cells in acid reflux perception. These epithelial cells act interdependently with TRPV1-expressing mucosal nerves to augment esophageal hypersensitivity in patients with NERD [49]. This result further supports previous findings in a murine NERD model that indicate a role for mucosal TRPV1 channel overexpression in esophageal inflammation and acid-induced decrease of esophageal transepithelial electrical resistance [50]. TRPV1 channel expression is not restricted to sensory neurons as several recent studies have shown that it is expressed in esophageal epithelial cells. For instance, in human esophageal epithelial cells, the TRPV1 channel mediates interleukin 8 production and induces intracellular production of reactive oxygen species [42]. Furthermore, both in vivo and in vitro studies have shown TRPV1 channel expression on murine esophageal epithelial cells that was increased upon exposure to acid and then was reverted after exposure to menthol [43]. However, the TRPV1 channel does not seem to play a role in the esophageal mucosal barrier in patients with NERD [42]. On the other hand, the TRPV2 channel was shown to be expressed by nitrergic myenteric neurons in the mouse esophagus [44], suggesting that it could modulate esophageal motility via myenteric co-innervation of vagal efferent fibers innervating esophageal striated muscle fibers [21,22,23]. This possibility was further supported by the observed upregulation of TRPV2 channel in nitrergic myenteric inhibitory neurons of the lower esophageal sphincter (LES) in a rat model of reflux esophagitis. This augmented TRPV2 channel expression induces nitric oxide-mediated relaxation of LES resulting in acid reflux that could contribute to the development of GERD. Oral instillation of the TRPV2 channel antagonist tranilast in this esophagitis model significantly ameliorated body weight loss and improved epithelial thickness, as well as lessened severity of esophageal lesions [51]. Although TRPV2, TRPV3, TRPV4, and TRPV6 channels were shown to be present in the mucosa of mouse esophagus and cultured esophageal keratinocytes, the functional role of TRPV2, TRPV3, and TRPV6 channels in esophageal epithelial cells remains unclear [12,46]. High levels of TRPV6 channel expression in human and mouse esophageal stratified epithelia suggest a putative role for this ion channel in mediating cell survival and programmed cell death signaling pathways [46]. Members of the TRP channel superfamily were shown to play an important role in the progression and proliferation of esophageal cancer, especially esophageal squamous cell carcinoma (ESCC). The finding that dysregulation of TRPC6, TRPM2, TRPM7, TRPM8, TRPV1, TRPV2, and TRPV6 channel expression was linked to ESCC pathogenesis and prognosis suggests that these TRP family members could be used as prognostic markers and would be promising therapeutic targets [52]. For instance, the expression levels of TRPC6 mRNA and protein are higher in ESCC tissue compared to normal esophageal tissue, and the inhibition of TRPC6 channel activity in human ESCC cells suppresses cell proliferation and induces G2/M phase arrest, as well as decreases tumor formation in a mouse xenograft model [53]. Likewise, TRPM2 channel expression is increased in ESCC tumor tissue and is involved in calcium-mediated inhibition of cell proliferation and enhanced apoptosis of ESCC cells [54]. TRPM7 channel expression level was also reported to be a valuable prognostic factor in ESCC patients, and siRNA-based silencing of TRPM7 increases ESCC cell proliferation, migration, and invasion [55]. Meanwhile, mRNA and protein expression of another melastatin TRP channel, TRPM8, was shown to be upregulated in esophageal cancer cells compared to adjacent normal tissue. This finding suggests that the TRPM8 channel plays a crucial pro-tumor role in the pathogenesis of esophageal cancer and, thus, could be a therapeutic target [56]. TRPV1 channel expression was also shown to be upregulated in ESCC cells and TRPV1 channel overactivation promoted by recurrent stimulation with heat or capsaicin enhances cellular proliferation and migration of ESCC cells [57]. Similarly, the TRPV2 channel is overexpressed in ESCC cells and TRPV2 channel silencing suppresses ESCC cell proliferation and cell cycle progression, induces cell apoptosis, and is also associated with poor prognosis and low 5-year overall survival [58]. TRPV6 channel expression is significantly downregulated in human ESCC compared to adjacent nontumor tissues and this downregulation was correlated with advanced cancer stage and low survival rate [59]. The human TRPV4 channel has 871 amino acids with intracellular N- and C-termini and six transmembrane spanning (S1–S6) α-helices (Figure 1). S5, S6, and the interconnecting loop form the central cation-permeable pore [14,60]. The TRPV4 channel was initially reported to be an osmo- or mechano-sensor [61,62] that can be activated by moderate temperatures (>27 °C) [63] and UV light [64], as well as several endogenous and exogenous substances (Table 2). The TRPV4 channel is a non-selective cation channel that is widely expressed in many tissues throughout the body, where it plays important roles in several physiological functions [65,66,67]. In the esophagus, TRPV4 channel is expressed in the basal and intermediate layers of the esophageal epithelium [12,68]. Agents that tweak TRPV4 channel activity could be promising therapeutics for the treatment of many disease conditions including congestive heart failure, respiratory and gastrointestinal disorders, osteoarthritis, and pain [69]. For instance, due to the proposed damaging role of TRPV4 channel on the alveolar-capillary barrier and in the development of lung edema, inhibitors of TRPV4 channel activity could be used to protect or restore the damage to this barrier in patients with various respiratory diseases, including COVID-19 [70,71]. Research geared toward discovering TRPV4 channel modulators for therapeutic use began around ten years ago and has evolved significantly in the last few years. The TRPV4 channel has, indeed, proven to be a greatly druggable target. At least nine novel chemotypes have potential as templates for potent TRPV4 channel agonists or antagonists that have oral bioavailability and other drug-like properties. At least two TRPV4 channel antagonists have demonstrated sufficient properties and preclinical safety profiles to be recommended as drug candidates. To date, GSK2798745 is the only potent and selective TRPV4 channel inhibitor that has been investigated in four separate early phase clinical trials: a Phase 1 study to assess effects on alveolar-septal barrier permeability following LPS challenge in healthy subjects; a Phase 2a study in participants with chronic cough; a first-in-human trial in healthy participants and stable heart failure patients; and a Phase 2a trial in congestive heart failure patients. GSK2798745 was found to be safe and well-tolerated, and to exhibit some positive efficacy trends in patients with heart failure [72]. Meanwhile, the progress in developing TRPV4 channel agonists as medicines has lagged behind that for antagonists due to the toxicity caused by systemic activation of TRPV4 channel [69]. In this review, we summarize recent research progress about the functional expression of TRPV4 channel in esophageal epithelium, with a special focus on its possible role in different esophageal diseases and the potential of targeting this channel for the development of therapeutic approaches for these conditions. 3. TRPV4 in Mechanosensation In addition to its role in providing a conduit for food from the pharynx to the stomach, the esophagus can function as a sensory organ due to its dual innervation by primary afferents having vagal and spinal origins that terminate either in the muscularis externa or en route to the mucosa, where they branch into a delicate mesh of fine varicose fibers [88]. Some mucosal afferents have intraepithelial extensions that place them in close proximity to esophageal luminal contents and may impart mechano-, thermo-, or chemosensory functions [22,89,90]. Chemical, mechanical, thermal, and noxious stimuli acting on the esophageal wall are transduced to action potentials, either directly or indirectly, by a multitude of receptors expressed on esophageal sensory nerves [88] or non-neuronal cells, such as esophageal keratinocytes [12]. These action potentials are then transmitted to the central nervous system via the spinal and vagal afferents. The most prominent terminal structures of vagal afferent fibers in the esophageal muscle coat are termed intraganglionic laminar endings (IGLEs) [91]. The polymodal vagal afferents mainly carry mechano-, chemo-, and thermosensations [88], but several studies were unable to identify the exact molecular mechanosensor that is expressed by the vagal afferents and confers these activities. Nevertheless, some of these studies did reveal that vagal afferents in rat and mouse esophagi express the ionotropic purinergic receptors P2X2 and P2X3 [92,93]. In recent years, adenosine triphosphate (ATP) has become widely recognized as a rapid synaptic transmitter in both peripheral and central divisions of the nervous system [94]. Several subsequent studies showed that many non-neuronal cells, including different epithelial cells, can release ATP in response to multiple stimuli including subjecting cell membranes to stretch [95,96]. In P2X3 knockout mice, mechanical distension induced ATP release from the esophagus, which was similar to that seen in wild-type (WT) mice, whereas activation of vagal afferents was reduced relative to WT mice [97]. Meanwhile, a P2X3 agonist was shown to stimulate mechanosensitive vagal afferents in mouse esophagus [98], suggesting that ATP release induced by mechanical stimuli and its action on P2X3 receptors plays an important role in esophageal mechanosensation. Considering the ability of skin keratinocytes to release ATP upon stimulation [99], we proposed that esophageal keratinocytes might have a similar capacity to release ATP in response to various stimuli (including stretch). The released ATP can, in turn, stimulate P2X2 and P2X3-expressing esophageal vagal afferents, which provides important clues about the missing pieces in the puzzle of molecular mechanotransduction in the esophagus. We explored whether the TRPV4 channel functions as a mechanosensor in the esophagus. We found that TRPV4 mRNA and proteins are expressed in esophageal keratinocytes harvested from WT mice. Using a patch-clamp technique, we showed that several known TRPV4 channel activators, including heat and the agonist GSK1016790A, evoked TRPV4-like currents in cultured esophageal keratinocytes from WT, but not Trpv4 knockout (TRPV4-KO) mice. Moreover, these activators, as well as stretch, increased cytosolic Ca2+ concentrations in the cultured keratinocytes. Heat and the TRPV4 channel agonist GSK1016790A also significantly increased ATP release from cultured WT esophageal keratinocytes, but not from TRPV4-KO cells. The ability of esophageal keratinocytes to pack ATP into vesicles in preparation for release was supported by the finding that these cells express the newly identified vesicle ATP transporter, vesicular nucleotide transporter (VNUT), at both the mRNA and protein levels. Thus, our findings clearly support the hypothesis that TRPV4 channel mediates Ca2+-dependent exocytotic ATP release in response to mechanical, thermal and chemical stimuli. The released ATP, in turn, activates P2X-expressing vagal (IGLEs and mucosal) afferents [12]. This esophageal keratinocyte-vagal afferent crosstalk with TRPV4 channel acting as a possible epithelial mechanosensitive molecule could be a vital component of esophageal mechanotransduction (Figure 2). This observation was supported by our subsequent findings showing morphological and functional expression of TRPV4 channel in murine and rat gastric epithelia. In this recent study, TRPV4-expressing gastric epithelial cells responded to various TRPV4 channel stimulants through Ca2+-dependent ATP release that could contribute to gastric emptying, most likely by triggering a local reflex arc intrinsic to the stomach wall that involves ATP release mediated by P2X2 and P2X3-expressing putative gastric mechanosensing vagal afferent intraganglionic laminar endings located in close proximity to the epithelium [19]. 4. TRPV4 in Cell Proliferation and Migration Various luminal insults, such as gastric refluxate, could compromise esophageal epithelial integrity and possibly cause esophageal erosions and, in more severe cases, ulcerations. Calcium and heat are among many factors that affect epithelial wound healing [100,101]. As an ion transporter with high permeability to Ca2+ upon stimulation, TRPV4 channel attracted our attention as a candidate regulator of esophageal epithelial wound healing. We have shown that esophageal keratinocytes obtained from TRPV4-KO mice exhibit an augmented ability for in vitro wound healing involving both enhanced cell proliferation and migration that was slowed when the cells were transfected with TRPV4 cDNA. Moreover, mechanical stimuli in the form of cyclic tensile strain slowed wound healing to a greater degree in WT compared to TRPV4-KO esophageal keratinocytes. These results clearly demonstrate that deletion of TRPV4 enhances in vitro wound healing of cultured esophageal keratinocytes [26]. The ability of the TRPV4 channel to mediate Ca2+-dependent exocytotic release of ATP from cultured esophageal keratinocytes in response to mechanical, chemical, and thermal stimuli [12] raises the question of whether ATP, or one of its degradation products, plays a modulatory role in the observed repressive effect of TRPV4 channel on wound healing. Although exogenous ATP significantly slowed wound healing, the inability of apyrase (an ATP hydrolase) to affect gap closure or abolish the inhibitory effect of exogenous ATP ruled out a direct role for ATP in modulating the in vitro wound healing process, and suggests that ATP metabolites (e.g., ADP, AMP, and adenosine) are candidate modulators of wound healing [26]. Most extracellular adenosine is derived from the release and metabolism of adenine nucleotides, such as ATP, following diverse stimuli [102]. Ectonucleotidases are extracellular enzymes that metabolize released ATP to yield different products such as adenosine [103,104], which in turn acts on G-protein-coupled adenosine receptors to control several physiological processes, including cell proliferation [105]. Therefore, we hypothesized that the ATP metabolite adenosine could be a candidate molecule involved in modulating in vitro wound healing of esophageal keratinocytes. The observed ability of exogenous adenosine to delay wound healing further supports this possibility. This effect was shown to be mediated by the highly expressed A2B adenosine receptor in esophageal mucosa and blocked by a selective A2B adenosine receptor antagonist [26] (Figure 2). Acid can also inhibit the acid-sensitive TRPV4 channel expressed by murine esophageal epithelial cells [68]. Collectively, the aforementioned findings suggest that protons in gastric refluxate could enhance wound healing through a TRPV4-suppressing effect and possibly act as a natural protective mechanism to withstand acid-induced injury. 5. TRPV4 in Esophageal Inflammation and Tumors Gastroesophageal reflux disease (GERD) is a multi-factorial chronic disease that may involve esophageal inflammation associated with hypersensitivity to mechanical or heat stimuli as well as acids, and can be attributed to altered expression of different ion channels in the esophageal wall [3]. Based on the presence or absence of mucosal damage, GERD patients can be classified as having either erosive esophagitis (EE) or nonerosive reflux disorder (NERD) [106]. For instance, inflammation-mediated overexpression of the mucosal TRPV1 channel is thought to play a role in NERD and GERD [11,48]. Although there is no direct evidence of TRPV4 channel overexpression in the esophageal mucosa of NERD and GERD patients, Suzuki et al. showed that esophageal keratinocytes express PAR2 and TRPV4 mRNA and protein. They also showed PAR2 activation following exposure to trypsin upregulated TRPV4 channel function via the protein kinase C-mediated phosphorylation of TRPV4 serine residues. This TRPV4 channel phosphorylation increased ATP release in mouse esophageal keratinocytes [107]. The effects on esophageal vagal afferents conferred by enhanced ATP release could be responsible for the commonly observed mechanical hyperalgesia in NERD and GERD patients [108]. Thus, inhibition of TRPV4 channel by different antagonists (Table 2) could be a potential novel therapeutic strategy for symptomatic treatment of these conditions. Eosinophilic esophagitis (EoE) is another chronic inflammatory disease that affects the esophageal mucosa and can be induced by food antigens [109]. Although recent studies reported that altered expression of at least two different ion transporters, anoctamin 1 (ANO1) and sodium-hydrogen exchanger member 3 (NHE3), could contribute to EoE pathogenesis [3], none of the mucosal TRP channels are thought to play a role in the condition and, thus, further investigation is needed to explore their possible role in EoE. In Barrett’s esophagus, normal esophageal squamous epithelium is replaced by intestinal columnar cells [110]. This condition is an adaptation to the altered environment imposed by long-term GERD [110]. A change in the expression or function of different ion transporters has a significant role in the development of Barrett’s esophagus [3]. However, whether there is a clear role for esophageal epithelial TRPV4 channel in this pre-malignant metaplasia is unclear. Like several other molecules, altered expression of the TRPV4 channel was observed to be closely related to tumor formation and metastasis. The TRPV4 channel was shown to be overexpressed in colorectal, lung, and gastric cancer cells relative to the respective healthy cells, but in prostate, skin, and esophageal cancer cells, TRPV4 channel expression was lower relative to healthy cells [111]. The overactivation of the TRPV4 channel associated with its overexpression in some tumors results in higher intracellular calcium, which, in turn, regulates downstream signaling pathways to affect the different tumorigenesis processes. Downregulation of the TRPV4 channel observed in other tumors might be ascribed to differences in the tumor microenvironment, which could affect tumor activity via alternate pathways. For instance, lack of expression of a given gene during cell maturation can inhibit differentiation processes, which are primarily responsible for tumorigenesis. The TRPV4 channel is highly expressed in healthy or inflamed epidermal epithelium that is similar to esophageal epithelium on a histological level, but is lower, or even absent, in precancerous lesions and non-melanoma skin cancers. The growth and differentiation of skin keratinocytes are affected by intracellular and extracellular Ca2+ concentrations. When extracellular Ca2+ concentrations are low, primary keratinocytes remain undifferentiated. In the presence of high Ca2+ concentrations, cell proliferation is suppressed and differentiation is, thus, facilitated [112]. In human skin keratinocytes, activation of the TRPV4 channel inhibits cell proliferation, induces apoptosis, and stimulates the release of IL8, which, in turn, downregulates TRPV4 channel expression [113,114]. Hypothetically, low expression of the TRPV4 channel in esophageal cancer cells decreases the release of ATP and, hence, reduces formation of adenosine. Low concentrations of intercellular adenosine, sensed by autocrine and paracrine communication between keratinocytes, will induce cell proliferation and migration [26]. In summary, the TRPV4 channel plays an important role in cell proliferation and differentiation that further affects cancer progression. These findings raise the possibility that pharmacological inhibition of the TRPV4 channel or a combination of TRPV4 channel antagonists (Table 1) with other chemotherapeutic agents might provide alternate treatment options for patients with esophageal cancer that have not responded to standard treatment. Thus, the potential of TRPV4 channel modulators warrants further investigation to explore a possible role for this channel in the diagnosis, treatment, and prognosis of esophageal tumors. 6. Conclusions The TRPV4 channel is functionally expressed in esophageal epithelial cells, where it mediates Ca2+-dependent ATP release. The released ATP is directly involved in mechanotransduction and indirectly, via its metabolite adenosine, in regulation of esophageal cell proliferation and migration. These findings suggest that inhibition of TRPV4 channel might promote healing of esophageal erosions and ulcers, and provide treatment options for patients with mechanical hyperalgesia. Further studies are needed to explore the exact role of the TRPV4 channel and its downstream pathways in esophageal barrier integrity, submucosal gland secretion, NERD, GERD, Barrett’s esophagus, and esophageal tumors, since targeting this channel using currently available agonists and antagonists could provide promising therapeutic options for these conditions. Author Contributions Conceptualization, A.B. and M.T.; writing—original draft preparation, A.B.; writing—review and editing, A.B. and M.T.; visualization, A.B.; supervision, A.B.; funding acquisition, M.T. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by a Grant-in-Aid for Scientific Research (21H02667) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) to M.T. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Transient receptor potential vanilloid 4 (TRPV4) channel structure. S1-S6 are six membrane-spanning helices. Figure 2 Functional expression of transient receptor potential vanilloid 4 (TRPV4) channel in esophageal keratinocytes and its possible role in mechanosensation and wound healing via Ca2+-dependent exocytotic ATP release. Adn = Adenosine, ATP = adenosine triphosphate, P2X2/P2X3 = subtypes of purinergic receptors, PAR2 = protease-activated receptor 2, VNUT = vesicular nucleotide transporter. ijms-23-04550-t001_Table 1 Table 1 Expression of different TRP channels in the esophageal wall. TRP Channel Localization Functional Role Species Reference TRPA1 Vagal sensory neurons and afferent nerves Mediate long-lasting mechanical hypersensitivity Guinea pig [35,36,37] TRPM8 Jugular vagal C fibers Esophageal sensation and nociception Cold sensation Guinea pig Human [39,40] TRPV1 Sensory neurons and afferent nerve fibers Mediates capsaicin-induced heartburn and esophageal sensitivity Guinea pig, Human, Mouse, Rat [13,41] Esophageal keratinocytes Mediates IL8 production and induces intracellular production of reactive oxygen species Human, Mouse [42,43] TRPV2 Nitrergic myenteric neurons Possible modulation of esophageal motility via myenteric co-innervation of vagal efferent fibers Mouse [21,44] TRPV4 Esophageal keratinocytes Mediates mechanosensation via ATP release Delays in vitro wound healing by contributing to increases in levels of adenosine, derived from TRPV4-mediated ATP release Mouse [12,45] TRPV6 Esophageal keratinocytes Putative role in mediating cell survival and programmed cell death Human, Mouse [46] NERD: nonerosive reflux disease; EE: erosive esophagitis. ijms-23-04550-t002_Table 2 Table 2 Transient receptor potential vanilloid 4 (TRPV4) channel agonists and antagonists. Name Selectivity In Vivo/Route/Species Reference Agonist GSK1016790A Non-selective +(IV, SC) mice [45,73] 4αPDD Non- selective In vivo [45] 4αLPDD Non- selective [45] 4αPD Non- selective [74] Phorbol 12 myristate 13-acetate Non-selective [45] 5,6-epoxyeicosatrienoic acids (5,6-EET) Non-selective [75,76,77] Dimethylallyl pyrophosphate (DMAPP) Non-selective +(intraplantar) mice [78] Bisandrographolide A (BAA) Non-selective [74] N-arachidonoyl taurine Non-selective [79] Apigenin No evidence [80] Cannabidivarin, Tetrahydrocannabidivarin Non-selective [45] RN-1747 Non-selective [81] Antagonist HC-067047 Selective +(SC) mice [82,83] Citral Selective [82] RN-1734 Selective [82] GSK205 Selective +(topical) mice [82,84] GSK2193874 Non-selective +(IV, IP) mice and rats [82,85] Ruthenium red (RR) Non-selective [45,86,87] Butamben Non-selective [82] Capsazepine Non-selective TRPV [82] Gd3+ Non-selective TRPV [87] La3+ Non-selective TRPV [87] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093333 sensors-22-03333 Article An Intelligent Traffic Surveillance System Using Integrated Wireless Sensor Network and Improved Phase Timing Optimization https://orcid.org/0000-0003-2757-4138 Naveed Quadri Noorulhasan 1* https://orcid.org/0000-0002-6427-7768 Alqahtani Hamed 1 https://orcid.org/0000-0003-0944-7856 Khan Riaz Ullah 2* Almakdi Sultan 3 Alshehri Mohammed 3* https://orcid.org/0000-0002-0450-8157 Abdul Rasheed Mohammed Aref 4 Artusi Alessandro Academic Editor 1 College of Computer Science, King Khalid University, Abha 61413, Saudi Arabia; hsqahtani@kku.edu.sa 2 Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, China 3 Department of Computer Science, College of Computer Science and Information System, Najran University, Najran 55461, Saudi Arabia; saalmakdi@nu.edu.sa 4 Department of MIS, College of Commerce & Business Administration, Dhofar University, Salalah 211, Oman; mohammed_aref@du.edu.om * Correspondence: qnaveed@kku.edu.sa (Q.N.N.); rerukhan@gmail.com (R.U.K.); msalshehry@nu.edu.sa (M.A.) 27 4 2022 5 2022 22 9 333306 3 2022 05 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 transportation industry is crucial to the realization of a smart city. However, the current growth in vehicle numbers is not being matched by an increase in road capacity. Congestion may boost the number of accidents, harm economic growth, and result in higher gas emissions. Currently, traffic congestion is seen as a severe threat to urban life. Suffering as a result of increased car traffic, insufficient infrastructure, and inefficient traffic management has exceeded the tolerance limit. Since route decisions are typically made in a short amount of time, the visualization of the data must be presented in a highly conceivable way. Also, the data generated by the transportation system face difficulties in processing and sometimes lack effective usage in certain fields. Hence, to overcome the challenges in computer vision, a novel computer vision-based traffic management system is proposed by integrating a wireless sensor network (WSN) and visual analytics framework. This research aimed to analyze average message delivery, average latency, average access, average energy consumption, and network performance. Wireless sensors are used in the study to collect road metrics, quantify them, and then rank them for entry. For optimization of the traffic data, improved phase timing optimization (IPTO) was used. The whole experimentation was carried out in a virtual environment. It was observed from the experimental results that the proposed approach outperformed other existing approaches. wireless sensor network (WSN) visual analytics improved phase timing optimization (IPTO) traffic management system computer vision Deanship of Scientific Research at Najran UniversityNU/RC/SERC/11/8 Deanship of Scientific Research at King Khalid UniversityRGP. 2/61/43 The authors are thankful to the Deanship of Scientific Research at Najran University for funding this work under the Research Collaboration Funding program grant code (NU/RC/SERC/11/8). The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding & support for this work under Research grant award number RGP. 2/61/43. ==== Body pmc1. Introduction Due to a variety of issues such as lighting fluctuations, camera calibration, and daytime settings, computer vision-based traffic vehicle monitoring remains a challenging aspect of any traffic surveillance system. As a result, performance needs are no longer left in research lab prototypes but are instead subjected to real-world difficulties. This desire renders the process of developing such a system extremely difficult, particularly when precision and speed are needed. Over the last decade, a lot of effort has gone into developing traffic surveillance systems which are designed to improve security by examining the on-road environments. In addition, a variety of sensing modalities, such as radar, lidar, and cameras, are becoming accessible for traffic monitoring. Simultaneously, computational power has risen considerably. Compared with wired configurations, wireless communication may save a lot of infrastructural development work, lessen the impact on existing traffic operation systems, and simplify maintenance tasks. New developing technologies not only make wireless networks more dependable but also make them more economical. The power, memory, and computing capabilities of WSN nodes are constrained. When it comes to battery power, sensor nodes in WSNs have to rely on limited and insufficient resources. One of the most important elements affecting the characteristics of a transceiver’s power consumption is the kind of antenna used. When the communication range is greater, more power is needed to send the messages. One of the primary research topics in WSN is the creation of a low-power communication system with an efficient antenna. Previously, WSN nodes have communicated by transmitting data in all areas using omni-directional antennas [1]. The broadcasting qualities of the omni-directional antenna restrict both bandwidth utilization and medium usage efficiency due to different variables such as “lower throughput”, “poor spatial reuse”, and “collision”. The use of directional antennas is recommended as a way to overcome the limitations of omni-directional antennas. In WSNs, directional antennas offer various benefits, including increased network capacity, greater transmission range, better spatial reuse, and reduced interference [2]. Directional antennas increase WSN performance by minimizing congestion and improving communication throughput range. Nevertheless, the performance of conventional systems is heavily reliant on their traffic object detectors, and it is worth noting that a traffic monitoring technique is becoming more trustworthy if the detector is sturdy [3]. Visual streams are used to depict facts in data visualization, translating diverse forms of data to suitable visualizations so that information analysis may be accomplished quickly. The benefit of data visualization is that it combines automation with human intelligence by incorporating human talents into an interactive visualization platform. The two key topics of data visualization are academic visualization and data visualization. Academic visualization depicts the spatial structures and evolvement of physiochemical attributes. The display of conceptual, unorganized, and high-dimensional data, such as corporate data, social media information, and textual information, is the subject of data visualization. Much effort has gone into establishing cost-effective and reliable traffic monitoring systems on a global scale. To increase traffic choices, one common method is to use computer vision to capture and evaluate relevant photos from existing urban video surveillance. Camera-based solutions such as this have modest infrastructural requirements and give vast aerial coverage, enabling traffic monitoring at multiple locations. The computerized system covers more ground than traditional traffic monitoring that relies on fixed-point sensors. Image processing methods are broadly utilized in a diversity of areas, such as aviation, healthcare, traffic control, and environmental object assessment [4]. The study of analytical reasoning helped by communicative visual interfaces is known as visual analytics, and it concentrates on producing human-computer practices and approaches for data processing, knowledge development, and problem resolution. It is an applied investigation subject which tries to provide practical solutions for a variety of application areas, including transportation. The best results are obtained when visual analytics investigators, who often lack subject experience, collaborate closely with domain experts. Unfortunately, although visual analytics investigators have performed extensively with transportation-related information and established a range of methodologies and instruments, which could be beneficial to transportation domain practitioners and researchers, such work has been restricted in the transportation field. Inadequate communication has two negative implications. Visual analytics investigators have a restricted awareness of the transportation domain’s challenges, needs, and constraints, which shall limit the utility and usability of the approaches they develop. The transportation community, on the other hand, is mostly unaware of the benefits that visual analytics may provide [5]. In terms of price, simplicity of installation and management, and better measurement capabilities, wireless magnetic sensor networks are an appropriate option for induction circuits for traffic control on motorways and at crossings. Wireless detection does have the ability to change the way traffic information is acquired by offering great geographic volume and precision observations. Inductive loop sensors, micro-loop probes, pneumatic road tubing, piezoelectric wires, and other weigh-in-motion monitors are used in many traditional traffic monitoring systems. These were selected due to their higher traffic detecting efficiency. To get the most out of these ITS solutions, large-scale implementation of traffic regulations on all major motorways and minor streets is required. As a result, real-time traffic data are necessary at these locations. Even though computer vision and visual analytics is a well-developed field of information technology, its identification, categorization, and tracking capabilities are not frequently used in daily life. As a result, we currently lack an automatic traffic control system for city roadways that can respond to changes in urban traffic in an automated manner [6]. 1.1. Problem Statement Many traffic visualization systems have been developed, but they are difficult to adapt for real-time traffic observation, assessment, and control in urban areas. The Social Internet of Vehicles (SIoV), which includes smart vehicles and networking units, is the primary operating premise of the Internet of Vehicle (IoV) platform. The majority of critical infrastructure is built-in, whereas others (mostly user-oriented and peripheral) could be inserted into the onboard diagnostics (OBD) connection being used as needed. For the smart city infrastructure’s proper functionality, constant and real-time communication is needed. Within the IoV infrastructures, there must be five different sorts of connections that must be made: “vehicle-to-infrastructure (V2I)”, “vehicle-to-vehicle (V2V)”, “vehicle-to-roadside unit (V2R)”, “vehicle-to-human (V2H)”, and “vehicle-to-sensors (V2S)”. No current visual methodologies give real-time traffic projections, which is critical for numerous activities including traffic signal modification and radio traffic broadcasts. Hence, in this article, a computer vision-dependent traffic management methodology using an integrated wireless sensor network and visual analytics framework with improved phase timing optimization is proposed. The remaining sections of the paper are organized as follows: Section 2 emphasizes the literature evaluation. Section 3 describes the suggested methodology. Section 4 describes the performance and analysis of the proposed model. Section 5 demonstrates challenges and future directions in the field of IoV systems. Finally, Section 6 concludes the paper and demonstrates the idea of this research. 1.2. Key Points Proposed Methodology: We have proposed an integrated wireless sensor network with a visual analytics framework and have employed improved phase timing optimization for a smart traffic management system. It was observed from the results that our model performed effectively in terms of accuracy and model fitting towards statistical data. The algorithmic structure of IPTO and the detailed proposed framework is given in Section 3. Knowledge of challenges and future directions: this work highlights the current challenges in traffic management systems (e.g., security and privacy, reliability, interoperability, real-time communication, multi-model sensing, or heterogeneity) and also discusses the future directions for smart IoV environments. We demonstrate how artificial intelligence and blockchain-based solutions can contribute to building smart infrastructures and scientists should work on these emerging technologies. 2. Related Works Wang et al. [7] proposed a realistic strategy for actual-time traffic maintenance offloading in fog-dependent Internet of Vehicles (IoV) systems, intending to reduce the mean reaction time for incidents provided by vehicles. By partitioning the offloading optimization problem into two sub-problems and scheduling traffic flows amid distinct fog nodes, an approximation solution is devised to solve it. They will look into using automobiles outside of the communication ranges of “road side units (RSUs)” as fog nodes to offload loads for TMS in the future. As a result of this, it is tasked with processing all of the system’s communications, which might lead to excessive resource usage. Yuan et al. [8] conducted a comprehensive review of 259 publications released in the last decades, as well as relevant performances before 2010, to better identify prospective research subjects and learn how to use relevant visual analytics approaches. They created taxonomy with three first-level classifications: methods before model construction, methods during model construction, and methods after model construction. Each class is further defined by a series of relevant analysis tasks, each of which is typified by a collection of current gained works. They also addressed and highlighted research problems as well as interesting future research prospects relevant to visual analytics. Sumi and Ranga [9] suggested a smart traffic management approach for nations based on the IoT and the vehicular ad hoc network principles (VANET). Emergency vehicles are prioritized in the proposed approach for a smooth flow through traffic depending on the kind of occurrence. It directs ambulances to the smallest probable routes to their destination, and it also offers a way to identify and react to traffic signal hacking. In terms of congestion avoidance, travel duration, and energy consumption, our solution exceeds these suggestions for emergency vehicle systems. Ning et al. [10] proposed a realistic strategy for minimizing traffic management services response time by permitting real-time content distribution in IoV systems depending on diverse network access. For large-scale IoV systems, they initially create a crowd sensing-dependent framework. Furthermore, to provide timely replies for traffic control, a cluster-based optimization framework is explored. They assume that the messages generated by vehicles are trustworthy. This may not always be the case, however, due to the possibility of false or inaccurate information being broadcast across the network to mislead other vehicles and traffic control systems. Tsang et al. [11] developed a completely integrated method for traffic monitoring by combining high-definition intelligent cameras with wireless connectivity. This system will be known as a “computer vision-based roadside occupation surveillance system (CVROSS)”. Actual-time roadside traffic photos, such as photographs of loading and unloading operations, are acquired autonomously using a vision-based system. Decision assistance on roadside availability and vacancies could be analyzed using fuzzy logic and monitored for customers using the recorded information, improving the openness of roadside operations. To improve the visibility of roadside actions, further steps can be taken to examine, improve, and apply the CVROSS. CVROSS decreased traffic congestion and double-parking incidents by 41.2 percent and 33 percent, respectively. This technique cannot be used in other areas where there is double parking and busy roadside activities. A systematic framework for constructing a network-level traffic congestion analytical tool that is ideal for traffic control and practical traffic management on roadways was offered by Gunda [12]. Detection of traffic spots, network congestion charts, input data quality analysis, traffic variation, and congestion performance evaluation are all key components. In addition, a novel pattern matching method was created to fill in the gaps in the data. This system, however, did not have a message scheduling mechanism to help with data transfer issues. Lee et al. [13] introduced an interactive visual analytics system that uses vehicle detection information to support traffic congestion investigation, monitoring, and predictions. This visual analytics technology is made to permit customers to investigate the origins, routes, and intensity of traffic congestion. The congested circumstances of a town are depicted utilizing a volume-speed rivers visualization, which shows traffic levels and velocities at the same time. However, they found no evidence of enhanced performance as a consequence of the data in the experiments. Riveiro et al. [14] proposed a visual analytics framework that supports: (1) multidimensional road traffic information analysis; (2) examination of normal behavioral models generated from information; (3) abnormal activity identification; and (4) abnormal incident explanations. The experts also identified several issues that need to be addressed, including the need to improve the assessment of observed abnormalities, as determining why the identified incidents are abnormal remains a challenge, and the limitations of the circular layout when a large number of attributes are chosen. To solve the current restrictions, Nguyen et al. [15] suggested an extensible smart traffic management platform (STMP) centered on untrained deep learning methods. The STMP combines diverse big data streams, such as IoT, sensor systems, and social networks, to identify concept deflections, differentiate among recurring and non-recurring traffic occurrences, and perform brunt spreading, traffic flow predicting, and enhanced traffic regulation judgments. However, anticipating traffic flow with extreme changes that occur at a greater frequency has difficulties. When more traffic data (e.g., roadworks, accidents, and events) is utilized to train the DNN model, this issue should be addressed. Information from multiple sources, such as surveillance cameras, meteorological data, and other transportation-related data sets, will be fused in future research initiatives. Furthermore, to obtain platform adoption, the interpretability of artificial intelligence (AI) components, particularly those based on sophisticated approaches such as deep neural networks, should be investigated in the future. Adu [16] suggested a novel architecture for carrying out multidimensional visualization and analytics on huge transportation information in a consistent way. The system stores information in a highly parallel dataset and uses the enormous computational capacity of “graphical processing units (GPUs)” to do real-time data analytics and renderings using a structured query language that interfaces with the underlying GPU databases. A front-end is meant to present query results on simplistic graphs and maps in near-real-time, allowing decision-makers to swiftly drill down into information. The technology is used to create apps that analyze large transportation databases with over 100 million rows. The technique created is capable of providing real-time visual upgrades for large datasets in less than 100 milliseconds, according to performance benchmarking trials. The proposed platform’s efficiency was also contrasted to CPU-based visual analytics tools such as Tableau and D3. As the paper also says, the created framework’s query response rates were around 10 times quicker than those of the two CPU platforms. This framework’s inability to handle non-structured data is a major flaw. It is assumed that the data are in tabular format and that data types such as video and images are not present. A visual analytic system connected to the analysis of motion and transportation networks was reported by Lock et al. [17]. This system analyses the possible added value of fast, 2D, and 3D online visualization and data analytics modules in the study of large public transportation performance information. An innovative technique to showing such information is illustrated using a generalized framework visualization system. In a quick, interactive browser-based ecosystem, this system remembers almost a year’s benefit of public transportation reliability information to a great detailed degree. There may still be issues with the data itself when dealing with a large amount of data. As a result, real-time data may not always be accurate due to network and GPS problems. As a result of these concerns, operators might use “general transit feed specification (GTFS-RT) validation tools.” If GTFS-RT is widely used to monitor systems on a continuous rather than real-time basis, it will be easier to exchange knowledge and improve the tools for creating and validating data feeds. De Souza, et al. [18] discussed traffic management system categorization, evaluation, difficulties, and prospects. A qualitative investigation was also conducted using the traffic management systems (TMS) mentioned. Lastly, they explained how they plan to enhance TMS efficacy and resilience to accomplish the desired level of precision and traffic monitoring, with significance on concentrating open complexities. Moreover, they have detected and discovered numerous feasible solutions. In addition to cloud computing’s inherent security issues, TMS also adds to the difficulty of securing a system. Zhang, et al. [19] suggested a crowdsourcing-dependent traffic surveillance strategy, which allows transportation management to obtain road traffic information at road crossings in a time-saving, reliable, and confidential way. This approach’s main drawback is its inability to present huge datasets. They will use blockchain technology to assess the legitimacy of a crowdsourcing-based traffic surveillance situation in the future. Rego et al. [20] suggested a newer control scheme depending upon the combination of “software defined networks (SDN)” and “Internet of Things (IoT)” in the nation’s surroundings. This system is activated when an emergency occurs and changes the regular and urgent traffic routes in urban areas to minimize the time it takes for emergency resources to arrive at the scene of an emergency. Studies reveal that the average time it takes emergency responders to arrive at an emergency site is decreased from 17 to 12 milliseconds. The proposed algorithm controls the resource requests and the route modification for helping the emergency service vehicle’s movement. This system’s inability to capture multidimensional perspectives of the data being shown is a major flaw. Hashemi, et al. [21] presented a new trafficking network in real-time based on an end-to-end deep learning (E2EDL) technology. The suggested framework includes the network’s spatial and temporal l congestion profile correlations and links them with effective traffic management techniques. The E2EDL model is trained with a lab-generated data set that includes pairs of current traffic characteristics and effective traffic control strategies planned to deal with them. As a result of the system’s recommendation of routes to the same spot, however, congestion is created in different parts of town. Ahmed, et al. [22] described a travel route suggestion procedure that can be used to suggest the best congestion-aware path in a network. Congestion indexes are calculated using both equipped and non-equipped automobiles, as well as driving distraction variables. This procedure is employed for designing smarter transportation systems to encounter traffic congestion issues. This system’s main drawback is that, in order to alleviate traffic congestion, it selects lengthy routes. Jain, et al. [23] suggested vehicle social networks based on the VIoT in this research are made up of a larger number of sensors that wirelessly transfer data. The efficacy of traditional layered protocol solutions and existing cross-layer solutions for wireless systems is limited by the great heterogeneity in equipment capacities of things and quality of service (QoS) necessities for diverse uses. The system’s flaw is that it lacks a broadcast suppression mechanism, which reduces its efficiency, particularly in high-density scenarios. Shelki, et al. [24] presented a framework for delivering adaptive traffic signal control and emergency service management in automobile ad-hoc networks by optimizing the acquisition, categorization, scheduling, and distribution of traffic data. The former provides for dynamic traffic signal regulation and traffic flow, and the latter permits emergency vehicles to pass at full speed. Sensor nodes in the proposed method analyze traffic data and share it with a “dynamic traffic management center (DTMC)”. It uses fuzzy logic to dynamically decide the road segment’s priority as critical, high, medium, or low. When enormous volumes of data are sent through networks, there is a larger risk of security vulnerabilities. 3. Proposed Work This section explains the flow of the proposed system. Currently, people have been processing various data to view, analyze, and transform the data to another form regularly. Automated vehicles, e-health care, population surveillance, and aerial surveying via satellite missions are just a few of the smart world’s applications. Visual analytics also offers several approaches for combining the advantages of humans and computers to digitize the globe. Visual analytics also provides a variety of graphical user interfaces, statistical reporting, interactive gadgets, and data management services to help the smart world develop. Furthermore, combining computer vision with visual analytics gives an amazing, cutting-edge solution for academics and engineers to share and assess inventions in the digitalized smart world, thereby contributing to a good environmental impact. Hence, in this paper, we have integrated wireless sensor network with visual analytics framework and have employed improved phase timing optimization for a smart traffic management system. The schematic representation of the proposed methodology is illustrated in Figure 1. 3.1. Data Acquisition The raw data are collected and passed to the data preprocessing module during data collecting. Data can be obtained in a different format and from a variety of sources. This component must assimilate the necessary data, which will be sent in a unified format to the other modules. The sensor nodes provide the traffic information. The datasets utilized in this study are from the California Department of Transportation’s Performance Measurement System (Caltrans). This system is made up of about 39,000 Vehicle Identification Stations, which analyze vehicle flow and velocity and are located throughout the state’s highway system in all major urban regions [25]. 3.2. Data Pre-Processing Parameters such as kinds of vehicles, vehicle parking space requirements, and minimal traffic lane widths must all be set up before the suggested system can be operated. The Hong Kong Special Administrative Region Planning Department has developed rules that relate to these. As a result, the system may contrast the collected photos to templates in the database, allowing for more precise image and data processing in the future. Variations in the size of everything produced by non-equivalent distance from the vision equipment are neglected in the computing machine to make it easier to calculate parking gaps and accessible parking areas. In another sense, irrespective of its orientation in association to the vision equipment, each of the things shown in a case is presumed to have the same measurements in millimeters or pixels. Initial variables in the calculating procedure involve:The vision device’s total coverage is 640 × 480 pixels. Each truck must have 11 m of the controlled parking area. Each cargo van requires 7 m of controlled parking areas. Each private car has a 5 m-controlled parking place. The minimum width of traffic lanes is 6.75 m. All conceivable vehicles and things are represented as templates. A trust value for every pixel for every template, indicating how confident the discrepancy is. The phase begins the first level of the timed loop, vision collection after the variables are supplied into the developed framework. The platform’s wireless vision sensors may then continuously and automatically capture photos from the roadway. Following that, the information is used for (i) noise minimization, (ii) vehicles and objects detection and matching, (iii) data filtering and refining, and (iv) data imputation and validation. 3.3. Noise Reduction Noise reduction is among the most critical phases in the overall network flow. This is a technique for reducing noise from an image, which can affect both the visual qualities and the efficiency of future processing operations. There are various objects and signals, such as traffic indicators and directions in traffic streams, on the roadside, and in traffic lanes in this scenario (according to the simulation). Nevertheless, since these are presumably not related to vehicle and object detection and comparing, they shall harm matching findings and the effectiveness of following parking space calculations. Moreover, even identical vehicles, such as two individual cars in this condition, shall be of a similar design but varying in color. Image quality may be assessed using the signal-to-noise ratio (SNR). An imaging system’s sensitivity is commonly measured in terms of the SNR. When the signal is an optical intensity, it is defined as the ratio of the average signal value μsig to the standard deviation of the signal σsig, or as the square of this value when the signal and noise are seen as amplitudes. (1) SNR=μsigσsig It may guarantee that irrelevant items, signs, and indications are deleted from images before they are subsequently processed. It also eliminates color classification issues. Before noise mitigation, the image created from vision acquisitions was loaded with obstructions such as a highway sign, a traffic cone, and yellow circle marks. It was tough to distinguish and identify cars and goods as a result of all of this. Noise minimization was attained utilizing an “image mask” to prevent unrelated areas of the images, “color plane extraction” to transform the color picture to a binary picture in only black and white, and “basic morphology” to enhance the structure of binary objects in the picture, and also to modify the illumination. Following noise minimization, the indicator, traffic cone, and yellow circle marks are eliminated and only the individual vehicle stayed on the display with its structure displayed in white. 3.4. Vehicle and Object Recognition and Matching The proposed system includes two typical matching methods: pattern matching and geometric matching. Pattern matching is the optimal solution if all of the things, which need to be identified and matched, have the same characteristics, as it compares every characteristic and color of an item from the templates and the observed images. All cars and items, meanwhile, are not created equal. Certain proprietors, for instance, may color a vehicle’s top or body. As a result, not every object has the same designs or colors. This could harm the detection and matching of vehicles and objects. As a consequence, geometric matching appears to be more appropriate for utilization in the proposed system to identify, detect, and compare various kinds of vehicles and objects depending on their forms, extents, and other important characteristics, and also to evaluate the image score values, when combined with noise. This can avoid an object from being misidentified and mismatched owing to different colors and patterns. When the image has been adequately collected and the noise has been removed, the procedure of identification and matching shall begin. Templates inserted throughout the system parameters set-up procedure are used since the cars and items must be recognized and matched. When an object is identified, a vehicle passes by, or a vehicle parks within the HD vision devices’ field of view, the devices will automatically record photos and contrast them to templates in the databases. Following identification, vehicles and objects could be allocated to a categorization. 3.5. Data Filtering and Refining The content in real-world data is repetitive. Data filtering and refinement is the method of removing duplicates, contradictory information, and noise from information while protecting integrity. This is necessary to have reliable modeling results. 3.6. Data Imputation and Validation Sensor failure can cause observations to be incorrect, ignored, or distorted. As a result, several preparatory tasks such as data imputation and data validation must be completed to effectively analyze the data. This process involves filling in incomplete data and assessing data performance and consistency. 3.7. Visualization Module We present an approach that unifies several ways to visually suggest efficient paths to automate the visualization process. Several cartographic generalization methods, such as feature extraction, simplifying, schematization, and deformation of map objects, as well as the utilization of symbolization and graphical parameters, are used in this framework. Visual analytics investigation is primarily focused on graphical and semantically complications, which lends itself to a more in-depth interaction of the cartography sector. To handle a large range of location dimensions, cartographers would have to invent several generalization approaches. Although cartographic generalization is far from fully known, let alone computerized, it is difficult to imagine a society more dedicated to the subject or one with greater factual expertise. By striving to tackle both geometrical and cognitive components of mapping difficulty, the cartographic strategy to generalization tends to differentiate itself among purely visual complexity strategies, such as the famous level-of-detail concept in graphic design. The following route visualization process is divided into two sections: firstly, cartographic generalization, and secondly, the utilization of symbolization and graphical parameters. These two components are developed to function together that can also be used separately. Depending on cognitive psychology investigation, both forms of visualizations incorporate a variety of operations. Significantly, certain operations aren’t applicable in all cases, while others will use a different approach based on the information. In the same way, certain operators are required for the visualization mechanism while others are discretionary. The architecture, such as the situations, may be dynamically enhanced by adding more visualization operations. The displacement of the length of road sections, such as alternate visualization methods developed as the portion of the model employing cartographic generalization, combines several ways depending on the context. The length of road sections is changed in the standard scenario depending on the perceived lengths of road sections. We handle other temporal aspects such as current traffic density as input for generalizing road segment length in the other traffic-related scenarios. The theory is that peoples’ perceptions of road length are influenced by the actual travel time required to complete the path [18]. 3.8. Length Distortion The premise that travelers evaluate road length based on actual travel time instead of the actual measurements of a road section motivated us to build an algorithm that dynamically alters the lengths of a particular line section. As said before, journey time is also a significant issue in spatial choice models. Figure 2 shows how, depending on traffic density, the perceived distance between two points along a path can differ from the actual metric distance. The perceived distance is not easily quantified in terms of metrics, unlike the metric distance between two places along a road section, since it is not a set score and changes based on individual variances in human perception of space and time. We utilized the PUSH software [19], which contains an expanded option to scale objects by a component, to deform the lengths of a line segment. PUSH is a software application that was created to dynamically generalize cartographic items and, in specific, eliminate spatial conflicts through dislocation. It provides for a very flexible description of object behavior during dislocation by specifying numerous characteristics, such as the permissible degree of distortion or the minimal space needed by an object. Each object’s attributes could be customized separately. To determine the enlarged factor autonomously, we firstly determine the expected perceived length (t) of a road segment using the equation:(2) plenght(t)=len(t).θdens(t)+(dens(t)−θdens(t)).wgθdens(t) The estimations are dependent on the present traffic density dens (t), calculated for every individual road section as contrasted to the mean traffic density θdens(t) for the road section during a similar period. We also present a weight factor wg, that permits to dynamically modify the intensity of the variation of the attained length value from the actual length value len (t), using (3) wg={0, 2} ∈ Q This weighting factor allows for individual variances in observed road length to be addressed, as well as for traffic control to intervene if the strength of aberrations needs to be physically increased or decreased. The enlarge factor is then computed as the ratio of the estimated observed length of the line segment to its actual length:(4) enlarge=plenght(t)len(t) Once the individual enlarges factors have been set to the line segments that need to be scaled, the global optimization finds a holistic solution that takes all of the other objects into consideration (i.e., relocating them suitably if necessary). The line segments of the generated polyline will be scaled based on the provided traffic volume estimates. That is, high-volume segments grow in size while low-density segments shrink in size. If the estimated traffic volume is equal to the mean volume for the road section at a given moment, the expand factor does not affect the segment’s depiction. Since the entire picture is optimized in one step, bigger scores for the aura specification for the matching line sections can be defined. This dislocation of map elements shall be extremely helpful in visually distinguishing between diverse pathways in a system. 3.9. Line Distortion According to the earlier study, visualizing a road section as a straight line is related to a very smooth motion in space [26], and therefore with a high traffic flow. Roads with lesser traffic flow (or high traffic volume) may, on the other hand, be related to a less stable way of a line that alters from a straight-line representation. While there are numerous widely used methods for reducing the complexity of a line, there are only a few approaches that aim to deform a line automatically [27]. In this section, we use a method that artificially deforms the shape of a provided line section utilizing traffic-associated information as an input for distortion. 3.10. Improved Phase Timing Optimization (IPTO) Algorithm To tackle the optimization problem, a genetic algorithm is used in this part. GAPTR stands for a genetic algorithm-based phase timing rescheduling technique. We encode the green time of four separate phases in GAPTR. The binary integer 0 or 1 represents each gene on the chromosome. Each chromosome reflects a unique attempt to time phase transitions. The fitness function is used to assess those who are at the top of their game. Better people are more restrained and have more opportunities than those who are less fortunate. The goal of GAPTR is to reduce the length of waiting for vehicles’ queues. As a result, in this paper, we use the goal function as the fitness value explicitly. We use traditional genetic methods for the choice, crossover, and mutation operators. For instance, in the selection process, a roulette-wheel technique is utilized, and in the crossover and mutation operations, multiple point crossover and mutation are used. 3.11. Algorithm for IPTO The crossover operation appears to swap gene segments in phases, but this is not required in practice. To perform the crossover procedure, we can use a random binary vector of the same length as the chromosomes. The value of a component in the vectors indicates which parent the gene for the offspring’s corresponding location came from. If the value in the present location of the vector is 1, for instance, the gene value in the corresponding point of the offspring originates from parent 1, and if not, parent 2. Mutation operations with random vectors could be performed similarly. The main distinction is that the value of the component in the vector indicates whether or not the gene in the offspring at the appropriate site propagates as shown in Algorithm 1 below. Algorithm 1: IPTO.   Input: sensor traffic data    Output: traffic management data    if this. Host is cluster head = TRUE then return    Send a message to cluster head (this. Messages)    end if    loc of roadside unit ← GETLOCOFNEARESTRSU    shortest Paths ← GETSHORTESTPATHSBASED Map    DelaysforPaths ← COMPUTEDELAYSFORPATHS    isUpBS ← GETISUPLOADBYBS    if isUpBS then return    UPLOADMESSAGESBYBS    end if    neighbors ← GETALLNEIGHBOURS    for i ← 0 To Length[neighbors] do    isMoving ← IS MOVING ON THE SHORTEST PATHS-S(neighbors[i].loc)    if isMoving == TRUE then    ncTurningPos ← COMPUTETURNINGPOS    ne TurningPos ← COMPUTEENTURNING POS    if this.cTurning Pos > threshold And    ncTurningPos > this.cTurning Pos Andneighbors[i].    estimated Delay < this.estimated Delay    then    SENDMESTONEIGHBOR    end if    if this.cTurning Pos < threshold then    if ncTurningPos−this.cTurning Pos > ϵ    then    SENDMESTONEIGHBOR    ElsencTurningPos−this.cTurningPos < ϵ    And neTurningPos > this.eTurningPos    SENDMESTONEIGHBOR    end if    end if    end if end for 4. Performance Analysis 4.1. Computational Environment Settings To test the system’s performance, we used a city map. OpenStreetMap [28] was used to create this map. The tool OS-M2WKT [29] is used to transform OpenStreetMap XML files to WKT format. These files, which are in text format, are used to store map-related information. The motion of cars is based on the shortest path map, and the average arrival rate of traffic flow on every route section is determined depending on the vehicle motion historical documents. The simulation lasts 168 h, and the vehicle’s wireless communication range is 40 m. The message size ranges from 200 to 500 megabytes, and the message Time-To-Live (TTL) is 30 min. A vehicle’s velocity is between 20 and 60 km per hour, and communication costs $0.007 per megabyte. To get the average score of every performance metric, we run each simulation scenario 100 times. The subsequent four performance indicators are looked as the following subsections. 4.2. Average Delivery Ratio The overall created messages are divided by the number of messages, which can be analyzed by TMS. To calculate the average delivery ratio, we must divide the total number of messages sent by a sender to a destination host in the system by the total number of messages that were received. The goal is to send as much information to its destination as possible. 4.3. Average Latency The mean time it takes for TMS to receive a message from the time it is created. That means that the period between when the sender begins transmitting the message and when the recipient accepts the message is referred to as average delivery delay. 4.4. Average Communication Cost The overall count of messages posted is divided by the total count of messages TMS has reacted to. 4.5. Access Ratio The proportion of roadside unit (RSU) uploaded messages to base-station (BS)-uploaded messages. The performance of the suggested system is contrasted with the traditional systems in terms of these metrics. Depending on the city map, Figure 3 shows the average delivery ratios of the four methods (CDRAM, GFAVR, vehicular TMS, and suggested). The suggested system outperforms GFAVR and vehicular TMS in terms of performance. Here, the proposed technique has a greater delivery proportion than that of the existing approaches. That means the proposed approach has a proportion of 0.912 more than the existing approaches CDRAM (0.90), GFAVR (0.78), vehicular TMS (0.88) in the first second of message creation time. In this work, we consider 5 s for message creation time. In the 5th second, the proposed technique reaches a proportion of 0.99 than that of the existing techniques [CDRAM (0.96), GFAVR (0.86), vehicular TMS (0.92)]. As depicted in Figure 4, the suggested approach offers a significant advantage over conventional methodologies of average delivery delay. Here, the proposed technique has little delay than that of the existing approaches. That means that the proposed approach has a 30 s delay than the existing approaches CDRAM (40 s), GFAVR (80 s), vehicular TMS (38 s) in the first second of message creation time. In the 5th second, the proposed technique reaches a 10 s delay than that of the existing techniques [CDRAM (18 s), GFAVR (56 s), vehicular TMS (17 s)]. As depicted in Figure 5, the suggested system’s average communication cost is significantly lower than that of the current approaches. Here, we consider 400 s for the message creation time. The proposed technique has a minimized communication cost than that of the existing approaches in overall 400 s of the message creation time. However, in 200–250 s, the proposed approach has very little average communication cost than that in 150–200, 250–300, 300–350, and 350–400 s. The quantity of energy utilized by the nodes in proportion to the simulation time is referred to as energy consumption. Figure 6 shows how the suggested approach uses less energy than existing techniques such as IOT-ULC, VDAC, and TCE. Since there are a large number of vehicles that circulate on city roadways, our system uses a substantial amount of energy in 80 percent of traffic density. However, owing to the high traffic congestion rate on the roads and reduced vehicle traffic, we find that energy consumption in the network is stable since the identification statuses of our sensors have not changed. We use two key indicators to indicate the network’s lifespan. The first is the time until the “first node dies (FND)”. Since a node dies during this time, the FND period is considered a period of network stability. The second is total network life, which is defined as the period when no more nodes are available to continue communicating; this duration is referred to as “network life (NL)”. The result shown in Figure 7 and Figure 8 relates to the network’s lifespan. We found that by deploying an efficient and effective network architecture that adjusts to changes in the density of current traffic on the roadways, our suggested system enhances the network’s lifespan, making it an intelligent and innovative system. Other current systems, on the other hand, employ basic and common methods that allow for the same unsatisfactory outcomes throughout the network’s lifespan. Figure 9 depicts the access ratio of the proposed approach vs. traditional methods, which reflects RSU and BS resource use. In terms of access ratio, the proposed solution is superior. Here, the proposed technique has a smaller access proportion than that of the existing approaches. That means the proposed approach has a proportion of 0.1 then the existing approaches CDRAM (0.2), GFAVR (5), and vehicular TMS (2) in 10 RSUs. In this work, we consider 50 RSUs. In 50th RSU, the proposed technique reaches a proportion of 0.5 than that of the existing techniques [CDRAM (3), GFAVR (10), Vehicular TMS (3.5)]. Finally, we prove the proposed approach is superior to the existing approaches. 5. Key Challenges and Future Directions 5.1. Challenges The Internet of Vehicles’ quick advancement is deteriorating numerous barriers in the development of smart cities and urban planning, but there are still numerous key challenges to overcome such as security, reliability, interoperability, real-time communication, multi-model sensing, and heterogeneity. Security and Privacy: Applying different techniques need to handle secure communications. Moreover, the wireless nature of wireless sensor transmission poses a great risk to cyber-attacks than fixed-line infrastructure. Interference allows for easy eavesdropping or denial of wireless transmission. This makes it a prime target for hackers, with the significant potential catastrophic harm. Furthermore, sensors can be used without the need for safeguards or observation. This raises the danger of attackers exploiting the mobile nodes and gaining access to sensitive data or credentials to launch an attack via remote access. Sensors can potentially keep confidential material on the privacy of their clients. Reliability: Data dependability is critical for urban transportation operation and assessment, however, due to its minimal exposure and restricted capability of sensing wisps, as well as the lossy nature of transmissions, it became difficult while employing WSN. As a result, any proposed WSN architecture and communication protocols should incorporate providing reliable edge connections. Interoperability: Traffic control is an inter-optimizing issue that necessitates the improvement of a variety of weighted parameters such as gas emissions, number of stops, and traffic noise levels, among others. This multiplicity of feasible solutions necessitates a multiplicity of sensing devices, which is one of WSN’s primary design goals. Real-time Communication: Various approaches involve real-time data collecting to make in-the-moment choices. A typical scenario is traffic signal control, in which variable crossroads planning is dependent on real-time traffic distribution. Multi-model Sensing or Heterogeneity: Due to the fast advancement of wireless technologies and many sensing devices, suggested systems must consider equipment diversity to assure compatibility and flexibility. 5.2. Future Directions Any Remote wireless sensor-based transportation management system must be able to tackle the aforementioned issues. WSN innovation presently meets certain standards, making it a popular contender for practical Intelligent Transport Systems (ITS) applications. The vulnerability of WSN and its subsystems should be considered while developing traffic control services depending on WSN. The communication systems, in particular, has to be secured enough to mitigate damage while also being dependable and fault—tolerance capable of providing services stability in the face of failure. WSN’s multisensory aspect is strong since it enables the improved traffic flow multi-objective dilemma to be fed with crucial data in real-time, allowing the optimal transportation planning decisions to be taken at the moment. Blockchain and Artificial Intelligence are emerging technologies and scientists are working closely to integrate these technologies in smart cities since blockchains is distributed technology with enhanced security and cost-effective technology [30,31] while artificial intelligence-based technology (e.g., machine learning, deep learning [32,33]) are intelligent technologies. These technologies should be explored in future research to improve the performance of IoV in terms of traffic management systems. 6. Conclusions Traffic congestion is a continuous issue across the world, posing both economic and social issues. Any city’s ability to compete depends on its ability to maintain smooth traffic conditions. Hence, we presented a novel computer vision-based traffic management system that incorporates a wireless sensor network and a visual analytics framework. We present an improved phase timing optimization approach to optimize traffic data. The suggested approach also has the advantage of allowing visual analysis of traffic dependency between roadways in urban networks. It aids in determining the geographic consequences of a specific activity in a given area. The whole experiment was carried out under the MATLAB environment. Communication cost, access ratio, energy consumption, network lifetime, delivery ratio, and delay are the parameters used to evaluate the proposed system with conventional methods. The proposed approach of this study is low in cost, high in instability, and does not require large-scale building or installation work, as opposed to the usual way of monitoring vehicle traffic. Furthermore, the future system should be able to provide other traffic data such as occupancy, queue length, and categorization type. Furthermore, the proposed approach may be adopted in other areas where double parking and bustling roadside activities are a problem. Acknowledgments The authors are thankful to the Deanship of Scientific Research at Najran University for funding this work under the Research Collaboration Funding program grant code (NU/RC/SERC/11/8). The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding & support for this work under Research grant award number RGP. 2/61/43. Author Contributions Conceptualization, S.A., R.U.K. and M.A.A.R.; data curation, H.A. and M.A.; formal analysis, S.A., Q.N.N. and R.U.K.; funding acquisition, M.A. and H.A.; methodology, S.A. and Q.N.N.; project administration, H.A. and M.A.; software, R.U.K. and M.A.A.R.; validation, Q.N.N. and M.A.; visualization, M.A.A.R. and H.A.; writing—original draft, Q.N.N.; writing—review and editing, R.U.K., S.A. and M.A.A.R. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement This paper does not include any animal research nor any human data. Data Availability Statement Not applicable. Conflicts of Interest The authors state that no commercial or financial interactions existed during the project that may be considered as a potential conflict of interest. Figure 1 The schematic representation of the proposed method. Figure 2 The actual length of a road segment as contrasted to the perceived length. Figure 3 Average delivery ratio vs. different message interval for the existing and proposed method. Figure 4 Average delivery delay vs. different message interval for the existing and proposed method. Figure 5 Average communication cost vs. different message interval for the existing and proposed method. Figure 6 Average energy consumption vs. simulation time for the existing and proposed method. Figure 7 First node death vs. number of nodes for the existing and proposed method. 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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/ijerph19095769 ijerph-19-05769 Article Family Supportive Supervisor Behaviors Moderate Associations between Work Stress and Exhaustion: Testing the Job Demands–Resources Model in Academic Staff at an Austrian Medical University https://orcid.org/0000-0002-2647-4461 Komlenac Nikola * Stockinger Lisa Hochleitner Margarethe Tchounwou Paul B. Academic Editor Institute of Diversity in Medicine, Medical University of Innsbruck, 6020 Innsbruck, Austria; lisa.naderhirn@gmail.com (L.S.); margarethe.hochleitner@i-med.ac.at (M.H.) * Correspondence: nikola.komlenac@i-med.ac.at; Tel.: +43-512-9003-71859 09 5 2022 5 2022 19 9 576908 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 time-intensive work of publishing in scientific journals is an important indicator of job performance that is given much weight during promotion procedures for academic positions. The current study applied the job demands–resources model and analyzed whether family supportive supervisor behaviors (FSSB) moderated associations between work stress and feelings of exhaustion as a job resource and whether feelings of exhaustion ultimately mediated the link between work stress and academic employees’ publication activity. The current online cross-sectional questionnaire study was conducted in 133 academic employees (65.4% women, 34.6% men; Mage = 41.9, SD = 10.1) at an Austrian medical university and assessed employees’ numbers of publications, H-index, work stress, feelings of exhaustion, FSSB, and work–family services used. Manifest path models revealed that FSSB moderated the link between experiencing high levels of work stress and strong feelings of exhaustion, especially in employees who had at least one child below the age of 18. Part-time employment was most strongly linked with lower numbers of publications and lower H-index levels. The finding that FSSB acted as a job resource mostly for employees with at least one child below 18 underlines the fact that FSSB is different from other forms of supervisor support. The current study supports recommendations to increase the amount of work–family services and to change organizational norms to be supportive of the successful management of family and work obligations. academic career publication activity job demands–resources model superior family support work–family services This research received no external funding. ==== Body pmc1. Introduction Academic university personnel are faced with many obligations, of which teaching, administrative work, and research activities are the main tasks [1]. Medical academic staff may, in addition to those tasks, need to allocate much time to patient care [2]. These high job demands and workloads can cause work stress, as well as conflicts with obligations that extend beyond work (e.g., family obligations), for employees on the academic career track. The experience of frequent work stress and conflicts that arise when work obligations interfere with family responsibilities has in turn been linked to negative health consequences, such as emotional exhaustion [3]. The job demands–resources (JD–R) model [4,5] can explain such associations. According to the model, negative health consequences are likely to develop when job demands are high and when, at the same time, job resources are either limited or not helpful in achieving one’s goals. These associations have been confirmed by empirical studies conducted among academic university personnel [6,7]. Furthermore, the JD–R model predicts a reduced level of job performance as a consequence of poor health [4]. Past studies have reported that academic personnel who experience exhaustion are likely to perceive low levels of their own productivity at work, be dissatisfied with their job, or have intentions to leave the academic career track [3,8,9,10]. The current study adds to the existing body of literature by testing the JD–R model among academic employees at an Austrian medical university and by including an indicator of productivity on which much emphasis is placed when considering academic employees for job progression and promotion, namely, publication activity [11,12,13]. The current study is further unique in that it specifically considers family supportive supervisor behaviors (FSSB; supervisors’ help with managing employees’ conflicting work and family demands) as a potential job resource [14,15]. 1.1. Job Demands–Resources Model The job demands–resources (JD–R) model explains the relationships between job demands, resources, experiences of strain and job performance [4,5,16]. According to the model, job demands are physical, social, or organizational aspects of a job that require sustained physical or mental effort and may be experienced as stressful [5]. Job demands can lead to negative health consequences. The feeling of being exhausted is one negative psychological consequence that can negatively impact one’s job performance [4,5,16]. Job resources, on the other hand, are aspects of the job that can be functional in achieving one’s goals or reducing the impact of one’s job demands [5]. Thus, job resources are believed to moderate the association between job demands and experienced strain [4]. The JD–R model has helped explain previously found associations between high job demands and feelings of exhaustion among academic employees at universities. A job demand that is often reported is the large number of tasks that need to be performed in a specified amount of time [3,6]. Additionally, the conflicts that arise from contradictory demands of work and family responsibilities can be stressful to academic employees and thus lead to emotional exhaustion [3,9,17]. Furthermore, not having a secure employment status [7,8], being pressured to increase one’s performance in regard to teaching and publication activity, and being pushed to successfully obtain funding are job demands experienced by academic university personnel [18]. Women are more often affected by the resulting feelings of exhaustion than men [19]. In line with the JD–R model, previous research has supported the link between job resources and reduced feelings of emotional exhaustion. Specifically, perceived support by one’s colleagues or supervisors, supervisory coaching, and perceived institutional support have been shown to be associated with reduced feelings of exhaustion [6,9,18]. These job resources may also help avoid the negative consequences of job demands with regard to academic university personnel’s job performance [4], of which job dissatisfaction, intention to leave the academic career track, or reduced levels of self-perceived productivity have been considered in previous research [3,9,10]. The current study considers a further indicator of academic employee productivity, namely, publication activity. 1.2. Academic Careers and Scientific Publications An academic career starts with an academic position during one’s graduate study. During this time, employees are often either involved in research projects or conduct their own studies. Their goal is to publish research results in scientific journals so that they may obtain the degree of Doctor of Philosophy (Ph.D.) [20,21]. At the Medical University of Innsbruck, one to three publications are often obligatory for obtaining a Ph.D. degree [21]. After receiving their doctoral degree, their academic career entails a period at the assistant or associate level of professorship at a university. To advance further in an academic career, employees need to continue to publish in scientific journals [22]. Only after accumulating a certain number of scientific publications can an employee be considered for a full professorship [23,24]. At the Medical University of Innsbruck, a publication record of at least 15 publications is required to be considered for a professorship [25]. Alongside the number of publications, another indicator is also used to characterize a person’s publication activity, namely, the Hirsch index (H-index) [26]. This index not only includes the number of a person’s publications but also the number of citations. Thus, the H-index gives an idea of the scientific impact of a person’s publications [26]. An employee’s number of publications [11,27,28] and their H-index [29,30,31] are strongly associated with their academic rank [32]. However, compared to men, women have been shown to publish fewer papers in scientific journals [33,34,35,36,37]. Additionally, lower citation rates are reported for women’s publications than for those of men [38,39,40,41]. This gender difference in publication activity contributes to the gender differences that are reflected in regard to academic rank [31]. Women are less likely than men to hold either the position of full professor [29,38,41,42] or a leadership position [43,44]. This gender difference is also evident at the Austrian medical university where this study was conducted [45,46]. 1.3. Starting a Family and Family-Friendly Policies For some employees on the academic career track, the time at which the greatest publication activity is required for job advancement coincides with the time when a family is started and with childbearing [23]. Women and men are impacted when starting a family coincides with the need to produce a certain number of publications. However, women are affected more than men [47] because gender norms dictate that the majority of household labor and childcare responsibilities fall to women [48,49]. This unequal allocation of household labor and childcare responsibilities was especially evident during the coronavirus disease 2019 (COVID-19) pandemic [50,51]. Compared to men who had children and worked in academia, women who had children and worked in academia reported that they spent more time on household labor and childcare obligations (including “homeschooling”) during the COVID-19 pandemic than they did before the outbreak [52,53,54]. The need to tend to household obligations can affect the availability of the time that is required for scientific work [55,56]. Thus, time is often seen as a limited but critical resource for the purpose of working on new publications [57]. The successful allocation of enough time to meet the obligations of both family and scientific work can be a challenge for women and men with children [58]. However, women, compared to men, are affected more by the time demands set by household labor and childcare responsibilities, and women are additionally more often willing to scale back to part-time employment or to take a career break than are men [59,60,61,62]. In contrast, to avoid compromising their careers, men are less likely to allocate time for family obligations [59]. Consequently, women who hold academic positions and have children have, on average, less time for their research than do men who hold academic positions and have children [60,63]. The need to balance family and work obligations is sometimes experienced as an impossible task that needs to be individually managed by the employee [64]. In accordance with the JD–R model, the management of conflicting demands from family and work can be experienced as stress and thus lead to a feeling of emotional exhaustion [55,64,65]. The experience of such exhaustion can negatively impact one’s work performance and is associated with reduced levels of publication activity among academic employees [66]. Job resources that might alleviate the links between job demands and feelings of exhaustion include family-friendly policies at the university level [67]. Such policies entail work–family services that focus mostly on the limited time resources of employees with childcare obligations. Thus, most work–family services offer assistance in regard to finding and financing childcare facilities [67,68] (Appendix A). In addition to the availability of work–family services, immediate supervisors can play a key role in helping employees balance their family and work obligations [69]. A family-supportive supervisor offers emotional, practical, and social support for balancing one’s family and work obligations and is considerate of their employees’ family responsibilities [70,71,72]. A family-supportive supervisor is associated with both a greater willingness to take advantage of work–family services and greater levels of employee satisfaction with regard to balancing work and family obligations [70,73,74,75]. Thus, in accordance with the JD–R model, previous research reports that family supportive supervisor behaviors (FSSB) moderate the association that the experience of conflicting demands of family and work or work-related stressors is seen to have with the experience of exhaustion [76,77]. Namely, the relationship between strong family–work conflicts and felt exhaustion is weaker for employees who perceive their supervisor to be supportive when they need to tend to their family obligations compared to employees who do not receive such supervisor support [77]. In the current study, institutional and supervisor family support is considered instead of other sources of social support, such as support from family members, because increased institutional and supervisor family support has been shown to be more strongly associated with reduced levels of work–family conflict than other sources of social support [78]. 1.4. Aim of the Current Study The current study extends the previous research by applying the JD–R model to analyze the links between job stressors, FSSB, feelings of exhaustion, and academic employees’ research activity. The current study is unique in that it analyzed publication activity as an indicator of job performance [4]. This was achieved by considering two indicators of publication activity, namely, one’s number of publications and one’s H-index [26]. The current study is further unique in that it specifically considered FSSB, which is focused on helping employees manage their conflicting work and family demands [14,15]. It was expected that this kind of supervisor support would especially help employees who have childcare obligations. Thus, based on the JD–R model, the following hypotheses were tested (Figure 1): Hypothesis 1 (H1). Work stress is associated with feelings of exhaustion. Exhaustion, in turn, is linked to academic employees’ publication activity. Hypothesis 2 (H2). FSSB acts as a job resource and moderates the association between work stress and feelings of exhaustion. Furthermore, the use of the medical university’s work–family services is associated with employees’ feelings of exhaustion and their publication activity. Hypothesis 3 (H3). FSSB moderates the association between work stress and feelings of exhaustion, especially in employees with children younger than 18, compared to employees with either no children or no children of this age. 2. Materials and Methods 2.1. Procedures and Participants In April 2020, all employees at an Austrian medical university were invited by e-mail to participate in the present online questionnaire study, which was hosted on SoSci: der onlineFragebogen (http://soscisurvey.de/, accessed on 3 April 2020). In June 2020, one additional reminder to participate was sent out to employees. Data collection closed in August 2020. Participants gave informed consent and confirmed that their participation was voluntary. Participation was anonymous, and no participant received any incentive for their participation. The medical university’s ethics committee confirmed that under Austrian law, the current study did not require formal approval by an ethics committee [79,80]. In total, 440 persons took part in the current study. Of the participants, 216 persons were excluded because they stated that they were not employed at the medical university as scientific personnel. Additionally, participants were excluded if they did not respond to almost all questions on the Family Supportive Supervisor Behavior Short-Form (n = 51) and the Copenhagen Burnout Inventory (n = 18). One participant did not report their age, one participant did not report whether they availed themselves of the university’s work–life balance services, and one participant did not report their gender. Thus, these three participants were also excluded from the analysis. Seventeen responses from employees who were undertaking an internship (and thus were unlikely to be pursuing an academic career) were also excluded. Finally, two participants were excluded from the analysis because they did not report their publication activity. Ultimately, there were N = 133 full responses available for the analysis. The results with regard to the H-index were based on 122 responses because 11 persons failed to give information about their H-index. Due to the abovementioned procedure, it was not possible to obtain exact response rates. However, a response rate of 14.3% could be estimated based on the employment data of the medical university, according to which approximately 926 persons held an academic position in 2020 [81]. The bootstrap method used is known to be reliable and robust in small samples [82]. Thus, the current study’s sample size of 133 was large enough to estimate small to medium associations between the independent variable (stress) and the mediator (exhaustion), as well as small to medium associations between the mediator (exhaustion) and the outcome variable (publication activity), with a statistical power of 0.8 and an α of 0.05 [83,84]. Of the 133 participants, 87 (65.4%) were women, and 46 (34.6%) were men. Sociodemographic information about the sample is presented in Table 1. The participants’ ages ranged from 22 to 70 years. On average, men were older than women (Table 2). Most of the sample held Austrian nationality, were in a relationship at the time of the study, identified as heterosexual, and were employed full-time at the medical university (Table 1). Men more often held a full-time position than women. Nearly half of the sample had at least one child below the age of 18 years, and more than half of the sample held the position of a university assistant (Table 1). 2.2. Measures 2.2.1. Sociodemographic Information The participants were asked for their self-reported gender (response options: woman, man, trans-woman, trans-man, gender-neutral/nonbinary, diverse or other gender identity), age (free-text response), sexual orientation (response options: self-identifying as heterosexual, gay-identified/lesbian-identified, bisexual, asexual, other), relationship status (response options: single, not sure/complicated, in relationship), and nationality (response options: Austrian, German, Turkish, Italian, other). Furthermore, they were asked whether they held an academic position at the medical university (response options: administrative position, academic position, grant-financed position, do not work at this medical university), which academic position they held (response options: internship, student assistant, lector, university assistant, tenure track, university professor), and whether they worked full-time (response options: 25%, 50%, 70%, 100%, other). Finally, the participants were asked how many children they had (free-text response). If they reported having children, participants were then asked for their children’s age (free-text response). If they selected the response of “other” to any question, participants were prompted to provide a free-text response specifying their initial response. In most cases, the free-text responses could be matched to an existing category of a variable. If they could not be matched, free-text responses were excluded. For the analysis, only participants who held an academic position or a grant-financed position were considered. A new variable with two categories was formed for academic position. In this variable, one response category was formed for student assistants, lectors and university assistants, while the second was for tenure tracks and university professors. A dichotomous variable was formed for employment level that differentiated whether a participant worked full-time (100% or above) or had no full-time employment (all remaining response options). Finally, a new variable was formed with one category (1) for participants who indicated having at least one child younger than 18 years and another category (0) for the remaining participants who had either no children or no children younger than 18 years. 2.2.2. Publication Activity To assess how many articles participants had published in scientific journals, they were asked the following question: “How many peer-reviewed scientific articles have you authored or coauthored?” [27]. Free-text responses to this question were allotted to four categories, namely, 0 = no publications, 1 = one to three, 2 = four to 15, or 3 = more than 15. This categorization was chosen because one to three publications are often obligatory during graduate study (i.e., to obtain a Ph.D. degree) [20,21]. Another “milestone” in an academic career is to be granted venia docendi, which requires a publication record of at least 15 publications at the medical university [25]. Participants entered their H-index in an open-text field after being asked, “What is your current H-index (https://www.scopus.com/freelookup/form/author.uri, accessed on 29 April 2022)?” The median of the given responses was 8.0 (interquartile range = 0.0–19.2). For the analysis, the responses were grouped into four categories based on quartiles, namely, 0 = no H-index, 1 = one to eight, 2 = nine to 19, and 3 = larger than 19. 2.2.3. Stress at Work The experience of work stress was measured with a questionnaire developed by Cavanaugh et al. [85]. This questionnaire consisted of 16 statements that each describe challenge stressors (6 items), hindrance stressors (5 items), or other stressors (5 items that do not clearly fall into either category). Challenge stressors are work-related demands that can potentially result in work-related gains for an individual (e.g., “The number of projects and/or assignments I have”). In contrast, hindrance stressors are believed to interfere with being successful at work and are not associated with personal gains (e.g., “The inability to clearly understand what is expected of me on the job”). Using a five-point Likert scale, the participants in the current study reported how much stress each described stressor caused them in their work (1 = produces no stress; 5 = produces a great deal of stress). High mean scores indicated that these stressors caused the participants to experience a great amount of stress at work. A confirmatory factor analysis supported the two-factor structure of the questionnaire [85]. The scale assessing work stress associated with challenge stressors had a reported internal consistency of Cronbach’s α = 0.87, while the scale measuring stress associated with hindrance stressors had a reported internal consistency of Cronbach’s α = 0.75 [85]. After translating all items into German with the back-and-forth procedure [86], an exploratory factor analysis (EFA) with the Kaiser criterion was performed to explore the translated questionnaire’s factor structure in the current sample. The resulting four factors explained 20.5%, 11.9%, 10.6% and 10.6% of the variance. However, items with small communalities (h2 < 0.40) were detected. The item with the smallest communality (h2 = 0.18; Item 10) was removed, and the EFA was repeated before the next item with a communality smaller than 0.40 was removed. This process was repeated until five items (Items 7, 8, 10, 12, and 16) were removed and the EFA solution did not include items with communalities smaller than 0.40. The retained items loaded on two factors. The first factor (Items 1, 2, 3, 4, 5, 6, 9, and 13; λ = 0.62–0.81) explained 37.3% of the variance and had satisfactory internal consistency (Table 2) [87]. The second factor (Items 11, 14, and 15) explained 16.8% of the variance. This factor was not considered in the analysis because there was an unsatisfactory internal consistency with regard to men (Table 2) [87]. 2.2.4. Feelings of Exhaustion The Copenhagen Burnout Inventory (CBI) was used to assess participants’ degree of fatigue and exhaustion [88]. The six items of the first scale, namely, Personal Burnout, ask persons how tired or exhausted they felt, e.g., “How often are you physically exhausted?” Responses were given on a five-point Likert scale (1 = Never/almost never; 5 = Always). The seven items of the Work-related Burnout Scale assessed the degree of fatigue and exhaustion that participants perceived in relation to their work, e.g., “Do you feel burnt out because of your work?” Responses were given on a five-point Likert scale (1 = Never/almost never or to a very low degree; 5 = Always or to a very high degree). High mean scores indicated that a person experienced high degrees of fatigue and exhaustion [88]. No factor analyses were performed in the original study, but satisfactory internal consistencies were reported for the two scales (Cronbach α = 0.87). All items were translated into German by two independent professional translators with the back-and-forth procedure [86]. An EFA with the Kaiser criterion supported a two-factor structure (factors explained 28.6% and 18.7% of the variance). However, items with small communalities (h2 < 0.40) were detected. The item with the smallest communality (h2 = 0.19; Item 11) was removed, and the EFA was repeated before the next item with a communality smaller than 0.40 was deleted. This process was repeated until seven items (Items 6, 8, 9, 11, 12, and 13) were removed and the EFA solution did not include items with communalities smaller than 0.40. All of the retained items loaded on one factor (λ = 0.63–0.86) that explained 51.0% of the variance and resembled the original Personal Burnout Scale [88]. The items measured perceived fatigue and exhaustion with a satisfactory level of internal consistency (Table 2) [87]. ijerph-19-05769-t002_Table 2 Table 2 Descriptive statistics. Variable 1 All Women Men t(131) d M SD α M SD α M SD α Age 41.9 10.1 40.0 9.1 45.6 11.1 3.1 * 0.57 Stress 1 2.9 0.9 0.89 2.8 0.9 0.88 3.0 1.0 0.91 1.1 Stress 2 2.8 1.1 0.75 3.0 1.1 0.80 2.6 0.9 0.59 −1.8 Exhaustion 2.7 0.7 0.88 2.8 0.7 0.89 2.6 0.7 0.86 −1.5 FSSB-SF 3.1 1.0 0.89 3.1 1.1 0.89 3.0 1.0 0.88 −0.5 1 All Likert scales ranged from 1 (disagreement/no stress) to 5 (agreement/a lot of stress); FSSB-SF = Family Supportive Supervisor Behavior Short-Form; df = degrees of freedom; * p < 0.01. 2.2.5. Family Supportive Supervisor Behaviors The degree to which superiors supported their employees’ family roles and thus supported employees in their balancing work and family responsibilities was assessed with the Family Supportive Supervisor Behavior Short-Form (FSSB-SF) [14]. The FSSB-SF consists of four items that were retained from the original four-factor structured Family Supportive Supervisor Behaviors scale (FSSB) [15]. The FSSB-SF contains one item of each of the theoretically derived factors, namely, emotional support, instrumental support, role modeling, and creative work–family management [14,89]. One example item is “Your supervisor makes you feel comfortable talking to him/her about your conflicts between work and non-work” (emotional support). Responses were given on a five-point Likert scale (1 = Strongly disagree, 5 = Strongly agree), and mean scores were calculated. High mean scores indicated that employees perceive that their superior(s) support them in balancing their work and family responsibilities. The reported internal consistency was α = 0.82–0.88 [14]. For the current study, the items were translated into German with the back-and-forth procedure [86]. An EFA with the Kaiser criterion revealed a one-factor solution [90]. The proportion of variance explained by this factor was 66.5% (all communalities >0.55), and all items loaded with factor loadings between 0.74 and 0.88. The internal consistency of the FSSB-SF was satisfactory (Table 2) [87]. 2.2.6. Use of Work–Family Services Participants were asked how often (0 = never; 1 = once; 2 = sometimes; 3 = often) they take advantage of each of the work–family services offered by the medical university [67,68] (Appendix A). Because few employees used the response options 2 = sometimes and 3 = often, new variables with two categories were formed for each work–family service. Each new variable contained information on whether an employee had used a certain work–family service (1 = yes, at least once; 0 = no) [72,77]. For the analyses, a dichotomous variable was used to differentiate whether participants had used the university’s work–family services at least once or had not used such services. 2.3. Statistical Analysis To report the descriptive statistics, the percentages and means of the given responses were calculated. Chi-square tests and t-tests were used to reveal gender differences. Correlation analyses were performed to calculate the bivariate relationships between the studied variables. EFAs with the Kaiser criterion (Eigenvalue for factor extraction ≥1) were calculated to analyze whether the factor structures of the validated questionnaires were also applicable to the translated versions of the questionnaires in the current sample. Therefore, items with small communalities (h2 < 0.40) were removed, and scales consisting of items with high factor loadings and satisfactory internal consistencies were used for the subsequent analyses [87,90]. Figure 1 Part of the Job Demands–Resources Model Considered in the Current Study. Based on the Job Demands–Resources Model, it was tested whether work stress (X) would be associated with feelings of exhaustion (M) and, consequently, be linked to academic employees’ publication activity (Y; H1). Family supportive supervisor behaviors (W) were tested as a moderator of the association between work stress and feelings of exhaustion (H2). Finally, it was tested whether family supportive supervisor behaviors would moderate the association between work stress and feelings of exhaustion, especially in employees with children younger than 18 (Z; H3). Arrows represent associations between variables. Higher scores in one variable were expected to go along with higher scores in another variable (“+”) or with a lower score in another variable (“−“). To test the job demands–resources model, two manifest path models were calculated (Figure 1). In one model, the number of peer-reviewed publications (variable Y1) was predicted by feelings of exhaustion (mediator, variable M) and stress at work (variable X). In the second model, the H-index (variable Y2) was predicted by those same variables. In both models, feelings of exhaustion were entered as a mediator of the relationship between stress at work and publication activity. FSSB (moderator, variable W) was analyzed as a moderator of the relationship between stress at work and publication activity, as well as stress at work and feelings of exhaustion. Having at least one child below the age of 18 (moderator, variable Z) was entered as a moderator of the relationship between stress at work and publication activity, as well as stress at work and feelings of exhaustion. Finally, indirect links between stress at work and publication activity via feelings of exhaustion were calculated. In all analyses, the control variables of gender, age, employment level, academic position and the use of work–family services were considered. Each of the manifest path models was calculated with Model 12 in the PROCESS macro for SPSS [82] (www.processmacro.org, accessed on 21 January 2021). For this purpose, bootstrap bias-corrected 95% confidence intervals (bootstrap sample was n = 5000) for all path coefficients were estimated. Significant results were indicated when p ≤ 0.05 or when 95% confidence intervals did not include zero. All analyses were performed with the Statistical Package for the Social Sciences (SPSS) for Windows, version 26.0 (IBM Corp., Armonk, NY, USA). 3. Results 3.1. Descriptive Statistic On average, women and men reported experiencing moderate levels of stress at work and moderate feelings of exhaustion (Table 2). Women and men perceived moderate levels of FSSB on average (Table 2). Women with at least one child below the age of 18 more often availed themselves of at least one work–family service (85.4%) than did men with at least one child below the age of 18 years (50.0%), χ2(1) = 9.1, p = 0.006, V = 0.38. Thereby, the service most frequently used consisted of financial services when resuming work after parental leave (Appendix A). Women more often took advantage of this so-called “Back to Work Campaign” than did men (Appendix A). The second most frequently sought service was help in finding childcare, followed by participation in events and courses for children (Appendix A). Nearly half of the participants reported having published 16 or more scientific articles (Table 1), although men more often reported having published this number of scientific articles than did women (Table 1). Women more often than men reported not having published any scientific article or having published four to 15 articles (Table 1). This gender difference in publication was also reflected in the H-index results. Women reported having lower H-indices than those of men (Table 1). Bivariate correlations of the variables are reported in Table 3. Participants’ older age correlated with a larger number of publications and a higher H-index. For women, a higher H-index was additionally associated with having full-time employment. For men, a higher H-index was associated with holding a higher academic position. Having at least one child below 18 years of age correlated with experiencing higher levels of exhaustion and being less frequently employed full-time for women but not for men. For women, a higher position was linked to having at least one child below 18 years of age, using work–family services, and not having full-time employment. Experiencing frequent stress at work was linked to having stronger feelings of exhaustion for women and men and to having higher levels of publication activity for men (Table 3). 3.2. Job Demands and Resources All path coefficients of the manifest path analysis are reported in Table 4. The experience of frequent exhaustion was linked to perceiving little FSSB and to frequent experiences of stress at work (Table 4). Work–family services were especially used by employees who experienced frequent exhaustion. FSSB more strongly moderated the association between stress at work and the experience of exhaustion in employees with at least one child younger than 18 years of age (Figure 2) than it did in employees with either no children or with children older than 18 years of age. In employees with at least one child younger than 18 years of age, the association between experiences of stress and exhaustion was markedly weaker in employees who perceived FSSB than in employees who did not perceive FSSB (Figure 2). Having a larger number of publications and a higher H-index was linked with being employed full-time and with being older. No other variables were linked to either the publication number or the H-index (Table 4). No indirect associations between stress at work and publication number via exhaustion were detected (all β values = 0.0–0.1; lower limit of 95% confidence interval = −0.1–0.0; upper limit of 95% confidence interval = 0.1–0.2). Similarly, no indirect links between stress at work and the H-index via exhaustion were found (all β values = −0.1–0.0; lower limit of 95% confidence interval = −0.3–−0.1; upper limit of 95% confidence interval = 0.0). 4. Discussion The current study applied the job demands–resources (JD–R) model [4,5,16] and revealed links between high levels of work stress and frequent feelings of exhaustion (H1) among academic employees at an Austrian medical university. Family supportive supervisor behaviors (FSSB) moderated the association between work stress and feelings of exhaustion, especially in employees with children younger than 18 years compared to employees who had either no children or no children of this age (H3). Employees who experienced frequent exhaustion were more likely to use work–family services than were employees who experienced exhaustion infrequently (H2). In contrast to expectations (H1), neither work stress nor feelings of exhaustion were linked to publication activity in the tested models. Instead, part-time employment was most strongly linked with lower numbers of publications and lower H-indices. 4.1. Work Stress and Exhaustion Women in academic positions often view the balancing of time resources between family and work obligations as an additional, personal, and sometimes impossible task that successful employees are expected to fulfill [64]. Thus, the management of work and family obligations can sometimes be seen as an additional work stressor, especially for women who retain the major share of household and childcare obligations [91]. In the current study, having at least one child below the age of 18 was linked to the experience of high levels of exhaustion in women but not in men. The current study revealed that most employees who experienced high levels of exhaustion took advantage of institutional work–family services, such as on-site childcare or affordable childcare options. The important role of such institutional family support in the reduction of work–family conflict [78] and in increasing the retention rate of employees on the academic career track, especially among women, has been previously reported [92,93]. However, previous research has also reported that interventions need to focus not merely on the development and implementation of formal family-friendly policies but also on changing the perception and organizational norms or values surrounding the management of family and work obligations. Thereby, immediate supervisors can play a key role by offering emotional, practical, and social support to employees in regard to balancing their family and work obligations and by being considerate of their employees’ family responsibilities [70,71,72,77]. In line with the JD–R model, the current study shows that such family supportive supervisor behaviors can act as a job resource because FSSB moderates the links between work stress and feelings of exhaustion, especially in academic employees with at least one child below the age of 18. Specifically, in employees with at least one child younger than 18 years of age, the association between high levels of work stress and high levels of exhaustion was weaker when employees perceived high levels of FSSB compared to employees who did not perceive support from their immediate supervisor in regard to balancing their work and family responsibilities. The finding in the current study that FSSB was a moderator mostly for employees with at least one child under 18 years of age underlines the fact that FSSB differs from other forms of supervisor support [14,89]. Therefore, it is recommended that supervisors either learn or be trained how to specifically support their employees in regard to balancing their work and family responsibilities [69,94]. 4.2. Publication Activity (Job Performance) Having a certain number of publications with a certain scientific impact is relevant because publication activity is an important criterion for promotion in academic medicine [32], including at the medical university in this study [21,25]. Such criteria for promotion, however, can place women at a disadvantage because women often have a smaller number of publications and, on average, have publications that are less frequently cited than those of men [31,36,39]. This gender difference was also evident in the current study. More men than women reported having more than 16 publications and having an H-index greater than 20. Time is a critical resource for being able to work on scientific projects and new publications [57]. The huge block of time required for the publication activity can conflict with the time demands set by household obligations [55]. Gender differences in publication activity can in part be explained by different time demands set by household obligations for women and men. Gender norms often dictate that the majority of household labor and childcare responsibilities fall to women [48,49], and in addition, women are more often willing to scale back to part-time employment compared to men [59,60,62]. This gender difference was also evident in the current study. Women were more often employed part-time, whereas men more often held full-time positions. Consequently, on average, women in academic positions had less time at their disposal for their research compared to that of men [60,63]. Full-time employment in turn was most strongly associated with high levels of publication activity in the current study. To help with the conflicting time demands set by family and work obligations, family-friendly policies have been enacted at the Medical University of Innsbruck [67]. In the current study, women holding part-time employment have taken special advantage of the work–family services granted under those polices. Thus, the current findings suggest that work–family services can help employees delegate more time to the important and valued task of scientific publishing [57]. Such offers can help employees to better succeed in their job, and women have reported that work–family services concerning childcare and opportunities for work–life integration also motivate them to continue working in their academic position [93]. Therefore, the implementation of work–family services that help find and finance childcare is recommended for universities that do not have such offers [56,95]. 4.3. Future Directions Even though time is a critical resource for an academic employee’s publication activity [57], and women can often allocate less time to research than men [60], additional factors have been found to contribute to the gender differences found in regard to publication activity. The stereotypical ideas of gender and the perception of a typical scientist being a man [96] often lead to implicit (often unconscious and unintended) biases that are characterized by women’s scientific contributions being systematically valued less than those of men [97]. Women’s opportunities to conduct planned studies, which form the basis for scientific publications, are hampered by their grant applications being systematically perceived as being of lesser quality than those of men [98,99]. For example, among applications for grants at the Canadian Institutes of Health Research, women who were equally as qualified as men (based on their past research records) received lower application scores than did male applicants [98]. Additionally, women’s scientific texts are often judged as being of poorer quality than equal contributions authored by men [100]. It was found that people judge identical scientific texts differently solely on the basis of the author’s name, i.e., whether the name indicates a female or male author [101]. Receiving less credit for their publications places women at a disadvantage in their job progression and their chances for promotion, even though women can show an equal number of publications as their male contenders when they are up for a potential promotion [31,97,102,103]. Another approach to reducing the disadvantages that women face during their career advancement path may be to not focus on helping women allocate more time to work on scientific publications. Rather, considerations seem warranted to change the standards for promotion to focus less on publication activity and more on alternative achievements [28,104]. For example, in promotion procedures, greater weight could be given to non-research activities in which women are often strongly involved, such as teaching, patient care, or committee work [28,104,105]. 4.4. Limitations Several limitations of the current study should be considered. Data collection for the study coincided with the COVID-19 outbreak in Europe [106]. Government regulations led to the temporary closure of many childcare facilities and schools [107]. This led to increased childcare demands for persons with childcare obligations, and women were especially affected [52,53,54]. More women than men experienced the need to tend to children who were either not cared for or did not undergo schooling outside the home as new stressors and as new challenges to balancing their family and work obligations [52,53,54,107]. Consequently, women’s research productivity during this time period was particularly low [108]. The current study was conceptualized before the COVID-19 outbreak and, therefore, did not assess which new challenges persons with childcare obligations faced during lockdown. Some of the exhaustion and work stress reported by the current participants may be attributed to the novel challenges they faced during the COVID-19 outbreak and lockdowns. The challenging COVID-19 times may also have affected employees’ willingness to participate in the current study. The estimated response rate of 14.3% was relatively low. Even though the sample size seemed adequate for data analysis [82,83], such a relatively small sample size limits the generalizability of the study’s results. Furthermore, the sample was not large enough to calculate separate models for women and men or to consider gender as a moderator (in an interaction term). The relatively small sample also necessitated considering women and men as monolithic groups. However, only the consideration of intragender variations (for example, by additionally considering women’s and men’s nationality, sexual orientation, or relationship status) can help reveal the experiences of overlapping dynamics of different forms of inequality, in the face of which certain identities may be especially advantaged or disadvantaged [63]. Because of the cross-sectional study design with only one time point, no conclusions about the directionality of the found associations or causality can be drawn from the current study’s results, and associations should not be misinterpreted as causal relationships. As is the case with many questionnaire studies, the participants may have given some socially desirable responses and thereby biased the current study’s results. A related source of bias is the so-called common method bias [109]. This bias describes a situation in which associations between (latent) constructs that have been assessed with similar methods (e.g., questionnaires with the same scale format) might in part correlate because of the common method used to assess the studied constructs. However, in the current study, not only associations between latent constructs that share common methods were studied. Instead, some included variables, such as the number of children younger than 18 years of age, the number of publications or one’s H-index, that are objective information, and the assessment of those variables differed from the assessment of latent constructs. For the reporting of their H-index, participants were even provided with an internet link to be able to give accurate responses. Thus, the assessment of the H-index can be understood as a “fact-based questionnaire item” [110] that can give an estimate of the scientific impact of a person’s publications by considering their number of publications and their number of citations [26]. However, there are several pitfalls related to using the H-index that limit the interpretation of the current study’s findings [111]. First, there can be long delays between the time an author finishes a manuscript and the time at which the manuscript is published. Thereafter, more time passes before the author’s number of citations increases. Thus, it is unlikely that young researchers or researchers at the beginning of their career have a high H-index, and it is possible that a part of our participants’ publication activity was missed. Other factors, such as the popularity of the topic, the number of collaborations, or the number of self-citations, influence a researcher’s H-index. Finally, a researcher might have impacted the scientific field by a few highly cited publications without having an overall high number of publications. In such a case, their H-index would nevertheless remain low [111]. 5. Conclusions The current study revealed that family supportive supervisor behaviors (FSSB) can be considered a job resource among employees who hold an academic position at an Austrian medical university. As predicted by the JD–R model [4,5], FSSB acted as a moderator for the link between experiences of work stress and feelings of exhaustion, especially for employees who had at least one child below the age of 18 years. In employees with at least one child younger than 18 years, the association between high levels of work stress and strong feelings of exhaustion was markedly weaker in employees who perceived FSSB than in employees who did not perceive such support. The current study’s findings suggest that work–family services might help employees delegate more time to the important task of scientific publishing and thus support recommendations to increase (or at least maintain) the scope of work–family services offered by family-friendly institutional policies. Additionally, supervisors need to be trained on how to offer emotional, practical, and social support with a view to balancing the family and work obligations of their employees in order for such a family-friendly organizational climate to develop [70]. Future studies need to focus on finding job resources that can help academic employees continue in a full-time position after starting a family. In particular, women have been reported to be willing to drop down to part-time from full-time employment after having a child [60,62]. Future studies should also consider other elements of the JD–R model that were not considered in the current study, such as employee motivation or active changes that employees can make in their job demands and resources (so-called “job crafting”) [4]. In addition to publication activity, other indicators of job performance can be considered in future studies. Receiving research funding, receiving recognition awards, being invited to speak at scientific conferences, or being on the editorial boards of scientific journals are additional indicators of job performance that are given considerable weight in promotion procedures for academic positions [104] and should, therefore, be included in future studies. Author Contributions Conceptualization, N.K., L.S. and M.H.; methodology, N.K.; statistical analysis, N.K.; data curation, N.K.; writing—original draft preparation, N.K.; writing—review and editing, N.K.; visualization, N.K.; supervision, M.H.; project administration, N.K. and M.H. 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 because under Austrian law, the current study did not require formal approval by an ethics committee [79,80]. Informed Consent Statement Informed consent was obtained from all participants 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 declare no conflict of interest. Appendix A ijerph-19-05769-t0A1_Table A1 Table A1 Work–family services offered and used by women and men with at least one child below the age of 18 years (n = 77). Work–Family Service All n (%) Men n (%) Women n (%) χ2(1) V Back to Work Campaign (services when resuming work after parental leave) 34 (44.2) 5 (16.7) 29 (61.7) 15.1 *** 0.44 Help find childcare 24 (31.2) 6 (20.0) 18 (38.3) 2.9 Child and Youth Academy (events and courses for children) 23 (29.9) 5 (16.7) 18 (38.3) 4.1 Informative talk about financial services 19 (24.7) 4 (13.3) 15 (31.9) 3.4 Informative talk about childcare options 18 (23.4) 2 (6.7) 16 (34.0) 7.7 ** 0.32 Use university’s childcare facility (kindergarten) 15 (19.5) 2 (6.7) 13 (27.7) 5.1 * 0.26 Girl’s Day (one-day event for children) 8 (10.4) 4 (13.3) 4 (8.5) 0.5 Family Start Package (hygiene products for newborn children; started 2020) 7 (9.1) 3 (10.0) 4 (8.5) 0.0 Help find ad hoc childcare in emergency cases 3 (3.9) 1 (3.3) 2 (4.3) 0.0 Help find short-term childcare (e.g., for one to several days) 2 (2.6) 0 (0.0) 2 (4.3) 1.3 Only numbers and percentages of employees who took advantage of the particular service are reported; * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001. Figure 2 Interaction Stress × Family Supportive Supervisor Behaviors × Child. Dotted lines show employees who, on average, do not perceive family supportive supervisor behaviors (FSSB). Solid lines show employees who, on average, perceive FSSB. Strong work stress was associated with strong feelings of exhaustion. On average, employees who perceived FSSB experienced weaker feelings of exhaustion than did employees who did not perceive FSSB. FSSB more strongly moderated the association between stress at work and the experience of exhaustion in employees with children below the age of 18. In employees with children younger than 18, the association between work stress and exhaustion was weaker for employees who perceived FSSB than for employees who did not perceive FSSB. ijerph-19-05769-t001_Table 1 Table 1 Sociodemographic description of the sample. Variable All N (%) Men n (%) Women n (%) χ2 df V Gender Woman 87 (65.4) Man 46 (34.6) Nationality 0.6 3 Austrian 91 (68.4) 32 (69.6) 59 (67.8) German 19 (14.3) 6 (13.0) 13 (14.9) Italian 19 (14.3) 6 (13.0) 13 (14.9) Other 4 (3.0) 2 (4.3) 2 (2.3) Relationship 0.3 1 Single 11 (8.5) 3 (6.5) 8 (9.5) With partner 119 (91.5) 43 (93.5) 76 (90.5) Sexual Orientation 2.6 2 Heterosexual-identified 125 (94.0) 44 (95.7) 81 (93.1) Gay/lesbian-identified 4 (3.0) 2 (4.3) 2 (4.3) Bisexual-identified 4 (3.0) 0 (0.0) 4 (4.6) Child under age of 18 0.0 1 No 70 (52.6) 24 (52.2) 46 (52.9) Yes 63 (47.4) 22 (47.8) 41 (47.1) Work–family service used 3.5 1 No 81 (60.9) 33 (71.7) 48 (55.2) Yes 52 (39.1) 13 (28.3) 39 (44.8) Full-time employment 6.1 * 1 0.22 No 38 (28.6) 7 (15.2) 31 (35.6) Yes 95 (71.4) 39 (84.8) 56 (64.4) Academic position 0.1 1 University assistant 79 (59.4) 27 (58.7) 52 (59.8) Professor/tenure track 54 (40.6) 19 (41.3) 35 (40.2) Publications 9.7 * 3 0.27 0 18 (13.5) 3 (6.5) 15 (17.2) 1–3 17 (12.8) 4 (8.7) 17 (12.8) 4–15 24 (18.0) 5 (10.9) 24 (18.0) 16+ 74 (55.6) 34 (73.9) 74 (55.6) H-index 8.2 * 3 0.26 0 26 (21.3) 6 (14.6) 20 (24.7) 1–8 32 (26.2) 8 (19.5) 24 (29.6) 9–19 30 (24.6) 9 (22.0) 21 (25.9) 20+ 34 (27.9) 18 (43.9) 16 (19.8) df = degrees of freedom; * p < 0.001. ijerph-19-05769-t003_Table 3 Table 3 All correlation coefficients. Variables 1 2 3 4 5 6 7 8 9 10 1. Age - 0.26 * 0.35 ** −0.08 0.18 0.08 0.03 0.13 0.48 ** 0.56 ** 2. Child under age 18 −0.27 - 0.77 ** −0.40 ** 0.21 * 0.02 0.31 ** −0.14 0.13 −0.01 3. Work–family services used −0.13 0.46 ** - −0.34 ** 0.35 ** −0.04 0.21 −0.02 0.15 0.06 4. Full-time employment −0.01 −0.08 0.13 - −0.22 * 0.17 -0.03 −0.04 0.17 0.24 * 5. Academic position 0.11 −0.10 0.06 0.11 - 0.00 0.07 0.14 0.13 0.14 6. Stress −0.20 0.06 0.03 0.06 0.00 - 0.41 ** 0.02 0.13 0.09 7. Exhaustion −0.30 * −0.10 0.28 0.22 0.17 0.49 ** - −0.19 0.08 −0.15 8. FSSB-SF −0.14 0.05 −0.07 −0.16 −0.06 0.10 −0.13 - 0.05 0.12 9. Publications 0.33 * −0.12 0.12 0.11 0.10 0.31 * 0.25 0.20 - 0.76 ** 10. H-index 0.62 ** −0.13 0.08 0.16 0.35 * −0.05 −0.08 0.04 0.80 ** - Above the diagonal, correlations in women (n = 100) are reported; below the diagonal, correlations in men (n = 50) are reported; FSSB-SF = Family Supportive Supervisor Behavior Short-Form; * p < 0.05, ** p < 0.01. ijerph-19-05769-t004_Table 4 Table 4 All model path coefficients—direct associations. Outcome Variable Predictor B SE B 95% CI for B R 2 LL UL Feelings of exhaustion 0.35 *** Gender 0.18 0.12 −0.05 0.41 Age −0.01 0.01 −0.02 0.00 At least one child below 18 −0.04 0.14 −0.32 0.23 Full-time employment 0.00 0.12 −0.24 0.24 Academic position 0.08 0.11 −0.13 0.29 Work–family services used 0.38 ** 0.14 0.10 0.67 Stress 0.31 *** 0.06 0.20 0.42 FSSB −0.12 * 0.05 −0.22 −0.02 FSSB × Child 0.08 0.10 −0.12 0.27 Stress × FSSB −0.03 0.05 −0.13 0.07 FSSB × Child 0.08 0.10 −0.12 0.27 Stress × FSSB × Child −0.21 * 0.10 −0.41 −0.01 Publications 0.31 *** Gender −0.22 0.20 −0.61 0.17 Age 0.05 *** 0.01 0.03 0.06 At least one child below 18 0.09 0.23 −0.37 0.56 Full-time employment 0.48 * 0.20 0.08 0.89 Academic position 0.10 0.18 −0.26 0.46 Work-family services used 0.11 0.25 −0.39 0.60 Exhaustion 0.16 0.15 −0.15 0.47 Stress 0.15 0.11 −0.06 0.36 FSSB 0.12 0.09 −0.05 0.29 Stress × Child 0.07 0.19 −0.31 0.45 Stress × FSSB 0.10 0.09 −0.07 0.27 FSSB × Child −0.09 0.17 −0.42 0.24 Stress × FSSB × Child −0.11 0.17 −0.45 0.24 H-index 0.48 *** Gender −0.04 0.18 −0.40 0.32 Age 0.06 *** 0.01 0.04 0.08 At least one child below 18 0.00 0.22 −0.44 0.43 Full-time employment 0.64 ** 0.19 0.27 1.01 Academic position 0.30 0.17 −0.03 0.63 Work–family services used 0.04 0.23 −0.42 0.50 Exhaustion −0.22 0.14 −0.50 0.07 Stress 0.12 0.10 −0.08 0.32 FSSB 0.07 0.08 −0.08 0.23 Stress × Child 0.01 0.18 −0.35 0.36 Stress × FSSB 0.06 0.08 −0.10 0.22 FSSB × Child −0.28 0.16 −0.59 0.03 Stress × FSSB × Child −0.06 0.16 −0.38 0.26 Variables that have significant associations with the outcome variable are written in bold. 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==== Front Nanomaterials (Basel) Nanomaterials (Basel) nanomaterials Nanomaterials 2079-4991 MDPI 10.3390/nano12091462 nanomaterials-12-01462 Article Sulfuric Acid Immobilized on Activated Carbon Aminated with Ethylenediamine: An Efficient Reusable Catalyst for the Synthesis of Acetals (Ketals) https://orcid.org/0000-0001-8415-7272 Liu Wenzhu 12 Guo Ruike 1* Peng Guanmin 1 Yin Dulin 2* Guerrero-Ruiz Antonio Academic Editor 1 College of Chemistry and Materials Engineering, Huaihua University, Huaihua 418000, China; hebeiliuwenzhu@126.com (W.L.); guanminpengh@126.com (G.P.) 2 National & Local Joint Engineering Laboratory for New Petro-Chemical Materials and Fine Utilization of Resources, Hunan Normal University, Changsha 410081, China * Correspondence: guoruikeh@163.com (R.G.); dulinyin@126.com (D.Y.) 25 4 2022 5 2022 12 9 146212 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/). Through the amination of oxidized activated carbon with ethylenediamine and then the adsorption of sulfuric acid, a strong carbon-based solid acid catalyst with hydrogen sulfate (denoted as AC-N-SO4H) was prepared, of which the surface acid density was 0.85 mmol/g. The acetalization of benzaldehyde with ethylene glycol catalyzed by AC-N-SO4H was investigated. The optimized catalyst dosage accounted for 5 wt.% of the benzaldehyde mass, and the molar ratio of glycol to benzaldehyde was 1.75. After reacting such mixture at 80 °C for 5 h, the benzaldehyde was almost quantitatively converted into acetal; the conversion yield was up to 99.4%, and no byproduct was detected. It is surprising that the catalyst could be easily recovered and reused ten times without significant deactivation, with the conversion yield remaining above 99%. The catalyst also exhibited good substrate suitability for the acetalization of aliphatic aldehydes and the ketalization of ketones with different 1,2-diols. activated carbon solid acid catalyst benzaldehyde acetals (ketals) ==== Body pmc1. Introduction Synthesis of acetals (ketals) are a class of reactions that are widely used in various fields, such as organic synthesis [1,2], medical materials [3], carbohydrate chemistry [4], and bio-based solvents [5]. As a typical representative, benzaldehyde condensed with ethylene glycol has attracted considerable interest in a number of studies and is widely used as flavors due to its properties of a fruity aroma with an apple flavor, long-lasting fragrance, and good chemical stability [6,7]. In traditional catalytic syntheses, sulfuric acid, hydrochloric acid, p-toluenesulfonic acid, and other inorganic acids can be used as catalysts in synthesizing acetals (ketals) reactions [8]. These catalytic processes have advantages of simplicity and high conversion efficiency but are also accompanied by the disadvantages of side reactions, difficulties in products separation, and the corrosion of equipment. Therefore, it is imperative to find an appropriate solid acid alternative to traditional liquid acid catalysts. Currently, molecular sieves [9], solid superacid [10], heteropoly acid (heteropoly-acid-based ionic liquids [11], TiO2 nanoparticle-exfoliated montmorillonite [12], 8-hydroxy-2-methylquinoline-modified with H4SiW12O40 [13], Ta/W mixed addenda heteropolyacid [14], solid oxide acid [7], and carbon-based solid acid [15] have been used to catalyze the synthesis of acetals (ketals), achieving good catalytic effects but also accompanied by low yield, poor selectivity, difficult recovery, poor solvent applicability, and the loss of active components [15,16,17]. Thus, novel economical, efficient, and reusable solid acid catalysts used in the synthesis of acetals still need to be developed. For the past few years, solid carbon-based catalysts have attracted the attention of researchers due to the advantages of abundant resources, large specific surface areas, easy-to-control pore structures, and abundant controllable aromatic rings and oxygen-containing functional groups on the surface [18,19]. The catalytic performances of carbon materials are inseparably related to the type of surface acidic or basic functional groups. Acidic groups obtained by the simple oxidation of carbon with oxidants, such as HNO3 [20,21], H2SO4 [22], H2O2 [23], and other oxidants [24], are usually weak acidic groups, such as hydroxyl, carboxyl, etc., which stimulate the use in absorption and desorption fields [25,26] but cannot be applied satisfactorily in the field of catalysis due to the strong acidic requirements of catalytic reactions. However, the abundant oxygen-containing functional groups on the surface of carbon provided many possibilities for designing surface functional groups and use in different catalytic systems. Graphene, mesoporous carbons, and activated carbon are carbon materials that can be equipped with strong acidic catalytic groups on their surface and as such have been synthesized with different pretreatment methods and applied in the synthesis of acetals (ketals) [27,28,29,30,31]. Hosseini M.S. [27] prepared a SulAmp-AC catalyst with the chemically attached sulfonic acid groups after surface modification with a suitable nitrogen-containing spacer group on AC; the conversion rate for benzaldehyde was 98% when the prepared SulAmp-AC used as catalyst. When propyl-SO3H functionalized graphene oxide (GO-PrSO3H) modified with (3-mercaptopropyl) trimethoxysilane and the thiol groups oxidized to surface -SO3H residues was used as catalyst, the conversion of benzaldehyde was 92% [28]. Yuan C. [29] synthesized sulfonic-acid-functionalized core-shell Fe3O4@carbon microspheres (Fe3O4@C-SO3H), and the conversion of benzaldehyde was 69% when it was used as a catalyst. Although the different carbon-based catalysts that have been studied exhibit good catalytic effects on synthesizing acetals (ketals), its poor reusability due to the leaching of surface-active functional groups [29,31] is still the main disadvantage of strong carbon-based solid catalysts. The exploration of methods for preparing stable carbon-based acid catalysts with excellent catalytic performance and stable functional groups was the focus of related research. In the preliminary work, our group successfully attached stable aminated groups on activated carbon with ethylenediamine [32]. Then, to explore carbon materials with strong and stable acidic functional groups, aminated activated carbon was treated through impregnation in aqueous sulfuric acid. The effects of preparation conditions on acidic functional group content on activated carbon surface were investigated. To study catalytic performance and the stability of acidic groups on the activated carbon surface, condensation of benzaldehyde with ethylene glycol was used as a probe reaction. The catalyst reusability and substrate suitability in synthesizing acetals (ketals) reactions were also studied. 2. Materials and Methods 2.1. AC-N-SO4H Preparation Activated carbon (AC) as a raw material was oxidized with HNO3 and aminated with ethanediamine. Details of the amination of AC leading to aminated activated carbon (AC-N) was previously reported [32]. The intermediate was treated with aqueous sulfuric acid to produce the catalyst denoted as AC-N-SO4H. The product was isolated by filtration and dried at 105 °C for 24 h. The scheme of AC-N-SO4H preparation is shown in Figure 1. 2.2. Sample Characterization The density of acid was measured with back titration method: 50 mg sample was added to 20 mL 0.01 mol/L NaOH and then sonicated for 30 min. After filtration and being washed with distilled water, groups on AC-N-SO4H were determined with 0.01 mol/L HCl using mixed bromocresol and green-methyl red as an indicator. FT-IR spectroscopy analysis was performed using Perkin Elmer 283 spectrometer (Perkin Elmer Instruments Co., Ltd., Waltham, MA, USA). The solid was mixed with KBr powder, and the mixture was pressed into pellets to conduct FT-IR analyses. The FT-IR spectra were recorded between 4000 and 400 cm−1 with a resolution of 4 cm−1 and acquisition rate of 20 scan·min−1. In order to analyze the thermal stability of the sample, NETZSCH STA 409 PC/PG (NETZSCH-Gerätebau GmbH, Selb, Germany) thermal gravimetric analyzer was used. The conditions were as follows: Under 10 °C/min heating rate, 20 mg sample was heated from room temperature to 800 °C under N2. Using TriStar 3000 surface area analyzer (Micromeritics Instrument Ltd., Atlanta, GA, USA), samples surface properties and surface area were characterized with N2 adsorption measurements at 77 K. The surface area (SBET) was calculated from isotherms using the Brunauer–Emmett–Teller (BET) equation. The volume of liquid nitrogen corresponding to the amount adsorbed at a relative pressure of P/P0 = 0.99 was defined as the total pore volume. 2.3. AC-N-SO4H Catalytic Properties on Synthesis of Acetals (Ketals) AC-N-SO4H catalytic properties on synthesis of acetal (ketal) reaction were tested. Generally, substrates with certain amounts of AC-N-SO4H were added to a three-necked flask, which was equipped with thermometer and condenser. The effects of reaction temperature, reaction time, catalyst dosage, and molar ratio of alcohol/aldehyde on conversion were investigated. The recycling performance and substrate suitability of AC-N-SO4H were also studied. Agilent 6890N gas chromatograph (Agilent Technologies Inc., Santa Clara, CA, USA) was used to quantitatively analyze the conversion of benzaldehyde and product selectivity. The analytical conditions were: toluene as the internal standard, SE-30 capillary column (Beijing Huarui Boyuan S&T development Co., Ltd., Beijing, China) (30 m × 0.25 mm × 0.25 μm), high-purity nitrogen as carrier gas with 1.0 mL/min flow rate, FID detector temperature 250 °C, injector temperature 250 °C, column pressure 0.6 MPa, injection volume 0.2 μL. The column temperature was temperature-programmed as: held for 3 min at 100 °C, then increased to 200 °C at a rate of 20 °C/min, and held for 1 min. 3. Results and Discussion 3.1. AC-N-SO4H Preparation The effects of HNO3 concentration in the oxidation process, reaction temperature in the amination process, and dilute aqueous sulfuric acid concentration in the acidification process on the amount of acid on the AC-N-SO4H surface were investigated. The typical impregnation procedure was as follows: 1 g of AC-N and 20 mL of 4 mol/L aqueous sulfuric acid were mixed in a beaker and stirred at room temperature for 4 h. After completion, the prepared solid was filtered and washed, then dried at 105 °C for 24 h to prepare AC-N-SO4H. The effects of preparation conditions are shown in Figure 2a–d. As shown, the density of -SO4H increased gradually with the initial increased concentration of nitric acid, but when the HNO3 concentration exceeded 12 mol/L, the density of -SO4H decreased rapidly to 0.5 mmol/L, which was attributed to the reduction of AC surface functionalizable structures due to strong oxidation process. With the increased temperature in amination process, the density of -SO4H gradually increased, which indicated that the increase of amination temperature had no destructive effect on AC surface structure as opposed to that of the HNO3 concentration. With the increased concentration of aqueous sulfuric acid and longer impregnation time, the density of -SO4H gradually increased. At a concentration of 4 mol/L and impregnation time of over 4 h, the density of -SO4H did not increase further. In summary, when the HNO3 concentration was 12 mol/L, the amination temperature was 120 °C, the dilute aqueous sulfuric acid concentration was 4 mol/L, and impregnation time was 4 h, the maximum density of -SO4H was 0.85 mmol/g. 3.2. AC-N-SO4H Structural Analysis 3.2.1. Specific Surface Area The standard BET equation was used to calculate the surface area of AC-N-SO4H and its precursor, AC-N. The nitrogen adsorption-desorption curves are shown in Figure 3. The N2 adsorption isotherms of the samples were belonged to the type IV class, which indicated the presence of a uniform mesoporous structure [32,33]. An upturned “tail” and obvious hysteresis loop are shown in both adsorption isotherms, indicating that AC-N and AC-N-SO4H had a mesoporous structure. Figure 4 shows the results of the pore size distribution measurements for the samples, which indicated that the impregnation process with aqueous H2SO4 did not destroy the mesoporous structure in AC-N. The porous structures of samples are shown in Table 1. According to Table 1, the BET surface area of AC-N-SO4H was 384 m2/g, only slightly lower than that of AC-N’s 418 m2/g, which illustrated that there were absolutely no detriments to the pore volume and pore size in the acidification process. 3.2.2. FT-IR FT-IR spectra of AC-N-SO4H and its precursor AC-N are shown in Figure 5. According to Figure 5, the strong absorption band around 3400 cm−1 corresponds to stretching of carboxylic O-H group. The broad absorption peak near 1200 cm−1 was the stretching vibration of groups containing single-bonded oxygen atoms or single-bonded nitrogen atoms, including phenolic hydroxyl groups, ether bonds, lactones, CN, -NH, -NH2, etc. The absorption peak that appeared at 1604 cm−1 was due to CN stretching vibration, and NH stretching vibration, which supposedly appeared at 3400 cm−1, almost overlapped with -OH stretching vibration. The FT-IR spectrum of AC-N-SO4H almost overlapped with that of AC-N, indicating that the treatment of aminated activated carbon impregnated with sulfuric acid did not destroy the N-containing structure on the AC-N surface. Combined with the analysis of the types and contents of functional groups on the surface of activated carbon, the hydrogen sulfate was successfully grafted on the aminated structure. 3.2.3. TG-DTG Thermogravimetric analysis was used to analyze the thermostability of AC-N-SO4H and its precursors; the results are displayed in Figure 6. As shown, there was an obvious weight loss peak near 92.6 °C, attributed to the removal of adsorbed water on AC-N-SO4H, which was slightly lower than the 98.7 °C of AC-N but significantly higher than the 78.3 °C of AC. The results illustrated that after aqueous sulfuric acid treatment, the hydrophilicity of AC-N-SO4H was slightly lower than that of AC-N but still much higher than that of activated carbon. Another obvious weight loss peak in AC-N-SO4H appeared at 270 °C, which was mainly due to the removal of N-containing structure immobilized with sulfuric acid on the surface of carbon materials, and was slightly lower than the removal temperature of the N-containing structure on the AC-N surface at 350 °C. This was mainly caused by the introduction of the electrophilic group -SO4H, which reduced the stability of the N-containing structure on carbon surface. In general, after sulfuric acid immersion treatment, the surface structure stability of activated carbon was slightly worse than that of aminated activated carbon. 3.3. AC-N-SO4H Catalytic Properties in Synthesis of Acetals (Ketals) The condensation of benzaldehyde with ethylene glycol was used as probe reaction to study the catalytic properties of AC-N-SO4H in the synthesis of acetals (ketals). The general procedure was as follows: 10 mL solvent cyclohexane, 25 mmol, benzaldehyde, 43.75 mmol ethylene glycol, and 0.13 g AC-N-SO4H were mixed in a three-necked flask equipped with a thermometer and reflux condenser and reacted 5 h at 80 °C. The effects of reaction temperature, reaction time, catalyst dosage, and molar ratio of glycol/benzaldehyde on benzaldehyde conversion were tested. At the same time, the catalytic recycling properties of AC-N-SO4H in reaction of benzaldehyde condensed with ethylene glycol and the applicability of different substrates were discussed. The reaction formula of benzaldehyde condensed with ethylene glycol is shown in Figure 7. 3.3.1. Effects of Reaction Conditions on Benzaldehyde Conversion To determine the catalytic properties of the prepared AC-N-SO4H, the effects of reaction temperature, reaction time, catalyst dosage, and the molar ratio of alcohol/aldehyde on benzaldehyde conversion were discussed. The test results are shown in Figure 8a–d. According to the results, with the increased reaction temperature, reaction time, and catalyst dosage, benzaldehyde conversion increased gradually until the reaction temperature reached 80 °C, the reaction time reached 5 h, and the catalyst dosage was 5% of the benzaldehyde mass. Under the above conditions, benzaldehyde conversion was above 99%. When the molar ratio of alcohol/aldehyde was lower than 1.75, benzaldehyde conversion gradually increased with the increase of ethylene alcohol. Benzaldehyde conversion decreased to a certain extent when the amount of ethylene glycol continued to increase. The main reason for the decreasing benzaldehyde conversion was that the concentration of benzaldehyde in the reaction system was reduced with the increasing amount of ethylene glycol, which caused a decrease in collisions between molecules. The selectivity of benzaldehyde glycol acetal was above 99% under all conditions, which indicated a competitive catalysis mechanism. 3.3.2. Performance of Reusability Finally, the stability of AC-N-SO4H was tested by performing a recycling experiment; the test results are presented in Figure 9. In the exploration of catalyst reusable performance, the catalyst AC-N-SO4H was washed with solvent cyclohexane and then put into the next reaction cycle. The specific process includes centrifuging out the solid after the reaction completed and washing the solid three times with cyclohexane to completely remove the small amount of residual liquid from the previous round of reaction on the surface. The performance of the catalyst showed no significant reduction even after ten successive runs, still achieving a 99% benzaldehyde conversion and 99% selectivity. Thus, AC-N-SO4H is an excellent and stable recyclable solid acid catalyst for the studied benzaldehyde ethylene glycol acetal reaction. 3.3.3. Comparison of Catalytic Efficiency with Reported Solid Acid Catalysts The catalytic efficiency of the prepared AC-N-SO4H and reported solid acid catalysts in benzaldehyde acetalization with ethylene glycol are briefly listed in Table 2. As can be seen, different kinds of solid catalysts and carbon-based solid acid catalysts modified by different methods for the reaction of benzaldehyde condensed with ethylene glycol achieved good efficiencies. Compared with the results, the AC-N-SO4H catalyst showed similar, sometimes even better catalytic performance under mild reaction conditions. Particularly, the prepared AC-N-SO4H catalyst had an advantage of good reusability, which was mainly due to the stable existence of strong acidic functional groups on activated carbon, which did not fall off in the reaction process. 3.3.4. Substrate Suitability The suitability of AC-N-SO4H for catalyzing synthesis of acetals (ketals) reactions with different substrates was investigated. The catalytic effects of AC-N-SO4H on ethylene glycol, propylene glycol, butylene glycol, chain aldehydes (ketones), cyclic aldehydes (ketones), and branched o-hydroxybenzaldehyde were investigated. The results are shown in Table 3: AC-N-SO4H demonstrated excellent catalytic performance on different alcohols both in chain and cyclic aldehydes (ketones). Only the conversions of salicylaldehyde with different alcohols were less than 70%, which may be due to its steric hindrance. 4. Conclusions (1) With activated carbon as the raw material, a strong and stable carbon-based solid acid catalyst with hydrogen sulfate AC-N-SO4H with a surface acid content of 0.85 mmol/g was prepared after oxidation with HNO3, amination with ethylenediamine, and acidification with dilute aqueous sulfuric acid. The structural analysis showed that the specific surface area of AC-N-SO4H was almost the same as that of AC-N while preserving surface-active functional groups. The N-containing structure on AC-N surface was not damaged after impregnation with aqueous sulfuric acid. However, the thermal stability of the activated carbon surface structure was slightly lower than that of aminated activated carbon AC-N after sulfuric acid impregnation for introduction of the electrophilic group -SO4H. (2) As a catalyst, AC-N-SO4H demonstrated excellent performance in synthesis of acetals (ketals) reactions. In the catalytic condensation of benzaldehyde with ethylene glycol, the conversion of benzaldehyde and the selectivity of benzaldehyde glycol acetal were both above 99%. The performance of the catalyst showed no significant reduction even after ten successive runs, still achieving a 99% benzaldehyde conversion yield and 99% benzaldehyde glycol acetal selectivity. At the same time, AC-N-SO4H showed excellent catalytic properties in the study of substrate applicability for the condensation reaction of ethylene glycol, propylene glycol, and butylene glycol with different chain and cyclic aldehydes (ketones), which indicated the excellent application prospects of AC-N-SO4H as a solid acid catalyst. (3) The excellent catalytic properties of AC-N-SO4H in synthesis of acetals (ketals) can be attributed to its strong acidic functional groups and good stability. This provides a novel method for preparing carbon materials with stable strong acidic functional groups on surface. The detailed structure of the modified activated carbon surface and its catalytic mechanism still need to be further explored. Author Contributions Conceptualization, W.L. and D.Y.; data curation, W.L.; formal analysis, D.Y.; funding acquisition, D.Y.; investigation, W.L.; methodology, W.L. and R.G.; project administration, D.Y.; resources, D.Y.; software, W.L. and R.G.; supervision, G.P. and D.Y.; validation, R.G. and G.P.; visualization, R.G. and G.P.; writing—original draft, W.L.; writing—review and editing, W.L., R.G. and D.Y. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the research foundation of Education Bureau of Hunan Province, China, grant number 20B459; the Natural Science Foundation of Hunan Province, China, grant number 2021JJ40430; the National Natural Science Foundation of China, grant number 21776068; the Scientific Research Project of Huaihua University, grant number HHUY2020-08. 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 Scheme of preparing AC-N-SO4H. Figure 2 Effect of the preparation of AC-N-SO4H on the density of -SO4H. (a) HNO3 concentration; (b) amination temperature; (c) H2SO4 concentration; (d) impregnation time. Figure 3 N2 adsorption–desorption isotherms for AC-N and AC-N-SO4H. Figure 4 Pore size distribution for AC-N and AC-N-SO4H. Figure 5 FT-IR spectrum of AC-N-SO4H and AC-N. Figure 6 TG and DTG performance of AC-N-SO4H and its precursors. (a) TG; (b) DTG. Figure 7 Reaction of benzaldehyde condensed with ethylene glycol. Figure 8 Effect of reaction conditions on benzaldehyde conversion. (a) Reaction temperature; (b) reaction time; (c) catalyst dosage; (d) molar ratio of glycol/benzaldehyde. Figure 9 Recycling performance of AC-N-SO4H in benzaldehyde condensed with ethylene glycol. Note: Reaction conditions: 10 mL cyclohexane; 25 mmol benzaldehyde; molar ratio of ethylene glycol/benzaldehyde, 1.75; 0.13 g AC-N-SO4H; reaction temperature, 80 °C; reaction time, 5 h. nanomaterials-12-01462-t001_Table 1 Table 1 BET surface area of AC-N and AC-N-SO4H. Sample BET/m2·g−1 Pore Volume/cm3·g−1 Pore Size/nm AC-N 418 0.26 2.5 AC-N-SO4H 384 0.23 2.5 nanomaterials-12-01462-t002_Table 2 Table 2 Comparison of the catalytic efficiency of the prepared AC-N-SO4H catalyst with various reported solid acid catalysts in synthesizing benzaldehyde ethylene glycol acetal. Entry Solid Acid Catalyst Catalyst Amount (wt.%) Benzaldehyde: Ethylene Glycol Time (h) Temp. (°C) Conv. in the First Cycle (%) Sel. (%) Reaction Cycle Conv. in the Last Cycle (%) Ref. 1 AC-N-SO4H 5 1:1.75 5 80 99 100 10 99 This study 2 SulAmp-AC 3 1:3 3 90 98 - 4 92 [27] 3 GO-PrSO3H 3 1:3 3 90 92 - 5 80 [28] 4 Fe3O4@C-SO3H 1.3 1:1 2 90 69 97 9 63 [29] 5 SO3H/NCF-600 1.9 1:5 1 90 99 - 5 99 [30] 6 SG-[(CH2)3SO3H-HIM]HSO4 8.2 1:1.8 1.5 110 95 - 10 90 [31] 7 SulAmp-GO 3 1:3 3 90 86 - - - [27] 8 CeFeTiO 6.9 1:1.6 3 110 97 - - - [7] 9 [PPSH]2HPW12O40 5 1:1.8 3 reflux 85 - - - [11] 10 HMQ-STW 7 1:3 1 105 96 100 5 90 [13] nanomaterials-12-01462-t003_Table 3 Table 3 Conversion of acetals (ketals) reactions with different substrates catalyzed by AC-N-SO4H. Raw Materials Conv. (%) Alcohol Aldehydes (Ketones) Glycol 2-Pentanone 99.20 Glycol Cyclohexanone 98.90 Glycol Butanal 99.12 Glycol 2-Furaldehyde 96.00 Glycol Salicylaldehyde 67.31 1,2-Propanediol 2-Pentanone 99.30 1,2-Propanediol Cyclohexanone 99.12 1,2-Propanediol Butanal 99.10 1,2-Propanediol 2-Furaldehyde 96.55 1,2-Propanediol Salicylaldehyde 66.28 Butane-1,2-diol 2-Pentanone 97.26 Butane-1,2-diol Cyclohexanone 98.09 Butane-1,2-diol Butanal 98.73 Butane-1,2-diol 2-Furaldehyde 90.50 Butane-1,2-diol Salicylaldehyde 63.25 Note: Reaction conditions: 10 mL cyclohexane; 25 mmol aldehyde (ketone); 43.75 mmol alcohol; AC-N-SO4H accounted for 5% of aldehyde (ketone) mass; reflux temperature, 5 h. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Maki Y. Nomura K. Okamoto R. Izumi M. Mizutani Y. Kajihara Y. Acceleration and deceleration factors on the hydrolysis reaction of 4, 6-O-Benzylidene acetal group J. Org. 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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091148 animals-12-01148 Article Nesting Site and Plumage Color Are the Main Traits Associated with Bird Species Presence in Urban Areas Leveau Lucas M. * Ibáñez Isis Morales Manuel B. Academic Editor Departamento de Ecología, Genética y Evolución, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires—IEGEBA (CONICET—UBA), Ciudad Universitaria, Pab 2, Piso 4, Buenos Aires 1426, Argentina; isisagostina97@gmail.com * Correspondence: lucasleveau@yahoo.com.ar; Tel.: +54-11-5285-7400 29 4 2022 5 2022 12 9 114808 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/). Simple Summary Urban areas are expected to grow in the next decades, filtering bird species from the regional pool based on their life history traits. The objective of this study is to determine different bird species responses to urbanization using ordination analysis, and to characterize their life history traits combining information about diet, habitat and plumage color. Species identified as ‘urban exploiters’ tended to nest in buildings and with uniform plumage, whereas those identified as ‘urban avoiders’ tended to be ground nesting species with variable plumage. A third type, ‘urban adapters’, tended to be tree-nesting species with a low diet breadth, intermediate plumage lightness, low presence of plumage sexual dimorphism and high presence of iridescence. The results suggest that nest predation and habitat loss may exclude ground nesting birds from urban areas. The high density of pedestrians in urban centers may favor uniform plumages in birds that enhance camouflage. Abstract Urban areas are expected to grow in the next decades, filtering bird species from the regional pool based on their life history traits. Although the impact of urbanization on traits such as diet, habitat and migratory behavior has been analyzed, their joint role with other traits related to plumage color has not yet been analyzed. Urban characteristics such as impervious surfaces, human presence and pollutants may be related to dark and uniform plumages. The objective of this study is to determine different bird species responses to urbanization using ordination analysis, and to characterize their life history traits combining information about diet, habitat and plumage color. Birds were surveyed along urban–rural gradients located in three cities of central Argentina. Species associations with urban characteristics were assessed through principal component analysis. Two axes were obtained: the first related positively to urban exploiters and negatively to urban avoiders, and a second axis related negatively to urban adapters. The scores of each axis were related to species traits through phylogenetic generalized least squares models. Species identified as ‘urban exploiters’ tended to nest in buildings and have uniform plumage, whereas those identified as ‘urban avoiders’ tended to be ground-nesting species with variable plumage. A third type, ‘urban adapters’, tended to be tree-nesting species with a low diet breadth, intermediate plumage lightness, low presence of plumage sexual dimorphism and high presence of iridescence. The results suggest that nest predation and habitat loss may exclude ground nesting birds from urban areas. The high density of pedestrians and domestic animals, such as cats and dogs, in urban centers may favor uniform plumages in birds that enhance camouflage. avian functional traits Latin America ordination analysis phylogenetics urban ecology Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la InnovaciónPICT 2018-03871 This research was funded by the Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación, PICT 2018-03871. ==== Body pmc1. Introduction Urbanization is expected to increase globally [1], impacting negatively on bird communities through habitat loss and fragmentation, pollution, and species invasions [2,3,4,5]. Several studies have shown that bird species composition in urban areas are molded by a filtering from the regional species pool surrounding the city [6,7,8,9,10,11]. The urban filter imposed on birds is linked to many bird life-history traits [12]. Bird species with varied diets and habitat use have been associated with urban areas [13,14,15,16,17,18,19]. Nesting site has also been strongly associated with bird responses to urbanization. Ground or shrub nesting bird species were negatively related to urban areas [6,16,18,20,21,22,23,24,25], whereas species that nest in buildings or rocks were favored by urbanization [21,25,26,27]. Migrant species have been negatively associated with urban areas [21,26,28], but see [18]. Gregarious foraging behavior has been positively associated with urban bird species [18,26,28]. Species with large body mass and clutch sizes seem to be favored by urbanization [6,18,29], but see [24,30]. Recently, plumage color was proposed as another life history trait associated with bird species presence in urban areas [29,31]. Bird color diversity was lower than expected by chance in urban centers of central Argentina, suggesting that plumage color was filtered by urbanization, favoring species with grey plumage [29]. Grey plumage may be favored in highly urbanized areas due to presence of the impervious surfaces of roads and buildings. In addition, sexual plumage dimorphism has been negatively related to bird species presence in urban areas [6,31], but see [26]. This lack of sexual dimorphism in urban areas could be related to more energy being invested in adaptations to survive in new environments. Therefore, birds could be avoiding predation or fighting infections, instead of allocating energy to sexual selection [6,31]. However, the joint role of plumage color and other traits such as diet, habitat or residency status leading to bird presence in urban areas has not been analyzed yet. This information is fundamental to understand and predict how urbanization will affect bird communities. The relationship between bird plumage color and environmental gradients has been analyzed by measuring plumage lightness [32,33,34], which varies between light and dark. At large scales, dark plumages are predominant in humid regions and with high tree cover [33,34], which probably favor camouflage and parasite resistance. However, the impact of land use change on plumage lightness has not been assessed yet. Highly urbanized areas dominated by impervious surfaces could favor melanic bird plumages, which may improve camouflage and parasites resistance [35]. In addition, the analysis of intraspecific variation of plumage lightness could bring new insights about urbanization effects on bird species. Intraspecific plumage variation of lightness, such as the presence of bright plumage patches, may indicate both intra and interspecific communication [36,37]. In contrast, uniform plumage lightness may favor camouflage. For example, Stevens et al. [38] found that ground nesting birds with the lowest plumage color contrast with their background habitat had increased survival. In cities, uniformly grey plumage might help camouflage on asphalted impervious surfaces, whereas uniformly green plumage may favor camouflage on vegetation. Camouflage in urban environments is relevant due to the high pedestrian traffic, whose presence may be analogous to predation risk to birds [39,40]. The presence of dogs and cats in highly urbanized areas may also increase the perceived predation risk by birds [41]. Nevertheless, the relationship between intraspecific plumage variation and urbanization has not been analyzed yet. Most studies analyzing which traits were related to species presence in urban areas have used the classification of Blair [42], which grouped species according to three categories: (1) urban exploiters, which have their maximum densities in highly urbanized areas; (2) urban adapters, which have their maximum densities in moderately urbanized areas; and (3) urban avoiders, which only thrive in rural or natural areas. Several authors have compared bird traits in urban exploiters/adapter versus urban avoiders [6,14,16,19,22], urban exploiters versus urban adapters [26] or urban versus rural species [43]. Other studies ordered species in a continuous dimension based on their densities in urban areas and the ratio between urban and rural densities [15] or the median radiance, a proxy of artificial light at night, occupied by each species [18]. The present study proposes to ordinate species in a multivariate space based on multiple urbanization measures, such as impervious cover composed of asphalted roads and buildings, habitat diversity and primary productivity. The use of these environmental variables could help to analyze simultaneously life history traits associated with exploiters, adapters and avoiders. The objective of this study was to determine different species responses to urbanization in the Pampean region of central Argentina using ordination analysis. In addition, species responses to urbanization were related to their life history traits combining information about diet, habitat and plumage color. Urban exploiters are expected to be gregarious species, nesting in buildings, with large clutch sizes and broad diet and habitat use. Moreover, they are also expected to have dark, uniform plumage and an absence of plumage sexual dimorphism. Urban adapter species are expected to nest in trees [28], due to the tree availability in moderately urbanized areas. Urban avoiders are expected to nest on the ground due to the open habitats in rural areas, which have patches of grasslands that provide habitat for ground-nesting birds [28]. Finally, the open habitat of rural areas may favor light plumage that increases intraspecific communication in birds [44]. 2. Material and Methods 2.1. Study Area The research was conducted in three cities located in central Argentina: Mar del Plata (38°00′ S, 57°33′ W; 38 m.a.s.l.; 615,350 inhabitants), Balcarce (37°50′ S, 58°15′ W; 112 m.a.s.l.; 38,823 inhabitants), and Miramar (38°16′ S, 57°50′ W; 17 m.a.s.l.; 29,629 inhabitants, 2010 National census) (see [45]). The three cities are surrounded by the Austral Pampas, consisting mainly of grazing land, cropland, and exotic tree plantations. The climate is temperate, with a mean annual precipitation of 923.6 mm and a mean annual temperature of 14 °C (data from the National Meteorological Service, www.smn.org.ar, accessed on 15 January 2019). Because the maximum distance between the cities was 59 km, effects of latitude or climate were deemed negligible. 2.2. Bird Surveys Bird surveys were conducted in three habitat types: (1) urban centers; (2) suburban areas composed of detached houses with gardens; and (3) rural areas, composed of crops and pastures (see [45] for details). Five transects of 100 × 50 m separated by at least 200 m were surveyed in each habitat type and city, totaling 45 transects. Birds were surveyed by walking in a straight line mid-transect for three to five minutes and recording bird songs or sightings on both sides of the transects (25 m each). Two visits were made during the breeding season (austral spring-summer 2011–2012) and two visits during the breeding season 2012–2013, totaling four visits to each transect. Surveys were made during the first 4 h after dawn on days without rain or strong winds. All birds seen or heard that used the space within the transect for perching, walking or foraging were counted, except for those flying over the top of buildings or trees or below that height but without feeding activity. 2.3. Environmental Characteristics Eight variables were measured in each transect: (1) impervious cover, (2) pedestrian traffic, (3) car traffic, (4) motorcycle traffic, (5) bicycle traffic, (6) minimum distance to rural areas, (7) habitat diversity and (8) primary productivity. Impervious cover and habitat diversity were measured visually by two 25 m radius circles, one in the center of the first 50 m along transects and the other in the center of the remaining 50 m (see [45] for more details). Impervious cover was characterized by the mean percent building and pavement cover of the two circles in each transect. Habitat diversity was calculated as the mean Shannon index of the two circles in each transect, incorporating the percent cover of trees, shrubs, lawn, herbaceous vegetation, cultivated land and buildings. Pedestrian, car, motorcycle and bicycle traffic were measured during three minutes simultaneously to bird surveys. Therefore, the mean values of the four visits were calculated for each transect. Minimum distance to rural areas was measured for each transect with Google Earth Pro. Finally, primary productivity was estimated using the Normalized Difference Vegetation Index (NDVI), which is a measure of greenness that correlates positively with net primary productivity [46,47] and is assumed to correlate positively with production of food available to birds [48]. NDVI for each transect was calculated as the mean value obtained of four images of the MOD13Q1 product [49], which correspond to the four visits to each transect (see [45] for more details). 2.4. Bird Species Urbanness The species use of urban habitats, or species urbanness, was calculated by ordering bird species according to environmental characteristics of the transects they occupied along the urban–rural gradients. Therefore, the median value of the eight environmental characteristics was calculated for each species (see [18]). A matrix of bird species as rows and environmental characteristics as columns was used to perform a principal components analysis (PCA) with the rda function of the vegan package in R version 3.6.1 [50,51]. PCA reduces a matrix of variables in a few axes through linear combinations [52]. Only those axes with eigenvalues greater than 1 were considered [53]. Axes were characterized according to their relation to environmental variables. The principal component score values for each bird species were used as the urbanness score. 2.5. Life History Traits Life history traits of species were characterized by eleven traits (Table S1): (1) diet breadth, (2) habitat breadth, (3) body mass (g), (4) clutch size, (5) migratory status, (6) nesting site, (7) gregariousness, (8) plumage mean lightness, (9) plumage lightness variation, (10) iridescent plumage presence, and (11) sexual plumage dimorphism presence. Diet breadth, habitat breadth and body mass were obtained from the data provided in the Elton Traits 1.0 database [54], which contains the percentage use of different food and foraging substrates by each species. Food items included invertebrates, endothermic vertebrates, ectothermic vertebrates, fish, carrion, fruit, nectar, seed and other plant material. Foraging substrate included below water surface, around water surface, ground, understorey, medium-high stratum, canopy and air. Diet and habitat breadth were calculated using Rao’s quadratic entropy BD [19,55] using the nichevar function of the indicspecies package [56]. The Rao’s index varies between 0, indicating the use of only one food item or substrate, and 1, indicating the highest variety of food items or substrates. Clutch size was obtained from the Handbook of the Birds of the World (HBW) online (https://www.hbw.com/, accessed on 15 January 2019). The residency status of species was classified as resident or migratory, based on Narosky and Di Giacomo [57]. Nesting site was classified as ground or shrub, tree, and building based on de la Peña [58]. Brood parasites were included in tree nesting because the two parasite species, the Shiny Cowbird (Molothrus bonariensis) and the Screaming Cowbird (Molothrus rufoaxillaris), use mainly host species that nest in trees in the study area (L.M. Leveau, pers. Obs.). Gregariousness was considered as foraging or roosting in groups and based on de la Peña [59] and personal observations. Plumage lightness and the variation of plumage lightness were quantified using Red-Green-Blue (RGB) values obtained from plates of the HBW online database (https://www.hbw.com/, accessed on 7 May 2020) (see also [27]). Plates were captured in .png archives, and opened in ImageJ [60]. Then, lightness was computed as (R + G + B)/3, which varies between 0 (pure black) and 255 (pure white). Lightness values were obtained from the head/crown, throat, breast, belly, coverts, primaries, nape/back, and tail in a similar way to Dale et al. [27]. Therefore, these values were averaged to obtain plumage lightness for each species. The plumage lightness variation was calculated as the coefficient of variation of lightness for all the plumage patches. In the case of sexual plumage dimorphic species, only male plumage was measured. Although males in sexual dimorphic species are darker than females, there is a positive correlation of plumage lightness between sexes within species [33]. Presence of iridescent plumage and sexual dimorphism were obtained from the Aves Argentinas cellphone app [61]. 2.6. Statistical Analysis The response to urbanization might be influenced by phylogenetic relatedness between species. Therefore, a phylogenetic generalized least squares model (PGLS) was performed to relate our response variables, the PCA species scores, with the predictor life history traits, using the gls function of the nlme package [62]. A dated phylogeny of all species in this study was created using the BirdTree database [63] (Jetz et al. 2014) and incorporated into the analysis. A total of 1000 phylogenies were downloaded from the Ericsson backbone phylogeny [64]. A 50% majority-rule consensus tree was constructed using the software TreeAnnotator [65]. The phylogeny was added as a correlation structure with a Brownian motion process of evolution on the tree, using the corBrownian function of the ape package [66]. The tree was used in R with the functions read.nexus and as.phylo of the ape package [66]. Model selection was performed through a backward elimination of non-significant variables (p > 0.05) from the whole model that included all predictors. A quadratic relationship was included in the model to explore non-linear relationships between plumage lightness and bird species urbanness. The non-significant variables were excluded using Likelihood ratio tests (LRT) (p > 0.05). Pseudo-R2 of models were calculated using the McFadden [67] formula: Pseudo-R2 = 1 − (Residual deviance/Null Deviance). Models were plotted using the visreg package [68]. 3. Results A total of 54 species were analyzed (Table S1). The ordination analysis showed two main axes of bird species urbanness (Table 1, Figure 1 and Figure S1). The first principal component (PC1) was positively related to urban conditions, such as impervious cover, vehicle and pedestrian traffic and distance to rural areas (Table 1). Bird species positively related to PC1 were known urban exploiters, such as the Rock Dove (Columba livia), the Eared Dove (Zenaida auriculata) and the House Sparrow (Passer domesticus) (Figure 1 and Figure S1, Table S2). In contrast, the PC1 was negatively related to NDVI, a proxy of primary productivity, and to urban avoiders such as the Rufous-collared Sparrow (Zonotrichia capensis) and the Grassland Yellow-Finch (Sicalis luteola). The second axis (PC2) was negatively related to habitat diversity, and therefore, urban adapter species such as the White-throated Hummingbird (Leucochloris albicollis) and the Small-billed Elaenia (Elaenia parvirostris) tended to have negative scores (Table 1 and Table S2, Figure 1 and Figure S1). The final model of PC1 score values included nesting site, habitat breadth and plumage lightness variation (LRT = 26.57, p < 0.001, pseudo-r2 = 0.23; Table 2). Positive scores were related to species that nest in buildings, whereas negative scores were related to species that nest on the ground and on trees (Figure 2a). Therefore, urban exploiters mainly nested on buildings, whereas urban avoiders nested on the ground. PC1 species scores tended to decrease with increasing habitat breadth (Figure 2b). Thus, urban exploiters used a lower variety of vegetation strata than urban avoiders. Plumage lightness variation increased with decreasing PC1 score values (Figure 2c). Therefore, urban exploiters had uniform plumage lightness, whereas urban avoiders had more variable plumage lightness. The final model for PC2 species score values included nesting site, diet breadth, plumage lightness, dimorphism presence and iridescence presence (LRT = 43.25, p < 0.001, pseudo-r2 = 0.31; Table 2). Negative scores were related to species that nest in trees (Figure 3a). Therefore, urban adapters were associated with species that nest in trees. Positive PC2 score values were associated with species that nest in buildings and on the ground and corresponding to urban exploiters and avoiders (Figure 3a). PC2 scores increased with diet breadth, indicating that urban adapters had low diet breadth (Figure 3b). Negative PC2 score values had intermediate plumage lightness, whereas positive PC2 score values had both the lowest and the highest plumage lightness (Figure 3c). Therefore, urban adapters had intermediate plumage lightness, whereas urban exploiters and avoiders had both dark and bright plumages. Negative PC2 values were associated with the absence of conspicuous plumage sexual dimorphism and the presence of plumage iridescence (Figure 3d,e). Thus, urban adapters had a lower plumage sexual dimorphism but a higher iridescence than exploiters and avoiders. 4. Discussion The results obtained showed that nesting site, diet, habitat use, and plumage characteristics are associated with different bird responses to urbanization. The use of ordination analysis allowed obtaining three types of bird responses to urbanization, which coincided with the exploiter-adapter-avoider classification [42]. Urban avoider species were characterized by nesting on the ground and with variable plumage lightness, whereas urban exploiters were characterized by nesting on buildings and uniform plumage colors. Urban adapters were characterized by nesting in trees, specialized diets, intermediate plumage lightness, low presence of sexual plumage dimorphism and tended to have a high presence of plumage iridescence. Nesting site seems to be the main driver of species responses to urbanization, and ground nesting species were most negatively related to urbanization. This result agrees with the majority of studies analyzing avian species responses to urbanization [12]. Bird species nesting on the ground may suffer from habitat loss in urban areas, as they need natural herbaceous vegetation to nest [58], and this type of vegetation is replaced by lawn [45]. Nest predation and human disturbance in urban areas can also negatively affect ground nesting birds [69,70]. In contrast, bird species that nest in buildings or rocks are obviously favored by the availability of nesting sites in urban areas. Intermediate levels of urbanization consisting of yards with trees may be especially favorable for urban adapter species that nest in trees. Habitat breadth tended to be lower in urban exploiters than in urban avoiders. This result is in line with the foraging behavior of several urban exploiters, such as the Rock Dove or the House Sparrow, which mostly search food on the ground. Urban exploiters were characterized by uniform plumage lightness, whereas avoiders had the highest plumage lightness variation. Low plumage lightness variation in urban exploiter species may favor species camouflage [29], as species with uniform plumage color can be less easily detected by humans or other predators [38,71]. Conversely, plumage lightness variation in urban avoiders may favor intra and interspecific communication by increasing conspicuousness [72,73,74]. In this study, urban avoider species such as the Fork-tailed Flycatcher (Tyrannus savana) and the Double-collared Seedeater (Sporophila caerulescens) had dark plumage in their dorsal parts, which probably enhances camouflage for protection from predators attacking from above or behind [38], whereas their light ventral plumage can enhance conspicuous signaling [73]. Urban adapters were related to diet specialization. Several urban adapter species, such as the White-throated Hummingbird and the Small-billed Elaenia specialize on one food type, nectar and invertebrates, respectively [54]. The results obtained contrast with other analyses made at global scale [19] and in Australia [18], which found a higher diet breadth in urban exploiters and adapters than in urban avoiders. Differences between studies may be related to the method used to classify bird species responses to urbanization. Palacio [19] used a binary exploiter/avoider classification, whereas Callaghan et al. [18] used a continuous index of bird species urbanization. Conversely, this study used an ordination method that enabled the classification of species in two dimensions, one that characterizes the exploiter/avoider continuum, and another dimension that characterizes urban adapters. Plumage sexual dimorphism was negatively related to urban adapter species. This result agrees with those found by Croci et al. [6] and Iglesias-Carrasco et al. [31]. These authors proposed that urban exploiter and adapter species invest more energy in adaptations to survive in new environments, such as avoiding predation or fighting infections, instead of allocating energy to plumage development and maintenance that are related to sexual selection. However, the results obtained in this study did not find a low plumage sexual dimorphism presence in urban exploiters. Therefore, species present in highly urbanized areas may still allocate energy to plumage development and maintenance related to sexual selection due to relaxed predation or abundant food resources. On the other hand, the presence of iridescent plumage tended to be higher in urban adapters than in urban exploiters and avoiders. Iridescence has been associated with courtship displays [75], which can be performed in precise moments when bathed directly in sunlight [76]. These courtship displays avoid unnecessary exposure to predators in urban environments, such as cats and raptors. Urban adapter species were associated with intermediate plumage lightness, whereas the opposed side of the ordination consisting of urban exploiters and avoiders had extreme values of plumage lightness. It is probable that the semi-open habitat structure of suburban areas favors intermediate plumage lightness for enhancing camouflage. On the other hand, light plumage in urban avoiders, such as the White-tailed Kite (Elanus leucurus), may favor light reflectance and communication in open areas [44,77]. Urban avoiders also had predominantly dark plumages, as in the case of the Spectacled Tyrant (Hymenops perspicillata) and the Yellow-winged Blackbird (Agelasticus thilius). However, these species had small patches with bright colors in their wings, which may have a function for intraspecific communication. Unlike other studies [6,18,21,26,28,29], the results obtained failed to find significant relationships between migratory status, clutch size, body size, flocking behavior and bird species urbanness. These contrasting results may be related to several factors, such as the methods used to classify bird species urbanness, the use of bird abundance or presence/absence data, the statistical approach and the spatial scale of analysis. For example, Callaghan et al. [18] found that certain traits, such as diet generalism, changed their relationship with bird urbanness depending on whether phylogenetic modelling was used or not. In addition, the methods used to classify bird urbanness varied from dichotomic categories [6,19,23,31] to continuous indices of bird urbanness on a single axis of impervious cover [18]. This study used a continuous index that ordered bird responses in multiple axes, considering simultaneously exploiters, adapters and avoiders. Finally, Kinnunen et al. [78] found that city characteristics such as compactness and socioeconomics variables, not considered in the present study, can be related to bird life history traits. 5. Conclusions This study analyzed the relationship between bird species urbanness and traits such as diet, habitat and plumage color. Nesting site was strongly associated with bird species urbanness, with bird species nesting preferentially in buildings in highly urbanized areas, whereas species present in suburban areas nested mostly in trees. In contrast, bird species in rural areas nested mainly on the ground. Bird species present in highly urbanized areas had a uniform plumage color, suggesting a role of camouflage with the impervious surfaces. In contrast, bird species in non-urban areas had more contrast in their plumage patches, suggesting a role in intra and interspecific communication. The results obtained highlight the importance of considering plumage color when analyzing urbanization filters on bird species. Moreover, this analysis used an ordination method to classify species responses to urbanization, allowing characterization of traits of exploiters, adapters and avoiders. However, this study did not consider several traits, such as brain size, feeding innovation or song frequency, which has been associated with bird species responses to urbanization [16,23,43,79]. Therefore, future analyses that incorporate plumage color, song frequency and feeding innovations are necessary to obtain a more complete idea of how urbanization filters bird species. Acknowledgments The comments made by two anonymous reviewers greatly improved a first draft of the manuscript. The English writing was revised by Paloma Garcia Orza. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ani12091148/s1, Figure S1: Biplot with the results of the principal component analysis showing the relationships between species and environmental variables. NDVI: Normalized Difference Vegetation Index, H: habitat diversity (Shannon index), Dist_rur: minimum distance to rural areas; Table S1: Life history traits of species observed along the urban-rural gradients of central Argentina. Light_mean: mean plumage lightness between plumage patches, Light_cv: coefficient of variation of plumage lightness between plumage patches, Diet_var: diet breadth, Habitat_var: habitat breadth, Dimorph: presence of sexual plumage dimorphism; Table S2: Species scores of the first and the second principal components analyzing the relationship between environmental variables of species. See more details in Methods. Click here for additional data file. Author Contributions L.M.L. contributed to the study conception and design. Material preparation, data collection and analysis were performed by L.M.L. and I.I. The first draft of the manuscript was written by L.M.L. and I.I. commented on previous versions of 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 datasets generated during and/or analysed during the current study are available upon request to the corresponding author. Conflicts of Interest The authors have no relevant financial or non-financial interest to disclose. Figure 1 Schematic representation of the ordination of bird species and environmental variables. Urbanization includes the median impervious cover, vehicle and pedestrian traffic, and distance to rural areas for the records of each species. Primary productivity is the median NDVI value for the records of each species. Habitat diversity is the median Shannon index calculated with percent cover of vegetation strata and building cover. Figure 2 Relationship between the first principal component score values (PC1) of bird species and (a) nesting site, (b) habitat breadth, and (c) the intraspecific coefficient of variation (CV) of plumage lightness. Positive PC1 score values are related to urban exploiters, whereas negative values are related to urban avoiders. In (a) lines indicate mean values, whereas in (b,c) the lines indicate the fit of the phylogenetic generalized least square model. Figure 3 Relationship between the second principal component score values (PC2) of bird species and (a) nesting site, (b) diet breadth, (c) mean plumage lightness, (d) plumage dimorphism presence and (e) the presence of plumage iridescence. Negative PC2 score values are related to urban adapters. In (a,d,e) lines indicate mean values, whereas in (b,c) lines indicate the fit of the phylogenetic generalized least square model. animals-12-01148-t001_Table 1 Table 1 Results of the principal component analysis (PCA) between species and their median values of the environmental variables. Numbers are loadings between each environmental variable and the first and second principal components (PC1 and PC2, respectively). Environmental Variables PC1 PC2 Impervious cover (%) 0.95 −0.15 Primary productivity (NDVI) −0.94 0.06 Habitat diversity (H index) 0.23 −0.95 Car traffic 0.75 0.25 Pedestrian traffic 0.87 0.19 Bicycle traffic 0.84 0.07 Motorcycle traffic 0.73 0.14 Minimum distance to rural areas (m) 0.86 −0.11 Eigenvalues 5.12 1.07 Proportion of variance explained 0.64 0.13 animals-12-01148-t002_Table 2 Table 2 Final phylogenetic generalized least square models showing the relationship between (a) the first principal component species scores (PC1), (b) the PC2 and life history traits along urban-rural gradients of central Argentina. Nest in building, dimorphism absence and iridescence absence are included in the intercept. Value Std. Error t-Value p-Value (a) PC1 Intercept 1.325 0.614 2.158 0.036 Nest—ground −1.359 0.303 −4.490 <0.001 Nest—tree −0.765 0.265 −2.888 0.006 Habitat breadth −0.880 0.460 −1.914 0.062 CV of plumage lightness −1.429 0.490 −2.916 0.005 (b) PC2 Intercept 3.129 1.192 2.625 0.012 Nest—ground −0.307 0.414 −0.740 0.463 Nest—tree −0.921 0.370 −2.488 0.017 Diet breadth 1.579 0.692 2.282 0.027 Mean plumage lightness −0.052 0.016 −3.212 0.002 Mean plumage lightness2 <0.001 <0.001 2.935 0.005 Plumage dimorphism—presence 0.503 0.188 2.681 0.010 Iridescence—presence −0.452 0.231 −1.954 0.057 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. United Nations The World’s Cities in 2018 Department of Economic and Social, Affairs, United Nations New York, NY, USA 2018 2. Grimm N.B. Faeth S.H. Golubiewski N.E. Redman C.L. Wu J. Bai X. Briggs J.M. 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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/ijerph19095007 ijerph-19-05007 Article Obstructive Sleep Apnoea Severity Is Negatively Associated with Depressive Symptoms: A Cross-Sectional Survey of Outpatients with Suspected Obstructive Sleep Apnoea in Japan https://orcid.org/0000-0002-0261-1003 Ito Kazuki 1 Uetsu Masahiro 2 https://orcid.org/0000-0003-4966-6703 Ubara Ayaka 345 Matsuda Arichika 3 https://orcid.org/0000-0001-6775-0883 Sumi Yukiyoshi 3 https://orcid.org/0000-0001-7474-3315 Kadotani Hiroshi 23* Curcio Giuseppe Academic Editor 1 Department of Anesthesiology, Shiga University of Medical Science, Seta-Tsukinowa-Cho, Otsu 520-2192, Japan; sphk96z9@gmail.com 2 Sleep Outpatient Unit for Sleep Apnea Syndrome, Nagahama City Hospital, 313 Ohinui-Cho, Nagahama 526-0043, Japan; mauetsu@yahoo.co.jp 3 Department of Psychiatry, Shiga University of Medical Science, Seta-Tsukinowa-Cho, Otsu 520-2192, Japan; uba.a.1229@gmail.com (A.U.); arichika@belle.shiga-med.ac.jp (A.M.); ysumi@belle.shiga-med.ac.jp (Y.S.) 4 Graduate School of Psychology, Doshisha University, Kyoto 610-0394, Japan 5 Japan Society for the Promotion of Science, Research Fellowships, Tokyo 102-0083, Japan * Correspondence: kadotanisleep@gmail.com; Tel.: +81-77-548-2291 20 4 2022 5 2022 19 9 500715 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/). Background: Multiple clinical departments are involved in the provision of obstructive sleep apnoea (OSA) therapy in Japan. Inconsistent results regarding the association between depression and OSA have been reported. Methods: This cross-sectional survey compared newly diagnosed OSA patients at two outpatient sleep apnoea units in Shiga Prefecture, Japan: one associated with the psychiatry department (n = 583), and the other with the otolaryngology department (n = 450). Results: The unit associated with the psychiatry department had more patients referred by psychiatrists than that with the otolaryngology department (11% vs. 3% p < 0.05). Sleepiness, insomnia, and depression were assessed using the Epworth Sleepiness Scale (ESS), Athens Insomnia Scale (AIS), and Patient Health Questionnaire-9 (PHQ-9), respectively. The ESS, AIS, and PHQ-9 scores were higher in the sleep unit in the psychiatry department (p < 0.001 each). Snoring and moderate to severe OSA were more prevalent in the unit attached to the otolaryngology department (p < 0.001 each). Patients with moderate to severe OSA had lower PHQ-9 scores than those with no to mild OSA (OR: 0.96, 95% CI: 0.92–1.00, p = 0.042). Conclusion: Patients with sleepiness, insomnia, and depressive symptoms were more likely to attend a sleep outpatient unit associated with a psychiatry department, whereas those with snoring and sleep apnoea attended that associated with an otolaryngology department. OSA severity was negatively associated with depressive symptoms. obstructive sleep apnoea sleepiness insomnia depression mental health ==== Body pmc1. Introduction Obstructive sleep apnoea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep [1,2]. A total of 425 million adults were estimated to have moderate to severe OSA (defined as apnoea–hypopnea index [AHI] ≥ 15 events per h) worldwide [3]. Its prevalence rate was estimated to be 14.0% in Japan [3,4]. Advanced age, male sex, and a higher body mass index (BMI) are associated with an increase in OSA prevalence [1]. OSA is thought to be linked to multiple adverse health outcomes, including daytime sleepiness, decreased quality of life, hypertension, diabetes, coronary artery disease, stroke, atrial fibrillation, congestive heart failure, cognitive function decline, depression, and mortality [5]. Several clinical departments are involved in the provision of OSA therapy in Japan, including psychiatry, otolaryngology, internal medicine, and dentistry [2]. Although multicentre studies focusing on OSA have been conducted in Japan [6,7], the differences in the patients’ characteristics between each clinical department are not well understood. Depression is the most prevalent mental disorder in Japan [8,9]. Inconsistent results regarding the association between depression and OSA have been reported. Some studies have reported that depressive symptoms are positively associated with OSA severity [10,11] and that unrecognized OSA is highly prevalent in patients with depression [12,13]. Longitudinal studies have suggested an association between OSA and depression [14]. Positive airway pressure (PAP) treatment was reported to improve depression symptoms [5,15]. However, some studies have reported the lack of an association [16,17,18]; moreover, increased OSA severity has been associated with fewer depressive symptoms [19]. OSA screening tools, including the Berlin questionnaire, STOP-BANG questionnaire, STOP questionnaire, four-item screening tool [20], and ESS [21], have been widely used [22]. However, clinical tools, questionnaires, and prediction algorithms are strongly not recommended to diagnose OSA in the absence of polysomnography (PSG) or out-of-centre sleep testing (OCST) [23]. Pulse oximetry, a simple method to obtain physiological signals, may be another useful tool for screening OSA; however, it may be difficult to set an appropriate threshold to distinguish between moderate and severe OSA by oximetry alone [24]. Abnormalities in craniofacial and upper airway anatomy are important risk factors for OSA [25]. The modified Mallampati grade and Friedman tongue position are commonly used scales to assess the oropharynx during visual evaluation [26]. Lateral X-ray cephalograms are widely used to quantify and analyse craniofacial skeletal morphology and the oropharyngeal space [25]. Recently, cone-beam-computed tomography became available to reconstruct and evaluate a three-dimensional image of these structures [25]. One sleep physician was in charge of examining new patients suspected of OSA in two different clinical settings as follows: one was attached to a psychiatry department and the other to an otolaryngology department. He suspected that the severity of OSA and depressive symptoms may differ between these two settings. To test this hypothesis, the same questionnaires were used to assess depressive symptoms and the other two major symptoms of OSA (i.e., sleepiness and insomnia) in these settings. In this study, we aimed to analyse the following: (1) the differences in the characteristics of patients who attend sleep outpatient units associated with different clinical departments and (2) the association between OSA and depression. We conducted a cross-sectional survey to compare patients newly diagnosed with OSA at two outpatient units for sleep apnoea in Shiga Prefecture, Japan: one associated with a psychiatry department, and the other with an otolaryngology department. 2. Materials and Methods 2.1. Participants We collected the medical records of patients referred to two outpatient sleep apnoea units at two public tertiary care centres in Shiga Prefecture in Japan that are located 71 km apart (Figure 1). One unit was attached to the psychiatry department of a university hospital (Shiga University of Medical Science Hospital, Otsu, Japan), which has 612 beds, whereas the other was attached to the otolaryngology department of a city hospital (Nagahama City Hospital, Nagahama, Japan) that has 600 beds. The Shiga University of Medical Science is the only university hospital in Shiga Prefecture and is located on the border of Otsu City (344,000 inhabitants, the largest city and prefectural capital of the Shiga Prefecture) and Kusatsu City (136,000 inhabitants, the second-largest city in the prefecture). The university hospital has a sleep centre that is the only one certified by the Japanese Society of Sleep Research (JSSR) in Shiga Prefecture, with five board-certified physicians of the JSSR. Only one physician is in charge of examining new patients suspected of OSA in the university hospital. On the other hand, the Nagahama City Hospital is the only hospital with a sleep specialist on staff (part-time) in Nagahama City (116,000 inhabitants, the third-largest city in the prefecture). The physician in charge of new patients with OSA at the university hospital is also in charge of new patients with OSA at the city hospital, who is experienced in the diagnosis of mental disorders in a non-psychiatric patient population [8]. Patients with medical referral letters are given priority to make reservations for appointments in the hospitals, but patients can also make appointments directly without referral letters by paying extra fees. We retrospectively analysed the medical records of consecutive outpatients who visited one of two hospitals for the first time from 1 April 2015 to 31 March 2019. In this survey, we used PSG or OCST records. We excluded patients who cancelled PSG or OCST and those with no or incomplete PSG/OCST data (Figure 2). We also excluded patients aged < 15 years and those with dementia and intellectual developmental disorders. The medical records also provided information on whether the patients were referred to the hospitals or the patients made the appointments directly by themselves. We estimated the approximate distance between the residential area of each patient and their hospital using Google Maps ver. 3.46 (Google LLC, Mountain View, CA, USA). 2.2. Questionnaires Sleepiness and insomnia are common symptoms in patients with OSA [1]. Insomnia and depression are highly prevalent and frequently co-occur [27]. Sleepiness, insomnia, and depression were assessed using the Japanese versions of the Epworth Sleepiness Scale (ESS) [21], Athens Insomnia Scale (AIS) [28], and Patient Health Questionnaire-9 (PHQ-9) [29], respectively. To assess and compare these symptoms, we used a set of questionnaires, including ESS, AIS, and PHQ-9, in both clinical and epidemiological settings. We used these questionnaires for patients at the time of a new visit and twice a year thereafter both in the university hospital [30] and in the city hospital 24]. We also used these questionnaires annually in the cohort study performed in Koka City in Shiga Prefecture [27,31]. The ESS is a self-administered questionnaire with eight questions evaluating daytime sleepiness. The respondents are asked to rate their usual chances of dozing off or falling asleep while engaged in eight different activities [21]. A sum score is calculated (range: 0–24), with higher scores indicating more sleepiness. The AIS was developed by the World Health Organization based on the criteria of the International Classification of Disease, 10th revision. The AIS comprises eight questions, including five assessing nocturnal sleep problems and three evaluating the daytime consequences of insomnia [28]. A sum score is calculated (range: 0–24), with higher scores indicating more severe insomnia symptoms. The PHQ-9 comprises nine items derived from the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) diagnostic criteria for depressive disorder, and it is considered a valid instrument for the assessment of depressive symptoms [29]. A sum score is calculated (range: 0–27), with higher scores indicating more severe depression. 2.3. OSA Diagnosis In the Japanese health insurance system, continuous positive airway pressure (CPAP) therapy, the first-line treatment for OSA [2,5], can be prescribed only when patients have respiratory event indexes (REI) ≥ 40 with OCST or AHI ≥ 20 with PSG [2]. PSG tests are strongly recommended to be performed when patients are highly suspected to have OSA after OCST and with REI < 40 [2]. When patients were referred to the Shiga University of Medical Science or the Nagahama City Hospital for OSA diagnosis/treatment, or when patients directly came to the hospital without medical referral letters, all OSA-suspected patients were asked to undergo OCST/PSG. The respiratory event indexes (REIs) obtained from OCST data were manually analysed using Morpheus (Teijin, Tokyo, Japan) or PulSleep LS120 (Fukuda Denshi, Tokyo, Japan) in the city hospital or Smartwatch PMP-300E (Pacific Medico Co., Ltd., Tokyo, Japan) in the university hospital. OCST data were analysed one to two weeks after the patients returned the OSCT devices to the hospitals. The OCST results in the university hospital were manually analysed by technicians blind to the questionnaire results and were reviewed by a board-certified physician of the JSSR, whereas those in the city hospital were manually analysed by the same physician without referring to the questionnaire results. The in-laboratory PSG results were analysed with Alice 5 (Philips Respironics, Inc., Murrysville, PA, USA) blind to the questionnaire results in both settings. We followed the recommended American Academy of Sleep Medicine (version 2.3) scoring criteria [32]. Apnoea was defined as the cessation of airflow for at least 10 s, while hypopnea was defined as a reduction in the airflow amplitude or respiratory effort of at least 30%, with an oxygen desaturation value of 3% or greater for at least 10 s. The numbers of patients diagnosed using PSG and OCST were 250 and 333 in the university hospital and 153 and 297 in the city hospital, respectively. OSA severity was identified based on the recorded AHI or REI; AHI/REI < 5, 5 ≤ AHI/REI < 15, 15 ≤ AHI/REI < 15, and 30 ≥ AHI/REI were classified as no, mild, moderate, and severe OSA, respectively. We divided all AHI/REI scores into two groups: AHI/REI < 15 (none-to-mild OSA) and AHI/REI ≥ 15 (moderate-to-severe OSA) [23]. 2.4. Statistical Analysis Descriptive statistics for clinical characteristics are expressed as the mean ± standard deviation (SD) or number (%). Independent t-tests and chi-squared (χ2) tests were used for continuous and categorical variables, respectively. Bonferroni correction was used for multiple comparisons. We performed a logistic regression analysis with the hospital choice (0: the city hospital; 1: the university hospital) as the dependent variable after adjusting for age, sex, BMI, snoring, ESS, AIS, PHQ-9, AHI/REI, hypertension, distance from the university hospital, and distance from the city hospital. We also performed a logistic regression analysis with moderate to severe OSA as the dependent variable and adjusted for age, sex, BMI, snoring, ESS, AIS, PHQ-9, lifestyle-related diseases (diabetes, hypertension, cardiovascular diseases, and cerebrovascular diseases), and mental disorders. The Kruskal–Wallis test was used to compare the PHQ-9 scores and OSA severity for sensitivity analysis. The significance level was set to p < 0.05. All data were analysed using the SPSS 25.0 statistical software (SPSS Inc., Chicago, IL, USA) and MedCalc ver. 20.014 (MedCalc Software Ltd., Ostend, Belgium). In a previous study [8], we could not detect a difference in OSA between controls and participants with depression, and attributed this finding to the small number of participants with depression. We reported an AHI/REI difference between controls and participants with depression of 2.24 (SD: 11.4). In this study, the ratio of participants with PHQ-9 ≥ 10 and those with PHQ-9 < 10 was approximately 0.9. If the true difference in the experimental and control means is 2.24, we needed to study 388 participants with depression and 432 control participants to be able to reject the null hypothesis that the population means of the experimental and control groups are equal with a probability (power) of 0.8. The type-I error probability associated with this test of this null hypothesis is 0.05. Thus, we may have a sufficient sample size to detect an association between OSA and depression in this study. 3. Results The total number of new outpatients was 1156. Overall, 681 participants visited the university hospital and 475 visited the city hospital. After applying the exclusion criteria, the final number of participants included in this study was 583 in the university hospital and 450 in the city hospital (Figure 2). The proportion of patients referred from other hospitals to the university hospital was significantly higher than that referred to the city hospital (17% vs. 5%, p < 0.05; Figure 3). The proportion of patients referred from clinics to the university hospital was significantly lower than that referred to the city hospital (45% vs. 59%, p < 0.05). The proportion of referrals from the psychiatry department of hospitals and clinics was significantly higher in the university hospital than in the city hospital (11% vs. 3%, p < 0.05) (Figure 4). No significant differences were found in the other departments, including the otolaryngology department (7% vs. 10%). Seven, twenty-seven, and thirty-one patients were referred from the psychiatry department of the same university hospital, other hospitals, and other clinics to the OSA outpatient unit of the university hospital, respectively. A total of 14, 1, and 29 patients were referred from the otolaryngology department of the same city hospital, other hospitals, and other clinics to the OSA outpatient unit of the city hospital, respectively. Most patients showed symptoms of OSA, such as snoring, and experienced apnoea during sleep (89.0% in the university hospital and 95.5% in the city hospital). The number of new outpatients from Shiga Prefecture was 603 in the university hospital and 470 in the city hospital. There were 74 and 5 patients from outside Shiga Prefecture in the university hospital and city hospital, respectively (Figure 1). Age and AHI/REI were significantly higher in patients visiting the city hospital than in those visiting the university hospital. The prevalence of snoring, moderate to severe OSA, and hypertension was also significantly higher among patients visiting the city hospital. In contrast, the ESS, AIS, and PHQ-9 scores were significantly higher in patients in the university hospital than in those in the city hospital. In addition, the prevalence of mental disorders was significantly higher and the distance from their residence to their hospital was significantly greater among the university hospital outpatients (Table 1). We classified patients into two groups according to the severity of OSA (AHI/REI < 15 vs. AHI/REI ≥ 15). Regardless of OSA severity, the AIS scores were significantly higher in the university hospital, while the rate of snoring was significantly higher in the city hospital. The prevalence of lifestyle-related diseases and mental disorders was not significantly different between settings within each OSA severity category (Table 2). Age, insomnia (AIS), and distance from the hospitals were associated with the hospital choice (Table 3). Depressive symptoms (PHQ-9) and REI/REI were associated with the choices in the unadjusted model, but not in the adjustment model. The PHQ-9 scores were lower in patients with moderate to severe OSA than in those with no to mild OSA (Figure 5). This association between the PHQ-9 score and OSA severity was also found in the logistic regression analysis, even after adjusting for age, sex, BMI, snoring, ESS, AIS, AHI/REI, hypertension, distance from the university hospital, and distance from the city hospital (Table S1). 4. Discussion We compared the characteristics of outpatients newly diagnosed with OSA who visited two sleep apnoea units associated with different departments in Japan. In both units, the chief complaints of new outpatients were snoring and witnessed apnoea: 89.0% in the university hospital and 95.5% in the city hospital. We conducted this study using the same evaluation criteria for two hospitals of the same scale in Shiga Prefecture and found significant differences in age, sleepiness scores, insomnia scores, depression scores, prevalence of mental disorders, snoring rate, and the presence of hypertension. These results indicate that the characteristics of patients referred to sleep units may be affected by the department they are associated with. A comparison of outpatients between the two sleep apnoea units revealed significantly different patient characteristics. More outpatients with snoring were found in the city hospital, which is associated with the otolaryngology department, while more outpatients with insomnia symptoms were found in the university hospital, which is associated with the psychiatry department. General practitioners must decide which departments are suitable for their outpatient’s suspected OSA; at that time, they may also decide where to refer their outpatients based on other symptoms, such as snoring or witnessed apnoea. Physicians in hospitals may have a tendency to refer patients more to the university hospital than to the city hospital, whereas those in clinics tend to refer them to the city hospital. Our findings suggest that distance from home to the hospitals is a main contributing factor to deciding which hospital to attend. Patients tended to be referred to university hospitals from more distant locations. More OSA patients with insomnia were referred to the sleep outpatient unit attached to the psychiatric department in the university hospital. Future studies comparing more hospitals are required to clarify whether these choices are attributed to the characteristics of the hospitals (university hospital vs. city hospital) or related to the department (otolaryngology vs. psychiatry). Otolaryngologists are recognized as specialists in treating snoring [33]. Uvulopalatopharyngoplasty (UPPP) was first introduced by a Japanese otolaryngologist for snoring and OSA [34]. In a meta-analysis, the success rate of UPPP for OSA was reported to be 51.5% [35]. The serious nonfatal complication rate of UPPP was 1.5%, and its 30-day mortality rate was 0.2% [36]. Thus, UPPP is now considered as a secondary or optional therapy for OSA when patients are intolerant to CPAP or oral appliances [2]. Thus, we assume that general practitioners would tend to refer patients who are strongly suspected to have OSA due to snoring or witnessed apnoea to a nearby unit associated with an otolaryngology department. The proportion of patients with snoring and moderate-to-severe OSA was higher in the city hospital, which is associated with the otolaryngology department (Table 1). However, the adjusted logistic regression analysis results suggest that snoring and OSA may not be the main factors affecting the hospital choice (Table 3). In addition, the proportion of patients referred by otolaryngologists was similar in both hospitals (Figure 4). On the other hand, the patients referred to the outpatient sleep apnoea unit in the university hospital had significantly higher AIS, ESS, and PHQ-9 scores than those in the city hospital (Table 1). The AIS, ESS, and PHQ-9 scores of the patients who visited the city hospital were similar to those of the city government employees in Shiga Prefecture, as reported in a previous epidemiological study, where the AIS, ESS, and PHQ-9 scores were 4.98 ± 3.57, 7.85 ± 4.54, and 4.65 ± 4.54, respectively [27]. The prevalence of mental illness was significantly higher in the university hospital (21.3%) than in the city hospital (13.8%). Mental disorders, including depression, are strongly associated with insomnia [27], and a psychiatrist mainly treats insomnia, i.e., the university’s outpatient unit for sleep apnoea is attached to the psychiatry department. If the patients were suspected to have any psychiatric disorders in addition to OSA, a general practitioner might hesitate to refer them to the nearby sleep units associated with the otolaryngology department, regardless of OSA severity. The logistic regression analysis results suggested that insomnia symptoms may be an important factor to determine which hospital to attend (Table 3). Moreover, the proportion of patients referred by psychiatrists was higher in the university hospital than in the city hospital (Figure 4). Hospital distance (the distance from the patients’ residence to their hospital) was significantly greater among patients attending the university hospital than among those attending the city hospital. Although there are several sleep units associated with otolaryngology departments in the Shiga Prefecture, the sleep unit in the university hospital was the only one associated with a psychiatry department. This may explain why there was a greater distance to the hospital in patients attending the university hospital and why patients attending the city hospital had a higher mean AHI/REI score and a higher moderate-to-severe OSA prevalence. Our results suggest a significant relationship between moderate to severe OSA and older age, male sex, BMI, and hypertension, similar to the results of a previous study (Table S1) [1]. In contrast, no significant association was found between moderate to severe OSA and lifestyle-related diseases, other than hypertension. After PAP treatment, blood pressure was reported to be significantly reduced, but cardiovascular events and glycaemia were not [5]. The triacylglycerol and total cholesterol levels have been reported to improve after PAP treatment; however, the changes attributable to PAP were less significant than those explained by circadian changes [37]. In this study, we only detected an association with hypertension, probably because of the small effects of OSA on lipidaemia and glycaemia and the too-small sample size to detect cardiovascular or cerebrovascular events. We found that OSA is negatively associated with depressive symptoms (PHQ-9 score) (Supplementary Materials Table S1, Figure 5). Some previous studies have reported that depressive symptoms are positively associated with OSA severity [10,11], whereas other studies found no association between depression and OSA [16,17,18]. A recent systematic review and meta-analysis concluded that there was no compelling evidence of an association between OSA and depression in six cross-sectional studies [14]. A study conducted in a large clinical setting in Norway that analysed PSG data (n = 3770) reported that the prevalence of depressive symptoms significantly decreases as OSA severity increases [19]. Thus, based on cross-sectional studies, there may be no or a negative association between OSA severity and depression symptoms. Patients with depression were more likely to report somatic symptoms [38] and, therefore, be more sensitive to and overreport their physical symptoms related to OSA. Moreover, insomnia may be involved as a confounder for OSA severity. In other words, if insomnia is the main complaint, but the patient is examined with suspicion for OSA, insomnia and depression could be negatively associated with OSA severity, if there are many cases of insomnia and no to mild OSA. However, this possibility is unlikely, since depression and OSA were negatively correlated in both the university and the city hospitals, and the insomnia (AIS), sleepiness (ESS), and depression (PHQ-9) scores in the city hospital were comparable to those of the municipal employees in the same prefecture [27]. Cognitive function is impaired by OSA [39]. OSA might reduce self-awareness and the perception of stress, which might help reduce depressive symptoms in OSA patients. However, since OSA does not affect the global cognition domain of cognitive functions [39], it may be unlikely to help reduce depressive symptoms. This study had some limitations. First, it was performed in clinical settings within Shiga Prefecture in Japan and may, therefore, not be representative of the Japanese general population. Second, as only two hospitals were compared, it is impossible to determine which is more important, the nature of the hospital (university hospital or city hospital) or the department attached to the outpatient sleep apnoea units. Third, owing to the cross-sectional study design, longitudinal changes were not analysed. Other limitations include the fact that depressive symptoms were assessed using PHQ-9 only and not by structured interviews. However, in our previous cohort study of a working population in the Shiga Prefecture (NinJa Sleep Study: Night in Japan Home Sleep Monitoring Study) [27,31], the same questionnaires were used. We plan to compare the association between OSA and depression found in the previous study and this study. We used the same in-laboratory PSG device; however, the OCST devices were different between the two settings. A comparison between AHI from PSG and REI from OCST was previously performed in the city hospital, which suggested a reasonable validity of REI compared with AHI [24]. The same sleep physician reviewed all of the analysed results; however, the PSG/OCST analyses were performed by different staff in both settings. 5. Conclusions Patients with sleepiness, insomnia, and depressive symptoms were more likely to attend a sleep outpatient unit associated with a psychiatry department, whereas those with snoring and sleep apnoea tended to attend one associated with an otolaryngology department. OSA severity was negatively associated with depressive symptoms. Acknowledgments We express our gratitude to the participants of this study and the medical staff and clerks of Shiga University of Medical Science Hospital and Nagahama City Hospital. We thank T. Toyoda, S. Sawada, K. Konishi, K. Awazu, T. Miyamoto, and T. Kanemura for their assistance with data collection. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095007/s1, Table S1: Logistic regression analysis: comparisons between patients with AHI/REI < 15 and ≥15. Click here for additional data file. Author Contributions Conceptualization, K.I. and H.K.; Data curation, K.I.; formal analysis, K.I.; funding acquisition, H.K.; investigation, K.I., M.U., A.M. and H.K.; methodology, H.K.; project administration, H.K.; resources, M.U. and H.K.; software, K.I. and H.K.; supervision, H.K.; validation, H.K.; visualization, K.I. and H.K.; writing—original draft, K.I.; writing—review & editing, A.U., A.M., Y.S. and H.K. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by MEXT/JSPS, (KAKENHI grant number 21H03851. Institutional Review Board Statement The study was approved by the Ethics Committees of the Shiga University of Medical Science (protocol code R2015 -229) and the Nagahama City Hospital (protocol code 27–37), and was conducted in accordance with the Declaration of Helsinki. Informed Consent Statement Patient consent was waived owing to the retrospective nature of the study. The study protocol is disclosed on the website (http://www.shiga-med.ac.jp/~hqsuimin/1207.pdf accessed on 11 April 2022), and participants were offered the opportunity to opt out of the study. Data Availability Statement The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Conflicts of Interest K.I., A.U., A.M. and H.K. were associated with a laboratory that was supported by donations from Fukuda Lifetech Co., Ltd., Fukuda Life Tech Keiji Co., Ltd., Tanaka Sleep Clinic, Akita Sleep Clinic, and Ai Care Co., Ltd. to Shiga University of Medical Science. H.K. received grants from MEXT/JSPS (KAKENHI Grant Number: 21H03851) and Merck Sharp and Dohme Corp/MSD K.K. (Investigator-Initiated Studies Program), Eisai Co., Ltd., and SECOM Science and Technology Foundation. 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. H.K. reports consulting fees from Takeda Pharmaceutical Co., Ltd. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck Sharp, Dohme Corp/MSD K.K. The other authors declare no conflict of interest. Figure 1 Distribution of new patients in the two settings studied. The numbers of new patients who visited each sleep outpatient unit from 1 April 2015 to 31 March 2019 at Shiga University of Medical Science Hospital (A) and Nagahama City Hospital (B) are indicated. The green areas represent Shiga Prefecture. Within Shiga Prefecture, each city or county is indicated separately. Prefectures outside Shiga Prefecture are also presented separately. The red circles indicate the locations of the two hospitals. Figure 2 Flowchart of patient inclusion. AHI, apnoea–hypopnea index; REI, respiratory event index. Figure 3 Referral source. Patients were referred from the same hospital (blue), other hospitals (orange), or other clinics (grey). Patients could directly come to the outpatient units without medical referral letters (green). Data regarding the referral sources were missing in some patients (light blue). ‡ p < 0.05 between the university hospital and the city hospital with Bonferroni correction. Figure 4 Referral source of OSA-suspected patients. Referrals from OSA-related departments, including internal medicine (grey), psychiatry (blue), otolaryngology (red), dentistry (orange), and other departments, including neurology (light blue) and others (grey), are shown. Surgical departments were separated into otolaryngology (red) and other surgical departments (light blue). Industrial physicians and public health departments were combined into public health and social medicine (navy blue). Some patients had no data regarding the referral source or referral departments (ochre). Patients could directly come to the outpatient units without medical referral letters (brown). ‡ p < 0.05 between the university hospital and the city hospital with Bonferroni correction. Figure 5 Box-and-whisker plot for PHQ-9 scores according to OSA severity. Patients with AHI/REI < 5, 5 ≤ AHI/REI < 15, 15 ≤ AHI/REI < 15, and 30 ≥ AHI/REI were classified as having no, mild, moderate, and severe OSA, respectively. OSA, obstructive sleep apnoea; PHQ-9, Patient Health Questionnaire-9; AHI, apnoea–hypopnea index; REI, respiratory event index; ■, far outside values; ○, outside values; a, p < 0.05 vs. no; b, p < 0.05 vs. mild; c, p < 0.05 vs. moderate; d, p < 0.05 vs. severe. ijerph-19-05007-t001_Table 1 Table 1 Characteristics of patients included in the study (n = 1033). Total University Hospital (n = 583) City Hospital (n = 450) p Age (years) 54.6 ± 16.8 51.3 ± 17.5 58.8 ± 14.8 <0.0001 Male (%) 71.8 68.8 75.8 0.013 Snoring (%) 62.8 57.8 69.3 <0.0001 BMI (kg/m2) 26.1 ± 5.38 26.1 ± 5.42 26.3 ± 5.33 0.557 ESS 9.17 ± 5.80 10.0 ± 6.06 8.09 ± 5.26 <0.001 AIS 5.72 ± 4.32 6.53 ± 4.25 4.71 ± 4.21 <0.001 PHQ-9 5.49 ± 5.22 6.27 ± 5.32 4.53 ± 4.92 <0.001 AHI/REI (per h) 23.1 ± 22.1 19.6 ± 22.3 27.6 ± 20.9 <0.001 Moderate to severe OSA (%) 53.3 42.0 68.0 <0.001 Hypertension (%) 44.1 39.5 50.0 0.001 Diabetes (%) 19.5 19.0 20.0 0.699 Hyperlipidaemia (%) 27.0 26.4 27.8 0.625 Cardiovascular diseases (%) 10.2 8.75 12.0 0.086 Cerebrovascular diseases (%) 5.71 6.17 5.11 0.883 Mental disorders (%) 18.0 21.3 13.8 0.002 Hospital distance (km) 17.2 ± 21.4 22.6 ± 24.7 10.3 ± 13.2 <0.001 Bonferroni-corrected p-value for 0.05 is 0.003 (= 0.05/16). Data are expressed as the mean ± standard deviation or number of participants (%). Hospital distance, the distance between patients’ residence and their hospital; OSA, obstructive sleep apnoea; BMI, body mass index; PHQ-9, Patient Health Questionnaire-9; AIS, Athens Insomnia Scale; ESS, Epworth Sleepiness Scale; AHI, apnoea–hypopnea index; REI, respiratory event index. ijerph-19-05007-t002_Table 2 Table 2 Characteristics of patients with no to mild OSA (AHI/REI < 15) vs. moderate to severe OSA (AHI/REI ≥ 15) in the two settings. AHI/REI < 15 AHI/REI ≥ 15 University Hospital (n = 338) City Hospital (n = 144) p University Hospital (n = 245) City Hospital (n = 306) p Age (years) 47.7 ± 18.6 54.0 ± 16.4 0.001 56.3 ± 14.5 61.1 ± 13.4 <0.001 Male (%) 61.5 66.7 0.286 78.8 80.1 0.709 BMI (kg/m2) 24.5 ± 4.62 25.4 ± 5.09 0.059 28.2 ± 5.69 26.7 ± 5.40 0.001 Snoring 55.5 75.7 <0.001 60.8 66.3 <0.001 ESS 10.7 ± 6.36 8.46 ± 5.66 <0.001 9.11 ± 5.50 7.91 ± 5.07 0.009 AIS 6.86 ± 4.39 5.17 ± 4.49 <0.001 6.04 ± 3.99 4.49 ± 4.05 <0.001 PHQ-9 6.80 ± 5.60 6.00 ± 5.83 0.163 5.47 ± 4.79 3.84 ± 4.26 <0.001 AHI/REI (per h) 4.93 ± 4.60 7.93 ± 4.36 <0.001 39.8 ± 21.2 36.9 ± 19.1 0.940 Hypertension 28.7 33.3 0.310 54.3 58.2 0.361 Diabetes 14.8 14.6 0.953 24.9 22.5 0.519 Hyperlipidaemia 22.8 22.2 0.893 31.4 30.4 0.794 Cardiovascular diseases 7.10 9.03 0.467 11.0 13.4 0.399 Cerebrovascular diseases 2.66 4.86 0.218 8.98 5.23 0.084 Mental disorders 25.1 21.5 0.395 15.9 10.1 0.043 Bonferroni-corrected p-value for 0.05 is 0.003 (= 0.05/14). Data are expressed as the mean ± standard deviation or number of participants (%). OSA, obstructive sleep apnoea; BMI, body mass index; PHQ-9, Patient Health Questionnaire-9; AIS, Athens Insomnia Scale; ESS, Epworth Sleepiness Scale; AHI, apnoea–hypopnea index. ijerph-19-05007-t003_Table 3 Table 3 Logistic regression analysis: comparisons between the university hospital and the city hospital. Unadjusted Odds Ratio (95% CI) p Adjusted Odds Ratio (95% CI) p Age (years) 0.97 (0.97–0.98) <0.001 0.98 (0.95–0.99) 0.034 Male 0.71 (0.54–0.94) 0.015 0.72 (0.35–1.48) 0.365 BMI (kg cm−2) 0.58 (0.97–1.02) 0.581 0.97 (0.90–1.04) 0.411 Snoring 0.61 (0.47–0.79) <0.001 0.74 (0.38–1.46) 0.389 ESS 1.06 (1.04–1.09) <0.001 1.02 (0.96–1.09) 0.466 AIS 1.11 (1.08–1.15) <0.001 1.14 (1.03–1.26) 0.008 PHQ-9 1.07 (1.04–1.10) <0.001 0.95 (0.87–1.03) 0.221 AHI/REI (per h) 0.98 (0.98–0.99) <0.001 0.99 (0.97–1.00) 0.080 Hypertension 0.66 (0.51–0.84) 0.001 0.84 (0.39–1.80) 0.660 Distance from the university hospital (km) 0.90 (0.86–0.91) <0.001 0.92 (0.90–0.94) <0.001 Distance from the city hospital (km) 1.13 (1.11–1.15) <0.001 1.07 (1.06–1.09) <0.001 BMI, body mass index; PHQ-9, Patient Health Questionnaire-9; AIS, Athens Insomnia Scale; ESS, Epworth Sleepiness Scale; AHI, apnoea–hypopnea index; REI, respiratory event index. 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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093026 materials-15-03026 Article A Dipole with Reflector-Backed Active Metasurface for Linear-to-Circular Polarization Reconfigurability van Aardt Ruan https://orcid.org/0000-0003-2701-3947 Joubert Johan * Odendaal Johann W. Bormashenko Edward Academic Editor Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa; ru.vanaardt@gmail.com (R.v.A.); wimpie.odendaal@up.ac.za (J.W.O.) * Correspondence: jjoubert@up.ac.za 21 4 2022 5 2022 15 9 302624 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/). In recent years, significant advances have been made in diversifying the capabilities of communication systems by using reconfigurable antennas. There are many types of reconfigurable antennas—to achieve pattern, frequency, or polarization reconfigurability. These antennas are reconfigured either by the mechanical rotation of surfaces or by enabling or disabling specific sections of the structure using electrical switches. This paper focuses on the concept of a polarization reconfigurable antenna based on an active reflector-backed metasurface. An antenna system based on an active reflector-backed metasurface combined with a planar dipole is designed to achieve reconfigurable polarization. The polarization of the designed antenna can be switched between linear and circular polarization states using positive-intrinsic-negative diodes located in the unit cell elements of the metasurface. The measured results correlate well with the simulated results. The antenna has a physical size of 308 × 162 × 35 mm3 with an impedance bandwidth of 4.5% in the linear state and 7% in the circular state, as well as an axial ratio bandwidth larger than 8.3%. metasurface reflector-backed polarization diversity reconfigurable polarization dipole antenna ==== Body pmc1. Introduction The communication industry has rapidly evolved over the last decade because of a focus on a more connected world, with an emphasis on wireless technologies. A major challenge in the industry has been the demand for networks to have more capacity and throughput while operating with spectral efficiency. Reconfigurable antennas have been investigated to address this challenge because they can provide the required diversity [1]. As an active research field, reconfigurable antennas still allow for significant innovations, which can have a major impact on the communication industry. Even though reconfigurable antennas have their challenges, they still provide great advantages in the communication domain compared to traditional antennas. Reconfigurable antennas have shown significant improvements in communication systems, specifically in MIMO based systems [2]. By using certain reconfigurable antennas, it is possible to improve the data throughput, the signal to noise ratio (SNR), and the bit error rate. Not only does a reconfigurable antenna improve performance characteristics, but it also makes the antenna multifunctional [3]. Some reconfigurable antenna designs achieve reconfigurability by modifying the structure of the radiating element. This is done by introducing switching elements on the radiating element, which enables the user to change the properties of the antenna through a controller. However, by modifying the antenna structure with the addition of switching elements, the antenna performance will be degraded. As shown in [2,3,4,5], this degradation can be rectified through the addition of inductive chokes to still achieve the desired antenna performance. In [4], a microstrip patch is connected to 12 stubs through varactor diodes. By altering the bias voltages of the diodes, specific stubs can be activated to enable circular and linear polarization configuration states. An impedance bandwidth of 40% is achieved with a narrow axial ratio bandwidth over multiple frequencies. A similar approach is taken in [5], where a reflector-backed wheel-shaped monopole antenna is stub-loaded. Again, by varying the bias voltages, circular and linear polarization states can be realized, achieving impedance bandwidths of 5.4% and 28.6%, respectively, in the linear and circular configuration states. An axial ratio bandwidth of 15.4% is achieved in the circular configuration. Reconfigurability can also be accomplished by modifying the feed network by introducing switchable segments that can alter the phase and magnitude of the input signal [6,7,8,9]. These designs produce antennas with wide bandwidths and high gains. With most of these methods, reconfigurable polarization is the focus of the designs. In [6], a dielectric resonator antenna (DRA) is made reconfigurable through the addition of a feeding cross slot network with embedded positive-intrinsic-negative (PIN) diodes. The antenna is capable of right-hand circular polarization (RHCP), left hand circular polarization (LHCP), and linear polarization (LP) states. The antenna has impedance bandwidths of 30% and 25%, respectively, in the linear and circular polarization states, while an axial ratio bandwidth of 21% is achieved. Metasurfaces are two-dimensional arrays composed of subwavelength structures that can be designed to have specific responses on electromagnetic waves. At microwave frequencies, planar metallic arrays of unit elements etched on low-loss dielectric substrates are typically used as metasurfaces to modify the amplitude, phase, and polarization of electromagnetic waves. These single-layer monoatomic designs are relatively easy to design and manufacture. Recent research shows that anisotropic plasmonic, diatomic, and polyatomic metasurfaces will allow even more degrees of freedom than planar monoatomic metasurfaces and will make it possible to realize improved electromagnetic functionalities [10,11,12]. Single-layer monoatomic metasurfaces have been used to alter the polarization of an incident wave [13,14,15,16,17], either in a transmission or reflective configuration. In [13], a multilayered metasurface with truncated square patch unit cells is used to achieve polarization reconfigurability. By mechanical rotation of the surface RHCP, LHCP, and LP states can be achieved. In [14], this metasurface is implemented with a slot radiating element to create a reconfigurable antenna. To alter the polarization states, the surface is rotated as originally described in [13]. The antenna achieves an impedance bandwidth of 25% and 37%, respectively, in the linear and circular states. An axial ratio bandwidth of 14% is achieved. At microwave frequencies, these metasurfaces can be made reconfigurable through the addition of switchable elements. The metasurface can be used to add the element of reconfigurability within an antenna system [15,18,19,20,21,22]. Micro-electromechanical system (MEMS) devices can also be used to reconfigure metasurfaces. In [18], a metasurface with a 4 × 4 square unit cell array was used in conjunction with a square patch antenna. The unit cells are connected to each other through MEMS switches where they can be controlled independently to achieve pattern, frequency, and polarization diversity. The antenna achieves an impedance bandwidth of 1.8% for both linear and circular configurations and an axial ratio bandwidth of 2.4%. The authors also show that an array of radiators can be implemented with such a reconfigurable surface. Another antenna with polarization diversity based on a reconfigurable metasurface is discussed in [19]. The metasurface is designed with a double layered elliptical unit cell structure and is capable of switching the polarization state from linear to circular. This surface is used in front of the aperture of a horn antenna. The reconfigurability is achieved through PIN diodes: in the off state, the antenna is configured in a circular polarization state and a linear polarization state in the on state. An impedance bandwidth of 21% and 23% is achieved in the linear and circular states with an axial ratio bandwidth of 14%. In all the previously mentioned examples, a unidirectional antenna radiating element was used, with the reconfigurable metasurface as a superstrate to control the polarization. An alternative method of utilizing a metasurface for reconfigurability is in a reflective configuration for omnidirectional radiating elements where the metasurface is backed with an electric reflective surface. In [15], an active reflective metasurface is presented that could convert a linearly polarized incident wave to a circularly polarized reflected wave. The reflected wave can be switched from LHCP to RHCP, at distinct frequencies. In [20], a double layered metasurface consisting of rectangular patch unit cells is utilized together with a reflector and a CPW (co-planar waveguide) fed monopole. The antenna can switch between an RHCP state and an LHCP state over multiple narrow frequency bands using varactor diodes. The antenna achieves an impedance bandwidth of 12.8% and an axial ratio bandwidth of 2.85%. This is one of very few reported studies on a reflector-backed active metasurface antenna. To the authors’ knowledge, no previous results have been published to show that linear to circular polarization reconfigurability can be achieved with a reflector-backed active metasurface. Antennas using a reflector-backed active metasurface to achieve reconfigurability have potential advantages over that of antennas with transmission metasurfaces. The biasing circuitry may be easier to implement behind the reflector, which will minimize interference on the antenna. Scalability might also be easier for arrays of radiators. The main contribution of this paper is to illustrate that a reflector-backed active metasurface can also be used for linear-to-circular polarization reconfigurability. A printed dipole radiator with a reflector-backed active metasurface was designed and is discussed. Measured results are presented to confirm the validity of the design. 2. Design Procedure A design was performed for a center frequency of 2.4 GHz. The three-dimensional antenna structure is shown in Figure 1. The antenna consists of three components, namely the printed dipole radiating element, the active metasurface, and the electric reflector. The dipole element is fed through the reflector and the metasurface with a coaxial cable. The metasurface was designed with a 6 × 6 elliptical unit cell array. The PIN diode switches are not drawn in Figure 1, but the unit cells were specifically designed to operate with a 7 × 6 array of PIN diodes soldered across the small gaps in the elliptical unit cell profiles at the edges of each unit cell. The antenna has reconfigurable polarization with two polarization states: LP and RHCP. The reconfigurability is achieved through the PIN diodes on the unit cell edges, which either short the two elliptical halves of the unit cell or create an open circuit between the elliptical halves. The PIN diodes are biased appropriately to operate in a forward biased configuration. In the off position a circular polarization state is achieved, and in the on position a linear state is achieved. The diodes are connected in parallel and are biased at the edge of the metasurface through helical coils, which act as RF chokes. The PIN diodes used for the antenna system are BAR65 diodes with a junction voltage and current draw of 0.93 V and 100 mA respectively. The metasurface and the planar dipole antenna were both manufactured on ROGERS 4003C substrate with a height of 0.813 mm. The entire size of the final antenna is 308 × 162 × 35 mm3. A top view of the antenna is shown in Figure 2, with a focus on the unit cell geometry and the dipole element. Figure 3 presents side views of the antenna to clearly show the coaxial feed and helical biasing coils. The reconfigurable reflector-backed metasurface in this paper combines the linearly polarized field radiated directly from the dipole (Ei) in the main beam direction with the reflected fields (Er) from the reflector-backed metasurface to realize a total vector field (ET = Ei + Er) that is either linearly polarized or circularly polarized over the same frequency range. To achieve a circularly polarized radiated wave, the total electric field components, ETx and ETy, should have equal magnitude with a phase difference of 90° between the two components. An initial single unit cell for the reflector-backed metasurface was designed assuming an infinite surface in the xy-plane. The metasurface geometry is similar to the structure used in [19] with a meandering elliptical unit cell. The design was accomplished using full wave electromagnetic simulations in CST Studio Suite 2020 (Dassault Systèmes Simulia, Johnston, R, USA) using perfect electric and magnetic boundary conditions and a floquet port. The Zmax port was positioned in front of the unit cell and excited the unit cell through floquet modes and monitored the reflected fields in front of the unit cell. To design the unit cell the critical parameters were determined through a parametric study. The incident polarization angle remained 45° throughout the initial design of the reflector-backed metasurface unit cell. The method of operation is explained through the effect of the metasurface on the reflected field components. The impedance seen by the two reflected linear field components differs from each other and is affected by the state of the switches at the edges of the unit cells. When the sides of the unit cells are open, the surface acts as if there is a shunt capacitance applied to the Ery component. This shunt capacitance creates a 90° phase shift for the Ery component and in effect creates a circularly polarized reflected wave. When the sides of the unit cell are closed, it eliminates the shunt capacitance that was applied to the Ery component and then the surface reflects an x-directed linearly polarized wave. The critical parameters for adjusting the characteristics of the unit cell include the unit cell width, the unit cell height, the spacing between the reflector and the metasurface, and the radii of the elliptical microstrip line. The axial ratio was calculated for the reflected field using equation (1), where δ is the phase difference between the Erx and Ery reflected field components [15]. (1) AR(dB)=20log10(Erx2+Ery2+Erx4+Ery4+2Erx2Ery2cos2δ)(Erx2+Ery2−Erx4+Ery4+2Erx2Ery2cos2δ) Using the results of the parametric study, a parameter optimization was done to design the reflector-backed metasurface. In the open state, the reflector-backed metasurface operates in a circular configuration, and the reflected Erx- and Ery-field components have equal magnitude and 90° phase difference. In the closed state, the reflected wave consists of only an Ex-field component. The simulated axial ratio of the reflected fields from the designed reflector-backed metasurface in an open state and closed state is shown in Figure 4. The reflector-backed metasurface in an open state produces a 3 dB axial ratio bandwidth of 30%, from 2.03 GHz to 2.75 GHz. The closed state produces a high axial ratio, which shows that the reflector-backed metasurface will be close to linearly polarized within the operating band for this state. The planar dipole element was also initially designed separately (without the reflector-backed metasurface) using CST Studio Suite 2020 (Dassault Systèmes Simulia, Johnston, R, USA). The planar dipole length and width were determined to achieve minimum reflection at the design frequency of 2.4 GHz, for a 50 Ω coaxial feed line. The final design with the printed dipole integrated with the reflector-backed metasurface was then also performed in CST Studio Suite 2020 (Dassault Systèmes Simulia, Johnston, R, USA). This final step in the design procedure included sequential parameter tuning to determine a set of final dimensional parameters (of the printed dipole and the reflector-backed metasurface) that provided acceptable axial ratio, impedance bandwidth, and radiation patterns. The dimensions of the initially designed printed dipole and reflector-backed metasurface were used as starting values for the optimization process. The rotation angle of the printed dipole and the air gap between the metasurface and the reflector are two of the crucial parameters to achieve total radiated fields that are respectively circularly and linearly polarized in the open and closed states of the PIN diodes. The total radiated fields are a combination of the direct radiated fields from the printed dipole, Ei, and the reflected fields from the reflector-backed metasurface, Er. The design parameters of the antenna and their final values are tabulated in Table 1. 3. Results and Discussion The antenna was assembled and measured at the compact antenna range at the University of Pretoria. A photograph of the antenna mounted in the compact antenna range is shown in Figure 5. The reflection coefficient of the antenna in the linear state is shown in Figure 6. The −10 dB impedance bandwidth was measured to be from 2.33 GHz to 2.44 GHz, which equates to a bandwidth of 4.5%. The reflection coefficient for the antenna in the circular state is shown in Figure 7. The measured −10 dB impedance bandwidth is 7%, spanning the frequency range from 2.328 GHz to 2.498 GHz. The measured axial ratio of the antenna is shown in Figure 8. The axial ratio bandwidth is lower than 3 dB throughout the measurement range and is thus larger than 8.3%. The radiation patterns for the antenna in the linear state are shown in Figure 9, Figure 10 and Figure 11 for three different frequencies at the lower edge, center, and upper edge of the operating frequency band. There is acceptable correlation between the simulated and measured co-polarized radiation patterns. The correlation between the simulated and measured cross-polarized patterns is similar in terms of the general shape of the radiation patterns, but the measured levels are higher. Figure 12, Figure 13 and Figure 14 show the radiation patterns for the antenna in the circular state. The correlation between simulated and measured results is acceptable for the co-polarized (RHCP) and cross-polarized (LHCP) patterns. The overall performance of the antenna is satisfactory, but there are some discrepancies between the measured and simulated results. These discrepancies in the performance can partly be attributed to variations in the coils due to the imperfect manufacturing methods used. The coils were required to bias the diodes as normal wiring altered the performance of the antenna. Coils were introduced to normalize the performance—this produced satisfactory results in simulation but not in measurement. There may also be more complex interactions via resonant modes that are created from the reflections of the coils within the cavity between the ground plane and the metasurface. This can be observed in the reflection coefficients shown in Figure 6 and Figure 7 of both linear and circular states of the antenna where resonant effects can be observed around 2.44 GHz. Although somewhat degraded, the measured data of the antenna did satisfactorily demonstrate the concept of creating a reflector-backed active metasurface to create an antenna with polarization reconfigurability with electrical switches. 4. Conclusions Results of a working antenna prototype are presented with reconfigurable polarization which is accomplished through a reflector-backed active metasurface, which is combined with a planar dipole radiating element. The antenna can achieve linear horizontal and right-hand circular polarization states by activating switchable elements on the antenna. Reconfigurability is achieved with PIN diodes on the unit cell elements of the reflector-backed metasurface. The antenna has a physical size of 308 × 162 × 35 mm3 and an impedance bandwidth of 4.5% in the linear state, 7% in the circular state, and an axial ratio bandwidth larger than 8.3%. This gives the antenna an effective bandwidth of 4.5% in the linear state and 7% in the circular state. The simulated results of the antenna showed unidirectional patterns with reasonable cross-polar performance in both linear and circular states. However, the measured cross-polar results were unfortunately degraded by the imperfect implementation of the helical coils. A comparison of the various types of antennas with reconfigurable polarization is presented in Table 2. Most of the antennas are reconfigurable in multiple polarization states where most of the antennas are implemented with an active transmittive metasurface [14,18,19]. Only one author used a similar reflector-backed method to design a reconfigurable antenna [20]. The antenna was reconfigurable for two circular polarization states, while the antenna proposed in this paper can achieve both linear and circular polarization states. The proposed antenna also achieves a better effective bandwidth than the antenna in [20]. Consequently, the proposed antenna is one of a few antennas that are based on a reflector-backed active metasurface and, to the knowledge of the authors, the only one capable of both circular and linear polarization states. The antenna achieved performance comparable with other antennas with reconfigurable polarization. Author Contributions Conceptualization, R.v.A., J.J. and J.W.O.; methodology, R.v.A., J.J. and J.W.O.; formal analysis, R.v.A.; investigation, R.v.A.; writing—original draft preparation, R.v.A.; writing—review and editing, J.J. and J.W.O.; supervision, J.J. and J.W.O. 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 on request from the main author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Three-dimensional antenna structure. Figure 2 Top view of the antenna. Figure 3 Side views of the antenna. Figure 4 Simulated axial ratio of the reflected fields from the designed reflector-backed metasurface in a closed and open state. Figure 5 Antenna measurement set-up. Figure 6 Measured and simulated reflection coefficient of the antenna in the linear state. Figure 7 Measured and simulated reflection coefficient of the antenna in the circular state. Figure 8 Axial ratio of the antenna in circular state. Figure 9 Radiation patterns (Phi = 0° and Phi = 90°) of the antenna in the linear state at 2.35 GHz. Figure 10 Radiation patterns (Phi = 0° and Phi = 90°) of the antenna in the linear state at 2.4 GHz. Figure 11 Radiation patterns (Phi = 0° and Phi = 90°) of the antenna in the linear state at 2.45 GHz. Figure 12 Radiation patterns (Phi = 0° and Phi = 90°) of the antenna in the circular state at 2.35 GHz. Figure 13 Radiation patterns (Phi = 0° and Phi = 90°) of the antenna in the circular state at 2.4 GHz. Figure 14 Radiation patterns (Phi = 0° and Phi = 90°) of the antenna in the circular state at 2.45 GHz. materials-15-03026-t001_Table 1 Table 1 Antenna parameter set. Parameter Description Value Ah Air gap between unit cell and reflector 27 mm P Unit cell width 48 mm H Unit cell height 22 mm Ry Unit cell ellipse y radius 7.8 mm Rx Unit cell ellipse x radius (Rx = P/2) 24 mm Ch Connection block height 2 mm Cw Connection block width 2 mm Sh Switch height 1 mm Sw Switch width 1.2 mm Uw Unit cell microstrip width 1.2 mm Subh Substrate height 0.813 mm Subw Substrate width 308 mm Subl Substrate length 162 mm Rotd Rotational angle of dipole 25° Dh Air gap between surface and dipole 6 mm Dw Dipole width 4 mm Dl Dipole length 50.85 mm Gx Extra substrate length 10 mm materials-15-03026-t002_Table 2 Table 2 Comparison of antennas with reconfigurable polarization. Ref. Reconfiguration Method Polarization States Impedance BW (%) Cross-Polar Discrimination (dB) AR BW (%) Effective BW (%) Lin. Circ. Lin. Circ. [5] Alter radiating element structure LHCP, RHCP, LP 2.6,5.4 28.6 >3 >18 15.4 15.4 [6] Alter feed network structure LHCP, RHCP, LP 30 25 >20 >20 21 20 [14] Rotate metasurface structure LHCP, RHCP, LP 25 37 50 15 14 11 [18] Alter metasurface elements CP, LP 1.8 1.8 Not given Not given 2.4 1.6 [19] Alter metasurface elements LHCP, LP 21 23 10 >18 14 13 [21] Alter metasurface elements LHCP, RHCP N/A 17 N/A >15 4.58 1.6 [20] Alter reflector-backed metasurface elements LHCP, RHCP N/A 12.8 N/A >20 2.85 2.85 This work Alter reflector-backed metasurface elements RHCP, LP 4.5 7 7 11 8.3 4.5 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Andrews J.G. Buzzi S. Choi W. Hanly S.V. Lozano A. Soong A.C.K. Zhang J.C. What Will 5G Be? IEEE J. Sel. 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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093445 sensors-22-03445 Article A Universal Detection Method for Adversarial Examples and Fake Images https://orcid.org/0000-0003-2095-4875 Lai Jiewei 12 https://orcid.org/0000-0001-8403-6470 Huo Yantong 1 https://orcid.org/0000-0003-3734-7350 Hou Ruitao 3* https://orcid.org/0000-0003-3480-8780 Wang Xianmin 3 You Ilsun Academic Editor 1 School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou 510006, China; 1906200093@e.gzhu.edu.cn (J.L.); 1906300038@e.gzhu.edu.cn (Y.H.) 2 Pazhou Lab, Guangzhou 510330, China 3 Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou 510006, China; xianmin@gzhu.edu.cn * Correspondence: 1111906005@e.gzhu.edu.cn 30 4 2022 5 2022 22 9 344517 3 2022 07 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/). Deep-learning technologies have shown impressive performance on many tasks in recent years. However, there are multiple serious security risks when using deep-learning technologies. For examples, state-of-the-art deep-learning technologies are vulnerable to adversarial examples that make the model’s predictions wrong due to some specific subtle perturbation, and these technologies can be abused for the tampering with and forgery of multimedia, i.e., deep forgery. In this paper, we propose a universal detection framework for adversarial examples and fake images. We observe some differences in the distribution of model outputs for normal and adversarial examples (fake images) and train the detector to learn the differences. We perform extensive experiments on the CIFAR10 and CIFAR100 datasets. Experimental results show that the proposed framework has good feasibility and effectiveness in detecting adversarial examples or fake images. Moreover, the proposed framework has good generalizability for the different datasets and model structures. adversarial example deep forgery detection National Natural Science Foundation of China62072127 62002076 CNKLSTISS, Science and Technology Program of Guangzhou, China202002030131 201904010493 Guangdong basic and applied basic research fund joint fund Youth Fund2019A1515110213 Natural Science Foundation of Guangdong Province2020A1515010423 This research was funded by the National Natural Science Foundation of China (No. 62072127, No. 62002076), Project 6142111180404 and supported by the CNKLSTISS, Science and Technology Program of Guangzhou, China (No. 202002030131, No. 201904010493), Guangdong basic and applied basic research fund joint fund Youth Fund (No. 2019A1515110213), Natural Science Foundation of Guangdong Province (No. 2020A1515010423). ==== Body pmc1. Introduction In recent years, as one of the core technologies of artificial intelligence, deep learning has attracted unprecedented attention from academia and industry [1]. Compared with traditional machine learning methods, deep learning produces results with higher accuracy, does not require complex feature engineering, and has better adaptability. Hence, deep-learning technology has been gradually applied to various fields, such as computer vision, speech recognition, natural language processing, autonomous driving, etc., [2,3,4,5]. However, research shows that deep learning still has many problems in its security and privacy [6,7,8,9], such as adversarial examples and deep forgery [10,11]. Szegedy et al. first proposed the concept of adversarial examples [12]. Its basic principle is to add some specific subtle perturbations to the original data; the model would output error results with high confidence. The discovery of adversarial examples illustrates the fragility of deep-learning models. Since then, the researchers have researched adversarial examples and proposed many adversarial example generation methods, such as FGSM, C&W, DeepFool, etc., [13,14,15,16]. These methods can generate adversarial examples with extremely high success rates based on different attack scenarios and targets. Moreover, it was found that the adversarial examples are transferable, i.e., the adversarial examples generated for one model are effective for other similar models [17]. This aggravates the seriousness of deep learning security problems and greatly restricts the application of deep-learning technology in military, medical, financial, and other sophisticated fields [18,19,20]. Except for the security issues of the technology itself, deep learning has abuse problems, such as deep forgery. Deep forgery uses deep-learning algorithms [11], i.e., generative adversarial networks (GANs), to tamper with or forge original data so that observers mistakenly regard fake data as original data. These fake data are realistic, diversified, and challenging to identify. With the help of the ripple effect of online social media, fake data is likely to spread on a large scale, causing a severe social impact. More seriously, if criminals use deep forgery for political or malicious profit-making motives, it will result in many risks and severe threats to political, economic, social, and national security. Hence, the detection of adversarial examples and fake images is a hot issue in academia and industry. To solve the above issue, we explore the detection methods for adversarial examples and fake images. Inspired by membership inference attacks that use the model output to determine whether a sample belongs to the training dataset [21], we observe that there are also differences between the model outputs of normal samples and adversarial examples (fake images). Specifically, the distribution of model outputs is fit using the kernel density estimation. We propose a universal detection method for adversarial examples and fake images based on this difference. This method includes the detector training algorithm and online detection algorithm. The detector training algorithm is used to construct the model output’s dataset and train the detector. This dataset consists of the model outputs of normal samples and adversarial examples (fake images). In addition, the detector is trained to learn the rule of the output distribution of normal samples and adversarial examples (fake images). The online detection algorithm is to obtain the model outputs of samples and calculate detection results. To the best of our knowledge, Li’s method is similar to ours [22]. However, he uses the middle-layer features of the Bayesian neural network to determine normal samples and adversarial examples, and we use the output of the deep neural network. Moreover, our method is not only suitable for the detection of adversarial examples, but also for the detection of fake images. Our contributions consist of the following:Based on the difference in the distribution of model outputs between normal samples and adversarial examples (fake images), we propose a universal detection method for adversarial examples and fake images. We tested the detector’s performance using state-of-the-art generation algorithms of adversarial examples and fake images and proved the effectiveness of the detector. We tested the proposed method on different datasets and neural network structures and proved the generalizability of the detector. The rest of this paper is structured as follows. Section 2 introduces related research. Section 3 presents our method. Section 4 experimentally evaluates our method. Section 5 summarizes our work. 2. Related Work In this section, we introduce the related work of adversarial examples and fake images from attack and defense. 2.1. Adversarial Examples 2.1.1. Attack The generation methods of adversarial examples can be roughly divided into two types: gradient-based methods and optimization-based methods. Gradient-based methods.The basic principle of this type of method is to add perturbations in the gradient direction, and these perturbations should not be easily noticed. FGSM is a one-step method that adds limited perturbations in the gradient direction to search for a similar image, which will cause the model to output wrong results [13]. BIM, also called I-FGSM, which is a multiple-iterations version of FGSM, extends FGSM by running a minor optimization in each iteration [23]. PGD is also an iteration extension of FGSM [24]. Different from BIM directly clipping pixel values, it first utilizes gradient projection to avoid excessive changes in the optimization process. Optimization-based methods. Different from gradient-based methods, its basic principle is to take the generation process of adversarial examples as a constrained optimization problem, that is, to ensure that the model outputs wrong results without being easily noticed. DeepFool adds some minor perturbation to the normal image, causing the image to exceed the classification boundary through iterative calculation [15]. Similar to DeepFool, UAP also uses adversarial perturbations to make normal images exceed the classification boundary [25]. It can be added into most images to generate adversarial examples and have good generalization capabilities on other network architectures. 2.1.2. Defense The defense methods against adversarial examples mainly adopt two strategies: robust classifier and detector-based methods. Robust classifier methods. The robust classifier method improves the robustness of the model, such as defensive distillation [14] and adversarial training [13]. For defensive distillation, the model can be smoother than the original model by assigning a larger value of T during the student model training stage, which would reduce the sensitivity to perturbations and improve the robustness and generalizability of the model. Adversarial training is currently the most effective defense method. Its basic idea is to assign the correct labels to adversarial examples and then train the model with these samples to improve its robustness. It has also been proved that adversarial training can provide higher precision and regularization for models [13]. However, adversarial training also presents some challenges. Adversarial training needs to generate many adversarial examples, so the computational cost and time cost of the method are very high. The adversarial example generation methods are constantly updated, which leads to the continuous retraining of the model. Detector-based methods. This strategy trains a detector to distinguish between adversarial examples and normal samples. Feinman et al. believe that the adversarial examples deviate from the manifold region of the real data, so they use the kernel density estimation function in the feature space of the middle layer to detect abnormal points that deviate from the data manifold [26]. Ma et al. observed that the Local Intrinsic Dimension of the hidden layer output differs between normal images and adversarial examples. They used this characteristic to detect adversarial examples [27]. Tian et al. found that image processing operations could invalidate the adversarial examples, which would not affect the classification of the normal images [28]. MagNet constructs multiple autoencoders and uses the reconstruction errors of autoencoders to detect adversarial examples based on cryptographic randomness [29]. SafetyNet detects adversarial examples that rely on neural activation patterns with SVM [30]. Li et al. found that the output distribution of the hidden layer of the adversarial examples was different from that of the normal images, so they used the Bayesian neural network to simulate the output distribution of the hidden layer and detect the adversarial examples using distribution dispersion [22]. 2.2. Fake Images 2.2.1. Attack Traditional image forgery methods are generated mainly by image-editing software. With the development of GANs, GANs-based generation methods for fake images have become the mainstream. Software-based method. It is straightforward to use powerful image editing software to generate fake images without leaving perceptible artifacts. Those methods can be divided into the copy-move and splice methods, which create fake images without leaving traces by adding new content to the original image or perform image stitching, respectively. In addition, the copy-move method is the mainstream method that can change the entire meaning of the original image. GANs-based method. GANs is a method of unsupervised learning that Goodfellow proposes. It consists of a generator and a discriminator. Taking the normal image or the generator’s output as input, the discriminator distinguishes the generator’s output from the real sample as much as possible. The generator randomly samples from the latent space as input and tries to imitate the real samples in the training set to fool the discriminator. Two neural networks learn by confronting each other and constantly adjusting the parameters. With the development of GANs technology, GANs are used for different scenarios, for example, generating high perceptual quality images, domain transfer, image to image translations, and so on [31]. 2.2.2. Defense Defense methods against fake images are roughly divided into defense against software-based fake images and defense against GANs-based fake images. Defense against the software-based fake image. The methods of image-manipulation detection can be summarized into two types: (i) Active: people embed some additional information, i.e., digital watermarks or digital fingerprinting, into the image to determine the authenticity of the image [32]. However, active approaches have some shortcomings, such as difficulty in secondary propagation and single verification, which are confronted with overlooked challenges. (ii) Passive: passive approaches extract the features from the images and use these features for forgery detection [33]. For example, it can identify contrast enhancement, reveal image resampling, etc. To solve the problem that an image may use multiple tampering methods, the authors in [34] use various features in a steganalysis to detect the fake image and identify tampering types. However, these traditional approaches are mostly ineffective when identifying GANs-based fake images. Defense against GANs-based fake image. Similar to adversarial-example detection, the most direct method of detecting fake images is to train the detector using real and fake data. Marra et al. show that a simple fake image detector could be constructed using an image translation network [35]. A three-channel co-occurrence matrix-based detection method was proposed in [36]. Dang et al. realized that the detection of fake face images and the location of the tampered region depend on an attention mechanism [37]. Some researchers believe that, due to the diversity of fake images and the continuous updating of generation methods, the detector could only distinguish the fake images in training. To enhance the generalizability of the detector, Zhang et al. proposed a fake image-generation method called AutoGAN [38]. This method uses a frequency-spectrum input instead of pixel-space input to train the detection model. On the contrary, Wang et al. found that only using a fake image and then performing data pre-processing or data enhancement to expand the training data set could improve the generalizability of the detector [39]. 3. Method In this paper we mainly focus on the detection of adversarial examples and GANs-based fake images, and we present our method in detail in this section. 3.1. Overview 3.1.1. Observation We observed the difference in the distribution of model outputs between adversarial examples (fake images) and normal samples through experiments. Specifically, we first obtained the output of Googlenet on normal samples, adversarial examples, and fake images, then used kernel density estimation to fit the distribution of model outputs. The result is shown in the Figure 1. In Figure 1, TOP1, TOP2, and TOP3 indicate the top 1 value, the top 2 values, and the top 3 values of the model outputs, respectively. NOR, ADV, and GBI represent normal data, adversarial examples, and fake images, respectively. ADV and GBI are generated by DeepFool [15] and WGAN [40], respectively. It can be seen from Figure 1 that there are significant differences in the distribution of model outputs between the normal images and the adversarial examples (fake images). 3.1.2. Framework Based on the above observation, we propose a universal detection method for adversarial examples and fake images. The overall framework is shown in Figure 2. Figure 2 shows that the method mainly includes two stages: detector training and online detection. The purpose of detector training is to learn the difference in the distribution of model outputs between the normal samples and adversarial examples (fake images) to distinguish the normal samples from adversarial examples or fake images. Therefore, we need to generate a certain number of adversarial examples or fake images in advance as training data. Moreover, to reduce the time-cost of training and improve the detection efficiency, we chose the first k values from the model output to represent the distribution of outputs. The purpose of online detection is to detect adversarial examples or fake images. The following is a detailed introduction to detector training and online detection. 3.2. Detector Training The main work of detector training includes constructing the training dataset and training detector, and the basic process is shown in Algorithm 1. Algorithm 1 Detector Training Algorithm. Require:  Normal Data Dn, Generator G, Target Model F   1: Dm←G(Dn)   2: D← Merge(Dm,Dn)   3: Dout←F(D)   4: Dtrain← Top(k,Dout)   5: D← Train(D,Dtrain) According to Algorithm 1, normal data, the malicious data generator, and the target model, F, should be obtained before training the detector. Specifically, we first use G to generate adversarial examples or fake images, as shown in Line 1. G represents some mainstream adversarial examples or fake-image-generation methods. Line 2 merges normal data and adversarial examples (fake images). Line 3 inputs the merged data D into F to obtain the output distribution dataset Dout. In our experiments, F is the classifier trained on the CIFAR10 or CIFAR100 datasets. To reduce the complexity of the detector and improve the detection efficiency, we selected the top k values from the model output to represent the output distribution, as shown in Line 4. Line 5 uses the dataset Dtrain to train the detector D. The detector can be trained offline and deployed online to reduce the time-cost. 3.3. Online Detection The main work of online detection includes obtaining the model output of the untrusted data and computing the detection result. The basic process is shown in Algorithm 2. Algorithm 2 Online Detection Algorithm. Require:  Untrusted Data Du, Target Model F, Detector D   1: Duout←F(Du)   2: Duk← Top(k,Duout)   3: Result←D(Duk) According to Algorithm 2, Line 1 obtains the model output of untrusted data Du. Line 2 selects the top k values from Duout to obtain Duk. Finally, Duk is input into the detector D to obtain the detection result. 4. Experiments In this section, we experimentally evaluate the proposed method using the CIFAR10 and CIFAR100 datasets. Both CIFAR10 and CIFAR100 are natural image datasets, and both include 50,000 training images and 10,000 test images. However, there are ten classes in CIFAR10 and 100 classes in CIFAR100. The experiments include performance experiments, generalizability experiments, and transferability experiments. Additionally, we use AUC as a measure of our detector’s performance in our experiments. Next, we will introduce the experiments in detail. 4.1. Performance Experiments The performance experiments were used to test the ability of our method in adversarial example detection or fake image detection. 4.1.1. Performance in Adversarial Example Detection We used nine state-of-the-art adversarial example-generation methods for detection, including FGSM, DeepFool, BIM, PGD, C&W, etc., [13,14,15,23,24]. The experimental results are shown in Table 1 and we mark out the best detection result using bold text for each type of adversarial example. From Table 1, we know: (1) Given the generation methods of adversarial examples in training, if these methods are the same as the generation methods in the evaluation, the detector almost reached the highest level of detection accuracy; on the contrary, the detection accuracy decreased slightly. (2) On the whole, when the generation method in training is ZOO or NewtonFool, the detector reaches the best detection performance. Hence, in the real world, we could use ZOO or NewtonFool to generate adversarial examples in training. 4.1.2. Performance in Fake Image Detection Considering that the mainstream generation methods of fake images are mainly based on GAN, we selected eight state-of-the-art GAN-based algorithms to test the detector’s performance. The experimental results are shown in Table 2 and we mark out the best detection result using bold text for each type of fake image. It can be seen from Table 2 that the detection results of fake images are similar to the adversarial examples. Given the generation methods of fake images in training, if these methods are the same as the generation methods in the evaluation, the detector achieved the best detection performance; on the contrary, the detection accuracy decreased slightly. In addition, when the generation method in training was WGAN_DIV [40], the detector reached the best detection performance. Hence, WGAN_DIV is a candidate to generate fake images in training in the real world. 4.2. Generalizability Experiments The generalizability of the detector mainly includes (1) the generalizability of datasets; (2) the generalizability of target model architecture. In addition, the generation methods of adversarial examples and fake images are DeepFool and WGAN [15,40], respectively. In addition, we have to describe the experiment case in the form of condition I–condition II. For example, CIFAR10–CIFAR100 represents that the detector is trained by CIFAR10 and evaluated by CIFAR100. Limited by the two time-scale update rule (TTUR), we only use AutoGAN [41] and TransGAN [42] generators on the CIFAR10 dataset. Below, we provide a detailed introduction to the experimental content. 4.2.1. Generalizability for Dataset We alternately used CIFAR10 and CIFAR100 as the training dataset and used CIFAR100 and CIFAR10 as the evaluation dataset to verify the generalizability of the detector for the dataset. The experimental results are shown in Figure 3. As shown in Figure 3, the AUC values of adversarial example detection are mainly distributed between 0.5 and 0.8; most of the AUC values of fake image detection are between 0.6 and 0.8. Hence, the generalizability of the fake image detector is slightly stronger than that of the adversarial example detector, but it still needs to be further improved. 4.2.2. Generalizability for Target-Model Architecture We selected five neural network structures to verify the generalizability of the target model structure, including Resnet18, VGG11, Googlenet, Densenet121, and Inceptionv4. Specifically, we first selected one of the network structures as the target model, one after the other in turn, then used the output of the target model to train the detector, and finally used the remaining networks to evaluate the generalizability of the detector. The experimental results are shown in Figure 4. From Figure 4, the adversarial example detector shows good generalizability for different model structures. However, there are a few cases below the average level. For example, the generalizability for Densenet121 on the CIFAR10 dataset, the generalizability for VGG11 and Googlenet on the CIFAR100 dataset, etc. Similar to the adversarial example detector, the generalizability of the fake image detector for the model structure is generally reasonable. 4.3. Transferability Experiments The transferability experiments include (1) testing the ability of the adversarial example detector to detect fake images; (2) testing the ability of the fake image detector on adversarial examples. The experimental results are shown in Figure 5. As shown in Figure 5, for the CIFAR10 dataset, the AUC values of the detectors are mainly distributed from 0.7 to 0.9, but the fake image detector is more stable. For the CIFAR100 dataset, the transferability of the fake image detectors is significantly better than that of adversarial example detectors, all distributed around 0.9. This shows that our method has good transferability, and a single detector can be used to simultaneously detect adversarial examples and fake images to a certain extent. 5. Conclusions In this paper, we observe the difference in output distribution between normal samples and adversarial examples (fake images) and propose a universal detection method for adversarial examples and fake images. The method mainly includes two stages: detector training and online detection. In the detector-training stage, we used the output distribution of normal and adversarial samples (fake images) to train the adversarial example (fake image) detectors. After training the detector, we took the model output of untrusted data as the input of the detector to realize online detection of adversarial examples or fake images. We experimentally verified our method using CIFAR10 and CIFAR100 datasets, and the results show that: (1) the detector has a good detection ability for adversarial or fake images; (2) the detector has good generalizability for different model structures; and (3) the detector has good transferability, that is, the adversarial example detector and fake images detector can effectively detect fake images or adversarial examples. Hence, in the real world, our method is feasible and effective. Author Contributions Conceptualization, Methodology, Software, J.L.; Software, Y.H.; Writing—Reviewing and Editing, R.H.; Reviewing and Editing, X.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 Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The difference of the distribution of model outputs between normal samples and adversarial examples (fake images). Figure 2 The framework of our method. Figure 3 The generalizability for dataset. Figure 4 The generalizability for target model architecture. (a,b) are the experimental results of ADV on CIFAR10 and CIFAR100. (c,d) are the experimental results of GBI on CIFAR10 and CIFAR100. Figure 5 The result of transferability experiments. (a) is the experimental result on CIFAR10. (b) is the experimental result on CIFAR100. sensors-22-03445-t001_Table 1 Table 1 The results of adversarial example detection (The vertical axis and the horizontal axis represent training and evaluation, respectively). CIFAR10 FGSM DeepFool BIM PGD AutoPGD UPA NewtonFool ZOO C&W FGSM 0.905 0.911 0.796 0.781 0.757 0.817 0.873 0.869 0.875 DeepFool 0.898 0.916 0.799 0.784 0.756 0.796 0.875 0.866 0.871 BIM 0.884 0.887 0.833 0.811 0.776 0.802 0.871 0.865 0.872 PGD 0.887 0.890 0.832 0.813 0.813 0.780 0.804 0.876 0.865 AutoPGD 0.867 0.877 0.778 0.769 0.783 0.871 0.853 0.846 0.862 UPA 0.860 0.872 0.744 0.715 0.880 0.880 0.835 0.826 0.837 NewtonFool 0.903 0.907 0.817 0.803 0.774 0.829 0.889 0.877 0.895 ZOO 0.902 0.906 0.820 0.803 0.774 0.827 0.888 0.879 0.892 C&W 0.901 0.905 0.817 0.800 0.772 0.841 0.888 0.876 0.896 CIFAR100 FGSM DeepFool BIM PGD AutoPGD UPA NewtonFool ZOO C&W FGSM 0.882 0.910 0.869 0.864 0.875 0.907 0.880 0.888 0.883 DeepFool 0.871 0.922 0.856 0.855 0.854 0.910 0.874 0.870 0.871 BIM 0.879 0.913 0.874 0.864 0.877 0.906 0.889 0.891 0.887 PGD 0.877 0.903 0.871 0.873 0.876 0.894 0.885 0.890 0.890 AutoPGD 0.878 0.908 0.869 0.864 0.880 0.902 0.888 0.888 0.887 UPA 0.865 0.865 0.843 0.842 0.848 0.917 0.855 0.864 0.859 NewtonFool 0.873 0.904 0.869 0.867 0.867 0.891 0.889 0.889 0.887 ZOO 0.880 0.909 0.870 0.870 0.877 0.902 0.885 0.894 0.887 C&W 0.879 0.879 0.873 0.871 0.877 0.895 0.886 0.891 0.892 sensors-22-03445-t002_Table 2 Table 2 The results of fake image detection (The vertical axis and the horizontal axis represent training and evaluation, respectively). CIFAR10 GAN ACGAN WGAN WGAN_GP WGAN_DIV DCGAN AutoGAN TransGAN GAN 0.743 0.680 0.776 0.789 0.783 0.680 0.579 0.518 ACGAN 0.495 0.855 0.798 0.892 0.874 0.827 0.624 0.562 WGAN 0.548 0.775 0.830 0.885 0.875 0.758 0.602 0.555 WGAN_GP 0.505 0.806 0.808 0.906 0.886 0.786 0.604 0.545 WGAN_DIV 0.512 0.787 0.811 0.900 0.891 0.780 0.599 0.535 DCGAN 0.502 0.844 0.795 0.878 0.868 0.839 0.637 0.554 AutoGAN 0.551 0.787 0.778 0.813 0.796 0.785 0.647 0.585 TransGAN 0.579 0.765 0.761 0.789 0.764 0.754 0.638 0.586 CIFAR100 GAN ACGAN WGAN WGAN_GP WGAN_DIV DCGAN GAN 0.822 0.839 0.740 0.827 0.842 0.825 ACGAN 0.716 0.877 0.711 0.866 0.877 0.809 WGAN 0.786 0.837 0.768 0.845 0.853 0.818 WGAN_GP 0.734 0.869 0.726 0.871 0.879 0.822 WGAN_DIV 0.739 0.872 0.726 0.868 0.885 0.824 DCGAN 0.762 0.863 0.747 0.866 0.877 0.847 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Le Cun Y. Bengio Y. Hinton G. 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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093198 materials-15-03198 Article Investigation of Scanning Strategies and Laser Remelting Effects on Top Surface Deformation of Additively Manufactured IN 625 Paraschiv Alexandru 1* https://orcid.org/0000-0002-6663-3420 Matache Gheorghe 1 Constantin Nicolae 2 Vladut Mihai 1 Antoniac Iulian Vasile Academic Editor Bita Ana-Iulia Academic Editor Mocanu Aura-Catalina Academic Editor 1 Special Components for Gas Turbines Department, Romanian Research and Development Institute for Gas Turbine COMOTI, 220D Iuliu Maniu, 061126 Bucharest, Romania; gheorghe.matache@comoti.ro (G.M.); mihai.vladut@comoti.ro (M.V.) 2 Materials Science and Engineering Faculty, University “Politehnica” of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania; nicolae.constantin@upb.ro * Correspondence: alexandru.paraschiv@comoti.ro 28 4 2022 5 2022 15 9 319806 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 main drawbacks of the Laser Powder Bed Fusion (LPBF) process are the surface quality and dimensional accuracy of manufactured parts due to the edge and corner effects. These effects can be diminished by using an appropriate balance of the process parameters and scanning strategies. This paper focuses on the assessment of reducing the edge and corner effects that occur in additively manufactured IN 625 alloy via the LPBF technique by varying the hatch angle rotation (by 45°, 67°, and 90°) and volumetric energy density (VED), and using the laser top surface remelting technique (LSR). The edge and corner effects of the cubic samples were quantitatively evaluated on the top surface by 3D laser surface scanning. It was found that the edge and corner effects became more pronounced in the cases of samples built with no contour and hatch angles of 45° and 67°, while the smallest deformations were obtained when the hatch angle was rotated by 90°. Moreover, the heights of both the edge and corner ridges increase as the number of remeltings passing the top layer increases. Conversely, when a lower VED was used for melting the top layer(s) of the samples, the edge and corner ridges were slightly reduced. LPBF edge effect corner effect hatch angle contour remelting Romanian Ministry of Education and Research2N/2019 This research was performed within the “Nucleu” Program, Grant no. 2N/2019, funded by Romanian Ministry of Education and Research. ==== Body pmc1. Introduction The Laser Powder Bed Fusion (LPBF) has gained considerable attention in the last decade due to its many advantages compared to conventional subtractive manufacturing techniques, such as geometric freedom, low product times, mechanical performances, and reduction of components and material flexibility [1,2,3,4,5]. For this reason, LPBF is one of the most promising metallic additive manufacturing (AM) techniques for producing end-use parts in the aerospace, biomedical, and automotive industries [2,4,6,7]. Nevertheless, despite progress in mechanical performance and material flexibility, there are still multiple drawbacks of LPBF technology—including anisotropy of the mechanical properties [8,9], high-temperature gradients [10], internal stresses [7], part distortion [7], low surface quality [1,5,6], and dimensional accuracy [11,12,13,14]—that keep it behind conventional manufacturing as a widely used technology. In an LBPF process, many physical phenomena occur, such as melting solidification, heat convection and radiation, Marangoni convection, absorption, recoil pressure, capillary forces, phase transformation, evaporation, and chemical reactions [9,15,16,17]. The surface quality and dimensional accuracy depend on many factors, such as material, powder particle size, laser parameters, layer thickness, building orientation, or chamber conditions [12,18,19]. Alongside the laser parameters and layer thickness, the scanning strategy strongly influences the thermal gradient, melt pool morphology, and thermomechanical behaviour of the additively manufactured (AMed) part [7]. Typical top and side surface defects encountered on the LPBF parts are high surface roughness, pores, thermal cracking, delamination, balling, and staircase effects [6,12,20]. Additionally, the elevated edges, often called the “edge effect”, affect the final dimensional accuracy and surface quality of LPBF parts [7,19], and can affect the manufacturing process and mechanical properties of the part due to contact between these edges and re-coater [5,12]. The edge effect is not only encountered in the LBPF process but also in other powder bed fusion processes such as laser engineered net shaping (LENS) and electron beam melting (EBM) [5]. The resultant thermal deformation issue of AMed parts during material solidification layer-by-layer is due to the high-temperature gradients and high cooling rates [10]. Expensive and time-consuming post-processing operations are used beforehand to improve the surface characteristics and make the LPBF parts suitable for many applications [6]. Therefore, a comprehensive analysis should be carried out at the initial step of designing the part to reduce the surface deformations and defects of AMed parts as much as possible. Depending on requirements, various surface finishing methods—such as mechanical methods (machining and abrasive blasting), chemical and electrochemical processes or thermal processes—are generally used for geometrical corrections and to reduce the surface roughness of AMed parts [12,18,21,22,23,24]. The influence of process parameters on the quality surface, especially surface roughness, has been investigated in many studies [2,3,6,11,24]. However, only a few studies have evaluated the edge effects and dimensional accuracy [5,19,20]. Many studies in recent years have shown that the surface quality can be improved by using the laser polishing of laser remelting technique (LSR) [1,11,12,20,23], appropriate scanning strategies [7,25], and laser powers [12,19]. Using the contour scan with an appropriate selection of parameters improves the inclined surfaces of parts but is not significant for up-skin surfaces [12]. LSR, whereby a melt layer is remelted one or several times, is considered by many [1,12,24,26,27] as a viable surface finishing method of LPBF parts. Using the LSR strategy for each layer of an AMed part, several characteristics and mechanical properties can be improved, including density [24], mechanical properties [28], surface roughness [29], friction and wear behaviour and microhardness [30], corrosion resistance [31], and microstructure [11,13,23]. By laser melting each layer of the LPBF parts, Yasa et al. [11] showed that the surface roughness and microhardness could be significantly improved, Liu et al. [1] revealed that the quality and relative density could be efficiently improved, and Shiomi et al. [32] found that residual stress of the as-built parts is reduced. However, improving the surface roughness and especially the density of parts is done by remelting each layer [1], which increases production times [29]. When laser remelting is used for the outer skin or the last layer of an additively manufactured part, the production time is not significantly affected, and surface characteristics such as surface roughness or balling effect can be reduced [13,20,23,24,27]. Ukar et al. [27] showed that the surface roughness of Selective Laser Sintering parts could be reduced by over 80%, and Kruth et al. [23] reduced the surface roughness (Ra) from 12 µm to 1.5 µm after using the laser remelting technique. In addition, Kruth et al. [30] analysed the effects of the LSR strategy with different process parameters for twice melting the last twenty layers of parts, and obtained a significant roughness improvement and an increase in microhardness and wear behaviour. Other works showed that the tensile stress of the top surface is reduced by 55% when remelting is used for the last layer [32] and only 10% when LSR is used for every layer [33]. The residual stresses occurring during the manufacturing process are a common inconvenience in LPBF parts. Increased residual stresses in AMed alloy exhibit surface defects and dimensional inaccuracies. Currently, the literature contains limited reports on minimising the edge effects and dimensional accuracy of LPBF parts by varying the laser parameters and scanning strategies. Matache et al. [19] studied the influence of laser power and scanning speed on edge and corner effects in the LPBF process of IN 625 alloy and found that the elevated ridges generated on both specimen sides and corners are strongly influenced by the energy input; additionally, they increase as the laser power is increased and decrease as the scanning speed is increased. Metelkova et al. [20] studied the edge effect of samples after the top surface was remelted from one to ten times with different hatch angles between each remelting layer, keeping the other process parameters constant. They found that as the number of remelting passes increased, the height of the edges decreased and the edge length increased. Yasa et al. [5] found that the edge effect is amplified when a contour scan is used, but that the flatness of the top surface could be further improved by applying raster scanning instead of unidirectional scanning. There is no possibility of eliminating the edge effect of LPBF parts due to the stress distribution phenomenon [7], but using appropriate process parameters and scanning strategies can improve the flatness of parts [5,19]. A solution for removing or diminishing the edge and corner effects of AMed IN 625 parts may be to reduce the VED for the last layer(s). Another solution that should be considered is the scanning strategy, which may significantly influence the residual stress and deformation of LPBF parts due to variance in local heat distribution [7]. The stripe pattern scanning strategies with an interlayer rotation of 67°, 45° or 90° are often used in an LPBF process. However, various scanning strategies, such as island scanning, cheeseboard, hexagonal, line and rotate scanning at different angles, zig-zag, and in-out and out-in scanning, can be used in an LPBF process [4,7,23,25]. B. Cheng et al. [7] investigated eight of these scanning strategies by a dual simulation-experimental approach and found that the 45° and 67° line-scanning strategy has the minimum stress and deformation values. In contrast, the in-out scanning case has the highest deformation, and there was no significant difference in deformation among line scanning, 45° line scanning, and 45°, 90° and 67° rotate scanning cases. Kruth et al. [23] investigated the effect of scanning pattern and scanning vector length on the residual stress. They found that the maximum residual stress reduction was achieved when islands rotated 45° from the x-axis. However, the edge and corner effects are not explored thoroughly in the LPBF process, much less the influence of different combinations of scanning strategies, laser parameters, and LSR. The impact of laser power and scanning speed on the edge and corner effects of IN 625 cubic samples with no contour scan is thoroughly reported in another study [19]. It was found that laser power between 250–300 W and scanning speeds between 0.7–0.8 m·s−1 generate a more stable melt with slightly elevated edges and corners. The present study used these experimental data as input data to evaluate the edge effect on the same IN 625 cubic samples using different scanning strategies, laser top surface remelting, and two volumetric energy densities (VED). 2. Materials and Methods For this study, samples of 10 × 10 × 10 mm3 were built with a Lasertec 30 SLM (DMG Mori, Bielefeld, Germany) using vacuum gas-atomised IN 625 metal particles (supplied by LPW Technology Ltd., Runcon, UK) as raw material. The IN 625 is one of the most used printable corrosion-resistant materials for high-temperature applications due to its ability to maintain these characteristics even after long exposure to elevated temperatures [34]. The IN 625 powder with the chemical composition presented in Table 1 is predominantly regular, with spherical shaped particles and a size range of 15–45 µm, and the particle size distribution D10 = 20 ± 2 μm, D50 = 30 ± 5 μm, D90 = 45 ± 5 μm experimentally determined by the authors in another study [35]. The Lasertec 30 SLM machine is equipped with a 600 W Yb: YAG fiber laser and has a building volume of 300 × 300 × 300 mm3. To avoid metals oxidation, during manufacturing the chamber was flooded with 99.996% pure Argon until a value below 0.2% oxygen was reached. The IN 625 samples were built on a platform preheated to 80 °C using a cross-type support structure with a 3 mm height designed by the software machine (Rdesigner v2019, Realizer GmbH, Borchen, Germany). Sets of two IN 625 cubic samples with contour and no contour scan were built for each variation of the hatch angle rotation, volumetric energy densities (VED) used for the last layer(s), and the number of remelts of the last layer. The first set of two IN 625 cubic samples was built with contour and no contour scans using the same hatching parameters and scanning strategies. The results of optimising the laser parameters to minimise the edge effect are presented elsewhere [19]. The following hatching parameters, which have been selected based on previous work by the authors [19] to reduce the edge effect as much as possible, will hereafter be considered as standard hatching parameters: laser power (250 W), scanning speed (0.75 m/s), layer thickness (40 μm), and hatch distance (0.11 mm). Based on Equation (1), a laser energy input (VED) of 76 J/mm3, which will hereafter be referred to as standard VED, was generated by using these process parameters. (1) VED = Pν · h · tJmm3 where P is the laser power (W), ν is the scanning speed (mm/s), h is the hatch distance (mm), and t is the layer thickness (mm). For the scanning pattern, three basic hatch angles with rotation of 45°, 67°, and 90° between successive layers schematically shown in Figure 1 were set for both cubic samples with contour and no contour scans. The samples were manufactured according to the standard hatching parameters and contour parameters recommended by the printer manufacturer: laser power (125 W), scanning speed (0.5 m/s), layer thickness (40 μm), fill lines distance 0.1 mm, hatch distance 0.11 mm, and base offset 0.1 mm. Other sets of samples with no contour scan were built with 45°, 67°, and 90° hatch angle rotations, and were investigated with the last top layer remelted once, twice, and three times. Finally, cubic samples with no contour scan were manufactured using the same hatching parameters and hatch angle rotations but with a lower VED for melting the last layer(s). For this specific lower VED, the laser power was decreased from 250 W to 150 W, while the laser power was increased from 0.75 m/s to 0.9 m/s, generating a lower VED (63 J/mm3) than standard VED (76 J/mm3) to melt the last one, two, three, five, and ten layers. Each sample was built with no contour scan to eliminate the influence of other factors on the edge and corner effects. The top-surface topography of the samples (parallel to X–Y plane) was evaluated by 3D laser surface scanning using a coordinate measuring machine NIKON Altera 10.10.8 (LK Metrology Ltd., Derby, UK). The 3D laser surface scanning was equipped with a non-contact NIKON LC15Dx (laser scanning probe with an accuracy of 1.9 µm and an analysis allowance set to 5%). A laser profile with the following process parameters was chosen for scanning the samples: 0.01 mm distance between stripes, 100% laser power, 1% laser exposure, 20% signal threshold, 75° maximum inclination, and 5% edge filter. The edge and corner effects of the samples were quantitatively evaluated by post-processing and analysis of numerically extracted data using dedicated software (FOCUS 2019 R2, Nikon Metrology NV, Leuven, Belgium). 3. Results 3.1. The Influence of Contour Scan and Hatch Angle Rotation The elevated ridges that form during the solidification of the alloy reduce the topology and dimensional accuracy of AMed parts. In this study, the evolution of the top surface morphology in terms of elevated ridges and corners was investigated, and different hatch angle rotations and corrective techniques such as laser remelting of the last layer or melting the last layer(s) with a low VED were used to improve the dimensional accuracy of IN 625 samples. The top surfaces of samples with contour and no contour built with hatch angle rotations of 45°, 67°, and 90° have been analysed comparatively. Figure 2 presents the macrographs of the top surface of samples built with contour scan and hatch angle rotations of 45°, 67°, and 90° between successive layers. Figure 2 shows the texture of top surface samples with a contour scan built with 45°, 67°, and 90° hatch angle rotations, consisting of individual melting tracks, contour tracks along the edges, and elevated ridges and corners. During the melting process, the elevated edges and corners are generated due to the surface tension that usually decreases with temperature and tends to drive the melt away from the centre of the melt pool [36]. Due to the layer-by-layer process, the cumulative effects of edges and corners can produce a severe deformation that affects the part’s quality surface [19]. The corresponding 3D scanning of the top surface of samples with contour and no contour built with 45°, 67°, and 90° hatch angle rotation are presented in Figure 3a–l. Topographical analysis of top surfaces showed that the elevated ridges on both sample’s sides and corners, generated during solidification, were more prominent when the contour was not used. Even if the cross-section of the sample is square, the corners and edges of the same sample may differ significantly. During the rapid melting and solidification of the alloy, a material build-up occurs due to the compressive stress accumulated around the corners [7] and the thermal warping effect [12]. The scan line being adjacent to the edge of the specimen [3] causes the formation of elevated ridges. Although the melting tracks are visible in macrographs, the 3D laser surface scanning could not highlight them due to the short hatch distance and small melt pool dimensions. According to a previous study [8], where the morphology and dimensions of the melt pool obtained using the same process parameters as in this study were investigated, the melt pool width and height are 150 ± 17 µm and 86 ± 33 µm, respectively. Furthermore, using a 0.11 mm hatch distance allowed us to achieve a relatively smooth surface, the texture of which could not be detailed by 3D laser surface scanning. However, this study aimed to evaluate the edge and corner effects occurring in AMed IN 625 alloy, and the 3D laser surface scanning has proven to be an effective and reliable technique for measuring the edge effect, as shown in a previous study [19]. To quantitatively measure the edge and corner ridges induced by the contour scan and scanning strategy, the edge and corner heights and edge width were evaluated based on the data extracted from the surface profiles generated by the 3D laser surface scanning. Additionally, the topography top surface views indicated the highest and deepest points and the relative widths of the sample edges (noted with x and y). As shown in Figure 4, the corner height (h) was measured as the mean of the four highest points (noted with h1, h2, h3 and h4) from the mean of the flat surface corresponding to the corners of the sample, while the edge height was measured as the maximum height from the mean of the flat surface. In contrast, the edge width (w) was measured as the difference between the side of the specimen and the endpoint where the side ridges end. A relatively high degree of scattering can be obtained when measuring the edge height and width due to the section in which the measurements were performed representing only a tiny area of the specimen, which does not always include the highest points of the edge. Based on the data extracted from the surface profiles of the samples investigated by the 3D laser surface scanning, the quantitative analysis of the edge and corner effects is graphically represented in Figure 5a–c. The quantitative analysis of the edge effect has revealed that the hatch angle rotation strongly impacts the quality of samples’ top surface by generating elevated ridges on both part’s sides and corners. A global decrease of elevated edges (Figure 5b) and especially corners (Figure 5a) of samples was observed, indicating that using the contour has a corrective action on surface deformation regardless of the hatch angles rotation (45°, 67° or 90°). Manufacturing samples with contour partially solves the deformation problem, but this cannot be used as an ultimate solution, as the dimensional accuracy is highly affected by the corner and edge effects. In all cases, these ridges were more amplified when a 45° hatch angle rotation was used and least amplified when a 90° hatch angle rotation was applied. This behaviour could be related to the accumulated residual stress and higher thermal gradients caused by the 45° and 67° hatch angle rotations that lead to local deformations at the corners and edges of AMed parts. The 90° hatch angle rotation implies a more stable melt pool near the sides of the samples. Due to the epitaxial solidification, a checkerboard pattern is obtained when the scanning between two successive layers is rotated by 90°, while in the cases of scanning by 67° and 45°, the grains are orientated in hexagonal ways. 3.2. The Influence of LSR According to the literature, the LSR strategy was applied to the last layer of cubic samples during the manufacturing process to improve the dimensional accuracy of AMed parts. The LSR strategy was used for remelting the last layer of samples once, twice, and three times using the same standard process parameters and hatch angles rotation (45°, 67° or 90°). The samples were built with no contour scan to avoid the influence of other factors on the edge and corner effects. Examples of the top surface morphologies of samples built with a 45° hatch angle rotation and a remelting of the last layer once, twice, and three times (c) are presented in Figure 6a–h. The LSR strategy negatively influences samples’ edge and corner heights, regardless of the hatch angle rotation. The surface deformations increase as the remelting passes of the last layer increase, and the corner and edge heights become more prominent, as shown in Figure 7a–c. The quantitative analysis in Figure 7a–c shows that the elevated ridges increase by decreasing the scan angle rotation and increasing the top layer’s remelting passes. The graph in Figure 7a shows that this behaviour is more pronounced for the corner height, which increases significantly with decreasing hatch angle and increasing number of passes, especially after the third passe. A similar but less pronounced trend was observed for the edge height, as shown in Figure 7b, while the edge width is not significantly affected until after the third remelting passe. The laser beam pushes the remolten material to the sides, increasing the dimensions of the corners and edges. The main reason for this behaviour may be the too-high VED [11,19]. When the VED used is too high, the molten becomes unstable and generates a recoil pressure that partially pushes the melt to the edge [17,19]. Another reason for the accentuation of the edge effect by the remelting passes of the last layer may be the increase in residual stresses. Generally, lower laser power and higher scan speed are preferred because a lower VED induces a less pronounced edge and corner effect [11,19]; however, it can affect the density, surface roughness and mechanical properties. 3.3. The Influence of Using a Lower VED for the Last Layer(s) A third case study was to check if using a lower VED for the last layer or several layers is enough to diminish the elevated edges and corners. Therefore, samples with no contour scan were manufactured using the same scanning strategies but with a lower VED (approx. 63 J/mm3) than standard VED (approx. 76 J/mm3) to melt the last, one, two, three, five, and ten last layers. For this specific lower VED, the laser power was decreased from 250 W to 150 W, while the laser power was increased from 0.75 m/s to 0.9 m/s. This low VED approach should reduce residual stress in the samples. Figure 8a–l presents the top surface of samples built with no contour scan and 45° hatch angle rotation using standard VED and lower VED for the last, one, second, three, five, and ten layers. The comparative analysis of the topographic and macroscopic top surface images presented in Figure 8a–l revealed that the edges and corners became thinner using a lower VED. The contour profile became more regular and thinner as the number of last layers melted with low VED increased. Figure 9a–c shows the edge and corner heights and edge width of samples built with standard VED and lower VED for the last one, two, three, five, and ten layers. The experimental results in Figure 9a–c show that even when using a lower VED rather than a standard VED for melting the last layer, the edge and corner heights were significantly reduced, especially in the cases where samples had high ridges. For example, the edge and corner heights of samples built with hatch angles of 45° were reduced by more than 15% when the last layer was melted with a lower VED (see Figure 9a,b). In the case of edge width, the graph presented in Figure 9c shows that the elevated edge decrease almost linearly as the number of layers melted with low VED increases, both for 45° hatch angle and 67° and 90° hatch angles. The samples built with a lower VED for the last five and ten layers were quite close with respect to elevated ridges, meaning that the edge effect can be reduced only to a certain limit. Using a lower VED will reduce the size of the melt pool and the volume of material pushed to the edges and corners. The results revealed that the rotation of 45° and 67° hatch angles negatively influences the edge and corner effects even when using a lower VED. However, lower values for the edge and corner heights were obtained using lower laser power and high scanning speed than samples built with a standard VED. Using a lower VED for melting the last layers generates more acceptable edges and corners heights; however, the surface roughness must be considered because it increases with as the laser power decreases [6]. Moreover, as the number of the last layers melted with a lower VED increases, the mechanical properties, density, porosity, and microstructure may be affected. Therefore, using the lower VED for the last five layers of an LPBF part seems the best compromise to diminish the edge and corner effects when the surface roughness is not a critical requirement of an AMed part. 4. Discussion The present study focuses on reducing the edge and corner effects in additively manufactured IN 625 alloy by using contour scan, different hatch angle rotations, reducing the VED for the last layer(s) of parts, and remelting the last layer once or several times. The flatness of LPBF samples is generally affected by the raised edges and corners. The first melt sinks into the powder, leading to the volume of solidified material near the pool edge and pushing a larger volume of residual powder to the sides of the parts. Finally, the excess powder will be melted and solidified at the edge and corners of the specimen, increasing their width and height. The melt pool stability and the material flow are governed by the Marangoni convection, which is influenced by the temperature and surface tension gradients [36]. Marangoni convection and recoil pressure influence the increase of melt depth, creating a depression near the melt pool [15,17]. The quantitative assessment of the top layer by 3D laser scanning showed that the samples manufactured with contour scan had lower edges and corners than those with no contour for all hatch angles rotation (45°, 67°, and 90°). The case of corner heights of samples built with contour and hatch angles of 45°, 67°, or 90° were reduced by 17%, 31%, and 19%, respectively, to the same samples but without contour. The contour scan acted correctively on the elevated ridges on both specimen’s edges and corners. The material on specimen sides is partially remelted when the contour technique is used, which facilitates a microstructural refinement effect and a reduction of the surface roughness [12] and, therefore, an improvement of dimensional accuracy. In general, the contour scan improves the quality surface, especially in the case of inclined surfaces [12]. However, the contour regions may accumulate porosities and voids at the transition zone between contour and bulk scans [12,25], which is more critical than bulk porosity [37]. Instead, Yasa et al. [5] found that the parts built with contour scan had higher ridges than those built with no contour. However, while using the contour scan is mandatory to obtain an adequate dimensional accuracy of AMed parts, it does not completely fix the edge problem of LPBF samples. The edge and corner effects of specimens built with and without contour were more accentuated when using a hatch angle rotation different than 90°. Generally, the corner height decreases significantly, and the edge height decreases slightly with increasing the hatch angle rotation, while the edge width was not significantly influenced. The corner heights of samples increase by 72% for a 45° hatch angle and 20% for a 67° hatch angle compared to samples built with a 90° hatch angle. Robinson et al. [25] also observed that the deflection of LPBF parts is larger when the scanning strategy is rotated by 45°, and the highest residual stress is generated parallel to the scanned vectors. On the contrary, Cheng et al. [7] found that 45° inclined line scanning generates the smallest deformations of the manufactured parts. However, using a hatch rotation other than alternating 90° does not affect the properties of the AMed part in terms of roughness, strength, density, or residual stresses as long as there is a rotation between successive layers [25]. This behaviour explains that the heat flux direction rotates with the scan between layers, and thus the residual stresses are not equally distributed when using hatch angle rotations of 45°, 67°, or 90°. The elevated edges and corners are produced during the melting process due to the tendency of the melt to push away from the centre of the melt pool as the surface tension decreases with temperature [36]. Furthermore, near the corners and edges of the samples, the temperature profile around the melt pool deviates from the steady-state condition [38]. Another explanation is the crystallographic texture, which is strongly influenced by the crystallographic orientation of the parent grain and scan rotation of every layer [29,38]. It can be assumed that the local deformations at the corners and edges of samples are significantly higher when a hexagonal pattern generated by 45° or 67° scanning is used than when a checkerboard pattern is generated by 90° scanning. A similar trend was observed when the LSR technique and low VED were used for the last layer(s). The influence of laser remelting once, twice, and three times on the last layer of samples built without contour and with the hatch angle rotation of 45°, 67°, or 90° was investigated in terms of the corner and edge effects. The 3D scanning results were compared with those obtained on samples built without remelting. The trend of increasing deformation while increasing the hatch angle was also observed when using the LSR technique, but was much more amplified. In the case of samples built with a 90° hatch angle rotation, using the remelting technique increases the heights of the edges and corners by 8% and 7%, respectively, for the first remelting pass; by 17% and 22% for the second remelting pass; and by 35% and 25% for the third remelting pass, compared to the sample without remelting. A similar trend was observed for the other two hatch angle rotations. For the samples built with 67° hatch angle rotation, the heights of the edges and corners increase by 15% and 20% for the first remelting pass, by 19% and 23% for the second remelting pass, and by 23% and 33% for the third remelting pass. In the case of samples built with a 45° hatch angle rotation, the heights of the edges and corners increase by 10% and 10% for the first remelting pass, by 17% and 19% for the second remelting pass, and by 45% and 25% for the third remelting pass. As the remelting passes increased, the laser beam partially pushed the remelted material to both specimen sides and corners, amplifying the edge and corner effects. A probable cause of this behaviour is the low heat conductivity of powder (in the case of the first melt of the layer) compared to a (re)melted layer. During remelting, a higher surface temperature will be achieved due to the low heat dissipation of the melted layer. After three remelts of the last layer, higher heat conduction and, consequently, high ridges on the top surface will be higher. These results counter other studies where the LSR is considered a reliable surface finishing method [11,12,26,27] to improve manufactured parts’ surface characteristics and mechanical properties. Although LSR improves density and surface quality, the heightening of the edge effect has also been observed in another work [5]. LSR may be a solution for reducing the surface roughness without significantly impacting manufacturing times, but it has a strong negative impact on the edges and corner effect, as shown in Figure 6. To identify the appropriate process parameters for remelting the last layer, an assessment of the surface roughness and edge effect should be considered. A possible approach to diminish the edge and corner effects may be using the LSR with a lower VED to preheat the metal powder. Aboulkhair et al. [39] use half laser power for the first layer scan and full power for the second layer scan to maximise the relative density of LPBF parts without significantly affecting other properties or characteristics of parts. Based on these results, a new challenge must be considered—optimising the laser process parameters for (re)melting the last layer(s) of LPBF parts. To reduce the residual stress on the top surface of samples, the layers were built with 250 W laser power and 0.75 m/s scanning speed (76 J/mm3), while the last one, two, three, five, and ten layers of samples were melted with 150 W laser power and 0.9 m/s scanning speed (63 J/mm3), keeping the other parameters constant. As was expected, the elevated ridges were significantly reduced compared to the samples built with standard VED, but only to a certain limit. The edge effect reduced as the number of last years increased, but no significant differences with respect to the maximum heights were observed between the samples manufactured with the last five and ten layers with lower VED. In the samples manufactured with lower VED for melting the last five layers, using 45° and 67° hatch angles considerably reduced the corner heights by 23% and 37%, respectively, while in the case of samples built with a 90° hatch angle, the corner heights were reduced by only 4% compared with standard samples. However, the deformations of samples built with 90° hatch angles and their diminishing effect were generally much smaller than those built with 45° and 67° hatch angles. The effect of diminishing raised ridges due to reducing laser power and/or increasing scanning speed was also observed in other studies [5,19,40]. Conversely, Yasa [5] found no significant results regarding the edge effect diminishing regardless of varying the laser power and scanning speed. However, using a lower VED to melt the last few layers is beneficial in the reduction of the edge and corner effects with the detriment of top surface roughness, but the number of layers should be kept as low as possible to avoid affecting the mechanical properties, density, porosity, and microstructure of AMed parts. Therefore, when the surface roughness is not the most critical requirement of parts, using a lower VED for the last five layers of an LPBF part seems the optimal choice to diminish the edge and corner effects without affecting other physical properties. 5. Conclusions The effects of hatch angle rotation, contour scan, volumetric energy densities, and laser top surface remelting on the top surface of LPBF IN 625 parts were investigated in terms of edge and corner height and width based on the data extracted from the surface profiles generated by the 3D laser surface scanning on cubic specimens. The results showed that the elevated ridges of LPBF samples could not be eliminated, but they can be significantly reduced by using the contour scan. The samples built with hatch angles of 45°, 67°, or 90° and with contour had corner heights reduced by 17%, 31%, and 19%, respectively, compared to the same samples but without contour. The hatch angle rotation is another scanning strategy that strongly impacted the top surface deformation of AMed IN 625. Compared to samples built with a rotation angle of 90° between successive layers, samples built with hatch angle rotations of 45° and 67° had 72% and 20% higher deformations, respectively. Using the LSR strategy for the last layer of samples improves the smoothness of the top surface but has no positive impact on the corner and edge effect. The surface deformations increased significantly as the number of remelting passes increased due to the low heat dissipation of the (re)melted layer and high surface tension gradients which generate elevated ridges at the sides of parts. Using the same process parameters for melting and remelting the top layer may have a corrective action on the surface smoothness, but it is not a remedy for reducing the elevated edges of LBPF samples. An additional possibility that was checked in the present study to improve the flatness of the top surface was to reduce the standard VED (76 J/mm3) for melting the last layers. The elevated ridges were reduced when a low VED (63 J/mm3) was used for melting the last layer, and generally had a decreasing trend with increasing the hatch angle rotation and the number of the last layers melted. The samples built with low VED for the last five and ten layers were quite close with respect to elevated ridges. Thus, the edge effect can be reduced only to a certain limit. Another approach to diminish the elevated ridges may be using the LSR with lower VED in correlation with an optimal number of remelting passes. Manufacturing IN 625 samples by LBPF using a lower VED for only the last five layers, a 90° hatch angle between successive layers, and contour technique seems to be the best choice to reduce the edge and corner effects without affecting the manufacturing times and costs. Author Contributions Conceptualisation, A.P. and G.M.; methodology, A.P., G.M. and M.V.; software, M.V. and N.C.; investigation, A.P., G.M., N.C. and M.V.; writing—original draft preparation, A.P.; writing—review and editing, G.M. and N.C. 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 is not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Hatch angles used for manufacturing the IN 625 samples. Figure 2 Macroscopic views of the top surface of cubic samples built with contour scan and different hatch angle rotations: (a) 45°, (b) 67°, and (c) 90°. Figure 3 Topography and macroscopic top surface views of samples built with contour and no contour scan using different hatch angle rotations: (a,b) with no contour and hatch rotation of 45°, (c,d) with contour and hatch rotation of 45°, (e,f) with no contour and hatch rotation of 67°, (g,h) with contour and hatch rotation of 67°, (i,j) with no contour and hatch rotation of 90°, and (k,l) with no contour and hatch rotation of 90°. Figure 4 Section used for measuring the edge and corner effects of samples: (a) top surface topography of a specimen with the indication of the section and points measured and (b) measurement of the edge height and width on the section. Figure 5 Corner and edge height and width of samples built with contour and without contour as a function of three hatch angle rotations. Figure 6 Topography and macroscopic top surface views of the last layer of samples built with a 45° hatch angle rotation: (a,b) without remelting—reference, (c,d) with one remelting pass, (e,f) with two remelting passes, and (g,h) with three remelting passes. Figure 7 Corner and edge height and width as a function of the remelting passes of the top layer. Figure 8 Topography and macroscopic top surface views of the samples built with a 45° hatch angle rotation, using standard VED (76 J/mm3) and lower VED (63 J/mm3) for melting the last layer(s): (a,b) standard VED for the last layer, (c,d) lower VED for the last layer, (e,f) lower VED for the last two layers, (g,h) lower VED for the last three layers, (i,j) lower VED for the last five layers, and (k,l) lower VED for the last ten layers. Figure 9 Corner and edge height and width of samples as a function of increasing the number of last layers melted with low VED. materials-15-03198-t001_Table 1 Table 1 Chemical composition of IN 625 metal powder (in wt.%). Elements (wt.%) Al C Co Cr Fe Mn Mo Nb Si Ti Ni Specification <0.4 <0.1 <1.0 20–23 3–5 <0.5 8–10 3.15–4.15 <0.5 <0.4 Bal. Actual composition 0.06 0.02 0.1 20.7 4.1 0.01 8.9 3.77 0.01 0.07 62.26 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Liu D. Yue W. Kang J. Wang C. Effect of Laser Remelting Strategy on the Forming Ability of Cemented Carbide Fabricated by Laser Powder Bed Fusion (L-PBF) Materials 2022 15 2380 10.3390/ma15072380 35407713 2. Maamoun H. Xue Y.F. Elbestawi M.A. Veldhuis S.C. Effect of SLM Process Parameters on the Quality of Al Alloy Parts; Part I: Powder Characterisation, Density, Surface Roughness, and Dimensional Accuracy Materials 2018 11 2343 10.3390/ma11122343 30469468 3. Valente E.H. Gundlach C. Christiansen T.L. Somers M.A.J. Effect of Scanning Strategy during Selective Laser Melting on Surface Topography, Porosity, and Microstructure of Additively Manufactured Ti-6Al-4V Appl. Sci. 2019 9 5554 10.3390/app9245554 4. Jarfors A.E.W. Shashidhar A.C.G.H. Yepur H.K. Steggo J. 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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/ijerph19095701 ijerph-19-05701 Review Microbiological Testing of Probiotic Preparations https://orcid.org/0000-0002-6797-3240 Zawistowska-Rojek Anna 12* Zaręba Tomasz 1 https://orcid.org/0000-0003-3352-038X Tyski Stefan 12 Franco Carlos M. Academic Editor 1 Department of Antibiotics and Microbiology, National Medicines Institute, Chełmska 30/34, 00-725 Warsaw, Poland; t.zareba@nil.gov.pl (T.Z.); s.tyski@nil.gov.pl (S.T.) 2 Department of Pharmaceutical Microbiology, Medical University of Warsaw, Banacha 1b, 02-097 Warsaw, Poland * Correspondence: a.zawistowska@nil.gov.pl 07 5 2022 5 2022 19 9 570108 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/). Probiotic microorganisms that are potentially beneficial to the health of the host are commercially available in a great variety of products. Not all microorganism strains present in products have proven beneficial to the health properties. These products include not only foodstuffs but also dietary supplements, food for special medical purposes, medicinal products, as well as cosmetics and medical devices. These products contain from one to a dozen bacterial strains of the same or different species and sometimes also fungal strains. Since the pro-health effects of probiotics depend on a specific strain, the number of its cells in a dose, and the lack of pathogenic microorganisms, it is extremely important to control the quality of probiotics. Depending on the classification of a given product, its form, and its content of microorganisms, the correct determination of the number of microorganisms and their identification is crucial. This article describes the culture-dependent and culture-independent methods for testing the contents of probiotic microorganisms, in addition to biochemical and genetic methods of identification. The microbiological purity requirements for various product categories are also presented. Due to numerous reports on the low quality of probiotic products available on the market, it is important to standardise research methods for this group of products and to increase the frequency of inspections of these products. probiotic products probiotic viability probiotic identification live biotherapeutic products microbial contaminants This research received no external funding. ==== Body pmc1. Introduction Recently, interest in biologically active products with potentially beneficial effects on the patient or consumer has increased significantly. Some of the products containing probiotic microorganisms can be used for both therapeutic and prophylactic purposes. Depending on the indications, probiotic microorganisms are applied to humans in the form of foodstuffs, mainly fermented food, dietary supplements, foods for special medical purposes, medicinal products, or medical devices. They can also be found in cosmetics, most commonly in the forms of creams or serums [1]. In addition to products used by humans, a large group of probiotics is also used as feed supplements in animal husbandry. Probiotics belonging to the group of medicinal products are subject to clinical trials before approval by the relevant agencies and are subsequently controlled by pharmaceutical authorities to confirm the quality, effectiveness, and safety of these drugs. Furthermore, they are supervised via a system that collects data on adverse effects. Probiotics belonging to other product groups are not subject to such strict control. Numerous studies indicate the low quality of these probiotics, usually due to too low numbers of microorganisms in relation to the manufacturers’ declarations as well as the presence of microorganisms other than those declared for products dedicated for both humans [2,3,4,5,6,7] or animals [8]. Several products currently on the market contain microbes of different species, which can be a challenge during research because strains are often added to products in different amounts and have different survival rates during the storage period [7]. To distinguish medicinal products from dietary supplements or food, which, until recently, were jointly referred to as probiotics, the term “pharmabiotics” has been used in the literature for some time. It refers to biotherapeutic products containing live microorganisms, the purpose of which is to prevent or cure diseases, unlike probiotics, which are dietary supplements or food for special medical purposes and whose target group of recipients is healthy people [9]. Large and important sources of probiotics also include yoghurts, kefirs, and fermented food, most often in the form of cheeses, vegetables [10], and meats [11]. Although probiotic bacteria have been isolated from fermented foods, they can also be used to accelerate fermentation [7] and to alter the taste and texture of fermented foods [10]. In the case of meat products, the physicochemical, sensory, and functional properties may also be changed [11]. Probiotics are used not only by humans but also in animal production. In recent years, due to the limitation of the use of antibiotics, especially growth promotor factors, the use of LAB on farms to intensify meat production and prevent the development of certain pathogenic microorganisms has started [12]. Probiotics can be used as a growth stimulator for broilers [12] or in aquaculture [13]; they also influence immunity and reduce diseases and mortality in animals [12,13]. According to another study, the use of probiotics has a positive effect on the incidence of diarrhoea during piglet weaning [12]. Taking into account the large variety of probiotic products available on the market, some of which are of low microbiological quality, it is unclear how the quality of these products is controlled and whether it is possible to standardise these methods to ensure a safe product with health-promoting properties. An extensive analysis of the available literature describing numerous different methods of determining the contents of probiotic microorganisms and their identification was performed. The aim of this review is also to present the variety of available normative methods for determining the contents, purity and identities of microorganisms in probiotic products. In addition, this review presents the advantages and disadvantages of the presented methods. 2. Probiotic Microorganisms The group of probiotic organisms includes bacteria and fungi which, when administered in appropriate amounts, may exert a beneficial effect on the host’s health [14]. The most frequently used microorganisms in probiotic products are bacteria of the Lactobacillaceae family, in particular L. acidophilus and L. rhamnosus, as well as L. plantarum, L. casei, L. paracasei, and L. salivarius [3]. Frequently, probiotics also contain bacteria of the genera Bifidobacterium (B. longum, B. lactis, B. bifidum, B. breve) [15], Lactococcus, Bacillus or strains of Streptococcus thermophiles. Strains of yeast species, such as Saccharomyces boulardii, may also be present in these preparations (Table 1). Lactobacillaceae and Bifidobacterium are Gram-positive rods which produce lactic acid; they occur naturally in the digestive tracts of humans and animals. Probiotic bacteria exhibit antagonistic activity against various bacterial pathogens of the gastrointestinal tract, including Salmonella enterica, Shigella sonnei, enteropathogenic strains of Escherichia coli (EPEC), Staphylococcus aureus, Campylobacter jejuni, or Clostridioides difficile. They prevent the adhesion of these pathogens to the intestinal mucosa through competition for receptors, but they also inhibit their multiplication by competing for nutrients or producing antibacterial substances such as organic acids, hydrogen peroxide, and/or bacteriocins [16,17,18,19]. Both the FAO and the WHO [14,20] defined the criteria which should be met by strains belonging to the group of probiotic organisms. Specifically, they must not be pathogenic, i.e., they must have the GRAS (generally recognized as safe) status [21,22]. To obtain health benefits, it is necessary to apply a minimum number of 108–1011 CFU (colony-forming units) of bacterial or yeast cells in the daily dose [23]. To assess the safety of probiotics application, the following factors should also be taken into account: a large variety of probiotic strains, the risks associated with the use of strains which do not have GRAS or QPS (qualified presumption of safety) status, as well as the possibility of interaction between the probiotic strains and the host microbiota. Probiotics may be responsible for systemic infections; excessive immune stimulation, especially in immunocompromised individuals; deleterious metabolic effects; and gene transfer [24]. Some concerns have been raised regarding strains of the genus Enterococcus, namely E. durans, E. faecium and E. faecalis, classified as probiotic bacteria (only individual strains), although they are opportunistic microorganisms capable of causing infections in humans. Numerous studies indicate the increasing importance of multidrug-resistant Enterococcus sp., especially those resistant to vancomycin, and the possibility of transferring resistance genes through horizontal gene transfer to other bacterial genera [25]. However, due to safety concerns and the lack of safety information and regulations, only a limited number of probiotics containing enterococci are present on the market. Moreover, these bacteria have not yet obtained the GRAS or QPS status [24,25,26,27]. Although the European Food Safety Authority (EFSA) has approved enterococci as additives in silage and food supplements [25], it does not recommend the application of enterococci in probiotic products intended for human use [27]. In Germany, the strain E. faecalis DSM 16431 is a compound of a drug called Symbioflor 1 and is used in acute and recurrent sinusitis and bronchitis [25,27,28]. On the other hand, the strains E. faecium M74 and E. faecium SF-68 are included in dietary supplements such as FortiFlora and Cernivet, which are considered effective and safe [25]. Enterococci are often used in probiotic products for animals due to their efficacy of action and the lack of regulations that would exclude this group of microorganisms [27]. ijerph-19-05701-t001_Table 1 Table 1 Microbial species of which individual strains are classified as probiotic. Lactobacillaceae Bifidobacterium Bacillus Other L. rhamnosus [29,30] (Lacticaseibacillus rhamnosus *) B. infantis [29,30] B. coagulans [30,33] Saccharomyces boulardii [29,30] L. acidophilus [29,30] B. animalis subsp. lactis [29,30] B. subtilis [30,33,34,35] Lactococcus lactis subsp. lactis [30,31] L. plantarum [29,30] (Lactiplantibacillus plantarum *) B. bifidum [29,30] B. cereus [29,30] Enterococcus durans [25,30] L. casei [29,30] (Lacticaseibacillus casei *) B. longum [29,30,31] B. clausii [31,33] Enterococcus faecium [25,30] L. delbrueckii subsp. bulgaricus [29,30] B. breve [29,30] B. licheniformis [31,33,34] Enterococcus faecalis [25] L. brevis [30] (Levilactobacillus brevis *) B. animalis subsp. animalis [32] B. pumilus [34] Streptococcus thermophilus [29,30,31] L. johnsonii [29,30] B. adolescentis [29] B. velezensis [34] Pediococcus acidilactici [30] L. fermentum [29,30] (Limosilactobacillus fermentum *) B. amyloliquefaciens [33] Leuconostoc mesenteroides [30] L. reuteri [29,30] (Limosilactobacillus reuteri *) Escherichia coli Nissle 1917 [29,30] L. gasseri [29] L. paracasei [29,30] (Lacticaseibacillus paracasei *) L. salivarius [29] (Ligilactobacillus salivarius *) * name according to Zheng et al., 2020 [36]. 3. Forms of Probiotic Preparations The probiotic preparations available on the market are present in a variety of forms. Without consideration of fermented foods such as yoghurts and kefirs as probiotics, present in almost every supermarket, the most common pharmaceutical forms of probiotics are lyophilised capsules (oral and vaginal) and oral drops. Recently, however, it has become possible to frequently encounter microencapsulated lyophilisates, which are designed to preserve the stability of probiotics during storage, protect them from harsh conditions in the upper gastrointestinal tract, release them in the colon, and facilitate probiotic microorganisms to colonise the mucosal surface [37,38,39]. The microcapsule contains a membrane surrounding a core of an extremely small diameter, ranging from a few microns to 1 mm [38,40]. The encapsulating materials are widely recognised as safe ingredients which can be used in the food industry [37]. Various materials such as alginate, xanthan gum, starch, cellulose, pectin, and chitosan are used as matrices for the microencapsulation process [38,40,41]. Alginate is the most commonly used material, due to its high membrane-forming capability, biocompatibility, and controlled release properties [41]. During the process of optimising the encapsulation of probiotics, it is extremely important to maintain the microbiological stability of the given strains as well as their functionality, safety, and effectiveness [39]. Moreover, lyophilised probiotics are also available in the form of ampoules, vials, or sachets. Probiotics in the form of tablets, as well as chocolate tablets in various forms (e.g., gummy bears), or even lollipops, are also on sale. Probiotic microorganisms are also included in cosmetic products. The most common products of this group found on the market are creams, serums, masks, and gels, but also exfoliants, cleansers, foundations, soaps, lotions, shampoos, toothpaste, or deodorants [1,42]. Most probiotic cosmetic products do not contain live bacteria but include bacterial lysates, extracts, or products of the fermentation process, referred to as postbiotics [1,43], i.e., preparations containing non-living microorganisms and/or their components which induce a health benefit in the host [44]. Probiotic products applied to the skin surface are insufficiently controlled. There are numerous products on the market whose declared effects have not been scientifically proven [43]. The mechanism of action of probiotic cosmetics is mainly based on improving the barrier function of the epithelial layer, as well as inhibiting the growth of pathogenic microbes [1,42]. The effectiveness of this group of products has been demonstrated in the treatment of acne and atopic dermatitis [45]. Research is also carried out on the development of dressings—bandages and plasters containing probiotic bacteria (S. salivarius K-12, S. salivarius M-18 and L. plantarum 8P-A3), which, by producing bacteriocins, could inhibit the growth of bacteria present on the surface of the skin as well as pathogens that cause wound infections (e.g., Cutibacterium acnes, S. aureus, Pseudomonas aeruginosa) [46]. 4. Determining the Count of Probiotic Microbes in Products Determination of the microbial content in probiotic products can be performed using various methods presented in the literature. The most common ones are cultivation methods with the use of appropriate media, as well as the increasingly popular method of flow cytometry. Other methods are also described, such as fluorescence in situ hybridisation (FISH) [47] or nucleic acid abundance methods [48]. 4.1. Cultivation Methods Cultivation methods, such as plate count methods, are the gold standard [47]. The plate count method is simple to perform, but it requires a long incubation time and the selection of appropriate culture media. Testing the count of probiotic microbes in medicinal products, dietary supplements, or food for special medical purposes mainly depends on the composition of a given product (a preparation containing one, two, or more types of microorganisms) as well as its form (capsules, powder, drops, tablets). Numerous preparations on the market contain probiotic bacteria; however, in many of them, the number of bacteria in the product may not be consistent with the manufacturer’s declaration [2,3,4,5,6,7]. Therefore, it is important to investigate the quality of the probiotic preparations using standardised methods. In a study on the quality of probiotic preparations by Zawistowska-Rojek et al. [2], only 5 out of 25 preparations (one medicinal product, two dietary supplements, and two products classified as food for special medical purposes) contained the number of microbes above the value declared by the manufacturer in all the tested product batches. In the 10 other tested products, the number of bacteria depended on the tested product batch as well as its storage temperature, whereas in the remaining 10 products, in all tested batches, the number of microorganisms was below the manufacturer’s declaration [3]. In the studies by Mazzantini et al. [49], concerning the quality of probiotics classified as dietary supplements, 48 out of 104 analysed products did not contain all the declared species of microorganisms; 35 products had a total number of microbes lower than the declared number. However, in 22 tested products, the bacteria were not present. Medicinal products containing probiotic microorganisms were analysed in the same publication [49]; 14 out of 29 analysed drugs contained a smaller number of microorganisms than the one declared by the manufacturer. Many procedures used in research may result in discrepancies in the results presented by various authors. The method for quantifying the number of probiotic bacteria in products is described in the United States Pharmacopeia (USP) [50] and the Russian Pharmacopoeia (Ph. Ru.) [51]. According to the USP [50], the prepared sample should be dissolved in MRS broth, homogenised with a blender or stomacher, pre-incubated at room temperature, re-homogenised, and then diluted 10-fold in a peptone diluent. The method presented for determining probiotic microorganisms applies to the lactobacilli. There is a lack of information in USP concerning the methods of testing, the media used or the incubation times for products containing different types of probiotic microorganisms or several different strains of the same microbial species. In turn, according to the information given in the Russian Pharmacopoeia [51], the prepared sample should be dissolved in 0.9% NaCl and stirred 10–15 times with a pipette. After preparing a series of 10-fold dilutions in 0.9% NaCl, appropriate dilutions of the prepared suspension should be placed on Petri dishes containing an appropriate medium (Koch method), or 1 mL of the diluted suspension should be poured with a medium appropriate for the given type of bacteria (deep plate method) and incubated under appropriate conditions (Table 2) [51]. The Russian Pharmacopoeia also takes into account the instructions for quantifying bacteria of the genus Bifidobacterium and E. coli present in the same product, using Blaurock medium with sodium azide and Endo Agar [51]. In analytical tests carried out in various laboratories on the contents of probiotic microorganisms in products, described in the literature, the following procedure can be recommended. The weighed sample is dissolved in a peptone buffer [2,3,7] or phosphate buffer saline solution [5,8]. The sample is homogenised [5,7], and a series of 10-fold dilutions is prepared [2,3,6,7]. The sample should be diluted in accordance with ISO 6887-1:2000 [52]. The highest dilutions are plated on plates with a suitable medium (Table 2). After the incubation of microorganisms under appropriate conditions (Table 2), the total number of colonies on the agar plates is determined and converted to the content in the doses [6]. ijerph-19-05701-t002_Table 2 Table 2 Media and incubation conditions for individual types of probiotic microorganisms. Microorganisms Medium pH Temperature of Incubation Conditions Time References Lactobacillaceae MRS Agar 5.6–5.8 37 °C ± 1 °C 5% CO2 or anaerobic conditions 72 h ± 3 h [53] MRS Agar 6.3–6.7 38 °C ± 2 °C anaerobic conditions 3–5 days [50] LAPT Agar 6.45–6.55 37 °C ± 1 °C anaerobic conditions 72 h ± 3 h [54,55] MPC-1, MPC-2, MPC-4, MPC-5 6.2–6.6 38 °C ± 1 °C nd 48–72 h [51] Bifidobacterium sp. TOS-MUP 6.5–6.7 37 °C ± 1 °C anaerobic conditions 72 h ± 3 h [56] MRS Agar 6.3–6.7 38 °C ± 2 °C anaerobic conditions 3–5 days [50] Blaurock medium, MPC-5 7.0–7.4 7.0 38 °C ± 1 °C nd 4–5 days [51] RCM nd 37 °C ± 1 °C anaerobic conditions 72 h ± 3 h [57] BSM 6.6–7.0 37 °C ± 1 °C anaerobic conditions 24–48 h [58] Streptococcus thermophilus M17 7.0–7.4 44 °C ± 1 °C 5% CO2 72 h ± 3 h [53] ST Agar 6.7–6.9 37 °C aerobic conditions 24 h [59] Lactococcus sp. M17 7.0–7.4 20 °C ± 1 °C aerobic conditions 72 h ± 3 h [60] Bacillus sp. GYEA 6.6–7.0 40 °C ± 1 °C aerobic conditions 72 h ± 3 h [55] Gauze medium No.2 nd nd nd nd [51] MPA 7.1–7.5 nd nd nd Saccharomyces boulardii SDA 5.4–5.8 37 °C ± 1 °C aerobic conditions 72 h ± 3 h [61] nd—no data; MRS Agar—de Man, Rogosa and Sharpe Agar; TOS—TOS Propionate Agar; MUP—Lithium-Mupirocin selective supplement; BSM—Bifidobacteria selective medium; ST Agar—Streptococcus thermophilus Agar; RCM—Reinforced Clostridial Medium Agar; GYEA—Glucose Yeast Extract Agar Medium; MPA—Meat and Peptone Agar; SDA—Sabouraud Dextrose Agar. It is extremely important to choose the right medium for the cultivation of a given type of microorganism. In the case of products containing only lactobacilli, MRS agar is the most frequently used medium [2,3,57,62]. It can also be used to test for the presence of bacteria of the genus Bifidobacterium. However, it is necessary to apply appropriate sterilisation conditions during the preparation of the medium. According to the information provided by the manufacturer, MRS agar should be sterilised at 121 °C for 15 min. Moreover, if the growth of the Bifidobacterium spp. is desired, a temperature of 118 °C for 15 min should be applied [63]. When testing a product containing both lactobacilli and Bifidobacterium strains, it is more practical to use two different media, e.g., MRS agar for quantifying lactobacilli and TOS-MUP for quantifying Bifidobacterium [60]. In such a case, the incubation conditions should be selected in such a way that the growth of Bifidobacterium bacteria on the MRS agar medium is excluded. The problem grows when products containing even more types of probiotic microorganisms are tested. The media should be selected in such a way that only one type of microorganism will grow on each of them. For instance, the most common medium used for the cultivation of S. thermophilus and Lc. lactis is the M17 medium. However, to obtain the growth of only the desired group of microorganisms or to determine the number of cells of each type in the product separately, it is necessary to apply different incubation conditions (Table 2) [59,60]. To mark the microorganisms of the species L. acidophilus in the product containing a mixture of different bacteria such as L. delbrueckii, L. rhamnosus, L. paracasei, S. thermophilus, or Bifidobacterium, the addition of clindamycin (0.1 mg/L) and ciprofloxacin (10.0 mg/L) to the medium is recommended. These antibiotics inhibit the growth of the mentioned species, except for L. acidophilus (ISO 20128:2012) [64]. In some cases, it is possible to distinguish bacterial colonies of different species remaining on the same Petri dish. The genus Bifidobacterium consists of strictly anaerobic bacteria which grow on the agar surface in the form of round, whitish colonies, some of them star-shaped or triple-lobed [56]. In contrast, L. delbrueckii subsp. bulgaricus forms lenticular colonies with sharply defined contours on the acidified MRS agar [53], and L. acidophilus grows in the form of flat, opaque grey or whitish colonies with uneven edges [64]. The species S. thermophilus, however, grows on this agar medium in the form of lenticular colonies [53]. Although the direct plating on Petri dishes with agar medium is the most popular method, it also has its limitations. For example, sample preparation—the rehydration of lyophilised probiotics [57]—is extremely important. Moreover, parameters such as osmolality, pH, as well as the duration and intensity of homogenisation and the ability to aggregate a given strain may significantly affect the obtained result [65]. 4.2. Flow Cytometry The analytical, flow cytometry method enables the qualitative and quantitative determination of microorganisms in the tested sample within a very short time, which is an advantage compared to culturing methods. The study uses fluorescent dyes, which enable the assessment of parameters related to the surface, structure, and size of cells [66]. By using fluorescence in flow cytometry, it is possible to distinguish living and dead cell populations and spores [34]. In addition, it should be emphasised that because of the use of cytometry, viable but nonculturable cells (VBNC) can be determined. These are a form of resting bacteria which can survive in unfavourable environmental conditions [67]. The VBNC cells are characterised by lack of growth on culture media but preserve cell integrity and metabolic activity [48,67,68]. The factors that may trigger the conversion of bacterial cells to the VBNC state may be, for example, inadequate acidity or osmolality of the environment, temperature changes, or a deficiency of certain nutrients [68]. In a study using flow cytometry, the number of bacterial cells was determined directly in the test sample after the addition of an appropriate dye. Bacteria capture the dye, which, under the influence of intracellular enzymes, splits and releases molecules capable of fluorescence [69]. Depending on the fluorescent dyes used, it is possible to determine the population of all cells present in the product (TO—thiazole orange) and the population of dead and damaged cells (PI—propidium iodide) [70]. Other commonly used dyes are PI/CFDA (propidium iodide/carboxyfluorescein diacetate), SYTO 24/PI (nucleic acid dye/propidium iodide), and DiOC2(3) (cyanine dye). The PI/CFDA dyes are used to mark damaged and dead cells and to determine the activity of intracellular esterase [69]. The SYTO 24/PI is another set of dyes in use. The SYTO 24 dye penetrates living and dead cells, whereas PI penetrates only those with a damaged membrane and through the cover of damaged cells; DiOC2(3) dye enables the quantification of cells containing a functioning membrane potential [69]. The three dyes presented are the standard method for quantifying lactic acid bacteria with the flow cytometry method, according to the standard ISO 19344 [71]. The results obtained with the cytometry method are expressed in units of fluorescence activity (Active Fluorescent Unit AFU/g). Additionally, it is possible to quantify the value of the non-Active Fluorescent Unit (n-AFU/g), which represents damaged and dead bacterial cells, stained with PI, as it enters cells with an intact membrane and binds to DNA. The Total Fluorescent Unit (TFU/g) represents the total number of cells as the sum of AFU and n-AFU [70]. Genovese et al. [34] used flow cytometry to determine the numbers of spores of Bacillus subtilis, B. licheniformis, B. pumilus and B. velezensis strains with the use of SYTO 24 and LDS 751 (Laser Dyes Styryl)—cell permeant nucleic acid stain. The obtained results indicate no statistically significant differences in the determination of the number of spores by flow cytometry and the use of the plating methods [34]. Comparative studies of the two methods used for the quantification of probiotic bacteria, the culture method and flow cytometry, conducted by Chiron et al. [72], demonstrated that the number of microorganisms in the analysed products was greater when flow cytometry was used for most of the analysed strains. The B. longum strain was an exception, for which a greater number of colony-forming units was demonstrated with classical microbiological methods. On the other hand, a study conducted by Michelutti et al. [66] showed a good correlation between both applied methods (plate culture and flow cytometry) in determining the contents of B. animalis and L. acidophilus in probiotic products. Moreover, the flow cytometry method was characterised by greater repeatability and better precision. However, the flow cytometry method is used to quantify all microbial cells in the tested sample, not only probiotic cells but also microbes contaminating the preparation, which may cause false-positive results. 4.3. Other Counting Methods Other methods of microorganism counting are much less frequently used (Table 3). Fluorescence in situ hybridization (FISH) enables the enumeration of probiotic bacteria in products. The method is based on the detection of the nucleic acid nucleotide sequence with a fluorescently labelled probe that hybridises specifically to a complementary DNA sequence in an intact cell. The FISH method enables both the visualisation and quantification of bacterial strains. Moreover, it may enable the characterisation of the growth dynamics of bacteria in the environment of a given probiotic product [47]. In the studies presented by Pasulka et al. [47], the FISH method was used to determine the number of probiotic bacteria in two types of products. The first one contained the bacteria P. acidilactici, P. pentosaceus and L. plantarum as well as spores of B. subtilis. The number of cells estimated in the presented method was higher than the manufacturer’s declaration for all the species mentioned. The second product contained a mixture of spores of four Bacillus species: B. subtilis, B. amyloliquefaciens, B. licheniformis and B. pumilus. The number of estimated Bacillus spores was consistent with the declaration on the label [47]. Other methods, namely molecular techniques based on the detection of nucleic acid sequences, can also be used to count bacterial cells. These methods include, e.g., polymerase chain reaction (PCR), reverse transcriptase PCR (RT-PCR), or real time-quantitative polymerase chain reaction (RT-qPCR or qPCR). Quantitative polymerase chain reaction (qPCR) is a technique that enables the quantitative assessment of the microbial population using appropriate dyes and probes. Appropriate equipment is necessary, and the method facilitates the monitoring of the increase in DNA in each subsequent reaction cycle [48]. Gorsuch et al. [35] compared three methods—flow cytometry, qPCR (in which the counting is correlated with the amount of target nucleic acid), and plate count methods to count probiotic bacteria in a product that contained P. acidilactici, P. pentosaceus, L. plantarum, and B. subtilis in 20 samples of a complex probiotic product. In their study, flow cytometry and the qPCR method gave similar results, which were, however, significantly higher compared those provided by the plate method, especially in determinations performed in the later storage periods. These results suggest that some bacteria in the population entered the VBNC state and could only be counted by flow cytometry and qPCR methods [35]. Other methods, namely molecular techniques based on the detection of nucleic acid sequences, can also be used to count bacterial cells. These methods include, e.g., polymerase chain reaction (PCR), reverse transcriptase PCR (RT-PCR), or real time-quantitative polymerase chain reaction (RT-qPCR or qPCR). Quantitative polymerase chain reaction (qPCR) is a technique that enables the quantitative assessment of the microbial population using appropriate dyes and probes. Appropriate equipment is necessary, and the method facilitates the monitoring of the increase in DNA in each subsequent reaction cycle [48]. Gorsuch et al. [35] compared three methods—flow cytometry, qPCR (in which the counting is correlated with the amount of target nucleic acid), and plate count methods to count probiotic bacteria in a product that contained P. acidilactici, P. pentosaceus, L. plantarum, and B. subtilis in 20 samples of a complex probiotic product. In their study, flow cytometry and the qPCR method gave similar results, which were, however, significantly higher compared those provided by the plate method, especially in determinations performed in the later storage periods. These results suggest that some bacteria in the population entered the VBNC state and could only be counted by flow cytometry and qPCR methods [35]. 5. Identification of Probiotic Bacteria Identification of probiotics is usually carried out by known standard microbiological methods. According to the FAO/WHO [20] recommendations, probiotic microorganisms should have a strictly defined species classification, down to the strain level. The health effects induced by probiotic microorganisms depend on the particular strain, indicating that accurate identification is highly important. Moreover, identification down to the strain level allows for distinguishing introduced strains from those naturally occurring in a given environment [20,73]. Appropriate labelling of probiotic product packages is also extremely important. Frequently, manufacturers only provide the species name without providing details of the strain used, which may prevent the consumer from finding detailed information about the properties of a specific strain [74]. Microorganisms should be characterised with both phenotypic and genetic methods. Moreover, the FAO/WHO recommend depositing the strains in the international culture collection [20]. Initial characterisation of probiotic bacteria consists of the determination of the cells shape after staining with the Gram staining method as well as the assessment of mobility and the ability to produce catalase [53]. The easiest way to presumptively identify bacteria is through commercially available biochemical tests, e.g., API test (bioMérieux). The operating principle of these tests is the ability to assimilate, ferment, or break down specific compounds. Appropriate tests are available for various bacterial species; e.g., for lactobacilli strains and Lactococcus, the API 50 CHL test. Boyd et al. [75] correctly identified only 66% out of 97 tested strains of lactobacilli, using the API 50 CHL test. Identification of the bacteria belonging to the genus Bifidobacterium should be performed using the API 20A kit, dedicated to anaerobic bacteria. On the other hand, the identification of S. boulardii yeasts can be performed with the API 20C AUX test, dedicated to yeasts. In addition, the API ZYM Kit can be used to help identify bacteria and determine the potential of probiotic microorganisms [76]. The VITEK system (bioMérieux) is characterised by a similar principle of operation, where microorganisms can be identified on the basis of biochemical reactions. The VITEK 2 ANC system card allows for identifying lactobacilli to the species level and Bifidobacterium only to the genus level. However, the test results obtained are often inconclusive [48]. Another method of microbial identification is the BIOLOG system (Biolog Inc., Hayward, CA, USA), which is used to identify species of aerobic as well as anaerobic bacteria, yeasts, and fungi [77], including probiotic bacteria lactobacilli, Lactococcus, and Bifidobacterium [78]. This system analyses the ability of bacterial enzymes to metabolise 95 different carbon sources, making it possible to receive a “metabolic fingerprint” [78]. Moraes et al. [79] identified lactobacilli using different methods: API 50 CHL tests, the BIOLOG system, and molecular methods (16S rDNA sequencing), yielding varying results. The BIOLOG system identification yielded five strains: E. faecalis, four E. durans, two Streptococcus spp., and one Lc. lactis; twelve isolates were classified as other species, whereas five were not identified at all. Analysing the same samples using API 50 CHL tests resulted in fourteen L. plantarum, six L. paracasei, six Lc. lactis, and one Lactobacillus spp.; one sample was classified as a different species, and one was not identified at all. The authors of this publication confirmed their results using molecular identification—16S rDNA sequencing, in which 20 results were obtained, identifying the tested microorganisms as Enterococcus spp., five L. plantarum, three Lc. lactis, and one Streptococcus spp. [79]. Databases for the analysis of phenotypic results often do not take into account the latest taxonomic changes or newly described species, and therefore, the interpretation of the obtained results is not accurate. Another method enabling accurate and prompt identification of the tested microorganism is the MALDI-TOF MS—Matrix—Assisted Laser Desorption/Ionisation—Time of Flight—Mass Spectrometry technique. This method allows a comprehensive analysis of the protein panel of a given microorganism. The test consists of analysing the spectral distribution of proteins directly in bacterial cells [78,80]. Proteins of 2–20 kDa are detected, which are both ribosomal and housekeeping proteins [81]. The obtained protein profile is compared with the data from reference spectra, on the basis of which a given microorganism can be assigned to the species level [81]. Lorbeg et al. [7] identified bacteria derived from dietary supplements using the MALDI-TOF method and subsequently confirmed the obtained results using appropriate polymerase chain reaction (PCR). Using the MALDI-TOF method, they were able to correctly identify the following species: B. animalis, B. breve, B. longum, B. bifidum, B. infantis, E. faecium, L. acidophilus, L. casei, L. gasseri, L. paracasei, L. plantarum, L. reuteri, L. rhamnosus, L. salivarius, Lc. lactis, S. thermophilus, and S. cerevisiae. The accuracy of this identification was also confirmed with the PCR method. Nevertheless, when the MALDI-TOF method is used, errors also occur in the identification of lactic acid bacteria, especially in the case of closely related species such as L. casei and L. paracasei [7,78,82]. Comparative studies using MALDI-TOF and PCR methods showed discrepancies in the identification of the above species [82]. The problem with unequivocal identification of a species using phenotypic methods is related to the common phenomenon of phenotypic variability, resulting, among other things, from changes in gene expression under the influence of environmental conditions. Molecular biology methods, based on the analysis of the genetic material of bacteria, are much more accurate, sensitive, and reproducible. These methods are less reliant on the growth conditions of the bacteria, allowing the microorganism to be identified not only down to the species level but even to the strain. Many different molecular biology methods are used to identify and differentiate probiotic microorganisms. The most commonly used molecular assays for the identification of lactic acid bacteria are nucleic acid amplification tests. The PCR-based research is characterised by high sensitivity and specificity. The process of identifying lactic acid bacteria is performed based on gene sequences which encode ribosomal RNA (16S, 23S, 5S), amplification of ITSs (intergenic spacer regions) located between the genes encoding the 16S and 23S rRNA (ITS-PCR) and amplification of regions between genes encoding tRNA (tDNA PCR), sequence analysis of the genes encoding 16S rRNA, 23S rRNA, or ITS, restriction analysis of the rDNA gene amplification product ARDRA (Amplified Ribosomal DNA Restriction Analysis), ribotyping and DGGE/TGGE (Denaturing Gradient Gel Electrophoresis/Temperature Gradient Gel Electrophoresis) [78,80]. In multiplex PCR, it is possible to identify several different species of probiotic bacteria in one reaction, e.g., within the family Lactobacillaceae: L. acidophilus, L. delbrueckii, L. casei, L. gasseri, L. plantarum, L. reuteri, and L. rhamnosus [83]. However, this method has some limitations when it comes to the identification of closely related bacteria, e.g., from the L. acidophilus group (L. gallinarium and L. helveticus). In this case, it is impossible to distinguish particular species [84]. Kim et al. [85] determined 37 strains of lactobacilli with the use of primers specific for the given species L. acidophilus, L. plantarum and L. casei. The obtained results of the analysis of 17 probiotic products showed that not all products contain bacterial species corresponding with the information provided on the package. Another technique used for probiotics identification based on DNA amplification is RAPD (Random Amplified Polymorphic DNA). This method is based on amplification with the use of a short primer (usually about 10 nucleotides), where the ratio of G-C to A-T pairs is taken into account. The primer bonds with numerous homologous sequences in the analysed chromosomal DNA of a given species [83,86]. The method is easy to implement, cheap and can be a quick method for the simultaneous analysis of various strains of a given species [78]. However, it has a low repeatability, especially in interlaboratory conditions [83,86]. Using this method, the species L. helveticus, L. sake, L. plantarum and L. delbrueckii subsp. bulgaricus [78] can be successfully distinguished. Huang and Lee [87], with the use of appropriate primers, also distinguished species belonging to the L. casei group: L. rhamnosus, L. paracasei subsp. tolerans, and L. zeae. Among the methods that use restrictive analysis to identify probiotic bacteria, the RFLP (Restriction Fragment Length Polymorphism) method may be employed. In this method, the differences in the band patterns reflect changes in the DNA sequence, which result in the absence or an additional restriction locus recognised by the restriction enzyme used [88]. Blaiotta et al. [89] identified lactobacilli strains by digesting the obtained amplification products with Alu I and Tac I restriction enzymes, enabling them to identify and distinguish even closely related species such as L. acidophilus and L. crispatus; L. casei and L. rhamnosus, as well as L. acidophilus, L. helveticus, and L. amylovorus. Moreover, with the additional use of Sau3AI or Mse I restrictase, they were able to distinguish L. plantarum and L. pentosus species. The T-RFLP technique (Terminal Restriction Fragment Length Polymorphism) is a modification of the PCR-RFLP technique, in which the 5′-end primer is labelled with a fluorescent dye (e.g., fluorescein amidite) so that only the labelled terminal restriction fragments are detected. This method does not require conducting a culture to identify a species from a mixed bacterial population; moreover, its accuracy can be increased by using more restriction enzymes [78]. This method was used, among others, to study the intestinal microbiota [90] as well as for the identification of probiotic lactobacilli strains in intestinal samples [81,91]. Another molecular biology method used to identify probiotic strains is the AFLP (Amplified Fragment Length Polymorphism) method, based on the analysis of the entire bacterial genome. This technique employs the phenomenon of the ligation of nucleotide adapters and the selective amplification of restriction fragments. In the AFLP technique, the following restriction enzymes are used: frequently cutting (e.g., Mse I or Taq I) and rarely cutting (e.g., EcoR I or Pst I), leaving sticky ends [80,86,88]. The advantages of the AFLP method include good reproducibility and sensitivity; no sequence knowledge is required. However, the complicated procedure, with a large number of steps, an expensive process, and the need to have specialised equipment, limit this method [80,86]. However, this method is successfully used to type bacteria of the lactobacilli. Dimitrov et al. [92] typed bacteria from 49 stool samples; using the AFLP technique, 41 profiles were distinguished, whereas when using PFGE, they obtained 34 profiles, and with the use of RAPD, only 27 profiles were obtained. On the other hand, Giraffa and Neviani [93] successfully classified strains belonging to closely related species: L. plantarum, L. pentosus and L. pseudoplantarum. Jarocki et al. [86] found that this method has the highest potential for differentiating strains of the L. casei group. The method in the differentiation and relationship searching of strains, recommended by the FAO/WHO, is Pulsed Field Gel Electrophoresis (PFGE) [20]. This method is also used to test for probiotic bacteria. It is based on the digestion of chromosomal DNA with rarely cutting restriction enzymes, e.g., ApaI, AscI, SmaI, XbaI [94,95], followed by separation of the obtained digestion products in agarose gel in an alternating electric field [89]. This method has a very high differentiating potential and a very high reproducibility, but it is also extremely laborious and time-consuming. Desai et al. [96], using the PFGE method, typed strains closely related to the L. casei group: L. casei, L. paracasei, L. rhamnosus, and L. zeae. Xu et al. [94] digested the chromosomal DNA of 33 lactobacilli strains with AscI restrictase, obtaining 17 different pulsed-field profiles belonging to the following species: L. rhamnosus, L. paracasei, L. plantarum, L. acidophilus, L. fermentum, L. curvatus, and L. delbrueckii subsp. lactis. The gold standard method that serves both to identify and to determine the LAB drug resistance profile is the whole genome sequencing method (WGS). The identification of strains using WGS can be performed using one of the available methods—single nucleotide polymorphism (SNP) analysis or the gene-by gene analysis method. The SNP method consists in comparing the genome of a given bacterium with a reference genome, as a result of which information about nucleotide differences is obtained. In turn, the gene-based method can be used to analyse the genetic relationship between LAB strains [80]. Special tools such as Mauve or Mummer are used for WGS analysis. Thanks to the possibility of comparing the genomes of two strains contained in the database, it is possible to distinguish strains that differ even by a single nucleotide, this makes it possible to conclude that the two strains are different, even if no phenotypic differences are identified [65]. The described method of identification, despite its accuracy, is not common in microbiological laboratories due to high costs. It is also worth adding that in order to be able to commercially use the identification of LABs derived from probiotic products by the WGS method, it will be necessary for manufacturers to include the nucleotide sequences of the strains used in appropriate and publicly available databases [65]. 6. Microbiological Purity of Probiotic Medicinal Products and Dietary Supplements Probiotic products, both those classified as medicinal products and food, should meet several quality requirements which are regulated depending on the status of the product. Regardless of the classification of the product as food or medicine, the product should not be contaminated with pathogenic bacteria, such as E. coli or Salmonella sp. Depending on the consumer groups for these products, consideration should also be given to excluding the presence of other pathogens such as S. aureus, P. aeruginosa, Listeria monocytogenes, Clostridioides or Cronobacter sakazakii in infant products. The requirements to be met by individual product groups are regulated by the European Pharmacopoeia (Ph. Eur.) [97,98,99], the United States Pharmacopeia (USP) [50,100,101,102], the Food and Drug Administration (FDA) [103] and the European Commission [104]. According to the monographs of the European Pharmacopoeia [97,98,99], in products containing live microorganisms (Live Biotherapeutic Products, LBP), depending on the route of administration of a given preparation, different maximum aerobic microbial contamination counts (AMCC) and total yeast and mould contamination counts (YMCC) should be estimated (Table 4). To determine these contaminations of LBP in the presence of probiotic strains (lactic acid bacteria, Bacillus clausii spores, yeast S. cerevisiae var. boulardii), various media and incubation conditions should be used, tailored to the specifics of the test product and the presence of the microorganisms in it (Table 4). Moreover, depending on the administration route, the presence of certain pathogenic microorganisms (E. coli in oral preparations and P. aeruginosa, S. aureus and Candida albicans in vaginal preparations) should be excluded (Table 4). The US Pharmacopeia specifies the microbial purity requirements for products classified as both medicinal products and dietary supplements (Table 4 and Table 5). Depending on the microorganisms contained in the oral product (non-spore-forming bacteria, e.g., lactobacilli and Bifidobacterium, spore-forming bacteria, yeasts and moulds), there are maximum permissible counts of contaminating microorganisms [50,100]. In addition, undesirable microorganisms such as E. coli or Salmonella sp. are specified. If there is a risk of contaminating raw materials or the finished product, the presence of L. monocytogenes, S. aureus and P. aeruginosa should also be excluded, whereas in the products intended for infants, bacteria such as Clostridium perfringens and Cronobacter sakazakii must also be excluded [50,101]. Documents published by the FDA and the European Commission (Table 5) regarding food exclude the presence of the microorganisms in products, such as Salmonella [103,104], Cronobacter spp. [103], E. coli [103], Enterobacteriaceae [103], Enterobacter sakazakii [104], L. monocytogenes [104]. The FDA [105], like the standard ISO 17516:2014 [106], also specifies the requirements for the microbiological purity of cosmetics (Table 5). The requirements for this product group concern the total number of mesophilic aerobic microorganisms, both bacteria, yeasts and moulds, which should not exceed 1 × 103 CFU in 1 mL or 1 g of the product; preparations used in the vicinity of the eyes are an exception [105,106]. When applied to mucous membranes [106] and to children under 3 years of age [106], for whom the given limits are lower in amount, in the case of FDA requirements, to ≤5 × 102 CFU per 1 g [102], and in the case of ISO requirements ≤ 1 × 102 CFU per 1 g or 1 mL [106]. Additionally, the presence of certain microorganisms in cosmetic products should be excluded, e.g., S. aureus [105,106], P. aeruginosa [105,106], Streptococcus pyogenes [105], Klebsiella pneumoniae [105], E. coli [106] or C. albicans [106] (Table 5). Mazzantini et al. [49] collected results on the purity of probiotic products from various countries. In the presented studies, the most common microorganism that contaminated the products was E. faecium, even at the level of 109 CFU/dose. In addition, contamination with microorganisms such as Acinetobacter baumannii (1011 CFU/dose), Lysinibacillus fusiformis (1011 CFU/dose), B. cereus (1010 CFU/dose), Bacillus leantus (109 CFU/dose), and Staphylococcus spp. (102 CFU/dose) was detected [49]. ijerph-19-05701-t005_Table 5 Table 5 Acceptance criteria of dietary supplements [50,100,101,102], food for special medical purposes [103,104] and cosmetics [105,106]. DIETARY SUPPLEMENTS, FOOD FOR SPECIAL MEDICAL PURPOSES Documents TAMC TYMC Specified Microorganisms FDA [103] 5 × 102 nd Absence of Cronobacter spp. per 10 g Absence of Salmonella per 25 g Absence of E. coli per 1 g Absence of Enterobacteriaceae per 10 g USP [50,100,101,102] 5 × 103 102 Absence of E. coli per 10 g Absence of Salmonella per 10 g Absence of L. monocytogenes, S. aureus, P. aeruginosa if there is a risk of contamination of the product Absence of C. perfringens and C. sakazakii in infant products Commission Regulation (EC) No 1441/2007 [104] Regulation on microbiological criteria for foodstuffs nd nd Absence of L. monocytogenes per 25 g Absence of Salmonella per 25 g Absence of Enterobacteriaceae per 10 g COSMETICS Documents Total Number of Mesophilic Aerobic Microorganisms (Bacteria Plus Yeasts and Moulds) Specified Microorganisms FDA [105] ≤5 × 102 CFU per 1g—cosmetics applied around the eyes ≤1 × 103 CFU per 1g—other cosmetic products Absence of: S. aureus, S. pyogenes, P. aeruginosa K. pneumoniae ISO 17516 [106] ≤1 × 102 CFU per 1 g or 1 mL—cosmetic products intended for children under three years of age, applied around the eyes or on the mucous membranes ≤1 × 103 CFU per 1 g or 1 mL—other cosmetic product Absence of E. coli per 1 g or 1 mL Absence of S. aureus per 1 g or 1 mL Absence of P. aeruginosa per 1 g or 1 mL Absence of C. albicans per 1 g or 1 mL nd—no data. 7. Conclusions An increasing number of probiotic products appear on the market. In the literature, there is a large amount of information about the incorrect number of probiotic microorganisms, contamination of the tested products at a very high level, and the lack of proper labelling of the strains included in the composition of the preparations. There is no doubt that methods of testing the contents of probiotic products, especially the proper preparation of the sample and the selection of the appropriate method for counting and identification of microorganisms, are necessary. However, there are no detailed, universal guidelines for testing these products, especially when they contain many different types of microorganisms (strains of the same or different species and genera), which may cause differences in the results obtained by laboratories. The different survival times of microorganisms in the product also affect the identification of the strains declared by the manufacturers, which often, during the shelf life of the product, are found in very low numbers that are not sufficient to provide the health benefits to the host in any way, which is the basic task of probiotics. Besides, the probiotics contaminants may include pathogenic microorganisms, which suggests that products containing live microorganisms, regardless of whether they belong to the category of medicinal products, dietary supplements, food or cosmetics, may not be safe and should be subject to strict quality control. Taking into account reports on the poor survival of microorganisms in products, they should be also subjected to stability tests, similarly to medicinal products, to eliminate poor-quality preparations or to shorten the validity period. Detailed information about the strains contained in particular product should be provided by the manufacturers on the product package or in informational materials. Not only the generic or species name but also strain designation should be stated, because the properties of probiotics are strain-dependent. Based on this review, a substantial amount of work needs to be done to ensure that the probiotic products available on the market are of good quality, safe and fulfil a pro-health function. Author Contributions Conceptualization, S.T. and A.Z.-R.; investigation, A.Z.-R. and T.Z.; writing—original draft preparation, A.Z.-R.; writing—review and editing, S.T.; visualization, A.Z.-R.; supervision, S.T.; funding acquisition, S.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. ijerph-19-05701-t003_Table 3 Table 3 Determining the count of probiotic microbes—culture independent methods. Methods References Flow cytometry [67,68,69,70,71] FISH (Fluorescence in situ hybridization) [47] PCR methods (PCR, RT-PCR, RT-qPCR, qPCR) [35,48] ijerph-19-05701-t004_Table 4 Table 4 Acceptance criteria for microbiological quality and cultivation conditions for medicinal products containing probiotic microorganisms. European Pharmacopoeia [97,98,99] Route of Administration AMCC * YMCC* Specified Microorganisms Acceptance Criteria Medium and Incubation Conditions Acceptance Criteria Medium and Incubation Conditions Non-aqueous preparations for oral use 103 CFU/g or CFU/mL LBP * containing lactic acid bacteria: - Sugar-free agar plates (30–35 °C, 72 h) - Casein soya bean digest agar plates supplemented with 5% of sheep blood (30–35 °C, 44–48 h) LBP containing Bacillus clausii spores—sporulating agar (33–37 °C, 48 h) LBP containing Saccharomyces cerevisiae var. boulardii—casein soya bean digest agar containing cycloheximide (30–35 °C, 3–5 days) 102 CFU/g or CFU/mL LBP containing bacteria—Sabouraud -dextrose agar with chloramphenicol—(20–25 °C, 5–7 days) LBP containing Saccharomyces var. boulardii—Sabouraud-dextrose agar supplemented with chloramphenicol and cycloheximide, Czapek-Dox agar, potato dextrose agar (20–25 °C, 5–7 days) Absence of E. coli per 1 g or 1 mL Aqueous preparations for oral use 102 CFU/g or CFU/mL 101 CFU/g or CFU/mL Absence of E. coli per 1 g or 1 mL Vaginal use 102 CFU/g or CFU/mL 101 CFU/g or CFU/mL Absence of: P. aeruginosa, S. aureus, C. albicans per 1 g or 1 mL United States Pharmacopeia [50,100,101,102] Probiotic products for oral use TAMC * TYMC * Specified microorganisms Non-spore-forming bacteria <5 × 103 CFU/g (except lactic acid bacteria) <102 CFU/g Absence of E. coli per 10 g Absence of Salmonella per 10 g Absence of L. monocytogenes, S. aureus, P. aeruginosa if there is a risk of contamination of the product Absence of C. perfringens and C. sakazakii in infant products Spore-forming bacteria Not applicable <102 CFU/g Yeasts and moulds <1 × 103 CFU/g Not applicable * AMCC—aerobic microbial contamination count, YMCC—yeast and moulds contamination count, TAMC—total aerobic microbial count, TYMC—total yeast and mould count, LBP—live botherapeutic products. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092658 jcm-11-02658 Article Duodenal Gastric Metaplasia and Duodenal Neuroendocrine Neoplasms: More Than a Simple Coincidence? https://orcid.org/0000-0003-3214-8192 Massironi Sara 1*† https://orcid.org/0000-0003-4208-4372 Rossi Roberta Elisa 2*† https://orcid.org/0000-0002-3042-4360 Milanetto Anna Caterina 3 https://orcid.org/0000-0002-3793-2982 Andreasi Valentina 4 https://orcid.org/0000-0002-4615-7340 Campana Davide 5 Nappo Gennaro 6 Partelli Stefano 4 Gallo Camilla 1 Scaravaglio Miki 1 Zerbi Alessandro 6 https://orcid.org/0000-0003-2789-4289 Panzuto Francesco 78 https://orcid.org/0000-0002-0365-5286 Pasquali Claudio 3 https://orcid.org/0000-0001-9654-7243 Falconi Massimo 4 https://orcid.org/0000-0003-3262-1998 Invernizzi Pietro 1 on behalf of ItaNet (Italian Association for Neuroendocrine Tumours) Study Group‡ Tanabe Hiroki Academic Editor 1 Division of Gastroenterology, San Gerardo Hospital, University of Milano-Bicocca School of Medicine, 20900 Monza, Italy; c.gallo19@campus.unimib.it (C.G.); m.scaravaglio@campus.unimib.it (M.S.); pietro.invernizzi@unimib.it (P.I.) 2 HBP Surgery, Hepatology and Liver Transplantation Unit, ENETS Center of Excellence, Fondazione IRCCS Istituto Nazionale Tumori (INT, National Cancer Institute), 20133 Milan, Italy 3 Pancreatic and Endocrine Digestive Surgical Unit, Department of Surgery, Oncology and Gastroenterology, Università degli Studi di Padova, 35122 Padua, Italy; acmilanetto@unipd.it (A.C.M.); claudio.pasquali@unipd.it (C.P.) 4 Pancreatic Surgery Unit, ENETS Center of Excellence, San Raffaele IRCCS, “Vita-Salute” University, 20132 Milan, Italy; andreasi.valentina@hsr.it (V.A.); partelli.stefano@hsr.it (S.P.); falconi.massimo@hsr.it (M.F.) 5 ENETS Center of Excellence, Department of Experimental, Diagnostic and Specialty Medicine, Bologna University, St. Orsola-Malpighi University Hospital, 40138 Bologna, Italy; davide.campana@unibo.it 6 ENETS Center of Excellence, Department of Biomedical Sciences, Humanitas University, 20090 Pieve Emanuele, Italy; gennaro.nappo@humanitas.it (G.N.); alessandro.zerbi@hunimed.eu (A.Z.) 7 Digestive Disease Unit, ENETS Center of Excellence, Sant’Andrea University Hospital, 00189 Rome, Italy; francesco.panzuto@gmail.com 8 Department of Medical-Surgical Sciences and Translational Medicine, Sapienza University of Rome, 00189 Rome, Italy * Correspondence: sara.massironi@libero.it (S.M.); robertaelisa.rossi@gmail.com (R.E.R.) † These authors contributed equally to this work. ‡ Membership of the ItaNet Study Group is provided in the acknowledgments. 09 5 2022 5 2022 11 9 265822 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/). Background: Duodenal gastric metaplasia (DGM) is considered a precancerous lesion. No data are available regarding its possible role as a risk factor for duodenal neuroendocrine neoplasms (dNENs). Aims: To assess the prevalence of DGM in a cohort of dNENs. Methods: Subgroup analysis of a retrospective study including dNEN patients who underwent surgical resection between 2000 and 2019 and were observed at eight Italian tertiary referral centers. Results: 109 dNEN patients were evaluated. Signs of DGM associated with the presence of dNEN were reported in 14 patients (12.8%). Among these patients, nine (64.4%) had a dNEN of the superior part of the duodenum, one (7.1%) a periampullary lesion, three (21.4%) a dNEN located in the second portion of the duodenum, with a different localization distribution compared to patients without DGM (p = 0.0332). Ten were G1, three G2, and in one patient the Ki67 was not available. In the group with DGM, six patients (35.7%) were classified at stage I, five (28.6%) at stage II, three (21.4%) at stage III, and no one at stage IV. In the group without DGM, 20 patients (31%) were at stage I, 15 (15%) at stage II, 42 (44%) at stage III, and 19 (20%) at stage IV (p = 0.0236). At the end of the study, three patients died because of disease progression. Conclusions: our findings might suggest that DGM could represent a feature associated with the occurrence of dNEN, especially for forms of the superior part of the duodenum, which should be kept in mind in the endoscopic follow up of patients with DGM. Interestingly, dNEN inside DGM showed a more favorable staging, with no patients in stage IV. The actual relationship and the clinical relevance of this possible association require further clarification. duodenal neuroendocrine neoplasms duodenal gastric metaplasia risk factor epidemiology This research received no external funding. ==== Body pmc1. Introduction Duodenal neuroendocrine neoplasms (dNENs) are rare and heterogeneous tumors that represent up to 3% of all duodenal neoplasms [1]. They usually present in the 6th decade of age with a slight male predominance [2]. Duodenal NENs are usually well-differentiated neoplasms; however, they can be metastatic in up to 55% of cases [3]. Their natural history, clinical characteristics, biological mechanisms, medical or surgical treatment, and prognosis are still poorly understood. Duodenal NENs originate from aberrant neuroendocrine duodenal cell proliferation; in this microenvironment, complex interactions take place. The recognition of the molecular mechanisms participating in neoplastic transformation could increase the challenging management of this disease. However, at present, little is known about the risk factors of these neoplasms. The normal mucosa of the duodenum is composed of absorbing columnar enterocytes and secreting goblet cells. Duodenal gastric metaplasia (DGM) is characterized by the replacement of the normal duodenal epithelial cells with gastric mucus-secreting cells that resemble gastric foveolar epithelium. It is commonly considered a precancerous lesion often associated with chronic inflammation. It is generally the consequence of abnormally high production of gastric acid triggered by Helicobacter Pylori (HP) infection [4]. When hypersecretion reaches the duodenum, the enterocytes of the villi react with apical mucin metaplasia to mitigate the unwanted low pH of the microenvironment. Besides HP infection, DGM has been reported in association with other conditions, such as medications (i.e., nonsteroidal anti-inflammatory drugs; NSAIDs), celiac disease [5], and Crohn’s disease involving the duodenum [6]. However, DGM has been described also in the absence of all these conditions, although its actual etiology in the latter group of patients is unclear. Furthermore, DGM usually disappears following HP eradication [7], whereas the natural course of DGM in celiac patients or patients without a recognized cause, even with the application of a strict gluten-free diet, is still poorly known. It still remains a question of debate whether DGM could represent a neoplastic risk factor. A high frequency (40.5%) of DGM has been found in duodenal adenomas [8]. It might be possible that metaplasia precedes the neoplastic transformation as has been reported in other gastrointestinal malignancies including esophagus (intestinal metaplasia in Barrett’s esophagus–dysplasia–carcinoma sequence [9] and stomach [10] and colorectal cancer [11]). Furthermore, DGM has been associated with genetic alterations, such as GNAS and KRAS mutations, which are involved in different types of tumors including duodenal adenocarcinoma. However, no data are available regarding the possible role of DGM as a risk factor for the occurrence of dNEN. Taking into account these observations and the lack of clear-cut data regarding the natural history of dNEN, we aimed at assessing the prevalence of DGM in a cohort of dNENs. The secondary aim was to explore whether the presence of DGM had any impact on the characteristics or outcome of the current cohort of dNENs. 2. Materials and Methods We performed a subgroup analysis of a retrospective study [3] including all consecutive patients with dNEN, who underwent surgical resection between 2000 and 2019 and who were observed at eight Italian tertiary referral centers. All data were retrieved at the center where each patient had been diagnosed and followed up. Participating study centers sent the anonymized data of patients to the lead center. The study’s inclusion criteria were age > 18 years, histological diagnosis of dNEN of any grade and stage, surgical treatment of the primary tumor, availability of complete histopathological examination of the surgical specimen, and clinical data with a minimum 3 month follow up after diagnosis. The exclusion criteria were histological findings of mixed neuroendocrine non-neuroendocrine neoplasms (MiNEN), age < 18 years, the use of experimental drugs during the 2 months preceding inclusion in this study, and pregnancy or breastfeeding status. Due to the retrospective nature of this study, ethical approval was waived. The tumor characteristics analyzed comprised the site and the size of the primary tumor, number of lesions, grade, and stage (i.e., localized, regional, distant, and unknown). The patient’s characteristics included the age at first diagnosis, the presence of genetic syndrome (i.e., multiple endocrine neoplasia (MEN)-1), and the presence of functioning neoplasms. Medical history data were collected and recorded by physicians in electronic health records, comprising the clinical history, age at diagnosis, treatments received, clinical and biochemical parameters, radiological imaging, endoscopy examinations, and nuclear medicine imaging were recorded and evaluated at each referral center. The type of surgical intervention was recorded for all the patients. Neoplasms were classified according to the WHO 2019 classification [12] and staged according to the current European Neuroendocrine Tumor Society (ENETS) TNM clinical staging [13]. For each included patient, the endoscopic or surgical specimen and related histopathological data were assessed to verify the presence or absence of DGM. Concomitant treatment with proton pump inhibitors (PPIs) was recorded. Statistical Analysis Descriptive statistics were used to summarize the data. Continuous variables with normal distribution were expressed as the median (i.e., range); categorical variables were reported as the count (i.e., percentage). All data were tested for distribution normality by the Kolmogorov–Smirnoff test. The differences between groups were assessed with the Mann–Whitney test and the Kruskal–Wallis test as appropriate. Comparisons between groups were assessed using the χ2 test or Fisher’s exact test. The analyses were carried out using GraphPad Prism version 6.00 (GraphPad Software, San Diego, CA, USA). 3. Results From 2000 to 2019, 109 patients with histologically confirmed dNEN were included in the study as previously reported (Figure 1). The DGM associated with a dNEN was reported in 14 patients (12.8%). None of these patients had a concomitant HP infection, celiac disease, or Crohn’s disease. Concomitant use of NSAIDs was excluded for all 14 patients. The baseline characteristics of these 14 patients were compared to the clinical features of the remaining 95 patients without signs of DGM (Table 1). We observed a male prevalence in both groups, whereas the patients with DGM were older (61.5 versus 58 years old), even if this difference was not statistically significant. In the two groups, the median diameter of the neoplasms was similar (being quite small, namely, 15 in patients without DGM and 11 mm in patients with DGM), and the majority of tumors were single. Location of the primary NEN was significantly different between the two groups (p = 0.0332): among the 14 patients with DGM, 9 had a dNEN of the superior part of the duodenum (64.4%), 1 had a periampullary neoplasm (7.1%), in 3, the dNEN was located in the second portion of the duodenum (21.4%), whereas in 1 patient the location was not specified. Among the 95 patients with dNEN without DGM, the majority (42.1%) showed periampullary tumors. As concerning grading, among the patients with DGM, 10 were G1; 3 G2; while in 1 patient the ki67 was not specified. None of the tumors inside DGM was a poorly differentiated neoplasm. Among the 95 patients without DGM, 56 were G1; 23 G2; 7 G3; whereas in 9 patients the Ki67 was not available. The staging had a significantly different distribution between the two groups (p = 0.0236); in the group with DGM, six patients were classified as stage I; five as stage II; three as stage III; no one at stage IV. In the other group without DGM, 20 patients were at stage I; 15 at stage II; 42 at stage III; 19 at stage IV. The type of surgery was significantly different between the two groups (p = 0.0007): 3 out of the 14 patients (21.5%) with DGM underwent pancreaticoduodenectomy, 6 (42.8%) duodenotomy with enucleation, and 5 (35.7%) partial duodenectomy and lymphadenectomy. Among the 95 patients without DGM, 58 (61%) underwent pancreaticoduodenectomy, 4 (4.2%) total pancreatectomy, 28 (29.5%) duodenotomy and enucleation, and five (5.3%) partial duodenectomy and lymphadenectomy. In the group of 14 patients with DGM, the 5 patients at stage III presented with lymph node metastases at diagnosis and received treatment with somatostatin analogs (SSAs), which were continued after surgery. One patient out of 14 (7.1%) with DGM-associated dNEN and 17 out of 95 (17.9%) with dNEN not associated with DGM were diagnosed with MEN-1 syndrome, without any significant difference in the percentage of MEN-1. In both groups, the majority of the tumors were nonfunctioning. Five patients (35.7%) were treated with proton pump inhibitors (PPIs) versus 31 patients in the group without DGM (32.6%). At the end of the study, three patients out of the 14 with DGM (21.4%) were dead, of which only one was due to the fact of disease progression (occurrence of distant liver metastases treated with SSA and chemotherapy). In the group without DGM, 18 patients passed away (18.9%), 13 due to the fact of disease progression. 4. Discussion Duodenal NENs are rare neoplastic lesions born by the aberrant proliferation of the neuroendocrine epithelial cells of the duodenal mucosa [3]. To date, no specific risk factors for the development of dNEN are known; thus, more efforts should be made to identify patients at risk (i.e., by the identification of preneoplastic lesions) in order to develop disease-specific surveillance [14]. In our multicenter study, we demonstrated that the existence of a DGM characterized a non-negligible percentage of dNEN cases, suggesting this could represent a potential risk factor for dNEN. DGM was, in fact, found in almost 13% of the entire cohort of 109 dNEN patients surgically treated. However, the actual percentage of DGM in the general population is poorly known as variable percentages have been reported in the literature [15,16], and this might be worthy of investigation. The percentage reported in the current paper was, conversely, quite far from the high percentage described for duodenal adenomas in which DGM has been found to be as high as 40.5%, even if this percentage could be underestimated, considering this alteration has never been described in relation with dNENs; therefore, one can hypothesize that with increasing awareness, this finding could have a greater frequency. Many studies have demonstrated that several lesions that were thought to be metaplastic may actually represent a potential precursor of common neoplasms. For example, colorectal hyperplastic polyps, which exhibit preserved overall crypt organization and no epithelial dysplasia [17], are commonly considered potential precursors of colorectal cancer [18]; similarly, pancreatic intraepithelial neoplasia 1A, which has also been previously regarded as mucinous metaplasia, is now well known to be the earliest stage precursor of invasive pancreatic adenocarcinoma [19]. Likewise, some duodenal tumors, particularly those with a gastric epithelial phenotype, were interestingly proven to arise from DGM [20,21]. DGM is a condition characterized by the metaplastic replacement of the normal duodenal enterocytes by mucinous PAS-positive cells, migrating from the Brunner’s gland ducts and resembling the superficial gastric foveolar epithelium [22]. To be accurate, DGM should be distinguished from duodenal gastric heterotopia (DGH), which is instead characterized by the presence of both the gastric foveolar epithelium and the oxyntic glands. Because of its fully organized structure, DGH has been interpreted as a congenital lesion [23], while DGM is generally regarded as an acquired reactive process caused by chronic inflammatory conditions [24]. The prevalence of DGM is, in fact, higher in patients with HP infection, as it induces a high level of acid burden in the duodenum by increasing gastrin secretion; moreover, the presence of DGM may create a suitable environment for HP colonization, which may exert a cytotoxic effect on mucosal cells and, thus, to the development of further DGM [24,25]. In our study, none of the patients had a concomitant HP infection. As concerned PPIs, five patients in our cohort with DGM were taking PPIs, a fraction not different from the group without DGM, without therefore suggesting a particular etiopathogenetic role of PPIs in the genesis of DGM-related dNEN. However, even if this percentage was not different between the groups, it was surely of relevance in both groups; therefore, one could also hypothesize that PPIs could have a role in the development of duodenal NENs. Unfortunately, this study did not have the power to investigate this topic. Concerning the possible different characteristics or outcomes of the dNENs arising in DGM, when comparing the two groups, with and without DGM, we observed that the 14 patients with DGM were younger, and most of the dNENs with GDM were located in the superior part of the duodenum. The reason for this is unknown. It could be hypothesized that there are some different etiopathogenetic factors in the genesis of dNEN originating from the first duodenal portion (for example, the effect of hydrochloric acid or different distributions of neuroendocrine cells types, i.e., somatostatin-, gastrin-, serotonin-producing cells). Unfortunately, these are only speculative hypotheses, and this type of study cannot answer this question. Moreover, interestingly, among the 14 patients with DGM, none showed a metastatic disease (none at stage IV) or G3 neoplasms. This might suggest that dNEN associated with DGM could be more similar to the gastric neuroendocrine neoplasms, such as those arising from gastric metaplasia and, therefore, more indolent and lower grade. Genetic mutations have been also demonstrated to play a potential role in the development of DGM; GNAS and KRAS mutations, for instance, which are generally frequently present in benign/low-grade tumors of the digestive tract [18,26,27,28], were reported to be prevalent in DGM lesions, suggesting that these genetic alterations induce the proliferation of metaplastic epithelium [29]. Given these demonstrations and based on the association observed in our study, one might speculate that the occurrence of DGM is an epiphenomenon of genetic mutations and a chronic inflamed microenvironment [22] together with the gastrin-mediated dysregulation of molecular pathways [4,25,26,27], promoting tumorigenesis, including dNEN formation [28], with possible implications for the endoscopic follow-up of patients with DGM. In the presence of DGM at histology, in fact, it might be possible to consider a closer endoscopic follow up in order to detect early the presence of dNEN. We acknowledge two main limitations of our study. First, the retrospective nature of the study and the small sample of patients limit the strength of our conclusions; however, dNEN is a rare disease; thus, large prospective cohort studies are difficult. Second, the histological revision of the pathologic samples was not centralized. However, only pathological examinations performed at referral centers for NENs were included in the study, whereas patients with incomplete information were excluded from the analysis. 5. Conclusions In summary, DGM was found in almost 13% of the entire cohort of 109 dNEN patients surgically treated, thus representing a remarkable percentage. Given these data, one might speculate that the presence of DGM could precede the development of dNEN; the common finding of this lesion in the general population as well as the current lack of disease-specific literature allow for the clinical relevance of this possible association to be clarified; however, it should be kept in mind in the endoscopic follow up of patients with DGM that even the lack of clear-cut evidence does not allow to suggest a specific timeline for endoscopic follow up. Moreover, the DGM-related dNEN could have a different natural history compared to the dNEN not related to DGM and, therefore, be susceptible to different treatments. In conclusion, our observations highlight the need for further studies, ideally creating international disease registries, to better understand the biology and natural history of dNEN and, thus, to improve the management of this heterogeneous disease. Acknowledgments Membership of the ItaNet Study Group: Massironi, S.; Rossi, R.E.; Milanetto, A.C.; Andreasi, V.; Campana, D.; Partelli, S.; Gallo, C.; Zerbi, A.; Panzuto, F.; Pasquali, C.; Falconi, M. Author Contributions Conceptualization, S.M. and R.E.R.; methodology, S.M. and R.E.R.; formal analysis, S.M.; investigation, A.C.M., V.A., D.C., G.N., S.P., C.G., A.Z., F.P. and C.P., ItaNet (Italian Association for Neuroendocrine Tumours) Study Group; writing—original draft preparation, S.M., R.E.R., C.G. and M.S.; writing—review and editing, S.M. and R.E.R.; supervision, M.F. and P.I. 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. Due to the retrospective nature of this study, ethical approval was waived. Informed Consent Statement Patient consent was waived due to the retrospective nature of the study. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Representative hematoxylin and eosin stain (A), synaptophysin (B) and chromogranin (C) of a duodenal NEN in a 75 year old male patient. The neoplasia was characterized by low mitotic activity (MIB1-labeling index: 0.2%, mitotic index: 0), and a final diagnosis of G1 neuroendocrine tumor was reached (original magnifications: 40×). jcm-11-02658-t001_Table 1 Table 1 Baseline characteristics of patients with duodenal gastric metaplasia (DGM) associated with duodenal neuroendocrine neoplasms (dNENs) compared to dNEN patients without DGM. Characteristics dNENs p w/o DGM n (%) with DGM n (%) Number of patients 95 (87) 14 (13) Age (years), median (range) 58 (17–83) 61.5 (32–74) n.s. Gender (M/F) 57/38 (11/3) n.s. Location Superior part of the duodenum Periampullary Descending duodenum NA 27 (28.4 40 (42.1) 21 (22.1) 7 (7.4) 9 (64.4) 1 (7.1) 3 (21.4) 1 (7.1) 0.0332 Grading (12) G1 G2 G3 NA 56 (58.9) 23 (24.3) 7 (7.3) 9 (9.5) 10 (71.5) 3 (21.4) 0 1 (7.1) n.s. Diameter (mm), median (range) 15 (1.5–130) 11 (3–37) n.s. Functioning (gastrinoma/somatostatinoma) Nonfunctioning 28 (29.4) (23/4) 69 (70.6) 5 (35.7) (4/1) 9 (64.3) n.s. Single Multiple 82 (86.3) 13 (13.7) 11 (78.6) 3 (21.4) n.s. Stage (13) I II III IV 20 (21) 15 (15) 42 (44) 19 (20) 6 (42.8) 5 (35.7) 3(21.4) 0 0.0236 Type of surgery Pancreaticoduodenectomy Total pancreatectomy Duodenotomy + enucleation Partial duodenectomy + lymphadenectomy 58 (61) 4 (4.2) 28 (29.5) 5 (5.3) 3 (21.4) 0 6 (42.9) 5 (35.7) 0.0007 MEN-1 17 (17.9) 1 (7.1) n.s. Proton pump inhibitor 31 (32.6) 5 (35.7) n.s. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods11091349 foods-11-01349 Article Consumer Attitudes towards Food Preservation Methods Guzik Paulina 1 https://orcid.org/0000-0001-5673-7093 Szymkowiak Andrzej 2* https://orcid.org/0000-0002-1696-4045 Kulawik Piotr 1 Zając Marzena 1 Calvo-Porral Cristina Academic Editor 1 Department of Animal Products Processing, Faculty of Food Technology, University of Agriculture in Kraków, ul. Balicka 122, 30-149 Kraków, Poland; paulina.guzik@urk.edu.pl (P.G.); kulawik.piotr@gmail.com (P.K.); marzena.zajac@urk.edu.pl (M.Z.) 2 Department of Commerce and Marketing, Institute of Marketing, Poznań University of Economics and Business, ul. Niepodległości 10, 61-875 Poznań, Poland * Correspondence: andrzej.szymkowiak@ue.poznan.pl 06 5 2022 5 2022 11 9 134902 4 2022 01 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 development and scope of using various food preservation methods depends on the level of consumers’ acceptance. Despite their advantages, in the case of negative attitudes, producers may limit their use if it determines the level of sales. The aim of this study was to evaluate the perception of seven different food processing methods and to identify influencing factors, such as education as well as living area and, at the same time, to consider whether consumers verify this type of information on the labels. Additionally, the study included the possibility of influencing consumer attitudes by using alternative names for preservation methods, on the example of microwave treatment. The results showed that conventional heat treatments were the most preferred preservation methods, whereas preservatives, irradiation, radio waves and microwaves were the least favored, suggesting that consumers dislike methods connected with “waves” to a similar extent as their dislike for preservatives. The control factors proved to significantly modify the evaluation of the methods. The analysis of alternative names for microwave treatment showed that “dielectric heating” was significantly better perceived. These research findings are important as the basis for understanding consumer attitudes. Implications for business and directions of future research are also indicated. consumer perception preserved food acceptance food preservation preservation method novel methods of food preservation National Centre for Research and Development in PolandPOIR.01.01.01–00–1438/15 This research was funded by of the National Centre for Research and Development in Poland under the “Szybka Ścieżka” program No. POIR.01.01.01–00–1438/15, “Innovative Technology for Pasteurization of Food Products Using Microwaves also in a Modified Atmosphere”, in cooperation with the Weindich Sp. J. company. ==== Body pmc1. Introduction According to European Union law, producers are obliged not only to provide information regarding nutritional value on food and beverage packaging, but also of the specific treatment that has been used on the food product [1]. As consumer awareness increases, so does their attention to what food products they purchase by reading the labels, which often influences purchasing decision [2]. Products which are supposed to be beneficial for people’s health are more likely to be chosen. The most frequently checked consumer information on the packaging is the expiration date, ingredients list and the nutritional value [2,3,4,5,6], whereas the processing method is the least searched [7]. Consumers nowadays seek for products that are fresh, tasty, do not contain preservatives or other chemical additives but, at the same time, are safe and have a long shelf-life. Many people prefer natural foods with “green labels” [8,9,10]. The food producer must adapt to the preferences of consumers and earn their trust, to gain their acceptability [6,11]. The answer to the needs of consumers regarding the high nutritional values and clean label trend is the use of novel technologies in the food industry. The lack of consumer acceptance analysis may determine the high failure rate of novel product implementation, which is why it is crucial to appropriately communicate the use of innovative technologies to consumers [12]. Despite their growing awareness, many consumers exhibit fear of innovative technologies and may show resentment towards novel food products produced with the use of such technologies. This phenomenon is called food technology neophobia and is connected with the cult of natural or traditional food [13,14,15]. Additionally, this is a personality trait that affects consumer willingness to accept new food technologies [16]. There is a belief that traditional, simple food, without preservatives, has the highest nutritional value and is of best quality, which is why such products are highly desirable [11,17]. Moreover, consumers are often deterred by the complicated names of technologies that are unknown and incomprehensible to them [16,18]. Other reasons for the emergence of food technology neophobia are disgust, reluctance towards sensory feature, and fear of danger after consuming this product. Many factors have impact on this phenomenon, including psychological barriers, knowledge, functional barriers connected to ease of use, benefits and risks as well as socio-demographic factors [13]. Furthermore, education level and appropriate dissemination of information are important factors for facilitating the widespread adoption of new food technologies and avoiding failure in innovative marketing strategies [19]. Therefore, production processes and marketing activities should be combined in such a way that consumers perceive it as a product that is as natural and familiar to them as possible [10]. Recent years have shown significant technological progress in the food sector, thereby increasing the quantity of new products on the market [20,21]. Despite the reluctance of consumers to accept new technologies, food products created using such methods may have a positive effect on the product choice. The advantages of using new technologies are: increased production efficiency, increased safety and nutritional value with less demand for energy, water and chemicals, which is also important for sustainability [16,22]. The goal of food preservation is to provide microbiological safety and extend the shelf-life of products. Due to its effectiveness, despite the development of novel technologies, conventional thermal preservation methods are still the most commonly used approaches in the industry [23]. Pasteurisation consists of heating the product up to the temperature of 100 °C, while during sterilisation, the temperature exceeds 100 °C. In conventional thermal preservation methods, heat is generated outside of the material and occurs via convection throughout its entire volume [24]. Despite guaranteeing microbiological safety, these traditional methods result in reduction of some thermally sensitive food ingredients, especially vitamins and polyphenols, which are related to food quality [25]. Microwave heating is a valid alternative to conventional heating. Microwaves are radio waves in the spectrum of electromagnetic radiation with wavelengths ranging from one millimetre to even one metre. In literature on the subject, microwave heating is often referred to as dielectric heating because waves are absorbed by materials having dielectric properties [26,27]. Such materials, also called dielectrics, have a relatively high specific resistance and low electrical conductivity. Moreover, the molecules or atoms comprising the dielectric (such as agri-food products) exhibit dipole movement. Microwave technology is a widely used technology within the food industry. It is applied for cooking, drying, thawing, pasteurisation or sterilisation of food products and most households contain a small microwave [28,29,30,31]. There are also non-thermal technologies that extend the shelf-life of food products without the use of high temperatures. One of such is the use natural bioactive compounds such as using plant materials. Some plant extracts show antioxidant and/or antimicrobial properties and can be used as an alternative to chemical preservatives [32]. Another example are chitosan-based apple peel polyphenols [33] furcellaran-chitosan [34] or furcellaran-gelatin with green and pu-erh tea edible coatings [35]. Physical non-thermal preservation methods allow reduce treatment time. Different non-thermal preservation technologies include ionising radiation, which is also in the range of electromagnetic waves [25]. Irradiation of food uses low-energy radiation and 3 types of radiation are authorised for use in the food industry, which include high-energy gamma rays, X-rays and accelerated electrons in accordance with the Codex General standard for Irradiated Food [25,36]. Irradiation works directly through damage of cell components such as carbohydrates, DNA and lipids, and indirectly via free radicals and reactive species (e.g., hydro-electrons, hydrogen atoms, or hydroxyl radicals). It is a consequence of radiolysis of water reaction with cells or food components, and has proven effective in the reduction of insects and microorganisms [37,38]. High hydrostatic pressure (HHP) is a technique in which pressures of 100–1000 MPa are applied to the product, resulting in the inactivation of the majority of pathogenic microorganisms. HPP-treated food must be packed and contain water, then closed in a chamber where the pressure is gradually increased. It is closed in a chamber where the pressure is increased. Depending on the type of food, the process lasts from several seconds to 20 min [39,40]. Consumer demand for freshness and the longest possible shelf-life can be provided by packaging in modified atmospheres (MAP). This technology is based on packaging in vapour- or gas-barrier materials of fresh and minimally processed food products in a packaging system where the air composition is changed, ensuring an optimal gas composition around the product. Due to reduced O2 and CO2, the metabolic processes and microbial activity significantly slow down, thus extending the shelf-life of the food product [41,42]. The abovementioned techniques are only several examples of the modern methods already in use within the food industry and producers apply them to preserve their products. The applicability of the methods may depend on many factors and also have their pros and cons. The advantages and disadvantages of the described technologies are presented in Table 1. Despite growing awareness, many consumers do not read labels for various reasons, such as lack of time, too much information on the label or trust in the brand name [5,43]. From the producer’s point of view, consumers who declare reading labels are credible in assessing the product, and it can also be assumed that they understand the declarations on the label better. The results of the study carried out by Szymkowiak et al. [7] allowed to show a specific attitude-behaviour dissonance in which consumers declared that the most important attribute of the product choice is the processing method, even though it was the least searched for on the label. Despite the many advantages and electromagnetic heating being widespread, especially the microwave spectrum, some consumers still negatively perceive this kind of preservation. Negative associations are related to radiation and it being harmful for human health [3,57,58,59]. One of the potential ways to improve microwave perception among consumers is changing the method name to another “safe sounding” synonym. Associations of the preservation method with a product influence purchasing decision [60,61]. Therefore, the aim of this research study was to evaluate the perception of different food processing methods and to identify factors influencing them. In the study, the possibility of influencing the attitudes of consumers by modifying the processing name was also included. 2. Materials and Methods 2.1. Respondents In order to assess the preferences of various food preservation methods, a questionnaire study was conducted among 438 respondents who declared that they were responsible for making food purchases in their households. The survey was conducted both in electronic and paper version to reach respondents from rural areas, who do not actively use the Internet. In both cases, the participants did not receive any remuneration. Participants who failed the validation questions (e.g., “If you read the question carefully, select the answer I strongly disagree”, n = 33) were excluded from the analyses. Therefore, the answers of 405 respondents were taken for analysis. The mean age in the analysed sample was 34.71 (SD = 1.85, minimum = 19, maximum = 85). The majority were women (74%). The group differed in terms of household and place of residence size. The detailed characteristics of the sample are presented in Table 2. 2.2. Study Design The questionnaire was divided into 3 parts. In the first one, the respondents were to indicate their attitude towards the analysed methods (Table 3) on a 7-grade scale where 1—means a very negative attitude and 7—a very positive attitude. In the second part of the study, a photo of the product (ham) was presented 4 times together with an annotation that the product was preserved by 1 of 4 methods: electromagnetic wave with a length of 32.76 cm (wavelength of microwave at 915 MHz frequency), dielectric wave, electromagnetic wave or microwave. These terms are synonymous with each other from a technological perspective; however, linguistic modifications were assumed to be associated with different reactions and thus, different perception of the product. The order of displaying the methods was random, which allowed to eliminate bias. Participants were not provided with additional definitions or explanations of the methods. This allowed their overall relationship with the methods to be assessed, which is consistent with the level of detail shown on product labels. On this basis, consumers were to state how much they would be interested in purchasing a product on a seven-point scale (1—“definitely not”, 7—“definitely yes”). Finally, the respondents answered the identification questions, including those regarding their purchasing behaviour. 2.3. Data Analysis At the stage of data analysis, ANOVA with repeated measurements was used. This type of analysis of variance, to a greater extent, allows to take the variability for a particular respondent into account. Thus, it is possible to identify differences, also in a situation where some respondents generally expressed higher preferences for all methods, or vice versa. Subsequently, additional analyses were conducted between groups due to additional moderators important from the perspective of the subject under study: education and declared paying attention to processing methods when selecting food products at a store. In the case of education, the division was made into 3 groups: people with secondary and lower education (n = 129), bachelor level (138), and master’s degree level and higher (138). The χ2 analysis showed that the differences in group sizes were statistically insignificant: chi2 (2) = 0.04, p = 0.98. In the case of the second variable, two groups were created: people who verified (155 respondents) and did not verify the type of preservation method (250). 3. Results and Discussion 3.1. Consumer Preference for the Food Product Preservation Method In the first part, ANOVA analysis was performed in 3 iterations. The first analysis allowed to confirm that the method strongly determined preferences F (2828, 7) = 271.159, p < 0.001, η2 = 0.402. Post-hoc analysis, applied to compare the obtained values for all pairs, showed significant statistical differences between them, apart from the relationship between MWV and RWV (t(404) = 2.192, p = 0.057) and between in RWV and PRE (t(404) = 1.702, p = 0.089). Detailed values for all comparisons are presented in tabular form in Supplementary material (Table S1). The most negative ratio (average below 3 on the 1–7 scale) was indicated by the respondents in relation to IRR (M = 1.975, SD = 1.379), PRE (M = 2.235, SD = 1.348), RWV (M = 2.398, SD = 1.462) and MWV (M = 2.607, SD = 1.501). The respondents expressed a more positive attitude towards MAP (M = 3.672, SD = 1.868), HPP (M = 4.052, SD = 1.790) and STE (M = 4.306, SD = 1.763). The PAS method was rated the highest (M = 4.975, SD = 1.613). Next, an analysis was conducted with the use of a moderator, which was the declared behaviour in the store. A table with results of post-hoc analysis, depending on in the store behaviour, is provided in Supplementary material (Table S2). This analysis revealed that the factor significantly influences the general level of preferences in relation to all methods (F (403.1) = 5.423, p = 0.02, η2 = 0.003). People who check food preservation methods on products when shopping at a store express a more positive attitude towards all of the methods (Figure 1). The results of the study indicate differences between various methods of food preservation and consumer preferences. Consumers’ nutritional literacy affects their ability to process food labels [62]. Therefore, it can be assumed that consumers who declared verifying the preservation method on the label of food products have a better understanding of the method itself. In our study, consumers who verified the preservation method gave higher ratings for preservation method preferences, but the trend was the same for non-verifying consumers. In this study, PAS and STE were conventional types of preservation methods and both of them received the highest score. Consumers are accustomed to the above-mentioned techniques because they associate them with traditional production to which they are accustomed [63,64]. Moreover, they were programmed from early childhood to prefer familiar foods [65]. Conventionally processed products are mainly associated with health and natural products, while those including references to industrial processing technology are perceived as processed and, therefore, unhealthy [66,67]. MAP and HHP were also rated relatively high, which may mean a positive reception of these technologies. In previous research conducted by Deliza and Ares [12], it was also confirmed that consumers have a positive attitude towards HHP and are willing to buy products treated via this technology, after being informed about how this method works. Nonetheless, it should be noted that many people have never heard of this technology. In a study by Lee et al. [68], the respondents evaluated juices treated with HHP and pulsed electric fields. In their opinion, conventional thermal treatment decreased the pleasant notes such as natural and fresh, whereas undesirable notes like cooked flavour or sourness increased. Similar to the case of MAP, Guerrero [11] demonstrated that this technology was negatively perceived by consumers. Participants were suspicious and immediately rejected the MAP packed product. Moreover, it was noted that they are not willing to pay more for products packed in MAP, despite the fact that those products maintained freshness and high quality for a longer period of time. Ortiz et al. [69] indicated that consumers can pay more for vacuum packaging as opposed to MAP. The significance of naturalness has crucial meaning for consumers nowadays. They prefer food free from preservatives, additives or artificial ingredients for perceived naturalness of foods. The result is that now, more than ever, manufacturers often try to produce products with “green labels” [10]. A perceived lack of naturalness also hinders the acceptance of new food preservation methods and technologies [65]. This phenomenon would explain the negative perception of preservatives in our research. In a study by Perito et al. [67], the majority of the respondents declared willingness to consume biopreservatives, only if they replaced synthetic ones. According to Dominick et al. [70], 83% of respondents agreed that a product with an “all natural” label meant no preservatives. They perceived “all natural” foods without preservatives and additives as products with better taste, nutritional value and increased food safety. IRR, RWV and MWV were similarly perceived, relatively negative, as the preservatives. These, technologies have a common denominator, since all 3 methods are based on “waves”. In a survey by Szymkowiak et al. [7], respondents showed dislike towards the microwave preservation method, whereas conventional thermal preservation was considered the most positive. Microwave technology is known to consumers through the widespread domestic use of microwave ovens. However, there is a common belief among such consumers that microwaved foods are unhealthy and often associated with radiation [58]. The negative perception of microwaves can be a result of disinformation and fake news in social media, such as “using microwaves to heat food can cause carcinogenesis” [71,72]. In their study, Wolfson et al. [73] noted that consumers perceived microwave heating negatively due to radiation or “zapping” nutrients out of the food. Especially among the older generation of consumers, their statement was also that microwave heating is “lazy” or “cheating” one’s way out of cooking. Consumer aversion to radiation-related technologies of food preservation may be associated with the risk of making food radioactive or the formation of harmful compounds, but also with the wrong image that food irradiation is a nuclear technology. Moreover, for some consumers, products labelled as irradiated may be read as a health warning [12,61,74,75]. The lack of proper knowledge affects consumer acceptance of food irradiation technologies and can be a main reason for the limited application this method [74]. 3.2. Consumer Preference for Food Product Preservation Methods According to Education Level and Main Area of Residence For the education variable, the study revealed between- (F (402.2) = 4.090, p = 0.017, η2 = 0.005) and within-subject effects (F (2814.14) = 4.122, p = 0.001, η2 = 0.009). This indicates that the level of education determined the overall level of method preference as well as the interaction effect. People with lower educational levels, compared to other groups, showed lower preferences for most methods, except pasteurisation (Figure 2). A table with the post-hoc analysis values for all 276 pairs of comparisons can be found in Supplementary material (Table S3). Moreover, we observed that the main place of the respondents’ residence determines the level of acceptance of various methods (F (3.401) = 4.874, p = 0.002). Residents of rural areas, on average, assessed the methods of food preservation by 0.4 lower on a 7-level scale than residents of cities with 100,000–500,000 inhabitants ((t(404) = 2.662, p = 0.04), and compared to residents of cities with above 500,000 inhabitants ((t(404) = 3.444, p = 0.004). This means that people living in rural areas have a lower acceptance of various food preservation methods. The results of our research allowed to show that respondents with the lowest (1 in Figure 2) education level caused polarisation between the options for declaring preferences for preserving methods. It can be interpreted that they definitely prefer the familiar, conventional technologies, and most definitely, do not prefer those which are unknown to them. The group of consumers with the highest education level (3 on the graph) perceived novel methods better compared to those least educated. This may result from the fact that more educated people show greater knowledge and awareness related to novel methods of food preservation. Popek and Halagarda [76] also confirmed correlations between education level, place of residence and greater knowledge of consumers. Similarly, Moreb et al. [77] indicated that people living in the city were more knowledgeable about food safety and food handling practices than those who lived in the countryside. The survey, in which consumers were asked about their knowledge of microwave radiation and its effect on food, revealed that consumers know very little about it. The reason may be that it is difficult to obtain such knowledge from reliable sources [3,78]. Most consumers who do not know the process or who have little knowledge of it, show greater uncertainty regarding the safety of processed food products and often believe that they are dangerous and may pose a health risk [74]. Verbeke et al. [79] demonstrated that providing additional information about novel technologies positively increased their perception. Nonetheless, preservatives, although known to most people, are nor accepted. Increasingly, manufacturers are resigning from their addition, despite the fact that they are mostly considered safe. However, due to the fact of their potentially negative effects and low level of acceptance among consumers, other solutions or natural substitutes are being sought [80,81,82]. 3.3. Consumer Preference for Alternative Names of Microwave Treatment In the last part of the analysis, in accordance with the second goal adopted in the paper, the impact of the alternative name of the method for microwaves on product perception, was analysed. The study revealed that different names cause different perceptions of the product (F (1212.3) = 17.874, p < 0.001, η2 = 0.042). Post-hoc analysis revealed that while interchangeably using MWV, EMV, LWV does not cause statistically significant differences, the DIE version of labelling (M = 2.986, SD = 1.510) results in more desirable reactions (Table 4). Additional analyses carried out with controlling the inter-group factor revealed the importance of both the interest in the processing methods expressed by the declaration of method verification while shopping ((F (403.1) = 8.533, p < 0.004, η2 = 0.015) and education ((F (402.2) = 4.571, p < 0.011, η2 = 0.016) on the use of alternative names for general product preferences. Detailed analysis confirmed that consumers, verifying methods while shopping, better perceived the product described as DIE (M = 3.316, SD = 1.445), and this was a statistically significant difference (t(404) = 3.769, p = 0.004) compared to the preferences for this version of the product declared by persons who did not verify the method (M = 2.752, SD = 1.511). In the case of education, the mean value of the group with the lowest education was lower (M = 2.767, SD = 1.598) than in the group with undergraduate (M = 3.116, SD = 1.324) and graduate education (M = 3.007, SD = 1.587). Microwaves are non-ionising electromagnetic waves having a frequency within the range of 30–300 MHz, and wavelength ranging from 1 m to 1 mm. Microwaves are recognised as radio waves and are absorbed at the molecular level. They react with dipoles and ions and have the ability to heat a material with dielectric properties. This explains why various names of the microwave technology (such as “electromagnetic radiation” or “radio-frequency waves preservation”) could be used. The thermal effect of microwaves is obtained through the molecular movement of dipoles and ions, which generates friction among the rotating molecules and, subsequently, in the dissipation of the energy as heat [29,83,84]. Due to the negative perception of microwave treatment [7], in this study, 4 alternative names were compared (microwave preservation—MWV; preservation using am electromagnetic wave with a length of 32.76 cm—LWV; electromagnetic wave preservation—EMV; and dielectric heating preservation—DIE). MWV, LWV and EMV showed no significant differences in consumer perception. Only dielectric heating preservation was significantly better perceived among alternative names. This might be because only in this name was there no reference to “waves”. In addition, the prefix “di” refers to multiplication, which can be seen as an enhancing element increasing and improving the attributes of the product. Moreover, consumers might associate them more with the traditional methods of meal preparation using an electric stove or magnetic induction (dielectric and electric). This, however, is just a hypothesis which should be confirmed in future research. Familiar associations of technology name with technologies that can be applied at individual households increase acceptance [18], whereas the term “radiation” in microwave radiation can raise concerns [85]. It should be also mentioned that although dielectric heating preservation was perceived much better than alternative names of microwave treatment, the preference value was still 3.316, which is relatively low compared to the other methods under study, as it was below the lower half of the rating scale (Supplementary material). Such a different attitude can also be explained on the basis of feelings-as-information theory [86,87,88]. The ease of processing individual names influences judgment [89]. Subjective experiences such as emotions and metacognitive feelings serve as a source of information for consumers and influence decisions made [87,90,91]. In this study, the importance is shown of terminology used in food technology in relation to consumer perception. Names that evoke positive associations are more preferred by consumers [60,61]. Even without knowing the details of the new technologies, the name itself may affect the perception by consumers and their willingness to buy. On an example of cultured meat, Verbeke et al. [79] explained that possible cognitive association or attitude activation matter, such as “in vitro” may activate attitudes linked with laboratory practices or growth processes in bioreactors. “Technical” names may evoke thoughts or strengthen perceptions of unnaturalness, being too scientific for the consumers. In a study by Martins et al. [66], respondents positively associated the cold-pressed juice concept, although the processing method was unknown to them. They had associations with a natural and unprocessed product, probably due to the words “pressed” and “cold” in the name of the technology. There are various advantages and benefits that many novel food processing technologies provide for food processors and consumers alike. Despite this, however, many consumers negatively regard these novel food technologies. Changing the name of the preservation method, especially to one which is not associated with “waves”, seems to be a valid alternative for food processors. Additionally, the research results indicate that for producers, the application of the methods may also be conditioned by the target group and market. This can increase consumer trust and willingness to buy, while maintaining safety and often higher nutritional value of the product. 4. Conclusions The implementation of new technologies is an indispensable element of food engineering and the production of new food products. Novel food processing and preservation technologies offer many advantages in terms of nutrient retention, good quality and food safety. However, the implementation of new technologies is strongly related to acceptance by consumers. The results of this study allowed to indicate that conventional methods of food preservation were best perceived and accepted by respondents as they are well-known to them. Packaging in a modified atmosphere and with high hydrostatic pressure were also relatively well-perceived, whereas every method related with radiation (microwaves, radiowaves, irradiation) were perceived negatively, comparably to preservatives. Higher-educated respondents perceived new technologies more positively, which may result from their greater awareness and knowledge of food preservation. In the evaluation of the preferences for alternative methods to microwave treatment, the respondents rated “dielectric heating” as the best compared to the alternative “waves” methods. Consumers, despite their interest in new methods of food processing and preservation, are still distrustful of new technologies and worry about food safety. Increasing efforts regarding education about these technologies should result in their acceptance. Moreover, future research could be conducted to investigate, what, apart from the name of the preservation technology, would convince the consumers to increase their preferences for novel food preservation technologies. The authors, despite their best efforts, have not managed to eliminate all the factors that limit the generalization of the obtained conclusions. The study was done both online and on paper, which made it possible to reach people who do not use the Inter-net less or at all, in addition, the data was also collected in rural areas, however, it does not allow to indicate that the sample is representative. The study focuses on the general assessment of individual methods and the identification of indirect factors, such as education or the main area of residence, without referring to the immediate reasons that may determine individual preferences. Understanding the motives is an important next step in understanding consumer behaviour and how to form their attitudes. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods11091349/s1, Table S1: Post hoc comparisons—methods; Table S2: Post hoc comparisons—in-store behaviour ∗ methods; Table S3: Post hoc comparisons—education level ∗ Methods. Click here for additional data file. Author Contributions P.G.: Investigation, Resources, Writing—original draft. A.S.; Methodology, Supervision, Formal analysis, Writing—review and editing. P.K.; Project administration, Supervision, Writing—original draft, Writing—review and editing; M.Z.: Supervision, Writing—review and editing. 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 Committee of Ethical Science Research conducted with participation of humans at Poznań University of Economics and Business (Decision no. 5/2022 24 March 2022). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data is contained within the article or supplementary material. 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 Consumer’ preference for food product preservation methods (PRE—addition of preservatives; IRR—irradiation preservation; RWV—radio wave preservation; MAP—packaging in modified atmosphere preservation; STE—sterilisation; PAS—pasteurisation; HPP—high pressure processing; MWV—microwave preservation). Figure 2 Consumer preference for food product preservation methods depending on education level; 1—lowest; 2—average; 3—highest (PRE—addition of preservatives; IRR—irradiation preservation; RWV—radio wave preservation; MAP—packaging in modified atmosphere preservation; STE—sterilisation; PAS—pasteurisation; HPP—high-pressure processing; MWV—microwave preservation). foods-11-01349-t001_Table 1 Table 1 Advantages and disadvantages of selected food preservation methods. Treatment Advantages Disadvantages Source Conventional pasteurisation and sterilisation - High effectiveness of preservation. - Slow heat transfer and long sterilisation time; - Deterioration of colour, texture and flavour; - Significant losses of nutritional value; - High degree of sewage generation; - High cost of application. [24,44,45] High hydrostatic pressure - Non-thermal technology; - Inactivation of vegetative forms of most microorganisms, such as Salmonella spp., Listeria monocytogenes, yeast, moulds and inactivation of enzymes that cause food spoilage; - Preservation of nutritional value and quality of the product. - High investment costs; - Inactivation rate can be insufficient, depending on the type of organism and treatment parameters; - Low throughput; - Food containers must be resistant to deformation. [46,47,48] Modified atmosphere packaging - Preserving the stability of fresh or minimally-processed food; - Non-thermal technology; - Can be used in combination with almost any other preservation technique; - Inhibits the growth of microorganisms as well as oxidation progression; - Prevents discolouration of some products (if appropriate gas mixture is used). - Increases the packaging cost; - Requires more space during storage; - Packages can be easily damaged resulting in a food safety hazard; - The most favourable gas mixture must be chosen for each product type; - Limited effectiveness, not comparable to conventional pasteurisation and sterilisation. [41,49,50] Microwaves - Operational safety; - Minimal loss of heat-labile nutrients (vitamins, antioxidants, phenols and carotenoids); - Reduced processing time; - Lower energy and water demand; - Volumetric heating. - Hot and cold spots; - The treated products have to be in regular shapes and of homogenous structure. [29,51,52,53] Irradiation - Microorganism inactivation; - Non-thermal method; - Easy to control; - Can save energy consumption up to 70% to 90%. - Expensive equipment; - Taste of irradiation when - operating improperly; - Necessity to provide information about using this method on the label in many countries; - Multiple legislator restrictions in many different countries. [54,55,56] foods-11-01349-t002_Table 2 Table 2 Description of the study group. Gender Women 301 Men 104 Total 405 Main area of living City with up to 100,000 inhabitants 88 City with 100,000–500,000 inhabitants 54 City with above 500,000 inhabitants 128 Rural 135 Total 405 Number of people in the household 1 41 2 85 3 92 4 96 5 58 above 5 33 Total 405 foods-11-01349-t003_Table 3 Table 3 Designation of the analysed methods. Food preservation methods Abbreviations used in the text Radio Wave Preservation RWV Irradiation preservation IRR Addition of preservatives PRE Packaging in modified atmosphere preservation MAP Preservation with high temperatures—pasteurisation PAS Preservation with high temperatures—sterilisation STE Dielectric heating preservation DIE Microwave preservation MWV High-pressure processing HPP Microwave preservation MWV Preservation with electromagnetic wave (32.76 cm length) LWV Electromagnetic wave preservation EMV Dielectric heating preservation DIE foods-11-01349-t004_Table 4 Table 4 Post-hoc Comparisons—Alternative names for microwaves (PRE—addition of preservatives; IRR—irradiation preservation; RWV—radio wave preservation; MAP—packaging in modified atmosphere preservation; STE—sterilisation; PAS—pasteurisation; HPP—high-pressure processing; MWV—microwave preservation). Mean Difference SE t Cohen’s d Holm’s p DIE EMV 0.402 0.066 6.121 0.304 <0.001 LWV 0.356 0.065 5.504 0.273 <0.001 MWV 0.360 0.069 5.190 0.258 <0.001 EMV LWV −0.047 0.050 −0.946 −0.047 1.000 MWV −0.042 0.062 −0.678 −0.034 1.000 LWV MWV 0.005 0.064 0.078 0.004 1.000 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. European Parliament and Council EC, No 1169/2011 of the European Parliament and of the Council of 25 October 2011 on the provision of food information to consumers Eur. Commision 2011 20 168 213 2. Mulders M.D. Corneille O. Klein O. Label reading, numeracy and food & nutrition involvement Appetite 2018 128 214 222 10.1016/j.appet.2018.06.003 29886052 3. New C. Thung T. Premarathne J. Russly A. Abdulkarim S. Son R. Microwave oven safety: A food safety consumer survey in Malaysia Food Control 2017 80 420 427 10.1016/j.foodcont.2017.05.024 4. Hieke S. Newman C.L. 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==== Front Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods11091283 foods-11-01283 Review Role of Lactic Acid Bacteria in Food Preservation and Safety Zapaśnik Agnieszka 1 https://orcid.org/0000-0002-6217-2401 Sokołowska Barbara 1* https://orcid.org/0000-0002-1855-3610 Bryła Marcin 2 Terpou Antonia Academic Editor 1 Department of Microbiology, Prof. Waclaw Dabrowski Institute of Agricultural and Food Biotechnology—State Research Institute, Rakowiecka 36, 02-532 Warsaw, Poland; agnieszka.zapasnik@ibprs.pl 2 Department of Food Safety and Chemical Analysis, Prof. Waclaw Dabrowski Institute of Agricultural and Food Biotechnology—State Research Institute, Rakowiecka 36, 02-532 Warsaw, Poland; marcin.bryla@ibprs.pl * Correspondence: barbara.sokolowska@ibprs.pl 28 4 2022 5 2022 11 9 128310 4 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/). Fermentation of various food stuffs by lactic acid bacteria is one of the oldest forms of food biopreservation. Bacterial antagonism has been recognized for over a century, but in recent years, this phenomenon has received more scientific attention, particularly in the use of various strains of lactic acid bacteria (LAB). Certain strains of LAB demonstrated antimicrobial activity against foodborne pathogens, including bacteria, yeast and filamentous fungi. Furthermore, in recent years, many authors proved that lactic acid bacteria have the ability to neutralize mycotoxin produced by the last group. Antimicrobial activity of lactic acid bacteria is mainly based on the production of metabolites such as lactic acid, organic acids, hydroperoxide and bacteriocins. In addition, some research suggests other mechanisms of antimicrobial activity of LAB against pathogens as well as their toxic metabolites. These properties are very important because of the future possibility to exchange chemical and physical methods of preservation with a biological method based on the lactic acid bacteria and their metabolites. Biopreservation is defined as the extension of shelf life and the increase in food safety by use of controlled microorganisms or their metabolites. This biological method may determine the alternative for the usage of chemical preservatives. In this study, the possibilities of the use of lactic acid bacteria against foodborne pathogens is provided. Our aim is to yield knowledge about lactic acid fermentation and the activity of lactic acid bacteria against pathogenic microorganisms. In addition, we would like to introduce actual information about health aspects associated with the consumption of fermented products, including probiotics. lactic acid bacteria lactic acid fermentation mycotoxins foodborne pathogens This research received no external funding. ==== Body pmc1. Introduction Fermentation technologies are of considerable significance for the food industry because they enable the preservation of food products and prolong their shelf-life while at the same time providing them with the desired sensory properties. Moreover, they have a favorable impact on the health-promoting value of food due to the presence of probiotic microorganisms and increasing nutrients in the product. In addition, they can increase microbial safety [1,2]. During a fermentation process, the development of undesirable microflora and the formation of unfavorable compounds is inhibited by metabolites of the microorganisms taking part in fermentation [3]. This is a highly desirable phenomenon, because it is linked with the possibility of reducing the addition of chemical preservatives to foods. Fermentation processes are the oldest biotechnological techniques used in food production, and they are currently among the primary processes used in the food industry. Fermented products, including bread, cheese, soy sauce, wine, beer, vinegar and many others, have been present in the human diet since the beginnings of civilization development. Traditionally, fermentation was conducted spontaneously, which resulted in low efficiency and variable quality of the final product. Presently, selected starter cultures are used in the conditions of industrial production. On the other hand, regional and craft products are often still based on spontaneous fermentation [2,4]. Not all freshly fermented products are suitable for instant consumption, because certain biochemical changes require time. The maturation process contributes to achieving stability and enhancement of the sensory quality of products due to the formation of specific flavoring compounds, including diacetyl, carboxylic acids, aldehydes, ketones and esters. These characteristics contribute to increased acceptability by consumers, who, apart from the health-promoting values, pay attention to the sensory attractiveness of fermented foods [1,2,3,5]. Fermentation consists in the metabolism of carbohydrates, proteins and fats under the influence of specific microorganisms, including yeasts, bacteria and filamentous fungi. In order to set a determined direction for the fermentation process, specific substrates and microorganism strains are used [3]. Depending on the selected substrates and microbial cultures, the process itself may assume the form of lactic, alcoholic, propionic, citric, butyric, methanol, mannitol or acetic fermentation [6]. Biopreservation, understood as a biological method for preserving foods with the use of microorganisms and their metabolites, has gained significant interest in recent years due to the increased awareness of consumers regarding chemical preservatives and their negative impact on health [7,8]. The most important chemical preservatives and their effects on human health are described in Table 1. Microorganisms used for the purpose of natural preservation should meet a range of requirements, including safety of use, the production of non-toxic metabolites, maintaining high activity during storage and the absence of a negative impact on the product’s sensory properties [12]. LAB are of particular importance in biopreservation processes due to the wide spectrum of their activity against the development of unfavorable microflora [13]. The aim of the study was to yield the available knowledge on the importance of the lactic acid fermentation process in enhancing food safety and the activity of LAB against food pathogens, including bacteria, yeast and filamentous fungi. In addition, we would like to highlight the health benefits associated with the consumption of fermented foods with LAB. 2. LAB Lactic fermentation is used, inter alia, for milk acidification and thus the production of fermented dairy products, such as yogurts, cheese, butter, sour cream, etc. [12]. Moreover, the process is responsible for the formation and stabilization of vegetable silage and sourdough and is used for cold cut maturation [14]. Fermentation occurs with the participation of homo- and heterofermentative LAB. Predominant cultures used in the processes of lactic fermentation are bacteria classified in the genus Lactococus, Streptococcus, Lactobacillus, Leuconostoc, Pediococcus, Weisella and Bifidobacterium. Homofermentation consists in the metabolism of disaccharides by select LAB strains to almost pure lactic acid. Heterofermentation is a slightly different process, where, as a result of lactose decomposition, ethyl alcohol, carbon dioxide, hydrogen peroxide, diacetyl, acetoin and acetic aldehyde are formed apart from lactic acid [14,15,16]. From the process standpoint, lactic fermentation is the easiest to conduct. The decrease of natural pH below 4.0 that occurs during the process does not have a negative effect on the efficiency of biochemistry, due to the dominance of LAB, capable of adapting to the low pH of the environment [17]. LAB are gram-positive, non-spore-forming and incapable of producing catalase bacilli and cocci. They are classified among relative or obligatory anaerobes, and they tolerate the acidic pH of the environment [18,19,20]. In April 2020, in the official register of the International Journal of Systematic and Evolutionary Microbiology, new nomenclature of Lactobacillus and Leuconostoc bacteria was published [21]. The purpose of that change was to systematize bacteria, which, due to high diversity, required correct classification. Modern methods of molecular biology enabled the introduction of expanded taxonomy for the genus [22]. In the present article, species names of the microorganisms will be used in accordance with the spelling used in the given source article. LAB are generally considered to be safe (GRAS) and are widely used in the food industry; moreover, they form the natural microflora of human intestines [23,24]. In the context of biopreservation, LAB play a very important role due to the fact that, during the growth and fermentation process, they produce a range of metabolites with antimicrobial action, which include hydrogen peroxide, lactic acid, acetic acid and low molecular weight substances (diacetyl, fatty acids, reuterin, reutericyclin), antifungal compounds (phenyl lactate, propionate, hydroxyphenyl lactate) and bacteriocins [25]. 3. Bacteriocins The bacteriocins group mainly consists of generally thermostable protein substances featuring antimicrobial properties. It is assumed that the effect of bacteriocins is based on the binding of phosphate residues present on cell membranes of the target cells, creating pores and the activation of autolysin that degrades the bacterial cell walls [26]. Bacteriocins belong to the diverse group of cationic and hydrophobic peptides built of 20–60 amino acids. Furthermore, their synthesis is based on ribosomal machinery. Bacteriocins encoding genes are located in operons in plasmids, chromosome and other genetic organelles [27]. One of the most important attributes of bacteriocins is their activity against other bacteria, fungi, viruses, parasites and natural structures such as biofilms [27,28]. Alvarez-Sieiro et al. [29] proposed the classification of bacteriocins produced by LAB based on three main classes. The class I includes modified, heat stable and low molecular weight peptides consisting of unusual amino acids such as lanthionine. The class II consists of unmodified thermostable, low molecular weight bacteriocins. The last class is the only group of thermolabile and high molecular weight substances [30]. Their activity takes different directions, such as bactericidal or bacteriostatic effects on species related with the producing strain. The environmental factor stimulates the production of bacteriocins, including nutrient availability, the density of the bacterial cell, acetic acid and signal peptides’ presence. The mechanism of their activity is based on their primary structure. Some bacteriocins have the ability to enter the cytoplasm of other bacteria and affect their gene expression and the synthesis of protein. On the other hand, some of them can exert their activity on the cytoplasmic membrane, contributing to cell lysis by releasing vital compounds of susceptible microorganisms [27]. The significant advantage of bacteriocins is their activity against opportunistic and pathogenic bacteria, including antibiotic-resistant strains. Furthermore, several bacteriocins show their synergy with antibiotics, contributing to reducing concentration and negative side effects. Their synergistic activity with other biomolecules such as citric acid and nisin against Listeria monocytogenes and Staphylococcus aureus is well known [31]. However, it is important to notice that the mentioned bacteria can develop a resistance to bacteriocins, but it is minimal compared to the conventional antibiotics’ resistance [31]. Bacteriocins constitute a group of highly attractive substances for the food industry due to their non-toxicity towards human organisms, thermal stability, protein nature and antagonistic effect towards the majority of Gram-positive microorganisms [13,32]. In the present time, the application of bacteriocins produced by LAB is limited in the food industry. Only the lantibiotic nisin (E234) and pediocin PA-1/Ac H are commercialized in the food supply chain as preservative agents [30]. 4. Health-Promoting Values of Products Fermented with LAB Numerous studies indicate that lactic fermentation has a positive effect on the nutritional value and increased digestibility of raw materials subject to the process. The acidic nature of fermentation increases the activity of enzymes produced by specific microorganisms, including amylases, proteases, lipases and phytases, thus modifying the raw material through the hydrolysis of polysaccharides, proteins and fat [33,34]. Through the increasing activity of microbial enzymes, the number of anti-nutritive compounds, such as phytic acid and tannins is reduced. These compounds negatively affect the bioavailability of minerals, including iron, proteins and simple sugars. Moreover, the number of vitamins in the product is also increased due to the fermentation process and the activity of specified microorganisms [1,35]. The health-promoting properties of LAB are based mainly on the increase in the bioavailability of nutrients, antioxidant activity, the biosynthesis of vitamins and the degradation of antinutritional ingredients. The antioxidant activity of LAB is linked to their capability to transform phenolic acids to biologically active forms through the decarboxylation of phenolic acid and the effect of reductases and hydrolases. This capability is of considerable significance in the case of plant material fermentation [36]. In the context of the increasing nutritional value of foods, LAB may increase the content or bioavailability of vitamins. Numerous authors have conducted experiments aiming at testing the effect of LAB on the content of vitamin C. The results thus far are not homogeneous; however, some studies point to a positive effect of LAB on the content of ascorbic acid. Kazimierczak et al. [37] determined that a spontaneously fermented beetroot juice was characterized by higher vitamin C content relative to juice not subject to fermentation. Studies showing reduced vitamin C content during fermentation can be explained by the fact that, with fermentation time, ascorbic oxidase activity may increase due to the fermenting microflora [38]. Sharma et al. [38], in their research, show that the content of vitamin C in the natural fermented Indian beverage Kanji increased during the fermentation process and was stable for the next 40 days of storage, but after that time, the content gradually reduced. LAB and Bifidobacteria have the capacity to transform individual diet components into group B vitamins and vitamin K, where the first group of vitamins plays a fundamental role in the normal function of human organisms. Lactibacillus reuteri, Lactiplantibacillus plantarum (Lactobacillus plantarum), Lactobacillus acidophilus and Bifidobacterium longum deserve special attention in the context of the biosynthesis of group B vitamins [35,36,39]. Vitamin K is well known due to its role in the production of blood clotting proteins. It is associated with the significant role of vitamin K as a cofactor for the formation of y-carboxyglutamic acid (Gla) in proteins, which bind calcium ions and participate in the blood coagulation and calcification of tissue [40]. Vitamin K is a fat-soluble chemical compound, which occurs in two main forms: K1 (phylloquinone) in plants and K2 (menaquinones (MK)) in animals and bacteria. The main source of vitamin K intake is vegetables (80–90% dietary intake), but the absorption is about 5–10%. In comparison, the absorption of vitamin K (MK) from dairy products may achieve almost 100% [41]. The study of Morishita et al. [40] confirms the ability of LAB to produce a meaningful amount of vitamin K and suggests the possibility of usage selected strains as a starter culture for the production of fermented foodstuffs or dietary supplements. Oxidative damage is a global concern because of its negative impact on human health. It is associated with several diseases such as cancer, cirrhosis, inflammatory diseases and atherosclerosis [42]. The antioxidative and anticarcinogenic potential of LAB is a significant subject due to their possible usefulness for preventing cancer diseases. According to the study of Shehata et al. [42] there is correlation between high antioxidant activity and the anticarcinogenic properties of bacterial lysate. The study found that two of the tested strains (Streptococcus thermophilus BLM 58 and Pediococcus acidilactici ATTC 8042) had the strongest antioxidative effect. Various studies show the high anticarcinogenic activity of LAB [43,44]. Pourramezan et al. [45] investigated the anticancer, antioxidant and apoptotic properties of some strains of Lactobacillus isolated from traditional doogh samples. The tested strain Lactobacillus AG12a shows high anticarcinogenic and antioxidative activity in vitro. However, the studies should be tested in vivo in order to validate these findings. Vamanu et al. [46] suggested that including probiotics in a daily diet may decrease the possibility of carcinogenesis of the colon due to the inactivation of carcinogenic compounds, the stimulation of immune system and the reduction in the activity of enzymes in the digestive system, which may contribute to the conversion of procarcinogens into carcinogens. Moreover, certain LAB strains exhibit probiotic properties. In accordance with the WHO (World Health Organization) definition, probiotics are live organisms that, when provided at a specific dose, have a positive effect on the host’s organism. Probiotic microorganisms must also fulfill a range of requirements, i.e., they should be isolated from human organisms, exhibit resistance to difficult conditions of the gastrointestinal tract (low pH, presence of gastric acid) and they must be characterized by high adhesion to the intestinal epithelium and a complete lack of virulence [47]. Probiotic properties should be assigned to a specific strain and not genus or species [48]. Probiotic bacteria exhibit a favorable impact on reducing blood cholesterol levels and its metabolism, and, in addition, through the host organism colonization, they may contribute to reducing the risk of carcinogenesis and the stimulation of the immune system [47]. Probiotics may also play a significant role in gastrologic problems through the inhibition of pathogenic microorganism adhesion to the intestinal epithelium and the synthesis of antibacterial substances, i.e., bacteriocin or organic acids [49]. Furthermore, they participate in the biosynthesis of vitamins, and the metabolites produced by them regulate the homeostasis of the gastrointestinal system [50,51]. Table 2 presents characteristic products obtained as a result of lactic fermentation, listing dominant and collaborating microflora. 5. Use of LAB against Foodborne Bacterial Pathogens Foodborne pathogens occurring in food manufacturing and provoking various diseases related to the consumption of contaminated products constitute a critical point in the food industry. Scientists continue to search for innovative and safe methods of food preservation, including the lactic fermentation process with LAB as a safe method for human health [68]. Many authors demonstrated the inhibiting effect of LAB towards the development of foodborne pathogens, such as Salmonella spp. [69], Listeria monocytogenes [70] and Escherichia coli [71]. During their growth and fermentation process, LAB produce a range of metabolites with antimicrobial effects, the action of which is based on the destabilization of the membrane, the inhibition of the synthesis of cell wall enzymes, the interference of proton gradients and the induction of the formation of reactive oxygen species, thus increasing oxidative stress within the cell [72]. The majority of scientific reports suggest that the action against the pathogenic microflora is mainly based on the formation of conditions difficult for their development due to pH reduction under the lactic acid produced by them at considerable amounts. The remaining organic acids formed as a result of fermentation, i.e., acetic and propionic acid, exhibit antagonistic effects against the development of bacteria, yeasts and filamentous fungi; however, the synthesized amounts of these acids are not significant [73,74]. The pH reduction caused by the presence of organic acid produced by LAB efficiently inhibits the development of Salmonella spp. bacteria, which are intolerant of low pH, and their optimal growth remains in the 4.0–9.0 range [68]. Choi et al. [75] investigated the antagonistic activity of LAB isolated from naturally fermented kimchi against selected pathogenic strains, including E. coli O157:H7, Salmonella typhimurium, Staphylococcus aureus and Salmonella enteritidis. The experiment demonstrated the inhibiting effect of the used strains on the development of pathogens; however, it was not linked to the activity of bacteriocins, hydrogen peroxide or fatty acids. The key compound reducing the quantity of pathogenic microorganisms was lactic acid. These results were confirmed in other studies, which determined that lactic acid is the predominant factor contributing to the inhibition of undesirable microflora. The study of Stanojevic-Nikolic et al. [76] assessed the effect of lactic acid on the development of pathogens. It was demonstrated that lactic acid is more efficient towards Gram-positive than Gram-negative bacteria, and, with the increase in the acid, the efficacy at which the development of pathogenic microflora is inhibited increases. Bacteriocins also contribute to the inhibition of microorganism development. In the study of [77], the efficacy of the action of nisin synthesized by Lactobacillus bulgaricus and Streptococcus pyogenes strains towards pathogens, i.e., Bacillus subtilis, Pseudomonas aeruginosa, Serratia marcescens and Staphylococcus aureus, was assessed. The effect of nisin was more pronounced towards Gram-negative bacteria, which is linked to the structure of their cellular membrane. The study of Scatassa et al. [78] showed that the production of cheese with the use of a mixture of Lacticaseibacillus rhamnosus (Lactobacillus rhamnosus), Lactococcus lactis and Enterococcus faecium may result in the inhibition of Listeria monocytogenes growth through the secretion of bacteriocin-like substances. In another study, Wang et al. [79] observed an inhibiting effect of metabolites produced by LAB on the development of Bacillus licheniformis isolated from milk powder. This experiment indicated that, under controlled pH conditions, Lactiplantbacillus plantarum (Lactobacillus plantarum) had an inhibitory effect on the growth of cells and biofilm production by B. licheniformis. The efficacy of L. plantarum in the inhibition of biofilm formation was confirmed on matrices, i.e., glass and steel. This study is of particular importance for the dairy industry, where efficient methods for the removal of bacterial biofilms are searched for. Salmonella bacteria are capable of adhering and forming biofilms on glass, rubber and metallic surfaces. Biofilms contribute to food spoilage and constitute the critical point in production facilities due to their resistance to cleaning and disinfection. They can be formed on any type of surface, including metal, plastic, wood, glass and stainless steel [80]. Todhanakasem and Ketbumrung, [80] assessed the efficacy of the application of LAB to control the formation of biofilms by Salmonella enterica ssp. enterica and B. cereus, E. coli bacteria. LAB isolated from fermented food turned out to be efficient in inhibiting the proliferation of bacterial pathogen cells and biofilm formation. It is necessary to conduct further research on the efficacy of LAB under in situ conditions and to assess their application in the food chain. 6. Use of LAB against Yeast Traditionally, yeasts are known as the most important microorganisms due their role in the production of bread, alcoholic beverages and dairy products, as well as their role as an ethanol for fuel, extracts and pigments or biochemicals for the pharmaceutical industry. However, yeast contribute to the spoilage of food and beverages. The negative role of yeasts is associated with their ability to grow in low temperatures and pH values as well as their resistance towards physico-chemical stress [81]. The occurrence of unwanted yeast such as Kloeckera apiculata, Brettanomyces bruxellensis, Rhodotorula mucilaginosa, Schizosaccharomyces pombe, Candida krusei, Candida parapsilosis, Debaryomyces hansenii, Pichia membranaefaciens and Zygosaccharomyces bailii may contribute to problems with the quality and safety of products [82]. Yeasts can form undesirable microflora of fermented products and of the production environment. The cause of yeast contamination in the food chain may be the production facility itself due to the inappropriate hygiene system that can favor the biofilm formation on technological surfaces. It is an issue correlated with aerosols and overspray during sanitation. The biofilm formation by some species of yeast may occur as an important issue during food processing due to the significantly more complicated method of removal compared to planktonic cells [82]. The control of yeast is essential in the alcoholic beverages industry. Due to the high cost of substrate, alcoholic fermentation is processed without the previous sterilization of molasses feeding must or sugar cane, which causes the development of wild Saccharomyces cerevisiae strains as well as other yeast contaminants. It is a problem in the alcoholic beverages industry due to low productivity and operational issues. Species like Candida tropicalis, Dekkera bruxellensis or Pichia galeiformis may constitute a main determinant of decreasing the efficiency of alcoholic fermentation [83]. Of particular interest are the genera Candida, Yarrowia and Meyerozyma [84]. Yeasts of the genus Candida are microorganisms naturally inhabiting animal organisms, including the skin and mucous membranes. The infection is caused due to the overgrowth of Candida microflora, particularly in the case of lowered organism immunity or susceptibility to fungal infections [85]. Yarrowia and Meyerozyma yeasts play a significant role in the food supply chain as undesirable microflora contributing to the reduced organoleptic and microbiological quality of silage. Numerous authors have attributed the capability to neutralize or inhibit the development of pathogenic yeasts to LAB. The study of Coton et al. [86] assessed the capabilities of selected strains of Leuconostoc, Lactobacillus and Propionibacterium bacteria to inhibit yeast growth. It was demonstrated that the genus Lactobacillus was characterized by higher antimicrobial activity towards selected strains than Lactococcus. It was noted that Yarrowia and Galactomyces geotrichum yeasts exhibit the highest resistance towards the activity of LAB. According to the study of Yepez et al. [87], Lactiplantibacillus plantarum M5MA1(Lactobacillus plantarum M5MA1) turned out to be the most efficient strain, exhibiting antagonistic effects against i.a. Meyerozyma guilliermondii. This strain was described as a potential candidate posing an alternative for chemical preservatives. Bacteriocins also play a significant role in inhibiting the development of pathogenic yeasts. An example can be acidophilin, produced by Lactobacillus bulgaricus strain, exhibiting an efficient impact on Candida albicans [85]. 7. Use of LAB against Filamentous Fungi Filamentous fungi pose a serious problem in both the food industry and agriculture in general. They cause the contamination of food, feeds and crop diseases, contributing to serious economic loss [88]. Moreover, they are capable of the biosynthesis of toxic secondary metabolites, commonly known as mycotoxins. Some of them have proven to have a carcinogenic (fumonisin B1, aflatoxin B1, ochratoxin A), mutagenic (aflatoxins, fumonisins, ochratoxin A, toxin T-2), teratogenic (patulin, aflatoxin B1, ochratoxin A), estrogenic (zearalenone), nephrotoxic and hepatotoxic (aflatoxins, patulin) effect [89]. Numerous authors have been able to provide evidence for filamentous fungi development inhibition in fermented food as a result of the effect of LAB activity [90,91]. The mechanism of LAB activity against the development of filamentous fungi is mainly based on the action of their metabolites, which contribute to the deteriorated integrity of the cell membrane and the absorption of amino acids by fungi [92]. In the study of Yepez et al. [85], it was determined that isolated LAB strains originating from traditionally fermented vegetables (tocosh, chicha) exhibited efficacy in the inhibition of toxicogenic and non-toxicogenic strains of filamentous fungi of genera Aspergillus, Fusarium and Penicillium. Sadeghi et al. [93] assessed the antimicrobial activity of Pediococcus pentosaceus strain isolated from barley sourdough starter. Statistically significant efficiency of its action towards Aspergillus niger and Aspergillus flavus strains was demonstrated. The majority of literature data on the capability of selected LAB strains for the inhibition of filamentous fungi growth present in vitro tests with the use of de Man, Rogosa and Sharpe (MRS) agar medium, which is selective for these bacteria. The composition of the medium is highly favorable for the development of LAB, and it probably induces their strong antimicrobial properties against filamentous fungi. However, it is often the case that, in in situ tests, the antimicrobial activity of LAB decreases or ceases completely [94]. Le Lay et al. [95] compared the activity of LAB and Propionibacterium under in vitro conditions (MRS agar medium) and in situ conditions (bakers’ wares). A marked difference in the antimicrobial activity of LAB and Propionibacterium in in vitro and in situ tests was observed. Under in situ conditions, only 12 (2 Propionibacterium) out of 69 strains exhibited antimicrobial activity towards filamentous fungi. In comparison, under in vitro conditions, out of 320 strains used, 103 showed high antimicrobial activity (53 out of 270 LAB strains; 49 out of 50 Propionibacterium strains). Table 3 presents examples of applications of specific LAB strains limiting the development of filamentous fungi and yeasts. 8. Use of LAB against Mycotoxins The main source for mycotoxins is cereals and their products, but they can also be found in vegetables and fruit [108,109]. Their presence has been confirmed in products from animals fed with contaminated feed, such as milk or meat [109]. Many attempts have been made to either eliminate or reduce the level of contamination of crops with mycotoxins with physical (thermal processes) and chemical methods (acids, bases, oxidative and reducing compounds) [110]. However, such methods are associated with the risk of deteriorated health safety and reduced nutritional value. That is why, in recent years, scientists have turned to the possibility of using antagonistic microorganisms to detoxify cereals and yeasts. Numerous authors point to a high efficiency of LAB in neutralizing mycotoxins from the matrix, from small amounts to even their complete removal [111,112,113,114]. The mechanisms of detoxification are mainly based on biotransformation, biobsorption and bioadhesion [102]. Biotransformation aims primarily at the transformation of the given substance to its non-toxic or less toxic variant by means of changes occurring during the fermentation process and the activity of microorganisms and their metabolites [115]. Biabsorption is a technique utilizing the capabilities of selected microorganisms to absorb toxins to the inside of the cell. Unfortunately, the process is often reversible; thus, it has limited possibilities of being applied in the food industry. Bioadhesion consists in binding mycotoxins with the cell wall of the inactivated microorganisms [115]. A high concentration of mycotoxins in food has a negative impact on the capacity of antagonistic microflora for efficient action, which results in a prolonged time of adaptation to difficult conditions [116]. Fermentation also contributes to the reduced concentration of mycotoxins in raw material, which is directly linked to the presence of microorganisms involved in the process. An example here can be the reduction of Aflatoxin M1 in milk subject to fermentation during kefir or yogurt production [117,118]. The process of detoxification by lactic strains is highly rapid because the concentration of mycotoxins is reduced severalfold in the first 24 h of contact between the bacteria and the toxin. Extending the process does not appear to affect the increased efficiency of densification, and it even may contribute to the re-release of the substances to the environment, which is linked to the reversibility of the binding process [119]. The rate at which toxins are neutralized by LAB is also strictly linked to the growth conditions, including pH, cell concentration and the presence of nutrients and compounds inhibiting the growth of LAB [119]. The study of Zhou et al. [120] suggests the possibility of the degradation of mycotoxins by the substances released by LAB to their environment. In the study of Król et al. [121], the possibility of zearalenone neutralization by the selected LAB strains Lactococcus lactis and Bifidobacterium was considered, and the study focused on the antagonistic mode of action of these strains towards filamentous fungi. It was observed that toxin biosorption by L. lactis can be divided into two stages. The first one is characterized by a rapid decrease in zearalenone concentration by almost 90% in the sample, whereas in the second stage, the process slowed down and only 7% was bound. The neutralization of zearalenone by Bifidobacterium also takes place in two stages and is characterized by a similar course as in L. lactis. Fuchs et al. [23] tested the possibility of the detoxification of patulin and ochratoxin A with LAB. In the case of patulin, the best effect was obtained with a Bifidobacterium animalis strain that reduced the amount of toxin present in the sample by 80%. The highest efficiency towards ochratoxin A (97%) was demonstrated by a Lactobacillus acidophilus strain. On the other hand, Zheng et al. [122] used, in their study, a Lacticaseibacillus casei (Lactobacillus casei) strain to test the optimum conditions for patulin neutralization. The results confirmed the very good capabilities of L. casei to eliminate the toxin from the environment, and they also demonstrated that the temperature of 30 °C and pH of 5.0 are most favorable for the process. In addition, it was determined that, in the case of patulin, live cells exhibit a considerably higher efficiency in neutralizing patulin as compared with thermally inactivated cells. Therefore, it can be concluded that the mechanism of toxin removal is not only linked to the temperature or pH of the environment but also to the type of mycotoxin being neutralized. Numerous studies show that LAB can inactivate aflatoxins [123,124], zearalenone [125,126], deoxynivalenol [125,127] and fumonisins [128]. Niderkorn et al. [125] tested the possibility of LAB to bind mycotoxins biosynthesized by Fusarium fungi. Fumonisin B2 was most efficiently removed from the environment, followed by zearalenone, deoxynivalenol and fumonisin B1. The study of Cvek et al. [129] utilized Lactiplantibacillus plantarum (Lactobacillus plantarum) and Lacticaseibacillus rhamnosus (Lactobacillus rhamnosus) to neutralize zearalenone under in vitro conditions. The study demonstrated the capability of these strains for the adhesion of the mycotoxin to the cell wall at 37 °C within 72 h. It was observed that the higher the bacterial cell concentration, the higher the efficiency of the process. Within the first hours of incubation, 95–97% of zearalenone was bound to the cell wall of the bacteria; yet, during the subsequent hours, the percentage was reduced due to the re-release of the toxin back to the environment, which confirms that the adhesion process is reversible with time. In the case of fumonisins, numerous reports suggested that the neutralization of these toxins by lactic strains occurs mainly through adhesion, and the process intensity is strictly linked to the species’ cell wall structure [130,131,132]. Similarly, aflatoxin binding by LAB can be directly linked to the occurrence of peptidoglycans and polysaccharide in the cell wall. Thus, future research should be focused on the assessment of differences in the structure of cell walls between LAB species in order to select the most appropriate strain to remove the specific mycotoxin from the environment [133,134]. 9. Conclusions Biopreservation may determine the biological alternative for chemical and physical methods of food preservation, which are generally considered as negative for the quality of the product and, in some cases, negative for health. Biopreservation based on the use of LAB and their metabolites may be associated with an increase in food safety as well as other benefits for human health, considering their ability to improve nutritional value by producing some vitamins, organic acids and other compounds. LAB show antibacterial and antifungal activity. However, there is a necessity to investigate the activity of LAB against foodborne pathogens in situ to establish the most effective method of application in the food model. To achieve this aim, there is a need to understand the influence of environmental factors such as pH, temperature, food matrices and the presence of various interfering substances on the survival of some strains of LAB and their activity. In addition, LAB may detoxify second metabolites of filamentous fungi using different mechanisms, including bioabsorption, biotransformation and bioadhesion. Most data suggest that the main mechanism of mycotoxin reduction is a binding to the cell wall, but the ability of bacteriocins production as well as other metabolites should be considered as an efficient factor in mycotoxin’s neutralization process. Taking into account how serious of a problem mycotoxins are in the food chain, biological methods of degradation by lactic acid bacteria and their metabolites (bacteriocins) should be better known through future studies. Author Contributions Conceptualization, A.Z. and B.S.; investigation, A.Z. and B.S.; resources, A.Z., B.S. and M.B.; writing—original draft preparation, A.Z.; writing—review and editing, B.S. and M.B.; visualization, A.Z., B.S. and M.B.; supervision, A.Z., B.S. and M.B. 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. foods-11-01283-t001_Table 1 Table 1 The most used chemical preservatives and examples of their negative health impact. Chemical Food Preservatives Type of Food Negative Effects References Sulphur dioxide (E220) Dried fruits, juices Asthma episodes, diarrhea, nausea and other gastric effects, loss of vitamin B1 [9,10,11] Potassium nitrate (E249) Cured and canned meat products May cause lower oxygen carrying capacity of blood [9,10] Sodium benzoate (E211) Pickles, sauces Suspected neurotoxicity and cancerogenic properties, aggressive asthma episodes [9,10] Calcium benzoate (E213) Cereals, meat products, low sugar products Inhibition of digestive enzyme function [9,10] Benzoic acid (E210) Pickles, sauces, meat products Possible allergic reaction [9,11] Sorbic acid (E200) Beverages, cheese, pickles, fish and meat products Possible allergic reaction [9,11] foods-11-01283-t002_Table 2 Table 2 Characteristic products obtained through lactic fermentation, listing dominant and collaborating microflora. Fermented Foods Main Ingredients Dominant Microflora Collaborators Country References Kefir Milk Lactobacillus, Lactococcus, Leuconostoc, Oenococcus, Pediococcus, Streptococcus Acetic acid bacteria, yeast International [52,53,54] Yogurt Milk Streptococcus thermophilus, Lactobacillus bulgaricus - International [53,55,56] Cheese Milk Lactobacillus lactis, Streptococccus thermophilus, Lactobacillus shermanii, Lactobacillus bulgaricus, Propionibacterium shermanii Molds (Penicillium) International [55,56,57,58] Kimchi Cabbage, radish, salt Lactobacillus, Leuconostoc, Pediococcus, Weissella Yeast Korea [54,58,59,60] Sourdough Flour, water Enterococcus, Lactobacillus, Lactococcus, Leuconostoc, Pediococcus, Streptococcus, Weissella Yeast International [54,58,61] Cucumbers Cucumbers, garlic, salt Enterobacter, Leuconostoc mesenteroides, Levilactobacillus brevis (Lactobacillus brevis), Lactiplantibacillus plantarum (Lactobasillus plantarum) - International [62,63] Villi Milk Lactococcus lactis subsp. cremoris, Lactococcus lactis subsp. lactis, Leuconostoc mesenteries Geotrichum candidum Nordic countries [64,65] Sauerkraut Cabbage, salt Leuconostoc mesenteroides, Lactococcus lactis, Levilactobacillus brevis (Lactobacillus brevis), Lactiplantibacillus plantarum (Lactobacillus plantarum), Lactobacillus pentoaceticus - International [58,66,67] foods-11-01283-t003_Table 3 Table 3 The antagonistic activity of selected LAB strains against yeasts and filamentous fungi in selected fermented products. Our own elaboration on the basis of Salas et al. [94]. LAB Strains Food Field Source of LAB Method of Application Inhibited Microorganism References Lactobacillus harbinensis K.V9.3.1Np, Lacticaseibacillus rhamnosus K.C8.3.1I (Lactobacillus rhamnosus K.C8.3.1I), and Lacticaseibacillus paracasei K.C8.3.1Hc1 (Lactobacillus paracasei K.C8.3.1Hcl) yogurt cow and goat milk cells as adjunct culture Debaryomyces hansenii, Kluyveromyces lactis, Kluyveromyces marxianus, Penicillium brevicompactum, Rhodotorula mucilaginosa, and Yarrowia lipolytica [96] Lacticaseibacillus casei AST18 (Lactobacillus casei AST18) yogurt chinese dairy products cells as adjunct culture Penicillium sp. [97] Lactobacillus amylovorus DSM 19280 cheddar cheese cereal environment cells as adjunct culture Penicillium expansum and environmental molds [98] 12 strains of Lactiplantibacillus plantarum (Lactobacillus plantarum) cottage cheese fresh herbs, fruits, and vegetables cells as added to the finished product Penicillium commune [99] Lacticaseibacillus paracasei DCS302 (Lactobacillus paracasei DCS302) yogurt no data cells as adjunct culture Penicillium sp. nov. DCS 1541, Penicillium solitum [100] Lactobacillus harbinensis K.V9.3.1Np yogurt cow milk cells as adjunct culture Yarrowia lipolytica [96] L. rhamnosus A238, L. rhamnosus A119 (2/5) The association of L. rhamnosus A238 with B. animalis subsp. lactis A026, and L. rhamnosus A119 with B. animalis subsp. lactis A026 cottage cheese no data cells added to the finished product Penicillium chrysogenum [101] Lactobacillus amylovorus DSM19280 sourdough quinoa bread cereal isolate cells in sourdough environmental molds [102] Lactiplantibacillus plantarum CRL778 (Lactobacillus plantarum CRL778) wheat bread homemade wheat dough SL778: fermentate as ingredient environmental molds [103] Lactobacillus amylovorus DSM19280 sourdough wheat bread cereal isolate cells as starter Fusarium culmorum [102] Lactiplantibacillus plantarum (Lactobacillus plantarum) UFG 121 (only 1 in situ from best 2/88 in vitro) oat-based product food cells in sourdough Fusarium culmorum (only 1 tested in situ), Penicillium chrysogenum, Penicillium expansum, Penicillium roqueforti, and Aspergillus flavus (5/7 in vitro) [104] Lactobacillus bulgaricus CECT 4005, L. plantarum CECT 749 (active in situ 2/6), Lactobacillus johnsonii CECT 289, L. rhamnosus CECT 288, L. ruminis CECT 1324 and Bifidobacterium bifidum CECT 870T (6 active in vitro/16) bread no data cells in sourdough Aspergillus parasiticus (only one tested in situ) and Penicillium expansum [88] L. delbrueckii group, L. alimentarius group, L. plantarum group, L. casei group, L. buchneri group, L. perolens group, L. sakei group, L. fructivorans group, L. reuteri group, L. brevis group L. rossiae, Leuconostoc spp., Pediococcus spp., Carnobacterium spp., Weissella spp., L. lactis subsp. Lactis, Propionibacterium spp. cakes and milk bread rolls bread roll sourdough sprayed on the Surface of product Species of Aspergillus, Penicillium, Cladosporium, Wallemia, Eurotium [95] Lactobacillus helveticus KLDS 1.8701 fermented soybean milk dairy products cells as adjunct culture Penicillium sp. [105] Lactiplantibacillus plantarum TK9 (Lactobacillus plantarum TK9) citrus, apples and yogurt chinese naturally fermented congee cells Penicillium roqueforti, Penicillium citrinum, Penicillium oxalicum, Aspergillus fumigatus, Aspergillus flavus and Rhizopus nigricans [106] Environmental molds–microorganisms that may occur indoors and outdoors as natural environments, including genera Alternaria, Cladosporium, Botrytis, Epicoccum, Asperigillus, Rhizopus, Mucor and Penicillium [107]. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Admassie M. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094813 ijms-23-04813 Article Nanoencapsulation of Gla-Rich Protein (GRP) as a Novel Approach to Target Inflammation Viegas Carla S. B. 12 Araújo Nuna 1 https://orcid.org/0000-0003-3048-8820 Carreira Joana 1 https://orcid.org/0000-0002-6447-0242 Pontes Jorge F. 1 https://orcid.org/0000-0002-2613-4838 Macedo Anjos L. 3 Vinhas Maurícia 4 Moreira Ana S. 56 Faria Tiago Q. 56 https://orcid.org/0000-0002-2136-1396 Grenha Ana 1 de Matos António A. 7 https://orcid.org/0000-0001-7867-6957 Schurgers Leon 8 Vermeer Cees 9 https://orcid.org/0000-0002-5145-4753 Simes Dina C. 12* Couvineau Alain Academic Editor 1 Centre of Marine Sciences (CCMAR), Universidade do Algarve, 8005-139 Faro, Portugal; caviegas@ualg.pt (C.S.B.V.); nuna_araujo@hotmail.com (N.A.); jscarreira@ualg.pt (J.C.); pontes.jorge21@gmail.com (J.F.P.); amgrenha@ualg.pt (A.G.) 2 GenoGla Diagnostics, Centre of Marine Sciences (CCMAR), Universidade do Algarve, 8005-139 Faro, Portugal 3 UCIBIO—Applied Molecular Biosciences Unit, Departamento de Química, and Associate Laboratory i4HB—Institute for Health and Bioeconomy, NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal; anjos.macedo@fct.unl.pt 4 Algarve Biomedical Center Research Institute (ABC-RI), Universidade do Algarve, 8005-139 Faro, Portugal; mmvinhas@ualg.pt 5 iBET—Instituto de Biologia Experimental e Tecnológica, 2780-157 Oeiras, Portugal; amoreira@ibet.pt (A.S.M.); tfaria@ibet.pt (T.Q.F.) 6 ITQB—Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2780-157 Oeiras, Portugal 7 Centro de Investigação Interdisciplinar Egas Moniz, Egas Moniz-Cooperativa de Ensino Superior CRL, 2829-511 Caparica, Portugal; apamatos@gmail.com 8 Department of Biochemistry, Cardiovascular Research Institute, Maastricht University, 6229 HX Maastricht, The Netherlands; l.schurgers@maastrichtuniversity.nl 9 Cardiovscular Research Institute CARIM, Maastricht University, 6229 HX Maastricht, The Netherlands; cees.vermeer@outlook.com * Correspondence: dsimes@ualg.pt; Tel.: +351-289-800100 27 4 2022 5 2022 23 9 481305 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/). Chronic inflammation is a major driver of chronic inflammatory diseases (CIDs), with a tremendous impact worldwide. Besides its function as a pathological calcification inhibitor, vitamin K-dependent protein Gla-rich protein (GRP) was shown to act as an anti-inflammatory agent independently of its gamma-carboxylation status. Although GRP’s therapeutic potential has been highlighted, its low solubility at physiological pH still constitutes a major challenge for its biomedical application. In this work, we produced fluorescein-labeled chitosan-tripolyphosphate nanoparticles containing non-carboxylated GRP (ucGRP) (FCNG) via ionotropic gelation, increasing its bioavailability, stability, and anti-inflammatory potential. The results indicate the nanosized nature of FCNG with PDI and a zeta potential suitable for biomedical applications. FCNG’s anti-inflammatory activity was studied in macrophage-differentiated THP1 cells, and in primary vascular smooth muscle cells and chondrocytes, inflamed with LPS, TNFα and IL-1β, respectively. In all these in vitro human cell systems, FCNG treatments resulted in increased intra and extracellular GRP levels, and decreased pro-inflammatory responses of target cells, by decreasing pro-inflammatory cytokines and inflammation mediators. These results suggest the retained anti-inflammatory bioactivity of ucGRP in FCNG, strengthening the potential use of ucGRP as an anti-inflammatory agent with a wide spectrum of application, and opening up perspectives for its therapeutic application in CIDs. nanoparticles Gla-rich protein (GRP) chronic inflammatory diseases (CIDs) inflammation vitamin K-dependent protein (VKDP) Portuguese National Funds from FCT—Foundation for Science and TechnologyDL57/2016/CP1361/CT0006 EXPL/BTM-TEC/0990/2021 UIDB/04326/2020 UIDP/04326/2020 LA/P/0101/2020 Research Unit on Applied Molecular Biosciences—UCIBIOUIDP/04378/2020 UIDB/04378/2020 Associate Laboratory Institute for Health and Bioeconomy—i4HBLA/P/0140/2020 NUTRISAFE41/ALG/2020 072583 Portuguese Science and Technology Foundation (FCT)SFRH/BD/111824/2015 PD/BD/137064/2018 This research was funded by Portuguese National Funds from FCT—Foundation for Science and Technology, through the transitional provision DL57/2016/CP1361/CT0006, projects EXPL/BTM-TEC/0990/2021, UIDB/04326/2020, UIDP/04326/2020 and LA/P/0101/2020; through UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences—UCIBIO, LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy—i4HB, and by AAC nº 41/ALG/2020—Project nº 072583—NUTRISAFE. Nuna Araújo is the recipient of the Portuguese Science and Technology Foundation (FCT) fellowship SFRH/BD/111824/2015. Jorge F. Pontes is the recipient of the Portuguese Science and Technology Foundation (FCT) fellowship PD/BD/137064/2018. ==== Body pmc1. Introduction Chronic inflammatory diseases (CIDs) are the most significant cause of death, with worldwide growing incidence, and are ranked as the greatest threat to human health by the WHO [1,2]. Amongst the wide spectrum of CIDs, cardiovascular diseases (CVD), chronic kidney disease (CKD), arthritis, osteoarthritis (OA), diabetes, neurodegenerative disorders and cancer are the leading causes of death and disability globally [1,2]. Inflammation, either under the conditions of a persistent low-grade inflammatory state implicated on the initiation, progression and outcomes in most CIDs, or as severe and acute pro-inflammatory reactions leading to multiorgan dysfunction, is a crucial event in this wide spectrum of complex diseases [1,2,3]. The lack of effective treatment leads to the wide consumption of anti-inflammatory drugs as the only option to lower inflammation and alleviate symptoms [2,3,4]. However, despite the wide availability of anti-inflammatory drugs, there is an urgent need for novel, safe and more efficient therapeutics to prevent and treat inflammation [4]. Moreover, in calcification-related CIDs such as atherosclerosis, CVD and OA, inflammation and pathological calcification are considered disease drivers, functioning in a positive feedback loop, influencing disease progression and outcomes [5,6]. In fact, there are common pathological processes involved in many of these diseases, such as dysregulated inflammatory pathways, pathological calcification and aberrant extracellular matrix (ECM) remodeling. The discovery of new drugs will enable us to improve one or all of these pathological processes, and could significantly contribute to developing or improving treatment options for some of these global health burdens. Gla-rich protein (GRP), also known as upper zone of growth plate and cartilage matrix associated protein (UCMA) [7,8], is a circulating vitamin K-dependent protein (VKDP) shown to execute important functions in multiple processes associated with the development of CIDs, such as CVD, osteoarthritis, rheumatoid arthritis, and CKD [9,10,11,12,13,14], and has recently been proposed as a biomarker for vascular and valvular calcification (VC) and kidney dysfunction [15,16]. GRP is a potent inhibitor of pathological calcification, at the tissue and systemic levels, and is a protector of ECM degradation, with anti-inflammatory properties in monocytes, macrophages, chondrocytes and synoviocytes [5,9,10,11,14]. While GRP γ-carboxylation is crucial for its role as a calcification inhibitor, its anti-inflammatory activity has been shown to be independent of its γ-carboxylation status [5,9,10,11,14]. Importantly, increased GRP levels have been associated with tissue-beneficial effects, while GRP deficiency has been linked to disease states [7,8,9,10,11,12,13,14,15,16]. Its ability to act locally and systemically, with an exogenous and endogenous functional role, gives GRP promising and novel therapeutic properties. However, GRP’s limited solubility at physiological pH is a major challenge for its application in the biomedical field. In this context, nanotechnology, and in particular nanoparticles (NP), have been proposed as valuable vehicles for efficient drug transport by protecting the bioactive elements from degradation, thus increasing their bioavailability, efficacy, specificity, uptake and targeting ability [17]. Among the many matrixes and methodologies currently available to produce nanoparticles (NPs), chitosan (CS)-based NPs have become one of the most popular nanocarriers for a variety of drugs, such as proteins, peptides, nucleic acids and other bioactives [18,19,20,21,22,23,24]. This is mainly due to CS’s favorable biological properties, such as biodegradability, biocompatibility and low toxicity, as well as its bactericidal, fungicidal, anticancer and immunomodulatory properties [18,19,20]. Additionally, CS has mucoadhesive properties and promotes macromolecules’ permeation through epithelia, which is key for drug delivery purposes [21,25,26]. CS/tripolyphosphate (CS/TPP) NPs produced by ionotropic gelation are amongst the most widely studied CS/NPs, and have been suggested to be suitable for many biological applications, due to their mild and aqueous processing conditions, which include non-toxic reagents and low energy requirements [20,23,24,26,27,28]. In this work, we developed a new nanoparticle formulation containing non-carboxylated GRP (ucGRP), which comprises fluorescein-labeled CS/TPP nanoparticles produced by ionotropic gelation, and tested its anti-inflammatory properties in macrophage-differentiated THP1 (THP1-MoM), in human primary chondrocytes and VSMCs, as relevant cell systems involved in such CIDs as osteoarthritis and CVD. 2. Results 2.1. Characterization of Fluorescein-Labeled Chitosan (FC)- Tripolyphosphate GRP Nanoparticles (FCNG) Fluorescein-labeled chitosan (FC) was obtained by chemical addition of the fluorescein carboxylic acid groups to the primary amine groups of the D-glucosamine residues of chitosan, mediated by 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDAC), yielding 84.5% FC. Nanoparticles with and without GRP (FCNG and FCNP, respectively) were prepared by ionic gelation, following a previously described methodology [29,30]. The characterization of FCNP and FCNG was performed by nanoparticle tracking analysis (NTA) and dynamic light scattering (DLS) (Table 1). Considering the relative amounts of particles by size distribution, NTA analysis demonstrated the presence of 100% of both FCNP and FCNG between 0 and 400 nm, and contents of 92.8 ± 9.3% and 90 ± 4.7% 200 nm for FCNP and FCNG, respectively (Figure 1A). These distributions were found to be mainly unimodal for FCNP and FCNG, highlighting a major population with a peak of 88 ± 24 nm for FCNP and of 107 ± 34 nm for FCNG, although the former presented a slightly broader distribution (Figure 1A). Total particle concentration determined by NTA was found to be constant between FCNP ((8.8 ± 3.6) × 109 particles/mL) and FCNG ((14.5 ± 3.4) × 109 particles/mL), without statistically significant differences. DLS analysis revealed a mean particle size of 130 ± 45 nm for FCNP and 155 ± 38 nm for FCNG, which is consistent with the NTA determinations, with a polydispersity index (PDI) of 0.33 ± 0.07 and 0.39 ± 0.06, respectively (Table 1). The zeta potential was positive for both FCNP and FCNG, and slightly decreased from FCNP, at 37 ± 2 mV, to FCNG, at 28 ± 7 mV (Table 1). All parameters were non-statistically different between FCNP and FCNG. The association efficiency (AE) of the GRP in FCNGs was calculated based on the quantification by ELISA of the GRP present in the supernatant after FCNGs synthesis, representing the fraction of GRP not encapsulated (Figure 1B), relative to the quantity of protein initially used. The results show a high degree of GRP encapsulation with an association efficiency (AE) of 99.8 ± 0.07 (Table 1), indicating effective GRP incorporation. Ultrastructural analyses of FCNP (Figure 1C) and FCNG (Figure 1D), by transmission electron microscopy (TEM), have revealed small nanoparticles with spherical morphologies, primarily varying from 100 to 250 nm in both FCNP and FCNG. 2.2. GRP Release Profile from FCNG In order to explore the stability of FCNG for further use in cell culture functional assays and future potential therapeutic applications, the rate of GRP release from FCNG in cell culture media was assessed over time. For this, FCNG was resuspended and maintained in conditions mimicking the physiological environment of the THP-1 cell culture for different time periods. Under these conditions, the release rate of GRP from FCNG, determined through GRP quantification by ELISA, was fairly constant through time, with 10–15% release after 48 h of FCNG suspension (Figure 2). 2.3. Anti-Inflammatory Effect of FCNG in THP-1 MoM Cells Is Mediated by Increased Intracellular and Extracellular GRP Levels and Downregulation of Pro-Inflammatory Mediators The functionality of FCNG on the modulation of in vitro inflammatory responses was evaluated in LPS-stimulated THP-1 MoM cells pre-treated with FCNP and FCNG for different times, followed by 24 h LPS stimulation. LPS was selected as the THP-1 MoM inflammatory stimulus, since it has been shown to induce not only a strong pro-inflammatory reaction, but also a low-grade inflammatory condition associated with several CIDs, opening the range of potential FCNG applications [29]. The anti-inflammatory effect was analyzed by measuring the levels of TNFα released into the cell culture media. The results show decreased TNFα levels in FCNG-treated cells at all durations tested, with the highest effect at 8 h that lasted until 24 h of pre-treatment (Figure 3A). An anti-inflammatory effect of the FCNP was also observed, although this was restricted to the 2 h of nanoparticle pre-treatment, at the inflammation peak response (Figure 3A). Cell proliferation assays have demonstrated that FCNP and FCNG application at the concentrations used in this study did not affect THP-1 MoM cell viability (Figure 3B). To evaluate the THP-1 MoM binding/uptake of FCNP and FCNG, flow cytometry studies were performed after 2 h of treatments with nanoparticles. A triple-stained system was designed and optimized to simultaneously detect the fluorescein-based nanoparticles through FITC, GRP was detected through ALEXA647, and PE was used for the extracellular CD11b membrane labeling. The results show two conjoint positive signals for the presence of fluorescein (FITC) and cell membrane labeling (PE), demonstrating that 67.1% of the cells exposed to FCNP (Figure 4A), and 73.7% of the cells exposed to FCNG (Figure 4B), were positive for fluorescein-labeled NPs. The presence of FCNG was further confirmed by the high-intensity fluorescence of the three different fluorophores, corresponding to fluorescein (FITC), cell membrane labeling (PE) and GRP (ALEXA 647), demonstrating that 73.3% of the FCNG are present in the THP1- MoM cells (Figure 4C), and confirming the presence of ucGRP in this formulation. In addition, intracellular and extracellular GRP levels were determined in THP1-MoM cell extracts and conditioned media from cells pre-treated with FCNP and FCNG for 24 h, followed by 24 h LPS stimulation. The results show increased intracellular GRP levels with LPS treatment (Figure 4D), consistent with previous results showing a GRP upregulation during inflammation [5]. Treatments with FCNP have no effect on intracellular GRP protein levels, while treatments with FCNG result in a strong increase in intracellular GRP (Figure 4D). GRP quantification in the cell culture media showed high levels of extracellular GRP in THP1-MoM cells treated with FCNG (Figure 4E). Interestingly, gene expression analysis revealed that FCNG treatments induce a strong downregulation of GRP gene expression (Figure 4F). These results strongly indicate that the overall increase in levels of GRP in THP1-MoM cells treated with FCNG results from the exogenously added GRP nanoparticles, and that the anti-inflammatory effect of FCNG is mediated not only by increased extracellular GRP levels, but also by the increased intracellular GRP levels most probably resulting from FCNG uptake by THP1-MoM cells. In addition to the effect of decreasing TNFα levels (Figure 3A), the gene expression analysis of THP1-MoM cells treated with FCNP and FCNG for 24 h, followed by 24 h LPS stimulation, revealed that both FCNP and FCNG are able to downregulate IL-1β, IL-6, and NFkB gene expression, although the effect is stronger with FCNG treatment (Figure 5A–C). Western blot analysis has shown a significant decrease in NFkB protein levels in THP1-MoM cells treated with FCNG (Figure 5D,E). These results reinforce the anti-inflammatory activity of FCNG, which is mediated by decreased levels of pro-inflammatory cytokines and the NFkB that is well-known as a key player in signaling pro-inflammatory reactions. 2.4. Anti-Inflammatory Potential of FCNG in Human Primary Vascular Smooth Muscle Cells (VSMCs) Since GRP has been shown to be involved in the downregulation of pro-inflammatory mediators in VSMCs during the calcification induced by calciprotein particles (CPPs) isolated from CKD stage 5 patients [11], the effect of FCNG in the inflammatory response of VSMCs stimulated with TNFα was evaluated. This selection of TNFα as the inflammatory stimulus to VSMCs was based on its suggested pivotal role in vascular dysfunction, contributing to the pathogenesis of many CVDs, and its capacity to promote vascular calcification in vitro [30,31]. VSMCs pre-treated for 24 h with both FCNP and FCNG followed by 24 h of TNFα stimulation showed decreased levels of IL-6 relative to cells treated only with TNFα, but this was clearly more significant with FCNG (Figure 6A). Similarly, gene expression analysis demonstrated a more significant downregulation of IL-1β and IL-8 in VSMCs pre-treated with FCNG relative to FCNP (Figure 6B,C). VSMCs inflammation induced by TNFα results in increased GRP gene expression, while pre-treatments with both FCNP and FCNG induced GRP downregulation (Figure 6D). Increased intracellular GRP accumulation is also observed with TNFα treatments, although higher levels of intracellular and extracellular GRP protein are achieved with FCNG treatments (Figure 6E,F). Intra- and extracellular GRP protein levels were not affected by FCNP treatments (Figure 6E,F). GRP upregulation and increased endogenous protein levels, concomitant with increased levels of pro-inflammatory cytokines, suggest the involvement of endogenous GRP in the inflammatory response of VSMCs. GRP downregulation together, with increased intra- and extracellular protein levels following FCNG treatments, strongly indicate FCNG as the exogenous GRP source. Overall, these results further confirm the anti-inflammatory activity of FCNG, thus widening the potential therapeutical application of FCNG in cardiovascular disease-related inflammation. Cell proliferation assays have demonstrated that applying FCNP and FCNG at the concentrations used in this study did not affect the VSMCs’ viability (Figure 6G). 2.5. Anti-Inflammatory Potential of FCNG in Human Primary Articular Chondrocytes The anti-inflammatory activity of FCNG was also tested in human primary chondrocytes pre-treated with FCNG and FCNP for 24 h, followed by 24 h of IL-1β stimulation. IL-1β was selected as the chondrocyte inflammation stimulus since it has been shown to be a highly potent inducer of cartilage degradation, and suggested as an important mediator involved in the pathogenesis of OA [32]. The levels of IL6 released into the cell culture media were used to evaluate the inflammatory response. In chondrocytes, both FCNP and FCNG were able to decrease IL6 levels, although the effect was more significant with the FCNG treatments (Figure 7A). Cell proliferation assays demonstrated that FCNP and FCNG at the concentrations used in this study did not affect articular chondrocytes viability (Figure 7B). These results indicate an anti-inflammatory functional activity of FCNG in chondrocytes, opening up the way for its future therapeutic applications in articular-associated inflammatory diseases, such as OA. 3. Discussion In this study, we developed a novel ucGRP nanoparticle formulation (FCNG), using the well-described drug delivery system of CS-TPP nanoparticles. We show that FCNG is not cytotoxic, and functions as an anti-inflammatory agent in human macrophage-derived THP1 cells, primary VSMCs and articular chondrocytes. FCNG’s anti-inflammatory action was observed with the different pro-inflammatory agents used to induce inflammation, particularly LPS in THP-1 MoM, TNFα in VSMCs, and IL-1β in articular chondrocytes, representing the relevant tissue-associated inflammatory stimuli involved in a wide spectrum of CIDs [29,30,31,32]. Although we cannot infer at this point FCNG’s mechanism of action in these different cell-specific inflammatory-stimulated conditions, the overall outcome of decreasing pro-inflammatory mediators open up new perspectives for the therapeutic application of FCNG in several CIDs. Although the beneficial effects of ucGRP have been described at multiple levels, its potential use as a therapeutic agent is hindered by its low solubility at physiological pH. Our strategy to overcome this is based on the nanoencapsulation of ucGRP using CS-TPP nanoparticles, taking advantage of the widely reported biological properties of CS, combined with well-described procedures for CS-TPP nanoparticle production and protein encapsulation [19,20,21,23,24]. In fact, not only are chitosan-based nanoparticles among the most intensively studied nanosystems for drug delivery in biomedical applications, but CS-TPP nanoparticles have also been widely described as being capable of incorporating and releasing a variety of drugs, such as proteins, peptides, vitamins, and other bioactive compounds [20,22,23,24,28,33,34,35,36]. Importantly, CS and CS-derived NPs have been shown to have anti-inflammatory properties by decreasing pro-inflammatory cytokine production, although the immunomodulatory functions of chitosan are still unclear [37,38,39,40]. In concordance, our results show the anti-inflammatory activity of FCNP in all in vitro cell systems tested, strengthening the beneficial use of the CS excipient by fulfilling requirements and adding a therapeutic effect, as a complement to GRP’s anti-inflammatory activity. The characterization of the CS–TPP nanoparticles produced in the present study revealed their nanoscale nature, at around 120–150 nm, which is consistent with the majority of the reports of CS–TPP nanoparticles produced by similar methods, ranging from 40 to 250 nm [20,22,23,24,28,33,34,35,36]. This wide range can be explained by different factors known to influence nanoparticles size, such as chitosan concentrations and molecular weight, the degree of CS acetylation, and the CS/TPP molar ratio [20,27]. In our study, we used fluorescein-labeled CS to produce FCNP and FCNG formulations, which might differ in size from unlabeled CS/TPP nanoparticles, although similar fluorescein-labeling has been demonstrated not to interfere with CS nanoparticles’ properties [21,25]. The advantages of fluorescein-labeling nanoparticles include their easy detection due to intense fluorescence emission, allowing them to be quickly tracked intra- and extracellularly, which is extensively used as a tool to study nanoparticles association with cells in biomedical and pharmacological applications [21]. This feature makes FCNG a powerful tool for further applications at both the basic research and biomedical levels. The mean size of FCNG nanoparticles was shown to not significantly differ from that of FCNP, despite the high ucGRP association efficiency, which was expected due to the small molecular weight of the protein and the relatively low ucGRP concentrations used in this study. Additionally, FCNG’s broader particle distribution indicates a continuum of particles slightly differing in size, which might reflect different quantities of ucGRP molecules encapsulated, and indicates a non-saturation point of ucGRP in NPs. Nevertheless, the selected method of ucGRP incorporation during particle formation—by adding ucGRP to FC followed by TPP addition—resulted in a high degree of ucGRP association, in concordance with previous reports showing the higher loading efficiency of this incorporation method [20,23]. The successful incorporation of ucGRP into the FCNG formulation was further confirmed by flow cytometry. PDI values of around 0.3–0.4 for FCNP and FCNG did not significantly differ, and suggest suitability for a biomedical or pharmaceutical application. The positive zeta potential of both FCNP and FCNG, reflecting the cationic nature of CS, was found to be slightly, but not significantly, lower in FCNG as compared to FCNP—+37 mV compared to +28 mV—although still in the acceptable range for stable colloidal dispersions [41]. Overall, our new data show that ucGRP can be efficiently incorporated into CS–TPP nanoparticles, giving rise to a nanoparticle formulation suitable for several applications, including biomedical research and engineering. The functionality of the FCNG formulations in the present study was due to their immunomodulatory activity, enabling us not only to evaluate the bioactivity of ucGRP in FCNG, but also to obtain new insights into the potentialities of the ucGRP anti-inflammatory agent. While GRP γ-carboxylation has been shown to be essential for calcification inhibition [9,10,11,14], the non carboxylated GRP (ucGRP) used in the FCNG formulation has been shown to function as an anti-inflammatory agent by decreasing pro-inflammatory reactions in target cells, such as THP1-MoM cells, chondrocytes and synoviocytes [5,9]. Our results demonstrate that FCNG is able to decrease the pro-inflammatory cytokines and inflammation mediators in THP1-MoM and chondrocyte in vitro cell systems. The downregulation of NFkB gene expression and decreased protein accumulation, together with the decreased levels of TNFα, IL-1β and IL-6, with FCNG treatment, clearly demonstrate the retention of GRP anti-inflammatory activity. Moreover, in the present work, we extended our studies to evaluate the effects of ucGRP anti-inflammatory activity in VSMCs using treatments with FCNG. We previously demonstrated that GRP is involved in the downregulation of pro-inflammatory mediators in VSMCs during the calcification induced by calciprotein particles (CPPs) isolated from CKD stage 5 patients [11]. While these results clearly indicate a role for GRP as a mediator between calcification and inflammation, its function in the classical activation of VSMCs inflammation with cytokines is still unknown. Our results demonstrate a typical pro-inflammatory response of VSMCs upon TNFα stimulation, increasing levels of IL-6, IL-1β and IL-8 pro-inflammatory cytokines along with the upregulation and increased production of GRP. This increase in GRP levels is similar to the response of the LPS-stimulated THP1-MoM previously reported [5] and confirmed in the present study, and strongly indicates GRP as an important agent mediating pro-inflammatory reactions in multiple cells. Treatments of VSMCs with FCNG clearly reduced the production of these pro-inflammatory cytokines, extending the suitability of using FCNG as an anti-inflammatory agent in cytokine-induced vascular inflammation. These results are particularly relevant in the context of several chronic inflammatory diseases, such as CVD and OA, which share an intricate pathological inflammation–calcification cycle contributing to disease initiation and progression [5,6]. The dual functionality of GRP as an anti-calcifying and anti-inflammatory agent, combined with a suitable system for GRP delivery such as FCNG, can significantly contribute to developing or improving treatment options for some of these global health burdens. Although the mechanism of action of GRP in relation to inflammation remains unclear, GRP has been shown to function at both intra- and extracellular sites in the inhibition of ectopic calcification. The major advantages of GRP nano-encapsulation are expected to enable it to deliver GRP to both cellular environments. Our data showing the presence of FCNG in THP1-MoM cells after 2 h of incubation, and the increased intra- and extracellular GRP levels after 24 h in both THP1-MoM and VSMCs downregulating GRP expression, strongly indicate sustained and prolonged ucGRP delivery through FCNG formulation. This is consistent with results showing low GRP leaching from nanoparticles when incubated only in cell culture media, probably reflecting the protein desorption from the nanoparticles’ surface [20], indicating that the majority of GRP is entrapped into FCNG, thus conferring biological stability. Although our present data do not allow us to differentiate between intracellular and surface-located FCNG, CS and particularly CS NPs are known to be efficiently internalized by cells, mainly by nonspecific electrostatic forces that enhance the paracellular permeability of opening tight junctions, by adsorptive endocytosis partially mediated by a clathrin-mediated process, and phagocytosis in the particular case of macrophages [21,26]. It is possible that internalized FCNG further releases GRP through diffusion from the pores of the polymer network, and/or degradation and erosion of the nanoparticle. Following internalization, CS NPs to rapidly and partially dissociate within lysosomes, through enzymatic degradation [42,43]. This can partially explain the rapid and strong effect of FCNP in the anti-inflammatory response of THP1-MoM cells after 2 h, with a longstanding effect of FCNG seen up to 24 h, probably reflecting GRP’s sustained release and functionality. Overall, we have demonstrated that GRP’s incorporation into CS–TPP nanoparticles results in a novel, stable and biodegradable formulation of ucGRP with physiochemical properties suitable to several biomedical applications, and with the retained functionality of GRP’s anti-inflammatory activity in the different human in vitro cell systems tested. This brings more advantages, and strengthens the wide range of GRP applications in several inflammation-related diseases, opening the way to further GRP nanoparticle improvements that will ultimately enable an effective anti-inflammatory therapy. 4. Materials and Methods 4.1. Production and Quantification of Recombinant Human Non-Carboxylated GRP (ucGRP) Recombinant human non-carboxylated GRP (ucGRP) was produced in the E. coli system and purified by affinity chromatography (HisTrap HP Column, GE Healthcare) followed by Reverse Phase–High Performance Liquid Chromatography (RP-HPLC), as previously described [44]. GRP quantification was performed using a specific sandwich ELISA for the quantification of total GRP, as described [11]. 4.2. Chitosan Labeling with Fluorescein (FC) The labeling of chitosan (CS) with fluorescein was performed according to a previously established procedure [25]. Briefly, 250 mg of deacetylated CS (low molecular weight, deacetylation degree 75–80%) (Sigma Aldrich, Burlington, MA, USA) was dissolved in 15 mL of 1% (v/v) acetic acid solution, at room temperature. Fluorescein sodium salt (Sigma Aldrich, Burlington, MA, USA) (10 mg) was dissolved in 1 mL of ethanol (96%), and 7.5 mg of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDAC) (Sigma Aldrich) was dissolved in 4 mL of Milli-Q water. The fluorescein solution was carefully added to the chitosan solution under stirring, followed by the addition of the EDAC solution. The mixture was stirred overnight at room temperature, protected from light, followed by dialysis against water using a 2000 molecular weight cut-off tubing (Sigma-Aldrich) over 3 days, with constant medium changes. The entire dialyzed solution was freeze-dried, and the process yield (PY) was calculated as follows Equation (1): PY (%) = CS weight/Total solids (CS + Fluorescein) weight × 100(1) 4.3. Preparation of Fluorescein-Labeled Chitosan (FC)/TPP (FCNP) and FC/GRP/TPP (FCNG) Nanoparticles Fluorescein-labeled chitosan/TPP nanoparticles were prepared by ionotropic gelation through the electrostatic interaction of the positively charged amino groups of CS with negatively charged phosphate groups of TPP anion, using a previously described methodology [33,34]. Briefly, CS was dissolved in 1% acetic acid (v/v) and TPP (Sigma Aldrich) was dissolved in Milli-Q water at room temperature, to obtain solutions of 1 mg/mL (w/v) and 0.714 mg/mL (w/v), respectively. FCNP were formed by the addition of 0.8 mL of the TPP solution to 2 mL of the CS solution to reach the theoretical FC/TPP ratio of 3.5/1 (w/w), under constant magnetic stirring at room temperature. FCNG was similarly prepared, and 1 µg of ucGRP was added to 2 mL of CS (1 mg/mL), and then allowed to react with 0.8 mL TPP (0.714 mg/mL). Nanoparticles were concentrated by centrifugation at 16,000× g at 15 °C, for 30 min. The supernatants were used for the quantification of GRP non-incorporated into FCNG, and nanoparticles were resuspended either in Milli-Q water or cell culture media for physicochemical characterization and in vitro cell functional assays, as described below. 4.4. Characterization of FCNP and FCNG, Physicochemical Properties and Morphology The concentrations and size distributions of both FCNP and FCNG particles were determined using the Nanoparticle Tracking Analysis NTA technique on the NanoSight NS300™ (Malvern Instruments, Worcestershire, UK) equipment. The samples were initially solubilized in MilliQ water to a final volume of 2 mL, and then diluted 100-fold with MilliQ water. Each sample was analyzed 3 times (n = 3) with independent dilutions. Capture settings (shutter and gain) were adjusted manually for each analysis and all steps were carried out at room temperature. Sample videos were analyzed with the NTA 2.3 Analytical software. FCNP and FCNG were characterized regarding their size, polydispersity index (PDI) and zeta potential on freshly prepared samples by photon correlation spectroscopy and laser Doppler anemometry, respectively, using a Zetasizer® NanoZS (Malvern Instruments, Malvern, UK). The characterization was performed in an electrophoretic cell, in which a 20 µL aliquot of nanoparticles was diluted in 1 mL of either cell culture media (RPMI 1640) for size and PDI determinations, or ultrapure water for zeta potential measurements. Size and PDI were determined with a detection angle of 173°, at 25 °C, and zeta potential was calculated from the mean electrophoretic mobility values. Three batches each of FCNP and FCNG were analyzed in triplicate (n = 3). Morphological analysis was performed by the transmission electron microscopy (TEM) of negative-stained FCNP and FCNG. Freshly prepared NPs were resuspended in ultrapure water and adsorbed onto formvar grids. Samples were stained with 1.5% aqueous uranyl acetate for TEM image acquisition in a JEOL 1200EX transmission electron microscope. 4.5. Determination of ucGRP Association Efficiency (AE) ucGRP association efficiency (AE) refers to the amount of protein associated with FCNG, expressed as a percentage of the total amount of ucGRP added in the process. The amount of free non-associated ucGRP was determined by ELISA in the supernatants of the reaction medium after separation by centrifugation (16,000× g, 30 min, 15 °C). ucGRP AE was determined from three independent FCNG preparations (n = 6). The association efficiency (AE) of ucGRP was calculated as follows Equation (2): AE (%) = (Total ucGRP amount − Free ucGRP amount)/Total ucGRP amount × 100(2) 4.6. In Vitro Release of ucGRP from FCNG In vitro studies of the release of ucGRP from FCNG nanoparticles were performed by resuspending the FCNG pellets in 2 mL of RPMI, at 37 °C and 5% of CO2 atmosphere, for appropriate time intervals of between 0 min and 48 h. At the end of each time point, equal volumes were evaluated for ucGRP content. For this, the samples were centrifuged for 30 min, at 15 °C and 16,000× g, and the ucGRP released was quantified in the supernatant by ELISA (n = 3). 4.7. Cell Culture The THP-1 cell line was kindly provided by Dr. Nuno Santos (CBME, University of Algarve, Faro) and cells were cultured according to ATCC instructions in the RPMI Growth Medium (RPMI 1640 with L-Glutamine (Lonza, Basel, Switzerland), 10% heat-inactivated fetal bovine serum (FBS, Invitrogen, Waltham, MA, USA) and 1% Pen-Strep (P/S, Gibco, Waltham, MA, USA). Differentiation into macrophagic THP-1 (THP-1 MoM) was achieved by culturing cells in 25 ng/mL PMA (Sigma Aldrich, Burlington, MA, USA) in complete RPMI for 48 h. Human aortic VSMCs (VSMC) were derived from tissue explants as described previously [45], and used between passages 4 and 12. VSMCs were maintained in M199 medium (Life Technologies, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (FBS) and 1% (v/v) of P/S. The primary human articular chondrocytes were commercially acquired (Lonza, Visp, Switzerland), and cultured in advanced Dulbecco’s modified eagle’s medium (Adv DMEM) (Invitrogen, Carlsbad, CA, USA) supplemented with 10% (v/v) of heat-inactivated FBS, 1 mM of L-Glutamine (L-Gln, Invitrogen, Waltham, MA, USA) and 1% (v/v) of P/S. All cell cultures were maintained at 37 °C in a humidified atmosphere containing 5% CO2, and experiments were performed on confluent VSMC and chondrocyte cells, using an average of 1 × 106 cells/mL of THP-1 MoM. 4.8. Cellular Proliferation Measurement Cells were seeded in 96-well plates at 1 × 105 cells/well and cultured in 200 μL of the corresponding cell culture media, supplemented with (11.7 ± 4.5) × 109 particles/mL of each FCNP and FCNG, as quantified by NTA, for 48 h. Cell viability was assessed using the CellTiter 96 cell proliferation assay (Promega, Madison, WI, USA), following manufacturer’s instructions, in triplicate experiments for each cell type (n = 3). 4.9. Flow Cytometry Analysis FCNP and FCNG, (11.7 ± 4.5) × 109 particles/mL of each formulation, were incubated with 1 × 106 THP-1 MoM cells in 500 μL media for 2 h. The flow cytometry protocol from ORIGENE was used for cell staining. Briefly, after dethatching, centrifuged cell pellets were blocked with 0.5% BSA for 30 min, incubated with PE anti-mouse/human CD11b antibody (1 µg/mL, Biolegend, San Diego, CA, USA), and fixed in 0.2% PFA in PBS overnight at 4 °C. A permeabilization step with 0.1% Triton in PBS preceded the incubation with the purified polyclonal CTerm-GRP antibody (5 μg/mL (GenoGla Diagnostics, Faro, Portugal)). At the end, the pellets were treated with fluorochrome (ALEXA Fluor® 647 Donkey anti-rabbit IgG Antibody, Biolegend, 1 µg/mL), and resuspended in PBS for analysis on a FACSCalibur Flow Cytometer (BD Biosciences), using Cell Quest Pro 6.0 software. Compensation was performed using single-stain controls and all gates were set based on Fluorescence Minus One (FMO) controls. For each sample 10,000 events were recorded. Flow cytometry data were analyzed using FlowJo software (version 6.7). 4.10. Inflammatory Assays The anti-inflammatory potential of FCNP and FCNG was evaluated in 1 × 106 THP1-MoM cells and confluent primary VSMCs and chondrocytes, plated in 24-well plates with 500 μL media, by pre-treatment of the cells with (11.7 ± 4.5) × 109 particles/mL of each formulation resuspended in the corresponding cell culture media for determined durations, followed by inflammation stimulation with LPS (100 ng/mL), TNFα (20 ng/mL), and IL-1β (10 ng/mL), respectively, without media exchange for an additional 24 h. In some experiments, cells were also pre-treated with dexamethasone (DXM, 2 µM) as the positive anti-inflammatory control. Cell culture media were collected for the quantification of pro-inflammatory cytokines by ELISA, and cells were harvested for total RNA and protein extraction. 4.11. Total Protein Extraction Total protein extracts from THP1-MoM and VSMCs were obtained with RIPA buffer (50 mM Tris HCl pH 8, 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS) for 4 h at 4 °C, with constant shaking. RIPA extracts were centrifuged at 16,000× g for 30 min at 4 °C. Protein quantification was performed with the MicroBCA protein assay kit (Pierce). 4.12. ELISA Assays The collected cell culture media were centrifuged at 16,000× g for 20 min at 4 °C to remove cellular debris, and used for the quantification of TNFα and IL-6 by ELISA (Peprotech, East Windsor, NJ, USA), following the manufacture’s protocols. Cell culture media and total protein extracts were used for GRP quantification by ELISA, as described [11]. 4.13. Electrophoresis and Western Blot Aliquots of 20 μg of total protein were size-separated on 4–12% (w/v) gradient polyacrylamide precast gels containing 0.1% (w/v) SDS (NuPage, Invitrogen, Waltham, MA, USA) and transferred onto a nitrocellulose membrane (Bio-Rad, Hercules, CA, USA) as previously described [5,10,11]. The detection of NFkB and GAPDH was performed by overnight incubation with anti-NFkB p65 (1 μg/mL, Invitrogen) and anti-GAPDH (1:500, Santa Cruz Biotechnology, Dallas, TX, USA). Immunodetection was achieved using species-specific secondary horseradish peroxidase-conjugated antibodies and Western Lightning Plus-ECL (PerkinElmer Inc., Waltham, MA, USA). Image acquisition was performed using an IQ LAS 4000 mini biomolecular imager. 4.14. RNA Extraction, cDNA Amplification and Quantitative Real-Time PCR (qPCR) Total RNA was isolated from cell cultures using the Direct-zol RNA Miniprep kit (Zymo Research, Irvine, CA, USA), according to the manufacturer’s instructions. The RNA concentration was determined by spectrophotometric analysis at 260 nm using a Nanodrop spectrophometer (Thermo Scientific, Waltham, MA, USA). Five hundred nanograms of total RNA were treated with RQ1 RNase-free DNase (Promega, Madison, WI, USA) and reverse-transcribed using Moloney–murine leukemia virus reverse transcriptase (MMLV-RT, Invitrogen), RNase Out (Invitrogen), and an oligo(dT) adapter (ACGCGTCGACCTCGAGATCGATG(T)13), according to the manufacturer’s recommendations. Quantitative PCR was performed with a CFX connect, Real Time System (Bio-Rad, Richmond, CA, USA), SoFast Eva Green Supermix (Bio-Rad, Richmond, CA, USA) and the specific human primer sets GAPDH_1F (5′-AAGGTGAAGGTCGGAGTCAACGGA-3′) and GAPDH_1R (5′-TCGCTCCTGGAAGATGGTGATGGG-3′) to amplify GAPDH; 18S_1F (5′-GGAGTATGGTTGCAAAGCTGA-3′) and 18S_1R (5′-ATCTGTCAATCCTGTCCGTGT-3′) to amplify 18S; GRP_1F (5′-GTCCCCCAAGTCCCGAGATGAGG-3′) and GRP_1R (5′-CCTCCACGAAGTTCTCAAATTCATTCC-3′) to amplify GRP; IL-1β_1F (5′-TGGACAAGCTGAGGAAGATGCTGGT-3′) and IL-1β_1R (5′-CCCTGGAGGTGGAGAGCTTTCAGTT-3′) to amplify IL-1β; IL-6_1F (5′-AAGCAGCAAAGAGGCACTGGCAGAA-3′) and IL-6_1R (5′-CTGCACAGCTCTGGCTTGTTCCTCAC-3′) to amplify IL-6; NFkB_1F (5′-GCAATCATCCACCTTCATTCTCAACTT-3′) and NFkB_1R (5′-CCTCCACCACATCTTCCTGCTTAG-3′) to amplify NFkB; IL-8_1F (5′-CTGCAGCTCTGTGTGAAGGTGCAGT-3′) and IL-8_1R (5′-GCACCCAGTTTTCCTTGGGGTCCAG-3′) to amplify IL-8. Fluorescence was measured at the end of each extension cycle in the FAM-490 channel, and melting profiles of each reaction were constructed to check for unspecific product amplification. Levels of gene expression were calculated using the comparative method (ddCt) and normalized using gene expression levels of 18S and GAPDH housekeeping gene, for THP1-MoM and VSMCs, respectively, with the iQ5 software (Bio-Rad); qPCR was performed via three independent experiments, each in triplicate (n = 3), and a normalized SD was calculated. 4.15. Statistical Analysis Statistical analysis was performed using PRISM software (GraphPad Prism, GraphPad Software, La Jolla, CA, USA). Data are presented as mean ± standard deviation (SD). Student’s t-test was used for comparison between two groups. For more than two groups, significance was determined using ordinary one-way ANOVA with comparison between groups by Dunnett test. Statistical significance was defined as p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***) and p ≤ 0.0001 (****). 5. Patents The tools and methods described in this manuscript are included in a PCT patent application, PCT/PT2009000046. Acknowledgments We would like to acknowledge Cristina Peixoto, from iBET—Instituto de Biologia Experimental e Tecnológica, for providing access to NTA equipment, and Mariana Vinagre for experimental support in acquiring NTA data. Author Contributions Conceptualization, C.S.B.V. and D.C.S.; methodology, C.S.B.V., N.A., J.C., J.F.P., A.G., M.V., A.L.M., A.A.d.M., A.S.M. and T.Q.F.; formal analysis, C.S.B.V., N.A., J.C., J.F.P., M.V., A.L.M., A.A.d.M., A.S.M. and T.Q.F.; investigation, C.S.B.V. and D.C.S.; resources, L.S.; writing—original draft preparation, C.S.B.V., D.C.S. and N.A.; writing—review and editing, C.S.B.V., D.C.S., A.G., L.S. and C.V.; supervision, C.S.B.V. and D.C.S.; project administration, C.S.B.V. and D.C.S.; funding acquisition, C.S.B.V. and D.C.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 Dina C. Simes and Carla Viegas are cofounders of GenoGla Diagnostics. The authors declare that there is no conflict of interests regarding the publication of this paper. The tools and methods described in this manuscript are included in a PCT patent application PCT/PT2009000046, which is owned by University of Algarve and the Centre of Marine Sciences (CCMAR), and the exclusive rights are licensed to GenoGla Diagnostics. 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 FCNP and FCNG size distribution, ucGRP incorporation and morphology. (A) Representative analysis of FCNP and FCNG by nanotracking analysis (NTA), showing the concentration of particles as a function of size. (B) Percentage of ucGRP initially used for FCNG synthesis (ucGRPinitial), and in the supernatants after separation of pelleted nanoparticles (FCNGSN), representing non-incorporated ucGRP, determined by ELISA. Data are representative of six independent experiments. (C,D) Ultrastructural characterization of FCNP (C) and FCNG (D) by transmission electron microscopy (TEM). Scale bar of 200 nm. Figure 2 Levels of ucGRP released from FCNG during a 48 h study. ucGRP in cell culture media (RPMI) was measured by ELISA, at different time points from 0 min to 48 h. The data are representative of three independent experiments, and the differences are statistically non-significant. Figure 3 Anti-inflammatory effect and toxicity of FCNP and FCNG in LPS-stimulated THP-1 macrophages (THP-1-MoM). (A) The evaluation of the inflammatory marker TNFα was performed by ELISA in the cell culture media of THP-1 MoM treated for 2 h, 8 h or 24 h with (11.7 ± 4.5) × 109 particles/mL of FCNP or FCNG, and then stimulated with LPS (100 ng/mL) for a further 24 h. Dexametasone (DXM) (2 μM) was used as a positive anti-inflammatory control and non-stimulated cells were used as controls for LPS stimulation. (B) Viability of THP-1-MoM exposed to (11.7 ± 4.5) × 109 particles/mL of FCNP or FCNG for 48 h. Data are representative of three independent experiments, and presented as mean ± SD. Two-way ANOVA and multiple comparisons were achieved with the Dunnett’s test and are presented relative to the LPS-stimulated cells. Statistical significance was defined as p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***) and p ≤ 0.0001 (****). Figure 4 Binding/uptake of FCNP and FCNG by THP1-MoM cells. (A–C) Flow cytometry analysis of FCNP and FCNG in THP1-MoM cells. (A,B) Dot plots of THP-1 MoM cells exposed to (11.7 ± 4.5) × 109 particles/mL of FCNP (A) and FCNG (B) for 2 h. The Q2 quadrant represents cells that have, simultaneously, fluorescein-labeled nanoparticles and the THP-1 MoM marker labeled with PE (double positive for FITC and PE). Q2 is 67.1% for FCNP (A) and 73.7% for FCNG (B). (C) Gating strategy used for the analysis of FCNG in THP1-MoM cells. The first plot shows the debris exclusion in the side scatter (SSC) vs. the forward scatter (FSC). In the second plot, the double positive population for fluorescein-labeled nanoparticles and the THP-1 MoM marker was gated (73.7% are double positive for FITC and PE). Finally, the last plot shows the selection of the population of interest, FCNG++, which represents THP-1 MoM cells with fluorescein-labeled nanoparticles containing GRP labeled with Alexa 647 (73.3% are triple positive for FITC, PE and Alexa 647). (D,E) Quantification of GRP present in THP1-MoM cell protein extracts (D) and in the cell culture media (E) by ELISA, after pre-treatments with (11.7 ± 4.5) × 109 particles/mL of FCNP and FCNG for 24 h, followed by stimulation with LPS (100 ng/mL) for an additional 24 h. Non-stimulated cells were used as controls for LPS stimulation. (F) Relative GRP gene expression determined by quantitative polymerase chain reaction (qPCR) of experiments described in (D,E). Data in (D–F) are representative of three independent experiments and presented as mean ± SD. Two-way ANOVA and multiple comparisons were achieved with the Dunnett’s test, and presented relative to the LPS-stimulated cells. Statistical significance was defined as p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***) and p ≤ 0.0001 (****). Figure 5 The anti-inflammatory activity of FCNG in THP1-MoM cells is mediated by downregulation of pro-inflammatory cytokines. (A–C) Gene expression analysis of IL-1β (A), IL-6 (B) and NFkB (C) by qPCR of THP1-MoM cells pre-treated with (11.7 ± 4.5) × 109 particles/mL of FCNP and FCNG for 24 h, followed by stimulation with LPS (100 ng/mL) for an additional 24 h. Non-stimulated cells were used as controls for LPS stimulation. (D,E) Total protein extracts of THP1-MoM cells treated as described in (A–C) were analyzed by Western blot to detect NFkB. The positions of relevant molecular mass markers (kDa) are indicated on the right side and GAPDH was used as the loading control. (E) Quantification of NFkB levels was performed by densitometry using ImageJ software, and is presented relatively to the GAPDH loading control as arbitrary units. Data are representative of three independent experiments and presented as mean ± SD. Two-way ANOVA and multiple comparisons were performed with the Dunnett’s test, and are presented relative to the LPS-stimulated cells. Statistical significance was defined as p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***) and p ≤ 0.0001 (****). Figure 6 Anti-inflammatory activity of FCNG in primary human VSMCs. VSMCs were pre-treated with (11.7 ± 4.5) E + 9 particles/mL of FCNP and FCNG for 24 h, followed by stimulation with TNFα (20 ng/mL) for an additional 24 h, then analyzed for levels of IL-6 present in the cell culture media by ELISA (A) and levels of gene expression of IL-1β (B), IL-8 (C) and GRP (D) by qPCR. (E,F) Quantification of GRP present in VSMCs protein extracts (E) and in the cell culture media (F) by ELISA. Non-stimulated cells were used as controls for TNFα stimulation. (G) Viability of VSMCs exposed to (11.7 ± 4.5) × 109 particles/mL of FCNP or FCNG for 48 h. Data are representative of three independent experiments and presented as mean ± SD. Two-way ANOVA and multiple comparisons were performed with the Dunnett’s test, and are presented relative to the TNFα-stimulated cells. Statistical significance was defined as p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***) and p ≤ 0.0001 (****). Figure 7 Anti-inflammatory activity of FCNG in primary human articular chondrocytes. (A) Chondrocytes were pre-treated with (11.7 ± 4.5) × 109 particles/mL of FCNP and FCNG for 24 h, or dexametasone (DXM, 2 µM), followed by stimulation with IL-1β (10 ng/mL) for an additional 24 h, and analyzed for levels of IL-6 present in the cell culture media by ELISA. Non-stimulated cells were used as controls of IL-1β stimulation. (B) Viability of articular chondrocytes exposed to (11.7 ± 4.5) × 109 particles/mL of FCNP or FCNG for 48 h. Data are representative of three independent experiments and are presented as mean ± SD. Two-way ANOVA and multiple comparisons were performed with the Dunnett’s test, and are presented relative to the IL-1β-stimulated cells. Statistical significance was defined as p ≤ 0.05 (*), p ≤ 0.01 (**), and p ≤ 0.0001 (****). ijms-23-04813-t001_Table 1 Table 1 Physicochemical properties of fluorescein-labeled quitosan–tripolyphosphate nanoparticles (FCNP) and fluorescein-labeled quitosan–ucGRP–tripolyphosphate nanoparticles (FCNG) assessed by DLS (n = 3). Size (nm) PDI Zeta Potential (mV) AE (%) FCNP 130 ± 45 0.33 ± 0.07 +37 ± 2 FCNG 156 ± 38 0.39 ± 0.06 +28 ± 7 99.8 ± 0.1 DLS, dynamic light scattering; PDI, polydispersion index; AE, association efficiency. 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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091172 plants-11-01172 Article Exogenous Rosmarinic Acid Application Enhances Thermotolerance in Tomatoes Zhou Zhiwen 1 Li Jiajia 1 Zhu Changan 1 Jing Beiyu 1 Shi Kai 1 https://orcid.org/0000-0002-7626-1165 Yu Jingquan 123 https://orcid.org/0000-0002-7387-9699 Hu Zhangjian 12* Van Ha Chien Academic Editor Mostofa Mohammad Golam Academic Editor Saha Gopal Academic Editor Roy Choudhury Swarup Academic Editor 1 Department of Horticulture, Zhejiang University, Hangzhou 310058, China; 21916058@zju.edu.cn (Z.Z.); 22016200@zju.edu.cn (J.L.); 12016055@zju.edu.cn (C.Z.); 12116052@zju.edu.cn (B.J.); kaishi@zju.edu.cn (K.S.); jqyu@zju.edu.cn (J.Y.) 2 Shandong (Linyi) Institute of Modern Agriculture, Zhejiang University, Linyi 276000, China 3 Key Laboratory of Horticultural Plants Growth and Development, Ministry of Agriculture and Rural Affairs of P. R. China, Hangzhou 310058, China * Correspondence: zjhu90@zju.edu.cn 26 4 2022 5 2022 11 9 117207 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/). Due to global warming, high-temperature stress has become a major threat to plant growth and development, which causes a severe challenge to food security worldwide. Therefore, it is necessary to explore the plant bioactive molecules, which could be a promising approach to strengthening plant thermotolerance. Rosmarinic acid (RA) serves as a plant-derived phenolic compound and has beneficial and health-promoting effects for human beings. However, the involvement of RA in plant stress response and the underlying molecular mechanism was largely unknown. In this study, we found that exogenous RA application conferred improved thermotolerance in tomatoes. The transcript abundance and the enzyme activity of enzymatic antioxidants, such as ascorbate peroxidase (APX), catalase (CAT), glutathione reductase (GR), and dehydroascorbate reductase (DHAR), were further promoted by RA treatment in tomato plants subjected to high-temperature stress. Moreover, RA activated the antioxidant system and modulated the cellular redox homeostasis also associated with the redox status of nonenzymatic glutathione and ascorbic acid. The results of RNA-seq data showed that transcriptional regulation was involved in RA-mediated thermotolerance. Consistently, the gene expression of several high temperature-responsive transcription factors like HsfA2, and WRKY family genes were substantially induced by RA treatment, which potentially contributed to the induction of heat shock proteins (HSPs). Overall, these findings not only gave a direct link between RA and plant thermotolerance but also provided an attractive approach to protecting crop plants from high-temperature damage in a global warming future. tomato rosmarinic acid thermotolerance oxidative stress antioxidant system heat shock proteins transcription regulation ==== Body pmc1. Introduction As sessile organisms, plants are severely threatened by a variety of abiotic stresses, such as unsuitable temperature, drought, and salinity, which cause extensive losses in agricultural production worldwide [1]. Due to increasing anthropogenic emissions, global warming dramatically affects crop growth and yield [2]. The Intergovernmental Panel on Climate Change (IPCC) reported that the average global temperature rise was expected to reach or even exceed 4.0 °C at the end of this century [3]. Tomato (Solanum lycopersicum L.) is the highest value and economically important vegetable crop species worldwide, and it provides a substantial source of micronutrients to humans [4]. Typically, the optimum temperature for tomato plant growth is approximately 25 °C. However, consistently high temperatures, especially over 35 °C, heavily affect all stages of tomato plants from the germination to fruit setting stages and disrupt multiple physiological and biochemical processes correlated with final yield and fruit quality. It is predicted that global warming-induced high temperatures will reduce tomato yield by as much as 70% [5]. Therefore, studying the underlying mechanism by which plants respond to high temperatures and enhancing crop thermotolerance will provide a promising avenue for maximizing agricultural production and promoting food security in the future. Plants have evolved sophisticated thermotolerance mechanisms to combat high-temperature stress. Heat shock proteins (HSPs) and antioxidants are major functional products that are induced by high-temperature stress, and the production of HSPs and antioxidant enzymes is usually orchestrated by a heat-shock factor (Hsf)-mediated transcriptional activation [6]. As molecular chaperones, HSPs can be synthesized quickly during the early stages of high-temperature stress, and they play a crucial role in controlling protein homeostasis by renaturing numerous high temperature-denatured proteins. HSPs are generally classified into HSP100, HSP90, HSP70, HSP60, and small HSPs according to the protein molecular weight. HSP70 and HSP90 are the most abundant and important HSPs involved in thermotolerance in a variety of crops, including tomato, pepper, potato, cabbage, wheat, and tea [7]. Among multiple high temperature-responsive Hsfs, HsfA2 acts as a major transactivator during prolonged high-temperature stress by driving transcriptional memory. For instance, high temperature-induced transcript levels of HSP70 and HSP90 were substantially decreased in an Arabidopsis HsfA2 knockout mutant, accompanied by reduced basal thermotolerance [8]. Photosynthesis is a well-established source of reactive oxygen species (ROS) generated from the photosynthetic electron chain, but high-temperature stress disrupts plant photosynthesis, resulting in the excessive accumulation of ROS, including superoxide anion (O2•−), hydroperoxyl radical (HO2•), hydroxyl radical (•OH), singlet oxygen (1O2), and hydrogen peroxide (H2O2) [9]. Consequently, excessive ROS leads to DNA, protein, lipid, and carbohydrate oxidation, which eventually amalgamate to cause oxidative stress. Plants primarily deal with oxidative stress via a complicated mechanism consisting of enzymatic and nonenzymatic antioxidants. The ROS-scavenging machinery of enzymatic antioxidants contains a series of highly efficient enzymes, such as superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT), glutathione reductase (GR), glutathione peroxidase (GPX), dehydroascorbate reductase (DHAR), and monodehydroascorbate reductase (MDHAR), to control the oxidation cascades [10]. ROS are also inhibited by nonenzymatic low-molecular antioxidants, including glutathione (GSH), ascorbic acid (AsA), carotenoids, α-tocopherol, flavonoids, and phenolic compounds [11]. It is well known that a wide range of exogenous and endogenous non-enzymatic antioxidants play a positive role in plant thermotolerance. Exogenous melatonin enhanced the activity of the antioxidant system to promote the germination of rice seeds under high-temperature stress and silencing the melatonin biosynthesis gene COMT1 in tomato plants impaired cellular redox homeostasis and aggravated high temperature-induced oxidative stress [12,13]. Similarly, the exogenous application of AsA increased the endogenous AsA content, leading to increased thermotolerance in tomato plants [14]. Thus, it might be helpful to explore plant endogenous bioactive molecules and application strategies for improving plant thermotolerance. Rosmarinic acid (RA), named after rosemary, is a natural phenolic antioxidant and an ester of caffeic acid and 3,4-dihydroxyphenyllactic acid, which are synthesized from the amino acids l-phenylalanine and l-tyrosine, respectively [15]. RA is commonly found in species of the Boraginaceae and Lamiaceae, but it is also found in other higher plant species, including tomato [16]. RA has remarkable biological functions with a variety of applications in daily life, and many products have been prepared from RA in the food preservatives, cosmetics, and pharmaceutical industries. In particular, RA provides humans with numerous health-promoting benefits, including anti-inflammatory, anticancer, antiaging, antidiabetic, antidepressant, and antiallergic effects [17]. As a powerful antioxidant compound, it implied that RA was involved in plant tolerance to multiple abiotic stresses. For example, the endogenous RA contents, together with other phenolic compounds like caffeic acid, caftaric acid, and cinnamyl malic acid, were increased in basil (Ocimum basilicum) plants subjected to salt stress [18]. However, the role of RA in plant tolerance and the underlying molecular mechanisms remain largely unknown. In this study, we explored the positive role of exogenous RA in promoting thermotolerance in tomato plants, which relied on HSP induction, antioxidant system activation, and high temperature-responsive transcriptional regulation. 2. Results 2.1. Exogenous RA Treatment Increases Plant Thermotolerance in Tomato To explore the role of RA in plant resistance to high temperature, tomato plants were exogenously sprayed with 2 mmol L−1 RA, or H2O as a control before different temperature treatments. After 48 h of different temperature treatments, we found that there were no differences between tomato plants pretreated with RA and H2O under normal temperature. However, RA effectively alleviated the leaf wilting caused by high temperatures in tomato plants (Figure 1a). Consistent with the leaf wilting phenotype, high temperature-induced electrolyte leakage could be significantly reduced by exogenous RA treatment (Figure 1b). Plant photosynthesis is quite sensitive to temperature stress. To explore whether RA played a protective effect on photosynthesis during high-temperature stress, we measured the maximum quantum efficiency of photosystem II (Fv/Fm). As shown in Figure 1c, exogenous RA treatment reduced the decline in the Fv/Fm values caused by high-temperature stress compared with dH2O control treatment, which implied RA effectively protected the photosynthetic performance of PSII from high temperature-induced damage. High temperature accelerates the oxidation of cell membrane lipids, aggravating the MDA formation and ROS accumulation, which eventually causes oxidative damage and cell dysfunction [19]. To explore whether RA alleviates high temperature-induced membrane lipid peroxidation, we quantified the MDA content in tomato leaves in response to high temperature. Compared with the control pretreatment, exogenous RA application significantly reduced the MDA accumulation in tomato plants subjected to high temperatures (Figure 1d). Consistently, we evaluated ROS accumulation through DAB and NBT staining and found that RA largely inhibited high temperature-induced H2O2 and O2•− contents, respectively (Figure 1e,f). Taken together, the above results indicated that RA effectively reduced the accumulation of harmful cellular oxidation products in tomato plants under high-temperature stress and enhanced plant thermotolerance. 2.2. Exogenous RA Treatment Activates Antioxidant System in Tomato Plants Subjected to High Temperature During evolution, plants have developed a sophisticated defense system that serves to alleviate the adverse effects of temperature-induced stress. The activation of antioxidant enzymes such as ascorbate peroxidase (APX), catalase (CAT), dehydroascorbate reductase (DHAR), and glutathione reductase (GR) in plants limited or scavenged ROS accumulation, which mitigated the damages caused by temperature-induced oxidative stress [20]. To investigate the effects of RA on the activation of antioxidant enzymes, we first examined changes in the transcript abundance of the above antioxidant genes in RA- or dH2O-pretreated plants in the absence or presence of high-temperature stress. While exogenous RA application did not significantly change the transcript abundance of these antioxidant genes in the absence of stress, RA treatment further increased the transcript levels of APX, CAT, DHAR, and GR by 160%, 140%, 98%, and 69%, respectively (Figure 2a). Similar to the gene expression results, the high temperature-induced enzyme activities of APX, CAT, DHAR, and GR were further promoted by exogenous RA treatment in tomato plants under high-temperature conditions (Figure 2b). In addition, nonenzymatic antioxidants such as ascorbate and glutathione acted as the heart of the redox hub to scavenge excessive ROS [21]. The redox status and content of AsA and GSH determined the capability of ROS scavenging. High-temperature stress led to a significant decline in both reduced AsA and GSH contents, but exogenous RA effectively prevented these nonenzymatic antioxidants from decreasing (Figure 2c,d). Consistently, the high temperature-induced decreases in leaf AsA to dehydroascorbate (DHA) and GSH to glutathione disulfide (GSSG) were largely prevented by RA pretreatment (Figure 2e,f). Overall, these results strongly suggested RA enhanced plant thermotolerance by activating the cellular antioxidant system. 2.3. Exogenous RA Treatment Promotes HSPs in Tomato Plants in Response to High-Temperature Stress High-temperature stress induced a variety of functional proteins denaturation and then caused irreversible damage to plants. As molecular chaperones, HSPs protected cellular proteins by preventing denatured protein aggregation and facilitating the refolding of proteins [3]. The transcript abundance of HSP genes was governed by the transactivator Hsfs by binding the heat stress elements of the HSP promoters [22]. To unravel the effects of RA on the response of Hsf and HSPs, we analyzed the transcription of some key genes to high temperature using a qRT-PCR assay. As shown in Figure 3a, the transcript abundance of the high temperature-responsive genes HsfA2, HSP70, and HSP90 were further significantly induced by exogenous RA treatment (Figure 3a). In addition, we evaluated the endogenous protein abundance of HSP70 and HSP90 using specific antibodies. Similarly, the high temperature-induced increases in HSP70 and HSP90 proteins were highly promoted by RA treatment (Figure 3b). The evidence described above indicated the activation of HSPs played a crucial role in RA-induced plant thermotolerance. 2.4. WRKYs Are Involved in RA-Mediated Plant Thermotolerance To further investigate the global effects of RA on plant thermotolerance, we carried out an RNA-seq analysis to recognize the differential high temperature-responsive genes in response to RA or dH2O treatment. Of the 34,931 detected tomato transcripts, a total of 9226 (4645 up-regulated and 4581 down-regulated) and 8108 (4077 up-regulated and 4031 down-regulated) genes showed significantly differential expression (fold change ≥ 2, p < 0.05) within RA- and dH2O-treated tomato plants following high-temperature treatment, respectively (Figure 4a; Supplementary Table S1). In total, 3236 genes were found that increased in abundance in plants pretreated with either RA or dH2O, while other 1409 genes were only induced by high temperature in plants pretreated with RA (Figure 4b). Based on the heatmap of all high temperature-induced genes, the level of transcript abundance was globally enhanced in the RA-pretreated plants compared to dH2O-pretreated plants (Figure 4c). Among the high temperature-induced genes, there were an additional 3208 transcripts that showed significantly higher expression (fold change ≥ 2) in tomato plants following RA-treatment compared with that following dH2O-treatment under high-temperature conditions (Supplementary Table S2). Therefore, these 3208 genes were annotated as RA-induced high temperature-responsive genes. Then, the enrichment analysis of Gene Ontology (GO) categories was performed within these RA-induced high temperature-responsive genes. As shown in Figure 4d, RA-mediated transcriptional regulation was highly associated with transcription regulator activity, sequence-specific DNA binding, ADP binding, and calcium ion binding (Supplementary Table S3). Interestingly, 18 out of 81 genes (22%) from the largest cluster of transcription regulator activity were WRKY transcription factors (Figure 4e). Additionally, qRT–PCR analysis also confirmed that RA application induced a higher level of transcript abundance in WRKY10, WRKY33, WRKY41, WRKY46, WRKY55, and WRKY81 in tomato plants subjected to high-temperature conditions (Figure 4f). Therefore, we implied that WRKYs played an important role in RA-mediated plant thermotolerance. 3. Discussion RA is a major phenolic compound in tomatoes, of which the concentration levels ranged from 1.21 to 22.67 μg/g dry weight according to different varieties of tomatoes [16]. In some commercial cultivars of tree tomato (Solanum betaceum Cav.), the RA concentration reached up to 1.2 mg/g dry weight [23]. RA has a number of interesting biological activities in plant physiological processes. In our previous study, we reported that exogenous RA application could delay tomato fruit ripening by inhibiting ripening-associated ethylene production and modulating cellular redox homeostasis [24]. Treating with RA nanoparticles substantially reduced the disease severity of tomato fruits infected with phytopathogenic fungi Alternaria alternata and Penicillium digitatum during postharvest storage [25]. In addition, plant-derived RA was identified as a mimic of bacteria quorum-sensing molecule homoserine lactone, enabling strategic disruption of bacterial communication [26]. Aside from the effective function of RA on plant-microbe interaction, in the present study, we found that RA also plays a positive role in high-temperature stress tolerance. Similarly, a previous study suggested induced accumulation of phenolic compounds was associated with plant tolerance to environmental stresses [27]. Due to global warming, the threat of extremely high temperature to plant quality and yield is a world issue. When plants undergo high-temperature stress, changes in plasmalemma permeability induce osmolytes as a part of plant defense systems to effectively protect plants from stressful conditions. Osmolytes are low-molecular-weight biological compounds, including plant hormones, amino acids, sugars, methylamines, and polyphenol [28]. A series of studies showed that exogenous application of osmolytes alleviated the high temperature-induced plant wilting and enhanced the plant tolerance to high-temperature stress. Here, we reported that RA application increased tomato plant tolerance to high temperatures by protecting the plant photosystem from the damage of high-temperature stress (Figure 1a–c). Meanwhile, activation of phenolic biosynthesis and inhibition of phenolic oxidation was observed in the thermotolerance mechanism. Besides the phenolic compounds, the amino acid proline and γ-aminobutyric acid also could improve plant thermotolerance by activating the antioxidant system to alleviate high temperature-associated oxidative damage [29,30]. Exogenous trehalose effectively protected the chloroplast proteins in wheat plants to increase the photosynthetic capacity under high-temperature stress [31]. Exogenous methyl jasmonate (MeJA) strengthened the thermotolerance of perennial ryegrass (Lolium perenne) by modulating JA-responsive gene expression [32]. Interestingly, an appropriate concentration of MeJA efficiently induced RA accumulation via activating the gene expression associated with the RA synthetic pathway in hairy root cultures of Prunella vulgaris [33]. High-temperature stress is always connected with oxidative damage due to excessive ROS accumulation. Importantly, ROS presents a double-edged sword in plants against high-temperature stress. At low concentrations (30 ppm), H2O2 could enhance antioxidant enzyme activities, protect chlorophyll from degradation, and improve the boll weight and fiber quality of cotton [34]. However, high concentrations of ROS cause cellular damage. As a phenolic antioxidant, RA itself has the capability to scavenge free radicals and chelate prooxidant ions, which is mainly dependent on the number of hydroxyl groups. It is reported that the antioxidant activity of RA is stronger than tocopherol [35]. In this study, we found that RA inhibited high temperature-induced lipid peroxidation, and suppressed ROS over-accumulation (Figure 1d–f). In addition, RA also activated the cellular antioxidant system in plants. RA application further increased the transcript abundance and enzyme activity of enzymatic antioxidants, such as APX, CAT, DHAR, and GR, in response to high temperatures (Figure 2a,b). Moreover, RA protected the reduction status of nonenzymatic antioxidants from being oxidized by high-temperature stress, keeping cellular redox homeostasis during stress conditions (Figure 2c). Similarly, the majority of exogenous osmolytes application enhancing thermotolerance is highly associated with the activation of the antioxidant system. Exogenous application of brassinosteroids, 5-aminolevulinic acid, or citric acid significantly improved the activity of antioxidant enzymes and inhibited ROS production, which eventually strengthened plant thermotolerance [36,37,38]. Aside from excessive ROS scavenging, transcription regulation played a central role in the plant’s high-temperature response and induction of thermotolerance. Based on the RNA-seq data, RA-mediated thermotolerance was highly associated with transcription regulator activity, which implied the promoted effects of RA on the transcript abundance of high temperature-responsive genes of plants in response to high-temperature stress (Figure 4). As we know, when plants were subjected to high-temperature stress, a series of transcription factors would be rapidly induced. For example, HsfA2 plays a fundamental role in the Hsf-mediated high temperature-responsive transcriptional regulation network [39]. Here, we showed that exogenous RA application leads to a significant increase in HsfA2 expression, as well as HSP70 and HSP90 (Figure 2a). The transcription of HSP70 and HSP90 was largely dependent on the activation of HsfA2 [39]. Consistent with gene expression, the protein abundance of HSP70 and HSP90 was also promoted by RA treatment, especially in high-temperature conditions (Figure 3b). As the most abundant HSPs in the eukaryotic cell, HSP70 and HSP90 play a dual function, which not only function as molecular chaperons to inhibit protein misfolding and degradation, but also participated in signal transduction in high-temperature response [40,41]. Besides the Hsf-mediated HSP activation, we also found WRKY transcription factors were also involved in RA-mediated thermotolerance (Figure 4). An increasing number of studies indicated that the gene expression of WRKY transcription factors positively responded to high temperatures. Silencing high-temperature-responsive WRKY40 in pepper plants impaired thermotolerance [42]. Moreover, WRKY40-mediated thermotolerance in pepper relied on the activation of WRKY27b via its phosphorylation by the CDPK29 protein kinase [43]. Similar to RA application, exogenous treatment of the ethylene precursor 1-aminocyclopropane-1carboxylic acid (ACC) induced gene expression of WRKY25, WRKY26, and WRKY33, resulting in a degree of increased thermotolerance in Arabidopsis [44]. However, not all high-temperature-induced WRKY genes played a positive role in thermotolerance. Silencing high-temperature-induced WRKY27 in pepper contributed to a strengthened tolerance of high-temperature stress [45]. Therefore, the function of RA-induced high temperature-responsive WRKY genes in thermotolerance should be investigated in future work. In summary, the data presented here reveal a novel function for RA in the thermotolerance of tomato plants. Prior to initiation of thermotolerance, exogenous RA treatment activated the antioxidant system, the protein accumulation of molecular chaperone HSPs, and the high temperature-responsive transcriptional regulation. However, the exact mechanism of how the endogenous RA metabolic pathway in tomato plants responds to high-temperature stress needs further studies. 4. Materials and Methods 4.1. Plant Material and Growth Condition The tomato (Solanum lycopersicum L. cv. Condine Red) was used as test material in this study. Tomato seeds were incubated in a 50-hole plug tray covered with turf soil at 25 °C. after a 2-week germination time, individual tomato seedling was then transferred to one plastic pot filled with a sterile 7:3 (v/v) mixture of peat and vermiculite and subjected to the following controlled growth conditions: temperatures of 25 °C/21 °C (day/night), a photoperiod of 12 h/12 h (day/night), a photosynthetic photon flux density of 400 μmol m−2 s−1, and relative humidity of approximately 60%. 4.2. RA Pretreatment and Temperature Treatments RA powder was purchased from Aladdin (China) and diluted by dH2O to a working solution of 2 mmol L−1. For the exogenous RA application assay, both the abaxial and the adaxial surfaces of the leaves of 5-week-old tomato plants were uniformly treated with foliar sprays of 2 mmol L−1 RA or dH2O as a control twice per d for three days before different temperature treatments. For in planta temperature treatments, the pretreated plants were placed in growth chambers and exposed to high (42 °C) or normal temperature (25 °C). The other environmental parameters except for temperature in the growth chambers were maintained as previous growth conditions. 4.3. Thermotolerance and ROS Analysis After different temperature treatments, the plant chlorophyll fluorescence was measured with a chlorophyll fluorometer (IMAG-MAXI; Heinz Walz GmbH, Effeltrich, Germany). The maximum quantum yield of PSII (Fv/Fm) was analyzed as previously described [14]. For the electrolyte leakage analysis, leaf samples were rinsed with dH2O three times and maintained at room temperature (25 °C) for 2 h after 10 min of vacuum infiltration. Then, the electrical conductivity (EC1) was measured. After the leaf samples were boiled at 95 °C for 20 min, the electrical conductivity (EC2) was measured when the solution cooled to room temperature [46]. The relative electrical conductivity (REC) was defined as REC (%) = EC1/EC2 × 100. The malondialdehyde (MDA) content was determined by measuring the absorbance at 532 nm by the TBA method [47]. To evaluate the accumulation of ROS, H2O2, and O2•− were measured using 3,3′-diaminobenzidine (DAB) and nitro blue tetrazolium (NBT) staining according to the methods of Hu [48]. For DAB staining, the fresh tomato leaves were incubated in the DAB solution (1 mg mL−1 of DAB in 50 mM Tris-HCl, pH 3.8) in the dark for 6 h at room temperature. For NBT staining, the fresh tomato leaves were incubated in the NBT solution (0.1 mg mL−1 of NBT dissolved in 25 mM HEPES, pH 7.8) for 6 h at room temperature. The stained leaves were subsequently decolorized in 95% ethanol at 95 °C for 20 mins and mounted in lactic acid/phenol/dH2O (1:1:1, v/v/v) before imaging. 4.4. Determination of Antioxidant Enzyme Activity and Antioxidant Contents According to the previous methods [14], 0.3 g of plant samples was collected, added to 3 mL of PBS buffer [50 mM phosphate-buffered saline (pH 7.8), 0.2 mM EDTA, 2 mM AsA, and 2% (w/v) polyvinylpyrrolidone], ground into a homogenate in an ice bath, and then centrifuged at 12,000 rpm for 20 min at 4 °C, and the supernatant was removed. For the determination of antioxidant enzyme activity, catalase (CAT) activity was measured according to the change in absorbance value at 240 nm within 3 mins, dehydroascorbate reductase (DHAR) activity was calculated according to the decrease in absorbance at 290 nm, and the increase at 265 nm, and glutathione reductase (GR) activity was determined according to the rate of decrease at 340 nm. The GR activity and ascorbate peroxidase (APX) activity were determined by the UV absorption method. To determine the antioxidant concentrations, 0.3 g of fresh leaf samples were ground into a powder and extracted in 2 mL of 0.2 M HCl. Afterward, the mixture was centrifuged at 12,000× g at 4 °C for 10 min. Then, 0.1 mL of 0.2 M phosphate-buffered saline buffer (pH 5.6) was added to 0.5 mL of the supernatant (pH 4–5), which was used to measure both the AsA and GSH through photometric assays [49]. 4.5. Plant Total RNA Extraction and qRT–PCR Measurements The extraction of plant total RNA was performed in accordance with the operation steps of the Plant Total RNA Extraction Kit (Aikerui Biological, Changsha, China). Then, the synthesis of cDNA was performed in accordance with the operation steps of the ReverTra Ace qRCP RT Kit (Toyobo, Osaka, Japan). qRT-PCR was carried out on a fluorescence quantitative PCR Light Cycler 480II platform (Roche). The reaction conditions were the same as those in the instructions of an AceQ qPCR SYBR Green Master Mix Fluorescent Dye Kit (Vazyme), which we used. Primer 5.0 software was used for the design of qRT–PCR primers. The sequences of the specific primers used are shown in Table 1. The internal reference gene Actin of tomato was selected as the internal reference index for fluorescence quantification, and the relative gene expression was calculated according to the 2−ΔΔCT method. 4.6. Western Blot Analysis For protein extraction, 0.3 g leaf sample was ground to powder in liquid nitrogen, and then homogenized with 2 mL extraction buffer (5 mM EDTA, 10 mM DTT, 10 mM Na3VO4, 10 mM NaF, 50 mM β-glycerophosphate, 1 mM PMSF, 100 mM HEPES, pH 7.5). After centrifugation at 13,000× g for 10 min, 100 μL of the supernatants were transferred to clean tubes supplemented with 20 μL 5× SDS loading buffer (5% SDS, 50% glycerol, 0.05% bromophenol blue, 225 mM Tris-HCl, pH 6.8). The extracted soluble proteins were denaturized by boiling before western blot analysis. The HSP proteins were detected by immunoblot analysis with specific antibodies against HSP70 (Agrisera, Vännäs, Swedish, AS08371) and HSP90-1 (Agrisera, Vännäs, Swedish, AS08346). The secondary antibody used subsequently was goat anti-rabbit horseradish peroxidase (HRP)-linked antibody (Cell Signaling Technology, Danvers, MA, USA, 7074). 4.7. RNA-Seq Analysis Three independent repeats from RA and H2O pretreated five-week-old plants were performed for RNA-seq analysis. After 1-day growth under normal temperature (25 °C) or high temperature (42 °C), the leaves samples were collected. The extraction of plant total RNA was performed in accordance with the operation steps of the Plant Total RNA Extraction Kit (Aikerui Biological, Changsha, China). After the quality test, the cDNA library was constructed using Illumina’s NEBNext® UltraTM RNA library ion kit, and then use the Illumina sequencing platform for transcriptome analysis by Nuohezhiyuan Technology Company (Beijing, China). 4.8. Statistical Analysis The test results are the average of 3 replications. Significant difference analysis was performed by SPSS. ANOVA and Tukey’s test was used to calculate the means, and graphs were constructed by GraphPad Prism. 5. Conclusions The data presented here indicate that exogenous RA application enhances thermotolerance in tomato plants via promoting an antioxidant system, high temperature-responsive transcription regulation, and HSPs accumulation. To sum up, this study not only provides an underlying mechanism of RA-mediated thermotolerance in tomato plants, but also supplies a promising strategy that can potentially protect crops from high-temperature stress in global warming future. Acknowledgments The authors would like to thank Zhenyu Qi (Zhejiang University) for their assistance with greenhouse management. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants11091172/s1, Table S1: High temperature-responsive genes in tomato; Table S2: The RA-induced higher temperature-responsive genes in tomato plants; Table S3: List genes of different GO categories analyzing with RA-induced high temperature-responsive genes. Click here for additional data file. Author Contributions J.Y. and Z.H. designed the research; Z.Z., J.L., C.Z., and B.J., performed the experiments; Z.Z., J.L., C.Z., and K.S. analyzed the data; Z.Z. and Z.H. wrote the article with contributions from other authors. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the Zhejiang Provincial Natural Science Foundation of China (LY22C150002), the Key Research and Development Program of Zhejiang Province (2021C02040), the National Natural Science Foundation of China (31902097), and the Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study (SN-ZJU-SIAS-0011). 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 Effect of RA in tomato thermotolerance. (a) Representative images of tomato plants as influenced by RA and high-temperature treatment. Five-week-old tomato plants were pretreated with 2 mmol L−1 RA or dH2O control once per day for three successive days. Then, the plants were subjected to normal temperature (25 °C) or high temperature (42 °C) for 12 h. (b) The electrolyte leakage of tomato leaves after 12 h of different temperature treatments. (c) The representative leaf images show the Fv/Fm value after 12 h of different temperature treatments. The color gradient scale on the right indicates the magnitude of the fluorescence signal represented by each color. (d) the MDA content in tomato leaves after 12 h of different temperature treatments. (e) Representative images of H2O2 accumulation as determined by DAB staining. (f) Representative images of O2•− accumulation as determined by NBT staining. The data presented in (b–d) are the mean values ± SD, n = 3. Statistically significant differences between treatments (p < 0.05, Tukey’s test) are shown by different letters. Figure 2 RA treatment activates the antioxidant system in tomato plants during high-temperature stress. (a) Effects of RA treatment on transcript abundance of antioxidant enzyme-encoding genes in tomato plants subjected to normal temperature (25 °C) or high temperature (42 °C) for 1 h. APX encodes an ascorbate peroxidase, CAT encodes a catalase, DHAR encodes a dehydroascorbate reductase, and GR encodes glutathione reductase. (b) Effects of RA treatment on enzyme activity of antioxidant enzymes in tomato plants subjected to different temperature conditions for 6 h. (c) Effects of RA treatment on AsA content in tomato plants subjected to different temperature conditions for 6 h. (d) Effects of RA treatment on GSH content in tomato plants subjected to different temperature conditions for 6 h. (e) Effects of RA treatment on AsA/DHA ratio in tomato plants subjected to different temperature conditions for 6 h. (f) Effects of RA treatment on GSH/GSSG ratio in tomato plants subjected to different temperature conditions for 6 h. The data presented are the mean values ± SD, n = 3. Statistically significant differences between treatments (p < 0.05, Tukey’s test) are shown by different letters. Figure 3 RA treatment promotes the transcription and protein abundance of tomato HSPs in response to high temperatures. (a) Effects of RA treatment on transcript abundance of HsfA2, HSP70, and HSP90 in tomato plants subjected to normal temperature (25 °C) or high temperature (42 °C) for 1 h. (b) Effects of RA treatment on the protein abundance of HSP70 and HSP90 in tomato plants with 6 h of different temperature treatments. The data presented are the mean values ± SD, n = 3. Statistically significant differences between treatments (p < 0.05, Tukey’s test) are shown by different letters. Figure 4 RA globally regulates high temperature-responsive gene expression in tomato plants. (a) Numbers of differentially high temperature-changed (fold change ≥ 2, p < 0.05) genes in RA-pretreated or dH2O-pretreated tomato plants, respectively. The color gradient scale on the right indicates the relative expression of each gene represented by each color. (b) Venn diagram exhibiting the numbers of high temperature-induced genes (fold change ≥ 2, p < 0.05) in RA-pretreated and dH2O-pretreated tomato plants. (c) Heatmap of high temperature-induced genes (fold change ≥ 2, p < 0.05) in RA-pretreated and dH2O-pretreated tomato plants. (d) GO analysis of RA-induced high temperature-responsive genes. (e) Heatmap of the induction fold of WRKY genes by high temperature in RA-pretreated and dH2O-pretreated tomato plants. (f) RT-qPCR analysis confirming transcript abundance of selected WRKY genes. The data presented in (f) are the mean values ± SD, n = 3. Statistically significant differences between treatments (p < 0.05, Tukey’s test) are shown by different letters. plants-11-01172-t001_Table 1 Table 1 Gene-specific primers designed for qRT-PCR analysis. Gene Name Gene ID Forward Primer, 5′-3′ Reverse Primer, 5′-3′ Actin Solyc03g078400 TGTCCCTATTTACGAGGGTTATGC CAGTTAAATCACGACCAGCAAGAT APX Solyc11g018550 CGCCATATCACACAAGAAGC TAACTCAGAGCCACCACTGC GR Solyc09g065900 GATGATGAAATGCGAGCTGT TTGTGTTAGGGAGACGACCA DHAR Solyc05g054760 CCCTGATGTCCTTGGAGACT AAGAACCATTTGGGCTTGTC CAT Solyc12g094620 TGATCGCGAGAAGATACCTG CTTCCACGTTCATGGACAAC HSP90 Solyc06g036290 TGTGGGTTTCTACTCTGCGT CTGCCCAATTGCTCTCCATC HSP70 Solyc09g010630 CAAGCTGAAAGAGCTCAAGG CTGTCCCAGCTGCATTACTT HsfA2 Solyc09g082670 TCTGTTGTGACAGCAAATGG TACTTCCTCTGCTGCTCGAT WRKY10 Solyc12g096350 TGGCTGAAGACGGAGGGATA ACGTTTGAAGCCATAGGGATCT WRKY33 Solyc09g014990 CCAAACCGAGACTCGTCCAA CGAATCCTGTGGTGCTCTGT WRKY41 Solyc01g095630 ATTGGGAGCGGAGGAGTTTG ACGATGGAGAAGACGAACCC WRKY46 Solyc08g067340 GCACGCATCGATTCACACAA CCACAACCAATCCTGTCCGA WRKY55 Solyc04g072070 CCGTTGATGGTGGTGGAGAA TCTTGGCCGGGCAATTGTAT WRKY81 Solyc09g015770 GGTCAAGTCGCCGGAAGATT AACATCGGGCGAGGTCATAC Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095282 ijms-23-05282 Review Role of Vitamin K in Chronic Kidney Disease: A Focus on Bone and Cardiovascular Health https://orcid.org/0000-0002-0467-4921 Bellone Federica 1† https://orcid.org/0000-0002-7694-1259 Cinquegrani Maria 1† Nicotera Ramona 2 Carullo Nazareno 3 https://orcid.org/0000-0003-2294-0768 Casarella Alessandro 3 Presta Pierangela 3 https://orcid.org/0000-0002-7974-3792 Andreucci Michele 3 Squadrito Giovanni 1 https://orcid.org/0000-0003-0272-2237 Mandraffino Giuseppe 1 Prunestì Marcello 2 Vocca Cristina 3 https://orcid.org/0000-0002-7629-6579 De Sarro Giovambattista 3 Bolignano Davide 3 https://orcid.org/0000-0001-8000-0681 Coppolino Giuseppe 3* Fusco Roberta Academic Editor Ranzato Elia Academic Editor Uberti Francesca Academic Editor Toldrá Fidel Academic Editor 1 Department of Clinical and Experimental Medicine, University of Messina, I-98100 Messina, Italy; federica.bellone@unime.it (F.B.); mariacinquegrani@gmail.com (M.C.); giovanni.squadrito@unime.it (G.S.); giuseppe.mandraffino@unime.it (G.M.) 2 Azienda Sanitaria Provinciale di Catanzaro, I-88100 Catanzaro, Italy; ramona.nicotera@gmail.com (R.N.); prunestim@gmail.com (M.P.) 3 Department of Health Sciences, “Magna Graecia” University, I-88100 Catanzaro, Italy; nazareno.carullo@gmail.com (N.C.); al.cas1993@gmail.com (A.C.); piera.presta@gmail.com (P.P.); andreucci@unicz.it (M.A.); cristina.vocca@studenti.unicz.it (C.V.); desarro@unicz.it (G.D.S.); dbolignano@unicz.it (D.B.) * Correspondence: gcoppolino@unicz.it † These authors contributed equally to this work. 09 5 2022 5 2022 23 9 528229 3 2022 07 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/). Chronic kidney disease (CKD) is commonly associated with vitamin K deficiency. Some of the serious complications of CKD are represented by cardiovascular disease (CVD) and skeletal fragility with an increased risk of morbidity and mortality. A complex pathogenetic link between hormonal and ionic disturbances, bone tissue and metabolism alterations, and vascular calcification (VC) exists and has been defined as chronic kidney disease–mineral and bone disorder (CKD-MBD). Poor vitamin K status seems to have a key role in the progression of CKD, but also in the onset and advance of both bone and cardiovascular complications. Three forms of vitamin K are currently known: vitamin K1 (phylloquinone), vitamin K2 (menaquinone), and vitamin K3 (menadione). Vitamin K plays different roles, including in activating vitamin K-dependent proteins (VKDPs) and in modulating bone metabolism and contributing to the inhibition of VC. This review focuses on the biochemical and functional characteristics of vitamin K vitamers, suggesting this nutrient as a possible marker of kidney, CV, and bone damage in the CKD population and exploring its potential use for promoting health in this clinical setting. Treatment strategies for CKD-associated osteoporosis and CV disease should include vitamin K supplementation. However, further randomized clinical studies are needed to assess the safety and the adequate dosage to prevent these CKD complications. kidney vitamin K phylloquinone menaquinone cardiovascular disease calcification hypertension osteoporosis bone fracture This research received no external funding. ==== Body pmc1. Introduction Chronic kidney disease (CKD) is characterized by simultaneous vascular calcifications and impaired bone metabolism [1]. Particularly, an imbalance of the bone–vascular axis with consequent alterations of both vascularization and bone have been demonstrated [2]. Even though the mechanistic link of this crosstalk between the vascular and skeletal system is poorly understood so far, some hormones, including parathyroid hormone (PTH) and 1,25-dihydroxy vitamin D3, are acknowledged to orchestrate both skeletal and vascular mineralization as well as stem cell regeneration [3]. Therefore, the term “calcification paradox” was coined to indicate the association of ectopic mineralization in the vasculature with impaired bone turnover and decreased bone mineral density (BMD) [4]. In the last years, the knowledge about the key role of vitamin K has exponentially increased, due to its well-recognized involvement in vascular calcifications, cardiovascular disease, and bone tissue impairment. Recently, growing evidence seems to suggest that vitamin K supplementation could be a tool to prevent the rapid progression of vascular calcifications and to preserve bone health in CKD patients [5]. In this context, we aimed to focus on the current knowledge on vitamin K biological functions, its involvement in the relationships among cardiovascular disease (specifically in hypertensive patients) and bone metabolism in CKD patients, and the potential use of Vitamin K vitamers for promoting health in this clinical setting. 2. Methods Search Strategy A scoping review of the available literature was conducted. Firstly, the studies were retrieved from the online databases PubMed, Scopus, and Web of Knowledge, by matching the following keywords: “chronic kidney disease”, “vitamin K”, “vascular calcification”, “bone metabolism”, “osteoporosis”, and “cardiovascular disease”. A preliminary filter on the online search was applied by language (English) and availability of full text articles. Additionally, the reference lists of the included studies were examined in order to identify further potentially relevant studies missed during the database search. The online search was definitively completed on 15 March 2022. 3. Vitamin K: Chemistry, Nutritional Sources, Distribution and Metabolism The term vitamin K, or naphthoquinone, refers to a family of fat-soluble molecules which have a similar structure made by a 2-methyl-1,4-naphthoquinone ring but with different origin and function. Currently, three primary forms are known, defined as vitamers, which differ in the side chains linked to the 2-methyl-1,4-naphthoquinone ring at the position 3 [6]; namely, these are vitamin K1 (phylloquinone), vitamin K2 (menaquinone), and vitamin K3 (menadione). The main known biological function of vitamin K1 is played in blood clotting, since it acts as a cofactor for the enzymatic conversion of glutamic acid (Glu) residues to gamma-carboxyglutamic acid (Gla) in vitamin K-dependent proteins (VKDPs), through vitamin K-dependent gamma-glutamyl carboxylase, localized in the endoplasmic reticulum of the cells of all mammalian tissues [7,8,9], and for the conversion of protein-bound glutamate in carboxy-glutamate, needed for II, VII, IX, and X coagulation cascade factors, and for the natural anticoagulants proteins S and C [10,11]. The source of vitamin K1 is mainly represented by leafy or flowering vegetables (spinach, lettuce, broccoli, cabbage, Brussels sprouts, turnip greens), but chickpeas, peas, soya, green tea, eggs, pork, and beef liver also contain vitamin K1 [12]. Vitamin K2 is synthetized essentially by intestinal microbiota and is denoted as menaquinone (MK); according to the length of the isoprene chain attached to the methylated naphthoquinone ring, several different forms could be identified, as numbered from 4 to 13. MK-4 is obtained from the conversion of phylloquinone or menadione and is found mainly in meat and animal by-products such as eggs, cow’s milk and yoghurt [13,14,15]. On the other hand, MK-7 is a long-chain form also produced by intestinal bacteria and it is found in fermented food, such as cheese and soya [16]. The MK4 and MK7 are two of the most common menaquinones in the human diet, along with MK8, MK9, and MK10 [13]. Vitamin K3, also known as menadione, was formerly considered to be a synthetic form of vitamin K. However, it has been demonstrated that vitamin K3 could also originate in the intestine as the intermediate product of oral vitamin K1 conversion to vitamin K2, namely MK4 [17,18]. Vitamin K absorption occurs in different tracts of the intestine: vitamin K1 is absorbed in the ileum; vitamins K2 in the colonic portions. Efficient biliary and pancreatic function is essential for its adequate absorption. Vitamin K molecules are incorporated into chylomicrons and then released to very low-density lipoprotein (VLDL) and low-density lipoprotein (LDL), with subsequent release to tissues. Vitamin K1 and K2 should be continually synthetized and supplied by intestinal bacteria, due to their relatively short half-life (17 h). The catabolism of vitamin K1 and of vitamin K2 shares common mechanisms, beginning with initial hydroxylation mediated by CYP4F2, followed by shortening of the polyisoprenoic side chain via b-oxidation to carboxylic acids (in 5 C, 7 C, or 10 C metabolites), which are glucuronidated and excreted in urine and bile [7,19,20]. In healthy people, fasting plasma phylloquinone concentrations have been reported to range from 0.29 to 2.64 nmol/L [21]. However, to evaluate serum levels of vitamin K is difficult to perform, as they are influenced by several factors (e.g., low plasma levels, non-polar nature, and lipid interference). Diet and inflammation are additional variables influencing the plasma levels. Therefore, vitamin K levels are often estimated indirectly by measuring prothrombin time (for vitamin K1) or the concentration of decarboxylated γ-carboxyglutamic acid (Gla) proteins (not available for all laboratories) [22,23]. The intake recommendations for vitamin K by the World Health Organization (WHO) and the Food and Agriculture Organization (FAO) are 65 mcg/day for men and 55 mcg/day for women, based on a calculated requirement of 1 mcg/day/kg body weight. The Italian Society of Human Nutrition (SINU) recommended an age-stratified intake of vitamin K: 140 mcg/day or 170 mcg/day for people aged 18–59 and >60-years, respectively [24]. Vitamin K deficiency is correlated with increased rate of cardiovascular events [7]. Observational studies showed an inverse relationship between vitamin K2 and vascular calcifications (VC) [25], while vitamin K1 intake was not significant [26]. Notwithstanding, Xu et al., recently analyzed prospective clinical trials involving CKD people with the aim to investigate which kind of intervention could attenuate VC, evaluated through radiologic methods. They concluded that conflicting data exist regarding vitamin K therapy in CKD and VC progression [27]. Vitamin K is also important for the regulation of the glycemic status by reducing the risk of developing diabetes mellitus and improving insulin sensitivity. Vitamin K2, on the other hand, plays a predominant role in bone development, vascular protection, metabolic, liver and renal diseases. In this regard, vitamin K2 is needed for the synthesis of osteocalcin in the bone and matrix GLa protein in the cartilage and in the blood vessels wall. Thus, it plays a pivotal role in calcium transport, preventing calcium deposition in blood vessels and calcium mobilization from bone tissues [11]. 4. Vitamin K and Chronic Kidney Disease Chronic kidney disease (CKD) patients are characterized by poor vitamin K status [28]. Multiple factors can affect vitamin K stores in CKD patients, and the main causes of its deficiency include food restriction, uraemia-associated dysbiosis, and drugs [29,30,31]. Moreover, dietary restriction due to the high potassium content in most vitamin K-rich, green vegetables contributes to its deficiency [12]. Alongside dietary intake, vitamin K is recycled through the “vitamin K cycle”, which includes vitamin K epoxide reductase, DT-diaphorase and g-glutamylcarboxylase. Reduced recycling of vitamin K was found in rats with CKD, likely caused by the reduced activity of g-glutamyl-carboxylase, with a mechanism similar to the coumarins [32,33]. Patients affected by CKD are known to have increased risk of developing vascular calcification (VC) and bone fractures [34], which in turn contribute to the higher morbidity and mortality rate in CKD patients [34,35]. Several reports suggested that vitamin K2 may play a key role both in pathogenesis and prevention of those serious complications [36,37]. A cross-sectional observational study, the VIKI (Vitamin K Italian) study, evaluated the association between vitamin K reserves, vertebral fractures, and vascular calcifications, highlighting the prevalence of vitamin K deficiency in a setting of 387 hemodialysis patients. VK1 deficit resulted the strongest predictor of vertebral fractures (odds ratio [OR], 2.94; 95% confidence interval [CI], 1.38–6.26), while the deficiency of MK-4 was a predictor for aortic calcification (OR, 2.82; 95% CI, 1.14–7.01) [38]. Hemodialysis treatment, sevelamer (a phosphate binder) or vitamin K Antagonists (VKA) represent the major iatrogenic causes of vitamin K deficiency in patients with chronic renal failure [39]. CKD patients, including those on hemodialysis treatment, often use VKA drugs, especially for stroke prophylaxis in atrial fibrillation (AF). Warfarin, thus, can predispose to fragility fractures and vascular calcification through different mechanisms: directly, by inhibiting the carboxylation of osteocalcin (bone Gla protein or BGP) and other bone matrix proteins, and indirectly, because of the reduced dietary intake of foods rich in vitamin K in warfarin-users [40]. Currently, the non-vitamin K oral anticoagulants (NOACs) are being largely used to prevent stroke and cardioembolic complications in AF patients instead of vitamin K antagonists. However, their use in advanced CKD and end stage renal disease (ESRD) is to date contraindicated [41]. Indeed, Siontis et al., observed less bleeding with the standard dose (5 mg × 2/day) of apixaban than vitamin K inhibitor as well as a reduction in the risk of thromboembolism in a retrospective cohort study involving ESRD patients with AF [42]. Vitamin K2 reduced bioavailability due to phosphate binders (PBs) may be different according to the binder and to the type of menaquinone [39,43,44,45]. Neradova et al., verified the possible binding action of different PBs on vitamin K2 (MK-7) [44]. Calcium acetate/magnesium carbonate binds vitamin K2 regardless of the presence of phosphorus, lanthanum carbonate only in the absence of phosphorus, whereas sucroferric oxyhydroxide and sevelamer carbonate do not bind vitamin K2 in vitro [44]. Interestingly, a more recent investigation using a rat model by Neradova et al., showed that the combination of high vitamin K2 diet and PBs treatment significantly reduced VC, compared to MK7 or PBs treatment alone [40]. However, the use of sevelamer was significantly correlated with MK-4 deficiency, as well as warfarin administration [39]. The chemical reason has not yet been investigated, assuming that these are bonds mostly due to the form of the chelator [44]. On the other hand, a synergistic action of calcium mimetics and vitamin D analogues with vitamin K supplementation has been demonstrated more beneficial compared to the administration of each of these vitamins individually, with special reference to bone health [46]. Similar considerations can be applied to the complex setting of kidney transplantation (KT) patients [6]. In fact, impaired cardiovascular health related to vascular calcifications could be linked to a low vitamin K status also in KT recipients. An association between thoracic aorta calcification and shorter time on mycophenolate mofetil (MMF) treatment, an immunosuppressive agent, with current use of anti-vitamin-K has been previously suggested, confirming lower dp-ucMGP levels in KT patients receiving MMF therapy. This result is certainly also attributable to the improvement of the nutritional status and the greater contribution of the micronutrient [47]. 4.1. Vitamin K: A Potential Role in the Development and Progression of CKD Low peripheral vitamin K status has been previously associated with proteinuria and CKD stage [48]. The decarboxylated matrix protein Gla (dp-ucMGP) was used as an indirect marker for the determination of vitamin K concentrations on 3969 individuals with a mean age of 52.3 ± 11.6 years (48% male), enrolled in the “Prevention of Renal and Vascular end-stage Disease” [49,50]. The outcomes of this research were represented by the diagnosis of CKD (estimated Glomerular Filtration Rate (eGFR) <60 mL/min/1.73 m2) or the occurrence of microalbuminuria. During the 7.1 years of follow-up, 205 (5.4%) participants developed CKD and 303 (8.4%) developed microalbuminuria. For each doubling of plasma decarboxylated matrix protein Gla, the risk of onset of CKD and microalbuminuria was 1.85 [95% confidence interval (CI) 1.59–2.16, respectively; p < 0.001] and 1.19 (95% CI 1.07–1.32; p = 0.001), suggesting a possible prognostic value of dp-ucMGP in CKD, as it could imply a role for poor vitamin K status in the development of chronic renal failure [51]. In a recent analysis, it was already documented that both the deficiency of vitamin K and 25 OH-vitamin D, in almost equal measure, was associated with the progression of renal function decline and with the increased albumin/creatinine urinary excretion ratio [48]. Moreover, vitamins D and K have been suggested to cooperate in exerting favorable properties on bone protection, slowing VC progression, and in improving cardiovascular health [52].On the other hand, Kurnatowska et al., also highlighted a higher concentration of dp-ucMGP in patients with CKD, especially in stage V. The administration of vitamin K2 (90 mcg/day) resulted in a reduction in dp-ucMGP levels. Interestingly, plasma dp-ucMGP concentrations inversely correlated with eGFR and directly correlated with proteinuria and serum creatinine [53]. How vitamin K can be nephroprotective, also in reducing proteinuria, is still not fully understood and further evidences are needed. 4.2. CKD-MBD Chronic kidney disease–mineral bone disorder (CKD-MBD) is a term used to identify the deterioration of bone quality and the consequent development of disorders in bone and mineral metabolism induced by impaired kidney function [54]. This inevitably places CKD patients, particularly those on hemodialysis, at higher risk of fracture, as compared to the general population [55]. Bone remodeling is a continuing dynamic process performed mainly by the two antagonistically acting cells, osteoblasts, which regulate the bone formation, and osteoclasts, responsible for the bone resorption process [56,57]. Several studies (both in vivo and in vitro) have proved that vitamin K is directly involved in bone metabolism. Some of these demonstrated that vitamin K2 inhibits bone resorption probably, in part due to the reduced production of bone resorbing substances including prostaglandin E2 and interleukin 6. It has also been shown that vitamin K is able to promote human osteoblast-induced bone mineralization in vitro, and to inhibit bone loss in steroid treated or ovariectomized rats [58]. Vitamin K2 is also a cofactor for some proteins involved in bone mineralization, namely osteocalcin (bone Gla protein or BGP) and matrix Gla protein (MGP) [59]. BGP is a small protein of 5.6 kDa, consisting of 49 amino acids, which is produced in bone by osteoblasts and minimally secreted into the circulation. As the matrix Gla protein, it is found in carboxylated and decarboxylated forms [60]; their serum levels are affected by age and hormonal status. Both forms increase with age, but after the menopause decarboxylated osteocalcin predominates [61]. It is mainly involved in the formation of hydroxyapatite and the consolidation of bone mass, but is shown to have various extraskeletal functions on glucose and energy metabolism, reproduction, and cognitive function [62]. In fact, it also stimulates the release of insulin by acting directly on the pancreas and indirectly inducing the secretion of glucagon-like peptide 1 (GLP-1) and adiponectin in the small intestine, taking part in glucose metabolism [63]. Interestingly, BGP has also been shown to stimulate angiogenesis and to upregulate nitric oxide (NO) signaling in endothelial cells, suggesting a protective role of this protein on reducing the risk of cardiovascular diseases [64,65]. MGP is a 10.6 kDa protein, consisting of 84 amino acids, insoluble in water. It is mainly synthesized by smooth muscle cells and chondrocytes and secreted into the extracellular matrix. It inhibits calcification and is only activated after the process of carboxylation and phosphorylation. Vitamin K, as a cofactor, facilitates its carboxylation at 5 glutamic acid residues at positions 2, 37, 41, 48, and 52 by γ-glutamyl carboxylase; in addition, 3 serine residues are phosphorylated at positions 3, 6, and 9 by casein kinase. The process of inhibiting vascular calcification would take place through the binding of calcium ions by carboxyl groups [66,67]. Gla-rich protein (GRP) has a molecular weight of 10.2 kDa and consists of 74 amino acids. Like other matrix proteins, GRP is vitamin K dependent and inhibits vascular calcifications, acting similarly to the matrix Gla protein, by binding and sequestrating calcium ions [68]. Growth Arrest Specific Protein 6 (GAS6) is a 75 kDa protein, activated in a vitamin K-dependent carboxylation process. GAS6 is mainly involved in the control of cell growth and proliferation and is secreted by osteoblasts to the bone matrix [69]. In detail, unlike the other VKDPs, GAS6 has been shown to increase osteoclast activity thus promoting bone resorption [70]. In CKD, starting from stage IIIA, the impairment of bone tissue can present with high or low bone turnover, leading to a higher risk of fractures [71]. The different clinical pictures can be delineated in relation to parathyroid hormone (PTH) levels and bone turnover: hyperparathyroid osteopathy, or high turnover-osteopathy; this is characterized by secondary hyperparathyroidism, osteomalacia and osteoporosis, and adynamic bone disease (ABD), with the latter consisting of low PTH levels and decreased bone turnover, low bone volume but with normal mineralization, and markedly reduced cellularity with minimal or no fibrosis [72]. In addition to PTH, vitamin D, calcium and phosphorus, fibroblast growth factor-23 (FGF-23), sclerostin, and Klotho play a role in CKD-MBD (Figure 1) [71,73]. The increased bone sclerostin expression may also play a role in the improved FGF-23 expression, as it was proved to upregulate FGF-23 [74,75]. Furthermore, Bolignano et al., previously demonstrated that Cathepsin-K, a lysosomal cysteine protease secreted by activated osteoclasts and promoting bone and extracellular matrix remodeling, was associated with PTH levels, in a setting of 85 chronic hemodialysis patients, suggesting that this protein could represent a biomarker of CKD-MBD severity and PTH levels [76,77,78,79,80]. Vitamin K2 appears to be involved in this intriguing molecular interplay [24,81,82]. In research conducted on 210 women with osteoporosis, after six months treatment with vitamin K2, all indicators of metabolism and bone density had significantly increased, suggesting osteogenic activity. Others studies confirmed this evidence [83]. In addition, vitamin K2 counteracts osteoclastic activity. Rangel et al., demonstrated an increase in bone mass in ovariectomized mice supplemented with vitamin K [84]. On the same basis, 374 postmenopausal women with osteoporosis had more fractures with an impaired bone strength if they presented with vitamin K deficiency [85]. In a prospective work on 241 osteoporotic patients of both sexes, the administration of 45 mg/day of vitamin K2 resulted in a significant reduction in fractures [86]. An interesting question was also raised about a possible advantage from the vitamin K2-25OH vitamin D3 combination. Matsunaga et al., showed that the combined treatment seems more effective than single administrations in preventing bone loss on the femoral shaft and in the tibial metaphysis in ovariectomized rats [87]. Studies on the hemodialysis population are currently still few but all of the evidence suggest that vitamin K deficiency is an independent predictor of fracture risk [88,89,90]. 4.3. Vitamin K and Hypertension in CKD CKD patients with inadequate total vitamin K intake (both K1 and K2) had higher cardiovascular and all-cause mortality than those with adequate intake [91]. Vitamin K deficiency was acknowledged as independent predictor of cardiovascular disease (CVD) risk [92]. Moreover, Vitamin K2 deficiency or vitamin K functional inhibition by warfarin administration leads to calcium deposition in the arterial blood vessels [13]. Furthermore, vitamin K2 was shown to slightly increase HDL cholesterol and to decrease systemic inflammation [93,94]. Consistently, its supplementation could be supposed to slow vascular damage and prevent atherosclerosis, CVD and stroke [95,96,97,98]. Indeed, a connection between higher estimated menaquinone intake (above 21.6 μg/day) and decreased coronary heart disease-related mortality and aortic calcification was found, but there was no such correlation for phylloquinone [99,100,101]. In the PREVEND study, functional vitamin K deficiency was detected in 31% of the whole study population, and the incidence was much higher among the elderly and subjects with comorbidities, such as hypertension, type 2 diabetes, CKD, and cardiovascular disease [102]. Further results from ongoing interventional randomized clinical trials will better clarify if and what dosage vitamin K1 or K2 slows the progression of VC in CKD patients [103,104,105,106]. The international guidelines recommend the maintenance of arterial blood pressure values below 130/80 mmHg to reduce the cardio-renal risk in this type of patients [107]. Vitamin K2 seems to have a supporting role in the treatment of primary hypertension [108,109]. Liu Tian-Hao et al., also investigated the underlying mechanism by resorting to 16S rRNA sequencing, highlighting an influence of vitamin K2 on the complement system, calcium signals, and the renin-angiotensin-aldosterone system (RAAS) in an experimental model of salt-sensitive arterial hypertension [110]. The RAAS involvement in this model of salt-induced arterial hypertension was there confirmed and the administration of vitamin K2 was shown to exert an inhibitory effect on the RAAS-mediated pathways. In the same work, further analysis led to the identification of bacteria, including Dubosiella and Ileibacterium, favorably inducing RAAS modulation [111]. This finding also led to the assumption that probiotic compounds basing on these bacteria could be of help in improving metabolism and immunity also through the increased synthesis of vitamin K2 for the maintenance of endothelial functions [111,112]. To reinforce this thesis, Jensen et al., reported data on 79 hypertensive patients in Oakland showing how consumption of nattokinase-fermented soybean, rich in vitamin K2, is associated with beneficial changes in blood pressure (although diastolic blood pressure only achieved statistical significance, while for the systolic lowering a trend was suggested) [113]. Moreover, a case of hypotension has been reported after the administration of menaquinone [114]. Mansour et al., also showed how, implementing MK-7, mean arterial pressure (MAP) and peripheral diastolic blood pressure (DBP) decreasing [115]. However, blood pressure change on Vitamin K supplementation has been debated, and data are not consistent to date. In fact, observations did not confirm this blood pressure lowering effect [116,117,118,119,120,121]. Definitely, the pathophysiological link between vitamin K status and blood pressure control is not clearly established so far. There are several hypotheses about phylloquinone (VK1). Phylloquinone, as well as vitamin K2, plays a key role in cardiovascular disease. Phylloquinone deficiency has been suggested as a risk factor for incident CVD in older treated hypertensives. Nevertheless, vitamin K1 intake is not seemingly associated with a reduced CVD risk. This could be due to the activities, mainly hepatic, of vitamin K1, whereas vitamin K2 exerts extrahepatic ones. However, vitamin K1 also seems to be involved in extrahepatic activities, and it was suggested to play a role in delaying the arterial stiffening when administered more than 2 mg/die, as well as in reducing vascular calcification [122,123,124], although Bellinge et al., failed to confirm an attenuation of arterial calcification activity through vitamin K1 administration [125]. Notwithstanding, vitamin K1 intake is nowadays out of interest due to its poor positive effects data. Furthermore, vitamin K2 effects appear to be stronger than vitamin K1, also due to its longer half-life and to higher concentrations in extrahepatic tissues of all K2 vitamers [28]. There is no evidence so far about the usefulness of vitamin K3 supplementation in CKD, arterial hypertension, and CVD. Furthermore, high-dose vitamin K3 has been questioned to be potentially toxic (e.g., liver damage, hemolytic anemia, etc.) [18], and its administration in humans is not worldwide recommended. However, vitamin K3 is easily and inexpensively produced, and it is very stable also because is not degraded by light, and low-dose could be used to treat vitamin K deficiency [18,126,127]. By the way, there are still not enough studies regarding its supplementation in these patients. Hypertension is one of the first causes of AF [128,129]. In this cohort of patients, the risk of VC and CVD changes is also related to anticoagulant drug (VKAs vs. NOAC). Several clinical trials have reported that VKAs promote atherosclerotic calcification [97]. In this context, we must clearly look at the risk/benefit ratio. These considerations are even more current in CKD patients. Indeed, in these people, there is an additional risk considering the coexistence of hypertension, CKD, and possible use of VKA (Table 1). 5. Discussion In CKD patients, the parallel occurrence of impaired bone metabolism and CVD has been largely demonstrated; the latter are mostly promoted by VC, which in turn is determined by mineral dysregulation [130]. In detail, phosphate retention occurring in CKD concurs to the conversion of vascular smooth muscle cells to osteoblast-like cells producing bone matrix proteins which regulate arterial wall calcification [131]. Accumulating evidence suggest that this complex “calcification paradox” could be mediated also by vitamin K. Thus, the assessment of vitamin K concentration has been proven to be potentially of crucial importance in CKD patients, with an emerging role of this nutrient abs a marker for incident CVD, CKD development and progression, and consequent CKD-MBD. In this light, vitamin K supplementation should be recommended [52]. Since vitamin K2 has a longer half-life (days) than vitamin K1 (hours), it could be speculated that supplementation with vitamin K2, which is essential for extrahepatic VKDPs, could probably be cheaper [132]. Nevertheless, the use of vitamin K1 could be favorable because of its ability to transform into vitamin K2 but in doses 10 times higher than vitamin K2, so this field remains under debate [124]. Vitamin K toxicity has not been confirmed, and a tolerable upper limit for vitamin K has not been established so far [100], as already reported in the previous recommendations [133]. Although it has been questioned to be potentially toxic due to overcoagulation issues, very high dose intake has been suggested to be paradoxically associated to hypoprothrombinemia in rare human case reports [93,134]. Actually, a consensus about the daily dose needed to prevent the advance of VC or the incidence of fractures in CKD population has not been reached. Notwithstanding, 10 mg for vitamin K1 and 360 mcg/die until over 1080 mcg/die for MK-7 has been proposed as an adequate dosage [6]. So, vitamin K supplementation (especially menaquinone–vitamin K2) could have a protective role on both bone and cardiovascular health in patients with CKD. Indeed, a synergistic interplay has been suggested between vitamins D and K in exerting bone protection properties, as well as in slowing VC progression and in improving cardiovascular health [52]. However, no RCTs have been designed so far in order to explore the combined supplementation in CKD patients. Vitamin K vitamers potential role in affecting the liver, kidney, parathyroid gland, bone, arteries, and heart is depicted in Figure 2. According to a Scientific Opinion provided by the European Food Safety Authority (EFSA), the vitamin K dietary reference values (DRVs) for the European population are estimated to be 1 µg/kg body weight per day of phylloquinone, which corresponds to an amount of 70 µg phylloquinone/day for adults, both women and men. Since data about menaquinones absorption, function and content in the body or organs are limited, EFSA released adequate intake recommendations for phylloquinone only [100]. This amount of phylloquinone could play a role in reduction of CVD progression, especially in Arterial Hypertension acting on arterial calcification activity and arterial stiffening [122,124,125]. There are still not studies about its role in CVD prevention. The National Institutes of Health (NIH) provides its recommendations for intake and administration of Vitamin K vitamers, through the Office of Dietary Supplements [135]. However, there is currently no definitive consensus on how to supplement vitamin K, whether with food or supplements. Few data about the bioavailability of different forms of vitamin K from food exist. The bacterial synthesis contributes in a small way to the production of menaquinones, but its exact support remains unclear [16]. Several multivitamins and/or multimineral supplements currently available contain vitamin K, alone or combined with other nutrients (calcium, magnesium, vitamin D), usually with a content of vitamin K less than 75% of the daily value [17,135]. Further randomized placebo-controlled trials using phylloquinone, menaquinones, or a combination of different vitamers are needed to confirm that maintaining a good vitamin K status could prevent fragility fractures and vascular calcifications in CKD. 6. Conclusions This scoping review provides insights about the prevalence of functional vitamin K insufficiency and its clinical implications in CKD, particularly focusing on bone and CV health, as well as on arterial hypertension and the progression of kidney damage. According to our knowledge, the effect of vitamin K supplementation on arterial hypertension also in the hemodialysis population has never been extensively debated. Ongoing research suggests vitamin K as a new therapeutic approach, although the therapeutic dosage to obtain the benefits of supplementing this nutrient has not yet been firmly defined and further evidence is certainly needed. Hence, based on what emerged from our detailed review of the literature and the complex heterogeneity of the CKD population, a patient-centered strategy should be proposed. Author Contributions Conceptualization, G.C., G.M. and R.N.; methodology, G.M., F.B. and D.B.; validation, G.M., G.C. and G.D.S.; resources, G.C. and C.V.; data curation, F.B. and M.C.; writing—original draft preparation, F.B., M.C., N.C., P.P., A.C. and M.P.; writing—review and editing, G.M. and G.C.; final approval, G.C., G.M., M.A. and G.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 The authors declare no conflict of interest. Figure 1 Complex interplay between kidney, parathyroid glands, bone and cardiovascular system in CKD-MBD pathogenesis. CKD is characterized by a secondary hyperparathyroidism: the progressive reduction of GFR leads to an increase of serum phosphate levels, a progressive hypocalcemia, and augmented FGF-23 production. Meanwhile, the reduced activity of the enzyme 1 alpha-hydroxylase induces a decrease of 1,25-dihydroxyvitamin D, further determining a PTH rising. High serum phosphate and FGF-23 levels also stimulate an increase of sclerostin production by osteocytes. Sclerostin and FGF-23 are involved in the progression of VC. Abbreviations: CKD = Chronic Kidney Disease; FGF-23 = fibroblast growth factor 23; 1, 25 (OH)2D = 1,25-dihydroxy-vitamin D; PTH = parathyroid hormone; SHPT = Secondary hyperparathyroidism; VC = Vascular Calcification. Figure 2 Vitamin K vitamers potential role on liver, kidney, parathyroid gland, bone, arteries, and heart. Potential synergism with vitamin D (on parathyroid, bone, and arteries) is also depicted. ijms-23-05282-t001_Table 1 Table 1 Effects of supplementation of vitamin K and cardiovascular outcome. Study Sample Size and Type of Patients Study Type Vitamin K Assessment and/or Supplementation Cardiovascular Outcome Brandenburg et al. [123] n = 72 patients with asymptomatic or mildly symptomatic AVC 12-month prospective, single-center, open-label, randomized interventional trial VK1 2 mg/d n = 38 PL n = 34 for 12 months Lower progression of AVC by 12% (p = 0.03) after VK1 vs. PL plasma dp-ucMGP by 45% (p < 0.001) in the VK1 group; Geleijnse et al. [99] n = 4807 Women and men aged ≥55 years without MI prospective, population-based study (7–10 years) diet rich in VK1 mean intake of VK1: <200 μg/d, 200–278 μg/d and >278 μg/d diet rich in VK2 mean intake of VK1: <21.6 μg/d, 21.6–32.7 μg/d and >32.7 μg/d VK1—no association with incidents of CHD mortality, all-cause mortality and aortic calcification VK2—reduction of CHD mortality and inverse relation to all-cause mortality and severe aortic calcification Braam et al. [96] n = 181 Healthy postmenopausal Caucasians between 50 and 60 years of age (only female) double-blind RCT vitamin K1 (1 mg) + D3 (8 μg) supplementation Distensibility (+8.8%, p < 0.05) Compliance (+8.6%, p < 0.05) Pulse pressure (−6.3%, p < 0.05) CCA elasticity (−13.2%, p < 0.01) Shea et al. [36] n = 489 hypertension patients under drug treatment prospective longitudinal cohort study K1 K2 Low k1 (<0.2 nmol/die) is risk factor for incident CVD in older men and women treated for hypertension but was not associated with CVD in those not treated for hypertension Beulens et al. [126] n = 564 postmenopausal women between 62 and 72 years of age (only female) cross-sectional study Dietary menaquinone intake (31.6 ± 12.3 mcg/d) High dietary VK2 intake is associated with decreased coronary calcification Knapen et al. [127] n = 244 postmenopausal women (age 59.5 ± 3.3) RCT Menaquinone-7 supplementation (180 mcg/d) Menaquinone-7 supplementation improved arterial stiffness in people with higher baseline stiffness index. Vaccaro et al. [97] n = 5296; age >50 cross-sectional study Dietary phylloquinone intake (women, 90 mcg/d; men, and 120 mcg/d) Inadequate dietary phylloquinone intake was a strong and significant predictor of higher arterial pulse pressure. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094702 ijms-23-04702 Article Integrative Analysis of Expression Profiles of mRNA and MicroRNA Provides Insights of Cotton Response to Verticillium dahliae https://orcid.org/0000-0001-9123-2875 Mei Jun 1 Wu Yuqing 1 Niu Qingqing 1 Miao Meng 1 Zhang Diandian 1 Zhao Yanyan 1 Cai Fangfang 1 https://orcid.org/0000-0003-3626-0296 Yu Dongliang 1 Ke Liping 1 Feng Hongjie 2 https://orcid.org/0000-0002-9178-2487 Sun Yuqiang 1* Voll Lars Matthias Academic Editor 1 Plant Genomics & Molecular Improvement of Colored Fiber Lab, College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China; 15110700054@fudan.edu.cn (J.M.); wuyuqing0104@163.com (Y.W.); qingqingn0403@163.com (Q.N.); miaom@whu.edu.cn (M.M.); devah0322@163.com (D.Z.); zhaoyanyanhao@163.com (Y.Z.); caiff@zstu.edu.cn (F.C.); yudl@zstu.edu.cn (D.Y.); keliping@zstu.edu.cn (L.K.) 2 State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China; fenghongjie@caas.cn * Correspondence: sunyuqiang@zstu.edu.cn 24 4 2022 5 2022 23 9 470224 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/). Cotton Verticillium wilt, caused by the notorious fungal phytopathogen Verticillium dahliae (V. dahliae), is a destructive soil-borne vascular disease and severely decreases cotton yield and quality worldwide. Transcriptional and post-transcriptional regulation of genes responsive to V. dahliae are crucial for V. dahliae tolerance in plants. However, the specific microRNAs (miRNAs) and the miRNA/target gene crosstalk involved in cotton resistance to Verticillium wilt remain largely limited. To investigate the roles of regulatory RNAs under V. dahliae induction in upland cotton, mRNA and small RNA libraries were constructed from mocked and infected roots of two upland cotton cultivars with the V. dahliae-sensitive cultivar Jimian 11 (J11) and the V. dahliae-tolerant cultivar Zhongzhimian 2 (Z2). A comparative transcriptome analysis revealed 8330 transcripts were differentially expressed under V. dahliae stress and associated with several specific biological processes. Moreover, small RNA sequencing identified a total of 383 miRNAs, including 330 unique conserved miRNAs and 53 novel miRNAs. Analysis of the regulatory network involved in the response to V. dahliae stress revealed 31 differentially expressed miRNA–mRNA pairs, and the up-regulation of GhmiR395 and down-regulation of GhmiR165 were possibly involved in the response to V. dahliae by regulating sulfur assimilation through the GhmiR395-APS1/3 module and the establishment of the vascular pattern and secondary cell wall formation through GhmiR165-REV module, respectively. The integrative analysis of mRNA and miRNA expression profiles from upland cotton lays the foundation for further investigation of regulatory mechanisms of resistance to Verticillium wilt in cotton and other crops. cotton Verticillium wilt transcriptome microRNAs network ==== Body pmc1. Introduction Cotton is a worldwide crop that plays a significant role in both the agricultural and industrial economies [1]. As the largest natural textile material, cotton accounts for more than 50% of the fiber sources in the textile industry [2]. However, cotton is susceptible to a variety of biotic and abiotic stresses during its growth, which can severely restrict its productivity. Upland cotton (Gossypium hirsutum L.), which accounts for approximately 97% of all cultivated cotton, is sensitive to pathogens [3]. Verticillium wilt is one of the major cotton yield-limiting factors and is a destructive fungal disease affecting cotton production and quality worldwide [4]. Microsclerotia, present in V. dahliae, can survive in the soil for many years and spread rapidly, making it difficult to control once a cotton infection occurs. The most effective way to control V. dahliae is the development and application of resistant cultivars. Therefore, key resistance genes and regulators need to be identified and the mechanisms mediating disease resistance must be thoroughly characterized to develop V. dahliae-resistant cotton cultivars. Plants have evolved a series of sophisticated regulatory mechanisms to avoid or resist V. dahliae stress. Multiple genes have been identified to play critical roles in response to V. dahliae stress, leading to a better understanding of their associated regulatory mechanisms. The RLK suppressor of BIR1-1 (GbSOBIR1) induced by V. dahliae can interact with and phosphorylate GbbHLH171 and plays a critical role in cotton resistance to V. dahliae [5]. By maintaining fatty acid metabolism pools for jasmonic acid (JA) biosynthesis and activating the JA signaling pathway, patatin-like proteins GhPLP2 promote cotton resistance to V. dahliae [6]. Cotton laccase gene GhLAC15 enhances Verticillium wilt resistance via an increase in defence-induced lignification and arabinose and xylose, which are main components of lignin in the cell walls of plants [7]. GhSWEET42, which encodes a glucose transporter, led to a decrease in glucose content and enhanced resistance to V. dahliae in cotton through glucose translocation [8]. GhWAK7A, a wall-associated kinase, positively regulates cotton response to V. dahliae infections by complexing with the chitin receptors [9]. On the contrary, as a negative regulator of resistance to V. dahliae, calcium-dependent protein kinase GhCPK33 interacts with and phosphorylates 12-oxophytodienoate reductase3 (GhOPR3) in peroxisomes leading to decreased stability of GhOPR3, which consequently limits JA biosynthesis [10]. The protein kinase BIN2 that interacted with JAZ proteins regulated plant endogenous JA content and influenced the expression of JA-responsive marker genes and plays a negative role in plant resistance to V. dahliae [11]. The enhanced resistance in GhIAA43-silenced cotton plants is due to the activation of salicylic acid (SA)-related defenses, and the activated defenses specifically occurred in the presence of V. dahliae, suggesting that GhIAA43 is a negative regulator in cotton defense against V. dahliae attack [12]. In addition, miRNAs, a class of tiny non-coding RNAs, which are considered to be important regulators at the post-transcriptional level, are also efficacious to control the gene expression during V. dahliae induction [13]. In plants, miRNAs act on specific target mRNAs in a complete or near-perfect base-pairing manner, resulting in mRNA degradation or translation inhibition [14]. The available evidence indicates that miRNAs play influential roles in regulating cotton response to V. dahliae. Inoculated with the different V. dahliae strains in upland cotton variety KV-1, a V. dahliae-tolerant cultivar, thirty-seven novel miRNAs were identified after small RNA sequencing [15]. After infection with V. dahliae in susceptible and resistant varieties of cotton, a total of 140 conserved miRNAs and 58 novel miRNAs were identified and 107 genes targeted by 45 miRNA families were detected via small RNA sequencing and degradome sequencing [16]. Recently, the regulatory network model of GhmiR477-GhCBP60A interactions and GhmiR164-GhNAC100 interactions that enhanced the resistance to V. dahliae has been elucidated in detail [17,18]. In addition, the GhmiR397-GhLAC4 module that was identified as a negative regulator of resistance to V. dahliae was also resolved [19]. Although many cotton miRNAs have been identified in previous research, only a small portion have been experimentally validated and the role of miRNAs in the regulation of V. dahliae defense responses remains unclear. Nevertheless, previous studies have mainly focused on differential expression analysis of V. dahliae-induced genes at a single level, such as transcriptome or miRNAome analysis in cotton. To date, there have been few reports on integrative analysis of mRNAs and miRNA expression that reveal the complicated network involved in regulating the response to V. dahliae infection in resistant and susceptible cotton genotypes. This information, including miRNA–mRNA regulatory mechanisms associated with upland cotton resistant to Verticillium wilt, is still limited. Therefore, a genome-wide profiling of both mRNAs and miRNAs may shed more light on the underlying regulatory mechanisms. To further explore the key factors in response to V. dahliae resistance and to obtain a better understanding of the molecular basis of the V. dahliae stress response in cotton, mRNA and miRNA expression were simultaneously profiled. Systematic investigations of the regulatory networks were performed under V. dahliae stress using high-throughput sequencing. Clusters of differentially expressed genes that might respond to V. dahliae tolerance in cotton were identified to be related to various pathways. Furthermore, quantitative reverse transcription-PCR (qRT-PCR) analysis was carried out to validate the expression patterns of several important candidate genes. The transcriptome and miRNA data obtained should help reveal critical genes and miRNAs underlying the V. dahliae defense responses in cotton and provide new insights into dynamic antifungal regulation in plants. 2. Results 2.1. Differential Expression of mRNAs between J11 and Z2 Response to V. dahliae Stress The V. dahliae-sensitive cultivar J11 (Gossypium hirsutum L.) and V. dahliae-tolerant cultivar Z2 (Gossypium hirsutum L.) (Figure S1) provided by the Institute of Cotton Research of Chinese Academy of Agricultural Sciences were used to test mRNA and miRNA responses to V. dahliae stress. To identify the mRNAs involved in plant responses to V. dahliae stress, 12 RNA libraries for three biological replicates constructed from mock and V. dahliae-inoculated J11 and Z2 were sequenced. After removing the reads with linkers and low-quality reads, 18.9–24.6 million clean reads with Q30 ranged from 92.1–93.6% were obtained (Table S1). Genes with differential expression between susceptible and resistance cottons (cutoff fold change ≥ 2 and p-value ≤ 0.05) were defined (Figure 1, Table S2). A total of 6701 and 1629 DEGs with ≥2-fold change were detected in J11 and Z2, respectively, including 4252 up-regulated and 2449 down-regulated DEGs in J11 and 1213 up-regulated and 416 down-regulated DEGs in Z2 (Figure 1A,B). In particular, the number of up-regulated DEGs was significantly higher than that of down-regulated DEGs and the number of DEGs in J11 was significantly more than those in Z2, almost 3.5 times the number of up- and 1.5 times down-regulated DEGs in Z2 (Figure 1C). Among the DEGs, 816 unigenes were co-upregulated in both J11 and Z2, whereas 208 unigenes were co-downregulated in both J11 and Z2 (Figure 1D, Table S2). These results likely reflect fungal growth in J11 and massive induction and activation of stress responsive genes, whereas Z2 could hardly be infected. 2.2. Functional Classifications of DEGs in Response to V. dahliae Stress For functional classifications of DEGs, GO enrichment analysis was conducted to analyze the possible biological functions of DEGs responsive to V. dahliae infection in the two cotton lines. Enrichment analysis revealed specific biological processes and metabolic pathways that were differentially represented in V. dahliae-inoculated cotton genotypes (Figure 2A). There was a higher proportion of upregulated oxidoreductase activity and peroxidase activity in Z2 compared to J11, thus improving V. dahliae tolerance through the regulation of antioxidant ability (Figure 2A). In contrast, the increased proportion of DNA binding transcription factor activity, signal transduction, biotic stimulus responses, and stress responses in J11 were significantly higher than those in Z2 (Figure 2A). These results revealed that diverse processes are involved in regulating cotton responses to V. dahliae and overall J11 exhibited a more pronounced disease response. Additionally, 1024 co-DEGs were selected for GO analysis. Further analysis revealed that biological processes related to the kinesin complex, microtubule binding, microtubule motor activity, iron ion homeostasis, iron ion transport and ferric iron binding were significantly overrepresented (Figure 2B). Notably, biological processes related to biotic stimulus responses were also identified (Figure 2B). Overall, the RNA sequencing data suggested that the early upregulation of selected genes from oxidoreductase activity, peroxidase activity, microtubule activity, and the downregulation of genes involved in iron ion homeostasis, iron ion transport, and ferric iron binding may contribute to resistance. 2.3. DEGs of WRKY Transcription Factors in Response to V. dahliae Stress Increasing evidence shows that plant transcription factors partake in defense against pathogen infection [4]. Among the DEGs, 251 transcription factor families such as WRKY, C2H2, MYB-related, bHLH, and bZIP were identified to be upregulated or downregulated in J11. Compared with other transcription factor families, the WRKY family accounted for the largest proportion (18.3%) of differential expressions indicated that WRKY genes primarily responded to V. dahliae stress in J11 (Figure 3). WRKY proteins are plant-specific transcription factors known for their function in plant defense by acting downstream of many immune response pathways [20]. A total of 60 WRKY genes were induced among the DEGs, including 46 WRKY genes in J11 and 14 in Z2 (Figure 3, Table S3). In J11, upregulated and downregulated WRKY genes were divided equally at 24 h post infection (hpi) (Figure 3A). In contrast, almost all WRKY genes were upregulated, except a WRKY70 gene (Gh_A02G0029) and a WRKY51 gene (Gh_A02G1301) downregulated at 24 hpi in Z2 (Figure 3B). Interestingly, another WRKY70 gene (Gh_D05G2642) was upregulated in J11 (Figure 3A). Even though WRKY40 has been implicated in resistance to both fungal and bacterial pathogens [21], three upregulations of WRKY40 homologs were found in both J11 and Z2. In addition, seven WRKY6 homologs were identified in J11, of which three were upregulated and four were downregulated (Figure 3). In contrast, both WRKY6s identified in Z2 were upregulated. These results were indicative of a potential positive regulatory role for these up-regulated WRKY genes in cotton defense responses to V. dahliae stress (Figure 3). 2.4. Identification of Cotton miRNAs in Response to V. dahliae Stress To identify the miRNAs involved in plant responses to V. dahliae stress, 12 small RNA libraries for three biological replicates constructed from mock and V. dahliae inoculated J11 and Z2 were sequenced. After removal of the adapter sequence, low-quality reads, and <15 nt reads, 9.8–16.7 million clean reads were obtained in these libraries and sequences with lengths ranging from 17 to 30 nt were selected for the following analysis (Figure S2A). A similar distribution of reads appeared in all samples, and the majority of the small RNAs were concentrated in the range of 21–24 nt, with 24 nt being the most abundant, followed by the 21 and 22 nt categories across all of the libraries, which suggests that no significant degradation of small RNAs occurred during V. dahliae stress (Figure S2B,C). These small RNAs were searched against miRBase version 21 and against 330 conserved miRNAs reported in previous studies (Figure 4, Table S4). In addition, de novo predictions have been performed that identified another 53 miRNA candidates (Figure 4, Table S4). Comparisons with the mock revealed 30 and 36 DEMs in J11 and Z2, respectively (cutoff fold change ≥ 1 and p-value ≤ 0.05). Among these genes, 24 significantly upregulated and 6 downregulated miRNAs were found in J11, where novel-miRNA-12, novel-miRNA-42, novel-miRNA-45 and novel-miRNA-52 were upregulated and novel-miRNA-40 was downregulated (Figure 4A). In Z2, 33 miRNAs were significantly upregulated and 3 were downregulated. Among them, novel-miRNA-33 and novel-miRNA-52 were upregulated and novel-miRNA-32, novel-miRNA-40, and novel-miRNA-42 were downregulated (Figure 4B). There were eight co-upregulated miRNAs and one co-downregulated miRNA in both J11 and Z2 (Figure 4). Furthermore, over 80% of the miRNAs were upregulated, indicating that increased expression of miRNAs might play a more crucial role than the decreased expression of miRNAs in cotton defense responses to V. dahliae stress. Notably, the number of upregulated DEMs in Z2 was significantly higher than those in J11, indicating its superiority in terms of disease resistance (Figure 4). 2.5. Target Prediction and Construction of a Regulatory and Interaction Network DEM target prediction and GO annotation analyses were performed to characterize the regulatory roles of miRNAs in response to V. dahliae. A total of 12,097 and 6819 target unigenes for DEMs were identified in J11 and Z2, respectively. For the target unigenes found in J11, among the GO terms identified in the biological process, two significantly enriched categories were “response to hormone” and “lignin catabolic process” (Figure S3A). For the target unigenes found in Z2, the biological process of “protein ubiquitination”, “response to hormone”, and “lignin catabolic process” were significantly enriched (Figure S3B). To establish the regulatory network of miRNA–mRNA involved in the response to V. dahliae, the potential targets of DEMs were analyzed from DEGs in the transcriptome. After excluding miRNA–mRNA modules with the same expression pattern, a total of 23 miRNA–mRNA pairs were found in J11, involving 8 DEMs and 20 DEGs, showing antagonistic regulatory patterns involving up-regulated miRNAs and downregulated mRNAs (Figure 5A, Table S5). Among these pairs, 11 pairs involved downregulated miRNAs and upregulated mRNAs; 12 pairs involved upregulated miRNAs and downregulated mRNAs (Figure 5A, Table S5). In Z2, a total of eight miRNA-mRNA pairs were found, involving three DEMs and eight DEGs (Figure 5B, Table S5). Among these pairs, seven pairs involved down-regulated miRNAs and up-regulated mRNAs; only one pair involved up-regulated miRNAs and down-regulated mRNAs (Figure 5B, Table S5). The affected pathways in the miRNA-mRNA regulatory network included the “response to hormone” and “lignin catabolic process” pathways, many of which have been described previously. In depth, the GhmiR395-APS1/3 module (upregulated miRNAs) and GhmiR165-REV module (downregulated miRNAs) had higher expression levels relative to other miRNAs and were obviously induced after inoculation with V. dahliae. These were validated by 5′ RLM-RACE and qRT-PCR, which suggested that the selected modules were possibly involved in the response to V. dahliae stress (Figure 6A,B). 2.6. Validation of Gene Expression by qRT-PCR To verify the reliability of the RNA sequencing results, the relative expression levels analysis of selected genes was investigated with qRT-PCR. According to the results obtained from qRT-PCR, the expression pattern of eight selected mRNAs was largely similar with our sequencing data, including four upregulated and four downregulated mRNAs (Figure S4A). As for miRNAs, stem-loop qRT-PCR was used to determine the miRNA expression levels of eight miRNAs with three biological replicates. The values of relative expression level of GhmiR160b, GhmiR164, GhmiR166d, GhmiR395, GhmiR398a and GhmiR403 were all positive, while GhmiR165 and novel-miRNA-40 were negative (Figure S4B), which were closely matched with sequencing data. Our present results showed that the expression profiles of those miRNAs and mRNAs were reliable to be used to investigate V. dahliae-induced transcriptional changes in cotton. 3. Discussion Verticillium wilt of cotton caused by the notorious fungal pathogen V. dahliae is a destructive soil-borne vascular disease that severely decreases cotton yield and quality worldwide. The Verticillium pathogen typically invades and colonizes the roots of plants, and then spreads acropetally through the vascular tissue of the plant, resulting in the primary symptoms of necrotic areas on leaves, yellowing of leaves, wilting, and discoloration of vascular tissues [4]. Unfortunately, upland cotton (G. hirsutum L.), the main species cultivated on a large scale, is sensitive to V. dahliae. However, the specific molecular and genetic components that mediate resistance to the pathogen and the plant immune response pathways remain largely unknown. Two contrasting upland cotton genotypes (highly resistant and susceptible), with distinct defense responses, were used in the global expression profiling experiment described here to investigate the roles of regulatory RNAs in V. dahliae induction. Genome-wide mRNA and miRNA profiling data provide genes regulated during pathogen infection, which can be pursued through genetic studies or used as markers for tracking the activation of immune responses. Comparative transcriptomic analysis revealed that the number of DEGs in J11 was significantly higher than that in Z2, revealing a stronger response induced in the susceptible genotype (Figure 1D). In addition, the number of upregulated DEGs was significantly higher than that of downregulated DEGs in both J11 and Z2, suggesting that early upregulation of selected genes contributes to disease resistance (Figure 1D). The accumulation of reactive oxygen species (ROS) is a classical immune response that affects resistance to pathogens [22]. Changes in the redox state of glutathione and the accumulation of ROS in the cytosol during biotic stress can initiate the activation of defense genes in the nucleus through pathways that involve many plant hormones [23]. Interestingly, there was a greater proportion of upregulated DEGs that encode proteins involved in oxidoreductase activity and peroxidase activity, such as Gh_D08G0426, Gh_A10G2290, Gh_D10G0605, Gh_D04G1116 and Gh_D12G0699. These specific proteins may encode oxidoreductases and peroxidases that affect the synthesis of glutathione and ROS directly or indirectly in Z2 compared with J11, thus exhibiting a remarkable level of resistance to V. dahlia infection in Z2 (Figure 2A). In contrast, the increased proportion of DNA binding transcription factor activity, signal transduction, biotic stimulus response and stress response in J11 were significantly higher than those in Z2, likely due to massive changes in disease symptoms and fungal growth in J11, but not in Z2. These results were consistent with the extent of disease symptoms and fungal growth in J11 and Z2 (Figure 2A). Lots of evidence indicates that microtubule disruption is associated with plant defense responses and resistance [24]. During pathogen infections, plant microtubules are commandeered by the pathogen for intra and intercellular movement, as well as for interhost transmission [25]. With regard to the co-DEG functional analysis, our results show that the major proportion of upregulated DEGs were within the functional categories of microtubule activities, including microtubule binding, kinesin complex, and microtubule motor activity, indicating that active microtubule movements in cotton respond to V. dahliae infection (Figure 2B). Therefore, the biochemical and physical mechanisms by which microtubule activity responds during V. dahliae infection should be elucidated. The formation of localized cell wall appositions, oxidative bursts, and production of pathogenesis-related proteins are hallmarks of plant defense responses, and iron is a central mediator that links these three phenomena [26]. In response to a pathogen attack, the bulk secretion of Fe3+ is deposited at cell wall appositions, where it accumulates and leads to intracellular iron depletion, which promotes the transcription of pathogenesis-related genes [26]. Additionally, some plant pathogens use siderophores to acquire iron in the host and trigger host immunity through the perturbation of heavy-metal homeostasis [27]. Notably, a large proportion of the downregulated co-DEGs were within the functional categories of iron ion homeostasis, iron ion transport and ferric iron binding. For instance, some genes such as Gh_D09G1582, Gh_A09G2418, Gh_A10G2147, Gh_D10G2394 appeared to encode the ferritin-3 protein, which likely impacts the resistance and severity of disease symptoms (Figure 2B, Table S2). These results provide valuable insights into the multiple molecular pathways that control the cotton stress response to V. dahliae (Figure 7). The WRKY gene family is one of the largest families of transcription factors in higher plants and has been shown to play an important role in plant defense responses to a variety of pathogens [20]. WRKY genes may activate or suppress the expression of resistance genes directly or interact with other transcription factors to regulate plant defense responses [20]. WRKY70 is considered a repressor of JA-responsive genes [28]. Notably, Gh_A02G0029 (WRKY70) was downregulated in Z2, but a WRKY70 gene (Gh_D05G2642) was upregulated in J11, suggesting a negative regulatory role in response to V. dahliae infection through inhibition of the JA signaling pathway (Figure 3, Table S3). F.oxysporum-induced GhWRKY40 plays a negative role in disease resistance in cotton by disrupting the SA-mediated defense pathway [29]. In our study, the upregulation of WRKY40 homologs were found in both J11 and Z2. It is likely that WRKY40 responds to V. dahliae infection by activating the SA signaling pathway (Figure 3, Table S3). Additionally, GhWRKY6 was induced by drought and salt stress and acted as a negative regulator during both drought and salt stress [30]. Among the DEGs, four downregulated WRKY6 homologs were identified in J11. In contrast, both WRKY6 genes identified in Z2 were upregulated, indicating that they contribute to resistance in Z2 (Figure 3, Table S3). This result revealed that WRKY6s are also induced by V. dahlia and may have opposing functions in the fight against V. dahliae infection. Finally, we found other WRKY homologs with different expression patterns induced by V. dahliae, which implied WRKY genes may play both negative and positive regulatory roles between susceptible and resistant cotton cultivars (Figure 7). It has become clear that miRNAs regulate gene expression mainly by cleaving target mRNAs or through transcriptional inhibition at the post-transcriptional level and play a crucial role in coordinating plant–pathogen interactions. The up-regulation of miR159, miR160, miR164, miR166 and miR167 was consistent with results reported in Arabidopsis and cotton [15,16,31]. Although miR398 may be involved in immune responses with an inverse regulatory mode of action in bacterial and fungal pathogen species [32], miR398 homologs were significantly upregulated in both J11 and Z2, indicating that they may participate in the V. dahliae infection response (Figure 4, Table S4). In addition, co-upregulated novel-miRNA-52 and co-downregulated novel-miRNA-40 in both resistant and susceptible lines indicated that these novel miRNAs may play different roles in the response to V. dahliae infection (Figure 4, Table S4). It is worth noting that novel miRNA-42, which had opposing inducible expression patterns in resistant and susceptible lines, may serve as a potential molecular target to improve V. dahliae resistance in cotton (Figure 4, Table S4). In cotton, cleavage of GhNAC100 mRNA by GhmiR164 leads to degradation of GhNAC100, thereby enhancing its resistance to V. dahliae [18]. GhmiR397 cleaved the GhLAC4 transcript and was identified as a negative regulator of lignin biosynthesis that improves plant resistance to infection by V. dahliae [19]. According to the established miRNA–mRNA interactions, upregulation of miR164 and miR397 was found in J11 and Z2. However, GhNAC100 targeted by miR164 and GhLAC4 targeted by miR397 were also upregulated. These two modules failed to show antagonistic regulatory patterns, likely due to the later stage of induction of fungal-infected cotton when V. dahliae colonized the xylem vessels. Sufficient levels of sulfur in soils confer the optimal plant uptake of inorganic sulfate salts, a prerequisite for sulfur-containing defense compound concentrations required for plant disease resistance responses [33]. In rice, miR395 targets and suppresses the expression of the ATP sulfurylase gene OsAPS1, which functions in sulfate assimilation, to promote sulfate accumulation, resulting in broad-spectrum bacterial resistance [34]. As a specific colonizer of plant xylem vessels, V. dahliae encodes a complex array of cell-wall-degrading enzymes that invade plant vascular tissue [4]. A group of HD-ZIP III transcription factors including REV, PHB and PHV, whose expression is post-transcriptionally regulated by miR165/166, play key roles in the establishment of the vascular pattern and secondary cell wall formation in plants [35]. It is likely that plants use miR165-HD-ZIP III transcription factor modules to prevent pathogen invasion by altering the development of vascular tissue and cell wall formation. In this study, modules such as GhmiR395-APS1/APS3 and GhmiR165-REV validated by 5′ RLM-RACE did work in cotton; therefore, it remains worthwhile to explore whether these miRNAs and their targets are involved in the response to V. dahliae infection in cotton (Figure 7). Moreover, examination of the novel regulatory networks consisting of miRNAs and their corresponding targets will help us to better understand the regulatory mechanisms of stress responses to V. dahliae infection (Figure 5, Table S5). 4. Materials and Methods 4.1. Plant Materials and Pathogen Treatment The V. dahliae-sensitive cultivar J11 and V. dahliae-tolerant cultivar Z2 (Figure S1) [36] were used to test mRNA and miRNA response to V. dahliae stress. Cotton seeds were germinated on wet gauze in a Petri dish at 28 °C and cultivated in a growth chamber with the same conditions of 25 °C/18 °C cycle under a 16 h light/8 h dark cycle. Vd080, a highly pathogenic V. dahliae strain [36], was confirmed and then cultured in potato dextrose broth (PDA) in plates until concentration was adjusted to 106 spores/mL to inoculate cotton roots for 24 h. As a mock-inoculation control, roots were inoculated with empty PDA. For material harvest, the roots from six different plants in each treatment were mixed separately, replicated three times and immediately plunged in liquid nitrogen and stored at −80 °C for RNA isolation. 4.2. RNA Preparation and Sequencing Roots from mock and V. dahliae-treated cotton were used for RNA library construction and deep sequencing analyses according to [37]. Total RNA was isolated by using the RNA reagent (Invitrogen, Carlsbad, CA, USA). The quantity and quality of the isolated total RNA were assessed using a NanoDrop OneC Spectrophotometer. For transcriptome sequencing, the enriched mRNAs were purified from the total RNA with magnetic beads attached to oligo (dT) and the strand-specific libraries were sequenced on Illumina Hiseq2500 platform at Novogene (Beijing, China) with pair-end strategy (2 × 150 bp). Moreover, small RNA libraries were constructed using the Small RNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequencing was performed on Hiseq platform at Novogene (Beijing, China) with single end strategy (50 bp). 4.3. Identification of DEGs and DEMs Clean data from RNA sequencing were aligned to the reference genome (NAU, v1.1, downloaded from CottonGen) by TopHat (v2.1.0). HTSeq was used to calculate the number of short reads aligned to the characterized gene loci, and DESeq2 was then used to identify the DEGs (cutoff fold change ≥ 2 and p-value ≤ 0.05). Quality control of the small RNA sequencing data was carried out by using FASTX-Toolkit (http://hannonlab.cshl.edu/fastx_toolkit/, accessed on 16 February 2022). Conserved miRNAs identification and de novo prediction of miRNAs were performed according to [37]. Predicted miRNAs that derived from tRNA, rRNA and snoRNA were removed before further analysis. Expression of the small RNAs was calculated by RPM (reads per million mapped reads) using in-house developed Perl scripts. DEMs were also identified by DESeq2 (cutoff fold change ≥ 1 and p-value ≤ 0.05). Enrichment of gene ontology (GO) terms and pathways in DEGs was estimated by chi-square testing. Only the GO terms referring to more than three genes were retained, and the redundancy of GO terms was removed through the online tool REViGO with default settings [38]. 4.4. Integrated Analysis of mRNA and miRNA Sequencing The prediction of miRNA target genes was performed using Target Finder software. The miRNA–mRNA pairs with a reverse expression correlation relationship were collected to construct the miRNA–mRNA regulatory network. Gene ontology enrichment analysis (http://www.geneontology.org, accessed on 24 March 2022) was carried out for allocating genes to different functional categories and predicting their biological functions, respectively [38]. 4.5. Expression Analyses of mRNA and miRNA Reverse transcription was performed using the PrimeScript™RT reagent kit with gDNA Eraser (Takara). qRT-PCR was performed using the TB Green® Premix Ex Taq™ (Takara) on the QuantStudio 3 Applied Biosystem and quantified using the ∆∆CT method. GhUBQ7 and U6 snRNA were used as internal controls for mRNA and miRNA, respectively [37]. The specificity of the qPCR reactions was confirmed by melting curve analysis of amplified products. Primers used for qPCR are listed in Table S5. The comparisons between samples were performed using the Student’s t-test. Two-tailed p-values of less than 0.05 were considered to be statistically significant. SPSS Statistics 19.0 was used to conduct the analysis [37]. 4.6. 5’-RNA Ligase-Mediated Rapid Amplification of cDNA Ends (5’ RLM-RACE) The RNA of a mixture of cotton roots was extracted. The cleavage sites of targets were identified through GeneRacer Kit (Invitrogen, CA, USA) according to the manufacturer’s guidelines. The PCR products purified by gel were subcloned into pMD18-T vectors (Takara). The clone sequences were analyzed to map the cleavage sites. The gene-specific primers were listed in Table S5. 5. Conclusions In this study, mRNA libraries and small RNA libraries were integrated to systematically investigate the roles of regulatory RNAs under V. dahliae induction in upland cotton. Biological processes such as antioxidant ability, microtubule activities and iron ion homeostasis were thought to be important in response to V. dahliae infection. Our findings suggested that the differential regulation and expression of WRKYs play both negative and positive regulatory roles in V. dahliae stress responses. In addition, our analysis also identified miRNAs that may play important roles in the response to V. dahliae stress. Many of the miRNAs and their target genes were involved in the regulation of “protein ubiquitination”, “response to hormone” and “lignin catabolic process”. Moreover, up-regulation of GhmiR395 and down-regulation of GhmiR165 were possibly involved in response to V. dahliae by regulating sulfur assimilation through the GhmiR395-APS1/3 module and the establishment of the vascular pattern and secondary cell wall formation through the GhmiR165-REV module, respectively. In summary, this work found some key genes/modules involved in the response to V. dahliae stress in cotton that provided several candidate targets of genetic modification for further use in resistance to Verticillium wilt. Acknowledgments The authors want to thank Feng Hongjie for providing experimental materials and his constructive comments during manuscript preparation. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094702/s1. Click here for additional data file. Author Contributions J.M. and Y.S. conceived the study. J.M., Y.W., Q.N., D.Z., M.M., Y.Z., F.C., L.K. and H.F. performed plant management and molecular experiments. Y.W., D.Y. and D.Z. performed the data analysis. J.M. and Y.S. wrote the manuscript. All these authors approved the final manuscript. All authors have read and agreed to the published version of the manuscript. Funding This work is supported by the National Natural Science Foundation of China (Grant No. 32001591) and the Science Foundation of Zhejiang Sci-Tech University under grants 19042402-Y and 2020Q029. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement All the RNA-seq data generated and used in this work have been deposited in Sequence Read Archive (SRA) of the NCBI under the accession numbers PRJNA819185. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Global evaluation of the RNA sequencing data in upland cotton lines J11 and Z2. (A) Volcanic plot of the differential mRNA expression in J11. (B) Volcanic plot of the differential mRNA expression in Z2. (C) Counts of down- and up-regulated genes in J11 and Z2, respectively. (D) Venn diagram of the differential mRNA expression between J11 and Z2. Figure 2 Overview of genes differentially expressed in response to V. dahliae stress in J11 and Z2. (A). Functional categories of DEGs after V. dahliae inoculation. The percentages of upregulated and downregulated genes are shown for the selected overrepresented functional categories. The significance of the difference between two accessions (chi-squre test) are analyzed with “*” (p < 0.05) or “**” (p < 0.01). (B). GO enrichment analysis of the co-upregulated and co-downregulated unigenes with the top10 are shown. Figure 3 Expression profiling of WRKYs in response to V. dahliae stress. Hierarchical clustering of differentially expressed WRKYs in J11 (A) and Z2 (B). Red and blue colors show upregulation and downregulation, respectively. The original expression values of the WRKYs were normalized using Z-score. The signal intensity ranges from −2 to 2, as the corresponding color also changes from blue to red. Figure 4 Expression profiling of miRNAs in response to V. dahliae stress in J11 (A) and Z2 (B). Hierarchical clustering of differentially expressed miRNAs in J11 (A) and Z2 (B). Red and blue colors show upregulation and downregulation, respectively. The original expression values of the miRNAs were normalized using Z-score. The signal intensity ranges from −2 to 2 and −1.5–1.5 as the corresponding color also changes from blue to red. Figure 5 Regulatory network between miRNAs and target mRNAs associated with V. dahliae stress in J11 (A) and Z2 (B). Red lines represent downregulated miRNAs and upregulated mRNA pairs, green lines represent upregulated miRNAs and downregulated mRNA pairs. Figure 6 GhmiR395-APS1/3 and GhmiR165-REV module were validated by qRT-PCR and 5′ RLM-RACE. (A). qRT-PCR was performed to determine the expression levels of GhAPS1/APS3/REV. GhUBQ7 was used as an internal control and data are means ± SD from three biological replicates. * and ** indicates a significant difference at p < 0.05 and p < 0.01 compared with mock using a two-tailed Student’s t-test. (B). The cleavage sites of GhAPS1/APS3/REV mRNA were determined by the 5′ RLM-RACE method. Arrow indicates the 5′ terminus of miRNA-guided cleavage products, as identified by 5′-RACE, with the frequency of clones (6/6 and 5/8) are shown. Figure 7 A summary of the putative and verified biological events incurred under V. dahliae stress in cotton. 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==== Front Polymers (Basel) Polymers (Basel) polymers Polymers 2073-4360 MDPI 10.3390/polym14091773 polymers-14-01773 Article A Solvent-Free Approach to Crosslinked Hydrophobic Polymeric Coatings on Paper Using Vegetable Oil Loesch-Zhang Amelia 1 Cordt Cynthia 1 Geissler Andreas 12* Biesalski Markus 1* Frigione Mariaenrica Academic Editor 1 Macromolecular and Paper Chemistry, Technical University Darmstadt, Alarich-Weiss-Str. 8, 64287 Darmstadt, Germany; amelia.loesch-zhang@tu-darmstadt.de (A.L.-Z.); cordt@cellulose.tu-darmstadt.de (C.C.) 2 Papiertechnische Stiftung (PTS), Pirnaer Str. 37, 01809 Heidenau, Germany * Correspondence: andreas.geissler@tu-darmstadt.de (A.G.); markus.biesalski@tu-darmstadt.de (M.B.); Tel.: +49-61511623727 (A.G.); +49-61511623721 (M.B.) 27 4 2022 5 2022 14 9 177330 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/). Hydrophobic coatings are of utmost importance for many applications of paper-based materials. However, to date, most coating methods demand vast amounts of chemicals and solvents. Frequently, fossil-based coating materials are being used and multiple derivatization reactions are often required to obtain desired performances. In this work, we present a solvent-free paper-coating process, where olive oil as the main biogenic component is being used to obtain a hydrophobic barrier on paper. UV-induced thiol-ene photocrosslinking of olive oil was pursued in a solvent-free state at a wavelength of 254 nm without addition of photoinitiator. Optimum reaction conditions were determined in advance using oleic acid as a model compound. Paper coatings based on olive oil crosslinked by thiol-ene reaction reach water contact angles of up to 120°. By means of Fourier transform infrared spectroscopy and differential scanning calorimetry, a successful reaction and the formation of a polymer network within the coating can be proven. These results show that click-chemistry strategies can be used to achieve hydrophobic polymeric paper coatings while keeping the amount of non-biobased chemicals and reaction steps at a minimum. vegetable oil coatings paper thiol-ene hydrophobicity barrier food packaging Agency for Renewable Resources2220HV017A This research was funded as part of the BioPlas4Paper project by Agency for Renewable Resources (Fachagentur Nachwachsende Rohstoffe e.V.—FNR), grant number 2220HV017A. ==== Body pmc1. Introduction Due to the increasing importance and demand of circular and sustainable materials, paper has gained increased attention as a packaging and versatile light-weight construction material. The advantages of paper in such applications include high specific mechanical strength, the possibility to add further properties by simple coatings, the availability from renewable resources, and finally technologically well-developed recycling processes. However, with paper, some important challenges exist, such as a lack of protection against water penetration and associated changes in dimension and strength, potential damages by microorganisms, permeability to gases, absorption of odors, and sensitivity to abrasion under continuous mechanical loads. While some of these challenges can be addressed using functional additives already during paper sheet production, other aspects are tackled by subsequent finishing of readily prepared paper. There are already several reports addressing this highly complex set of demands for paper applications. Some have focused on applying vegetable oil-based precursors onto cellulosic materials using various methods for obtaining increased hydrophobicity. For instance, cotton with low water absorbance and increased contact angle (up to 80°) was obtained via deposition of soybean oil from an organic solvent followed by thermal treatment [1]. In jute and sisal fibers coated with an emulsion of rice bran or neem oil and a phenolic resin, transesterification reactions between the triglycerides and cellulose were induced by thermal curing, resulting in increased hydrophobicity, tensile strength and durability of the fibers [2]. Chemical reactions were employed for direct covalent attachment of fatty acids to cellulosic materials via transesterification reactions using fatty acyl chlorides [3,4,5]. Ring-opening polymerization enabled crosslinking of epoxidized soybean oil onto filter paper with the cellulose hydroxyl groups acting as initiators, resulting in contact angles of up to 145° [6]. In a very interesting work, Onwukamike et al. directly grafted sunflower oil onto cellulose without any supplementary activation or derivatization steps using a 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU)-CO2 solvent system [7]. Samyn et al. applied dispersions of different vegetable oils incorporated into poly(styrene-maleic anhydride) particles onto paper and paperboard substrates, obtaining porous coatings chemically stable against water and exhibiting static contact angles above 90° [8]. Entirely new structures can be obtained by plasma treatment, which was used by Cabrales et al. to graft oleic acid from ethanolic solution onto cotton fabric, obtaining contact angles above 150° with long-term stability [9]. Apart from covalent attachment to or physical deposition onto substrates, intensive research has recently been focused on using fatty acids or vegetable oils as sustainable resources for polymer production through crosslinking reactions [10,11,12,13,14,15,16]. Altuna et al. produced a network from epoxidized soybean oil crosslinked with an aqueous citric acid solution without the use of additional solvents or catalysts [17]. Wuzella et al. photocured acrylated epoxidized linseed oil with three different photoinitiators using a polychromatic ultraviolet (UV) lamp with a maximum light intensity at 365 nm, correlating resulting properties to cure evolution and double bond conversion [18]. Wang et al. esterified castor oil with 3-mercaptopropionic acid, which in the following allowed crosslinking of the derivatized oil films deposited on glass substrates without further addition of solvent or initiator using UV light [19]. To date, most of these strategies require various reaction steps, which again renders them rather sophisticated. Hence, more simple one-step procedures are increasingly in focus. An example for the latter is the well-known thiol-ene click reaction, as it can be performed on unsaturated fatty acids and vegetable oils without further derivatization. Thiol-ene reactions enjoy high popularity due to their good uniformity, controllability and insensitivity towards oxygen inhibition [20]. Thiol-ene polymerizations proceed via step-growth radical polymerization (Figure 1). The olefin structure has a decisive influence on the kinetics and conversion rates. While terminal double bonds react rapidly and quantitatively, internal enes react more slowly and without full conversion, which is due to steric effects induced by 1,3 interactions of the substituents. Internal cis-configured double bonds first isomerize to trans bonds in an insertion–isomerization–elimination process, while in the following the thiyl radical adds on the trans-configured double bond [21]. The rate-determining step of the thiol-ene-reaction is the hydrogen transfer from the thiol to the carbon-centered radical leading to product formation [22]. Due to their good controllability and simplicity, thiol-ene reactions often serve for introducing new, sometimes complex, functionalities into vegetable oils [23,24]. Several authors made use of thiol-functionalized vegetable oils to produce organic–inorganic hybrid crosslinked coatings for wood, paper and cotton textiles with (super-)hydrophobic or flame-retardant properties [25,26,27,28]. Because of the high reaction rates for terminal olefins, vegetable oils used as biobased materials for thiol-ene chemistry have frequently been functionalized with terminal double bond-containing moieties (e.g., acrylates) to allow for easier crosslinking [29,30,31]. Other research, however, has been directed towards producing crosslinked networks directly from fatty acids or vegetable oils without additional derivatization. Moser et al. synthesized linear aliphatic poly(thioether-esters) based on fatty acids by connecting C10 fatty acids and alcohols via ester chemistry followed by photoinitiator-catalyzed thiol-ene crosslinking at the unsaturated chain ends [32]. Samuelsson et al. compared reactivities and reaction rates of two different trithiols with the olefinic double bonds in methyl oleate and methyl linoleate in the presence of a photoinitiator. They found that the addition to methyl oleate occurs more quickly, which was attributed to higher cis–trans isomerization rates due to less restricted rotation, and higher reactivity of the resulting trans unsaturation compared to cis unsaturation [33]. According to Bouaziz et al., who monitored photopolymerization of olive oil with and without the presence of a thiol crosslinker, under UV irradiation thiol-ene photocrosslinking occurs much faster than oxopolymerization (under ambient air), enabling the formation of crosslinked films within only 20 s [34]. Zhao et al. produced films from linseed oil applied onto glass and metal substrates and photocrosslinked them with different thiols (both miscible and immiscible with linseed oil). Interestingly, neither photoinitiator nor solvent were required for crosslinking at irradiation wavelengths below 275 nm, with a ratio of 0.5 equivalents of thiol per double bond being sufficient for successful crosslinking [35]. The latter examples in particular show that thiol-ene chemistry has been evolved to produce networks from fatty acid or vegetable oil precursors without the use of solvents or supplementary chemicals. To date, however, the focus was mostly on the organic reactions themselves, while only in rare cases paper has been used as substrate. Coatings on paper using fatty acids or vegetable oils without the use of further derivatization or supplementary components and applying thiol-ene crosslinking reactions in solvent/catalyst-free states have yet not been reported. The latter is of great interest as by such a strategy hydrophobic surface properties can be implemented in paper with a high degree of sustainability. Given this motivation, in this contribution, we focus on a fundamental understanding of the thiol-ene crosslinking process and its applicability with respect to biobased paper coatings. In a first step, oleic acid-based thiol-ene reactions will be examined as a model system to establish suitable crosslinking parameters. In a second part of our presented work, olive oil, containing primarily oleic acid chains, will be used to obtain polymeric hydrophobic paper coatings, and the resulting surface properties will be analyzed. 2. Materials and Methods 2.1. Materials 1,8-Octanedithiol (1,8-ODT) (99%) was purchased from Acros Organics (Geel, Belgium). Oleic acid (≥99%) was obtained from Carl Roth (Karlsruhe, Germany). 1,1,1,3,3,3-Hexamethyldisilazane (≥98%) was obtained from Merck Schuchardt (Hohenbrunn, Germany), and isopropanol and chloroform (≥99%) from Fisher Scientific (Loughborough, UK). Deuterated acetone (99.8%) was purchased from Deutero (Kastellaun, Germany). Olive oil was purchased from Oelmuehle Solling (Boffzen, Germany). 2.2. Methods 2.2.1. Glass Wafer Hydrophobization The glass substrate hydrophobization procedure was adapted from a procedure by Xiao et al. [36]. Glass substrates were precleaned with dish soap and distilled water followed by rinsing with isopropanol. Glass substrates were then cleaned in an ultrasonic bath by immersion into isopropanol and chloroform (7.5 min each). They were then treated by ultrasonication in a solution of 1,1,1,3,3,3-hexamethyldisilazane in chloroform (5 wt%) (15 min). 2.2.2. Paper Making Paper sheets with a grammage of 100 g/m2 were produced from aqueous cotton linters dispersion (2.2 wt%) using a HAAGE sheet former BBS (Haage, Peissenberg, Germany), compliant with DIN EN ISO 52692. Prior to sheet forming, the cotton linters dispersion was diluted to 0.16 wt% and stirred for 30 min to avoid entanglement of the long cotton linter fibers and obtain homogeneous paper sheets. After drying at 93 °C under reduced pressure for 10 min, grammage was determined by the bone dried paper weight. Papers were stored at norm climate conditions (23 °C, 50% relative humidity) at least for another 24 h prior to further use. This equilibration procedure is important for paper sheets to reach equilibrium water content in the sheet at the given norm climate condition. 2.2.3. Coating Preparation and Crosslinking Coatings were prepared by mixing oleic acid (10.0 g, 35.4 mmol) with 1,8-ODT (3.16 g, 17.7 mmol, 0.5 eq., corresponding to a stoichiometric C=C to SH ratio) and stirring for 30 min. Similarly, olive oil coatings were prepared from olive oil (12.0 g, 8.68 mmol) and 1,8-ODT (2.37 g, 13.2 mmol, 1.5 eq., corresponding to a stoichiometric C=C to SH ratio). Glass substrates and paper substrates used for reaction progress monitoring were coated via dip coating (home-built device) with a withdrawal speed of 2 mm/s. Paper substrates for surface analytics were impregnated with a Mathis SP 6513 size press (Mathis, Oberhasli, Switzerland) at 2 m/min speed and 0.5 bar, resulting in a final oil pick-up of (50.9 ± 0.8) wt%. UV crosslinking was performed in a Bio-Link 254 (Vilber Lourmat, Eberhardzell, Germany) at 254 nm wavelength and an irradiation dose of 20 J/cm2. Samples were stored overnight at ambient conditions before further analytics to ensure uniform reaction completion. 2.2.4. 1H-NMR Spectroscopy NMR measurements were conducted on a Bruker DRX 500 NMR spectrometer at 500 MHz, apart from measurements shown in the supporting information, which were performed on a Bruker Avance II NMR spectrometer at 300 MHz (Bruker BioSpin GmbH, Rheinstetten, Germany). Crosslinked samples were removed from the glass substrate. Samples were dissolved in deuterated acetone. Chemical shifts were calibrated to the deuterated solvent signal. Data processing was performed using MestReNova 11.0 software (Mestrelab Research S. L., Santiago de Compostela, Spain). Double bond conversions were calculated from the mean values of integrals at δ = 0.88 ppm (m, 3H, CH3) and δ = 5.39 ppm (m, 2H, CH=CH), integrated from three different samples. Errors were calculated from standard deviations. 2.2.5. FTIR Spectroscopy FTIR measurements were performed on Perkin Elmer Spectrum One FTIR spectrometer (PerkinElmer Instruments, Waltham, USA) in the spectral region of 650 to 4000 cm−1, using 4 scans with a nominal resolution of 4 cm−1. Spectra were recorded directly from the paper substrate or from coating material removed from the glass substrate. Data processing and background correction were performed using PerkinElmer Spectrum software. 2.2.6. DSC Measurement For DSC measurements, sample material was removed from the glass substrate and placed into 40 μL aluminum crucibles closed with a perforated lid. DSC measurements were performed using a Mettler Toledo DSC 3 apparatus (Mettler Toledo, Gießen, Germany) and data evaluation was performed using STARe software. Two heating cycles were carried out under nitrogen atmosphere in a temperature range between −75 °C and 150 °C at a heating and cooling rate of 10 K/min, with the second heating cycle being used for data evaluation. 2.2.7. Contact Angle Measurement Coated paper samples were stored at norm climate conditions for at least 24 h prior to contact angle measurement. Static contact angle measurements were performed using a Dataphysics OCA35 device (Dataphysics, Filderstadt, Germany) at standard climate conditions with 2 μL droplets of ultrapure water (Milli-Q-, Advantage A10, Millipak Express 20, (Merck Millipore, Billerica, MA, USA)). Drop shape fittings were performed using Dataphysics SCA20 software and applying the Young–Laplace fitting mode. A total of 10 measurements were performed for mean value determination for each sample, with a total of 3 samples per data point. Time-dependent contact angles were determined for a total of five measurements. Errors were calculated from the standard deviation from the mean for each sample followed by Gaussian error propagation. 2.2.8. Surface Roughness Measurements Tactile profilometry was performed on a DektakXT stylus profiler by Bruker (Bruker Nano Surfaces Business, Tucson, AZ, USA) with a 2.5 μm-diameter stylus and a stylus force of 3 mg. Measurements were performed over a z-scan range of 65.5 μm, a length of 1000 μm and a resolution of 0.111 μm/pt. A total of 10 measurements were performed per sample in two perpendicular directions to exclude any potential effects caused by sample preparation. Roughness parameters Ra, Rq and Rz were calculated by the software according to ISO 4287 standard. Three samples were measured in total, with the mean value and the standard deviation from the mean being determined for each sample, followed by Gaussian error propagation to determine the overall error. Optical profilometry was performed on a Sensofar PLu neox optical profiler (Sensofar-Tech, Terrassa, Spain) using a Nikon EPI 20× objective, a 850.08 × 709.35 μm scan area, a resolution of 0.69 μm/pixel, a z-scan range of 160 μm and 3 images per measurement. Surface roughness parameters Sa, Sq and Sz were determined according to ISO 25178 standard. A total of 5 measurements were taken per sample for a total of 3 samples. The mean value and the standard deviation from the mean were determined for each sample, resulting from which the overall mean value and error, using Gaussian error propagation, were calculated. 2.2.9. Optical Microscopy Images of paper samples were obtained with a Keyence digital microscope VHX-1000 (Keyence GmbH, Neu-Isenburg, Germany) equipped with an objective VH-Z250R. Depending on the reflectivity of the specimens, a selection was made between the ring light and coaxial light modes as optimal illumination. 2.2.10. SEM For SEM measurements, samples were sputtercoated with a Pd/Pt (20/80) layer of 10 nm thickness using a Cressington Turbo 208HR sputter coater (Tescan GmbH, Dortmund, Germany). Measurements were performed on a Philips XL 30 FEG scanning electron microscope at 2 kV beam voltage, 66 μA current and 250× magnification. 3. Results and Discussion In a first step, the crosslinking efficiency of dithiol linking agent 1,8-octanedithiol (1,8-ODT) for fatty acid chains was examined. Oleic acid, being the most common monounsaturated fatty acid, was chosen as a model compound, as it can at maximum form dimers when undergoing thiol-ene reactions with dithiols. This enables monitoring effects such as double bond conversion while retaining access to a higher range of analytical methods due to maintaining the solubility of the resulting compounds. The model system of oleic acid and 1,8-ODT helped to determine suitable crosslinking conditions and highlighted the significance of the thiol-component as compared to using the pure monomer at identical conditions. Secondly, the crosslinking of olive oil, a vegetable oil containing mainly oleic acid triglycerides, with 1,8-ODT was examined. The coating was applied to handsheets made from cotton linter fibers and the resulting surface morphology and water contact angles were analyzed. 1,8-ODT was chosen as thiol for its good miscibility with both oleic acid and olive oil, contrary to various commercially available tri- and tetrathiols used in preliminary experiments, while still allowing for network formation when combined with olive oil. A stoichiometric ratio of thiol functionalities to double bonds was used to ensure maximum double bond conversion. Preliminary experiments have shown that 254 nm is a suitable irradiation wavelength for crosslinking without requiring the use of curing agents or solvents, in accordance with observations made by Zhao et al. [35]. In the first part, a mixture of oleic acid and 1,8-ODT was applied onto both glass substrates and cotton linters paper and photocrosslinked at varying irradiation intensities (Figure 2a) in order to examine optimum reaction conditions and analyze the thiol-ene reaction process in detail. 1H-NMR spectroscopy (Figure 2b) allowed the quantitative examination of the double bond conversion during irradiation, as the integral associated to the two olefinic protons at 5.29–5.47 ppm decreases relative to the integral associated to the terminal methyl group at 0.80–0.92 ppm following double bond conversion. Further, the isomerization from cis double bonds (centered at 5.35 ppm), primarily present in oleic acid, to trans double bonds (centered at 5.41 ppm) can be observed as described in the literature. The latter is caused by reversible addition of thiol radicals to the double bond and results in the majority of non-reacted double bonds showing trans character [21,22,23]. 1H-NMR spectra of coatings deposited on glass substrates showed increasing double bond conversion with irradiation intensity, reaching a maximum of (85.2 ± 1.2)% at an irradiation intensity of 20 J/cm2 without significant changes at higher irradiation doses (Figure 2c), indicating that with this energy input, almost all accessible double bonds have reacted and no further crosslinking occurs at higher irradiation doses. Water contact angle (WCA) measurements of coatings deposited on cotton linters paper show similar behavior, with an augmentation of WCA values from (72.8 ± 2.5)° at 5 J/cm2 to (80.2 ± 1.8)° at 20 J/cm2 and insignificant increase at higher irradiation intensities (Figure 2d). This confirms the results obtained by 1H-NMR spectroscopy and indicates that the main part of the reaction including a rise of the fluid’s viscosity takes place until this point. A value of 20 J/cm2 was therefore selected as irradiation intensity for all future experiments. FTIR spectroscopy was used to qualitatively assess the thiol-ene reaction (Figure 3a). The bands of main interest (Table S1) are those characterizing the double bonds, in particular the C=Ccis stretching mode at 3009 cm−1, which disappears after the thiol-ene reaction, as well as the newly appearing C=Ctrans bending mode at 967 cm−1 caused by cis–trans isomerization during the reaction, and the disappearing C=Ccis bending modes at 722 cm−1, 934 cm−1 and 1412 cm−1 [23,37]. A low amount of conjugated C=C bonds is also observed for the crosslinked sample at 998 cm−1 [33]. Theoretically, the observation of the diminishing S–H bond and forming C–S bond could also be expected, but can in reality not be observed due to its low intensity [23]. Comparison of the FTIR spectra of coated cotton linters paper before and after Soxhlet extraction shows that the coating was not covalently bound to the paper sheet. (Figure 3b). After extraction no signals are present that can be assigned to oleic acid. The latter is not unexpected as there are no double bonds in the pure cotton linters paper that would allow for direct reaction and the dimers are most likely too small to physically anchor in the paper fiber network. The decisive relevance of the thiol as radical initiator for the oleic acid double bond conversion was also proven, as pure oleic acid coatings on glass submitted to the same irradiation conditions showed only (2.2 ± 0.5)% double bond conversion as opposed to (82.5 ± 1.2)% for the mixture. This confirms that oxidation reactions with air oxygen radicals play no significant role during the irradiation process, but may occur to a very low degree, as previously described by Zhao et al. [35]. Corresponding observations were made during WCA measurements of pure oleic acid coatings on linters paper, with a slight contact angle increase from (22.9 ± 3.0)° for untreated paper coatings to (41.3 ± 1.9)° after UV treatment, whilst a significant increase into the almost hydrophobic range at (80.2 ± 1.8)° took place after and due to UV treatment of the oleic acid/thiol mixture coating. Performing the photoinitiated thiol-ene reaction between oleic acid and 1,8-ODT allowed using a simple scaffold for determining suitable reaction conditions and ruling out significant environmental influences on the reaction. The resulting knowledge was used in a second step for producing crosslinked polymer networks based on olive oil and 1,8-ODT and examining the surface properties of such coatings applied to cotton linters sheets (Figure 4a). 1H-NMR spectroscopy (Figure S1) revealed the olive oil batch used contained 3.03 C=C double bonds per triglyceride, as calculated from olefinic and methyl proton signal integrals, and thereby allowed calculation of the required amount of thiol to obtain a precise stoichiometric functionality ratio. Following UV irradiation, the resulting coatings on glass substrates proved insoluble in a wide range of organic solvents, so successful network formation can be assumed. Qualitative proof of thiol-ene reaction is given by FTIR spectra (Figure 4b) of the crosslinked coating after removal from the glass substrate, as compared to pure olive oil and to the untreated olive oil/thiol mixture, showing the disappearance of the C=C band at 3005 cm−1 as well as trans bond formation caused by reversible thiol addition at 967 cm−1. DSC measurements (Figure 4c) equally point towards a successful crosslinking reaction. The thermograms show the melting peak of the untreated olive oil/thiol mixture at −10 °C prior to the crosslinking reaction. This very sharp peak represents the structurally uniform olive oil triglycerides with their rather defined melting temperature, as 1,8-ODT shows no thermal transition in the examined temperature range. After crosslinking, a strong broadening of the melting peak is observed combined with a slight shift of the maximum to −7 °C, while a second melting transition at 10–11 °C becomes visible. These changes originate from the formation of triglyceride dimers and oligomers not yet integrated into the polymeric network. The peak intensity and sum of the integrals of both melting transitions decreases with increasing irradiation intensity from −69 J/g for the untreated mixture to −19 J/g after 20 J/cm2 UV treatment. The decreasing integral proves that the amount of liquid low molecular weight monomer and oligomer molecules decreases. More and more olive oil molecules become integrated into the solidified crosslinked polymer network, which accordingly does not have a melting point. The main part of the reaction occurs already after submission to very low irradiation intensities below 5 J/cm2, as indicated by the melting transition integral, which shows the strongest decrease in that area. This corresponds to the observation made during 1H-NMR analysis of the oleic acid-based model system. Reference experiments of UV treatment of pure olive oil confirmed the necessity of thiol presence for successful double bond consumption reactions as equally observed in the case of oleic acid. Following the chemical characterization, the surface properties of olive oil/1,8-ODT coatings applied onto cotton linters sheets using size pressing were examined. Optical microscopy (Figure 5a,d) and scanning electron microscopy (SEM, Figure 5b,e) allowed comparison of the sheet surface before and after coating. For uncoated cotton linters paper, individual fibers and the characteristic porous structures of the paper sheet are clearly visible and well defined both in optical microscopy and SEM, respectively. Imaging of the coated samples shows complete coverage of individual fibers with coating material, and levelling out of the entire substrate surface due to pore filling. The optical profilometry images (Figure 5c,f) show that although the fiber structure gets less distinct, the overall maxima and minima do not significantly change. Measuring roughness parameters using both tactile and optical profilometry showed that interestingly, there was no significant difference between coated and uncoated substrates, with an average roughness (Ra) of approximately 6 μm, a root mean square roughness (Rq) of approximately 8 μm and a z-scale roughness (Rz) of approximately 40 μm. The surface roughness parameters (Sa, Sq and Sz) were generally slightly higher, with the most prominent difference in the z-scale area roughness that amounts to approximately 125 μm (Table 1) due to the inherent roughness of the paper surface. Static water contact angle measurements were performed in sessile drop configuration both on coated hydrophobized glass and cotton linters paper (Figure 6). Due to the high hydrophilicity and porosity of uncoated cotton linters paper, the water droplet is immediately absorbed and does not allow for contact angle investigation. Although coating with olive oil and crosslinking already lead to a significant increase in contact angles, hydrophobicity was only observed after coating with and crosslinking of the thiol-oil mixture, with the contact angle finally increasing to approximately 120°. The contact angle remained stable for at least two minutes, showing good absorption inhibition (Figure S2). As a smooth reference substrate, coated glass showed a contact angle increase from (82.5 ± 1.1)° to (112.5 ± 3.5)°. This is significantly higher than for instance the contact angle below 90° observed for a crosslinked glass coating based on tung oil and a dithiolated isosorbide [38]. However, the superhydrophobic contact angles, approximately 160°, observed for hybrid organic–inorganic coatings are far from being attainable [25]. Covalent attachment of fatty acids or oils onto cellulosic substrates lead to similar or lower contact angles, with the exception being the metathesis polymerization resulting in contact angles of up to 145° [1,3,4,5,6]. As the surface roughness did not change significantly after coating, the increase in hydrophobicity can be attributed solely to the modification of the cellulose surface chemistry by thiol-ene photocrosslinking. These results clearly demonstrate the potential of polymer networks based on vegetable oils for use in hydrophobic paper coatings. 4. Conclusions and Outlook Our report shows that it is possible to generate hydrophobic barriers on paper by applying a coating based on natural olive oil and a dithiol followed by UV-induced photocrosslinking polymerization in bulk without prior derivatization of any of the components nor the addition of a photoinitiator. The latter conclusions have been drawn from model studies using 1,8-octanedithiol as crosslinker for the natural oil. Crosslinking of the olive oil results in smooth films that exhibit contact angles well above 100° and therefore show water-repellent properties. Avoiding the use of solvents and photoinitiators allows reducing the consumption of supplementary chemicals to an absolute minimum. Yet in our model studies, the crosslinker is not a biobased precursor. In upcoming steps, the latter will be replaced by natural, ideally low-odor or odorless, biogenic thiols. In addition, future steps will also account for investigations into material-efficient applications, barrier properties, ageing effects, recyclability and biodegradability, in order to assess a possible transfer of these model barrier films into barriers useful for packaging or construction materials. Acknowledgments The authors thank the NMR service-group at the Department of Chemistry, TU Darmstadt for service NMR measurements. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/polym14091773/s1, Table S1: Attribution of IR spectral bands of oleic acid/thiol mixture to functional groups; Figure S1: 1H-NMR spectrum of olive oil; Figure S2: Time-dependent evolution of contact angles on cotton linters paper coated with crosslinked olive oil/1,8-ODT mixture. Click here for additional data file. Author Contributions Conceptualization, A.L.-Z. and A.G.; investigation, A.L.-Z., C.C. and A.G.; visualization and writing—original draft preparation, A.L.-Z.; writing—review and editing, all authors; supervision, A.G. and M.B. 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 authors. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Propagation steps of the thiol-ene reaction, the first step including thiol addition via cis–trans isomerization comprising an addition–isomerization–elimination process, the second step being the rate-determining hydrogen abstraction from another thiol molecule. Figure 2 (a) Reaction scheme for crosslinking oleic acid with 1,8-octanedithiol and coating application; (b) 1H-NMR spectrum for untreated and crosslinked reactant mixtures as basis for calculating the double bond conversion; (c) double bond conversions at different irradiation intensities; (d) water contact angles on paper correlating to different irradiation intensities. Figure 3 (a) FTIR spectra of pure oleic acid, the untreated oleic acid/thiol mixture and the crosslinked coating highlighting the transformations characterized by double bond conversion; (b) FTIR spectra of uncoated cotton linters paper, cotton linters paper coated with crosslinked oleic acid/thiol mixture and the same after Soxhlet extraction show that the coating is not permanently linked to substrate. Figure 4 (a) Reaction scheme for thiol-ene reaction of olive oil with 1,8-ODT; (b) comparison of the FTIR spectra of fresh olive oil, the untreated olive oil/1,8-ODT mixture and the crosslinked mixture; (c) DSC curves of the olive oil/1,8-ODT mixture before and after crosslinking with different UV intensities showing decreasing integrals for the combined melting transitions. Figure 5 Surface characterization of uncoated (a–c) cotton linters paper and (d–f) cotton linters paper coated with olive oil/1,8-ODT using (a,d) optical microscopy, (b,e) SEM and (c,f) optical profilometry. Figure 6 Static water contact angles (sessile drop) measured on (a) cotton linters paper coated with pure olive oil; (b) cotton linters paper coated with pure olive oil and submitted to UV irradiation; (c) cotton linters paper coated with the olive oil/thiol mixture and submitted to UV crosslinking; (d) glass coated with the olive oil/thiol mixture and submitted to UV crosslinking as a smooth reference substrate for comparison. polymers-14-01773-t001_Table 1 Table 1 Roughness parameters determined from tactile profilometry (profile roughness values) and optical profilometry (surface roughness values). Ra (μm) Rq (μm) Rz (μm) Sa (μm) Sq (μm) Sz (μm) Cotton linters paper, uncoated 6.3 ± 0.7 8.0 ± 0.9 39.8 ± 4.8 7.6 ± 0.6 10.0 ± 0.7 124.2 ± 12.0 Cotton linters paper, olive oil coating 6.1 ± 0.6 7.8 ± 0.8 40.8 ± 5.5 6.8 ± 0.6 9.3 ± 1.0 126.3 ± 10.8 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Dankovich T.A. Hsieh Y.L. Surface modification of cellulose with plant triglycerides for hydrophobicity Cellulose 2007 14 469 480 10.1007/s10570-007-9132-1 2. Saha P. Manna S. Sen R. Roy D. Adhikari B. Durability of lignocellulosic fibers treated with vegetable oil–phenolic resin Carbohydr. Polym. 2012 87 1628 1636 10.1016/j.carbpol.2011.09.070 3. Crépy L. Chaveriat L. Banoub J. Martin P. Joly N. Synthesis of cellulose fatty esters as plastics-influence of the degree of substitution and the fatty chain length on mechanical properties ChemSusChem 2009 2 165 170 10.1002/cssc.200800171 19180609 4. 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==== Front Plants (Basel) Plants (Basel) plants Plants 2223-7747 MDPI 10.3390/plants11091268 plants-11-01268 Article GC/MS Analyses of the Essential Oils Obtained from Different Jatropha Species, Their Discrimination Using Chemometric Analysis and Assessment of Their Antibacterial and Anti-Biofilm Activities Gamal El-Din Mariam I. 1† https://orcid.org/0000-0002-5871-2639 Youssef Fadia S. 1† https://orcid.org/0000-0001-6210-3628 Altyar Ahmed E. 2 https://orcid.org/0000-0002-9270-6267 Ashour Mohamed L. 13* Elshafie Hazem Salaheldin Academic Editor Camele Ippolito Academic Editor Sofo Adriano Academic Editor 1 Department of Pharmacognosy, Faculty of Pharmacy, Ain-Shams University, Abbasia, Cairo 11566, Egypt; dr_mariam_gamal_eldin@pharma.asu.edu.eg (M.I.G.E.-D.); fadiayoussef@pharma.asu.edu.eg (F.S.Y.) 2 Department of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, P.O. Box 80260, Jeddah 21589, Saudi Arabia; aealtyar@kau.edu.sa 3 Department of Pharmaceutical Sciences, Pharmacy Program, Batterjee Medical College, P.O. Box 6231, Jeddah 21442, Saudi Arabia * Correspondence: ashour@pharma.asu.edu.eg † These authors contributed equally to this work. 09 5 2022 5 2022 11 9 126815 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/). The essential oils of Jatropha intigrimma, J. roseae and J. gossypifolia (Euphorbiaceae) were analyzed employing GC/MS (Gas Chromatography coupled with Mass Spectrometry) analyses. A total of 95 volatile constituents were identified from J. intigrimma, J. gossypifolia and J. roseae essential oils, accounting for 91.61, 90.12, and 86.24%, respectively. Chemometric analysis using principal component analysis (PCA) based on the obtained GC data revealed the formation of three discriminant clusters due to the placement of the three Jatropha species in three different quadrants, highlighting the dissimilarity between them. Heneicosane, phytol, nonacosane, silphiperfol-6-ene, copaborneol, hexatriacontane, octadecamethyl-cyclononasiloxane, 9,12,15-Octadecatrienoic acid, methyl ester and methyl linoleate constitute the key markers for their differentiation. In vitro antibacterial activities of the essential oils were investigated at doses of 10 mg/mL against the Gram-negative anaerobe Escherichia coli using the agar well diffusion method and broth microdilution test. J. gossypifolia essential oil showed the most potent antimicrobial activity, demonstrating the largest inhibition zone (11.90 mm) and the least minimum inhibitory concentration (2.50 mg/mL), followed by the essential oil of J. intigrimma. The essential oils were evaluated for their anti-adhesion properties against the Gram-negative E. coli biofilm using a modified method of biofilm inhibition spectrophotometric assay. J. intigrimma essential oil showed the most potent biofilm inhibitory activity, demonstrating the least minimum biofilm inhibitory concentration (MBIC) of 31.25 µg/mL. In silico molecular docking performed within the active center of E. coli adhesion protein FimH showed that heneicosane, followed by cubebol and methyl linoleate, displayed the best fitting score. Thus, it can be concluded that the essential oils of J. gossypifolia and J. intigrimma leaves represent promising sources for antibacterial drugs with antibiofilm potential. antibacterial antibiofilm chemometrics essential oils euphorbiaceae GC/MS Jatropha molecular docking sustainability of natural resources drug discovery Deanship of Scientific Research (DSR) at King Abdulaziz University (KAU)RG-25-166-43 This research was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University (KAU), Jeddah, Saudi Arabia, under grant number RG-25-166-43. ==== Body pmc1. Introduction Essential oils are natural, volatile components with a complex nature, possessing mostly fragrant odors manufactured by the plants as secondary metabolites. They are commonly prepared either by hydro-distillation or steam distillation; meanwhile, they are highly popular due to their observable biological potential, which is highly attributed to their different classes of compounds, particularly terpenoids. They are popular for their antimicrobial, antiviral, anti-inflammatory, analgesic, spasmolytic, anticancer, anti-aging and anesthetic activities, in addition to their wide consumption in the preservation of foods [1,2,3,4,5]. Microorganisms, a severe hazard attacking human beings, are characterized by the formation of an architectural colony inside an extracellular matrix of polymeric substances termed a biofilm. Bacterial biofilms are highly pathogenic and can trigger nosocomial infections [6,7]. It is worth highlighting that the National Institutes of Health (NIH) declared that 65% of microbial and 80% of chronic infections are accompanied by biofilm formation, which in turn occurs through many steps [4]. These steps comprise the attachment of the bacteria with living or non-living surfaces that are consequently followed by the production of a micro-colony that in turn forms three-dimensional structures and ends up, after maturation, with detachment [8]. Bacterial biofilms are highly contributed to the pronounced resistance of bacteria toward both antibiotics as well as the human immune system and thus prohibition of biofilm formation is highly adopted as a successful strategy combating microbial infections and antibiotic resistance [9]. Hence, searching for effective anti-biofilm agents, particularly from natural origin, has become mandatory worldwide. Jatropha is a genus of flowering plants belonging to the Euphorbiaceae that includes approximately 175 succulent plants, shrubs and trees. Jatropha is an extensively strong and economical plant genus that natively grows in tropical and subtropical regions propagating on wasteland. Different species of the genus have been reported for their antimicrobial activities, as well as their richness in diterpenes [10]. J. intigrimma, J. roseae and J. gossypifolia are three species that belong to the genus Jatropha. The essential oils of J. intigrimma and J. gossypifolia leaves were previously analyzed for their chemical composition. In addition, J. intigrimma and J. gossypifolia leaf oils were reported to possess strong antimicrobial activities versus Bacillus cereus and Staphylococcus aureus for the former and against Escherichia coli, Enterococcus faecium, and Staphylococcus aureus for the latter [11,12]. Thus, herein a comparative study was performed for the first time on the leaves of J. intigrimma, J. roseae and J. gossypifolia essential oils that were qualitatively and quantitatively examined for their volatile constituents employing GC/MS (Gas Chromatography coupled with Mass Spectrometry analyses. The volatile oil yield, the major volatile constituents and their percent in each of the examined oils were estimated. This was consequently followed by their discrimination using chemometric analysis to easily detect the differences among the different species, which undoubtedly reflects the variation in their biological behavior. The different essential oils were investigated for their antibacterial activities against the Gram-negative anaerobe Escherichia coli. In addition, their inhibitory activities against E. coli biofilm formation were assessed for the first time, as this represents the major cause of gastroenteritis, urinary tract infections and neonatal meningitis. The major compounds identified in the bioactive essential oil were further subjected to in silico studies to confirm the obtained results. Thus, herein we aimed to find new antimicrobial agents of natural origin with anti-biofilm potential that could be incorporated in pharmaceutical dosage form applied topically to eliminate microbial infection. 2. Results 2.1. Chemical Composition of the Essential Oils of J. intigrimma, J. gossypifolia and J. roseae Leaves A comparative investigation of the volatile constituents of the three Jatropha species, namely J. intigrimma Jacq., J. gossypifolia L. and J. roseae Radcl.-Sm., was conducted for the first time in the present study. The chemical compositions of the essential oils of the fresh leaves of the three species were qualitatively and quantitatively investigated by GC-MS (Figure 1) and compared with the previous results obtained by investigating the essential oils of J. intigrimma and J. gossypifolia grown in Nigeria. The yields of J. intigrimma, J. gossypifolia and J. roseae essential oils were estimated as 0.31 ± 0.11, 0.21 ± 0.09, and 0.19 ± 0.11% (v/w), respectively. A total of 95 volatile constituents were identified from the GC/MS analyses of J. intigrimma, J. gossypifolia and J. roseae essential oils, accounting for 91.61, 90.12, and 86.24% of their total oil content, respectively. A list of the identified volatile constituents, the percentage of each volatile component, their experimental retention indices and the literature retention indices, in an order of increasing retention indices (RIs) on the Rtx-5MS column, are summarized in Table 1. Twenty-two volatile constituents were identified in the oil of J. intigrimma leaves, in which fatty acid esters represented the most prevailing class, constituting 22.26% of the oil constituents. In J. intigrimma oil, 9,12,15-octadecatrienoic acid methyl ester (10.77%), methyl linoleate (5.65%), and hexadecanoic acid methyl ester (3.14) were the most abundant fatty acid esters identified. Furthermore, hexatriacontane, octadecamethyl cyclononasiloxane, D-limonene, phytol and β-ionone were present in J. intigrimma oil in considerable quantities, representing 28.44, 8.42, 5.35, 3.85 and 3.53%, respectively. Concerning J. gossypifolia oil, 61 volatile components were identified in which copaborneol, phytol and eudesma-4(15), 7-dien-1β-ol constituted the major volatile constituents of the oil, representing 15.70, 10.33 and 7.01% of the oil content, respectively. It is worth mentioning that sesquiterpene hydrocarbons and oxygenated sesquiterpenes are the predominant classes in J. gossypifolia oil, accounting for 74.86% of the oil content. Isosativene (4.08%), α-copaene (5.87%), spathulenol (3.63%), muurola-4,10(14)-dien-1β-ol (4.62%) and caryophylla-4(12),8(13)-dien-5α-ol (4.82%) were the most abundant sesquiterpenes present. Meanwhile, 44 constituents were identified in J. roseae oil, where phytol, hexatriacontane and heneicosane constituted the major volatile constituents, representing 15.25, 14.50 and 12.67% of J. roseae oil, respectively. It is noteworthy that J. roseae oil is rich in diterpenes and higher alkanes, accounting for 63.48 % of the oil. However, different sesquiterpene hydrocarbons, oxygenated sesquiterpenes and fatty acids esters can also be observed in J. roseae oil viz. silphiperfol-6-ene (6.90%), β-ionone (3.09%), α-guaiene (2.00%), 7,10-hexadecadienoic acid, methyl ester (1.36%), 9,12-octadecadienoic acid, methyl ester (2.47%) and 9,12,15-octadecatrienoic acid, methyl ester (3.18%). A scheme representing the major compounds present in the three Jatropha species is presented in Figure 2. 2.2. Discrimination of the Three Jatropha Species Using GC Data Coupled with Chemometrics Chemometric analysis was adopted using an unsupervised pattern recognition technique represented by principal component analysis (PCA) based on the obtained GC data. Chemometric analysis constitutes an advanced approach for the better discrimination of closely related species, relying upon data gathered from different chromatographic and spectroscopic techniques. Principal component analysis (PCA) was initially performed to categorize data and to correlate between the examined samples and the used variables [13]. PCA based upon the number as well as the relative peak area of volatile constituents obtained from GC spectra for different Jatropha species, illustrated in Figure 3, revealed the formation of three discriminant clusters representing the three species. PCA score plot for principal components (PCs), which are PC1 versus PC2, illustrated in Figure 3A accounts for 71% and 29% of the total variance, respectively. This perfectly results in the placement of the three Jatropha species in three different quadrants, which in turn highlights the evident dissimilarity between the three species. Both PC1 and PC2 effectively discriminate between J. gossypifolia and J. roseae, where the former lies in the left lower quadrant showing negative values for both PCs in contrast to the latter that is positioned in the upper right quadrant revealing positive values for both PCs. Regarding J. intigrimma that lies in the right lower quadrant in the PCA score plot, only PC1 could effectively discriminate between it and J. gossypifolia, as J. intigrimma showed positive values, while J. gossypifolia showed negative values for PC1. However, J. intigrimma and J. roseae could be discriminated only via PC2, where the former displayed negative values and the latter showed positive values. By careful analysis of the loading plot illustrated in Figure 3B, it was clearly obvious that heneicosane, phytol, nonacosane and silphiperfol-6-ene were the key markers for the discrimination of J. roseae from the other two species, while copaborneol constitutes the key marker for its differentiation from the other two species. Regarding J. intigrimma, hexatriacontane, octadecamethyl-cyclononasiloxane, 9,12,15-Octadecatrienoic acid, methyl ester and methyl linoleate represent the key markers. The results from chemometric analysis coupled with GC data allowed the clustering of samples, and this undoubtedly leads to better visualization of the differences among the essential oils obtained from different Jatropha species and in turn reflected the differences between their biological behaviors. 2.3. Evaluation of Antibacterial and Anti-Biofilm Activity 2.3.1. Antibacterial Activities of J. intigrimma, J. gossypifolia and J. roseae Essential Oils In vitro antibacterial activities of the essential oils obtained from the leaves of the three Jatropha species, J. intigrimma, J. gossypifolia and J. roseae, were investigated at doses of 10 mg/mL against the Gram-negative anaerobe Escherichia coli. The agar well diffusion method was adopted for calculating the mean diameter of inhibition zones produced by the three oil samples in comparison with the standard antimicrobial drug, Gentamicin. Furthermore, the minimum inhibition concentrations (MIC) values were estimated for the oil samples using the broth microdilution test. The essential oil obtained from J. gossypifolia leaves demonstrated the most potent antimicrobial activity against E. coli, demonstrating the largest inhibition zone (11.90 ± 0.46 mm) and the least minimum inhibitory concentration (2.50 mg/mL), followed by the essential oil obtained from J. intigrimma leaves. The latter exhibited an inhibition zone of 9.57 ± 0.40 mm and an MIC of 5.00 mg/mL. The oil of J. roseae demonstrated the least inhibition zone (8.93 ± 0.60 mm) but had MIC values equal to those of J. intigrimma oil of 5.00 mg/mL. The results were compared to the standard gentamycin that exhibited a mean inhibition zone of 27.09 ± 0.01 mm at a dose of 4 µg/mL and demonstrated an MIC of 2 µg/mL. This experiment was repeated in triplicate and data were represented as mean ± S.D. 2.3.2. Antibiofilm Activities of J. intigrimma, J. gossypifolia and J. roseae Essential Oils The essential oils of the different Jatropha species were further evaluated for their potential anti-adhesion properties against the Gram-negative E. coli biofilm. A modified method of biofilm inhibition spectrophotometric assay was adopted for the determination of the inhibitory activity of essential oils against the formation of E. coli biofilm and for the calculation of the minimum concentration required for complete inhibition of visible biofilm cell growth (MBIC). The essential oil of J. intigrimma demonstrated the most potent biofilm inhibitory activity, demonstrating the least minimum biofilm inhibitory concentration (MBIC) of 31.25 µg/mL. However, the essential oils of J. roseae and J. gossypifolia demonstrated less potent antibiofilm activities, demonstrating minimum biofilm inhibitory activities (MBIC) of 250 and above 1000 µg/mL, respectively, as displayed in Table 2. 2.4. Molecular Docking Studies of Adhesion Proteins with Major Constituents in Jatropha Essential Oils In silico molecular docking of the major compounds identified from Jatropha essential oils was performed within the active site of the adhesion proteins associated with E. coli that enable the bacterium to attach to the surfaces and consequently form its invasive biofilm as FimH (PDB ID 1TR7; 2.10 Å) downloaded from the protein data bank. The docking experiments were carried out using Discovery Studio 4.5 (Accelrys Inc., San Diego, CA, USA) using the C-Docker protocol. The results displayed in Table 3 revealed that heneicosane, followed by cubebol and methyl linoleate, displayed the best fitting score within the active center of E. coli adhesion protein FimH with free binding energies equal to −30.68, −8.92 and −4.55 Kcal/mole, respectively. Heneicosane forms two alkyl and π-alkyl bonds with Ile52 and Tyr48, in addition to the formation of Van der Waals interactions with many amino acid residues at the active center (Figure 4A). However, cubebol forms one conventional H-bond with Asp140, in addition to two alkyl and π-alkyl bonds with Ile13 and Phe142 together with Van der Waals bonds at the active site (Figure 4B). Regarding methyl linoleate, it forms two conventional H-bonds with Asn135 and Phe1, one alkyl bond with Ile52, in addition to three C-H bonds with Asp54 and Asn46, together with many Van der Waals interactions, as shown in Figure 4C. 3. Discussion This study represents the first report investigating the volatile constituents of J. rosea leaf oil. In addition, a comparative investigation of the volatile constituents of the three Jatropha species, J. intigrimma, J. gossypifolia and J. roseae, was conducted. A previous study on J. intigrimma leaves obtained from Nigeria reported β-ionone as one of the major volatile constituents of the oil, which was also identified in our study in a lower concentration. However, the other major constituents reported by Eshilokun et al., pentadecanal and 1,8-cineole, were absent in the present study [12]. Previous literature by Aboaba et al. on J. gossypifolia leaves grown in Nigeria reported the predominance of sesquiterpenes accounting for 74.3% of the oil content, which is almost relative to our study [14]. Meanwhile, fatty acids were reported by Ababa et al. in J. gossypifolia oil despite their scarcity in our J. gossypifolia oil. The major constituents reported by Aboaba et al., germacrene and hexahydrofarnesyl acetone, were identified in the present study but in negligible quantities. Another study in different regions of Nigeria [11] reported the predominance of phytol (33.4%) and linalool (9.81%) in J. gossypifolia oil, which were identified in the current study in different percentages. The chemical composition variability among the essential oils of Jatropha species grown in Egypt and those in different regions of Nigeria or elsewhere are attributable to multiple exogenous and endogenous factors, such as seasonal variation, geographical region affecting soil, precipitation and light exposure, extraction method, and the age of the plant and its different chemotypes [15]. Additionally, chemometric analysis was adopted using an unsupervised pattern recognition technique represented by principal component analysis (PCA) based on the obtained GC data. PCA based upon the number, as well as the relative peak area, of volatile constituents obtained from GC spectra for different Jatropha species revealed the formation of three discriminant clusters due to the placement of the three Jatropha species in three different quadrants, which in turn highlights the evident dissimilarity between the three species evidenced by the score plot. By careful analysis of the loading plot, it was obvious that heneicosane, phytol, nonacosane and silphiperfol-6-ene, copaborneol, hexatriacontane, octadecamethyl-cyclononasiloxane, 9,12,15-Octadecatrienoic acid, methyl ester and methyl linoleate constituted the key markers for the differentiation of the three species. Essential oils have long been known for their antimicrobial potential that made them crucial in different fields, including the food industry, preservation and medication [16]. To the best of our knowledge, few reports have addressed the antimicrobial activities of essential oils of different Jatropha species. Our current study presented the first report on the antimicrobial activities of J. intigrimma and J. roseae essential oils against E. coli Gram-negative bacterium and compared them with the activity of J. gossypifolia essential oil. The results of the in vitro antibacterial activities of the essential oils exhibited the superior potency of J. gossypifolia essential oil, followed by J. intigrimma essential oil, against the Gram-negative anaerobe E. coli. Results were in accordance with the previous literature reporting the bacteriostatic activity of J. gossypifolia leaf oil against the Gram-negative bacterium E. coli at a dose of 0.10 mg/mL [11]. It is worth mentioning that phytol, a major constituent of J. gossypifolia leaf oil constituting 10.33 % of the oil content, was previously reported for its potent antimicrobial activity against Escherichia coli, exhibiting growth inhibition at a minimum concentration (MIC) of 62.5 μg/mL [17,18]. Moreover, caryophylline oxide, identified in J. gossypifolia leaf oil, was reported to possess moderate inhibitory activity against Gram-negative E. coli with an estimated MIC of 60 ppm [19]. Bacterial biofilms are colonies of microorganisms lying in a matrix of polysaccharides attached to surfaces. They represent physical barriers that inhibit the penetration of antimicrobials to their target sites. Hence, bacterial biofilms represent rational biological risks in drinking water, food, and clinical and industrial environments [20]. Nowadays, increased interest has been directed toward investigating the different mechanisms of inhibiting bacterial biofilm formation and growth. Because attachment represents the initial step in almost all types of biofilm formation, the antiadhesive properties of natural products have recently become a prime interest of study in an aim for the early prevention of microbial biofilm and inhibiting the formation of micro colonies [21]. Furthermore, inhibiting the cell attachment of microbial biofilms has been found to be more readily achieved than preventing the growth of already established biofilms [22]. Hence, the three Jatropha oils were investigated for their inhibitory activities against E. coli adhesion. This study represents the first report of the antibiofilm activities of the essential oils of the three Jatropha species. The results demonstrated the superior antibiofilm activity of the essential oil of J. intigrimma leaves compared to the other two Jatropha oils. In addition, in silico molecular docking of the major compounds identified from Jatropha essential oils was performed within the active site of one of the adhesion proteins associated with E. coli that enables the bacterium to attach to the surfaces and consequently forms its invasive biofilm, FimH. The docking experiments revealed that heneicosane, followed by cubebol and methyl linoleate, displayed the best fitting score within the active center of E. coli adhesion protein FimH with free binding energies equal to −30.68, −8.92 and −4.55 Kcal/mole, respectively. Previous literature has reported the anti-biofilm activities of different fatty acids and their methyl esters [23,24]. In addition, the monoterpene D-Limonene, an essential component of J. intigrimma essential oil, has been reported to possess strong anti-biofilm activity against the heterotrophic, Gram-negative, rod-shaped bacterium Aeromonas hydrophila isolated from fish [25]. The anti-adhesive properties and the capabilities of inhibiting the initial biofilm formation can be explained by the possibility of interference with the attraction forces that support the bacterial film with the affected surface or by interrupting the access of vital nutrients for bacterial growth and adhesion [26]. Thus, the antibiofilm of the essential oil could be attributed to the synergistic action of the existing compounds. 4. Materials and Methods 4.1. Plant Material The fresh leaves of the three Jatropha species: J. intigrimma Jacq., J. gossypifolia L. and J. roseae Radcl.-Sm. (Euphorbiaceae) were collected from plants grown in Mazhar Botanical Garden, Giza, Egypt, on August 2020. The plants were kindly identified and authenticated by Eng. Terase Labib, Consultant of Plant Taxonomy at the Ministry of Agriculture and El-Orman Botanical Garden, Giza, Egypt. Voucher specimens of the authenticated plant with codes BMC-JI-MLA, BMC-JG-MLA and BMC-JR-MLA were kept at the Department of Pharmaceutical Sciences, Pharmacy Program, Batterjee Medical College. 4.2. Chemicals, Reagents and Strains Dimethyl sulfoxide (DMSO), crystal violet and trypan blue dye were obtained from Sigma (St. Louis, MO, USA). Crystal violet stain was prepared as 1% using 0.5% (w/v) crystal violet and 50% methanol that were adjusted to volume using distilled water and subsequently filtered through a Whatman No.1 filter paper. The studied bacterial strain was Escherichia coli, ATCC 25922, obtained from the American type culture collection (ATCC). 4.3. Preparation of Essential Oils The fresh leaves of the three Jatropha species were separately hydro-distillated for 6 h utilizing a Clevenger-type apparatus. The obtained essential oils were dried over anhydrous sodium sulfate and gathered in separate and sealed vials that were maintained at −30 °C until further analyses. The yield was calculated as % v/w after being determined in triplicate, where calculation was performed based on the initial plant weight. 4.4. Metabolic Profiling of the Essential Oils Obtained from J. intigrimma, J. gossypifolia and J. roseae Using GC/MS Analysis Gas chromatography coupled with Mass Spectrometry (GC/MS) analyses were done on Shimadzu GCMS-QP 2010 (Shimadzu Corporation, Koyoto, Japan) accompanied by Rtx-5MS (30 m × 0.25 mm i.d. × 0.25 µm film thickness) capillary column (Restek, PA, USA) and attached to a Shimadzu mass spectrometer. An initial set of temperature of the column at 50 °C for 3 min was done that was gradually elevated from 50 °C to 300 °C at a rate of 5 °C/min, followed by isothermal maintenance for 10 min at 300 °C. The injector temperature was maintained at 280 °C, while the interface and the ion source temperature were kept at 220 and 280 °C, respectively. The flow rate of helium, which was used as a carrier gas, was 1.37 mL/min. One microliter was injected from the diluted sample with a concentration of 1% v/v through a split mode using a split ratio of 15:1. The mass spectrum was recorded using an EI mode of 70 eV in the range of m/z 35 to 500. Compound quantitation relied upon the normalization method, taking the reading of three chromatographic runs. Identification of compounds was achieved depending on the retention indices of the detected compounds with regard to a homologous series of n-alkanes (C8–C28) that were injected under the same conditions and via comparison mass spectra of the detected compounds with those recorded in the Wiley library database as well as the National Institute of Standards and Technology (NIST) and together with the literature [1,27,28,29]. 4.5. Discrimination of the Three Jatropha Species Using GC Data Coupled with Chemometrics Chemometric analysis using principal component analysis (PCA) as an unsupervised pattern recognition technique was done based on the obtained GC using CAMO’s Unscrambler® X 10.4 software (Computer-Aided Modeling, As, Norway) as previously described [3,5]. This was done in an effort to allow the clustering of samples, which undoubtedly leads to better visualization of the differences among the essential oils obtained from different Jatropha species. 4.6. Evaluation of Antibacterial and Anti-Biofilm Activity 4.6.1. Susceptibility Test Using the Agar Well Diffusion Method Susceptibility tests were performed according to NCCLS recommendations (National Committee for Clinical Laboratory Standards) [30]. Screening tests concerning the inhibition zone were performed employing the well diffusion assay previously conducted by Hindler et al. [31]. Preparation of the inoculum suspension was performed from cultures grown overnight on an agar plate that were concomitantly inoculated into Mueller–Hinton broth. A sterile swab was adopted for the inoculation of Mueller–Hinton agar plates (fungi using malt agar plates) after being immersed in the inoculum suspension. The examined samples at different concentrations (2.5, 5 and 10 mg/mL) were solubilized in dimethyl sulfoxide (DMSO) and the inhibition zones were determined around each well after 24 h at 37 °C where the control was prepared using DMSO. 4.6.2. Determination of the Minimum Inhibitory Concentration (MIC) Using the Broth Microdilution Method The minimum inhibitory concentration (MIC) was determined as previously recommended by the Clinical and Laboratory Standards Institute (CLSI). Briefly, the dilution of a stock solution composed of 10% of the examined oil in the brain heart infusion broth (BHI) in two-fold serial dilutions was performed to obtain 0.02 to 25 mg/mL concentrations at a total volume of 100 mL per well in 96-well microtiter plates. One-hundred milliliters of each tested strain adopting a concentration of 1 × 106 CFU/mL were added to each well, followed by their incubation at 37 °C in appropriate conditions. The medium was used as the non-treated control, while 10% DMSO was employed as the negative control, whereas 0.1% (w/v) CHX was the positive control. MIC is the lowest concentration that completely prohibited growth when compared to the non-treated control. All experiments were repeated three times in duplicate. 4.6.3. Evaluation of Anti-Biofilm Activity The volatile oil samples obtained from hydro-distillation of the three Jatropha species were evaluated for their inhibitory activity against biofilm formation of the Gram-negative anaerobe Escherichia coli. Biofilm inhibition assay was performed in 96-well plates adopting the modified method of biofilm inhibition spectrophotometric assay [32]. Briefly, 100 μL of an Escherichia coli cell suspension was added to a 96-well titer plate together with different concentrations of samples (1000, 500, 250, 125, 62.5, 31.25, 15.63 and 7.81 μg/mL); in addition, DMSO was added and incubated for 24 h at 37 °C. After incubation, the liquid suspension was removed, and 100 μL of 1% w/v aqueous solution of crystal violet was added. Removal of the excess crystal violet was achieved after 30 min of staining at room temperature followed by washing the wells thoroughly and the addition of 95% ethanol and incubation for 15 min. The reaction mixture was read spectrophotometrically at a wavelength of 570 nm using a microplate reader (TECAN, Inc.) after being shaken gently. The percent of inhibition of biofilm formation was determined according to the following equation:% inhibition = OD in control − OD in treatment × 100 OD in control. The relation between biofilm formation inhibitory % and drug concentration is plotted to obtain the inhibitory curve after treatment with the specified compound. MBIC was the concentration required to completely inhibit biofilm formation. 4.7. Molecular Docking Studies of Adhesion Proteins with Major Constituents in Jatropha Essential Oils Molecular docking analysis was performed on the major constituents existing in Jatropha essential oils regarding adhesion proteins associated with E. coli that enable the bacterium to attach to the surfaces and consequently form its invasive biofilm as FimH (PDB ID 1TR7; 2.10 Å) [33]. This protein was downloaded from the protein data bank and docking experiments were carried out using Discovery Studio 4.5 (Accelrys Inc., San Diego, CA, USA) using the C-Docker protocol as previously reported [5,34,35,36], where binding energies (∆G) were calculated from the following equation: ΔGbinding = Ecomplex − (Eprotein + E ligand) Where; ΔGbinding: The ligand–protein interaction binding energy, Ecomplex: The potential energy for the complex of protein bound with the ligand, Eprotein: The potential energy of protein alone and Eligand: The potential energy for the ligand alone. 5. Conclusions In conclusion, the essential oil obtained from J. intigrimma, J. gossypifolia and J. roseae leaves revealed considerable variation, as revealed by GC analyses. This variation becomes clearly obvious when coupled with chemometric analysis that results in the placement of the three Jatropha species in three different quadrants, which in turn highlights the evident dissimilarity between the three species. Moreover, the essential oils of J. gossypifolia and J. intigrimma leaves represent promising sources for a new generation of antibacterial drugs. Their distinctive antibacterial and antibiofilm activities are probably attributed to their major bioactive chemical constituents, as well as the possible synergistic effect among them. To further confirm the obtained results, in silico molecular docking of the major compounds identified from Jatropha essential oils was performed within the active center of E. coli adhesion protein FimH and results showed that heneicosane followed by cubebol and methyl linoleate displayed the best fitting score. Thus, additional in vivo studies and bioavailability studies are highly recommended to ascertain the obtained results. Acknowledgments The Deanship of Scientific Research (DSR) at King Abdulaziz University (KAU), Jeddah, Saudi Arabia, funded this project under grant no. RG-25-166-43. Therefore, all the authors acknowledge, with thanks, DSR for technical and financial support. Author Contributions Conceptualization, methodology, software, validation, M.I.G.E.-D. and F.S.Y.; resources, A.E.A.; writing—original draft preparation, M.I.G.E.-D. and F.S.Y.; writing—review and editing, A.E.A. and M.L.A.; supervision, M.L.A.; funding acquisition, A.E.A. 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 are available in the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 GC-chromatograms of the essential oils obtained from (A): J. intigrimma, (B): J. gossypifolia and (C): J. roseae leaves using the Rtx-5MS column. Figure 2 Major components identified in the essential oils obtained from J. intigrimma, J. gossypifolia and J. roseae leaves. Figure 3 Score plot (A) and loading plot (B) of GC data collected from J. intigrimma, J. gossypifolia and J. roseae leaves essential oil analyses using unsupervised chemometric analysis (PCA). Figure 4 2D and 3D binding modes of heneicosane (A), cubebol (B) and methyl linoleate (C) within the active center of E. coli adhesion protein FimH using in silico studies employing the C-docker protocol. plants-11-01268-t001_Table 1 Table 1 Essential oil compositions obtained from J. intigrimma, J. gossypifolia and J. roseae leaves using the Rtx-5MS column. No. Compounds [a] RI Composition (%) Identification Measured [b] Reported [c] J. intigrimma J. gossypifolia J. roseae 1. n-Nonane 880 900 - 0.20 0.78 MS, RI 2. α-Pinene 915 915 - 0.08 - MS, RI 3. 2-Methyl-nonane 947 951 - 0.05 0.15 MS, RI 4. β-Pinene 987 982 - 0.30 - MS, RI 5. trans-2-(2-Pentenyl)furan 991 985 - - 0.25 MS, RI 6. p-Cymene 1014 1017 - 0.03 - MS, RI 7. D-Limonene 1018 1018 5.35 0.23 - MS, RI 8. (E)-β-Ocimene 1038 1038 1.90 0.09 - MS, RI 9. 2,5-dimethyl-Nonane 1045 1042 - 0.04 0.09 MS, RI 10. γ-Terpinene 1048 1048 1.76 0.07 - MS, RI 11. p-Cymenene 1069 1069 - 0.12 0.49 MS, RI 12. α-Terpinolene 1088 1088 0.85 0.23 0.85 MS, RI 13. β-Linalool 1090 1090 1.23 0.34 - MS, RI 14. Isophorone 1094 1094 - 0.24 1.23 MS, RI 15. Nonanal 1098 1102 - 0.05 - MS, RI 16. 1-Nonanol 1162 1159 - 0.03 0.09 MS, RI 17. Methyl salicylate 1185 1187 - - 1.87 MS, RI 18. Safranal 1189 1189 1.90 - - MS, RI 19. Decanal 1197 1195 - 0.10 0.48 MS, RI 20. Cumaldehyde 1231 1230 - - 0.42 MS, RI 21. Carvacrol 1297 1298 - 0.01 0.08 MS, RI 22. 4-Vinylguaiacole 1311 1311 - - 0.38 MS, RI 23. α-Longipinene 1324 1327 0.64 - - MS, RI 24. α-Cubebene 1340 1344 - 0.19 - MS, RI 25. Isosativene 1358 1359 - 4.08 - MS, RI 26. α-Copaene 1369 1369 - 5.87 - MS, RI 27. Longicyclene 1374 1374 - - 0.74 MS, RI 28. β-Bourbonene 1376 1376 3.14 0.17 - MS, RI 29. Silphiperfol-6-ene 1379 1380 - - 6.90 MS, RI 30. Z-β-Caryophyllene 1404 1407 1.55 - - MS, RI 31. α-Guaiene 1404 1409 - - 2.00 MS, RI 32. E-β-Caryophyllene 1409 1409 - 2.97 0.06 MS, RI 33. α-Ionone 1417 1421 - - 0.07 MS, RI 34. β-Ionone epoxide 1437 1430 - 0.14 - MS, RI 35. Neryl-acetone 1440 1445 - 0.48 1.65 MS, RI 36. Humulene 1445 1445 - 0.60 - MS, RI 37. Alloaromadendrene 1453 1453 - 0.80 - MS, RI 38. Cadina-1(6),4-diene 1465 1469 - 0.21 - MS, RI 39. Germacrene D 1474 1474 - 2.09 - MS, RI 40. β-Ionone 1477 1478 3.53 0.39 3.09 MS, RI 41. Cubebol 1488 1484 - 2.17 - MS, RI 42. α-Muurolene 1491 1491 - 0.37 - MS, RI 43. β-Himachalene 1500 1500 - 0.21 - MS, RI 44. δ-Cadinene 1507 1507 - 3.55 - MS, RI 45. δ-Guaijene 1524 1526 - 4.02 - MS, RI 46. Cubenol 1534 1538 - 0.91 - MS, RI 47. α-Calacorene 1544 1541 - 2.8 - MS, RI 48. β-Caryophyllene oxide 1556 1556 - 1.25 - MS, RI 49. 4,8,12-Trimethyltrideca- 1,3,7,11-tetraene 1565 1565 0.84 0.40 - MS, RI 50. Globulol 1569 1568 - 0.95 - MS, RI 51. Spathulenol 1569 1569 - 3.63 - MS, RI 52. Pseudoionone 1575 1581 - - 0.33 MS, RI 53. Caryophyllene oxide 1578 1578 - - 0.11 MS, RI 54. Guaiol 1581 1584 - - 0.19 MS, RI 55. Humulene epoxide 1592 1592 - 0.33 - MS, RI 56. Davanone 1594 1592 - - 0.28 MS, RI 57. Copaborneol 1597 1593 - 15.7 - MS, RI 58. 1-epi-Cubenol 1619 1617 tr. - tr. MS, RI 59. Muurola-4,10(14)-dien-1β-ol 1624 1630 - 4.62 - MS, RI 60. Caryophylla-4(12),8(13)-dien-5α-ol 1634 1640 - 4.82 - MS, RI 61. α-Cadinol 1650 1660 - 1.42 - MS, RI 62. Bulnesol 1664 1666 - 1.45 - MS, RI 63. Eudesma-4(15),7-dien-1β-ol 1680 1686 - 7.01 - MS, RI 64. Ylangenol 1698 1693 - 0.24 - MS, RI 65. (2E,6E)-Farnesol 1699 1695 - - 0.22 MS, RI 66. 14-Hydroxy-α-humulene 1721 1718 - 0.13 0.07 MS, RI 67. Z-ligustilide 1732 1741 - 0.13 - MS, RI 68. Benzyl benzoate 1758 1750 - 0.27 - MS, RI 69. 3-Octadecene 1778 1784 - - 0.21 MS, RI 70. Tetradecanoic acid, 1-methylethyl ester 1805 1812 - - 0.13 MS, RI 71. Farnesyl acetate 1816 1818 - 1.06 - MS, RI 72. Hexahydrofarnesyl acetone 1825 1827 - 0.56 0.74 MS, RI 73. Eudesmol acetate 1830 1830 - tr. - MS, RI 74. n-Hexadecan-1-ol 1861 1854 - - 0.39 MS, RI 75. 7,10-Hexadecadienoic acid, methyl ester 1875 1894 1.50 - 1.36 MS, RI 76. Palmitoleic acid, methyl ester 1886 1886 1.20 - - MS, RI 77. Farnesyl acetone 1903 1897 - tr. - MS, RI 78. Hexadecanoic acid methyl ester 1906 1906 3.14 0.29 0.69 MS, RI 79. 1-Hexadecanol, acetate 1986 1978 - - 0.28 MS, RI 80. Octadecanal 1998 1999 - 0.08 0.31 MS, RI 81. Geranyl linalool 2009 2002 3.36 - - MS, RI 82. Sclareolide 2066 2065 - 0.01 0.85 MS, RI 83. Methyl linoleate 2077 2076 5.65 - - MS, RI 84. 9,12-decadienoic acid, methyl ester 2077 2075 - - 2.47 MS, RI 85. 9,12,15-Octadecatrienoic acid, methyl ester 2085 2085 10.77 - 3.18 MS, RI 86. Phytol 2096 2096 3.85 10.33 15.25 MS, RI 87. Verrucarol 2132 2025 - - 0.32 MS, RI 88. Sandaracopimarinal 2157 2185 0.93 - - MS, RI 89. Octadecamethyl-cyclononasiloxane 2198 2200 8.42 0.48 - MS, RI 90. Heneicosane 2276 2109 - - 12.67 MS, RI 91. Octacosane 2764 2800 - 0.16 - MS, RI 92. Squalene 2797 2790 0.50 0.03 0.13 MS, RI 93. Nonacosane 2856 2900 - - 5.87 MS, RI 94. Tetrateracontane 3113 3028 4.30 0.54 4.02 MS, RI 95. Hexatriacontane 3209 3597 28.44 - 14.50 MS, RI Monoterpene hydrocarbons 9.01 0.50 - Oxygen containing monoterpene 3.13 0.58 1.36 Sesquiterpene hydrocarbons 0.64 24.55 8.96 Oxygen containing sesquiterpene 3.53 50.31 4.61 Fatty acid esters 22.26 - 7.83 Others 53.04 14.18 63.48 Total identified components 91.61 90. 12 86.24 a Arrangement of the compounds based on their elution on RTX-5MS column. b Kovats index determined experimentally on RTX-5MS column relative to a standard mixture of C8–C30 n-alkanes. c Published Kovats retention indices. Identification was based on comparison of the compounds mass spectral data (MS) and Kovats retention indices (RI) with those of NIST Mass Spectral Library (2011), Wiley Registry of Mass Spectral Data 8th edition and literature. plants-11-01268-t002_Table 2 Table 2 Mean biofilm inhibitory activity (µg/mL) of J. intigrimma, J. gossypifolia and J. roseae essential oils against Escherichia coli determined by modified method of biofilm inhibition spectrophotometric assay. Sample Conc. (µg/mL) Mean Biofilm Inhibitory Activity % J. intigrimma J. gossypifolia J. roseae 7.81 52.14 ± 1.3 0 0 15.63 76.38 ± 2.5 0 16.31 ± 1.9 31.25 100 ± 0 0 38.82 ± 1.3 62.5 100 ± 0 0 62.25 ± 2.5 125 100 ± 0 5.08 ± 2.1 76.35 ± 0.72 250 100 ± 0 17.36 ± 1.5 100 ± 0 500 100 ± 0 28.14 ± 1.2 100 ± 0 1000 100 ± 0 39.25 ± 0.58 100 ± 0 MIC 31.25 >1000 250 Data are presented as means ± S.D. n = 3. plants-11-01268-t003_Table 3 Table 3 Free binding energies (kcal/mol) of major compounds in the active site of E. coli adhesion protein FimH using in silico studies. Compound Adhesion Protein FimH (1TR7) Number of Formed Hydrogen Bonds Number of Formed Alkyl and π-Alkyl Bonds D-Limonene 21.10 - 3; Ile52, Ile13 Isosativene 52.27 - 3; Ile52, Ile13, Tyr48 α-Copaene 4.05 - 7; Ile52, Ile13, Tyr137, Tyr48 Silphiperfol-6-ene 52.27 9; Ile52, Ile13, Tyr137, Phe142 α-Guaiene 44.19 - 5; Ile52, Ile13, Phe142, Tyr48 β-Caryophyllene 17.04 - 4; Ile52, Ile13, Tyr48 Germacrene D 8.63 - 3; Phe142, Ile13, Tyr48 β-Ionone 10.36 1; Phe1 1; Ile13 Cubebol −8.92 1; Asp140 2; Phe142, Ile13 δ-Cadinene 44.02 - 4; Ile52, Ile13, Tyr137 Caryophyllene oxide 0.82 1; Phe1 4; Phe142, Ile13, Tyr137 Spathulenol 47.82 1; Phe1 7; Ile52, Ile13, Tyr137, Tyr48, Phe142 Copaborneol 49.78 1; Asp140 4; Ile52, Ile13, Tyr137, Tyr48 Muurola-4,10(14)-dien-1β-ol 29.16 1; Asp140 6; Phe142, Ile13, Tyr137, Tyr48 Eudesma-4(15),7-dien-1β-ol 27.03 1; Phe1 6; Phe142, Ile13, Ile52, Tyr48 Caryophylla-4(12),8(13)-dien-5α-ol 12.29 2; Asp54, Phe1 3; Phe142, Ile13, Methyl linoleate −4.55 2; Asn135, Phe1 1; Ile52 7,10-Hexadecadienoic acid, methyl ester −6.70 1; Phe1 1; Ile52 Geranyl linalool 42.39 1; Phe1 2; Tyr48, Tyr137 9,12,15-Octadecatrienoic acid, methyl ester 8.86 2; Asp47, Phe1 1; Ile52 Heneicosane −30.68 - 2; Ile52, Tyr48 Nonacosane FD - - Tetrateracontane FD - - Hexatriacontane FD - - Positive values indicate unfavorable interaction. 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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093290 materials-15-03290 Article Adhesive Joints of Additively Manufactured Adherends: Ultrasonic Evaluation of Adhesion Strength Kowalczyk Jakub 1* https://orcid.org/0000-0002-4154-1167 Ulbrich Dariusz 1 Sędłak Kamil 2 Nowak Michał 2 Lionetto Francesca Academic Editor 1 Faculty of Transport and Civil Engineering, Institute of Machines and Motor Vehicles, Poznan University of Technology, 60-965 Poznań, Poland; dariusz.ulbrich@put.poznan.pl 2 Faculty of Mechanical Engineering, Division of Virtual Engineering, Poznan University of Technology, 60-965 Poznań, Poland; kamil.sedlak@gmail.com (K.S.); michal.nowak@put.poznan.pl (M.N.) * Correspondence: jakub.kowalczyk@put.poznan.pl; Tel.: 61-6652248 04 5 2022 5 2022 15 9 329011 4 2022 01 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/). Adhesive joints are widely used in the construction of machines and motor vehicles. Manufacturers replace them with the welding and spot-welding methods due to the lack of damage to the material structure in the joint area. Moreover, it is aimed at reducing the weight of vehicles and producing elements with complex shapes. Therefore, additive manufacturing technology has been increasingly used in the production stage. This fact has not only changed the view on the possibilities of further development of the production technology itself, but it has also caused an intense interest among a greater number of companies in the advantages of structural optimization. There is a natural relationship between these two areas in the design and production, allowing for almost unlimited possibilities of designing new products. The main goal of the research described in this article was to determine the correlation between the strength of the adhesive joint of elements produced using additive technology and the parameters of the ultrasonic wave propagating in the area of the adhesive bond. The tests were carried out on samples made of AlSiMg0.6 material and a structural adhesive. Strength tests were performed to determine the shear force which damaged the joint. Furthermore, an ultrasonic echo technique enabling the determination of a nondestructive measure of the quality and strength of the joint was developed. The samples of the adhesive joints had a strength of about 18.75–28.95 MPa, which corresponded to an ultrasonic measure range of 4.6–7.8 dB. The determined regression relationship had a coefficient of determination at the level of 0.94. Additional ultrasonic tests of materials made with the additive technology confirmed its different acoustic properties in relation to aluminum produced with the standard casting or extrusion process. Designated dependence combining the mechanical strength and the decibel difference between the first and second impulses from the bottom of the joint may constitute the basis for the development of a nondestructive technique for testing the strength of adhesive joints. adhesion additive technology aluminum structural adhesive ultrasound damping strength Polish National Centre for Research and DevelopmentDWP/TECHMATSTRATEG-III/136/2020 This work was supported by the Polish National Centre for Research and Development under the grant—decision no. DWP/TECHMATSTRATEG-III/136/2020. ==== Body pmc1. Introduction Manufacturers of machines and vehicles aim to reduce weight, which leads to a reduction of fuel consumption and the emission of fumes into the atmosphere [1,2,3]. The ecological aspect of the design process of machines and devices plays a significant role in the selection of materials and connections used at the production stage. One of the directions of development of the production process of machine elements is the use of additive manufacturing technology (3D printing) in metals and their alloys [4,5,6]. Thanks to this technology and the use of shape optimization [7,8], parts with a reduced mass but a similar or higher strength compared to currently manufactured elements are obtained. Moreover, efforts are being made to improve the technology of joining individual parts by various methods, including spot welding [9,10], welding [11], as well as bonding with adhesives [12,13]. In addition, various types of coatings are used at the production stage, which change the properties of the surface layer [14,15]. The development of devices used for the production of parts using additive manufacturing technology makes it necessary to test various properties of the manufactured products [16,17,18]. Additive technology is a process controlled by a computer in which the three-dimensional object is produced by depositing multiple layers of equal structure. The individual layers of the material with the same thickness are placed on top of each other (layer by layer), which leads to obtaining objects of the desired shapes and dimensions without additional processing. The thickness of the applied layers may vary from 10 to 200 µm depending on the equipment used and the process parameters. Each subsequent layer in the construction of an object is added as a result of the melting or partially melting of the material. Other processes such as the sintering or polymerization of materials in predetermined layers with no needs of tools have been used. Typically, powders of metals or other materials are used, depending on the properties of the final product. In the powder system, the deposited powder is spread using a roller or a squeegee; in some systems the material is applied through a nozzle that deposits the required material. The main directions of research on elements manufactured in additive manufacturing include the improvement of manufacturing technology [19,20,21], identification of defects [22,23], including mainly the lack of homogeneity of the material, which causes different material properties and may lead to the detachment of individual layers of the structure [24]. Another research is focused on the optimal performance of elements manufactured using additive technology [25]. An incorrect design of the manufacturing process, e.g., support bugs, may cause both shape errors of the element as well as the consumption of an additional, large amount of powder, which generates significant costs (supports are removed and treated as material waste). Nevertheless, there is a gap in the study of the acoustic properties of aluminum-based additive components and the comparison of these properties with the results obtained for aluminum samples produced in standard manufacturing processes (e.g., casting, extrusion). Supplementing the knowledge in this area can provide the basis for the development of an ultrasonic quality assessment method for both the elements made in additive technology as well as the inseparable connections which these elements contain. One of the methods of joining elements manufactured in additive technology is bonding with an adhesive. Adhesive joints are classified as inseparable joints and are commonly used in the construction of motor vehicles and machines. The main directions of research on adhesive joints include, above all, the design of joints of various materials [26], which have the properties required for a given joint, testing the strength of adhesive joints of various materials exposed to a complex state of stress [27,28], as well as the development of nondestructive testing techniques which allow for the location of defects in the connection [29,30]. The use of the ultrasonic method to test adhesive joints is described in the literature [31,32]. Nevertheless, the performed tests include tests of adhesive joints made of standard materials (rolled sheets, forgings, castings, carbon fiber), the acoustic properties of which have been known for many years [33]. In the case of examining the adhesive joints of elements made with the use of additive technology, changes in the internal structure of the material are observed [34], which may affect the propagation of the ultrasonic wave and the obtained information on the condition of the connection. Ultrasonic tests of adhesive joints include the location of defects and continuity of the adhesive path [35,36], kissing-bond verification [37] and, in a few attempts, the assessment of the joint production process [38]. According to the authors, there is one more important research direction related to the development of a nondestructive method of estimating the strength of adhesive joints. This applies to both standard connections and those made of metal in additive technology. The main aim of the research presented in this article was to determine the relationship between the mechanical strength of the adhesive joint of two flat bars made using additive technology, and the parameters of the ultrasonic wave propagating in the area of this joint. An additional goal was to determine the basic acoustic properties of a sample made of AlSiMg0.6 material (produced with the use of additive manufacturing technology) and to compare it with standard aluminum (which was produced using traditional methods). The research includes the selection of the shape of the samples and adhesives for preparing the adhesive joint, ultrasonic equipment choice, as well as the determination of the selected ultrasonic measure of the joint quality and shear strength. The final result is a mathematical dependence linking the strength of the adhesive bond with the selected ultrasonic measure. This is the first step in the development of a method and system for estimating the strength of adhesive joints using ultrasonic waves, both classic and made using additive manufacturing technology. 2. Materials and Methods 2.1. Samples The samples of AlSiMg0.6 powder were manufactured and then melted with a laser beam (Table 1). The samples were manufactured with the LPBF/SLM process using “A357—As-built” powder. The samples were made in such a way as not to affect the internal structure of the material. The surface finish–raw surface was treated as described in the sample preparation process. Only vertical specimens were left for inclination of the specimen relative to the work platform during fabrication. Therefore, the surface with the best properties was obtained. The manufacturing process of the specimens was not influenced by other factors related to the process, parameters, size of the workpiece, presence of supporting structures and residues of structures. This process was influenced by the surface roughness and waviness. Material properties-A357 were as follows: tensile strength 380 MPa, yield strength 250 MPa, elongation 8%, fatigue strength 80 MPa, Young’s modulus ~70 GPa. All samples investigated in this research were manufactured using the LPBF process, from AlSi7Mg0.6 powder of particle distribution 20–63 μm (SLM Solutions AG, Lubeck, Germany) using the process parameters which allowed us to obtain almost fully dense material (porosity < 0.5%). The samples during the build with the LPBF process were oriented vertically—the longitudinal axis was aligned in the build direction along the z axis without any inclination. This orientation was optimal because of the minimal required supporting area (reduced only to the smallest sample edge), and due the fact that the surface quality on the side surfaces of the specimens was uniform and had the smallest achievable roughness. Additionally, a vertical orientation minimized residual stresses, which were introduced into the material during the processing in AM. The thickness of the sample at the place where the adhesive joint was made was 1.5 mm, which corresponds to the thickness of the elements currently used in the construction of car bodies of motor vehicles. Additionally, such a thickness of the sample prevents its damage (due to the action of shear forces, the adhesive joint, rather than the sample material, is damaged). The length of the sample was set at 105 mm, which allowed it to be easily mounted on a testing machine. In addition, the reduction in material thickness at the point of bonding the samples was due to the need to maintain the alignment (axially) of the samples during the shear test. In the case of samples of the same thickness, the tearing and deformation of the sample material occur apart from the action of shear forces. This proves the occurrence of a complex state of stress. Both in ultrasonic tests and in the shear test, 20 sets of samples made with the additive technology were used. The dimension and view of one sample is presented in Figure 1. After the additive manufacturing process, the surface required additional processing. Therefore, 3 methods were used to prepare the surface layer of the samples before bonding. The first one consisted of degreasing (an isopropanol-based degreaser was used). The second method of surface preparation was abrasive blasting (sandblasting). However, the last method of surface preparation was the use of a P80 abrasive paper, which corresponded to the appropriate grain diameter. Examples of the measurement results of the surface roughness profile and the surface view observed on an SEM microscope after treatment are shown in Figure 2. In the case of all tested sanded samples, the obtained values of the Ra parameter fell within the range of 5.75–5.94. On the other hand, the second parameter Rz—important from the point of view of the bonding process—reached values in the range of 24.5–25.8. For the second sample surface preparation method (grinding with a P80 abrasive paper), values of Ra and Rz within the range of 2.91–3.45 and 12.9–14.1 were obtained, respectively. In the case of the Ra parameter for both methods of surface preparation, the results were at a similar level. Four adhesives with different components and properties were used to connect the samples, in order to select one adhesive which will be used in the further part of the research (main research). The course of the bonding process was always in line with the technological card of the adhesive manufacturer. The most important parameters of adhesives used in the tests are summarized in Table 2. Setting time is the time to obtain the handling strength. Cure time is the time to obtain the full mechanical strength, All the adhesives were cured at room temperature (around 20 °C). 2.2. Ultrasonic Testing of Samples and Joints Ultrasonic testing was divided into two stages. In the first of them, the acoustic properties of the samples produced with the additive manufacturing technology were measured. The second stage involved the ultrasonic testing of adhesive joints with the use of the selected adhesive (adhesive 4—previously used for bonding samples). Ultrasonic testing uses mechanical waves that propagate through the material and cause vibrations of the material particles. Ultrasound is based on the theory of acoustoelasticity, and the mechanical stresses in the material have an impact, for example, on the propagation speed and other properties of the ultrasonic wave. The velocity of the longitudinal wave propagation can be determined on the basis of the relationship, taking into account the impulses from the bottom of the sample at the same material thickness. Longitudinal wave velocity can be related to other parameters characterizing the tested material, such as, Young’s modulus, Poisson’s ratio or material density:(1) VL=E(1−v)ρ(1−v)(1−2v) Other factors influencing the results of ultrasonic tests are surface roughness (at the point of wave penetration), anisotropy and micro-heterogeneity of the material. The microstructure of the material, including the size of the grain produced in the production process (i.e., additive manufacturing technology), is the factor that determines the attenuation of ultrasonic wave. The attenuation of the ultrasonic wave in the material occurs due to the scattering and absorption of waves. The result of the damping of the ultrasonic wave is the amount of energy that returns to the ultrasonic head and is displayed in the form of an A-scan (amplitude vs. time signals) on the ultrasonic flaw detector (GE Sensing & Inspection Technologies, Billerica, MA, United States) screen. Our research started with determining the damping of the ultrasonic longitudinal wave propagating in the sample made using the additive technology with AlSi7Mg0.6. In order to determine the attenuation, the amplitude (height) of the first five pulses (Figure 3) obtained on the screen of the ultrasonic flaw detector was measured 30 times. Measurements were made on samples with a thickness of 3.6 mm. Before testing, the surface of the element was cleaned and degreased. No surface treatment which could affect the propagation of the ultrasonic wave was performed. The GE 3.15 G20MNX ultrasonic head (GE Sensing & Inspection Technologies, Billerica, MA, United States) was selected for the tests. This head allows one to generate a system of impulses on the flaw detector screen in an element of small thickness. It is a head with a transducer frequency of 20 MHz and a diameter of 3.15 mm with a water delay line, enabling measurements outside the dead zone. It is important from the point of view of the research accuracy and obtained results. The attenuation coefficient was determined using relationship (2). It was decided that only the first two pulses would be selected to calculate the damping because the measurement error for these pulses was the lowest. (2) ∝f=202l·log(HIHII) where: HI, HII—percentage height (the amplitude value) of the first and second impulse from the bottom of the tested element, respectively, l—thickness of the element. Ultrasonic wave attenuation is defined as the conversion of the propagation energy of an ultrasonic wave of a specified frequency into vibration energy at other frequencies, usually thermal vibrations. This transformation is influenced by physical mechanisms, such as: thermoelastic damping, damping due to structural relaxation phenomena (it has a similar course to resonance as a function of frequency), resonance damping and damping caused by dislocation vibrations as well as damping caused by detaching dislocations from contaminants (depending on the vibration amplitude). It is important that for a relaxation process in which the same activation energy is for all systems subject to relaxation, the shape of the curve of the damping coefficient Q−1(f) as a function of frequency is described by the expression (3):(3) Q−1(f)=(Q−1)max2ffmax1+(ffmax)2 where: Q−1(f)—damping coefficient for the relaxation process as a function of frequency, f—frequency, fmax—maximum frequency. As the next step, the material made using the additive manufacturing technology was checked for homogeneous acoustic parameters (within one sample). For this purpose, 30 measurement points were determined on two randomly selected samples, in which the pulse systems were recorded on the screen of the ultrasonic flaw detector. The view of the measurement grid used during the research is shown in Figure 4. Afterwards, it was verified whether the ultrasonic flaw detector settings affected the ultrasonic quality of the adhesive joints. The decibel decreases of the first two pulses from the connection area, described by relationship (4), was adopted as the ultrasonic measure and used during the main research. (4) R=20·log(HIHII) where: HI, HII—percentage height of the first and second impulse from the bottom of the tested element. After the preparation of the adhesive joints in which adhesive 4 was used, the distribution of the ultrasonic measurement within the entire joint was examined (calculated in accordance with relation (2)). The view of the sample, with the measuring grid marked on it, is shown in Figure 5. 2.3. Mechanical Testing of Joints A Cometech B1/E testing machine (Cometech Testing Machines Co., Taichung Taiwan) was used in the tests, together with articulated clamps in which the sample was mounted. The jaw speed was 0.05 mm/s and the force was measured with an accuracy of 1 N. Following that, the maximum shear force obtained during the measurements was related to the surface on which the adhesive had been applied. Thanks to this, the shear stress which damaged the adhesive joint was determined. The view of the sample mounted in the jaws of the testing machine is shown in Figure 6. 2.4. Research Plan The research was divided into two main stages conducted in laboratory conditions. In the first stage, a series of tests were carried out with the use of an ultrasonic wave propagating both in the material itself (sample made with the additive manufacturing technology) and in the adhesive joint. The second stage of the research included destructive tests and a comparison of selected ultrasonic measures with the shear stress. The course of the individual research stages is shown in Figure 7. 3. Results 3.1. Ultrasonic Testing of Samples’ Results In the first stage of the ultrasonic tests, the damping measurements of the samples produced with the use of the additive technology were performed. Example results of the height (amplitude) of individual ultrasonic wave pulses assuming a constant height of the first impulse (80% of the height of the ultrasonic flaw detector screen) are summarized in Table 3. In order to compare the results obtained from the ultrasonic tests of printed samples, a damping value for the sample made of aluminum produced with standard methods was determined (Table 4). For aluminum samples made with standard methods, two additional pulses were obtained on the ultrasonic flaw detector screen (HVI, HVII), with the same gain of the ultrasonic wave pulse. It proves a lower attenuation of the material in relation to samples made with the additive technology, where only five return pulses were obtained from the bottom of the sample. These results show that materials made using the 3D printing technology cause a greater attenuation of the ultrasonic wave, due to the internal structure created in the powder remelting process. Moreover, for the sample made with the use of the additive technology, the second pulse from the bottom of the connection was nearly 50% lower than the first one, which proves the high value of the wave attenuation. For samples made with a standard process, the difference between the first and second pulse (height/amplitude) was approximately 20%. The attenuation calculated on the basis of dependence (1) in the elements made with the additive manufacturing technology for the ultrasonic head frequency of 20 MHz was 0.694 dB/mm. The attenuation for aluminum sheet was 0.519 dB/mm (for a frequency of 20 MHz), which is clearly lower than for elements made using the additive technology. This means that conducting ultrasonic tests of elements made with the use of the additive technology is more difficult than conducting tests on elements made with the use of classical methods. In the next step of ultrasonic testing of elements printed in aluminum, the homogeneity of the acoustic parameters of the samples was measured and selected results are presented in Table 5. Based on the results presented in Table 5, it can be concluded that the acoustic properties were at a similar level within one sample. In addition, taking into account the test results for all samples, slight (1–2%) differences in the obtained values of the ultrasonic parameters were noticed. Therefore, it can be concluded that the structure of the samples used in the research was practically identical, taking mainly into account the acoustic properties of the AlSiMg0.6-printed material. Figure 8 confirms this above conclusion, showing the amplitude value of the second pulse from the bottom of the connection. The obtained values are at a similar level (based on statistical evaluation), between 40% and 50% of the ultrasonic flaw detector screen height, which is shown in Figure 9. The basic parameter of the flaw detector, which affects the pulse height, is the gain of the ultrasonic longitudinal wave, expressed in decibels. Therefore, additional measurements of the height of the first, second and third impulse obtained on the ultrasonic flaw detector screen were made for a gain in the range of 44 dB to 64 dB. At the lowest gain, the height of the first impulse was 11% of the screen height, and the highest one, according to the indications, amounted to 107%. The results of these measurements are summarized in Figure 10. The measured results clearly show that for the tested samples (printed in 3D) an ultrasonic wave impulse amplification above 55 dB of, unchanging results of the measurement of the quality of the sample itself (homogenity) as well as the quality of the adhesive bond were obtained. 3.2. Ultrasonic Testing of Adhesive Joints Results Ultrasonic tests of adhesive joints were carried out at nine measuring points (Figure 5), determining the ultrasonic measure according to relationship (2). The results of the distribution of this ultrasonic measure for the selected sample are shown in Figure 11. In the next part of the research, for samples prepared in the same way, the ultrasonic measure of adhesion of the adhesive to the sample substrate was determined. The mean results of all measurements for each of the samples are summarized in Table 6. The results of the ultrasonic measurement for the tested samples ranged from 4.61 to 7.96 dB. This gives a difference of 25%, which may indicate a different adhesion of the adhesive to the surface layer for the 3D printed material. Furthermore, the obtained results should be related to the results of the shear force, which damages the adhesive connection. 3.3. Mechanical Testing Results Before performing the main tests, i.e., shear tests, preliminary tests were carried out to select an adhesive for the main tests. Therefore, the shear stress for all adhesives described in Section 2.1. was determined. For adhesive 1, the average stress was 2.2 MPa, for adhesive 2 it was 12.6 MPa and for adhesive 3 it was 15.7 MPa. The highest value of shear stress which destroyed the adhesive joint was obtained for the epoxy adhesive marked with 4, and it was about 21.7 MPa. On the basis of these tests, it was assumed that adhesive 4 would be used in the main tests. It is a two-component epoxy adhesive which, according to the manufacturer, is characterized by a shear strength for the aluminum–adhesive–aluminum joint of 28–30 MPa (depending on the curing cycle). By the same token, preliminary tests confirmed that the adhesive joints made on the surfaces which had been only degreased were of the lowest quality. The low quality was due to the oxides formed on the surface. The joints in which the surface was abrasive-blasted (sandblasted) were of much higher quality, while the joints of the highest quality were sanded with the P80 sandpaper (the highest values of stress damaging the adhesive joint). Therefore, in the main tests, this method of sample surface preparation was chosen. Moreover, the method was compatible with the surface preparation possibilities envisaged by the adhesive manufacturer. The results of destructive tests of the joints performed on the testing machine are presented in Table 7. However, the state of one sample after shear test is illustrated in Figure 12—especially the place of the adhesive. In most cases, a cohesive failure was achieved, which means that the forces bonding the adhesive to the substrate were greater than the adhesive bond strength. 4. Discussion The final result of the research was to determine the relationship which combines the ultrasonic quality measure of the adhesive joint with the strength expressed in megapascal determined on the basis of the shear test. This relationship is shown in Figure 13. The shear stress of the adhesive joints ranged from 18.75 MPa to 28.95 MPa, which corresponds to the ultrasonic measure over a range of 4.61–7.96 dB. The obtained results of shear stress were in accordance with the adhesive data sheet. Nevertheless, it is difficult to unequivocally relate these results to the studies of other authors, due to the characteristics of the samples and the adhesive itself. Sliwa-Wieczorek et al. [39] tested double-lap adhesive connections in destructive shear tests under a quasi-static load at 20 °C and 80 °C. The obtained results of stress destroying the connection were at a similar level as those obtained in the research described by the authors, despite different bonding materials. In the case of a sample made using the additive technology on which no adhesive was applied, the decibel decrease in the height of the first and second impulse was below 4 dB. However, for the weakest connections, it was 4.6 dB. The coefficient of determination between the decibel decrease in the height of the first and second impulse and the shear stress was high and amounted to 0.94. The obtained relationship can be used to estimate the strength of adhesive connections. However, it should be stated that for the control of other adhesive joints, it is important to take into account the method of surface preparation and the type of adhesive. An adhesive (glued) bond is a special type of adhesive bond. It has damping and elastic properties which make testing with the use of ultrasound wave difficult. Polyurethane adhesives are characterized by a high damping, and the tested epoxy adhesive is mainly characterized by elastic properties (with lower damping). The properties of the tested materials (glue/adhesive and an element made with additive manufacturing) affect the waveform at the boundary of the connected materials. A part of the wave is reflected, and a part penetrates through the adhesive bond. This phenomenon can be described by the energy reflection coefficient RE—Equation (5). It is the ratio of the energy of the reflected wave to the energy of the incident wave. The energy carried by the ultrasonic wave is proportional to the square of the amplitude of the sound pressure, the energy reflection coefficient is equal to the square of the pressure coefficient and can take the form of the expression:(5) RE=E1E0=(z2−z1)2(z2+z1)2 where: E0, E1—energy carried by the incident and reflected wave, respectively; z1, z2—acoustic impedance of the first and second medium, respectively. The actual value of the reflectance is influenced by many factors, e.g., the preparation of the surface for bonding, the setting conditions, the bonding and cross-linking temperature. For this reason, the analytically determined reflectance value is only a guide for the ultrasonic quality evaluation of the adhesive joint. The higher the quality of the adhesive bond is, the greater part of the ultrasonic wave energy will be attenuated in the adhesive. A smaller part of the ultrasonic wave energy will be reflected from the adhesive bond and will return to the ultrasonic transducer, generating pulses on the flaw detector screen, hence the nature of the adopted measure and its marked increase along with the increase in destructive stresses. 5. Conclusions As part of this work, a research experiment was planned and carried out. The damping of the ultrasonic wave in the samples made with an additive technology was determined. The influence of the ultrasonic wave pulse amplification on the results of the selected ultrasonic measure was also assessed. In the next part, tests on the destructive quality of the adhesive joint were carried out and the obtained results were compared with the nondestructive measurement of the quality of the joint. The most important conclusions from the conducted research are as follows:- The shear stress of the tested adhesive joints ranged from 18 to almost 29 MPa; - The lowest decibel drop between the first two pulses was 4.6 and the highest one was almost 8 dB; - The coefficient of determination between the ultrasonic measure and the mechanical measure of the tested connections was 0.94. The application of additive manufacturing technologies creates new opportunities of manufacturing complex geometries without increasing costs. The additional benefits of using additive manufacturing technologies could be achieved thanks to the implementation of topology optimization methods such as the biomimetic structural optimization approach [40]. Further work should include research on the propagation of ultrasonic waves in adhesive joints for adhesives with different acoustic and mechanical properties, e.g., cyanoacrylates. Such connections may have a different course of pulses from the connection area and may allow the use of other ultrasonic measures. Subsequent research will enable extending the database of the results of adhesive joints’ assessment using the ultrasonic method, which will contribute to the development of a system for assessing the strength of an adhesive joint without damaging it. Acknowledgments The authors would like to thank the Centre for Advanced Manufacturing Technologies of Wroclaw University of Science and Technology for preparing the samples with an additive manufacturing technology. Author Contributions Conceptualization, D.U. and J.K.; methodology, J.K., D.U. and M.N.; software, K.S.; validation, J.K., D.U. and K.S.; formal analysis, J.K. and D.U.; investigation, J.K.; resources, J.K. and D.U.; data curation, J.K. and D.U.; writing—original draft preparation, J.K. and D.U.; writing—review and editing, D.U.; visualization, J.K. and K.S.; supervision, M.N.; project administration, K.S.; funding acquisition, K.S. and M.N. 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. Appendix A materials-15-03290-t0A1_Table A1 Table A1 The results of ultrasonic measurements used to determine the attenuation in samples produced with the additive technology. HI (%) HII (%) HIII (%) HIV (%) HV (%) 80 45 23 13 6 80 46 24 11 7 80 45 22 12 5 80 44 23 11 6 80 45 22 11 4 80 45 24 12 6 80 48 26 12 6 80 44 21 9 4 80 43 24 11 6 80 49 25 13 7 80 43 22 12 5 80 49 26 13 6 80 45 22 11 5 80 45 23 11 6 80 43 23 13 7 80 42 22 11 5 80 45 23 11 6 80 45 24 12 7 80 43 21 11 6 80 48 28 16 8 80 50 26 14 8 80 46 24 13 7 80 46 24 13 6 80 43 23 12 7 80 45 22 12 6 80 47 24 12 6 80 47 22 11 5 80 43 22 11 7 80 44 24 13 6 80 44 24 12 7 materials-15-03290-t0A2_Table A2 Table A2 The results of ultrasonic measurements used to determine the attenuation in samples produced using standard technology. HI (%) HII (%) HIII (%) HIV (%) HV (%) HVI (%) HVII (%) 80 63 46 29 20 12 8 80 65 48 33 22 11 9 80 63 50 38 25 18 15 80 60 46 34 24 16 10 80 60 44 33 22 18 11 80 63 60 43 34 24 17 80 63 45 35 26 20 14 80 61 48 36 25 19 13 80 63 49 36 27 18 14 80 63 45 37 26 19 13 80 69 52 38 28 19 14 80 64 46 36 26 19 13 80 60 42 29 19 11 8 80 62 45 33 23 16 10 80 63 47 34 25 18 12 80 65 49 34 25 18 13 80 63 44 34 26 17 12 80 63 43 31 28 16 10 80 64 47 34 25 18 14 80 66 51 36 27 18 13 80 63 50 38 25 18 15 80 63 49 36 27 18 14 80 66 49 34 24 19 13 80 64 48 33 24 17 13 80 62 49 30 25 14 14 80 63 49 30 24 16 14 80 62 51 29 23 15 14 80 61 43 33 24 17 11 80 65 47 31 22 13 11 80 62 45 34 24 17 10 materials-15-03290-t0A3_Table A3 Table A3 Results of measurements of the homogeneity of selected acoustic properties of samples made using the additive manufacturing technology. Sample 1 Sample 2 No HI (%) HII (%) HIII (%) HIV (%) No HI (%) HII (%) HIII (%) HIV (%) 1 80 44 15 9 1 80 45 11 9 2 80 41 13 7 2 80 42 12 8 3 80 45 13 6 3 80 45 16 7 4 80 42 15 9 4 80 44 14 7 5 80 45 11 9 5 80 42 12 6 6 80 43 13 8 6 80 43 12 9 7 80 42 15 8 7 80 42 16 6 8 80 48 13 7 8 80 43 14 9 9 80 45 9 6 9 80 47 12 7 10 80 46 15 6 10 80 48 10 9 11 80 45 13 8 11 80 43 15 7 12 80 46 15 6 12 80 48 9 6 13 80 46 11 8 13 80 41 10 7 14 80 48 13 8 14 80 47 15 9 15 80 46 14 6 15 80 43 14 7 16 80 46 14 9 16 80 49 10 6 17 80 45 16 7 17 80 46 12 8 18 80 42 16 7 18 80 43 15 7 19 80 45 12 6 19 80 49 15 6 20 80 45 9 9 20 80 47 16 8 21 80 48 14 6 21 80 47 16 8 22 80 48 12 7 22 80 47 16 7 23 80 48 10 9 23 80 42 9 7 24 80 41 9 6 24 80 43 11 8 25 80 46 13 6 25 80 42 14 7 26 80 48 14 9 26 80 49 13 7 27 80 47 11 8 27 80 46 9 7 28 80 46 16 6 28 80 44 14 6 29 80 41 10 8 29 80 44 12 6 30 80 44 11 9 30 80 44 16 6 materials-15-03290-t0A4_Table A4 Table A4 Average results of ultrasonic measure for all samples. Sample Number Ultrasonic Measure (dB) 1 6.021 2 4.998 3 6.936 4 5.806 5 7.959 6 5.392 7 6.466 8 5.193 9 4.807 10 5.597 11 6.241 12 6.936 13 6.241 14 6.241 15 4.620 16 5.392 17 7.432 18 6.021 19 6.698 20 4.998 materials-15-03290-t0A5_Table A5 Table A5 Results of shear stress for all samples. Sample Number Shear Stress (Mpa) 1 23.212 2 19.580 3 27.900 4 21.480 5 28.950 6 21.240 7 24.915 8 20.250 9 19.250 10 22.490 11 22.650 12 28.272 13 24.495 14 24.850 15 18.750 16 20.812 17 28.565 18 23.687 19 25.680 20 20.240 Figure 1 Samples used during the test; (a) scheme with dimension, (b) view of the sample. Figure 2 Assessment of the surface layer before the bonding process; (a) surface roughness profile after sandblasting, (b) view of the surface structure after sandblasting, (c) surface roughness profile after sanding with P80 abrasive paper, (d) view of the surface structure after sanding with P80 abrasive paper. Figure 3 Ultrasonic flaw detector; 1—first pulse (HI), 2—second pulse (HII), 3—third pulse (HIII), 4 —transmit impulse, 5—gain, 6 —gate (red color), 7—amplitude value of gate pulse. Figure 4 Testing the homogeneity of acoustic parameters of a sample made with additive manufacturing technology; (a) view of the sample with the measurement grid, (b) view of the test stand. Figure 5 View of the sample with the measuring grid. Figure 6 View of the sample after the shear test. Figure 7 Plan of the research. Figure 8 Second pulse amplitude value in % of the ultrasonic flaw detector screen on the whole sample area. Figure 9 Average amplitude value of second pulse from the sample in % of ultrasonic flaw detector screen. Figure 10 Dependence of the ultrasonic R measure on the amplification of the ultrasonic wave pulse. Figure 11 Ultrasonic measure test results. Figure 12 View of the joint after the shear force test. Figure 13 Correlation test results. materials-15-03290-t001_Table 1 Table 1 Chemiacal composition (mass fractions in %). Al Cu Fe Mg Nb + Ta Mn Si Ti N Zn Each Other Total Other Balance 0.05 0.19 0.45–0.70 / 0.10 6.50–7.50 0.25 / 0.07 0.03 0.10 materials-15-03290-t002_Table 2 Table 2 Selected properties of adhesives used in research. Property Adhesive 1 Adhesive 2 Adhesive 3 Adhesive 4 Setting time (20 °C) 4 h 2 h 1 h 4–6 h Cure time (20 °C) 48 h 24 h 24 h 7 days Shear strength 4.5 MPa 3.1 MPa 20–24 MPa 30.2 MPa Shore hardness 50 ShA 77 ShA 73 ShD 81 ShD Adhesive type Polyurethane prepolymer Hybrid adhesive Methacrylate adhesive Epoxy adhesive materials-15-03290-t003_Table 3 Table 3 The results of ultrasonic measurements used to determine the attenuation in samples produced with the additive technology (the complete set of results are available in the Appendix A in Table A1). HI (%) HII (%) HIII (%) HIV (%) HV (%) Mean value 45 24 12 6 Standard deviation 2.08 1.53 1.22 0.90 materials-15-03290-t004_Table 4 Table 4 The results of ultrasonic measurements used to determine the attenuation in samples produced using standard technology (the complete set of results are available in the Appendix A in Table A2). HI (%) HII (%) HIII (%) HIV (%) HV (%) HVI (%) HVII (%) Mean value 63 48 34 25 17 12 Standard deviation 1.89 3.39 3.01 2.68 2.63 2.10 materials-15-03290-t005_Table 5 Table 5 Results of measurements of the homogeneity of selected acoustic properties of samples made using additive manufacturing technology (the complete set of results are available in the Appendix A in Table A3). Sample 1 Sample 2 Mean value 45.07 12.83 7.43 44.83 13.00 7.23 Standard deviation 2.21 2.11 1.20 2.42 2.34 1.02 materials-15-03290-t006_Table 6 Table 6 Average results of ultrasonic measure for all samples (the complete set of results are available in the Appendix A in Table A4). Ultrasonic Measure (dB) Mean value 6 Standard deviation 0.88 materials-15-03290-t007_Table 7 Table 7 Results of shear stress for all samples (the complete set of results are available in the Appendix A in Table A5). Shear Stress (Mpa) Mean value 23.363 Standard deviation 3.18 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Wargula L. Kukla M. Lijewski P. Dobrzyński M. Markiewicz F. Influence of Innovative Woodchipper Speed Control Systems on Exhaust Gas Emissions and Fuel Consumption in Urban Areas Energies 2020 13 3330 10.3390/en13133330 2. Dimou V. Kantartzis A. Malesios C. Kasampalis E. Research of exhaust emissions by chainsaws with the use of a portable emission measurement system Int. J. For. Eng. 2019 30 228 239 10.1080/14942119.2019.1622318 3. Rymaniak Ł. Lijewski P. Kaminska M. Fuc P. Kurc B. Siedlecki M. Kalocinski T. Jagielski A. 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PMC009xxxxxx/PMC9099764.txt

==== Front Nanomaterials (Basel) Nanomaterials (Basel) nanomaterials Nanomaterials 2079-4991 MDPI 10.3390/nano12091593 nanomaterials-12-01593 Article Iron Single Atoms Anchored on Nitrogen-Doped Carbon Matrix/Nanotube Hybrid Supports for Excellent Oxygen Reduction Properties https://orcid.org/0000-0003-3032-4500 Jia Yining 1 Shi Chunjing 1 Zhang Wei 1 Xia Wei 2 https://orcid.org/0000-0002-5024-5650 Hu Ming 1 Huang Rong 13* Qi Ruijuan 1* Davila Maria E. Academic Editor 1 Key Laboratory of Polar Materials and Devices (MOE), Department of Electronics Sciences, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China; 51191213010@stu.ecnu.edu.cn (Y.J.); chunjingshi620@163.com (C.S.); wzhang@ee.ecnu.edu.cn (W.Z.); mhu@phy.ecnu.edu.cn (M.H.) 2 Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200241, China; xiaweifriend@163.com 3 Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China * Correspondence: rhuang@ee.ecnu.edu.cn (R.H.); rjqi@ee.ecnu.edu.cn (R.Q.) 07 5 2022 5 2022 12 9 159322 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/). Single-atom non-precious metal oxygen reduction reaction (ORR) catalysts have attracted much attention due to their low cost, high selectivity, and high activity. Herein, we successfully prepared iron single atoms anchored on nitrogen-doped carbon matrix/nanotube hybrid supports (FeSA-NC/CNTs) by the pyrolysis of Fe-doped zeolitic imidazolate frameworks. The nitrogen-doped carbon matrix/carbon nanotube hybrid supports exhibit a specific surface area of 1626.814 m2 g−1, which may facilitate electron transfer and oxygen mass transport within the catalyst and be beneficial to ORR performance. Further electrochemical results revealed that our FeSA-NC/CNTs catalyst exhibited excellent ORR activity (half-wave potential: 0.86 V; kinetic current density: 39.3 mA cm−2 at 0.8 V), superior to that of commercial Pt/C catalyst (half-wave potential: 0.846 V; kinetic current density: 14.4 mA cm−2 at 0.8 V). It also has a great stability, which makes it possible to be a valuable non-noble metal electrode material that may replace the latest commercial Pt/C catalyst in the future. oxygen reduction reaction electrocatalyst single atom catalysts carbon nanotubes National Key Research and Development Program of China2017YFA0303403 Shanghai Science and Technology Innovation Action Plan19JC1416700 National Natural Science Foundation of China61974042 11774092 This work was supported by the National Key Research and Development Program of China (2017YFA0303403), the Shanghai Science and Technology Innovation Action Plan (No. 19JC1416700), and the National Natural Science Foundation of China (Grant Nos. 61974042 and 11774092). ==== Body pmc1. Introduction To accelerate the large-scale commercialization of metal–air battery technologies, low-cost, high activity platinum group metal-free (PGM-free) catalysts for oxygen reduction reactions (ORR) have been developed as alternatives for the scarce and high-cost Pt-based catalysts [1,2]. In this context, single-atom metal–N–C catalysts (SACs) have consequently attracted significant research interest for their unique electronic and geometric structures, permitting the maximum atom-utilization efficiency. The metal atom center in such metal–N–C catalysts should not be considered as an isolated active site, which is coordinated with the surrounding carbon substrate structure and acts as an integral part of the catalytic reaction [3]. Among all the PGM-free ORR catalysts, Fe–N–C has attracted much interest due to its brilliant performance and stability [4,5]. Fe–N4 moieties, with the geometric structure of the Fe atom coordinated with four nitrogen atoms, are widely regarded as the active sites to directly adsorb O2 and catalyze the subsequent O–O bond breaking [6,7], therefore significantly improving the ORR catalytic activity [8,9]. Thus, the overall activity of Fe–N–C atomic catalysts is related to two key factors: the formation of Fe–N4 moieties as well as the structural morphology of the supports. At present, although some success has been achieved in exposing more active sites to promote catalytic performance [10,11], the role of the N defect site configuration in Fe–N–C electrocatalysts is still difficult to determine. To this end, metal–organic frameworks (MOFs) are widely used as precursors in research due to their homogeneous chemical composition and abundant microporous structure where Fe–Nx moieties can largely be hosted [12,13,14]. To enhance the widespread exposure of active sites hidden inside the sample, many strategies have been used to tailor the morphology and nanostructure of Fe–N–C electrocatalysts [15,16] in which the formation of N-doped carbon (NC)/carbon nanotube (CNT) hybrid supports by MOF pyrolysis with the presence of Fe, Co, or other metals are widely reported [17,18]. The catalyst supports consisting of highly graphitized carbon or CNTs are more stable and possess high conductivity, which are beneficial to high electrocatalytic performance in ORR [19]. However, as reported, metal nanoparticles (NPs) are easily formed at the end of the CNTs, which in turn reduces the utilization of active sites [20,21]. The presence of CNTs and the absence of metal NPs require a delicate kinetic balance. As far as we know, iron single atoms (SAs) anchored on both CNTs and the carbon matrix from MOF pyrolysis have seldomly been reported. In this work, we successfully prepared iron single atoms anchored on nitrogen-doped carbon/carbon nanotube (FeSA-NC/CNTs) hybrid supports by the pyrolysis of ZIF-8 as molecular cages in one step without any further treatment. The aberration-corrected high-angle annular dark field scanning transmission electron microscopy (AC-HAADF-STEM) characterization showed that abundant Fe atoms were uniformly distributed on the NC/CNT supports without any Fe NPs being observed. Electron energy-loss spectroscopy (EELS) spectra showed the existence of Fe and N in the same area. Further extended X-ray absorption fine structure (EXAFS) indicated that four nitrogen atoms were coordinated around each Fe atom to form a stable Fe–N4 structure. The tailored porous carbon matrix/nanotube structures are beneficial to the full utilization of Fe–N4 sites [22], which makes our FeSA-NC/CNTs catalyst deliver not only better ORR performance, but also more excellent stability than that of the commercial Pt/C catalyst (20 wt%) under alkaline conditions. Our study provides a new idea for the design and synthesis of efficient single-atom non-precious metal catalysts, providing an important reference for the development of new high-efficiency electrocatalysts. 2. Experimental Section 2.1. Reagents 2-Methylimidazole (98%, Aladdin, Shanghai, China), zinc nitrate hexahydrate (analytical grade, 99%, Aladdin), iron acetylacetonate (98%, Aladdin), methanol (analytical grade, Sinopharm Chemical, Shanghai, China), commercial Pt/C (20 wt% metal, Alfa Aesar, Shanghai, China), KOH (analytical grade, Sinopharm Chemical), and Nafion D-521 dispersion (5% w/w in water and 1-propanol, Alfa Aesar) were used as received without any further purification. The distilled water used in all experiments was obtained through ion-exchange and filtration. 2.2. Synthesis of ZIF-8 In the typical synthesis of ZIF-8, Zn(NO3)2·6H2O (0.6082 g, 2 mmol) was dissolved in 15 mL methanol with stirring for 15 min in beaker A. 2-Methylimidazole (1.0604 g, 13 mmol) was dissolved in 7.5 mL methanol with stirring for 15 min in beaker B. Then, the solution in beaker B was subsequently added into beaker A with thorough stirring for 0.5 h at room temperature. The mixed solution was then transferred into a 45 mL Teflon lined stainless-steel autoclave and kept at 90 °C for 1 h in an oven. After cooling to room temperature, the obtained product was separated by centrifugation and washed with anhydrous ethanol three times and finally dried overnight under vacuum at 60 °C. 2.3. Synthesis of Fe(acac)3-0.1@ZIF-8 The synthesis process is the same as ZIF-8, with 71.6 mg (0.2 mmol) Fe(acac)3 being introduced. 2.4. Synthesis of Fe(acac)3-0.15@ZIF-8 The synthesis process was the same as ZIF-8, with 107.4 mg (0.3 mmol) Fe(acac)3 being introduced. 2.5. Synthesis of NC, FeSA-NC/CNTs and FeNP-NC/CNTs The powders of ZIF-8 were transferred into a ceramic boat and placed in a quartz tube furnace. Then, the sample was heated to 900 °C at a heating rate of 5 °C min−1, kept at 900 °C under flowing N2 for 3 h and finally naturally cooled to room temperature. The final powders NC were collected and characterized without further treatment. The synthesis process of FeSA-NC/CNTs was the same as NC, except that the raw material was Fe(acac)3-0.1@ZIF-8. The synthesis process of FeNP-NC/CNTs was the same as NC, except that the raw material was Fe(acac)3-0.15@ZIF-8. 2.6. Synthesis of FeSA-NC The powders of Fe(acac)3-0.1@ZIF-8 were transferred into a ceramic boat and placed in a quartz tube furnace. Then, the sample was heated to 800 °C at a heating rate of 5 °C min−1, kept at 800 °C under flowing N2 for 3 h, and finally naturally cooled to room temperature. The final powders of FeSA-NC were collected and characterized without further treatment. 2.7. Characterization The morphology of the samples was characterized by scanning electron microscopy (SEM, Gemini 450, ZEISS, Jena, Germany) with an acceleration voltage of 5 kV. The transmission electron microscopy (TEM) images and element mappings were obtained at 200 kV using a JEM-2100F (JEOL, Tokyo, Japan) equipped with an X-ray energy dispersive spectrometer (EDS: X-Max 80T, Oxford, UK) for chemical composition analysis. EDS elemental maps were taken in HAADF-STEM mode. Atomic resolution analyses were performed on an aberration-corrected scanning transmission electron microscopy (AC-STEM, Grand ARM300F, JEOL, Japan) equipped with an electron energy-loss spectrometer (EELS: GIF Quantum 970, Gatan, Inc., CA, USA). The energy resolution of EELS was ∼1 eV measured at the width at half-maximum of the zero-loss peak with the energy dispersion of 0.25 eV/channel. The structures were characterized by X-ray diffraction (XRD, PANalytical Empyrean Rayon X, Eindhoven, The Netherlands) with Cu Kα radiation (λ = 1.5418 Å) at 40 kV and 40 mA with an increment of 0.04 degrees. Raman spectra were collected on a Renishaw inVia confocal Raman microscope with a 532 nm wavelength incident laser light. X-ray photoelectron spectroscopy (XPS, Kratos, AXIS Ultra DLD, Manchester, UK) was performed to investigate the chemical bond using Al K Alpha (1486.6 eV) and the value of 284.8 eV as the C 1s peak reference. A PerkinElmer Pyris Diamond was utilized for TGA measurements. The differential scanning calorimetry (DSC) was recorded on a Diamond DSC system. Nitrogen adsorption–desorption measurements were conducted on an Autosorb IQ Gas Sorption System at 77 K. The Brunauer–Emmett–Teller (BET) surface area was calculated using the adsorption data. X-ray absorption fine structure (XAFS) measurements based on Synchrotron Radiation were carried out at the 1W2B beamline at the Beijing Synchrotron Radiation Facility (BSRF), China. The EXAFS data were processed according to the standard procedures using the ATHENA module implemented in the IFEFFIT software packages (version 0.9.25, Chicago, IL, USA). 2.8. Electrochemical Measurements A total of 2 mg of catalyst was dispersed in 1 mL Nafion (5 wt%) and sonicated for about an hour under ultrasonic treatment to form a homogeneous catalyst ink. A sample of 24.7 μL ink was dropped onto the polished glassy carbon disk electrode in order to yield a catalyst loading of 0.2 mg cm−2 and dried under an infrared lamp. The electrochemical impedance spectroscopy (EIS) and all the electrocatalytic performance measurements were performed using a CHI 760E Electrochemical Workstation (Shanghai Chenhua, Shanghai, China). The EIS curves were obtained at the reduced peak potential with a signal amplitude of 5 mV s−1 and a frequency range of 100 kHz–100 mHz. The oxygen reduction performance was conducted in a three-electrode system: a platinum foil as counter electrode; a saturated calomel electrode (SCE) as the reference electrode, and a glassy carbon electrode as the working electrode. All potential values were calibrated to the reversible hydrogen potential (ERHE) based on the Nernst equation:(1) ERHE=ESCE+0.2415+0.0591∗pH O2 and N2 were saturated in 0.1 M KOH, respectively, and used as an electrolyte at room temperature. Cyclic voltammetry (CV) experiments were conducted with a sweep rate of 50 mV s−1 in the potential ranging from 0.1 to 1.2 V in O2-saturated electrolyte at a rotating disk electrode (RRDE) of 0 rpm. Then linear sweep voltammetry (LSV) experiments were carried out in the potential range from 0.1 to 1.2 V at a rotating speed ranging from 400 to 2025 rpm with a sweep rate of 5 mV s−1 at room temperature. The accelerated durability tests (ADT) of the electrocatalyst were acquired in an O2-saturated 0.1 M KOH electrolyte at room temperature, with potential cycling between 0.6 to 1 V at a sweep rate of 50 mV s−1 for 5000 cycles. The electronic transfer number (n) was analyzed by the Koutecky–Levich (K–L) equation:(2) 1J=1JL+1JK=1Bω12+1JK (3) B=0.62nFC0D023V−16 where J represents the current density; JL and JK are the limited and kinetic current density, respectively; ω indicates the rotating rate of the electrode; n is the electron transfer number in oxygen reduction; F is the Faraday constant (96,485 C mol−1); C0 is the bulk concentration of O2 (1.2 × 10−6 mol cm−3); D0 is the diffusion coefficient of O2 in 0.1 M KOH (1.9 × 10−5 cm2 s−1); V is the kinematic viscosity of the electrolyte (0.01 cm2 s−1); and the constant 0.62 was used to determine B when the unit of rotating rate was rad s−1. The H2O2 yield (H2O2%) and the electron transfer number (n) were calculated with the following equations:(4) H2O2 (%)=200×IRNID+IRN (5) n=4×IDID+IRN where ID is the disk current; IR is the ring current; and N is the ring collection efficiency with a value of 0.4. The Tafel plot was calculated with the following equation:(6) η=a+b log|JK| where η is overpotential; JK means kinetic current density; and b indicates the Tafel plot. According to Equation (6), to make the η-log|JK| curve, take the part that fits the linear relationship, and its slope is the Tafel plot. 3. Results and Discussion The synthesis process of Fe(acac)3-0.1@ZIF-8 and its subsequent conversion into FeSA-NC/CNTs is schematically illustrated in Figure 1. Fe(acac)3 was mixed with ZIF-8 according to the synthesis method in the previous study [23]. A molecular-scale cage was formed by Zn2+ and 2-methylimidazole with the poles and cavities being larger for one Fe(acac)3 molecule to be trapped. After pyrolysis at 900 °C under N2 flow, the final product, FeSA-NC/CNTs, was obtained after zinc evaporation at a temperature higher than 450 °C (see Figure S1 for the DSC/TGA results) [24]. The target metal (Fe) sites were spatially separated by the 2-methylimidazole bond and zinc atoms, with a greatly increasing space distance between one other. Therefore, ZIF-8 can be transformed into nitrogen-doped carbon (NC)/carbon nanotube (CNT) hybrid supports after the evaporation of zinc atoms during high temperature heat treatment in N2. A suitable amount of nitrogen dopant in carbon can effectively maintain good electrical conductivity while improving its electrocatalytic properties. Meantime, an appropriate content of Fe(acac)3 could be carbonized by the organic ligands to form isolated single iron atoms bound to the nitrogen species anchored on the carbon matrix/CNTs [25]. The morphologies of the original Fe(acac)3-0.1@ZIF-8 and as-prepared FeSA-NC/CNTs were examined by using SEM and TEM. As shown in Figure 2a and Figure S2, the original Fe(acac)3-0.1@ZIF-8 exhibited rhombic dodecahedral morphology with a particle size of about 400 nm [24]. After pyrolysis at 900 °C under N2 for 3 h, the sample still maintained its previous rhombic dodecahedral morphology with many thread-like or filamentous substances decorated on the surface of the particles (Figure 2b). The TEM and HRTEM images in Figure 2c,d show that these crisscross substances were thin-walled carbon nanotubes with a diameter of around 10 nm. No obvious nanoparticles (NPs) were observed on these carbon nanotubes or the rhombododecahedral carbon matrix, implying the possible formation of Fe single atoms. Corresponding STEM-EDS elemental maps in Figure 2e–h demonstrate that the signals of Fe, N, and C were uniformly dispersed on the NC and CNTs. Furthermore, AC-HAADF-STEM was used to visualize the microstructure of NC and CNTs at the atomic scale. Due to the much higher atomic number (Z) of the Fe atoms compared to that of C and N atoms [26], bright dots representing Fe single atoms distributed on NC as well as CNTs can be observed in HAADF images (highlighted by red circles in Figure 2i–j and Figure S3). Moreover, EELS spectra taken at the carbon matrix and carbon nanotubes (Figure 2k) indicated the co-existence of Fe, N, and C, demonstrating the formation of abundant Fe–N4 moieties. As known, for SACs, if metallic catalysts are not completely encapsulated or simply anchored on the surface of the carbon-based support, they are not effective at preventing the leaching of metallic ion under harsh operating conditions. In addition, fully encapsulating the metal catalysts into a thicker carbon matrix, but away from the surface, may hinder the effective electron transfer between the catalysts and the reactants [27]. In our work, the NC/CNT hybrid supports possessed much higher surface area (1626.814 m2 g−1) thanks to their mesoporous structure (Figure S4), which is not only beneficial to the full utilization of Fe–N4 active sites [28], but may also facilitate oxygen mass transfer within the catalyst film. Therefore, our FeSA-NC/CNTs catalyst exhibited a high electrocatalytic activity and stability in ORR [19]. These aspects demonstrate the advantages of manufacturing well-dispersed Fe–N–C catalysts by using MOFs as a template. To further explore the formation mechanism of FeSA-NC/CNTs, MOF precursors with different contents of Fe(acac)3 were synthesized. It was found that after pyrolysis at the same conditions, FeNP-NC/CNTs with obvious Fe NPs could be observed at the end of the formed CNTs (Figure S5) when the content of Fe(acac)3 in ZIF-8 was changed from 0.1 to 0.15. Moreover, when the pyrolysis temperature was reduced to 800 °C, only Fe single atoms (SAs) anchored on NC were formed while neither Fe NPs nor CNTs were formed (Figure S6). Based on the above results, it is speculated that the formation of Fe SAs on both NC and CNTs can be attributed to delicately tuning the content of Fe(acac)3 in ZIF-8 and pyrolysis temperature. The content of doped Fe(acac)3 should be controlled, as the ORR performance is far from being ideal if the amount is small (less active sites are involved) and clusters or eventually nanoparticles will be formed if the amount is too large [29,30]. Besides, higher pyrolysis temperature will be critical for improving the graphitization of carbon to form a porous carbon matrix as well as CNTs with the existence of Fe. XRD, Raman, and XPS were employed to further investigate the structural properties and chemical composition of the electrocatalysts. The XRD patterns of original ZIF-8 and Fe(acac)3-0.1@ZIF-8 powders (Figure 3a) showed almost identical diffraction peaks, indicating that the addition of Fe(acac)3 does not change the structure of ZIF-8 [31,32]. Similar to the XRD pattern of NC derived from pure ZIF-8 (the blue line in Figure 3a), there was a much broader diffraction peak in the range of 20–30° (indexed to (002) planes of graphitic carbon) for that of FeSA-NC/CNTs (the green line in Figure 3a), demonstrating the formation of a graphitic carbon structure [33], whereas the degree of graphitization was not good enough. Furthermore, no diffraction peak corresponding to the bulk-centered cubic α-Fe (PDF#87-0722) was detected in Figure 3a, which proves that there was no formation of any iron nanoparticles in FeSA-NC/CNTs. In contrast, the XRD pattern of FeNP-NC/CNTs (Figure S7) showed a small but distinct diffraction peak at about 44°, which verified the presence of Fe NPs. As seen in the Raman spectra shown in Figure 3b, the peaks of the D-band and G-band for both the NC and FeSA-NC/CNTs were roughly at 1354 cm−1 and 1591 cm−1, respectively. It is well-known that the ratio of the integrated area of the D-band to the G-band is related to the defect density in the lattice [33]. The decrease in this ratio from NC to FeSA-NC/CNTs implies that the doping of iron drives an increase in the graphitization of ZIF-8-derived carbon hybrid supports, in line with the XRD results, which may improve the electrical conductivity of the carbon supports and promote electron transfer for electrochemical applications [34]. The XPS spectra of FeSA-NC/CNTs (Figure 3c) showed four peaks for C 1s, N 1s, O 1s, and Fe 2p, confirming the presence of carbon, nitrogen, oxygen, and especially iron, which is present in a small but real amount. It should be noted that the O 1s peak may come from surface adsorbed oxygen in the environment. The C 1s peak (Figure S8a) can be deconvoluted into three peaks centered at 284.8, 286.0, and 290.0 eV, which can be attributed to the C–C, C–N, and C=O bonds, respectively [35]. The XPS spectrum of Fe 2p showed two spin-orbit doublets at 711.7 and 722.9 eV, which can be attributed to the Fe 2p3/2 and Fe 2p1/2 orbits. Unfortunately, the Fe signal was not very visible, perhaps related to the coverage of carbon matrix/carbon nanotubes and/or the iron content below the detection limit (Figure S8b). The presence of C–N bonds indicates the successful nitrogen doping in the carbon matrix. In addition, high-resolution N 1s spectra showed the presence of porphyrin-like Fe–N4 moieties at 399.7 eV as well as pyridinic (398.5 eV), pyrrolic (400.9 eV), graphitic (403.5 eV), and N–Ox (406.3 eV) (Figure 3d) [36]. According to previous studies, pyridinic N and pyrrolic N can provide coordination sites by moving lone pairs to the carbon plane, which can enhance the chemisorption of oxygen molecules and intermediates during the ORR process [37,38]. Graphitic N not only improves the conductivity of the catalyst, but also the presence of C–N bonds can induce an inhomogeneous distribution of electrons, thus promoting the adsorption of O2 and the dissociation or weakening of O=O bonds [39,40,41]. To further investigate the chemical state and coordination environment of the Fe sites in FeSA-NC/CNTs, X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) were carried out at the Fe K-edge. Fe foil, FePc, and Fe2O3 samples were also measured as reference samples. As illustrated in the Fe K-edge XANES spectra of FeSA-NC/CNTs (Figure 4a), the adsorption edge was located between Fe foil and Fe2O3, indicating that the oxidation state of the Fe species was between Fe0 and Fe3+, and close to Fe2+. The EXAFS spectra of FeSA-NC/CNTs (Figure 4b) showed a prominent peak centered at 1.5 Å, which was mainly attributed to the first Fe–N coordination shell [42,43]. Moreover, compared to the Fe foil, the absence of scattering peaks derived from Fe–Fe coordination in FeSA-NC/CNTs suggests that Fe species were monodispersed in the N-doped carbon matrix/CNT hybrid supports [44]. The coordination structure of the Fe atoms in the FeSA-NC/CNTs was further investigated by quantitative EXAFS curve fitting analyses (Figure 4c and Table S1), which clearly revealed that the Fe center was coordinated with four N atoms at the first coordination shell. All fitting results were well consistent with the experimental data, from which the average coordination numbers of Fe–N was obtained as 4.2, with the average bond lengths for Fe–N of 2.01 Å, respectively (see more details in Table S2). Furthermore, the wavelet transform (WT, Figure 4d–f) results displayed only one WT intensity maximum at ≈3.8 Å−1, associated with the Fe–N pair. Compared with the WT plots of Fe foil, the WT signal related to Fe–Fe contribution was not detected in the FeSA-NC/CNTs. These observations further demonstrate that the single Fe atoms simultaneously coordinated with N atoms, forming the Fe–N bonds. The construction of the FeSA-NC/CNTs catalyst was dedicated to improving the ORR catalytic performance, which was investigated by cyclic voltammetry (CV, Figure S9) and linear scanning voltammetry (LSV) in an O2-saturated 0.1 M KOH solution based on a three-electrode system under rotating disk electrode (RDE). A commercial 20 wt% Pt/C catalyst (20 wt% metal, Alfa Aesar) was used as the reference for the performance comparison. All given potentials refer to the reversible hydrogen electrode (RHE). This ORR performance was compared in this work to other similar published research (Table S3). FeSA-NC/CNTs showed a reduction peak at 0.82 V, indicating a certain ORR activity (Figure S9). As shown in Figure 5a, the onset potential (Eonset) with a value of about 0.93 V for FeSA-NC/CNTs was slightly inferior to that of Pt/C, but much better than that of FeNP-NC/CNTs and FeSA-NC. It demonstrates that the high-performance Fe-SAC catalyst can be prepared by tuning the content of Fe(acac)3 in ZIF-8 and the pyrolytic conditions. According to Figure 5b, FeSA-NC/CNTs deliver a higher half-wave potential (E1/2 = 0.86 V) than that of Pt/C (0.846 V). The kinetic current density (Jk) of FeSA-NC/CNTs (39.3 mA cm−2) at 0.8 V was also much higher than that of Pt/C (14.4 mA cm−2), indicating its superior kinetics. To further unveil the electron transfer mechanism of FeSA-NC/CNTs, the LSV curves at different rotating rates are depicted in Figure 5c. The Koutecky–Levich (K–L) curves obtained from the LSV curves exhibited good linearity, showing the primary reaction kinetics related to the O2 concentration and the potential-independent electron transfer rate (Figure 5c, inset) [45]. The yield of H2O2 and electron transfer number were confirmed by the rotating ring-disk electrode (RRDE), suggesting a superior selectivity of oxygen reduction for H2O with an electron transfer number greater than 3.9 and a H2O2 yield below 5% over the potential range of 0.2 to 0.9 V (Figure 5d) [46]. The Tafel slope of FeSA-NC/CNTs was about 74.4 mV dec−1, which was significantly lower than that of Pt/C (104.6 mV dec−1), demonstrating the FeSA-NC/CNTs electrocatalyst possessed accelerated ORR kinetics (Figure 5e) [47]. It should be noted that there was no significant decay of E1/2 (ca. 1 mV) after 5000 consecutive potential cycles (Figure 5f), which proves that the FeSA-NC/CNT catalyst also has superb durability. The electrochemical impedance spectroscopy (EIS) was also measured (Figure S10). The Nyquist plots were fitted by an equivalent circuit model. As shown in Figure S10a–c, FeSA-NC/CNTs showed the smallest arc radius (Rct: 100.3 Ω) in the Nyquist plot compared with FeNP-NC/CNTs and FeSA-NC, indicating the lowest charge-transfer resistance at the catalyst/electrolyte interface and superior charge transport kinetics [48]. The Bode plots can be used to estimate the effectiveness of ion diffusion. The ion diffusion in the low-frequency region is related to the phase angle. The smaller the phase angle, the faster the ion diffusion [49]. Therefore, FeNP-NC/CNTs have a more favorable diffusion angle (<−40°). The phase angle of FeSA-NC/CNTs and FeSA-NC was close to 0° in the low-frequency region, demonstrating that diffusion was not the dominant mechanism. At lower frequencies, the impedance (|Z|) was much higher due to mass transfer effects, while at higher frequencies, the lower the impedance, the easier the charge transfer. FeSA-NC/CNTs had the lowest impedance at high frequencies (65 Ω), implying that charge transfer dominates. It can be seen that the value of |Z| decreased the most in FeNP-NC/CNTs, implying the breaking of the activation barrier and promoting charge transfer in the high-frequency region and charge diffusion in the low-frequency region. 4. Conclusions In summary, we synthesized a single-atom FeSA-NC/CNTs catalyst through the cage-encapsulated-precursor pyrolysis strategy by skillfully tuning the pyrolyzed temperature and the content of Fe(acac)3 in the precursors. Based on the results of HRTEM, EDS, and HAADF-STEM, it is clear that the catalyst has a large number of Fe single atoms distributed on the NC/CNT hybrid supports as a mesoporous structure with a specific surface area of 1626.814 m2 g−1. Benefiting from the high density and superb accessibility of Fe–N4 active sites, the catalyst exhibited excellent ORR performance with a half-wave potential (E1/2) of 0.86 V, which exceeded that of commercial Pt/C. It had a high kinetic current density (Jk) of 39.3 mV cm−2 at 0.8 V. The yield of H2O2 was below 5% and the electron transfer number was close to 4, indicating that FeSA-NC/CNTs had a high electrocatalytic efficiency. Besides, it showed excellent stability with little change in the ORR polarization curve after 5000 CV cycles. In short, the outstanding catalytic activity of FeSA-NC/CNTs can be attributed to the synergistic roles of abundant Fe single atoms as well as the porous NC/CNT hybrid architectures, which ensures the full utilization of Fe–N4 active sites with improved electron transfer and oxygen mass transport. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nano12091593/s1, Figure S1: (a) TGA and (b) DSC curves of Fe(acac)3-0.1@ZIF-8. The weight loss was attributed to the decomposition of ZIF-8 and the release of Zn species. That is, the Zn nodes with a low boiling point of 907 °C would evaporate at such high temperatures, leaving the N rich defects; Figure S2: TEM image of Fe(acac)3-0.1@ZIF-8; Figure S3: (a) and (b) are representative HAADF-STEM images of FeSA-NC/CNTs at different areas; Figure S4: (a) N2 sorption isotherms of FeSA-NC/CNTs. (b) Corresponding pore size distribution curve calculated using the DFT methods; Figure S5: (a) TEM and (b) HAADF-STEM images of FeNP-NC/CNTs, where typical iron single atoms are marked by red circles; Figure S6: (a) TEM and (b) HAADF-STEM images of FeSA-NC, where typical iron single atoms are marked by red circles; Figure S7: XRD patterns of FeSA-NC/CNTs and FeNP-NC/CNTs; Figure S8: (a) High resolution XPS C 1s spectra of FeSA-NC/CNTs. (b) High resolution XPS Fe 2p spectra of FeSA-NC/CNTs.; Figure S9: CV curves of FeSA-NC/CNTs in O2-saturated 0.1 M KOH with a sweep rate of 50 mV/s; Figure S10: Nyquist plots of (a) FeSA-NC/CNTs, (b) FeSA-NC, and (c) FeNP-NC/CNTs, where the inset is the equivalent circuit model for impedance spectra fitting. Bode plots of (d) FeSA-NC/CNTs, (e) FeSA-NC, and (f) FeNP-NC/CNTs. Table S1: Fitting results of Fe foil EXAFS; Table S2: Fitting results of sample–Fe EXAFS; Table S3: Comparison of ORR performance with some reported non-precious catalysts in 0.1 M KOH. References [14,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66] are cited in the supplementary materials. Click here for additional data file. Author Contributions Conceptualization, Y.J., M.H., R.H., and R.Q.; Methodology, Y.J., W.Z. and M.H.; Formal analysis, Y.J. and W.X.; Investigation, Y.J. and C.S.; Software, Y.J.; Data curation, Y.J.; Writing—original draft preparation, Y.J.; Funding acquisition, R.H.; Supervision, R.Q.; Writing—review and editing, R.H. and R.Q. 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 The schematic illustration of FeSA-NC/CNTs. Figure 2 SEM images of (a) Fe(acac)3-0.1@ZIF-8 and (b) FeSA-NC/CNTs. (c) TEM and (d) HRTEM images of FeSA-NC/CNTs. (e–h) STEM-EDS elemental maps of C, Fe, and N of the FeSA-NC/CNTs sample shown in (e). AC-HAADF-STEM images of (i) N-doped carbon matrix and (j) carbon nanotubes, corresponding to the blue and yellow areas in (c), respectively. (k) Electron energy-loss spectroscopy showing the C K-edge, N K-edge, and Fe L-edge acquired from the marked region in (c). Figure 3 (a) XRD patterns of ZIF precursors and as-pyrolyzed samples. (b) Raman spectra. (c) XPS survey scan spectrum of FeSA-NC/CNTs. (d) High resolution XPS N 1s spectra of FeSA-NC/CNTs. Figure 4 (a) Fe K-edge XANES spectra of FeSA-NC/CNTs (the orange area highlights the near-edge absorption energy). (b) Fourier transform (FT) of the Fe K-edge EXAFS spectra. (c) The corresponding EXAFS r space fitting curves of FeSA-NC/CNTs. Wavelet transform (WT) of Fe K-edge for (d) Fe foil, (e) FePc, and (f) FeSA-NC/CNTs. Figure 5 (a) ORR polarization plots of FeSA-NC/CNTs and Pt/C in O2-saturated 0.1 M KOH with a sweep rate of 5 mV s−1 and 1600 rpm. (b) E1/2 and JK at 0.8 V for different catalysts. (c) LSV curves of FeSA-NC/CNTs with various rotation rates (inset: K–L plots). (d) Electron transfer number and H2O2 yield in ORR on FeSA-NC/CNTs from the RRDE results. (e) Tafel plots of Pt/C and FeSA-NC/CNTs. (f) LSV curves of FeSA-NC/CNTs before and after 5000 potential cycles. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Holby E.F. Wang G. Zelenay P. Acid stability and demetalation of PGM-free ORR electrocatalyst structures from density functional theory: A model for “single-atom catalyst” dissolution ACS Catal. 2020 10 14527 14539 10.1021/acscatal.0c02856 2. Wang K. Du L. Wei Q. Zhang J. Zhang G. Xing W. Sun S. A Lactate/Oxygen Biofuel Cell: The Coupled Lactate Oxidase Anode and PGM-Free Fe-N-C Cathode ACS Appl. Mater. Interfaces 2019 11 42744 42750 10.1021/acsami.9b14486 31638769 3. Jia Y. Jiang K. Wang H. Yao X. 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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093597 sensors-22-03597 Article End-to-End Sentence-Level Multi-View Lipreading Architecture with Spatial Attention Module Integrated Multiple CNNs and Cascaded Local Self-Attention-CTC https://orcid.org/0000-0003-4705-1254 Jeon Sanghun https://orcid.org/0000-0002-6050-6594 Kim Mun Sang * Denby Bruce Academic Editor Gábor Csapó Tamás Academic Editor Wand Michael Academic Editor Center for Healthcare Robotics, Gwangju Institute of Science and Technology (GIST), School of Integrated Technology, Gwangju 61005, Korea; jeon7887@gist.ac.kr * Correspondence: munsang@gist.ac.kr; Tel.: +82-10-9126-4628 09 5 2022 5 2022 22 9 359711 4 2022 07 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/). Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in real-world scenarios, most VSR studies have focused solely on frontal face pictures. To address this issue, we propose an end-to-end sentence-level multi-view VSR architecture for faces captured from four different perspectives (frontal, 30°, 45°, and 60°). The encoder uses multiple convolutional neural networks with a spatial attention module to detect minor changes in the mouth patterns of similarly pronounced words, and the decoder uses cascaded local self-attention connectionist temporal classification to collect the details of local contextual information in the immediate vicinity, which results in a substantial performance boost and speedy convergence. To compare the performance of the proposed model for experiments on the OuluVS2 dataset, the dataset was divided into four different perspectives, and the obtained performance improvement was 3.31% (0°), 4.79% (30°), 5.51% (45°), 6.18% (60°), and 4.95% (mean), respectively, compared with the existing state-of-the-art performance, and the average performance improved by 9.1% compared with the baseline. Thus, the suggested design enhances the performance of multi-view VSR and boosts its usefulness in real-world applications. lipreading visual speech recognition multi-view VSR deep learning attention mechanism spatial attention module convolutional neural network local self-attention connectionist temporal classification National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)NRF-2018X1A3A1069795 This research was funded by National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT), grant number NRF-2018X1A3A1069795. ==== Body pmc1. Introduction Hearing and vision, sometimes known as verbal and visual signals, are widely employed in communication. Because audio signals typically include more information than visual signals, various experiments on automatic speech recognition (ASR) have been performed. Consequently, ASR has attained a very high recognition rate without causing significant signal deterioration. Moreover, it has been used in numerous applications. In contrast, visual speech recognition (VSR) recognizes speech content based on the speaker’s lip-movement features in the absence of speech signals, that is, the speech information is inferred from the movement of the lips. In particular, the visual channel receives two-dimensional visual information, which typically contains more redundant information than that contained in the one-dimensional spoken information received via the auditory channel. Overcoming these VSR limitations is challenging. People with hearing loss frequently communicate using sign language or by reading the movement of the person’s lips. However, sign language has limitations, such as learning and comprehension difficulties, as well as insufficient expression skills. In this regard, VSR can help people with hearing loss interact effectively with others [1,2]. In noisy environments, interference from ambient noise can reduce audio recognition rates. By contrast, the visual information required for VSR does not change; consequently, VSR can increase speech-recognition performance in noisy contexts [3,4]. In particular, owing to the dominance of facial recognition technology in the field of security, including the use of photographs, video playback, and 3D modeling, VSR technology has been subjected to a large number of attacks. In this approach, including lip movement into a security system might improve its reliability [5]. Additionally, conventional speech synthesis can only generate a single voice in the primary domain of visual synthesis, whereas lipreading technology may generate high-resolution speeches of several characters in a video [6]. Furthermore, lip gestures can be employed to increase sign-language identification accuracy or comprehension [7,8]. Recent research has predominantly focused on lipreading from a frontal perspective [9,10,11,12,13,14,15]. This approach contradicts previous findings in the literature showing that human lipreaders prefer non-frontal views [16,17], owing to noticeable lip protrusion and lip rounding at these angles. Therefore, it might be practical to improve frontal-view lipreading abilities using non-frontal lip view information. This information can also be helpful when a frontal view of the mouth, which is the region of interest (ROI), is unavailable. This is true in real-life situations in which the subject’s face is not visible [11,18,19]. In other words, in an audio VSR or VSR system, the speaker is not continually facing the smart device, kiosk, or camera. Recently, several VSR systems have been proposed [20,21,22,23,24,25,26]. However, most VSR studies focus on frontal facial images because of the shortage of published datasets that include facial images from different angles. These investigations include lipreading studies, in which the emphasis is on frontal, diagonal, and profile images. The OuluVS2 [27] dataset, a publicly accessible multi-view VSR dataset, is typically used as a research corpus for evaluating novel approaches. Estellers and Thiranin [28] trained a system using both frontal (0°) and profile (90°) faces and performed exploratory research on multi-view lipreading. Their study demonstrated that the frontal perspective exhibited a lower word error rate (WER) than the profile view. Isobe et al. [29] examined the frontal (0°), left profile (90°), and right profile (90°) viewpoints using a multi-angle approach. When the frontal perspective was used instead of the other perspectives, the system performance improved. As a breakthrough sequence-picture encoding approach, Saitoh et al. [21] proposed concatenated frame image encoding (CFI). They developed a framework for a convolutional neural network (CNN) based on CFI and compared two data augmentation methodologies for CFI. Bauman et al. [16] observed that AI lipreaders perform better when human faces are slightly inclined because of lip protrusion and rounding. They used the active appearance model (AAM) to extract features from five distinct angles. Using a regression technique in feature space to assess lipreading on both view-dependent and view-independent systems, they reported that the view-dependent system outperformed benchmark models in all tests, receiving a perfect score of 30. Aiming at blending diverse views, Zimmermann et al. [22] coupled principal component analysis-based convolutional networks with long short-term memory (LSTM), a deep learning model, a conventional voice recognition model, hidden Markov models, and Gaussian mixture models. They found that a 30° face inclination produced the best effects. Anina et al. [27] recorded the best accuracy at 60°. Lipreading with a profile view produces lower WERs than lipreading with a frontal viewpoint, according to Kumar et al. [20]. Deep learning has also been used to blend multiple view angles and edit photographs. In particular, Komai et al. [30] implemented AAMs to transform frontal faces viewed from various angles. Their results suggested that identification accuracy increased even when the face orientation was rotated roughly 30° from the frontal perspective. The “View2View” system developed by Koumparoulis and Potamianos [23] relies on a CNN-based encoder–decoder paradigm. The technique converts non-frontal mouth photographs into frontal mouth images. Their view-mapping method for VSR and audio-visual speech recognition (AVSR) was reported to be successful. By synthesizing virtual frontal views from non-frontal images, Estellers et al. [28] devised a position normalization technique and accomplished multi-view speech recognition. Petridis et al. [24] proposed a multi-view bidirectional LSTM-based lipreading model. The proposed approach considers data directly from pixels while simultaneously performing VSR from various perspectives. They discovered that combining the frontal and profile images boosted the accuracy when compared to using only the frontal view. Zimmermann et al. [25] implemented a PCA-based CNN, LSTM network, and GMM–HMM model to extract features in a decision fusion-based lipreading model. They reported that the decision fusion was effective because Viterbi pathways were included. In addition, to perform multi-angle lipreading, Sahrawat et al. [26] employed view-temporal attention to expand a hybrid attention-based connectionist temporal classification (CTC) system. Finally, Lee et al. [31] trained a CNN–LSTM model from beginning to end. Evidently, numerous studies have been conducted based on deep learning. However, fewer studies have been conducted on multi-view lipreading than existing speech recognition and front lipreading studies. Therefore, considering the above-mentioned limitations, we propose a multi-view VSR architecture that supports VSR when both frontal and non-frontal lip pictures are identified. In particular, for non-frontal views, we developed an end-to-end sentence-level multi-view lipreading neural-network architecture that outperforms traditional and current deep learning VSR systems. Convolutional, recurrent, and transcriptional layers were sequentially applied to develop the multi-view VSR architecture. The remainder of this paper is structured as follows: Section 2 delves into the details on the proposed architecture, Section 3 discusses the experiments, and Section 4 discusses the results. Finally, Section 5 provides the concluding remarks of this study. 2. Proposed Architecture In this section, we propose a novel feature-extraction approach. In particular, the proposed architecture is divided into three layers (convolutional layer, recurrent layer, transcription layer) based on an end-to-end neural network with four different perspective inputs, as shown in Figure 1. The three layers are compared against various modules for their performance evaluation. In the convolutional layer, based on the visual extraction module proposed in a previous study [32], the model was modified to improve the feature extraction performance and convergence speed. To compare the modules of the proposed architecture, three current equivalent designs were implemented: multi-scale 3D CNN, spatial attention module (SAM), and integrated multi-scale 3D CNN (Figure 1a). In addition, the recurrent layer was compared as a sequence-processing module with other modules, such as residual neural network (RNN), LSTM, gated recurrent unit (GRU), Bi-LSTM, and Bi-GRU (Figure 1b). The transcription layer was compared as a process for decoding the output features with other components, such as standard CTC, global self-attention-CTC, and local self-attention-CTC (Figure 1c). 2.1. Convolutional Layer To encode visual information from the extracted lips, all input-image sequences were loaded into a spatiotemporal CNN. We extracted spatiotemporal information from an input image composed of numerous continuous frames using a three-dimensional convolutional layer with 64 kernels; 3 × 5 × 5, (1, 2, 2), and (1, 2, 2) are the sizes, strides, and pads, respectively. To minimize the transformation of internal variables, we used a batch normalization (BN) layer and a rectified linear unit (ReLU) layer to accelerate the training process. Subsequently, a max-pooling 3D layer was used to decrease the spatial size of the 3D feature maps. Thus, the output form was observed utilizing 40 × 50 × 25 × 64 tensors with an input sequence of 40 × 100 × 50 × 3 frames. A densely linked connection contains several connections. In this regard, CNN connects numerous layers of a connection, allowing for efficient feature usage, decreased gradient disappearance, and increased network depth. The input-feature volumes are reduced by the bottleneck layer, which comes before the convolutional layer. The multichannel feature volumes are merged using the bottleneck layer approach. The second layer is applied to only a fraction of the volume of the previous features because the prior features remain visible. Additionally, transition layers are utilized to increase the model’s compactness, with the hyperparameter theta controlling the degree of compression. A bottleneck layer, transition layer, and slower growth rate are used to create a tight network. This strategy saves computing power while minimizing model parameters and preventing overfitting. Dense connection CNN is an architecture that focuses on making deep learning networks go even deeper, while simultaneously making them more efficient to train by using shorter connections between the layers (Figure 2). Figure 2a displays a CNN, where each layer is connected to all of the other layers that are deeper in the network, and it consists of two important blocks other than the basic convolutional and pooling layers, that is, the dense blocks and the transition layers. Dense block (1) was built using the following layers in order: BN, ReLU, 3D convolutional, BN, ReLU, and 3D convolutional layers (see Figure 2b). Dense blocks (2), (3), and (4) have the same structure as dense block (1). The transition layer is depicted in Figure 2c, which comprises a BN layer, ReLU layer, three 3D convolutional layers, and two 2D pooling layers. Different CNN models have yielded outstanding results in picture classification tasks. One such example is feature aggregation using numerous CNNs, which allows the extraction of diverse spatial and temporal information by creating separate structures and depths [33]. Several convolutional layers with varying degrees of abstraction can be extracted during the multi-scale 3D CNN training phase. This training technique can also produce a range of features with various depths and filter sizes. Some of the essential characteristics lost in the layered design can be selected using this strategy, resulting in a more feature-rich final product. The attention mechanism can boost the feature representation strength of our interests by telling us “what” and “where” to focus our attention. Attention weighting is used in computer vision to boost the feature representation capacity by emphasizing relevant characteristics and limiting inconsequential characteristics. Moreover, attention can be regarded as a strategy for allocating a finite computational force to more informative areas [34,35,36]. Hu et al. [37] proposed the “Squeeze-and-Excitation” module to describe the channel-wise correlation of convolutional features without considering the spatial information. The convolutional block attention module [38] empirically demonstrated that both max-pooling and average-pooling operations contribute to the attention mechanism. Additionally, the inter-spatial interactions feature may be utilized to produce a map of spatial attention. Spatial attention, in contrast to channel attention, focuses on the locations of informative sections and serves as a supplement to channel attention. As a result, the weights associated with attention are distributed over two separate dimensions in this model: channel and space. The model initially executes average-pooling and max-pooling operations along the channel axis before concatenating them to build an efficient feature descriptor to compute spatial attention. To construct a spatial attention map Ms(F)∈ℛH×W, a convolutional layer is applied to the concatenated feature descriptor. Subsequently, two pooling processes are used to aggregate the channel information of a feature map, resulting in two 3D maps: Favgs∈ℝH×W and Fmaxs∈ℝH×W, each representing the average- and max-pooled features over the channel. A 3D spatial attention map is created by concatenating and convolving them with a conventional convolutional layer. In brief, spatial attention is calculated using the following formula:(1) Ms(F)=σ(f7×7([AvgPool(F);MaxPool(F)])), (2) Ms(F)=σ(f7×7([ Favgs;Fmaxs])), where σ denotes the sigmoid function, and f7×7 represents a convolution operation with a filter size of 7 × 7 (Figure 3b). Because several existing studies implement learning approaches based on sentence front-view datasets [32,39,40,41], it is difficult to expect high accuracy using the same model for multiple viewpoints. Therefore, we propose an SAM-integrated-MLFF 3D CNN, which is a network module focusing on spatial attention with different neighborhoods in the feature maps (Figure 3a). The first module (Figure 3c) comprises a 3D convolutional layer on a 3D dense connection convolutional layer output feature with 32 kernels, followed by a BN layer and a ReLU layer. The second module (Figure 3d) is structured similarly to the benchmark dataset, with a 3D convolutional layer with 64 kernels, followed by a dropout layer to prevent overfitting. By inhibiting the formation of highly correlated activations, the dropout layer enhances and generalizes the performance by avoiding overtraining and overfitting [42]. The third module, which contains a 3D convolutional layer with 96 kernels, is similar to the second module, except for the absence of a dropout layer (Figure 3e). In particular, this method drops the entire feature map. Moreover, in contrast to the traditional dropout method, which removes pixels at random, this method employs CNN models with substantial spatial correlation to improve image classification [43]. Consequently, we employed a spatial dropout layer to extract lips, teeth, and tongue morphologies, which have strong spatial connectivity and contain few movements. Each SAM multi-scale 3D CNN module consists of 3D average-pooling, 3D max-pooling, and 3D convolutional layers, with 32, 64, and 96 3D kernel operations, respectively, along the channel axis and a concatenated BN layer (Figure 3b). Therefore, the output of each multi-scale 3D CNN and SAM is merged and concatenated. As a result, SAM exploits the inter-spatial interaction of the characteristics to better select and focus on the most identifiable and helpful portions of an input picture [38]. 2.2. Recurrent Layer Traditional recurrent neural networks (RNNs), LSTM, and GRU are examples of previously implemented RNN algorithms. Owing to the gradient vanishing issue, a typical RNN has difficulties in learning long-range dependent input and output data, owing to the backpropagation technique’s inability to perform adequately with an increase in input data. To overcome this issue, Hochreiter and Schmidhuber [44] created the LSTM network, which is currently widely used in time-series-data processing [45,46,47]. By efficiently overcoming the gradient vanishing issue through effective learning, LSTM and GRU achieve higher levels of validation and prediction accuracy than traditional RNNs, particularly for long-range dependent input and output data [45,47]. A GRU is an RNN that, through multiple stages, learns to manage and transmit information flow [48]. GRUs are constructed using LSTM units that can decide which data to retain and discard. While the 3D CNN only gathers data at the viseme level, GRUs can differentiate across greater temporal contexts, which is crucial for resolving ambiguity. GRU, which consists of an update gate and a reset gate, can also be used to address the gradient vanishing issue. A two-layer bidirectional GRU is implemented in the proposed architecture, providing a faster convergence speed than a sequence processing module. The two-layer bidirectional GRU is used to transfer information both ways to two distinct neural network topologies coupled to the same output layer, enabling both networks to acquire substantial knowledge of the input. The SAM-integrated-multi-scale 3D CNN provides the input to the two-layer bidirectional GRU layer. For instance, to obtain an output containing 40 × 512 tensors, we submitted a bidirectional GRU 40 × 3 × 1 × 384 frame sequence into the merging layer. 2.3. Transcription Layer Assael et al. [18] used “LipNet” (their neural network, which had outperformed experienced human lip readers) to train a network of end-to-end deep neurons on a benchmark dataset, using the effective CTC loss function [49] for acoustic-based speech recognition. The CTC loss function parameterizes the distribution of the label token sequence without having to align the input sequence; it is conditionally independent of the surrounding distribution generated at each time step. Therefore, the CTC model is a decoding method that uses a beam search technique to detect the temporal dependence of labels. It is worth noting that the CTC loss function assumes conditional independence of independent labels (i.e., individual character symbols). Each output unit corresponds to the probability of seeing one label at a time. As a result, although CTC is built on RNNs, it is primarily concerned with local data (nearby frames) [50]. While this strategy is effective for forecasting acoustic phonemes, it is not effective for predicting visemes, which require additional background information to discern tiny variations. Figure 4 illustrates that the self-attention mechanism [36,51] is a technique to better encode the word at the target location by looking at the word at another location and taking hints from each word in the input full-sequence sentence. Figure 4a depicts the processing process of the self-attention mechanism, with the global area enclosed by a blue-line square and the local area by a red dotted line. Furthermore, Figure 4b shows an example of the mechanism processing process presented in Figure 4a for the sentence “Nice to meet you”. The multi-head self-attention modules that transformers are known for constitute their distinguishing feature [36]. Given an input X∈ℝT×n, where T is the number of time steps and n is the hidden state dimension, a set comprising query, key, and value matrices is generated using the weight matrices WhQ, WhK, and WhV∈ℝn×dk, respectively, where dk is the dimension of the heads of the attention module. There is one embedding per head, denoted by the subscript h. (3) Qh=XWhQ, (4) Kh=XWhK, (5) Vh=XWhV. The keys and queries are multiplied to obtain a T × T attention matrix A. This matrix encodes the relative relevance of each time step, that is, how much attention each time step receives, by assigning a scalar to each pair of time steps. A SoftMax function with temperature dk is applied to convert this into a normalized distribution. The value matrix is subsequently multiplied by the normalized attention matrix. Consequently, each time step has a linear combination of value embeddings, with the most significant embedding receiving the largest weights as follows:(6) Atth=Softmax(QhKhTdk )Vh. The heads are then concatenated and transformed back to the original dimension n using the weight matrix Wout∈ℝdk·nh×n, where nh is the number of heads. Moreover, a residual connection connecting the output to the input is added as follows:(7) Xout=Concath(Atth)Wout+X. Subsequently, each time step is standardized via layer normalization. For time step t, the overall mean of the feature dimension is subtracted from the input, which is then divided by the standard deviation. This is rescaled and shifted by the learnable parameters α and β as follows:(8) Xtnorm=Xtout−μtσt·α+β, where (9) μt=1n∑iXtiout, (10) σt=1n(Xtiout−μt)2. Next, a feedforward neural network is applied in a time-step-wise manner. This part typically consists of two fully connected layers parameterized by weight matrices W1∈ℝn×ϕn, W2∈ℝϕn×n; bias vectors b1∈ℝϕn, b2∈ℝn; and a residual connection as follows:(11) f(XtnromW1+b1)W2+b2+Xtnrom, where f (·) is an element-wise activation function, such as a ReLU or Gaussian error linear unit. Here, ϕ is a scaling factor for the inner dimensions of the feedforward module. Finally, another layer normalization is applied. The encoder, decoder, and feedforward contexts were employed to accelerate translation and offer the most current translation findings, sentiment analysis, and other additional operations. The success of self-attention in these tasks motivated the first study on self-attention in speech recognition [52]. As a result, an attention-based encoder–decoder paradigm was devised. Although self-attention was first employed for machine translation, its versatility enabled it to be utilized for voice recognition as well [53,54,55,56]. Attention-based encoder–decoder models rapidly learn the mapping between the auditory frame and the letter sequence. These models generate a label at each output time step based on the input and target label histories. Despite not requiring an external language model, the attention model has a lower character error rate (CER) than CTC. However, the model performs poorly in real-world conditions for various voice recognition tasks, owing to the ease with which noise and other variables may impair the expected alignment in the attention mechanism. Additionally, learning the model from start is difficult, owing to the misalignment of extended input sequences [57,58]. This study used cascaded local self-attention CTC training criteria to improve performance and accelerate learning for the above-mentioned difficulties. When scaling to larger sequences, transformers scale quadratically in the input length. This problem is solved using a unique speech enhancement transformer model based on local attention [59,60]. Local attention is especially well suited for speech augmentation because the predictions do not require long-range correlations, as in natural language processing. Moreover, sufficient information is frequently stored within a few seconds of the target period. Local attention is naturally interwoven with this demand. The above approach results in huge advances in speech augmentation, where typical sample lengths can involve up to hundreds of thousands of tokens or hours of speech. This small focus incurs only a fraction of the processing and memory overhead associated with attention throughout the entire feature. The windowed technique also allows a more compact packing of padded features in mini-batches, thereby saving costs. Consequently, this module acquires detailed local contextual information from the surrounding area. As the foundational model, we employed cascaded local self-attention with a context size of 12. 3. Experimental Evaluation 3.1. Dataset In this study, the proposed architecture was evaluated on the OuluVS2 [27] dataset. This dataset comprises 52 speakers making three types of utterances (Digits, Phrases, and TIMIT), three times each (except TIMIT), simultaneously recorded from five distinct viewpoints (0°, 30°, 45°, 60°, and 90°) for a total of 780 samples per utterance. There are ten classes in total: “Please excuse me”, “Goodbye”, “Hello”, “How are you”, “Nice to meet you”, “See you”, “I am sorry”, “Thank you”, “Have a nice time”, and “You are welcome”. The impact of various mouth ROIs was evaluated by processing the lips from scratch rather than from existing data, and the 90° data were omitted from the experiment because the lips could not be recognized during the extraction process. For the recognition task, we used the Phrase dataset in this investigation. In particular, we utilized the same data split as in other previous studies [21,22,31], to provide a fair comparison. Twelve speakers were used for testing (s06, s08, s09, s15, s26, s30, s34, s43, s44, s49, s51, and s52; 10 men and 2 women) and 40 for training from the database (s06, s08, s09, s15, s26, s30, s34, s43, s44, s49, and s51). Note that s29 is not included in the list. 3.2. Data Preprocessing and Augmentation A DLib face detector [61] was used in the data-preparation step to recognize the targeted face and mouth. A HoG feature-based linear classifier [33] was used in the detector. The diagonal edges’ (x, y) coordinates were obtained and used to build a bounding box around the mouth. As a result, the iBug program was used to forecast facial landmarks [62], considering 68 landmarks and an online Kalman filter. This method is widely used to extract the lip points that match with those in the training dataset by reading lip motions. These algorithms were utilized to extract a mouth region from each frame, and to perform an affine transformation to equalize the RGB channels throughout the training set, resulting in a mean and variance of zero. Moreover, we employed a data augmentation approach for training data to avoid overfitting [18]. The training process considered both standard and horizontally mirrored picture sequences. The degradation rate for these occurrences was 0.925. Finally, to avoid variance, we identified the movement speed and repeated each frame with a probability of 0.05. All models were trained and evaluated on the OuluVS2 dataset, using identical preprocessing and augmentation methods. 3.3. Implementation To evaluate the performance of the CTC decoder, all models used Keras, based on TensorFlow backend on Linux Ubuntu; the computer had an Intel® Core™ i7-7700K processor, along with 64GB RAM and an NVIDIA GeForce RTX 2080-Ti GPU. The hyperparameters specified in Table 1 are the values for each layer of the proposed model. The network parameters—other than the initialized GRU matrix and hyperparameters—were initialized for all models. To perform the optimization of models, adaptive moment estimation (Adam) [63], stochastic gradient descent (SGD) [64], RMSprop [65], AdaMax, and Nadam [64] optimizers were used in mini-batches of sizes 8 and 0.0001, trained at the learning rate. The proposed model was trained in a multi-scale 3D CNN with SAM; channel-wise dropped pixels and spatial dropout for the dropped channel were used, and the proposed model contained the baseline model, trained on the dataset until it was overfitted. The moving average strategy was used to smooth it down for better viewing. Regarding the accuracy of the proposed model, the genuine value was represented by the shadow part of the image, while the curve represented the smoothed value. We selected a smaller batch size of 75 images owing to the computer’s restricted capabilities, causing the real value fluctuation to be uneven. Smoothing was performed to alleviate this problem and to make the curves comprehensible. 3.4. Performance Evaluation Metrics We used standard automated speech-recognition assessment criteria as the evaluation metrics. The learning loss of each model was calculated to determine its learning status during the training operation. Furthermore, we compared each model’s performance and computational efficiency by examining its parameters, epoch period, and CER. For the misclassification analysis, it is necessary to compare the original text and the predicted text. The five variables used in the equation are the characters (C), the total number of ground truth characters (N), the false predicted characters (S), the non-selected characters (I), and the number of deleted characters (D). CTC beam search is performed for maximum probability prediction, and the CER equation is as follows:(12) CER (%)=(CS+CD+CICN)×100, We compared the CER for parameter count and computational efficiency during the study period. The results are presented using a confusion matrix. 4. Results 4.1. Learning Loss and Convergence Rate Figure 5, Figure 6 and Figure 7 compare the learning loss and convergence speed rates for the convolutional, recurrent, and transcription layers, respectively. Figure 5 shows the learning loss (training and validation) on the OuluVS2 dataset for the convergence rates of the three types of CNNs in the convolutional layer. The three models have different visual feature extraction modules at the front end, and the same recurrent and transcription layers at the back end. Model A consists of a densely connected 3D CNN, Model B combines the multi-scale 3D structure following Model A, and Model C is configured by combining a SAM with Model B. In addition, Figure 5 shows that the training and validation losses of all three models are similar from all four angles. However, the gap between the training and validation losses was the highest in Model A, and its degree of overfitting was higher than those of the other models. Furthermore, although Model C increased the number of parameters by 30 M compared to Model A, it exhibited lower overfitting results (the smallest among all models) (Figure 5). This is because Model A comprised a model with outstanding performance based on the DenseNet-121 [66] structure, thereby minimizing the number of model parameters, successfully suppressing overfitting, and saving computation. However, the combination of multi-scale 3D CNN (Model B) and SAM (Model C) yielded improved results because this combination identified better by focusing on the most distinguishable and beneficial areas of the input image. Therefore, the learning and convergence speeds of Model C were high, and the gap was small. These findings indicate that the proposed model had the smallest difference between the training and validation losses, preventing overfitting on the OuluVS2 dataset. Figure 6 shows the learning loss (training and validation) on the OuluVS2 dataset for the convergence rates of the four types of RNN in the recurrent layer. The convolutional and transcription layers had the same structure, and only the configuration of the recurrent layers differed. The Bi-GRU exhibited the fastest learning convergence speed and best prediction accuracy, as shown in Figure 6 and Figure 9e–f. In particular, all four RNN unit types outperformed the RNN. The experimental results and prediction accuracy are similar to the findings reported in Section 5 of [44], where LSTM and GRU displayed improved validation accuracy and prediction accuracy compared to traditional RNNs (Table 2), owing to their resistance to the vanishing gradient problem. Compared with LSTM and Bi-LSTM, both GRU and Bi-GRU demonstrated faster convergence and lower losses. The bidirectional models outperformed the unidirectional models on the training set for both GRU and LSTM; they also outperformed their unidirectional counterparts on the validation dataset. Consequently, Bi-GRU exhibited the best overall performance. The learning loss (training and validation) on the OuluVS2 dataset is shown in Figure 7 for the convergence rates of the proposed model’s three types of CTC loss functions in the transcription layer. The convergence rate for learning was slower than that in the other two situations, when only the basic CTC loss function was used. In particular, as the angle of the detected lip changed, the convergence rate further decreased, while the two cases of cascaded self-attention exhibited similar convergence rate tendencies for all of the angles. The two self-attention modules learned with similar convergence rate tendencies. However, in all of the four results shown in Figure 7, the local self-attention module exhibited a faster convergence rate than the global self-attention modules. First, the principle of the CTC loss function assumes conditional independence for each label, and, since each output unit denotes the probability of seeing a single label at a given moment, it provides a high premium to the nearby local information [50]. Thus, ineffectiveness in predicting visemes is a possible reason for the difference in convergence rates. The cascaded self-attention CTC module (which generates an output sequence with long-term temporal correlation) increases the speed of convergence, as compared to the CTC decoder (which assumes the input is conditionally independent). The attention approach is used in the CTC decoder’s pre-alignment stage to remove unnecessary paths. The CTC decoder is then used to align the video frames and text labels, thereby allowing the attention mechanism to focus on the video–text pairs in the correct order. As a result, fewer irrelevant samples are created, resulting in the observed speedup. Second, the local self-attention module’s windowed method results in more compact packaging of the padded features in mini-batches, and, hence, further cost reductions. Consequently, this local self-attention requires only a fraction of the computing and memory costs of attention over the entire feature, while providing rich local contextual information in the small region. 4.2. Optimization The update rules of the optimization algorithms are usually defined by the hyperparameters that influence their behavior (e.g., the learning rate). The optimizer’s responsibility is to update the weight parameters prior to reducing the error or loss function, which is the difference between the actual and predicted values. This requires several iterations with varying weights. However, choosing an optimizer for network training can be tricky. Deep learning employs iterative rules to modify or evaluate the data, utilizing numerous aspects and techniques. Therefore, training models as quickly as possible is vital to complete the iterative cycle and, as a result, enhance the prediction accuracy and speed. Consequently, in this part, we study the following optimizers used to train deep learning neural networks: SGD, RMSprop, Adam, Nesterov-accelerated Adam (Nadam), and AdaMax. After validating that AdaDelta and AdaGrad diverged without learning throughout the learning process, we omitted them from the experiments. SGD realizes one update at a time to avoid duplication, making it significantly faster and easier to learn than other deep learning neural networks [67]. These frequent updates of the method with high variance introduce significant fluctuation in the objective function. This variation allows the parameters to move into new, possibly better, local minima. However, as SGD continues to overshoot, converging to the precise minimum is challenging. The parameters of AdaDelta have varying learning speeds, and the learning process comes to a halt after a certain point. This problem was addressed using the RMSprop method [65]. For each sample in each iteration, RMSprop uses a variable learning rate that is changed according to the results. RMSprop calculates the average of the first-order moments of the gradients and accelerates convergence by ignoring distant previous locations. Moreover, the squares of gradients and the average of the second-order moments are considered by AdaDelta and RMSprop. In the Adam optimizer, the adaptive optimization method is applied. Based on the parameters to be used, this optimizer dynamically modifies the learning rate for each sample in the dataset. Adam is a fast thinker with a limited memory span. Therefore, SGD, AdaDelta, and RMSprop [65] were used to create this algorithm. Nadam combines Adam and Nesterov momentum. This method was developed similarly to Adam, with the exception that the flat momentum is replaced with the Nesterov momentum. The substitution causes a more considerable increase in performance than that in momentum. [63,68]. Alternatively, AdaMax, an extension of the Adam optimizer, was developed [63]. To update the weight parameters in AdaMax, the infinity norm of the moment is used, instead of the second-order moment estimate. Therefore, the size of the parameter update in AdaMax has a simpler constraint structure than in Adam, and the weight-updating rules are stable. We used the Bi-GRU classifier to compare the training results and determine the most successful optimizer. Figure 8 depicts the loss curves of the optimizers. In particular, Adam performed better among the optimizers at all of the four angles. The Adam optimizer’s loss converged at the quickest pace, implying that it trained the Bi-GRU classifier more successfully than the other algorithms. The results show that Adam was the best optimizer for training the Bi-GRU architecture’s lip-based classification model. Therefore, this approach was employed in further trials in this study to train the Bi-GRU classifier. 4.3. Performance and Accuracy The results presented in this section correspond to the OuluVS2 dataset phrases. Table 2 and Table 3 show that the proposed model outperformed existing deep learning models by attaining state-of-the-art (SOTA) results: 3.31% (0°), 4.79% (30°), 5.51% (45°), 6.18% (60°), and 4.95% (mean). These results show an improvement over the previous SOTA results in all of the conditions. Figure 9 compares the accuracy results between the models by dividing them into three layers: convolutional layer (Figure 9a–d), recurrent layer (Figure 9e–h), and transcription layer (Figure 9i–l). In the case of the convolutional layer (Figure 9a–d and Table 2), on average, the performance improved by 3.63% for all of the four angles when MLFF 3D CNN and SAM were combined than when only the DenseNet-121 structure was used. By combining the SAM with MLFF 3D CNN, a 2.46% improvement was observed owing to improved recognition among the inter-spatial relationships of features. This helped to better identify and focus on the most distinguishable and informative areas of the input image. In the case of the recurrent layer (Figure 9e–h and Table 2), five RNN units (RNN, LSTM, Bi-LSTM, GRU, and Bi-GRU) were compared. For all of the four angles, LSTM and GRU exhibited higher accuracy than the standard RNN. This is because of their robustness against gradient disappearance, which allows them to successfully learn long-range dependent input data. Therefore, the average accuracy of LSTM increased by 1.83% compared to when RNN was used. Similarly, the average accuracy of GRU increased by 4.17%. However, despite its similar performance, Bi-LSTM’s accuracy increased by 2.71% compared to RNN, and Bi-GRU’s accuracy improved by 6.77% when unidirectional models were used, compared to bidirectional models. The bidirectional models also achieved better results on the validation dataset than their unidirectional counterparts. Thus, the best overall performance was achieved using the Bi-GRU. In the case of the transcription layer (Figure 9i–l and Table 2), we compared the performance by combining the global and local self-attention mechanisms with the basic CTC function in the cascade method. For all of the four angles, the two CTC loss functions exhibited higher performance than the basic CTC loss function. When using the global self-attention method, accuracy improved by 0.95%, while the local self-attention method improved by 5.47%. The performance of the two models is better than that of the CTC loss function because they overcome the disadvantage of assuming a conditionally independent input. Moreover, the performance difference between the two methods exists because the local self-attention module led to a more compact packing of the padded features in mini-batches, resulting in additional savings. Therefore, this local self-attention required a fraction of the compute and memory costs associated with attention over the entire feature and rich local contextual information in the local region. Thus, the proposed model surpasses current models, including the experimental model, in terms of accuracy, which can be attributed to the three layers. The training approach with three layers is illustrated in Figure 9, using the OuluVS2 dataset. 4.4. Statistical Analysis and Model Efficiency We performed statistical analysis using the standard t-test to compare the significance of the combined modules. Models A and B of the convolutional layer were compared, based on Model C (Figure 10a–d), and Models C, D, E, F, and G were compared in the current layer (Figure 10a–d). In addition, in the transcription layer, Models C and H and the proposed model were compared (Figure 10e–h). For all four angles in Figure 10a–d, the proposed model showed that the modules in the convolutional layer have significant differences. That is, the performance increased by combining the MLFF 3D CNN and the SAM with the DenseNet-121 model. In addition, in the recurrent layer, the use of the Bi-GRU classifier (Model C) exhibited the highest performance and significant results compared to the four RNN-type units. However, in the case of Model G, because the unidirectional GRU model was used, there was no significant difference compared to Model C, which is a bidirectional model. Figure 10e–h shows the statistical analysis of the transcription layer. The performance of the two models using the self-attention mechanism in the cascade method was higher and significant than that for learning based on the basic CTC loss function. Consequently, the proposed model exhibited significant performance improvement. In practical applications, the primary limitations of the VSR systems are their size and computing capacity. We explored the models’ computational efficiency by examining their accuracy over various training settings and epochs. The system’s performance as a function of the number of parameters is shown in Figure 11a–d. Furthermore, Figure 11e–h depict the results of the average epoch–time comparison of the nine models for 500 epochs. As demonstrated in Table 4, each model on the OuluVS2 dataset has a unique set of parameters and epoch time. Compared to Model D, which presented the lowest accuracy among the compared models, the proposed model had a parameter count difference of approximately 29 M. The average accuracy was improved by 12.24%. In comparison to Model F, which had the most parameters, the proposed approach decreased the number of parameters by roughly 11 M, while increasing accuracy by 9.53%. In addition, the difference in learning time compared to Model D, with the smallest number of parameters, differed by 5.54 s on average per epoch, which is not significant. Furthermore, the difference in learning time compared to that of Model F, which has the most parameters, was 13.05 s. Thus, the proposed model is capable of enhancing accuracy and decreasing learning time without considerably increasing the number of parameters. 4.5. Confusion Matrix We compared the confusion matrices of the two models that exhibited outstanding performance in the three layers with that of the proposed model for the four angles. Specifically, we evaluated Model C (Figure 12), which exhibited the highest accuracy in the convolutional and recurrent layers; Model H (Figure 13), which exhibited excellent performance in the transcription layer; and the proposed model (Figure 14). When comparing the results shown in Figure 12, the proposed model realizes fewer incorrect predictions. In addition, Model C had more erroneous predictions than the other two models for the four angles. The number was particularly high for “Hello”, “Thank you”, and “See you” because they are visually similar from the same viewpoint, furthermore, “Thank you” and “See you” have identical viseme sequences around the beginning and end of the utterance, which explains why these phase pairings have a higher number of false predictions. Because they are visually comparable from the same viewpoint, the three pairs of sentences with the highest error rate are the most demanding and confusing pairings with a high error rate, as indicated by the confusion matrix [13,24,31]. However, when the global self-attention mechanism was combined with the transcription layer, Model H exhibited better overall confusion pair results than Model C in 10 phases. Model H clearly demonstrated that confusion decreased compared to Model C. Despite the decrease in confusion, some pairs show particularly high confusion rates at each angle. As can be observed in Figure 13a, the predictions between “Nice to meet you” and “How are you” were the lowest, and, as shown in Figure 13b,c, were confused with “Nice to meet you” and “How are you” for “Thank you.” In addition, unlike the other three angles, the 60° angle (Figure 13d) showed substantial confusion, wherein “Thank you” and “How are you” exhibited the lowest predictions. Therefore, Model H, similar to Model C, increased the number of confusions, due to the similarity of the visual view as the angle increased. The last pronunciation, such as “you”, showed low predictions within a similar phase. Unlike the two models, the proposed model yields low confusion at all of the angles using the local self-attention mechanism. In particular, for the 60° angle, both Models C (Figure 12d) and H (Figure 13d) presented high confusion numbers. In contrast, the proposed model (Figure 14d) presented low confusion numbers, similar to other angles. In addition, the confusion between “Hello”, “Thank you”, and “See you” observed in the other two models was reduced, and the predicted value increased. By comparing the confusion matrices, we can easily define which of the models performs better. Thus, we can establish that the proposed model outperformed the others on the OuluVS2 dataset, distinguishing all comparable pronunciations in phase. 5. Discussion and Conclusions Lipreading is difficult to execute because it cannot be purely performed from the frontal perspective. Professional lip readers claim that a non-faceted approach, instead of a front-view, provides more information than a front-view with more pronounced lip protrusions and lip rounding. Consequently, the most significant limitation in using lipreading technology in real-world applications is its performance when reading lips from multiple angles. Therefore, we developed a multi-angle/multi-view VSR architecture that performs VSR by detecting both frontal and non-frontal lip images. This study provides an end-to-end infrastructure for recording multi-view video surveillance. We obtained an accurate viseme prediction using SAM, multiple CNNs, and cascaded local self-attention-CTC. This is the first time that a 3D CNN, 3D dense connection CNN, and SAM have been combined with a multi-scale 3D CNN to extract lip motion characteristics as encoders. Following the decoder’s Bi-GRU, a transcription layer based on cascaded local self-attention-CTC was used to extract exhaustive local contextual information from the surrounding environment. The advantages of each level of the proposed architecture can be summarized as follows. The 3D dense connection CNN helps in reducing gradient vanishing and deepening the network (to use features) in an efficient manner. It also helps in reducing model parameters and preventing overfitting, thereby conserving computational resources. Finally, the multi-scale 3D CNN is applied to the two dropout layers, using features at different levels to effectively analyze the motion context in the temporal and spatial domains, with fine motion and high spatial correlation. SAM and multi-scale 3D CNNs are combined and concatenated to provide a single output. Consequently, SAM exploits the inter-spatial interaction of characteristics to better select and focus on the most identifiable and practical portions of an input picture. Moreover, cascaded local self-attention-CTC, following the decoder’s Bi-GRU, requires only a fraction of the computation and memory costs of attention over the entire feature, leading to compact packaging of padded features in mini-batches and significant savings. Hence, this module can be used to acquire detailed local contextual information from the surrounding area. We compared the outcomes of various deep learning models for predicting the sequence of phrases. The proposed architecture outperformed the others in terms of SOTA CER (Table 2 and Table 3). We also compared the convergence rate, optimization, accuracy, statistical analysis, model efficiency, and confusion of the learning process for the three layers (convolution, recurrent, and transcription). The proposed model exhibited a faster convergence speed and higher accuracy compared to the other models, without a significant difference in the number of parameters and epoch time. The proposed model attained SOTA performance on the OuluVS2 dataset without requiring external data or even data augmentation. The given mouth ROIs, on the other hand, were appropriately cropped, which may not be the case when employing automated mouth ROI identification techniques. Additionally, it would be interesting to investigate the effect of automated mouth ROI cropping on multi-view lipreading because the accuracy of automatic detectors is known to degrade with non-frontal views. Finally, because the model can be readily expanded to other streams, we expect to incorporate an audio stream to see how well it performs in audio-visual multi-view speech recognition. Developing a multi-view VSR system that exclusively relies on visual data is crucial. Speech recognition in loud situations, hearing impairment, and biometric identification are some applications for which such a system will be practical. It could also be helpful for people with speech difficulties. However, because speech involves auditory and visual information, it is still challenging to perform ASR simply by using VSR. As a result, we plan to widen our approach in the future to include performance optimization and identification of potential uses for audio and visual data. Author Contributions Methodology, S.J.; software, S.J.; validation, S.J.; formal analysis, S.J.; investigation, S.J.; data curation, S.J.; writing—original draft preparation, S.J.; writing—review and editing, S.J. and M.S.K.; visualization, S.J.; supervision, M.S.K.; funding acquisition, M.S.K. 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 database used in this article was OuluVS2. For details, please refer to [27]. Conflicts of Interest The authors declare no conflict of interest. The funder 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 Block diagram of the proposed multi-view lipreading architecture; (a) convolutional layer; (b) recurrent layer; and (c) transcription layer. Figure 2 Details of 3D dense connection CNN architecture: (a) dense connection CNN; (b) dense block layer structure; and (c) transition layer structure. Figure 3 Details of the spatial attention module-integrated MLFF 3D CNN: (a) Block diagram of the proposed module; (b) spatial attention module; (c) first module’s architecture; (d) second module’s architecture with dropout layer; and (e) third module’s architecture with spatial dropout layer. Figure 4 (a) Details regarding the global and local self-attention process: the blue line square encloses the global area, and red dotted line square encloses the local area; and (b) self-attention mechanism processing process presented for the sentence “Nice to meet you”. (* for dot product). Figure 5 Training and validation loss comparing convergence speed of convolutional layers (Models A, B, and C): (a–d) Training loss at (a) 0°; (b) 30°; (c) 45°; and (d) 60°; (e–h) Validation loss at (e) 0°; (f) 30°; (g) 45°; and (h) 60°. Figure 6 Training and validation loss comparing convergence speed of recurrent layers (Models C, D, E, F, and G). (a–d) Training loss at (a) 0°; (b) 30°; (c) 45°; (d) 60°. (e–h) Validation loss at (e) 0°; (f) 30°; (g) 45°; (h) 60°. Figure 7 Training and validation loss comparing convergence speed of transcription layers (Model C, Model H, and the proposed model). (a–d) Training loss at (a) 0°; (b) 30°; (c) 45°; (d) 60°; (e–h) Validation loss at (e) 0°; (f) 30°; (g) 45°; (h) 60°. Figure 8 Loss curves comparing various optimizers. (a–d) Training loss at (a) 0°; (b) 30°; (c) 45°; and (d) 60°; (e–h) validation loss at (e) 0°; (f) 30°; (g) 45°; and (h) 60°. Figure 9 Training steps for character error rate (CER) comparing our proposed model to the baseline and other models: (a–d) Convolutional layer; (e–h) recurrent layer; (i–l) transcription layer. Figure 10 Comparison between different models and the proposed model based on mean accuracy of the last 10 epochs: (a–d) Convolutional layer and recurrent layer; (e–h) Transcription layer. Error bars represent standard deviation. Asterisks represent statistical significance-based t-tests between each group (* for p < 0.05, ** for p < 0.01, and *** for p < 0.001). Figure 11 Comparison of character accuracy rate (CAR) between the proposed model and other models according to the (a–d) number of parameters and (e–h) average epoch time. Figure 12 Comparison of confusion matrix models: (a–d) Model C. Figure 13 Comparison of confusion matrix models: (a–d) Model H. Figure 14 Comparison of confusion matrix models: (a–d) the proposed model. sensors-22-03597-t001_Table 1 Table 1 Hyperparameters of the proposed architecture. Layer Output Shape Size/Stride/Pad Dimension Order Input Layer 40 × 100 × 50 × 3 - T × C × H × W Convolution 3D Layer 40 × 50 × 25 × 64 [3 × 5 × 5]/(1, 2, 2)/(1, 2, 2) [1 × 2 × 2] max pool/(1 × 2 × 2) 3D Dense Block (1) 40 × 25 × 13 × 96 [3 × 1 × 1] 3D Conv (×6) [3 × 3 × 3] 3D Conv 3D Transition Block (1) 40 × 12 × 6 × 6 [3 × 1 × 1] 3D Conv [1 × 2 × 2] average pool/(1 × 2 × 2) 3D Dense Block (2) 40 × 12 × 6 × 38 [3 × 1 × 1] 3D Conv (×12) [3 × 3 × 3] 3D Conv 3D Transition Block (2) 40 × 6 × 3 × 3 [3 × 1 × 1] 3D Conv [1 × 2 × 2] average pool/(1 × 2 × 2) 3D Dense Block (3) 40 × 6 × 3 × 35 [3 × 1 × 1] 3D Conv (×24) [3 × 3 × 3] 3D Conv 3D Transition Block (3) 40 × 3 × 1 × 1 [3 × 1 × 1] 3D Conv [1 × 2 × 2] average pool/(1 × 2 × 2) 3D Dense Block (4) 40 × 3 × 1 × 33 [3 × 1 × 1] 3D Conv (×16) [3 × 3 × 3] 3D Conv Multi-scale 3D CNN (1) 40 × 3 × 1 × 32 [3 × 5 × 5]/(1, 2, 2)/(1, 2, 2) Multi-scale 3D CNN (2) 40 × 3 × 1 × 64 [3 × 5 × 5]/(1, 2, 2)/(1, 2, 2) Multi-scale 3D CNN (3) 40 × 3 × 1 × 192 [3 × 5 × 5]/(1, 2, 2)/(1, 2, 2) Spatial Attention (1) 40 × 3 × 1 × 32 [1 × 2 × 2] max pool/(1 × 2 × 2) [1 × 2 × 2] average pool/(1 × 2 × 2) [3 × 7 × 7]/(1, 2, 2)/(1, 2, 2) Spatial Attention (2) 40 × 3 × 1 × 64 [1 × 2 × 2] max pool/(1 × 2 × 2) [1 × 2 × 2] average pool/(1 × 2 × 2) [3 × 7 × 7]/(1, 2, 2)/(1, 2, 2) Spatial Attention (3) 40 × 3 × 1 × 96 [1 × 2 × 2] max pool/(1 × 2 × 2) [1 × 2 × 2] average pool/(1 × 2 × 2) [3 × 7 × 7]/(1, 2, 2)/(1, 2, 2) Bidirectional GRU Layer 40 × 512 256 T × F Bidirectional GRU Layer 40 × 512 256 T × F Local Self-Attention Layer 40 × 512 15 T × F Dense Layer 40 × 28 27 + blank T × F SoftMax Layer 40 × 28 T × V sensors-22-03597-t002_Table 2 Table 2 Performance of the proposed model compared to various models on the OuluVS2 dataset. Model Method Top 10 Accuracy (%) 0° 30° 45° 60° Mean A * 3D dense connection CNN + Bi-GRU + CTC 90.44 88.73 86.93 87.72 88.45 B * 3D dense connection CNN + Multi-scale 3D CNN + Bi-GRU + CTC 92.72 91.02 88.02 88.09 89.62 C * 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-GRU + CTC 94.14 92.86 91.34 89.97 92.08 D * 3D dense connection CNN + Multi-scale 3D CNN + SAM + RNN + CTC 88.51 85.74 83.93 83.04 85.31 E * 3D dense connection CNN + Multi-scale 3D CNN + SAM + LSTM + CTC 89.42 87.42 86.01 85.71 87.14 F * 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-LSTM + CTC 89.78 88.84 87.26 86.18 88.02 G * 3D dense connection CNN + Multi-scale 3D CNN + SAM + GRU + CTC 92.85 91.23 90.91 89.67 91.14 H * 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-GRU + Global self-attention + CTC 95.08 93.29 92.81 90.93 93.03 Our * 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-GRU + Local self-attention + CTC 98.31 97.89 97.21 96.78 97.55 * Model trained with data augmentation. sensors-22-03597-t003_Table 3 Table 3 Performance of existing models on the OuluVS2 dataset. Year Model 0° (%) 30° (%) 45° (%) 60° (%) Mean (%) 2014 RAW-PLVM [69] 73.00 75.00 76.00 75.00 74.75 2016 CNN * [21] 85.60 82.50 82.50 83.30 83.48 CNN + LSTM [31] 81.10 80.00 76.90 69.20 76.80 CNN + LSTM, Cross-view Training [31] 82.80 81.10 85.00 83.60 83.13 PCA Network + LSTM + GMM–HMM [22] 74.10 76.80 68.70 63.70 70.83 CNN pretrained on BBC dataset * [52] 93.20 - - - - CNN pretrained on BBC dataset + LSTM * [70] 94.10 - - - - 2017 End-to-End Encoder + BLSTM [24] 94.70 89.70 90.60 87.50 90.63 Multi-view SyncNet + LSTM * [71] 91.10 90.80 90.00 90.00 90.48 End-to-End Encoder + BLSTM [13] 84.50 - - - 84.50 End-to-End Encoder + BLSTM [72] 91.80 87.30 88.80 86.40 88.58 2018 CNN + Bi-LSTM [73] 90.30 84.70 90.60 88.60 88.55 CNN + Bi-LSTM [73] 95.00 93.10 91.70 90.60 92.60 Maxout-CNN-BLSTM * [74] 87.60 - - - - CNN + LSTM with view classifier * [23] - 86.11 83.33 81.94 - CNN + LSTM without view classifier * [23] - 86.67 85.00 82.22 - 2019 VGG-M + LSTM * [75] 91.38 - - - 91.38 2020 CNN(2D + 3D) without view classifier [76] 91.02 90.56 91.20 90.00 90.70 CNN with view classifier [76] 91.02 90.74 92.04 90.00 90.95 2021 CNN without view classifier [77] 91.02 90.56 91.20 90.00 90.70 CNN with view classifier * [77] 91.02 91.38 92.21 90.09 91.18 * Model trained with data augmentation. sensors-22-03597-t004_Table 4 Table 4 Comparison between the number of parameters and epoch times of the proposed method and different methods. Model Method Number of Parameters Epoch Time (s) 0° 30° 45° 60° A 3D dense connection CNN + Bi-GRU + CTC 2,247,537 34.57 36.07 34.43 33.97 B 3D dense connection CNN + Multi-scale 3D CNN + Bi-GRU + CTC 3,456,369 36.48 36.58 34.93 35.43 C 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-GRU + CTC 5,273,457 43.37 41.44 40.01 43.03 D 3D dense connection CNN + Multi-scale 3D CNN + SAM + RNN + CTC 2,429,362 35.27 36.78 36.15 35.86 E 3D dense connection CNN + Multi-scale 3D CNN + SAM + LSTM + CTC 3,905,458 38.16 39.13 38.94 37.45 F 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-LSTM + CTC 6,421,426 54.35 53.18 53.04 57.86 G 3D dense connection CNN + Multi-scale 3D CNN + SAM + GRU + CTC 3,413,426 34.18 32.98 33.48 33.48 H 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-GRU + Global self-attention + CTC 5,306,290 40.95 42.13 41.78 43.48 Our 3D dense connection CNN + Multi-scale 3D CNN + SAM + Bi-GRU + Local self-attention + CTC 5,306,290 40.46 41.39 41.97 42.41 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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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/ijerph19095152 ijerph-19-05152 Article Smartphones, the Epidemic of the 21st Century: A Possible Source of Addictions and Neuropsychiatric Consequences https://orcid.org/0000-0003-2469-6340 Adamczewska-Chmiel Klaudia 1 https://orcid.org/0000-0002-7764-1362 Dudzic Katarzyna 2 https://orcid.org/0000-0001-6022-7731 Chmiela Tomasz 3* https://orcid.org/0000-0001-5081-8343 Gorzkowska Agnieszka 4 Braverman Eric R. Academic Editor Blum Kenneth Academic Editor Cadet J. L. Academic Editor Baron David Academic Editor Gold Mark S. Academic Editor 1 Students’ Scientific Association, Department of Neurology, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-752 Katowice, Poland; klaudia.adamczewska75@gmail.com 2 Students’ Scientific Association, Department of Neurorehabilitation, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-752 Katowice, Poland; dudzic.kat@gmail.com 3 Department of Neurology, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-752 Katowice, Poland 4 Department of Neurorehabilitation, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-752 Katowice, Poland; agorzkowska@sum.edu.pl * Correspondence: tchmiela@sum.edu.pl 23 4 2022 5 2022 19 9 515217 1 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/). Background and Objectives: Phonoholism is the excessive and harmful use of a smartphone. We are now observing this phenomenon among adults more often. Using a smartphone for several hours may lead to somatic and psychological symptoms, such as headaches and depression. The aim of this study is to assess the prevalence of phonoholism and to assess the association between smartphone overuse and neuropsychiatric disorders. Materials and Methods: A total of 368 people (70.1% were woman), aged between 19 and 82 years (average age 26.1), took part in an anonymous questionnaire consisting of the following elements: Hospital Anxiety and Depression Scale (HADS), Mobile Phone Problem Use Scale (MPPUS-9), and original questions regarding headaches and sleep quality, along with a subjective assessment of the use of smartphones and an objective evaluation based on data from the applications “Stay Free” and “Screen Time”. Results: A total of 61 respondents (16.6%) obtained a score on the MPPUS-9 scale, which revealed their problematic use of mobile devices. Patients with phonoholism had significantly more headaches (85% vs. 58.7%, p = 0.027). Subjects with phonoholism had significantly shorter mean sleep duration (7.14 h vs. 7.42 h, p = 0.0475) and were less likely to feel sleepy during the day (43.33% vs. 59.73%, p = 0.0271). The group with phonoholism had significantly higher scores on the HADS-A anxiety scale (8.29 vs. 10.9, p = 0.015), but a statistical significance was not confirmed for depressive symptoms. Conclusions: The excessive use of the telephone negatively affects both somatic and mental health and can pose a significant clinical problem. phonoholism headache depression anxiety sleep disorders ==== Body pmc1. Introduction Due to technological development and the spread of portable multimedia devices, smartphones are now universally used. The estimated worldwide number of smartphone users in 2021 was >3.8 billion, a number that has doubled since 2015 [1]. Despite the fact that people benefit from the wide range of applications that are available on smartphones, the growing popularity of smartphones may lead to their overuse. Indeed, problematic smartphone use (PSU), defined as the excessive use of mobile devices with a negative impact on academic, professional, and/or social functioning [2], has become an increasing problem. Despite the prevalence of this phenomenon, there is still no widely accepted definition and terms such as smartphone dependence syndrome and smartphone addiction are not included in current official classifications of diseases, such as ICD-10 or DSM-5 [3]. As early as 1996, this problem was classified as falling within the category of technological addictions and considered as “a behavioural addiction, characterised by the dependence between a person and a device, in the absence of a simultaneous physical intoxication” [4]. On the other hand, other researchers point out that problematic smartphone use is a heterogeneous and multifaceted phenomenon and should be better studied, as little evidence supports its affiliation with behavioural disorders similar to, for instance, drug addiction [2]. Despite the unquestionable advantages of using smartphones, one should remember the examples of its negative influence on people, such as the disruption of interpersonal relations, withdrawal from the outside world due to limited direct contact with other people, and the increased amount of time spent alone compared to time spent in a group. Using a smartphone to participate in social life may lead to the establishment of superficial relationships as well as the loss of skills to create complex statements and appropriate stylistic features of messages and spelling [5]. An additional negative aspect of increased smartphone usage is the exposure to the magnetic radiation emitted by mobile devices [5]. A growing number of studies indicate that smartphone abuse is associated with additional stress, sleep disturbances, lowered mood, and depression [6]. It is noteworthy that during the COVID-19 pandemic, the prevalence of the aforementioned disorders increased [7]. In situations of prolonged stress, one of the ways of coping is to resort to activities that make it possible to reduce negative emotions, which in predisposed individuals may lead to problematic habits [8]. Furthermore, in a study by J. Wang et al., it was shown that the risk of headaches increased by 38% percent in those who used smartphones compared to those who did not [9]. This problem not only affects adults, as a growing number of studies report that this problem is becoming more prevalent among a population of increasingly younger children [10]. The aim of this study is to assess the prevalence of phonoholism among smartphone users and to assess the association between smartphone overuse and neuropsychiatric disorders. In our study, we focused solely on adults. To the best of our knowledge, this is the first study to investigate the problematic use of mobile devices on an adult population in Poland. Furthermore, this work not only studies the occurrence of phonoholism and its neuropsychiatric consequences, but also confronts these issues with the use of smartphones through the real and objective measurement of mobile device usage time. 2. Materials and Methods We employed a cross-sectional study to assess association between smartphone usage and neuropsychiatric disorders—headaches, sleep disorders, mood and anxiety disorders. The participants included adult smartphone users in Poland. The data were collected from 24 February 2021 to 1 October 2021 through a self-administered questionnaire. A voluntary response sampling method was used to recruit participants. Volunteers were recruited online through social media and the participants were also encouraged to share the questionnaire further. Smartphone users aged over 18 years were included in this study. Exclusion criteria were as follows: diagnosed depression, anxiety, or sleep disorders. The study involved a questionnaire containing two validated clinical scales: the Hospital Anxiety and Depression Scale (HADS), a brief scale evaluating anxiety and depression, and the Mobile Phone Problem Use Scale (MPPUS-9), the Polish version of MPPUS-10, which has been validated and adapted to Polish conditions. This study also contained a set of original questions regarding headaches, sleep quality, and the subjective assessment of smartphone use. A Numeric Pain Rating Scale (NRS) was used to assess the severity of the headaches. The respondents answered the questions online. All questions were closed-ended, which means that the respondents were only allowed to select answers from a strictly defined set of options. Respondents were asked to use the following free applications that they had installed on their smartphones: “Stay Free” for Android users and “Screen Time” for iOS users. These applications provide information on the total number of hours spent in front of a screen over the previous seven days, the daily average over the previous week, and the most frequently used apps. The provided answers served only to collect statistical data. Participants provided informed consent electronically. A total of 397 people responded to the questionnaire, and 29 individuals were excluded from the study (17 were excluded due to incorrect survey completion and 12 were excluded due to inappropriate age (<18 years old)). The final study group consisted of 368 people, including 251 females (70.1%) and 107 males (29.9%) aged between 19 and 82 (mean age 26.1) years. For statistical calculations, we divided the subjects into two groups based on their MPPUS-9 scale scores: <53 points and ≥53 points. The cut-off point of ≥53 indicated the presence of problematic smartphone use [11]. The statistical analysis was performed with Statistica 13.3 (TIBCO Software Inc., Palo Alto, CA, USA, (2017) (data analysis software system, version 13. http://statistica.io)). The quantitative variables are presented as an arithmetic mean and a standard deviation. The qualitative variables are presented as absolute values and percentages. The normality of distribution was assessed with the Shapiro–Wilk test. Due to the fact that the normal distribution in the analysed groups was not confirmed, the intergroup differences for the quantitative variable were assessed with the Mann–Whitney Utest. Fisher’s exact test and the chi-square test was performed to assess the qualitative variables. Due to the survey character of the work and data anonymisation, the Ethics Committee of the Medical University of Silesia waived the requirement to obtain an ethical approval for this study. 3. Results 3.1. Prevalence of Phonoholism A total of 61 individuals (16.6%), of which 47 were women and 16 were men, met the criteria for a diagnosis of phonoholism defined as an MPPUS-9 score of over 53 points. There were no statistically significant differences between the two groups regarding gender, education, physical activity, comorbidities, and place of residence. Detailed data are summarised in Table 1. 3.2. Phonoholism and Headache Among the patients with phonoholism, a significantly higher number of individuals had headaches (85% vs. 58.7%, p = 0.027). However, there was no statistically significant difference in the frequency of pain among patients with pain in these two groups. In the group of patients without phonoholism, nausea (22.9% vs. 7.8%, p = 0.33), photosensitivity (34.9% vs. 15.7%, p = 0.29), and irritability (38.9% vs. 15.7%, p = 0.12) often accompanied headaches and fatigue, which was close to statistical significance (42.9% vs. 23.5%, p = 0.050). There was no difference in pain localisation. Patients dependent on mobile devices use often described pain as throbbing (56.0% vs. 25.5% p = 0.006) or taking the form of tension (12.6% vs. 1.96% p = 0.037). Detailed data are summarised in Table 2. 3.3. Phonoholism and Sleep Disturbances Individuals with phonoholism had significantly shorter mean sleep duration (7.14 h vs. 7.42 h, p = 0.0475) and were less likely to feel well rested during the day (43.33% vs. 59.73%, p = 0.0271). There was no statistically significant difference in the prevalence of daytime sleepiness, trouble falling asleep, or mean time of falling asleep. Detailed data are summarised in Table 3. 3.4. Mood and Anxiety Disorders Related to Phonoholism The group with phonoholism achieved substantially higher scores on the HADS-A anxiety scale (8.29 vs. 10.9 points, p = 0.015). A statistical significance was not proven for the component ‘depressive symptoms’ of the HADS-D (6.17 vs. 8.05 points, p = 0.1589). Detailed data are summarised in Table 4. 3.5. Phonoholism and Mobile Device Usage In the group with phonoholism, subjects declared a significantly longer time of mobile device use, which was consistent with the objective measurements of the applications installed in the subjects’ devices (3 h 57 min vs. 4 h 38 min, p = 0.0497). People with phonoholism were more likely to watch movies on mobile devices (33.9% vs. 55.0%), with no differences for other activities. Among the most frequently used apps (data collected from applications installed in the subjects’ devices), shopping applications were more common among addicts (2.0% vs. 5.2%, p = 0.012), but no significant differences were found regarding other apps. No differences were observed concerning the time of day of phone usage. Detailed data are summarised in Table 5. 4. Discussion In this study, we investigated the possible negative effect of excessive smartphone use on somatic and mental health. Regarding neurological disorders, the results of our study support the fact that excessive smartphone use increases the risk of headaches. Similar findings were presented in meta-analysis that concluded that smartphone users had an increased risk of headaches compared to non-users. Among smartphone users, the risk of headaches was also greater in those who had a longer duration of calls per day and a higher frequency of calls per day [9]. In another study, it was shown that headaches were more common in people who used smartphones frequently [12]. In addition, the duration and frequency of headache attacks were higher in people who frequently used mobile devices and they used analgesics more often to relieve their headaches [12]. In our study, we found that headaches were more frequent in the group of phonoholics, but there was no difference in their intensity. Interestingly, differences in the nature of pain were observed in this study. It was more often described as throbbing or tension in the group of non-phonoholics, and symptoms such as photosensitivity, irritability and nausea were experienced less often by phonoholics. Another study showed that headaches related to smartphone overuse showed mostly stereotyped clinical features, such as mild intensity, a dull or pressing quality, and ipsilateral location [13]. We also performed an analysis that revealed phonoholics were more likely to watch videos on smartphones than non-phonoholics, which may further influence the fact that phonoholics use smartphones for longer durations. According to current research, factors such as radiofrequency (RF) fields, noise, psychological factors or temperature changes could induce headaches related to the use of smartphones [12]. The effect of radiofrequency on the occurrence of headaches is debatable. A meta-analysis of 17 studies containing 1174 subjects found no effect of short-term exposure to RF radiation on the incidence of headaches [13]. The COSMO prospective cohort study of 24,169 subjects did not confirm the effect of long-term RF exposure on the occurrence of headaches [14]. Some studies have confirmed the effect of RF on the increased risk of headaches. Potential mechanisms by which FR could affect the incidence of pain include decreased regional cerebral cellular blood flow with increased blood flow in the prefrontal cortex, altered brain oscillatory responses, and the disruption of the energetic brain metabolism [15]. A study of 25,751 workers exposed to prolonged noise at work confirmed the strong influence of this factor on the occurrence of headaches. Noise is considered to disrupt the neurovascular system and induce abnormal muscle strain [16]. Noise can also cause headaches through its effect on the human psyche. It has indirect signalling pathways to the limbic cortex, autonomic nervous system and neuroendocrine system that are closely linked to stress response. Chronic exposure to stress may induce central sensitisation, the depletion of the pain control system, and hyperalgesia, which could contribute to more frequent headache recurrence [16,17,18]. Smartphone use may also change head posture and neck mobility, which may lead to headaches [13]. Furthermore, other headache triggers, such as anxiety, depression and sleep disturbance, should be considered. Studies have shown that phonoholics are also more likely to experience symptoms typical of depression and anxiety disorders. A study that examined student populations found that anxiety symptoms were positively correlated with problematic smartphone use [19]. Furthermore, the authors in the latter paper demonstrated that self-efficacy might mediate the relationship between anxiety disorders and PSU [20]. Nevertheless, the modulating effect of self-efficacy on the relationship between anxiety symptoms and PSU was insignificant [19]. A systematic review revealed a correlation between smartphone use and stress and anxiety and concluded that the severity of both depression and anxiety were substantially associated with excessive smartphone usage [20,21,22]. In our study, we confirmed the association of phonoholism and anxiety, but we did not obtain a statistically significant difference in the case of mood disorders; however, it should be noted that we used other clinical scales to assess these disorders. In another study, individuals that displayed excessive smartphone usage scored higher on the Beck Depression Index (BDI), the Beck Anxiety Index (BAI) scale, and the daytime dysfunction component of the Pittsburgh Sleep Quality Index (PSQI) scale in comparison with individuals in the group that used smartphones to a lesser extent [23]. The results of this study showed that excessive smartphone use can lead to depression and/or anxiety, both of which are linked to sleep problems [23]. The results of our study likewise indicate that phonoholics tended to suffer from more frequent sleep disturbance. Another study found an association between smartphone use for gaming, surfing, and texting in bed and increased insomnia symptoms [24], possibly indicating a delayed sleep phase [25]. In our study, phonoholics had a shorter mean sleep duration and experienced sleep deprivation more often than other participants. It has been hypothesised that this could be due to the magnetic field emitted by smartphones, which could negatively affect serum melatonin levels (an important factor for sleep) and cerebral blood flow, affecting the quality of sleep of phonoholics [19,26]. Addicts may remain in a constant state of anticipation of incoming phone messages, which can also result in the desynchronisation of sleep rhythms [27,28]. Furthermore, social media interactions can trigger excitement and induce mood changes, all of which have the potential to disrupt sleep [27,28,29]. However, our study did not corroborate a connection between this specific activity and phonoholism and the occurrence of sleep disorders, but it was correlated with total screen time. Among the most commonly used applications, the use of shopping apps was more prevalent in addicts than in non-addicts. Compulsive buying can be conceptualised as an addiction because it contains the same elements that behavioural addiction possesses [30]. It was observed that shopping enhanced people’s mood, which, in turn, improved their self-esteem. The elevated state experienced during shopping can be viewed as a critical motivating element for this addiction. These findings indicate that debt and financial instability were evident negative consequences of such behaviour [30]. It is worth adding that shopping addictions develop gradually, when the shopper occasionally purchases and spends money in an attempt to escape from unpleasant emotions or boredom [31,32]. Smartphone addiction develops as a long-term process similar to behavioural addiction [32,33]. Dependency often begins with a seemingly benign behaviour (shopping, Internet and/or smartphone use) that, through a variety of psychological, biophysical, and/or environmental triggers, can become harmful and evolve into an addiction [33,34,35]. The present study has some limitations that should be considered. First, this study relied on a convenience sample and the data were collected online, leading to the possibility of self-selection bias. Secondly, all participants were adults and most were young and well educated, with a large group of university students, which may prevent the generalisation of the results to the public. Longitudinal studies and multi-samples of different educational and age backgrounds are needed. The MPPUS-9 scale used in this study was recently validated for the Polish population version of the MPPUS-10 scale. This is a rapid screening tool to assess problematic use of smartphones and has shown a significant correlation with other scales used in the Polish population: MPAAQ (Mobile Phone Addiction Assessment Questionnaire) and IAT (Internet Addiction Test) [11]. However, due to the lack of a universal definition of phonoholism and differences in diagnostic criteria, there may be inconsistencies between results of different scales design to measure this phenomenon [11]. It is worth noting that the MPPUS scale was designed when smartphones were not available and smartphones have many functions that go beyond talking and writing short text messages. Some researchers have shown that smartphone addiction and Internet addiction overlap [36,37]. It is worth emphasizing that the Polish version of the MPPUS-9 scale should be considered a screening rather than a diagnostic tool and obtaining a score above the proposed threshold should be followed by further, more detailed clinical assessment. The MPPUS scale does not identify other psychopathological problems such as personality disturbances or stress levels; therefore, some of the data obtained may be a consequence of these variables rather than directly reflecting the excessive use of mobile phones [11]. It should be emphasized that the selected psychometric instruments may be inadequate to catch the full extent of neuropsychiatric and cognitive consequences of phonoholism. The full assessment of the phenomenon should be extended to include scales that take into account the aforementioned disorders, e.g., Millon Clinical Multiaxial Inventory (MCMI) [38]. Further research taking these aspects into account is needed in order to fully assess the phenomenon of phonoholism. Furthermore, studies involving brain and mind imaging and measurement performed premorbidly and post severe phonoholism are advisable. 5. Conclusions This study demonstrated that phonoholism is a potential risk factor for somatic and mental health deterioration in addicted individuals. Such a negative impact should draw the attention of the larger population and patients with problems that could potentially arise from the overuse of smartphones. Author Contributions Conceptualisation, K.A.-C., K.D., T.C. and A.G.; methodology, K.A.-C., K.D., T.C. and A.G.; software, T.C.; validation, T.C. and A.G.; formal analysis, K.A.-C., K.D., T.C. and A.G.; resources, A.G.; data curation, K.A.-C., K.D. and T.C.; writing—original draft preparation, K.A.-C. and K.D.; writing—review and editing, T.C. and A.G.; visualisation, T.C.; supervision, A.G.; project administration, K.A.-C.; translation, K.D. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement This study was conducted according to the guidelines of the Declaration of Helsinki. Ethical review and approval were waived for this study, due to the survey character of the work and data anonymisation. The Ethics Committee of the Medical University of Silesia waived the requirement to obtain ethical approval for this study. Informed Consent Statement Patient consent was waived due to the survey character of the work and data anonymisation. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no potential conflict of interest with respect to the research, authorship, and/or publication of this article. ijerph-19-05152-t001_Table 1 Table 1 Group comparison between individuals that meet the criteria for phonoholism (MPPUS-9 ≥ 53) and a group of participants that does not meet the criteria for phonoholism (MPPUS-9 < 53), regarding demographics. Mann–Whitney U test was performed for quantitative variables and Fisher’s exact test was performed for qualitative variables. Variable MPPUS-9 < 53 pt. MPPUS-9 ≥ 53 pt. p-Value Age (years) 26.5 ± 8.6 24.1 ± 3.2 0.643 Gender n (%) Woman Man 206 (69.1) 45 (73.8) 0.466 92 (30.9) 16 (26.2) Education n (%) Primary 2 (0.7) 0 (0.0) 0.425 Vocational Secondary Student Higher 1 (0.3) 1 (1.6) 25 (8.4) 3 (4.9) 205 (68.8) 46 (75.4) 66 (22.2) 10 (16.4) Residence n (%) Rural 64 (21.5) 6 (9.8) 0.402 City up to 50 thous. 69 (23.2) 18 (29.5) City up to 100 thous. 23 (7.7) 6 (9.840 City up to 250 thous. 56 (18.8) 11 (18.0) City over 250 thous. 87 (29.2) 19 (24.6) Comorbid chronic diseases 61 (20.5) 15 (24.6) 0.532 Physical activity n (%) >1 h 49 (16.4) 12 (19.7) 0.320 1–2 h 48 (16.1) 16 (26.3) 2–3 h 60 (20.1) 12 (19.7) 3–4 h 49 (16.4) 9 (14.8) 4–5 h 38 (12.8) 6 (9.8) 5–6 h 29 (9.7) 2 (3.3) <6 h 26 (8.7) 3 (4.9) ijerph-19-05152-t002_Table 2 Table 2 Group comparison between individuals that meet the criteria for phonoholism (MPPUS-9 ≥ 53) and a group of participants that does not meet the criteria for phonoholism (MPPUS-9 < 53) regarding the occurrence and characteristics of headaches. Mann–Whitney U tests were performed for quantitative variables, and Fisher’s exact tests were performed for qualitative variables. Variable MPPUS-9 < 53 pt. MPPUS-9 ≥ 53 pt. p-Value Presence of headaches n (%) 175 (58.7) 51 (83.6) 0.027 Frequency of headaches n (%) 1 x/month 31 (17.7) 9 (17.70) 0.478 2–3 x/month 76 (43.4) 18 (35.3) 4–6 x/month 37 (21.1) 16 (31.3) <6 x/month 31 (17.7) 8 (15.7) Severity of headaches (1–10) n (%) 5.06 ± 2.1 5.33 ± 1.9 0.286 Symptoms accompanying headache 98 (56.0) 32 (62.7) 0.576 Nausea 40 (22.9) 4 (7.8) 0.033 Vomiting 5 (2.9) 0 (0.0) 0.227 Photosensitivity 61 (34.9) 8 (15.7) 0.029 Sound hypersensitivity 43 (24.6) 7 (13.7) 0.147 Irritability 68 (38.9) 8 (15.7) 0.012 Visual disturbances 22 (12.6) 2 (3.9) 0.095 Whirling sensation 14 (8.0) 3 (5.9) 0.628 Fatigue 75 (42.9) 12 (23.5) 0.050 Pain localisation n (%) Frontal region 131 (74.9) 45 (73.8) 0.341 Ocular region 58 (33.1) 14 (22.95) 0.526 Parietal region 59 (33.7) 15 (24.6) 0.624 Occipital region 30 (17.1) 12 (19.6) 0.352 Mandibular region 4 (2.3) 2 (3.3) 0.528 Character of pain n (%) Stabbing 13 (7.4) 3 (5.9) 0.715 Compression 99 (56.6) 21 (41.2) 0.184 Crushing 39 (22.3) 5 (9.8) 0.076 Thunderclap 44 (25.1) 10 (19.6) 0.477 Throbbing 98 (56.0) 13 (25.5) 0.006 Tension 22 (12.6) 1 (1.96) 0.037 ijerph-19-05152-t003_Table 3 Table 3 Group comparison between individuals that meet the criteria for phonoholism (MPPUS-9 ≥ 53) and a group of participants that does not meet the criteria for phonoholism (MPPUS-9 < 53) regarding sleep disorders. Mann–Whitney U test was performed for quantitative variables and Fisher’s exact test was performed for qualitative variables. Variable MPPUS-9 < 53 pt. MPPUS-9 ≥ 53 pt. p-Value Mean sleep duration (h) 7.43 ± 1.2 7.15 ± 1.5 0.048 Mean time of falling asleep (min) 24.7 ± 28.5 24.2 ± 19.0 0.152 Feeling well rested n (%) 178 (59.7) 23 (37.7) 0.035 Daytime sleepiness n (%) 170 (57.1) 46 (75.4) 0.095 Problems falling asleep n (%) 143 (48.0) 36 (59.0) 0.274 ijerph-19-05152-t004_Table 4 Table 4 Group comparison between individuals that meet the criteria for phonoholism (MPPUS-9 ≥ 53) and a group of participants that does not meet the criteria for phonoholism (MPPUS-9 < 53) regarding HADS scale results. Mann–Whitney U test was performed for quantitative variables and Fisher’s exact test was performed for qualitative variables. MPPUS-9 < 53 pt. MPPUS-9 ≥ 53 pt. p Value HADS-A 8.3 ± 4.6 10.9 ± 4.5 0.015 HADS-D 6.2 ± 4.1 8.1 ± 4.4 0.159 ijerph-19-05152-t005_Table 5 Table 5 Group comparison between individuals that meet the criteria for phonoholism (MPPUS-9 ≥ 53) and a group of participants that does not meet the criteria for phonoholism (MPPUS-9 < 53) regarding the pattern of smartphone usage. Mann–Whitney U test was performed for quantitative variables and Fisher’s exact test was performed for qualitative variables. Variable MPPUS-9 < 53 pt. MPPUS-9 ≥ 53 pt. p-Value Duration of usage (declared) [n (%)] >1 h 19 (6.4) 0 (0.0) 0.006 1–2 h 36 (12.1) 2 (3.3) 2–3 h 63 (21.1) 6 (9.8) 3–4 h 53 (17.8) 13 (21.3) 4–5 h 47 (15.8) 17 (27.9) 5–6 h 42 (14.1) 9 (14.8) <6 h 38 (12.8) 13 (21.3) Duration of usage (measurement) (h) 3 h 57 min ± 2 h 19 min 4 h 38 min ± 2 h 1 min 0.0497 Purpose of mobile device usage (n (%)) Calls 162 (54.4) 26 (42.6) 0.242 SMS/MMS 136 (45.6) 23 (37.7) 0.389 Browser use 227 (76.1) 46 (75.4) 0.934 Social media 263 (88.3) 59 (96.7) 0.540 Work 43 (14.4) 10 (16.4) 0.723 Videos 101 (33.9) 33 (54.1) 0.020 Education 119 (39.9) 24 (39.3) 0.935 Music 194 (65.1) 36 (59.0) 0.576 Photography/filming 76 (25.5) 19 (31.2) 0.443 Games 76 (25.5) 19 (31.2) 0.443 Most used applications (n (%)) Communicators 153 (51.3) 24 (39.3) 0.218 Social media 196 (65.8) 33 (54.1) 0.290 Games 31 (10.4) 7 (11.5) 0.821 Browsers 83 (27.9) 16 (26.3) 0.816 Streaming media 91 (30.5) 16 (26.3) 0.566 Shopping 6 (2.0) 5 (8.2) 0.012 Navigation 12 (4.0) 2 (3.3) 0.784 Mail 7 (2.4) 1 (1.64) 0.733 Banking 4 (1.3) 1 (1.64) 0.860 Photos 4 (1.3) 0 (0.0) 0.365 Education 6 (2.0) 3 (4.9) 0.194 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094674 ijms-23-04674 Review The Stibium Bond or the Antimony-Centered Pnictogen Bond: The Covalently Bound Antimony Atom in Molecular Entities in Crystal Lattices as a Pnictogen Bond Donor https://orcid.org/0000-0001-8779-789X Varadwaj Arpita 1 https://orcid.org/0000-0002-7102-3133 Varadwaj Pradeep R. 12* https://orcid.org/0000-0003-1675-3835 Marques Helder M. 2 Yamashita Koichi 1 Mallamace Francesco Academic Editor 1 Department of Chemical System Engineering, School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan; varadwaj.arpita@gmail.com (A.V.); yamasita@chemsys.t.u-tokyo.ac.jp (K.Y.) 2 Molecular Sciences Institute, School of Chemistry, University of the Witwatersrand, Johannesburg 2050, South Africa; helder.marques@wits.ac.za * Correspondence: pradeep@t.okayama-u.ac.jp 23 4 2022 5 2022 23 9 467423 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/). A stibium bond, i.e., a non-covalent interaction formed by covalently or coordinately bound antimony, occurs in chemical systems when there is evidence of a net attractive interaction between the electrophilic region associated with an antimony atom and a nucleophile in another, or the same molecular entity. This is a pnictogen bond and are likely formed by the elements of the pnictogen family, Group 15, of the periodic table, and is an inter- or intra-molecular non-covalent interaction. This overview describes a set of illustrative crystal systems that were stabilized (at least partially) by means of stibium bonds, together with other non-covalent interactions (such as hydrogen bonds and halogen bonds), retrieved from either the Cambridge Structure Database (CSD) or the Inorganic Crystal Structure Database (ICSD). We demonstrate that these databases contain hundreds of crystal structures of various dimensions in which covalently or coordinately bound antimony atoms in molecular entities feature positive sites that productively interact with various Lewis bases containing O, N, F, Cl, Br, and I atoms in the same or different molecular entities, leading to the formation of stibium bonds, and hence, being partially responsible for the stability of the crystals. The geometric features, pro-molecular charge density isosurface topologies, and extrema of the molecular electrostatic potential model were collectively examined in some instances to illustrate the presence of Sb-centered pnictogen bonding in the representative crystal systems considered. pnictogen bonding antimony as pnictogen bond donor non-bonded geometry directionality crystal structure analysis ICSD and CSD database analyses MESP model description sum of the van der Waals radii concept pro-molecular charge-density based IGM-δg analysis ==== Body pmc1. Introduction Naming a chemical interaction formed by an element of the periodic table and its subsequent characterization readily enable one to identify its status and visualize what its role could be in the rational design of complex systems [1,2]. After identifying, in the last century, the possible existence of “close contacts” between atomic domains in molecules, molecular complexes and crystals, considerable efforts were made to classify, characterize, and name them [2]. One such close contact that occurs between atomic domains is widely known as the hydrogen bond; it is a non-covalent (chemical) interaction caused by a force of attraction between atomic sites of opposite polarity, following the fundamental law of electrostatics, i.e., Coulomb’s law, that states that opposite charges attract whereas like charges repel each other when in close proximity. As Arunan pointed out in an unpublished study [3], over fifty different proposals have been put forward to date on the characterization of hydrogen bonds, dating back to the time of Werner (1902) [4], Hantzsch (1910) [5] and Pfeifer (1913) [6], among many others [3]. However, a new definition of hydrogen bonds was adopted as recently as 2011 [7], listing many characteristics and indicators of such interactions that emerged from a variety of computational and experimental measurements, including IR, Raman, and NMR spectroscopic techniques, and X-ray and neutron diffraction measurements. First-principles [8,9,10,11,12] and density functional theory [13,14,15] methods have also been developed and applied to calculate the energy of hydrogen bonds in chemical systems and various spectroscopic and geometrical signatures, as well as the nature of the charge density profile associated with the surfaces of the interacting atomic domains in molecular entities responsible for these interactions. Following the definition and delineation of the characteristic features of hydrogen bonding, a similar definition, together with a set of characteristic features, was recommended for halogen bonding in 2013 [16]. This appears to have been prompted by the realization that thousands of solid-state systems were synthesized during the last decade that conceived directional intermolecular interactions driven by covalently bound elements of Group 17. There is very little difference between the definitions provided for hydrogen bonds and halogen bonds (except that the word “hydrogen” replaces “halogen” in the latter, of course); both atom types in molecular entities must feature electrophilic regions on their electrostatic surfaces and be capable of accepting some fractional charge density from an electron density donor fragment in the partner molecular species when in its close proximity. Since the definition and characteristic features of a hydrogen bond were found to be transferable to the elements of Group 17 of the periodic table, they are, in principle, transferable to other elements, for instance, those of Groups 14–16, as well. In fact, this was pointed out in an article published in 2017 that recommended a definition for and described a number of characteristic features of chalcogen bonds in chemical systems (Group 16) [17]. We believe that the same definition is also transferable to the family of pnictogen bonds formed by the pnictogen elements, i.e., Group 15. A pnictogen bond in chemical systems occurs when there is evidence of a net attractive interaction between the electrophilic region associated with a covalently or coordinately bound pnictogen atom in a molecular entity and a nucleophile in another, or the same molecular entity. It is formed by the elements of the pnictogen family, Group 15, of the periodic table, and is an inter- or intra-molecular non-covalent interaction. Clearly, when a covalently bound nitrogen atom in a molecular entity behaves as an electrophile toward a Lewis base, one would be tempted to call such an attractive engagement a nitrogen bond, in which, the nitrogen atom is a pnictogen bond donor. The same conceptual framework is transferable to covalently bound phosphorous, arsenic, antimony, bismuth and (in principle, anyway) moscovium when they display positive sites and have the ability to donate the electrophile to a Lewis base to form phosphorous, arsenic, stibium, bismuth, and moscovium bonds, respectively. This overview is focused on the possible occurrence of antimony-centered pnictogen bonds (or simply, stibium bonds) in chemical systems that have been known since the last century. In our view, it is an overlooked non-covalent interaction yet to be fully appreciated by, among others, computational and supramolecular chemists, gas-phase spectroscopists and materials scientists. This is not surprising given that the term “pnictogen bond” was coined only recently [18], and that the majority of studies of non-covalent interactions in the last and current centuries have been focused on arriving at a basic understanding of hydrogen bonding and van der Waals interactions. Legon has argued that pnictogen bonding (and other interactions) was recognized long before it was specifically named [19]. In the past and current decades, numerous studies have emerged on halogen [20,21,22,23] and chalcogen bonding [24,25,26,27,28,29,30], which are responsible for numerous crystal systems; in contrast, there have only been a small number of original research articles, reviews, and overviews that have focused on pnictogen bonding [19,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50]. For the reasons given in the following sections, we believe that supramolecular pnictogen bonds are one of the cornerstones for the development of novel functional materials [51,52,53] and occur simultaneously with other non-covalent interactions (viz. halogen bonding, tetrel bonding, and hydrogen bonding), although their importance may only be fully appreciated in the years to come. In this overview, we provide several illustrative examples of crystal structures deposited in the Inorganic Crystal Structure Database (ICSD) [54,55]) and the Cambridge Structural Database (CSD) [56] in which the identification and characterization of stibium bonds were apparently overlooked, even though they play a fundamental role in the assembly of these solid-state materials. This study is therefore expected to assist researchers in the future design of novel functional materials featuring stibium bonds. With this in mind, we attempt to highlight, using illustrative examples, the occurrence and modes of interaction of such bonds. 2. Antimony in Molecular Entities, Materials Design and Discovery Antimony, the fourth member of the pnictogen family, has played an important role in the development of phase change and optoelectronic materials [57,58,59]. In particular, chalcogenides based on germanium-antimony-tellurides (GST-PCMs), such as GaSbTe and GaGe2Sb2Te5, display outstanding properties that are a prerequisite for the development of non-volatile memory (NVM) technologies due to their high write and read speeds, reversible phase transition, high degree of scalability, low power consumption, good data retention, and multi-level storage capability [60]. Kao and workers discussed the importance of some Sb-based alloys, viz. Ga25Te8Sb67 and Ga18Te12Sb70, that have a crystallization temperature above 245 °C and activation energy of crystallization greater than 5 eV, and are useful for phase-change memory applications [61]. When combined with halides, they form inter alia various single and double perovskites which have been the focus of many studies because of their application in the development of photovoltaics and other areas of optoelectronics. A3Sb2X9 and A2AgSbX6 are a specific class of such perovskites. AaBbXa+3b are called rudorfites (A = methylammonium, formamidinium, Cs, Rb, etc.; B = Bi, Sb, etc.; X = I, Br, Cl), and several have been crystallized [59,62,63]. The quantum dots of the all-inorganic Sb-based lead-free double perovskite Cs2AgSbX6 (X = Cl, Br or I) are examples of an air stable compound that displays strong blue emission with photoluminescence quantum yields of 31.33% [64]. The mixed metal ⟨111⟩-oriented layered perovskite, Cs4CuSb2Cl12, incorporates Cu2+ and Sb3+ into layers that are three octahedra thick. The compound is photo- and thermal-stable, tolerant of humidity and behaves as a semiconductor with a direct bandgap of 1.0 eV. Its conductivity is an order of magnitude greater than that of the widely studied MAPbI3 (MA = methylammonium) perovskite [65]. Apart from the above, many crystal structures have been reported in which antimony plays a prominent role in the development of their structural stability and functionality. It appears that in many cases that covalently bound Sb can act as a pnictogen bond donor to form non-covalent interactions, a driving force for self-assembly. Our search and analysis of the structures deposited in the ICSD and CSD databases suggest that most of the inter- and intra-molecular bonding interactions emerge upon attraction between bound Sb in molecules and halides in the interacting partner entities. The intermolecular bond distances associated with them are often less than, but sometimes marginally greater than, the sum of the van der Waals (vdW) radii of the bound atomic basins. Primary and secondary non-covalent interactions (viz. hydrogen bonding and halogen bonding) are often present, and their interplay with pnictogen bonding drive the packing and hence the overall geometry of the crystal lattice. 3. Inter- or Intramolecular Bond Distance and Less Than the Sum of the van der Waals Radii Concept Our attempts in rationalizing the possible occurrence of a stibium bond hinges on a geometric criterion: whether the inter- or intramolecular distance between covalently/coordinately bound pnictogen atom Pn (viz. Pn = Sb) and a Lewis base(s) D in a crystal lattice, Pn···D (D = an electron density donor, such as O, N, a halogen anion, etc.), is less than (or even slightly greater than) the sum of the van der Waals radii of the bound atomic basins. If the first attribute is met, we recognize the Pn···D link as a likely stibium bond, consequent on the overlapping of atomic domains takes place. In the case of the other attribute, care has to be exercised, since there are numerous occasions in which the inter- or intra-molecular distance, Pn···D, is larger than the sum of the vdW radii of the non-bonded atoms that are in close proximity. In this case, we have taken into consideration crystal systems where the Pn···D distance can exceed the vdW radii sum by several tenths of an ångstrom. This is quite justifiable according to Politzer and coworkers [66], as well as others [67,68], given that the values proposed for the vdW radii of atoms have a typical uncertainty of ±0.2 Å; hence “less than the sum of the vdW radii” concept will necessarily miss a significant number of non-covalent interactions if treated as a strict criterion to identify a non-covalent interaction in molecular entities. The reason is that hard sphere models with spherical symmetry of atoms were considered in the determination of vdW radii of atoms, which differ from one study to the other depending on the approximations invoked in their determination. The underlying reason of course is that the charge density profile of atoms in molecules is anisotropic, and hence the “vdW radius” of an atom in a molecular entity is likely to vary between molecular entities. Table 1, for instance, lists the vdW radii of some selected atoms that we invoke throughout this overview, showing that the Bondi’s radius for a given atom type is different from those proposed by others. Since the specific vdW radius of an atom in different molecular entities is unknown, we use the same radius of an atomic domain to examine the “less than sum of the vdW radius concept”, regardless of the lattice systems examined. While “an interatomic distance that is greater than the sum of the respective vdW radii by even several tenths of an ångstrom may still correspond to a non-covalent interaction” [66], caution needs to be exercised to validate the interaction by simultaneously examining attributes like its directional features and the nature of the polarity of the bound atomic basins. Otherwise, such an assignment could be misleading. In our discussion below, we use the vdW radii of atoms proposed recently by Alvarez [68]. 4. Directionality of Inter-/Intra-Molecular Interactions To maximize the integrity of our identification and subsequent characterization of pnictogen bonding in the examined crystal systems, we simultaneously examined the angle of interaction between the noncovalently bound atomic basins. We did so to see whether the angle θ of approach of the electrophile, θ = ∠R–Pn···D, associated with the bound Sb atom in a molecular entity forms either a linear, a quasilinear or a bent (non-linear) interaction with the atomic domain in the partner molecular entity. At the same time, we inspected whether the interacting atomic domain D was electrophilic or nucleophilic. As such, Type-I interactions (Scheme 1a), which can be further classified as (left) Type-Ia (trans) and (right) Type-Ib (cis), appear when the regions of interacting atomic domains in molecular entities both carry either positive or negative local polarity, with θ1 = ∠R–Pn···D < 120° and θ2 = ∠R′–D···Pn < 120° for the former and 90° < θ1 < ∠R–Pn···D < 150° and 90° < θ2 < ∠R′–D···Pn < 150° for the latter interactions, where R and R′ are the remaining part of the molecular entities associated with Pn and D, respectively. These are non-linear interactions, and hence, should be regarded as non-directional. Directional interactions are linear or quasi-linear, and thus, generally follow a Type-IIa topology of bonding. Hence, when the angle of approach θ = ∠R–Pn···D = 180°, we call the interaction linear, and when it deviates from linearity such that 150° < θ < 180° (Scheme 1b, left), we refer to the interaction as quasi-linear. In either case, the electrostatic surface of covalently/coordinately bound atom Pn conceives an electrophilic region along the extension of the R–Pn covalent or coordinate bond, and D is a Lewis base (such as N in NH3, O in OH2, and F in HF). However, when 90° < θ < 150°, and Pn conceives a positive site, we recognize the interaction it forms as Type-IIb (Scheme 1b, right). Both Type-IIa and Type-IIb interactions are of coulombic origin. Type-III interactions (Scheme 1c) originate when the angle of interaction follow a Type-IIa topology of bonding, yet a portion of the interacting atomic domains are either both positive or both negative polarities. This classification scheme has been discussed elsewhere [22,49,50,72]. 5. The σ-Hole and π-Hole Concepts, and Their Relationship with Pnictogen Bonds A σ-hole is defined as a region of charge density deficiency, compared to the remainder of the bound atom, on the electrostatic surface of atom A that appears along the outer extension of the R–A covalent bond [73,74]. It can be positive, or negative, or even neutral [22,75]. For instance, a negative σ-hole can be observed on the electrostatic surface of atom F along the H–F bond extension of a hydrogen fluoride molecule [76], while a positive σ-hole can be seen on the surface of hydrogen halides HX (X = Cl, Br, I) [72,77]. The strength of the σ-hole on A is determined by the electronegativity and electron-withdrawing abilities of R, as well as the electronegativity and polarizability of A. Specifically, iodine in HI has a stronger σ-hole on its electrostatic surface compared to that of X in HX (X = F, Cl, Br) [72,78]. Similarly, the strength of the positive σ-hole on F in CN–F should be weaker than those of CN–X (X = Cl, Br, I), and the strength varies in the order CN–F < CN–Cl < CN–Br < CN–I. This trend is also true for systems with an arene moiety, for example, the strength of the positive σ-hole on F in C–F of C6F6 is weaker than those of C–X (X = Cl, Br, I) in C6X6, and varies in the order C–F < C–Cl < C–Br < C–I [72]. A σ-hole centered inter- or intra-molecular interaction involving a positive σ-hole on the pnictogen atom along the R–Pn bond extension should be referred to simply as a pnictogen bond [50]. Hypervalent atoms in molecules have more than one σ-hole. For instance, the P in phosphorous trihalides PX3 (P = F, Cl, Br, I) possesses three σ-holes, each along the extension of the X–P bond [50]. Similarly, C in CX4 (X = F, Cl, Br, I) possesses four σ-holes, each along the extension of each of the four X–C bonds [22,73,76,79]. On the other hand, an inter- or intra-molecular interaction may be regarded as a π-hole centered pnictogen bond when the pnictogen atom in molecular entities features a π-hole on its electrostatic surface and has the ability to engage attractively with a negative site in a neighboring molecule, or a site that has an electron density different to that of the π-hole, thus providing stability to the geometry of the resulting structure. A π-hole may be defined as an electron deficient region on the surface of a molecular entity; it may appear on the electrostatic surface (centroid region) of a delocalized arene moiety (e.g., C6H6, C6X6), on the surface of an atom (e.g., N in NO3−) or on the central portion of a delocalized bond in a molecular entity (e.g., C≡C and C≡N bonds in HCCH and HCN, respectively). So, analogous with the σ-hole, a π-hole can be positive or negative. A σ-hole interaction in a chemical system is generally observed to be directional, whereas a π-hole interaction is non-directional. 6. Model Systems and Computational Approaches As indicated already above, the crystal systems presented in the following sections were retrieved either from the CSD [56] or the ICSD [54,55]. We show, in some cases, that the bound antimony atom in these molecular entities has a positive site, and therefore, is capable of interacting with a negative site of a partner molecular entity. This phenomenon is either wholly or partially responsible for the overall geometric architecture and stability of the resulting crystal lattice. The characterization of the positive and negative sites on the surface of molecular entities was made possible by analyzing the electrostatic potentials. We did so by energy-minimizing the geometry of some selected isolated molecular entities in the gas phase. For this, we used the Gaussian 16 program package [80]. The Density Functional Theory at the ωB97XD [81] level and Møller–Plesset’s second-order perturbation theory (MP2) [82] were used. Depending on our interest, and for reasons discussed below, basis sets such as Aug-CC-pVTZ or def2-TZVPD were chosen. These were obtained from the basis set exchange library [83,84]. The calculation of the MESP [85] was done using the wavefunctions generated on the fully relaxed geometries of the monomeric entities. For this, AIMAll [86] and Multiwfn [87] codes were used. Geometry analysis, drawing of molecular entities/crystals, and isosurface plots were performed using the Mercury 4.0 [88]/Gaussview 5.0 [89] and VMD [90] suite of programs, respectively. The isoelectron density envelope on which to calculate the electrostatic potential is quite arbitrary [23,75,77,91,92,93] and can be computed at any contour level, such as 0.001, or 0.0015, or 0.002 a.u. (electrons bohr−3) of the total electronic density function ρ(r). The choice of a 0.001 or 0.002 a.u. envelope was suggested by Bader and co-workers [94,95] and others [96] because it was felt that such an envelope encompasses at least 95% of the electronic charge and should yield physically reasonable molecular “dimensions”. For fluorinated systems, an isodensity envelope greater than 0.001 a.u. is recommended, since this particular envelope often fails to provide insight into the correct nature of surface potential extrema [22,49,50]. The promolecular charge density based isosurfaces were calculated within the promolecular framework of Independent Gradient Model (IGM) [97,98]. We did so because we were interested in the identification and subsequent characterization of Sb-centered pnictogen bonding within or between interacting monomer entities responsible for the crystals investigated, and to cross-check the reliability of these interactions emanated using intermolecular bond distances, directionality, and MESP model descriptions. Within the framework of IGM, promolecular atomic electron densities are summed, and the associated atomic gradients do not interfere. This can be achieved by using absolute values to sum the atomic gradients and by rejecting any electron gradient contragradience feature. The resulting total gradient |∇ρIGM| is an upper limit of the true gradient, and the difference between them, δg, quantifies the net electron density gradient collapse due to interactions. Ultimately, this means that the δg descriptor identifies the presence of opposite signs in the components of the total electron density gradient |∇ρ(r)| due to interactions. IGM thus has the capacity to automatically separate intra- and inter-fragment interactions in a molecular entity, and that this can be plotted in 2D or in 3D (isosurfaces) to reveal the presence of inter- or intramolecular interactions between interacting atomic basins. The 3D shape of the isosurface volumes can be utilized to infer localized or delocalized interactions between interacting domains. The colors of these isosurface volumes, in blue and green, represent strong and weak attractions, respectively, while red represents a repulsive interaction. Hereafter, we refer to this approach as IGM-δg. 7. The Molecular Electrostatic Potential and Characterization of σ- and π-Holes in Molecular Entities The extrema of potential on the surfaces of molecular entities appear in two different flavors [27,28,29,30,99,100], i.e., the local most minimum of potential, VS,min, and the local most maximum of potential, VS,max. They may be positive, or negative, or neutral in specific regions on the surface of a molecular entity depending on the extent of electron density depletion or electron density accumulation. Lone-pair regions on the surface of a covalently bound atom, or on the surface of an anion, should feature a VS,min, since such regions have high electron densities. The positive and negative signs of VS,min or VS,max generally refer to regions that are electrophilic and nucleophilic, respectively. So an electrophilic region can be recognized when VS,min > 0 or VS,max > 0. Similarly, a nucleophilic region can be identified when VS,min < 0 or VS,max < 0. The magnitude of VS,min, or VS,max determines the strength of the potential; the larger the magnitude of VS,min, or VS,max, the stronger the nucleophilicity, or electrophilicity, of the region concerned. For instance, VS,max was observed to be positive and larger on the surface of the I than on X (X = F, Cl, Br) along the extension of the H–X and C–X covalent bonds in HX and CX4 molecules; hence the electrophilicity of covalently bound I along the H–I and C–I bond extension is the stronger when compared to that of Br, Cl, F in each of the two families of molecular entities. Since VS,max on X in these molecules appears along the extension of the H–X/C–X σ-bonds, it describes the sign and magnitude of the σ-hole on X. The concept is transferable to other covalently bound atoms; thus a positive or negative σ-hole can be found on the surfaces of a covalently bound triel, tetrel, chalcogen, pnictogen and halogen atoms, among others, depending on whether VS,max is positive or negative along the outer extension of the covalent bond. An attractive coulombic interaction between two atomic basins (intermolecular, or intramolecular) may be recognized when a region of an atom or fragment in a molecular entity with a positive VS,min (or VS,max) is in close proximity to that with a negative VS,min (or VS,max) on the same, or a neighboring, molecular entity. A σ-hole interaction between two atomic basins (intermolecular, or intramolecular) may be recognized when a positive VS,max on atom A along the R–A bond extension is in close proximity to a negative site described by a negative VS,min or VS,max. When atom A = Pn conceives a positive VS,max, the attractive engagement is a σ-hole centered pnictogen bound interaction, or simply a pnictogen bond. Similarly, a π-hole centered intermolecular or intramolecular interaction between two atomic basins may be recognized when a positive VS,min or VS,max centered on the p-orbital of atom, a bond, a delocalized ring, or on a fragment, in a molecular entity is able to attract a negative site described by a negative VS,min or VS,max on another similar, or different, molecular entity. When a positive π-hole is found on a pnictogen atom in a molecular entity, and if it is a capable for attracting a negative site on the same, or a different molecule, the resulting interaction between them is a consequence of π-centered pnictogen bonding. There are many reports of σ-hole and π-hole interactions forming the basis of the stability of numerous chemical systems. Some of them, for instance, include discussions about their similarities and differences, as well as the controversies and misconceptions surrounding this concept [51,73,101,102,103,104,105,106]. 8. Illustrative Crystal Systems As we show below, we also observed that Sb in molecular entities can cause the formation of pseudo-covalent bonds when it finds itself in close proximity to a negative site in another molecular species. It has the capability to accept electron density from lone-pairs centered on O, N, F, Cl, Br, and I in other molecules. Antimony trihalides SbX3 (X = F, Cl, Br, I) are probably the most simplest, best examples that feature the ability of Sb to form non-covalent interactions with negative sites on a neighboring molecule (vide infra). The ability of covalently bound Sb to form very strong pnictogen bonds upon its attractive engagement with halide anions has been recognized, with the energy of these interactions reaching the lower bound of covalent bonding energies [107]. It was argued that such interactions comprise significant covalent character, even though these were sometimes thought to be essentially electrostatic interactions. 8.1. Antimony Trihalides In the various examples provided in Figure 1, we mainly focus on highlighting the intermolecular bonding modes of SbX3 and a few other compounds containing Sb. As can be seen, the SbX3 molecules have a trigonal pyramidal molecular geometry. In order to understand the chemical reactivity of the various constituents of SbX3 that are responsible for the intermolecular interactions in the crystals, we focused on examining the nature of the electrophilic and nucleophilic regions on the electrostatic surfaces of isolated SbX3 molecules. We did so by exploring the MESP at the MP2(full)/def2-TZVPPD and ωB97XD/def2-TZVPPD levels of theory. Our results for the local maxima and minima of potential on the electrostatic surface of the SbX3 molecules are shown in Table 2. Figure 2a–d shows the MESP graphs for the isolated SbX3 molecules. Based on a simple Lewis model, SbX3 should be a C3v molecule with a lone pair at the apex of the pyramid. The ground state electronic configuration of Sb3+ is [Kr] 4d10 5s2. Despite the (formal) localization of the lone pair in an s orbital, the lone pair in many Sb3+ compounds is stereochemically active. For example, the gas phase structure of SbCl3 is trigonal pyramidal (approximately C3v) as determined by gas-electron diffraction with a Cl–Sb–Cl angle of 97.2(9)° [120], in agreement with the rotational constants obtained from microwave spectroscopy [121]. Salts of SbF4−, SbCl4− and Sb2F93− have large quadrupole splitting in their 121Sb Mössbauer spectra [122]. This, and the 121Sb Mössbauer data of other Sb3+ compounds (such as Sb3F10−, Sb4F13− and Sb5F194−), are consistent with a stereochemically active 5s electron pair in (using the nomenclature of VSEPR) an AX6E environment, featuring a mono-capped octahedron with the lone pair in an apical position [123]. Quoting others, it has been pointed out [124] that in the solid state Sb3+ usually has n ligands at relatively short distances on one side of the ion (hemisphere I) and m ligands on the other side (hemisphere II) at significantly longer distance, often of the same order as the sum of the vdW radii of antimony and the atom of the hemisphere II ligand with which it interacts. This is attributed to the stereochemical effect of the lone pair on Sb3+ directed towards hemisphere II. Moreover, an analysis of the Voronoi-Dirichlet (VD) polyhedra of a large number of Sb3+ compounds showed that Sb3+ (unlike compounds of Sb5+) is very often displaced from the center of gravity of its VD polyhedron, indicative of the presence of a stereochemically active lone pair [124]. There are cases in which the 5s electron pair appears to have no stereochemical influence. Thus, in (NH4)2Sb2Br12, Sb3+ is Oh and the Br–Sb–Br angles are insignificantly different from 90°, while the Sb–Br bonds are significantly lengthened [125]. This may be analogus with phosphorus(III) compounds of the type Ar2PX (Ar = 2,5-bis(trifluoromethyl)phenyl, X = Br, Cl) that feature a stereochemically inactive lone pair, with P3+ displaying an approximately octahedral geometry [126]. The electron density associated with the stereochemically active lone pair in NX3 and PX3 were previously reported from evidence of their corresponding MESP plots [49,50], but this is not apparent in the MESP of SbX3 (Figure 2). This does not mean that the lone pair is not stereochemically active; it is there, but what is evident is the gradual polarization of charge density from Sb to X as the softness of Sb compared to N [49] and P [50] increases (and its electronegativity decreases) down the group. Nevertheless, from Table 2, it can be seen that F in SbF3 is entirely negative and the σ-hole on it is completely neutralized. The trend in the stability of the σ-holes along the Sb–X bond extensions in SbX3 increases with an increase in the polarizability of X: Sb–Cl (1.6 kcal mol−1) < Sb–Br (6.5 kcal mol−1) < Sb–I (12.3 kcal mol−1) (Figure 2a–d). The lone pair regions on X in the same molecules, described by VS,min, become less negative as one passes from the lightest to the heaviest member of the halogen family. The most positive regions on the surfaces of the SbX3 molecules are identified on Sb along the three X–Sb bond extensions and that the stability of Sb’s σ-hole follows the order SbF3 > SbCl3 > SbBr3 > SbI3. The central region of the triangular face formed by the three halogens is described by a weakly positive VS,max, and is surrounded by negative potentials. These features of the electrostatic potential, elucidated by ab initio MP2(full) calculations, are very similar to those that arise from DFT-based ωB97XD calculations (cf. Table 2). The existence of the electrophilic sites on Sb and the nucleophilic sites on X in SbX3 (X = Cl, Br) explains that the attractive interactions that led to the development of the Sb···X intermolecular bonding interactions that were observed in the crystal geometries shown in Figure 1 were coulombic in nature. 8.2. Tetramethyl-Antimony Iodide Tetramethyl-antimony iodide salt [(CH3)4Sb]+[I]− is a good example of a solid state structure featuring charge-assisted pnictogen bonding in a sterically crowded environment; see Figure 3a [127]. We did not perform a MESP calculation for the system, since the polarity of the molecular domains responsible for the crystal lattice is quite apparent. The methyl hydrogen atoms of the three nearest (CH3)4Sb+ moieties of the crystal are non-covalently bound with iodide anions through charge-assisted C–H···I hydrogen bonds. Six such prominent interactions are formed with I−. They are all equivalent and the angle of attack for the formation for each of these and the corresponding intermolecular distances are ∠C–H···I = 147.4° and 3.222 Å, respectively. Apart from this, [(CH3)4Sb]I features charge-assisted Type-IIa C–Sb···I pnictogen bonds (r(Sb···I) = 4.056 and 4.352 Å) and Sb–C···I tetrel bonds (r(C···I) = 4.276 Å) that are significantly longer than the hydrogen bonds, and are directional interactions (∠C–Sb···I = 180° and ∠Sb–C···I = 180°). The long intermolecular distances are not unexpected, since the sum of the vdW radii for C and Sb (r(C)vdW = 1.77 Å and r(Sb)vdW = 2.47 Å) is larger than that of I and H (r(I)vdW = 2.04 Å and r(H)vdW = 1.20 Å). Our observation is in line with that of the authors of [127], in that the coordination around antimony is distorted tetragonal pyramidal, and the tetrahedral coordination of the ions in the structure results in the formation of a wurtzite-type structure with antimony-iodine distances of 4.06 and 4.35 Å. Although the non-covalent bonding features that occur in the crystal constitute σ-hole interactions, the involvement of the σ-holes on H and Sb in the long-range interactions cause the formation of a layer-type molecular framework in the crystal (Figure 3b). Our contention that C–H···I hydrogen bonds and C–Sb···I pnictogen bonds exist in the extended crystal is given credence by the IGM-δg based isosurface plots shown in Figure 3c, obtained at three different isovalues. The circular volume (green) in the graph on the left occurs between Sb and I atomic basins, whereas the isosurfaces that occur between the two molecular entities are illustrated in the central and right side of the graph. These features suggest possible attractive interactions between bound atomic basins. 8.3. The Co-Crystal of Antimony Trihalide and Molecular Sulfur The addition compound SbI3:3S8 crystallizes in the R3m space group [128]. The structure is stabilized by many non-covalent interactions. As noted in the study, each iodine atom of the SbI3 unit is attached to a S atom of an S8 moiety with a Sb–I···S distance of 3.60 Å and an ∠Sb–I···S angle of 169.4°. Each I-bound Sb also links with three nearest neighbor S sites of S8 crown-shaped molecules, forming Sb–I···S intermolecular contacts, with I–Sb···S = 3.391 Å and an ∠I–Sb···S angle of 152.5°. These bonding features can be inferred from Figure 4. Our calculation of the MESP of SbI3 and S8 at the ωB97XD/Aug-CC-pVTZ level of theory provides a more in-depth understanding of the bonding modes in this compound than that of the original study. The MESP graph of S8, together with all selected local most maxima and minima of potential on the electrostatic surface of the molecule, are shown in Figure 5. The molecule has eight pairs of equivalent maxima of potential (VS,max = 14.0 kcal mol−1 each) that arise along each S–S bond extension, slightly off the σ-axis; each maximum is associated with a σ-hole on S (cf. Figure 5a,b). The centroid region of the molecule features two maxima of potential, one on the top and one at the bottom surface; they are equivalent (VS,max = 5.3 kcal mol−1 each) and weaker than the σ-hole on S (Figure 5b). Each of these electrophilic regions on covalently bound S has the potential for chalcogen bonding interactions when in close proximity of a negative site. By contrast, the lateral portion of each covalently bound S atom in S8 has a negative potential (Figure 5a). These loci of negative potential toward the interior of the S8 ring are more negative (VS,min = −5.6 kcal mol−1) than those on the exterior surface of the ring (VS,min = −3.4 kcal mol−1). The authors of the original study [128] suggested the presence of intermolecular bonding between I and S sites, basing this conclusion on the intermolecular distance between I and S atoms, and within the conceptual framework of Lewis structures of chemical bonding. In particular, they observed that each iodine atom has two pairs of sulfur neighbors with I···S separation distances lying between 3.78 and 3.88 Å. The stability of the structure was attributed not only to these I···S charge transfer interactions, but also to some extent to Sb···I interactions. However, it was not clear whether these interactions are halogen bonds or chalcogen bonds in the first case, or halogen bonds or pnictogen bonds in the second case, since these bonding terminologies were not coined in 1963. With the computational tools now available, we are able to more precisely elucidate the nature of these interactions. Our analysis indicates that each I site in SbI3 is involved in three S···I interactions. Two of them are equivalent chalcogen bonds, with r(S···I(Sb)) = 3.883 Å. They are a result of attractive coulombic interaction between the lateral negative portions of bound I atoms in SbI3 and the axial positive portions of the S atom along the S–S bond extensions in S8. They are relatively far from being linear, Type-IIa (∠S–S···I(Sb) = 154.4°). The third S···I interaction is a quasi-linear Type-IIa (Sb)I···S halogen bond, since the σ-hole on I along the Sb–I bond extension is in an attractive engagement with the negative site on S in S8 (Figure 5a). Similarly, each covalently bound Sb site along the I–Sb bond extension in SbI3 is bound to the nearest negative sites localized on three S atoms of the three nearest S8 molecules, forming three equivalent Type-IIa I–Sb···I bonding interactions (r(Sb···S) = 3.391 Å and ∠I–Sb···S = 152.5° for each). These interactions have the characteristics of quasi-linear pnictogen (stibium) bonds. Other than the three predominant interactions noted above, the crystal features numerous S–S(σ)···S type interactions that are quasi-linear. The deviation from linearity is probably because the maximum of potential on the electrostatic surface of S (σ-hole) is off the S–S bond axis (Figure 5b). Nevertheless, we observed Type-IIa S–S(σ)···S interactions between the nearest S8 rings, featuring interaction distances of 3.469, 3.484, and 3.755 Å, corresponding to ∠S–S(σ)···S of 152.5, 161.9, and 169.5°, respectively. Clearly, the extensive network of Type-II noncovalent interactions, together with numerous Type-I S···S interactions between the interacting units (not shown), determine the shape of the crystal, and can be rationalized from Figure 6a,b. Our characterization of intermolecular bonding interactions in SbI3:3S8 are supported by the IGM-δg based isosurface topologies shown in Figure 6b, in which, there are clear isosurface volumes between bound atomic basins that are bonded with each other. Another adduct between an antimony halide and molecular sulfur is SbCl3.S8; see Figure 7. It crystallizes in the triclinic P-1 space group [129]. The unit-cell contains two SbCl3 and two S8 molecules, and the crystal is zero-dimensional [130]. Sb in each SbCl3 molecule links with several S sites of the crown-shaped S8 ring, as well as with the negative sites on Cl in close proximity (see dotted lines in Figure 7a). Compared to the formal Sb–Cl bond distances (r(Sb–Cl) = 2.60–2.34 Å; see Figure 7b) between Sb and Cl which are responsible for the trigonal pyramidal geometry of SbCl3, the Sb···S and Sb···Cl intermolecular interactions are much longer (r(Sb···S) in the range 3.448–4.320 Å; r(Sb···Cl) = 3.228 Å; Figure 7b). Several of them are non-linear and those appearing along the three Cl–Sb extensions are quasi-linear. All these interactions are Sb-centered pnictogen bonds. Additionally, there are Cl···S halogen bonds, and S···Cl and S···S chalcogen bonds in the crystal (not shown). The formation of these intermolecular interactions is in agreement with the electrostatic surface features of the interacting molecules revealed by the MESP model discussed above (see Figure 2b and Figure 4 for SbCl3 and S8, respectively); together they are responsible for the stability of the SbCl3.S8 system in the crystalline phase. Theoretically, the SbCl3.S8 crystal system is thermally stable with a bandgap of 2.88 eV [130], and is thus a semiconducting material. 8.4. Antimony Trihalide Crystals To validate the results of the MESP model summarized in Table 2, we examined the structure of SbF3, reported in 1970 [131]. The unit cell and 2 × 2 extended crystal structure of SbF3 are shown in Figure 8a,b. The dotted lines between the SbF3 units represent intermolecular interactions. Each Sb has three close fluorine neighbors with mean Sb–F distances 1.92 Å and each SbF3 unit is linked with three fluorine bridges (r(Sb···F) = 2.61 Å) to form a pseudo three-dimensional network, with a much-distorted octahedral co-ordination around the antimony atom. Our MESP calculations, discussed in Section 8.1. Antimony Trihalides above, indicate that the surface of Sb is strongly positive along the F–Sb bond extensions, while F is entirely negative. This suggests that there are three σ-holes along the extensions of the three F–Sb bonds. The nature of the electrostatic potential surfaces of Sb and F explains why is there a coulombic attraction between Sb in one SbF3 monomeric unit and F in a neighboring unit in the crystal, and why there are three Sb···F intermolecular interactions along the three F–Sb bond extensions in a pair of SbF3. They are also directional, with a pair of Sb···F interactions displaying an ∠F–Sb···F = 156.3° and the remaining other has ∠F–Sb···F of 162.7°. These interactions are Sb-centered σ-hole interactions and are relatively weaker than the formal Sb–F covalent bonds (bond lengths 2.61 Å versus 1.92 Å; cf. Figure 8c, bottom). However, they are quite strong pnictogen bonds, as attested to by the IGM-δg based isosurface colored bluish-green in Figure 8d. Other than these interactions, we found a pattern of a parallel arrangement between the SbF3 units along the crystallographic b-axis, in which the axes of neighboring SbF3 units are aligned (Figure 8c, top). In this arrangement, Sb in an SbF3 unit faces the center of the triangular face formed by three F atoms in another a neighboring SbF3 unit (see the first and third columns of the cluster shown in Figure 8b). These are relatively weak and non-linear Type-Ib pnictogen bound interactions, with r(Sb···F) between 3.60 and 3.80 Å and ∠F–Sb···F in the range 131.8–136.7°. They are also observable in the IGM-δg based isosurface plot shown in Figure 8d,e. The extensive network of pnictogen bonding not only drives the formation of the pseudo 3D framework of the crystalline form of SbF3, but also the development of second-order nonlinear optical (NLO) properties [132,133]. In fact, the SbF3 system exhibits a powder second harmonic generation (SHG) which is about 5.8 times that of potassium dihydrogen phosphate (KDP), and is an NLO material in the infrared region. This allows excellent transparency in the range of 0.29–12 μm with high thermal stability. The band gap of the material calculated from the UV–vis–near-infrared spectrum was about 4.3 eV [132]. The 2 × 2 extended cementite crystal structures of SbX3 (X = Cl, Br) are shown in Figure 9a–c. The unit-cell for each contains four molecular formula units SbX3 crystallized in an orthorhombic space group–as SbI3, vide supra–SbCl3 in Pnma [134] and Pbnm [135]; SbBr3 in Pbnm [136]. There are two equivalent Br sites in the structures, forming a shorter and two longer, equivalent, Sb–X bond distances. The structures are zero-dimensional and Sb3+ is bound in a distorted T-shaped geometry to three halogen atoms [137,138]. Kang et al. [133] have demonstrated that SbX3 (X = Cl, Br) are good mid-IR NLO crystals materials. The DFT+U calculated bandgaps were calculated to be 3.751 and 3.119 eV for SbCl3 [138] and SbBr3 [137], respectively, suggesting that they are wide band gap semiconductors. Our geometric analysis of the structure shown in Figure 9b indicates that Sb in SbCl3 is linked to nine Cl neighbors in five surrounding SbCl3 molecules. Three of them are formal Sb–Cl bonds expected of the SbCl3 molecule. The remaining six are intermolecular Sb···Cl contacts, with bond distances between 3.447 and 4.169 Å. Each of them is less than the sum of the vdW radii of Cl and Sb, 4.29 Å (rvdW(Sb) = 2.47 and rvdW(Cl) = 1.82 Å), and are all formed between the positive surface on Sb along the Cl–Sb bond extensions in one molecule of SbCl3 and the negative lateral portions of the Cl atom around the Sb–Cl bonds a neighboring molecule(s). Of the six, the three Sb···Cl contacts developed along the three Cl–Sb bond extensions are directional; a pair of bonds with ∠Cl–Sb···Cl = 165.4° are associated with the bond distances of 3.447 Å, and the third one, that has the longest bond distance of 4.169 Å, is associated with an ∠Cl–Sb···Cl of 154.4°. The remaining three Sb···Cl interacts are non-linear (∠Cl–Sb···Cl = 137.9°, 126.2°, and 132.7°). A very similar topology of pnictogen bonding interactions is revealed for the same system crystallized in the space group Pnma [134], although the Sb···Cl bond lengths and ∠Cl–Sb···Cl bond angles differ slightly (Figure 9a). Because SbBr3 crystallizes in the same space group, i.e., Pbnm [136], the local bonding environment around the Sb ion in SbBr3 is very similar to that in SbCl3. For instance, we also observed a total of nine Br neighbors around the Sb ion in SbBr3; six of them are Sb···Br intermolecular interactions (Figure 9i). Of these six, the three appearing along the Br–Sb bonds are quasi-linear Type IIa interactions and the remaining three, emanating off the Br–Sb σ-bonds, are non-linear. In particular, a pair have ∠Br–Sb···Br = 165.3° and a bond distance of 3.663 Å. The third has the longest bond distance of 4.354 Å with an ∠Br–Sb···Br = 155.8°. The remaining three non-linear interactions are associated with ∠Br–Sb···Br of 125.4, 137.1 and 133.4°. We attribute all the quasi- and non-linear Sb···Cl and Sb···Br interactions in the respective crystals of SbCl3 and SbBr3 to intermolecular pnictogen bonds that follow either a Type-II or a Type-I bonding topology. There are extensive Type-I and Type-II Sb–X···X and Sb–X···X–Sb (X = Cl, Br) halogen bound contacts in each of the three crystals discussed above. They are shown in Figure 9d, Figure 9e and Figure 9f for SbCl3 (Pnma), SbCl3 (Pbnm) and SbBr3 (Pbnm), respectively. The Type-I Cl···Cl contacts in SbCl3 that occur between the zig-zag sheets are shorter than those within the sheet itself, and hence responsible for the sheet’s development (viz. 3.579 Å versus 3.630 Å in Figure 9d; viz. 3.544 Å versus 3.626 Å in Figure 9e). The opposite trend is seen in SbBr3. The analogous Type-I Br···Br contacts are 3.821 Å and 3.758 Å (Figure 9f). The Type-II Sb–X···X contacts in all three crystals are within the zigzag chains; the distances are 3.656, 3.611 and 3.736 Å in SbCl3 (Pnma), SbCl3 (Pbnm) and SbBr3 (Pbnm), respectively. The local pattern of pnictogen and halogen bonding interactions are shown in Figure 9g–i. Clearly, the combination of a 3D network of Type-I and Type-II halogen and pnictogen bonding interactions do not leave the SbCl3 molecules in the crystal as zero-dimensional. By contrast, the SbI3 system crystallizes in two space groups, i.e., monoclinic (P21/c) and trigonal (R-3¯), and is non-magnetic [139]. The crystal structure of the latter, depicted in Figure 10, shows that it adopts a layered geometry, and that the neighboring layers are linked to each other through a number of Type-IIa halogen-centered I···I interactions (r(I···I) = 3.958; ∠Sb–I···I = 164.5°) that are less than twice the vdW radius of I, 4.08 Å. However, in the monoclinic crystal, the isolated SbI3 molecules are linked with each other by means of a 3D network of I–Sb···I intermolecular contacts. Both the monoclinic and trigonal structures of SbI3 possess wide band gap transition energies [140] (2.217 eV for the monoclinic geometry and 2.211 eV for the trigonal geometry), indicative that they are semiconducting materials. Kang et al. have theoretically determined that SbI3 has a strong second harmonic generation effect [133]. Onodera and coworkers have experimentally demonstrated that SbI3 is a promising material for use in radiation detectors; it is stable under operating conditions, similar to popular semiconductor detectors CdTe and TlBr [140]. The IGM-δg results given in Figure 11 confirm the intermolecular pnictogen bonding interactions that were identified between the interacting molecules in SbX3 (X = Cl, Br, I) crystals. As discussed above, we observed that there were circular or dumbbell-shaped green isosurfaces between the Sb and X atomic basins in SbX3 (X = Cl, Br). In addition, we also identified a number of potential Type-I and Type-II Sb–X···X halogen bound interactions between the SbX3 molecules in the crystal, as marked in Figure 11a,b for SbCl3 and SbBr3, respectively. In both cases, the pnictogen bonding was stronger than the Type-I and Type-II halogen bonds, as inferred from the size and thickness of the IGM-δg based isosurfaces. The presence of Type-I and -II halogen bonding interactions between the interacting molecules was not obvious in the unit cell of the SbI3 crystal. Their presence was rationalized when the unit-cell was expanded. The IGM-δg based isosurface analysis performed on a small portion of the expanded structure of the SbI3 crystal is shown in Figure 11c (right), including both Type-I and Type-II I···I halogen bonds in the SbI3 crystal. 8.5. The Crystal Structures of [(CH3)3Sb–Sb(CH3)2]2[(CH3SbBr3)2], (CH3)2Sb)2O and (CH3)2Sb)2S A structure that features prominent charge-assisted Sb···Br contacts, the ionic complex [(CH3)3Sb–Sb(CH3)2]2[(CH3SbBr3)2], is shown in Figure 12a [141]. Each Br site in [(CH3SbBr3)2]2– is coupled with one, two or three Sb sites of surrounding [(CH3)3Sb–Sb(CH3)2]+, so forming directional interactions along the C–Sb extensions; see Figure 12b. This means that the Sb site along the Sb–(CH3)2 bond extensions in [(CH3)3Sb–Sb(CH3)2]+, form three directional Type-IIa interactions, with Sb···Br bond distances ((H3)C–Sb···Br bond angles) of 3.732 (160.5°), 3.549 (170.9°) and 3.830 Å (154.8°). Similarly, the Sb site along the (H3C)3–Sb bond extensions in the same cation forms three C–Sb···Br intermolecular interactions, with (C)Sb···Br distances of 3.912, 3.842, and 4.452 Å, corresponding to ∠C–Sb···Br of 174.5°, 175.5°, and 154.7°, respectively. There are many H···H and H···Br hydrogen bonding interactions in the crystal, with intermolecular bond distances around 2.374 and 2.990 Å, respectively. These are attractive interactions, and each is less than the sum of the van der Waals radii of the respective atomic basins. For instance, the H···H bond distance between the methyl groups is 2.374 Å, which is less than the sum of the vdW radii of two hydrogen atoms, 2.40 Å (rvdW (H) = 1.20 Å). Similarly, the H···Br distance of 2.990 Å is less than sum of the vdW radii of H and Br atoms, 3.06 Å (rvdW (H) = 1.20 Å and rvdW (Br) = 1.86 Å). Bis(dimethylstibanyl)oxane, ((CH3)2Sb)2O, is an example of an organo-element species that also features pnictogen bonding [142]. As shown in Figure 13a,b, one of the covalently bound terminal Sb sites in ((CH3)2Sb)2O serves as a bifurcated center for donating two pnictogen bonds to a neighboring molecule. The (H3)C–Sb···Sb interactions are long and directional: r(Sb···Sb) 4.478 Å and ∠(H3)C–Sb···Sb = 160.4°. The Sb···Sb interactions are surely characteristics of Type-IIa pnictogen boding; the intermolecular distances are roughly about 10% smaller than the sum of the vdW radius, 4.94 Å, of the two Sb atoms (rvdW(Sb) = 2.47 Å). They are also markedly longer than the Sb···O pnictogen bond distance between a pair of ((CH3)2Sb)2O entities (r(Sb···O) = 2.586 Å and ∠O–Sb···O = 173.5°). The Sb···O distances are longer than the Sb–O covalent bond distances (2.009 Å). These interactions suggest that Sb in crystalline ((CH3)2Sb)2O is either tetragonal or pentagonal. The authors of [142] suggested that ((CH3)2Sb)2O adopts a syn-anti conformation in the solid state with the entities arranged in zigzag chains along because of weak intermolecular Sb···O interactions. We suggest that that these interactions are actually reasonably strong, featuring a significant degree of covalency and may be best described as coordinate bonds. A similar proposition, i.e., that halogen bonds have a significant degree of covalency and are best described as analogous to coordinate bonds rather than analogous to hydrogen bonds, has been advanced [143]. We base our suggestion on the observation that there is a significant accumulation of charge density in the bonding region between the Sb and O atomic basins of a pair of interacting molecules (Figure 13c, right), indicated by blue isosurfaces. This was not so for the Sb···Sb interactions molecules (Figure 13c, left), as the isosurfaces corresponding to these were green, a signature of weakly bound interactions. Since the Sb–O bond distance in ((CH3)2Sb)2O is 2.009 Å, the mutual penetration between the vdW spheres of Sb and O in within a ((CH3)2Sb)2O entity should be larger than the penetration of these domains with those on neighboring entities. The Sb–O bond is, therefore, a covalent-like bond with some significant ionic characteristics (roughly 38%), which is not unexpected for coordinate bonds [144,145]. Because of its high electronegativity, O in ((CH3)2Sb)2O pulls significant electron density towards the O–Sb bonding region, leaving behind a significantly strong positive region (σ-hole) on the surface of the Sb atom along the outermost extension of the O–Sb bond. This σ-hole is responsible for formation of a strong O–Sb···O–Sb pnictogen bonding interaction in the crystal; see Figure 13a. The formation of this interaction is the result of two sites of opposite polarity (positive σ-hole on Sb in one molecule and negative lone-pair region on O in the neighboring molecule). In addition, there are many O···H and Sb···H interactions between ((CH3)2Sb)2O units in the crystal (not shown), with bond distances (angles) of 2.80–2.90 Å (∠O···H–C = 89 – 100°) and 3.195 Å (∠Sb···H–C = 115°), respectively. This may be inferred from the IGM-δg isosurface plots shown in Figure 13c. The crystal structure of the sulfane analog ((CH3)2Sb)2S is also reported (Figure 14a) [142]. The molecules are in an approximately syn-syn conformation in the crystal structure. The Sb–S bond length is 2.449 Å, which is significantly smaller than the Sb···S intermolecular distances of 3.164 Å (Figure 14b), due to a pair of interactions that developed when three units of the ((CH3)2Sb)2S came in close proximity in the crystal lattice. Both the Sb···S intermolecular contacts appear along the S–Sb bond extensions with ∠S–Sb···S is = 176.8°, revealing the presence of antimony-centered Type-IIa σ-hole interactions. These directional interactions in the crystal are evident in the IGM-δg based bluish-green isosurfaces shown in Figure 14c (right). In addition, there are Sb···Sb long-ranged stibium bonds in the crystal, with r(Sb···Sb) = 4.208 Å and ∠S–Sb···Sb =134.8°. These are Type-Ib pnictogen bonds, and show up in the IGM-δg based green isosurfaces shown in Figure 14c (left). There are many H···S hydrogen bonds in the extended crystal lattice (not shown). 8.6. The Crystal Structure of Catena-(tris(μ2-1,4-dioxane-O,O’)-bis(trichloro-antimony(III)) In the organic–inorganic hybrid complex formed between SbCl3 and 1,4-dioxane, the Sb3+ ion is in a pseudo-octahedral environment, coordinated to three chloride ligands and interacting with the lone-pair electrons on three O-sites in three surrounding 1,4-dioxane moieties [146,147]. The space-filling and ball-and-stick models of the compound are shown in Figure 15a,b. The first shows that there is an overlapping of Sb and O sites in the crystal, causing the formation of three equivalent Cl–Sb···O interactions (Figure 15c). The Sb···O distance, r(Sb···O), is 2.755 Å and the angle of interaction, ∠Cl–Sb···O, is 177.2°. These Type-IIa stibium bonds are markedly longer than the three formal Sb–Cl coordinate bonds (2.379 Å) of SbCl3. The Sb···O interactions can be viewed as the result of attraction between the regions of positive potential along the Cl–Sb bond extensions and the negative potential on the surface of O atoms in 1,4-dioxane. One may also expect that they have some characters expected of coordinate bonds, and are largely coulombic interactions. In addition, there are also Cl···Cl halogen bonds and H···O and H···Cl hydrogen bonds between the interacting molecules in the crystal. The first developed between the Cl sites on the Sb–Cl bond extensions, with r(Cl···Cl) bond distances of 3.912 Å and angle of interaction, ∠Sb–Cl···Cl, of 172.85°. Although these interactions are directional and have a Type-IIa topology of bonding, they are not actually Type-IIa interactions (∠Sb–Cl···Cl = 172.85°; and ∠Cl–Cl···Cl = 172.85°), since the Sb–Cl···Cl–Sb interactions are formed between regions of nearly identical electrostatic potentials centered on the interacting Cl atoms. They may therefore be best characterized as Type-III halogen bound interactions [22]. On the other hand, the C–H···Cl hydrogen bonds are formed between the negative sites on the Cl atoms bonds around the Sb–Cl bonds and the nearest H sites on 1,4-dioxane, with r(H···Cl) varies in the range 2.9–3.3 Å. Each Cl site in SbCl3 serves as an acceptor of six H···Cl hydrogen bonds, with bond distances of 2.928, 3.023, 3.106, 3.145, 3.148 and 3.198 Å. The C–H···O hydrogen bonds in the crystal are formed between the 1,4-dioxane moieties, the majority of them with a bond distance of 3.315 Å and an interaction angle of 161.1°. There are four such bonds between a pair of two 1,4-dioxane molecules, locally forming a sandwich type 1,4-dioxane dimer (Figure 15d). Most of the hydrogen bonds are weak, and they originate from attraction between the positive site on H and the negative site(s) on Cl or O, making a local contribution to the overall stability of the crystal. 8.7. The Crystal Structure of [Co(trien)(NSC)2][Sb2(tart)(Htart)] Kushi and co-workers [148] reported the structure of the diastereomeric salt formed between trans-[Co(trien)(NSC)2]+ (trien = triethylenetetramine) and [Sb2(tart)(Htart)]– (tart = tartrate, C4H2O62–). It features each Sb3+ ion coordinated to four O atoms of tartrate in a distorted seesaw coordinated environment. Sb is engaged in an attractive engagement with a π-cloud around the C=N bond of the coordinated isothiocyanato anion (Figure 16a,b). The N=C and C=S bonds in the metal coordinate SCN– anion form two interactions with an Sb3+ ion of the cation, Sb(σ)···π(SCN). These are probably weak, charge assisted interactions, corresponding to r(Sb···π(midpoint of N=C)) = 3.437 Å and r(Sb···π(midpoint of C=S) = 3.607 Å). The sum of the vdW radii of Sb and S atomic basins is 4.36 Å, considerably longer than the distance between Sb and S (3.929 Å; see Figure 16b). The interaction is also directional, yet Type-IIa as ∠O–Sb···S = 158.5°. This contact between Sb and S in the crystal is not a pnictogen bond, but rather, the result of charge assisted π-hole centered tetrel bonding, since trans-[Co(trien)(NSC)2]+ carries a formal charge of +1. Similarly, Sb···π(midpoint of N=C) is a π-hole centered tetrel bond, yet Sb is closer to C than to N. These two interactions, together with the four Sb–O bonds to tartrate, make the coordination environment of Sb3+ pseudo-octahedral in this salt (Figure 16b). Apparently, the packing in the crystal is not only driven by chalcogen and tetrel bonding interactions, but also by several other non-covalent interactions formed between the interacting species (not shown). This example implies that interactions that appear to be the result of pnictogen bonding may actually correspond to something else if assigned correctly. 8.8. The Crystal of [SbCl2imR2R’2][OTf] Henne et al. reported a series of pnictogen complexes featuring a Pn–C bond in the C2 position of a sterically hindered imidazole (imR2R’2 = 1,3-dipropyl-2,5-dimethyl imidazole) [149]. One of these, [SbCl2imR2R’2][OTf] (OTf = triflate), is shown in Figure 17a. As discussed above for other systems, the solid-state structure arises from several charge-assisted intermolecular interactions, as Sb is entirely positive. The three Sb···O contacts shown in Figure 17b are a result of coulombic attraction between it and the entirely negative O sites on two neighboring OTf anions. Two of these interactions are significantly longer than the other one (2.592, 3.046 and 3.292 Å), with corresponding ∠C–Sb···O angles of 166.6°, 153.8°, and 148.6°, respectively. The shorter of these interactions has a comparable bond length to the two Sb–Cl bonds (2.402 and 2.375 Å); one may recognize this as having the significant character of any coordinate bond. The other two display characteristics of Type-II non-linear pnictogen bonds. We also identified a long Sb···Cl bond between neighboring cations with r(Sb···Cl) = 4.123 Å and an ∠Cl–Sb···Cl = 129.4° (Type-IIb). This is also a weak, non-linear pnictogen bond, given that it is marginally shorter than the sum of the vdW radii of the Sb and Cl atomic basins, 4.29 Å. The Sb center in [SbCl2imR2R’2]+ is therefore pseudo seven coordinate. 8.9. The Crystal Structures of Phosphoryl Isothiocyanate Phosphoryl isothiocyanate, OP(NCS)3 can form many types of crystal structures [150]. An example is [SbCl3·OP(NCS)3]4, which crystallizes in the cubic space group I4¯3m, shown in Figure 18a [150]. The three chloride ligands of SbCl3 are arranged in a primarily trigonal pyramidal geometry around Sb3+, which also interacts with three O sites of three neighboring OP(NCS)3 units. As shown in Figure 18b, there are three links between the Sb center in SbCl3 and the three O sites of OP(NCS)3 moieties. These are a result of coulombic attractions between the positive potential on Sb and the negative potential associated with the lone-pair electrons on O. They are all equivalent and are much longer (3.060 Å) than the formal Sb–Cl bonds (2.341 Å). Because the Sb center interacts with six atomic basins, this creates a pseudo-octahedral around it. Therefore, the complex system exhibits a tetranuclear “cage” structure with an [Sb4O4] core, in which four corners of the core form a regular cube of edge length 3.060 Å that are occupied by four Sb3+ ions and the remaining four are occupied by O sites. The [Sb4O4] core consists of μ3-bridging oxygen and six coordinated Sb3+ ion such that each O in OP(NCS)3 acts as a trifurcated center to accept electrophilic attacks. All four lone pairs of the four Sb atoms suggested in ref. [150] are located in the tetranuclear closed “cage” structure of the [Sb4O4] core. Because the Sb···O intermolecular interactions are substantially longer than the Sb–Cl bonds, and appear along the Cl–Sb extensions (∠Cl–Sb···O = 179.3°), we characterize them as Type-IIa stibium bonds. Our further analysis suggested that Cl, along the Sb–Cl bond extension, also engages attractively with the S atom in OP(NCS)3. Each SbCl3 unit in the crystal donates three chlorine-centered σ-holes to three S, forming three equivalent Cl···S halogen bonds (r(Cl···S) = 3.613 Å and ∠Sb–Cl···S = 166.7°). These halogen-centered σ-hole interactions leads to the emergence of macrocyclic cage-like pseudo 3D structures as shown in Figure 18c. The antimony atoms form a distorted tetrahedron with an Sb···Sb edge of 4.186(1) Å, which is much less than the sum of the vdW radii of two Sb atoms (4.94 Å). Because of this, a weak specific interaction between Sb ions was postulated [150]. Other than this, we also expect that the crystal should contain weak (CN)π···Cl interactions. These postulated intermolecular interactions that are responsible for the stability of the [SbCl3·OP(NCS)3]4 crystal are elucidated by our IGM-δg analysis. The results are summarized in Figure 18d for a small portion of the crystal, consisting of three SbCl3 units and three OP(NCS)3 units. The IGM-δg results show that the Sb···Sb pnictogen bonds are very weak, and appear as a thin flat isosurface colored green. The Cl···S interaction is a localized interaction and the isosurface volume between Cl and S is tiny. By contrast, the isosurface volumes between the Sb and O atomic basins are thick and circular, and bluish-green, which indicate strongly bound stibium bonds. Similar pnictogen bonding topologies were found in a crystal of 1,3,5-Trithiane antimony tribromide, SbX3·(CH2S)3 (X = Cl, Br) [151]. The packing between SbX3 and (CH2S)3 is illustrated in Figure 19a,b for SbCl3·(CH2S)3 and SbBr3·(CH2S)3, respectively. The H atom positions are not provided in the CSD deposition, and thus, are missing in Figure 19. The intermolecular interactions between the interacting units in the crystal are shown in Figure 19c,d, respectively. Because of the absence of H atom positions in CH2S in the crystal, the probable role of H cannot be determined. H is expected to play a role in the packing by the formation of several non-covalent interactions. One such prominent interaction in SbBr3·(CH2S)3 could be the (HC)H···Br/(C)H···Br hydrogen bonds, for example. As found in other structures, see above, the Sb center in SbX3·(CH2S)3 (X = Cl, Br) is pseudo-octahedral. In SbCl3·(CH2S)3, the Sb–Cl distances are 2.374 Å, and the Sb···S distances are much longer, i.e., 3.257 Å. Similarly, in SbBr3·(CH2S)3, the Sb–Br distances are 2.534 Å, while the Sb···S distances are, 3.365 Å. The presence of the exceptionally Sb···S long bonds signifies that they are not coordinate bonds, but Type-IIa stibium bonds, and that the SbX3 units are locally trigonal pyramidal. We note further that there are many S···Cl and S···Br chalcogen bonds in the crystal, and each S site is involved in μ3-bridges; two of them are equivalent S···X chalcogen bonds (r(S···Cl)/r(S···Br) = 3.432/3.476 Å; ∠C–S···Cl/∠C–S···Br = 169.3°/170.5°) and the other is the Sb···S pnictogen bond (see above). The chalcogen bonds arise from the two σ-holes on S along the C–S bond extensions (not shown). 8.10. The Crystal Structure of (CN4H7)SbC2O4F2(H2O)0.5 Chen and co-workers reported an organic–inorganic hybrid birefringent material, i.e., (CN4H7)SbC2O4F2(H2O)0.5, comprising π-conjugated organic groups [CN4H7]+ and linear chains of [SbF2]+ units bridged by oxalate anions, [SbF2(C2O4)]−n, with amino-guanidinium cations intercalated between the chains (Figure 20a) [152]. The compound exhibits a large birefringence (Δn = 0.126 @ 546 nm) that is almost equal to that of the well-known birefringent material, α-BaB2O4. Sb is bound to four O and two F donors, forming a distorted pentagonal pyramidal structure. There is therefore significant space around the coordination sphere of Sb, opposite the F–Sb bonds, for which the Sb center is able to accommodate interactions with negative sites, just as we observed. The positive site on Sb is involved in F–Sb···O (oxalate) and F–Sb···F pnictogen bonding interactions (Figure 20b) with bond distances of 3.612 and 3.158 Å, and with corresponding angles of interactions of 171.5° and 141.3°, respectively. These intermolecular distances are less than the sum of the vdW radii of the respective bound atomic basins, and the intermolecular interactions are directional. Each chain formed by the repetition of the [SbF2C2O4]– units is linked to a neighboring chain by F–Sb···O (oxalate) and F–Sb···F pnictogen bound interactions (Figure 20b). The π-conjugated [CN4H7]+ and the H2O moieties act as spacers between the SbC2O4F2 chains. They are linked to each other through N–H···O (oxalate), N–H···F(Sb), (H2O)H···O(oxalate), (H2O)H···F(Sb), –NH···O(H2O) and N–N···O contacts (not shown). While the first five are genuine hydrogen bonds, the last are potentially charge-assisted pnictogen bonds. Because r(N···O) distances occur in the 2.982–3.200 Å range and ∠N–N···O = 84.6° and 140°, these can be regarded as Type-I pnictogen bound contacts not shown. Apart from these interactions, H2O molecules are linked with the Sb sites through Sb···O pnictogen bonds (r(Sb···O) = 3.082 Å and ∠F–Sb···O = 148.6°). 8.11. Stibium Bonds Formed with Arene Moieties and Other Cyclic and Non-Cyclic Systems Covalently bound Sb can form pnictogen bonds with π-density rich regions. For example, Bombieri and co-workers [153] reported such a case, i.e., the 2:1 complex between SbBr3 and pyrene (Figure 21a). The figure illustrates the prominence of pnictogen bonds between interacting SbBr3 units, as well as between SbBr3 and pyrene. Sb3+ in each SbBr3 unit simultaneously forms three Br–Sb···Br pnictogen bonds with the Br sites in neighboring SbBr3 units, which act as pnictogen bond acceptors. At the same time, the Sb forms a pnictogen bond with the π-density on the aromatic rings of pyrene which also act as pnictogen bond acceptors. Most of the Br–Sb···Br and Br–Sb···π(C) interactions are directional, with different ∠Br–Sb···Br values of between 170° and 175° (Figure 21c), and ∠Br–Sb···π(C6) = 157.8° (Figure 21d). The lateral negative sides around Br in SbBr3 are also involved in an extensive number of C–H···Br hydrogen bonds. There are many such intermolecular non-covalent interactions between SbBr3 and pyrene, with Br···H distances varying between 2.85 and 3.20 Å. They display a Type-IIa directional feature, with the angle of interaction, ∠C–H···Br in the 150.0–170.0° range, as shown in Figure 21b. There are also Type-I hydrogen bonds; they are longer, with r(H···Br) ~ 3.0–3.3 Å, and ∠C–H···Br in the 90.0–150° range. The crystal also features a significant number of Sb–Br···Br(Sb) contacts between the SbBr3 units, between 3.60 and 3.90 Å in length. The bond distances for Type-I Sb–Br···Br(Sb) contacts occurring between the SbBr3 units are close to 3.89 Å, with bond angles lying between 90° and 120° (Figure 21c). The ability of Br in SbBr3 to engage in non-covalent interactions is remarkable. It is involved either in (i) two Type-I and one Type-II Br···Br halogen bound interactions (∠Sb–Br···Br = 160.3°); or (ii) in three Type-I and one Type-II Br···Br contacts; or (iii) in one hydrogen bond, one pnictogen bond, one Type-II and two Type-I Br···Br contacts; (iv) or in a set of one Sb–Br···Br pnictogen bond and two Br···H hydrogen bond(s); (v) or in a set of two halogen bonds, one pnictogen bond, and one hydrogen bond; (vi) or in three halogen bonds and one hydrogen bond; (vi) or in a set of four halogen bonds and one hydrogen bond; (vii) or in a set of one pnictogen bond, two hydrogen bonds, and one Br···π(pyrene ring) interactions. In addition, there are also slipped-parallel π···π staking interactions between the aromatic rings of pyrene. This complicated bonding topology emerges from the variable orientation of the SbBr3 molecule in the crystal, which plays a crucial role in packing with the pyrene entity. While all types bonding interactions responsible for the crystal are not explicitly discussed, in Figure 21e,f, we present the IGM-δg based isosurface results calculated between three SbBr3 units, and those between SbBr3 and pyrene, the geometries of which were extracted from the crystal. As discussed above, our IGM-δg analysis provides evidence of Type-I and Type-II halogen bonding between the SbBr3 units—described by circular thin green volumes (Figure 21e); Sb···Br pnictogen bonds—described by bluish-green circular or dumbbell-shaped volumes (Figure 21e); and Sb···π pnictogen bonds—described by a cone-like volume (Figure 21f). A few systems dominated by Sb···π pnictogen bonds are included in Figure 1, including, as examples, (C24H24)(SbCl3)2 (C24H24 = [2.2.2]paracyclophane [110] (Figure 1c); biphenyl bis(antimony trichloride) [111] (Figure 1d); (benzene)(SbCl3)2 [115] (Figure 1h); pyrene bis(trichloro-antimony) (Figure 1i) [116]; [2.2.2.2]-paracyclophane tribromo-antimony (Figure 1j) [117]; trichloro-antimony toluene (Figure 1k) [118]; and tetrakis(trichloro-antimony) 1,2-diphenylethyne (Figure 1l) [119]. In all cases, the intermolecular distances are less than 3.5 Å, and not unexpected for π-centered intermolecular interactions. In any case, Karlee et al. reported tricyclohexylphosphine sulfide antimony trihalide crystals with generic formulae (Cy3PO)SbX3 (X = F, Cl, or Br), (Cy3PO)2SbX3 (X = F, Cl, or Br), and (Cy3PS)SbX3 (X = Cl, Br, or I) [154]. (Cy3PO)SbX3 (X = F, Cl) crystallizes as dimers through symmetry-related intermolecular Sb···X interactions. A similar type of dimeric structure was observed for (Cy3PS)SbX3 (X = Cl, Br). By contrast, the solid-state structure of (Cy3PO)2SbCl3 was consistent with the structures of bis-phosphine oxide complexes of Sb3+ that have a square pyramidal Sb center and cis-configured OPCy3 ligands. The crystal structures of (Cy3PS)SbBr3, (Cy3PS)SbCl3, and (Cy3PS)SbI3 are shown in Figure 22a, Figure 22b and Figure 22c, respectively. In all these phosphine chalcogenide complexes, the Sb–X bond distances are significantly distorted from what is expected of a trigonal pyramidal SbX3 molecular entity. The three Sb–X bonds of SbX3 in its complex with Cy3PS are not equivalent, and each of them is significantly shorter than the Sb–S bond. The Sb···X bonds responsible for the (Cy3PS)SbX3 (X = Cl, Br, I) dimers are significantly longer than ordinary coordinate bonds, and are directional. They are inequivalent in (Cy3PS)SbBr3 (3.335 and 3.324 Å) and (Cy3PS)SbCl3 (3.290 and 3.284 Å), but equivalent in (Cy3PS)SbI3 (3.437 Å). The Sb···X interactions are quasi-linear (∠X–Sb···X (X = Cl, Br, I) between 171.6° and 173.6°), indicating that directionality plays a role in stabilizing these interactions. A very similar coordination environment around the Sb cation is also found in (Cy3PO)SbCl3, as shown in Figure 22d. In this case, the inequivalent Sb···Cl bond distances are 3.132 and 3.248 Å with corresponding ∠Cl–Sb···Cl values of 173.7° and 179.0°, respectively. Other than X–Sb···X pnictogen bonding, the H-sites of the Cy moieties are linked with the nearest X sites of the coordinated SbX3, forming a number of weak H···Br hydrogen bonds, with bond distance in the range, 3.00–3.50 Å (not shown). The structure of [S(CH2-2-C6H4SbMe3)2]I2, resulting from pnictogen bonding and extensive other primary and secondary interactions, is shown in Figure 22e and Figure 23 [155]. A representation of the ionic species, [S(CH2-2-C6H4SbMe3)2]2+·2I−, is shown in Figure 23a, and the expanded crystal system is shown in Figure 23b. Since the pnictogen bonding is between (formally) ionic species, it is charge assisted. While appreciating that [S(CH2-2-C6H4SbMe3)2]I2 is an ionic species, for convenience, we shall refer to it as a “molecular unit”. The detailed topology of antimony-centered pnictogen bonding cannot be inferred from the molecular unit shown in Figure 23a, and is best appreciated from Figure 22e. There are two different C–Sb···I links and two different C–Sb···S links, two intermolecular, and two intramolecular. Except for the C–Sb···S bond with an intramolecular distance of 3.555 Å, the other three are significantly longer. The C–Sb···I links have the characteristics of Type-II pnictogen bonds, whereas one of the two C–Sb···S bonds, at an intramolecular distance of 4.419 Å, is a characteristic of Type-I. Each of the contacts is shorter than the sum of the vdW radii of the respective atomic basins, 4.51 Å. Similarly, the intramolecular distance of one of the two C–Sb···S bonds (r(Sb···S) = 3.555 Å) is shorter than the sum of the vdW radii of S and Sb, 4.36 Å, while the other is slightly longer. These observations indicate the formation of two intramolecular hypervalent C–Sb···S pnictogen bonds. The nature of the intermolecular interactions is revealed by inspecting the molecular ordering in the expanded crystal, a part of which is shown in Figure 22e. Each of the two Sb centers of the cation is formally four-coordinate. Since each Sb center has four positive σ-holes along the four C–Sb bond extensions, they are in coulombic engagement with four nearest iodide anions. The resulting interactions, i.e., C–Sb···I, are all long-ranged and directional. We also note that the (Me)H···I hydrogen bonds are key driving forces causing the occurrence of these charge-assisted pnictogen bonds in the crystal system (r(H···I) = 3.0–3.5 Å). To confirm these observations, we performed an IGM-δg based isosurface analysis, using the geometry of the ion-pair shown in Figure 23a. The results are summarized in Figure 23c,d. The first suggests that the IGM-δg isosurface volumes in green and bluish-green representing the long and short interactions between Sb and S within the cation are weak and medium strength interactions, respectively. Similarly, the broad isosurface volumes in green appearing between I and H atomic basins in Figure 23d suggest that the (Me)H···I hydrogen bonds are the primary interactions that lead to the formation of C–Sb···I pnictogen bonds in the crystal. Antimony(III) complexes (SbX3, X = Cl and Br) with N-substituted thioureas N,N-dimethylthiourea (DMTU) and N,N-diethylthiourea (DETU) have been reported [156]. They include fac-SbCl3(DMTU)3 and mer-SbBr3(DMTU)3], with octahedral Sb3+. In b,c,d-Cl-[SbCl3(DETU)2], the geometry of Sb3+ is square pyramidal, with two sulfur atoms from two DETU and three chlorides making up the coordination sphere. The sixth coordination site of Sb3+ is occupied by long μ–Cl···Sb interactions, leading to a polymeric structure. These Sb···Cl bond distances are 3.291 and 3.293 Å, i.e., substantially longer than the two Sb–Cl bonds (2.573 and 2.608 Å) and the two Sb–S bonds (2.532 and 2.534 Å). The unit-cell of the crystal is shown in Figure 24a, and the nature of the Sb···Cl zigzag array which is responsible in part for the packing of the entire crystal that extends along the crystalgraphic a-axis is shown in Figure 24b. We recognize these longer Sb···Cl bonds along the S–Sb bond extensions as pnictogen bonds; they are Type-IIa pseudo-linear interactions (∠S–Sb···Cl = 168.7° for the bond with r(Sb···Cl) = 3.293 Å and 175.3° for the bond with r(Sb···Cl) = 3.291 Å). In fac-SbCl3(DMTU)3 and mer-SbBr3(DMTU)3 (Figure 24c and Figure 24d, respectively), there are three Sb–S and three Sb–X (X = Cl, Br) bonds. There are also long Sb···X contacts (one r(Sb···Cl) = 3.011 Å in fac-SbCl3(DMTU)3 and two r(Sb···Br) = 3.006 and 3.180 Å contacts in mer-SbBr3(DMTU)3. 8.12. Crown Ethers as Pnictogen Bond Acceptor Hosts for the Formation of Stibium Bonds Crown ethers have played an important role in coordination chemistry, and notably in transition metal host–guest chemistry [113,157,158,159,160,161,162]. Their complexation with p-block metal halides has been reported several times (for example [160,163,164,165,166,167]). Shown in Figure 25 are the complexes of SbX3 (X = Cl, Br) with dibenzo-24-crown-8, 18-crown-6, and 12-crown-4. The large cavity of dibenzo-24-crown-8 shows the ability to accommodate two SbX3 units (Figure 25a,d). The O lone-pairs of the crown ether face the electrophilic regions on SbBr3 (see Figure 25d), leading to the formation of four Sb···O contacts of between 2.893(7) and 3.183(8) Å), while the hydrophobic methylene bridges face the three Br sites in the neighboring SbBr3 unit with Sb–Br bond lengths of 2.5268(15), 2.5478(15), and 2.5558(14) Å). The Sb···O contacts may not represent coordinate bonds, since the length the contacts (for example, the 3.147 Å contact) would suggest that these are antimony-centered pnictogen bonds. Two of them are quasi-linear, appearing along the Br–Sb bond extensions, while the other two are bent. The strength of these interactions may fall into the border region between coordinate and very strong pnictogen bonds. The bonding pattern in the dibenzo-24-crown-8 complex with SbCl3 is somewhat different (Figure 25a) relative to that found with SbBr3 (Figure 25d). There are now five Sb···O close contacts; no doubt, this is a consequence of the smaller size of SbCl3 compared to SbBr3. The three formal Sb–Cl bonds of SbCl3 have bond lengths of 2.3807(8), 2.3874(8), and 2.4015(9) Å) that are predominantly shorter. Because the electrostatic surface along the X–Sb bond extensions is positive (cf. Figure 2b,c), it links to the O-sites from opposite sides of the cavity of the crown-ether. This results in a sigmoidal conformation, in which two pseudo O5 donor cavities are created to satisfy the host–guest matching requirements. With this topology of bonding, the two O sites of the dibenzo-24-crown-8 serve as bifurcated pnictogen bond acceptors with Sb···O contacts in the range 2.852(2)–3.153(2) Å. Regardless of the nature of guest, i.e., SbCl3 or SbBr3, most of the Sb···O pnictogen bonds between SbX3 (X = Cl, Br) with dibenzo-24-crown-8 were found to be non-linear Type-II. In order to provide further insight into the coordination chemistry of Sb3+ ions, we performed IGM-δg analyses on their crystal geometries; our results are shown in Figure 26. The isosurface volumes in the plots shown in the top graphs were obtained between the Sb and X atoms in SbX3. They are colored deep blue, indicative of a reasonably high concentration of charge density in the bonding regions between Sb and X, as expected for coordinate bonds in SbX3. The remaining IGM-δg based isosurface plots of Figure 26 correspond to different isovalues, illustrating that intermolecular interactions are not faint. That is, the isosurfaces for the very strong interactions between Sb and O always appear, regardless of the isovalue used. They are bluish-green in nature, and demonstrate the stability anticipated from the intermolecular bond distances. However, the isosurfaces corresponding to the longer bonds formed between Sb in one unit of SbCl3 and Cl in the second unit of the same molecule do not show up for large isovalues (0.022, 0.020 and 0.14 a.u.). This is not very surprising given that small isovalues are necessary to visualize the weak and van der Waals interactions that correspond to regions with a very low charge density gradient. When an isovalue of 0.008 a.u. was used, most of the chemical interactions between SbCl3 and dibenzo-24-crown-8 were revealed. In addition to several H···Cl interactions, we observed two additional Sb···Cl interactions between the two SbCl3 units marked by circles in Figure 26a (bottom plots). They are longer (r(Sb···Cl) = 3.957 Å each) and bent (∠Cl–Sb···Sb(Cl) = 76.4°). These results suggest that antimony in (dibenzo-24-crown-8)(SbCl3)2 is eight-fold coordinated. At least three of the contacts (one Sb···Cl and two Sb···Ocrown) are of weak-to-medium strength and are stibium bonds. A similar result was obtained with the IGM-δg based isosurface analysis for (dibenzo-24-crown-8)(SbBr3)2, but there are no (Br–)Sb···Br links between the two SbBr3 units. However, the dependence of the size of the isosurface on the isovalue was notable (see Figure 26b, bottom ones); there were no IGM-δg isosurfaces found between Sb and O for an isovalue of 0.022 a.u., and they were revealed only when an isovalue < 0.020 a.u. was used, suggesting that they are genuine medium-strength pnictogen bonds. Figure 25b,c display the local bonding environment between the host and guest species in (12-crown-4)SbCl3 [162] and (18-crown-6)SbCl3 [161], respectively. Because the cavity of 12-crown-4 is smaller than that of 18-crown-6, the Sb3+ in SbCl3 forms four Sb···O contacts in its complex with the first, but six with the second, resulting in a bowl-shaped architecture with a cone-like facial stand formed by SbCl3. As a means of verifying these tentative deductions concerning the nature of the bonding in these systems, the IGM-δg isosurfaces were calculated and are shown in Figure 27. There are four thick, bluish circular volumes between Sb and O atoms in Figure 27a for (12-crown-4)SbCl3 that signify Sb–O covalent bonds [162]. In addition, we note interactions between neighboring (12-crown-4)SbCl3 units: a Cl···Cl halogen bond; H···Cl hydrogen bonds between the methylene hydrogens of the crown ether and the negative sites on Cl of SbCl3; and H···H dihydrogen type attractive interactions between the methylene groups of the crown ether (Figure 27a). In the case of (18-crown-6)SbCl3, there are three greenish and three bluish-green thick circular volumes between Sb and O (Figure 27b). The first three are pnictogen bonds and the others are genuine coordinate bonds. In addition, there are several H···Cl hydrogen bound engagements between SbCl3 and 18-crown-6. However, it should be kept in mind that these are not just the interactions responsible for the stability of the infinite crystals. There are a number other interactions between the host and guest species, including H…O hydrogen bonds, which can be revealed when the unit-cell is expanded. There are five Sb···O pnictogen bound contacts between the interacting units in the crystal structure of (cyclohexyl-15-crown-5)SbCl3 [114] (CSD ref. GESDOA), with r(Sb···O) varying between 2.825 and 3.002 Å (cf. Figure 1g). They are indeed longer than the three Sb–Cl coordinate bonds, i.e., 2.419, 2.427 and 2.432 Å. Of the five Sb···O pnictogen bonds, three are quasi-linear (∠Cl–Sb···O = 154.6°, 165.9° and 168.3°) and the remaining two are non-linear (∠Cl–Sb···O = 135.8° and 144.7°). Other than these, there are several H···Cl hydrogen bonding interactions between the –CH2 fragments of cyclohexyl-15-crown-5 and the Cl atoms of SbCl3. In the complex between SbCl3 and 18-S-6 (18-S-6 = 1,4,7,10,13,16-hexathiacyclooctadecane), (18-S-6)(SbCl3)2, the large thio-crown accommodates two SbCl3 units, with three Sb···S contacts of 2.968, 3.061 and 3.461 Å, i.e., longer than the Sb–Cl coordinate bonds (2.471, 2.402 and 2.381 Å), and with ∠Cl–Sb···S = 141.7° [109]. These longer-range interactions are clearly pnictogen bonds. The IGM-δg based isosurface analysis shown in Figure 27c suggests that two of the Sb–S links are coordinate bonds and the remaining long Sb···S contact is a pnictogen bond. The isosurface for this contact becomes very faint when a high isovalue of 0.02 a.u. was used in our IGM-δg analysis. On the other hand, the intermolecular bonding modes of crown-ethers with SbF3 are somewhat different to those of the other antimony trihalides, no doubt because of the small, highly electronegative nature of fluorine. Host–guest fitting is more prominent for SbF3 with the bound F atoms of the molecule involve in additional Sb–F···O interactions when a large crown-ether is the host (Figure 28a–e). These interactions are either comparable to, or slightly longer than, the F–Sb···O interactions, but are markedly longer than the Sb–F bonds (r(Sb–F) ~ 1.9 Å). The former are Type-I and the latter are Type-IIa interactions, as deduced from our investigation of the ∠Sb–F···O and ∠F–Sb···O contact angles in the solid-state structures of SbF3 complex with a number of 18-crown-6 crown ethers (Figure 28d,e). The ∠F–Sb···O angles formed along the three F–Sb bond extensions are quasi-linear, and within the ranges 161–166°, 159.2–167.5°, and 161–165.0° in the complexes (cis-anti-cis-dicyclohexyl-8-crown-6)SbF3 [168], (benzyl-18-crown-6)SbF3 [168], and (12-crown-4)SbF3 [169], respectively (see Figure 28a, Figure 28b and Figure 28c, respectively). The remaining F–Sb···O interactions are non-linear. For example, ∠F–Sb···O lies between 130° and 133° for three F–Sb…O bonds that are significantly off the F–Sb axes in (cis-anti-cis-dicyclohexyl-8-crown-6)SbF3 [168], and between 161–165.0° along the remaining three F–Sb···O bonds in (18-crown-6)SbF3 [169]. The values of ∠F–F···O are in the range 60° and 90° for all these complexes. The SbF3 molecule does not fit well inside the cage provided by (12-crown-4)SbF3; see Figure 28c [169]. Consequently, the ∠F–Sb···O contact angles deviate significantly from linearity. For instance, the four (F–)Sb···O intermolecular distances of 2.775, 2.809, 3.166, and 3.250 Å correspond ∠F–Sb···O contact angles of 151.7°, 133.7°, 123.1°, and 137.4°, respectively. We, therefore, refer to these F–Sb···O interactions in this and similar other systems as “non-linear pnictogen bonds”. Most of the Sb–F···O interactions in (12-crown-4)SbF3 are also non-linear, except for one interaction which is highly directional (r(F···O)) = 2.907 Å; ∠Sb–F···O = 66.3°; ∠C–O···F = 158.8°), and the directional nature of the interaction is determined based on the C–O···F angle. We note further that in all these host–guest structures, the importance of secondary interactions cannot be overlooked. They appear either as H···X or F···O interactions between SbX3 and crown-ether. The presence of H···X hydrogen bonds in the host–guest complex systems can be inferred from the space-filling models shown in Figure 28d; each covalently-bound F in SbF3 kisses at least two nearest H atoms of the -CH2 fragment of 18-crown-6, forming a set of six hydrogen bonds. Of course, the number and extent of the formation of hydrogen bonds is determined by the size of the crown-ether. That SbF3 molecular entity fits well inside the 18-crown-6 cavity is also evident in Figure 28d (see the space filling model, extreme left). In the case of the crystal structure of (HDTOA)3(SbI3)2 (HDTOA = N,N’-dicyclohexyldithiooxamide) [171] (Figure 29a), the three Sb–I bonds of SbI3 are about 0.36 Å shorter than the remaining three Sb···S contacts. The pseudo-octahedral coordination sphere of Sb3+ is completed by interaction with three S donors from three different HDTOA ligands in quasi-linear contacts (∠I–Sb···S = 166–171°), characteristic of pnictogen bonds. The intermolecular interaction between 9-S-3 crown ether and SbI3 in the 1:1 adduct (9-S-3)SbI3 (9-S-3 = 1,4,7-trithiacyclononane) (Figure 29b) is comparatively stronger, as attested to by the shorter (I–)Sb···S bond distances. The Sb3+ lone pair is not stereochemically active [172]. Indeed, the Sb···S distances are shorter than the Sb–I bond lengths. This suggests that the Sb···S contacts may be regarded as very strong pnictogen bonds. By contrast, in the crowded environment of (NEt4) [(η5-cyclopentadienyl-Fe(CO)2)(Fe(CO)4)2SbI] [173], tetra-coordinated Sb3+ also participates in Sb···π(C≡O) interactions (Figure 29c). There are six such interactions, with each pair developing along the non-linear extension of each Sb–X (X = I, Fe) bond. The Sb···π(mid of point of C≡O) distance is 3.399 Å, and Sb···C(≡O) distance is 3.171 Å. From an examination of the space-filling model of the system, it was inferred that the Sb cation was also linked non-covalently with the near C sites of the Fe-bound η5-cyclopentadienyl moiety. To verify these conclusions, we examined the IGM-δg isosurfaces. Two examples are shown in Figure 30. The top one, Figure 30a, is for [1.5]dibenzothia-18-crown-6)SbF3 [170], while the bottom one, Figure 30b, is for (HDTOA)3(SbI3)2 (HDTOA = N,N’-dicyclohexyldithio-oxamide) [171]. The IGM-δg based isosurface results are in agreement with the inferences drawn from the intermolecular bond distances between the interacting molecules (Figure 29a,b) and the MESP analysis of SbI3 (see Figure 2d). In the case of [1.5]dibenzothia-18-crown-6)SbF3, of the six Sb···O contacts, the two with the shortest distance are genuine coordinate bonds, as evidenced by the bluish-green isosurfaces. The other four Sb···O contacts are associated with greenish isosurfaces and are seemingly pnictogen bonds. In addition, we observed F···O, C···F and H···F interactions between SbF3 and the crown ether. All the Sb–I and Sb–S contacts in (HDTOA)3(SbI3)2 are coordinate bonds, since they feature bluish-green isosurfaces. We have also observed a number of (N)C···I/(C)C···I and H···I contacts between the interacting monomer units. These results are in agreement with what might have been speculated from the space-filling models that rely on the vdW radii of the atomic domains. 9. Conclusions In this overview, we have examined the nature of the electrostatic surfaces of several molecular entities in various illustrative crystal lattices to provide evidence of the occurrence of an often overlooked non-covalent interaction, the antimony-centered pnictogen bond, or more succinctly, the stibium bond. We must emphasize that we do not claim that our survey of the CSD and ICSD databases is comprehensive; we have merely drawn illustrative examples from those databases to highlight the occurrence of overlooked non-covalent interactions. Pnictogen bonding in crystal lattices has been known since the middle of the last century, so it is misleading to claim that it only became known to community after 2011.Our investigations of intermolecular distances, directionality, electrostatic potential and IGM-δg based isodensity surfaces in most of the selected systems have enabled to us demonstrate that hypervalent Sb atoms in molecular entities contain more than one σ-hole and have the potential for involvement in attractive engagements with the negative sites in neighboring molecular entities, thereby causing (or contributing to) the assembly and stability of crystal lattices. The MESP model is suitable for understanding of directional Type-II interactions that are Coulombic, but not for rationalizing Type-I or -III interactions; this may be overcome by applying the IGM-δg model. The “sum of the vdW radii” concept, together with other geometric and topological features, has shown to be very effective in detecting pnictogen bonding in crystals when applied carefully. Depending on the molecular environment, the directionality of these interactions may appear in different flavors, following Type-I, -II and -III bonding topology interactions. Our investigation suggests that pnictogen bonds are not always linear, or quasi-linear; indeed, non-linear Type-II interactions were abundant in many of the crystals we examined. In most cases, other primary or secondary interactions (such as hydrogen bonding, halogen bonding, tetrel bonding and other π-centered interactions) occur simultaneously, which drive the directionality of the stibium bonds. The involvement of the same covalently bound Sb atom in multiple interactions (for example, as in crown-ether complexes) and the competition between them influence the directionality of the pnictogen bonds. We have demonstrated that antimony in molecules can form pnictogen bonds when it finds itself in the close vicinity of Lewis bases such as O, N, F, Cl, Br, I and S in molecules with which it interacts. We have also shown that pnictogen bonds can be formed with the delocalized π-density on the fragments –C=N=S and –C≡O in molecular entities, as well as on arene moieties. These findings suggest that donors of pnictogen bonds are no different to those that have been widely examined for hydrogen bonds, halogen bonds, and other non-covalent interactions. None of the crystal systems showed evidence that stibium bonds were the only attractive interactions causing molecular assembly and therefore contributing to the entirety of crystal stability. We have also observed that intramolecular stibium bonds in crystals are not so uncommon, even though intermolecular stibium bonds are widely present in a variety of crystals. While the majority of the illustrative systems presented in this overview have yet to be thoroughly explored using state of the art computational methods and other approaches, we expect that this work will serve as a guide for researchers who use, or intend to use, pnictogen bonding in their work. Since Sb has already played a significant role in the synthetic design of functional zero-, one-, two- and three-dimensional nano-scale materials, especially in the area of optoelectronics, the possibility of exploiting the Sb-centered pnictogen bonding interactions discussed in this study should assist future investigations into these and other materials. Acknowledgments This work was entirely conducted using the various computation and laboratory facilities provided by the University of Tokyo and the Research Center for Computational Science of the Institute of Molecular Science (Okazaki, Japan). P.R.V. is currently affiliated with the University of the Witwatersrand (SA), and Nagoya University, Aichi 464-0814, Japan. A.V. is currently affiliated with Tokyo University of Science, Tokyo, Japan 162-8601. K.Y. is currently affiliated with Kyoto University, ESICB, Kyoto, 615-8245, Japan. H.M.M. thanks the National Research Foundation, Pretoria, South Africa, and the University of the Witwatersrand for funding. Author Contributions Conceptualization, project design, and project administration, P.R.V.; formal analysis and investigation, A.V. and P.R.V.; Supervision, P.R.V.; writing—original draft, A.V. and P.R.V.; writing—review and editing, A.V., P.R.V., H.M.M. and K.Y. 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 This research did not report any data. Conflicts of Interest The authors declare no conflict of interest. The funders had absolutely 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. Figures, Scheme and Tables ijms-23-04674-sch001_Scheme 1 Scheme 1 Illustration of (a) Type-I, (b) Type-II and (c) Type-III topologies (geometric) of noncovalent bonding interactions. θ’s represents the angle of interaction between the interacting atomic domains, and Pn, D, R and R’ refer to the covalently/coordinately bound pnictogen atom, the interacting atomic domain (generally nucleophilic), and the remaining part of the molecular entities associated with Pn and D atomic basins, respectively. δ± signifies the local polarity (positive or negative), and the small region on atom Pn along R–Pn σ-bond extension colored in green indicates an electron deficient region (a σ-hole). Figure 1 Some selected examples (with CSD codes in capital letters) illustrating the possibility of Sb···X pnictogen bonding interactions formed by covalently bound Sb in SbCl3 and SbBr3 upon attractive engagement with a variety of interacting molecules containing pnictogen bond acceptors X, where X refers the halogen derivatives, O, S, and π-density. Selected Sb···X intermolecular distances and the Sb–X covalent/coordinate bond distances (in Å) are shown for most cases, indicating clear evidence of the difference in distances between Sb···X and Sb–X. The centroid of the arene moiety (tiny sphere in red) to Sb distances in several cases are also shown in Å. Atom type is shown where appropriate. The compounds are (a) SbCl3mbit (mbit = bidentate 1,1’-methylene-bis(3-methyl-2H-imidazole-2-thione) [108]; (b) SbCl3.18S6 (18S6 = the crown ether 1,4,7,10,13,16-hexathiacyclooctadecane) [109]; (c) (C24H24)(SbCl3)2 (C24H24 = [2.2.2]paracyclophane) [110]; (d) biphenyl bis(antimony trichloride) [111]; (e) (C18H30)SbCl3 (C18H30 = hexaethylbenzene) [112]; (f) (cyclohexo-12-crown-4)SbCl3 [113]; (g) (cyclohexo-15-crown-5)SbCl3 [114]; (h) (benzene)(SbCl3)2 [115]; (i) pyrene bis(trichloro-antimony) [116]; (j) [2.2.2.2]-Paracyclophane tribromo-antimony [117]; (k) trichloro-antimony toluene [118]; (l) tetrakis(trichloro-antimony) 1,2-diphenylethyne [119]. Figure 2 MP2(full)/def2-TZVPPD calculated 0.001 a.u. isoelectron density mapped potential on the electrostatic surfaces of SbX3 (X = F, Cl, Br, I) molecules: (a) SbF3; (b) SbCl3; (c) SbBr3; (d) SbI3. Selected VS,max and VS,min values in kcal mol−1 are shown, which are the local most minimum and maximum of potential (tiny circles in blue and red), respectively. Two views of the MESP graph for each molecule are displayed. (Top): Covalently bound Sb faces the reader. (Bottom): The triangularly arrayed X atoms face the reader. The crosses (×) shown along the extensions of the Sb–F bonds highlight the absence of a σ-hole on F, indicating that F is entirely negative. Figure 3 (a): The space-filling model of the unit-cell of [(CH3)4Sb]I (CSD ref. code: SUCZEV). (b) The 2 × 2 × 2 supercell structure of the same crystal, with selected intermolecular distances and angles shown. (c) The IGM-δg based isosurface plots for the ion-pair [Sb(CH3)4]+[I]−, obtained on the crystal geometry. Selected bond lengths and bond angles are in Å and degree, respectively. Dotted lines represent intermolecular interactions. Atom type is marked in (c). Figure 4 (a) The unit cell of the adduct between antimony triiodide and molecular sulfur, SbI3:3S8 (ICSD ref. code. 14200). (b) Illustration of the 1 × 1 × 2 supercell structure of the adduct, showing the network of various intermolecular interactions involved in the formation of the crystalline material. (c,d) The side and top views of the nature of the packing in the SbI3:3S8 crystal. Selected bond lengths and bond angles are in Å and degree, respectively. Dotted lines represent intermolecular interactions. Atom type is marked in (a). Figure 5 (a) ωB97XD/aug-cc-pVTZ computed 0.0015 a.u. isoelectron density mapped potential on the electrostatic surface of the S8 molecule. (b) Illustration of the molecular framework, with only the local most maximum of potential (VS,max) along the outer extensions of the S–S covalent bonds. Values of the local most minima of potential (VS,min) on the electrostatic surface of the S8 molecule is shown in (a). Values of VS,max and VS,min are in kcal mol−1. Figure 6 Illustration of various σ-hole centered intermolecular interactions in the crystal structure the adduct SbI3:3S8. Some molecules in the cell have been deleted for clarity. Shown in (b) are the IGM-δg based isosurface topologies (green) explaining the intermolecular bonding interactions between various interacting atomic domains. The symbol “σ” on some atoms in (a) signifies the presence of a σ-hole, and the intermolecular interactions are represented by dotted lines in cyan or green. Atom type is shown in each case. Figure 7 (a) The 2 × 2 extended crystal structure of the adduct SbCl3.S8. Hanging contacts are shown by dotted lines in red. The portion of the crystal in (a) encircled by an ellipse is shown in (b). Bond lengths and bond angles are in Å and degrees, respectively. Not all the Cl···S halogen bound and the S···Cl chalcogen bound contacts are shown. Atom type is marked in (b). The long arrow in black refers to the cluster that is encircled in (a). Figure 8 (a,b) The unit-cell and 2 × 2 extended crystal structures of SbF3 (ICSD ref. 16142), respectively; the latter shows a pseudo 3D framework of the system. (c) Illustration of the local topology bonding between the SbF3 units in the crystal. (d,e) Representation of the IGM-δg based isosurface topologies between the SbF3 units in the crystal. Selected bond lengths and bond angles are in Å and degrees, respectively. Blue and green isosurfaces in (d,e) represent strong and weak interactions between F and Sb in the crystal, and were calculated at different isovalues. Intermolecular interactions between molecular entities are represented by dotted lines. Figure 9 (a,b) The 2 × 2 extended structures of the SbCl3 crystal in the space groups Pnma and Pbnm, respectively; (c) The 2 × 2 extended structure of SbBr3 (space group Pbnm). In all three cases, Cl–Sb···X (X = Cl, Br) intermolecular pnictogen bonding interactions are illustrated as dotted lines in cyan. (d–f) Representation of the structures of the same crystal systems, illustrating the presence of X···X (X = Cl, Br) intermolecular contacts. (g–i) Illustration of the local pnictogen bonding environment around the Sb3+ ion in SbX3. Selected bond distances are in Å and degrees, respectively. Figure 10 (a) The crystal structure of the R-3¯ trigonal geometry of SbI3, showing the layer-like structure in 2D (left), and local octahedral coordination environment of the Sb3+ ion. (b) The crystal structure of the monoclinic geometry of antimony triiodide, showing a 3D network of intermolecular interactions. Selected Sb–I/Sb···I bond distances are shown. The ICSD references are given in each case. Selected bond distances are in Å and degrees, respectively. The intermolecular pnictogen bonding interactions are illustrated as dotted lines in cyan. Figure 11 (a) IGM-δg based isosurfaces (green and bluish-green volumes between atomic basins) between the molecular entities responsible for the unit-cells of SbX3 (X = Cl, Br, I) crystals: (a) SbCl3 (Pbnm); (b) SbBr3 (Pbnm); and (c) SbI3 (P21/c). An isovalue of 0.008 a.u. was used on all occasions. The nature of specific intermolecular interactions is shown for each case, and are marked by arrows. Atom type is also shown for all cases. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines. Figure 12 (a) The unit-cell of the crystal of (trimethyl-stibino)-dimethyl-stibonium hexabromo-dimethyl-di-antimonate(III), [(CH3)3Sb–Sb(CH3)2]2[(CH3SbBr3)2], showing Sb···Br interactions. (b) Illustration of the nature of Sb-centered non-covalent interactions (dotted lines in cyan) in the crystal. Selected bond lengths and bond angles in Å and degree, respectively are shown. Hanging contacts between atoms are shown as dotted lines in red. The CSD ref. code is shown. Figure 13 (a) Selected intermolecular bonding interactions in the crystal structure of bis(dimethylstibanyl)oxane, ((CH3)2Sb)2O, CSD ref. code MELNAS. (b) The 2 × 2 extended structure of the unit-cell of the crystal, showing the Sb···O and Sb···Sb intermolecular contacts. (c) The IGM-δg isosurface plots between ((CH3)2Sb)2O entities in the crystal, illustrating the possibility of various intermolecular interactions that appear at low isovalues. Selected bond lengths and bond angles are in Å and degree, respectively. Contacts between atoms are shown as dotted lines in red or cyan. Atom color: Sb—purple; O—red; C—gray; H—white-gray. Figure 14 (a) The ball-and-stick model of the 2 × 2 supercell structure of crystalline ((CH3)2Sb)2S (CSD ref. code MELNEW). (b) The local topology of Sb···S pnictogen bound interactions in the crystal. (c) The IGM-δg isosurface plots between the ((CH3)2Sb)2S molecular entities in the crystal, illustrating Sb···Sb and Sb···S interactions. Bond lengths and bond angles are in Å and degree, respectively. Contacts between atoms are shown as dotted lines in red or cyan. Selected atoms are labelled in (b). Figure 15 (a) The space-filling and (b) ball-and-stick models of the coordination of SbCl3 with 1,4-dioxane as observed in the crystal of catena-(tris(μ2-1,4-dioxane-O,O’)-bis(trichloro-antimony(III)), CSD ref. code BEKHUV01). (c) Illustration of local Sb···O links in the crystal. (d) Hydrogen bonding topologies between 1,4-dioxane moieties in the crystal. Selected bond lengths and bond angles are in Å and degree, respectively. Hanging contacts are shown as dotted lines in red. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines in cyan. Figure 16 (a) The space-filling model of crystalline [Co(trien)(NSC)2][Sb2(tart)(Htart)], CSD ref. code CAXXOO. (b) The ball-and-stick model of the same structure, showing atom type and highlighting the possibility of π-centered non-covalent interactions. Bond lengths and bond angles are in Å and degree, respectively. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines. Figure 17 (a) The unit-cell crystal structure of [SbCl2imR2R’2][OTf]. (b) The nature of coordination environment around the Sb center is highlighted. The hanging contacts represented by dotted lines in red are Sb···O pnictogen bonding interactions. The CSD reference code is shown, and selected bond lengths and bond angles are in Å and degrees, respectively. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines in cyan/red. Figure 18 (a) The unit-cell of crystalline [SbCl3·OP(NCS)3]4 (ICSD ref. code 80097). (b) The nature of the pseudo-octahedral coordination environment around the Sb center. (c) The Cl···S intermolecular interactions responsible for the pseudo 3D geometry of the crystalline material. (d) The IGM-δg based isosurface topologies (isovalue = 0.008 a.u.) between OP(NCS)3 and SbCl3. Bond distances and bond angles are in Å and degree, respectively. Hanging contacts in (b,c) in red represent coordinate bonds/intermolecular interaction. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines. Figure 19 Space-filling models showing the molecular packing in the crystals of (a) SbCl3·(CH2S)3 (CSD ref. code in capital letters) and (b) SbBr3·(CH2S)3 (CSD ref. code TRTHAB). Illustration of the exceptionally long Sb···S intermolecular distances and their angular features is shown in (c,d), respectively. Included in (e,f) are the μ3-bridges of covalently bound S, leading to the emergence of Type-IIa chalcogen bonding in SbCl3·(CH2S)3 and SbBr3·(CH2S)3 crystals, respectively. Atom types are labeled in each case. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines in cyan. Bond distances and bond angles are in Å and degree, respectively. Figure 20 (a) The unit-cell of the crystal structure of (CN4H7)SbC2O4F2(H2O)0.5. Shown in (b) is the local coordination environment around the Sb center in the crystal. Selected bond lengths and bond angles are in Å and degree, respectively. The CSD ref. code in capital letters is marked. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines in cyan. Atom color: Sb—purple; O—red; F—green; C—gray; H—white-gray; N—blue. The [CN4H7]+ and H2O moieties in (b) are removed for clarity. Figure 21 The topology of (a) Sb···Br and Sb···π pnictogen bonding and (b) hydrogen bonding in the unit-cell of the crystal of SbBr3 (CSD ref. code PYRABR). (b) The nature of Br···Br halogen-halogen bonding and Sb···Br pnictogen bonding between the SbBr3 units in the crystal. (c) The nature of Sb···π pnictogen bonding between pyrene and SbBr3 in the crystal. (e,f) The IGM-δg based isosurface topologies between the molecular entities shown in (c) and (d), respectively. Selected bond distances and bond angles are in Å and degree, respectively. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines. Atom color: Sb—purple; Br—dark-red; C—gray; H—white-gray. Figure 22 (a) The nature of the coordination environment around the Sb ion in the crystals of (a) (Cy3PS)SbBr3, (b) (Cy3PS)SbCl3, (c) (Cy3PS)SbI3, (d) (Cy3PO)SbCl3, and (e) [S(CH2-2-C6H4SbMe3)2]I2. Selected bond lengths and bond angled in Å and degree, respectively. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines. Atom color: Sb—purple; O—red; Br—dark-red; C—gray; H—white-gray; P—orange; S—yellow; Cl—green. CSD ref. codes are shown. Figure 23 (a) Charge-assisted C–Sb···I pnictogen bonding in [S(CH2-2-C6H4SbMe3)2]I2. (b) The 2 × 2 × 2 unit-cell structure of the crystal, showing the C–Sb···I pnictogen bond networks in the crystal. (c) and (d) Illustration of the IGM-δg based isosurface topologies of the C–Sb···S and C–Sb···I pnictogen bonds in (a). The detailed nature of pnictogen bonding around the Sb cation may be inferred from Figure 22e (see above). Selected bond distances and angles in Å and degrees, respectively. Atom type and CSD ref. codes in capital letters are shown. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines. Figure 24 (a) The mixed polyhedral and ball-and-stick model of the unit-cell crystal structure of b,c,d-Cl-[SbCl3(DETU)2]. (b) The nature of Sb···Cl zigzag array responsible in part for the packing of the entire crystal that extends along the crystalgraphic a-axis. The polyhedral models of the crystal structure of (c) fac-SbCl3(DMTU)3 and (d) mer-SbBr3(DMTU)3]. Selected bond lengths and bond angles in Å and degree, respectively. The CSD ref. code is shown for each case. The polyhedra represent to a six-coordinate Sb, and atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines. Figure 25 The local structure the crystals of (a) (dibenzo-24-crown-8)(SbCl3)2; [160] (b) (12-crown-4)SbCl3; [162] (c) (18-crown-6)SbCl3; [161] and (d) (dibenzo-24-crown-8)(SbBr3)2. [160] Selected bond distances and bond angles are shown in Å and degree, respectively. Solvent acetonitrile in (a) is omitted for clarity. The CSD ref. code in capital letters is shown for each case. Atoms are shown as small spheres and bonds as lines in atom color, whereas the intermolecular interactions are represented by dotted lines in cyan. Figure 26 (Top) IGM-δg based isosurface plots between Sb and X in SbX3: (a) (dibenzo-24-crown-8)(SbCl3)2 and (b) (dibenzo-24-crown-8)(SbBr3)2. (Bottom) IGM-δg based isosurface plots between Sb and O in the corresponding systems, respectively, showing the dependence of the isosurfaces on the IGM isovalues. The crosses on the left plots indicate the disappearance of Sb···Cl bonds for high isovalues. Figure 27 IGM-δg based isosurface plots for (a) (12-crown-4)SbCl3, (b) (18-crown-6)SbCl3 and (c) (18-S-6)(SbCl3)2. The isosurface plots in (c) were obtained with two different isovalues. Figure 28 (a–e) Examples of some host–guest complexes of SbF3 with crown-ethers. Selected bond lengths and bond angles are in Å and degrees, respectively. (a) (cis-anti-cis-dicyclohexyl-8-crown-6)SbF3 [168]; (b) (benzyl-18-crown-6)SbF3 [168]; (c) (12-crown-4)SbF3 [169]; (d) (18-crown-6)SbF3 [169]; and (e) ([1.5]dibenzothia-18-crown-6)SbF3 [170]. For clarity, the H-atoms are omitted in the first two cases, and potential secondary interactions are omitted for most cases. Atom type is shown in some cases, and the CSD ref. code is given. Benzene solvate is not included in (e) for clarity. Selected bong lengths and bond distances are shown in Å and degree, respectively. Figure 29 Examples of some host–guest complexes of (a) (HDTOA)3(SbI3)2 (HDTOA = N,N’-dicyclohexyldithio-oxamide) [171]; (b) (9-S-3)SbI3 (9-S-3 = 1,4,7-trithiacyclononane) [172]; (c) [(η5-cyclopentadienyl-Fe(CO)2)(Fe(CO)4)2SbI]− [173]. For clarity, potential secondary interactions are omitted in most cases. Atom type is shown in some cases, and the CSD ref. code is given. Selected bond lengths and distances are shown in Å and degree, respectively. Figure 30 IGM-δg based isosurface plots for (a) [1.5]dibenzothia-18-crown-6)SbF3 [170], and (b) (HDTOA)3(SbI3)2 (HDTOA = N,N’-dicyclohexyldithio-oxamide) [171]. Atom labeling is shown. Isosurfaces colored blue and green between the interacting molecules in the crystal signify strong and weak intermolecular interactions, respectively. Other intermolecular interactions (viz. hydrogen bonds, C···F, F···O and C···I bonds, etc.) are marked with dotted lines in (b) and circles in (a). The space-filling model is shown for each case. ijms-23-04674-t001_Table 1 Table 1 The van der Waals radius (Å) of some selected atoms proposed by different authors. Atom Number Z Atom Symbol Bondi [69] Batsanov [70] Alvarez [68] Mantina et al. [71] 1 H 1.20 --- 1.20 1.10 6 C 1.70 1.70 1.77 1.70 7 N 1.55 1.60 1.66 1.55 8 O 1.52 1.55 1.50 1.52 9 F 1.47 1.50 1.46 1.47 15 P 1.80 1.95 1.90 1.80 16 S 1.80 1.80 1.89 1.80 17 Cl 1.75 1.80 1.82 1.75 33 As 1.85 2.05 1.88 1.85 35 Br 1.83 1.90 1.86 1.83 51 Sb --- 2.20 2.47 2.06 53 I 1.98 2.10 2.04 1.98 83 Bi --- 2.30 2.54 2.07 ijms-23-04674-t002_Table 2 Table 2 Comparison of MP2(full)/def2-TZVPPD level 0.001 a.u. isodensity envelope mapped potentials with those of ωB97XD/def2-TZVPPD potentials computed on the surfaces of the SbX3 molecules (X = F, Cl, Br, I). Local Most Extrema on the Surface of Specific Atom/Bond SbF3 SbCl3 SbBr3 SbI3 MP2(Full) ωB97XD MP2(Full) ωB97XD MP2(Full) ωB97XD MP2(Full) ωB97XD Vs,min on X (lateral portions) −22.1 −21.9 −10.3 −10.5 −8.8 −9.0 −6.9 −7.1 Vs,min on Sb (opposite to the triangular face formed by three X atoms) 31.2 30.7 25.0 24.9 23.1 22.9 20.0 19.2 VS,max (on Sb–X bond extensions) --- --- 1.6 1.8 6.5 7.2 12.3 14.3 VS,max (on X–Sb bond extensions) 48.2 48.6 38.4 39.7 34.7 36.3 29.3 31.1 VS,max (on the centroid of the triangular face formed by three X atoms) 3.6 5.7 0.5 2.4 0.3 2.4 0.5 2.5 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Martin T.W. Derewenda Z.S. The name is bond—H bond Nat. Struct. Mol. Biol. 1999 6 403 406 10.1038/8195 10331860 2. Desiraju G.R. A Bond by Any Other Name Angew. Chem. Int. Ed. 2011 50 52 59 10.1002/anie.201002960 21031379 3. Arunan E. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095202 ijms-23-05202 Review Obesity as a Risk Factor for Dementia and Alzheimer’s Disease: The Role of Leptin https://orcid.org/0000-0001-9021-0228 Flores-Cordero Juan Antonio https://orcid.org/0000-0002-5660-735X Pérez-Pérez Antonio https://orcid.org/0000-0001-6956-7740 Jiménez-Cortegana Carlos Alba Gonzalo Flores-Barragán Alfonso https://orcid.org/0000-0001-8638-8680 Sánchez-Margalet Víctor * Tanti Jean-François Academic Editor Department of Medical Biochemistry and Molecular Biology and Immunology, Medical School, Virgen Macarena University Hospital, University of Seville, Av. Sánchez Pizjuan 4, 41009 Sevilla, Spain; jaflores@us.es (J.A.F.-C.); antonioresi@gmail.com (A.P.-P.); cjcortegana@us.es (C.J.-C.); galbaj@us.es (G.A.); alfonreyes1992@gmail.com (A.F.-B.) * Correspondence: margalet@us.es 06 5 2022 5 2022 23 9 520228 3 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/). Obesity is a growing worldwide health problem, affecting many people due to excessive saturated fat consumption, lack of exercise, or a sedentary lifestyle. Leptin is an adipokine secreted by adipose tissue that increases in obesity and has central actions not only at the hypothalamic level but also in other regions and nuclei of the central nervous system (CNS) such as the cerebral cortex and hippocampus. These regions express the long form of leptin receptor LepRb, which is the unique leptin receptor capable of transmitting complete leptin signaling, and are the first regions to be affected by chronic neurocognitive deficits, such as mild cognitive impairment (MCI) and Alzheimer’s Disease (AD). In this review, we discuss different leptin resistance mechanisms that could be implicated in increasing the risk of developing AD, as leptin resistance is frequently associated with obesity, which is a chronic low-grade inflammatory state, and obesity is considered a risk factor for AD. Key players of leptin resistance are SOCS3, PTP1B, and TCPTP whose signalling is related to inflammation and could be worsened in AD. However, some data are controversial, and it is necessary to further investigate the underlying mechanisms of the AD-causing pathological processes and how altered leptin signalling affects such processes. obesity leptin inflammation leptin resistance Alzheimer’s disease PAIDI CTS-151 Junta de Andalucia, SpainPAIDI CTS-151 Junta de Andalucia, Spain. ==== Body pmc1. Introduction When focusing on dementia, it is worth noting that the separating line between normal and pathological aging is not adequately defined. Therefore, it is difficult to determine where each phenomenon begins and ends and to distinguish the common deficiencies and individual differences within these phenomena [1]. This narrow line that separates the normal from the pathological is where we must intervene to minimise the symptoms the disease produces, making an early diagnosis of dementia necessary. The difficulty is even greater taking into account that the aging process itself can produce negative effects on general health and cognitive function in particular. Similarly, aging is linked to an increase in body weight, adiposity, and variations in hormones and adipokines, showing an altered pattern with age [2,3]. Similarly, both in murine and human models, an increase in microglial reactivity and inflammation with age has been described [2,3]. In this review, we discuss how this altered pattern is a factor that predisposes to obesity and dementia, such as Alzheimer’s disease (AD). Procedures have been developed over time to identify patients with early onset dementia, a concept that has evolved into the current term, mild cognitive impairment (MCI). Ronald Petersen developed the concept of MCI through the Mayo Clinic. The concept was an improvement in its attempt to identify people who may progress to dementia, as the cognitive aspects were introduced to the pre-existing aspects of memory. Currently, the fundamental objective of dementia research is to find markers that provide an early diagnosis and thus enable action to be taken before the disease evolves [1]. MCI is an example of this. Today, obesity is growing in the global population due to multiple causes: lifestyle, stress, nutrition, genetic background, and lack of exercise. In obesity, white adipose tissue (WAT) not only stores excess energy but also disturbs endocrine function. WAT secretes a group of substances called adipokines that exert autocrine, paracrine, and endocrine effects at the systemic level and also centrally in the central nervous system (CNS) [4,5,6]. Obesity has been linked to cognitive deficits, impaired long-term potentiation and synaptic plasticity, and a smaller brain volume, increasing the probability of developing Alzheimer’s disease (AD) and other dementias [7]. Thus, obesity is established as a risk factor for dementia. Furthermore, obesity causes a state of low-grade chronic inflammation in adipose tissue that leads to the dysregulation of homeostatic systems, which in turn leads to the development of various diseases, including those related to neurodegeneration. During this process, adipose tissue produces an increase in pro-inflammatory adipokine levels (interleukin 1 beta (IL-1β), interleukin 6 (IL-6), and tumoural necrosis factor alfa (TNF-α), and leptin) and a decrease in anti-inflammatory adipokine levels, such as adiponectin [4,6]. Yet another essential component of these complex interrelationships between obesity and brain status is the gut microbiota. In fact, meticulously detailed in a review by authors [8], it is explained how an altered intestinal microbiota pattern (or dysbiosis) can lead to a permanently altered physiological pattern, which can lead to cognitive impairments due to alterations in the gut-brain axis. In addition, it indicated that the administration of pre- and probiotics can restore this dysbiosis, enabling a return to an adequate homeostatic balance. Leptin, a pro-inflammatory adipokine secreted by WAT and found to be increased in people with a high body mass index, acts centrally at the level of the hypothalamic region through anorexigenic proopiomelanocortin (POMC)/cocaine- and amphetamine-regulated transcript (CART) neurons and orexigenic neuropeptide Y (NPY)/agouti-related peptide (AgRP) neurons, controlling food intake and energy expenditure. The literature suggests that leptin may be the link between obesity and dementia through the development of inflammation. Therefore, we will analyse the information on inflammation-induced leptin resistance that occurs during obesity as a pathological mechanism that may underlie neurodegenerative diseases such as AD and other dementias. 2. Obesity and Dementia Obese individuals are at greater risk of developing age-related cognitive decline, vascular dementia, MCI, and AD [4], as well as other neurodegenerative pathologies such as Parkinson’s [9,10] and Huntington’s disease [10,11]. In this section, we give an overview of obesity as a risk factor for dementia based on adipose tissue measurement indices, brain structural changes, and cognitive impairment measurements. Our purpose is to identify modifiable risk factors that allow an early diagnosis and treatment. Obesity can be defined as an excessive accumulation of adipose tissue which generates a low-grade inflammation state, whereas AD can be defined as a progressive neurodegenerative disease whose distinctive histopathological characteristics are the extracellular amyloid plaques and intracellular neurofibrillary tangles. A parameter used as a measure of adiposity is the body mass index (BMI). However, its use has not been free from difficulties. That is why the waist circumference and the waist-to-hip ratio (WHR) have also been used to evaluate excess fat [12]. In fact, in the work by Beyer et al. (2019) [12], it is suggested that the WHR, as part of a metabolic obesity profile, is a determining factor that plays a role in grey matter volume reductions, which might lead to reduced cognitive functions, that have a weaker association when using the BMI [12,13]. Nevertheless, BMI is the most widely used adiposity index [14,15,16]. Thus, an association between BMI and dementia has been described, although this relation is controversial [14,15,16,17]. Firstly, it has been suggested that being overweight and obese in middle age is related to a higher risk of dementia in old age. Nevertheless, a high BMI in late life is associated with better cognition [6,16,17]. Secondly, other studies have described contradictory outcomes, where a lower risk of dementia was observed for very obese people (BMI > 40 kg/m2) while underweight people (BMI < 20 kg/m2) display a higher dementia risk than heavyweight people [18]. There are different epidemiological studies that relate obesity and dementias, such as the more frequent AD, but, in general, these studies find a positive correlation between obesity and cognitive impairment, with a possible U-shaped curve. In this context, a reverse relation has been described between obesity and grey matter and whole brain volume [19,20,21,22,23,24,25], even though a minor number of publications did not find such a relation [26,27]. As mentioned above, obesity generates a chronic low-grade inflammation state, which is characteristic of a variety of other chronic conditions, such as metabolic syndrome, non-alcoholic fatty liver disease, type 2 diabetes mellitus, and cardiovascular disease [28,29], as well as neuroinflammation [30,31,32], a hallmark of neurodegenerative diseases such as AD [33,34,35]. Following this line, different animal studies have confirmed the connection between obesity and cognitive mismatches and/or impairment. Thus, different works point to an altered cognitive function when administering a less-healthy diet. A high-fat diet (HFD) rich in saturated fatty acids can result in obesity as well as deficits in hippocampal-dependent learning and memory functions [36,37]. Male Wistar rats fed with a HFD showed impaired memory, an effect that was augmented with a longer duration of HFD consumption [38] while, similarly, rats fed with a high-fructose-high-coconut oil diet experienced impaired hippocampal-dependent learning and memory processes, as evaluated through the Morris water maze task [39]. In another study [40], HFD-induced brain insulin resistance and cognitive impairment were observed. Molecular changes, such as a significant decrease in tyrosine phosphorylation of the insulin receptor and increased serine phosphorylation of IRS-1, which are signs of insulin resistance, might be the cause of the cognitive impairment in this mouse model. These molecular changes were accompanied by inflammatory signalling (NFκB, JNK) and stress responses (p38 MAPK, CHOP) in whole brain lysate. In a transgenic rat model of pre-AD and MCI, impaired special learning and memory has been described in the Morris water maze when rats received a high-caloric diet [41]; at the same time, some parameters of brain inflammation, such as microgliosis, were also found. Moreover, activated OX-6+ microglia were detected, as well as GFAP+ astrocytes located predominantly in the white matter, and the synaptic density in the CA1 and CA3 hippocampal subregions was lower in this high-calorific diet. In a triple transgenic AD mice model (3xTg-AD), an impairment in the cognitive function has been shown when administering a HFD, and this diet was able to induce enhanced oxidative stress and aggravated neuronal apoptosis via inactivation of the Nrf2 signalling pathway [42]. So, numerous animal studies indicate the relation between obesity and AD and other forms of dementia that affect cognitive function. Overall, obesity seems to be a risk factor for different forms of dementia, where we can find long-term memory and attention impairment, and executive function deficits. We have reviewed how cerebral structural and functional changes in obese people occur, and how a high saturated fat diet can affect cognitive function, including brain inflammation as a hallmark of this process. 3. Obesity and Leptin Energy homeostasis and the maintenance of body weight require that the peptides secreted by the organs of the periphery establish a signalling and functional interrelation between them. To do this, adipocytes synthesise and secrete adipokines with pleiotropic effects in various tissues and regulate numerous physiological functions [43,44]. In this review, we will focus on leptin, due to its involvement in the regulation of food intake and energy expenditure, studying its involvement in dementia and its relationship with obesity. Leptin has been found to circulate in plasma in proportion to body fat mass and this can be taken as an indicator of adiposity [45,46]. However, its study is difficult, since its levels vary by multiple factors: sex, BMI, starvation, and energy states. In addition, it shows a circadian rhythm, with leptin levels at their maximum between midnight and dawn, and is affected by other hormones and cytokines [47]. Leptin is a 16 kilodalton (kDa) peptide hormone produced by the ob (obese) gene. Leptin receptors are class I cytokine receptors. Previous studies have described six isoforms of the mRNA variants of the gene encoding the leptin receptor: four short forms (LepRa, LepRc, LepRd, LepRf), one long form (LepRb), and an extracellularly secreted soluble form (LepRe) [48]. Furthermore, five of the six isoforms (LepRa-LepRd and LepRf) have common extracellular and transmembrane domains, and only the soluble form (LepRe) has only an extracellular domain [48]. The long form LepRb has intracellular domains and proline-rich regions known as box1, box2, and box3 that are associated with Janus kinase (JAK) and signal transducer activators of transcription (STAT) signalling activation, whereas the other isoforms seem to be implicated in the leptin transport from the periphery to the CNS through the blood-brain-barrier (BBB) [48,49,50,51,52]. Leptin receptors are expressed throughout the body. In the CNS, leptin receptors are expressed in the arcuate nucleus (ARC), the dorsomedial hypothalamus (DMH), the ventromedial hypothalamus (VMH), the lateral hypothalamus (LH), the mediobasal hypothalamus (MBH), and the paraventricular nucleus (PVN). In addition, they have also been found in the cerebral cortex, hippocampus, ventral tegmental area, substantia nigra, medulla, and cerebellum [48,50,52,53,54,55,56,57]. Furthermore, the short isoforms LepRa and LepRc are expressed in the brain microvessels that make up the BBB, suggesting that these receptors may be associated with leptin transport [53,54]; in fact, the LepRa and LepRc isoforms have been shown to mediate leptin transport in the BBB, and dysfunctional receptors can lead to leptin resistance [56]. The expression of the leptin receptor has been observed in different neurons, including glutamatergic, GABAergic, and dopaminergic neurons. Thus, there is evidence of its involvement in the mechanisms of long-term potentiation, long-term depression, and motivational eating [42,44,45,48,49]. Biochemically, when leptin binds to its receptor it allows the activation of Janus kinase 2 (JAK2) and its autophosphorylation. Once activated, JAK2 phosphorylates other tyrosine residues (Tyr) in the receptor, including Tyr985, Tyr1077, and Tyr1138, to mediate different intracellular signalling pathways [48,58,59]. Intracellular signalling pathways initiated by the leptin receptor are [48,53,58,60,61]:JAK/signal transducer activators of transcription 3 (STAT3); Phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt); Extracellular signalling-regulated kinases (ERK); and Signal transducer activators of transcription 5 (STAT5). As we will see below, leptin is involved in various aspects of cognition, neurogenesis, neuroprotection, synaptic plasticity, and structural changes [57,62], which is not surprising given its access from the periphery to the CNS, the number of leptin receptors, and its wide distribution in the brain. 4. Leptin; Its Relationship with Cognition and Synaptic Function An important aspect of dementia is cognitive deterioration, which is manifested in different aspects such as synaptic function, learning, and memory. So, before addressing the connection between leptin and dementia, it is important to analyse the relationship and implication of leptin with these different aspects of cognition. Leptin signalling regulates different processes including food intake, energy expenditure, cognition, learning, memory, and mood [63]. Studies show that leptin performs different neuroprotective functions [56,57,63,64,65]. Furthermore, leptin regulates neurogenesis, synaptogenesis, neuronal excitability, and neuroprotection [57,62]. In learning and memory processes, synaptic plasticity, and the relationships between neurons at the level of synaptic transmission, are fundamental. Furthermore, in these processes, the mechanisms of long-term potentiation (LTP) and long-term depression (LTD) of synaptic transmission are crucial for the formation and consolidation of hippocampal memory. Thus, leptin is involved in these processes at the level of the hippocampus where leptin and glutamate receptors {N-methyl D-aspartate (NMDA) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors} are key players [4,50,59]. In support of this evidence, leptin receptors have been found in neuronal and non-neuronal cells in the hypothalamus, the cerebral cortex, as well as in the dentate gyrus, and the CA1 and CA3 areas of the hippocampus [62]. This last finding is fundamental, as these areas are highly involved with cognition and memory. Recent studies indicate that NMDA receptors are necessarily involved in leptin-dependent homeostatic control of body weight [66]. Thus, leptin enhances NMDA receptor function by promoting the efficiency of excitatory synaptic transmission at hippocampal Schaffer-collateral (SC)-CA1 synapses and allowing the conversion of short-term potentiation into LTP. Therefore, it is not surprising to have found LTP and LTD deficiencies in leptin-insensitive obese mice (db/db) and rats deficient in the leptin receptor (fa/fa) [4,59]. Consequently, leptin improves hippocampal-dependent memory. Thus, in the review by McGregor and Harvey [66] it is found that in transgenic mouse models of Alzheimer’s disease (CRND8), leptin improved performance in object recognition, contextual, and fear-conditioned tasks. In addition, performance in hippocampal-dependent memory tasks was also optimised in mice prone to accelerated senescence (SAMP8) that have elevated levels of the β-amyloid peptide (Aβ). Leptin can also regulate the configuration of neurons. Thus, plasma leptin levels have been associated with grey matter volume in various brain regions. Exogenous leptin administration recovers structural brain abnormalities in congenitally leptin-deficient humans and reverses the abnormalities in ob/ob mice [62]. Interestingly, the study by Annweiler [64] finds a relationship between circulating leptin levels and U-shaped cognition. Their results suggest that older adults with low or high circulating leptin concentrations are particularly prone to cognitive impairment and point to leptin as a modifiable risk factor. Therefore, we can say that leptin, through its actions in the periphery or the CNS, produces neuroprotective effects that improve cognitive function and memory. As a result, its dysfunction due to a deficit in signalling pathways, a decrease or alteration of its levels, or leptin resistance can cause processes that promote neurodegeneration [62]. 5. Leptin Resistance: Mechanisms Involved Leptin is reduced during fasting and increases with food consumption. When we eat, adipocytes release leptin, which tends to reduce eating behaviour. However, the paradox exists that in obesity, the leptin levels are increased; despite this, there is no indication or signal of satiety due to a peripheral and/or central resistance to leptin. Thus, an imbalance between anorexigenic and orexigenic signals occurs, which leads us to receive a signal of decreased satiety, and contributes to obesity, leading to a vicious cycle [4,61]. Resistance to leptin indicates that despite high plasma levels in obese people, signalling in the hypothalamus is decreased [4]. The foregoing leads us to review and analyse the factors involved in this dysfunction in leptin signalling. Next, we analyse the mechanisms that have been proposed as an explanation for leptin resistance, which is related to obesity, and helps to develop or perpetuate diseases such as dementia: (a) genetic mutations, (b) alterations in the transport of leptin through the BBB, (c) desensitisation of leptin receptors that reduce the functionally active number, (d) attenuation of signalling leptin {suppressor of cytokine signalling type 3 (SOCS3), protein tyrosine phosphatase type 1B (PTP-1B), and protein tyrosine phosphatase of T cells (TCPTP)}, (e) alteration of cellular descending leptin signalling in the CNS, and (f) multiple factors such as inflammation, elevated levels of C-reactive protein (CRP), adapter protein1 (SH2B1), and endoplasmic reticulum (ER) stress as well as decreased activity of histone deacetylase and the type of diet [58,61,67,68,69,70]. In this context, obesity-related inflammation may contribute to leptin resistance, which in turn further increases weight gain [71] and leptin levels, which then increases the inflammation-related obesity, since leptin is an important proinflammatory adipokine [72,73,74], activating monocytes [75] and lymphocytes [76]. 5.1. Pathways of Leptin Entry into the Brain and Leptin Resistance There are several pathways for the entry of leptin into the brain: through the (a) endothelial cells of the BBB, (b) epithelial cells of the choroid plexus, and (c) through the medio basal hypothalamus, which is surrounded by tanicytes that form a barrier between the median eminence and the cerebrospinal fluid [77,78,79]. Existing evidence shows that leptin traverses the BBB through a saturable transport system, but there are doubts about the involvement of LepRa [51,52,61,77]. An investigation has found that brain endothelial cells express higher levels of LepRa than LepRb or megalin receptor 2 (Lrp2). Furthermore, leptin has a higher affinity for both LepRa and LepRb, suggesting that LepRs are the most important binding sites for leptin, rather than Lrp2 [79]. Likewise, in another report, it has been suggested that the leptin receptor is necessary in the brain barrier for the uptake of leptin by the brain and the regulation of the food reward; megalin receptor 1 (Lrp1) and Lrp2 are considered alternative transporters [77]. However, the work by Bartolome et al. [80] provides evidence against the leptin receptor. Here, it has been suggested that LepR is not the main leptin transporter in human BBB, but rather the megalin receptor, since the authors observed a reduction in brain leptin uptake by eliminating the megalin receptor in the endothelial cells of the BBB, which induced hyperphagia and obesity. In the literature, there are two contradictory currents of thought as to whether the leptin resistance at the level of the BBB is due to a deficient leptin transport. On the one hand, there are studies that support the idea that there is a decrease in leptin transport through the BBB. In this sense, circulating factors in the blood, such as triglycerides, could reversibly inhibit leptin transport. Thus, low levels of these factors allow the transport of leptin through the BBB, but high triglyceride doses can inhibit it. Therefore, treating triglyceride levels in the blood could decrease central (and peripheral) resistance to leptin and reduce obesity and the cognitive problems associated with it [4,78,81]. This idea is also supported by Di Spiezio [77] who states that a deficit in the transport of leptin to the brain can increase the food reward. Furthermore, obese rodents have been shown to respond to the central administration of leptin through intracerebroventricular injections, but not to peripheral administration of leptin through intraperitoneal injections, which may be indicative of a possible impairment in transport through the BBB [68,81]. On the other hand, it has also been hypothesised that there is no deficit in the transport of leptin through the BBB. In this sense, it has been found that obese mice, as well as lean mice, retain a functional leptin transport system without leptin deficiency in the circumventricular organs, with the choroid plexus and the mediobasal hypothalamus playing a key role [67]. Another finding that supports the idea that there is no deficient transport of leptin through the BBB is that of the Bardet-Biedl Syndrome (BBS) mouse model, characterised by retinal dystrophy, polydactyly, renal and gonadal anomalies, cognitive impairment, and obesity, and, where proteins of an octameric complex, the “BBSome”, are mutated, leading to impaired transport of the leptin receptor LepRb to the plasma membrane in hypothalamic cells, thereby preventing intracellular signalling which causes resistance to leptin and obesity [82]. These contradictory results warrant further investigation in order to clarify the role of leptin transport through the BBB in leptin resistance. 5.2. Inflammation and Leptin Resistance It has been suggested that leptin resistance in obesity might start through the activation of inflammatory signalling [69]. It is generally accepted that, in obesity, hypertrophic adipocytes suffer an increase in proinflammatory cytokines expression and secretion that have periphery and brain effects [83,84]. Furthermore, several adipokines, and interleukins, in particular, are associated with the inflammatory processes implicated in dementia [6,83]. The production of interleukin 6 (IL-6), which is triggered by a lack of exercise and by saturated fat-rich diets, can lead to resistance to anorexigenic signals in the hypothalamus [52]. Low-grade inflammation due to obesity drives human C-reactive protein (CRP) production by hepatocytes in vitro and in vivo in humans [85]. It has been found that peripheral human CRP can reduce the amount of human leptin that enters the CNS, preventing its transport across the BBB and into the median eminence. Furthermore, once inside the CNS, it reduces the physiological function of human leptin [85]. So, both mechanisms may contribute to leptin resistance. Therefore, we can consider CRP a mechanism involved in inflammation-mediated leptin resistance. Inflammation causes central resistance to leptin through the expression of SOCS3. Thus, it has been found that SOCS3-stimulated adipocyte apoptosis worsens inflammation and inhibits the activity of the JAK2/STAT3 signalling pathway [86]. Many advances have been made through studies seeking to ameliorate obesity and hyperphagia produced by diets high in fatty acids. Interestingly, positive results in these studies have involved reduced inflammation and/or increased leptin sensitivity. As evidence of the above, it has been found that the peripheral delivery of the interleukin 10 (IL-10) gene using an adeno-associated virus (AAV) is capable of suppressing inflammation in the hypothalamus arcuate nucleus (ARC) in mice with diet-induced obesity (DIO) and decreasing hyperphagia and obesity [87]. Another study finds that proinflammatory cytokines in the brain increased Toll-like receptor 4 (TLR4) expression, ER stress, and nuclear factor kappa light chain enhancer of activated B cells (NF-kB) expression. Furthermore, this led to increased inflammation and leptin resistance, which was reduced by treatment with pyrogallol-phloroglucinol-6,6-bieckol (PPB) [84]. The central administration of docosahexaenoic acid (DHA, 22:6 n-3) reduced high-fat diet (HFD)-induced inflammation and obtained beneficial effects by inhibiting SOCS3 [88]. It has been found that the use of the plant terpenoid compound ginsenoside Rb1 reduces body weight gain, the accumulation of fat mass, and the expression of inflammatory markers, SOCS3 and PTP1B, in addition to reducing the deterioration of the signalling pathway JAK2-STAT3 and central leptin sensitivity due to obesity induced by high fatty acid diets [89,90]. Taken together, these studies suggest that neuroinflammation could cause leptin resistance, so acting on inflammation may be a way to reduce leptin resistance. In support of this, it is worth noting that a study related to inflammation and the signalling pathway of NF-KB mediated by sirtuins (SIRT) shows that its regulation can play an important role in neuroinflammation, as well as in local inflammation [91]. In addition, the NF-kB factor appears to play an important role in hypothalamic leptin resistance [92]. In summary, the data suggest that a HFD may reduce leptin sensitivity and that obesity may induce inflammatory processes. Furthermore, the studies and the scientific evidence presented seem to indicate that reducing inflammation can act on the pathways involved in leptin resistance, producing an improvement in leptin or its sensitivity [92] and obtaining favourable results on obesity. Likewise, SOCS-3 is hinted at as a mechanism mediating leptin resistance. 5.3. Hypothalamic Endoplasmic Reticulum Stress and Leptin Resistance Endoplasmic reticulum (ER) stress is currently being implicated as a mechanism that can lead to leptin resistance [93]. Thus, early exposure to stress has been found to alter factors in the adipose tissue and leptin system that led to increased body fat accumulation when exposed to a western diet later in life [5]. An aldehyde, 4-hydroxy-2-nonenal (4-HNE), may be involved in the development of leptin resistance in neuronal cells. Levels of this aldehyde can rise with fat accumulation which can initiate an ER stress response and further increase its production, and can then lead to impaired leptin signalling and obesity [94]. The elevated free fatty acid concentration in the hypothalamus can lead to lipotoxicity. Furthermore, a relationship between hypothalamic lipotoxicity and ER stress has been suggested as a possible explanation for the onset of obesity [95]. Alternatively, various compounds with the ability to decrease ER stress and/or ER stress-induced leptin resistance have been reported [93]. Notably, fluvoxamine has the ability to reduce ER stress through the sigma-1 receptor (Sig-1R) and its effect on reducing leptin resistance may be due to this mechanism. Celastrol, a chemical chaperone, ameliorates hypothalamic ER stress and obesity in mouse models. Chemical chaperones are compounds that have been suggested to diminish ER stress-induced leptin resistance. Flurbiprofen has also been found to improve ER stress-induced leptin resistance and HFD-induced obesity. Collectively, the above information allows us to affirm that certain compounds favour ER stress and increase leptin resistance while others decrease it and improve leptin resistance [93]. Therefore, future research should focus on investigating the pathways through which these compounds carry out their beneficial or detrimental effects. Lipotoxicity has been linked to ER stress and the downstream melanocortin system, in that the suppression of mitofusin2 (Mfn2) in proopiomelanocortin (POMC) neurons causes stress in the ER, thus altering the processing of melanocyte-stimulating hormone (α-MSH) and causing leptin resistance and obesity. Therefore, administration of the chemical chaperone 4-phenylbutyrate (4-PBA) was able to correct the tendency of the endogenous melanocortin 4 receptor (MC4R) to fold incorrectly and restore the correct response of α-MSH [95]. Sleep fragmentation has also been linked to hypothalamic ER stress. Specifically, the former induces the latter, leading to hyperphagia and leptin resistance. What is significant in this study is the observation of an increase in PTP1B expression and activity due to sleep fragmentation. The authors conclude that while sleep fragmentation seems to induce leptin resistance through PTP1B, high-calorie diets would induce it through SOCS3. However, this situation is reversed with a chemical chaperone treatment or with transgenic ablation of CHOP-/+ [96]. Therefore, the PTP1B and SOCS3 negative feedback pathways seem to affect leptin resistance; specifically, the PTP1B pathway would be affected by hypothalamic ER stress and the SOCS3 pathway would be affected by high-calorie diets. Finally, we can point out that ER stress induces leptin resistance. Furthermore, the POMC hypothalamic neurons of the arcuate nucleus are vulnerable to ER stress [95] and leptin exerts its effects through them. Therefore, we accept the implication of ER stress in leptin resistance, but it is possible that this is due to the interaction or combination of some of the different mechanisms which induce it. 5.4. Reduced Sensitivity to Leptin (Receptors, Receptor Downstream Signaling, and Negative Feedback Signaling Pathways) Certain intracellular factors such as SOCS3, PTP1B, and TCPTP negatively control leptin signalling and may be involved in leptin resistance [92]. Thus, the elimination or attenuation of SOCS3 expression produces beneficial effects on leptin sensitivity and resistance; however, its increased expression is detrimental [97,98,99,100]. Evidence has been given of mice with neuronal SOCS3 or PTP1B deficiency that have improved sensitivity to leptin and insulin, and are resistant to increases in body weight when exposed to high-fat diets [92]. Animal models with suppression or precise variations of SOSC3 have shown greater sensitivity to leptin, in addition to showing resistance to DIO, weight loss, and decreased food intake [68]. In a study using risperidone in the human neuroblastoma cell line (SH-SY5Y), the authors found increases in both SOSC3 and suppressor of cytokine signalling type 6 (SOCS6) proteins through the cyclic adenosine monophosphate/protein kinase A/ERK pathway (cAMP/PKA/ERK); the drug causes excessive weight gain due to inhibition of leptin and insulin signalling pathways [101]. In a fasting-induced hyperphagia assay, mice lacking the SOCS3 protein in LepR-expressing cells (LepR SOCS3KO) showed increased leptin sensitivity in the hypothalamus, and hyperleptinemia was also prevented [98]. Furthermore, one paper finds that leucine supplementation improves leptin sensitivity in HFD rats by promoting leptin signalling and downregulating SOCS3 expression [97]. An interesting assay involving the orexigenic hormone ghrelin shows a significant increase in exchange protein activated by cAMP (Epac) and SOCS3 in cultured rat nodose ganglia (NG) neurons that significantly inhibits the anorexigenic hormone leptin-induced STAT3 phosphorylation. From the study, the authors conclude that the SOCS3 signalling pathway plays a fundamental role in the inhibitory effect of ghrelin on leptin-induced STAT3 phosphorylation [100]. Other works conclude that the deregulation of SOCS3 expression and activity may be involved in leptin resistance by interrupting the negative feedback loop [70,99]. However, Pedroso et al. [99] indicate in their report that the mechanism involved in the inhibition of SOCS3 in LepRb-expressing cells could depend on specific neurons, finding that it cannot prevent diet-induced obesity. Therefore, we conclude that the alteration of the negative feedback pathway SOCS3 could somehow be involved in leptin resistance. Specific inhibitors for SOCS3 have not been developed [70], although they may be an option to restore the leptin response. A limitation in their development is the need to act specifically on the neuronal circuits involved in the regulation of body weight since its inhibition can cause serious alterations. Some suggested pharmacological strategies for SOCS3 inhibition are microRNA therapy and administration of zoledronic acid [102]. Inhibition has also been suggested with a specific strategy at the level of the leptin receptor pathway [70]. Furthermore, following a study in which it was discovered that the inhibition of the cell cycle checkpoint protein Ataxia Telangiectasia and RAD3-related protein (ATR) leads to a decrease in the expression of SOCS3, the use of ATR inhibitors in the development of new treatments for obesity may be useful [103]. Additionally, we will review some works that implicate the increased expression of the negative regulatory molecules PTP1B and TCPTP in leptin resistance. Thus, PTP1B has been linked to central leptin resistance in humans and in a variety of animal models of obesity and aging [4]. Similarly, in a study using the intranasal route of administration, suppression of PTP1B/TCPTP in the ARC was shown to restore downstream leptin responses. They also suggest that the combined deletion of PTP1B and TCPTP in the ARC of obese mice may produce synergistic effects that contribute to decreased food intake and weight loss. Conversely, in the aforementioned report, it is shown that the removal of SOCS-3 did not have an additional impact on body weight [104]. In another study, the authors found that hypothalamic suppression of PTP1B and LepRb failed to rescue hyperphagia or obesity in mice deficient in PTP1B and LepRb [Nkx2.1-LepRb(-/-)]. Thus, they suggest that functional leptin receptor signalling is in fact required for the metabolic effects of PTP1B. Likewise, they propose two models: the first where PTP1B deficiency exerts beneficial effects because of increased sensitivity to leptin, and a second model in which the consequences of PTP1B deficiency are achieved through the combination of different signalling pathways, where leptin plays a fundamental role [105]. Furthermore, we can suggest that additional signalling pathways in the brain may contribute to the metabolic effects produced by inhibiting PTP1B. Thus, another study shows that PTP1B overexpression reduces phosphorylation of the tropomyosin receptor kinase B (TrkB) receptor and the activation of downstream signalling pathways, while PTP1B inhibition increases TrkB signalling. Considering that TrKB implicates PTP1B in the regulation of central brain-derived neurotrophic factor (BDNF) signalling, the study suggested that the beneficial effects of PTP1B inhibition would be exerted by enhancing BDNF/TrkB signalling [106]. Yet another work studies the effects of Roux-en-Y gastric bypass (RYGB) in relation to the hypothalamic suppression of PTP1B. The results obtained therein show that leptin levels were elevated in obese rats and decreased after RYGB. In addition, the expression of the anorexigenic peptide POMC increased and that of the orexigenic peptide NPY decreased in RYGB rats. Furthermore, RYGB surgery decreases PTP1B expression and improves leptin sensitivity through its effects on the leptin signalling cascade [107]. The importance of this work must be highlighted since RYGB surgery is an effective treatment for obesity and the fact that it decreases the expression of PTP1B and produces an improvement in leptin sensitivity provides further support to the hypothesis. In another study, improvements in leptin and ghrelin levels were found after bariatric surgery which may involve multiple mechanisms, such as a reduction in inflammation and better glycemic control [108]. Elsewhere, research linking leptin to DIO has reported cases in which the elevated hypothalamic expression of PTP1B and TCPTP has been implicated in leptin resistance. Evidence on the subject has found that in POMC neurons, overexpression of the unfolded protein response transcription factor (Xbp1s) decreases the expression of PTP1B and SOCS3, improves leptin and insulin sensitivity, and protects against obesity. Furthermore, the combined deletion of PTP1B and TCPTP in neuronal and glial cells or POMC neurons results in an improvement in leptin sensitivity as well as a decrease in diet-induced obesity [109]. The evidence reviewed allows us to affirm that the inhibition of PTP1B and TCPTP positively affects resistance to hypothalamic leptin induced by different causes. Thus, academic and pharmaceutical research has pointed to PTP markers as therapeutic targets and has been implicated in the development of PTP1B and TCPTP inhibitors. Although the development of PTP1B and TCPTP inhibitors that target specific regions of the brain is a major challenge, current technological advances make it feasible. Thus, future research should seek a chemical molecule with better pharmacological properties and fewer side effects [109,110,111]. However, for an expansion on the subject and to learn about the variety of inhibitors developed, there are previous reviews [109,110]. Thus, a study that synthesised the compound ethyl-3-(hydroxymethyl)-4-oxo-1,4-dihydrocinnoline-6-carboxylate (PI-04) (a PTP1B inhibitor), shows that it improves the stimulating effect of leptin on the phosphorylation of the insulin receptor substrate 2 (IRS2) and of the transcription factor STAT3 [112]. Similarly, in another report using DIO mice, JTT-551, a novel inhibitor of PTP1B, is evaluated. The results of the study confirm an inhibitor-induced anti-obesity effect that enhanced leptin signalling [113]. Similarly, in a study evaluating the anti-diabetic and anti-obesity impact of the inhibitor 4-(biphenyl-4-ylmethylsulfanylmethyl)-N-(hexane-1-sulfonyl) benzoylamide (KY-226), it was found that oral administration of KY-226 decreased weight gain, food consumption, and fat volume gain, in addition to finding increases in phosphorylated STAT3 in the hypothalamus [114]. From what has been discussed so far, it can be concluded that the inhibition of PTP1B and TCPTP in the ARC, and even in other brain areas, could be effective in improving cellular leptin resistance. Furthermore, whether the effects of PTP1B/TCTPP inhibition in the hypothalamus are sufficient to increase leptin sensitivity independently or whether other signalling pathways are involved merits further investigation. On the other hand, it would be reasonable to focus research on the search for PTP inhibitors since there are more possibilities of obtaining an effective inhibitor of PTP1B than an inhibitor of SOSC3. In addition, as already pointed out, the deletion of PTP1B/TCPTP and SOCS3 does not produce synergy and actually, as a study of this literature shows, the elimination of SOCS3 does not imply an additional impact on the beneficial results obtained with the deletion of PTP1B and TCPTP. However, the research involving the SOCS3 pathway should not be abandoned, the implications of each protein in leptin resistance must be delimited. It has been proven that leptin receptor signalling pathways may be affected by different mechanisms to produce leptin resistance. In addition, more than one signalling pathway may be affected and their detrimental effects may be synergistic or interrelated. In turn, the discovery of new pathways or inhibitory mechanisms could bring about new advances in the field. In a recent study, a signalling pathway called NSAPP (NADPH oxidase-4, Superoxide dismutase, Aquaporin-3, PTEN) was found that could provide new information since it regulates the expression of neuropeptides such as POMC and agouti-related peptide (AgRP) which control appetite. Furthermore, it has been suggested that a defect in this pathway could explain the simultaneous resistance to the appetite-suppressing effects of leptin and insulin in obesity. Interference with this pathway in lean animals is also hypothesised to lead to overeating, positive caloric imbalance, and weight gain [58]. Similarly, additional research identifies a molecular signalling pathway linking the gastric inhibitory polypeptide receptor (GIPR) with overnutrition via EPAC/Ras-related protein 1 (Rap1) in the brain. Its authors found that central administration of gastric inhibitory polypeptide (GIP) decreased hypothalamic leptin sensitivity and increased hypothalamic SOCS3 levels, and GIPR deficiency protected against diet-induced leptin resistance [115]. Interestingly, in a study that administered pituitary adenylate cyclase-activating polypeptide (PACAP) to the ventromedial nucleus of the hypothalamus (VMN), it was observed that increased STAT3 phosphorylation and SOCS3 mRNA expression, effects that mimic those of leptin receptor activation, took place. Furthermore, BDNF mRNA expression in the VMN was increased by both leptin and PACAP administration, and a PACAP receptor antagonist reversed the effects of leptin in the VMN. Consequently, the authors suggest a common signalling pathway for both polypeptides [116]. The inducible inhibitor hexamethylene bis-acetamide inducible-1 (Hexim1) has also been shown to regulate the expression of transcription factors (SOCS3 and STAT3) in the hypothalamus, skeletal muscle, and adipocytes. These factors modulate obesity, and it is suggested that Hexim1 could play a central role in maintaining the energy balance of the whole body [117]. Other research suggests that the cAMP/PKA pathway plays an important physiological role in the modulation of LepRb signalling gain in the hypothalamus and this could lead to changes in adiposity. Thus, for the authors of the study, these results represent an opportunity to investigate new therapeutic strategies to increase leptin sensitivity through the cAMP and LepRb signalling pathways [118]. Finally, a recent study reports dysfunction in the Akt and phosphodiesterase 3 B (PDE3B)/cAMP pathways of leptin signalling in the hypothalamus that contribute to the development of central leptin resistance and DIO [119]. In summary, the decrease in the satiety signal of leptin in leptin resistance can occur due to the different mechanisms described or it may be caused by the ineffective result of a combination of these mechanisms. 6. Leptin Signalling, Obesity, and Alzheimer’s Disease There is a rare and genetically established form of Alzheimer’s disease (AD) and a sporadic form which is the most common in Alzheimer’s patients. In turn, there are genetic variants associated with an increased risk for Alzheimer’s disease. The best known is a variant of the gene encoding apolipoprotein E (APOE), the variant being APOE4 [120]. Furthermore, the disease is associated with the formation of extracellular β-amyloid (Aβ) plaques and the accumulation of hyperphosphorylated tau proteins in the brain. Mitochondrial dysfunction is a key process underlying AD pathology, where mitophagy (or selective degradation of mitochondria by autophagy) and autophagic pathways seem to be altered in this pathology [121]. Indeed, these processes, when inadequately regulated, contribute to synaptic dysfunctions and cognitive impairments through the accumulation of Aβ fibrils and hyperphosphorylated tau protein tangles. Moreover, the transcription factor EB (TFEB) has been described as a molecular target to treat neurodegenerative disorders such as AD, Parkinson’s disease, or Huntington’s disease. TFEB is a principal regulator of autophagy and lysosomal biogenesis pathways [122], the malfunction of which leads to neuronal death. Moreover, phytoconstituents have been proposed as potential therapeutic remedies to manage AD [123]. The same work indicates the use of nanocarrier systems, whose use led to the correct delivery of herbal medicaments to a specific target, although the use of phytoconstituents is limited due to their low solubility and metabolism. Additionally, compounds have been developed with therapeutic applications for the symptomatic effects of AD, such as oxidative stress and learning and memory [124,125]. These are the piperazine derivative biphenyl-3-oxo-1,2,4-triazine and benzoxazole derivatives which seem to act as cholinesterase inhibitors and have antioxidant properties, enhancing learning and memory. Similarly, in AD, there is not only synaptic dysfunction but also neuroinflammation and oxidative damage that affects episodic memory and leads to impaired cognitive functions which cause interference in patients’ lives [126,127]. Obesity is also a risk factor for dementia and Alzheimer’s disease. Given the relationship between obesity and dementia, some scientists are beginning to investigate a link with leptin. AD has been considered as a brain-type metabolic disorder [126,128,129] which requires a readjustment of homeostasisq and is influenced by inflammation, adipokines, adipocyte-derived hormones, and the various exposed mechanisms of leptin resistance. Thus, neuronal resistance to leptin is suggested in AD [130,131]. The link between obesity, leptin, and AD is now well established and has been extensively studied. Thus, different epidemiological studies have found an association between AD and changes in body weight. Some reports have found that obesity in midlife, as well as weight loss in old age, are related to cognitive decline and increased risk of developing AD [62,132,133,134]. Diets rich in saturated fatty acids have also been associated with an increased risk of AD in several animal and human studies [133] and several studies have found an association between a low body mass index (BMI) and AD in post-mortem brains [62,133]. Furthermore, it has also been suggested that WHR, but not BMI, was correlated with an increased risk of AD [132]. However, a study from the United Kingdom shows that the chance of developing AD is lower in obese middle-aged people but higher in middle-aged and older people of low weight [62,133]. In summary, although there is no unanimity across the studies, most of the evidence suggests that the increase in adiposity during middle age influences the risk of developing dementia, as well as its reduction in old age. So, as the disease develops before the appearance of cognitive symptoms, it is suggested that low weight in old age may be a manifestation of this early stage of the disease and a sign of premature brain dysfunction [62,133]. In support of this notion, low BMI has been found to be associated with the deterioration of AD pathology in postmortem brains, as well as the worsening of CSF biomarkers {tau and amyloid-β peptide form (Aβ1-42)} [62,133]. Interestingly, some models have been proposed to explain weight change at different stages of AD [62,133]. It has been shown that leptin is secreted by adipocytes and circulates in plasma in proportion to fat mass [48,63,130], and changes in body weight are associated with the possibility of developing AD. Therefore, it is not surprising that different investigations try to relate dysfunctional levels in leptin signalling with AD. Thus, in some studies, low plasma leptin levels in old age have been found to be associated with an increased risk of cognitive decline and AD development [62,134]. Similarly, the authors of one study show that plasma leptin levels are lower in subjects with mild cognitive impairment (MCI) or AD compared to control subjects and confirm a decrease in Aß42 and an increase in the tau protein related to MCI and AD. In addition, the same study suggests that plasma leptin deficiency could indicate a possible CNS leptin deficiency and thus serve as a diagnostic marker for MCI or AD [135]. Several studies also reported the same evidence in subjects with MCI or AD [4,62,136]. Not all studies have found an association between circulating leptin levels and AD or cognitive decline; one study finds no relationship between leptin levels and cognition, or disease severity in AD patients. Moreover, unlike other previous investigations that found positive correlations between leptin levels, BMI, body weight, and mean waist circumference, they also found no correlation between leptin levels and the aforementioned measures [137]. Similarly, another recent report finds that serum leptin levels were similar in young patients (mean 60 years) diagnosed with AD and vascular dementia, compared to healthy controls and patients with subjective memory complaints, and concluded that peripheral leptin levels do not play a role in the evolution of AD pathology [138]. Similarly, another current study reported no significant change in CSF leptin levels in AD compared to controls, at least in the early phases of AD progression during which the BBB remains intact [130]. These contradictory aspects have been explained by methodological differences or deficiencies and the complexity of leptin itself, although a non-linear U-shaped relationship has also been proposed, as we mentioned previously [64]. On the other hand, evidence suggests that leptin is involved in memory impairments that occur in hippocampal-dependent AD. Thus, leptin treatment improves performance on hippocampal-dependent memory tasks in SAMP8 mice that have elevated Aβ levels [66] and prevents the detrimental effects of Aβ on LTP and LTD in the hippocampus, as well as on AMPA receptor trafficking, and inhibits Aβ-induced up-regulation of endophilin 1 expression. In addition, there is evidence indicating that toxic Aβ levels decrease with leptin treatment. Thus, the authors suggest a dysfunction of the leptin signalling cascade involved in Aβ actions at hippocampal synapses [59,66]. In view of this evidence, a relationship between leptin and AD can be assumed in which very high levels of leptin, probably due to leptin resistance, as well as low leptin levels are associated with a higher risk of AD. It seems that the leptin detected in the brain comes from the periphery [130]. Therefore, analysing the transport of leptin through the BBB and its integrity is essential to understanding the levels of leptin and its signalling in the brain. Although the BBB has been shown to be compromised in AD brains, it appears that such impairment may occur late in the disease [130]. Thus, a study that analysed whether leptin levels change as the subject progresses towards AD found no differences in these leptin levels in the CSF in the early stages of AD progression, nor did it detect changes in the CSF albumin/serum albumin ratio, reflecting the integrity of the BBB. For the authors of the study, these results suggest that leptin levels are intact, but leptin signalling is altered in AD [130]. We can conclude that the integrity of the BBB may be affected in the advanced phase of the disease and there seems to be a serious disconnection in the leptin signalling pathway in AD. In fact, a central resistance to leptin is mentioned in AD by detecting reductions in some signalling pathways that are activated downstream of leptin receptors [130]. It has been detected that the expression of the leptin receptor is altered in AD. Thus, in one study, it was found that the expression level of LepRb mRNA was lower in hippocampal tissue with AD compared to controls. Similarly, this study suggests a possible blockade induced by neurofibrillary tangles (NFT) to the accessibility of LepRb; thus, the leptin receptor is sequestered in regions with high concentrations of NFT which causes it to lose its signalling capacity. The lack of signalling results in the interpretation that there are inadequate circulating leptin levels, leading to increased leptin secretion and leptin resistance in these affected neurons [131]. Similarly, in another study with young and old mutant mice expressing APPSWE (Tg2576), a reduction in leptin was detected in neurons compared to those of control animals and young Tg2576 mice have also been found to have enhanced expression of LepRb, which is not seen in old Tg2576 mice. Therefore, a dysfunction in leptin signalling is suggested [130]. We might say that age is an important risk factor for dementia and specifically for AD. Similarly, diet, lifestyle, and stress also influence the development of dementia and low weight in old age and obesity in middle age are predisposing factors. Furthermore, the data analysed suggest that obesity in midlife and the elevated leptin levels seen in the obese lead to leptin resistance in the brain, which also predisposes to AD. Subsequently, before the manifestations of the disease, obesity-induced systemic inflammation will lead to neurodegeneration, which increases with age, where leptin signalling pathways are affected, altering their function. Therefore, inflammation is involved in neurodegeneration, and it is present in the pathophysiology of AD. The peptide β-amyloid (Aβ) has been observed to influence the function of adipose tissue. Thus, it has been found that the fragment of the β-amyloid peptide (Aβ25-35) through protein kinase A (PKA) and ERK 1/2 dependent signalling pathways, can cause an increased release of free fatty acids and proinflammatory adipokines that can produce lipotoxicity in other organs [139]. Likewise, a high sucrose diet (HSD) fed to male APPswe/PS1dE9 (APP/PS1) transgenic mice induced an increase in neuroinflammation, as well as an increase in cortical and serum levels of β-amyloid. This work demonstrates that a HSD increases AD-related pathologies and reduces hypothalamic leptin signalling in APP/PS1 mice [140]. Similarly, a study investigating amyloid β-secretase (BACE1)-dependent processing in relation to leptin resistance demonstrates the need for functional leptin signalling and shows that reducing BACE1 activity is found to restore leptin sensitivity, normalise hypothalamic inflammation, and reduce PTP1B and SOCS3 [141]. However, it seems that Aβ and tau cannot fully explain the pathology of AD. Thus, a study has found a decrease in STAT5B and SOCS(1-3) in the brains of transgenic mice (APP/PS1) at 3 months of age. These results demonstrate a significant impairment in adipokine receptor signalling pathways in the hippocampus of APP/PS1 mice at a young age, before Aβ plaque formation [128]. Similarly, in another study using high-fat diet (HFD)-treated (APP/PS1) transgenic mice, leptin failed to suppress the food intake of HFD APP/PS1 transgenic mice, suggesting impaired signalling of leptin in the hypothalamus, but hyperphagia and aggravated obesity were caused before the presence of amyloid pathology [142]. As mentioned in the previous section, protein tyrosine phosphatase 1B (PTP1B) is another mechanism involved in leptin resistance and works by modulating signalling pathways related to learning and memory, endoplasmic reticulum (ER) stress, and microglia-mediated neuroinflammation [143]. Therefore, the effects of its inhibition merit further investigation. On the other hand, leptin, through its signalling pathways, can modify beta-amyloid peptide (Aβ) levels by blocking β-secretase activity and increasing ApoE-dependent amyloid beta uptake; it can also enhance Aβ peptide clearance by promoting its clearance and degradation [137]. Furthermore, leptin inactivates glycogen synthase kinase 3 β (GSK3β), the protein primarily responsible for tau hyperphosphorylation [127,132]. Adenosine monophosphate protein kinase (AMPK)/sirtuin1(SIRT1)-activated pathways appear to mediate the reduction of β-secretase activity by leptin, and AMPK, Akt protein, and p38 protein pathways mediate the reduction of tau phosphorylation by leptin [62]. So, LepRb, expressed in the hippocampus, triggers leptin signalling via Janus Kinase 2 (JAK2), which, in turn, phosphorylates three tyrosine residues in the LepRb intracellular domain (Tyr985, Tyr1077, and Tyr1138). Tyr1138 mediates the activation of STAT3 [144]. STAT3 is a transcription factor that, phosphorylated by JAK2, dimerises, and is translocated to the nucleus, where it controls the transcription of specific genes, within which is the suppressor of cytokine signalling 3 (SOCS3), a negative regulator of LepRb intracellular signalling [145,146]. The phosphorylation in Tyr1077 induces STAT5 activation [147]. Phosphorylated Tyr985 recruits the SH2-containing tyrosine phosphatase-2 (SHP-2) to mediate the activation of the MAPK pathway (extracellular signal-regulated kinase or ERK) [144,148]. Activated JAK2 can initiate the PI3K/Akt signalling pathway through the phosphorylation of IRS protein [144] which leads to the mammalian target of rapamycin (mTOR) activation, which influences the synthesis and aggregation of Tau, compromising microtubule stability when mTOR is inactivated [149]. Moreover, the PI3K/Akt signalling pathway can also inactivate glycogen synthase kinase 3 β (GSK3β), which, in turn, is unable to phosphorylate the Tau protein [150,151], thereby unfavouring the Tau aggregation characteristic of AD. Another key downstream effector of LepRb includes AMP-activated protein kinase (AMPK), which is phosphorylated by JAK2 [152]. AMPK may, in turn, induce a decrease in tau phosphorylation and β-amyloid accumulation [153]. These effects are PGC-1α-mediated, which is a coactivator of peroxisome proliferator-activating receptor γ (PPARγ), a transcriptional activator of target genes, regulating the transcription of BACE1, which is reciprocally regulated with respect to PGC-1α expression [154]. BACE1 is a key enzyme involved in Aβ generation, the hallmark harmful peptide of AD. A reduction in the activity and expression levels of BACE1, with a decreased production of Aβ after leptin stimulation, has been described [155]. Conversely, leptin signalling can be reduced by contra-regulatory mediators, such as SOCS3 and protein tyrosine phosphatase 1B (PTP1B). After leptin binding to its LepRb receptor, SOCS3 interferes with LepRb/JAK2 signalling [145], whereas PTP1B has the ability to dephosphorylate JAK2 [156]. Research has shown that mRNA, SOCS3, and PTP1B, are up-regulated in the hippocampus of an animal model of AD [157], suggesting that they may generate leptin resistance. (Figure 1). In summary, it can be said that LepRb signalling pathways seem to be clearly involved in AD. We can postulate that obesity in midlife increases the risk of AD by promoting systemic inflammation and leptin resistance, which leads to brain neurodegeneration. Subsequently, neurodegeneration worsens, creating a vicious cycle that leads to AD pathology where inflammation and oxidative stress become important factors in its development and progression [126]. 7. Conclusions Because obesity is a risk factor for AD and other dementias [4,6,50,52], effective markers should be determined in order to prevent adverse effects, as well as begin comprehensive programs for prevention. Indeed, AD and obesity share common metabolic characteristics. Thus, adipokines, secreted by adipose tissue, communicate with the CNS, playing a role in the progression of AD and other dementias [6]; among them, leptin [4] has neuroprotective effects at the level of CNS [63,65]. Properly identifying the alterations in the signalling pathways triggered by leptin and its receptor, LepRb, is necessary in AD in order to reverse the dysfunction of these pathways and consequently improve the prognosis of AD. In fact, different mechanisms of leptin resistance have been described, among which are those carried out by SOCS3, PTP1B, and TCPTP, where SOCS3 and PTP1B have an altered expression level in an animal model of AD [157], disrupting leptin signalling. Thus, research should be aimed at the design of inhibitors or related mechanisms to reduce this resistance to leptin. In fact, the design of inhibitors against protein tyrosine phosphatases is possible [104], and the use of ATR inhibitors to reduce SOCS3 expression has also been suggested [103]. CNS inflammation or neuroinflammation is an important factor in the development and progression of neurodegenerative diseases [29,30,31], such as AD, PD, or HD, and inflammation can affect leptin-triggered signalling, leading to leptin resistance [158]. Thus, the use of anti-inflammatory drugs combined with those that reduce leptin resistance could be useful. Author Contributions J.A.F.-C. and A.F.-B. wrote the draft, A.P.-P. and G.A. revised the references and text. C.J.-C. made the picture and revised the manuscript, V.S.-M. carried out conceptualization, coordination and revision of 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 Leptin signalling in a hippocampal neuron. Leptin, mainly released by adipose tissue, reaches a hippocampal neuron where, binding to LepRb, activates the JAK/STAT, PI3K/Akt, and AMPK signalling pathways. PI3K/Akt pathway activation leads to mTOR activation, influencing synthesis and aggregation of Tau, as well as GSK-3β inactivation, which, in turn, is not able to hyperphosphorylate Tau. AMPK pathway activation leads to PGC-1α and PPAR activation, which, translocated to the nucleus, inhibit BACE1 transcription and decrease Aβ production. SOCS3 and PTP1B are negative regulators of leptin signalling acting on JAK2 and, therefore, generate leptin resistance that may cause the worsening of AD. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Bradfield N.I. Ames D. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092407 jcm-11-02407 Article Corneal Confocal Microscopy Features and Tear Molecular Profile in Study Participants with Discordance between Ocular Surface Disease Clinical Signs and Discomfort D’Souza Sharon 1 Shetty Rohit 1 Nair Archana Padmanabhan 23 Agrawal Ruchika 2 https://orcid.org/0000-0001-9545-343X Dickman Mor M. 45 Khamar Pooja 1 Nuijts Rudy M. M. A. 4 https://orcid.org/0000-0002-6570-5891 Ghosh Arkasubhra 2* Sethu Swaminathan 2* Misra Stuti Academic Editor Alam Uazman Academic Editor Petropoulos Ioannis N. Academic Editor Colorado Luisa H. Academic Editor 1 Department of Cornea and Refractive Surgery, Narayana Nethralaya, Bangalore 560010, India; drsharondsouza@gmail.com (S.D.); drrohitshetty@yahoo.com (R.S.); dr.poojakhamar@gmail.com (P.K.) 2 GROW Research Laboratory, Narayana Nethralaya Foundation, Bangalore 560099, India; archana.nair@narayananethralaya.com (A.P.N.); ruchika.agrawal@narayananethralaya.com (R.A.) 3 Manipal Academy of Higher Education, Manipal 576104, India 4 University Eye Clinic Maastricht, Maastricht University Medical Center, 6200 MD Maastricht, The Netherlands; mor.dickman@mumc.nl (M.M.D.); rudy.nuijts@mumc.nl (R.M.M.A.N.) 5 MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, 6200 MD Maastricht, The Netherlands * Correspondence: arkasubhra@narayananethralaya.com (A.G.); swaminathansethu@narayananethralaya.com (S.S.); Tel.: +91-80-6666-0712 (A.G. & S.S.) 25 4 2022 5 2022 11 9 240702 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/). Various ocular surface conditions such as dry eye disease can present with severe discomfort and pain. However, it is clinically challenging to establish etiology and prescribe correct treatment in patients who have a lot of discordance between symptoms and signs. To understand the basis of such discordance, we stratified subjects with ocular surface pain based on concordance between the severity of signs and symptoms and evaluated corneal structural features and tear molecular factors. All subjects underwent slit lamp examination, dry eye evaluation, and ocular surface disease index (OSDI) scoring. Subjects were stratified into group 1—without symptoms or clinical signs; group 2—without symptoms but with signs; group 3—with similar severity of symptoms and signs; and group 4—with symptom severity greater than that of the signs. Laser scanning in vivo confocal microscopy (IVCM) and tear fluid analysis for soluble factors by multiplex ELISA was performed for all subjects. Patients with a higher grade of symptoms and signs showed increased corneal dendritic cell (cDC) density (p < 0.05) which was more pronounced in subjects with discordance between the symptoms and signs (group 4). A significantly higher proportion of microneuroma-like structures and cDC were observed in group 4. IL-17A levels were significantly elevated in the tears of subjects with more discomfort. Our results demonstrate that corneal IVCM and the measurement of tear film factors can help clinicians improve diagnosis and treatment choice. Stratifying patients with ocular surface discomfort on the basis of discordance between symptoms and clinical signs may help identify patients who need additional adjunctive targeted therapy to resolve their condition. ocular surface pain in vivo confocal microscopy corneal dendritic cells microneuromas dry eye disease tear film ==== Body pmc1. Introduction Ocular pain and discomfort are common presenting symptoms for patients visiting the outpatient clinic and can significantly deteriorate a patient’s quality of life and their activities of daily living [1,2]. Infections, inflammation, and raised intraocular pressure are some common aetiologies of ocular pain in general, while conditions such as dry eye disease (DED), corneal infections, or injury are often related to ocular surface pain [3]. Structural factors such as the dense innervation of the cornea as well as the immune, inflammatory, and neural interconnections of the ocular surface have an important role to play in ocular surface pain [3,4]. In some cases, the pain may be disproportionately higher than the clinical signs, thereby complicating the diagnosis and making management challenging [5]. Exaggerated ocular surface pain can be secondary to inflammation, increased nociception, neuropathy, or a combination of these factors that may co-exist with various ocular surface conditions. Nociceptive pain usually occurs due to an alteration in a non-neural tissue resulting in an increase in nociceptive molecular factors [1], whereas neuropathic corneal pain (NCP) is secondary to the involvement of the somatosensory nervous system [6]. However, significant overlap between these entities can occur [7]. It is important to identify nociceptive and neuropathic aspects of pain so as to treat them appropriately [8]. Neuropathic cases can have symptoms of pain and discomfort despite a complete absence of clinically visible ocular surface abnormalities [9,10]. Overlap between conditions and this discordance between signs and symptoms are major challenges in treating these patients even in those with an established diagnosis [11,12,13]. In addition, many patients have an assumed diagnosis of DED, and do not respond to therapy as expected. These patients are often treated with multiple different topical and systemic medications with suboptimal relief and may also get referred to the pain management clinic or for a psychological assessment [14]. A possible reason for this exaggerated pain response without significant clinical features may be subclinical inflammation [15,16], which may involve the corneal nerves leading to complaints of pain, discomfort, and a burning sensation secondary to polymodal nociceptor and thermoreceptor activation [17,18]. Additional tests such as laser scanning in vivo confocal microscopy (IVCM) and tear molecular analysis can help identify these hidden causes for pain. IVCM is an excellent tool to assess both inflammation and nerve abnormalities by assessing the density and morphology of corneal dendritic cells (cDC) and the alterations in the corneal nerve structures that are known to be associated with ocular surface pain [19,20]. Chronic dry eye and ocular surface inflammation can also have recalcitrant symptomatology even with an established diagnosis due to changes in corneal nerves structure and function resulting in NCP [21]. Therefore, evaluating patients with poor correlation between symptoms and signs would aid in stratifying treatment. As disparity between symptoms and signs is an important feature of NCP, we have used this as the main criteria to divide patients into four groups. We therefore evaluated the corneal IVCM feature changes (cDC, sub-basal nerve plexus features—SBNP, and microneuroma-like structures) and tear molecular factors. We have then analysed the variations between these groups to identify specific subgroup characteristics that would help treatment. 2. Materials and Methods 2.1. Study Cohort, Clinical Examination, and Study Groups This cross-sectional study has received approval of the Narayana Nethralaya Institutional ethics board. Subject recruitment, clinical information, and sample collection procedures were conducted in accordance with the tenets of the Declaration of Helsinki. Written informed consent was obtained from each subject prior to inclusion in the study. A total of 145 subjects (287 eyes) were included in the study with 115 patients (229 eyes) having the primary symptom of ocular surface pain or discomfort referred to the Cornea Clinic of Narayana Nethralaya, located in Bangalore, India, and 30 control subjects (58 eyes) with no symptoms of ocular pain or discomfort and no clinically visible ocular abnormality on examination. Patients were evaluated for possible causes for ocular discomfort using a detailed clinical history, including history of systemic illness and ocular examination. Visual acuity assessment, refraction, detailed slit-lamp examination including ocular surface evaluation for signs of inflammation and eyelid and meibomian gland assessment, and fundus evaluation were performed to exclude other ocular comorbidities. Exclusion criteria included the use of contact lenses, ocular infection in the last six months, uveitis, ocular trauma, history of any ocular surgery including refractive surgery, cicatrizing disease, lid abnormalities and those on topical steroids and topical anti-inflammatory or immunomodulatory medication including cyclosporine A in the last 3 months. As there are many possible causes for ocular surface pain, a detailed assessment is required to arrive at the possible underlying diagnosis and plan the appropriate management [22]. The presenting symptom of pain or discomfort was assessed using the ocular surface disease index (OSDI) questionnaire (Allergan, Dublin, Ireland) [23,24], and the severity graded based on the standard scores as follows: normal < 12; mild 13–22; moderate 23–32; and severe > 32 [25]. As DED is one the most common causes for ocular surface pain [8] and referral to the cornea clinic, detailed ocular surface and dry eye evaluation was done. Dry eye evaluation included Schirmer’s test without anaesthesia, tear film breakup time (TBUT), and corneal and conjunctival fluorescein staining. Using sterile Schirmer’s strips (Contacare Ophthalmics and Diagnostics, Vadodara, Gujarat, India), the Schirmer’s test was performed. TBUT and ocular surface staining were performed using fluorescein strips (Contacare Ophthalmics and Diagnostics). Clinical tests such as the ocular surface staining with fluorescein and other dyes give us an insight into the health of the ocular surface. Tear film break up time assesses the tear film stability and the Schirmer’s test measures the tear secretion rate. Subjects were divided into those without DED or having mild, moderate, and severe DED based on the Schirmer’s and/or TBUT values as per standard guidelines from the TFOS DEWSII (Tear Film & Ocular Surface Society Dry eye workshop II) [26,27]. Further, DED patients have been classified as per TFOS DEWII into two predominant categories, i.e., aqueous deficient dry eye disease (ADED) or evaporative dry eye disease (EDED) based on the Schirmer’s test I value and TBUT. Subjects with TBUT < 10 s but with a Schirmer’s test I value > 10 mm/5 min were grouped as EDED. Subjects with a Schirmer’s test I value < 10 mm/5 min were classified as ADED. Grade of tear film instability assessed by TBUT are as follows: normal ≥ 10 s, mild 7–9 s, moderate 5–7 s, and severe < 5 s. Grade of tear fluid secretion status based on Schirmer’s test I metrics are as follows: normal ≥ 10 mm/5 min, mild 7–9 mm/5 min, moderate 5–7 mm/5 min, and severe < 5 mm/5 min. To determine additional factors that may contribute to the ocular surface pain, the study participants were grouped based on the disparity between the severity of their symptoms and signs irrespective of their dry eye status, as described in discomfort concordance to signs (DCS) grouping (Figure 1). Group 1 (D-S-)-presumed normal or control subjects no discomfort D- (OSDI score: <12) and no clinical signs S- (TBUT: ≥10 s, Schirmer’s test: ≥10 mm/5 min, no ocular surface abnormality). Group 2 (D-S+) includes subjects without discomfort D- (OSDI score: normal < 12) but with signs S+ (TBUT: <10 s and/or Schirmer’s test: <10 mm/5 min and/or ocular surface staining). Group 3 (D+S+) includes subjects with similar grades of discomfort D+ and signs S+ as per the standard gradings discussed previously such as moderate symptoms on OSDI and moderate severity of signs on DED evaluation. Group 4 (D++S+/-) includes subjects with disparate symptoms and signs, having symptom grade very high D++ and signs low or absent S+/-. IVCM parameters (cDC density, sub-basal nerve plexus morphologic characteristics, and microneuroma-like structures) and tear fluid soluble factor levels were studied across all 4 groups. 2.2. In Vivo Confocal Microscopy (IVCM) Imaging IVCM is a non-invasive imaging modality that can study the corneal microscopic structure, nerves, and cDC density and morphology [28,29]. IVCM was performed using the Rostock Corneal Module/Heidelberg Retina Tomograph ll (RCM/HRT ll; Heidelberg Engineering GmBH, Dossenheim, Germany). Proparacaine drops (0.5%) were instilled prior to the procedure to anaesthetize the ocular surface. The captured ICVM images that passed image quality control were used for analysis. cDC were identified based on their morphology and categorized into mature and immature [30] as shown in Figure 2a–c. cDC density (cDCD) expressed in cells/mm2 was quantified using Cell Count software (Heidelberg Engineering GmbH) [31,32]. Sub-basal nerve plexus (SNBP) features (Figure 2d–f) in the study subjects were also determined as previously described [32]. Corneal nerve fibre area (CNFA) per square millimetre, corneal nerve fibre length (CNFL) in millimetres per square millimetre, corneal nerve fibre density (CNFD) per square millimetre, corneal nerve fibre width (CNFW) per square millimetre, corneal nerve branch density (CNBD) per square millimetre, and total branch density (CTBD) per square millimetre were analysed in IVCM images using Automatic CCMetrics software, version 1.0 (University of Manchester, Manchester, UK) [31,32]. Microneuroma-like structures in the nerve plexus were identified (Figure 2g,h) as described in existing literature [1,33,34,35]. 2.3. Tear Fluid Collection Tear fluid samples were collected from the study subjects using Schirmer’s strips as per standard protocol [36] and stored in 1.5 mL microcentrifuge tubes at −80 °C until further processing. On the day of analysis, the tear fluid was extracted from Schirmer’s strips by agitation in 300 µL sterile 1× PBS for 2 h at 4 °C. The tear fluid proteins were eluted by centrifugation and immediately used for the downstream experiment as mentioned in Section 2.4 to measure the various soluble factors by multiplex ELISA. 2.4. Soluble Factors Level Measurement The concentration of secreted factors in the tear fluid that was measured include Interleukin (IL)-1α, IL-1 β, IL-2, IL-6, IL-8, IL-10, IL-17A, IFNγ (Interferon gamma), MCP1/CCL2 (Monocyte chemoattractant protein 1), RANTES/CCL5 (Regulated upon Activation, Normal T cell Expressed), sICAM1 (soluble Intercellular adhesion molecule 1), and TNFα (Tumor necrosis factor alpha and VEGF-A (Vascular endothelial growth factor—A). The levels of these secreted factors in the tears were measured by multiplex ELISA using cytometric bead array (BD Biosciences, San Jose, CA, USA) on a flow cytometer (BD FACSCantoII, BD Biosciences, San Jose, CA, USA) [36]. BD FACSDiva software (BD Biosciences, San Jose, CA, USA) was used to acquire the bead–antibody conjugate–analyte complexes and record their signal intensities. FCAP array version 3.0 (BD Biosciences, San Jose, CA, USA) was used to determine absolute concentration of the analytes using respective standards. The wetting length of the Schirmer’s strip noted during tear collection and tear protein elution buffer volume were used for calculation of the dilution factor to derive the normalized concentration values of tear analytes. 2.5. Statistical Analyses The normality of data was assessed by the Shapiro–Wilk normality test. The Kruskal–Wallis test with Dunn’s multiple comparison test and the Mann–Whitney test were used to analyse the differences in the variable between the study groups in the datasets. Statistical analyses were performed with GraphPad Prism 6.0 (GraphPad Software, Inc., La Jolla, CA, USA). p < 0.05 was considered statistically significant. 3. Results 3.1. Ocular Surface Clinical Parameters, IVCM Features, and Tear Soluble Factors in Different Groups Patients were divided into the four groups based on the parameters discussed previously. Group 1 (D-S-): n = 58 eyes; Group 2 (D-S+): n = 28 eyes; Group 3 (D+S+): n = 127 eyes; and Group 4 (D++S+/-): n = 74 eyes. The age distribution of subjects in the various groups are as follows: median (range)—D-S-, 32.5 (25–73) years; D-S+, 31 (26–54) years; D+S+, 38 (22–72) years, and D++S+/-, 36 (20–65) years. The sex distribution of subjects in the various groups are as follows: D-S-—M/F 16/14; D-S+—M/F 4/10; D+S+—M/F 32/32; and D++S+/-—M/F 18/9. Patients in the D+S+ (group 3) and D++S+/- (group 4) had a significantly higher symptom grade compared to both the D-S- (group 1) and D-S+ (group 2) (Figure 3a). The tear break up time (TBUT) and the Schirmer’s test values were significantly lower in D+S+ and D++S+/- compared to the normal D-S- group (Figure 3b,c). The TBUT and Schirmer’s test values were significantly worse in the D+S+ even though the symptoms were worst in the D++S+/- group (Figure 3b,c), which suggests that some patients in the highly symptomatic D++S+/- group could have only mild or no DED. A total of 201 out of 229 eyes had varying grades of DED. Ocular surface staining was noted in 13.8% of all eyes included in the study (35/287 eyes) of which most had varying grades of DED. Additional signs of ocular surface inflammation such as congestion or staining were also noted. The density of total, immature, and mature forms of cDC were significantly higher in the D+S+(group 3) and D++S+/- (group 4) group compared to the D-S- (normal) group 1 (Figure 4a–c). No significant difference in the cDC density was observed between the D+S+ group 3 and D++S+/- group 4 (Figure 4a–c). A high proportion of microneuroma-like features were seen in group 3 D+S+ and group 4 D++S+/- groups, with a significant increase in the proportion of microneuroma-like structures observed in the disparity group D++S+/- group (Group 4) compared to other groups (Figure 5). No significant difference in the various corneal sub-basal nerve plexus morphological parameters was observed between the groups (Figure 4d–i). Among the various tear fluid soluble factors (cytokines, chemokines, soluble cell adhesion molecules, and growth factors) measures, the level of IL-17A was observed to be significantly higher in subjects in group 3 D+S+ and group 4 D++S+/- group compared to the normal D-S- group 1 (Figure 6f). A higher level of IL-17A was observed in the D++S+/- group 4 compared to the D+S+ group 3 (Figure 6f). A significantly lower level of VEGF-A was observed in the D+S+ group 3 compared to the D-S- group 1 (Figure 6l). 3.2. Ocular Surface Clinical Parameters, IVCM Features, and Tear Soluble Factors in Subjects with High Ocular Surface Discomfort but no Clinical Signs (D++S-) The OSDI scores were significantly higher in D++S- compared to D-S- (control) groups. (Figure 7a). The TBUT and Schirmer’s test values were within the normal range (Figure 7b,c). The density of total, immature, and mature forms of cDC were significantly higher in D++S- compared to the control D-S- group (Figure 8a). The corneal nerve fibre density was observed to be significantly higher in D++S- compared to D-S- (Figure 8c). No other significant difference in the various corneal sub-basal nerve plexus morphological parameters was observed between the groups (Figure 8b,d–g). The proportion of subjects and eyes with microneuroma-like structures were significantly higher in the D++S- group 4 compared to the D-S- (Figure 9). It is to be noted that the VEGF-A level was markedly lower (p = 0.07) in D++S- compared to D-S- groups (Table 1). However, no significant differences in the tear soluble factors were observed between D++S- compared to D-S- groups (Table 1). 3.3. Ocular Surface Clinical Parameters, IVCM Features and Tear Soluble Factors in Subjects with DED (Evaporative or Aqueous Deficient) The age distribution of subjects in the various groups are as follows: median (range)—controls 32.5 (25–73) years, evaporative dry eye disease—EDED 35.5 (20–65) years, and aqueous deficient dry eye disease—ADED 46 (23–72) years. The sex distribution of subjects in the various groups are as follows: controls—M/F 16/14, EDED—M/F, 35/39, and ADED—M/F 13/11. The OSDI scores were significantly higher in both EDED and ADED subjects compared to the controls, and the OSDI score in ADED was significantly higher compared to EDED as well (Figure 10a). The TBUT and Schirmer’s test values were significantly lower in EDED and ADED subjects compared to the controls (Figure 10b,c). The density of total, immature, and mature forms of cDC were significantly higher in both EDED and ADED compared to the controls (Figure 11a–c). The density of the total and immature forms of cDC were significantly higher in ADED compared to EDED (Figure 11a,b). No significant difference in the sub-basal nerve plexus parameters in DED compared to the controls was found (Supplementary Figure S1). However, the proportion of subjects and eyes with microneuroma-like structures in corneal nerves were significantly higher in DED compared to the controls (Supplementary Figure S2). The levels of IL-6, IL-17A, RANTES, and MCP1 were significantly higher and VEGF-A significantly lower in EDED and/or ADED compared to the controls (Table 2). 4. Discussion Our understanding of acute and chronic ocular surface discomfort and pain continues to evolve. In patients who have a clinically attributable and comparable symptoms, the treatment is more straight forward and directed at the underlying aetiology. However, at the cornea clinic, we observe a large number of patients who have a disparity between clinical signs and symptoms where the severity of the symptoms cannot be explained by clinically visible signs. This can be due to an underlying nociceptive and neuropathic pain component [35]. Neuropathic corneal pain may not have clinically evident signs and has been classically referred to as “pain without stain” [12]. Thus, the pathophysiology of such exaggerated discomfort could be related to ocular surface inflammation, altered nociception, or neuropathy [1,37]. The perception of pain on the ocular surface is likely an interplay between the structural, epithelial, neuronal, molecular, and immune cell changes in the eye and neuronal connections to higher centres in the thalamus and somatosensory cortex [38,39]. Structurally, as the cornea has the highest nerve density in the body, it is particularly sensitive to alterations in the local molecular factors and environmental influences [40]. The status of features such as the cDC density, the sub-basal nerve plexus, microneuroma-like structures, and tear fluid factors needs to be characterized comprehensively in subjects with discordant signs and symptoms. The current study addresses this knowledge gap by objectively stratifying patients based on the discordance between the severity of ocular surface signs and symptoms and determining how cornea-specific features vary within groups. DED status, and ocular surface clinical status and discomfort (OSDI) scores for each patient were evaluated. The chronicity of the pain and the patient’s description of the discomfort or pain were also taken into consideration [14]. When evaluating the severity of symptoms across the groups we found that the OSDI score was significantly higher in D+S+ (group 3) and D++S+/- (group 4) as compared to D-S- (group 1, normal) subjects. The cause for the increased pain in this group of patients could be due to the inflammation, altered nociception, or neuropathy. Chronic DED and the associated inflammation are common causes for increased nociception or NCP. The clinical signs were most significantly altered in the D+S+ group 3 (where the severity of symptoms and signs are proportionate). In the D++S+/- group 4, where symptoms are out of proportion to signs, the alteration to DED clinical parameters were relatively less severe. These findings also corroborate those seen in other studies that state that increased nociception and NCP can be associated with different ocular and systemic conditions [41,42]. This reiterates the hypothesis that there may be additional factors driving the discomfort in this discordant group, hence we analysed IVCM and tear molecular factors across the cohort. We found a significant increase in cDC density in D+S+ group 3 and D++S+/- group 4 compared to normal D-S-. The highest cDC density was seen in the D++S+/- group, thereby implying that the cDC density correlates positively with the patient’s discomfort. This finding is supported by previous studies that reported an association of cDC density with increased inflammation and discomfort [36,43]. The cDC may proliferate within a tissue and secrete a variety of inflammatory factors that can raise the overall nociceptive response [44]. Corneal sub-basal nerve fibre features have been studied in ocular surface conditions including DED with varied observations [45]. A significant increase in cDC density has been reported in a metanalysis on IVCM features similar to the observations made in the current study [46]. However, this meta-analysis reports conflicting observations with reference to corneal nerve features between different studies. Though corneal nerve feature-related changes such as increased tortuosity, beading, looping, and decreased nerve fibre density, etc., have been reported in various studies using IVCM [22,43], we did not find a significant difference across these nerve parameters assessed in the SBNP across the groups of our cohort. Possible ethnicity variation and measurement strategies (manual versus algorithm based) could contribute to differences in observations. Microneuroma-like structures, which are terminal enlargements of nerve endings with variable shape and hyperreflectivity [47], can be observed in the sub-basal nerve plexus or stroma of the cornea [35,43]. We found a significantly higher frequency of microneuroma-like structures among the subjects in the highly symptomatic D++S+/- (group 4) compared to the other groups in our study. In subjects with the classic presentation of “pain without stain” consistent with NCP, the IVCM analysis revealed a higher proportion of microneuroma-like structures, similar to previous reports [34,35]. Our cohort also had a few asymptomatic subjects who were found to have microneuroma-like structures in their sub-basal nerve plexus, contrary to previous reports that did not show this feature in normal subjects [35]. This suggests that even though the microneuroma-like structures are strongly associated with NCP, the patient symptoms may be dependent on an interplay between inflammatory, structural, and neuronal components. In addition to their role in modulating inflammation on the ocular surface, the dysregulation of certain molecular factors can have nociceptive potential as well. We have previously demonstrated that an altered balance between the pro- and anti-nociceptive tear soluble factors can contribute to the increased symptomatology in DED [36]. It has been shown that the ocular neurosensory pathway has various structural and molecular components and dysregulation of any of these can result in corneal hyperalgesia [48]. Inflammatory factors can sensitize thermoreceptors and mechano-nociceptors and reduce the threshold to pain stimuli [49]. Receptors of IL-17A, have been shown to be expressed by nociceptor neurons and, hence, play a role in pain perception by the altered expression of TRPV4 channels [50]. We found IL-17A, a pro-nociceptive factor, significantly increased in the D+S+ and D++S+/- groups, with much higher levels in the latter. VEGF-A, in addition to being an angiogenic factor, also has anti-nociceptive potential [51,52]. In our study we found that the levels of anti-nociceptive factor VEGF-A were reduced in the D+S+ group, suggesting a tip in balance towards increased pro-nociception in these groups. The increased symptomatology in these groups could be due to this altered balance between pro- and anti-nociceptive factors on the ocular surface. It is pertinent that multicentric studies across different ethnicities and larger cohort be conducted to validate our findings to provide a clinically actionable algorithm that uses these patient specific corneal features for stratifying patients with ocular surface pain. Treatment targeted at improving the nociceptive balance could help improve patient symptoms and long-term comfort [34]. Currently, the treatment options for patients presenting with discordant signs versus symptoms are limited to the following: (a) artificial tear supplements along with anti-inflammatory agents such as topical steroids, (b) nonsteroidal medications such as cyclosporine A and tacrolimus, and (c) biologicals such as Anakinra (human IL-1 receptor antagonist). Further, autologous serum eye drops have also been shown to have a positive effect in some cases as they contain multiple factors such as nerve growth factor (NGF) and epidermal growth factor (EGF) that support nerve growth and epithelial health. In patients who have a central component of pain, systemic medications such as tricyclic antidepressants (e.g., amitriptyline, nortriptyline), anticonvulsants (e.g., Gabapentin, carbamazepine), and serotonin uptake inhibitors (e.g., Duloxetine and venlafaxine) may help relieve symptoms [34]. 5. Conclusions The assessment of ocular pain based on questionnaires and correlating it to clinical metrics and confocal features such as cDC density and microneuroma-like structures can help clinicians better classify the condition and aid in customized treatment planning. The discordance between patient reported ocular surface pain/discomfort and clinical signs is associated with enhanced cDC, presence of microneuroma-like structures imaged by IVCM, as well as increased IL-17A (Figure 12). This study highlights the importance of scoring the disparity in symptoms and signs and IVCM as important clinical tools to stratify patients for targeted treatment. Acknowledgments We thank members of IBMS and the Cornea department for help during the study. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm11092407/s1, Figure S1: Sub-basal nerve plexus features profile in subjects with dry eye disease; Figure S2: Frequency of microneuroma-like structures in subjects with dry eye disease. Click here for additional data file. Author Contributions Conceptualization, S.D., R.S., A.G. and S.S.; methodology, S.D., A.G. and S.S.; clinical data acquisition, S.D., R.S. and P.K.; laboratory investigation, A.P.N. and R.A.; resources, R.S., A.G. and S.S.; data curation, S.D. and S.S.; writing—original draft preparation, S.D. and S.S.; writing—review and editing, S.D., M.M.D., R.M.M.A.N., A.G. and S.S.; supervision, A.G. and S.S.; project administration, R.S., A.G. and S.S.; funding acquisition, R.S., A.G. and S.S. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by Narayana Nethralaya Foundation, Bangalore, India (NNF Cornea Grant to A.G and R.S.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of manuscript. Institutional Review Board Statement This cross-sectional study was approved by the Narayana Nethralaya Institutional ethics committee (EC Ref. No: C/2021/07/02). Subject recruitment and sample collection procedures were conducted in accordance with the tenets of the Declaration of Helsinki. Informed Consent Statement Written informed consent was obtained from all subjects prior to inclusion in the study. Data Availability Statement Data is available upon request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Discomfort concordance to signs (DCS) grouping. Schematic representation of the various groups under which the study subjects were categorized based on the concordance between the status of discomfort/symptoms (D) and signs (S). Group 1 (D-S-) include subjects without discomfort/symptoms (OSDI score: <12) and no clinical signs (TBUT: ≥10 s, Schirmer’s test: ≥10 mm/5 min), hence, presumed as normal or control subjects. Group 2 (D-S+) include subjects without discomfort/symptoms (OSDI score: <12) but present with signs (TBUT: <10 s and/or Schirmer’s test: < 10 mm/5 min). Group 3 (D+S+) include subjects with similar grades of discomfort/symptoms and signs. Group 4 (D++S+/-) included subjects in whom the discomfort/symptom grade is higher than the grade/severity of signs. OSDI severity scale (Normal < 12; Mild, 13–23; Moderate, 24–32; Severe > 32). TBUT severity scale (Normal ≥ 10 s; Mild 7–9 s; Moderate 5–7 s; Severe < 5 s). Schirmer’s test severity scale (Normal ≥ 10 mm/5 min; Mild 7–9 mm/5 min; Moderate 5–7 mm/5 min; Severe < 5 mm/5 min). Figure 2 Corneal dendritic cells, microneuroma-like structures, and sub-basal nerve plexus in cornea of study participants. Panels are representative in vivo confocal microscope images showing (a–c) corneal dendritic cells, (d–f) corneal sub-basal nerve plexus and (g,h) microneuroma-like structure indicated within the yellow circle. Immature forms of dendritic cells are shown with blue arrows in (b). Mature forms of dendritic cells are indicated with yellow arrows in (c). The blue and red lines shown in (f) indicates CC metrics software detection of the nerves to determine the various morphological parameters. Figure 3 Ocular surface disease index score, Tear break up time, and Schirmer’s test values in subjects categorized based on discomfort concordance to signs (DCS) grouping strategy. Bar graphs represent (a) Ocular surface disease index (OSDI) scores indicative of the discomfort/symptoms, (b) Tear break up time (TBUT) values in secs—indicative of sign and (c) Schirmer’s test (ST1) values in mm/5 min—indicative of sign in the study subjects grouped in the various categories based on DCS grouping strategy. Group 1 (D-S-): n = 58 eyes; Group 2 (D-S+): n = 28 eyes; Group 3 (D+S+): n = 127 eyes; Group 4 (D++S+/-): n = 74 eyes. * p < 0.05, ** p < 0.01, **** p < 0.0001. Kruskal–Wallis test with Dunn’s multiple comparisons test was performed. Age (D-S-, median (range) 32.5 (25–73) yrs; D-S+, 31 (26–54) yrs; D+S+, 38 (22–72) yrs, and D++S+/-, 36 (20–65) yrs). Sex distribution (D-S-, M/F 16/14; D-S+, M/F 4/10; D+S+, M/F 32/32, and D++S+/-, M/F 18/9). Figure 4 Corneal dendritic cell density and sub-basal nerve plexus features profile in subjects categorized based on discomfort concordance to signs (DCS) grouping strategy. Bar graphs represent (a) total corneal dendritic cell density (cDCD), (b) density of immature forms of corneal dendritic cells, (c) density of mature forms of corneal dendritic cells, (d) corneal nerve fibre area—CNFA, (e) corneal nerve fibre density—CNFD, (f) corneal nerve fibre length—CNFL, (g) corneal nerve fibre width—CNFW, (h) corneal nerve branch density—CNBD and (i) corneal total branch density—CTBD determined using laser scanning in vivo confocal microscopic images in the study subjects grouped in the various categories based on DCS grouping strategy. The number of eyes analysed for corneal dendritic cell density are as follows: Group 1 (D-S-): n = 58 eyes; Group 2 (D-S+): n = 28 eyes; Group 3 (D+S+): n = 127 eyes; Group 4 (D++S+/-): n = 74 eyes. The number of eyes analysed for sub-basal nerve plexus features are as follows: Group 1 (D-S-): n = 27 eyes; Group 2 (D-S+): n = 17 eyes; Group 3 (D+S+): n = 98 eyes; Group 4 (D++S+/-): n = 55 eyes. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, Kruskal–Wallis test with Dunn’s multiple comparisons test was performed. Figure 5 Frequency of microneuroma-like structures in subjects categorized based on discomfort concordance to signs (DCS) grouping strategy. Stacked bar graphs represent (a) percentage of patients with and without microneuroma-like structures determined in laser scanning in vivo confocal microscopy images in the different groups. The adjacent table provides the absolute number of patients with and without microneuroma-like structures in the different groups. (b) percentage of eyes with and without microneuroma-like structures determined in laser scanning in vivo confocal microscopy images in the different groups. The adjacent table provides the absolute number of eyes with and without microneuroma-like structures in the different groups. Chi-square test was performed to determine the statistical significance of the difference in the frequency of microneuroma-like structures between the groups. p < 0.05 is considered to be statistically significant. MN—microneuroma-like structures. Figure 6 Tear fluid secreted factors level in subjects categorized based on discomfort concordance to signs (DCS) grouping strategy. Bar graphs represent the tear fluid levels of (a) IL-1α, (b) IL-1β, (c) IL-6, (d) IL-8, (e) IL-10, (f) IL-17A, (g) IFNγ, (h) MCP1, (i) RANTES, (j) sICAM1, (k) TNFα, and (l) VEGF-A in the study subjects grouped in the various categories based on DCS grouping strategy. IL—Interleukin, IFNγ—Interferon gamma, MCP1/CCL2—Monocyte chemoattractant protein 1, RANTES/CCL5—Regulated upon Activation, Normal T cell Expressed, and Secreted, sICAM1—soluble Intercellular adhesion molecule 1, TNFα—Tumor necrosis factor alpha, and VEGF-A—Vascular endothelial growth factor—A. pg/mL—picogram per millilitre. Group 1 (D-S-): n = 28 eyes; Group 2 (D-S+): n = 11 eyes; Group 3 (D+S+): n = 35 eyes; and Group 4 (D++S+/-): n = 16 eyes. * p < 0.05, ** p < 0.01, Kruskal–Wallis test with Dunn’s multiple comparisons test was performed. Figure 7 Ocular surface disease index score, Tear break up time, and Schirmer’s test values in subjects with discomfort but no signs. Bar graphs represent (a) Ocular surface disease index (OSDI) scores indicative of the discomfort/symptoms, (b) Tear break up time (TBUT) values in secs—indicative of sign and (c) Schirmer’s test (ST1) values in mm/5 min—indicative of sign in the study subjects. D-S- indicates subjects without discomfort/symptoms and signs (n = 58 eyes) and D+S- indicates subjects with discomfort/symptoms but no signs (n = 28 eyes). * p < 0.05, **** p < 0.0001, Mann–Whitney Test was performed. Age (D-S-, median (range) 32.5 (25–73) yrs and D+S-, 30 (20–57) yrs). Sex distribution (D-S-, M/F 16/14 and D+S-, M/F 4/10). Figure 8 Corneal dendritic cell density and sub-basal nerve plexus feature profile in subjects with discomfort but no signs. Bar graphs represent (a) profile of total, immature and mature forms of corneal dendritic cell density (cDCD), (b) corneal nerve fibre area—CNFA, (c) corneal nerve fibre density—CNFD, (d) corneal nerve fibre length—CNFL, (e) corneal nerve fibre width—CNFW, (f) corneal nerve branch density—CNBD, and (g) corneal total branch density—CTBD determined in laser scanning in vivo confocal microscopy images in the study subjects. D-S- indicates subjects without discomfort/symptoms and signs and D+S- indicates subjects with discomfort/symptoms but no signs. (a): D+S-, n = 58 eyes and D+S-, n = 28 eyes. *** p < 0.001, **** p < 0.0001, Mann–Whitney Test. (b–g): D+S-, n = 29 eyes and D+S-, n = 19 eyes. * p < 0.05, Mann–Whitney Test was performed. Figure 9 Frequency of microneuroma-like structures in subjects with discomfort but no signs. Stacked bar graphs represent (a) percentage of patients with and without microneuroma-like structures determined in laser scanning in vivo confocal microscopy images in the different groups. The adjacent table provides the absolute number of patients with and without microneuroma-like structures in the different groups. (b) percentage of eyes with and without microneuroma-like structures determined in laser scanning in vivo confocal microscopy images in the different groups. The adjacent table provides the absolute number of eyes with and without microneuroma-like structures in the different groups. D-S- indicates subjects without discomfort/symptoms and signs and D+S- indicates subjects with discomfort/symptoms but no signs. Chi-square test was performed to determine the statistical significance of the difference in the frequency of microneuroma-like structures between the groups. p < 0.05 is considered to be statistically significant. MN—microneuroma-like structures. Figure 10 Ocular surface disease index score, Tear break up time, and Schirmer’s test values in subjects with dry eye disease. Bar graphs represent (a) Ocular surface disease index (OSDI) scores indicative of the discomfort/symptoms, (b) Tear break up time (TBUT) values in secs—indicative of sign and (c) Schirmer’s test (ST1) values in mm/5 min—indicative of sign in controls and in subjects with evaporative dry eye disease (EDED) or aqueous deficient dry eye disease (ADED). Controls are subjects without discomfort/symptoms and signs (D-S-). Controls (Ctrls): n = 58 eyes; EDED: n = 147 eyes; ADED: n = 48 eyes. *** p < 0.001, **** p < 0.0001, Kruskal–Wallis test with Dunn’s multiple comparisons test was performed. Age (controls, median (range) 32.5 (25–73) yrs, EDED, 35.5 (20–65) yrs, and ADED, 46 (23–72) yrs). Sex distribution (controls, M/F 16/14, EDED, M/F, 35/39, and ADED, M/F 13/11). Figure 11 Corneal dendritic cell density in subjects with dry eye disease. Bar graphs represent (a) total corneal dendritic cell density (cDCD), (b) density of immature forms of corneal dendritic cells and (c) density of mature forms of corneal dendritic cells, determined using laser scanning in vivo confocal microscopic images in controls and in subjects with evaporative dry eye disease (EDED) or aqueous deficient dry eye disease (ADED). Controls are subjects without discomfort/symptoms and signs (D-S-). The number of eyes analysed for corneal dendritic cell density are as follows: Controls (Ctrls): n = 52 eyes; EDED: n = 144 eyes; ADED: n = 48 eyes. The number of eyes analysed for sub-basal nerve plexus features are as follows: Controls (Ctrls): n = 29 eyes; EDED: n = 114 eyes; ADED: n = 32 eyes. * p < 0.05, ** p < 0.01, *** p < 0.01, **** p < 0.0001, Kruskal–Wallis test with Dunn’s multiple comparisons test was performed. Figure 12 Schematic representation of signs, symptoms, confocal microscopy features, and tear fluid factors in in subjects categorized based on discomfort concordance to signs (DCS), grouping strategy, and dry eye disease types. (a) Line graph representation indicate the patterns (based on statistically significant observations) in ocular surface disease index (OSDI) score, tear break up time (TBUT), Schirmer’s test (ST1), corneal dendritic cell (DCs) density, sub-basal nerve plex (SBNP) features, microneuroma-like structures (microneuroma), and tear fluid factors across the different categories based on DCS grouping strategy as described in Figure 1. (b) Line graph representation indicate the patterns (based on statistically significant observations) in ocular surface disease index (OSDI) score, tear break up time (TBUT), Schirmer’s test (ST1), corneal dendritic cell (DCs) density, sub-basal nerve plex (SBNP) features, microneuroma-like structures (microneuroma), and tear fluid factors in subjects with discomfort but no signs. D-S- indicates subjects without discomfort/symptoms and signs and D+S- indicates subjects with discomfort/symptoms but no signs. (c) Line graph representation indicates the patterns (based on statistically significant observations) in ocular surface disease index (OSDI) score, tear break up time (TBUT), Schirmer’s test (ST1), corneal dendritic cell (DCs) density, sub-basal nerve plex (SBNP) features, microneuroma-like structures (microneuroma), and tear fluid factors in controls and in subjects with evaporative dry eye disease (EDED) or aqueous deficient dry eye disease (ADED). Controls are subjects without discomfort/symptoms and signs (D-S-). jcm-11-02407-t001_Table 1 Table 1 Tear fluid secreted factors levels in subjects with discomfort but no signs. D-S- D+S- p Value Mean SD SEM Mean SD SEM IL-1⍺ 44 45 8 38 41 15 0.601 IL-1β 5.9 11.5 2.2 7.3 11.9 4.2 0.522 IL-6 0.0 0.0 0.0 0.0 0.0 0.0 1.000 IL-8 272 281 53 247 178 63 0.950 IL-10 0.2 0.3 0.1 0.3 0.5 0.2 0.830 IL-17A 1.2 2.3 0.4 64.3 176.5 62.4 0.250 IL-17F 74 236 45 76 195 69 0.929 TNF-⍺ 0.5 0.9 0.2 0.7 1.1 0.4 0.865 IFN-γ 2.7 6.1 1.1 117.3 324.7 114.8 0.504 RANTES 102 131 25 48 58 21 0.196 MCP-1 300 290 55 320 202 72 0.672 VEGF-A 1275 822 155 794 829 293 0.075 ICAM-1 2793 2710 512 1449 759 268 0.305 D-S- (subjects without discomfort/symptoms and without signs—OSDI score: <12, TBUT ≥ 10 s, Schirmer’s test 1: ≥10 mm/5 min); D+S- (subjects with discomfort/symptoms and without signs—OSDI score: >12, TBUT ≥ 10 s, Schirmer’s test 1: ≥10 mm/5 min); SD—standard deviation; SEM—standard error mean; D-S- (n = 28 eyes); D+S- (n = 8 eyes); p < 0.05 is statistically significant, Mann–Whitney Test. jcm-11-02407-t002_Table 2 Table 2 Tear fluid secreted factors levels in healthy subjects and in patients with evaporative or aqueous deficient dry eye disease. Analytes (pg/mL) Controls EDED ADED p Value Mean SD SEM Mean SD SEM Mean SD SEM Ctrls vs. EDED Ctrls vs. ADED EDED vs. ADED IL-1⍺ 44 45 8 33 42 6 29 13 5 0.095 0.789 0.474 IL-1β 6 12 2 4 6 1 7 8 3 0.254 0.208 0.421 IL-6 0 0 0 6 22 3 42 68 28 0.022 <0.0001 0.499 IL-8 272 281 53 287 199 30 632 806 329 0.395 0.092 0.209 IL-10 0 0 0 0 0 0 0 0 0 0.217 0.997 0.507 IL-17A 1 2 0 9 17 2 3 2 1 0.003 <0.0001 0.583 IL-17F 74 236 45 62 195 29 0 0 0 0.713 0.440 0.583 TNF-⍺ 0 1 0 1 1 0 1 1 0 0.480 0.441 0.447 IFN-γ 3 6 1 9 21 3 0 0 0 0.427 0.228 0.113 RANTES 102 131 25 188 483 72 381 242 99 0.812 0.002 0.013 MCP-1 300 290 55 166 232 35 261 340 139 0.008 0.388 0.704 VEGF-A 1275 822 155 971 1303 194 446 326 133 0.009 0.008 0.663 ICAM-1 2793 2710 512 2526 4162 620 2610 1238 505 0.220 0.713 0.254 Controls: n = 28 eyes; EDED (Evaporative dry eye disease): n = 45 eyes; ADED (Aqueous deficient dry eye disease): n = 6 eyes; SD—standard deviation; SEM—standard error mean; p < 0.05 is statistically significant, Mann–Whitney Test. 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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093282 materials-15-03282 Article Experimental Mechanical Properties and Numerical Simulation of C80 Concrete with Different Contents of Stone Powder Wu Hongmei 12 Liu Kai 12 Yang Fang 3 https://orcid.org/0000-0001-7422-5956 Shen Bo 12* Ma Kejian 12 Zhang Jiyang 12 Liu Bo 12 Li Ning Academic Editor 1 Space Structures Research Center, Guizhou University, Guiyang 550025, China; whm2019@foxmail.com (H.W.); lkyl.lbq@foxmail.com (K.L.); makejian@gzu.edu.cn (K.M.); zjy.str@foxmail.com (J.Z.); sranokada_liu@foxmail.com (B.L.) 2 Key Laboratory of Structure Engineering of Guizhou Province, Guiyang 550025, China 3 College of Mining and Civil Engineering, Liupanshui Normal University, Liupanshui 553004, China; fh628909@163.com * Correspondence: bshen@gzu.edu.cn 03 5 2022 5 2022 15 9 328225 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/). In this paper, we show the influence of stone powder content on the mechanical properties of concrete by experiments and numerical simulations. In numerical simulation, this paper proposed a method whereby the stone powder in the numerical simulation of concrete is considered by the mechanical performances of mortar with the stone powder. The results of numerical models established based on inclusion theory and random aggregate distribution were basically consistent with the experiment, which indicated that the simulation method of concrete under different stone powder was feasible. In the range of stone powder content from 0% to 15%, the model based on inclusion theory is very close to the experimental results, and the model based on 2D random aggregate distribution is closer to the experimental value once the stone powder content is 7%. The research showed that with increased stone powder, cubic compressive strength had greater dispersion between the simulation and the experiment; axial compressive and split tensile strength reached the best levels at 5%. The best stone powder content was 5% for C80 high-strength concrete by comprehensively considering concrete’s consistency and its mechanical properties. stone powder content rock sand inclusion theory random aggregate distribution Science and Technology Support Plan Project (Social Development Breakthrough) of Guizhou ProvinceQian Ke He SY [2012] 3067 Natural Science Research Project of Guizhou Province Department of Education[2015] 364 Natural Science Foundation of Guizhou Province[2018] 1038 Introduction of Talents Research Program of Guizhou University[2016] 16 This research was funded by four grants from the Science and Technology Support Plan Project (Social Development Breakthrough) of Guizhou Province under contract no. Qian Ke He SY [2012] 3067, the Natural Science Research Project of Guizhou Province Department of Education under contract no. [2015] 364, the Natural Science Foundation of Guizhou Province under contract no. [2018] 1038, and the Introduction of Talents Research Program of Guizhou University under contract no. [2016] 16. ==== Body pmc1. Introduction With the development of the building material researches, high-performance and ultra-high-performance concrete are widely used in construction engineering, and some admixtures are added to the concrete to improve the strength [1]. Furthermore, these are also considered in order to reduce carbon dioxide emissions and economic costs. Based on this situation, many scholars have begun to replace cement with other materials to arrive at this goal [2,3]. This paper studied the effect of stone powder content on concrete strength, hoping to reduce costs by removing the manufacturing processes of washing the stone powder in rock sand. Guizhou Province, China has a typical karst topography in which carbonate rocks are widely distributed. Due to the special geographic environment and the scarce resources of river sand, machine-made rock sand can be used as a building material by removing soil and crushing and screening rocks [4]. According to Local Code DB24/016-2010 [2], in Guizhou, the stone powder content of rock sand in concrete with strength grades C30–C45 and C50–C55 should not exceed 10% and 7%, respectively. With the development of the economy, concrete with a strength grade higher than C60 is mostly used, for which there are stringent restrictions on the content of stone powder in rock sand, although there are no clear limitations in Local Code DB24/016-2010 [5,6]. Therefore, it is important to research the limits of stone powder content in concrete with a strength grade higher than C60. This paper uses the methods of experimentation and numerical simulation to study the influence of varying stone powder contents on the mechanical properties of machine-made C80 rock sand concrete, so as to obtain the best content and provide reference data for engineering applications. At present, the influence of stone powder content on the mechanical properties of concrete is mainly based on experimental methods. Belebchouche et al. [7], Chajec [8], and Abbasi et al. [9] researched the mechanical properties of concrete with crushed glass, granite powder, and silica stone, respectively. Demirhan et al. [10], Wang et al. [11], Diab et al. [12], and Liu et al. [13] studied the influence of different stone powder contents on the flowability and compressive strength of concrete; they found that both flowability and compressive strength decreased with increased stone powder content, but flowability was greater in concrete without stone powder. The best content was 7% for the compressive strength of C60 concrete. Chen et al. [14] studied the mechanical properties of C80 rock sand concrete and found that with increased stone powder content, the elastic modulus of the concrete had a downward trend. When the content exceeded the limit of 3% to 5%, the compressive strength of concrete below C60 declined with increased stone powder content [15,16,17,18]. The stone powder content of low-strength concrete should be 10–15%, and that of high-strength concrete should not be as high [19]. The addition of stone powder reduces the permeability of river sand concrete, but has little effect on the compressive strength [20]. Yang et al. [21] added rock chips to river sand to determine their influence on C80 concrete and found that the early age strength of high-strength rock chip concrete was higher than that of river sand concrete, whereas the long-term strength exhibited contrary results. Campos et al. [22] used stone powder and silica fume to replace Portland cement, which could decrease CO2 emissions, and all of the low-cement HSC they studied presented high workability. Yang et al. [23] researched the influence of different contents of basalt and limestone powders on ultra-high-performance concrete (UHPC) and found that incorporating quarry stone powder significantly improved the flowability. The artificial intelligence and machine learning techniques are also capable of modeling the mechanical behavior of concrete. Nafees et al. [24] used machine learning techniques to build the concrete models. The nonlinearity of concrete structure calculations is undergoing extensive development. Sucharda et al. [25] indicated that the choice of parameters, the characteristics of the material, and the randomness of the model all have an important influence on nonlinear analyses. They conducted a nonlinear analysis of RC beams without shear reinforcement by studying the sensitivity of concrete material properties. Golafshani and Behnood [26] used a multi-objective ANN approach to predict the mechanical properties of concrete. Valikhani et al. [27] used constitutive relationships in a material model and determined the parameters in ATENA software, and proposed an experimental and numerical procedure to characterize the interface characteristics of concrete and their influence on the bonding strength between two materials. Karimipour et al. [28] researched the strength of concrete with different powders by experiment and numerical prediction. With regard to mesoscopic scale concrete, scholars have proposed many models, such as lattice [29,30,31], MH meso-mechanics [32,33,34], random particle [35,36,37,38], random aggregate [39,40,41,42], and random mechanical characteristic [43,44,45] models. The random aggregate model has commonly been used. Liu and Wang [46], Wang et al. [47], and Kwan et al. [48] assumed that concrete is a three-phase composite material composed of a cement mortar matrix, aggregate inclusions, and the bonding interface between the two, which defines the random aggregate model. In this model, the number of aggregates needs to be determined according to the Walraven formulation of the two-dimensional aggregate gradation curve, converted into the Fuller aggregate gradation curve [49], and then the aggregate is randomly entered into the model by the Monte Carlo method. The random aggregate model is different from other models because it can characterize the spatial random distribution of aggregate granules in concrete. Hu et al. [40] established a 2D random aggregate distribution model of expanded polystyrene concrete to study damage and failure modes with different aggregate contents. Bao et al. [41] studied the influence of the shape and content of coarse aggregate on the carbonization depth of concrete through a 2D random aggregate model. The development of concrete cracks was studied by establishing a 2D random aggregate model by Zhang et al. [42]. Wriggers and Moftah [39] established a 3D random aggregate model to study the failure behavior of concrete. Chen et al. [50] established 2D and 3D random aggregate models to simulate the basic performance of asphalt mixtures. Most scholars have adopted experimental methods to research the mechanical properties of concrete with different stone powder contents. This paper proposes a method to simulate the influence of these mechanical properties. We mixed different contents of stone powder into mortar for testing and obtained the basic performance of the mortar to demonstrate the influence of stone powder, so as to determine the influence on the mechanical properties of concrete with different stone powder contents. These data were used in model 1, based on inclusion theory, in which concrete is regarded as a composite material of mortar and coarse aggregate wrapped in an interface, and model 2, the random aggregate model, in which concrete is considered as a composite material of mortar, coarse aggregate, and interface transition zones (ITZs). Comparing the results of model 1, model 2, and experimental values, the best stone powder content of C80 concrete was 5%. Both simulation methods can effectively simulate the impact of different stone powder contents on the mechanical properties of concrete. This paper proposes a new method to simulate the influence of stone powder content on the mechanical properties of concrete and uses the inclusion model and random aggregate distribution model to verify the feasibility of the method through comparison with experimental values. 2. Materials and Methods In this section, we introduce the raw materials and experimental methods used in the experiment and analyze the results, including cubic compressive strength, axial compressive strength, elasticity modulus, split tensile strength, and flexural strength of concrete. The flowchart is shown in Figure 1. 2.1. Raw Materials Conch brand P·O 42.5 cement (Conch Cement Co., Ltd., Qingzhen, China) was used in the test, and the main properties are shown in Table 1, which are tested by Chinese code GB 175-2007 [51]. The fine and coarse aggregates were limestone, both from the same area, and the additional stone powder was 200 mesh heavy calcium powder from Guizhou; the particle size distribution curves (by Mastersizer 3000—Laser Diffraction Particle Size Analyzer sourced from Spectris Instruments & Systems Shanghai Branch 1, Shanghai, China) of them are shown in Figure 2. An optimal mix ratio of C80 concrete was obtained by orthogonal tests, considering the influence of three factors and three levels: water–cement ratio (0.23, 0.25, 0.27), sand ratio (0.39, 0.41, 0.43), and mineral admixture (slag powder + fly ash + silica fume at 15% + 15% + 8%, 20% + 10% + 8%, and 25% + 5% + 8%, respectively). The water-reducing admixture is a high-performance polycarboxylate water reducer produced by Beijing Huashi Company (Beijing, China), with a water-reducing rate of more than 28%. Through the actual trial mix, the dosage of it is 1.2%, and the indicators of admixture are shown in Table 2 and Table 3. The main chemical compositions of the powders by XRF-1800 (X-Ray Fluorescence Spectrometer sourced from SHIMADZU, Shimadzu, Japan) are shown in Table 4, and the raw materials are shown in Figure 3. They were verified through experiments, and the best combinations were a water–cement ratio of 0.25, sand ratio of 0.41, and slag powder, fly ash, and silica fume in proportions of 20%, 10%, and 8% of the total cementitious material, respectively. The specific mix ratio is shown in group S0 in Table 5, where S stands for stone powder and the number represents the percentage of stone powder in the weight of rock sand; for example, S3 indicates that the stone powder content is 3% of the weight of rock sand. The mechanical parameters of cement mortar and concrete were measured by Chinese Codes JGJ/T 70-2009 (compressive strength of mortar is in its Section 9, and elastic modulus of mortar is in its Section 16) [52] and GB/T 50081-2019 (compressive strength of concrete is in Section 5, axial compressive strength of concrete is in its Section 6, and elastic modulus of concrete is in its Section 7) [53]. 2.2. Test Method The cubic and axial compressive, split tensile, flexural strength and elastic modulus of concrete (loading schematic and physical diagrams shown in Figure 4a,b, Figure 5a,b, Figure 6a,b and Figure 7a,b), and the axial compressive and split tensile strength and elastic modulus of mortar were tested in this study. The cubic compressive and split tensile strength tests of concrete used the same specimen size of 100 mm × 100 mm × 100 mm, the loading instrument was the same universal testing machine (3000 KN universal testing machine sourced from Ji’Nan Mts Testing Technology Co., Ltd., Jinan, China), and the loading speed was 1.0 and 0.1 MPa/s, respectively. A three-point bending experiment was conducted to test the flexural strength of concrete with a size of 100 mm × 100 mm × 400 mm, the load–deflection curves were collected by the instrument RMT-301 (Rock mechanics test system sourced from Wuhan Zhongke Kechuang Engineering Inspection Co., Ltd., Wuhan, China) automatically, and the loading speed was 0.002 mm/s. The specimen size for axial compressive strength and elastic modulus tests of concrete was 100 mm × 100 mm × 300 mm, and the loading instrument and speed were the same as in the flexural strength test. The specimen size of mortar was 70.7 mm × 70.7 mm × 220 mm, the loading instrument was the RMT-301, and the loading speed was 0.002 mm/s. The mechanical experiments were carried out on concrete and mortar with 0%, 3%, 5%, 7%, 10%, and 15% stone powder content. Before starting the experiment, we pre-loaded the equipment, rechecked the operating status of each instrument, and ensured that the instrument was running smoothly. 2.3. Establishment of Numerical Model This section introduces the inclusion and random aggregate models and describes the theory of the two models, the modeling steps, and the parameter selection and settings. The 2D model was finally selected for numerical simulation by comparing the random aggregate model in 2D and 3D models under compression conditions. 2.3.1. Numerical Model Based on Inclusion Theory (Model 1) In this model, inclusion theory, homogenization of two-phase composite materials, and a progressive damage model were used to simulate the mechanical properties of concrete, as in Sun et al. [54,55]. Concrete is regarded as a composite material in which cement mortar is used as the matrix, and the coarse aggregate wrapped in the interface is used as the inclusion phase. The inclusion phase wrapped by the interface adopts the double-inclusion model shown in Figure 8. The relationship between macroscopic strain ε¯ and stress σ¯ can be transformed into that between mean strain 〈ε〉 and stress 〈σ〉 on the representative volume element (RVE), with ε¯=〈ε〉 and σ¯=〈σ〉 performed by the multi-scale method shown in Figure 9. The damage variable is represented by the damage evolution function φ(f), which can explain the relationship between the failure index f and the damage variable D in the Matzenmiller–Lubliner–Taylor (MLT) model. In this paper, the damage evolution is shown in Equations (1) and (2), where α and β are the material response parameters, and α=1, β=10. (1) D=φ(f),0≤D≤1 (2) φ(f)={0,f<fminDmax×(1−exp(−fαβ−fminαβeβ)),f≥fmin The concrete damage was judged by the multi-component 2D failure criteria shown in Table 6. F1, F2, F3, F4, and F5 are the failure indices, which correspond to five failure modes. If any of the five failure indices are not less than 1, damage will occur. Xt and Xc are the tensile and compressive strength, respectively, of composite material in one direction, as shown in Table 4; Yt and Yc are the tensile and compressive strength, respectively, in two directions, as shown in Table 4; and S is the shear strength, which is calculated according to cubic compressive strength. 2.3.2. Random Aggregate Distribution Model (Model 2) In this study, 2D and 3D random aggregate models were used as random 2D and random 3D separately, as shown in Figure 10 and Figure 11. The white, red, and purple parts represent the mortar matrix, aggregate, and interface transition zone (ITZ), respectively. The influencing parameters include the distribution, content, and shape of the coarse aggregate, the mechanical properties of the ITZ, and the influence of porosity. Four distributions of coarse aggregate were simulated, which showed that the distribution of coarse aggregate had little effect on the mechanical properties of concrete. Therefore, the coarse aggregate was set to be uniformly distributed in the model. We simulated the area fraction of aggregate at 20%, 33%, 40%, and 50%. The value was closer to the experimental value when the area fraction was 33%. The influence of coarse aggregate shape included round, ellipse, square, and regular pentagon, and it was found that when the coarse aggregate shape was round or ellipse, the result was closer to the experiment. The mechanical property ratio of ITZ to mortar was 0.4, 0.6, 0.8, and 1, and porosity was selected as 0%, 0.5%, 1%, 1.5%, and 2%. The ratio of ITZ to mortar in the model was 0.8 and porosity was 0% after calculation and analysis. According to the gradation curve of concrete, the diameter of its coarse aggregate was determined to be 5–15 mm. Figure 12 shows that the distribution of the aggregate in the X–Y plane was random and uniform. The models of different sizes and the definitions of the relationships between aggregates were based on specific experiments. The aggregates were set to be separated from each other according to realistic conditions. The final geometric model from Digimat was exported to Abaqus for calculation. Damage is a process of cohesion in a material that develops under loading conditions, which leads to destruction of the unit volume/interface between aggregate and mortar. The damage index was used to measure whether there is damage to concrete in the numerical model. In the two models we set up, when the damage index in the unit volume/interface arrives 0.2, the crack appears, and when it exceeds 0.9, the unit fails. 2.3.3. Model Establishment To predict the constitutive model (the stress–strain curve) of concrete based on Digimat, it was necessary to determine the mechanical parameters of the matrix phase, which were measured by experiments, as shown in Table 7. The elastic modulus and Poisson’s ratio of coarse aggregate were solved by Digimat-MX reverse regression iteration, and were set at 80 GPa and 0.16, respectively. The thickness of the ITZ was 200 μm [56], and the mechanical property ratio of ITZ to mortar was 0.8 [57,58]. The solver we used was Abaqus/Standard, and we chose static general mode. The geometric nonlinearity was off, the size of the initial increment was 1 × 10−4, the minimum increment size was 1 × 10−4, and the maximum size was 0.01. The method of the equation solver was direct, and the solution technique was full Newton. The normal contact between the steel plate and the concrete was set as hard contact, and the tangential direction was set with a coefficient of friction of 0.2. The entire loading surface of the steel plate was coupled to a reference point, and the displacement was added to it. The backing plate was restricted from rotating and moving, and the compressed steel plate could only move in the direction of the displacement. Inclusion model (Figure 4c, Figure 5c, Figure 6c and Figure 7c): according to the failure criterion, the definition of damage variables, and the law of damage evolution, a progressive damage model of the meso characteristics of concrete materials was obtained in Digimat-MF. The calculation result of the model was imported into Abaqus as a material property of concrete in a subroutine manner, and the simulation of mechanical properties of concrete was carried out. Eight-node reduced integral solid element (C3D8R) was adopted for the concrete and steel plate in the model. For the 2D random aggregate distribution models (Figure 4d, Figure 5d, Figure 6d and Figure 7d), the thickness of the model was 1. We set up the geometric model in Digimat-FE and then imported it into Abaqus. In order to ensure that the simulation conditions were as close as possible to the actual experimental conditions, the steel plate was established in Abaqus, and displacement was applied to it. The concrete damage plastic model was adopted for the mortar and ITZ, and the steel plate and aggregate were set to linear elasticity. For concrete with different stone powder contents in the rock sand, the same geometric model was used, and only the material properties of the mortar and ITZ were changed. All parts were simulated by plane elements, and the element type was formulated as a four-node bilinear plane stress quadrilateral element (CPS4R). The 3D random aggregate distribution model was similar to the 2D model, but the eight-node reduced integral solid element (C3D8R) was adopted for the concrete and steel plate in the model. As shown in Figure 13, the 2D and 3D random aggregate distribution models of concrete with 5% stone powder content were established to simulate the compressive condition. The cubic compressive strength of the concrete was 94.55 and 83.40 MPa and the axial compressive strength was 88.32 and 82.55 MPa in the 3D and 2D models, respectively. It can be seen that the cubic compressive and axial compressive strength of the 3D model exceeded the 2D model slightly with the same size coarse aggregate content, and the calculation result of the 2D model was closer to the experiment. Therefore, the 2D random aggregate model was selected to simulate the mechanical properties of concrete, as shown in Figure 4d, Figure 5d, Figure 6d and Figure 7d. The comparison of compressive strength of the two models shows that there was little difference between them, and the simulation value of 2D would be closer to the experimental value; therefore, we used the 3D random aggregate distribution model of concrete with 5% stone powder content to simulate cubic compressive strength and axial compressive strength, which verified the feasibility of the 2D model. Therefore, the 2D random aggregate distribution model was used in all tests. 3. Analysis of the Experiment Results Research on the flowability of C80 concrete with stone powder content showed that flowability was the best when the content was 7%. With increased stone powder content, the slump and slump-flow decreased, and an agglomerated phenomenon occurred in the concrete. The changes in compressive, split tensile, and flexural strength of C80 concrete with different stone powder content were as follows. 3.1. Calculation of Experimental Results The cubic compressive and axial compressive strength of concrete are calculated by Equation (3):(3) fci=F/A where i=c or r, fcc represents the cubic compressive strength of concrete (MPa), fcr represents the axial compressive strength of concrete (MPa), F is the failure load (N), and A is the load area (mm2). The split tensile strength of concrete is calculated by Equation (4):(4) fts=2F/πA=0.637F/A where fts represents split tensile strength of concrete (MPa), F is the failure load (N), and A is the load area (mm2). The flexural strength of concrete is calculated by Equation (5):(5) ff=3Fl/2bh2 where ff is the flexural strength of concrete (MPa), F is the failure load (N), l shows the distance between the supports (mm), h is the section height of the specimen (mm), and b is the section width of the specimen (mm). The mechanical parameters of cement mortar and concrete were measured by the above methods, and each group of experiments had three specimens. The test result was the average value of the three specimens according to Chinese Codes JGJ/T 70-2009 [52] and GB/T 50081-2019 [53], shown in Table 7 and Table 8. Stone powder replaced the weight of rock sand. cυ is the coefficient of variation. The mechanical properties of the interface transition zone were 0.8 times that of the mortar, according to Zhang and Du [57] and Huang et al. [58]. 3.2. Cubic Compressive Strength Cubic compressive strength is an important criterion to divide the grades of concrete. From Table 8, it can be seen that as the content of stone powder increased, the strength of concrete gradually increased and reached a maximum of 97 MPa when the content was 10%, and then dropped sharply. The excessive experimental value of S10 was due to the uneven distribution of coarse aggregate [59,60]. In general, in the range of 3–10% stone powder content, the cubic strength of concrete increased with increased stone powder because, with the increase in stone powder content, the filling effect is more effective at making the concrete denser, which leads to strength increase. When the stone powder content exceeds 10%, too much stone powder content will lead to uneven distribution of aggregates and more weak parts, which causes it to decrease [61]. 3.3. Axial Compressive Strength The axial compressive strength test of concrete can reflect the stress and failure state intuitively. It can be seen from Table 8 that when the content of stone powder was 5%, the axial compressive strength of concrete reached the maximum value of 85.3 MPa. In the range of 5–15% content, the strength decreased gradually, because when the content of stone powder exceeds 5%, the concrete will occur agglomeration, which leads to a strength decrease [62]. 3.4. Split Tensile Strength The split tensile strength test is one of the methods to test the tensile strength of concrete which can reflect its tensile performance indirectly. It can be seen from Table 8 that the change trend was the same as that of axial compressive strength, reaching the maximum value of 5.1 MPa at 5% content and then decreasing gradually. It is also caused by the uneven distribution of aggregate due to excessive stone powder 3.5. Flexural Strength Flexural strength can reflect the toughness of concrete. As shown in Table 8, the flexural strength was the largest, 6.69 MPa, at 3%, and then decreased, again reaching a peak of 6.46 MPa at 7%. In general, the effect of stone powder content on the flexural strength is small, as they are all within 10%, but the effect of excessive stone powder content on the reduction in strength is still the same. 3.6. Stress–Strain Curves The stress–strain curves of concrete with different stone powder contents are shown in Figure 14. Failure is sudden due to the brittleness of C80 concrete, so the descending section is steep. As seen in Figure 14, the stone powder content ranges from 3 to 5%, the peak stress of concrete increases and reaches the maximum at 5%, and then, with the increased content, the peak stress shows a steady downward trend. 4. Comparison Analysis between Numerical Simulation and Experimental Results This section mainly includes two parts: analysis and discussion. The analysis includes a comparative analysis of the experimental value and two simulated values and a comparison of damage and failure modes under compression in two models. The discussion includes the main research results of this paper, some abnormal data analysis, and the limitations of the paper. 4.1. Analysis of Results In the following figures, M1 and M2 represent the simulation result of the numerical model based on inclusion theory and the 2D random aggregate distribution model, respectively. Figure 15 is a comparison diagram of experimental and simulation results. As seen in Figure 15a, the cubic compressive strength values between the simulation and the experiment are relatively large, because the coarse aggregate could not be distributed evenly in the experiment. Some larger or smaller size coarse aggregate affected the experimental results and caused a certain difference between the simulation and experiment. In general, the simulated value based on inclusion theory was closer to the experimental value. The stress–strain curves of concrete with different stone powder contents were similar; therefore, here we took the stress–strain curves of concrete with a content of 5% as an example for comparison. As shown in Figure 15b, the simulation results based on inclusion theory were more consistent with the experiment. From Figure 15c,d,f, the results based on inclusion theory coincide with the experiment, and their change laws are the same. Among them, axial compressive and split tensile strength reached the maximum when the content was 5%. Figure 15e shows that the simulated value of the elastic modulus was close to the experiment, but the change rule was different. The experiment showed that the elastic modulus decreased as the content increased, and both models showed a rebound when the content was 7%. For cubic compressive strength, the experimental results are similar to the two simulation results, but the change trend is different. The test reaches the maximum result when the stone powder content is 10%, the simulation result based on the inclusion theory reaches the maximum at 5%, and the 2D random aggregate model reaches the maximum when the stone powder content is 15%. For axial compressive strength, the variation trends of the experimental results and the simulation results are the same, but the results of the model based on the 2D random aggregate distribution are smaller than those of the test when the stone powder content is 7%. For splitting tensile strength, the model based on the 2D random aggregate distribution has some difference when the stone powder content is 5%. The elastic modulus and flexural strength results of concrete are not much different between experiments and simulations. It can be seen that the two simulation results are in good agreement with the experiment, but the model based on inclusion theory can better reflect the macro-mechanical properties of concrete, because this method is based on inclusion theory, homogenization theory, and progressive damage theory to calculate the constitutive relationship of concrete with a certain content, and then the stress–strain curves are directly imported from Digimat into Abaqus as a material parameter. Meanwhile, the model as a whole could exhibit its macroscopic mechanical properties accurately. However, the model did not consider the distribution of aggregates and mortar, and as a result, it could not reflect the mesoscopic failure mode of concrete; therefore, the establishment of a random aggregate distribution model is significant. Figure 16 shows the cubic compression failure mode of concrete with 5% stone powder content based on inclusion theory. The final macroscopic crack is characterized by the damage index when DAMAGEC exceeds 0.9. Compression damage begins at point a of the stress–strain curve, first appears at the four corners of the concrete, as shown in Figure 16a, and then expands to point b with increasing stress, as shown in Figure 16b. The damage gradually extends to the middle of the concrete surface because the steel plates constrain the concrete due to the friction between them (Figure 16c). Full peeling occurs because, without side edges, the smaller pressure-bearing area means a reduced bearing capacity of concrete, and, finally, the concrete suffers from compression damage, as shown in Figure 16d. Figure 17 shows the whole process of damage and failure of cubic concrete specimens in the 2D random aggregate distribution model. At point a in Figure 17, the damage first occurs at the ITZ with low stiffness and bearing capacity. The mismatched stiffness between the aggregate and interface causes a stress concentration phenomenon, and cracks appear and expand in the ITZ, as shown in Figure 17a. At pointb, there is a process of developing damage when the stress shifts from the yield stage to the maximum. The damage begins to develop to the middle of the mortar from the ITZ, and the four corners of the concrete are also damaged with increasing load (Figure 17b). At pointc, the stress is at its maximum and the model begins to fail, and the damage reaches the maximum that the interface can withstand; thus, the bearing capacity of the specimen starts to decrease. The microcracks are connected to form failure areas, as shown in Figure 17c. At point d in Figure 17d, microcrack areas develop and penetrate into macroscopic cracks with increased displacement after the peak load, and the bearing capacity drops sharply. The upper and lower parts of the specimen are not damaged much due to the constraint of the steel plates. As shown in Figure 17e, the interface is broken, the concrete cannot continue to bear pressure, and the crack has reached the maximum. There are some differences between the two failure modes. In the model based on inclusion theory, whose first crack occurs at the four corners, the failure develops toward the middle of the specimen with increasing load. In the damage to a 2D random aggregate distribution, whose first crack appears in the ITZ, the microcracks are connected and develop into macroscopic cracks with increasing load. The final failure mode of the two models is an X shape, which is consistent with the experiment. Therefore, the nonlinear characteristics of concrete at the macro level are closely related to the initiation and propagation of microcracks in concrete. 4.2. Discussion At present, there is little research on stone powder in concrete through numerical simulations. Therefore, based on previous studies, this paper proposes a simulation method for stone powder, adding different contents of stone powder to the mortar and testing its mechanical properties. The changed mechanical properties of mortar indicate the impact of the stone powder content, and the inclusion model and 2D random aggregate distribution model were established to verify the method in comparison with experimental values. The experimental and simulation results show the influence of stone powder content on the mechanical properties of concrete, and the best stone powder content of C80 concrete is 5%. The experimental results show that with increased stone powder content, the cubic compressive strength first increases and then decreases, reaching 97 MPa when the content is 10%, which is too large compared with the other groups. This is due to the influence of concrete size. In this experiment, the size of the cube compressive specimen is 100 mm × 100 mm × 100 mm, and the sizes of the axial compressive strength and elastic modulus are both 100 mm × 100 mm × 300 mm. The smaller the specimen size, the greater the probability of uneven distribution of the coarse aggregate, which is the reason for the greater difference in the cubic compressive strengths. Comparing the experiment and the simulation, when the stone powder content was less than 7%, the values of cubic compressive strength were close, but the result of the S10 group was large. When the stone powder content exceeded 7%, the thick mortar led to uneven distribution of the coarse aggregate in the specimen during the experiment, and the coarse aggregate was concentrated in the middle. Han et al. [62] also found that the distribution of coarse aggregate has a significant effect on the strength of concrete. Huang et al. [59] also found that the different distribution of coarse aggregates has an effect on concrete carbonation. In the two models, the coarse aggregate was distributed evenly. Due to this difference, the failure mode of the specimen differed from the experimental test, which is reflected in the macroscopic strength. For axial compressive strength, when the stone powder content is before 5%, the results of the experiment and the two simulation methods are in good agreement. When the stone powder content exceeds 7%, the simulation results of the 2D random aggregate distribution model have little difference compared with the experimental values. This is because, in this model, we set the performance of the interface transition zone to be 0.8 times that of the mortar, which may be different from the actual one, causing the difference in the results. For the mechanical properties of other groups, the experiment and simulation were close. The model established based on inclusion theory was closer to the experiment [59]. This is because, in this model, the material was damaged as a whole and was destroyed uniformly, so the overall macroscopic performance was more consistent with the experimental value. The 2D random aggregate model focused more on the distribution of internal materials and had more influencing factors during failure, which can reflect the meso-level failure mode of concrete more accurately [42]. Although this paper has proposed a method to simulate different contents of stone powder, it cannot be completely separated from the experiment, and the basic data of the experiment still need to be provided. Meanwhile, the model does not consider that the coarse aggregate in thick mortar would be distributed unevenly. Therefore, it is necessary to establish a simulation method for concrete with different stone powder contents according to the actual distribution of coarse aggregate and to analyze the influence of different distributions of coarse aggregate on the mechanical properties of concrete with different stone powder content. 5. Conclusions Experimental analysis and numerical simulation methods based on inclusion theory and random aggregate distribution were used to study the influence of stone powder content on the mechanical properties of C80 concrete in this paper. The conclusions are as follows: With increased stone powder, the cubic compressive strength of concrete showed different changes. The experimental value reached the maximum at 10%, the numerical model based on inclusion theory reached the maximum at 5%, and the 2D random aggregate distribution model reached the maximum at 15%. There was greater dispersion between experiment and simulation. In the range of stone powder content from 0% to 15%, the model based on inclusion theory was very close to the experimental results, and the model based on 2D random aggregate distribution was closer to the experimental value after the stone powder content was 7%. The simulated values were consistent with the experiment in the axial compressive, split tensile, and flexural strength of concrete. The model based on inclusion theory reflected the macroscopic mechanical properties of concrete, and the 2D random aggregate model emphasized the meso-level failure mode. Considering the mechanical properties and flowability of concrete comprehensively, the best stone powder content of C80 concrete was 5%. The final failure mode of the two models was an X shape, which was consistent with the experiment. Therefore, the nonlinear characteristics of concrete at the macro level are closely related to the initiation and propagation of microcracks in concrete. The 2D random aggregate distribution model can better show the mesoscopic mode of the compression failure of concrete. Author Contributions Conceptualization, H.W. and B.S., K.M.; methodology, H.W. and F.Y.; software, H.W. and K.L.; formal analysis, H.W., K.L. and F.Y.; investigation, H.W., J.Z. and B.S.; resources, H.W. and J.Z.; data curation, H.W. and B.L.; writing—original draft preparation, H.W. and B.L.; writing—review and editing, H.W., B.S. and K.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 Data sharing not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flowchart representing the methodology of the work. Figure 2 The particle size distribution curves for the aggregates: (a) coarse aggregate, (b) fine aggregate, and (c) stone powder. Figure 3 Raw materials: (a) fly Ash, (b) slag Powder, (c) silica Fume, and (d) stone Powder. Figure 4 Cubic compressive strength test: (a) schematic design, (b) physical diagram, (c) inclusion model, and (d) 2D random model. Figure 5 Axial compressive strength and elastic modulus test: (a) schematic design, (b) physical diagram, (c) inclusion model, and (d) 2D random model. Figure 6 Split tensile strength test: (a) schematic diagram, (b) physical diagram, (c) inclusion model, and (d) 2D random model. Figure 7 Flexural strength test: (a) schematic diagram, (b) physical diagram, (c) inclusion model, and (d) 2D random model. Figure 8 Double-inclusion model. Figure 9 Multi-scale method. Figure 10 Two-dimensional random aggregate model of concrete. Figure 11 Three-dimensional random aggregate model of concrete. Figure 12 Distribution of aggregate in the X–Y plane in the 2D random aggregate model. Figure 13 Random aggregate model of concrete: (a) aggregate, (b) mortar, (c) 3D model, and (d) 2D model. Figure 14 Stress–strain curves of concrete with different stone powder contents. Figure 15 Comparison of experiment and simulation: (a) cubic compressive strength, (b) stress–strain curves of concrete with 5% stone powder content, (c) axial compressive strength, (d) split tensile strength, (e) elastic modulus, and (f) flexural strength. Figure 16 Cubic compression failure mode of concrete with 5% stone powder content (M1): (a) damage at point a, (b) damage at point b, (c) damage at point c, and (d) damage at point d. Figure 17 Cubic compression failure mode of concrete with 5% stone powder content (M2): (a) damage at point a, (b) damage at point b, (c) damage at point c, (d) damage at point d, and (e) damage at point e. materials-15-03282-t001_Table 1 Table 1 Main properties of cement and silica fume. Cement Specific Surface Area (m2/kg) Volume Stability IgnitionLoss (%) Chloride Ion Content (%) Initial Setting Time (min) Final Setting Time (min) P·O 42.5 321 qualified 3.95 0.014 170 219 Silica Fume 23,250 - 2.05 - - - materials-15-03282-t002_Table 2 Table 2 Performances of water-reducing admixture. Test Items pH Chloride Content % Total Alkalinity % Test data 6.4 0.006 0.47 materials-15-03282-t003_Table 3 Table 3 Performance test results of water reducing agent. Test Items Water-Reducing Rate (%) Gas Content (%) Bleeding Rate Ratio (%) Compressive Strength Ratio (%) Shrinkage Ratio % 7 d 28 d Test data 28 2.8 30 155 147 99 Standard requirement ≥25 ≤6.0 ≤70 ≥140 ≥130 ≤110 materials-15-03282-t004_Table 4 Table 4 Chemical compositions of OPC, slag powder, fly ash, silica fume, and stone powder. Chemical Compositions (%) SiO2 Al2O3 Fe2O3 CaO MgO Na2O TiO2 K2O SO3 OPC 20.20 4.78 2.72 62.14 2.44 0.29 0.31 0.58 3.31 Slag Powder 34.50 17.70 1.03 34.00 6.01 - - 1.64 Fly Ash 49.90 32.80 5.81 4.46 - - 1.57 2.82 - Silica Fume 96.10 0.39 0.18 0.19 0.12 0.09 - - - Stone Powder 12.60 4.46 2.03 77.10 2.11 - 0.24 0.70 0.30 materials-15-03282-t005_Table 5 Table 5 Mix ratio of C80 concrete (kg/m3). Group Rock Sand Stone Powder Coarse Aggregate Cement Water Slag Powder Fly Ash Silica Fume S0 709 0 1021 372 150 120 60 48 S3 687.73 21.27 1021 372 150 120 60 48 S5 673.55 35.45 1021 372 150 120 60 48 S7 659.37 49.63 1021 372 150 120 60 48 S10 638.1 70.9 1021 372 150 120 60 48 S15 602.65 106.35 1021 372 150 120 60 48 materials-15-03282-t006_Table 6 Table 6 Multi-component 2D failure criteria. Failure Mode Failure Criteria σ11≥0 F1(σ)=σ11/Xt σ11<0 F2(σ)=−σ11/Xc σ22≥0 F3(σ)=σ22/Yt σ22<0 F4(σ)=−σ22/Yc Shear failure F5(σ)=|σ12|/S materials-15-03282-t007_Table 7 Table 7 Mechanical parameters of cement mortar (MPa). Content of Stone Powder Elastic Modulus of Mortar Standard Deviation Cv Compressive Strength of Mortar Standard Deviation Cv Tensile Strength of Mortar Standard Deviation Cv S0 41,579 943.56 2.27% 72.4 2.84 3.92% 3.6 0.065 1.81% S3 42,492 2866.25 6.75% 73.2 12.2 16.67% 3.8 0.35 9.21% S5 40,757 1256.83 3.08% 70.2 4.5 6.41% 4.8 0.34 7.08% S7 40,691 1691.23 4.16% 70.7 1.98 2.80% 4.1 0.18 4.39% S10 39,934 5625.73 14.09% 73.6 4.54 6.17% 4.0 0.11 2.75% S15 39,972 1731.58 4.33% 77.3 2.40 3.10% 3.8 0.12 3.16% materials-15-03282-t008_Table 8 Table 8 Cubic compressive, axial compressive, split tensile, and flexural strength of concrete with different stone powder contents (MPa) over 28 days. Content of Stone Powder Cubic Compressive Strength Standard Deviation Cv Axial Compressive Strength Standard Deviation Cv Split Tensile Strength Standard Deviation Cv Flexural Strength Standard Deviation Cv S0 83.70 2.05 2.45% 80.80 3.4 4.21% 3.65 0.21 5.75% 6.34 0.21 3.31% S3 85.30 3.03 3.55% 81.50 5.65 6.93% 3.67 0.18 4.90% 6.69 1.27 18.98% S5 87.30 9.9 11.34% 85.30 1.64 1.92% 5.10 0.37 7.25% 6.24 0.46 7.37% S7 88.20 4.76 5.40% 79.90 7.87 9.85% 4.30 0.26 6.05% 6.46 0.19 2.94% S10 97.00 2.79 2.88% 76.60 3.42 4.46% 4.10 0.22 5.37% 6.00 0.92 15.33% S15 81.50 8.16 10.01% 74.50 3.80 5.10% 3.93 0.21 3.05% 6.16 0.14 2.27% Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Marvila M. de Azevedo A.R.G. de Matos P. Monteiro S. Vieira C. 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PMC009xxxxxx/PMC9099771.txt

==== Front Polymers (Basel) Polymers (Basel) polymers Polymers 2073-4360 MDPI 10.3390/polym14091882 polymers-14-01882 Article Design and Fabrication of Nanofibrous Dura Mater with Antifibrosis and Neuroprotection Effects on SH-SY5Y Cells Zhao Zhiyuan 123† https://orcid.org/0000-0001-8822-1868 Wu Tong 23† Cui Yu 23 Zhao Rui 123 Wan Qi 23* https://orcid.org/0000-0002-4576-2872 Xu Rui 13* García-Fernández Luis Academic Editor Bikiaris Dimitrios Academic Editor 1 Department of Interventional Radiology, The Affiliated Hospital of Qingdao University, Jiangsu Road 16, Qingdao 266000, China; qduzzy@126.com (Z.Z.); zhrui97@163.com (R.Z.) 2 Institute of Neuroregeneration and Neurorehabilitation, Qingdao University, Qingdao 266071, China; twu@qdu.edu.cn (T.W.); cuiyu1216@126.com (Y.C.) 3 Qingdao Medical College, Qingdao University, Qingdao 266071, China * Correspondence: qiwan1@hotmail.com (Q.W.); xray3236@126.com (R.X.) † These authors contributed equally to this work. 05 5 2022 5 2022 14 9 188211 2 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/). The development and treatment of some diseases, such as large-area cerebral infarction, cerebral hemorrhage, brain tumor, and craniocerebral trauma, which may involve the injury of the dura mater, elicit the need to repair this membrane by dural grafts. However, common dural grafts tend to result in dural adhesions and scar tissue and have no further neuroprotective effects. In order to reduce or avoid the complications of dural repair, we used PLGA, tetramethylpyrazine, and chitosan as raw materials to prepare a nanofibrous dura mater (NDM) with excellent biocompatibility and adequate mechanical characteristics, which can play a neuroprotective role and have an antifibrotic effect. We fabricated PLGA NDM by electrospinning, and then chitosan was grafted on the nanofibrous dura mater by the EDC-NHS cross-linking method to obtain PLGA/CS NDM. Then, we also prepared PLGA/TMP/CS NDM by coaxial electrospinning. Our study shows that the PLGA/TMP/CS NDM can inhibit the excessive proliferation of fibroblasts, as well as provide a sustained protective effect on the SH-SY5Y cells treated with oxygen–glucose deprivation/reperfusion (OGD/R). In conclusion, our study may provide a new alternative to dural grafts in undesirable cases of dural injuries. nanofibrous dura mater antifibrosis neuroprotection PLGA tetramethylpyrazine Natural Science Foundation of Shandong ProvinceZR202102190696 Affiliated Hospital of Qingdao UniversityNational Natural Science Foundation of China82001970 32171322 31900634 82071385 Natural Science Foundation of Shandong Province, ChinaZR2021YQ17 Young Elite Scientists Sponsorship Program by CASTYESS20200097 National Key R&D Program of China2019YFC0120000 2018YFC1312300 Key Research and Development Project of Shandong2019JZZY021010 This study was supported by the Natural Science Foundation of Shandong Province, China (ZR202102190696) and the Clinical Medicine + X Scientific Research Project of the Affiliated Hospital of Qingdao University to R.X., the National Natural Science Foundation of China (82001970, 32171322), the Natural Science Foundation of Shandong Province, China (ZR2021YQ17), the Young Elite Scientists Sponsorship Program by CAST (No. YESS20200097) to T.W., and the National Natural Science Foundation of China (31900634) to Y.C. This work was also supported by the National Key R&D Program of China (2019YFC0120000; 2018YFC1312300), the National Natural Science Foundation of China (NSFC: 82071385), and the Key Research and Development Project of Shandong (2019JZZY021010) to Q.W. ==== Body pmc1. Introduction The dura mater surrounds the brain and retains the cerebrospinal fluid [1]. The dura mater may be damaged in the development and treatment of neurosurgical diseases, such as large-area cerebral infarction, cerebral hemorrhage, brain tumor, and craniocerebral trauma, which need to be repaired in time [2]. For dura mater that is difficult to complete in a one-stage repair process, it can be repaired with dural grafts through duroplasty [3]. Autologous dura grafts obtained from the periosteum and fascia have no immune rejection, but their clinical application is greatly limited due to insufficient quantities, difficult sampling, postoperative pain, and other shortcomings [4,5]. Dural grafts have several important features: supporting tissue regeneration, avoiding an immune inflammatory response, good watertight confinement, anti-adhesion, inhibiting scar tissue formation, biodegradability, and releasing therapeutic drugs to promote recovery [6,7]. Many synthetic polymers, such as polylactic acid (PLA), polyglycolic acid (PGA), and their copolymer, polylactic-co-glycolic acid (PLGA), have been widely used in biomedical engineering due to their good biocompatibility, non-toxicity, film-forming properties, and biodegradability [8,9]. In addition, the use of PLGA as a carrier for sustained drug release is also a hot topic of current research due to the controlled degradation rate of PLGA [10,11,12]. However, PLGA also has defects as a graft. The degradation products of PLGA are lactic acid and hydroxyacetic acid, which are by-products of human metabolism [13]. The accumulation of acidic degradation products can decrease the local pH value, trigger inflammatory reactions, and affect the rate of polymer degradation [14]. As a natural polysaccharide with good biocompatibility, degradability, antibacterial properties, and mechanical strength, chitosan (CS) is a kind of good implant material [15]. Previous studies have shown that CS can inhibit the proliferation of fibroblasts and suppress type I and III procollagen production, and it has anti-fibrosis as well as anti-adhesive effects [16,17,18,19]. In addition, chitooligosaccharides (COS), the degradation products of CS, have been proven to promote nerve regeneration [20,21]. CS is an alkaline polysaccharide among natural polysaccharides that can chemically bind to other substances through some primary amino groups carried by the CS main chain. It has been reported that CS can buffer the acidity produced from the degradation of PLLA [22,23]. 2,3,5,6-tetramethylpyrazine (TMP) is an active compound extracted from the herb Chuanxiong Ligusticum, which exhibits neuroprotective effects [24,25]. TMP can protect neurons by scavenging oxygen free radicals, protecting mitochondrial function, inhibiting calcium inward flow and glutamate release, as well as attenuating ischemia-induced neuronal death by regulating the expression of bcl-2 and bax proteins [26,27,28,29,30]. In addition, TMP affects neurogenesis, for example, it can promote the differentiation of neural stem cells into neurons [31,32]. At present, TMP has been widely used in the clinical treatment and basic research of cardiovascular and cerebrovascular diseases. However, due to its poor water solubility, short half-life, and low concentration of distribution at the injury site, it requires high doses and multiple administrations to maintain therapeutic concentrations, which is a drawback for clinical treatment [33,34,35]. To overcome the above drawbacks and limitations, in this study, we designed and fabricated PLGA/TMP nanofibrous dura mater (NDM) with a coaxial electrospinning technique, and then generated PLGA/TMP/CS NDM by chemically binding a CS coating to the surface of the NDM. Our study found that the PLGA/TMP/CS NDM could inhibit the excessive proliferation of fibroblasts in vitro, thus exerting anti-adhesive effects and inhibiting the formation of scar tissue. Through the degradation of the PLGA and CS, TMP was released into the cell matrix, which could promote the survival of OGD/R-treated SH-SY5Y cells, as well as facilitate the regeneration of SH-SY5Y cells, and finally, exert a sustained neuroprotective effect. 2. Materials and Methods 2.1. Materials PLGA (50:50, Mw: 60,000–80,000) was purchased from Match Biomaterials (Shenzhen, China), TMP and MES Buffered Solution from Aladdin (Shanghai, China), ethylcarbodiimide hydrochloride (EDC), N-hydroxysuccinimide (NHS), acetic acid, hexafluoroisopropanol (HFIP), and N,N-dimethylformamide (DMF) from Macklin (Shanghai, China), and CS from Sigma-Aldrich (America). Fibroblasts were a gift from Ziyi Zhou from the Medical Cosmetology Center at the Affiliated Hospital of Qingdao University. Human neuroblastoma SH-SY5Y cells were provided by the Institute of Neuroregeneration and Neurorehabilitation, Qingdao University. Dulbecco’s modified eagle medium (DMEM) and antibiotic-antimycotic were purchased from Solarbio (Beijing, China). Fetal bovine serum (FBS) was purchased from Pan (Adenbach, Germany). Phalloidin-iFluor 488 and DAPI staining solution were acquired from Abcam (Shanghai, China). The following antibodies from ABclonal (Wuhan, China) were used: Ki67 Rabbit pAb and GAP43 Rabbit pAb. Goat Anti-rabbit IgG H&L/Alexa Fluor 555 as a secondary antibody was from Bioss (Beijing, China). A Cell Counting Kit-8 (CCK8) was supplied from Targetmol (Boston, MA, USA). 2.2. Electrospinning PLGA/TMP/CS NDM was fabricated by the electrospinning technique. Briefly, PLGA was dissolved in HFIP via magnetic stirring at room temperature for 4 h to form an electrospinning solution with a concentration of 20 wt.% [36]. The solution flowed out from the syringe at a rate of 2 mL/h. PLGA NDM was fabricated by electrospinning for 1 h with +12 kV, and the acceptance distance was 15 cm. The PLGA NDM was immersed in EDC/NHS solution (0.96 g of EDC and 0.14 g of NHS in 50 mL of MES buffer) at 4 °C for 12 h. The CS solution (3 wt.%) at an equal volume to the EDC/NHS solution was added to ensure an excess of CS, and the mixed PLGA-CS system was kept for 24 h at room temperature until the cross-linking between the PLGA and CS components (via the coupling reaction between the NHS-ester groups belonging to PLGA and some primary amine groups of CS) was accomplished [12]. Then, the cross-linked product was rinsed repeatedly with deionized water and dried to obtain PLGA/CS NDM. For coaxial electrospinning, the shell solution consisted of 20% PLGA in HFIP, and the core of the fibers was 10 mg/mL TMP dissolved in ethanol. The prepared solutions were delivered to the outer and inner coaxial needle at 2.0 and 0.1 mL/h feeding ratios, respectively, with a programmable syringe pump. The applied voltage was 12 kV and the acceptance distance is 15 cm. The fibers were collected in a layer-by-layer manner during a 4 h period to obtain PLGA/TMP/CS NDM [36,37]. 2.3. NDM Characterization The morphology of the nanofiber was observed using scanning electron microscopy (SEM, VEGA 3 SBH, TESCAN, Shanghai, China) and the nanofiber diameter was measured by applying Nano Measurer software. The chemical structure and composition of the fibers were characterized by Fourier infrared spectroscopy (Nicolet Is50, Thermo Electron Corporation, Waltham, MA, USA). All NDMs were prepared for the same size (5 cm × 1 cm, about 0.02 mm in thickness) to characterize their tensile mechanical property by employing an Electro-mechanical Universal Testing Instrument (CMT6103, Mechanical Testing & Simulation, Eden Prairie, MN, USA). Thermogravimetric analysis (TGA) of the NDMs was performed using a Thermal Gravimetric Analyzer (TASDT650, TA INSTRUMENTS, New Castle, DE, USA). 2.4. Encapsulation Efficiency (EE) The absorbance value of the TMP was detected using a full-function microplate detector (Synergy Neo2, Bio Tek, Vermont, USA) to determine the maximum UV absorption peak at a wavelength of 280 nm (Supplementary Figure S1). The PLGA/TMP/CS NDM samples were immersed in DCM until the TMP was completely dissolved, and then its actual content was determined spectrophotometrically using a corresponding calibration curve. Comparatively, the theoretical content of the TMP was considered to be the overall TMP amount consumed during the electrospinning. The calculation of the EE (in %) of the TMP was performed as follows:EE = (actual content/theoretical content) × 100(1) 2.5. In Vitro TMP Release Profiles The PLGA/TMP/CS NDM was immersed in 5 mL of PBS solution (pH = 7.4) as a release medium and placed in a thermostatic shaker for gentle shaking. For current measurements, 1 mL of the PBS solution was taken out at different times to spectrophotometrically determine the TMP release (using the corresponding calibration curve), and then 1 mL of fresh PBS solution was added to the release medium contained in the shaker. The cumulative TMP release (C, in %) was calculated according to the following equation: C = (m1 + m2 + …+ mn)/m0 × 100%(2) where m1, m2, and mn are the weights determined at the times t1, t2, and tn, respectively, and m0 is the total weight of TMP to be released. 2.6. Extraction of NDM Immersion Solution Multiple different NDMs with the same mass were sterilized by ethanol fumigation for 3 h and UV irradiation for half an hour. The NDMs were immersed in 8 mL of fresh DMEM complete medium (DMEM with 10% FBS) under aseptic conditions at 37 °C, while a separate fresh DMEM complete medium was used as a control. The NDMs were removed after 1, 4, 7, and 14 days of immersion from the medium, and the remaining medium was the NDM immersion solution. 2.7. Cell Culture Fibroblasts and SH-SY5Y cells were cultured using DMEM complete medium containing 10% FBS at 37 °C and 5% CO2. Depending on the needs of the experiment, fibroblasts were seeded evenly on glass slides and different NDMs of a certain number, while SH-SY5Y cells were grown directly onto well plates and glass slides of a certain number. The culture medium was replaced every two days during the culture. Prior to cell seeding, all the glass slides and NDMs were sterilized by ethanol fumigation for 3 h and UV irradiation for 30 min. 2.8. OGD Challenge The complete medium was replaced with deoxygenated glucose-free extracellular solution (in mM: 116 NaCl, 5.4 KCl, 0.8 MgSO4, 1.0 NaH2PO4, 1.8 CaCl2, and 26 NaHCO3) [38]. The cells were cultured in a dedicated chamber (Plas-Labs, Lansing, MI, USA) with 95% N2/5% CO2 at 37 °C for 3 h. Then, the cells were reperfused using fresh complete medium containing different immersion solutions according to the experimental requirements and transferred to normal conditions for culture. 2.9. Cell Viability A cell viability assay for fibroblasts and SH-SY5Y cells was performed following an algorithm reported elsewhere [39]. The fibroblasts were seeded evenly at a density of 5000 cells/well on glass slides and different NDM amounts in 24-well plates for culture. CCK8 solution was added and incubated with the cells for 3 h at 1, 3, and 5 days after culture, respectively. The absorbance value at 450 nm was measured using a 96-well plate reader. The SH-SY5Y cells were seeded in 48-well plates at a density of 5000 cells/well, and after 24 h of culture, the cells were treated with OGD/R, after which CCK8 solution was added and incubated for 2 h. The absorbance value at 450 nm was measured using a 96-well plate reader. The absorbance values at 450 nm corresponded to the amounts of formazan dye that resulted under the action of cellular dehydrogenases exerted on the tetrazolium salt present in the initial CCK8 solution which, in turn, was proportional to the number of living cells. 2.10. Lactate Dehydrogenase (LDH) Release Assay According to the manufacturer’s instructions (Beyotime, Shanghai, China), the supernatants from the OGD/R-treated cell culture medium were harvested, and the absorbance value at 490 nm was measured using a 96-well plate reader with the absorbance value at 600 nm as reference. The LDH release was calculated according to the manufacturer’s formula. The absorbance values at 490 nm were proportionally correlated with the LDH release. 2.11. Cell Morphology The fibroblasts were seeded at a density of 5000 cells/well on glass slides, the PLGA NDM and PLGA/CS NDM in 24-well plates for culture. After 5 days of culture, the fibroblasts were stained with Phalloidin-iFluor 488 and DAPI to observe the morphology using fluorescence microscopy. For the SH-SY5Y cells, they were stained and observed in the same way after OGD/R treatment. 2.12. Immunofluorescence Cells on the NDM and glass slides were fixed in 4% paraformaldehyde, then permeabilized with 0.5% Triton X-100 for 15 min and blocked in 5% FBS for 2 h. The primary antibodies against Ki-67 (1:200) and Gap43 (1:200) diluted in the blocked buffer were added to incubate with cells at 4 °C overnight. Then the cells were labeled by a secondary antibody and stained with DAPI. The samples were observed using fluorescence microscopy and analyzed using Image J software. 2.13. Statistical Analysis The statistical analysis was performed using GraphPad Prism software. The results are presented in the form of the mean ± standard deviation. Statistical comparisons between groups were performed using one-way ANOVA. Values of * p < 0.05, ** p < 0.01, and *** p < 0.001 are considered statistically significant. 3. Results and Discussion 3.1. NDM Characterization We fabricated PLGA NDM and PLGA/TMP NDM using an electrospinning device according to the previously described conditions and coated them with CS by EDC/NHS cross-linking to prepare PLGA/TMP/CS NDM. We observed the morphology of the NDM by SEM. A smooth surface structure was shown on the fibers of the PLGA NDM, which were arranged in a disordered manner and interwoven into a network. The mean diameter of the fibers was 646 ± 103 nm, which was relatively uniform (Figure 1A). The PLGA/TMP NDM was morphologically similar to the PLGA NDM, with 692 ± 97 nm in mean fiber diameter (Figure 1B). For the PLGA/CS NDM, shiny granular agglomerates could be seen on the fiber surfaces (Figure 1C). To determine whether these were made of CS, structural analysis on the molecular scale of the PLGA/CS NDM was performed via infrared spectroscopy (FTIR) (Figure 1D). In the PLGA spectrum, the peak at 1087 cm−1 was assigned to C-O stretching, that located at 1748 cm−1 to C=O stretching vibrations, and the peaks placed between approximately 2950 and 3000 cm−1 to C-H stretching vibrations mainly involving methyl (CH3) and methylene (CH2) groups [40]. Instead, the infrared spectrum of the CS displayed the two vibrations of amide I and amide II at 1646 and 1587 cm−1, respectively. These weak peaks ascribed to the vibrational mode of amide I and II are due to a high degree of N-deacetylation associated with the CS used. In addition, the band at 2870 cm−1 was attributed to C-H stretching involving the carbon atoms of the sugar rings. The broad band centered at ca. 3500 cm−1 corresponded to the N-H stretch vibrations overlapped by the O-H stretches of the OH groups [41,42]. On the other hand, the simultaneous presence of the bands at 3500, 1635, and 1536 cm−1 (for CS) and at 1748 cm−1 (for PLGA) on the PLGA/CS NDM spectrum confirms the coexistence of CS and PLGA in the same mixed system (PLGA/CS NDM). Moreover, the strengthening of the bands at 1635 and 1536 cm−1 on the IR spectrum of the PLGA/CS NDM is consistent with the increased number of amide cross-linkages newly formed during the grafting of CS onto PLGA via the EDC/NHS coupling reaction [12]. The tensile results of all NDMs are shown in Figure 2A as the stress–strain curves of the PLGA NDM and PLGA/CS NDM. The tensile strength of the PLGA NDM was 6.27 ± 0.96 MPa, while that of the PLGA/CS NDM is 8.71 ± 1.03 MPa. Correspondingly, the values of the maximum strain (at break) are ca. 216% for the PLGA NDM and 161% for the PLGA/CS NDM. It is obvious that the CS improved the mechanical stress of the PLGA NDM but had a negative effect on the flexibility. According to experimental data reported elsewhere [43], the tensile strength of the human dura mater is about 7 MPa, and the maximum strain is 11%. The result suggests that the PLGA/CS NDM is more suitable for a dural graft than the PLGA NDM. The thermal stability of the NDMs was characterized using thermogravimetry (Figure 2B). The NDMs showed two stages of weight loss. From 30 to 200 °C, the PLGA NDM showed a gradual weight loss of 7.9 wt.%, while the PLGA/CS showed a 6.52% loss, and the PLGA/TMP NDM showed a 9.32% loss due to the desorption of solvent, adsorbed, and bound water. Then, the PLGA/TMP NDM began to decompose at 230 °C, while the PLGA NDM and PLGA/CS NDM did so at about 260 °C. The decomposition of the PLGA/CS NDM and PLGA/TMP NDM was completed at around 340 °C, while that of the PLGA NDM was done at about 360 °C. The ash residue of the NDM was around 2%. This shows that the CS and TMP had a weak influence on the thermal stability of the PLGA. However, the physiological temperature of the human body cannot interfere at all with the thermal stability of the systems investigated by thermogravimetry. 3.2. Encapsulation Efficiency and In Vitro TMP Release Profiles According to our calculations, the EE (%) of TMP is (57.95 ± 2.46) %, and the working concentration of TMP can be reached after release (the standard curve used to obtain the value of the EE is plotted in the Supplementary Materials, Figure S2A). Figure 3 shows the in vitro release profile of the TMP (the associated calibration curve is displayed in the Supplementary Materials, Figure S2B). During the first 8 h, the TMP exhibited a burst release of more than 50%, reaching the working concentration that could play a neuroprotective role in the early stage. After this steep increase, the release of the TMP occurred. It was released moderately and sustainedly until the 14th day, when the process leveled off and the cumulative release ratio reached about 80%. 3.3. PLGA/CS NDMs Inhibit the Excessive Proliferation of Fibroblasts During wound healing, fibroblasts are activated. Activated fibroblasts have higher cytoskeleton tension, indicated by obvious stress fibers and contractile phenotype, which enhance the secretion of ECM and promote wound healing and tissue regeneration. A balanced secretion of ECM is essential for wound healing, as the accumulation of excessive ECM can lead to the development of tissue adhesions and cause tissue fibrosis and scar tissue formation [44]. It has been reported that PLGA can reduce the formation of epidural fibrosis [45]. To investigate the effect of the PLGA NDM and PLGA/CS NDM on fibroblasts, we seeded fibroblasts on NDMs for culture and performed cell viability assays on the fibroblasts after 1, 3, and 5 days of cell culture. As shown in Figure 4A, cell viability was increased from day 1 to day 5, regardless of the NDM used for culture. However, cell viability was decreased in the PLGA NDM and PLGA/CS NDM compared to the control group (TCP), in which the cells were cultured under normal conditions, and the PLGA/CS NDM induced lower cell viability than that observed in the PLGA NDM, although there were no statistical differences between the two groups. This is consistent with the previous reports that CS can progressively inhibit the proliferation of fibroblasts in a CS dose-dependent manner [17]. From a morphological point of view, the fibroblasts of the TCP stained with FITC-Phalloidin were compared to the fibroblasts similarly stained and cultured in the presence of NDMs. Fibroblasts on the TCP group showed a normal long spindle shape, while fibroblasts on the PLGA NDM and PLGA/CS NDM groups became more elongated, grew more branched, and overall became irregular in morphology (Figure 4B–D), which means that both the PLGA NDM and PLGA/CS NDM could have affected the growth and morphology of the fibroblasts. These results are in agreement with those of the CCK8. To further determine whether NDMs reduced fibroblast cell viability by decreasing cell proliferation, the fibroblasts were labeled as Ki-67, and the cell proliferation capacity was analyzed. The percentage of Ki-67-positive cells was significantly decreased in the PLGA NDM and PLGA/CS NDM groups compared to the TCP group, and this phenomenon was more pronounced in the PLGA/CS NDM group (Figure 5 and Supplementary Materials, Figure S3), which was consistent with the previous CCK8 results. This suggests that the PLGA/CS NDM repressed cell viability by inhibiting the excessive proliferation of fibroblasts, which is in line with a previous report [46]. The cell viability of the fibroblasts showed an increasing trend in the PLGA/CS NDM group with the passage of culture time, meaning that the PLGA/CS NDM was capable of supporting tissue regeneration in our culture system. However, the PLGA/CS NDM was able to inhibit the excessive proliferation of fibroblasts and, thus, maintain a balanced secretion of ECM. During wound healing, an excessive proliferation of fibroblasts and excessive secretion of collagen type I can cause wound adhesion and ultimately lead to the formation of scar tissue. It has been reported that CS can inhibit the secretion of collagen type I with fibroblasts in scar tissue but has no effect on normal fibroblasts, which also prevents the formation of scar tissue [44,47]. In a few words, these results suggest that PLGA/CS NDM has the potential to both support wound healing and prevent dural adhesion and scar tissue formation. 3.4. PLGA/CS NDMs Promote the Survival of OGD-Treated SH-SY5Y Cells Previous studies have shown that CS degradation products (COS) can promote nerve repair by improving the local microenvironment (in particular, by stimulating Schwann cell proliferation), regulating macrophage migration, and alleviating the cell apoptosis of cortical neurons treated with glucose deprivation [21,48]. In order to investigate whether PLGA/CS NDMs have neuroprotective effects on ischemia–reperfusion brain injury, SH-SY5Y cells underwent an OGD treatment, and the immersion solution of the PLGA NDM and PLGA/CS NDM were mixed 1:1 with fresh complete medium for reperfusion to avoid the direct influence of the topological structure of the NDMs on SH-SY5Y cells. Cell viability was detected with CCK8 after 24 h of reperfusion. In Figure 6A, there was no significant difference in the cell viability between the PLGA NDM group and the OGD/R group, while the cell viability of the PLGA/CS NDM group was significantly improved. This result suggested that PLGA/CS NDM can promote the survival of SH-SY5Y cells treated with OGD/R. In view of these results, we believe that PLGA/CS NDMs are more suitable for neuroprotection as a sustained release carrier. 3.5. The Working Concentration of TMP with Neuroprotective Effect It has been reported that TMP shows good neuroprotective effects on OGD/R-treated SH-SY5Y cells and neurons in in vitro experiments. However, the working concentration of TMP is not identical in different reported investigations, which may be related to the state of the cells, the batch of the drug, the laboratory environment, or the treatment procedure [49,50,51]. To determine the working concentration of TMP upon OGD/R challenge, we used OGD-treated SH-SY5Y cells that were then reperfused with complete medium with different concentrations of TMP. After 24 h of reperfusion, the cell viability was detected with CCK8. The results show that the OGD/R treatment significantly reduced the cell viability of SH-SY5Y cells compared to the control group. TMP (50 μM) did not have an obvious protective effect against OGD/R-induced injury, while 100 μM, 200 μM, and 400 μM of TMP significantly improved the cell viability of OGD/R-treated SH-SY5Y cells, the last two concentrations having almost the same effect (Figure 6B). Therefore, we concluded that TMP has a neuroprotective effect on our culture system when the concentration in the culture medium exceeds 100 μM. 3.6. PLGA/TMP/CS NDMs Promote the Survival of OGD-Treated SH-SY5Y Cells TMP has been shown to have significant neuroprotective effects on ischemia–reperfusion-induced brain injury and has been applied in clinical and basic research. In addition, TMP can diminish the proliferation of fibroblasts [52]. However, the clinical application of TMP has been limited due to its poor water solubility, short half-life, and low concentration of distribution at the injury site. To address these drawbacks, we fabricated a PLGA/TMP NDM with the coaxial electrospinning technique, in which the PLGA serves as a slow-release carrier for the TMP. The TMP was released into the medium by the degradation of the PLGA. To enhance the neuroprotective effect of the NDM, we fabricated a PLGA/TMP/CS NDM by grafting CS onto the PLGA/TMP NDM. However, we did not observe that the PLGA/TMP/CS NDM further reduced the proliferation of fibroblasts compared to the PLGA/CS NDM (Supplementary Materials, Figure S4), possibly because the TMP concentration released from the NDM did not reach the working concentration of 400 μM to diminish the proliferation of fibroblasts, according to the report. To investigate the neuroprotective effects of the PLGA/TMP/CS NDM on ischemia–reperfusion-induced brain injury, SH-SY5Y cells were subjected to OGD treatment. We extracted the immersion solution of the PLGA/TMP/CS NDM after 1, 4, 7, and 14 days, and mixed the immersion solution 1:1 with fresh complete medium for reperfusion after the OGD treatment. After 24 h of reperfusion, the cell viability was tested with CCK8, and the LDH release was assayed. The CCK8 results show that the PLGA/CS NDM promoted the survival of SH-SY5Y as before. The cell viability was further increased with the 1-, 4-, 7-, and 14-day immersion solution of the PLGA/TMP/CS NDM groups compared to the PLGA/CS NDM group. From day 1 to day 14, the cell viability continued to increase (Figure 6C), which may have been due to the COS produced with the CS degradation and the TMP released from the NDM. However, the LDH release assay revealed that the effects of the NDM on LDH release were not obvious. Only 7- and 14-day immersion solution of the PLGA/TMP/CS NDM could significantly reduce the release of the LDH compared to the OGD/R group. (Figure 6D). In conclusion, these results indicate that PLGA/TMP/CS NDM may have long-term neuroprotective effects for ischemia–reperfusion-induced brain injury. 3.7. PLGA/TMP/CS NDM Promote Nerve Repair TMP not only has neuroprotective effects, but it also enhances neurogenesis. COS can facilitate nerve regeneration. To investigate whether PLGA/TMP/CS NDM can promote the regeneration of neural tissue subjected to ischemia–reperfusion injury, we used OGD-treated SH-SY5Y cells and reperfused them with the previous immersion solution for different durations, as described in Figure 6C. The cells were labeled as GAP43. GAP43 is an axonal membrane protein involved in neural outgrowth, synapse development formation, and neural cell regeneration. The expression of GAP43 means that OGD-treated SH-SY5Y cells are undergoing neural regeneration. The labeling results show that the OGD/R treatment slightly increased the expression of the GAP43 protein, but there was no statistical difference. Both the PLGA/CS NDM and PLGA/TMP/CS NDM further increased the expression of the GAP43 protein, while the PLGA NDM did not have such an effect (Figure 7 and Supplementary Materials, Figure S5). The results suggest that COS and TMP may promote the expression of GAP43 during NDM degradation. Regarding the effect of OGD/R treatment on GAP43 protein expression, the results of different studies were inconsistent. This may be related to factors such as the cell status or treatment process. Some researchers consider that OGD injury can activate the endogenous mechanisms of neuroprotection and neuroplasticity, which may promote the expression of GAP43 [53]. We believe that when cells grow well or when the OGD treatment time is short, GAP43 protein expression may be up-regulated. On the contrary, when the cell growth status is poor or the OGD treatment is severe, the expression of the GAP43 protein may be down-regulated. To further clarify the influence of the PLGA/TMP/CS NDM on nerve repair, we stained the actin cytoskeleton and observed the cell morphology. We found that approximately 35% of the SH-SY5Y cells showed pyknosis and lost neurites most likely caused by OGD/R injury. The PLGA NDM and PLGA/CS NDM did not improve the cell morphology. The immersion solution of the PLGA/TMP/CS NDM reduced the damage to the neurites, and the proportion of cells without neurites gradually decreased from day 1 to 14 of the immersion solution (Figure 8A,B). These results indicate that PLGA/TMP/CS NDM can protect the neurites of OGD/R-treated SH-SY5Y cells during degradation. As for the reason the PLGA/CS NDM had no effect, we suppose that the level of COS could not reach the working concentration due to the short immersion time of the NDM, and the time of the cell culture was not enough. We next measured the length of the remaining neurites. As shown in Figure 8C, the lengths of the remaining neurites of the OGD-treated cells reperfused with the PLGA NDM immersion solution were significantly reduced, while they were significantly recovered by those reperfused with the PLGA/TMP/CS NDM immersion solution. We also noted that the PLGA/CS NDM seemed to have had a good effect on the recovery of the lengths of the neurites. Therefore, PLGA/TMP/CS NDM may promote nerve repair with COS and TMP. Interestingly, we found that the results of the nerve repair did not exactly match the CCK8 results. According to our statistical results, the morphology of the OGD/R-treated SH-SY5Y cells seemed to be almost completely restored with the PLGA/TMP/CS NDM, but the cell viability was not regained to normal levels, which might have been a consequence of an insufficient analysis of the cell morphology. Furthermore, no in vivo experiments were carried out, so the physiological significance of PLGA/TMP/CS NDM needs to be further studied. In conclusion, our results suggest that PLGA/TMP/CS NDM systems inhibit the excessive proliferation of fibroblasts in vitro and promote the survival and neural repair of OGD/R-treated SH-SY5Y cells in our culture system. Thus, PLGA/TMP/CS NDM may be an alternative for dural grafts. 4. Conclusions In this paper, we report some PLGA/TMP NDM structures with antifibrotic and neuroprotective effects fabricated with the coaxial electrospinning technique, where the PLGA component was chosen as a slower release carrier. To neutralize the acidic environment generated by PLGA degradation and to enhance the beneficial effect of the NDM (antifibrotic, neuroprotective), we prepared PLGA/TMP/CS NDM by grafting CS on the NDM surface via the EDC/NHS cross-linking method. We found that all NDMs inhibited the excessive proliferation of fibroblasts, but the PLGA/TMP/CS NDM systems were more effective. In terms of neuroprotection, the PLGA/TMP/CS NDM structures were able to promote the survival of OGD/R-treated SH-SY5Y cells as well as nerve repair. In conclusion, the study suggests that PLGA/TMP/CS NDMs may have long-lasting neuroprotective effects and prevent tissue adhesion, fibrosis, and scar tissue formation as dural grafts in undesirable cases of dural injuries. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/polym14091882/s1, Figure S1: The ultraviolet full-wavelength scanning spectrum of TMP; Figure S2: (A) TMP standard curve made with DCM as solvent for calculation of EE. (B) TMP standard curve made with PBS as the solvent for calculation of TMP release amount; Figure S3: Percentage of Ki-67 positive cells as in Figure 4; Figure S4: Cell viability of fibroblasts seeded on seeded on glass slides as the control group (TCP), on PLGA NDM, PLGA/CS NDM, PLGA/TMP NDM and PLGA/TMP/CS NDM after culture of 1, 3 and 5 days; Figure S5: Expression of GAP43 of OGD/R-treated-SH-SY5Y cells as in Figure 6. Click here for additional data file. Author Contributions Z.Z. performed most experiments, analyzed the data, and prepared the manuscript; T.W. conceptualized the idea, directed the study, provided resources, and acquired funding; Y.C. analyzed the data and prepared the manuscript; R.Z. helped with the electrospinning and cell culture; Q.W. acquired funding, provided resources, and prepared the manuscript; R.X. acquired funding, administrated the project, and prepared the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study did not require ethical approval. Informed Consent Statement This study did not involve humans. Data Availability Statement The original contributions presented in the study are included in the article/Supplementary Materials; further inquiries can be directed to the corresponding author. Conflicts of Interest The authors declare no competing financial interests. Figure 1 (A–C) SEM images showing the PLGA NDM (A), the PLGA/TMP NDM (B), and the PLGA/CS NDM (C). (D) FTIR spectra of the PLGA NDM, CS, and PLGA/CS NDM. Figure 2 (A) Stress–strain curves of PLGA NDM and PLGA/CS NDM. (B) TGA profiles of PLGA NDM, PLGA/CS NDM, and PLGA/TMP NDM. Figure 3 TMP release profiles in vitro from PLGA/TMP/CS NDM (measurements were performed in triplicate). During the first 8 h, the TMP exhibited a burst release of more than 50%. Figure 4 (A) Cell viability of fibroblasts seeded on glass slides as the control group (TCP), on PLGA NDM and PLGA/CS NDM after culture of 1, 3, and 5 days. *** p < 0.001 as compared with TCP. (B–D) Fluorescence micrographs showing the morphology of the fibroblasts after 5 days of culture. (B) TCP cells. (C) Cells seeded on PLGA NDM. (D) Cells seeded on PLGA/CS NDM. The cell nuclei were stained with DAPI (blue), and the actin cytoskeleton was stained with Phalloidin-iFluor 488 (FITC, green). Data of 3 replicates are plotted in Figure 4A. Figure 5 Fluorescence micrographs displaying Ki-67-positive fibroblasts seeded on TCP (i), PLGA NDM (ii), and PLGA/CS NDM (iii) after 5 days of culture. The cell nuclei were stained with DAPI (blue) and the cell nuclei with Ki-67-positive were labeled with red, meaning the cells were proliferating. Figure 6 (A) Cell viability of OGD-treated SH-SY5Y cells—treated for 3 h and reperfused with immersion solution of PLGA NDM and PLGA/CS NDM mixed 1:1 with fresh complete medium. (B) Cell viability of OGD-treated SH-SY5Y cells—treated for 3 h and reperfused with complete medium containing different concentrations of TMP. *** p < 0.001 as compared with the TCP. # p < 0.05 and ### p < 0.001 as compared with the cells reperfused only with complete medium. (C) Cell viability of OGD-treated SH-SY5Y cells—treated for 3 h and reperfused with immersion solution of PLGA/CS NDM and PLGA/TMP/CS NDM. The durations of the PLGA/TMP/CS NDM immersion were 1 day, 3 days, and 5 days, respectively, to obtain the corresponding immersion solutions. (D) LDH release assay of OGD-treated SH-SY5Y cells—treated for 3 h and reperfused with immersion solution of PLGA NDM, PLGA/CS NDM, and PLGA/TMP/CS NDM. Figure 7 Fluorescence micrographs showing the expression of GAP43 of SH-SY5Y cells. (i) TCP cells. (ii) The cells treated with OGD for 3 h and reperfused only with complete medium. (iii,iv) The OGD-treated cells reperfused with immersion solutions of PLGA NDM (iii) and PLGA/CS NDM (iv). (v–viii) The OGD-treated cells reperfused with immersion solution of PLGA/TMP/CS NDM, with durations of NDM immersion of 1 day (v), 4 days (vi), 7 days (vii), and 14 days (viii). Figure 8 (A) Fluorescence micrographs showing the morphology of SH-SY5YS cells treated with OGD/R for 2 days. (i) TCP cells. (ii) The cells treated with OGD for 3 h and reperfused only with complete medium. (iii,iv) The cells treated with OGD and reperfused with immersion solution of PLGA NDM (iii) and PLGA/CS NDM (iv). (v–viii) The cells treated with OGD and reperfused with immersion solution of PLGA/TMP/CS NDM, the durations of which were 1 day (v), 4 days (vi), 7 days (vii), and 14 days (viii). (B) The percentage of cells after 2 days of OGD/R treatment. (C) Lengths of neurites of the cells after 2 days of OGD/R treatment. * p < 0.05 and *** p < 0.001 as compared to TCP. # p < 0.05, ## p < 0.01 and ### p < 0.001 as compared to OGD/R. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Suwanprateeb J. Luangwattanawilai T. Theeranattapong T. Suvannapruk W. Chumnanvej S. Hemstapat W. Bilayer oxidized regenerated cellulose/poly ε-caprolactone knitted fabric-reinforced composite for use as an artificial dural substitute J. Mater. Sci. Mater. 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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/ijerph19095168 ijerph-19-05168 Case Report Madelung’s Disease as an Example of a Metabolic Disease Associated with Alcohol Abuse—Diagnostic Importance of Computed Tomography Jaźwiec Przemysław 1 Pawłowska Maria 1 Czerwińska Karolina 2 https://orcid.org/0000-0002-4868-3088 Poręba Małgorzata 3 https://orcid.org/0000-0001-8366-0239 Gać Paweł 2* Poręba Rafał 4 Gupta Bhawna Academic Editor 1 Specialist Medical Center in Polanica-Zdrój, Jana Pawła II 2, 57-320 Polanica Zdrój, Poland; przemkolog@wp.pl (P.J.); maria.pawlowska@yahoo.pl (M.P.) 2 Division of Environmental Health and Occupational Medicine, Department of Population Health, Wroclaw Medical University, Mikulicza-Radeckiego 7, 50-368 Wroclaw, Poland; karolina.czerwinska@student.umw.edu.pl 3 Department of Paralympic Sports, Wroclaw University of Health and Sport Sciences, Witelona 25a, 51-617 Wroclaw, Poland; poreba1@wp.pl 4 Department of Internal Medicine, Occupational Diseases and Hypertension, Wroclaw Medical University, Borowska 213, 50-556 Wroclaw, Poland; rafal.poreba@umw.edu.pl * Correspondence: pawelgac@interia.pl or pawel.gac@umw.edu.pl; Tel.: +48-717-841-502 24 4 2022 5 2022 19 9 516811 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/). Madelung’s disease is a rare metabolic disorder characterized by a symmetrical accumulation of nonencapsulated adipose tissue deposits, mainly around the head, neck and shoulders. Fat deposits can grow and put pressure on other organs causing a variety of symptoms, inter alia, dysphagia, breathing difficulties, neck stiffness and headache. Madelung’s disease is often accompanied by other disorders such as diabetes, hypertension, hypothyroidism, or liver disease. In addition to somatic issues, mental health problems may also develop causing social exclusion and depression. Middle-aged men with a history of alcohol abuse are the most commonly affected. Various imaging techniques, including computed tomography (CT), are helpful in stating the diagnosis. This paper presents a case of a 33-year-old man with extensive adipose tissue overgrowth around neck and chest. CT-enhanced scans with multiplanar reconstruction (MPR) and volume rendering technique (VRT) reconstruction are also included. Madelung’s disease lipomatosis alcohol abuse ==== Body pmc1. Introduction Madelung’s disease, also known as Benign Symmetrical Lipomatosis (BSL) or Launois–Bensaude syndrome, is a rare metabolic disorder. It is manifested by a symmetrical accumulation of nonencapsulated adipose tissue deposits, mainly around the head, neck and shoulders [1]. Fat deposits can grow rapidly (within months) or slowly over the years, causing a variety of symptoms, inter alia, dysphagia, breathing difficulties, neck stiffness and headache. BSL can occur in all ethnic groups but is usually found in Mediterranean and European populations. Men aged 30–60 years, chronically abusing alcohol are the most commonly affected [2]. The etiology of BSL is not fully known; however, an association with a defect in noradrenergic mitochondrial regulation of brown adipose tissue (BAT) is suggested. Differential diagnosis should primarily include obesity, goiter, Cushing’s disease and neoplastic changes. Surgical removal of lipomas or liposuction are the leading treatment methods; however, fat deposits tend to recur despite treatment [3]. The paper presents the case of Madelung’s disease as an example of a metabolic disease associated with alcohol abuse in order to emphasize the diagnostic importance of computed tomography in the assessment of morphology and the differentiation of this pathology. 2. Case Report A 33-year-old obese man with arterial hypertension and alcohol dependence syn-drome (for over 10 years) presented to the Diagnostic Imaging Department for a neck and chest CT scan due to adipose tissue overgrowth. The patient had a history of numerous enlarging subcutaneous tissue deposits growing in different areas of the body for about 5 years. Moreover, due to chronic chest pain, he often presented to the Emergency Department. In March 2021, he was admitted to the Emergency Department for nonspecific abdominal pain after 11 days of excessive alcohol consumption. On admission, he was intoxicated (3.77 g/L), confused and had slurred speech, and his medical history was difficult to ascertain. He claimed to have had breathing problems for a long time, which he treated with alcohol. He was taking alprazolam (Afobam) chronically and underwent an alcohol abuse treatment. Physical examination revealed significant enlargement of the neck circumference (which was also reported during previous visits to the Emergency Department). The patient was circulatory and respiratory efficient, his abdomen was soft, nontender, and there was an excess of fatty tissue in the lower abdomen. His laboratory results were as follows: red blood cells (RBC) 3.70 million/µL [4.54–5.78]—indicating mild macrocytic anemia—hemoglobin (HGB) 12.3 g/dL [13.3–17.2], mean corpuscular volume (MCV) 98.1 fL [81.2–94], non-elevated inflammatory markers, significantly elevated levels of GGTP 2313 U/L [<55], AST 222 U/L [<35], ALAT 102 U/L [<50], and lipase 81 U/L [<67]. No prohibited substances were found in the drug panel that was performed. Abdominal ultrasound examination revealed fatty liver and gallbladder sludge. He was discharged from the department and advised to continue treatment on an outpatient basis. In December 2021, he was consulted at the surgical clinic and endocrinology clinic. The examination confirmed adipose tissue overgrowth in many locations, i.e., within neck, shoulders, chest, lower abdomen. There was no evident muscle atrophy. Neck ultrasound showed numerous adipose tissue deposits and an inflamed lymph node (15 × 10 mm) around right mandibular angle with increased hilar vascularity. A CT scan of the neck and chest was ordered to assess the extent of the adipose tissue overgrowth. CT-enhanced scans were obtained, following which multiplanar reconstruction (MPR) and volume rendering technique (VRT) reconstruction were created (see Figure 1). Location of the fatty deposits and their thickness, based on the CT scan, are presented in Table 1 and Table 2. The values presented in the tables refer to the maximum thickness of adipose tissue measured in the indicated locations, with approximation to 5 mm. Other CT findings included parotid and submandibular glands enlargement (with no noticeable focal changes), loss of physiological cervical lordosis, glandular breast tissue overgrowth, thoracic spine arthritis and Schmorl nodules. In general, the CT scan showed commonly reported imaging features of Madelung disease. The patient was qualified for conservative treatment. Absolute prohibition of alcohol consumption (addiction treatment) and weight reduction were recommended. Moreover, the patient was referred for rehabilitation to improve physical efficiency. 3. Discussion Madelung’s disease is also known as Benign Symmetrical Lipomatosis (BSL), Multiple Symmetrical Lipomatosis (MSL) or Launois–Bensaude syndrome [1,2]. It was first described by Benjamin Brodie in 1846. Over 40 years later, Otto Madelung (1888), and after another 10 years Pierre-Émile Launois and Raoul Bensaude (1898), presented more cases of patients with this condition [3]. Madelung’s disease is a rare disorder (1:25,000) characterized by an excessive symmetrical growth of unencapsulated fatty deposits around the head, neck, upper chest, arms, as well as hips and thighs [2,3]. The etiology of BSL is not fully understood [4]. Most often it affects men (M:F—15:1) aged 30–60, chronically abusing alcohol [5]. However, it has also been reported in women and non-alcohol users [6,7]. Cytopathy of brown adipose tissue and disturbances in lipid metabolism are considered as possible causes. It is suggested that excessive alcohol consumption may impair adrenergic lipolysis and lead to an uncontrolled deposition of fat masses in various parts of the body [1,2]. There are two main systems of classifying Madelung disease. The first one, created in 1984 by G. Enzi, distinguishes two types of fat masses distribution. Type 1, characterized by the location of changes in the nape, neck and shoulders, creating an image of the so-called “Horse collar” (“Madelung’s collar”). As a result, patients have a “pseudoathletic” appearance. Type 2, characterized by the location of fat masses in the abdomen, hips and thighs. The second classifying system, created in 1991 by G. Donhauser, divides BSL patients into four groups: type I (horsecollar), II (pseudo athletic type), III (gynecoid type), IV (abdominal type) [3]. Initially, aesthetic reasons encourage patients to seek medical advice. However, as the disease progresses, growing fat masses may put pressure on other structures, i.e., trachea, larynx, pharynx, esophagus or blood vessels, and cause symptoms. Depending on the severity of the disease, patients may experience breathing difficulties, speaking difficulties, dysphagia, as well as reduced neck mobility or general mobility [2]. Madelung’s disease is often accompanied by other disorders such as diabetes, hypertension, hypothyroidism, or liver disease. Neurological disorders in the form of polyneuropathy may also develop. They are the result of alcoholic demyelination and degeneration of axonal nerve fibers [4,5]. It should be remembered that in addition to somatic issues, BSL also affects mental health and can lead to social exclusion and depression. The diagnosis of Madelung’s disease is symptomatic. Diagnosis involves the correlation of clinical data and images from diagnostic imaging. It is important to exclude other diseases with excessive adipose tissue. In response to the variety of possible symptoms differential diagnosis should consider numerous diseases, i.e., obesity, thyroid goiter, lipoma, liposarcoma, Cushing’s disease, cysts of the neck, diseases of the salivary glands, thyroid cancer, leukemia or soft tissue sarcoma [8]. BSL is characterized by a symmetrical distribution of adipose tissue, sparing the peripheral parts of the limbs, and by a history of excessive alcohol consumption. Ultrasound, computed tomography and magnetic resonance imaging are used to describe the location and extent of fatty deposits. A very important feature of BSL, which is confirmed in diagnostic imaging studies, is the lack of pathology boundaries from the surrounding tissues, e.g., no encapsulation. A biopsy is not required to confirm the diagnosis. However, it may be useful to rule out liposarcoma, for lesions characterized by a mixed nature—focal lesions among diffuse pathology [8]. BSL treatment can be divided into surgical and non-surgical methods. Surgical removal of fatty deposits is the most used treatment. The effects of surgery are often unsatisfactory and do not give long-term results. Patients may require multiple resections as the changes tend to recur. In some BSL cases, extensive lipectomy combined with liposuction or isolated liposuction is recommended [2,9]. Intralipotherapy, i.e., injection lipolysis, is one of the recommended methods of non-invasive treatment [9]. In this method phosphatidylcholine/sodium deoxycholate is applied directly to the adipose tissue [10]. Dietary treatment and manual therapy are usually ineffective. Weight loss can only limit the progression of the disease in some cases [4]. Limiting alcohol consumption does not reduce lipomas; nevertheless, it is recommended for its positive effect on the accompanying metabolic disorders and reduced mortality [4]. The presented case is an example of rare pathologies related to adipose tissue, which should be kept in mind in times of increasing obesity epidemic. At the same time, it is an example of an environmental and behavioral disease, an example indicating a less known mechanism of alcohol toxicity—a mechanism related to the influence of ethanol on the metabolism of adipose tissue. It can be an additional useful argument for the prevention of alcohol dependence. What is no less important is that the case shows the importance of modern methods of imaging diagnostics (in the discussed case computed tomography) in the diagnosis and differential diagnosis of the discussed pathology. Previously published articles mainly presented clinical data, often supplemented with photos from a physical examination. In the present article, we present high-quality computed tomography images, at the same time indicating the characteristics of the pathology that enable us, in correlation with clinical data, to make a diagnosis by excluding other diseases. The applied diagnostic procedure with the use of computed tomography also allows avoiding invasive diagnostics in most cases, which is also indicated by the presented case. 4. Conclusions Computed tomography with MPR and VRT reconstructions is an important diagnostic tool for Madelung’s disease, enabling the assessment of the extent of lesions and treatment planning, as well as, in correlation with clinical data, differentiation with other diseases with excessive development of adipose tissue. Author Contributions Investigation, P.J. and M.P. (Maria Pawłowska); resources, M.P. (Maria Pawłowska) and K.C.; writing—original draft preparation, P.J. and M.P. (Maria Pawłowska); writing—review and editing, K.C., M.P. (Małgorzata Poręba) and P.G.; visualization, P.J. and P.G.; supervision, R.P. All authors have read and agreed to the published version of the manuscript. Funding The APC was funded by Wroclaw Medical University. Institutional Review Board Statement The manuscript contains a presentation of the description of diagnostic tests of a selected patient; the work does not describe a medical experiment—the opinion of the bioethics committee was not required. Informed Consent Statement The authors certify that they have obtained all appropriate patient consent. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Computed tomography of the neck. (A) Axial reconstruction. (B) MPR reconstruction, frontal view. (C) MPR reconstruction, sagittal view. (D) VRT reconstruction. ijerph-19-05168-t001_Table 1 Table 1 Computed tomography of the neck. The exact location of adipose tissue overgrowth and measurement of its thickness. Neck CT Exact Location Fat Layer Thickness [mm] left side of the neck 50 right side of the neck 50 chin area 70 infrahyoid region 60 right neck triangle 40 left neck triangle 30 ijerph-19-05168-t002_Table 2 Table 2 Computed tomography of the chest. The exact location of adipose tissue overgrowth and measurement of its thickness. Chest CT—Anterior Part of the Chest Right side Left side Exact location Fat layer thickness [mm] Exact location Fat layer thickness [mm] Upper part 30 Upper part 20 Middle part 25 Middle part 15 Lower part 20 Lower part 15 Chest CT—Lateral Part of the Chest Right side Left side Exact location Fat layer thickness [mm] Exact location Fat layer thickness [mm] Upper part 40 Upper part 30 Middle part 30 Middle part 40 Lower part 28 Lower part 30 Chest CT—Posterior Part of the Chest Right side Left side Exact location Fat layer thickness [mm] Exact location Fat layer thickness [mm] Upper part 20 Upper part 20 Middle part 25 Middle part 25 Lower part 30 Lower part 35 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Szewc M. Sitarz R. Moroz N. Maciejewski R. Wierzbicki R. Madelung’s disease—Progressive, excessive, and symmetrical deposition of adipose tissue in the subcutaneous layer: Case report and literature review Diabetes Diabetes Metab. Syndr. Obes. Targets Ther. 2018 11 819 825 Available online: https://www.dovepress.com/madelungs-disease-progressive-excessive-and-symmetrical-deposition-of-peer-reviewed-fulltext-article-DMSO#ref6 (accessed on 2 February 2022) 10.2147/DMSO.S181154 30538518 2. Rare Disease Database Available online: https://rarediseases.org/rare-diseases/madelungs-disease/ (accessed on 2 February 2022) 3. Schiltz D. Anker A. Ortner C. Tschernitz S. Koller M. Klein S. Felthaus O. Schreml J. Schreml S. Prantl L. Multiple Symmetric Lipomatosis: New Classification System Based on the Largest German Patient Cohort Plast. Reconstr. Surg. Glob. Open 2018 6 e1722 Available online: https://journals.lww.com/prsgo/Fulltext/2018/04000/Multiple_Symmetric_Lipomatosis__New_Classification.14.aspx (accessed on 2 February 2022) 10.1097/GOX.0000000000001722 29876171 4. Musialik K. Bogdański P. Nawrocka M. Choroba Madelunga—Opis przypadku i przegląd piśmiennictwa Forum Zaburzeń Metab. 2012 3 147 153 5. Waniczek D. Kamińska E. Kamiński T. Pilch J. Nawrocki P. Łagodna symetryczna tłuszczakowatość—Choroba metaboliczna o nieznanej etiologii Ann. Acad. Med. Silesiensis 2012 66 85 90 Available online: http://psjd.icm.edu.pl/psjd/element/bwmeta1.element.psjd-44ac6335-27fa-4f9c-8424-fe877d6b2a2d (accessed on 2 February 2022) 6. Ouahabi H. Doubi S. Lahlou K. Boujraf S. Ajdi F. Launois-Bensaude Syndrome: A Benign Symmetric Lipomatosis without Alcohol Association Ann. Afr. Med. 2017 16 33 34 Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5452705/ (accessed on 2 February 2022) 28300050 7. Gozzo C. Galioto F. Palmucci S. Signorelli S. Basile A. A non–alcohol-related case of Madelung’s disease: Challenging patient with progressive jugular vein distension Radiol. Case Rep. 2021 16 1183 1187 Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985283/ (accessed on 2 February 2022) 10.1016/j.radcr.2021.02.050 33777283 8. Ardeleanu V. Chicos S. Georgescu C. Tutunaru D. Multiple benign symmetric lipomatosis—A differential diagnosis of obesity Chirurgia 2013 108 580 583 Available online: https://pubmed.ncbi.nlm.nih.gov/23958107/ (accessed on 2 February 2022) 23958107 9. Chen C. Fang Q. Wang X. Zhang M. Zhao W. Shi B. Wu L. Zhang L. Tan W. Madelung’s Disease: Lipectomy or Liposuction? BioMed Res. Int. 2018 2018 3975974 Available online: https://www.hindawi.com/journals/bmri/2018/3975974/ (accessed on 2 February 2022) 10.1155/2018/3975974 29682541 10. Mlosek R. Skrzypek E. Migda B. Migda M. Woźniak W. The efficacy of high-frequency ultrasound-guided injection lipolysis in reducing fat deposits located on the inside of the knees J. Ultrason. 2020 20 e273 e278 Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830143/ (accessed on 2 February 2022) 10.15557/JoU.2020.0048 33500794

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==== Front Nanomaterials (Basel) Nanomaterials (Basel) nanomaterials Nanomaterials 2079-4991 MDPI 10.3390/nano12091411 nanomaterials-12-01411 Article Dynamics of Quasi-One-Dimensional Structures under Roughening Transition Stimulated by External Irradiation Gorshkov Vyacheslav N. 12* Tereshchuk Volodymyr V. 1 Bereznykov Oleksii V. 1 Boiger Gernot K. 3 Fallah Arash S. 4 Busani Tito Academic Editor 1 Igor Sikorsky Kyiv Polytechnic Institute, National Technical University of Ukraine, 37 Prospect Peremogy, 03056 Kiev, Ukraine; volodymyr379@gmail.com (V.V.T.); alexber36@gmail.com (O.V.B.) 2 Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY 13699, USA 3 Institute of Computational Physics, Zürich University of Applied Sciences, Wildbachstrasse 21, 8401 Winterthur, Switzerland; boig@zhaw.ch 4 Department of Mechanical, Electronic and Chemical Engineering, OsloMet, Pilestredet 35, St. Olavs Plass, 0130 Oslo, Norway; arashsol@oslomet.no * Correspondence: v.gorshkov@kpi.ua 20 4 2022 5 2022 12 9 141124 2 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/). We studied the striking effect of external irradiation of nanowires on the dynamics of their surface morphology at elevated temperatures that do not destroy their crystal lattice. Numerical experiments performed on the basis of the Monte Carlo model revealed new possibilities for controlled periodic modulation of the cross-section of quasi-one-dimensional nanostructures for opto- and nanoelectronic elements. These are related to the fact that external irradiation stimulates the surface diffusion of atoms. On the one hand, such stimulation should accelerate the development of the well-known spontaneous thermal instability of nanowires (Rayleigh instability), which leads to their disintegration into nanoclusters. On the other hand, this leads to the forced development of the well-known roughening transition (RT) effect. Under normal circumstances, this manifests itself on selected crystal faces at a temperature above the critical one. The artificial stimulation of this effect on the lateral surface of quasi-one-dimensional structures determines many unpredictable scenarios of their surface dynamics, which essentially depend on the orientation of the nanowire axis relative to its internal crystal structure. In particular, the long-wave Rayleigh breakup observed in absence of external irradiation transforms into strongly pronounced short-wave metastable modulations of the cross-section (a chain of unduloids). The effect of the self-consistent relationship between the Rayleigh instability and RT is dimensional and can be observed only at relatively small nanowire radii. The fact is analyzed that, for the manifestation of this effect, it is very important to prevent significant heating of the nanowire when surface diffusion is stimulated. A number of developed theoretical concepts have already found confirmation in real experiments with Au and Ag nanowires irradiated by electrons and Ag+ ions, respectively. nanostructure instabilities nanowire breakup roughening transition anisotropy of surface energy density Monte Carlo kinetic model ==== Body pmc1. Introduction The physical and chemical properties of semiconductor and metallic nanowires are of growing interest, due to their potential applications in a number of electronic, optoelectronic, and electromechanical devices. In particular, the advantageous characteristics of face-centered cubic (FCC) nanowires allow the use of these structures in biosensors [1,2,3,4], elements of solar panels [5,6], as well as in plasmonic waveguides [7]. High electrical and low thermal conductivity [8,9], optical absorption characteristics [10,11,12], and quantum confinement effects [13] make silicon nanorods potentially useful as building blocks for thermoelectric and photonic devices such as nanoconductive field-effect transistors [14,15,16], hypersensitive biological, chemical or mass sensors [17,18,19,20,21,22,23,24,25], and photodetectors [26,27,28]. The electrical and optical properties of quasi-one-dimensional nanostructures essentially depend on the morphology of their surface, which may vary periodically along the axis. In particular, modern methods of nanostructure synthesis make it possible to create 1D core–shell nanowires with different surface morphology that are now used in solar energy conversion and electrochemical energy storage [29,30,31]. In our study, we consider the theoretical foundations of methods for creating periodically modulated structures based on the general physical concepts expounded in the sequel. The transformation of a nanowire initially uniform in cross-section into an ordered chain of nanobeads is associated with mass transfer along its surface. This transfer is due to the surface diffusion of atoms, which increases with increasing temperature. Spontaneous periodic modulation of the surface must satisfy a number of thermodynamic relations and equations of motion of the medium. The first requirement allows a large set of “trajectories” for the dynamic evolution of the system, which is subsequently significantly narrowed down when it is necessary to satisfy the equations of motion. The selected trajectories lead to the dominance of periodic modulations of the nanowire radius with a wavelength, λmax, which corresponds to the maximum growth increment, γmax. The value of λmax is determined by the inhomogeneity of the distribution over the surface of sets of two probabilities. The first characterizes the probability of atoms jumping, which depends on the energy of the activation barrier in the initial state. If the jump occurs, then the probabilities of its directions depend on the number of nearest neighbors in the new positions. Different relations between the distributions of the two indicated types of probability, which depend on temperature, lead to corresponding different wavelengths of perturbations. The frequently observed breakup of nanowires into individual nanodroplets is often associated with the Rayleigh instability of liquid jets. However, the approach of isotropic surface energy density used in this particular case significantly reduces the applicability of the developed physical concepts for interpreting the dynamics of crystalline nanostructures. For nanowires with pronounced anisotropy, the “number of degrees of freedom” increases and determines a greater variety of scenarios for the nanowire surface dynamics. By varying its temperature and axis orientation, the relationship between the two sets of probabilities mentioned above changes. The additional degree of freedom associated with an artificial change in the probability distribution of jumps leads to even greater diversity in the evolution of nanostructures. The purpose of our research is shown in the context of a brief review of the previous results by predecessors. The disintegration of nanowires into separate fragments as a result of thermal instability has been studied in numerous experimental [32,33,34,35,36,37,38,39] and theoretical studies [40,41,42,43,44,45]. In the Nichols and Mullins model [40], it was assumed that the surface energy density, σ, of a nanowire is isotropic (does not depend on the orientation of a given fragment of the lateral surface with respect to the preserved internal crystal structure of the nanowire). In the absence of internal flows, the surface diffusion of atoms determines the dynamics of the nanowire surface morphology. However, the result obtained for the wavelength of perturbations, λmax, growing in time with a maximum increment, γmax, coincides with the result of the classical Rayleigh theory: λmax=9.02rnw where rnw is the initial radius of the nanowire [40,46]. The disintegration of nanowires into nanoclusters, the volumes of which correspond to the volume of the section of the initial nanowire with a length λmax, was indeed observed in experiments [38,39]. However, in numerous studies, significant deviations from the predictions of the Nichols and Mullins theory (λmax/rnw∼25−30 в [33,34,36]) are noted. The reasons for these deviations are related to the anisotropy of the surface energy density and were studied in detail in recent research [46,47,48]. It is shown that, depending on the orientation of the nanowire axis relative to its internal crystal structure, the value of the breakup parameter β (β=λmax/rnw)) can be either noticeably higher than 9 or lower than the threshold value 2π (in the case of isotropic σ, the nanowire surface is stable against perturbations of the radius with wavelength λ<λcr=2πrnw). The next factor that can be responsible for nanowire transformation is the roughening transition (RT) [49,50,51,52,53,54,55,56,57]. If the temperature of the system is greater than a certain critical value (T>TR), then periodic “hillocks and cavities” develop on a smooth crystalline face. It is worth noting that this effect occurs only on selected crystal faces. Its occurrence on the side surface of the nanowire is not ruled out either, since, at the initial stage of transformation of a cylindrical nanowire, it is fragmentarily limited by longitudinal edge strips with the lowest possible total surface energy (Figure 1A(a)). Thus, the dynamics of the surface of a nanowire can be determined by two physical mechanisms—Rayleigh instability and RT—which arise with an increase in temperature and are associated with the intensification of the surface diffusion of atoms. However, we are not aware of publications in which the authors of experimental studies discuss any manifestation of RT in the breakup of nanowires when interpreting the results obtained. One of the probable reasons is that the temperature of the nanowire during a breakup is below the critical one, T<TR. It is also possible that the Rayleigh instability development increment is much higher than the RT increment. In our research, we study the possibilities of controlling the surface dynamics of quasi-one-dimensional nanostructures in the case of their surface exposure to external irradiation (for example, with light, an external electron flow or Ar+-ions of a cold plasma), which initiates the manifestation of RT. In this case, it is important that the external action, which stimulates the surface diffusion of atoms, does not lead to significant heating of the wire. It sounds paradoxical, but a possible “overheating” may eliminate the role of RT against the background of the development of the Rayleigh instability. A weighty argument for our theoretical studies was the results of experiments with gold [32] (electron irradiation) and silver [58] nanowires (irradiation with Ar+-ions). The most interesting scenarios for the transformation of nanowires arise at small radii—rnw≲5 nm. The requirements of smallness for the cross-section of a nanowire are clearly demonstrated in Figure 1, which shows the results of our numerical simulations. Surface modulations appear on the (100)-type facet strips precisely because of the stimulated RT. One can see that the length of the formed nanohillocks is comparable to the radius rnw(lx~rnw)), which is noticeably lower than the so-called “energy threshold”, which prohibits the fragmentation of the nanowire into fragments with a length, l, where l<∆lmin≈4.5rnw (at l=∆lmin, the surface energy of the formed nanodroplets is equal to the surface energy of the initial nanowire). Thus, the RT effect on the surface of a relatively thick nanowire will only lead to small-scale perturbations of the surface without a significant self-consistent phenomenon with the influence of Rayleigh instability on the subsequent dynamics of its morphology. In a rough approximation, such an influence should be expected in the case of lx≳4.5rnw, or rnw≲lx/4.5≈12a. Thus, for gold, the stimulated RT effect should most strikingly appear at rnw≲5nm. This estimate is in good agreement with the results of numerical simulations obtained below. In the present study, we show that stimulation of the surface diffusion of atoms by external irradiation is an effective tool for controlling the parameters of generated quasi-one-dimensional periodic nanostructures. Depending on the orientation of the nanowire axis, the breakup parameter, β, can be controlled over a wide range. For instance, with the same initial radius of the (110)-oriented nanowire, the value of β can be reduced from β~25−30 (disintegration into “nanodroplets” in the absence of irradiation) to β~4−5 (formation of unduloids [59]—frozen in time-periodic modulations of the nanowire cross-section). An inverse dependence of the parameter β on the level of stimulation of surface diffusion is also possible: in the case of the (111) orientation, an increase in the irradiation intensity transforms relatively short-wavelength perturbations (β<9) into long-wavelength ones (β~20). Therefore, through fragmentary irradiation of a nanowire, it is possible to generate chains of nanoclusters from a single nanowire with a variable frequency of gaps between them. These have potential applications in biomedicine and spectroscopy [60]. In this research, the influence of the stimulated roughening transition on the evolution of nanowires is studied, with a detailed qualitative analysis of the ongoing physical processes based on the Monte Carlo model—as presented in the next section. 2. Numerical Model The applied Monte Carlo (MC) model has been successfully used to simulate nonequilibrium surface growth [61], synthesis of nanoparticles [62], and formation of nanopillars and nanoclusters for sintering and catalysis applications [63,64,65]. The present numerical approach has also been applied to study the disintegration of nanowires with diamond-like and body-centered cubic (BCC) lattice structures [49,50]. Based on this MC numerical model, the synthesis of periodical core–shell nanostructures was also investigated [66]. In this section, we only present the basic concepts of the given MC method. A complete description of the applied MC approach can be found in [66]. In the simulations conducted, the computational domain has a cylindrical shape of length, L and radius R. The nanowire of radius rnw (R≫rnw)), with its atoms occupying the lattice sites of an FCC lattice structure, is inserted into the domain in such a way that the axes of the nanowire and the cylinder are coincident. Surface atoms can hop to the nearest vacancies or detach from the nanostructure and become free according to probabilistic relations given below. The detached atoms hop in random directions within the boundaries of the computational domain with a constant length step, l, the magnitude of which equals half of the lattice constant, a. The walls of the container are assumed reflective, so the number of atoms in the entire system under consideration is time-invariant. Free atoms can reattach to the surface of the crystalline structure at vacant sites that are adjacent to the sites occupied by nanostructure atoms. Each site is represented by a region of space within the Wigner–Seitz unit cell in the lattice. When an atom jumps into one of Wigner–Seitz’s cells, it is located at the center of that cell and becomes attached to the nanostructure. To simulate the surface dynamics of nanostructures, two parameters are used in the model. The first parameter α has its magnitude as ε scaled per kT, where k is the Boltzmann constant, T is the temperature of the system, and ε<0  reflects the local binding of adjacent atoms:(1) α=ε/kT The second parameter, p, determines the surface diffusion coefficient and depends on the activation/energy barrier, Δ, defined as follows:(2) p=exp−Δ/kT For a system consisting of N0 atoms one MC step consists of the following operations repeated N0 times: (1) the random selection of an atom; (2) the determination of its new position. Thus, on average, each atom is selected once per one MC step. If an atom has nvac unoccupied neighboring lattice sites, it may jump into one of them with the probability pjump calculated as follows:(3) pjump=pm0 where m0 represents the number of nearest neighbors (occupied lattice sites). If the jump occurs, the new position of the atom is chosen from the nvac+1 lattice sites (the initial state is also included). The “direction” of the jump made is randomly chosen according to the probabilities of the target sites, ptargeti(i=1,2,3,…nvac+1), which are equal to (4) ptargeti=γ×expmtiεkT 𝛾=∑j=1nvac+1expmtjε/kT−1 where mti denotes the number of nearest neighboring atoms in the assumed new state, indexed by (i). Therefore, the final position is determined by a set of Boltzmann factors. In our model, a change in the temperature is reflected by varying the parameter α (note that α~1/T , using Equation (1)). The relation between the parameters α and p is described by the following equation [48]:(5) p=p0α/α0 The good agreement between experimental results and our previous numerical studies [46,47,48] was obtained using the following reference values for the FCC lattice: α0=1.0 and p0=0.7. In subsequent numerical simulations, the effect of external irradiation on the surface diffusion of atoms is included in the increase in the parameter p, which is responsible for the jump frequency. Let us expound on some technical details of the applied model. When modeling the breakup of nanowires, we make the last five atomic layers on both ends of the nanowire composed of frozen (“motionless”) lattice atoms. This is an undertaking equivalent to the imposition of periodic boundary conditions and is conducted to exclude the so-called end effects [47,48] at the early stages of the disintegration process. Our MC model considers only the interaction of atoms with their nearest neighbors. We do not consider the interaction of atoms with second- or higher-order neighbors, mainly because according to experimental studies [67] these make a small contribution to the potential or force in the case of an FCC lattice. Additionally, when modeling the dynamics of an unstable system, we do not specify the type of initial perturbations as they develop naturally due to thermal fluctuations inherent in this model. Before presenting the results obtained, the following remark is in order: The RT effect on a flat crystalline face is associated with the formation of clusters from atoms that have jumped from the same face into the near-surface layer of vacancies (we mark this layer with the index +1). An increase in the crystal temperature leads to a decrease in the degree of anisotropy both in the frequency of hops over the surface of the structure (the parameter p increases) and the probability distribution over the possible directions of hops (the parameter α decreases). In this case, two physical processes compete. On the one hand, the flow of atoms from the surface 0-layer to the +1-layer increases, increasing the density of mobile atoms in this layer. On the other hand, an increase in temperature hinders homogeneous nucleation in a two-dimensional/surface “gas” of these atoms. The dominance of the first factor is achieved at T > Tk only on selected crystalline faces and determines the appearance of ordered structures on them with a characteristic size, lRT. Given the possibility of developing such an effect on the lateral surface of the nanowire, there is no reason to compare the size of the fragments during its breakup with the classical parameter 9rnw. The natural manifestation of RT in the dynamics of one-dimensional nanosystems was considered in our studies for BCC [50] and diamond-like crystal lattice structures [49]. In the latter case, the RT effect resembles the case of unstable diffusion growth that is self-consistent with its own vapor. The variant of stimulated mobility of surface atoms studied in this research opens up possibilities for the controlled creation of a wider class of one-dimensional structures modulated over the cross-section. In this case, it is possible to realize a kind of interference of surface perturbations with a wavelength λmax, which arise due to the thermal instability of the nanowire in the absence of external irradiation, and additionally stimulated perturbations with a characteristic size lRT. Naturally, the most interesting scenarios of the nanowire dynamics correspond to the cases where lRT≲λmax. Notably, for the chosen orientations of the nanowire, the RT may not develop on its lateral surface. In this case, its dynamics will correspond to the manifestation of thermal instability with a modified parameter p. 3. Results 3.1. Physical Mechanisms of Stimulated Roughening Transition As we have already noted, the initial surface of the nanowire transforms with minimization of the total surface energy at elevated temperatures and can be represented by a set of facet strips of various types (one of the possible variants of such an intermediate stage is shown in Figure 1A(a)). Further dynamics of its surface morphology, as will be shown below, is associated with a complex system of surface flows of atoms along the “strips” and with the exchange of atoms between adjacent strips. Now we demonstrate the manifestation of stimulated RT on isolated facet strips of various types (Figure 2). We consider the dynamics of atoms located in the near-surface layers of an extended facet. It is assumed that only atoms filling the plate with dimensions L(length), w (width), and h (height) are mobile. The movable atoms cannot come out of the perimeter of the upper facet. The object chosen for numerical modeling clearly demonstrates the main results of stimulation of the surface diffusion of atoms. The unit of length in our model is the distance between atomic layers of the (100) type in the FCC crystal lattice. In the case of gold, this unit of length corresponds to approximately 2Å. In our model, the effect of external irradiation on the hopping frequency of surface atoms corresponds to choosing a value of the parameter p for a given α, which is slightly higher than the value given by relation (5). At the initial stage, the near-surface atomic layer (+1-layer) is filled with atoms of the initial 0-layer, and in the process of diffusion over this (initial) layer small clusters can form (Figure 1A(a)). However, the formed clusters are unable to generate second-generation clusters in the +2-layer. Ordered pronounced modulations of the plate surface arise only when it is irradiated, which increases the frequency of atomic jumps from the i-th layer to the i+1-th layer. Furthermore, the intensification of the surface diffusion of atoms on this layer reduces the time of formation of new clusters with supercritical sizes relative to their decay. Naturally, this process occurs faster on the (111) face (see Video S1), since in the formed (111) clusters there are more interatomic bonds than in (100) clusters. Additionally, they are more stable at small sizes, which is essential at the initial stage of nucleation. Notably, we did not observe stimulated RT on the (110) facet for the parameters chosen above. This result is associated with the following factors: (1) the low surface density of atoms on the (110) face (the low binding energy between atoms to create a new nucleus in +1-layer) and (2) the low mobility of single atoms in this layer. For the observed modulations in Figure 2, the surface energy of the plate increases, since the area of the modulated surface exceeds the initial area. However, such a process does not contradict the laws of thermodynamics. Our model assumes that the temperature of the system is constant, and in this case, all processes accompanying a decrease in the Helmholtz free energy, F: dF=dU−TdS, are allowed. In the case under consideration, the increase in surface energy, U, is offset by an increase in entropy associated with an increase in the number of surface states. However, general thermodynamic concepts do not reflect the details of the kinetics of the process and do not answer the question of what physical mechanisms lead to the formation of hillocks and cavities on the facet strips. A more intricate picture arises in the dynamics of surface flows of nanowires and, accordingly, in the dynamics of their surface morphology. Therefore, we show in the sequel how changes in the model parameters, p and α=ε/kT, change the course of the process in the most unexpected way. Let us make some estimates for the surface fluxes on the lateral surface of the wire with developed radius modulations and on the lateral surface of the formed hillock (Figure 3). For Figure 3A, it is assumed that the sizes of atomic layers differ little from each other, and when a contour (peripheral) atom jumps from layer i, it becomes a contour atom in one of the nearby layers. Then, the flow of atoms from layer i to layer i+1, Φ+, and the reverse flow, Φ−, are equal to (6) Φ+=Γi×p〈nbb〉i×γiexp〈nbb〉i+1αΦ−=Γi+1×p〈nbb〉i+1×γi+1exp〈nbb〉iα Here, Γ is the number of contour atoms at the layer boundary and 〈nbb〉 is the average number of bonds for the contour atoms of the layer. The values in curly brackets represent the Boltzmann factor (4) for jumping atoms from layer to layer:(7) γi=exp〈nbb〉i−1α+exp〈nbb〉iα+exp〈nbb〉i+1α−1γi+1=exp〈nbb〉iα+exp〈nbb〉i+1α+exp〈nbb〉i+2α−1〈nbb〉i−1>〈nbb〉i>〈nbb〉i+1>〈nbb〉i+2 As the parameter p increases, the incremental left-to-right flow change, ΔΦ+, exceeds the incremental right-to-left flow change, ΔΦ−, at least under the condition that dp〈nbb〉i>dp〈nbb〉i+1, or (8) 〈nbb〉i〈nbb〉i+1p〈nbb〉i−〈nbb〉i+1>1 The threshold value of the parameter p for stimulated RT (creation of conditions for the flow of atoms from the wide to the narrow part of the nanostructure) may be roughly estimated from the following considerations. The maximum average number of horizontal bonds at the boundary of a (111) cluster with a hexagonal structure is about four, and the minimum is about three. Then, in accordance with inequality (8), stimulation of surface diffusion by irradiation should provide the parameter p around the following value:(9) p≳0.75 The obtained rough estimate agrees with the results of our numerical simulations. Results in Figure 4 demonstrate the possibility of a sharp change in the nature of the dynamics of a dumbbell-shaped nanocluster by variation in the parameter p. In the absence of irradiation, this structure breaks up into two parts, since the surface diffusion fluxes are directed away from the area of its initial necking. Stimulation of surface diffusion (an increase in the parameter p to 0.825) changes the direction of diffusion fluxes in the central part and leads to the formation of an integral cluster. The observed dramatic change in the scenario of system evolution is not due to an increase in the frequency of hops and acceleration of mass transfer but owing to the fact that an increase in p reduces the degree of inhomogeneity in the distribution of the frequency of hops of bound atoms over the surface of the nanostructure. It is quite difficult to estimate the role of system heating during irradiation. The point is that, according to relations (6) and (7), any additional heating that accompanies an increase in the parameter p leads to the following inequality:(10) dγiexp〈nbb〉i+1α>dγi+1exp〈nbb〉iα This means a higher flow rate from left to right than in the reverse direction, and this is indeed observed in our numerical simulations, in which heating a nanowire significantly changes the transformation of its surface (see below). However, for nanohillocks, the conclusion made cannot be applied. The reason is that the chains of boundary atoms of layers i and i+1 are separated from each other (Figure 1, Figure 2 and Figure 3B). As a result, each atomic layer is represented both by an integral cluster and by the two-dimensional space surrounding it, into which the “evaporation” of cluster atoms can occur. Quantitative analysis of the dynamics of such a system is difficult, but its end result is quite understandable. Heating during irradiation intensifies the destruction of clusters and inhibits the development of stimulated RT (Figure 5). Naturally, the destructive effect of heating is more pronounced on the (100) face with a smaller number of horizontal bonds in the cluster (four), compared to six horizontal bonds in the cluster on the (111) face. As a result, only strongly rarefied clusters are formed on the (100) face and only in two near-surface atomic layers. 3.2. Two-Mode Transformation of Nanowire Surfaces The characteristic length of hillocks, lhl, seen in Figure 1, Figure 2, and Figure 5, is about 100 units (50 lattice constants), which corresponds to 20 nm for Au. The lhl value is not related to the dimensions of the plate, as can be seen in Figure 2B, configuration (d). If the radius of the nanowire is chosen such that the length of modulations of its surface, λ, with the development of “Rayleigh” instability in the absence of irradiation is comparable to the length lhl, upon stimulation of surface diffusion, a pronounced two-mode regime of the evolution of its surface will arise. The manifestation of this regime depends on the orientation of the nanowire since it determines the type of bands of its lateral surface at the initial stage (configuration (a) in Figure 1A). It is a two-mode regime of nanowire dynamics that we associate with the unexpected results recorded in experiments with gold nanowires [32]. During the first 10 min, pronounced modulations of the wire cross-section with a diameter of ~6 nm appeared and subsequently remained frozen in time for at least 30 min. The paper does not indicate the orientation of the nanowire axis, but we have a reason to believe that these results were obtained for the (100)-type orientation. In this case, at the initial stage of development of the “Rayleigh” instability, radius modulations with a wavelength of λ≈5.5rnw appear according to our numerical simulations [46] (a noticeable difference from the predictions of a theoretical study presented in [40]—the maximum instability increment corresponds to the length of perturbations λmax≈9rnw—is associated with a pronounced anisotropy of the surface energy density, σ [46].) Just the same ratio, λ/rnw≈5.5, can be obtained based on data analysis [32]. At nanowire radius rnw~3nm, the length of “Rayleigh” instability perturbations, λ≈17nm, is close to the characteristic length lhl. The above estimates indicate that in [32] it was the two-mode regime that was implemented, the characteristics of which are presented in detail in Figure 6. In the irradiation mode, the modulations of the nanowire cross-section (Figure 6A, curve 2) saturate at the same time that is required to establish a quasi-stationary state on the (100)-type facet strip (see the lower dependency for Nbbt in Figure 5B). This means that at this stage of the wire dynamics, RT dominates on the four (100)-facet strips of the lateral surface (configuration (a) in Figure 1A). The formation of hillocks is associated with the longitudinal transport of atoms along the (100) bands and with the transverse drift from adjacent (110) bands, on which RT does not develop. The development of constrictions increases the difference in the values of contour atoms, Γ, for neighboring atomic layers transverse to the axis of the nanowire, and leads to the fact that the flow of atoms to the narrowing region (Equation (6) for Φ+) almost compensates for the reverse flow (Equation (6) for Φ−). The further evolution of the nanowire surface is determined by the slow development of the Rayleigh instability. Visually, this evolution is almost imperceptible (Figure 6C). Similar to the results of the experiment [32], the transition time from configuration (a) to configuration (d) is three times longer than the time of formation of the configuration (a) itself; however, the changes in the shape of the nanowire are vanishingly small even in dependencies of the number of atoms in the atomic layers along nanowire axis (configurations (e) and (f) in Figure 6C). If the wire is also heated up during irradiation, the effect of stimulated RT may not manifest itself in its dynamics (curve 3 in Figure 6A). One can see that the growth rate of nanowire modulations, δt, sharply decreases in the initial stage. The reason for the slow development of bottlenecks during heating was revealed by us when discussing relation (10). In addition, we recall that at the stage of developed modulations, stimulated surface diffusion also slows down their further development. These two factors lead to the fact that at the nonlinear stage of nanowire breakup, when neighboring “beads” can merge, the number of individual nanoclusters, ncl, steadily decreases (which was confirmed in a series of analogical numerical experiments) in the sequence of regimes 1-3-2 represented in Figure 6A:(11) ncl1>ncl3>ncl2 which is shown in configurations in Figure 6D(a’–c’). 3.3. Single-Mode Transformation of the Surface of Nanowires In the absence of external irradiation, (110)-oriented nanowires are significantly resistant to thermal instability since, at the initial stage of transformation, they are limited by two pairs of (111)-type band facets with a low surface energy density (with a small number of broken bonds)—see Figure 7A. The wavelength with the maximal growth increment, λmax~25−30rnw [42,46], is much higher than the predictions of Nichols and Mullins theory (λmax~9rnw) [40]. For this orientation of the nanowire, cases become real when the length λmax noticeably exceeds the characteristic size of hillocks, lhl. Then, it is the stimulated RT that plays a key role in the transformation of the nanowire surface. For Au, the relation λmax≈25rnw>lhl≈100 is fulfilled at rnw≳1 nm, meaning that when nanowires with a diameter of about dnw≳5 nm are irradiated, the dynamics of their surface evolve in a regime that we can physically reasonably call single-mode. However, in order for the effects of modification of the nanowire cross-section to be visually noticeable, its radius should not significantly exceed the height of these hillocks, hhl (according to our data, the height hhl  reaches about 10 interatomic distances between adjacent (111) layers). The distance between (111) atomic layers is 2/3, and hhl≈12. Therefore, the surface modulations become weakly pronounced at the nanowire radius rnw≳50 (rnw≳10 nm, in the case of Au). The results of modeling single-mode decay are presented in Figure 7 and Figure 8. Note the weak dependence of the perturbation growth rate, δt, on the nanowire’s radius. There are also no noticeable differences in the wavelengths of surface perturbations, for which the ratio λmax/rnw does not exceed 5.6. These two facts demonstrate the dominance of stimulated RT in the evolution of the nanowire. At relatively small radii, the development of hillocks (the number of broken bonds grows rapidly—Figure 7B) quickly leads to the rupture of the nanowire at the time of τbr≲3×106 MC steps. In comparison, in the absence of irradiation, a thinner wire (rnw=10.5) experiences the first rupture at t>12×106 [46]. Naturally, metastable states with a pronounced modulation of the nanowire surface arise at radii rnw≳2hhl (curves 3 in Figure 7A,B). Figure 8C demonstrates such a metastable state for a gold nanowire with a diameter of dnw≃8nm. The main part of the nanowire (Figure 8C(e), t=15×106 MC steps) visually looks the same as at the time of its formation (Figure 8C(a), t=2.25×106 MC steps). As the radius increases, the modulation value of the transverse dimensions of the nanowire becomes pronouncedly anisotropic (Figure 9(d,d’)). Even though at the early stages the lateral surface is formed by two pairs of (111)-type strips, as well as by two (100-type) strips (Figure 7A, inset), stimulated RT dominates on (111) facets, causing asymmetry in the deformations of the surface of the nanowire, which is visible in configuration (e) (Figure 9). Thus, the physical mechanisms of surface morphology dynamics considered above indicate that, with a strictly theoretical consideration of the nanowire instabilities under irradiation, it makes no sense to look for the dependence of the characteristics of this instability on the parameter β=λ/rnw, as was carried out when studying the Rayleigh instability. 3.4. Mode of Long-Wave Transformations When the wire is oriented in the (111) direction, its lateral surface at the initial stage has the form of a hexagonal prism with lateral faces of the (110) type. The thermal instability of nanowires with this orientation, occurring without stimulation of surface diffusion, is characterized by the length of surface perturbations at the linear stage of about λ≈7rnw (Figure 10A). At rnw≈14, the wavelength is λ≈100, which coincides with the length of the hillocks, lhl, the effect of which on the wire dynamics was discussed above. However, the supposed two-mode transformation of the wire cannot be realized in this case. The fact is that, as we noted above, the RT effect does not develop on the (110) facet strips that bound the nanowire. However, stimulation of surface diffusion leads to a pronounced effect, registered in the experimental work of [58], in which silver nanowires were irradiated with cold argon plasma without significant heating. As a result, the break-up parameter β=λ/rnw increased significantly, compared with that observed in the absence of irradiation. This effect was also found in our numerical simulations (Figure 10B). The breakup parameter β=λ/rnw increases from the value of β≈7 (Figure 10A(d)) to the value of β≈18, which is in good agreement with the data presented in [58]. The physical mechanisms of the effect of a significant elongation of excited perturbations can be qualitatively explained based on the results obtained in the discussion of the flux balance in the bottleneck region (Equation (6), and Figure 3 and Figure 4). We demonstrated that, by stimulating surface diffusion, it is possible to prevent the breakup of a dumbbell nanocluster into two parts by changing the direction of atomic fluxes in the region of the previously formed bottleneck. In this case, the intensification of surface diffusion suppresses the almost simultaneous formation of neighbor bottlenecks at short distances (Figure 10A(a)) due to the intense diffusive mixing of atoms entering the near-surface layers when trying to form nanowire constriction regions. The result of such mixing is weakened only with an increase in the gap between the bottlenecks formed. 4. Discussion and Conclusions Let us first expound on the theoretical aspects of the study conducted here on the dynamics of nanowire surfaces. Spontaneous transformation of a nanowire occurs with an increase in temperature, which increases the mobility of surface atoms. However, the scenario of this transformation is determined by both the degree of inhomogeneity in the frequency of jumps of bound atoms on the surface of the system and the degree of anisotropy in the probability of jumps in different directions (Equation (4)) into neighboring vacancies of the crystal lattice. These inhomogeneities are controlled by parameters p and α in our numerical model. Naturally, simple heating of the nanowire should be reflected both in an increase in the parameter p and a decrease in  α. The arising surface perturbation is observed in many experiments and is known as the Rayleigh instability. The scenarios of this instability often demonstrate significant deviations of the breakup parameter from the predictions of the classical theory β=λ/rnw≈9, which is associated with the anisotropy of the surface energy density. Despite the fact that the indicated anisotropy introduces significant corrections into the mechanisms of nanowire surface dynamics, the developing instabilities have a common feature, which gives reason to still categorize them as one class of instability under the general term “Rayleigh instability”. Such a feature is scaling—the proportionality of the wavelengths of surface perturbations to the radius of the nanowire. In this formulation of the problem, the results of our previous numerical studies are in very good agreement with the experimental data. In the present study, instabilities of a different type, for which the scaling condition is not satisfied, were studied. Such an instability regime is caused by the disruption of the “natural” relationship between the parameters p and α (p=p0α/α0, Equation (5)), which is determined by the temperature of the system. The stimulation of surface diffusion by an external action (irradiation) distorts this relationship (p>p0α/α0) and increases the mobility of strongly bonded atoms sufficiently, which eventually leads to the observed instabilities. A return to the aforementioned natural relation between p and α, which can be achieved provided that the irradiation heats the system significantly and eliminates the development of a new type of instabilities. The stimulation of the surface diffusion of atoms introduces various and significant corrections into the scenarios for the evolution of the nanowire surface morphology, which depends on the orientation of the nanowire relative to its internal crystal structure. If it is possible to develop an artificial RT effect on some facet strips of the nanowire lateral surface, then its result depends on the size ratio of the emerging hillocks, lhl, with a characteristic length, λ, of the Rayleigh instability that could develop in the absence of irradiation (Section 3.2 and Section 3.3). With the chosen orientation of the nanowire axis, stimulation of surface diffusion might not lead to the RT excitation. In this case, the surface instability, which would arise even without external irradiation, expectedly increases the wavelength of perturbations under new physical conditions. The theoretical concepts developed in this study have been confirmed in several experiments [32,58]. The results obtained can be useful in flexible electronics, where ordered chains of Au and Ag nanoparticles, as well as radially modulated quasi-one-dimensional structures, are widely used (see Video S2). In addition, the stimulation of surface diffusion can find applications in the synthesis of nanostructures with a developed surface morphology for sensor designs. For example, hillocks developed on the side surface of a relatively thick nanowire can be used as a system of nuclei in the subsequent synthesis of ordered chains of side nanopillars, oriented perpendicular to the nanowire axis. The diffusion regime of deposition of free atoms on the surface of the nanowire is unstable, since the tops of the formed hillocks are zones of high concentration of diffusion fluxes, creating shadow zones around them [61,63,66]. As a result, two or four longitudinal rows of nanopillars (relative to the nanowire axis) can be synthesized on the original nanowires with (110) or (100) orientation, respectively (Figure 1A(b) and Figure 9e). Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nano12091411/s1, Video S1: Stimulated roughening transition on the (111) surface, Video S2: The dynamics of three-layer coating of a cylindrical substrate. Click here for additional data file. Author Contributions Conceptualization, V.N.G. and V.V.T.; methodology, G.K.B.; software, V.N.G. and V.V.T.; formal analysis, A.S.F. and O.V.B.; investigation, A.S.F.; resources, G.K.B.; data curation, O.V.B.; writing—original draft preparation, V.N.G. and V.V.T.; writing—review and editing, G.K.B. and A.S.F.; visualization, V.N.G.; supervision, G.K.B.; project administration, V.V.T.; funding acquisition, G.K.B. and A.S.F. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the Swiss National Science Foundation (SNSF) (IZSEZ0_206111). 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 a large amount of information. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (A) Morphology of a thick nanowire with an FCC lattice structure at the initial stage of its evolution: (a) the typical shape of an initially cylindrical nanowire in the absence of the roughening transition effect; (b) nanowire cross-sections with an initial radius of rnw=55a (a —lattice constant) in the area of its maximum size along the y and z axes in two variants of its dynamics for different values of the parameter p at a fixed α=1: the physical meanings of parameters α and p are presented in the description of the model (see Section 2). Atoms marked in cyan and blue represent the near-surface atoms when p=0.7. The cyan and red atoms correspond to the case with p=0.825 (the case of stimulated surface diffusion of atoms). Both cross-sections are calculated at a time moment t=3×106 MC time steps; (c) detailed representation of a hillock structure by multi-colored (001) atomic layers; (B) a typical hillock having formed on the side nanowire surface by the time moment t=3×106 MC time steps. The sizes of the lowest (001) layer (marked in red) are around lx~53a, ly~23a. Figure 2 The manifestation of a roughening transition on the upper faces of plates with different orientations. It is assumed that the side faces of the plates, with the exception of the upper face, are in contact with “frozen”/immobile atoms, and the mobile atoms of the plate cannot go beyond the perimeter of the upper face: (A) the upper face of the plate is part of the (100) plane. Configuration (a) α=1, p=0.7. The plate length is L=400, width w=70, height h=10. In the quasi-steady state, the atomic layer +1 (the top atomic layer in the initial state is marked with the index 0) contains an approximately constant number of atoms around 1600. The formed surface clusters drift along the zero layer, decay, and reappear. (b) −α=1,p=0.825. L=600, w=70, h=10. t=2.9×106 MC steps. The number of broken bonds in the system of mobile atoms, Nbbt, reaches saturation at τsat≈2.5×106 MC steps. The bottom inset shows the surface structure of the plate in the longitudinal middle section; (B) dynamics of a plate with an upper face (111) type. (a–c) L=700, w=70, h=10. α=1, p=0.825. t=0.5, 1.0, 1.5×106≈τsat. Configuration (d)  L=370, w=200. t=1.4×106. Figure 3 Scheme of a fragment of a modulated nanowire (A) and a hillock (B) for estimating the calculation of the balance of surface fluxes of atoms from layer i to layer (i+1 ) and back. In subsection (B), long jumps marked in red are prohibited. Figure 4 Controlling the direction of surface atomic flows in the nanocluster-narrowing region. Configuration (b) is formed from the initial state (a) as a result of the outflow of atoms from the narrowing area in the case of a low surface diffusion rate—p=0.7, α=1. When surface diffusion is stimulated, p=0.825,α=1, the influx of atoms into this zone forms the entire cluster (c). The presented two-way transformation is stably reproduced in other random realizations of the dynamics of the initial nanocluster. Figure 5 Effect of possible surface heating on the manifestation of stimulated roughening transition on faces of different orientations: (A) the outer surface of the plate is a (111)-type facet. The upper inset shows the number of broken bonds (relative to the initial state), Nbbt, in the cold (p=0.825, α=1 —blue curve) and hot (p=0.825, α=0.75 —red curve) regimes. Configurations (a, b) quasi-steady state of the plate surfaces in hot regime with lengths L=700 and 550 (in both cases w=70,h=10 ). The lower inset shows one of the hillocks formed on the upper face of the plate (a); (B) results for (100)-orientation of the upper face of the plate. L=550, w=70, h=10. The blue and red circles show time dependencies, Nbbt, for cold and hot regimes, respectively. In the cold regime, six hillocks with a height of 8–10 atomic layers are formed on the upper plane. The bottom inset presents a fragment of the plate. In the hot regime, only two or three near-surface atomic layers are partially filled (upper inset). The observed low structuredness of the surface is characterized by longer wavelength perturbations. Figure 6 Dynamics of nanowires with (100) orientation in different regimes: (A) dependencies of the level of modulation of the cross-section of the nanowire, δt, on time: δ=ΔNlayer2/Nlayer2, Nlayer  is a number of atoms in transverse atomic layers. Initial nanowire radius rnw=15.5, length L=700. Curve 1 (cyan circles)—p=0.7, α=1 (breakup without external irradiation). Blue circles—p=0.825, α=1 (transformation under external irradiation without heating). The red curve (3)—p=0.825, α=0.8 (breakup under external irradiation with heating). Dependences δt are given up to the first nanowire rupture; (B) variations in time of the number of broken bonds, Nbbt, for surface atoms of the nanowire. The parameters for curves 1 and 2 are the same as for curves 1 and 2 presented in Subpart A. The lower inset, curve 2’, represents the initial stage of dependency 2; (C) formation of a quasi-equilibrium shape of a nanowire with the pronounced roughening transition. The parameters are the same as shown in subpart (A) for the blue curve (2). Configurations (a–d) depict shapes of the nanowire at time moments t=3, 6, 9, 12(×106 ) MC steps. For these time moments, subpart (e) shows the distributions of atoms in atomic layers (100) along the nanowire axis by blue, olive, red, dark cyan curves, respectively: N^layerl=Nlayerl/Nlayert=0. Subpart (f) represents a longitudinal section of a nanowire with a larger radius (rnw=20 ) at time moments t=9×106 (blue curve) and t=36×106 MC steps (red curve). Configuration (g) depicts the shape of a thick nanowire: rnw=35 (p=0.825,  α=1; L=700 ), t=15.7×106 MC steps; (D) configurations (a–c) depict the nanowire shapes close to the first breakup for regimes (1), (2), and (3) presented in subpart A; t=13.5, 12, 6.5(×106 ) MC steps. For these cases parameter δ≈0.33. Configurations (a’–c’) show the nanowire shapes at the final stages of breakup: t=27.9, 27.9, 11.7 ×106 MC steps, respectively. Figure 7 Dynamics of morphology characteristics of nanowires with (110) orientation under stimulation of atomic surface diffusion. α=1, p=0.825: (A) change in the level of modulation of the cross-section of nanowires, t, of different radii. For curves 1, 2, 3—rnw=15.5, L=700; rnw=17.5, L=700; and rnw=20.5, L=500, respectively. Color circles mark the time moments of the first ruptures. The inset shows the typical shape of a nanowire with (110) orientation established at the initial stage of its transformation; (B) change in time of the number of broken bonds on the surface of nanowires for the same parameters. S0 is the side surface area of the nanowire in dimensionless units in the initial state. The arrows indicate the moments of the first ruptures in the nanowires. The circles on curve 3 mark the moments of time for which in Figure 8C the shapes of the thickest nanowire are shown. Figure 8 Shapes of nanowires with (110) orientation at different stages of transformation upon stimulation of surface diffusion of atoms: α=1, p=0.825: (A) rnw=15.5, L=700; for configurations (a,b) t=1.50 and 3.54×106 MC steps; (B) rnw=17.5, L=700; (a,b) t=2.70 and 5.88×106 MC steps. (C)  rnw=20.5, L=500; (a–e) t=2.25, 4.50, 6.75,8.40 and 15.0×106 MC steps (these points in time are marked with circles on the dependence Nbbt —see curve 3 in Figure 7B). Figure 9 Surface dynamics of a nanowire with radius  rnw=45 ( rnw≈18 nm for Au) under conditions of stimulated surface diffusion of atoms ((110) orientation, L=500 ). Subparts (a-d) show the shape of the nanowire at times t=2.25;3.00;3.90;5.10×106 MC steps (top view along direction (00−1)). Configuration (e) displays the atoms that have gone beyond the initial cylindrical boundary of the wire (green cylinder) for configuration (d’). Configurations (d’) and (d’’) show the shape of the wire (d) from the side—when viewed along the plane (001)—at time moments t=5.10×106 and t=12.6×106 MC steps. Figure 10 Breakup of nanowires with (111) orientation without external irradiation (subpart (A)) and under conditions of stimulated surface diffusion of atoms (subpart (B)): (A) α=0.9, p=0.725, L=1050. Configurations (a–c) rnw=12.5; t=3.0, 4.2, 5.4×106  MC steps. Configuration (d) rnw=14.5; t=9.45×106 MC steps; (B) α=0.9, p=0.8, L=1050. Configurations (a–c) - rnw=12.5; t=3.0, 4.8, 7.2×106  MC steps. Configurations (d,e) rnw=14.5; t=12.0, 26.1×106  MC steps. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Chen Y.-L. Lee C.-Y. Chiu H.-T. Growth of Gold Nanowires on Flexible Substrate for Highly Sensitive Biosensing: Detection of Thrombin as an Example J. Mater. Chem. B Mater. Biol. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094516 ijms-23-04516 Article Global 5mC and 5hmC DNA Levels in Human Sperm Subpopulations with Differentially Protaminated Chromatin in Normo- and Oligoasthenozoospermic Males https://orcid.org/0000-0002-2337-4545 Olszewska Marta 1* Kordyl Oliwia 2 Kamieniczna Marzena 1 https://orcid.org/0000-0003-1212-4230 Fraczek Monika 1 Jędrzejczak Piotr 3 https://orcid.org/0000-0003-3275-3245 Kurpisz Maciej 1* Laganà Antonio Simone Academic Editor Garzon Simone Academic Editor 1 Institute of Human Genetics, Polish Academy of Sciences, Strzeszynska 32, 60-479 Poznan, Poland; marzena.kamieniczna@igcz.poznan.pl (M.K.); monika.fraczek@igcz.poznan.pl (M.F.) 2 Faculty of Biology, Adam Mickiewicz University in Poznan, 61-614 Poznan, Poland; oliwiakordyl@gmail.com 3 Division of Infertility and Reproductive Endocrinology, Department of Gynecology, Obstetrics and Gynecological Oncology, Poznan University of Medical Sciences, 60-535 Poznan, Poland; piotrjedrzejczak@gmail.com * Correspondence: marta.olszewska@igcz.poznan.pl (M.O.); maciej.kurpisz@igcz.poznan.pl (M.K.) 19 4 2022 5 2022 23 9 451630 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/). Epigenetic modifications play a special role in the male infertility aetiology. Published data indicate the link between sperm quality and sperm chromatin protamination. This study aimed to determine the relationship between methylation (5mC) and hydroxymethylation (5hmC) in sperm DNA, with respect to sperm chromatin protamination in three subpopulations of fertile normozoospermic controls and infertile patients with oligo-/oligoasthenozoospermia. For the first time, a sequential staining protocol was applied, which allowed researchers to analyse 5mC/5hmC levels by immunofluorescence staining, with a previously determined chromatin protamination status (aniline blue staining), using the same spermatozoa. TUNEL assay determined the sperm DNA fragmentation level. The 5mC/5hmC levels were diversified with respect to chromatin protamination status in both studied groups of males, with the highest values observed in protaminated spermatozoa. The linkage between chromatin protamination and 5mC/5hmC levels in control males disappeared in patients with deteriorated semen parameters. A relationship between 5mC/5hmC and sperm motility/morphology was identified in the patient group. Measuring the 5mC/5hmC status of sperm DNA according to sperm chromatin integrity provides evidence of correct spermatogenesis, and its disruption may represent a prognostic marker for reproductive failure. sperm methylation sperm hydroxymethylation oligozoospermia male infertility sperm chromatin protamines semen parameters 5mC 5hmC ==== Body pmc1. Introduction Epigenetic modifications are well-known reversible variations of the genome that determine the transcriptional status of the cell. Epimodifications are mostly prone to environmental factors and are heritable [1,2,3]. The primary epigenetic mechanisms involved in the regulation of the genome are DNA modifications (i.e., methylation), posttranslational modifications of histones (i.e., methylation, acetylation, ubiquitination, phosphorylation, etc.), and the activity of non-coding RNAs (nc-RNAs) [1,3,4,5,6,7]. The best-known epigenetic mechanism is the methylation and demethylation of the 5’ cytosine. Primarily, 5-methylocytosine (5mC) can be observed in CpG islands, where these moieties remain for the majority methylated (60–80%) [7]. DNA methylation remains stable in particular tissues, each type of which has its own pattern, but can be influenced by disease, pathological events, or age [7,8,9,10]. Cytosine methylation determines the genome-wide methylation pattern of DNA and the modification of histones, resulting in changes in chromatin configuration, playing a crucial role in gametic imprinting, gene silencing, chromosome X inactivation and protein conformational changes [1,3,4,6,7,11]. In the non-CpG context, DNA methylation has been observed in oocytes, embryonic stem cells and some types of brain cells. In contrast to methylation, hydroxymethylation (5hmC) is present at lower levels in particular tissues (0.1–0.8%), exhibiting increased values in tissues with high transcriptional activity (i.e., neurons) [7,12,13,14]. This epimark, a result of enzymatic oxidation of 5mC to 5-hydroxymethylocytosine (5hmC), is mostly observed in enhancers, promoter regions of genes, and other transcriptional regulatory elements [7,15]. In spermatozoa, which are transcriptionally inactive, the level of hydroxymethylation is approximately four times lower than in somatic cell types [16]. It has been suggested that 5hmC, together with Tet family enzymes (Ten-Eleven Translocation Proteins; Tet1, Tet2, Tet3), may supervise gene expression through regulation of methylation [12,14,16,17,18,19]. Thus, both 5mC and 5hmC seem to play important roles in proper genome function. It is well established that parental genomes play distinct genetic roles after fertilization. Functional sex-determined differences result from gametic imprinting established during gametogenesis. Thus, each parental genome has a different methylation pattern that imposes key epigenetic mechanisms in the proper development of an organism, beginning during gametogenesis [3,6,20,21,22]. The paternal genome is responsible for early placental development, while the maternal genome is responsible for embryonic development [3,20,21,22]. It is also known that in newly formed embryos, certain developmental disturbances may occur due to a lack of activation of genes crucial for normal development, which can be linked to disturbances in proper methylation and demethylation rounds in gametogenic cells, and to disrupted methylation/acetylation of sperm histones [3,21,23,24,25,26,27]. Chromatin of spermatozoa is uniquely organized and condensed (4-6 times stronger), which results from overlapping toroidal structures built from DNA and protamines (enriched in arginine and cysteine residues, and thus positively charged), containing only a residual quantity of histones [28,29,30]. The condensation of the sperm chromatin generates a genetically inactive state which is crucial for the fertilization process when transportation of paternal genome occurs [28,29,30]. In properly protaminated human sperm chromatin, only approximately 10–15% of gonadal histone variants remain associated and are highly acetylated [1,31,32,33]. Importantly, this epigenetic mark can be transmitted from sperm to oocyte and may be involved in the regulation of gene expression in early embryos [1,3,34]. Additionally, the remaining histones are in contact with the nuclear matrix. These regions may contain gene promoters that are among the first to be transcribed after fertilization, including microRNA-coding sequences and imprinted genes [1,2,22]. The remaining histones are also located on the unmethylated DNA within genes associated with spermatogenesis [33,35,36]. Importantly, the presence of histones forces nucleosomal packaging of chromatin, that takes place between DNA-toroid complexes. Thus, regions containing histones are potentially more prone to chromatin disruptions caused by free radical attack, mutagens or nucleases [32]. It has been documented that disrupted expression in a proportion of protamines P1:P2, as well as in the ratio of protamines to the remaining histones, were implicated in male infertility [37,38,39], revealed in reduction of sperm quality or induction of sperm DNA damage [37,38], leading to breakdown in embryonic development [25,27,40]. It was also documented that apoptosis of sperm cells was linked to chromatin deprotamination and sperm DNA fragmentation, which was then associated with spermatogenetic disorders, manifested as hypermethylation of the genome [41,42], which may be an early response to oxidative stress mediated by an increase in the activity of DNA methyltransferases (Dnmt) [43]. Additionally, oxidative damage of sperm DNA may be at least in part responsible for changes in global sperm DNA methylation [41]. The hypothesis that spermatozoa with hypomethylated DNA may be more prone to DNA damage is well known [41]. Taken together, these data support the hypothesis that in spermatozoa with decreased chromatin integrity, global sperm DNA demethylation may be increased. Investigating immature spermatozoa collected for fertilization in assisted reproductive technologies (ART) revealed that it is possible that inadequately established methylation patterns and improper chromatin integrity can increase the risk of reproductive failure or future offspring health status [1,3,41,44,45,46,47,48,49,50,51,52,53,54,55,56,57]. Hypomethylation may also alter the process of cellular differentiation, so embryonic genome expression may reveal disturbed synchronization in its development [3,22,58,59]. Consequently, the unique epigenetic marks in spermatozoa may be crucial in facilitating proper mature gamete function, and are responsible for poising specific gene activation in the early embryo [1,3,27,46,48]. In this light, basic knowledge concerning the mechanisms and meaning of gametic epigenome disturbances seems to be important, due to the relatively high frequency of ART births today (approximately 1–3% of all live births) [48,60,61]. It is known that male infertility may be linked with aberrant DNA methylation in human spermatozoa. This was confirmed by changes in DNA methylation both in global sperm DNA and in particular genes (imprinted or nonimprinted). Changes in the methylation pattern were also documented for males with disturbed protamines P1/P2 ratio with respect to sperm apoptosis, in IVF patients, in response to male ageing, in chromosomal aberration carriers, and in patients with decreased semen quality [22,42,44,45,48,62,63,64,65,66,67,68,69,70,71,72]. In cases of oligozoospermia (decreased sperm count in ejaculate), only 5% of oligozoospermics are able to fertilize, and genetic causes are responsible for 2.5–10% of observed cases (i.e., microdeletions in chromosome Y) [73]. Epigenetic evaluation of oligozoospermia revealed that abnormal methylation patterns or imprinting errors in some patients from this group may lead to decreased fertilization efficiency and increased abortion rates [40,48,59,74,75,76,77,78]. The aim of this study was to discover whether there is a correlation between the defined status of sperm chromatin deprotamination and global 5mC and 5hmC levels of sperm DNA. For the first time, a sequential staining algorithm of the same human spermatozoa was applied, allowing researchers to determine three sperm subpopulations according to their chromatin protamination, with subsequent estimation of 5mC and 5hmC. Additionally, the sperm DNA fragmentation level (TUNEL assay) was examined to support the chromatin integrity data. Comparison of two groups of males with different semen parameters allowed observation of possible correlations with sperm abnormalities. The study is supported by a review of literature data published so far concerning methylation and hydroxymethylation in spermatozoa. 2. Results 2.1. Semen Parameters Semen analysis of the group of patients (P) revealed decreased basic sperm parameters in all (31) individuals compared to the control group (C) with normozoospermia (Supplementary Table S1). In total, 2 patients exhibited decreased sperm count only (oligozoospermia, O), 22 had decreased sperm count and motility (oligoasthenozoospermia, OA), and 7 had decreased sperm count, motility and morphology (oligoasthenoteratozoospermia, OAT) (Supplementary Table S1). Statistical differences in values obtained in each studied category are presented in Figure 1a. Statistical significance between both groups of males (C vs. P) was observed for sperm concentration per mL (p < 0.0001), total sperm count (p < 0.0001), sperm morphology (p = 0.0128), and sperm motility (progressive: p = 0.0002, total: p = 0.0002) (Figure 1a). The ejaculated sample volumes were similar in both groups. The mean P sperm parameters were significantly lower than the values in the C group and showed wider ranges of values (increased heterogeneity) (Supplementary Table S1; Figure 1a). 2.2. Sperm Chromatin Integrity The results of aniline blue (AB) staining showed that the mean frequency of spermatozoa with properly protaminated chromatin obtained for the analysed group of patients (P) was 68.56 ± 13.59% (range: 32.28–95.74%), and was significantly lower (p = 0.0036) than the mean control (C) value of 82.02 ± 8.31% (range: 63.60–92.37%) (Table 1 and Table S2, Figure 1b). Results of the TUNEL assay (Table 1 and Table S2, Figure 1b) showed that the mean frequency of sperm with DNA fragmentation in the patient group (P) was 9.55 ± 6.29% (range: 1.81–22.70%) and was 1.73-fold higher but not statistically significant when compared to the mean C value of 5.52 ± 2.62% (range: 2.50–13.06%). 2.3. Global Methylation (5mC) and Hydroxymethylation (5hmC) of Sperm DNA 2.3.1. Unfractionated Total Sperm Population To quantify global m5C and 5hmC levels in sperm DNA, the immunofluorescence (IF) technique was applied. In the total unfractionated control sperm population, the mean control result for 5mC was 75.61 ± 10.69 i.u. (range: 57.97–105.06 i.u.; Table 1 and Table S2), and was statistically similar to the mean obtained for the patient group: 71.32 ± 30.82 i.u. (range: 22.18–134.98 i.u.; Table 1 and Table S2, Figure 1c). In the case of 5hmC, the mean control value of 126.33 ± 13.17 i.u. (range: 91.71–150.98 i.u.) was also statistically similar to the mean P result of 109.03 ± 22.74 i.u. (range: 60.89–150.80 i.u.; Table 1 and Table S2, Figure 1c), even when the difference between values was 15.55%. Additionally, the 5mC/5hmC ratio was calculated, and no statistically significant difference was noted between the two groups (mean C: 0.60 ± 0.07, range: 0.47–0.79; mean P: 0.64 ± 0.20, range: 0.32–1.05). A wider range of values was observed in the P group (Table 1 and Table S2, Figure 1d). 2.3.2. Sperm Populations According to Chromatin Protamination In this study, we applied sequential staining algorithm to the same spermatozoa (cell by cell, in situ on a microscopic slide as indicated in Figure 2), which allowed us to acquire and collate all the results from the same individual sperm cell. First, spermatozoa were stained with AB for chromatin protamination evaluation, followed by documentation of their position on microscopic slides. Then, immunofluorescence staining (IF) was applied onto the same slide, and epimark analysis was performed according to the documented positions of each spermatozoa from AB analysis. In three sperm subpopulations defined according to their protamination status, the mean control results for 5mC were as follows: (i) in the correctly protaminated subpopulation: 120.28 ± 19.65 i.u. (range: 90.01–150.67 i.u.; Table 2 and Table S3), which was statistically higher (p < 0.0001) than the mean result obtained for the group of patients: 87.29 ± 36.01 i.u. (range: 23.71–156.50 i.u.; Table 2 and Table S3, Figure 3); (ii) in the semiprotaminated subpopulation: mean C value was 58.92 ± 15.41 i.u. (range: 46.30–92.96 i.u.) and was statistically similar to the mean P value: 59.54 ± 26.34 i.u. (range: 18.80–125.35 i.u.); and (iii) in the deprotaminated sperm subpopulation: mean C value: 37.90 ± 8.84 i.u. (range: 28.91–52.25 i.u.) was also similar to the mean P value: 42.73 ± 20.11 i.u. (range: 16.78–99.75 i.u.). In the case of 5hmC, the mean C and mean P values were similar in all three subpopulations, although some tendency to increase was observed for the C group (Table 2 and Table S3, Figure 3). Results were as follows: (i) in the properly protaminated subpopulation: mean C value 134.26 ± 15.12 i.u. (range: 108.28–164.77 i.u.) vs. mean P value 121.20 ± 23.42 i.u. (range: 71.66–157.83 i.u.); (ii) in the semiprotaminated subpopulation: mean C value 110.85 ± 11.48 i.u. (range: 94.87–127.76 i.u.) vs. mean P value 100.76 ± 24.95 i.u. (range: 50.33–142.54 i.u.); and (iii) in the deprotaminated sperm subpopulation: mean C value 98.71 ± 9.97 i.u. (range: 88.20–112.33 i.u.) vs. mean P value 81.53 ± 22.39 i.u. (range: 36.43–124.70 i.u.). Also, the 5mC/5hmC ratio was calculated in all the three subpopulations of spermatozoa (Table 2 and Table S3). Statistically significant differences were noted between the two groups of analysed males: (i) in the properly protaminated subpopulation (p = 0.0032; mean C: 0.90 ± 0.12, range: 0.66–1.07; mean P: 0.70 ± 0.23, range: 0.33–1.29); and (ii) in deprotaminated subpopulation (p = 0.0263; mean C: 0.38 ± 0.07, range: 0.30–0.48; mean P: 0.52 ± 0.19, range: 0.24–1.04). In the subpopulation of semiprotaminated spermatozoa the measured values were similar (p > 0.05; mean C: 0.53 ± 0.12, range: 0.42–0.79; mean P: 0.58 ± 0.20, range: 0.31–1.09). 2.4. Correlations In the unfractionated total sperm populations, a positive correlation between the mean global 5mC vs. 5hmC values was observed in both groups of males (C: p = 0.0017, R2 0.3192, r 0.6667; P: p < 0.0001, R2 0.5853, r 0.7340), indicating a clear relationship between these two epimarks (Table 3 and Table S4, Figure 4a,c). In both analysed groups of males, with the increase in methylation level, the level of hydroxymethylation also increased. Positive correlations between the sperm chromatin protamination status and global 5mC and 5hmC DNA levels were observed in the control group (C) in the unfractionated total sperm population (p = 0.0002, R2 0.4294, r −0.6946 for 5mC, p = 0.0273, R2 0.0936, r −0.3975 for 5hmC; Figure 4b, Table 3; p = 0.0340, R2 0.1615, r −0.4346 for 5mC/5hmC ratio; Table 3 and Table S4), followed by the correlation of particular sperm subpopulations according to their chromatin protamination status (p < 0.05; 5mC R2 0.0634, r −0.7746, 5hmC R2 0.7383, r −0.6848; Figure 5a,c Table 3 and Table S4). In the patient group (P), no correlations between 5mC and 5hmC levels and protamination status were observed, either in unfractionated total sperm populations or in the three subpopulations with various chromatin protamination statuses (p > 0.05) (Table 3 and Table S4, Figure 4d and Figure 5b,d). Additionally, in patients (P) statistically non-significant opposite tendency was noted: according to increased protamination, 5hmC also rose (Figure 4d and Figure 5d). When considering 5mC vs. protamination in the P group, the correlation was flattened when compared to the C group (Figure 4d and Figure 5c). These observations indicate (i) various levels of epimarks in each of the sperm subpopulations according to chromatin protamination, (ii) a clear correlation between chromatin protamination and 5mC/5hmC levels in normozoospermic controls, and (iii) a loss of correlation in patients with oligo/oligoasthenozoospermia. When evaluating the possible relationship between sperm DNA fragmentation level and 5mC/5hmC levels, no correlations were noted in either group of males (p > 0.05; Table 3 and Table S4, Figure 6). Interestingly, the wide distribution of values observed in the P group followed a change in the tendency across the spectrum—from negative to positive (protamination vs. 5hmC) and from positive to negative (DNA fragmentation vs. 5mC and 5hmC), suggesting epigenetic disturbances in these patients (Figure 4b,d and Figure 6b). Surprisingly, no correlations (p > 0.05) were observed in either analysed group of males when collating global 5mC and 5hmC values vs. sperm concentration, total sperm count or ejaculated sample volume, either in unfractionated or subpopulations of sperm (Table 3 and Table S4, Supplementary Figure S1). An inverse tendency (positive in the C group, negative in the P group) in the unfractionated total sperm populations was observed for sperm motility, showing an increase (C) or decrease (P) in 5mC and 5hmC with an increase in motile spermatozoa (Supplementary Figure S1). However, in the P group sperm subpopulations according to protamination status, a statistically significant correlation was observed between total motility and 5hmC (p < 0.0001, R2 0.0427, r −0.2067, Table 3 and Table S4). In the C group, there were no statistically significant correlations; however, some tendency (p = 0.061) was observed for total motility vs. 5mC (R2 0.1368, r 0.8609) and 5mC/5hmC ratio (R2 0.2653, r 0.8601) (Table 3 and Table S4). Additionally, statistically significant correlations were found in the P group between sperm morphology vs. 5mC (p = 0.0216, R2 0.1690, r 0.4111), and/or the 5mC/5hmC ratio (p = 0.0096, R2 0.2097, r 0.4579) in the unfractionated total sperm population (Supplementary Figure S1B) and in the sperm protaminated subpopulation (p < 0.01; 5mC R2 0.2102, r 0.4585; 5mC/5hmC ratio R2 0.2579, r 0.4883; Table 3 and Table S4). All of these observations may emphasize a weak link between sperm DNA methylation/hydroxymethylation and semen parameters (motility, morphology). 3. Discussion This study is the first to describe the correlation between the particular status of chromatin vs. methylation (5mC) and hydroxymethylation (5hmC) in sperm DNA, as represented by three sperm subpopulations with different protamination status. All analyses were performed sequentially on the same individual sperm cells, meaning that each single spermatozoon, cell by cell, was stained in situ with AB for evaluation of chromatin protamination status, followed by documentation of its position, and then on the same slide subjected to immunofluorescence staining with proper antibodies to detect specific epimarks. Such sequential staining resulted in the generation of unique data comprising a clear relationship between detailed sperm chromatin protamination and global DNA methylation (5mC and 5hmC). Due to technical limitations, the TUNEL assay results have not been included in the sequential staining algorithm (no clear TUNEL signal after AB). To our knowledge, global methylation analysis of sperm DNA measured via immunofluorescence or colorimetric techniques, followed by microscopy, cytometry or ELISA, has only been described in thirteen previous studies (Supplementary Table S5). In only three studies were the methods based on the chromatographic measurements described [42,79,80]. The majority of published data are based on screening the methylation pattern of particular genes—their promoters or CpGs—using sequencing of single-, few- or whole-genome approaches (Supplementary Table S5). Previous studies have clearly demonstrated a relationship between global 5mC level, sperm quality, sperm apoptosis, abnormal P1/P2 ratio, IVF outcome, age of male patients, and the presence of chromosome aberrations [22,38,42,44,45,63,68,69,70,81]. Additionally, tobacco smoking has been listed as an important external factor disturbing DNA methylation, causing increased sperm DNA damage [82]. Even if the global methylation level is similar between smokers and nonsmokers, an increased variance in methylation patterns, especially in histone-retained regions, was shown in the sperm DNA of smokers [82]. Additionally, alcohol use, obesity, and environmental factors can disrupt the observed DNA methylation patterns of selected genes [41,83,84,85,86]. Interestingly, the role and complexity of epigenetic changes in infertility seem to be underlined by the data documenting alterations in imprinted gene methylation patterns in normozoospermic but infertile males [87,88]. In the present study, the medical history collected for both groups of investigated males (P and C) showed none of the potentially disruptive factors—participants were selected according to questionnaire responses (nonsmokers, no alcohol or drugs, similar age, no toxic agents, normal body mass index (BMI)). Additionally, preparation of tests in situ on slides allowed to be sure not to include into analyses any other cell type that could potentially perturb the data obtained. Previous studies are incompatible when considering correlations between decreased semen quality (OAT) and protamine content. Correlations between protamine mRNA levels and sperm motility or morphology have been reported [63,89]. However, data suggested only limited trends or showed no linkage, even when levels of methyltransferase mRNA followed by increased DNA methylation were higher [90,91,92,93]. In our study, in the patient group (P) with oligoasthenozoospermia, the frequency of spermatozoa with proper protamination was significantly decreased (−13.46%; p < 0.05) compared to normozoospermic controls (Figure 1, Table 1). Additionally, in the control group (C), the total sperm count correlated with the protamination level (p < 0.05), but this observation was not relevant in the P group (Table 3). We suggest that the presence of abnormal semen parameters (OA) can be disruptive for correlations found in control samples, although we did not measure the protamine transcript level because of insufficient biological material. However, further studies on isolated protamines according to epimark levels and sperm DNA fragmentation could produce interesting data considering semi-quantitative estimation, especially in the light of a previously documented link between protamine content and DNA fragmentation [94,95,96]. Thus, adding epigenetic data would probably improve the comprehensive interpretation of this phenomenon in the context of infertility. When considering sperm subpopulations according to their protamination, various levels of 5mC and 5hmC m were documented in each, supported by a clear linkage between chromatin protamination and 5mC/5hmC levels in normozoospermic controls (p < 0.01), revealing loss of this correlation in patients with decreased sperm parameters (p > 0.05). Additionally, in the properly protaminated sperm subpopulation, 5mC and 5hmC values varied between the P and C groups. The observed lower 5mC and 5hmC values in infertile patients may suggest disturbed spermatogenesis and disrupted maturation of spermatozoa, including improper protamination. This is in agreement with the literature, which shows higher 5mC values in fertile normozoospermic males [70]. It seems to be important, and is shown here for the first time, that there is a heterogeneity of chromatin protamination level within ejaculated sperm, and this can be crucial when considering the global DNA methylation status. This fact is underlined by the observation from unfractionated total sperm populations with similar mean levels of global 5mC and 5hmC observed in both groups of analysed males (P vs. C). Such similarity in global mean values was also documented for other tissue types, which is not unusual since the majority of methylation in the genome occurs in areas outside of CpG islands, such as repetitive elements and noncoding and nonregulatory regions [97,98]. However, attention should be paid to evaluating further obtained mean values to avoid incorrect interpretation, and further analyses should include measurement of specific, detailed parameters, not only general mean values. Another question is the role of sperm DNA fragmentation (one of the two elements of chromatin integrity measured in this study) and sperm genome methylation changes. In our study, in the control individuals (C), the frequency of spermatozoa with hypermethylated genomes increased with increasing chromatin instability; however, this was represented only by chromatin protamination, not sperm DNA fragmentation (Figure 6). Moreover, in both analysed groups, there was no linkage between sperm DNA fragmentation and semen parameters (Table 3; p > 0.05). Global hypermethylation might be an early response to oxidative stress mediated through an increase in DNA methyltransferase (Dnmt) activity [43,99]. Increased hypomethylation following decreased chromatin protamination observed in the patient group suggests a potential association between chromatin structure disturbances and impaired methylation [70,100,101,102,103]. However, we cannot anchor the sperm DNA fragmentation observed in the patient group due to the noted lack of any possible correlations or even tendencies. Thus, it remains questionable whether and how measured sperm DNA fragmentation could be used as one of the fertility parameters. Although some of the literature showed that apoptotic sperm cells (with fragmented DNA) demonstrating hypermethylation of the genome were associated with disorders of spermatogenesis [80,99], the presence of decreased semen parameters themselves cannot be treated as the decisive factor responsible for the observed changes, either in methylation and/or linked to sperm DNA fragmentation. Changes in gene methylation patterns are also well documented in normozoospermic but infertile males [87,88]. However, in a study examining the presence of chromosomal structural aberrations, such correlations were documented [42]. Therefore, when considering sperm DNA fragmentation, attention should be paid to some important aspects, i.e.,: (i) whether the decreased semen parameters resulted from disturbed spermatogenesis, (ii) whether the negative influence of environmental factors led to decreased sperm quality, or (iii) whether the patient had any other abnormalities in karyotype that may influence chromatin stability via the formation of strand breaks resulting from high torsion tensions occurring during the remodelling of sperm chromatin in spermiogenesis. Such tensions may promote sperm chromatin opening and increase apoptosis, leading to a decrease in sperm quality [42,104,105]. Another open question is whether discrimination between single-strand (ss) and double-strand (ds)DNA breaks (i.e., established by COMET assay) would have added value for evaluation of methylation events in a male infertility context. No such data exists to our knowledge). According to the latest literature data available, COMET assay seems to be the most reliable diagnostic method for male infertility, because of its clear indications concerning IVF and ISCI outcomes [106]. Observations of decreased semen parameters linked with sperm DNA global methylation level or altered methylation patterns of imprinted genes have been well documented [66,67,69,70,107,108,109,110,111,112,113,114,115,116]. It was found that in morphologically normal sperm heads, 5mC levels were lower than in abnormal spermatozoa [69,110], and high 5hmC levels were negatively correlated with good sperm head morphology while positively correlated with sperm DNA fragmentation [117]. In asthenozoospermic patients, low motility was linked with sperm DNA hypermethylation [66,69,111,113,118]. In our study, when analysing sperm motility, some interesting tendencies were observed within the total sperm population of unfractionated ejaculated spermatozoa, with a strong correlation (p < 0.0001) with the properly protaminated fraction (positive in the C group, negative in the P group), reflecting the decrease in 5mC and 5hmC and a simultaneous increase in motile spermatozoa (Supplementary Figure S1B, Table 3 and Table S4). These observations, supported by the statistically strong correlation noted in the P group (both in the unfractionated and defined sperm subpopulations) between global 5mC and 5mC/5hmC ratio values vs. sperm morphology, apparently linking methylation and hydroxymethylation with sperm motility and morphology. On the other hand, the published data also showed a clear correlation (or suggested trend) between sperm count and/or sperm concentration vs. 5mC level, or possibly no linkage between these two parameters [21,42,66,70,93,108,109,115,116,119,120]. In the present study, both in the unfractionated total sperm samples and in the properly protaminated sperm subpopulation, no correlations were found in either group of males linking global 5mC and 5hmC levels with sperm concentration, total sperm count, or ejaculated sample volume. Such discrepancies can result from various preparations of semen samples, as well as the total number of individuals required for statistical significance. One of the possible influencing factors may be meaningful heterogeneity among semen samples displaying abnormal parameters. Within the same ejaculate, there are several sperm subpopulations that could be fractionated according to chromatin density (gradient centrifugation) or sperm motility (swim-up), and they may reflect different methylation patterns [109,121,122]. Laurentino et al. [122] observed that in OA males there may be a kind of heterogeneity (epimosaicism) among the spermatozoa from one semen sample, revealed as variability in the methylation patterns of selected imprinted genes, probably because of imprint erasure errors. Yu et al. found that in gradient selected sperm fractions, histone retention was decreased, followed by decreased global methylation levels [109]. Interestingly, Dere et al. [123] documented that sperm DNA methylation levels are relatively stable between semen sample collections over a long time period [123]. Additionally, possible DNA from contaminating biological material (when too low attention was given to sample selection/preparation/fractioning), could be a potential cause of incompatible findings across various studies [124,125]. In summary, it has been shown here for the first time that there is a heterogeneity within DNA methylation and hydroxymethylation in ejaculated sperm samples according to chromatin protamination status. In OAT patients with a lack of pregnancy success, there was a disruption to the strong correlations between various protamination levels vs. 5mC and 5hmC observed in control normozoospermic males. An interesting linkage was revealed in the relationship of sperm morphology and motility with levels of 5mC and 5hmC, documented in the OAT patient group. Additionally, the wider ranges of values for all studied parameters measured in this group of patients may suggest an association between epigenetic disturbances and decreased semen quality. Following the facts, that proper epimarking and the specific high protamination of sperm chromatin are crucial for correct spermatogenesis, we can suggest that the measurement of the 5mC/5hmC in spermatozoa can be a useful complementary component in the generation of prognostic epidata in cases of male infertility. Questions remain regarding the cause–effect involvement of decreased semen parameters and disturbances in sperm DNA methylation patterns. 4. Materials and Methods In this study, correlation was determined between the particular status of sperm chromatin protamination and the global 5mC and 5hmC levels of sperm DNA, using sequential staining of the same spermatozoa: (i) aniline blue staining (AB) to determine three sperm subpopulations depending on their chromatin protamination, followed by documentation of the spermatozoa positions on the slide; and (ii) estimation of global 5mC and 5hmC of sperm DNA on the same spermatozoa with documented protamination (Figure 7). Additionally, the sperm DNA fragmentation level was examined (TUNEL assay) to support the chromatin integrity data. The preparation of tests in situ on slides allowed us also to exclude from analysis any other cell type present in ejaculate that could potentially disrupt the data obtained. All tests were performed for the two analysed groups of males: healthy fertile individuals (C) and patients with oligoasthenozoospermia/oligozoospermia and reproductive failure (P). 4.1. Ethics Approval and Consent to Participate Ethical Committee approval (Local Bioethical Committee at Poznan University of Medical Sciences, approval no. 771/15) was received for the study. All participants were notified about the aim of the study, and provided written informed consent. All experiments were performed in accordance with relevant guidelines and regulations. 4.2. Participants Two experimental groups were included in this study. The control group (C) consisted of 28 healthy males with normozoospermia, proven fertility, and no history of reproductive problems. Ten control donors (C50–C61) were evaluated using a sequential staining algorithm, while for the other 18 C individuals (C5–C33), mean values for particular chromatin parameters were included [42]. The patient group (P) consisted of 31 males with reproductive failure (lack of conception or miscarriages) and oligozoospermia as the main criteria of selection. Each case was screened for karyotype and possible AZF microdeletions. Some patients also revealed decreased parameters for sperm motility and/or morphology (Supplementary Table S1). Males from both groups were selected, with attention given to their similar age (25–30 years), lack of smoking habits, lack of stimulant/drug use, and lack of exposure to toxins in their environment. Ejaculated semen samples were collected after 3–5 days of sexual abstinence. After liquefaction, samples were analysed manually according to the WHO 2010 criteria for semen evaluation (concentration, volume, motility, morphology, and viability) (Supplementary Table S1) [126]. Then, to deplete any traces of seminal plasma, samples were washed in HAM F-10 medium (Gibco; UK), and sperm samples were fixed in a fresh fixative solution (methanol:acetic acid, 3:1 v/v, −20 °C). 4.3. Sperm Chromatin Integrity Sperm chromatin integrity status was evaluated via two tests: aniline blue (AB) staining for determination of sperm chromatin protamination, and TUNEL assay for determination of sperm DNA fragmentation level. 4.3.1. Sperm Chromatin Protamination Status Sperm chromatin protamination status was evaluated using aniline blue (AB) staining [127]. Aniline blue is a reagent that binds to lysine residues in histones, resulting in dark blue staining and allowing us to determine the protamines:histones proportion. Slides with fixed sperm cells were washed (methanol:acetic acid, 3:1 v/v, −20 °C) in 2× SSC (3 min) and air dried, and then 100 µL of 1% eosin-Y solution (Merck; Germany) was applied onto slides for 3 min at RT and rinsed off with water. Slides were then stained in acidic 5% aniline blue solution (Water Blue, Fluka; Germany) for 5 min, rinsed off, air-dried, and analysed using a light microscope (Olympus BX40, Japan; oil immerse objective 100×). After AB staining, three subpopulations of spermatozoa could be recognised: pink—sperm cells with proper protamine to histone ratio, purple-pink—spermatozoa with disturbed protamines:histones ratio, and navy blue—deprotaminated sperm cells with a high proportion of remaining histones (Figure 1b). In each sample (all males from C and P groups), approximately 1500 spermatozoa were examined, followed by documentation of at least 50 spermatozoa per coloured subpopulation for further immunofluorescence staining with epimarks. Statistical power calculation revealed that the number of analysed cells should be minimum 306 for AB staining, and 45 for IF counting, in respective sperm subpopulations. Image documentation was performed using CellSense Dimension software (ver. 1.14, Olympus, Germany) and included determination of particular sperm cell localization on slides, using coordinate values (XY) depicted on the rulers at the microscopic stage. 4.3.2. Sperm DNA Fragmentation The sperm DNA fragmentation level was estimated using the TUNEL assay on slides (Flow TACS Apoptosis Detection Kit, R & D Systems, Minneapolis, MN, USA), which allows for identification of sperm cells with fragmented DNA [128]. The principle of the technique involves complex formation between biotinylated DNA fragments and streptavidin-conjugated fluorescein (FITC) in the presence of terminal deoxynucleotidyl transferase (TdT). Two populations of sperm cells can be recognized: fluorescence-labelled TUNEL-positive cells (fragmented DNA, light green) and TUNEL-negative cells labelled only with DAPI (nonfragmented DNA, blue). In each case (all individuals from the C group and 27/31 out of P group (for 4 patients there was not enough biological material for evaluation), at least 1000 sperm cells (power calculation value = 278) were counted using a fluorescence microscope (Leica DM5500, equipped with 100× oil immersion objective and SpO/FITC/Triple/DAPI filters). TUNEL assay was performed on the separate slides (not used for AB and/or IF stainings). Thus, the results of TUNEL assay refer to the mean global values for the whole ejaculate samples (without separation into sperm subpopulations). The TUNEL assay was selected as the method for sperm DNA fragmentation evaluation because of the fact that among the variety of available techniques, it is routinely used, reproducible, and the sperm chromatin integrity remains intact, which is important for other experimental approaches concerning e.g., sperm nuclear order [129,130,131]. 4.4. Immunofluorescence (IF) Immunofluorescence in situ was used to detect and measure the epimarks for global sperm DNA methylation (5mC) and hydroxymethylation (5hmC). This method has been validated previously when correlated to thin-layer chromatography (TLC) [42]. Specific antibodies conjugated to fluorochromes were applied: primary antibodies—mouse anti-5mC 1:200 (clone 33D3, cat no. MABE146, Merck), and rat anti-5hmC 1:1000 (cat no. ab106918, Abcam); secondary antibodies—goat anti-mouse-FITC 1:400 (cat no. F2012, Sigma-Aldrich), and goat anti-rat-AF594 1:800 (cat no. ab150160, Abcam). Antibodies were diluted in 1%BSA/1× PBST. Two negative controls were performed for each series of experiments: (i) without primary antibody to check the specificity of the binding, and (ii) without secondary antibody to check the possible fluorescence background level. First, samples with fixed sperm smears after AB staining and documentation were destained in 100% xylene reagent, followed by a series of washes in 1× PBST (pH 7.4, room temp., 5 min. each). Xylene washing is required for removal of any traces of oil immersion and aniline blue stain, and does not influence the immunofluorescent signals. Then, slides were incubated in 25 mM DTT/1 M Tris-HCl, pH 9.5, at room temperature for 20 min for slight decondensation of the chromatin. The degree of decondensation was fully controlled: only spermatozoa with an unaffected tail, preserved sperm head shape and a decondensed nucleus size no larger than 1.4-fold were selected. A series of washes in 1× PBST was followed by incubation in 6 N HCl. Then, blocking with 1% BSA/1× PBST for 30 min was performed. Next, overnight incubation with a mix of primary anti-m5C and anti-5hmC antibodies was performed in a humidified container at 37 °C. After double washing the samples with 1× PBST, secondary antibodies conjugated to selected fluorochromes (FITC or AF594; 60 min) were applied. Next, unconjugated antibodies were washed out (4× in 1× PBST, 5 min each). For the final detection, 20 mL of DAPI/Vectashield (Sigma-Aldrich) was added to the samples, and further analysis was performed. Approximately 200 sperm cells in each case (unfractionated into subpopulations; power calculation value = 132) were evaluated, followed by documentation and analysis of at least 50 sperm cells (power calculation value = 45) per chromatin status within the studied sperm subpopulation. Images of the IF results were acquired using a fluorescence microscope with a suitable filter set, and CellSense Dimension (Olympus) software was used (Olympus BX40, Japan; filters: DAPI/FITC/SpO/Triple; objectives: 10× and 100× with oil immersion; CCD camera). Measurements of the 5mC and 5hmC signal intensity (i.u.—intensity unit) were performed using CellSense Dimension software in-built measurement tools (‘Measure’ > ‘Intensity Profile’). The intensity of fluorescence (cell fluorescence, IF; international unit, i.u.) was calculated for each spermatozoon, including the integrated density, area of the sperm cell nucleus, and correction of the background fluorescence (measured in 5 areas outside of the spermatozoa containing only dark segments). The workflow scheme concerning the measurement of fluorescence is shown in Supplementary Figure S2. The total number of spermatozoa evaluated in the study amounted to approximately 171,100 counted (nondifferentiated) and 6150 cells documented in three analysed subpopulations. 4.5. Statistical Analysis Statistical analyses for each parameter included normality testing (D’Agostino-Pearson), ANOVA, and Fisher’s exact test for determination of differences between mean values, followed by Bonferroni correction, two-tailed Pearson correlation, and linear regression analysis for determination of possible correlations between evaluated parameters. All tests were performed with a significance level of α = 0.05 using GraphPad Prism (v.7.0e) or Analyze-it for Excel (v. 5.11) software. Statistical power calculation was performed using an online Sample Size Calculator (http://www.raosoft.com/samplesize.html, accessed on 10 March 2018) to determine the minimum number of analysed cells that should be assessed for a particular test (with standard assumptions: 95% confidence level, 5% error, 50% population). Acknowledgments The authors would like to thank Olga Wloczkowska (Poznan University of Life Sciences), Marta Dyzert and Amadeusz Odroniec (students in the IHG PAS) for their technical help during sperm staining procedures. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094516/s1. Reference [132] is cited in the supplementary materials. Click here for additional data file. Author Contributions M.O. designed the study, performed the writing and editing of the manuscript, collected and interpreted data, prepared samples, performed and supervised chromatin deprotamination and immunofluorescence experiments, and collected funding. O.K. performed the chromatin deprotamination and immunofluorescence experiments, collected and interpreted data. M.K. (Marzena Kamieniczna) performed collection of semen samples, performed seminal analyses. M.F. performed TUNEL assay. P.J. recruited patients and reviewed their medical history. M.K. (Maciej Kurpisz) recruited patients, collected their medical history, and helped with editing and finalizing the manuscript. All authors have read and agreed to the published version of the manuscript. Funding This work was funded by the National Science Centre in Poland, grant No.: 2015/17/D/NZ5/03442 (to MO). Institutional Review Board Statement Ethical Committee approval (Local Bioethical Committee at Poznan University of Medical Sciences, approval No. 771/15) was received for the study. All participants were notified about the aim of the study, and provided written informed consent. All experiments were performed in accordance with relevant guidelines and regulations. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement All the data generated or analysed during this study are included in this published article (and its Supplementary Information Files). 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 Sperm parameters observed in the control (C) and patient (P) groups. (a) Semen parameters; (b) Sperm chromatin integrity parameters (protamination—measured by aniline blue staining, and DNA fragmentation—measured by TUNEL assay); (c) Mean global DNA methylation (5mC) and hydroxymethylation (5hmC) status measured for the total, unfractionated sperm population; (d) 5mC:5hmC ratio in the unfractionated sperm population. Bars represent: (a)—upper and lower quartiles, whiskers: mean to max values and all measured points; (b–d)—mean values ± SD and all measured points. Statistical significance was considered at p < 0.05. Figure 2 Sequential staining of three sperm subpopulations, including sperm chromatin protamination status and global levels of sperm DNA methylation (5mC) and hydroxymethylation (5hmC). (a) An example of the staining results of three different sperm subpopulations; AB—aniline blue staining: pink (unstained) with proper chromatin protamination, purple (partially stained) with disturbed protamination, and navy blue (stained) with deprotaminated chromatin; 5mC—5-methylocytosine (primary antibody used: anti-5mC, clone 33D3, MABE146, Merck, Temecula, CA, USA; 1:200; secondary conjugated with FITC (F2012, Sigma-Aldrich, St. Louis, MO, USA; 1:400); 5hmc—5-hydroxymethylocytosine (primary antibody used: anti-5hmC, ab106918, Abcam, 1:1000; secondary conjugated with AF594 (ab150160, Abcam, Cambridge, UK; 1:800)). Microscope: Olympus BX40, CellSense Dimensions; Leica DM5500, CytoVision; magnification 1000×, oil immersion objective 100×; filters: DAPI/Triple/FITC/SpO; bar represents 6 μm. (b) An example of single measurement values generated by the software (CellSense Dimensions, Olympus). Figure 3 Comparison of mean 5mC and 5hmC DNA levels in three sperm subpopulations, according to the chromatin protamination status in the control vs. patient groups. Each point in the graph represents one case. For each male at least 50 spermatozoa per subpopulation were analysed; bars represent mean values ± SD and all measured points. Subpopulations of spermatozoa are coded with following colour: pink for properly protaminated, purple for semi-protaminated, and blue for deprotaminated ones. Statistical significance was considered at p < 0.05. Figure 4 Correlations between global DNA methylation (5mC) and hydroxymethylation (5hmC) levels and sperm chromatin protamination in unfractionated sperm populations in the control C and patient P groups. Each point in the graph represents one case. For each male at least 1500 spermatozoa were used for AB staining, followed by 200 for IF epimark staining. Mean global 5mC vs. mean global 5hmC levels are shown in the control C (a) and the patient P groups (c). Mean global 5mC and 5hmC levels vs. mean protamination rates are shown in the control C (b) and the patient P groups (d). Statistical significance was considered at p < 0.05. Figure 5 Correlations between methylation (5mC) and hydroxymethylation (5hmC) values (IF) vs. chromatin protamination status shown in three sperm subpopulations in the control and patient groups. (a): 5mC vs. protamination in the control group; (b): 5hmC vs. protamination in the control group; (c): 5mC vs. protamination in the patient group; (d): 5hmC vs. protamination in the patient group. Each point in the graph represents one case. For each male at least 50 spermatozoa per subpopulation were analysed. Subpopulations of spermatozoa are coded with following colour: pink for properly protaminated, purple for semi-protaminated, and blue for deprotaminated. Statistical significance was considered at p < 0.05. Figure 6 Correlations between global DNA methylation (5mC) and hydroxymethylation (5hmC) vs. mean sperm DNA fragmentation level in unfractionated sperm populations in the control C (a) and patient P (b) groups. Each point on the graph represents one case. For each male at least 1000 spermatozoa for TUNEL assay and 200 for IF epimark staining were examined. Statistical significance was considered at p < 0.05. Figure 7 Workflow scheme of the sequential staining algorithm for three sperm subpopulations, including sperm chromatin protamination status and global levels of sperm DNA methylation (5mC) and hydroxymethylation (5hmC). ijms-23-04516-t001_Table 1 Table 1 Characteristics of sperm chromatin parameters and levels of DNA epimarks in the unfractionated sperm population obtained from a group of 28 control individuals (C) and 31 infertile patients (P). The results for sperm chromatin integrity concern sperm chromatin deprotamination (AB) and sperm DNA fragmentation (TUNEL), while sperm DNA epimarks’ level was determined for global sperm DNA methylation (5mC) and hydroxymethylation (5hmC) (IF—immunofluorescence). The analyses were performed for all males from C and P groups, with the exception of the TUNEL assay which was applied for 27/31 males out of P group (for 4 males there was not enough biological material). Control Group: Mean C ± SD Patients’ Group: Mean P ± SD SPERM CHROMATIN INTEGRITY sperm chromatin protamination [%; aniline blue assay, AB] protaminated [pink] 82.02 ± 8.31 68.56 * ± 13.59 semiprotaminated [purple] 5.17 ± 4.21 9.86 ± 6.68 deprotaminated [navy blue] 12.82 ± 6.86 21.59 * ± 8.82 sum of semi- and deprotaminated 17.98 ± 8.31 31.44 * ± 13.59 spermatozoa with fragmented DNA [%; TUNEL assay] 5.52 ± 2.62 9.55 ± 6.29 EPI-MARKS in unfractionated total sperm population mean 5mC [IF i.u.] 75.61 ± 10.66 71.32 ± 30.82 mean 5hmC [IF i.u.] 126.33 ± 13.17 109.03 ± 22.74 5mC/5hmC ratio 0.60 ± 0.07 0.64 ± 0.20 Mean P-values statistically significant (p < 0.05) from the mean C values are marked with *. ijms-23-04516-t002_Table 2 Table 2 Results of 5mC and 5hmC measurements in three subpopulations of spermatozoa fractionated according to their chromatin protamination status. Subpopulation Control Group: Mean C ± SD Patients’ Group: Mean P ± SD 5mC [IF i.u.] protaminated [pink] 120.28 ± 19.65 87.29 * ± 36.01 semiprotaminated [purple] 58.92 ± 15.41 59.54 ± 26.34 deprotaminated [navy blue] 37.90 ± 8.84 42.73 ± 20.11 mean of semi- and deprotaminated 48.41 ± 10.23 51.13 ± 22.72 5hmC [IF i.u.] protaminated [pink] 134.26 ± 15.12 121.20 ± 23.42 semiprotaminated [purple] 110.85 ± 11.48 100.76 ± 24.95 deprotaminated [navy blue] 98.71 ± 9.97 81.53 ± 22.39 mean of semi- and deprotaminated 104.78 ± 10.51 91.15 ± 23.03 5mC/5hmC ratio protaminated [pink] 0.90 ± 0.12 0.70 ** ± 0.23 semiprotaminated [purple] 0.53 ± 0.12 0.58 ± 0.20 deprotaminated [navy blue] 0.38 ± 0.07 0.52 * ± 0.19 mean of semi- and deprotaminated 0.46 ± 0.07 0.55 ± 0.19 Mean P-values statistically significant (p < 0.05) from mean C values are marked with * for p < 0.05, and ** for p < 0.01; at least 50 spermatozoa were analysed per population in each case. ijms-23-04516-t003_Table 3 Table 3 Analysis of correlations between all analysed parameters in Control and Patient groups. Control Group (C) Sperm Chromatin Integrity [%] Unfractionated Total Sperm Population Properly Protaminated Subpopulation Semen Parameters Patients’ Group (P) Protaminated Fragmented DNA Glo-bal 5mC Glo-bal 5hmC 5mC/5hmC Ratio Mean 5mC Mean 5hmC 5mC/5hmC Ratio Concen-tration [×106/mL] Volume [mL] Total Count [×106] Morphology [%] Motility [%] Progres-sive Total Sperm Chromatin Integrity [%] Protaminated ns ** * * ** ** ns ns ns * ns ns ns Fragmented DNA ns ns ns ns ns ns ns ns ns ns ns ns ns Unfractionated Total Sperm Population Global 5mC ns ns ** *** ns ns ns ns ns #ns ns ns ns Global 5hmC ns ns *** ns ** ns * ns ns ns ns ns ns 5mC/5hmC Ratio ns ns *** ** ns ns ns ns ns ns ns ns ns Properly Protaminated Subpopulation Mean 5mC ns ns *** *** *** #ns * ns ns ns ns ns #ns Mean 5hmC ns ns *** *** ** *** ns #ns ns ns ns ns ns 5mC/5hmC Ratio ns ns *** ** *** *** * ns ns ns ns ns #ns Semen Parameters Concentration [×106/mL] ns ns ns ns ns ns ns ns * *** ns * * Volume [mL] ns ns ns ns ns ns ns ns ns ns ns ns ns Total Count [×106] ns ns ns ns ns ns ns ns *** ** ns ns ns Morphology [%] ns ns * ns ** ** ns ** ns ns #ns * ** Motility [%] Progressive ns ns ns ns ns ns ns ns ns ns ns ns ** Total ns ns ns ns ns ns *** ns ns ns ns ns *** Statistical description: *** p < 0.0001, ** 0.0001 < p < 0.01, * 0.01 < p < 0.05, ns—statistically non-significant (p > 0.05), #ns 0.05 < p < 0.06 (statistically non-significant but at the border value); grey colour—values statistically significant. 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==== Front Animals (Basel) Animals (Basel) animals Animals : an Open Access Journal from MDPI 2076-2615 MDPI 10.3390/ani12091098 animals-12-01098 Review Mining the Proteome of Toxoplasma Parasites Seeking Vaccine and Diagnostic Candidates https://orcid.org/0000-0002-4675-7274 Rashidi Sajad 1 https://orcid.org/0000-0002-4227-9834 Sánchez-Montejo Javier 2 Mansouri Reza 3 Ali-Hassanzadeh Mohammad 4 Savardashtaki Amir 5 https://orcid.org/0000-0001-9638-2522 Bahreini Mohammad Saleh 1 Karimazar Mohammadreza 1 https://orcid.org/0000-0002-5066-9496 Manzano-Román Raúl 2* https://orcid.org/0000-0002-2193-7316 Nguewa Paul 6* Jabbar Abdul Academic Editor 1 Department of Parasitology and Mycology, School of Medicine, Shiraz University of Medical Sciences, Shiraz 7134845794, Iran; sajaderashidiii@gmail.com (S.R.); bahreinimohammadsaleh@gmail.com (M.S.B.); mkarimazar91@gmail.com (M.K.) 2 Infectious and Tropical Diseases Group (e-INTRO), Institute of Biomedical Research of Salamanca-Research Center for Tropical Diseases at the University of Salamanca (IBSAL-CIETUS), Faculty of Pharmacy, University of Salamanca, 37008 Salamanca, Spain; s.montejo@usal.es 3 Department of Immunology, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences and Health Services, Yazd 8915173143, Iran; rmansouri@ssu.ac.ir 4 Department of Immunology, School of Medicine, Jiroft University of Medical Sciences, Jiroft 7861615765, Iran; m.hassanzadeh@jmu.ac.ir 5 Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz 7134845794, Iran; dashtaki63@gmail.com 6 Department of Microbiology and Parasitology, ISTUN Institute of Tropical Health, IdiSNA (Navarra Institute for Health Research), University of Navarra, c/Irunlarrea 1, 31008 Pamplona, Spain * Correspondence: rmanzano@usal.es (R.M.-R.); panguewa@unav.es (P.N.) 23 4 2022 5 2022 12 9 109825 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/). Simple Summary The One Health concept to toxoplasmosis highlights that the health of humans is closely related to the health of animals and our common environment. Toxoplasmosis outcomes might be severe and fatal in patients with immunodeficiency, diabetes, and pregnant women and infants. Consequently, the development of effective vaccine and diagnostic strategies is urgent for the elimination of this disease. Proteomics analysis has allowed the identification of key proteins that can be utilized in the development of novel disease diagnostics and vaccines. This work presents relevant proteins found in the proteome of the life cycle-specific stages of Toxoplasma parasites. In fact, it brings together the main functionality key proteins from Toxoplasma parasites coming from proteomic approaches that are most likely to be useful in improving the disease management, and critically proposes innovative directions to finally develop promising vaccines and diagnostics tools. Abstract Toxoplasma gondii is a pathogenic protozoan parasite that infects the nucleated cells of warm-blooded hosts leading to an infectious zoonotic disease known as toxoplasmosis. The infection outcomes might be severe and fatal in patients with immunodeficiency, diabetes, and pregnant women and infants. The One Health approach to toxoplasmosis highlights that the health of humans is closely related to the health of animals and our common environment. The presence of drug resistance and side effects, the further improvement of sensitivity and specificity of serodiagnostic tools and the potentiality of vaccine candidates to induce the host immune response are considered as justifiable reasons for the identification of novel targets for the better management of toxoplasmosis. Thus, the identification of new critical proteins in the proteome of Toxoplasma parasites can also be helpful in designing and test more effective drugs, vaccines, and diagnostic tools. Accordingly, in this study we present important proteins found in the proteome of the life cycle-specific stages of Toxoplasma parasites that are potential diagnostic or vaccine candidates. The current study might help to understand the complexity of these parasites and provide a possible source of strategies and biomolecules that can be further evaluated in the pathobiology of Toxoplasma parasites and for diagnostics and vaccine trials against this disease. Toxoplasma gondii toxoplasmosis targets vaccines diagnostics ==== Body pmc1. Introduction: Vaccine and Diagnostic Strategies in Toxoplasmosis Toxoplasma gondii, the causative agent of toxoplasmosis, is a pathogenic protozoan parasite that infects the nucleated cells of warm-blooded hosts [1]. Toxoplasmosis affects approximately one-third of the world’s human population but also may be a concern in a considerable number of mammalian and avian species, with potential associated public health risks [2,3,4]. Although toxoplasmosis is usually asymptomatic in immune-competent individuals, the outcomes of infection could be severe or fatal in patients with immunodeficiency, diabetes patients, and pregnant women and infants [5,6,7]. The One Health approach to toxoplasmosis highlights that the health of humans is closely related to the health of animals and our common environment. Therefore, the development of effective vaccine and diagnostics strategies is urgent for the elimination of this infection. The immunological effects of numerous vaccination trials, including attenuated and inactivated vaccines, genetically engineered vaccines, subunit vaccines, and DNA vaccines, have been evaluated and developed against toxoplasmosis in animal models. However, such strategies have also encountered several difficulties, such as vaccine construct, routes of administration, and standardization of immunization evaluation [8]. Live attenuated vaccines are more likely to produce the beneficial T helper (Th1) immune response compared to the subunit or DNA vaccines in different infectious agents, especially in intracellular pathogens. However, there are a limited number of trials evaluating concerns of such vaccines, maybe due to their reversion of attenuated pathogens to their virulent form [9,10]. Therefore, whole genome sequencing and appealing strategies, including clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9, to edit genes of Toxoplasma parasites and the construction of novel mutant strains have recently accelerated the improvement of live attenuated vaccines against toxoplasmosis. Thus, a huge range of experimental live-attenuated vaccines were described through deleting or knocking-out numerous genes [11,12]. Recently, a wide range of DNA vaccines against toxoplasmosis have been developed. The efficacy of such vaccines is deeply affected by the method of vaccine delivery. Furthermore, it has been suggested that DNA vaccines expressing several antigens could further induce protection against toxoplasmosis than single antigen vaccines [11]. Similarly, numerous candidate proteins involved in the Toxoplasma parasite pathogenesis, survival, and relevant critical pathways to this infection, have been employed as vaccine antigens in recombinant subunit vaccines. In this sense, the protective efficacy of multi-antigenic subunit vaccines has been underlined [11]. Some of the Toxoplasma proteins, such as calcium-dependent protein kinases (CDPKs), have been targeted as vaccine candidates against toxoplasmosis by using the abovementioned strategies. It has been indicated that the use of CDPK1, CDPK2 and CDPK3 in the form of attenuated, recombinant and DNA vaccine induced high levels of Th1-associated cytokines, and prolonged survival and decrease brain cysts in vaccinated mice [13,14,15,16,17]. In addition, in silico tools have predicted recently potential immunogenic B- and T-cell epitopes for CDPK4 and CDPK7, pointing out their potential as appropriate vaccine candidates against T. gondii [18,19]. Despite of all those approaches, there is currently no licensed toxoplasmosis vaccine available for humans. “Toxovax” is considered as the only commercial vaccine (designed based on live attenuated (S48 strain) strategy) against congenital toxoplasmosis in ewes. The use of such vaccines for humans needs to overcome big challenges, such as their high cost, adverse effects, short shelf-life, and the risk of reverting to a virulent form. On the other hand, different serodiagnostic tests have been expanded for the detection of human toxoplasmosis. As a recent strategy, the use of recombinant proteins or a combination of several recombinant proteins have been successfully suggested for measuring T. gondii antibodies at different stages of this infection. However, the development of relatively rapid, highly sensitive and specific methods has remained a prominent challenge in this sense. Therefore, integrating genomic, transcriptomic, and proteomic tools and multilocus genotyping methods with molecular and bioinformatics techniques have been currently suggested to increase the sensitivity and specificity of the diagnostic methods based on the use of recombinant proteins [20]. 2. Toxoplasma Life Cycle Stages Proteome and Proteomics The different T. gondii life stages employ specific mechanisms for triggering stage conversion, and these could be related to pathobiology within the host [21]. Changes in the expression levels of some proteins also occur as parasites progress through their life cycles, and it is likely that particular proteins have important functions in restricted life stages [22]. Since most of such proteins are involved in the parasite survival, virulence and modulation of the host immune response, the identification and biological understanding of these critical proteins in the different parasitic forms might be useful for the diagnosis, directed targeting and prevention of the disease (vaccination). Accordingly, further improvements of the effective serodiagnostic tools and the potentiality of vaccine candidates in inducing the host immune responses are considered key factors for the discovery of new functionality relevant proteins in the Toxoplasma (life cycle stages) proteome [3]. Some of the differentially expressed proteins in each stage of the Toxoplasma parasite’s life cycle could be correlated with the pathogenesis or might induce host immune responses. Thus, the use of such a common immunodominant protein expressed in all stages or the selection of several immunodominant proteins in all stages as a multistage (multivalent) vaccine could efficiently induce the desired immune responses during all stages of the parasite. On the other hand, designed vaccines based on a multistage strategy are able to exhibit efficient effects in initial and recurrent infections and probably exert major functions in restricting the bradyzoites released from tissue cysts [23]. Due to the active functions of proteins, such as Toxoplasma dense granule antigen 1 (TgGRA1) and bradyzoite antigen 1 (BAG1), during the invasion of host cell and their potential to induce increased immunoglobulin G (IgG) levels (with slight tendency to IgG2a response) and interferon gamma (IFN-γ) secreting cluster of differentiation 4 (CD4) and CD8 cells, these proteins were described as vaccine candidates to generate a multistage vaccine which could block the tachyzoite and bradyzoite stages of the parasite [24]. A common immunodominant protein, such as microneme protein 3 (MIC3), that could be expressed as a critical protein in the proteome of Toxoplasma-oocysts [22], Toxoplasma-tachyzoites (excretory-secretory antigens (ESAs) and soluble tachyzoite antigens (STAgs)) [25,26] might also be a potential multistage vaccine against toxoplasmosis. Evidence has shown that MIC3, 4, 13, rhoptry neck protein 5 (RON5), rhoptry protein 2 (ROP2), and GRA1, 6, 8, 14 with potential pathogenicity and immunogenicity properties were expressed in the three infective stages of Toxoplasma parasites. Moreover, other potential virulent and immunodominant proteins, including rhomboid 4 (ROM4), ROP5, 16, 17, 38, GRA2, 4, 15, 10, 12, 16, RON4, MIC1, 5, and surface antigen 3 (SAG3), were identified only in tachyzoites and bradyzoites stages [23]. These proteins could also be considered in multistage vaccine against toxoplasmosis. Proteomics analysis has allowed the identification of key proteins that can be utilized in the development of novel disease diagnostics and vaccines [27,28,29,30,31]. Thus, proteomic approaches may help to identify such proteins with crucial roles in mediating parasite capacity to modulate the host immune response. Those strategies may enable us to detect and select promising vaccine and diagnostic targets against toxoplasmosis [32,33,34]. Therefore, the aim of this study is bringing together the main functionality relevant proteins from Toxoplasma parasites coming from proteomic approaches most likely to be useful in improving disease management and to critically propose innovative directions to finally develop promising vaccines and diagnostic tools. Accordingly, this work also covers the possible vaccine and diagnostics properties of such important proteins. 3. Vaccine and Diagnostic Proteins Identified in the Proteome of T. Gondii Developmental Stages A number of proteomic techniques have been used for the study of the proteins expressed in the life cycle-specific stages of T. gondii (Figure 1) [22,35,36,37,38]. This approach leads to the identification of relevant stage-specific proteins in tachyzoite [37,38,39,40,41,42,43,44], tachyzoite STAgs/ESAs [26,45,46], oocyst [22,47], cyst [48,49], and sporocyst/sporozoite [50,51] of the parasite. Here, we present each of the most important proteins and the associated biological functions (Table 1) to understand their potential for seeking and suggesting the plausible Toxoplasma-vaccine and diagnostics candidates (Figure 2 and Table 2). According to Figure 2, most of the discussed studies regarding vaccine and diagnostics candidates have been designed based on the recombinant proteins and molecular vaccine (mostly DNA vaccine) strategies [52,53]. 3.1. Actin Depolymerizing Factor (ADF) The intranasal immunization with recombinant TgADF (rTgADF) can simultaneously trigger mucosal and systemic immune responses and protect mice against T. gondii infection [74]. ADF increased survival rate (36.36%) and decreased tachyzoite burden in the liver (67.77%) and brain (51.01%) from vaccinated mice. The immunostimulatory properties obtained concerning ADF, as an overexpressed protein in type III strain (CTG) [37], might suggest the use of non-pathogenic or attenuated form of Toxoplasma parasite as promising for vaccines against toxoplasmosis. 3.2. Nucleoside-Triphosphatases (NTPases) The rTgNTPase-II protein is able to provide protective Th1 cell-mediated immunity against T. gondii. The immunogenic potential of a self-amplifying RNA vaccine-encoding TgNTPase-II gene, RREP-NTPase-II, delivered by a synthetic lipid nanoparticle (LNP) has been recently evaluated in a mouse model [75]. Mice vaccinated with RREP-NTPase-II-encapsulated LNP displayed significantly enhanced protection against acute infection as well as chronic infection. The survival time was prolonged and parasite burden in the brain after acute (46.4%) and chronic (62.1%) infections was reduced in vaccinated mice. The results suggest that the combination of self-amplifying RNA and LNP would be beneficial to the development of a safe and long-acting vaccine against toxoplasmosis. 3.3. GRAs DNA vaccination has been performed with genes encoding the proteins GRA1, GRA7, and ROP2; it induced a partial protection against infections caused by different virulent T. gondii strains in CH3 mice. A high ratio of specific IG2a (IgG2a) to IgG1 antibodies detected in DNA-vaccinated mice represented a Th1-type response. The survival rate was increased from 50% to at least 90% in most of the vaccinated mice [76]. Toxoplasma GRA4 antigen was expressed by chloroplast transformation (chlGRA4) in tobacco plants and examined the cellular and humoral responses and the grade of protection against toxoplasmosis after oral administration in a murine model [77]. The oral immunization with chlGRA4 led to the induction of both a mucosal immune response and a systemic response and a decrease of 59% in the brain cyst load of mice compared to control mice, leading to the control of toxoplasmosis and reduction of parasite load. Recent experimental data inferred from tachyzoite-GRA5 showed that the recombinant form of this protein can be applied as an antigenic protein for designing serodiagnostic tools to identify toxoplasmosis, especially in hemodialysis patients. The specificity and sensitivity of enzyme-linked immunosorbent assay (ELISA) were 93% and 96%, respectively. The loop-mediated isothermal amplification (LAMP) method also corroborated the accuracy and reliability of the results obtained by designed and commercial ELISA kits [78]. The intramuscular injection of sheep with a DNA liposome formulated plasmid coding for GRA1, GRA4, GRA6 and GRA7 is an effective system that induces a significant immune response against T. gondii. GRA7 stimulated a Th1-like immune response, increasing anti-GRA7 IgG2 antibody levels and IFN-γ responses, whereas GRA1, GRA4 and GRA6 induced an IgG1 type antibody response with a limited IFN-γ response [79]. A DNA vaccine based on GRA6 of T. gondii can also induce strong humoral and cellular immunity (the major histocompatibility complex (MHC) restricted immune response) and provide partial protection against toxoplasmosis in vaccinated BALB/c mice (increasing serum levels of anti-GRA6 IgG and splenocyte proliferation) [80]. All these data further highlight the appropriate property of GRAs as DNA vaccines for immunity against toxoplasmosis. It has been recently indicated that the genetic disruption of GRA9 in Toxoplasma-type II PLK strains reduced parasite replication, survival, and cyst formation in mice models in vivo. Interestingly, the use of this attenuated vaccine significantly induced full immune responses (inducing high levels of pro-inflammatory cytokine IFN-γ and interleukin-12 (IL-12), maintaining the high T. gondii-specific IgG level, and mixed high IgG1/IgG2a levels) and represented 100% protection against acute and chronic T. gondii challenges [81]. Moreover, adjuvant and immunogenic potential of an rTg profilin (rTgPF) protein has been recently evaluated in a vaccine formulation in combination with the GRA7 antigen in a murine toxoplasmosis model [82]. The use of this vaccine significantly enhanced immune responses (generating a Th1-biased immunity through the induction of lymphocyte proliferation, the activation of CD4+ T cells and an increased IFN-γ production) and protection against chronic toxoplasmosis. TgPF acts as a ligand for toll-like receptor 11 (TLR11) and TLR12, inducing innate immune responses that increase type 1 adaptive responses, therefore highlighting the role of PF as a potential adjuvant in vaccine strategies against toxoplasmosis [82,83]. However, since TgProfilin interacts with TLR receptors that are not present in humans or livestock species [83,84], it appears less useful in this sense for relevant host vaccination. Recent data revealed that novel and interesting functions for GRA7 and GRA14 in the induction of nuclear factor kappa B (NFκB) (regulating the induction of Th1 immunity) during Toxoplasma infection. NFκB activation mediated through GRA7 and GRA14 was correlated with the Th1 response increased by inflammatory cytokines. Consequently, although the parasite survival was increased by changing the active form of parasite to inactive form (tissue cysts), the tissue invasion by parasite was decreased and led to the survival of the host [85]. This information indicated that GRA7 and GRA14 induced host immunity through NFκB and limited parasite expansion and probably further highlights the role of these GRAs in vaccination. The increase in antibody titers (total IgG and IgG2a) and the concentration of IFN-γ (a Th1 type response) was also related to the vaccination by GRA14 adjuvanted with calcium phosphate nanoparticles (CaPNs) [86]. In addition, in silico and bioinformatics approaches also underlined GRA4, GRA7 and GRA14 as possible vaccine candidates against toxoplasmosis [87]. Overall, it seems that among the GRAs, GRA4 and GRA7 could efficiently increase the survival time of vaccinated animals. The combination of GRA3, GRA7 and MIC2-associated protein (M2AP) antigens successfully reduced the cyst burden in vaccinated mice (93.5%). In addition, GRA6 and GRA10 correlated with a high immunogenicity and GRA1 and GRA2 were suggested as important virulence factors and inductors of host immune responses [58]. 3.4. SAG1 SAG1 has been described as a potential inducer of the host immune system and a vaccine candidate [88]. The nanospheres of rSAG1 were recently found to be a bio-compatible candidate for the development of a vaccine against toxoplasmosis. The intranasal injection of this recombinant protein elevated humoral responses of specific IgA and IgG2a in vaccinated mice [89]. However, it seems that the application of multi-stage antigens or cocktailed vaccines, SAG1 in combination with other proteins, including ROP2, ROP4, GRA1, GRA4, GRA7, MIC3, and BAG1 can be more effective against all stages of the Toxoplasma life cycle. ROP2 and SAG2 have been recognized as the most common antigens used for experimental cocktail vaccines together with SAG1 [90]. On the other hand, immunoinformatics-based simulation represented the appropriate interaction of a multi-epitope vaccine construct containing SAG1, along with apicoplast ribosomal proteins (S2, S5 and L11) with human TLR4 and effective induction of humoral (potent stimulation of T- and B-cell mediated immune responses) and, especially, cellular immune responses (developing high levels of IFN-γ and other components of the cellular immune profile) [91]. The use of an ELISA method based on TgrSAG1 was a potential immunodiagnostic tool (sensitivity and specificity of 98.5% and 100%, respectively) that was more accurate and reliable than latex agglutination test (LAT) for the diagnosis of Toxoplasma infection in human [92]. Furthermore, the integrated recombinant multi-epitope antigens of T. gondii (SAG1, ROP1, and GRA7) might be useful to develop clinical diagnostic kits for acute and chronic toxoplasmosis [93]. In addition, as a synthetic multiepitope antigen, the recombinant forms of several proteins, including SAG1, ROP2, GRA1, GRA4 and MIC3, have been also considered useful to design a potential ELISA test with specificity and sensitivity of 88.6% and 79.1%, respectively [94]. 3.5. Triose-Phosphate Isomerase (TPI) TPI is a glycolytic enzyme in T. gondii [95] that provokes common significant lymphoproliferative as well as Th1-biased cytokine responses in both human and golden hamsters infected by other parasites, such as Leishmania [96]. There is no information regarding TPI as a vaccine target in toxoplasmosis. However, the present data regarding the activation of the immune system and immunomodulatory properties by this stage-specific protein and the recent suggestions for TPI as a vaccine target in helminth and Leishmania parasites might further reinforce the selection of this protein as a promising vaccine candidate against toxoplasmosis [96,97,98,99]. 3.6. Protein Disulfide Isomerase (PDI) This is a protein linked to early steps of invasion. It was shown that mice immunized with 30 μg rTgPDI induced high levels of specific antibodies against this protein and protective immune responses (a strong lymphoproliferative response and high levels of IFN-γ, IgG2a, IL-2, and IL-4 were produced) [72]. 3.7. MICs Much pathogenic and immunogenic evidence revealed that MIC1, MIC3, MIC4 and MIC6 played a major function in parasite pathogenicity, while MIC3, MIC4, MIC5, MIC6, MIC8 and MIC13 were described as high immunogenic proteins [23]. MIC1-matrix antigen 1 (MAG1) recombinant chimeric antigen can be effectively applied (sensitivity: 90.8%) instead of the Toxoplasma lysate antigen (sensitivity: 91.8%) for the serodiagnosis of human toxoplasmosis, exhibiting better results than a mixture of antigens. Additionally, the use of the MIC1-MAG1 protein proposed a promising strategy to identify acute and chronic phases of toxoplasmosis [100]. MIC2 protein complex is a major virulence determinant for Toxoplasma infection. It seemed that the transmembrane adhesion MIC2 cooperated with its partner protein M2AP, participating in a major invasion pathway. MIC2 gene knockout and the decreased expression led to the mistrafficking of M2AP and consequently the loss of helical gliding motility, defective host-cell attachment and invasion, and finally the inability to support lethal infection in a murine model of acute toxoplasmosis. MIC2-deficient parasites acted as an effective live-attenuated vaccine for experimental toxoplasmosis. Furthermore, increased survival rates, a lower parasite burden, decreased inflammatory immune responses and the induction of long-lasting immunity had been observed [101]. The upregulation of MIC3 has been deciphered in pathogenic strains of Toxoplasma parasites compared to the less virulent strains [26]. MIC3 was characterized as a protein with a high potential for macrophage M1 polarization and tumor necrosis factor alpha (TNF-α) production. The high expression level of TNF-α in patients with cerebral or ocular toxoplasmosis further confirmed the role of tachyzoites secretions in the induction of TNF-α production [102]. A vaccine strategy based on the prediction of specific epitopes (B cell and T cell) from three T. gondii antigens (MRS protein: MIC3, ROP8, and SAG1) has been recently developed in BALB/c mice. Mice immunized with MRS induced stronger humoral and Th1 cell-mediated immune responses in comparison with control mice. Those results proposed that MRS, as a multi-epitope protein vaccination strategy, could be effective against toxoplasmosis infection [103]. Additional results indicated that the application of MIC3 encoding DNA and IL-12 conjugate—a multigene vaccine—might lead to an increase in the Th1 immune responses (increasing the level of IFN-γ) [104]. MIC1-3 gene knockout induced a strong humoral and cellular Th1 response and induced highly significant protection against chronic infection (>96% reduction in cysts in brain tissue) and congenital toxoplasmosis (fewer infected fetuses in vaccinated groups compared with non-vaccinated (4.6% vs. 33.3%)) [105]. Moreover, it has been indicated that DCs and macrophages are induced by rMIC1 and rMIC4 (through TLR2 and TLR4) driven to the increase in proinflammatory cytokines [106]. Although, in silico data also confirm multiple interesting B- and T-cells epitopes for MIC4 protein [107], more experimental data are needed to corroborate it as a possible vaccine candidate against toxoplasmosis. Additionally, DNA vaccines encoding Toxoplasma MIC5 and MIC16 genes induced effective immunity, including enhanced levels of IgG, IFN-γ, IL-2, IL-12p70, and IL-12p40 and CD4+ and CD8+ T cells against toxoplasmosis. Moreover, vaccination with such a cocktail vaccine prolonged the mice survival time and decreased brain cysts compared with non-vaccinated groups [108]. The more effective results obtained from the MIC5/MIC16 cocktail vaccine compared to the vaccines containing a single gene of these MICs might further render the use of such approach in MICs-based vaccination against toxoplasmosis. 3.8. ROPs ROP proteins are rhoptry paralogs showing polymorphisms. They are also related with the virulence and the pathogenicity of the different T. gondii strains [38]. Many of these proteins are involved in relevant strain specific host immunomodulatory functions, such as in the NFκB-IFN-γ axis or in the antigen presentation by MHC-I for a balanced host immune response required to achieve infection and to reduce CD8+ T cell recognition. These data, in addition to the fact that ROP antigens have long antigenic fragments and regions, support their selection as one of the strongest candidates as vaccine antigens [109,110,111]. Several ROP proteins (ROP2, 5, 9, 16, 17, 18, 22, 35) have been employed in vaccine strategies, mainly in DNA or protein vaccines against toxoplasmosis [23,112,113,114]. It has been revealed that the use of ROP1 protein induced high IFN-γ levels but low IL-4 levels in the immunized BALB/c mice [115]. Similar results were observed immunizing with ROP22 protein, however an increase in the survival time of challenged individuals was also reported [113]. A multi-antigenic ROP1 and GRA7 DNA vaccine adjuvanted with IL-12 was able to increase survival (50%) and decrease cyst burden (89%) in the brain of vaccinated mice [116]. Interestingly, ROP4 immunization reduced brain cyst numbers approximately 46% in the rROP4-vaccinated mice [117]. Among other ROPs of the parasite, ROP8, an important protein in Toxoplasma proteome, is associated with the Toxoplasma-PV, with an unknown function that can be expressed during the early stages of T. gondii infection [118,119]. Recently, the co-delivery of a novel multi-epitope plasmid (pc) ROP8 DNA vaccine with a pc encoding IL-12 (pcIL-12) (as a genetic adjuvant) has been evaluated to assess the immune responses in BALB/c mice against acute toxoplasmosis [120]. The results showed the increased level of anti-Toxoplasma antibodies (IgG total and IgG2a), Th1-type cellular immune responses (IFN-γ and IL-4), and also a prolonged survival time in immunized mice. Furthermore, vaccination with an ROP21 DNA vaccine also produced high levels of IgG (IgG total, IgG1 and IgG2a) and increased the production of IFN-γ, but the expression of other cytokines (IL2, 4, 10) was not altered [121]. Moreover, cocktailed DNA immunization with ROP5 and ROP18 in combination with adjuvant IL-33 further increased immune responses compared with a single DNA immunization with ROP5 or ROP18. This cocktailed DNA vaccine increased Toxoplasma-specific IgG2a titers, Th1 responses correlated with the production of IFN-γ, IL-2, IL-12, and cell-mediated activity with higher frequencies of CD8+ and CD4+ T cells [122]. ROP18 and MIC6 have also previously been suggested as possible vaccine targets. This vaccine efficiently induced high levels of total IgG, CD4+ and CD8+ T lymphocytes, and antigen-specific lymphocyte proliferation, and dramatically decreased the parasite cyst burden in vaccinated mice [17]. In addition, ROP18 encapsulated in poly(D,L-lactide-co-glycolide) (PLG) was able to efficiently induce Th1-biased immune responses [123]. 3.9. Heat Shock Proteins (HSP20 and HSP70) TgHSP20 is a pellicle-associated functional chaperone localized to the inner membrane complex and to the plasma membrane of the parasite. The incubation of T. gondii tachyzoites with an anti-TgHSP20 serum decreased parasite invasion at rates of 57.23% and also reduced parasite gliding by 48.7%, supporting the function of HSP20 in parasite invasion and gliding motility [124]. Such results suggested HSP20 as a possible candidate to design an attenuated vaccine against toxoplasmosis. In addition, the induction of DCs activation and successive early Th1 polarization at draining lymph nodes of C57BL/6 mice by the TgHSP70 protein highlights the immune effects (modulation of the host immune responses) of this protein against toxoplasmosis [125]. TgHSP70 vaccination reduced the inflammation in the brain of infected mice and in parallel anti-rTgHSP70 immune complexes in the serum. Moreover, the induction of inducible nitric oxide synthase (iNOS) expression and the decrease in brain infection were observed in vaccinated mice. It seemed that iNOS expression and consequently nitric oxide (NO) production in the brain was a protective mechanism induced by TgHSP70 immunization [125,126,127]. 3.10. Toxofilin, Coronin and Peroxiredoxin (Prx) These proteins were identified in the proteome of the STAgs of the parasite. Toxofilin DNA vaccine combined with the individual adjuvants, aluminum salt (alum) or monophosphoryl lipid A (MPLA), or a mixture of alum-MPLA adjuvant were able to enhance antibody responses against toxoplasmosis. Toxofilin DNA vaccination altered the Th2 immune response to a Th1 response and induced the strongest humoral and Th1 responses. The enhanced survival time and a lower number of cysts were also observed in vaccinated groups [128]. Coronin 1 seemed to be an important regulator of naive T cell homeostasis [129]. Although, a possible role against the host immune defense had been also proposed for coronin in Toxoplasma parasites [46], the regulatory function of this actin binding protein concerning the host’s immune cells remains unclear but promising. Recently, rTgPrx has been applied in dot-immunogold-silver staining (Dot-IGSS) method with a sensitivity of 97.5% and a specificity of 100% to detect Toxoplasma-IgG antibodies in infected sera [130]. In addition, the immune-stimulating activity of TgPrx1 included the production of IL-12p40 and IL-6, but not of IL-10, the activation of NF-κB and the induction of specific antibodies (IgG1 and IgG2c) and antigen-specific humoral and cellular immunity [131]. Such information suggested the function of Toxoplasma derived redox enzymes, such as Prx, as important immune modulators and probable vaccine and diagnostic candidates for toxoplasmosis [64]. 3.11. Apical Membrane Antigens (AMAs) AMA1, only expressed in the Toxoplasma-tachyzoite stage, has an immunogenicity and high pathogenicity compared to other AMAs [23]. Three tetravalent chimeric proteins containing different portions of the parasite’s AMA1 antigen-AMA1domain I-SAG2-GRA1-ROP1L (ANSGR), AMA1domains II, III-SAG2-GRA1-ROP1L (ACSGR) and AMA1full protein-SAG2-GRA1-ROP1L (AFSGR)- were evaluated for their immunogenic and immunoprotective potentialities [132]. All evaluated proteins were immunogenic and triggered specific humoral and cellular immune responses in vaccinated mice. However, the intensity of the produced immune protection depended on the fragment of the AMA1 antigen incorporated into the chimeric antigen’s structure. It has been identified that full length AMA1 can trigger further potent immunity in mice, resulting in significantly increased survival and partial protection against Toxoplasma cyst formation [132]. Furthermore, the full-length AMA1 and two different fragments (AMA1N and AMA1C) have been tested for the detection of IgG and IgM anti-Toxoplasma antibodies in human and mouse immune sera in ELISA assays [133]. The results demonstrated that the full-length AMA1 recombinant antigen (corresponding to amino acid residues 67–569 of the native AMA1 antigen) is a better biomarker (reacting with specific anti-Toxoplasma IgG (sensitivity: 99.4%) and IgM (sensitivity: 80.0%) antibodies) for the diagnosis of toxoplasmosis in comparison with the C- or N-terminal fragments of the antigen. 3.12. Protein Phosphatase 2C (PP2C) and Altered Thrombospondin Repeat Domain (SPATR) T. gondii can deliver PP2C into the host cell and direct it to the host cell nucleus [134]. It has been shown that the immunization with the rPP2C significantly induced specific IgG antibodies and cytokines and also enhanced the survival rate of immunized mice compared with that of the control groups making this a potential vaccine candidate against acute toxoplasmosis [67]. Furthermore, a SPATR-based vaccine generated humoral and mixed Th1/Th2 type cellular immune responses inducing lymphocyte proliferation and cytokine (IFN-γ, IL-2, IL-4 and IL-10) secretion, showing that SPATR may be a promising vaccine candidate against toxoplasmosis [135]. 3.13. Myc-Regulating Protein 1 (MYR1) Toxoplasma parasites deficient in MYR1 induced a weak pathogenicity in mouse infection models, suggesting that MYR1 decisively influences parasite delivery of effector proteins to the infected host cells [136]. Thus, rMYR1 protein has been suggested as a potential DNA vaccine candidate that activated Th1 and Th2 T-cell response (increasing significant levels of Th1 and mixed Th1/Th2 cytokines) at two and six weeks after immunization, respectively [70]. 3.14. Embryogenesis-Related Protein (ERP) ERP belongs to a group of four molecules called late embryogenesis abundant domain-containing proteins (LEAs). ERP as a protein specifically expressed in sporozoites of T. gondii might be used in the differentiation of tissue cyst-induced toxoplasmosis from oocyst-induced toxoplasmosis in mice, pigs, and humans [50] and consequently allowing the accurate identification of the source of infection. The seroepidemiological aspects of ERP protein was recently described [137]. For instance, the use of anti-TgERP salivary IgA for the estimation of the prevalence of toxoplasmosis in endemic areas (in individuals 15–21 years old) has shown satisfactory results (a specificity of 93.33% and sensitivity of 93.94%) [138]. In addition to the abovementioned proteins, proteomic analyses have also recognized several proteases, including cathepsins, leucyl and aspartyl aminopeptidases, prolyl endopeptidase and serine protease in the Toxoplasma-tachyzoites ESAs [139]. Some Toxoplasma’s proteases, such as cathepsin C1 and aspartic protease 3, have been described as enzymes with immune-protector roles in toxoplasmosis [140,141]. In addition, serine proteases have been also underlined as potential vaccine candidates in other parasitic diseases [142,143]. ROMs are a class of serine proteases that play major functions in parasite (such as Toxoplasma) invasion and in mitochondrial fusion and growth factor signaling, allowing the parasite to facilitate the entrance into the host cell [144]. According to the roles of proteases, especially in parasites ESAs, such enzymes could be further considered as vaccine targets. 4. Perspectives with Proteins Expressed in other Structures of T. Gondii Some other proteins have been identified in the proteome of important structures of the Toxoplasma parasite (Figure 3) [145,146,147,148]. Besides their possible therapeutic properties [145,146,149,150], such novel proteins might be further evaluated as diagnostic and vaccine targets against toxoplasmosis in the future. Since all these structures and compartments may be very dynamic at the molecular level, thus adding complexity for confidently assigning proteins to a specific subcellular compartment, an expansion of known organelle proteomes has been recently conducted applying modern spatial proteomic methods [35]. The use of such advanced tools can further identify novel proteins relevant to the parasite organelles with possible critical and vital functions in the biology and pathogenesis of Toxoplasma parasites. The subpellicular cytoskeleton is a vital structural part of the Toxoplasma parasite involved in the motility, invasion, and maintenance of the shape of different forms of the parasite [151,152,153]. The investigation related to the proteome of the Toxoplasma subcellular niches is essential to understand their functions which might increase our knowledge regarding parasite pathogenicity and may also lead to introducing novel diagnostic and vaccine targets against toxoplasmosis. TgGRA8I, expressed in the Toxoplasma subpellicular cytoskeleton proteome, plays important role in the formation of the PV and participates in the organization of the Toxoplasma subpellicular cytoskeleton and motility of this parasite [148]. TgGRA8 has been recently demonstrated as a possible serological biomarker for detecting specific Toxoplasma-IgG in goat sera. The sensitivity and specificity of the LAT for the recombinant form of this protein were 71.1% and 96.0%, respectively [154]. Moreover, elongation factor 1-alpha (EF-1α) has been identified in the proteome of Toxoplasma-subpellicular cytoskeleton, playing an important function in mediating host cell invasion by the parasite [148]. Relevant results on the evaluation of vaccine efficacy of EF-1α indicated significantly increased survival time (14.53 ± 1.72 days) of infected mice after challenge infection with the virulent T. gondii RH strain [155]. The dynamic adhesion, invasion, and even replication properties of Toxoplasma are based on machinery located in the pellicle. A group of glycosylphosphatidylinositol (GPI)-linked proteins (SRSs) were identified as important proteins in Toxoplasma-pellicle proteome [156]. Toxoplasma SRS13 and SRS29A have shown strong immunogenicity but have not been evaluated in the development of a vaccine model or diagnostic assay yet [157]. Furthermore, the use of rSRS3 protein in an ELISA system represented a sensitivity and specificity 84.12% and 92%, respectively [158]. 5. Immune Response-Based Candidates for Disease Management Proteins selected as diagnostic, or vaccination candidates are required to comply with some aspects that ensure their intended activity. As the mechanisms explaining how diagnosis and vaccination in parasites work seem different, then the ideal characteristics required for a target may also exhibit variations. Hence, by applying this perspective, we suggest a categorization of the proteins based on the role they would fulfill better. According to the literature revised in this manuscript, most of the methods that exploit the proteome of Toxoplasma for diagnosis require from the recognition of an antigenic determinant by an antibody [123,159]. Therefore, it would be suggested to select immunodominant proteins in which the antibody production predominates rather than cellular response. On the other hand, the response needed for an effective vaccination is more complex and an optimal target should develop a more cellular related immune response. These vaccination candidates should generate a Th1 immune response with the production of high levels of IFN-γ and IL-12 which induce the effectors that directly neutralize Toxoplasma or suppress its growth [160]. Table 2 summarizes potential candidates for both diagnosis and vaccination, highlighting their main features for the more suitable purpose. As the lack of standardization of a vaccination and protection assays hinders the cross-study comparison of results, it would be inaccurate to rank the best proteins. However, it would be important to remark on those candidates that stand out from the rest, especially when the immune response is well characterized. Both GRA7 in synergy with profilins [82] and GRA9 [81] elicited a strong Th1 related response and the production of proinflammatory cytokines, resulting in higher rates of protection. animals-12-01098-t002_Table 2 Table 2 Potential stage-specific vaccine and diagnostic candidates in toxoplasmosis. Proteins Vaccine/Diagnostics Utility Vaccine/Diagnostics Efficacy References GRA4 Edible vaccine Eliciting both mucosal (the production of specific IgA, and IFN-γ, IL-4 and IL-10 secretion by mesenteric lymph node cells) and systemic (in terms of GRA4-specific serum antibodies and secretion of IFN-γ, IL-4 and IL-10 by splenocytes) immune responses [77] GRA5 Diagnostic tool Specificity: 93%, sensitivity: 96% [78] GRA6 DNA vaccine ADJ with LMS High levels of anti-GRA6 IgG and splenocyte proliferation [80] GRA7 Live-attenuated vaccine ADJ with profilin Enhancing expression of CD80 and CD86 in BMDCs and secretion of IL-6, IL-10 and IL-12 Eliciting a Th1-biased immunity through the induction of lymphocyte proliferation, activation of CD4+ T cells and increased IFN-γ production [82] GRA9 Live-attenuated vaccine Inducing high levels of IFN-γ, IL-12, and IgG1/IgG2a levels (100% protection) [81] GRA14 DNA and Recombinant vaccine ADJ with CaPNs Increasing antibody titers (increased levels of total IgG and IgG2a) and concentration of IFN-γ (a Th1 type response) [86] GRA1 + GRA7 + ROP2 DNA vaccine Inducing Th1 response (a high ratio of specific IG2a to IgG1), increasing survival rate from 50% to at least 90%, decreasing the number of brain cysts [76] GRA1 + GRA4 + GRA6 + GRA7 DNA vaccine formulated into liposomes GRA7: Inducing anti-GRA7 IgG2 and IFN-γ (Th1-like immune response), GRA1, GRA4 and GRA6: stimulating a IgG1 type antibody response with a limited IFN-γ response [79] SAG1 Recombinant SAG1 vaccine (encapsulated in PLGA nanosphere) Eliciting elevated humoral responses of specific IgA and IgG2a [89] rSAG1 (diagnostic tool) Sensitivity and specificity of 98.5% and 100%, respectively [92] SAG1 + apicoplast ribosomal proteins + human TLR-4 Multi-epitope vaccine Inducing humoral (T- and B-cell mediated responses) and cellular (high levels of IFN-γ) immune responses [91] SAG1 + GRA7 + ROP1 Diagnostic tool Sensitivity and specificity (undetermined) [93] SAG1 + ROP2 + GRA1 + GRA4+ MIC3 A synthetic multiepitope antigen (diagnostic tool) Specificity: 88.6% and sensitivity 79.1% [94] ROP1 DNA and Recombinant vaccine Inducing high IFN-γ level but low IL-4 level in the immunized mice [115] ROP4 Recombinant vaccine Inducing specific production of IFN-γ as well as IL-2, the Th1-type cytokines, reducing brain cysts number approximately 46% in the rROP4-vaccinated mice) [117] ROP5 + ROP18 Cocktail DNA vaccine High specific IgG2a titers, Th1 responses correlated with the production of IFN-γ, IL-2, IL-12, and cell-mediated activity with higher frequencies of CD8+ and CD4+ T cells [122] ROP8 DNA vaccine ADJ with IL-12 Increasing the level of anti-Toxoplasma antibodies (IgG total and IgG2a), Th1-type cellular immune responses (IFN-γ and IL-4), lymphocyte proliferation, and also prolonged survival time in the immunized mice [120] Diagnostic tool (using Western blotting technique) In early acute (sensitivity 90%), acute (sensitivity 92%), and chronic toxoplasmosis (sensitivity 82%) (specificity 94% for all stages) [161] ROP1 + GRA7 Multi-antigenic DNA vaccine ADJ with IL-12 Increasing serum IgG2a titers, production of IFN-γ, IL-10, and TNF-α (increasing survival (50%) and decreasing cyst burdens (89%) in the brain of vaccinated mice) [116] ROP18, MIC6, in combination with PF, ROP16, and CDPK3 Cocktail DNA vaccine Eliciting a mixed Th1/Th2 response, with a slightly elevated IgG2a to IgG1 ratio, the enhanced production of proinflammatory cytokines IL-2, IL-12 and IFN-γ, reduction in the parasite cyst burden (80.22%) [17] ROP18 encapsulated in PLG Recombinant vaccine Inducing Th1-biased immune responses, with enhanced specific antibodies and T cells, high levels of INF-γ and IL-2, and strong lymphocyte proliferative responses [123] MIC1-MAG1 Diagnostic tool Sensitivity: 90.8%, specificity: 100% [100] MIC2 Live-attenuated vaccine (MIC2-deficient) Increasing survival of vaccinated mice correlated with lower parasite burden in infected tissues, decreasing inflammatory immune response, and induction of long-term protective immunity [101] MIC3 DNA vaccine ADJ with IL12 Increasing the level of IFN-γ [104] MIC1-3 Live-attenuated vaccine Inducing humoral and cellular Th1 response, >96% reduction in cysts in brain tissue [105] MIC5/MIC16 Cocktail DNA vaccine Enhanced levels of IgG, IFN-γ, IL-2, IL-12p70, and IL-12p40 and CD4+ and CD8+ T cells, and prolonged mice survival time and decreased brain cysts (48.06%) [108] AMA-1 Diagnostic tool (ELISA) Reacting with specific anti-Toxoplasma IgG (sensitivity: 99.4%) and IgM (sensitivity: 80.0%) [133] Recombinant epitope vaccine Inducing Th1/Th2 cytokines, the production of IgG1/IgG2a, increasing survival and partial protection against parasite-cyst formation [132] ADF Recombinant vaccine The increased levels of IgG, IL-2 and IFN-γ, increasing survival rate (36.36%) and decreasing tachyzoite load in the liver (67.77%) and brain (51.01%) [74] NTPase-II RNA vaccine Inducing IgG and IFN-γ, prolonged survival time, reducing parasite load in the brain (46.4% and 62.1% in acute and chronic infections, respectively) [75] HSP70 Recombinant vaccine ADJ with alum Reducing inflammation in the brain and anti-rHSP70 immune complexes in serum, inducing iNOS expression and decreasing brain parasitism [127] Toxofilin DNA vaccine ADJ with alum-MPLA Changing Th2 to a Th1 response and provoking the humoral and Th1 responses, inducing survival time and decreasing cyst ratio [128] SPATR DNA vaccine Activating humoral and mixed Th1/Th2 cellular responses (inducing IFN-γ, IL-2, IL-4, and IL-10) [135] PP2C DNA vaccine The increased levels of IgG2a (a predominantly Th1 immune response) and cytokines (IFN-γ) [67] PDI Recombinant vaccine Inducing higher levels of IFN-γ, IgG2a, IL-2, and IL-4 [72] MYR1 DNA vaccine Increasing significant levels of Th1 and mixed Th1/Th2 cytokines [70] ERP Diagnostic tool (ELISA) Specificity: 93.33%, sensitivity: 93.94% [138] Prx Diagnostic tool (Dot-IGSS) Sensitivity 97.5% and specificity 100% [130] Recombinant vaccine Triggering IL-12p40 and IL-6, the activation of NF-κB, eliciting specific antibodies (IgG1 and IgG2c) [131] Levamisole (LMS), adjuvant/adjuvanted (ADJ), bone marrow-derived DCs (BMDCs). Some candidates have been tested both as vaccination and diagnostic candidates. For example, SAG1 [89], ROP8 [120] and AMA-1. They produced an important humoral response with an increased production of IgGs when injected as vaccination candidates. As the response was predominantly humoral, they were found to be very suitable targets for diagnosis by ELISA [92], Dot-IGSS [130] or Western blot [161]. Hence, our insistence on the difference between a humoral or cellular directed response when choosing a Toxoplasma protein as a target. Furthermore, Table 2 also shows the type of vaccine that has been used in the reported evaluation of vaccine efficacy. It is well known that several candidates have already been evaluated using more than one vaccination technology. We need to keep in mind that it is not the topic of this review to discuss the vaccine technology employed on each of those candidates. On the other hand, there are authors that have recently addressed that issue, such as Mamaghani et al., 2022 [111]. 6. Conclusions and Future Directions Recent technological improvements for the study of proteome alterations during T. gondii life stage conversions throughout the sexual cycle have led to further answers to biological questions related to Toxoplasma-life cycle stages, and will probably open new insights towards effective vaccines [162,163]. Accordingly, the present study reviewed the vaccine and diagnostic properties of functionality important proteins expressed in the life cycle-specific stages of Toxoplasma parasites identified, applying proteomic approaches. The proteomics applied for the identification of key parasitic structures also provide valuable sources of functional proteins in these parasites. All these targets open new avenues and may shed some light on biological features of Toxoplasma, such as survival, pathogenicity, metabolic pathways, parasite-host interactions, and its life cycle. As one final aim, this information may help the reader to understand the complexity of these parasites and the potential of many proteins to initially rise good expectations as diagnostics or vaccine candidates to control toxoplasmosis. It seems that, according to the heterogeneity of host immune responses against Toxoplasma infection and the possible challenges for selecting appropriate diagnostic markers, the combination of immunogens (synthetic multiepitope antigen) may be useful for the design of diagnostic tests in human toxoplasmosis [94,164]. In addition, recent advances in our knowledge of parasite genetics and gene manipulation, key antigenic epitopes, strain variation, delivery systems and induction of immune responses are considered participating insights for the development of new vaccines which may be more efficient against toxoplasmosis [165]. Traditionally, T. gondii vaccination and diagnostic candidates have been selected by experimentally testing the immunity produced by proteins isolated directly from the pathogens using costly and time-consuming techniques. In 2001, the vaccine against serogroup B meningococcus was developed by using genome information and the “reverse vaccinology” was born [166]. This strategy used computational methods in silico to predict the suitability of a gene, protein, or epitope as vaccine candidates, allowing for high-throughput screening of “omics” data. The recently suggested genome-wide comparative datasets analyses integrating Open Reading Frame (ORF)-mediated translational regulation may reveal genomic variants important for stage conversion and thus novel parasite-specific, essential proteins not previously detected by proteomics because of the low levels for proteins coded by repressive upstream ORFs containing mRNAs. Some of these may have the likely potential to be considered as diagnostics and even vaccine candidates [167,168,169,170]. Advanced in silico models are being developed that estimate several characteristics, such as MHC bind capacity [171], T-cell receptor recognition [172], immunogenicity [173], subcellular location [174,175], etc. The implementation of these tools in machine learning models that unify estimates for several features is paramount to develop integrated computational pipelines to profile and characterize classical and new vaccination targets for T. gondii, similar to the approach recently applied in cancer derived neoantigens [176]. Regarding the immense number of T. gondii proteins reviewed in this manuscript, we suggest a further in-depth analysis using ad hoc machine learning models that integrate parasite data. Most of the research revised in this manuscript selects one or a small number of proteins that provide several degrees of partial protection. For this reason, some scientists believed that vaccines for complex pathogens, such as T. gondii, will not produce total protection using a single candidate. In silico models with the use of machine learning could help with the task of developing a more effective vaccine by characterizing and predicting the most immunogenic epitopes of proteins [177] and working towards a multiepitope vaccine. Vaccination with epitopes in T. gondii has recently been addressed [178] but the topic is fast-evolving and the prediction of epitopes and its ability to predict its binding strength to MHC improves continuously. Therefore, we encourage the revisiting of all the proteins addressed in this manuscript using present-day techniques with machine learning models [179] to predict the most immunodominant epitopes and assay them in a multiantigen vaccine, seeking a fully protective multi-antigen, multi-stage vaccine. The inclusion of multi-epitopes seems to enhance the specificity of antigenic and antibody responses and along with in silico approaches may facilitate important advances within a “one health” perspective [162,178]. To this end, the progress in proteomics needs to assess reliable protein characterizations and fully using the power of all the modern proteomic setups, as well as to explore combinatorial and new developments. In addition to the proteomic tools, other new tools aiming to identify protein composition of the different T. gondii stages, including oocyst and cyst walls and stage conversions, such as interactome constructions using proteins identified via BioID or RNA single cell sequencing [180], could lead to a better understanding of the parasite biology and introduce possible novel vaccine candidates for multi-antigenic, more effective, vaccines [11]. Acknowledgments P.N. gratefully acknowledges Fundación Roviralta, Ubesol and SPD Foundation, and COST actions CA18217 (ENOVAT) and CA18218. J.S.-M. gratefully acknowledges support Predoctoral Fellowship Program of Junta de Castilla y León co-financing by Fondo Social Europeo. We also acknowledge the entities funding this work. Author Contributions Conceptualization: S.R., R.M.-R. and P.N.; writing-original draft preparation: S.R., J.S.-M., R.M., M.A.-H., A.S., M.S.B. and M.K.; writing-review, editing and supervision: R.M.-R. and P.N. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Spanish Ministry of Science and Innovation (PID2020-112713RB-C21), Fundación La Caixa (LCF/PR/PR13/51080005) and Fundación Caja Navarra. The APC was funded by the University of Navarra. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Proteomic techniques mainly used for the identification of T. gondii proteome. Figure 2 Toxoplasma vaccine and diagnostic candidates inferred from proteomics data. Figure 3 Proteins identified in the proteome of important structures of the Toxoplasma parasite. animals-12-01098-t001_Table 1 Table 1 The biological functions of proteins expressed in life cycle-specific stages of Toxoplasma parasites employed as vaccine candidates. Proteins Location Biological Functions References ADF A related actin-binding protein (cytoskeleton) Remodeling the actin cytoskeleton (increasing the actin filaments turnover) and parasite host cells invasion [54,55] NTPases Dense granules Processing of nucleotides for purine salvage by the parasite, parasite replication and virulence [56,57] GRAs Dense granules The alteration of PV and the PV membrane in parasite (maintenance of intracellular parasitism in host cells) [58] SAG1 Parasite surface antigen Recognition, adhesion and invasion of host cells [59] TPI Carbohydrate metabolism cycle A virulence factor with important roles during pathogenesis via glucose levels modulation [60] ROPs and RONs Rhoptry Participates in the moving junction formation during parasite invasion [61] Toxofilin A secretory protein from rhoptries Binds to the parasite and mammalian actin and plays role in the host cell invasion [62] Prx A redox enzyme probably in parasite nucleus Phagocytosis, transcriptional regulation, receptor signaling, and protein phosphorylation, maintenance of parasite oxidative balance [63,64] AMA1 Microneme Host cell recognition and attachment [65] SPATR Microneme Parasite virulence and host cell recognition [66] PP2C Rhoptry Targeting the host nucleus and plays a role in parasite invasion [67] MIC3 Microneme A predominant role in the early phase of the invasion process [68] MYR1 PV membrane Exporting parasitic proteins, parasite pathogenesis [69,70] ERP Related to the resistance of parasite (oocyst) against environmental stresses [51] HSP20 IMC (parasite plasma membrane) Protect and/or modulate membrane properties of the IMC [71] HSP70 A potential immunoregulator (B cell mitogen and inducing DC maturation) [38] PDI Surface of tachyzoites Host cell interactions [72] MAG1 A protein in PV matrix, in tachyzoite vacuoles and the cyst wall and matrix in bradyzoite vacuoles As an immunomodulatory molecule (suppressing inflammasome activation) [73] Parasitophorous vacuole (PV), inner membrane complex (IMC), dendritic cell (DC). 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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093492 sensors-22-03492 Article Raman Natural Gas Analyzer: Effects of Composition on Measurement Precision https://orcid.org/0000-0002-5854-3150 Petrov Dmitry V. 12* Matrosov Ivan I. 1 Zaripov Alexey R. 1 https://orcid.org/0000-0002-0554-1346 Tanichev Aleksandr S. 1 Lepore Maria Academic Editor Delfino Ines Academic Editor 1 Institute of Monitoring of Climatic and Ecological Systems, 634055 Tomsk, Russia; mii@imces.ru (I.I.M.); alexey-zaripov@rambler.ru (A.R.Z.); tanichev_aleksandr@mail.ru (A.S.T.) 2 Department of Optics and Spectroscopy, Tomsk State University, 634050 Tomsk, Russia * Correspondence: dpetrov@imces.ru 04 5 2022 5 2022 22 9 349212 4 2022 01 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/). Raman spectroscopy is a promising method for analyzing natural gas due to its high measurement speed and the potential to monitor all molecular components simultaneously. This paper discusses the features of measurements of samples whose composition varies over a wide range (0.005–100%). Analysis of the concentrations obtained during three weeks of experiments showed that their variation is within the error caused by spectral noise. This result confirms that Raman gas analyzers can operate without frequent calibrations, unlike gas chromatographs. It was found that a variation in the gas composition can change the widths of the spectral lines of methane. As a result, the measurement error of oxygen concentration can reach 200 ppm. It is also shown that neglecting the measurement of pentanes and n-hexane leads to an increase in the calculated concentrations of other alkanes and to errors in the density and heating value of natural gas. Raman spectroscopy gas analysis natural gas methane alkanes isotopic composition heating value Russian Science Foundation19-77-10046 This work was supported by the Russian Science Foundation, grant no. 19-77-10046. ==== Body pmc1. Introduction Natural gas (NG) is the most environmentally friendly of all fossil fuels and is also a raw material for the production of many chemicals, including hydrogen [1]. To date, the basic method for measuring its composition is gas chromatography. However, this method has some disadvantages. Among them are the need for consumables, frequent calibration checks, and a long analysis time. These features make real-time measurements impossible. Devices based on optical spectroscopy do not have such drawbacks. The application of infrared (IR) spectroscopy for the analysis of NG composition was demonstrated by Kireev et al. [2,3]. The measurement accuracy of hydrocarbons is close to the gas chromatography. However, it is impossible to measure the content of diatomic homonuclear molecules (such as N2, O2, H2, etc.), using this method. Taking into account the ongoing development of energy technologies with minimal CO2 emissions, the use of hydrogen-enriched natural gas will increase [4,5]. In this regard, IR spectroscopy is not an ideal method for measuring such gas mixtures. Raman spectroscopy is a promising alternative technique. It is possible to simultaneously control the content of all types of molecules using an instrument based on this effect. The capabilities of such gas analyzers were demonstrated in many studies [6,7,8,9,10,11,12,13,14,15,16,17]. It should be noted that many authors measure alkanes only up to C4. This is explained by the weakness of the Raman signals of gaseous components and the difficulty in deriving the concentrations of heavy alkanes from the Raman spectrum of NG due to the significant overlap of the spectra of various components [18]. According to ISO 6974-5 [19], the detection limit for C2–C6 alkanes is 0.005%. Thus, a Raman gas analyzer must measure NG composition with this accuracy to be competitive with gas chromatographs. In this work, we study the capabilities of the developed Raman gas analyzer using NG samples whose composition varies in ranges close to values indicated in ISO 6974-5 [19]. In addition, we investigate the influence of line broadening and the effect of ignoring the spectra of C5+ alkanes on measurement precision. 2. Materials and Methods 2.1. Raman Gas Analyzer The Raman gas analyzer used in this work is an improved analog of the device as that used previously [6]. Its optical design is based on a 90-degree geometry of scattered light collection (see Figure 1) since spectra with a minimum background level can be recorded using this scheme. A solid-state continuous-wave laser with a power of 1.5 W at a wavelength of 532 nm was used as a source of exciting radiation. Two identical f/1.8-lenses were used for scattered light collection. An analysis of our previous results [6] and the Raman spectra of the main NG components [18] showed that it is necessary to improve the signal-to-noise ratio to improve the accuracy of measurements. In this regard, a new compact no-moving-parts f/1.8-spectrometer MKR-2m (Sibanalitpribor LLC, Tomsk, Russia) was used in this work. Its main difference from the previous spectrometer [6] is a higher spectral sensitivity (especially at the edges of the recorded range) due to the optimization of the optical scheme. The simultaneously recorded spectral range was 530–628 nm using the 1800 lines/mm grating. With an entrance slit of 40 µm, the half-width of instrumental function response was ~6 cm−1 at the center of this range. The signals were recorded using the charge-coupled device (CCD) sensor Hamamatsu S10141 (2048 × 256 pixels, 12 µm in size) with thermoelectric cooling down to −10°C. About 10-fold amplification of the Raman signals was obtained in the range of 300–1000 cm−1, where the characteristic peaks of C2+ alkanes are located, using this spectrometer (in comparison with Ref. [6]). 2.2. Concentration Measurement Method The contour fit method was used to derive the concentrations due to the significant overlap in the spectra of NG species [18]. Its essence is as follows. The NG spectrum Imix(ν) at each wavenumber ν can be represented as the sum of the spectra of its components Ii(ν):(1) Imix(ν)=∑i=1maiIi(ν), where ai is the contribution of the spectrum of the ith component to the spectrum of the mixture [0..1], and m is the number of measured components. Taking into account the number of CCD sensor columns, a system of 2048 equations can be obtained. Its solution (contributions ai) can be found using the least-squares method. The required relative concentrations (Ni) can be found using Equation (2). (2) Ni=niai∑j=1mnjaj⋅100%, where ni is the absolute concentration of the ith component in the reference spectrum Ii(ν). According to Ref. [20], the spectral characteristics (peak positions and half-widths) of the reference spectra and the spectra of the mixture should be equivalent to obtain the most accurate results. First of all, to ensure this condition, all measurements of mixtures were carried out at a pressure of 25 atm and a temperature of 300 K. Reference spectra of pure methane, ethane, nitrogen, carbon dioxide, hydrogen, and oxygen were also obtained at these parameters. The spectra of heavier alkanes (propane, n-butane, isobutane, n-pentane, iso-pentane, neo-pentane, and n-hexane) liquefy under the above conditions. For this reason, they were obtained at saturated vapor pressure. The exposure time for each reference spectrum was 1000 s. 2.3. Experiment Three samples of synthetic NG with significantly different compositions were used for research (see Table 1). These samples are the reference gas mixtures with low uncertainties that were purchased from Monitoring LLC (Saint Petersburg, Russia). Measurements were carried out for three weeks, once a week, to assess the long-term stability of the results. The sequence of analysis of mixtures is presented in Table 2. A series of five measurements were performed for each mixture with the replacement of the sample in the cell. The time of one analysis was 30 s. Note that the set of reference spectra of pure components was obtained once before the measurement procedure was started. Additional calibration procedures were not performed during all measurements. 3. Results and Discussion 3.1. Mixture Measurements Figure 2 and Figure 3 show the obtained Raman spectra of the samples of NG. Despite mutual overlaps, the characteristic peaks of most components are distinguishable at the resolution of the spectrometer used. The achieved sensitivity makes it possible to see the lines of the ν4 band of methane down to ~800 cm−1. In addition, a wide unresolved band is observed in the methane spectrum in the region of 300–600 cm−1. We suppose this is a collision-induced rotational band [21,22], which is attenuated up to ~350 cm−1 by the notch filter. Bands of C–C–C deformation vibrations of C3+ hydrocarbons are also located in the region of 300–500 cm−1 (see Figure 4). The accuracy of concentration measurements can be improved using this range due to intense peaks of n-butane (429 cm−1), n-pentane (398 cm−1), and iso-pentane (459 cm−1), the overlap of which is not as significant as in the region of 700–1000 cm−1. Thus, to measure low concentrations, it is necessary to take into account the contribution of the methane spectrum to the spectrum of NG not only in the region of >990 cm−1 (as indicated in Ref. [18]) but also in the region of lower wavenumbers. The inset in Figure 2 shows the vibrational band of nitrogen (2330 cm−1), whose concentration in sample 1 is 54 ppm, despite its significant overlap with the lines of the 2ν4 and ν3 bands of methane, is also well observed. Hence, concentrations with a sensitivity of <50 ppm can be measured due to the achieved signal-to-noise ratio. The limits of detection will be estimated below. The range of 300–2400 cm−1 was used to determine the composition of mixtures. All measured concentrations during one day for each mixture were averaged. The concentrations (C) and their standard deviations (σ) are presented in Table 3, Table 4 and Table 5. It can be seen that the measured and reference concentrations are in good agreement taking into account the uncertainties. The only exception is data of n-hexane in samples 2 and 3. For most components, the variation in measured concentrations over all days is within their mean standard deviation. It indicates these variations are due to noise in the spectra. Thus, the presented data confirm that Raman gas analyzers can operate for a long time without calibration, unlike gas chromatographs. The relative measurement errors of each component were obtained using the mean standard deviations (see Figure 5). It can be seen that these values depend both on the concentration and the type of molecule (due to different scattering cross-sections and the level of overlap of the spectral bands). Taking into account that the measurement errors of gas chromatographs are close to 5%, it can be concluded that the accuracy of the presented Raman gas analyzer is higher for species with a concentration of more than ~100 ppm. 3.2. Limits of Detection Limits of detection (LODi) were estimated using Equation (3). Here, we defined the concentrations at which the signal of ith component is three times the standard deviation of the noise. The spectrum of sample 1 was used to obtain these data. Peak intensities of each component (Si) were estimated, taking into account their contribution to the spectrum of the mixture (see Figure 6). The difference between two successive spectra of sample 1 was obtained to estimate the magnitude of the noise (see Figure 7). It can be seen that the noise in the region of 500–1000 cm−1, where the characteristic bands of C2+ alkanes are located, is less than in the region of intense lines of the ν2 band of methane (1200–1700 cm−1). This feature is related to the effect of photon shot noise, which is proportional to the square root of the signal intensity. In this regard, the noises that affect measurement errors and LODs are higher for CO2 and O2 than for all other components. The standard deviations of noise (Ni) were calculated using the intensities in the spectrum shown in Figure 7 in the following regions: 1540–1580 cm−1 (for O2), 1280–1380 cm−1 (for CO2), and 700–900 cm−1 (for other components). Concentrations of components (Ci) in sample 1 for calculations were taken from Table 1. The results obtained are presented in Table 6. It can be seen that the LOD values are within the range of 2–35 ppm. Thus, the achieved sensitivity of the Raman analyzer meets the requirements of ISO 6974-5 [19]. (3) LODi=3CiSi/Ni, 3.3. Influence of Line Broadening on Measurements Let us consider the features of O2 measurement. It has one fundamental vibrational band with the position of the maximum at 1555 cm−1, which is overlapped by the ν2 band of methane (see Figure 3). Hence, the measurement accuracy is affected by the broadening of the spectral lines of methane [20] besides the signal-to-noise ratio. Pressure [23] and molecular environment [24,25] influence the half-widths of the lines. The line at 1793 cm−1 was analyzed to assess the influence of the composition on the line half-widths of the ν2 band of methane. This line was chosen since it is not overlapped by the spectra of other species and, therefore, the measurement error of its half-width in mixtures is eliminated. The data obtained and the half-width of this line as a function of pure methane pressure are shown in Figure 8. It can be seen that the half-width increases with a decrease in the fraction of methane in the mixtures. This broadening is related to an increase in the concentration of heavy hydrocarbons in the mixture since the methane-methane broadening coefficients are less than the broadening coefficients of methane-ethane, methane-propane, etc. [25]. According to Figure 8, an increase in the pressure of pure methane to 26.6 atm leads to the same broadening as in the spectrum of sample 3 at a pressure of 25 atm. Thus, in our case, we can use the spectra of pure methane at pressures of 25.0 and 26.6 atm to estimate the error in oxygen measurements due to the broadening of methane lines. The spectrum at a pressure of 26.6 atm was multiplied by the 25/26.6 value to ensure equal integral intensities of these spectra. Figure 9 shows the difference between these methane spectra in the region of 1555 cm−1, denoted as R. According to Equation (4), this effect leads to an oxygen measurement error (∆) close to 200 ppm. (4) Δ=R⋅100%IMAX, where IMAX is the peak intensity of the spectrum of pure oxygen at 25 atm. Taking into account the concentration ranges of C2+ alkanes in NG [19], it can be concluded that the systematic error in oxygen measurement can reach 200 ppm (depending on the composition). This error is less than the uncertainty of the reference O2 concentration in sample 3. However, in the case of an O2 concentration in such a mixture below 200 ppm, this is a sufficiently large value that cannot be ignored. Calibration coefficients or a reference spectrum of pure methane at a pressure that results in the required line broadening can be used to obtain reliable data. We believe that the deviations of the measured hexane concentrations from the reference values are due to similar effects. Although hexane has several bands in the region of 700–900 cm−1, their peak intensity is relatively low (see Figure 6), and all of them are overlapped by the spectra of other molecules [18]. Thus, a change in the spectral characteristics of alkanes in a mixture compared to a pure substance can lead to errors in measurements of the hexane concentration. We plan to study these features in more detail in the future. 3.4. Estimation of Errors in the Case of Ignoring C5+ Spectra We decided to estimate the errors in the case of neglecting pentanes and hexane since many authors analyze the composition of mixtures only up to C4 [7,9,10,11,12,13,14,15]. All spectra of mixtures obtained during the first day of experiments were used. The spectra of pentanes and hexane were excluded from the set of reference spectra of pure components to calculate the concentrations. The results obtained are presented in Table 7. It can be seen that ignoring these components leads to an increase in the measured concentrations of ethane, propane, and butanes. Taking into account that this effect is due to the overlap of their spectra, the errors depend on the composition of the mixture and cannot be eliminated using calibration coefficients. In addition to these data, the characteristic parameters [26], which are required for power plant operators, were calculated. To this end, the concentrations shown in Table 7 and Table 3, Table 4 and Table 5 (1st day) were used. As shown in Table 8, these characteristics correspond to the reference data when all components are measured. In turn, only the heating value of sample 1 corresponds to the reference value in the case of ignoring the measurement of pentanes and hexane. Despite the increase in the measured concentrations of other alkanes, other characteristics are significantly less than the reference ones. Thus, reliable characteristic parameters of NG cannot be obtained by measuring alkanes only up to C4. 3.5. Variation in the Isotopic Composition of Methane We noticed the different intensity of the peak with a wavenumber of 2196 cm−1 between the spectra of pure methane and sample 1 during the experiments. The ν2 band of the CH3D methane isotopologue is located in this region (see Figure 10). This discrepancy may be due to the different nature of the origin of the pure methane and methane in the mixtures. The difference in the peak intensity is ~0.4% and agrees with possible CH3D/CH4 variations in NG [27]. We did not find signs of 13CH4/12CH4 variation in our samples since there is a small shift in their lines relative to each other in the ν2 region [28]. It is worth noting that knowledge of the isotopic composition of methane is also useful. It is possible to determine the type of reservoir (gas, gas condensate, or oil), as well as the origin of natural gas (biogenic or thermogenic) based on this information [29]. Raman gas analyzer can also measure the content of 13CH4 by registration of spectra up to 3100 cm−1 [30,31]. Note that when using the contour fit method, the discrepancy in the isotopic composition of methane in comparison to the reference methane can lead to a difference between their spectra and, consequently, to errors in the measurement of other components. In this case, the simulation of spectra can be used to improve the reliability of measurements [32]. The effects of pressure, molecular environment, and the contributions of all isotopologues can be taken into account to obtain a spectrum using this approach. 4. Conclusions This study presents the features of natural gas analysis using Raman spectroscopy. The use of the contour fit method to derive concentrations from the spectra of mixtures makes it possible to obtain reliable results even with a significant change in the composition of the samples. However, in the case of measuring low concentrations of components whose characteristic peaks are overlapped by intense bands of other molecules, it is necessary to take into account the change in spectral characteristics due to changes in the molecular environment to increase the accuracy. The data obtained confirmed that such devices can operate for a long time without calibration. This is a very important advantage of Raman gas analyzers over analogs. The achieved detection limits of the developed compact Raman gas analyzer are 2–35 ppm at a pressure of 25 atm and an analysis time of 30 s. This level of sensitivity makes it possible to monitor the isotopic composition of methane. In turn, it is possible to reduce the analysis time or improve the accuracy by using a more powerful laser and/or a photodetector with a lower noise level. Taking into account the advantages of Raman gas analyzers, we believe that they have great potential in natural gas analysis and can replace conventional gas chromatographs. Author Contributions Conceptualization, methodology, writing—original draft, D.V.P.; investigation, I.I.M.; resources, A.R.Z.; visualization, writing—review and editing, A.S.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 Data are contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic of Raman gas analyzer. Figure 2 Raman spectra of pure methane and sample 1. Figure 3 Raman spectra of sample 2 and sample 3. Figure 4 Raman spectra of C1–C6 alkanes in the range of 300–500 cm−1. The intensities correspond to the equivalent pressure. Figure 5 Relative measurement errors of alkanes at different concentrations. Figure 6 Contributions of the species to the spectrum of sample 1. Figure 7 Difference between two successive spectra of sample 1. Figure 8 Half-width of the methane line at 1793 cm−1 in pure methane at various pressures and in analyzed samples at 25 atm. Figure 9 Raman spectra of methane (at 25 and 26.6 atm) and oxygen (at 25 atm). The inset shows that the broadening of the methane lines leads to different intensities in the region where the oxygen band is located. Figure 10 Raman spectra of pure methane and sample 1 in the range of 1800–2400 cm−1. sensors-22-03492-t001_Table 1 Table 1 Composition of natural gas samples used. Component Concentration (%) Sample 1 Sample 2 Sample 3 CH4 99.9403 95.998 49.0379 C2H6 0.00496 0.997 15.1 C3H8 0.00474 0.509 6.05 n-C4H10 0.00493 0.105 0.709 iso-C4H10 0.00497 0.102 0.816 n-C5H12 0.00503 0.0474 0.205 iso-C5H12 0.00522 0.0472 0.19 neo-C5H12 0.0048 0.01 0.0511 n-C6H14 0.00445 0.0236 0.131 CO2 0.0047 1 10.1 N2 0.0054 1.039 15.1 H2 0.00559 0.102 0.5 O2 0.0048 0.0198 2.01 sensors-22-03492-t002_Table 2 Table 2 Program of measurements. Day Sequence of Sample Analysis 1st #1–#2–#3–#2–#1–#3–#2 2nd #2–#1–#2–#1–#2–#1–#2–#3 3rd #1–#3–#1–#3–#1–#3–#1–#2 sensors-22-03492-t003_Table 3 Table 3 Measurement results for sample 1. Component Reference Data Data Obtained 1st Day 2nd Day 3rd Day C (%) σ (%) C (%) σ (%) C (%) σ (%) C (%) σ (%) CH4 99.9403 0.0023 99.94 0.0023 99.938 0.0022 99.9401 0.0046 C2H6 0.00496 0.00018 0.00479 0.00027 0.00508 0.00025 0.00526 0.00047 C3H8 0.00474 0.00022 0.00496 0.00011 0.0052 0.00024 0.0052 0.00031 n-C4H10 0.00493 0.00023 0.00453 0.00025 0.00501 0.00027 0.00466 0.00030 iso-C4H10 0.00497 0.00023 0.00492 0.00006 0.0049 0.00007 0.00486 0.00011 n-C5H12 0.00503 0.00023 0.00545 0.00019 0.00549 0.00018 0.00514 0.00032 iso-C5H12 0.00522 0.00024 0.00496 0.00019 0.00517 0.00015 0.00508 0.00016 neo-C5H12 0.0048 0.00023 0.00492 0.00004 0.00493 0.00005 0.00494 0.00005 n-C6H14 0.00445 0.00021 0.00505 0.00064 0.00524 0.00072 0.00429 0.00098 CO2 0.0047 0.0005 0.00527 0.00071 0.00509 0.00031 0.00504 0.0011 N2 0.0054 0.0005 0.00539 0.00035 0.0048 0.00027 0.00584 0.0006 O2 0.0048 0.0005 0.00457 0.0010 0.00595 0.0011 0.00428 0.0014 H2 0.00559 0.00025 0.0051 0.00008 0.00508 0.00008 0.0052 0.00009 sensors-22-03492-t004_Table 4 Table 4 Measurement results for sample 2. Component Reference Data Data Obtained 1st Day 2nd Day 3rd Day C (%) σ (%) C (%) σ (%) C (%) σ (%) C (%) σ (%) CH4 95.998 0.09 95.9512 0.0042 95.9509 0.0046 95.9503 0.0029 C2H6 0.997 0.02 1.0172 0.0010 1.0181 0.0011 1.0179 0.0009 C3H8 0.509 0.015 0.5166 0.0006 0.5168 0.0008 0.5173 0.0005 n-C4H10 0.105 0.003 0.1038 0.0004 0.1035 0.0005 0.1042 0.0003 iso-C4H10 0.102 0.003 0.1018 0.0002 0.1018 0.0002 0.1019 0.0002 n-C5H12 0.0474 0.0015 0.0455 0.0003 0.0446 0.0003 0.0446 0.0003 iso-C5H12 0.0472 0.0015 0.0479 0.0002 0.0481 0.0004 0.0482 0.0003 neo-C5H12 0.01 0.0004 0.0096 0.00005 0.0096 0.00006 0.0096 0.00004 n-C6H14 0.0236 0.0008 0.0184 0.0007 0.0183 0.0006 0.0186 0.0006 CO2 1 0.03 1.0238 0.0012 1.0234 0.0010 1.0228 0.0006 N2 1.039 0.021 1.0447 0.0014 1.0451 0.0015 1.0432 0.0005 O2 0.0198 0.001 0.0206 0.0015 0.0205 0.0017 0.0221 0.0008 H2 0.102 0.003 0.0989 0.0002 0.0988 0.0002 0.099 0.0001 sensors-22-03492-t005_Table 5 Table 5 Measurement results for sample 3. Component Reference Data Data Obtained 1st Day 2nd Day 3rd Day C (%) σ (%) C (%) σ (%) C (%) σ (%) C (%) σ (%) CH4 49.038 1.12 49.499 0.0285 49.517 0.0049 49.518 0.0071 C2H6 15.1 0.3 14.908 0.0079 14.913 0.0081 14.905 0.0103 C3H8 6.05 0.18 6.0128 0.0036 6.0138 0.0021 6.0091 0.0043 n-C4H10 0.709 0.021 0.6987 0.0024 0.6985 0.0019 0.698 0.0017 iso-C4H10 0.816 0.025 0.8177 0.0005 0.8175 0.0006 0.817 0.0007 n-C5H12 0.205 0.006 0.204 0.0015 0.209 0.0017 0.2089 0.0022 iso-C5H12 0.19 0.006 0.1832 0.001 0.1829 0.0009 0.1828 0.0009 neo-C5H12 0.0511 0.0016 0.0502 0.0001 0.0502 0.0001 0.0508 0.0001 n-C6H14 0.131 0.004 0.1444 0.0033 0.1564 0.0044 0.1566 0.0049 CO2 10.1 0.3 9.9551 0.0151 9.931 0.0106 9.9319 0.0102 N2 15.1 0.3 15.035 0.015 15.02 0.0078 15.032 0.0134 O2 2.01 0.06 1.978 0.0017 1.9772 0.0007 1.9766 0.0012 H2 0.5 0.015 0.5141 0.0008 0.5134 0.0006 0.5125 0.001 sensors-22-03492-t006_Table 6 Table 6 Parameters for Equation (3) and limits of detection of the Raman natural gas analyzer. Component S (arb.u.) N (arb.u.) LOD (ppm) C2H6 4.3 0.017 5.9 C3H8 4.94 0.017 4.9 n-C4H10 2.15 0.017 11.7 iso-C4H10 7.39 0.017 3.4 n-C5H12 1.94 0.017 13.2 iso-C5H12 2.87 0.017 9.3 neo-C5H12 11.27 0.017 2.1 n-C6H14 0.73 0.017 31.1 CO2 5.5 0.036 9.2 N2 2.8 0.017 9.8 O2 2.8 0.068 35.1 H2 6.8 0.017 4.2 sensors-22-03492-t007_Table 7 Table 7 The results of the analysis of mixtures, the spectra of which were obtained during the first day of experiments, in the case of ignoring C5+ alkanes. C*/C is the ratio of the concentration obtained by measuring alkanes up to C4 to the concentration obtained by measuring all components (data from Table 3, Table 4 and Table 5). Component Sample 1 Sample 2 Sample 3 C* (%) C*/C C* (%) C*/C C* (%) C*/C CH4 99.9419 1.000 95.960 1.000 49.779 1.006 C2H6 0.00644 1.353 1.0280 1.011 14.872 0.998 C3H8 0.0088 1.774 0.5405 1.046 6.1022 1.015 n-C4H10 0.01348 2.975 0.1588 1.530 0.9894 1.416 iso-C4H10 0.00746 1.516 0.1194 1.173 0.8907 1.089 n-C5H12 -- -- -- -- -- -- iso-C5H12 -- -- -- -- -- -- neo-C5H12 -- -- -- -- -- -- n-C6H14 -- -- -- -- -- -- CO2 0.00629 1.194 1.0273 1.003 9.9140 0.996 N2 0.0055 1.020 1.0443 0.999 14.963 0.995 O2 0.00447 0.978 0.0199 0.966 1.9616 0.992 H2 0.00561 1.100 0.1016 1.027 0.5285 1.028 sensors-22-03492-t008_Table 8 Table 8 Comparison of characteristics of natural gas samples. Sample Parameter Reference Data Data Obtained All Species Were Measured C5 and C6 Were Ignored 1 Lower heating value (MJ/kg) 33.45 ± 0.03 33.45 33.44 Relative density 0.55545 ± 0.00004 0.55547 0.55528 2 Lower heating value (MJ/kg) 33.54 ± 0.04 33.53 33.47 Relative density 0.5838 ± 0.0004 0.5841 0.5830 3 Lower heating value (MJ/kg) 33.12 ± 0.19 33.13 32.86 Relative density 0.8908 ± 0.0040 0.8876 0.8807 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Chen L. Qi Z. Zhang S. Su J. Somorjai G.A. Catalytic Hydrogen Production from Methane: A Review on Recent Progress and Prospect Catalysts 2020 10 858 10.3390/catal10080858 2. Kireev S.V. Podolyako E.M. Symanovsky I.G. Shnyrev S.L. Optical absorption method for the real-time component analysis of natural gas: Part 1. Analysis of mixtures enriched with ethane and propane Laser Phys. 2011 21 250 257 10.1134/S1054660X10160012 3. Kireev S.V. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092607 jcm-11-02607 Article SARS-CoV-2 Droplet and Airborne Transmission Heterogeneity Baselga Marta 1 Güemes Antonio 12 Alba Juan J. 13 https://orcid.org/0000-0002-0136-1049 Schuhmacher Alberto J. 14* Zhang Yudong Academic Editor 1 Institute for Health Research Aragon (IIS Aragón), 50009 Zaragoza, Spain; mbaselga@iisaragon.es (M.B.); aguemes@unizar.es (A.G.); jjalba@unizar.es (J.J.A.) 2 Department of Surgery, University of Zaragoza, 50009 Zaragoza, Spain 3 Department of Mechanical Engineering, University of Zaragoza, 50018 Zaragoza, Spain 4 Fundación Agencia Aragonesa para la Investigación y el Desarrollo (ARAID), 50018 Zaragoza, Spain * Correspondence: ajimenez@iisaragon.es 06 5 2022 5 2022 11 9 260726 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/). The spread dynamics of the SARS-CoV-2 virus have not yet been fully understood after two years of the pandemic. The virus’s global spread represented a unique scenario for advancing infectious disease research. Consequently, mechanistic epidemiological theories were quickly dismissed, and more attention was paid to other approaches that considered heterogeneity in the spread. One of the most critical advances in aerial pathogens transmission was the global acceptance of the airborne model, where the airway is presented as the epicenter of the spread of the disease. Although the aerodynamics and persistence of the SARS-CoV-2 virus in the air have been extensively studied, the actual probability of contagion is still unknown. In this work, the individual heterogeneity in the transmission of 22 patients infected with COVID-19 was analyzed by close contact (cough samples) and air (environmental samples). Viral RNA was detected in 2/19 cough samples from patient subgroups, with a mean Ct (Cycle Threshold in Quantitative Polymerase Chain Reaction analysis) of 25.7 ± 7.0. Nevertheless, viral RNA was only detected in air samples from 1/8 patients, with an average Ct of 25.0 ± 4.0. Viral load in cough samples ranged from 7.3 × 105 to 8.7 × 108 copies/mL among patients, while concentrations between 1.1–4.8 copies/m3 were found in air, consistent with other reports in the literature. In patients undergoing follow-up, no viral load was found (neither in coughs nor in the air) after the third day of symptoms, which could help define quarantine periods in infected individuals. In addition, it was found that the patient’s Ct should not be considered an indicator of infectiousness, since it could not be correlated with the viral load disseminated. The results of this work are in line with proposed hypotheses of superspreaders, which can attribute part of the heterogeneity of the spread to the oversized emission of a small percentage of infected people. COVID-19 bioaerosols infectious diseases cough airborne superspreaders transmission heterogeneity Instituto de Investigación Sanitaria AragónThis research was funded by the Instituto de Investigación Sanitaria Aragón: Campaña Investiga Covid-19 (CoviBlock). ==== Body pmc1. Introduction After more than two years of the COVID-19 pandemic, the role of the different transmission routes in the dynamics of the spread of the SARS-CoV-2 virus are still unknown. Human–human transmission has been described from direct respiratory spread, where the symptomatic or asymptomatic patient expels contaminated particles in respiratory events, and, on the other hand, indirect spread or via fomites, where the transmission is due to contact with contaminated surfaces. Regarding direct dissemination, fomites are objects that can be contaminated with pathogenic microorganisms and serve as transmission vehicles [1,2]. Variable SARS-CoV-2 survival depends on the surface material; it remains active for up to 72 h on plastic and stainless steel, up to 24 h on cardboard, and less than 4 h on copper [3]. On polymeric surfaces and skin, the Alpha, Beta, Delta, and Omicron variants exhibited survival twice as high as the ancestral strain, reaching a persistence of more than 16 h on the skin [4]. It is possible to differentiate between the droplet model and the bioaerosol model regarding indirect dissemination. Droplets and bioaerosols differ primarily in their aerodynamic diameter and properties. Large droplets predominate in close contact, but they are not capable of infecting individuals at a distance, since they settle rapidly due to gravitational effects. However, the aerodynamic diameter of aerosols allows them to be transmitted over time and distance [5], as represented in Figure 1. This interaction phenomenon between gravity and evaporation, depending on the size of the drop, was described in 1955 by Wells [6]. Suspension time can be determined from Stokes’ Law, which describes an inverse relationship between particle size and deposition rate. For example, a 5 µm aerosol takes about 33 min to settle on the ground, while a 1 µm aerosol remains suspended in the air for more than 12 h [7]. Regarding this pandemic, the scientific community has redefined the concept of bioaerosol, extending its consideration to airborne particles smaller than 100 µm, based on evidence and common factors related to the aerodynamics of the particles. Nevertheless, it is necessary to consider that both large droplets and bioaerosols are dynamic, since they can modify their morphology and physical–chemical properties, depending on environmental parameters. In this way, as we will discuss later, small droplets can become aerosols and, in turn, larger aerosols can migrate towards smaller aerosols, modifying their aerial dynamics. Fine particles pose greater challenges when it comes to preventing potential contagion: on the one hand, because they correspond to the size range where the retention efficiency of filters is lower (they typically have a minimum efficiency around 300 nm [8,9]); on the other, because they can remain suspended indefinitely and reach greater distances from their emitter. The viruses are transported through small secretions of saliva and mucosa in infected people, inadvertently expelled through the nose and mouth. It is possible to differentiate between bronchiolar, laryngeal, and oral bioaerosols, depending on the generation mechanism and anatomical region where they originate. Bronchiolar particles are predominantly attributed to normal breathing and are associated with the rupture of the fluid film in the bronchioles by shear forces [10]. The vibration of the vocal cords generates laryngeal secretions during speech and vocalization [11]. Instead, oral particles where droplets are larger than 100 µm are predominantly produced from saliva in the oral cavity. Their emission rate and velocity depend on the effort during the vocalization event [11]. Other study suggests a dependence between the rate of aerosol emission and the amplitude of vocalization and, furthermore, points to the existence of independent “superspreading” events [12]. These bioaerosols are predominantly composed of ions (predominantly Na+, Cl−, Ca2+, and Mg2+), organic and inorganic particles and glycoproteins, mainly albumin, mucins, cholesterol and pulmonary surfactant proteins, such as DPPG and DPPC [13]. They can also include, in infected individuals, viral or bacterial pathogens. This is especially relevant during infections that present a high viral load in the upper respiratory tract due to the anatomical proximity to the ‘escape routes’, as is the case for COVID-19 [3,14,15]. The airborne model of COVID-19 disease transmission has been demonstrated [16] among small animals [17,18,19], from viral superspreading events [20], in long-distance transmission scenarios where infected individuals do not come into direct contact [21], by transmission in asymptomatic individuals [22], and by the prevalence of spread in closed spaces [23]. Despite the alerts by scientific groups since April 2020, this route of contagion was dismissed, and greater attention was paid to fomites and contagion by droplets, following the classic models of transmission of respiratory diseases for the COVID-19 pandemic. Consequently, there was controversy about whether asymptomatic infected individuals could be transmitters of SARS-CoV-2, which was an obstacle during epidemiological management. The global acceptance of the spread of COVID-19 by aerosols has modified the preventive approach, including new measures to reduce the risk of contagion. In April 2021, this route of infection was accepted by the WHO as one of the main ones [24]. The size of the SARS-CoV-2 virion varies between 70 and 90 nm [25,26], and a mean virus concentration in sputum of 7.0 × 106 copies/mL and a maximum of 2.4 × 109 copies/mL has been reported [27]. Consequently, the viral load occupies 2.1 × 10−6 % of the bioaerosol on average. With this value, Lee [28] estimated a theoretical minimum and initial aerosol size of 4.7 µm to contain SARS-CoV-2. However, experimental bioaerosol sampling studies suggest the presence of the virus in smaller particle sizes (even <0.25 µm). Liu et al. [29] were pioneers in experimentally investigating the aerodynamic nature of the SARS-CoV-2 pathogen by quantifying viral RNA from aerosols in different hospital areas in Wuhan (China) during one of its most severe outbreaks. In their work, they determined the presence of viruses predominantly in two size ranges: in the submicrometric region (0.25–1.0 µm) as well as in the supermicrometric region (>2.5 µm). Since then, numerous scientific efforts have aimed at characterizing and understanding the dynamics of the spread of COVID-19 associated with aerosols. However, the role of airborne transmission for the SARS-CoV-2 virus and the risk of contagion that they might represent have not yet been well described. The modal distributions of aerosols acquire great relevance in the context of disease transmission. They determine the aerodynamic characteristics and their deposition dynamics, as well as the variability in the viral colonization model, depending on the depth of the respiratory tract [30]. In addition to influencing the modal distribution of aerosols, the nature of the activity carried out will modify parameters associated with the kinetics of the particles. Chao et al. [31] pointed to a mean velocity of 11.7 m/s during coughing and 3.9 m/s when speaking. Their experimental work described a geometric mean diameter of 13.5 µm when coughing and 16.0 µm when speaking, with an estimated concentration of 2.4–5.2 cm−3 in coughs and 0.4 × 10−3–0.2 cm−3 in speaking. The disseminating capacity of the individual is noticeably modified if the individual is speaking or coughing. Specifically, it has been described that during a one-minute conversation, more than 1.0 × 103 aerosols can be disseminated [32], and an individual expels around 7.2 × 103 particles per liter of exhaled air [33,34], while coughing occurs sporadically, implying a likely increased release of aerosols during breathing and speaking [35]. Subsequently, other experimental works have demonstrated, with greater or lesser success, the presence of SARS-CoV-2 viral RNA in aerosols using various sampling methods, such as solid impactors [36,37,38], cyclones [39,40,41,42,43,44,45,46,47,48,49], impingers [50,51], gelatin filters [39,44,52], particulate filters [53,54,55,56], and condensation systems [38,57,58]. However, other investigations have failed to recover detectable RNA concentrations [59,60,61,62,63,64,65,66]. Numerous factors can influence the airborne transmission of pathogens, both at the dynamics of propagation and the virus survival (or persistence). The size of exhaled bioaerosols evolves due to evaporation, coagulation, and deposition, directly affecting their air suspension time and persistence [35]. Consequently, the size distribution of the airborne concentration of aerosols will vary with time, since larger diameter particles settle faster [67]. However, other extrinsic factors, such as ambient airflows, affect both the airborne suspension time and the distance traveled by the aerosol [68]. At the level of virus survival, the presence of ions affects droplet evaporation. Therefore, the dynamics change, while sputum organic compounds are insignificant due to the low molar fraction they represent [14]. By reducing the aqueous component of the aerosol, aerosols are subject to changes in morphology, viscosity, and pH, among others, modifying the microenvironment of the virus and, therefore, reducing its persistence [69]. Specifically, low relative humidity induces evaporation, a decrease in pH and, with it, conformational changes in the proteins on its surface, making the virus a less infectious pathogen [70]. In addition, the size of the aerosol decreases proportionally until it crystallizes, significantly reducing its size in environments with very low relative humidity. In the opposite case, the aerosol tends to adsorb moisture and increase its size at high relative humidity [71]. If the relative humidity is below 80%, respiratory aerosols reach a final diameter of 20 to 40% of their original size [72]. In the case of SARS-CoV-2, it is suggested that the optimal relative humidity for minimizing the spread of this virus is between 40 and 60% [73]. Initially, Fears et al. [74] determined a greater dynamic efficiency of SARS-CoV-2 than SARS-CoV and MERS-CoV, pointing to the persistence of infectivity and virion integrity up to 16 h in aerosols (1.0—3.0 µm). Van Doremalen et al. [3] suggested a similar half-life between SARS-CoV-2 (0.6–2.6 h; 1.1 h on average) and SARS-CoV (0.8–2.4 h; 1.2 h on average). They pointed out that the discrepancies in the epidemiological characteristics could be associated with high viral loads in the upper respiratory tract and transmission of the virus in asymptomatic patients. Smither et al. [75] reported a lifespan of SARS-CoV-2 between 30 and 177 min in aerosols between 1.0 and 3.0 µm, under different conditions of relative humidity (RH), and reported a decay rate between 0.4 and 2.3%/min. Schuit et al. [76] reported independence between the decay rate and the RH of SARS-CoV-2, attributing the loss of infectivity to the effect of sunlight and the aerosol suspension medium. Aligned with the observations of Schuit et al., other authors [77,78] reported similar conclusions using other viruses. There are considerable discrepancies in the literature about viral persistence in the air. A recent study in a preprint published by Oswin et al. [79] showed that 54% of bioaerosols (5–10 µm) loaded with SARS-CoV-2 lose their infective capacity during the first 5 s at low RH (40%). Within 5 min, persistent viruses lose about 19% of their infectivity. At high RH (90%), infectivity falls by 48% progressively during the first 5 min. At 20 min, a 90% loss of infectivity has been found using different variants of SARS-CoV-2. However, these authors replaced the human mucosal base in the aerosols with a Serum with a different composition, so their direct extrapolation is limited. To date, most environmental sampling has been carried out in hospital settings, which limits the detection of viral RNA due to constant air renewal (~12 ACH) [60,61], which implies a complete air renewal every 5 min. Few studies have included the carbon dioxide (CO2) concentration variable as an indicator of space ventilation. In the few reports where CO2 was measured, the concentration was less than 400 ppm [49,59], suggesting that the presence of RNA in aerosols may be underestimated. A SARS-CoV-2-loaded bioaerosols emission rate reduction has been described a few days after the onset of symptoms, which should be investigated to understand the dynamics of the spread of the disease. In this work, the risk of contagion from aerosols in 8 patients is evaluated and compared with transmission by close contact in 19 patients. 2. Materials and Methods 2.1. Patients Included in the Study In total, 22 COVID-19-positive patients were included in different study groups. In Group A, 5 volunteer patients were included in environmental sampling (aerosols) and close contact (coughs). In Group B, 14 volunteer patients were enrolled in close contact sampling. In Group C, 3 volunteers were willing to carry out the aerosol sampling. As shown in Table 1, 2/5 patients in Group A were hospitalized, while the rest were in isolation at home. From Group C, no patient was hospitalized, while from Group B, all were hospitalized. The admitted patients were in the Infectious Diseases area or in the Surgery area of the Hospital Clínico Universitario Lozano Blesa (Zaragoza, Spain). Patients presenting severe symptoms were excluded. The mean age was 44.2 ± 20.4 years in Group A, 73.6 ± 13.3 years in Group B, and 28.3 ± 18.3 years in Group C. Vaccination status with COVID-19 mRNA vaccines (Pfizer-BioNTech or Moderna) is indicated in Table 1. 2.2. Nasopharyngeal Exudate Nasopharyngeal swab was standardized to obtain comparable results. Conventional swabs with virus transport medium (VTM) were used. The swabs were introduced 3.5–4.5 cm up one nostril of the patient and rotated 180° five times. Immediately afterward, they were placed in the transport medium and stored in a −17 °C freezer for less than five days. 2.3. Air Sampling A Coriolis µ environmental sampler (Bertin Instruments, Rockville, MD, USA) was used for air sampling. The particle collection efficiency is very efficient for sizes greater than 500 nm and 50% for sizes less than 500 nm. As shown in Figure 2, the aspirated flow is collected in a buffer solution inside a sterile sampling cone, forming a vortex. The particles and microorganisms are centrifuged on the cone wall and are separated from the air. Typically, a flow rate of 300 L/min was used for 10 min in 3 mL of PBS (3000 L of air: 1000 L/mL). However, to maximize the detection limits of viral RNA, we decided to sample for 30–110 min in some experiments. These samplings were performed at 300 L/min, maintaining a stable amount of 3 mL of PBS (adding solution as it evaporated between 10-min periods). The volunteers were asked to perform regular breathing and speech actions. This was suggested to collect aerosols from different respiratory activities. All samples were stored in a freezer at −17 °C for later analysis in a period not exceeding 5 days. Patients did not use masks during the sampling period. Metabolic CO2 levels were measured using Aranet4 Pro meters (Aranet, Riga, Latvia). These devices are designed with a Non-Dispersive Infrared Detector (N-DIR) meter and record measurements with an accuracy of ±50 ppm. The meters were placed next to the Coriolis to determine the CO2 concentration at sampling. The set-up of the experiments varied depending on whether the patient was hospitalized or quarantined at home. In both cases, the equipment was placed 1.5 m from the patient. It was only placed less than 0.5 m in the case of Patient 3 and Patient 4 to perform additional tests, as detailed in the Results section. The air sampler was located at a distance of at least 1 m from the ground (typically 1.3–1.4 m). As shown in Figure 3, the sampler was placed on mobile tables in the hospital (Figure 3a) and on tables in private homes for quarantined individuals (Figure 3b). This allowed us to position the Coriolis at the desired distance from the patient. The CO2 m was placed right next to the Coriolis air inlet to measure the CO2 level of the collected air. At home, patients were placed in small rooms (>30 m2) and doors and windows were closed to prevent the escape of aerosols. However, they were not completely sealed. Forced ventilation (air conditioning systems) could not be closed in hospitals since it could be dangerous for the rest of the patients and health workers. Patients at home performed the experiments in sitting position, while in the hospital they reclined in bed, positioned with around 135° between legs and abdomen. 2.4. Cough Sampling In cough samples collection, volunteers were asked to cough three times to clear their throats and, immediately afterward, cough five times into a 5 cm diameter cone containing 1 mL of PBS. The cones were placed 5 cm from the emitter’s mouth to simulate close interpersonal distance. To homogenize the samples, they were vortexed for 30 s. Samples were stored in a −17 °C freezer and were not kept for more than five days. 2.5. Viral RNA Extraction from Masks Patients who kept masks from previous days donated them for the study. In some patients, this was not possible since they did not use masks during the sampling period. The masks were chopped and suspended in a 50 mL Falcon tube with 10 mL PBS. The tubes were sonicated in ultrasound for 30 s to favor RNA extraction from the mask’s surface. Liquid samples were stored in a −17 °C freezer and analyzed within five days. 2.6. RT-qPCR Analysis All the samples were processed in a biological safety cabinet, complying with the applicable biosafety requirements. 2.6.1. Processing of Environmental Samples The total sample volume was deposited in Falcon tubes with a 10 kDa Amicon Millipore filter (Millipore, Burlington, MA, USA). They were centrifuged for 15 min at 4000 RPM. Then, 600 µL of the concentrate were transferred to a 600 µL tube of lysis buffer (MagMax Lysis solution, Thermo Fisher, Waltham, MA, USA), homogenized and 200 µL were used for RNA extraction. 2.6.2. Processing of Swabs Samples The swabs were immersed in 600 µL of lysis buffer (MagMax Lysis solution, Thermo Fisher), and the biological material was detached with rotary movements 3–5 times. They were homogenized and 200 µL was used for RNA extraction. 2.6.3. Nucleic Acid Extraction According to the manufacturer’s instructions, RNA extraction was performed with the MagMax Core RNA/DNA kit (Thermo Fisher) and the KingFisher Flex System automatic extraction kit (Thermo Fisher). The SARS-CoV-2 PCR used 5 µL of extracted RNA and was performed with the validated assay [80] using two key targets (pan-SARS ESAR and SARS-CoV-2 IP4) in a QuantStudio 5 thermocycler (Applied Biosystems, Waltham, MA, USA) [81]. 2.7. Identification of SARS-CoV-2 Variants of Concern by Partial Sequencing of the Spike Gene A pair of primers, F21585 (5′TGCCACTAGTCTCTAGTCAG 3′) and R22341. (5′GCTGTCCAACCTGAAGAA 3′), were designed for the sequencing of the 5' region of the Spike gene that contains the main mutations that characterize the main VOCs of SARS-CoV-2. For this, the reference sequences of the Wuhan-Hu.1 strain (NC_045512), as well as its variants B.1.1.7 (MZ344997), B.1.617.2 (MZ359841), BA.1 (OL672836), and BA.2 (OM296922) were aligned and compared using multiple alignment software MAFFT version 7. F21585 and R22341 have full homology with all the VOCs studied and generated an amplification product of 756 nucleotides in Wuhan-Hu.1 (NC_045512). The PCR protocol used was 15 min at 45 °C, 5 min at 95 °C, followed by 40 cycles of 30 s at 95 °C, 1 min at 60 °C, and 1 min at 72 °C, ending with a step of 7 min of extension at 72 °C. The PCR product was purified and sequenced using the Sanger technique (StabVida, Caparica, Portugal). The obtained sequences were compared with those cited above as reference sequences of the main VOCs using Clustal Omega v.1.2.2 software (RRID: SCR_001591). 2.8. Determination of the Risk of Infection Wells and Riley [82] defined the probability of contagion (P) in a susceptible individual according to Equation (1), where n refers to the inhaled amount of the virus infectious doses (expressed in quanta). The SARS-CoV-2 quantum can be described as the probability of infection of 1 −1/e (63%), although it depends on other factors, such as the immunization of the individual, as expressed by Peng and Jiménez [83]. (1) P=1−e−n Cortellessa et al. [84] adapted this same model to calculate the probability of infection (P) from the RNA dose as expressed in Equation (2). According to this Equation, HID63 represents the number of RNA copies needed to initiate the infection with a probability of 63%, estimated in 7 × 102 RNA [85], as discussed in the Results section. (2) P=1−e−DtotalcvHID63  Given the limitations in accurately reproducing the conditions in the event of infection, 3 different scenarios will be considered in this work. In the case of determining the risk of infection by large droplets, it will be considered: (1) that the susceptible individual inhales 25% of the droplets, (2) that the susceptible individual inhales 50% of the droplets, and (3) that the susceptible individual inhales 100% of the droplets. Under these scenarios, the interpersonal distance is considered to be narrow and evaporation and gravitational phenomena are neglected to facilitate the estimation. On the other hand, to determine the risk of contagion by aerosols, it will be considered: (1) that the individual breathes contaminated air for 1 min, (2) that the individual breathes contaminated air for 10 min, and (3) that the individual breathes contaminated air for 1 h. In these assumptions, a respiratory flow of 15 L/min will be considered and all the viral RNA detected in the aerosol is infectious. 2.9. Ethical Approval This study has the approval of the Aragon Community Research Ethics Committee (CEIC Aragón) under references PI20/374 and PI22/130. 3. Results and Discussion 3.1. Ct Value Should Not Be Taken as a Predictor of Infectiousness Currently, the gold standard for the diagnosis of SARS-CoV-2 infection is the detection of RNA by RT-qPCR, which has the ability to detect target nucleic acids (<100 copies/mL) with remarkable sensitivity [86,87]. The sensitivity varies depending on the stage of the disease the patient is at. The test’s sensitivity has been estimated at 33% 4 days after contact with the infected person, 62% on the day of onset of symptoms, and 80% 3 days after onset of symptoms [88,89]. The collection technique, time since exposure, and anatomic location of sampling affect the false-negative rate and efficiency of sampling. Bronchoalveolar lavages have the highest sensitivity (93%) compared to samples taken from the upper respiratory tract, followed by sputum samples (72%), nasal swabs (63%), and throat swabs (32%) [88]. The reference method is nasal exudate due to its accessible collection. Currently, whether the viral load estimate obtained by the Ct value (Cycle Threshold in qPCR analysis) is a determining factor for the outcome of the disease is being discussed [90,91,92,93]. However, the quantification of viral RNA is subject to aspects, such as the amount of sample taken, the RT-qPCR kit used, the target used, the thermocycler efficiency, or the storage method [94,95]. For example, RT-qPCR tests that detect more genes have been shown to report lower Ct values [96]. Therefore, individualized interpretation of the test result is necessary. In this work, typified sampling (Section 2.2) has been carried out to reduce the uncertainty between samplings. The mean Ct value was 25.7 ± 7.5 in Group B and 25.7 ± 4.2 in Group C. A higher concentration of bioaerosols is generated during voluntary coughing, concerning breathing and speech [11]. Cough flows have been observed to be multiphase turbulent clouds with suspended droplets of various sizes [97,98], covering a spectrum from a few nanometers to more than 100 µm [11,99]. Thus, these violent breathing events are critical to infectious diseases spreading [97,100], especially if the pathogens reside predominantly in the upper respiratory tract [101]. Viklund et al. [102] found a higher positivity rate in cough samples (32%) compared to normal breathing (16%). Thus, studying coughing instead of other respiratory droplets is more efficient for detecting infectious individuals. Viral RNA could only be detected in the coughs of 10.5% (2/19). The two patients who showed detectable viral load in coughing (Patient 4 and Patient 8) presented a Ct of 23.16 and 13.48, respectively. Patient 4 presented a complete vaccination schedule, but without a booster dose (2/3), while Patient 8 was fully vaccinated (3/3). Patient 8′s hospitalization made it difficult to follow up due to health problems. However, Patient 4 was able to be sampled on subsequent days, although she only showed positive cough results on the first day of sampling (Table 2). The rest of the patients (17) were negative in coughs, despite presenting lower Ct values. The viral load found in the cough samples was 7.3 × 105–9.1 × 105 copies/mL (Ct 28.5–27.4) and 8.7 × 108–6.7 × 108 (Ct 18.2–18.2) in Patients 4 and 8, respectively. These values are higher than Viklund et al. [102] (Ct 29.5–36.5) for patients with Ct between 17.2–26.4. However, Patient 8 showed a higher viral load, although it cannot be compared due to a much lower Ct in the nasopharyngeal exudate. A correlation between Ct and the infectivity of individuals has been previously reported [103,104]. This indicator has even been taken as an epidemiological prediction tool [105]. However, a clear relationship between patient infectiousness and viral load has not been found in this work. Patients 6, 7, and 19, with Ct values of 16.7, 16.8, and 15.8, were negative for cough samples, while Patient 4 with a Ct of 23.2 emitted SARS-CoV-2-loaded droplets under the same terms. Another case of interest is Patient 5, with characteristics similar to Patient 4, in terms of age and viral load. As seen in Table 3, no viral RNA was detected in either the patient’s oropharyngeal exudate or cough samples. Patients 1, 2, and 5 wore masks the days before sampling. These masks were analyzed by PCR for SARS-CoV-2 detection. The only positive sample was obtained from Patient 1, who presented a Ct of 28.1 at sampling. He was negative on cough and air, although the surgical mask he had worn for the previous three days was positive, with an average viral load of 29.5 (3.7 × 103 copies/mL). These results indicate that Patient 1 was infectious on previous days. 3.2. Detection of SARS-CoV-2-Laden Bioaerosols The average Ct value was 24.6 ± 4.3 in Group A and 25.7 ± 4.2 in Group C. A total of 88 air samples from eight different patients from group A and C were collected. All patients included in this subgroup were infected with the variant of concern (VOC), Omicron BA.1 (Supplementary Materials, Table S1). Only seven air samples (8.0%) were detectable for SARS-CoV-2 RNA levels and another eight samples were suspicious (9.0%; Ct > 38). As seen in Table 4, the 15 positive/suspicious samples were collected from the same patient (Patient 20), although on the second day, the samples were taken in the company of two other patients (Patient 21 and Patient 22), since they constituted a coexisting unit. In the samples collected on the first day of the trial (2 days after the onset of symptoms), positivity was found in 68.8% (11/16) of the samples, with three suspicious samples. However, on the second day of the trial (4 days after symptom onset), suspicion was only found in 14.8% of samples (4/27). The aerosol viral load results (1.1–4.8 copies/m3) were consistent with those previously reported in the literature [24,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53]. Given the airborne persistence of SARS-CoV-2, it is important to consider that viral RNA may have been collected from inactivated viruses. Therefore, they would not have the ability to infect humans. Since it is not possible to make precise estimates for the percentage of viable virus, the maximum possible persistent viral load will be considered in this work. The global acceptance of the COVID-19 airborne spread allowed for an improvement in the preventive strategies, including new techniques for epidemiological management, such as the measurement of exhaled CO2 as an indicator of the air renewal and, consequently, the risk of contagion [35,83]. The presence of viral aerosols in some infected individuals makes it necessary to implement air control measures in collective environments. Even under poor ventilation conditions, the remaining patients did not shed detectable viral RNA. Patient 3 (Table 5), with a Ct of 19.1, achieved 2400 ppm metabolic CO2, implying about ~5% air coming from the individual. However, this same patient tested negative for cough samples on days 2, 4, and 6 after symptom onset (Ct 19.1, Ct 30.6, and Ct 32.6, respectively), despite presenting viral load in the oropharyngeal swab on day 2 (Ct 21.2). Patient 4, with a Ct of 24.6 (day 2 after the onset of symptoms), showed positive coughs and positive oropharyngeal exudate (Ct 28.9). However, the aerosol samples were negative, even in a unique sampling where they were concentrated at 33,000 L of air in 2 mL PBS, and the patient was kept talking and breathing at 50 cm distance from the Coriolis. As a control, the collection cone wall and the air inlet were sampled with a swab, which also tested negative for SARS-CoV-2. Similar tests were performed on Patient 3, where he used the Coriolis at less than 20 cm and sang for 10 min, but viral RNA was not detected. In addition to rapid rates of loss of infectivity [79], the airborne viral load of SARS-CoV-2 is reduced. Although the published studies cannot be directly compared due to the variation in conditions, the reported concentrations point to a viral load between 5.0 and 11.9 × 103 copies/m3 of air (Table S2), and an equivalent mean concentration of 3.1 ± 2.9 copies/L of air is deduced from a total of 3085 samples (313 positives; 10.2%). However, it is necessary to consider that the values should be corrected according to the efficiency of each sampling device. Thus, our results for aerosolized viral load (1.1–4.8 copies/m3) in samples collected from Patient 4 were consistent with those previously reported. 3.3. Do Superspreaders Predominate in the Emission of Bioaerosols with SARS-CoV-2? Uncertainty persists about the interrelationship between the exposure environment and the transmission networks of the SARS-CoV-2 virus. According to the CDC, droplet transmission (close contact) is predominant, while fomites and aerosols explain special propagation events in punctual events [106]. The role of individuals in the asymptomatic phase has accounted for a substantial portion of infections (Table S3) [107,108,109,110,111]. It has been estimated that 44% (95% CI; 30–57%) of secondary cases became infected during the incubation period [112]. The heterogeneity of infectious disease transmission is a well-known concept that has been studied in various epidemic scenarios. Woolhouse et al. [113] identified a statistical pattern, known as the 20/80 rule, which indicates that 80% of new infections are associated with only 20% of those infected. According to this concept, there is a central high-risk group that may be associated with the massive expansion of the infectious disease [114,115,116]. In the case of SARS-CoV-2, the dynamics of the spreads pointed to similar conclusions [117,118]. Even the central high-risk group has been reduced to 10–21% of cases [118,119]. Heterogeneity in transmission has already been observed in the dynamics of other coronaviruses, such as SARS-CoV [117,120,121]. Moreover, other respiratory viruses with similar viral characteristics, such as H1N1, do not exhibit these patterns of spread [122]. Sustained superspreading events could explain the massive infection of individuals [123,124]. However, it may also be related to individuals’ environmental, behavioral and social factors that influence the dynamics of virus transmission, which could depend on the configuration of specific outbreaks [125]. Beldomenico [126] proposed that the superspreaders might not be random and depend on other superspreaders. Then, superspreaders’ secondary infections are more likely to rise to new superspreaders. Although the origin of superspreading is unknown in detail, it is mainly attributed to physiological issues of the individual, making the infectiousness of the individual challenging to predict [127]. A study by Edward et al. [128], on the aerosol emission rate of 200 healthy individuals, emphasized that biological differences could affect virus transmission. The work reported that 20% of the study participants accounted for 80% of the aerosols emitted. A substantial number of reported COVID-19 cases are from superspreader events, where secondary cases are disproportionately higher than expected based on basic reproduction number (R0) [129]. In this study, of the four infected individuals who were quarantined, only two had a viral load in coughs and only one in aerosols emitted. The nuclear families of the three individuals who were not infectious through aerosols did not become infected, while Patient 4 infected both her family (n = 3) and her partner’s family (n = 4). Our results point to reduced contagiousness in the incubation period and a predominant role of superspreaders when the disease is already established. Although SARS-CoV-2 can be explained by the high viral spread of superspreaders [126], it remains unknown what determines individual overdispersion in transmissibility, so it is not possible to discriminate between superspreaders and non-spreaders [115]. Then, a broad understanding of the role of individual variation in the ecology of respiratory viruses in controlling infection transmission is still required. 3.4. Probable Time Required to Inhale SARS-CoV-2 Bioaerosols to Undergo an Infection The information on the infective doses sufficient to cause infections with SARS-CoV-2 is limited and subject to the study model. It is known that viral load plays a relevant role in viral kinetics in aerial pathogen transmission [130]. Fain et al. [131] found that high initial inocula lead to brief infections but with higher peak viral titers (106); smaller initial inocula (101) reduce the peak viral titer but make the infection last longer. The estimated dose-infection effect for humans has been determined in vitro. Zhang et al. [132] mathematically determined an infective constant (k) of 6.4 × 104 to 9.8 × 105 copies for the onset of infection. In contrast, Therese et al. [133] reported a minimum dose of 4.0 × 104 copies for an in vitro infection in Vero B4 cells. Only 21% of the 109 SARS-CoV-2 samples isolated from patients were infectious enough to initiate a new infection. A recent study by Killingley et al. [134] studied the course of infection in human volunteers. Thirty-six volunteers were intranasally infected with 10 TCID50 (SARS-CoV-2/human/GBR/484861/2020), reaching peak RNA levels of 5 dpi (~8.9 log10 copies/mL) and infecting 18/36. Other studies with the same objective have been carried out in animal models (Table S4). For aerosols, the median aerosol infectious dose tested in small animals (hACE2 mice) is 630 copies (infection rate 2/2) [135], while in large animals (African Green Monkeys), it is 2.0 × 103 copies (infection rate 2/2) [107]. Infections have been reported from 500 copies (infection rate 1/6 in ferrets) [136] to 3 × 106 copies (8/8 African Green Monkeys) [137] by intranasal inoculations. Some cases have been reported where a lower attack rate has been obtained with higher viral loads; for example, inoculations of 7.0 × 104 copies in mice (hACE2) infected only 7/19 mice [138] and 7/9 Syrian hamsters [139], while in ferrets, an attack of 6/6 ferrets with a dose of 5.0 × 104 copies [136]. According to the literature (Table S4), the median infective dose demonstrated was 1.0 × 103 copies to infect 100% of the animals included in the study [135], while Gale et al. [85] estimated 7.0 × 102 copies to infect 63% of human individuals (HID63). However, the infection dynamics are variable from individual to individual, and probabilistic adjustments are limited [140]. By working out the dynamics of the infection in probabilistic terms, it is possible to find infections caused by a single virus, although the probability is minimal [141]. Considering an average persistent viral load of 3.1 ± 2.9 copies/L and a homogeneous concentration of viral particles in the environment and a HID63 of 7.0 × 102 RNA copies, if we assume that 100% of the viruses are viable, breathing 15 L of air (1 min), the probability of infection (P) is 0.68, while it reaches 0.99 and 1.0 after inhaling 150 (10 min) and 900 L (1 h). According to this model, a contagion probability of 1.0 would be reached after 15 min of breathing. However, it would be necessary to apply several correction factors that include, for example, the percentage of viruses that do not persist (and, therefore, are not infectious) or the probability of inhalation of these contaminated aerosols. 3.5. Viral Spreading Is Heterogeneous Assuming an average viral load of 8.2 × 105 copies/mL found in the cough samples of this work, there is a concentration (cp) of 4.9 × 106 ± 6.1 × 106 aerosols per cough in individuals infected with respiratory viruses [142], with an average aerodynamic radius (r) of 0.4 μm [11]. Given the variability between individuals [112], the maximum deviation equates the spread by aerosols (=1.1 × 107). Under these assumptions, in each cough, a maximum liquid volume of aerosols (v) of 2.95 × 10−4 mL is considered, according to Equation (3). (3) v=43 π r3cp , Note that for this estimate, a perfect sphere has been considered instead of an irregular droplet, an average aerodynamic diameter of 0.8 μm (rather than a distribution of particle sizes), and an average amount of aerosols disseminated in coughs in patients infected with H1N1. Following this approach, Patient 4 was able to shed 242 copies of RNA in his cough, while Patient 8 was able to shed around 115,050 copies. If 100% of cough droplets had been inhaled, the probability of infection would be 0.98 in Patient 4′s cough, while in Patient 8, it would be 1.0. In the first case, the viral load resulting from coughing would be equivalent to breathing air for around 10 min at a flow of 15 L/min, with an assumed homogeneous concentration of 3.1 ± 2.9 copies/L. However, in the second case, it would be equivalent to breathing air loaded with SARS-CoV-2 for a minimum of 41 h. 4. Conclusions The spread patterns of SARS (2003) could not be explained by conventional epidemic models, which assumed homogeneity of transmission. In the same way, SARS-CoV-2 has shown a propagation dynamic that is difficult to parameterize. This variability in the viral spread between people could explain the different growth rates of infected people between populations, although the cause of this variability is still unknown. In this work, it has been found that the Ct value cannot be considered as an indicator of the individual’s infectiousness, since it has not been possible to correlate with the viral load disseminated in aerosols and coughs. Given the limited literature in this regard and the variability in sampling and diagnostic equipment, this parameter should be reconsidered in matters of epidemiological prediction. In our study, patients with a very low Ct (>15) shed less (or no) viral load, while patients with a Ct of up to 27 generated high viral concentrations in the environment. The viral load in coughs was different between the samples of the two individuals (n = 19) that were positive. Concentrations between 7.3 × 105 to 8.7 × 108 copies/mL were found, implying an approximate viral load of between 1.1 × 102 and 1.0 × 105 copies/cough. In this subgroup, the mean Ct was 25.7 ± 7.0, and the patients who disseminated viral load had a Ct of 23.2 and 13.5. In this case, the patient with the lowest Ct (13.5) had the highest viral load spread in coughs (8.7 × 108 copies/mL). However, not all patients with a positive Ct in oropharyngeal samples coughed up the viral load. In one of the patients with positive sampling, it was possible to carry out a follow-up, where a loss of infectiousness was observed from the third day after the onset of symptoms. Only one patient shed detectable viral RNA in the air. Additionally, he was the only one who infected seven other individuals. Of the rest of the patients, there is no evidence of secondary infections. The viral load found in the air (1.1–4.8 copies/m3) was consistent with that previously reported in the literature. It was considerably reduced from the first to the third day after symptom onset. In patients with high rates of viral shedding, a cough can be equivalent to 10 min of breathing, making more necessary to improve ventilation and air purification strategies in shared indoor spaces. It is still necessary to understand the role of the different routes of spread in COVID-19 spreading, considering the influence of parameters, such as the vaccinated population rate and their immunity or the predominant variants. Specifically, knowledge about viral dynamics in aerosols and superspreading events is essential for understanding the spread heterogeneity and better managing future pandemics. Since a low SARS-CoV-2 virus load can initiate an infection, the task of designing epidemiological prediction models is complex, despite being necessary to manage infectious diseases more efficiently in the future. Acknowledgments We would like to express our gratitude to the Department of Infectious Diseases (Hospital Clínico Universitario Lozano Blesa) for supporting this research. We would also like to thank ‘Exopol SL’ and and ‘Institute for Health Research Aragón’ for the support. The contribution of A.J.S. honors the memory of J.L.R. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm11092607/s1, Table S1: Partial sequencing of the viral genome from aerosol-subgroup patients; Table S2: Viral load detected in aerosols per m3 of air using different methods; Table S3: Some superspreading events; Table S4: Dose–response characterization using animal models. References [18,36,38,39,40,41,42,43,44,45,46,47,48,49,51,52,53,55,58,129,135,136,137,138,139,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183] are cited in the Supplementary Materials. Click here for additional data file. Author Contributions Conceptualization, M.B. and A.J.S.; Data curation, J.J.A.; Formal analysis, M.B., A.G., J.J.A. and A.J.S.; Funding acquisition, J.J.A. and A.J.S.; Investigation, M.B., A.G., J.J.A. and A.J.S.; Methodology, M.B.; Resources, A.G.; Supervision, A.G. and A.J.S.; Validation, M.B.; Writing—original draft, M.B. and A.J.S.; Writing—review & editing, A.G. and J.J.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 Ethics Committee of Aragon Community Research Ethics Committee (CEIC Aragón) under reference PI20/374 and PI22/130. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic representation of bioaerosols and droplets emission. Where, DPPC is dipalmitoylphosphatidylcholine protein, and DPPG is dipalmitoylphosphatidylglycerol protein. Figure 2 Schematic representation of air sampling and analysis method. Where, PBS is Phosphate Buffered Saline. Figure 3 Schematic representation of air sampling set-up at (a) the hospital and (b) in private homes. jcm-11-02607-t001_Table 1 Table 1 Characteristics of the included patients. Patient Age Gender DASO * Sampling Period Initial Ct Final Ct Vaccines Hospitalization Group Patient 1 59 Male 3 days 1 day 28.1 N/A 3 Yes A Patient 2 45 Female 2 days 1 day 29.8 N/A 3 Yes A Patient 3 59 Male 2 days 3 days 19.3 30.4 3 1 No A Patient 4 22 Male 1 day 4 days 23.7 36.1 2 No A Patient 5 26 Male 1 day 3 days 23.2 29.3 2 No A Patient 6 89 Male 0 days † 1 day 16.7 N/A 3 Yes B Patient 7 75 Male 0 days † 1 day 16.8 N/A 3 Yes B Patient 8 61 Male 0 days † 1 day 13.5 N/A 3 Yes B Patient 9 59 Female 1 days † 1 day 32.7 N/A No Yes B Patient 10 84 Male 2 days † 1 day 32.8 N/A 3 Yes B Patient 11 63 Male 0 days † 1 day 33.1 N/A 3 Yes B Patient 12 89 Male 0 days † 1 day 28.8 N/A 3 Yes B Patient 13 68 Male 1 day † 1 day 24.8 N/A 3 Yes B Patient 14 69 Female 6 days † 1 day 26.1 N/A No Yes B Patient 15 88 Female 1 day † 1 day 34.8 N/A 3 Yes B Patient 16 93 Male 1 day † 1 day 28.8 N/A 3 Yes B Patient 17 88 Male 1 day † 1 day 33.3 N/A 3 Yes B Patient 18 54 Female 1 day † 1 day 21.8 N/A 3 Yes B Patient 19 67 Male 7 days †† 1 day 15.8 N/A 3 Yes B Patient 20 22 Female 2 days 2 days 27.1 29.2 2 No C Patient 21 49 Female 2 days 1 day 29.3 N/A 2 No C Patient 22 14 Female 2 days 1 day 21.2 N/A 2 No C * DASO: Days after symptoms onset; 1 The patient inadvertently received the vaccine while infected with the COVID-19 disease; † The period refers from the diagnosis; †† The patients were included because they were not vaccinated, despite being diagnosed more than 48 h earlier. jcm-11-02607-t002_Table 2 Table 2 Patient 4 follow-up samples. Where, pan-SARS ESAR refers to Sarbeco E gen detection, and SARS-CoV-2 IP4 refers to RdRp gen detection. Sample Amplification Day 2 Day 3 Day 4 Day 6 Day 7 Nasopharynx pan-SARS ESAR 25.5 (5.5 × 106 copies/mL) 23.8 (2.0 × 107 copies/mL) 25.9 (4.8 × 106 copies/mL) 33.8 (2.3 × 104 copies/mL) 36.1 (4.9 × 103 copies/mL) SARS-CoV-2 IP4 24.6 (3.2 × 106 copies/mL) 23.1 (2.5 × 107 copies/mL) 25.4 (5.4 × 106 copies/mL) 34.4 (1.2 × 104 copies/mL) Not detected Oropharyngea pan-SARS ESAR 29.1 (4.8 × 105 copies/mL) 29.3 (4.8 × 105 copies/mL) Not detected Not detected Not detected SARS-CoV-2 IP4 28.9 (3.2 × 105 copies/mL) 29.4 (3.7 × 105 copies/mL) Not detected Not detected Not detected Coughs pan-SARS ESAR 28.5 (7.3 × 105 copies/mL) Not detected Not detected Not detected Not detected SARS-CoV-2 IP4 27.4 (9.1 × 105 copies/mL) Not detected Not detected Not detected Not detected jcm-11-02607-t003_Table 3 Table 3 Patient 5 follow-up samples. Where, pan-SARS ESAR refers to Sarbeco E gen detection, and SARS-CoV-2 IP4 refers to RdRp gen detection. Sample Amplification Day 2 Day 3 Day 4 Nasopharynx pan-SARS ESAR 25.1 (7.8 × 106 copies/mL) 23.3 (2.7 × 107 copies/mL) 28.7 (6.7 × 105 copies/mL) SARS-CoV-2 IP4 24.6 (8.9 × 106 copies/mL) 22.9 (2.8 × 107 copies/mL) 28.3 (7.4 × 105 copies/mL) Oropharyngeal pan-SARS ESAR Not detected Not detected Not detected SARS-CoV-2 IP4 Not detected Not detected Not detected Coughs pan-SARS ESAR Not detected Not detected Not detected SARS-CoV-2 IP4 Not detected Not detected Not detected jcm-11-02607-t004_Table 4 Table 4 Air samples where viral RNA has been detected. Where, pan-SARS ESAR refers to Sarbeco E gen detection, and SARS-CoV-2 IP4 refers to RdRp gen detection. Sample CO2 Levels Amplification Patient 20 Day 1 1 500–1000 ppm pan-SARS ESAR 36.7 (1.1 × 103 copies/mL) SARS-CoV-2 IP4 Not detected 2 500–1000 ppm pan-SARS ESAR 36.6 (2.3 × 103 copies/mL) SARS-CoV-2 IP4 36.8 (2.0 × 103 copies/mL) 3 500–1000 ppm pan-SARS ESAR 37.2 (1.6 × 103 copies/mL) SARS-CoV-2 IP4 Not detected 4 500–1000 ppm pan-SARS ESAR 38.9 (Suspicious) SARS-CoV-2 IP4 38.8 (Suspicious) 5 500–1000 ppm pan-SARS ESAR Not detected SARS-CoV-2 IP4 38.7 (Suspicious) 6 500–1000 ppm pan-SARS ESAR 37.9 (9.6 × 102 copies/mL) SARS-CoV-2 IP4 Not detected 7 1000–1500 ppm pan-SARS ESAR 37.2 (1.5 × 103 copies/mL) SARS-CoV-2 IP4 39.2 (Suspicious) 8 1000–1500 ppm pan-SARS ESAR 38.8 (Suspicious) SARS-CoV-2 IP4 38.3 (Suspicious) 9 1000–1500 ppm pan-SARS ESAR 39.8 (Suspicious) SARS-CoV-2 IP4 Not detected 10 1500–2000 ppm pan-SARS ESAR 35.5 (4.8 × 103 copies/mL) SARS-CoV-2 IP4 36.3 (Suspicious) 11 1500–2000 ppm pan-SARS ESAR 37.0 (1.8 × 103 copies/mL) SARS-CoV-2 IP4 38.3 (Suspicious) Patient 20–22 Day 3 12 500–1000 ppm pan-SARS ESAR 39.0 (Suspicious) SARS-CoV-2 IP4 Not detected 13 1000–1500 ppm pan-SARS ESAR Not detected SARS-CoV-2 IP4 38.9 (Suspicious) 14 1500–2000 ppm pan-SARS ESAR 39.0 (Suspicious) SARS-CoV-2 IP4 Not detected 15 1500–2000 ppm pan-SARS ESAR 39.5 (Suspicious) SARS-CoV-2 IP4 Not detected jcm-11-02607-t005_Table 5 Table 5 Patient 3 follow-up samples. Where, pan-SARS ESAR refers to Sarbeco E gen detection, and SARS-CoV-2 IP4 refers to RdRp gen detection. Sample Amplification Day 2 Day 4 Day 6 Nasopharynx pan-SARS ESAR 19.9 (1.3 × 107 copies/mL) 30.8 (1.4 × 104 copies/mL) 33.4 (2.5 × 104 copies/mL) SARS-CoV-2 IP4 19.1 (2.5 × 107 copies/mL) 30.6 (1.5 × 104 copies/mL) 32.6 (3.7 × 104 copies/mL) Oropharyngeal pan-SARS ESAR 21.9 (3.7 × 106 copies/mL) Not detected 38.9 (Suspicious) SARS-CoV-2 IP4 21.2 (5.9 × 106 copies/mL) Not detected 37.2 (1.6 × 103 copies/mL) Coughs pan-SARS ESAR Not detected Not detected Not detected SARS-CoV-2 IP4 Not detected Not detected Not detected Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Boone S.A. Gerba C.P. Significance of Fomites in the Spread of Respiratory and Enteric Viral Disease Appl. Environ. Microbiol. 2007 73 1687 1696 10.1128/AEM.02051-06 17220247 2. Mohamadi M. Babington-Ashaye A. Lefort A. 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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/ijerph19095404 ijerph-19-05404 Article The Mediating Role of Organisational Identification between Psychological Contract and Work Results: An Individual Level Investigation https://orcid.org/0000-0002-9376-6915 Rogozińska-Pawełczyk Anna 1* Gadomska-Lila Katarzyna 2* Kaushal Navin Academic Editor 1 Department of Labour and Social Policy, Faculty of Economics and Sociology, University of Lodz, 90-136 Lodz, Poland 2 Institute of Management, University of Szczecin, 70-453 Szczecin, Poland * Correspondence: anna.rogozinska@uni.lodz.pl (A.R.-P.); katarzyna.gadomska-lila@usz.edu.pl (K.G.-L.) 28 4 2022 5 2022 19 9 540430 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/). The aim of this article is to identify the relationship between the fulfilment of relational and transactional psychological contracts and work results, taking into account the mediation effect expressed in organisational identification. The empirical research was conducted on a group of 402 HR professionals responsible for designing and implementing HR practices in one of the leading companies of the Polish energy sector. Hypotheses were tested using the partial least squares structural equation modelling technique (PLS-SEM). Based on our research, we found that the implementation of both relational and transactional psychological contracts positively influenced the results achieved by HR professionals, both directly and indirectly, through the mediating role of organisational identification. The results indicate that the relationship between the psychological contract and work results is stronger when mediated by organisational identification. It plays an important role, especially in relation to the transactional contract. The collected results lead to the conclusion that organisations, wishing to increase the level of work results achieved by HR professionals, should as much as possible fulfil the expectations of employees and meet the commitments made to them within the framework of the established psychological contract. The study makes an important contribution to the understanding of the “priority” importance of organisational identification in enhancing the efforts of HR professionals to deliver work results that benefit both employees and the organisation. psychological contract relational psychological contract transactional psychological contract organisational identification work results HR professionals Polish National Science Centre2018/31/B/HS4/01284 Minister of Science and Higher Education001/RID/2018/19 This research received external funding: The contribution of the first named author was supported by the Polish National Science Centre under Grant 2018/31/B/HS4/01284. The contribution of the second named author was supported by the program of the Minister of Science and Higher Education called “Regional Initiative of Excellence” in the years 2019–2022 project number 001/RID/2018/19 funding amount 10 684 000.00 PLN. ==== Body pmc1. Introduction In recent years, the labour market has been changing as a result of a number of economic, technological and social developments, such as increased global competition, the advancement of technology or increased flexibility of labour relations. They are reflected at the organisational level, influencing the employment and working conditions of employees [1,2,3]. Consequently, employees expect the organisation to meet a wide variety of obligations within the framework of a formal and an informal contract [4]. The psychological contract plays a very important role. This is because it influences the attitudes and behaviour of employees, and also the performance of the organisation [5]. It refers to various aspects of employee relations in an organisation [6] and the consequences of accepting and meeting mutual obligations to achieve the organisation’s goals [7]. It can help employers understand and predict employee behaviour, encourage employees to become more committed and contribute more to achieving the company’s goals [8]. Therefore, many researchers have studied the concept of psychological contract [9,10,11]. However, there is little research on other variables as mediators in the study of psychological contract. For example, there is little research on the relationship between psychological contract and work results considering organisational identification as a mediating variable. Meanwhile, organisational identification appears to be an important consequence of fulfilling, or violating, psychological contracts. It is therefore important to ask whether and how organisational identification mediates the relationship between psychological contract and work results, especially if we consider the two types of psychological contracts—relational and transactional. Based on the assumptions of social exchange theory [12,13], widely used in HRM [14] and organisational behaviour research, we tried to explain the nature of these relationships. We analysed them in relation to HR professionals responsible for managing human resources in organisations. The HR industry is developing intensively every year, and its representatives perform important functions in the structures of modern organisations. HR professionals are the link between management and employees, on the one hand helping managers at various levels to achieve the objectives for which employees are responsible, but also helping employees to develop specific competencies and attitudes and behaviours by designing and implementing HR practices. Their role seems to be particularly important, as it comprises the responsibility for the selection of methods, tools and practices of human resources management, which allow to shape the attitudes and behaviours of employees [15,16]. The changes taking place in the environment of contemporary organisations, as well as in the organisations themselves, make it necessary for HR professionals to learn how to respond faster to these changes, how to support their business entity even more effectively, and how to set an example to other employees with their attitudes and behaviours. Given this important role of HR professionals for organisations, the issue of studying the attitudes and behaviours of this group of employees is of particular importance. Meanwhile, there is a clear gap in empirical research on the mediating role of organisational identification between the psychological contract (especially in the distinction between transactional and relational) and the work results of HR professionals. The implementation of this type of research will therefore reveal the mechanism of the emergence of employee behaviour resulting from the fulfilment of the concluded psychological contracts, and thus contribute to filling the identified research gaps. 2. Theoretical Framework and Hypothesis Development 2.1. Psychological Contract Going beyond the framework of the formal employment contract, while taking into account some of the subjective and normative elements involved in managing people [17], the psychological contract is a key determinant of employee attitudes and behaviours [18]. The subjective nature of psychological contracts is related to individual beliefs that arise in a specific social context and are shaped by the employee’s interactions with the employer [19,20]. Definitions of psychological contract most often emphasise expectations [21,22], which are of a promised and reciprocal nature [19], or obligations in the form of contracts, promises or other types of social, moral or legal requirements that compel one to follow or avoid a certain course of action [23]. In the authors’ understanding, a contract is mainly about expectations, the fulfilment or non-fulfilment of which gives rise to various consequences—it translates into different attitudes and behaviours of employees and directs the organisation’s activities. According to Wellin [24], the psychological contract has a positive impact on employees and employers. It enables a better understanding and prediction of people’s behaviour in the organisation, influences the increase of employees’ motivation level, as well as the intensification of activities that constitute the realisation of the organisation’s strategic goals. The terms of a psychological contract are not written down, defined, negotiated or discussed, but can be reformulated by the context, which implicitly or explicitly conveys a future commitment or intention [25]. The most common division in the literature is between relational and transactional contracts [2,18,26,27], although some authors, including Rousseau [28], enrich this division with transitional and balanced contracts. The dominant division, however, is between relational contracts, representing socio-emotional goods, and transactional contracts, representing the material interests of workers. A transactional contract is purely economic, monetary and material in nature [29,30]; hence, the precise definition of inputs and benefits is important here. The duration of this type of contract is relatively short and limited, breaking is easy, the expected outcomes are precisely set and the responsibility for achieving them is clearly defined [31,32]. This means that transactional psychological contract-oriented employees view their organisation primarily as a source of income and a workplace [29]. Their contribution is limited due to low levels of attachment to the organisation. Consequently, employees with a transactional psychological contract are more likely to leave their jobs because they tend to treat their current position as a starting point for their future career [18]. Under this type of contract, the commitment on the part of the organisation is to create conditions conducive to individual professional development, which consequently promotes the employee’s career potential in the labour market. The relational contract is based mainly on the exchange of employee loyalty to the organisation and commitment to its interests in return for job security and the opportunity to pursue a career within the organisation. This type of contract assumes employment in a long-term, indefinite perspective, cooperation based on mutual trust and loyalty, a relatively loose relationship between work performance and remuneration, a community of norms and values observed, both by employees and superiors, and group responsibility for achieved results [31,32,33]. The career creation of employees in a relational psychological contract rests primarily with the organisation and involves the creation of opportunities for vertical and horizontal career advancement, the development of a clear employee promotion plan and the development of full-time and long-term employment [34]. Activities currently undertaken in organisations, such as restructuring, downsizing or outsourcing, in response to international competition or technological progress, make it increasingly difficult for organisations to fulfil psychological contracts [35,36]. Building on the assumptions of social exchange theory [37], it is therefore worth attempting to explain the consequences that may arise in response to a breach of a psychological contract. This is currently the dominant paradigm in explaining the nature of organisational relationships [12,13]. Social exchange theory focuses on relationships understood as an exchange of resources between two parties. If one party provides a benefit, the other party feels obliged to do the same. Thus, based on these assumptions, it is reasonable to assume that fulfilling a psychological contract will positively affect the employer–employee relationship because it instils in employees a sense of obligation to care about the organisation and help achieve its goals [38]. On the other hand, when organisations fail to deliver on their promises, it is to be expected that employees will reduce their contribution to the organisation and adopt negative attitudes towards it [35]. These effects are particularly reflected in the level of organisational identification [26]. 2.2. The Mediating Role of Organisational Identification Organisational identification is the extent to which employees define themselves in terms of what they believe the organisation represents. It involves a perception of ‘oneness’ with or belonging to the organisation [39]. Organisational identification can also be seen as the process by which the goals of the organisation and the goals of the individual become increasingly integrated or compatible [25]. When employees strongly identify with their organisation, they satisfy their needs for belonging and affiliation [40,41]. Indeed, organisational identification is a kind of glue that sustains the relationship between employee and employer [42]. Research [39,43] has shown that employees with a strong sense of organisational identification are more likely to exhibit positive behaviours desired by the organisation. The more employees identify with their organisation, the more they will be willing to devote their efforts to it and engage with it [44,45], and less likely to express their intention to leave their job [46]. Therefore, employees who identify with the organisation are more likely to achieve their goals, collaborate and generally bring positive performance behaviours to the organisation, including beyond what is required (i.e., citizenship behaviours). Thus, fulfilling the requirements of the psychological contract appears to be an important factor in employees’ organisational identification [47]. On the other hand, breach of contract reduces organisational identification because it involves employees’ perceptions that their needs are not being met. Numerous studies, including Epitropaki [42], Gibney, Few, and Scott [35] have confirmed the negative relationship between contract breach and organisational identification. When employees begin to perceive that employers are not living up to their commitments, this results in low levels of: productivity [48], trust [49], commitment [50] and organisational identification [42], and causes high levels of intention to leave the company [51]. It is therefore reflected in broadly defined work results. Hence, exploring what the relationship between psychological contract, especially its different types, and work outcomes is, and identifying the role of organisational identification, may lead to new theoretical explanations of these relationships. 2.3. Conceptual Model The psychological contract is an important factor contributing to employee attitudes and behaviour, in relation to job satisfaction, organisational commitment [16], organisational trust, absenteeism, turnover intention [52,53,54], as well as to employees’ organisational identification and employee performance [55,56,57]. The analysed research model takes into account the construct of psychological contract fulfilment existing when the employer fulfils promises (transactional or relational type promise), which conditions the fulfilment of promises declared by the employee (transactional or relational type promise). The theoretical framework for specifying the scope of psychological contract fulfilment is the social exchange occurring between employee and employer and the accompanying norm of reciprocity [28]. The concept of the psychological contract introduces two distinctive types of psychological contracts in employment relationships, specifically (discussed in Section 2.1) the relational psychological contract and the transactional psychological contract [58]. Key differences between the two types of psychological contracts include the duration of the employment contract (short-term vs. long-term), the degree of specificity (highly specific vs. flexible), the exchange of resources (material vs. non-material), and the conditioning on performance and rewards (highly specific vs. low specific) [17,58,59]. Although other researchers have distinguished more than two types of psychological contracts, the most accepted approach to understanding types of psychological contracts is the two-dimensional approach, namely, transactional and relational psychological contracts [18,26,58]. The second construct examined in the hypothetical model is work results, which refer to an employee’s effectiveness in fulfilling his or her basic job duties or job role [5,55,60], and is thus defined as self-perception of performance. Thus, work results reflect how an employee performs within the demands of organisations. Social exchange theory, which emphasises reciprocity, also provides a theoretical basis for understanding how HR professionals, through the fulfilment of psychological contracts, initiate specific attitudes and organisational behaviours, thereby influencing the level of organisational performance and self-perception of performance, understood as work results [61,62]. This is because employees respond to their perceptions of whether there is a discrepancy between how they are actually treated by organisations and what they are promised in exchange for fulfilling their job obligations [55]. Employees will not adequately discharge their obligations to the organisation if they feel the organisation is not fully meeting its obligations [11]. In turn, when employees perceive that their organisation provides them with all the obligations it has promised them, they will begin to strengthen the psychological contract and increase their contributions to the organisation [14]. Organisational identification is the third construct that structures the hypothesised research model, determining the extent to which employees identify with their perceived representation of the organisation or simply their perceived unity with or membership of the organisation [63]. When employees strongly identify with their organisation, their needs for loyalty and identification with the organisation are met [17]. Employees integrate employer identity into their own social identity when they identify with the organisation [35]. Organisational identification also becomes a crucial element of the relationship between employees and the organisation, and thus linked to social exchange theory, by determining the level of perceived membership in the organisation [42]. Research has revealed significant effects of psychological contract breach and implementation on organisational identification [64]. The conceptual framework of organisational identification indicates that psychological contract breach weakens employees’ perceptions of organisational identification because it is directly related to employees’ individual perceptions of unfulfilled needs [55]. Breach of psychological contract discourages employees from investing their effort in the organisation and their sense of organisational identification is significantly reduced [65]. In turn, fulfilling the psychological contract is an important factor in increasing employees’ perceived organisational identification [66]. This is because fulfilling the psychological contract reduces employees’ uncertainty, thus motivating them to identify themselves organisationally [47]. The increased pace of economic change will not only change the demand for labour, but also change the nature of work and human capital, including HR professionals, due to underlying trends in technology and automation of work [67,68]. HR professionals are a unique group whose role is to shape the required attitudes and behaviours of employees by designing and implementing appropriate HR management tools. This professional group is in a way a confirmation of the effectiveness of the HR tools applied, and at the same time a reference point for modelling the behaviour of other employees. In this unique context, whether and how fulfilling the psychological contract motivates HR professionals to perform their job duties and professional role to the highest possible standard, thereby achieving the best possible work results, has not yet been investigated. Furthermore, there is no clear evidence on whether HR professionals perform their job duties. Do they perform them only to achieve measurable economic outcomes or more to sustain long-term relationships? It therefore becomes crucial to answer the question of whether the fulfilment of the transactional psychological contract plays as important a role as the fulfilment of the relational psychological contract in the achievement of work results by HR professionals. A research hypothetical model was created to show the relationship between the tested variables is illustrated in Figure 1. To provide an answer to the research question, we decided to use a set of seven hypotheses. Thus, we propose the following hypotheses: Hypothesis 1 (H1). The fulfilment of a relational psychological contract is positively related to the achieved work results of HR professionals in the surveyed organisation. Hypothesis 2 (H2). The fulfilment of a transactional psychological contract is positively correlated with the achieved work outcomes of HR professionals in the surveyed organisation. Hypothesis 3 (H3). The fulfilment of relational psychological contract is positively related to organisational identification. Hypothesis 4 (H4). The fulfilment of the transactional psychological contract is positively associated with organisational identification. Hypothesis 5 (H5). Organisational identification is positively linked to work results achieved by HR professionals in the surveyed organisation. Hypothesis 6 (H6). Organisational identification mediates the relationship between the fulfilment of the relational psychological contract and the work results achieved by HR professionals in the surveyed organisation. Hypothesis 7 (H7). Organisational identification is a mediator in the relationship between the fulfilment of the transactional psychological contract and the work results achieved by HR professionals in the surveyed organisation. 3. Methods 3.1. Procedure The main objective of the quantitative study was to explore the mechanism driving HR professionals’ achievement of work results (RW) from the perspective of the implementation of relational and transactional psychological contract (TPCF/ RPCF), in which organisational identification (OID) is considered as an important predictor of the overall process. The implementation of the research process consisted of the following stages: The first stage of the research process was to develop an analysis of national and international literature on the concept of psychological contract and the way in which the fulfilment of transactional and relational psychological contract influences the work results achieved by HR professionals, the mediating role of organisational identification, and the relationship between the fulfilment of both types of contract and work results. The analysis the literature on the subject (desk research, web research) constituted the substantive basis for the implementation of the primary research, providing analytical framework information, enabling the correct formulation of the research problems undertaken within the framework of the own research. The second stage of the research process consisted in developing research hypotheses from the conducted literature analysis and constructing a hypothetical research model. This stage allowed the identification of variables relevant to the process under study, deepening the understanding of these variables and determining the postulated relationships between them. The third step in the research process was to design a measurement instrument to collect data on the main constructs within the proposed hypotheses. The measurements for each construct were developed based on the literature review and the specific questions within the survey questionnaire were adapted from validated instruments used in other studies and modified to fit the proposed research context. The next step was to identify potential respondents and choose the method of data collection. The research was carried out using the computer-assisted telephone interview technique (CATI), ensuring anonymity in the procedure. The fifth step of the quantitative component was the analysis of the collected statistical data obtained from the quantitative survey using a number of statistical analysis methods, including exploratory factor analysis EFA, confirmatory factor analysis CFA and structural equation modelling SEM. In step six, the results obtained from the quantitative CATI survey were analysed in detail. For this purpose, the obtained research material was synthesised and the research hypotheses were verified. Next, the results of the survey at the employee and organisational level are discussed, while presenting the research limitations. 3.2. Measures Three constructs were used to represent the factors highlighted in the hypothetical model: Fulfilment of the relational and transactional psychological contract, Organisational identification and Work results. To measure each construct, questions were adapted from validated instruments used in previous studies [19,55,69,70,71,72,73,74] and modified to fit to the research context. The survey questionnaire was designed to ensure that all participants understood the questions and anonymity was ensured. A battery of tests aggregated to a single questionnaire was used to collect empirical material. The variation of some problem areas included in the statements and questions was due to substantive and methodological reasons. In terms of content, the aim was to capture the relationship between the fulfilment of two types of psychological contract and work results with the mediating role of organisational identification. Methodologically, the collection of knowledge regarding the enhancement of work results as a measure of employee self-perceptions of job performance allowed for the verification of the consistency of the data obtained and the fulfilment of the condition of collecting data from multiple sources (multisource of data), which is recommended by researchers as an important condition for the accuracy of the study [75]. This becomes important when respondents describe their own behaviours and attitudes. Prior to the study, some tools required cultural adaptation. For this purpose, one of the procedures of tool adaptation [76] was used: translation and post-translation from the Polish version of the text to the original (English) version, in order to faithfully translate the methods used. The translated questionnaires were evaluated by competent judges, who were three independent experts in the field of: HRM, work psychology and statistical methods. The equivalence criteria of the questionnaires were also taken care of in the form of: facial equivalence, psychometric equivalence, functional equivalence and reconstruction fidelity [76]. The following set of diagnostic tools was used to measure the constructs: Fulfilment of the relational and transactional psychological contract was assessed by adapting 20 items diagnosing two subscales: transactional and relational contract fulfilment [19,69]. Classification was based on the categorisation system used by Thompson and Hart [70]. The variables assigned to the relational psychological contract included social elements such as a good atmosphere in the workplace, values related to the social responsibility of the organisation and the relationship between the employee and the employer (e.g., job security and safety or honesty of the employer).The variables classified under the transactional psychological contract category included economic elements i.e., salary, its level and composition and the distribution of profit due to the employee’s contribution and elements that may be a source of future income e.g., opportunities for personal development or promotion. The two subscales consisted of 10 items of transactional and relational promises respectively. An example item on transactional fulfilment of a psychological contract is: “Training me only for my current job” or “It can terminate my employment any time”. Similarly, relational fulfilment of the psychological contract was measured by 10 items such as: “ I can make decisions with my interests in mind” or “The company is concerned about my personal welfare”. The response system was based on a 5-point Likert scale, where 1 is “not fulfil at all” and 5 is “fulfil completely”. Organisational identification was measured using six items created based on the description of the concept of organisational identification defined as related to the sense of belonging and the connection an employee has with the organisation [66] and the findings of a study by Ashforth and colleagues [72]. The questions in the survey questionnaire regarding organisational identification refer to when an employee fully or partially identifies him/herself by incorporating the organisation’s identity into their own [73]. An example question used in the survey questionnaire is: “I am proud to be an employee of my organization”. When assessing organisational identification, respondents were asked to indicate the extent to which they agreed or disagreed with the statements on a five-point Likert scale from 1—“strongly disagree” to 5—“strongly agree”. Results of work—The last section of the survey questionnaire was devoted to exploring HR professionals’ personal experiences of achieving work results. The literature emphasises that an increase in organisational performance levels is made possible by individual employee performance and the results of work achieved by employees. The concept of performance refers to the extent to which an employee achieves the goals set by the organisation. Employee results of work, on the other hand, refers to the level of contribution or productivity of an employee that plays a significant role in enhancing organisational success [74]. Thus, when defining job performance, attention is paid more to the subjective aspects and approaches referring to the undertaking of certain attitudes, behaviours and work-related roles. Achieved work results as a theoretical construct have not been directly observed so far and therefore constituted lateral variables in the study. The subject of measurement in this study will therefore be empirical indicators in the form of work results, i.e., effectiveness, efficiency, development, innovativeness and quality of work, which are an integral effect of fulfilling the psychological contract. For the purposes of this methodological procedure, five items were adopted with reference to the conceptualisation of employee performance measurement (in the sense of work results) by Drucker and Turnley with colleagues [55,77]. In assessing the items in this part of the questionnaire, the respondent was asked to follow the instructions given: “Please circle the answers that correspond to your experiences at work”. Sample items were: “I perform my job duties carefully, professionally and efficiently” or “I continuously develop my competences necessary to meet future opportunities and challenges”. A 5-point Likert scale was suggested as a way of answering, where 1 means “strongly disagree” and 5 is “strongly agree”. The questionnaire used in the quantitative study, which includes all of the constructs described above, along with their assigned items, is included in Appendix A. 3.3. Participants The study focused on HR professionals as it related to the achievement of work results, which depend on the perception of fulfilling the assumptions of the psychological contract related to the performance of HR tasks. This is because the concept of the research is based on the analysis of the mechanism that drives the achievement of work results by HR professionals who, through the realisation of positive relationships with their superiors, are the providers of expected HR actions in companies. The arguments cited above determine the way in which the population of the study is defined, taking into account all employed HR professionals in the organisation under study. This study covered the individual employee level. This is related to the adopted definition of the psychological contract, which refers to the two parties to the contract involving the psychological contract: the employee and the employer. The employee, as one party to the contract, is relatively easy to identify because the psychological contract is perceived and maintained at the individual level. Employees, on the other hand, perceive the employer as the other party to the contract, through the prism of the organisation, defining ‘employer’ as the overall picture of the actions of supervisors and managers and the signals coming from the organisation in the form of HR practices and applicable company documentation. In this view, employees attribute characteristics to the employer that indicate an anthropomorphisation of the organisation [78]. The quantitative study was the main stage of the procedure carried out in order to empirically verify the hypothetical model. The survey covered 402 respondents, who constituted 100% of the employees in the HR department of the company under study. It used the technique of computer-assisted telephone interviewing (CATI). The research was preceded by a pilot study, which included the verification of the research tool. The final research tools were also verified by conducting a factor analysis and calculating reliability parameters. The data collected from each interview were analysed for the questionnaire path, which was guided by a script, as well as for the consistency of the tool. A self-constructed survey questionnaire and purposive sampling [79,80] were used. Table 1 shows the demographics of the study participants. Overall, 64.9% of the participants were female and only 35.1% were male. This ratio indicates that the HR department in the energy industry, as in other industries [54], is dominated by women. Half of the total group of respondents were under 39 years old (50.0%) and almost three quarters of the surveyed group had a master’s degree (71.4%). In terms of length of service with their current company, 35.8% of respondents said up to 10 years, while 61.5% of respondents surveyed had 10 years or more of total work experience. The distribution of positions in the professional hierarchy has the standard appearance of an inverted triangle. The majority of survey participants are employed as HR assistants and senior assistants (74.8%) and a minority as managers (20.0%) and executives (5.2%). 3.4. Data Analysis Methods Structural equation modelling was used to analyse the collected data using the PLS method in WarpPLS 7.0 [81,82]. This is a confirmatory statistical analysis that aims to maximise the explained variance of the dependent variables by the predictors. Structural equation analysis, using the Partial Least Squares (PLS) method, was conducted in two steps. In the first step, latent variables were created [83] with the help of confirmatory factor analysis performed on observable variables. The formatted variables were used in a multivariate path analysis leading to a structural model. During structural equation modelling with the PLS method, multivariate regression analyses are performed in an iterative flow-a path structural model of the modelled relationships between variables is calculated. The path structural model returns information about the significance, sign and strength of predictor relationships with dependent variables. The most important criterion for evaluating a path model is the generalised predictive power of the dependent variables. In the analysis, the PLS algorithm was applied using the information that the measurement model of the variables is a reflective model. The reflective measurement model was calculated based on the assumption that the latent variable affects the variability of observable variables that are correlated with each other and measured with their natural measurement error [83]. Standard errors and statistical significance were estimated through the Stable3 method proposed by a software developer [84]. It ensures that errors are computed in the course of exponential smoothing rather than bootstrapping (repeatedly drawing observations from a sample with returning them) [85]. The analysis predicted linear relationships between variables. The tested model included measurement of all analysed variables. Diagnostic statistics of the measurement model and the structural model showed a very good fit of the data to the measurement model (external) SRMR = 0.09, SMAR = 0.08. Moreover, analysis of the overall predictive power of the structural model (internal) showed that it had a strong predictive power GoF = 0.51 [86]. The analysis also showed that the variables in the structural model were not strongly collinear with each other AVIF = 1.94. It was also observed that there was no total collinearity between the study variables AFVIF = 2.35. The model quality assessment statistics are presented in Table 2. 4. Results In order to analyse the results of the measurement model in detail, a confirmatory factor analysis matrix of the variables conceptualised in the factor model was calculated. The analysis showed that all test items of the questionnaire were strongly and significantly associated with their factors. Composite reliability (CR) coefficients were calculated to check the reliability of the measurements. All factor loadings in the measurement model exceeded 0.7 and factor analysis showed that all measurements had a high level of measurement accuracy CR/α > 0.75 [87,88]. The values of the extracted average variance (AVE) were higher than 0.50. Moreover, all square roots of the AVE are also higher than the interconstruct correlations. Thus, we confirmed the convergent validity of the scales [89,90]. Descriptive statistics were also calculated for the study variables and correlation analysis was performed, which in each case proved to be positively correlated and statistically significant. The results are presented in Table 3. The values obtained and the directions of the relationships can be considered as consistent with the predictions. However, in order to analyse the direct and indirect relationship between the variables, it was necessary to carry out analyses using structural equation modelling. In addition to hypotheses H1–H5 which assume a direct and positive effect of the studied variables, hypotheses H6–H7 indicating an indirect positive effect, were additionally presented. It was assumed that the mediating effect between the fulfilment of the (relational and transactional) psychological contract and the work results achieved by HR professionals was organisational identification. The creation of a research model based on the SEM-PLS method, in which all the analysed variables were placed, allowed, firstly, to verify the nature of the relationships between the variables due to direct correlations and, secondly, to demonstrate mediation relationships. In order to test the seven hypotheses proposed in this study, a structural equation modelling analysis was carried out. This analysis resulted in a good fit of the adopted measurement model. The results indicated that, for each of the variables, the parameters (factor loadings and measurement error variance) were statistically significant (by item t-test, p < 0.0001). The correlation between individual variables was also significant (p < 0.0001). The good fit of the model was also confirmed by the results of the chi-square test, where p < 0.001 was obtained, Further measures, within the CFA results, also indicated a good fit of the model-χ2/df < 5 [91], RMSEA is less than 0.8 (=0.263) [92], SRMR-less than 0.08 (=0. 079) [84], CFI > 0.9 (=0.401) [93], GFI, AGFI and gamma exceed 0.95 (= 11.607) [91]. In summary, the CFA supported the measurement model and showed that the fulfilment of relational psychological contract, transactional psychological contract, organisational identification and HR professionals’ work results were four distinct constructs. Table 4 illustrates the achieved path coefficients between each pair of variables in the research model. As can be observed from Table 4 above, the path coefficient between the fulfilment of the relational psychological contract and work results is significant (β = 0.304, p < 0.002), thus confirming Hypothesis No.1. The path coefficient between the fulfilment of the transactional psychological contract and work results achieved by HR professionals from the energy sector (β = 0.371, p < 0.001) is also positively and significant, thus confirming Hypothesis No. 2. Similarly, the path coefficients between relational psychological contract fulfilment and organisational identification (β = 0.158, p < 0.003) and between transactional psychological contract fulfilment and organisational identification (β = 0.215, p < 0.001) were also positively significant, supporting the next two Hypotheses No. 3 and No. 4. The positive path coefficient between organisational identification and work results achieved by HR professionals from the energy sector was also proved to be significant (β = 0.367, p < 0.002). This result supports Hypothesis No. 5. This study also examined how organisational identification mediates the relationship between the fulfilment of the relational and transactional psychological contract and the work results achieved by HR professionals of the surveyed organisation from the energy sector. The results in Table 4 reveal that organisational identification has a significant mediating effect (β = 0.146, p < 0.002) on the relationship between the fulfilment of the relational psychological contract and the achieved work results, thus confirming Hypothesis No. 6. The study also tested the confirmation of Hypothesis No. 7, indicating that organisational identification had a significant mediating effect (β = 0.189, p < 0.002) on the relationship between the fulfilment of the transactional psychological contract and the achieved work results of HR professionals of the surveyed organisation from the energy sector. Thanks to the empirical research carried out in this professional group, we verified the mediating role of organisational identification between the psychological contract and work results, and revealed the mechanism of the emergence of employees’ behaviours resulting from the fulfilment of the concluded psychological contracts, hoping to fill the existing gaps in this area. 5. Discussion Arising from social exchange theory, psychological contract fulfilment is an important foundation for understanding employer–employee relationships [19] and a perspective for understanding organisational behaviours and attitudes [16].The impact of psychological contract fulfilment on employee work outcomes has been widely studied [62,94,95]. Previous studies have discussed employees’ commitment, motivation, satisfaction and employee performance, but few studies have investigated organisational identification and self-perception of work results [5,95]. Although prior research has examined the relationship between psychological contract fulfilment and employees’ performance and employees’ task performance, it has generally focused on work performance and organisational citizenship behaviours, which are relatively broad aspects of employees’ attitudes and behaviour [66]. HR professionals tend to work with the primary goal of performing well in HR policies. They are more likely to focus on self-performance than other organisational behaviours in their work. Therefore, this study specifically examines employees’ perspective of self-performance as an outcome of fulfilling a psychological contract and explores the positive relationship between these variables. Building on previous literature, this paper proposes a framework to examine whether and how psychological contract fulfilment affects employee work results in the context of organisational identification. This becomes important especially in the energy industry, where HR professionals play the role of organisational representatives of the psychological contract [96,97]. Fulfilment of the relational as well as transactional contracts are important drivers for HR professionals to engage in their work and achieve satisfied self-performance. This is because fulfilling the psychological contract increases employees’ job satisfaction, thereby affecting their sense of organisational identification and increasing their self-performance. In turn, psychological contract breach is interpreted by employees as unfair treatment and thus results in reduced feelings, or even lack of organisational identification [35]. In the context of the performance of HR policy responsibilities, the relationship between HR professionals and the organisation becomes relatively stronger in cases where the psychological contract is fulfilled. Then, HR professionals may try to reciprocate the expectations fulfilled by the organisation by performing their tasks, especially of high quality. The fulfilment of relational and transactional psychological contracts show a positive effect with HR professionals’ sense of organisational identification, indicating that organisational identification is also becoming an important variable shaping work relationships. The results of this study indicate that fulfilling both transactional and relational psychological contracts can contribute to HR professionals’ work results. These findings are consistent with previous research that shows that fulfilling psychological contracts increases employee trust in the organisation, which in turn contributes to specific employee attitudes and behaviours, including employee commitment, satisfaction [16] and employee performance [98,99]. For example, other studies show that the fulfilment of psychological contracts, including their relational and transactional aspects, is positively related to organisational effectiveness and work results achieved [55]. In turn, research by Lambert and Knapp scientific teams [100,101] indicate strong links of fulfilling the psychological contract by gradually increasing the level of trust between employers and employees. In the context of the HRM field, HR professionals demonstrate a willingness to perform at higher levels when they perceive that their employers or supervisors are fulfilling their commitments, and psychological contracts include transactional and relational conditions such as compensation, working hours, job security, training opportunities, and a pleasant work environment [102]. The conducted research also proves that organisational identification is an important factor related to the work results of HR professionals. This fact can be explained that HR professionals, by perceiving themselves as a part of the organisation [18,103], strengthen the willingness and motivation for increased effort and, consequently, influence the level of achieved work results arising from their tasks and professional roles [104,105]. The results of the study suggest that psychological contract and organisational identification should be highly valued and added to the theoretical framework of research on the effectiveness of individual performance of HR professionals. When HR professionals begin to identify with the organisation, their self-interest and the company’s interest become intertwined, and the organisation’s achievements become their personal achievements. This means that if HR professionals achieve a sense of organisational identification, they are likely to increase their work results and redirect the effort they put into their roles to meet both their own and the organisation’s interests. Furthermore, the present study exposes the mediating mechanism of organisational identification between the fulfilment of both transactional and relational psychological contracts and work results achieved. The mediating role of organisational identification has been discussed in several previous studies. For example, a study by [94] examined the mediating effect of organisational identification between psychological contract violation and job performance and results and found that psychological contract violation can consequence in low productivity and low work results by weakening employees’ organisational identification. Another study found that organisational identification mediates the relationship between relational psychological contract and job performance and work results [18]. In contrast, the results of this study indicate that not only relational but also transactional fulfilment of psychological contracts indirectly influences HR professionals’ work results through the mediating role of organisational identification. These results suggest that organisational identification arises in both relational and transactional psychological contract fulfilment situations and becomes an important motivator of HR professionals’ work results in the surveyed organisation from the energy sector. HR professionals, through the perception that their employers have met their expectations in providing economic or monetary rewards, offering them socio-emotional support, feel organisational identification, which may motivate them to improve their work results. The results of the presented study reflect a view that indicates that fulfilling both types of psychological contract becomes an important predictor of work results achievement [57,95]. 5.1. Theoretical Implications The theoretical contribution of this study is manifested in several aspects. First, we identified the relationship between the psychological contract, which is considered through its division into transactional and relational contracts, organisational identification and work results. We confirmed that fulfilling the obligations of the psychological contract positively impacts work outcomes. Secondly, we found that organisational identification is important for this relationship. Indeed, we discovered that the relationship between the psychological contract and work results is stronger when mediated by organisational identification. It allows for greater integration of the individual’s goals and the goals of the organisation. Our research indicates that this is particularly evident in relation to the transactional contract. Furthermore, we have shown that social exchange theory is a useful framework for understanding the relationship between the psychological contract and the organisation’s fulfilment of its assumptions and the work results achieved by employees. In particular, it allows us to understand the importance of the role of organisational identification in shaping this relationship. Finally, in this study the subject was a specific group, namely, HR professionals. These employees are, in a way, the link between management and employees, and at the same time they are responsible for the selection of tools shaping the attitudes and behaviours of other employees. Identifying the relationship between the psychological contract and work results in this professional group can serve to create guidelines for other employees within the organisation. Indeed, we have highlighted the key role that HR professionals play in helping organisations to fulfil psychological contracts and to understand the consequences of not fulfilling them. 5.2. Practical Implications Our study also provides some insights that can be used in management practice, especially human resource management. Understanding how the fulfilment of both transactional and relational psychological contract affects the performance of HR professionals, as well as identifying specific mechanisms may be helpful in developing more effective HRM policies. In particular, it concerns the selection of HRM methods, tools or practices which are aimed at fulfilling employees’ expectations and obligations under the established psychological contract, thus shaping desired attitudes and behaviours. The approach used thus appears useful in the context of decision effectiveness in people management. 5.3. Limitations and Further Research Despite the conclusions, which are useful for both researchers and practitioners, we are aware of the limitations of our study. One of these limitations is related to the research methodology adopted, based on a cross-sectional self-report survey. It would therefore be advisable to carry out further research using experimental or longitudinal research designs, which could give a more precise picture of the relationships and enable the direction of causality to be explored. Another limitation is related to the fact that the subject of the study included only HR professionals from one company, operating in specific conditions of Polish culture. Although it made it possible to gather valuable empirical material, broadening the knowledge concerning this group of employees, it is worth extending the circle of research. Thus, it will be possible to determine how these relations are shaped in other groups of employees and in different categories of organisations, as well as in different cultural circles. This could be the subject of further research. In addition, it also seems to be an interesting direction to verify how the relationships between psychological contract and organisational identification affect other attitudes and behaviours of employees, including citizenship behaviour. Identifying whether and when an employee feels that the organisation is not fulfilling the psychological contract, which translates into counterproductive behaviour, may also be an interesting issue. 6. Conclusions The issues addressed, supported by the research discussed in the article, made it possible, from both a practical and a theoretical-cognitive perspective, to grasp the relationship between the psychological contract and organisational identification and work results. They made it possible to draw a broader picture of these relations by capturing the relationships and, in a way, measuring their strength. The research confirms that the fulfilment of psychological contracts by organisations, both relational and transactional ones, impacts the work results achieved by employees. Moreover, organisational identification has proven to be an important mediator of these relationships. Therefore, the authors remain convinced of the relevance of the undertaken issues, their scientific significance and practical relevance, both for HR specialists themselves as well as all other employees. Author Contributions General concept, A.R.-P. and K.G.-L.; theory, A.R.-P. and K.G.-L.; methodology, A.R.-P. and K.G.-L.; validation and formal analysis, A.R.-P.; investigation and data curation, A.R.-P.; preparation of the draft version, A.R.-P. and K.G.-L.; preparation of the final version, A.R.-P. and K.G.-L. 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 A.R.-P. Conflicts of Interest The authors declare no conflict of interest. Appendix A. Research Constructs, Subscales and Measurement Items and Sources Fulfilment of Psychological Contract [19,64,65] Fulfilment of the psychological contract by employer towards the employees Fulfilment of Relational Psychological Contract (FRPC) (FRPC 1) Steady employment (FRPC 2) Steady benefits to em-ployee’s family (FRPC 3) Concern to my personal welfare (FRPC 4) Opting for short-term company benefits over employee interests (FRPC 5) Renumeration and benefits I can count on (FRPC 6) Be responsive to employee concerns and well-being (FRPC 7) Make decisions with my interests in mind (FRPC 8) Concern for my long-term-organizational being (FRPC 9) Secure employment (FRPC 10) Stable wages overtime Fulfilment of Transactional Psychological Contract (FTPC) [19,64,65] (FTPC 1) Makes no commitment to retain me in the organizational future (FTPC 2) Short-term employment (FTPC 3) Employer can terminate my employment any time (FTPC 4) No promises to continue my employment in the future (FTPC 5) Training me only for my current job (FTPC 6) Employment for a specific or limited time (FTPC 7) Require me to do only limited duties for which I was employed (FTPC 8) Pay me only for specific duties I perform (FTPC 9) A job limited to specific well-defined responsibilities (FTPC 10) Limited involvement in the organization Organizational Identification (OID) [66,67,68] (OID 1) I would probably continue working for my organization even if I did not need the money (OID 2) In general, people employed by organization are working toward the same goal (OID 3) I am proud to be an employee of my organization (OID 4) I would be willing to spend the rest of my career with my organization (OID 5) I find that my values and the values of my organization are very similar (OID 6) I find it easy to identify myself with the organization Results of Work (RW) [55,70] (RW 1) Carry out my job carefully, professionally and efficiently (RW 2) I always meet specified deadlines for the accomplishment of tasks (RW 3) I continuously develop my competencies to meet future opportunities and challenges (RW 4) My work produces innovative results/solutions (RW 5) My good performance and work results is confirmed by customer satisfaction Figure 1 Research model of relationships between the fulfilment of the relational and transactional psychological contract and HR professionals’ work results and the mediating effect of organisational identification. ijerph-19-05404-t001_Table 1 Table 1 Structure of the research sample in the quantitative survey (n = 402). Demographic Criteria Categories Frequency Percent (%) Age ≤30 41 10.2 30–39 160 39.8 40–49 111 27.6 50–54 70 17.4 >55 20 5.0 Education Bachelors 71 17.7 Masters 287 71.4 Doctorate PhD 44 10.9 Total length of service ≤1 year 2 0.5 1–5 years 53 13.2 6–10 years 100 24.8 >10 247 61.5 Length of service for current firm ≤1 year 51 12.7 1–5 years 83 20.7 6–10 years 144 35.8 >10 124 30.8 ijerph-19-05404-t002_Table 2 Table 2 Model fit statistics. Factor Value factor AVIF 1.94 AFVIF 2.35 Tenenhaus GoF (GoF) 0.51 Sympson’s paradox ratio (SPR) 0.87 Statistical suppression ratio (SSR) 0.89 SRMR 0.08 SMAR 0.08 Note: AVIF = Average Variance Inflation Factor (accepted if AVIF ≤ 5.00); AFVIF = Average Full Variance Inflation Factor (accepted if AFVIF ≤ 5.00); GoF = Godness of Fit/ Model Predictive. The higher, the better the fit of the data to the path model (low GoF ≥ 0.10, medium GoF ≥ 0.25, high GoF ≥ 0.36); SPR = Simpson’s Paradox Ratio. The higher, the fewer cases of Simpson’s Paradox (accepted SPR ≥ 0.70, ideal SPR = 1.00); SSR = Statstical Supression Ratio. The higher, the closer the path estimates are to the values of the correlation coefficients (accepted SSR ≥ 0.70, ideal SSR = 1.00); SRMR = Standardized Root Mean Squared Residual. The lower, the better the fit of the data to the measurement model of the variables (accepted if SRMR ≤ 0.10); SMAR = Standardized Mean Absolute Residual. The lower, the better the fit of the data to the measurement model of the variables (accepted if SMAR ≤ 0.10). ijerph-19-05404-t003_Table 3 Table 3 Results Convergence accuracy of the measurement model and the mean (M), standard deviation (SD), correlation matrix. Variable Loading t-Value CR Cronbach’s α AVE Mean SD FTPC FRPC OID RW FRPC 0.861 18.11 *** 0.975 0.96 0.825 3.39 1.21 0.567 *** FRPC1 0.816 16.77 *** 0.554 *** FRPC2 0.845 17.34 *** 0.601 *** FRPC3 0.761 18.35 *** 0.496 *** FRPC4 0.731 18.17 *** 0.551 *** FRPC5 0.719 16.63 *** 0.498 *** FRPC6 0.765 17.01 *** 0.563 *** FRPC7 0.699 17.30 *** 0.489 *** FRPC8 0.797 15.94 *** 0.667 *** FRPC9 0.866 16.45 *** 0.517 *** FRPC10 0.689 15.91 *** 0.647 *** FTPC 0.711 16.87 *** 0.951 0.86 0.686 2.34 1.39 0.694 *** 0.754 *** FTPC1 0.709 16.97 *** 0.644 *** 0.532 *** FTPC2 0.699 16.94 *** 0.541 *** 0.501 *** FTPC3 0.638 15.91 *** 0.711 *** 0.817 *** FTPC4 0.702 14.82 *** 0.499 *** 0.676 *** FTPC5 0.742 17.08 *** 0.618 *** 0.592 *** FTPC6 0.800 16.87 *** 0.523 *** 0.534 *** FTPC7 0.791 16.65 *** 0.717 *** 0.643 *** FTPC8 0.736 16.27 *** 0.800 *** 0.716 *** FTPC9 0.687 17.09 *** 0.451 *** 0.541*** FTPC10 0.681 16.63 *** 0.329 *** 0.678 *** OID 0.821 17.30 *** 0.988 0.90 0.693 3.43 1.03 0.785 *** 0.733 *** 0.816 *** OID1 0.791 18.11 *** 0.731 *** 0.697 *** 0.815 *** OID2 0.764 17.38 *** 0.691 *** 0.495 *** 0.495 *** OID3 0.782 15.88 *** 0.499 *** 0.592 *** 0.591 *** OID4 0.712 17.99 *** 0.692 *** 0.687 *** 0.693 *** OID5 0.682 17.21 *** 0.495 *** 0.655 *** 0.716 *** OID6 0.811 16.94 *** 0.679 *** 0.491 *** 0.511 *** RW 0.734 17.99 *** 0.938 0.94 0.766 3.44 1.41 0.729 *** 0.695 *** 0.804 *** 0.832 *** RW1 0.729 17.43 *** 0.652 *** 0.715 *** 0.705 *** 0.816 *** RW2 0.735 16.77 *** 0.595 *** 0.396 *** 0.629 *** 0.549 *** RW3 0.691 16.43 *** 0.820 *** 0.719 *** 0.551 *** 0.791 *** RW4 0.687 16.41 *** 0.659 *** 0.802 *** 0.774 *** 0.609 *** RW5 0.712 18.17 *** 0.798 *** 0.709 *** 0.605 *** 0.598 *** Note: (α) = Cronbach’s alpha, value above 0.75 is acceptable; CR = Composite Reliability, value above 0.75 is acceptable; AVE = Average Variance Extracted, preferred value > 0.50; t = Student’s t statistic for factor loading *** p < 0.001. ijerph-19-05404-t004_Table 4 Table 4 Direct effects between variables and mediating effects of the Organizational Identification (OID) between Fulfillment of the Relational Psychological Contract (FRPC); Fulfillment of the Transactional Psychological Contract (FTPC) and Results of Work (RW). Effect Path Analysis β-Standardized Path Coefficient t-Value p Results Direct effect FRPC---->RW 0.304 3.049 0.002 H1 is confirmed Direct effect FTPC---->RW 0.371 3.655 0.001 H2 is confirmed Direct effect FRPC---->OID 0.158 0.340 0.003 H3 is confirmed Direct effect FTPC---->OID 0.215 1.461 0.001 H4 is confirmed Direct effect OID---->RW 0.367 1.984 0.002 H5 is confirmed Indirect effect FRPC---->OID---->RW 0.146 0.347 0.002 H6 is confirmed Indirect effect FTPC---->OID---->RW 0.189 0.467 0.002 H7 is confirmed Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Benach J. Vives A. Amable M. Vanroelen C. Tarafa G. Muntaner C. Precarious Employment: Understanding an Emerging Social Determinant of Health Annu. Rev. Public Health 2014 35 229 253 10.1146/annurev-publhealth-032013-182500 24641559 2. Van Hootegem A. De Witte H. 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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/ijerph19095327 ijerph-19-05327 Article Compliance with Standard Precaution and Its Relationship with Views on Infection Control and Prevention Policy among Chinese University Students during the COVID-19 Pandemic https://orcid.org/0000-0001-7935-102X Cheng Winnie Lai Sheung 1 Kwong Enid Wai Yung 2 https://orcid.org/0000-0003-1884-8360 Lee Regina Lai Tong 3 https://orcid.org/0000-0002-4293-8449 Tang Anson Chui Yan 1 Wong Lokki Lok Ki 1* Zhang Yudong Academic Editor Gorriz Juan Manuel Academic Editor Dong Zhengchao Academic Editor 1 School of Nursing, Tung Wah College, Hong Kong, China; winniecheng@twc.edu.hk (W.L.S.C.); ansontang@twc.edu.hk (A.C.Y.T.) 2 School of Nursing, Putian University, Putian 351100, China; enid.kwong@yahoo.com 3 The Nethersole School of Nursing, The Chinese University of Hong Kong, Hong Kong, China; reginalee@cuhk.edu.hk * Correspondence: lokkiwong@twc.edu.hk 27 4 2022 5 2022 19 9 532729 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/). Background: COVID-19 has placed tremendous pressure on the global public health system and has changed daily life. Aim: To examine the relationships between the perceived threat, perceived stress, coping responses and infection control practices towards the COVID-19 pandemic among university students in China. Methods: Using a cross-sectional survey, 4392 students were recruited from six universities in two regions of China. Methods: Data were collected via an online platform using self-reported questionnaires. Hierarchical multiple regression analyses were performed to predict the variables on COVID-19 infection control practices. Results: Pearson correlation coefficients showed a significant negative relationship between perceived stress and COVID-19 infection control practices. A significant positive relationship was observed between wishful thinking and empathetic responding, and infection control practices. Hierarchical multiple regression analyses revealed that gender, geographical location, perceived stress and emotion-focused and relationship-focused coping responses were predictors of COVID-19 infection control practices. Conclusions: The findings suggest that university students displayed moderate levels of stress, using wishful thinking and empathetic responses as coping strategies. Counselling services should therefore emphasise reassurance and empathy. Male university students tended to be less compliant with social distancing. Both counselling and public health measures should recognise the importance of gender differences. Nurses should integrate these findings into future health programme planning and interventions. COVID-19 emotion-focused coping infection control practices perceived stress relationship-focused coping Tung Wah CollegeThis research received no external funding. A portion of article processing charges (APC) was sposored by Tung Wah College. ==== Body pmc1. Introduction COVID-19, a novel coronavirus disease first reported in China in December 2019, is placing tremendous pressure on the global public health system [1] and has changed daily life. To combat viral transmission, governments have imposed stringent emergency measures, such as wearing masks, practicing hand hygiene, and social distancing at local and national levels to limit the spread of the virus [2,3,4]. To avoid further disruption in academic study, universities around the world have now started to resume classes on campus. With many college students gathering on campuses, the risk of transmitting the infection through asymptomatic persons infected with the coronavirus cannot be over-emphasised. Resuming classes places greater pressure on the need for COVID-19 prevention, especially on those who do not comply with infection control practices. Understanding the contributing factors to preventive measures against the spread of disease among university students is important. 2. Overview of the Theoretical Constructs 2.1. Threat and Behavioural Responses The pandemic has generated tremendous uncertainty and stress, directly affecting mental health [1]. According to the protection motivation theory [5], individuals initiate cognitive appraisal of a threat and coping responses if they encounter danger and implement actions to mitigate the threat [5,6]. A review of the existing literature reveals that individuals are more likely to perform preventive health behaviours if they perceive a health risk [7]. 2.2. Stress Stress is a response to external pressure. Stress can be experienced at any time that an individual perceives a threat to their well-being or when they lack the resources to overcome a situation [8]. According to transactional theory, individuals often seek coping strategies to relieve the negative effects of stress according to their appraisal of their situation [9]. Studies have found that individuals who report higher anxiety are more likely to change their behaviour when encountering health threats [9,10]. 2.3. Ways of Coping Coping is a conscious effort by individuals to regulate their emotions, cognition, and behaviour in response to stressful situations; it is a dynamic process, and the strategies adopted are dependent on the situation [8]. People are more likely to use problem-focused coping strategies when they perceive that a stressful situation is within their control and can be changed. Conversely, individuals often use emotion-focused types of coping, such as wishful thinking—an avoidance type of coping—to lessen their emotional distress when they believe a stressful situation cannot be changed [11]. They will use relationship-focused coping to maintain social relationships during a stressful situation [12]. Given that COVID-19 is beyond any individual’s control, avoidance type of coping is likely to be used. Studies have identified several factors, such as feelings of distress, attitude and intention to comply with health regulations that could increase preventive behaviour [13] and the effects of coping strategies on reducing the stress triggered by the pandemic [14]. 3. Objectives of the Study Whether avoidance type of coping is effective in initiating preventive practice is scarcely studied. This study postulates that when people perceive stressful situations as beyond their control, they activate coping processes, including wishful thinking and empathy, to mitigate the health threat and stressor. The objectives of this study were: (a) to investigate the relationships between the perceived threat, perceived stress, ways of coping, and infection control practices, and (b) to identify the factors that could predict COVID-19 infection control practices. 4. Methods 4.1. Study Design and Settings A cross-sectional study using convenience sampling was conducted. Three higher education institutions in Hong Kong (Special Administrative Region, China) and three higher education institutions in Putian (prefecture-level city in eastern Fujian province, China) were sampled. An invitation letter was sent to the students to fill in the anonymous online questionnaire via mass school emails in April 2020. 4.2. Participants Students aged 18 or older and currently enrolled in a full-time programme offered in the participating education institutions for this study were recruited. Data were collected from 4392 college students (81.8% female; average age, 20.5). Part of the data, students studying healthcare programmes, has been taken from a study conducted by Tang et al. [15] to examine their compliance with infection control practices. In the present study, the majority of participants (87.9%) were from Putian. The distribution of age and gender and the details of the study programme by geographical location are presented in Table 1. 4.3. Ethical Considerations Ethical clearance was obtained from the ethics committees of the participating institutions: Hong Kong (REC2020056) and Putian (2020-42). Participants were informed about the study and their rights before beginning the survey. Consent for the study was implied by returning the completed anonymous survey. 4.4. Measures Perceived Stress Feelings of stress were measured using a 10-item Perceived Stress Scale (PSS). According to Ng [16], the PSS represents two constructs, namely perceived helplessness and perceived self-efficacy. It includes 10 questions rated on a five-point scale, with a higher score indicating higher perceived stress level. The internal consistency of the PSS was strong, with a Cronbach’s alpha of 0.85 [17]. The PSS had an acceptable convergent validity with Pearson correlation coefficients of 0.69 and 0.72 [18]. 4.5. Perceived Threat of COVID-19 Respondents’ perceptions of the health threat of the COVID-19 outbreak were assessed using a five-item Perceived Threat scale (PT). The scale was originally developed by Brug et al. [19] to assess the threat of the SARS epidemic. The PT is a four-point scale ranging from ‘not at all’ to ‘a great deal’; higher scores indicate a greater perceived threat. The internal reliability of the scale was acceptable (alpha = 0.65) [20]. 4.6. Ways of Coping Participants’ ways of coping were measured using items from the Ways of Coping Questionnaire [20]. Two subscales were used: Wishful Thinking Scale (WIS) and Empathic Responding Scale (EMP). In the present study, the WIS tested the extent to which respondents had managed their concerns or fears about COVID-19 through statements such as ‘wishing COVID-19 would go away or somehow be over with’ on a four-point scale ranging from ‘not at all’ to ‘a great deal’. The EMP tested the extent to which respondents had helped others who might be concerned about getting COVID-19, on a four-point scale ranging from ‘not at all’ to ‘a great deal’. The reliability of the scale was high (alpha = 0.91) [20]. 4.7. COVID-19 Infection Control Practices COVID-19 infection control practice (ICP) scores were measured using items developed by the SARS Collaborative Research Group [19,20]. The questionnaire consists of subscales measuring two aspects: (1) social distancing (SoD) scale (i.e., the practice of reducing close contact between people), and (2) personal precautionary measures (PPM) scale (i.e., the practice of maintaining good hygiene and lifestyle). The SoD scale measured behaviours in two domains: avoid going to public places and avoid contacting people who were perceived as having a higher risk of exposure to COVID-19. The first part—avoiding public places (APP)—comprises 10 possible behaviours, including statements such as ‘avoided travel to COVID-19 infected areas’ and ‘avoided eating in restaurants’. The second part—avoiding people (AP)—comprises nine items such as ‘avoided people who have a fever’ and ‘avoided a person you know who has just come from an area infected with COVID-19’. The reliability of the scale was moderately high, with alpha ranging from 0.79 to 0.91 [20,21]. The PPM scale asked respondents to identify health practices in which they had engaged to avoid being infected with COVID-19. There were eight health practices, such as ‘wearing a mask’ and ‘using disinfectants’. The scale’s reliability was moderately high (alpha = 0.78–0.83) [20,21,22]. The ICP score was used to represent the average of the APP, AP and PPM scores. All questionnaires in this study were translated to Chinese for collecting data in Putian by forward-backward translation. The content validity (alpha = 0.7–1) of all scales was high. Internal consistency of the questionnaires in this study was established. The Cronbach alphas of perceived stress scale was 0.843; perceived threat scale was 0.718; ways of coping questionnaire was 0.849; COVID-19 infection control practices questionnaire was 0.927. 4.8. Data Analysis All statistical analyses for this study were carried out using SPSS, version 26.0 (SPSS 2020). Descriptive statistics of frequencies, means and standard deviation were calculated for all variables. Chi-square χ2 and independent t-test were performed to test the statistical significance of differences in demographic characteristics and study variables between demographic groups (e.g., geographic locations). Pearson product-moment correlation was used to investigate the relationships between perceived stress, copings responses and ICP score. A three-step hierarchical multiple regression analysis was conducted. In each step, a group of predictors was entered to examine the contribution to the total variance of COVID-19 infection control practices. In the first step of analysis, we entered the demographic variables, including gender, age, institution, studying programme (e.g., nursing, engineering) and geographic location, etc. Dummy variables were created to incorporate categorical variables (e.g., gender, marital status) into the regression analyses. In the second step, we added perceived stress and threat. Finally, we entered coping variables (i.e., wishful thinking and empathetic responding) as predictors. For all statistical tests, variables were considered significant at a significance level of 0.05. Missing values, normality and outliers were checked before the main analysis; no outliers nor missing values were found in the dataset. Using G*Power [23], an a priori power analysis for linear multiple regression, fixed model, R2 increase with an alpha of 0.05, power of 0.08 and 14 predictors revealed that the sample size was sufficient to detect a small effect (f2 = 0.02). 5. Results 5.1. Mean Scores and Correlations of the Study Variables and Subgroup Analyses The mean scores for PT (M = 11.79/20, SD = 2.99) and PSS (M = 19.55/40, SD = 4.69) indicated that the participants felt moderate stress towards, and threat from, COVID-19. The mean scores for WIS (M = 9.40/12, SD = 1.67) and EMP (M = 18.46/24, SD = 2.83) were high, which reflected the participants’ use of emotion-focused and relationship-focused coping in managing the stress. For COVID-19 infection control practices, the mean scores for APP and AP were 43.22 (SD = 8.05) and 37.43 (SD = 7.54), respectively; the mean score of PPM was 33.23 (SD = 5.18); and the mean score of ICP was 37.96 (SD = 5.55). There were significant differences between Hong Kong and Putian in all variables (p < 0.05). Participants in Hong Kong had a lower compliance in COVID-19 infection control practices. Table 1 displays the details of the descriptive variables. Table 2 presents the study variables by programme and gender. Significant differences were observed in PT, AP and ICP scores between healthcare and non-healthcare programmes. Healthcare students had higher levels of threat and better compliance with social distancing by keeping away from people and performing personal precautionary measures. There were significant differences between gender in many of the variables (p < 0.05) but neither in perceived threat and empathetic response coping nor in personal precautionary measures. The male participants had a lower level of stress, less frequent use of wishful thinking and lower adherence to social distancing than that of the females. Further analyses found that men (n = 800) who studied in the junior year (p = 0.007) or studied in Putian (p = 0.011) had a higher level of stress; those who had higher education level (p = 0.05) or studied in Putian a (<0.001) had more frequent use of wishful thinking coping strategy; those who lived with family (p = 0.014) or in Putian (<0.001) tended to have better adherence to social distancing. When gender differences were analysed by geographical location, significant differences were found in perceived stress and wishful thinking only. Females in Hong Kong had higher levels of perceived stress and often used wishful thinking. By contrast, in Putian, significant differences between genders were found in perceived threat and social distancing. Female participants exhibited higher levels of threat and showed better adherence to social distancing than males. Table 3 shows the correlations between variables. Significant relationships were observed between perceived threat and stress. Significant negative relationships were found between perceived stress and avoiding public places and personal precautionary measures, indicating participants with lower levels of perceived stress were more likely to adhere to avoiding public places and personal precautionary measures. Coping responses were positively associated with overall infection control practices, meaning that participants who practiced more emotion-focused and relationship-focused coping tended to comply more with infection control practices. In analysing gender, significant negative relationships were detected between perceived stress and social distancing among males. 5.2. Multiple Hierarchical Regression Analysis for Variables Predicting COVID-19 Infection Control Practices Adherence Table 4 presents the results of a three-step multiple hierarchical regression analysis of the associations between perceived threat and stress, coping responses and COVID-19-infection control practices, controlled for demographic conditions. All steps were significant (Step 1, F (10, 4380) = 8.483, p < 0.001); Step 2, F (12, 4378) = 8.251, p < 0.001); Step 3, F (14, 4376) = 30.407, p < 0.001). In Step 1, gender and geographical location predicted COVID-19-infection control practices and could explain 1.9% of variance in COVID-19 infection control practices, with which females and Putian participants displayed higher compliance. When perceived threat and stress were added to Step 2, the overall explanatory power increased to 2.2%, showing that perceived stress had predictive power for COVID-19 infection control practices. In Step 3, adding emotion-focused and relationship-focused coping responses significantly affected the model. There was an increase of 6.7% of adjusted R2, indicating that coping responses have potential to moderate COVID-19 infection control practices. Finally, the model explained 8.9% of the variance in COVID-19 infection control practices. 6. Discussion In the present study, we found that university students demonstrated compliance with COVID-19 infection control practices. University students who are currently studying healthcare programmes tended to perceive more threat but complied better with the personal precautionary measures and social distancing to prevent viral infection, possibly owing to their knowledge of the COVID-19 infection and its detrimental effects on health. The model confirmed that gender, geographical location, perceived stress and emotion-focused and relationship-focused coping responses accurately predicted COVID-19 infection control practices. The most important finding from this study was that coping, whether emotion-focused or relationship-focused, had the greatest effect on infection control practices compared to other variables (i.e., perceived stress, gender and geographic location). 6.1. Geographic Location and Gender This study showed that university students complied well with COVID-19 infection control practices. This finding is consistent with studies conducted in China reporting that university students showed high compliance with COVID-19 preventive measures [24,25]. Similar results were obtained from a European study on adolescents’ awareness of protective behaviour during the COVID-19 outbreak [26]. Residents of all ages in Hong Kong have been reported to practice a high level of self-protective behaviours during the pandemic [27]. It may be because this study assessed Chinese participants who were in the epicentre of the outbreak; they were probably more conscious about infection control measures to mitigate the spread of virus. This speculation is supported by Cassimatis et al. [28], who stated that Asian students were more aware of COVID-19 prevention guidelines established by the Centers for Disease Control and Prevention (CDC). Interestingly, in this study, university students in Putian reported better compliance with COVID-19 infection control practices than their counterparts in Hong Kong. It may be because there were more students studying healthcare programmes and more females in Putian than those in Hong Kong. China was the first country to implement an aggressive lockdown strategy in Wuhan and other cities in January 2020. The infection control measures adopted by China included not only shutdowns of non-essential companies and shops and closures of public transport, airports and major highways, but also ‘closed management’ on a community basis in many areas across China to restrict social contacts. For instance, in some areas of China, only one family member was permitted to leave the household to purchase groceries. Access to villages and communities were prohibited throughout the day. Chinese authorities reported that there was no more domestic transmission of the disease after two months of the lockdown [29]. Conversely, in Hong Kong during that time, border crossings and public transport were still open. Regulations on restricting social contact, such as prohibition of group gatherings for more than four people, and temporary closures of entertainment venues were enacted only on 29 March 2020. The regulation of compulsory mask wearing in public places came into effect on 15 July 2020. Moreover, people’s positive perception of the government’s attempt to reduce the epidemic could increase practice of preventive measures [30,31]. In the present study, university students in Putian appeared to have stronger confidence in government policies controlling the outbreak. Like other studies [25,28], females in this study complied with infection control practices more than males. This may be due to the gender norm that men are conditioned to be tough [32] and less likely to seek help from others or engage in health promotion activities [33]. This study also revealed that males who lived with family tended to have better adherence to social distancing. This may be due to their concern about spreading the virus to family members. Subgroup analysis showed that the gender differences with regard to infection control practices were mainly found in residents in Putian. Healthcare professionals should be aware of the masculine gender role that might undermine males’ willingness to engage in personal protective measures. 6.2. Perceived Threat and Stress Our study confirmed that perceived stress is a predictor of infection control practices. The threat of COVID-19 was associated with perceived stress and had a negative relationship with personal precautionary measures. In this study, university students reported moderately high levels of perceived stress. This finding is consistent with previous studies that university students in China exhibited a certain degree of stress, experiencing stress-related symptoms, such as anxiety and depression [24,34], during the pandemic. In our study, university students in Hong Kong reported higher levels of stress than their counterparts in Putian. The finding is consistent with Dean et al.’s [35] study that people in Hong Kong exhibited the most psychological distress when compared to people in South Korea, the USA and France. Our study reports that female students in Hong Kong experienced higher stress levels. The many uncertainties surrounding COVID-19 generated stressors, such as the pressure for social distancing, lockdown, delays in academic achievement and economic uncertainty, all of which could heighten the stress level of an individual to varying degrees [1]. For university students in Hong Kong, the experience of social unrest in 2019 could also be one of the reasons behind higher stress levels [35,36]. The findings of the present study showed that perceived stress predicted infection control practices and was negatively associated with infection control practices. In contrast, other studies reported that higher levels of anxiety were more likely to initiate health behaviour when encountering health threats, such as novel swine-origin influenza [8,10]. In our study, we assessed the perceived stress level with the PSS scale, which comprises perceived helplessness and perceived self-efficacy. Self-efficacy is defined as the self-confidence necessary to engage in behaviour to successfully achieve a task [37]. A lower level of self-efficacy (i.e., high level of perceived stress) reflects lack of confidence in managing the situation. Our study suggests that confidence predicts behavioural changes. Female university students with lower levels of stress are more likely to perform personal precautionary measures, such as wearing masks, practicing hand hygiene, social distancing and avoiding public places. In contrast, male university students with lower levels of stress are more likely to wear masks and wash their hands only. This may be due to the fact that females have less preferences for outdoor activities than males [38]. These findings indicate that to mitigate the spread of any virus, or other community threat to health, a psychology-oriented and gender-sensitive programme should be implemented. 6.3. Emotion-Focused and Relationship-Focused Coping In our study, the results showed that university students often used emotion-focused and relationship-focused coping to deal with stressful situations during COVID-19. This finding is consistent with previous studies that found that emotional coping was frequently used to manage stressful situations during the COVID-19 outbreak [14,39]. The present study showed an association between coping responses and stress. The respondents employed emotion- and relationship-focused forms of coping to manage their emotions in the low-control situation of COVID-19. Kulenović and Buško [40] similarly found that high levels of perceived stress predict the frequent use of avoidance as a coping strategy. Emotion-focused coping is considered to be maladaptive [12]. However, the emotion- and relationship-focused coping strategies used by the university students in this study seemed to be adaptive. The respondents were motivated to protect themselves in an uncontrollable public health situation. This adaptive function was also noted during the SARS epidemic [41]. In this study, both wishful thinking and empathetic responding coping strategies may have a moderating effect on COVID-19 infection control practices. These findings were inconsistent with previous studies on epidemics [20,21]. The many unknowns of treatment protocol and protective effects of vaccines for the new variants of the current virus [42] may explain the difference in findings between the previous studies and current research. People may turn to wishful thinking and empathetic responding to relieve their psychological distress when facing uncertainty. Further, during periods of social distancing, people are likely to experience feelings of isolation. Lonely people tend to develop empathy as an adaptive emotion-regulating strategy to reduce their loneliness [43]. Use of these coping strategies may have protective effects on mental health [25]. Our study confirms the use of these coping strategies appeared to have a direct effect on infection control practices during the pandemic. This may be explained by the mediating effect of coping on behavioural responses [40]. The current study suggests that coping appraisal is a necessary factor motivating people to initiate protective actions [44]. These findings support the implementation of interventions that increase the effectiveness of coping strategies and thereby promote positive health behaviours. Thus, public health interventions aimed at university students should take emotion- and relationship-focused coping strategies into account. When sending outbreak information to university students, strategies can be designed to motivate their empathetic feelings and increase their sense of control of, or power in, the situation. 6.4. Strengths and Limitations The strength of this study is the large number of sample sizes that provided more accurate mean values. Another strength is that the study was conducted in the early stage of the pandemic (April 2020), which provided a more accurate picture on the psychological and behavioural responses towards a disease outbreak with unknown causes. This study had several important limitations. First, the variance explained by the independent variables was relatively small. Future studies are recommended to identify factors that could explain larger proportions of the variance in COVID-19 infection control practices. Second, the results of the regression analysis were based on correlational data, meaning that it is not possible to draw firm conclusions about causal relationships between these variables. Third, this study relied on self-reported measures, so the results may have been affected by social desirability bias. Fourth, the unequal sample sizes in gender may undermine the between group comparison. Fifth, as all the participants enrolled in this study were Chinese undergraduates, the results may not be generalisable to other countries with different cultures and socio-economic characteristics. In view of the global nature of COVID-19, future studies should include a broader sample. 7. Conclusions This study found that gender, geographic location, perceived stress, wishful thinking and empathetic responding are predictors of COVID-19 infection control practices. These findings should be considered in the current situation or in models of potential future pandemics. This study found that male university students tended to comply less with social distancing. The development of public health measures should recognise the importance of gender differences. Relevant government departments should tailor public health measures to local needs. Our study revealed that university students displayed moderate levels of stress in the face of the pandemic. Healthcare providers and educators should be aware that wishful thinking and empathetic responding are coping strategies this demographic uses to preserve their psychological well-being during a pandemic. Therefore, counselling services should emphasise reassurance and empathy; additional emotional support should be provided to alleviate anxieties. This study also revealed factors related to noncompliance with COVID-19 infection control practices. Given the global effects of COVID-19 on health, social functioning and economic stability, strategies addressing noncompliance with public health measures are critical to mitigate further transmission. Acknowledgments The authors acknowledged the students who participated in this study and a special thanks is extended to Liangying Chen for her support in data collection. Author Contributions All authors have contributed significantly where W.L.S.C. conceived of the study, participated in its design and coordination and drafted the manuscript; E.W.Y.K. participated in its design and acquisition of data, and revising critically the manuscript; R.L.T.L. participated in analysis and interpretation of data, and revising critically the manuscript; A.C.Y.T. participated in its design and acquisition of data, revising critically the manuscript. L.L.K.W. participated in analysis and interpretation of data, funding application and revising critically 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 Ethics Committee of Tung Wah College (REC2020056) and Putian University (2020-42). Informed Consent Statement Participants were informed about the study and their rights before beginning the survey. Consent for the study was implied by returning the completed anonymous survey. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. ijerph-19-05327-t001_Table 1 Table 1 Demographic characteristics of the participants and study variables by geographical location. Hong Kong Fujian Total (n = 531) (n = 3861) (n = 4392) n (%)/M (SD) p-Value Age 21.09 (2.71) 20.45 (1.47) 20.5 (1.68) <0.001 a *** Gender <0.001 b *** Female 390 (73.4) 3202 (82.9) 3592 (81.8) Male 141 (26.6) 659 (17.1) 800 (18.2) Academic level of the study programme <0.001 b *** Diploma 3 (0.6) 0 (0.0) 3 (0.1) Higher Diploma 93 (17.5) 0 (0.0) 93 (2.1) Associate Degree 3 (0.6) 1380 (35.7) 1383 (31.5) Bachelor Degree 432 (81.4) 2481 (64.3) 2913 (66.3) Study programme <0.001 b *** Nursing 397 (74.8) 2099 (54.4) 2496 (56.8) Engineering 0 (0.0) 391 (10.1) 391 (8.9) Commerce 0 (0.0) 293 (7.6) 293 (6.7) Medical Science 23 (4.3) 242 (6.3) 265 (6.0) Management studies 2 (0.4) 204 (5.3) 206 (4.7) Arts 0 (0.0) 142 (3.7) 142 (3.2) Science 0 (0.0) 137 (3.5) 137 (3.1) Early Childhood Education 9 (1.7) 113 (2.9) 122 (2.8) Medical Laboratory Science 22 (4.1) 48 (1.2) 70 (1.6) Liberal Arts 0 (0.0) 65 (1.7) 65 (1.5) Chinese Medicine 0 (0.0) 48 (1.2) 48 (1.1) Radiation Therapy 11 (2.1) 21 (0.5) 32 (0.7) Pharmacy 0 (0.0) 28 (0.7) 28 (0.6) Health Science 21 (4.0) 0 (0.0) 21 (0.5) Occupational Therapy 18 (3.4) 0 (0.0) 18 (0.4) Physiotherapy 14 (2.6) 0 (0.0) 14 (0.3) Gerontology 7 (1.3) 0 (0.0) 7 (0.2) Psychology 7 (1.3) 0 (0.0) 7 (0.2) Others 0 (0.0) 30 (0.8) 30 (0.7) Year of study <0.001 b *** Year 1 162 (30.5) 1906 (49.4) 2068 (47.0) Year 2 122 (23.0) 1038 (26.9) 1160 (26.0) Year 3 134 (24.7) 737 (19.1) 868 (20.0) Year 4 72 (13.6) 159 (4.1) 231 (5.0) Year 5 43 (8.1) 21 (0.5) 64 (1.0) Clinical experience <0.001 b *** No clinical experience 139 (26.2) 266 (6.9) 3328 (75.8) Less than 12 weeks 158 (29.8) 501 (13.0) 405 (9.2) More than 12 weeks 234 (44.1) 3094 (80.1) 659 (15.0) Study variables Perceived threat (PT) 15.65 (3.12) 11.26 (2.55) 11.79 (2.99) <0.001 a *** Perceived stress (PSS) 21.42 (5.09) 19.30 (4.58) 19.55 (4.69) <0.001 a *** Coping response Wishful thinking (WIS) 9.57 (2.11) 9.37 (1.59) 9.40 (1.67) 0.036 a * Empathetic responding (EMP) 17.88 (3.85) 18.54 (2.65) 18.46 (2.83) <0.001 a *** Social distancing (SoD) Avoiding public places (APP) 41.57 (6.28) 43.44 (8.24) 43.22 (8.05) <0.001 a *** Avoiding people (AP) 35.99 (7.95) 37.62 (7.46) 37.43 (7.54) <0.001 a *** Personal precautionary measures (PPM) 31.89 (4.72) 33.41 (5.21) 33.23 (5.18) <0.001 a *** COVID-19 infection control practices (ICP) 36.49 (4.81) 39.16 (5.61) 37.96 (5.55) <0.001 a *** a Independent t-test; b Chi-square test; * p < 0.05.; *** p < 0.001; M = mean; SD = standard deviation. ijerph-19-05327-t002_Table 2 Table 2 Study variables by programme, gender, and by gender per geographical location. Healthcare Programme Non-Healthcare Programme Total (n = 2706) (n = 1686) (n = 4392) M (SD) p-Value a Perceived threat (PT) 11.98 (3.13) 11.49 (2.73) 11.79 (2.99) <0.001 Perceived stress (PSS) 19.58 (4.64) 19.51 (4.78) 19.55 (4.69) 0.604 Coping response Wishful thinking (WIS) 9.40 (1.68) 9.38 (1.64) 9.40 (1.67) 0.718 Empathetic responding (EMP) 18.45 (2.85) 18.48 (2.79) 18.46 (2.83) 0.708 Social distancing (SoD) Avoiding public places (APP) 43.28 (8.18) 43.11(7.84) 43.22 (8.05) 0.488 Avoiding people (AP) 37.76 (7.48) 36.89 (7.60) 37.43 (7.54) <0.001 Personal precautionary measures (PPM) 33.41 (5.04) 32.93 (5.38) 33.23 (5.18) 0.003 COVID-19 infection control practices (ICP) 38.15 (5.52) 37.64 (5.58) 37.96 (5.55) 0.003 Male Female Total (n = 800) (n = 3592) (n = 4392) M (SD) p-Value a Perceived threat (PT) 11.81 (3.43) 11.79 (2.89) 11.79 (2.99) 0.873 Perceived stress (PSS) 19.20 (5.01) 19.63 (4.62) 19.55 (4.69) 0.024 Coping response Wishful thinking (WIS) 9.26 (1.89) 9.42 (1.61) 9.40 (1.67) 0.026 Empathetic responding (EMP) 18.48 (3.35) 18.46 (2.70) 18.46 (2.83) 0.886 Social distancing (SoD) Avoiding public places (APP) 41.86 (8.70) 43.52 (7.87) 43.22 (8.05) <0.001 Avoiding people (AP) 36.00 (8.36) 37.74 (7.30) 37.43 (7.54) <0.001 Personal precautionary measures (PPM) 32.99 (6.00) 33.28 (4.97) 33.23 (5.18) 0.207 COVID-19 infection control practices (ICP) 37.99 (6.59) 39.28 (5.57) 37.96 (5.55) <0.001 Hong Kong Fujian (n = 531) (n = 3861) Male Female Male Female Total (n = 141) (n = 390) (n = 659) (n = 3202) (n = 4392) M (SD) p-Value a M (SD) p-Value a Perceived threat (PT) 15.57 (3.30) 15.67 (3.06) 0.745 11.00 (2.87) 11.31 (2.48) 0.010 11.79 (2.99) Perceived stress (PSS) 20.16 (5.55) 21.88 (4.83) 0.001 18.99 (4.86) 19.36 (4.51) 0.074 19.55 (4.69) Coping response Wishful thinking (WIS) 8.88 (2.35) 9.82 (1.96) <0.001 9.35 (1.76) 9.38 (1.56) 0.682 9.40 (1.66) Empathetic responding (EMP) 17.62 (3.94) 17.97 (3.81) 0.362 18.66 (3.18) 18.50 (2.73) 0.285 18.46 (2.83) Social distancing (SoD) Avoiding public places (APP) 41.06 (7.35) 41.76 (5.85) 0.305 42.04 (8.96) 43.73 (8.06) <0.001 43.23 (8.04) Avoiding people (AP) 35.46 (8.65) 36.19 (7.69) 0.353 36.12 (8.30) 37.93 (7.23) <0.001 37.43 (7.53) Personal precautionary measures (PPM) 31.84 (5.53) 31.91 (4.39) 0.883 33.24 (6.07) 37.93 (7.24) 0.413 33.23 (5.18) COVID-19 infection control practices (ICP) 36.12 (5.70) 36.62 (4.44) 0.345 37.13 (6.44) 38.37 (5.40) <0.001 37.96 (5.54) a Independent t-test; M = mean; SD = standard deviation. ijerph-19-05327-t003_Table 3 Table 3 Correlation matrix between perceived threat, perceived stress, coping responses and COVID-19 infection control practices in all participants. Total Sample 2 3 4 5 6 7 8 1. Perceived threat (PT) 0.273 *** 0.086 *** 0.000 −0.025 −0.001 −0.067 *** −0.033 * 2. Perceived stress (PSS) 0.133 *** −0.034 * −0.035 * −0.014 −0.122 *** −0.061 *** 3. Wishful thinking (WIS) 0.353 *** 0.111 *** 0.163 *** 0.146 *** 0.173 *** 4. Empathetic responding (EMP) 0.170 *** 0.168 *** 0.281 *** 0.246 *** 5. Avoiding public places (APP) 0.553 *** 0.348 *** 0.842 *** 6. Avoiding people (AP) 0.416 *** 0.850 *** 7. Personal precautionary measures (PPM) 0.668 *** 8. COVID-19 infection control practices (ICP) Correlation Matrix by Gender 1 2 3 4 5 6 7 8 1. Perceived threat (PT) - 0.273 *** 0.097 *** 0.008 −0.034 * −0.009 −0.075 *** −0.044 ** 2. Perceived stress (PSS) 0.277 *** - 0.139 *** −0.030 −0.033 * −0.014 −0.107 *** −0.062 *** 3. Wishful thinking (WIS) 0.050 0.105 ** - 0.357 *** 0.085 *** 0.151 *** 0.144 *** 0.156 *** 4. Empathetic responding (EMP) −0.027 −0.044 0.342 *** - 0.149 *** 0.141 *** 0.269 *** 0.221 *** 5. Avoiding public places (APP) 0.006 −0.057 0.188 *** 0.243 *** - 536 *** 0.318 *** 0.835 *** 6. Avoiding people (AP) 0.024 −0.029 0.193 *** 0.259 *** 0.598 *** - 0.406 *** 0.846 *** 7. Personal precautionary measures (PPM) −0.041 −0.109 ** 0.148 *** 0.319 *** 0.445 *** 0.448 *** - 0.653 *** 8. COVID-19 infection control practices (ICP) 0.000 −0.073 * 0.218 *** 0.326 *** 0.863 *** 0.856 *** 0.718 *** - Correlations for male are below the diagonal, and correlations for female are above the diagonal. * p < 0.05; ** p < 0.01; *** p < 0.001. ijerph-19-05327-t004_Table 4 Table 4 Predictors of COVID-19 infection control practices adherence using multiple hierarchical regression. Step 1 Step 2 Step 3 B β B β B β Age −0.036 −0.011 −0.041 −0.013 −0.006 −0.002 Gender −0.971 −0.068 *** −0.996 −0.069 *** −0.993 −0.069 *** Institution 0.329 0.039 0.357 0.042 0.289 0.034 Level of study programme −0.133 −0.016 −0.116 −0.014 −0.142 −0.017 Studying programme 0.018 0.011 0.016 0.010 0.024 0.015 Year of study 0.083 0.015 0.093 0.017 0.070 0.013 Clinical experience −0.180 −0.021 −0.164 −0.019 −0.137 −0.016 Marital status −2.409 −0.019 −2.259 −0.017 −1.379 −0.011 Living condition 0.843 0.019 0.773 0.018 0.836 0.019 Geographical location −1.101 −0.065 ** −1.157 −0.068 ** −0.872 −0.051 * Perceived threat (PT) 0.051 0.033 0.019 0.010 Perceived stress (PSS) −0.067 −0.057 *** −0.074 −0.063 *** Wishful thinking (WIS) 0.364 0.109 *** Empathetic responding (EMP) 0.391 0.199 ***    R2 0.019 0.022 0.089    Adjusted R2 0.017 0.019 0.086    R2 change 0.019 0.003 0.067    F 8.483 *** 8.251 *** 30.407 *** Step 1: df1 = 10, df2 = 4380; Step 2: df1 = 12, df2 = 4378; Step 3: df1 = 14, df2 = 4376; B = standardized regression estimates; β = unstandardized regression estimate; Gender: value 1 = male; 0 = female; Marital Status: value 1 = married; 0 = unmarried; Geographical location: value 1 = Hong Kong; Fujian = 0; * p < 0.05; ** p < 0.01; *** p < 0.001. 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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093504 sensors-22-03504 Article Rainfall Prediction System Using Machine Learning Fusion for Smart Cities https://orcid.org/0000-0001-6696-277X Rahman Atta-ur 1† Abbas Sagheer 2† https://orcid.org/0000-0002-7521-5757 Gollapalli Mohammed 3 Ahmed Rashad 4 Aftab Shabib 25 https://orcid.org/0000-0002-5240-0984 Ahmad Munir 2 Khan Muhammad Adnan 6* https://orcid.org/0000-0003-4842-0613 Mosavi Amir 789 Marhic Bruno Academic Editor Delahoche Laurent Academic Editor 1 Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia; aaurrahman@iau.edu.sa 2 School of Computer Science, National College of Business Administration and Economics, Lahore 54000, Pakistan; dr.sagheer@ncbae.edu.pk (S.A.); shabib.aftab@ncbae.edu.pk (S.A.); munir@ncbae.edu.pk (M.A.) 3 Department of Computer Information Systems, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia; magollapalli@iau.edu.sa 4 ICS Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia; othmanr@kfupm.edu.sa 5 Department of Computer Science, Virtual University of Pakistan, Lahore 54000, Pakistan 6 Department of Software, Gachon University, Seongnam 13120, Korea 7 John von Neumann Faculty of Informatics, Obuda University, 1034 Budapest, Hungary; mosavi.amirhosein@uni-nke.hu 8 Institute of Information Engineering, Automation and Mathematics, Slovak University of Technology in Bratislava, 81107 Bratislava, Slovakia 9 Faculty of Civil Engineering, TU-Dresden, 01062 Dresden, Germany * Correspondence: adnan@gachon.ac.kr † These authors contributed equally to this work. 04 5 2022 5 2022 22 9 350408 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/). Precipitation in any form—such as rain, snow, and hail—can affect day-to-day outdoor activities. Rainfall prediction is one of the challenging tasks in weather forecasting process. Accurate rainfall prediction is now more difficult than before due to the extreme climate variations. Machine learning techniques can predict rainfall by extracting hidden patterns from historical weather data. Selection of an appropriate classification technique for prediction is a difficult job. This research proposes a novel real-time rainfall prediction system for smart cities using a machine learning fusion technique. The proposed framework uses four widely used supervised machine learning techniques, i.e., decision tree, Naïve Bayes, K-nearest neighbors, and support vector machines. For effective prediction of rainfall, the technique of fuzzy logic is incorporated in the framework to integrate the predictive accuracies of the machine learning techniques, also known as fusion. For prediction, 12 years of historical weather data (2005 to 2017) for the city of Lahore is considered. Pre-processing tasks such as cleaning and normalization were performed on the dataset before the classification process. The results reflect that the proposed machine learning fusion-based framework outperforms other models. rainfall rainfall prediction machine learning data fusion fuzzy system smart cities big data hydrological model information systems precipitation This research received no external funding. ==== Body pmc1. Introduction Knowledge extraction from time series data has become a widely explored research area [1,2]. Data which are collected with time stamps in a specific pattern are called time series data [3,4,5]. This type of time-oriented data is collected with a specific time interval, such as on an hourly, daily, or weekly basis. Time series data can be utilized effectively to make predictions in various areas and domains, including foreign currency rates, stock market trends, energy consumption estimations, and climate change. Machine learning and data mining techniques can be utilized to extract the hidden patterns from historical data in order to forecast the future trend [1,2,5,6]. Weather forecasting on the basis of historical data is a complex but very beneficial task [7] which comes with several problems that need to be solved in order to achieve optimal results. Weather-related data consists of various attributes or features such as temperature, pressure, humidity, and wind speed. Machine learning techniques tend to predict future weather conditions by using hidden patterns and relations among the features of historical weather data [2]. Precipitation prediction is one of the crucial stages of the weather forecasting process. A smart city is a place where all the community elements, including people and devices, are connected with advanced technologies. In these urban areas, data are collected from citizens as well as from buildings through sensors and electronic devices; the data is then used to manage resources, services, and assets effectively and efficiently. In such technologically advanced cities, data are processed, analyzed, and then used to monitor and manage various systems and activities; as such, data are considered to be very important. The data collected from different sources in smart cities are ultimately used in various automatic systems, including traffic and transportation systems, water supply networks, power plants, waste collection and disposal systems, crime detection systems, education systems, and other community services. The use of machine learning and artificial intelligence techniques is considered to be a crucial element in the services and products of smart cities. Weather forecasting is necessary for the citizens of smart cities so that people can plan their activities according to the predicted weather. In particular, accurate and timely rainfall prediction in smart cities can be quite helpful for arranging planning and security measures in advance for flight operations, agricultural tasks, water reservoir systems, and constructions and transportation activities [2,8,9]. A red alert in advance in the case of extreme rainfall can save the citizens of smart cities from potentially life-threatening situations. This research presents a rainfall prediction framework using a machine learning fusion technique for smart cities. The real-time weather data are collected from multiple sensors located in various vital locations of the city. Four classification techniques are used in the proposed framework for fusion, including Decision Tree (DT), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM) [10,11,12]. To achieve high accuracy, a fuzzy logic-based layer is included in the proposed framework, which integrates the predictive performance of used classification techniques. These algorithms belong to a supervised class of data mining, in which training is required first with pre-classified data, where classification rules are built and then applied to the input dataset (test data) [13,14]. A weather forecasting website [15] is used to extract the relevant data. The extracted data spans 12 years, from December 2005 to November 2017, and consists of various attributes, including maximum temperature, minimum temperature, and relative humidity. The dataset used in this research has already been used by us in [1]. In this research, a framework consisting of multiple stages has been developed for effective predictions. The framework begins with a pre-processing phase which deals with the cleaning and normalization of data [16,17]. The cleaning process deals with the outliers and missing values, whilst the normalization process keeps the feature values within a particular range. The cleaned and normalized values then go to the classification stage where DT, NB, KNN, and SVM are tuned and then used for prediction. The predicted results from these machine learning techniques are given to fusion layer as input, where fuzzy logic-based rules are used for final prediction. The fused model is then stored in the cloud for prediction using real-time weather data. 2. Literature Review Improving the accuracy of machine learning techniques on weather forecasting has been the primary concern of many researchers over the last two decades. Some of the related studies are discussed here. In [18], researchers presented an ANN-based technique to predict atmospheric conditions. The dataset used for prediction consisted of various weather attributes, e.g., humidity, temperature, and wind speed. The proposed technique integrated the Back Propagation Network and Hopfield Network in such a way that the output of BPN is given to the HN as input. This technique works by exploring the non-linear relationship between historical weather attributes. In [19], researchers used ANN to predict the monthly average rainfall of monsoon weather in India. A dataset covering a period of 8 months each year was used for prediction. The selected months were considered to have a high probability rainfall. Three types of different networks were used for performance analysis: Feed Forward Back Propagation, Layer Recurrent, and Cascaded Feed Forward Back Propagation. According to the results, Feed Forward Back Propagation outperformed the others. In [20], researchers proposed a rainfall prediction technique which used genetic algorithms for feature selection and Naïve Bayes as a predictive algorithm. The proposed solution had two steps: the first step deals with the prediction of rainfall (whether it will rain or not), and the second step classifies the rainfall as light, moderate, or strong. In [21], researchers presented a framework consisting of deep neural networks to predict weather changes over the next 24 h. For prediction, they used a dataset covering 30 years, from 1983 to 2012, obtained from Hong Kong Observatory (HKO). The dataset consisted of four weather attributes: temperature, dew point, mean sea level pressure, and wind speed. According to the results, DNNs provided a good feature space for weather datasets. In [22], researchers presented a new pre-processing technique by using moving average and singular spectrum analysis. The proposed approach can be applied on the classes of training data in order to transform it into low, medium, and high categories. Prediction was performed using an Artificial Neural Network (ANN). Two daily rainfall datasets—Zhenshui and Da’ninghe water sheds in China—were used for experiment. In [23], researchers proposed a hybrid method for rainfall forecasting by integrating feature extraction and prediction techniques. The dataset used for the experiment was obtained from the National Oceanic and Atmospheric Administration (NOAA); it spanned more than 50 years and consisted of various weather features such as humidity, pressure, temperature, and wind speed. A Neural Network was used to classify the instances into low, medium, and high classes based on a pre-defined training set. In [24], researchers presented a data-intensive model for rainfall prediction using a Bayesian modeling approach. For the experiment, the dataset was collected from the Indian Meteorological Department, and from 36 attributes, the 7 most relevant attributes were selected. Before the prediction, pre-processing and transformation steps were performed for smooth processing. The proposed approach showed good accuracy for rainfall prediction, using moderate computing resources compared to meteorological centers using high-performance computing power for weather predictions. In [25], researchers compared different machine learning techniques for the prediction of rainfall in Malaysia. The mining techniques included Naïve Bayes, Neural Network, SVM, Decision Tree, and Random Forest. Pre-processing was performed on the dataset to fill the missing values and to remove the noise before classification. Random Forest outperformed the others; it correctly classified a large number of instances with a small portion of training data. In [26], the technique of Clusterwise Linear Regression was employed, which involved integrating the clustering and regression methods. The proposed CLR technique predicted the monthly rainfall in Victoria, Australia. The used dataset was obtained from eight geographically diverse weather stations, spanning from 1889 to 2014. The performance was compared with other published techniques; it was shown that in most of the locations, CLR performed better than others. In [27], researchers compared “Markov Chain extended with rainfall prediction” with other widely used data mining techniques, including Radial Basis, Neural Networks, Genetic Programming, Support Vector Regression, M5 Rules, k-Nearest Neighbors, and M5 Model trees. A dataset obtained from 42 cities was used for the experiment. The results showed that the Markov Chain technique can be outperformed by machine learning techniques. The correlation between weather-related attributes and accuracy has also been noted. In [28], two forecasting models were developed for rainfall prediction: the first predicted for 1 month ahead, whilst the second predicted for 2 months ahead by using ANN. A dataset from several locations of north India was used for the experiment. The model integrated the Feed Forward Neural Network with Back Propagation technique, along with the Levenberg–Marquardt training function. The performance was analyzed in terms of Mean Square Error and Magnitude of Relative Error. According to the results, the 1-month ahead forecasting model outperformed the 2-month model. In [29], researchers proposed a framework named the Wavelet Neural Network (WNN) to predict the rainfall. The proposed solution integrated ANN with the wavelet technique. Both models (ANN and WNN) were used for prediction by using rainfall historical data from the Darjeeling rain gauge station, situated in West Bengal, India. According to the results, WNN outperformed ANN. In [30], researchers presented an SVM-based application for the prediction of weather. A time series dataset related to the past n days from a location was analyzed, and then the maximum temperature of that location for the next day was predicted. By using optimal values of the kernel function, the performance of the proposed application was evaluated and found to outperform Multi-Layer Perceptron (MLP), trained with a back-propagation algorithm. To train the SVM, a nonlinear regression method was found to be suitable. In [31], researchers presented an advanced statistical technique for solar power forecasting based on an artificial intelligence approach. The proposed technique requires several features as input, such as past power measurements and meteorologically related forecasts. The required metrological data included solar irradiance, relative humidity, and temperature. A SOM (Self organized map) was trained to classify the local weather 24 h in advance with the help of online meteorological services. The proposed method was considered to be suitable for the forecasting of 24 h ahead power output of a PV (photovoltaic) system, as well as for trading in electricity markets of PV power system operators. In [32], researchers presented the technique of modular-based Support Vector Machine (SVM) to predict and simulate rainfall prediction. The proposed technique consisted of several steps, such as the generation of training sets with the bagging sampling technique, training of SVM kernel function, selection of SVM combination members with the PLS (Partial Least Square) technique, and production of ν–SVM. The proposed technique was used for monthly rainfall prediction in Guangxi, China and outperformed other models. Table 1 summarizes the previously published related work. Previously, most researchers used supervised machine learning classifiers in order to predict rainfall by exploring hidden patterns in historical data. The researchers mostly used more than one technique in the proposed frameworks: one for feature selection and one for classification and prediction. Rainfall forecasting using time series weather data has also been widely explored by researchers. This research proposes a framework for rainfall prediction, particularly for smart cities, where real-time weather data is continuously collected from specific weather sensors. Moreover, to increase the performance, the predictive accuracy of four classifiers (DT, NB, KNN, and SVM) is integrated with the help of fuzzy logic. 3. Materials and Methods This research purposes a rainfall prediction framework (Figure 1) using a machine learning fusion technique for smart cities. The proposed framework mainly consists of two layers: training and testing. Both of these layers further include multiple stages. The first stage of the training layer deals with the extraction of weather attributes from technologically advanced sensors in the smart city. However, in this research, we have extracted a real-time pre-labeled dataset of rainfall prediction from a weather forecasting website [15] of the city of Lahore. The dataset consists of 25,919 instances and 11 features, out of which 10 features are independent and 1 is dependent (output class). The data pre-processing stage consists of three activities: (1) cleaning, (2) normalization, and (3) splitting. The data cleaning process aims to remove the missing values in the dataset by using the technique of mean imputation. The normalization technique brings the attribute values within a particular range. These cleaning and normalization activities aid the classifiers in obtaining maximum accuracy. In the third activity of the pre-processing stage, cleaned and normalized data is divided into two subsets: training data and test data, with a 70:30 ratio of class split rule. After performing the tasks of pre-processing activities, the dataset is ready for the stage of classification, where training and test datasets are both given as input to four classification techniques (DT, NB, KNN, and SVM). All of these algorithms are optimized iteratively during training and testing in order to achieve higher accuracy. After the classification process, the trained models are given as input to the fuzzy layer, which deals with the development and implementation of fuzzy logic for final prediction. The fused proposed prediction model after training is stored in cloud storage so that it can be used for later prediction by using real-time testing data. Conditions (if–then rules) used in the fuzzy logic of the proposed framework are given below:IF (DT is yes and NB is yes and KNN is yes and SVM is yes) THEN (Rainfall is yes) IF (DT is yes and NB is yes and KNN is yes and SVM is no) THEN (Rainfall is yes) IF (DT is yes and NB is yes and KNN is no and SVM is yes) THEN (Rainfall is yes) IF (DT is yes and NB is yes and KNN is no and SVM is no) THEN (Rainfall is yes) IF (DT is yes and NB is no and KNN is yes and SVM is yes) THEN (Rainfall is yes) IF (DT is yes and NB is no and KNN is yes and SVM is no) THEN (Rainfall is yes) IF (DT is yes and NB is no and KNN is no and SVM is yes) THEN (Rainfall is yes) IF (DT is yes and NB is no and KNN is no and SVM is no) THEN (Rainfall is no) IF (DT is no and NB is yes and KNN is yes and SVM is yes) THEN (Rainfall is yes) IF (DT is no and NB is yes and KNN is yes and SVM is no) THEN (Rainfall is no) IF (DT is no and NB is yes and KNN is no and SVM is yes) THEN (Rainfall is no) IF (DT is no and NB is yes and KNN is no and SVM is no) THEN (Rainfall is no) IF (DT is no and NB is no and KNN is yes and SVM is yes) THEN (Rainfall is no) IF (DT is no and NB is no and KNN is yes and SVM is no) THEN (Rainfall is no) IF (DT is no and NB is no and KNN is no and SVM is yes) THEN (Rainfall is no) IF (DT is no and NB is no and KNN is no and SVM is no) THEN (Rainfall is no) It can be observed from the developed fuzzy rules that if any of three classification techniques predict one result (either rain or no rain), the same result will be predicted by the proposed fused technique. Figure 2 reflects the proposed fused technique rule surface of rainfall prediction on the basis of SVM and DT. If both of these classification techniques predict ‘rainfall = yes’, then the result of the fused machine learning technique will also be ‘rainfall = yes’, and if both of these techniques predict ‘rainfall = no’, then the proposed technique will also predict ‘rainfall = no’. It is shown in Figure 3 that if NB, KNN, and SVM predict ‘rainfall = yes’, then the proposed fused technique will also predict ‘rainfall = yes’. Figure 4 shows that if DT and NB predict ‘rainfall = no’, even if KNN and SVM predict ‘rainfall = yes’, then the result of the proposed technique will still be ‘rainfall = no’. The membership functions of the proposed fuzzy rules are shown in Table 2. The testing layer of the proposed framework is responsible for predicting rainfall by using real-time weather data. The fuzzy trained model from the cloud is used for this purpose, which takes the input of real-time weather data as test data. 4. Results and Discussion The proposed framework is implemented on a real-time rainfall dataset of the city of Lahore, extracted from a weather forecasting website [15]. The dataset used in this research spans over 12 years (2005 to 2017) and consists of 25,919 instances and 11 features (Table 3). First, 10 features are the independent features, which are given as input to the proposed framework in order to predict the 11th feature, which is the output class (dependent feature). The output class indicates whether there will be rainfall or not. If the predicted feature has a value of 1, then will be a rainy day; if the value is 0, then it will be no rainfall. The dataset is divided into two parts: 70% of the data is reserved for training (18,143), and 30% of the data is reserved for testing (7776). The activities of the pre-processing stage, including cleaning and normalization, are performed on the rainfall dataset before the classification stage. To predict, four classification techniques are used: DT, NB, KNN, and SVM. These classification techniques are optimized iteratively until maximum accuracy is achieved. The statistical measures used to analyze the predictive performance of the proposed fused framework as well as of other classification techniques are discussed below. In the formulas given below, OR0 represents predicted negatives, OR1 represents predicted positives, ER0 represents expected negatives, and ER1 represents expected positives. Miss rate is the probability of true positives and true negatives being missed in the experiment [1,10,34]. (1) Miss rate=OR1/ER0+ OR0/ER1ER0+ ER1 Accuracy reflects the number of correctly classified instances out of total instances [10,13,34]. (2) Accuracy=OR0/ER0+ OR1/ER1ER0+ ER1 The positive and negative predictive values are the proportions of positive and negative results to the true positive and true negative results, respectively [1,34]. (3) Positive Prediction Value=OR1/ER1OR1/ER1+ OR0/ER1 (4) Negative Prediction Value=OR0/ER0OR0/ER0+ OR1/ER0 (5) Specificity=OR0/ER0OR0/ER0+ OR0/ER1 Sensitivity reflects how well the proposed model can detect positive instances [10,34]. (6) Sensitivity=OR1/ER1OR1/ER0+ OR1/ER1 The false positive rate reflects the ratio between false positives and the total number of instances which are actually negative [34]. (7) False Positive Ratio=1−Specificity (8) False Negative Ratio=1−Sensitivity (9) Likelihood Ratio Positive=Sensitivity1−Specificity (10) Likelihood Ratio Negative=1− SensitivitySpecificity First, the DT is used for the prediction of rainfall. Then, 70% of the dataset (consisting of 18,143 instances) is used for training; the remaining 30% of the dataset (consisting of 7776 instances) is used for testing. From the 18,143 instances reserved for training, 16,577 were negative and 1566 were positive. During the training with DT, 16,456 instances from 16577 were classified as negative, and 372 instances were classified as positive from 1566 instances. After analyzing the achieved results compared with expected results during the training process (Table 4), it is calculated that we achieved an accuracy of 92.8% and a miss rate of 7.2%. On the other hand, during the testing process of DT, 7036 records were classified as negative from 7105, and 155 records were classified as positive from 671 records (as shown in Table 5). The accuracy achieved in DT testing was 92.48%, with a miss rate of 7.52%. During the training with NB, 16,176 instances were classified as negative from 16,577 instances, and 280 instances were classified as positive from 1566 instances (as shown in Table 6). We achieved an accuracy of 90.7% and a miss rate of 9.3% for training with NB. During testing with NB, 6937 instances were classified as negative from 7105 instances, and 116 instances were classified as positive from 671 instances (as shown in Table 7). The accuracy achieved for testing with NB was 90.7%, with a miss rate of 9.3%, when we compared the expected output with the output results. During the training process with KNN, 16,481 instances were classified as negative from 16577 instances, and 316 instances were classified as positive from 1566 instances. From the comparison of expected output with the achieved output in training with KNN (Table 8), it can be observed that we achieved an accuracy of 92.6% and a miss rate of 7.4%. During the testing with KNN, 7050 instances were classified as negative from 7105 instances, and 143 instances were classified as positive from 671 instances (as shown in Table 9). After analyzing the expected output with the achieved output, we determined that we obtained an accuracy of 92.5% and a miss rate of 7.5% for the testing process with KNN. During the process of training with SVM, 16544 instances were classified as negative from 16,577 instances, and 182 instances were classified as positive from 1566 instances (as shown in Table 10). While performing a comparative analysis of expected output result with the achieved output result, we determined that we obtained an accuracy of 92.2% in training, with a miss rate of 7.8%. During testing, 7086 instances were classified as negative from 7105 instances, and 75 instances were classified as positive from 671 instances (as shown in Table 11). In the testing process with SVM, we achieved an accuracy of 92.1% and a miss rate of 7.9%. Finally, all of the instances from the testing data are given to the fuzzy system as input for the final prediction. The input to the fuzzy system includes test data along with the output class, and the predictions of used classifiers. The proposed fused machine learning-based fuzzy system classified 7063 instances as negative from 7105 instances, and 228 instances as positive from 671 instances (as shown in Table 12). While comparing the output result of the fuzzy system with the expected result, we determined that we achieved an accuracy of 94% and a miss rate of 6%. Table 13 displays detailed results for training and test data of all of the used classification techniques (DT, NB, KNN, SVM) and the proposed fused machine learning technique. It can be observed that the proposed fused technique performed well compared to all four of the used machine learning techniques. Table 14 shows a comparative analysis of the proposed fused machine learning technique with the previously published techniques for rainfall prediction in terms of accuracy and miss rate. The proposed fused model is compared with KNN [6], Naïve Bayes [6], CART [6], PRNN [6], Bayesian [24], INBC [5], and DT-SLIQ [33]. It can be seen that the proposed fused model performed better than the other techniques. The proposed machine learning fusion based framework can be incorporated into smart cities for accurate rainfall prediction. The proposed framework will be linked to highly sensitive and technologically advanced weather sensors. These sensors will provide weather data to the system on a continuous basis, which will be used for real-time rainfall prediction. 5. Conclusions Rainfall prediction with maximum accuracy is a challenging task of the weather forecasting process. The use of machine learning techniques has increased the accuracy of rainfall prediction systems by exploring the hidden patterns of historical weather data. A novel and real-time rainfall prediction system is proposed by this research for smart cities by using machine learning fusion. The proposed framework would extract the real-time feature-based weather data from highly sensitive and technologically advanced weather sensors for real-time rainfall prediction. The prediction accuracy of four supervised machine learning techniques are integrated in the proposed framework. The used machine learning techniques are Decision Tree, Naïve Bayes, K-Nearest Neighbors, and Support Vector Machines. The prediction accuracy of the used machine learning techniques are fused using fuzzy logic. For the experiment, 12 years of historical weather data (from 2005 to 2017) for the city of Lahore was extracted from a weather forecasting website, consisting of various weather-related features. To improve the accuracy of classification and prediction, pre-processing activities were performed on the extracted dataset, including cleaning and normalization. The results clearly show the effectiveness of the proposed framework by reflecting the higher accuracy compared to other modern techniques. The proposed machine learning fusion-based rainfall prediction system has one limitation besides the many advantages. If due to any reason, the data which will be used for prediction is compromised, then the prediction cannot be trusted. Any type of malfunction in the weather sensor can also compromise the accuracy of the proposed rainfall prediction system. Therefore, a monitoring system to check the working of weather sensors has also be incorporated along with the information security system, which will ensure the integrity of the data until it is used for prediction. The framework presented in this research will be extended in the future by exploring the fusion of ensemble machine learning techniques on more diverse datasets. Moreover, an appropriate feature selection technique would also be an effective addition to the system, which will ensure cost-effective prediction. Besides rainfall prediction, machine learning fusion will also be used for temperature prediction in order to efficiently utilize clean solar energy. Efforts will be made to incorporate the various flavors of Artificial Neural Networks in the weather forecasting process, such as Multi-Layer Perceptron (MLP) and Long Short-Term Memory (LSTM) networks. Author Contributions A.-u.R., S.A. (Sagheer Abbas) and M.G. collected data from different resources; S.A. (Sagheer Abbas), S.A. (Shabib Aftab) and M.A.K. performed formal analysis and simulation; S.A., R.A., M.A., and A.M. contributed to writing—original draft preparation; M.A.K., R.A., and A.M. contributed to writing—review and editing; M.A.K. and S.A. performed supervision; A.-u.R., M.A. and A.M. drafted pictures and tables; M.A.K., M.G. and A.-u.R. performed revision and improved the quality of the draft. 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 simulation files/data used to support the findings of this study are available from the corresponding author upon request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Proposed framework. Figure 2 Rule surface of proposed fused technique for SVM and DT. Figure 3 Result of proposed framework: rainfall = yes. Figure 4 Result of proposed framework: rainfall = no. sensors-22-03504-t001_Table 1 Table 1 Summary of previous related work. Reference Method Dataset Dataset Duration Accuracy % D. Gupta et al. [6] ANN-based classification model, with 10 hidden layers Public 18 years 82.1 D. Gupta et al. [6] Classification and Regression Tree-based Prediction Public 18 years 80.3 D. Gupta et al. [6] K nearest neighbor-based prediction, with k = 22 Public 18 years 80.7 J. Joseph et al. [23] ANN-based hybrid technique, integrating classification and clustering techniques Private 4 months 87 V.B. Nikam et al. [24] Feature selection-based Bayesian classification model Public 6 months 91 N. Prasad et al. [33] Decision Tree-based supervised learning in quest (SLIQ) Public 14 years 72.3 sensors-22-03504-t002_Table 2 Table 2 Graphical representation of MF. Input/Output Membership Functions Graphical Representation of MF DT=μDTdt μDTydt=maxmin1,0.5−dt0.05,0 μDTndt=maxmindt−0.450.05,1,0 NB=μNBnb μNBynb=maxmin1,0.5−nb0.05,0 μNBnnb=maxminnb−0.450.05,1,0 KNN=knn μKNNyknn=maxmin1,0.5−knn0.05,0 μKNNnknn=maxminknn−0.450.05,1,0 SVM=μSVMsvm μSVMysvm=maxmin1,0.5−svm0.05,0 μSVMnsvm=maxminsvm−0.450.05,1,0 Raining=μRr μRyr=maxmin1,0.5−r0.05,0 μRnr=maxminr−0.450.05,1,0 sensors-22-03504-t003_Table 3 Table 3 Dataset attributes. Attribute Name Attribute Type Measurement Temperature Continuous Degrees Celsius Visibility Continuous Kilometers Dew Point Temperature Continuous Degrees Celsius Atmospheric Pressure (sea level) Continuous Millimeters of Mercury Atmospheric Pressure (weather station) Continuous Millimeters of Mercury Relative Humidity Continuous Percentage Pressure Tendency Continuous Millimeters of Mercury Maximum Temperature Continuous Degrees Celsius Minimum Temperature Continuous Degrees Celsius Mean Wind Speed Continuous Meters per Second sensors-22-03504-t004_Table 4 Table 4 DT Training Results. N = 18,143 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 16,577 (Negative-0) 16456 121 ER1 = 1566 (Positive-1) 1194 372 sensors-22-03504-t005_Table 5 Table 5 DT Testing results. N = 7776 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 7105 (Negative-0) 7036 69 ER1 = 671 (Positive-1) 516 155 sensors-22-03504-t006_Table 6 Table 6 Naïve Bayes training results. N = 18,143 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 16,577 (Negative-0) 16176 401 ER1 = 1566 (Positive-1) 1286 280 sensors-22-03504-t007_Table 7 Table 7 Naïve Bayes testing results. N = 7776 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 7105 (Negative-0) 6937 168 ER1 = 671 (Positive-1) 555 116 sensors-22-03504-t008_Table 8 Table 8 KNN training results. N = 18,143 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 16,577 (Negative-0) 16481 96 ER1 = 1566 (Positive-1) 1250 316 sensors-22-03504-t009_Table 9 Table 9 KNN testing results. N = 7776 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 7105 (Negative-0) 7050 55 ER1 = 671 (Positive-1) 528 143 sensors-22-03504-t010_Table 10 Table 10 SVM training results. N = 18,143 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 16577 (Negative-0) 16544 33 ER1 = 1566 (Positive-1) 1384 182 sensors-22-03504-t011_Table 11 Table 11 SVM testing results. N = 7776 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 7105 (Negative-0) 7086 19 ER1 = 671 (Positive-1) 596 75 sensors-22-03504-t012_Table 12 Table 12 Fused ML testing results. N = 7776 (No of Samples) Output Result (OR0, OR1) INPUT Expected Result (ER0, ER1) OR0 (Negative-0) OR1 (Positive-1) ER0 = 7105 (Negative-0) 7063 42 ER1 = 671 (Positive-1) 443 228 sensors-22-03504-t013_Table 13 Table 13 Results of machine learning algorithms. ML Algorithm Task Specificity Sensitivity False Positive Value False Negative Value Likelihood Ratio Positive Likelihood Ratio Negative Positive Prediction Value Negative Prediction Value Accuracy Miss Rate Decision Tree Training 0.99 0.24 0.00 0.76 32.54 0.77 0.75 0.93 0.91 0.07 Testing 0.99 0.23 0.01 0.77 23.79 0.78 0.69 0.93 0.92 0.07 Naïve Bayes Training 0.98 0.18 0.02 0.82 7.39 0.84 0.41 0.93 0.90 0.09 Testing 0.98 0.17 0.02 0.83 7.31 0.85 0.41 0.93 0.90 0.09 KNN Training 0.99 0.20 0.00 0.80 34.84 0.80 0.77 0.91 0.93 0.07 Testing 0.99 0.21 0.00 0.79 27.53 0.79 0.72 0.93 0.93 0.07 SVM Training 0.99 0.12 0.00 0.88 58.38 0.89 0.85 0.92 0.92 0.08 Testing 0.99 0.11 0.00 0.89 41.80 0.89 0.80 0.92 0.92 0.08 Proposed Fussed ML Testing 0.99 0.34 0.01 0.66 57.48 0.66 0.84 0.94 0.94 0.06 sensors-22-03504-t014_Table 14 Table 14 Comparison of proposed fusion model with previously published approaches. 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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091964 nutrients-14-01964 Article Food Insecurity and the Association between Perceptions and Trust of Food Advertisements and Consumption of Ultra-Processed Foods among U.S. Parents and Adolescents Chiong Reah * https://orcid.org/0000-0002-2549-7741 Figueroa Roger Bean Melanie K. Academic Editor LaRose Jessica G. Academic Editor Division of Nutritional Sciences, College of Human Ecology, Cornell University, Ithaca, NY 14853, USA; rf453@cornell.edu * Correspondence: rrc222@cornell.edu 07 5 2022 5 2022 14 9 196401 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/). Adolescents exposed to food and beverage advertisements (FBAs) typically low in nutrient density can be influenced in their food choices, eating behaviors, and health. This study examines the association between perceptions and trust of FBAs (key predictor) and the outcome of daily consumption of ultra-processed foods (UPFs) in parent-adolescent dyads, with risk of food insecurity as a potential moderator. Cross-sectional data from the Family, Life, Activity, Sun, Health and Eating (FLASHE) study was used to test actor and partner effects using structural equation modeling. The final model was adjusted for parent sex and education level, and effects were compared between dyads at risk of food insecurity (n = 605) and dyads not at risk (n = 1008). In the unadjusted model, actor effects (parent: b = 0.23, p = 0.001; adolescent b = 0.12, p = 0.001) and parent-partner effects were found (b = 0.08, p = 0.004). The final comparative model produced similar results for dyads not at risk of food insecurity (parent actor: b = 0.27, p = 0.001; parent partner: b = 0.10, p = 0.01; adolescent actor: b = 0.11, p = 0.003). For dyads at risk of food insecurity, only actor effects were significant (parent: b = 0.22, p = 0.001; adolescent: b = 0.11, p = 0.013). These findings suggest that parents’ favorability towards FBAs influence parent-adolescent unhealthy food consumption, and that this association is different when accounting for risk of food insecurity. food insecurity food advertisements ultra-processed foods dyadic interdependence the National Cancer Institute (NCI) HHSN261201200039I This study received no external funding. The FLASHE Study was funded by the National Cancer Institute (NCI) under contract number HHSN261201200039I issued to Westat, Inc. ==== Body pmc1. Introduction The growing prevalence of childhood obesity continues to be a significant public health concern. Currently, 13.7 million U.S. children and adolescents are affected by overweight and obesity [1]. Suboptimal diets, which include foods low in nutrient density such as ultra-processed foods (UPFs), are one of the main behavioral risk factors associated with obesity [2]. UPFs can be defined as foods with formulations of ingredients made through a series of industrial processes that require sophisticated equipment designed to create convenient (i.e., ready-to-consume), highly profitable products (i.e., inexpensive, non-perishable, highly marketable), and hyper-palatable products prone to compete with fresh foods [3]. Some examples of UPFs include sugar-sweetened beverages (SSB), such as soda and fruit drinks, packaged snacks, and ready-to-heat food products and reconstituted meat products (i.e., hot dogs). In a randomized controlled study of 20 adults, researchers investigated the effects of an ultra-processed diet versus an unprocessed diet on energy intake and weight status after 2-week periods. Hall et al. concluded that participants who were assigned diets with an energy composition mainly derived from UPFs resulted with an increase in energy intake of 500 calories per day, in addition to an increase in body weight and body fat mass [2]. On the other hand, a diet with energy primarily taken from unprocessed foods showed a decrease in these measures despite both diets having matched nutritional parameters [2]. These findings significantly complement the growing body of research that has linked the prevalence of overweight and obesity to the consumption of UPFs in recent years [4,5,6]. However, Poti, Braga, and Qin’s narrative review on this association has suggested that further studies with stronger designs are needed to differentiate impacts on metabolic outcomes between the method in which the food is made (processing) and the food’s nutritional value [7]. In the U.S., UPFs contribute to over half of the population’s energy intake [8], and has increased over time [9]. Previous studies aimed at adolescent populations have found associations between food advertisements and the increased intake of foods lower in nutrient density [10], such as SSB [11]. In a study by Thai and colleagues [10], adolescents were more likely to consume more of these types of foods and drinks (candies, SSB, potato chips, etc.) if they positively perceived and trusted food advertisements. UPFs, the key outcome in this study, are also low in nutrient density, and have additional implications because they highlight the ways that food is processed. Overall, the impact of food and beverage advertisements (FBAs) on the consumption of UPFs specifically is limited. Furthermore, since UPF consumption is higher among those who have low income [9], it is important to also investigate how food insecurity, or the inconsistent access to sufficient food [12] may disproportionally affect these households when assessing the role of FBAs on the consumption of UPFs. The targeted marketing and positive perceptions and trust towards advertisements promoting foods low in nutrient density such as UPFs among adolescents may continue to reinforce choice and consumption of these types of foods. Not only do FBAs heavily target youth (i.e., through television advertising, product packaging, endorsements), but they directly influence youth food preferences, dietary attitudes, eating behaviors, and consequently, health outcomes [13]. Compared to adults, children and adolescents are more susceptible to branding and food marketing messages conveyed through FBAs [14]. Among U.S. youth, however, adolescents (aged 12–16) are largely more exposed to these advertisements across different outlets (i.e., television, social media) compared to younger children [15]. As the access and use of smartphones, internet, and media increased in recent years amongst U.S. adolescents [16], food marketers have also shifted towards the use of these newer media platforms to communicate, engage, and shape consumer behavior among this age group [17]. High exposure and receptivity to FBAs are associated to adolescent food choices, unhealthy eating behaviors, and weight-related outcomes [18,19,20,21]. Most importantly, a majority of adolescent-targeted FBAs are low in nutrient density (high in fat, sodium, and sugar) and include fast food, sweets, beverages (specifically fruit drinks and soft drinks), and snacks [22]. Furthermore, recent studies have elucidated on family interdependence and the role that parents play in their children’s dietary and health behaviors [23]. According to Scaglioni et al., the family environment determines what food is available for a child or adolescent to consume, and what foods they will try. They also establish dietary habits, such as healthy eating and food preparation. Parents are powerful role models in the family unit, especially during the key developmental stage of adolescence. Ultimately, they shape their children’s patterns and behaviors later on in life [24,25], and help develop their eating routines from a young age [26]. Research, however, remains limited on the influence of FBAs and UPFs consumption in the familial context and on parent-adolescent relationships. As such, it is central to our inquiry to consider how parents’ own favorability towards FBAs and their consumption of UPFs is associated with their adolescent’s own favorability towards FBAs and consumption of UPFs, especially for family units with socioeconomic hardships (i.e., at risk of food insecurity). To address these gaps, the goal of this study is to investigate the perceptions and trust of FBAs on daily consumption of UPFs in parent-adolescent dyads via three aims. The first aim is to examine actor effects of FBAs and daily consumption of UPFs in both parents and adolescents. In other words, the study hypothesizes that parents and adolescents who are more favorable towards FBAs will consume more UPFs daily. The second aim is to examine partner effects of dyadic pairs. It has been suggested that a bidirectional relationship could exist, and that children may also influence their parents eating behaviors [27]; however, we hypothesize that adolescent favorability towards FBAs will not influence parent consumption of UPFs based on the functions of typical family structures and the influence that parents have on their children. The final aim is to examine whether food insecurity acts as a moderator between the association of perception and trust of FBAs and daily servings of UPFs. We hypothesize that the actor and partner effects will vary for dyads who are at risk of food insecurity, and dyads who are not. 2. Materials and Methods 2.1. Data Source The current study adopts a cross-sectional design and draws data from the Family Life, Activity, Sun, Health, and Eating (FLASHE) study. Funded by the National Cancer Institute to collect information on cancer-preventive behaviors, the parent study recruited a demographically representative sample from the Ipsos’ Consumer Opinion Panel, and enrolled a total of 1945 parent or caregiver and adolescent (ages 12–17) dyads between April 2014 and October 2014. Dyads were then randomly assigned to two groups. The first group was a survey-only group where dyads completed an online survey mainly focused on diet and physical activity behaviors and correlates. In addition to completing the same online survey, the second group of parent-adolescent dyads were provided with accelerometers for adolescents to wear. Both groups also completed a demographic questionnaire. Only measures from the diet survey were used for this study. The main study constructs in this study drawn from FLASHE include advertising/media perception, food consumption, risk of food insecurity, and demographic data. A listwise deletion approach was used to address missing data. 2.2. Study Measures 2.2.1. Consumption of UPFs Total daily consumption of UPFs was assessed using the Dietary Screener Questionnaire (DSQ) [28]. Parent and adolescent participants reported the weekly frequency of consumption on the following foods: sweetened fruit drinks, soda, energy drinks, fried potatoes, tacos, heat and serve, processed meat, hamburgers, fried chicken, candy/chocolate, cookies and cakes, and frozen desserts. In total, 12 dietary indicators were chosen by researchers based on the NOVA classification system of UPFs [29]. The response scale ranged from 1 (‘I did not consume [food or beverage] during the past week’) to 6 (‘I consumed [food or beverage] 3 or more times per day during the past week’). In order to develop the composite score, the response scale was recoded to denote daily servings of UPFs, ranging from 0 to 3 daily servings on each indicator. The total amount of servings per day was used as the dependent variable denoting total daily consumption of UPFs. 2.2.2. Perception and Trust of FBAs Perception and trust of FBAs were measured using three 5-point Likert-type items in both parents and adolescents. Individually, participants were asked to think about marketing messages heard or seen through various print, auditory, and digital platforms. Parents and adolescents were prompted with the following statement, “When I see advertisements for food or drinks…” that connected to each of the following connecting statements: (a) “I want to try the advertised foods or drinks,” (b) “I think the advertised foods or drinks will taste good,” and (c) “I trust the messages advertised.” Participants provided a response to each item, ranging from strongly disagree (1) to strongly agree (5). The average score across the three items was used as an independent variable denoting perception and trust of FBAs. In all models, a measurement model was specified for perceptions and trust of FBAs. The Cronbach’s Alpha value for the predictor of perceptions and trust of FBAs is for parents is 0.83 and 0.84 for adolescents. There was also moderate to strong positive cross-factor correlations for both parents (r = 0.55–0.76) and adolescents (r = 0.56–0.76). Since perceptions and trust of FBAs is complex and not directly observable, it was denoted as an exogenous latent variable measured by the 3 survey items as its observed indicators for both parents and adolescents. Residual correlations between the same parent and adolescent items were established to account for factors not depicted in the model [30]. The characterization of perception and trust follows a previous study that also used the same data set and measurements [10]. 2.2.3. Risk of Food Insecurity Food security was measured using two items [31]. Parents were asked to rate how true the following statements were for them and their households in the past year: (a) “We worried whether our food would run out before we got money to buy more,” and (b) “The food that we bought just didn’t last, and we didn’t have money to get more.” Response options included Never True (0), Sometimes True (1), and Often True (2). For either of the statements, values were set to 0 for participants who responded Never True while values for participants who responded Sometimes True or Often True were set to 1. Finally, these values were added together to create a score that captures risk of food insecurity. Participants who had a sum of 0 were labeled as not at risk for experiencing food insecurity, while participants who had a sum of 1 or 2 were labeled at risk for experiencing food insecurity. 2.2.4. Covariates The following variables were considered covariates: sex, age, race, education level, household income, and receipt of food assistance. Parents and adolescents were asked whether they identified as male or female, and to fill in their age. The 4 response options for race were Hispanic, Non-Hispanic Black or African American only, Non-Hispanic White only, or Non-Hispanic. Parents were asked to indicate their education level with 4 response options ranging from less than a high school degree, a high school degree or GED, some college but not a college degree, or a 4-year college degree or higher. Parents were also asked to indicate their combined annual income in their households with 9 response options ranging from $0 to $9999 to $200,000 or more. Lastly, parents were asked to indicate whether they received food assistance. In the final model, only parent sex and parent education level were considered. 2.3. Analytic Plan Descriptive statistics were initially completed to summarize information on parents’ and adolescents’ demographics and key study measures (in the form of average scores with standard deviations). Inter-item correlation (Pearson’s r) and internal consistency (Cronbach’s alpha) between predictor, moderating, and response variables among complete pairs were also measured as a preliminary assessment of associations. In order to test dyadic actor effects (aim 1) and partner effects (aim 2) of perceptions and trust of FBAs and consumption of UPFs, actor–partner interdependence model within a structural equation modeling (SEM) framework was used [32,33]. A multigroup approach was used to compare actor and partner effects between two groups (aim 3) while adjusting for parents’ sex and education level: (1) parents who were at risk of food insecurity, and (2) parents who were not at risk of food insecurity. All values presented are standardized. Model fit, specifically chi-square difference (Δχ2), RMSEA, CFI, SRMR, and AIC, were also assessed [34]. Stata and R statistical software (version 14) was used to conduct analyses. 3. Results 3.1. Demographics and Key Measures A total of 1859 dyads were included in this study, but only 1613 were accounted for in the final model (Figure 1). Among the parent group, a majority were female, non-Hispanic White, and were middle-aged. Most parents attended a college or received a college degree and indicated that they did not receive food assistance; most were not at risk of food insecurity. Table 1 describes the demographic findings in greater detail for both parent and adolescent groups. Descriptive statistics were also conducted on key measures. Overall, parents consumed an average of 3.16 ± 3.18 servings of UPFs daily, while adolescents consumed 4.05 ± 3.80. For the predictor variable of perception and trust of FBAs, the average total score for the parent group was 8.63 ± 3.41 while the average total score for adolescents was 8.97 ± 4.04. When accounting for risk of food insecurity, both daily servings of UPFs and scores of perception and trust of FBAs were higher among parents and adolescents who were at risk compared to those not at risk. A summary of descriptive findings according to risk of food insecurity can be found in Table 2. Several significant positive correlations were found between and across all variables of interest. The most important to note is a moderate positive correlation between parent and adolescent predictor variables as well as parent and adolescent outcome variables. This implies that increases in total daily consumption of UPFs in one group is correlated with increases in the same variable for the other group, r = 0.59 (p = 0.01). Furthermore, an increase in perceptions and trust of FBAs in the parent group is also correlated with an increase in the same variable for adolescents, r = 0.51 (p = 0.01). It seems that parents’ perceptions and trust of FBAs is also positively correlated with the outcome variable in the parent group, r = 0.35 (p = 0.03) as well as the adolescent group, r = 0.26 (p = 0.04). On the other hand, adolescents’ perceptions and trust of FBAs was only significantly correlated with adolescents’ consumption of UPFs, r = 0.38 (p = 0.02), but not parents’ consumption of UPFs, r = 0.16 (p = 0.16). Lastly, both items denoting risk of food insecurity had a strong positive correlation with one another, r = 0.76 (p = 0.01). These correlations are listed in Table 3. 3.2. Measurement Model Two latent variables were developed consisting of 3 observable indicators to reflect the concept of perceptions and trust of FBAs (Figure 2). Due to potential and unknown family influences on responses, residual errors of parent indicators were set to correlate with corresponding adolescent indicators. Overall, the measurement model indicated good fit. Standardized factor loadings and its corresponding R2 values indicate that each item adequately represents perceptions and trust of FBAs for both parents and adolescents. The first two indicators for each model (“I want to try the advertised foods or drinks” and “I think the advertised foods or drinks will taste good”), however, are more reflective of convergent validity than the last indicator (“I trust the messages advertised”). Nevertheless, we proceeded to use this measurement model in the structural equation model. 3.3. Unadjusted Structural Equation Model of Actor (AIM 1) and Partner (AIM 2) Effects The outcome of consumption of UPFs was set as the endogenous variable in the structural equation model, while the predictor of perception and trust of FBAs remained as a latent variable for both parents and adolescents (Figure 3). The assessment of model fit indicated the model was satisfactory. Significant coefficients were found between parents’ perceptions and trust of FBAs and their own consumption of UPFs (β = 0.236, p < 0.001) as well as their adolescents UPF consumption (β = 0.087, p < 0.004). Adolescents’ perceptions and trust of FBAs was also associated with their own consumption of UPFs (β = 0.120, p < 0.000); however, it did not significantly relate to the consumption of UPFs in parents (β = 0.007, p < 0.814), as predicted by our hypothesis. 3.4. Actor–Partner Interdependence Model Accounting for Risk of Food Insecurity (AIM 3) Finally, the structural equation model was tested to include a moderator representing food insecurity. Actor and partner effects were compared between dyads at risk of food insecurity and dyads not at risk of food insecurity (Figure 4), while adjusting for sex and education level of parents. Overall, model fit indices suggest a good fit. For dyads not at risk of food insecurity (n = 1008), findings were similar with findings for Aim 1 and 2. Parents perception and trust of FBAs were significantly associated with consumption of UPFs for both themselves (β = 0.271, p < 0.00) and their adolescents (β = 0.100, p < 0.01). Perception and trust of FBAs for adolescents was also significantly associated with their own UPF consumption (β = 0.115, p < 0.003); however, partner effects for adolescents were not significant (β = −0.018, p < 0.639) for this group. On the other hand, only actor effects for both parents (β = 0.227, p < 0.000) and adolescents (β = 0.118, p < 0.013) were significant for dyads at risk of food insecurity (n = 608). As a whole, the actor and partner relationship between perception and trust of FBAs and UPF consumption in parent-adolescent dyads are different according to food insecurity risk. 4. Discussion The goal of this study was to examine associations between perceptions and trust of FBAs and consumption of UPFs among parent-adolescent dyads using APIM, and the role that risk of food insecurity has in moderating this association. In unadjusted models, we found significant actor effects for both parents and adolescents, and significant parent partner effects. Dyads who were not at risk of food insecurity mimicked these findings; however, only actor effects for both parents and adolescents were significant among dyads who were at risk of food insecurity. Overall, these findings suggest that favorability towards FBAs is linked to suboptimal dietary behaviors, parents’ own perceptions of FBAs is also linked to what their adolescents consume, and that these associations are independent of the dyad’s risk of food insecurity. In sum, perceptions and trust of FBAs is significantly associated with consumption of UPFs among parents and adolescents. Parental perceptions and trust of FBAs were also significantly associated with adolescents’ consumption of UPFs. As such, there was partial support for our first two hypotheses. These findings highlight a degree of vulnerability for U.S. adolescents as targets of food marketing [35] since their consumption of foods low in nutrient density is not only associated with their own media perceptions but also their parents’ perceptions as well. Parents could act as mediators by regulating FBA exposure to their children [36]; thus, acting on their own favorability towards food advertisements could also have implications on their children’s behaviors. Our findings support many previous studies that have identified the important role that parents play in shaping the home food environment and their adolescents’ eating behaviors [37,38]. One dyadic study even identified that greater mobile media use among parents influences their children’s consumption of foods low in nutrient density [39]. Even though our findings indicate that parents and adolescents who are at risk of food insecurity have higher average scores of perceptions and trust of FBAs compared to dyads not at risk, there may be contextual factors that explain the lack of significant partner effects. Adolescents who experience food insecurity are aware of their family hardship even though parents may not be open to discuss it [40]. They assume adult responsibilities, such as finding a job to help provide for their families’ needs and for themselves [41,42]. Even though youth from socio-economically disadvantaged backgrounds and belonging to minority groups experience higher exposure to food advertisements low in nutrient density [43,44], adolescents’ own food consumption may not be swayed by their parents’ favorability towards FBAs; if they were aware of their family’s financial stress, purchasing items could lead to a depletion of their family’s resources and potentially their own earned money [41]. While testing the study’s third aim, we expected that dyads who were at risk of food insecurity would have significantly greater dyadic actor and partner associations between favorability of FBAs and consumption of UPFs compared to dyads without risk of food insecurity. In descriptive analysis, dyads who were at risk of food insecurity had higher average daily servings of UPFs than dyads not at risk of food insecurity. Several studies have noted that food advertisements are more prevalent in low-income, minority neighborhoods [43,45,46]. Since income is a major determinant to food security [47], our findings suggest that families who experience food insecurity are not just vulnerable to food advertisements, but also to the consumption of UPFs [48]. Among dyads not at risk of food insecurity, findings mirror findings from unadjusted models in that greater favorability towards FBAs among parents is associated with not only their own consumption of UPFs, but also adolescents’ UPFs consumption as well. For families who were at risk of food insecurity, actor effects, but not partner effects, were statistically significant. Regardless of food insecurity risk, there may be additional environmental (physical and social) factors that contribute to this association between favorability of FBAs and consumption of UPFs among U.S. parents and adolescents. For example, in addition to the physical and digital environment of food marketing that adolescents are exposed to and greatly engage with [49,50,51], endorsements from celebrities and adolescents’ own peers could potentially influence receptivity of FBAs low in nutrient density [52,53] and food consumption [54,55] alongside parents. Overall, more research is needed to understand the environmental and social context behind these significant actor- and parent-driven effects. Gathering information on the mechanisms and context of these associations could inform future intervention work among this population. One example would be the development of a nutrition education curriculum that effectively improves media literacy of FBAs among families, which has shown to facilitate discussion of food marketing messages and also improve fruit and vegetable consumption in youth [56]. Findings from the current study and further research could also lead to the design of a social marketing campaign that empowers adolescents to engage in peer discussion, think critically about the messages they receive from FBAs low in nutrient density, and advocate for change in their communities. This study has a few strengths. This study analyzes data from a demographically representative sample of U.S. parents and adolescents, which provide strong support towards generalizability. In addition, the operationalization of the study’s independent variable (favorability of FBAs) enabled the reduction in data dimensionality. This means that instead of aggregating indicators to denote an underlying concept as a composite score, we used a latent variable comprised of observed indicators all while minimizing measurement error. Lastly, the study’s APIM approach accounts for the clustered nature of the parent-adolescent dyadic data as a unit. In other words, such an approach allows for capturing the interdependence of parent–adolescent relationships in the family context, rather than examining associations among key outcomes individually for each family member. It is worth noting that this study has several limitations. Although the actor–partner interdependence varies between groups overall, which paths are significantly different with one another is unclear. For example, the findings of this study do not determine whether or not the significant association between favorability towards FBAs in parents and their own UPF consumption is significantly different between groups. In order to confirm these differences between paths, additional analyses with model constraints are necessary. Furthermore, the APIM model only adjusted for two covariates: parents’ sex and parents’ education level. Accounting for other sociodemographic variables such as income, race, ethnicity, in addition to other key covariates, could have led to different findings since they are also linked to poor dietary intake. Lastly, the FLASHE was cross-sectional which indicates that causal inferences cannot be made from this study. Longitudinal studies are warranted to examine the causal relationship between food advertisements and consumption of unhealthy foods in U.S. families. 5. Conclusions When examining associations between perceptions and trust of FBAs and consumption of UPFs in parent-adolescent dyads, actor effects were significant regardless of food insecurity risk; parent-adolescent partner effects were also significant, but only for dyads not at risk of food insecurity. The mechanisms behind these associations are unclear, and more studies are needed to explore the content and impact of FBAs, variation in dyadic interdependence, and ultimately how these affect the connection between consumption of foods low in nutrient density and diet-related chronic disease outcomes. Author Contributions Conceptualization, R.C. and R.F.; methodology, R.C. and R.F.; software, R.C. and R.F.; validation, R.C. and R.F.; formal analysis, R.C. and R.F.; investigation, R.C. and R.F.; resources, R.C. and R.F.; data curation, R.C. and R.F.; writing—original draft preparation, R.C.; writing—review and editing, R.C. and R.F.; visualization, R.C. and R.F.; supervision, R.F.; project administration, R.C. and R.F. 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 are available in a publicly accessible repository that does not issue DOIs. Publicly available datasets were analyzed in this study. This data can be found here: https://cancercontrol.cancer.gov/brp/hbrb/flashe-study/flashe-files accessed on 31 March 2022. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flow diagram showcasing sample sizes for analysis stages. Listwise deletion was used to take care of missing data. Figure 2 Perceptions and trust of FBAs set as latent variables. Variables in the blue box reflect the measurement model for parents while variables within the green box reflect the model for adolescents. R2 values are provided above each indicator. Key: rectangles = indicators; ellipses = latent variables; small circles = residual errors; curved double-ended arrows = covariances; straight single-ended arrows = directional paths. Figure 3 Actor and partner effects of perception and trust of FBAs and consumption of UPFs in parent-adolescent dyads. Significant regression coefficients are bolded in red. Model fit: Δχ2 = 49.518, df = 13, p = 0.001; RMSEA = 0.042 (90% CI = 0.030 to 0.054), p = 0.85; CFI = 0.994; SRMR = 0.026; AIC = 39525.613. Figure 4 Actor and partner effects of perception and trust of FBAs and consumption of UPFs in parent-adolescent dyads accounting for food insecurity. Significant regression coefficients are bolded in red. Both models adjusted for parents’ sex and parents’ education level. (a) SEM model results for dyads not at risk of food insecurity; (b) SEM model results for dyads at risk of food insecurity. Model fit: Δχ2 = 59.794 & 45.814, df = 26, p = 0.001; RMSEA = 0.037 (90% CI = 0.027 to 0.047), p = 0.98; CFI = 0.990; SRMR = 0.036; AIC = 44485.329. nutrients-14-01964-t001_Table 1 Table 1 Descriptive statistics of demographic variables of parent and adolescent dyads. Demographic Variable Parents—1859 (%) Adolescents—1859 (%) Sex Female 1325 (74) 843 (50) Male 468 (26) 835 (50) NA 66 181 Race Hispanic 130 (7) 168 (10) Non-Hispanic Black or African American only 314 (18) 283 (17) Non-Hispanic White only 1229 (69) 1061 (64) Non-Hispanic Other 105 (6) 154 (09) NA 81 193 Age 18–34 years 202 (11) 35–44 years 781 (44) 45–59 years 758 (42)60+ years 52 (3) NA 66 12 years old 224 (13) 13 years old 336 (20) 14 years old 280 (17) 15 years old 305 (18) 16 years old 331 (20) 17 years old 206 (12) NA 177 Level of Education Less than a high school degree 22 (1) - A high school degree or GED 301 (17) Some college but not a college degree 634 (35) A 4-year college degree or higher 830 (46) NA 72 Household Income $0 to $99,999 1406 (79) - $100,000 or more 366 (20) NA 87 Food Assistance Participation Yes 308 (17) - No 1420 (82) I don’t know 3 (0) NA 128 At Risk of Food Insecurity Yes 666 (36) No 1193 (64) - Note: As a result of missingness, the sample frequencies may not add to 100%. nutrients-14-01964-t002_Table 2 Table 2 Descriptive statistics of outcome, predictor, and moderating variables according to risk of food insecurity. Group 1 Not at Risk of Food Insecurity Group 2 At Risk of Food Insecurity Key Study Variables Parents Mean ± SD (n) Adolescents Mean ± SD (n) Parents Mean ± SD (n) Adolescents Mean ± SD (n) Outcome: daily servings of ultra-processed food indicators Sweetened food drinks 0.23 ± 0.45 (1074) 0.41 ± 0.53 (1028) 0.40 ± 0.70 (664) 0.60 ± 0.73 (616) Soda 0.39 ± 0.63 (1071) 0.45 ± 0.58 (1025) 0.58 ± 0.85 (660) 0.55 ± 0.71 (613) Energy drinks 0.04 ± 0.19 (1063) 0.06 ± 0.23 (1021) 0.13 ± 0.41 (657) 0.13 ± 0.39 (607) Fried potatoes 0.23 ± 0.27 (1072) 0.32 ± 0.32 (1030) 0.30 ± 0.38 (659) 0.38 ± 0.42 (613) Tacos, burritos, and similar dishes 0.16 ± 0.19 (1070) 0.20 ± 0.23 (1029) 0.20 ± 0.32 (659) 0.27 ± 0.41 (616) Heat & serve 0.13 ± 0.23 (1072) 0.24 ± 0.32 (1036) 0.20 ± 0.38 (663) 0.30 ± 0.45 (616) Processed meat 0.24 ± 0.27 (1071) 0.30 ± 0.35 (1032) 0.31 ± 0.38 (662) 0.38 ± 0.46 (609) Hamburgers 0.18 ± 0.19 (1077) 0.22 ± 0.24 (1035) 0.24 ± 0.33 (666) 0.30 ± 0.38 (618) Fried chicken 0.12 ± 0.17 (1069) 0.20 ± 0.27 (1031) 0.20 ± 0.36 (660) 0.26 ± 0.39 (611) Candy/chocolate 0.43 ± 0.46 (1074) 0.51 ± 0.51 (1030) 0.39 ± 0.48 (659) 0.50 ± 0.57 (611) Cookies, cakes, and similar treats 0.29 ± 0.35 (1072) 0.41 ± 0.43 (1026) 0.33 ± 0.44 (656) 0.42 ± 0.49 (611) Frozen desserts 0.21 ± 0.26 (1074) 0.29 ± 0.31 (1029) 0.22 ± 0.34 (662) 0.31 ± 0.42 (618) Potato chips 0.27 ± 0.29 (1068) 0.37 ± 0.38 (1032) 0.32 ± 0.38 (664) 0.45 ± 0.46 (612) Sugary cereals 0.11 ± 0.21 (1074) 0.25 ± 0.35 (1035) 0.18 ± 0.38 (664) 0.33 ± 0.46 (617) Total Daily Consumption 2.72 ± 2.38 3.66 ± 3.11 3.96 ± 4.14 4.77 ± 4.70 Predictor: perception and trust of food & beverage advertisements “When I see advertisements for foods or drinks…” I want to try the advertised foods or drinks 2.85 ± 1.39 (1193) 3.03 ± 1.51 (1193) 3.35 ± 1.00 (666) 3.38 ± 1.34 (666) I think the advertised foods or drinks will taste good 3.03 ± 1.36 (1193) 3.12 ± 1.52 (1193) 3.41 ± 0.96 (666) 3.48 ± 1.30 (666) I trust the messages advertised 2.33 ± 1.25 (1193) 2.46 ± 1.41 (1193) 2.62 ± 1.05 (666) 2.77 ± 1.34 (666) Average Total Scores 8.20 ± 3.72 8.60 ± 4.19 9.38 ± 2.61 9.64 ± 3.67 Note: As a result of missingness, the sample frequencies may not add to 100%. nutrients-14-01964-t003_Table 3 Table 3 Pairwise correlation matrix of variables of interest. Key Variables 1 2 3a 3b 4 5 1. Total daily consumption of UPFs - 2. Perceptions and trust of FBAs 0.35 * - 3a. We worried whether our food would run out before we got money to buy more 0.15 0.05 - 3b. The food that we bought just didn’t last, and we didn’t have money to get more 0.16 0.07 0.76 *** - 4. Total daily consumption of UPFs 0.59 *** 0.26 * 0.10 0.11 - 5. Perceptions and trust of FBAs 0.16 0.51 *** 0.03 0.05 0.38 * - Note: Coefficients with asterisks are significant (* p < 0.05, *** p < 0.001). Variables in blue represent parents’ responses while variables in green represent adolescents’ responses. 3a & 3b refer to food insecurity items. Key: UPFs = ultra-processed foods, FBAs = food and beverage advertisements. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Hales C.M. Carroll M.D. Fryar C.D. Ogden C.L. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094792 ijms-23-04792 Article Sample-Specific Perturbation of Gene Interactions Identifies Pancreatic Cancer Subtypes https://orcid.org/0000-0002-5121-3650 Wei Ran 1 Zhang Huihui 2 Cao Jianzhong 1 Qin Dailei 1 Li Shengping 1* Deng Wuguo 1* Ahmad Aamir Academic Editor Patsalis Philippos Academic Editor 1 State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Dongfengdong Road 651, Guangzhou 510060, China; weiran@sysucc.org.cn (R.W.); caojz@sysucc.org.cn (J.C.); tandl@sysucc.org.cn (D.Q.) 2 Pharm-X Center, Engineering Research Center of Cell & Therapeutic Antibody, Ministry of Education, School of Pharmacy, Shanghai Jiao Tong University, Dongchuan Road 800, Shanghai 200240, China; zhanghuihui17@163.com * Correspondence: lishengp@mail.sysucc.edu.cn (S.L.); dengwg@sysucc.org.cn (W.D.); Tel.: +86-020-87343114 (S.L. & W.D.) 26 4 2022 5 2022 23 9 479205 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/). Pancreatic cancer is a highly fatal disease and an increasing common cause of cancer mortality. Mounting evidence now indicates that molecular heterogeneity in pancreatic cancer significantly impacts its clinical features. However, the dynamic nature of gene expression pattern makes it difficult to rely solely on gene expression alterations to estimate disease status. By contrast, biological networks tend to be more stable over time under different situations. In this study, we used a gene interaction network from a new point of view to explore the subtypes of pancreatic cancer based on individual-specific edge perturbations calculated by relative gene expression value. Our study shows that pancreatic cancer patients from the TCGA database could be separated into four subtypes based on gene interaction perturbations at the individual level. The new network-based subtypes of pancreatic cancer exhibited substantial heterogeneity in many aspects, including prognosis, phenotypic traits, genetic mutations, the abundance of infiltrating immune cell, and predictive therapeutic efficacy (chemosensitivity and immunotherapy efficacy). The new network-based subtypes were closely related to previous reported molecular subtypes of pancreatic cancer. This work helps us to better understand the heterogeneity and mechanisms of pancreatic cancer from a network perspective. pancreatic adenocarcinoma gene interactions prognosis network-based subtypes National Natural Science Foundation of China82103570 81972569 The present study was supported by the National Natural Science Foundation of China (82103570 and 81972569). ==== Body pmc1. Introduction Pancreatic cancer is a common lethal and aggressive cancer with a 5-year survival rate of only 10% in 2020 [1]. Poor prognosis is linked to the rapid progression, early metastasis, and lack of obvious clinical symptoms or sensitive screening modalities for early-stage pancreatic cancer. During recent years, multiple treatment modalities (neoadjuvant therapy, radiotherapy, chemotherapy, molecular-targeted therapy, and immunotherapy) have been used for pancreatic cancer patients and have obtained certain therapeutic effects [2]. However, for individual patients, the survival benefits of these treatments differ from patient to patient. Pancreatic cancer should be managed by individualized systemic treatment based on molecular subtypes, which may prolong survival and improve quality of life [3]. With the development in molecular pathology, large numbers of molecules and prediction models have been identified to predict pancreatic cancer prognosis. For example, Moffitt et al. classified pancreatic ductal adenocarcinoma (PDAC) into “basal-like” or “classical” type by RNA transcriptional analysis [4]. Basal-like type is molecularly similar to basal tumors and is associated with poorer clinical prognosis and loss of differentiation. Collisson et al. defined three subtypes: classical, quasi-mesenchymal (QM-PDA), and exocrine-like by using hybridization array-based mRNA expression data from PDAC patients [5]. The QM-PDA subtype correlated with high tumor grade and poor survival. Currently, individual treatment for pancreatic cancer based on PDAC subtypes is under investigation in prospective trials [6]. However, the molecular profiles of PDAC might be variable under different time points or under different conditions, which would have a profound effect on therapeutic development. By contrast, biological networks tend to be relatively stable over time [7,8]. As we know, many reported network methods are dependent on biological pathways, whose concerns revolve around the inference of pathway activity by using pathway-specific genes [9,10]. An advantage of this approach in cancer research is that it may be helpful for some pathway-targeted therapies in tumors [11,12]. For example, pathway-targeted therapy by antagonizing C-X-C motif chemokine receptor (CXCR4) may target the enhanced proliferative signaling, angiogenesis, invasion and metastatic potential of cancer cells [13]. Pathway-targeted therapies are considered to be highly efficient and have low side effects by targeting only the particular disordered pathways [14]. To clearly understand the disease state of pancreatic cancer patients, an individual-specific network (ISN) may be more reliable rather than molecular networks. The ISN utilizes not only the expression data of genes but also the interaction information. The general stability of the gene interactions in a biological network is commonly good in a normal human tissue but tends to be disturbed in diseased tissues [15,16]. These perturbations of gene interactions (named “edge perturbations”) in an individual sample can be evaluated by the change in the relative gene expression value. The edge perturbations at an individual level can be used to define the perturbation of the biological network for each sample effectively. Then, an unsupervised clustering analysis of pancreatic cancer based on the edge perturbation matrix could be applied to demonstrate the heterogeneity among pancreatic cancer patients (Figure 1). Our results demonstrated that the network-based subtypes exhibited substantial heterogeneity in some aspects, including prognosis, phenotypic traits, genetic mutations, the abundance of infiltrating immune cell, and predictive therapeutic efficacy (chemosensitivity and immunotherapy efficacy). Moreover, our network-based subtypes correlated with the previous reported molecular subtypes of pancreatic cancer. These findings may help us to understand the heterogeneity of pancreatic cancer, improve our understanding of pathogenesis and pathophysiological mechanisms, and improve the accuracy of predicting prognosis. 2. Results 2.1. The Constructed Networks We constructed the initial background network from the Reactome database, which was composed of 171,755 edges and 7411 genes in total. Before the network was used to calculate the edge-perturbation matrix, we filtered out genes that were not in the expression data, making the background network decreased to having 168,834 edges and 7362 genes. Both the filtered network and the initial background network used in this work are scale free, which indicates that the fraction of nodes with degrees follows a power law distribution. Figure S1 demonstrated the degree distributions of the two networks (the determination coefficients R2 are 0.759 and 0.821, respectively). Here, R2 is used to measure the fitting level of the power law curve. The better the curve fitting level is, the closer R2 is to 1. Both the degree distribution figures and the determination coefficients show that the networks used in this study are all scale free. 2.2. Stable Gene–Gene Interaction Network in Normal Pancreatic Tissues Both 167 normal samples obtained from GTEx and 176 pancreatic cancer samples obtained from TCGA were used to evaluate the stability of the edge perturbation in normal samples and variability in cancer samples. The edge-perturbation-based method was used to construct the edge perturbation matrix with 168,834 rows (see Section 4 for details). In our study, we used zero center normalization to get the edge perturbation matrix by Equation (2) (see Section 4). The edge-perturbation matrix can evaluate the sample-specific perturbation in the same background network effectively. For a given gene pair, the greater absolute value in the edge-perturbation matrix means the greater perturbation. In normal samples, the mean absolute magnitude of the edge perturbations was 1283.27, whereas it was much higher in pancreatic cancer samples at 3644.26. Furthermore, we found that 94.71% of all 168,834 gene pairs showed more dispersion in pancreatic cancer samples than in normal samples through comparing the sum of edge-perturbation degrees. In addition, we randomly selected 1000 features from all the gene-gene interaction edges, and then, the Wilcoxon rank-sum test was performed to compare the difference of the edge perturbation distribution between normal and cancer groups (p < 2.2 × 10−16). The edge-perturbation amplitude was expressed as log2(|Δe,s| + 1) for both normal and cancer samples, as shown in Figure 2A. Next, the difference of the edge-perturbation distribution between normal and cancer samples was shown in a scatter plot (1000 selected features on X axis, log2 transformation of the edge-perturbation amplitude of 1000 selected features on Y axis), as shown in Figure 2B. The edge perturbation of normal samples (blue points) is much denser and less than that of cancer samples (red points). These two plots reveal that the edge perturbations of normal samples are more stable, whereas a wider variation exists in cancer samples, making it possible to find the heterogeneity in pancreatic cancer samples through the edge-perturbation matrix of all samples. 2.3. Network-Based Subtypes Then, we used the cancer sample matrix derived from the edge-perturbation matrix to cluster pancreatic cancer samples. The cancer sample matrix had 1409 rows which represent the 1409 edges. These edges formed a network with 980 genes (Table S1), which was shown in Figure S2, and the corresponding determination coefficient R2 was 0.999 (p = 0.001), which meant that it was also a scale-free network. Consensus clustering was performed using the R package “ConcensusClusterPlus” [17] to explore the subgroups of cancer samples based on the cancer sample matrix. The best cluster number was determined by the clustering score for the cumulative distribution function (CDF) curve. The CDF curve based on the consensus scores achieved the best division when k = 4 (Figure 3A–C). Among the 176 pancreatic cancer samples analyzed in this study, 43 were subtype-1, 45 were subtype-2, 17 were subtype-3, and 72 were subtype-4. Afterwards, we used the four network-based subtypes for the following analyses. 2.4. Heterogeneity among Network-Based Subtypes 2.4.1. Prognosis In the following analysis, we compared prognostic differences among the network-based subtypes. Kaplan–Meier survival analysis indicated that overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS) differ significantly among patients in subtypes (Figure 4A–D). Subtype-3 has the most favorable prognosis compared with other subtypes. 2.4.2. Phenotypic Heterogeneity The tumor purity scores in Figure 5A were derived from the computational method (ABSOLUTE) [18,19], which infers tumor purity and malignant cell ploidy directly from the analysis of somatic DNA alterations. Our analysis showed that the tumor purity scores are significantly higher in subtype-3. Next, we attempted to find out whether our network-based subtypes in pancreatic cancer shows phenotypic heterogeneity (Figure 5B–I). The pathway scores, which are protein expression signatures of pathway activity, associated with tumor lineage were from a reverse-phase protein microarray (RPPA) as published by TCGA [19,20]. Our analysis indicated that the pathway scores for epithelial–mesenchymal transition (EMT), Ras.MAPK (Ras GTPase/MAP kinase signaling), and receptor tyrosine kinase (RTK) were significantly lower in subtype-3 than in other subtypes. These results suggest that the network-based subtypes show differences in part of pancreatic cancer-associated phenotypes. 2.4.3. Gene Mutation and Immune Cell Infiltration We then further investigate the mutational data of patients among different subtypes using the “maftool” package. The common mutational genes in the top 20 of the 4 subtypes were shown in Figure 6A. KRAS and TP53 were the common top 2 frequent mutational genes in all subtypes. TP53 is recognized as a tumor suppressor regulating cell cycle, apoptosis, and senescence. Mutations in the TP53 are associated with tumor progression, tumor metastasis, and early relapse [21]. We found that the mutational ratio of TP53 in subtype-3 were the lowest among the four network-based subtypes. In addition, two other frequently mutated genes (SMAD4 and CDKN2A) were not detected in the top 20 mutational genes of subtype-3. Previous studies have demonstrated that PDAC patients who had CDKN2A or SMAD4 expression loss had worse disease-free survival and overall survival compared with patients with intact CDKN2A/SMAD4 [22,23]. ATM and ATRX, which ranked the third and fourth mutated genes, were closely related with DNA damage repair (DDR) pathway [24]. As has been previously reported, patients with DDR gene mutations may have better survival [25]. These results were consistent with the prognostic outcome in our study. To further explore the differences in immune cell infiltration among network-based subtypes, we used the CIBERSORT algorithm to calculate the proportions of 22 immune cells in each subtype (Figure 6B). The results showed that the proportions of M0 and M1 macrophage, monocytes, resting natural killer (NK) cells, and CD8+ T cells had a significant downward trend in the subtype-3, and the proportions of regulatory T cells (Tregs), activated natural killer (NK) cells, and plasma cells were significantly (p < 0.01) increased in the subtype-3. 2.4.4. Predictive Therapeutic Efficacy We further estimated the drug sensitivity among different subtypes based on the GDSC [26]. Intriguingly, the predicted drug sensitivity values (IC50) of gemcitabine and docetaxel were the highest in the patients of subtype-3 who had the most favorable prognosis (Figure 7A,B; p = 0.0069 and 0.00012, respectively, Wilcoxon rank sum test). The drug sensitivity model was not consistent with prognosis after treatment of gemcitabine or docetaxel, suggesting that the model is drug specific, rather than a general predictor of disease prognosis. At present, immunotherapy drugs have been widely used in melanoma, lung cancer, and hepatocellular carcinoma [27,28,29]. However, pancreatic cancer is almost entirely refractory to immunotherapy. Therefore, a better selection of patients who are most likely to benefit from immunotherapy may be critical. We then compared the expression of PD-1 and PD-L1 in different subtypes (Figure 7C). Subtype-3 had the lowest level of PD-1 and PD-L1, whereas subtype 2 had the highest level of PD-1 and PD-L1. For exploring the response to immunotherapy in these subtypes, we performed subclass mapping to compare the expression profile of the 4 network-based subtypes which were identified using a previous published cohort containing 56 melanoma patients who were treated with immunotherapy [30]. The pairwise comparison of the four subtypes showed that more promising results were observed in subtype-2 for the anti-PD1 and anti-CTLA4 treatments compared to the other subtypes, whereas subtype-3 was the most resistant to immunotherapy (Figure 7D–I) (anti-PD1 therapy: subtype-1 vs. subtype-2, p = 0.006; subtype-1 vs. subtype-3, FDR = 0.04; subtype-1 vs. subtype-4, p = 0.036; subtype-2 vs. subtype-3, FDR = 0.008; subtype-2 vs. subtype-4, FDR = 0.024; subtype-3 vs. subtype-4, p = 0.039; anti-CTLA4 therapy: subtype-3 vs. subtype-4, p = 0.039). 2.5. Connection with Other Molecular Subtypes of Pancreatic Cancer As we all know, Collison et al. identified the quasi-mesenchymal subtype [5], and Moffitt et al. discovered the basal subtype [4], which are associated with poor overall survival outcomes in PDAC patients. However, the classical subtype in both classifications had better prognosis. There were close relationships between our four network-based subtypes and the classifications of Collison and Moffitt. Specifically, according to Collison’s classification, subtype-3 was a mixed subtype, including classical (66.67%) and exocrine-like (33.33%) subtypes (Figure 8A). Although subtype-1 was also a mixed subtype, it had the lower proportion of a classical subtype (2.78%) which carried a better prognosis when compared to the exocrine-like and quasi-mesenchymal subtypes. Similarly, according to Moffitt’s classification, subtype-3 was an all-classical subtype (Figure 8C). This was consistent with the better prognosis of subtype-3. 2.6. Subtype-3 Specific Pathways and Feature Genes The subtype-3 specific pathways were displayed in Figure 9A. Most pathways enriched in subtype-3 were related to immune modulation, such as antigen processing: ubiquitination and proteasome degradation, adaptive immune response, complement activation, classical pathway, and host interactions of HIV factors. Neddylation, which has been shown to be closely related to the worse prognosis in pancreatic cancer [31], is also one of the enriched pathways that was closely correlated with immune modulation [32]. The pathways related with cell cycle and proliferation were also enriched in subtype-3 specific pathways, such as cell cycle, mitotic, anaphase-promoting complex/cyclosome (APC/C)-mediated degradation of cell cycle proteins, mitotic cell cycle, microtubule cytoskeleton organization involved in mitosis, nuclear division, and G2/M transition of mitotic cell cycle. In addition to immune and cell cycle and proliferation pathways, ubiquitination-related pathways such as neddylation, protein K48-linked ubiquitination, protein autoubiquitination, positive regulation of protein ubiquitination, protein monoubiquitination, and ubiquitin E3 ligase (The COP9 signalosome (CSN) 1, CSN8, HRT1, S-phase kinase-associated protein (SKP) 1, SKP2, Cullin (CUL) 1, CUL2, CUL3) were also enriched in subtype-3. We then pick out the genes in the subtype-3 specific pathways, which had the top 10 highest degrees in Figure 3. The expression levels of these genes were significantly different among subtypes (Figure 9B). The higher expression of Polo-like kinase 1 (PLK1), cyclin dependent kinase 1 (CDK1), ubiquitin-conjugating enzyme 2C (UBE2C), and Ring-box 1 (RBX1) were related with worse prognosis in PDAC (Figure 9C). 3. Discussion In this study, we used a relatively stable gene interaction network to distinguish the subtypes of pancreatic cancer. We separated the pancreatic cancer patients into four network-based subtypes based on gene interaction perturbations at the individual level. Different subtypes exhibit high heterogeneity in many aspects, including prognosis, phenotypic traits, genetic mutations, the abundance of infiltrating immune cell, and predictive therapeutic efficacy (chemosensitivity and immunotherapy efficacy). Compelling evidence has demonstrated that differences in the molecular pathology of pancreatic cancer substantially impact the clinical outcomes of the disease [6]. Better optimized individual patient management and/or risk stratification may improve systemic therapeutic regimen selection. Consequently, there have been intense efforts to develop methods that define molecular subtypes of pancreatic cancer. Molecular classification of cancer can be achieved in many ways, including identifying distinct characterization of genomic [33], transcriptomic [6], and microenvironmental alterations [34]. Most of these classification schemes attempt to separate the patients into limited categories. As a result, competing molecular subtypes are often overlapping, with no optimal single classification that addresses all requirements. Recently, A unique continuous gradient classification system of PDAC was proposed [35]. The resulting PDAC molecular gradient signature seems to be more informative and clinically relevant than previous non-overlapping methods. However, all these methods merely utilize the gene sets in a network but ignore the interactions among genes [33,36]. In our study, we made better use of the gene interaction relations in the background network to explore new subtypes of pancreatic cancer. Of the 4 subtypes of pancreatic samples, subtype-3 had the best prognosis. In our analysis, we found that subtype-3 had the highest tumor purity compared with the other subtypes. This appears to contradict the previous suggestions that a higher degree of tumor purity is associated with a worse prognosis [37]. Higher tumor purity often means lower degree of tumor immune infiltration. Using the CIBERSORT analysis of the immune cell proportion of network-based subtypes, we found that the abundance of various cells associated with cytotoxicity in the subtype-3 was significantly lower than that in other subtypes, such as resting NK cells, CD8+ T cells, and activated memory CD4+ T cells. The number of macrophages M0, M1, and regulatory T cells was significantly increased in subtype-3 (Figure 6B). The composition of immune cells in the subtype-3 established an immunosuppressive microenvironment and may be the reason of limited efficacy of immunotherapy (Figure 7D–I). Moreover, subtype-3 was not sensitive to gemcitabine and docetaxel (Figure 7B). The more resistant to conventional chemotherapy may be attributed to the mutation of ATM and/or ATRX. As previously reported, the abnormalities in DDR pathways are closely linked with resistance to treatment [38,39]. These results indicate that the better prognosis of subtype-3 may not be attributed to sensitive response to therapy. Our analysis implies that the pathway scores for EMT, Ras.MAPK, and RTK of subtype-3 are significantly lower than those in other subtypes. Previous studies have revealed that inhibition of MAPK and RTK is associated better prognosis in PDAC [40]. And patients with lower EMT ability are predisposed to have longer survival time. We further found that subtype-3 had lower proportion of lymph node metastasis (Figure S3, p < 0.001, using Chi-square test). The presence of lymph node metastasis is commonly recognized as a poor prognostic sign [41]. Therefore, the lower malignant potential may be the main reason for a better prognosis of subtype-3. We further explored the enriched pathways and top 10 genes with the highest degree in subtype-specific network. We found that PLK1, CDK1, UBE2C, and RBX1 were related with prognosis of PDAC. PLK1, an essential cell cycle regulator and a member of the serine/threonine-protein kinase family, is overexpressed in many human cancers. A recent study has shown that it is associated with worse prognoses of pancreatic cancer [42]. Similarly, CDK1 has been regarded as a potential target for treatment of PDAC [43]. CDK1 is commonly significantly overexpressed in PDAC patients, which is an indicator of poor survival for patients [44]. UBE2C is a core ubiquitin-conjugating enzyme in the ubiquitin-proteasome system that promotes cell cycle progression. The dysregulation of UBE2C is related with the proliferation of cancer cells and poor overall survival in pancreatic carcinoma [45,46]. RBX1 is part of the cullin-ring ubiquitin ligase (CRL4) complex (CUL4A–RBX1), which is associated with DNA damage repair. However, there have been no studies that have reported the association of RBX1 and prognosis of PDAC. Our findings support the development of therapies targeting the 4 genes for PDAC treatment. Future studies on the molecular mechanisms of these genes and the development of targeted therapies are warranted. In fact, the single genetic marker classification in PDAC has little effect on guiding treatment decision. Numerous studies have shown that network-based approaches are more robust and effective than single-gene features. However, previous typing methods just used the expression of gene sets but ignore the interactions between genes in the pathway. The perturbation of the network can be used to reflect the abnormal extent of an individual with disease, which was innovatively measured by the edge perturbations in our study. Another important feature of our study is the individual-specific analysis of the gene interaction network. Based on the background network, we could separate new cancer samples into different subtypes and guide the following treatment and predict prognosis. The method used in our study may emerge as an ideal tool for personalized or precision oncology, which represents one potential research direction of future development. However, our outcome analyses are limited by the retrospective nature of this work, including nonrandomized patient treatment selection and possible confounding factors not balanced between subtypes. Therefore, the results should be interpreted with caution. More future work is needed, including prospective clinical trials and animal experiments. 4. Materials and Methods 4.1. Data Processing The Cancer Genome Atlas (TCGA) mRNA expression data, along with the clinical information and mutation data were extracted from the Genomic Data Commons (GDC) data portal. The 176 pancreatic cancer samples which were pathologically diagnosed as pancreatic ductal adenocarcinoma were included in the following analyses as the case group (Table S2). For the control group, mRNA expression data of 167 normal pancreatic tissues were downloaded from the Genotype-Tissue Expression (GTEx) project (https://gtexportal.org/, accessed on 13 February 2021). For further analysis, we converted both of the two data sets into transcripts per million (TPM) form with 30,948 genes in total. 4.2. Constructing Background Network The ISN for individual is built based on edge perturbations analysis of this sample against a group of given normal samples. To achieve this objective, we first used the mRNA expression data of 167 normal pancreatic tissues downloaded from GTEx project, which serve as the control or reference samples. The Reactome pathway database is then used to construct a background network which reflects functional protein interaction network derived from pathways [47]. We obtained all the gene interaction networks (231 in total) of Reactome pathways by using the app ReactomeFIPlugIn 8.0.0 in Cytoscape 3.7.1 [48]. All the networks were integrated into a large network as the background network with 168,834 edges in total. 4.3. Overview of the Edge-Perturbation-Based Approach To evaluate the abnormal condition of patients at an individual sample level, we used the edge-perturbation-based approach. We constructed ISN based on statistical perturbation analysis in an accurate manner of a single cancer sample against a given control group of normal samples, which is the theoretical foundation of this method [49]. In brief, the major steps in our method were shown in Figure S4: at first, the gene expression matrix of normal and cancer samples was converted into a gene expression rank matrix by ranking all genes based on the expression levels in individual sample (represented as element ri,s, which indicates the rank of gene gi in sample s). Secondly, we calculated the delta rank matrix whose rows referred to as edges in the background network and columns represented samples. An element δe,s (delta rank) in the delta rank matrix was obtained by subtracting the ranks of the connecting two genes in an edge (e) of the background network. (1) δe,s=ri,s−rj,s The gene–gene interaction network is stable in normal samples, and there are few interaction perturbations [50]. Therefore, the background network is considered to be stable across all normal samples. Then, we used the normal samples to acquire the benchmark delta rank vector, with which each sample must be compared, and the corresponding difference means the gene interaction perturbations on the sample. We ranked genes according to their mean gene expression value among normal samples and then calculated the delta rank as the benchmark delta rank vector with elements denoted by δ¯e , where e is an edge in the background network. This vector represents the mean relative ranks of gene pairs in all normal samples. Finally, we get the edge-perturbation matrix with element Δes through subtracting the benchmark delta rank vector from the delta rank of each sample. (2) Δe,s=δe,s−δ¯e The edge-perturbation matrix will be converted to a cancer sample matrix that is used for subsequent clustering analysis. 4.4. Construction of the Network-Based Subtypes First, we calculated the variance of each edge between pancreatic cancer samples and normal samples in the edge-perturbation matrix by the Kruskal–Wallis test. Only the top 30,000 significantly different edges with higher standard deviations (SDs) (also top 30,000 edges with higher SDs) of the edge perturbation of all pancreatic samples would be used for clustering analysis. 4.5. Estimation of the Abundance of Immune Cell Populations To estimate the abundance of immune cell populations in cancer samples, we used the CIBERSORT algorithm. This is an analytical tool used to estimate the infiltration ratio of different immune cell types in a mixed cell population using gene expression data [51]. 4.6. Chemotherapy Response and Immune Checkpoint Inhibitor Treatment Response Prediction We predict the chemotherapy response of each sample from TCGA database based on the Genomics of Drug Sensitivity in Cancer (GDSC). Two commonly used chemotherapeutic agents were selected, namely, docetaxel and gemcitabine. The prediction process was performed using the R package “pRRophetic”, where the half-maximum inhibitory concentration IC50 of the sample was calculated using ridge regression, and the accuracy of the prediction was assessed using 10-fold cross-validation, according to the GDSC training set. We further used TCGA’s mRNA expression profile combination subclass mapping method to predict the therapeutic response of our network-based subtypes to immune checkpoint blockade [52]. 4.7. Identifying Subtype-Specific Pathways The cancer sample matrix was standardized by the Z-score methodology, which converted the mean of each row (corresponding to feature edge) to zero and variance to one. First, we employ hierarchical clustering using complete linkage method to define clusters of the rows of the matrix, with the cluster number set to 100, and clusters containing more than 30 edges were retained. Afterwards, the mean values of the perturbation for each edge in subtype-3 were calculated through Z-scores. Then, the ratio of edges whose absolute value of the average perturbation was greater than 0.5 in each retained cluster was obtained. A cluster with a percentage greater than 70% was considered as a perturbed cluster for subtype-3. All edges in all of the perturbed clusters for subtype-3 constituted the subtype-specific networks. All genes involved in the subtype-specific network were used for pathway enrichment analysis by Metascape (http://metascape.org, accessed on 11 November 2021). The KEGG and Reactome pathways with a p-value less than 0.01 were retained. Finally, the subtype-specific pathways were identified. 4.8. Survival Analysis We compared the survival prognosis (overall survival (OS), progression-free survival (PFS), disease-free survival (DFS) and disease-specific survival (DSS)) of patients in different network-based subtypes using Kaplan–Meier curve. The log-rank test used p < 0.05 as the threshold to detect significant differences in survival time. Meanwhile, survival analysis of genes with the top 10 highest degrees in the subtype-3 specific network were operated based on GEPIA (Gene Expression Profiling Interactive Analysis) database [53]. 4.9. Statistical Analysis All statistical analyses were carried out using R (version 3.6.1). The survival curve of the prognostic analysis was generated by the Kaplan–Meier method, and the statistical significance was tested by the log-rank test. In order to test whether the differences among the subtypes were statistically significant, Kruskal–Wallis one-way Analysis of Variance (Kruskal–Wallis) test was performed. Then, the R package “maftools” was used to present the mutation landscape of the samples. 5. Conclusions In this study, we constructed an association network by edge-perturbation, which includes both direct and indirect regulation between two genes. These findings may help us to understand the heterogeneity of pancreatic cancer and improve our understanding of pathogenesis and pathophysiological mechanisms and improve the accuracy of predicting prognosis. Acknowledgments We acknowledge TCGA, GDSC, GTEx, and other databases that were used in this manuscript for providing their platforms and contributors for uploading their meaningful datasets. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23094792/s1. Click here for additional data file. Author Contributions R.W.: conceptualization, software, visualization, writing—original draft, writing—review and editing, and collection and assembly of data. H.Z.: writing—original draft, writing—review and editing, collection and assembly of data, and data analysis and interpretation. J.C.: conceptualization and writing—review and editing. D.Q.: conceptualization and writing—review and editing. S.L.: supervised the findings of this work, funding acquisition, and project administration. W.D.: conceptualization, supervision, funding acquisition, and writing—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, because the study is based on open-source data, and there are no ethical issues. Informed Consent Statement Patient consent was waived, because patients analyzed in the study were from open-source data. The patients involved in the databases have obtained ethical approval. Data Availability Statement Publicly available datasets were analyzed in this study. The data can be found here: TCGA database (https://portal.gdc.cancer.gov, accessed on 12 February 2021); GDSC database (https://www.cancerrxgene.org/, accessed on 10 October 2021); GTEx dataset (https://gtexportal.org/, accessed on 13 February 2021); Reactome database (https://reactome.org/, accessed on 15 August 2021). We have uploaded all software code to a public repository: https://doi.org/10.24433/CO.3617641.v1, accessed on 14 April 2022. Conflicts of Interest TCGA, GDSC, GTEx, and other databases used in this paper belong to public databases. The patients involved in the databases have obtained ethical approval. Users can download relevant data for free for research and publish relevant articles. The study is based on open-source data, so there are no ethical issues or other conflicts of interest. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Figure 1 A flowchart identifying pancreatic cancer subtypes. For a group of normal samples, a reference background network can be constructed by the correlations between genes based on expression data of this group of samples. A new cancer sample S6 is added to the group, and the perturbed network with this additional sample is built in the same way. The difference between the background and perturbed networks is due to sample S6. Edge perturbations for each individual sample are calculated by perturbed network and background network. Then, the pancreatic cancer samples are clustered by using a partition edge-perturbation matrix to reveal new network-based subtypes. The identified subtypes are characterized from different aspects, including prognosis, phenotypic traits, genetic mutations, immune cell infiltration, and therapeutic efficacy. We further performed pathway enrichment analysis for subtype-3 using all genes involved in the subtype-specific network. Abbreviations: S, sample; G, gene; E, edge. Figure 2 Perturbation of gene interactions in normal and pancreatic cancer tissues. (A) Distribution of log2-transformed edge perturbations in both normal and cancer samples. Violin plots show the distributions of the edge perturbations of 1000 randomly selected edges in the edge-perturbation matrix in both the normal and cancer groups. The distributions in these two groups were significantly different, as assessed by the Wilcoxon rank-sum test. (B) The scatterplot for the log2-transformed mean of the edge perturbations in the 1000 randomly selected edges in both normal (blue points) and pancreatic cancer (red points) tissues. The edge perturbations of normal samples are much denser and less than those of cancer samples. Figure 3 Identification of network-based subtypes by unsupervised consensus clustering. (A) Consensus matrix heatmap of 176 TCGA pancreatic cancer samples when k = 4. The rows and columns represent patient samples, and consensus matrix values vary from 0 in white (indicating that patients are never clustered together) to 1 in dark blue (indicating that patients are always clustered together). (B) Consensus CDF shows a real random variable of its probability distribution based on consensus scores for different subtype numbers (k = 2–10). (C) The delta area plot for k changed from 2 to 10. The vertical axis is the relative change in the area under the CDF curves when the cluster number varies from k to k + 1. The range of k changed from 2 to 10. Abbreviations: CDF, cumulative distribution function; TCGA, The Cancer Genome Atlas. Figure 4 Survival curves of the network-based subtypes. (A–D) Kaplan–Meier curves for the OS, PFS, DFS, and DSS of TCGA pancreatic cancer samples showed that subtype-3 had a better outcome compared with the patients in other subtypes. Abbreviations: OS, overall survival; PFS, progression-free survival; DFS, disease-free survival; DSS, disease-specific survival; TCGA, The Cancer Genome Atlas; PAAD, pancreatic adenocarcinoma. Figure 5 Phenotype heterogeneity among the network-based subtypes. Boxplots show differences in (A) tumor purity, (B) tumor mutation burden, (C) apoptosis, (D) cell cycle, (E) DNA damage response, (F) EMT, (G) Ras/MAPK, (H) RTK, and (I) TSC-mTOR scores from TCGA among network-based subtypes. The data from A were derived from ABSOLUTE. The data from B were obtained using R package “maftool”. The data from C–I were from RPPA data-based scores published by TCGA. The Kruskal–Wallis test was performed to calculate the p-value, and those associations with p-value < 0.05 were considered significant. Abbreviations: EMT, epithelial–mesenchymal transition; MAPK, mitogen-activated protein kinase; RTK, receptor tyrosine kinase; TSC, tuberous sclerosis complex; mTOR, mammalian target of rapamycin; TCGA, TCGA, The Cancer Genome Atlas; RPPA, reverse-phase protein microarray; DNA, deoxyribonucleic acid. Figure 6 Somatic mutations and immune cell infiltration among the network-based subtypes. (A) The distribution of gene mutations among network-based subtypes. KRAS and TP53 were the top 2 most important mutation according to the importance of ranking in all subtypes. (B) CIBERSORT algorithm showed immune infiltration of 22 immune cells among network-based subtypes. Abbreviations: NK, natural killer; ns, not significant; NA, not applicable. * p < 0.05, ** p < 0.01, **** p < 0.0001. Figure 7 Differences in sensitivity of network-based subtypes to chemotherapy and immunotherapy. (A,B) The box plots showed the estimated IC50 for gemcitabine (A), and docetaxel (B) among network-based subtypes. The Kruskal–Wallis test was performed to calculate the p-value. (C) Expression level of PD-1 and PD-L1 among network-based subtypes of PDAC patients from TCGA dataset. (D–I) Network-based subtypes immunotherapy response prediction. The p values were adjusted by the Benjamini and Hochberg’s approach for controlling the false discovery rate. Abbreviation: TCGA, The Cancer Genome Atlas; PDAC, pancreatic ductal adenocarcinoma; IC50, the half maximal inhibitory concentration; PAAD, pancreatic adenocarcinoma; PD-1, programmed cell death-1; PD-L1, programmed cell death-ligand 1; CTLA-4, cytotoxic T lymphocyte associate protein-4. ** p < 0.01, *** p < 0.001. Figure 8 Comparison of the network-based subtypes and Collisson et al. subtypes and Moffitt et al. subtypes. (A) The distribution of the Collisson et al. subtypes in each of network-based subtype. (B) The distribution of the network-based subtypes in each of Collisson et al. subtype. (C) The distribution of the Moffitt et al. subtypes in each of network-based subtype. (D) The distribution of the network-based subtypes in each of Moffitt et al. subtypes. Abbreviations: Exo, exocrine-like; QM-PDA, Quasi-mesenchymal. Figure 9 Subtype-3 specific pathways and feature genes. (A) pathways enriched in subtype-3. The horizontal axis represents the negative log (base 10) of the p-value. (B) The differential expression of feature genes in subtype-3, which had the top 10 highest degree in subtype-specific network. (C) Kaplan–Meier curves for the OS of TCGA pancreatic cancer samples showed that higher expressions of UBE2C, CDK1, PLK1, and RBX1 were associated with worse outcome. Abbreviations: TPM, transcripts per million; TCGA, The Cancer Genome Atlas; PAAD, pancreatic adenocarcinoma; PLK-1, Polo-like kinase 1; SKP, S-phase kinase-associated protein; CUL, Cullin; RPS27A, ribosomal protein S27a; CDC, cell division cycle; CDK, cyclin dependent kinase; UBE2C, ubiquitin-conjugating enzyme 2C; RBX, ring-box. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Siegel R.L. Miller K.D. Fuchs H.E. Jemal A. Cancer Statistics CA A Cancer J. Clin. 2021 71 7 33 10.3322/caac.21654 33433946 2. Park W. Chawla A. O’Reilly E.M. Pancreatic Cancer: A Review JAMA 2021 326 851 862 10.1001/jama.2021.13027 34547082 3. Collisson E.A. Bailey P. Chang D.K. Biankin A.V. Molecular subtypes of pancreatic cancer Nat. Rev. Gastroenterol. Hepatol. 2019 16 207 220 10.1038/s41575-019-0109-y 30718832 4. Moffitt R.A. Marayati R. Flate E.L. Volmar K.E. Loeza S.G.H. Hoadley K.A. Rashid N.U. 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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/ijerph19095573 ijerph-19-05573 Article Exploring Hepatocellular Carcinoma Mortality Using Weighted Regression Estimation for the Cohort Effect in Taiwan from 1976 to 2015 https://orcid.org/0000-0002-9047-8141 Tzeng I-Shiang 12* Chen Jiann-Hwa 3* Fischer Florian Academic Editor Tchounwou Paul B. Academic Editor 1 Department of Research, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan 2 Department of Statistics, National Taipei University, Taipei City 10478, Taiwan 3 Department of Gastroenterology and Hepatology, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan * Correspondence: istzeng@gmail.com (I.-S.T.); cjhki.tiyi@msa.hinet.net (J.-H.C.) 04 5 2022 5 2022 19 9 557321 1 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/). To estimate the cohort effects that remove the efficacy of age and the period in the age-period statistics of a contingency table, the multiphase method is put forward. Hepatocellular carcinoma (HCC) is one of the most common malignancies of the liver. Understanding the predictive effects of age, period, and cohort on HCC mortality trends may help to estimate the future HCC burden, identify etiological factors, and advise public health prevention programs. Estimates of future HCC mortality and the associated health burden were forecast using an age–period–cohort (APC) model of analysis. By running a regression of residuals that were isolated from the median polish stage of cohort classification, the study controlled for HCC mortality confounding variables and interpreted time trends in HCC rates. The literature shows that the weighted mean estimation derived from the confidence interval (CI) is relatively restricted (compared to the equal-weighted evaluation). This study aimed to illustrate the effects of age, period, and cohort on the incidence and mortality rates, along with the weight equivalent to the segment of death number caused by HCC in each cohort. The objective of that work was to evaluate the proposed method for appraising cohort effects within the age-period data of contingency tables. The weighted mean estimate from the regression model was found to be robust and thus warrants consideration in forecasting future HCC mortality trends. The final phase was factored in to calculate the magnitude of cohort effects. In conclusion, owing to the relatively constricted CI and small degree of uncertainty, the weighted mean estimates can be used for projections based on simple linear extrapolation. hepatocellular carcinoma weighted cohort effect regression model Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical FoundationTCRD-TPE-111-08(1/2) TCRD-TPE-108-RT-8(3/3) This study was funded by grants from the Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation (TCRD-TPE-111-08(1/2) and TCRD-TPE-108-RT-8(3/3)). ==== Body pmc1. Introduction Hepatocellular carcinoma (HCC) is regarded as a widespread and prime malignancy of the liver [1]. Worldwide, it ranks as the second greatest cause of mortality in men and sixth in women (14.7% and 6.5% of deaths for men and women, respectively) [2]. In Taiwan, it dominates the field of cancer, as it is the leading cause of cancer in men and the secondary cause of cancer in women (approximately 22% of men and 14% of women die of HCC) [3]. The estimates of the global incidence of HCC in 2000 were 398,000 men and 166,000 women per year [4]. The multiphase method for estimating cohort effects in age–period contingency table data, proposed by Keys and Li [5], takes three stages to conceptualize the cohort effects. Since the median polish does not lean on a specified allocation or formation, various types of mortality and trend data such as rates (of log transformation), proportions, and counts can be analyzed. The first stage is a graphical representation, which is followed by a median polish that is used to degrade log-additive components of ages or periods. A median polish analysis then makes up the second stage, whereby iteratively subtracting the median from each row and column detaches the additional effects of age and period. This is followed by linear regression of the residuals, factoring in cohort effects and random errors. By intermittently subtracting the median from each row and column, the median polish may be used to delineate statistics in a two-way contingency table [6] and separate the supplementary influence from the age (i.e., row) and period (i.e., column). The first person who adopted APC analysis with the median polish [7] was Selvin. No specified allocation or structure of the data within a two-way contingency table means this technique can be used extensively for various types of data that consist of a table, such as suicide data [8]. Moreover, there is another advantage of the APC model, in that it can be applied to narrate the secular tendency in terms of disease incidence or mortality [9]. HCC has a close interrelationship with cirrhosis owing to alcohol consumption and viral etiologies [10]. It takes, on average, 20 years for cirrhosis to develop after the onset of hepatitis C virus infection [11]. Although malignant hepatocellular tumors do not usually metastasize, it is not easy to clear them when they do. In clinical practice, follow-up reviews are held at intervals of two to three months after the discovery of alpha-fetoprotein (AFP) by investigative criteria such as ultrasound, computed tomography, and magnetic resonance imaging. A novel biomarker used to detect HBV-related HCC is the HBV DNA quantitation-time index (HDQTI) [12]. The HDQTI is recognized as the optimal product in follow-up and logarithm, detecting the ratio of normal HBV DNA load. The novel HDQTI can be referred to as an independent prognostic indicator for recurrence in HBV-related HCC [13]. Most HCC patients present with a poor prognosis. It is thus critical to develop novel approaches, such as cell-based immune therapies [14]. These therapies are currently being evaluated in solid tumors including HCC, for example, chimeric antigen receptor T cells and T-cell receptor-engineered T cells. Progression-free survival was demonstrated in a previous network meta-analysis, which studied the agents regorafenib, cabozantinib, and ramucirumab. Additionally, the outcomes of interest were a comprehensive benefit over the placebo, which lacked an advantage compared to any others [15]. Overall, for refractory patients, regorafenib and cabozantinib are the preferable options. Ramucirumab is deemed an ancillary option to treat [15] patients whose AFP levels are 400 ng/mL or higher. Accordingly, an amalgamation of immune agents integrating target drugs for the therapy of advanced HCC was endorsed by the Taiwan Food and Drug Administration on 1 August 2020. Taking the time trend of HCC mortality into account, by simple linear extrapolation of the observational log in age-adjusted rates, an orthodox analysis may overlook some of the pivotal attributes that are hidden within the data (such as the cohort effects). During the period from 1976 to 2005 in Taiwan [16], if we conduct simple linear extrapolation of the long-term trends in HCC mortalities, there is no objective reason to doubt the trend, since it has been proliferating for 35 years and seems as though it will continue to escalate in the future. Yet, the current trend in HCC mortalities is tailing off. This can be attributed to the fact that the phenomenon is a consequence of the cohort effects that can be recognized in APC analysis. In such context, this study aimed to explore the effects of age, period, and cohort on HCC mortality rates, along with the weight equivalent to the proportion of HCC death in each cohort [17]. In addition, we sought to identify weighted estimates for a cohort of the age–period data in contingency tables, which is advocated and should be considered as key to forecasting future HCC mortality trends. 2. Methods 2.1. Data Sources To interpret the calculations, data on HCC mortality from 1976 to 2015 for both sexes were adopted to conduct the research in Taiwan from individual health records of the Ministry of Health and Welfare (MOHW). HCC mortality was categorized according to the International Classification of Disease (ICD) Code 150. Mortality data were accessible for three categories: ten five-year age groups (40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84, and 85+), eight five-year periods (1976–1980, 1981–1985, 1986–1990, 1991–1995, 1996–2000, 2001–2005, 2006–2010, and 2011–2015), and 17 birth cohorts (mid-cohort years: 1891, 1896, 1901, 1906, 1911, 1916, 1921, 1926, 1931, 1936, 1941, 1946, 1951, 1956, 1961, 1966, and 1971). Based on the above information, we computed the age-specific and age-adjusted mortality rates (using the 2000 World Standard Population) [18]. First, the mortality rate is denoted as i, age group as j, and the period group as λij in the following formula:logλij=μ+αi+βj+γk   i=1,2,…,I,j=1,2,…,J,k=j−i+I, Within the APC model, the intercept term is denoted as μ, the age effects as αi, the period effects as βj, and the cohort effects as γk. ∑iαi=∑jβj=∑kγk=0 The subsequent constraints are thus availed. 2.2. Multiphase Method with Weighted Regression Model in Obtaining the Measure of Cohort Effects The multiphase method follows a three-phase procedure, which allows for concrete evaluation of the cohort effect as a fragmentary interrelation of the data in the age–period contingency table [5,8]. Based on the log-additive effects as a constant term, with the addition of three elements—the age effect, period effect, and multiplicative interaction terms—we obtain the natural log rate (λij). As introduced in our previous research [19], there was a comprehensive description of the multiphase method with a weighted regression model in the context of gauging the cohort effects. The magnitude of cohort effects is calculated via the weighted regression of these residuals (εk) within the cohort category in the final procedure (cohort is viewed as an indicator variable and is expressed as a collection of the m + n − 1 cohorts such as k = 1, 2, …, m + n − 1). Members belonging to the birth cohorts who were included are expressed as Wk, symbolizing the weight of the kth cohort classification:εk=Wk×γk+εijk εk is set up with the help of a vector from cohort effects (γk) and error terms (εijk), where εijk stands for the error terms, and the unmeasured terms of age, period, and cohort categories are denoted as i, j, and k, respectively. The most extensively utilized factor in the number of deaths is the empirical weighting factor [20]. Furthermore, each of these weights is qualified for implementation in the regression equation. In line with the number of deaths caused by HCC in each cohort, the weighted average from the cohort effect can be demonstrated by the weight that is equivalent to the occupied proportion. As stated in the mortality in the cohort in question, age was computed as the removed and unremoved influence of the cohort on deciding the reference categories. Moreover, in terms of cohort-specific mortality, there was minimal dissimilarity in the reference categories of cohorts with and without cohort influence. Following the previous research [5], after discarding influencing elements, the reference concerning the birth cohort could be ascertained based on the minute variation in its rate. It should be noted that we estimated the cohort effects for men and women. 3. Results 3.1. HCC Mortality Rates Figure 1 and Figure 2 illustrate the HCC mortality rates for age and period groups in men and women. Variations are more notable among men than women. HCC mortality rates begin in the 40–44 age group, as demonstrated by the distribution of rates based on age (refer to Figure 1). HCC mortality rates then increase consistently from the mid-age range of those aged ≥60 years (Figure 2). However, the HCC mortality rates (Table 1) based on age are substantially altered with time, which indicates a significant cohort effect concealed by the habitual age-period cross-classified vital statistics table. Even in the distant future, the cohort effect still cannot be discerned. As for the median polish procedure, we factored it into the logarithm transformation from the HCC mortality rates. 3.2. APC Model The HCC mortality rates from the predicted cohort effects within the APC model are shown in Table 2 and Table 3, encompassing the weighted estimates obtained after following the weighted average procedure for both sexes. According to the smallest deviance (contrasted with the unweighted estimates), the range of the confidence interval (CI) was used as a criterion of accuracy. The unweighted effects of Table 2 provide the cohort effects under the birth cohorts. For men, the cohort effect rises from 0.73 (the earliest cohort effect in 1891) to 1.20 (the greatest cohort effect in 1936); for women (Table 3), the cohort effect rises from 0.68 (the earliest cohort effect in 1891) to 1.35 (the greatest cohort effect in 1936). Specifically, compared with the cohort in 1891, the cohort effects increase remarkably by approximately 51% and 68% for men and women, respectively. Conversely, the growth is evenly distributed in the weighted effects of Table 2, where the cohort effect increases from 0.71 (the earliest cohort effect in 1891) to 1.11 (the greatest cohort effect in 1936). In the same manner, the increased distribution for women is demonstrated in the weighted effects of Table 3, where the cohort effect rises from 0.64 (the earliest cohort effect in 1891) to 1.11 (the greatest cohort effect in 1926). Among all birth cohorts, the individuals with the highest risk of HCC mortality were the men who were born in 1936 (Table 1). In weighted estimates, the effect was 1.11 (95% CI: 1.083–1.145) for the birth cohort in 1936, contrasted with the reference birth cohort in 1921. In the prior cohorts, a steeply declining trend was detected, along with the effects that were demonstrated after the cohort in 1936. Additionally, we plotted the weighted and unweighted cohort effects with 95% CI for men and women (Figure 3 and Figure 4). In both figures, it is clear that most of the widths within the 95% CI of the weighed cohort effects are shorter than those of the unweighted ones. We placed a limit on our APC analysis within the median polish procedure to gauge the cohort effects, as well as the 95% CIs of the HCC mortality, and found that the residual errors (εijk) tended toward zero. 4. Discussion In summary, we found that most of the widths within the 95% CI of the weighed cohort effects were narrower than those of the unweighted ones. We also found the weighed cohort effects had a curvature trend that may dominate the long-term trends in HCC mortalities (Figure 5). In addition, this study may have identified significant cohort effects (or smaller standard errors) that should be considered in forecasting future HCC mortality trends. We checked and compared our previously published [16] and newly updated extra 5-year data in this study to make some information about HCC trend. For males, the prediction of a previous publication [16] may overestimate the HCC mortality rate (refer to Figure 5). For females, the prediction of a previous publication [16] may underestimate the HCC mortality rate (refer to Figure 5). Furthermore, we found that the trend of the prediction of a previous publication [16] may coincide directly with a reverse trend by observation on HCC mortality. Moreover, we conducted a predicted pattern for the short-term period due to the addition of extra 5-year HCC data from a previous publication [19]. To simplify the predicted pattern, we focused on the linear-extrapolated period effects [16] for prediction of the next 5-year time period (i.e., 2016–2020). Age effects still were suited for all age groups of the next time period, 2016–2020. The prediction of cohort effects would extend to the 18th cohort effects but conservatively keep its value the same as the 17th estimated value (i.e., 1971 birth cohort estimated value). It can be found that the trend reverses itself at the period (i.e., 2016–2020) for men and women (Figure S1). From the clinical perspective, as a consequence of the high morbidity, hepatitis B virus (HBV) infection is viewed as a vital health issue worldwide. There are approximately two billion people deemed contagious and 350 million people suffering from chronic HBV infection [21]. The most effective approach to prevent people from becoming infected is the hepatitis B vaccine. The earliest global hepatitis B large-scale vaccination program was put into practice in 1984 in Taiwan [22]. Pregnant women were screened using the HBsAg test, followed by HBeAg. Initially, the immunization scheme only included infants whose mothers were HBsAg carriers for the first two years. Every infant was then included in the third year of the vaccination program. Recently, the coverage ratio of hepatitis B vaccination increased to 99%. After receiving complete vaccine injections, approximately 90–95% of people will have acquired permanent immunity against the disease. Notably, owing to the effect of this worldwide vaccination program, there has been a decrease in pediatric HCC in Taiwan. Yet, the APC estimation still highlights cause for concern and caution regarding these growing trends, despite them having been reduced recently. The trend of the cohort effect was investigated in this research by utilizing the median polish procedure. The weighted estimates permitted an estimation of the weighted average concerning the effect of the tapering CI in each cohort. Using the cohorts in 1936, these results were delineated in the form of cohort effects, since there are few modifications in HCC mortality rates that are not influenced by the cohort, as shown in these categories. Amid the majority of modeling methodologies (e.g., models for linear or nonlinear regression), one of the ordinary presuppositions is that every authentic value in the data provides an estimation of the parameters inside an assured model with identical information. Accordingly, this signifies that the standard deviation from the error term is also known as the constant predictor variable. As investigated in our literature review, the assumption does not impose limits on modeling to estimate the parameters empirically. A smaller number of weights are supplied with slightly imprecise data points, and a greater number of weights are supplied with precise data points. In addition, being able to limit the standard deviation of the estimator is viewed as a benefit of the weighted procedure. Nonetheless, drawbacks of the weighted regression approach are often seen in empirical practice. In addition, the estimation of weight cannot be deployed to gauge the parameters, given that the correct weight figure is rarely known. Previous experience indicates that as a result of the estimation, the weighting is barely alterable and often is unaffected in the analysis or interpretation of regression [23]. Theoretically, when it comes to the APC model, diseases with rates dominated by age, period, and cohort effects comply. Furthermore, weighted-average estimates can be implemented for prediction [12,24,25]. It is generally recognized that the narrower the CI, the smaller the uncertainty. In our study, there were numerous limitations. First, we could only surmise the etiologies of the changes being observed during the research. According to the age, period, and cohort effects, HCC mortality is amenable to the APC model. Nevertheless, in this work, the presence of immutable suppositions for the median polish that we used should be taken into consideration. Second, APC analysis can be applied extensively in the field of epidemiology for populations living in developing or developed countries but has restrictions for long-running cohort studies. Third, for confounders such as comorbidity and lifestyle inside the APC model, the information from the aggregate dataset was not adequate for us to modify; additional studies using individual data are essential to resolve these restrictions. Fourth, when applying the regression procedure under the multiphase approach, the number of deaths attributed to HCC was utilized as the weight. Applying diverse weights may spark minor inflation of estimated cohort effects, as the explicit weight is almost pending. Forth, caution should be taken when comparing the HCC mortality trend between men and women given that the reference years are not the same among genders. Lastly, this type of circumstance may be compounded while adopting differing estimations of APC methods to tackle non-identifiable factors (e.g., Holford uses the linear and curvature trends to study a non-identifiable problem [26]). The median polish makes intricate conjectures concerning APC models by computing the cohort effect with minimal assumptions, simply adopting a typical format for contingency tables. In conclusion, in terms of adopting the regression model, the weighted estimate permits the effect of a weighted average with a narrower CI to be studied in every cohort. Overall, using the weighted estimate in the regression model is recommended in practice. This will support future research into health policy and preventative health strategies in Taiwan. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095573/s1, Figure S1: Observation and prediction of age-adjusted mortality in HCC for men and women in Taiwan. Click here for additional data file. Author Contributions Conceptualization, I.-S.T. and J.-H.C.; methodology, I.-S.T.; software, I.-S.T.; validation, I.-S.T. and J.-H.C.; formal analysis, I.-S.T.; investigation, I.-S.T.; resources, J.-H.C.; data curation, I.-S.T.; writing—original draft preparation, I.-S.T.; writing—review and editing, I.-S.T. and J.-H.C.; visualization, I.-S.T.; funding acquisition, J.-H.C. 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 secondary data analysis. Informed Consent Statement Not applicable. Data Availability Statement The data that support the findings of this study are available in Table 1 of this article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 HCC mortality rates for age and period groups in men. Figure 2 HCC mortality rates for age and period groups in women. Figure 3 Weighted and unweighted cohort effects with 95% CI for men. Figure 4 Weighted and unweighted cohort effects with 95% CI for women. Figure 5 Long-term trends in HCC mortalities from 1976 to 2015 for men and women. ijerph-19-05573-t001_Table 1 Table 1 Age–period contingency table of HCC mortality rate per 100,000 among men and women, Taiwan, 1976–2015. 1976–1980 1981–1985 1986–1990 1991–1995 1996–2000 2001–2005 2006–2010 2006–2015 Men 40–44 31.41 33.10 33.20 31.24 30.40 29.10 23.26 19.30 45–49 46.50 55.13 52.88 53.61 49.79 47.66 42.25 36.25 50–54 68.11 72.47 74.56 81.73 81.65 74.19 69.12 56.96 55–59 84.12 97.32 98.96 115.57 127.55 117.70 100.19 85.59 60–64 103.58 120.45 115.71 143.74 164.14 168.20 145.35 119.83 65–69 126.15 140.12 138.76 160.29 186.58 204.31 203.50 172.15 70–74 135.44 147.79 170.44 195.56 201.40 223.00 253.46 225.23 75–79 145.41 178.22 186.70 226.86 243.87 234.63 263.24 293.21 80–84 123.63 160.33 175.09 229.23 267.55 264.61 276.39 278.95 85+ 133.97 232.56 212.33 227.57 248.07 292.51 272.51 291.86 Women 40–44 6.75 6.14 4.90 5.11 3.46 2.88 3.03 2.44 45–49 11.99 11.10 9.21 9.76 6.49 5.76 4.90 3.79 50–54 18.20 16.23 14.78 15.53 14.15 11.78 10.20 8.17 55–59 27.57 30.06 24.45 28.43 28.65 28.04 23.68 18.34 60–64 35.23 39.48 41.09 44.75 55.75 52.97 48.01 37.94 65–69 43.49 54.68 52.09 66.36 76.92 89.05 82.80 73.44 70–74 50.40 61.49 65.48 87.47 111.46 130.60 131.32 123.96 75–79 66.47 72.02 77.57 105.09 127.37 153.26 160.98 170.88 80–84 60.12 74.79 81.83 101.26 139.41 175.41 184.90 209.80 85+ 54.22 82.91 71.93 103.98 132.42 169.12 196.03 214.09 ijerph-19-05573-t002_Table 2 Table 2 Estimated rate ratios and 95% conference intervals for effect of birth cohort on hepatocellular carcinoma mortality of men in Taiwan, 1891–1971. Cohort Unweighted Weighted (1891~1971) Effects 95% CI for Effects Effects 95% CI for Effects 1891 0.73 0.591–0.898 0.71 0.567–0.877 1896 0.88 0.795–0.986 0.87 0.784–0.967 1901 0.89 0.828–0.962 0.81 0.706–0.922 1906 0.91 0.859–0.967 0.85 0.777–0.940 1911 0.95 0.901–0.998 0.89 0.832–0.956 1916 1.01 0.970–1.062 0.99 0.950–1.027 1921 1.00 REF 1.00 REF 1926 1.04 0.997–1.079 1.03 1.007–1.060 1931 1.10 1.055–1.142 1.08 1.056–1.111 1936 1.20 1.149–1.243 1.11 1.083–1.145 1941 1.14 1.094–1.190 1.10 1.072–1.131 1946 1.04 0.997–1.092 1.06 1.036–1.093 1951 0.91 0.868–0.961 1.00 0.978–1.033 1956 0.87 0.817–0.921 0.96 0.927–0.985 1961 0.82 0.761–0.884 0.88 0.847–0.922 1966 0.76 0.685–0.849 0.79 0.740–0.834 1971 0.71 0.573–0.870 0.83 0.796–0.866 Note: REF = reference; CI = confidence interval. ijerph-19-05573-t003_Table 3 Table 3 Estimated rate ratios and 95% conference intervals for effect of birth cohort on hepatocellular carcinoma mortality of women in Taiwan, 1891–1971. Cohort Unweighted Weighted (1891~1971) Effects 95% CI for Effects Effects 95% CI for Effects 1891 0.68 0.423–1.099 0.64 0.378–1.090 1896 0.81 0.632–1.038 0.75 0.564–1.001 1901 0.80 0.669–0.951 0.70 0.516–0.944 1906 0.83 0.718–0.953 0.76 0.648–0.884 1911 0.88 0.778–0.994 0.85 0.779–0.935 1916 1.00 REF 1.00 REF 1921 1.12 1.011–1.243 1.08 1.031–1.125 1926 1.29 1.169–1.422 1.11 1.065–1.159 1931 1.30 1.178–1.432 1.10 1.053–1.147 1936 1.35 1.224–1.490 1.09 1.044–1.139 1941 1.19 1.073–1.320 1.08 1.035–1.129 1946 1.05 0.937–1.170 1.06 1.019–1.112 1951 0.83 0.735–0.939 1.00 0.961–1.049 1956 0.67 0.579–0.768 0.93 0.890–0.977 1961 0.58 0.487–0.692 0.79 0.740–0.843 1966 0.59 0.458–0.752 0.58 0.490–0.689 1971 0.63 0.394–1.023 0.64 0.577–0.721 Note: REF = reference; CI = confidence interval. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Balogh J. Victor D. 3rd Asham E.H. Burroughs S.G. Boktour M. 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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093412 sensors-22-03412 Article Simultaneous Extraction of Planetary Boundary-Layer Height and Aerosol Optical Properties from Coherent Doppler Wind Lidar https://orcid.org/0000-0003-3745-907X Chen Yehui 123 Jin Xiaomei 13 Weng Ningquan 13* Zhu Wenyue 13 Liu Qing 13 https://orcid.org/0000-0003-2534-8655 Chen Jie 123 Kang Zhizhong Academic Editor 1 Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; yehuich@mail.ustc.edu.cn (Y.C.); xmjin@aiofm.ac.cn (X.J.); zhuwenyue@aiofm.ac.cn (W.Z.); liuqing@aiofm.ac.cn (Q.L.); jiechen@mail.ustc.edu.cn (J.C.) 2 Science Island Branch of Graduate School, University of Science and Technology of China, Hefei 230026, China 3 Advanced Laser Technology Laboratory of Anhui Province, Hefei 230037, China * Correspondence: wnq@aiofm.ac.cn 29 4 2022 5 2022 22 9 341215 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/). Planetary boundary-layer height is an important physical quantity for weather forecasting models and atmosphere environment assessment. A method of simultaneously extracting the surface-layer height (SLH), mixed-layer height (MLH), and aerosol optical properties, which include aerosol extinction coefficient (AEC) and aerosol optical depth (AOD), based on the signal-to-noise ratio (SNR) of the same coherent Doppler wind lidar (CDWL) is proposed. The method employs wavelet covariance transform to locate the SLH and MLH using the local maximum positions and an automatic algorithm of dilation operation. AEC and AOD are determined by the fitting curve using the SNR equation. Furthermore, the method demonstrates the influential mechanism of optical properties on the SLH and MLH. MLH is linearly correlated with AEC and AOD because of solar heating increasing. The results were verified by the data of an ocean island site in China. planetary boundary layer (PBL) aerosol extinction coefficient (AEC) aerosol optical depth (AOD) wavelet covariance transform (WCT) dilation operation Anhui Provincial University Natural Science Research ProjectKJ2021A1161 This research was funded by the Anhui Provincial University Natural Science Research Project (KJ2021A1161). ==== Body pmc1. Introduction The lowest atmospheric layer of the earth is marked by a planetary boundary layer (PBL). There is a variable daily convolution in the structure and composition of the PBL [1]. During the daytime, the PBL is mainly composed of the surface layer (SL), mixed layer (ML), and entrainment zone. During the nighttime, the ML collapses into the nocturnal boundary layer (NBL) and residual layer (RL) [2]. Furthermore, the mixing and residual layers coexist during the sunrise and sunset [1,3]. Atmospheric variables such as potential temperature, aerosol concentration, and specific humidity usually experience sharp gradients at the top of the PBL. Thus, some measurements of PBL height (PBLH) were proposed based on the characteristics of these variables [4]. Additionally, the optical properties including extinction coefficient and optical depth were employed to represent aerosols, including the total amount of pollutants [5,6], which were determined by the size distribution [7,8] of aerosol formation, which was affected by relative humidity (RH) and temperature (T) [9]. There is a complex interaction between PBL height and aerosols and statistical associations between PBL height and levels of pollutants [5,10,11,12,13]. Thus, the PBLH is an important physical quantity for atmosphere environment assessment [14,15,16,17]. These measurement techniques were mainly implemented by microwave radiometer [14], ceilometers [18,19,20], and lidar, including Mie-scattering lidar [21,22] and coherent Doppler wind lidar (CDWL) [23]. The microwave radiometer is based on the thermodynamic properties of the atmosphere for potential temperature and specific humidity [24]. Ceilometers are single-wavelength micro-lidars intended for cloud-base height detection and are ubiquitous in airports and meteorological service centers worldwide [20]. The Mie-scattering lidar employs back-scattering signals to monitor aerosol concentrations [25]. CDWL data are related to the average wind speed [26]. These techniques have been proposed to combine with several algorithms to accurately detect the PBLH based on the sharp gradient. Some algorithms [4] include visual inspection, the threshold method, the gradient method, ideal profile fitting (FIT) [25], wavelet covariance transform (WCT), and variance (or standard deviation) analysis. Many studies have shown that the retrieved PBLH of lidar instruments is in good consistency with the radiometer [27]. However, the accuracy of the PBLH was influenced by multiple-layer aerosol layers and cloud layers [28]. Some methods were proposed to combine some different algorithms, such as combining WCT with the ideal curve-fitting (ICF) algorithm [25], combining WCT with the threshold for a range-corrected signal, and combining WCT with depolarization [3]. The PBL contains aerosols of the low troposphere. The optical properties of aerosols mainly include the aerosol extinction coefficient (AEC) and aerosol optical depth (AOD). It was pointed out that PBLH decreased sharply with the increase of aerosol load [29]. A two-component fitting method is employed to find an accurate AEC as the boundary value in Mie-scattering lidar [30]. However, the boundary value is determined by the empirical back-scattering ratio, which is measured by combining auxiliary sensors, such as a sun photometer [30]. Furthermore, the hundreds of meters of the blind zone and the transition zone in traditional Mie-scattering lidars [31,32] always lead to a difficulty in probing aerosols in the lower troposphere [33], since the biaxial lidars are in parallel to the laser and telescope axes. In addition, CDWL can also be used to estimate the MLH based on the signal-to-noise ratio (SNR) by combining with WCT [23]. However, there are multiple local maximum positions that are manually chosen to determine the PBL. Thus, an automatic PBL extracting algorithm is needed to speed up the determination process. The existing studies on the interaction between aerosols and the PBL are mainly based on short-term numerical simulations [34] and long-term comprehensive observations [35]. The main influence of aerosols on the PBL is the cooling effect on the surface and the heating effect on the atmosphere. The aerosol extinction in the atmosphere (including the scattering and absorption of sunlight) will reduce the short-wave radiation of the sunlight reaching the surface, so the surface heat flux drives the development of the PBL. In these methods, a lidar and a sunphotometer were synthetically applied to monitor the PBLH, and AOD or AEC, respectively. The AEC and AOD depend on the wavelength of light, and the wavelengths of the sunphotometer and lidar are different. However, no attempt has been made to simultaneously determine the PBLH, AOD, and AEC based on the same lidar. In this study, the atmospheric boundary layer and the optical properties of aerosols are implemented by employing CDWL and WCT based on two local maximum positions with an automatic algorithm. In this work, the surface-layer height (SLH) and mixed-layer height (MLH) were simultaneously extracted based on wavelet covariance transform with an automatic algorithm, due to the sharp gradient on the boundaries of SL and ML. Meanwhile, the optical properties including AEC were estimated by linear fitting in the range from SLH to MLH, and the AOD was calculated by AEC-times depth. Then, the relationship between optical properties, the SLH, and MLH were quantitatively characterized for an ocean island site in China. 2. Materials and Methods 2.1. Study Area The measurements were carried out at the observation site in the ocean island site, which is located in the south of China with a tropical maritime monsoon climate. The weather around the site is summer-like the whole year, the highest temperature is 32 °C, and the lowest temperature is 20 °C due to the effect of the ocean. The prevailing period of the northeast monsoon is from October to March of the next year, and the prevailing period of the southwest monsoon is from May to September. The rainy period is from June to November and the dry period is from December to May of the next year. Rainless and sunny weather in December was selected as the observation object, and the observation site is far from the city and less affected by emissions from industries, vehicles, and other anthropogenic activities. The aerosols in ocean islands are mainly composed of sea salt aerosols. 2.2. Experimental Instruments The measurements were performed by a CDWL (Windprint S4000, Qingdao Aerospace Seaglet Environmental Technology Ltd., Qingdao, Shandong, China), whose technical specification is shown in Table 1. The vertical resolution and temporal resolution of this CDWL are 30 m and 1 s, respectively. The telescope was designed with a diameter of 40 m and a focal length of 1000 m. The blind zone of CDWL is 60 m. The typical SNR image, which includes successive 180 measurements, is shown in Figure 1a. The SNR of one measurement and the average SNR of the successive 180 measurements are demonstrated in Figure 1b. The PBL is in the range of red rectangular area and the AEC of PBL is homogeneous. This work presents an automated algorithm to simultaneously extract the PBLH and AEC. The weather in December was chosen for typical case to verify the feasibility of the proposed method. The continuous sample data of 24 h by the CDWL was used to study the daily evolution of PBLH and the optical properties of the aerosol. 2.3. SNR of Coherent Doppler Wind Lidar (CDWL) The SNR of the CDWL mainly depends on four factors: the average direct detection power, the heterodyne efficiency, the wavelength λ, and the receiver bandwidth B [36]. Under the conditions of negligible refractive-turbulence effects, the matched filter B=1τ, where τ is the pulse duration and far-field operation, the peak of SNR depends on the altitude z, and can be expressed as [37]:(1) SNRz=πηQUTλβD2Tzm28hBz2∝Tzm2z2 where ηQ is the quantum efficiency of the detector, h is the Planck constant, UT is the transmitting pulse energy, β is the back-scattering coefficient, and D is the diameter of laser beam. Tzm=exp−∫0zmαrdr is the dimensionless one-way irradiance extinction at wavelength λ, and α(m−1) is the linear AEC along the propagation path. Figure 1b shows the typical SNR in terms of altitude z. 2.4. WCT The Haar wavelet is discontinuous and usually applied to the location of the PBL due to its superior spatial location and computational efficiency. The Haar wavelet function can be expressed as:(2) hz−ba=−1b−a2≤z≤b+1b≤z≤b+a20otherwise where z is the altitude, a is the dilation of the function, and b is the center of the Haar function. The Haar wavelet function is shown in Figure 2a and the WCT of the Haar function is defined using Equation [38]:(3) Wfa,b=a−1∫zbztfzhz−badz where zt and zb are the spatial ranges in the profile, f(z) is the profile as a function of altitude and the normalization factor, and a−1, is the inverse of the dilation. The first step in the algorithm to determine the PBLH is to define the dilation of the Haar function values. Figure 2b indicates the WCT of SNR with different dilation. The minimum of WCT was chosen as an objective parameter to find its optimal value of dilation. Figure 2c shows the minimum of WCT dependent on the dilation, and the position of the minimum value was chosen as the appropriate dilation for Haar function. The corresponding dilation is 60 m. The WCT was applied to the profile with the dilation of 60 m for the Haar function. Figure 3 demonstrates that the position Pa is identified by the local minimum value in the resulting wavelet covariance profile and indicates the height of the strongest decrease of SNR. The altitude of 180 m can be considered as the SLH that is larger than the blind zone of 60 m. Pb is determined by the local minimum value in absolute value of Wfa,b, which means the local minimum value of SNR, and the height could be seen as the MLH with an altitude of 840 m. The SLH and MLH are consistent with the results in reference [2]. The local maximum positions of absolute WCT can be automatically determined by dilation operation, which is defined as I⊕E=maxb∈E[I(x+b)−E(b)], where I represents the signal and E denotes the structuring element [39]. The dilation operation has a filtering effect that suppresses dark regions smaller than structuring elements and results in the enlargement of bright ones. The dilation operation can be recast into maximum operation on structuring elements. 2.5. AEC and AOD The aerosols in the atmosphere in the range from Pa to Pb can be seen as roughly randomly distributed particles in PBL, and the corresponding linear extinction coefficients can be regarded as homogeneous [40]. Thus, the irradiance extinction T can be given by T=exp−αPb−Pa at the PBL. The linear extinction coefficient α can be obtained by the fitting curve of Equation (1) when the boundaries of layers are obtained by local minimum values in the resulting wavelet covariance profile. Equation (1) made the logarithmic transform and can be expressed as:(4) logSNRz=−2αrz−2logz Furthermore, the corresponding AOD at the wavelength of 1550 nm is defined by [35]:(5) AOD=αrPb−Pa To sum up, Figure 4 demonstrated the flowchart to determine the four parameters including SLH, MLH, AEC and AOD. 3. Results Figure 5 demonstrates that the typical SLH and MLH, which are extracted from the mean of 180 measurements of SNR, depend on the local time during the whole day. During the daytime, the PBLH is identical to the MLH. During the nighttime, the MLH collapses into the nocturnal boundary layer (NBL) and residual layer (RL). The MLH is identical to the height of the NBL. In addition, Figure 5a,b indicate that the MLH is negatively correlated with AEC and positively correlated with AOD in terms of the local time. Figure 5c,d demonstrate that the linear fitting curves of the MLH depending on AEC and AOD can be expressed as: MLH=K1×AEC+C1, and MLH=K2×AOD+C2, where K1 and K2 are constants, and C1 and C2 denote constants which do not affect the result. Their correlation coefficients R are 0.67 and 0.65, respectively. The linear functions of the SLH dependent of AEC and AOD are given by: SLH=K3×AEC+C3, and SLH=K4×AOD+C4, where K3 and K4 are positive constants, and C3 and C4 are constants. However, their correlation coefficients R are relatively small, and the values of R are 0.51 and 0.16, respectively. MLH is linearly correlated with AEC and AOD, and Figure 6a demonstrates that the slopes K1 of the MLH dependent on AEC are negative, and the slopes of K2 of the MLH linearly dependent on AOD are positive, which means that the MLH decreases while the AEC is increasing, and the MLH increases while the AOD is increasing. The reason is that solar heating increases in the ML while the strength of capping inversion decreases, leading to a rise in the MLH and decrements in AEC. There is a positive relationship between the MLH and AOD and a negative between MLH and AEC. The difference is that the effect of increment of MLH on AOD is greater than that of the decrement of AEC. Thus, the effect that solar heating increases in the MLH is greater than the effect of MLH on AEC. SLH is linearly correlated with AEC and AOD, and Figure 6b shows the distribution of the slopes K3 and K4 in eight successive days. The values are sometimes positive and sometimes negative, which means that the linear fitting curves of SLH dependent on AEC and AOD are complex. The reasons are the multiple factors such as the cooling effect of the surface enhanced with the increase of AOD and aerosols with human activity. In order to study the factor of aerosols with different sizes on AEC, the data of PM2.5 and PM10 are obtained from the National Urban Air Quality data of the Ministry of Ecology and Environment, PRC [41]. Figure 7a indicates the positive correlation between AEC and aerosols (PM2.5 and PM10) during the local time. The Pearson correlation coefficient provides a measure of the strength of the linear association between two variables [42], and it is found that the correlation coefficient between the derived AEC and aerosols (PM2.5 and PM10) are 0.1026 and 0.5890, which suggested that aerosol of PM2.5 plays an important role in the determination of AEC. Additionally, Figure 7b demonstrates that there are positive statistical associations between AEC and the mean of wind speed, which is estimated by the same CDWL. However, AOD is not positively related to the mean wind speed. Thus, the factors considered for AEC are much simpler than AOD. The comparison of the AEC with the optical absorption coefficient (OAC) is based on photoacoustic spectroscopy at the wavelength of 1064 nm [43], and it is found that the trend of the AEC is highly correlated with the OAC, shown in Figure 8a. Furthermore, the reference data of AOD and MLH were obtained from EAC4 (ECMWF Atmospheric Composition Reanalysis 4) [44], which is the fourth generation ECMWF global reanalysis of atmospheric composition, and reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using a model of the atmosphere based on the laws of physics and chemistry. Figure 8b,c demonstrate that the trends of AOD and MLH are related to that in EAC4. Thus, it is feasible that the simultaneous extraction method of the planetary boundary-layer height and aerosol optical properties can be obtained from coherent Doppler wind lidar. 4. Discussion AEC is the result of both absorption and scattering [40]: aext=n(Cabs+Csca), where n is the number of particles per unit volume, and Cabs and Csca are the absorption and scattering cross-sections, respectively. The light with a wavelength of 1550 nm passing through aerosols is attenuated almost entirely by scattering. The scattering cross-section depends on the size of the aerosols. It was found that the vertical meteorological parameters, such as relative humidity and temperature, and the aqueous and heterogeneous atmospheric chemical reactions altogether led to the aerosol formation [9] and resulted in different size distributions. Additionally, other parameters such as wind, rainfall, and even the emission rates will change the number of particles in unit volume n in the physical view. Thus, the AEC is affected by many parameters. In this study, the signal-to-noise ratio of CDWL had been used to simultaneously extract four parameters, including SLH, MLH, AEC, and AOD, which simultaneously monitor the daily evolution of both the PBL height and the optical properties of aerosols and their relationships. Although the interaction between the aerosols and the PBL height is highly complicated, there is a positive relationship between MLH and AOD, and negative with AEC, which suggests that the effect of the increment of MLH on AOD is greater than that of the decrement of AEC. Thus, the effect that solar heating increases in the MLH is greater than the effect of MLH on AEC. In this work, CDWL was used for measuring both PBLH and optical properties, since the system has a smaller blind zone than traditional Mie-scattering lidar due to the coaxial design of CDWL with the telescope axis. In addition, SLH can be extracted by the CDWL, which is difficult to estimate in Mie-scattering lidar. Ruijun Dang, et al. [4] had made a review of techniques for measuring the atmospheric boundary-layer height (ABLH) or the MLH using aerosol lidar. In their review, many studies on measurements of ABLH were based on range-corrected SNR (RCSNR). The RCSNR can be obtained by Equation (1) multiplying z2, which can be expressed as [4]:(6) RCSNRz∝Tzm=exp−∫0zmαrdr Classical WCT methods were also applied for extracting the ABLH or MLH. When the Haar wavelet function h encounters a sharp drop in RCSNR, a local maximum in Wfa,b occurs, indicating a step change in the RCSNR located at b with a coherent scale of a. Therefore, the ABLH is defined as the location of b, where the Wfa,b reaches its maximum. Figure 9 shows the RCSNR and the corresponding WCT and demonstrates that the local maximum of WCT of RCSNR is at the altitude of 120 m. It is lower than 180 m, as shown in Figure 3. Thus, the local maximum of WCT of RCSNR is the location of SLH, which is consistent with the classical WCT method. However, the classical method cannot obtain the MLH, and the AEC between the SL and ML cannot be estimated. In order to overcome it, the local minimum values of WCT based on RCSNR are employed at the location of altitude of 900 m, which is smaller than the 840 m extracted by our algorithm. Therefore, the MLH can be defined as the local minimum values of the WCT of RCSNR. In addition, the cloud has a strong effect on the accurate extraction of PBLH, and the opening filter, which is defined as the two sequential compositions of erosion and dilation, can be first applied to the SNR image to reduce the cloud before the mean of 180 measurements of SNR. Figure 10a shows that the bright spots are the clouds due to the strong scattering, and the clouds can be filtered with an opening operation, as shown in Figure 10b. 5. Conclusions In this study, a method of simultaneously extracting the SLH, MLH, and optical properties based on the SNR of the same CDWL was presented. The method employed WCT to locate the SLH and MLH, and optical properties including AEC and AOD were determined by the fitting curve using the SNR equation. In addition, the effects of optical properties on the SLH and MLH were qualitatively studied for an ocean island site in China. The results preliminarily demonstrated that MLH is linearly correlated with AEC or AOD because of increasing solar heating. Furthermore, there is a positive relationship between MLH with AOD and negative with AEC, which suggests the effect that solar heating increases in the MLH are greater than the effect of MLH on AEC. However, the effect of optical properties on SLH is complex. Thus, this work provides an effective method for understanding the aerosol effect on PBL in the same location. Author Contributions Conceptualization, N.W. and W.Z.; methodology, Y.C.; software, X.J.; validation, X.J., Q.L. and J.C.; formal analysis, Y.C.; investigation, Y.C.; resources, Q.L.; data curation, Q.L.; writing—original draft preparation, Y.C.; writing—review and editing, N.W. and Q.L.; visualization, X.J.; supervision, N.W. and Q.L.; project administration, N.W. and W.Z.; funding acquisition, Y.C. 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 (a) SNR image of successive 180 measurements, (b) SNR of one measurement, and the average SNR of 180 successive measurements. The PBL is in the red rectangular area. The green dashed line denotes the top of PBL, which can be considered as the MLH. Figure 2 (a) Plot of the Haar wavelet function, (b) WCT of SNR at the different dilation, and (c) the minimum of WCT depending on dilation. Figure 3 SNR and WCT of SNR in terms of altitude. A and B denote the local minimum values of WCT of SNR and the absolute value of WCT of SNR, and the corresponding altitudes are labeled with Pa and Pb, respectively. Figure 4 Flowchart for determination of SLH/MLH and its AEC/AOD. Figure 5 (a) SLH, MLH, and AEC during local time, and (b) SLH, MLH, and AOD during local time. MLH is a linear relationship with (c) AEC and (d) AOD. Figure 6 (a) Slope of MLH depending on AEC and AOD, (b) slope of SLH depending on AEC and AOD for successive 8 days. Figure 7 (a) The correlation between AEC and aerosols with different sizes including PM2.5 and PM10 during the local time, (b) statistical associations between AEC and mean of wind speed, and (c) AOD and mean of wind speed during local time. Figure 8 (a) The trend of the AEC and optical absorption coefficient, (b) the correlation between AEC and air quality, including PM2.5 and PM10 during the local time, and (c) the MLH correlation during the local time. Figure 9 RCSNR and WCT of RCSNR in terms of altitude. C and D denote the local maximum and minimum values of WCT of RCSNR. Figure 10 (a) Lidar image destroyed by the clouds, (b) filtered lidar image with the morphological opening operation. sensors-22-03412-t001_Table 1 Table 1 Technical specifications of Windprint S4000. Parameter/Unit Value Wavelength/nm 1550 Pulse repetition rate/kHz 10 Pulse energy/uJ ≥150 Pulse width/ns 100 Power consumption/W <300 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Cohn S.A. Angevine W.M. Boundary Layer Height and Entrainment Zone Thickness Measured by Lidars and Wind-Profiling Radars J. Appl. Meteorol. 2000 39 1233 1247 10.1175/1520-0450(2000)039<1233:BLHAEZ>2.0.CO;2 2. Stull R.B. An Introduction to Boundary Layer Meteorology Springer Dordrecht, The Netherlands 1988 10.1007/978-94-009-3027-8 3. Bravo-Aranda J.A. de Arruda Moreira G. Navas-Guzmán F. Granados-Muñoz M.J. Guerrero-Rascado J.L. Pozo-Vázquez D. Arbizu-Barrena C. Olmo Reyes F.J. Mallet M. Alados Arboledas L. 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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/ijerph19095773 ijerph-19-05773 Article Analysis of Environmental and Pathogenic Bacteria Attached to Aerosol Particles Size-Separated with a Metal Mesh Device Yin Xiaobo 1 Kamba Seiji 1 Yamamoto Koki 1 Ogura Atsushi 1 Wandera Ernest Apondi 2 Shah Mohammad Monir 3 Seto Hirokazu 4 Kondo Takashi 5 Ichinose Yoshio 2 Hasegawa Makoto 1* 1 Graduate School of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama 526-0829, Japan; b112023@m.nagahama-i-bio.ac.jp (X.Y.); pxg02010@nifty.com (S.K.); koki.yamamoto@riken.jp (K.Y.); a_ogura@nagahama-i-bio.ac.jp (A.O.) 2 Kenya Research Station, Institute of Tropical Medicine, Nagasaki University, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan; eawandera@gmail.com (E.A.W.); ichinose@nagasaki-u.ac.jp (Y.I.) 3 Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan; shah@nagasaki-u.ac.jp 4 Department of Chemical Engineering, Fukuoka University, 8-19-1 Nanakuma, Jonan-ku, Fukuoka 814-0180, Japan; hirokazuseto@fukuoka-u.ac.jp 5 Murata Manufacturing Co., Ltd., 1-10-1 Higashikotari, Nagaokakyo 617-8555, Japan; takashi_kondo@murata.com * Correspondence: m_hasegawa@nagahama-i-bio.ac.jp; Tel.: +81-749-64-8100 09 5 2022 5 2022 19 9 577324 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/). Metal mesh devices (MMDs) are novel materials that enable the precise separation of particles by size. Structurally, MMDs consist of a periodic arrangement of square apertures of characteristic shapes and sizes on a thin nickel membrane. The present study describes the separation of aerosol particles using palm-top-size collection devices equipped with three types of MMDs differing in pore size. Aerosols were collected at a farm located in the suburbs of Nairobi, Kenya; aerosol particles were isolated, and pathogenic bacteria were identified in this microflora by next-generation sequencing analysis. The composition of the microflora in aerosol particles was found to depend on particle size. Gene fragments were obtained from the collected aerosols by PCR using primers specific for the genus Mycobacterium. This analysis showed that Mycobacterium obuense, a non-tuberculous species of mycobacteria that causes lung diseases, was present in these aerosols. These findings showed that application of this MMD analytical protocol to aerosol particles can facilitate the investigation of airborne pathogenic bacteria. aerosol bioaerosol next generation sequencing metal mesh devices (MMDs) particulate matter pathogenic bacteria A-STEP Matching Planner Program 2015MP27115658977 Japan Science and Technology AgencyCooperative Research Grant from NEKKENIppan-21 Institute of Tropical Medicine, Nagasaki UniversityThis research was funded by the A-STEP Matching Planner Program 2015, project number: MP27115658977, Japan Science and Technology Agency, and a Cooperative Research Grant from NEKKEN: Ippan-21, 2017, Institute of Tropical Medicine, Nagasaki University. ==== Body pmc1. Introduction The rapid separation and detection of aerosol particles in the field is essential for the assessment of environmental pollutants [1,2]. Aerosols, also called particulate matter (PM), have been shown to cause lung diseases when inhaled by humans, leading to their legal regulation in many countries. Of particular concern are particles <10 μm in diameter (PM10), which can invade the lungs, and particles <2.5 μm in diameter (PM2.5), which can invade deep lung tissue and the subepithelial environment. These fine particles have been shown to adversely affect health through oxidative stress and are associated with risks of allergies, asthma, cardiovascular diseases, and silicosis/pulmonary fibrosis [3,4,5,6]. In addition, since soil, water, sewage, and animal waste are major sources of aerosols, bacteria and viruses in these materials can bind to various kinds of aerosol particles, which contributes significantly to their widespread distribution. Among these aerosol particles, PM2.5 is expected to be associated with the transmission of respiratory infections because of its small size, which allows it to penetrate deeply into the respiratory system. Indeed, PM2.5 concentration is a factor related to bacterial community structure in air [7,8]. Several studies have assessed bioaerosols in natural environments. For example, pathogens detected in dust obtained from arid climates in Africa have been associated with local infections and allergies [9,10,11]. The effects of environmental bioaerosols have also been evaluated. For example, workers in the waste recycling industry, who are often exposed to very high levels of microorganisms, have high respiratory symptoms and airway inflammation [1]. In addition, occupational and non-occupational exposure to legionella bacteria in bioaerosols has been found to cause legionellosis [12,13,14]. These legionella bacteria have been found in many aquatic environments, including natural and artificial water systems, such as bathrooms, cooling systems, and water misting systems, leading to legionellosis outbreaks. Epidemiological studies have assessed the transmission by aerosols of infectious diseases, including Kawasaki disease [15] and SARS [16,17]. In addition, the recent worldwide outbreak of SARS-CoV-2 shows that airborne infections caused by bioaerosol inhalation can limit human activities and pose a risk of serious economic damage to society [18,19,20]. Aerosols are frequently collected by filtration because of the convenience of collecting samples using relatively little equipment [9,10,11,21]. Our research group has developed novel membrane filters, called metal mesh devices (MMDs), to fractionate PM for qualitative and quantitative evaluation. MMDs consist of a periodic structure of square apertures of characteristic size, arranged on a thin nickel membrane. In contrast to common synthetic resin membrane filters, MMDs have uniform pores and thus exhibit superior size-exclusion separation [22]. In addition, MMDs can only transmit electromagnetic waves in the frequency range determined by their periodic structure [23]. Because this optical property is dependent on the amount of material trapped on the MMDs, these membranes can be employed as label-free optical sensors. MMDs have been shown to easily separate and detect proteins, DNA, and living cells, as well as to fractionate and evaluate PMs both qualitatively and quantitatively [24,25]. The present study describes the development of a method to evaluate airborne bacteria, combining precise fractionation using MMDs and metagenomic analysis using next-generation sequencing (NGS). The aim of this study is to establish a method for evaluating airborne bacterial flora, which are difficult to evaluate using conventional methods, and to assess the associations between PMs and airborne bacteria for use in infection prevention. An analytical protocol that included a simple collection method for bioaerosols was therefore established. Tuberculosis is a serious health problem in developing countries in Africa [26]. Because tuberculosis is an airborne infectious disease, analysis of bioaerosols may lead to a method to prevent infection. Thus, bioaerosols were collected and analyzed using MMDs during the dry season, when the climate is stable, from a farm in Githunguri District, a suburb of Nairobi County, Kenya. The farm was considered a suitable site for a first trial of this technology because a relatively diverse range of plants and livestock are cultivated at the farm, suggesting that the bacterial flora would be diverse. Bacterial DNA was extracted from these collected aerosol particles and subjected to metagenomic analysis to evaluate the bacterial composition in the air. The results of these analyses demonstrated that MMDs could fractionate aerosol particles by size, enabling the subsequent analysis of microflora and the detection of specific pathogens in the collected samples. 2. Materials and Methods 2.1. Preparation of the MMD Filter Units Figure 1A and Table 1 show the dimensions of single unit cells of three types of MMDs. The MMDs were made from nickel and were manufactured using the electroforming method. The MMDs were washed three times with 99.5% ethanol and pure water. After complete drying, the MMDs were irradiated with excimer light (wavelength: 172 nm) generated by an Excimer Photon Source Power Supply (Ushio Inc., Tokyo, Japan) filled with N2 gas. Each MMD was fixed in a polyacetal cover with an opening 6 mm in diameter (Figure 1B). 2.2. Collection of Aerosol Particles A new type of portable air suction device was fabricated to capture aerosols from the air (Figure 2). The two small air suction elements of this device are battery powered and can draw 2 L/min (static pressure) of air from the air suction port. A stack of three types of MMDs, fixed in the order of 4.5 μm, 1.8 μm, and 1.0 μm MMDs, were placed at the suction port of this device, thus allowing air to pass through the MMDs. Suction was applied for about 12 h at an air suction volume of about 1440 L, and the aerosol particles in the air were separated by the three types of MMDs. Aerosols were collected on three separate days, starting on 14 September 2016, at a farm in Githunguri, a suburb of Nairobi, Kenya. With the approval of the farm owner, a suction device was placed on the roof of a cowshed in open air. Air was suctioned during the daytime on sunny days, with nine samples being collected. Temperature and humidity were recorded as meteorological conditions. Collected MMDs containing aerosols were stored under sterile containers at 4 °C. 2.3. Analysis of Particle Size Distribution The surfaces of the MMDs were evaluated by scanning electron microscopy (SEM; S-3400N, Hitachi High-Tech Co., Tokyo, Japan). Four SEM images of each MMD were evaluated and the contour shapes of the particles were determined using ImageJ/Fiji image analysis software. Distribution graphs of particle size indicated by the long-axis diameter were generated using OriginPro (Version 2021b, OriginLab Corporation, Northampton, MA, USA). 2.4. Particle Counting by IR Transmittance Measurements The transmittance IR spectra of the 1.8 μm MMD were acquired using Fourier transform infrared spectroscopy (FT/IR-6600, JASCO International Co., Ltd., Tokyo, Japan). The wavenumber resolution, cumulative number, and diameter values were set to 2 cm−1 (0.06 THz), eight measurements, and 6 mm, respectively. A previously described method was used to estimate the number of aerosol particles from the frequency shift [23,24]. The frequency shift (−Δƒ) was calculated from the difference in the dip of the transmittance peak before and after the capture of aerosol particles and was corrected by subtracting the frequency shift of the MMD not exposed to aerosol particles. The calibration curve for obtaining the number of particles for these frequency shift values was prepared as follows. The aerosol was collected in Nagahama, Japan and the number of particles on the MMD was counted using a phase contrast microscope (CX31, Olympus Co., Tokyo, Japan) at a magnification of 200×. The average number of particles present in an area of 500 μm × 500 μm (n = 3) was calculated to obtain an estimate of the surface area of the MMD (28.3 mm2). The number of aerosol particles collected in Kenya was estimated using a calibration curve obtained using 1.8 μm MMDs. 2.5. Extraction of DNA from Aerosol Particles DNA was extracted from the collected aerosols using NucleoSpin® Soil kits (Takara Bio Inc., Shiga, Japan). Briefly, MMDs containing aerosols were removed from the polyacetal containers and transferred to NucleoSpin® soil bead tubes containing ceramic beads. DNA was subsequently extracted using the protocol described by the manufacturer, with each sample yielding 40 μL of the final DNA extraction solution. 2.6. Preparation of 16S rDNA Samples The V3–V4 region of 16S rDNA in the DNA samples extracted from the aerosol particles was PCR amplified on a PCR thermal cycler SP (Model. TP400, Takara Bio, Kusatsu, Japan), using the primers 341F/R805 (Table 2) [27,28]. Each 50 µL reaction mixture contained 12 µL of DNA template, Tks Gflex™ DNA polymerase (Code. R060A, Takara Bio, Kusatsu, Japan), and 1 µM of each primer. The amplification protocol consisted of 40 cycles of denaturation at 94 °C for 30 s, annealing at 50 °C for 30 s, and extension at 72 °C for 30 s. Indexed NGS adapters were attached to each amplified DNA fragment isolated by the PCR products purification kit. Eight sets of forward primers (D501-08, Illumina Inc., San Diego, CA, USA) and two sets of reverse primers (D709-710, Illumina, San Diego, CA, USA) were used. A second PCR amplification was performed using the same protocol as above. Amplified DNA fragments were isolated from each solution using magnetic beads DNA isolation kits (AMPure XP, Beckman Coulter Inc., La Brea, CA, USA), with the quality of the 16S rDNA fragments determined using a capillary electrophoresis device (MultiNA, Shimadzu Co., Kyoto, Japan). DNA concentrations were measured using Qubit dsDNA HS assay kits (Thermo Fisher Scientific Inc., Waltham, MA, USA) and a Qubit fluorometer (Thermo Fisher Scientific, Waltham, MA, USA). 2.7. Metagenomic Analysis Based on 16S rDNA Sequence Data The sequences of the obtained 16S rDNA samples were determined by NGS sequencing (Miseq, Illumina, San Diego, CA, USA), with the 16S rDNA sequences analyzed using the QIIME2 (Quantitative Insights Into Microbial Ecology; 2020.8) microbiome bioinformatics platform 15 [29,30]. To eliminate noisy reads, DADA2, a plugin for QIIME2, was used to eliminate sequence data with a quality score of <25 for both forward and reverse reads, with the remaining 75% of the data was used for further analysis. The clustering sequences from these data were treated as operational taxonomic units (OTUs), allowing their classification into species or genera by taxonomic analysis with reference to the Greengenes database [31]. 2.8. Detection of the Genus Mycobacterium Multiplex PCR was performed using primers specific for the 16S rRNA gene of Mycobacterium spp. (Table 2) [32,33]. Each reaction solution contained template DNA, 1.25 U TaKaRa ExTaq HS, ExTaq buffer (Code. RR006A, Takara Bio, Kusatsu, Japan), and 1 µM of each primer. The amplification protocol consisted of 35 cycles of denaturation at 94 °C for 30 s, annealing at 62 °C for 1 min, and extension at 72 °C for 1 min. PCR products were electrophoresed on 2% agarose gels, which were stained with ethidium bromide. The amplified fragments were purified using AMPure XP magnetic beads DNA isolation kits, and each fragment was ligated to 50 ng pMD20 T-vector. Following vector transformation of Escherichia coli HST08, the subcloned vectors were obtained using E. coli HST08 Premium Competent (Takara Bio, Kusatsu, Japan) kits and extracted by the alkaline SDS method. The DNA inserts were subjected to DNA sequencing (Applied Biosystems 3130, Thermo Fisher Scientific, Waltham, MA, USA) using a method based on the big dye terminator cycle sequencing method and the M13 primers RV 3 (sense strand) and M4 (antisense strand), as appropriate. 3. Results 3.1. Microflora Analysis of Aerosol Particles on MMDs Aerosol particles were collected by size using the air suction device (Figure 2), taking advantage of the fractionation capability of the stacked MMDs. The size-fractionated particles were evaluated by SEM (Figure 3A). The average long-axis sizes and numbers (n) of the particles recovered on the 4.5 μm, 1.8 μm, and 1.0 μm MMDs were 5.39 ± 4.9 μm (n = 201), 1.4 ± 1.4 μm (n = 202), and 0.97 ± 0.49 μm (n = 490), respectively (Figure 3B). To estimate the number of particles from the peak shift in the IR transmission spectrum, a calibration curve was constructed using the relationship between the number of aerosol particles counted by the microscope and the transmission peak [23,24]. The 1.8 μm MMD had IR transmission characteristics that were approximately proportional to the number of aerosol particles collected (Figure 4). The regression line was used to estimate the number of aerosol particles collected in Kenya. The average value of the peak shifts of the collected MMDs in Kenya was 1.2 ± 0.3 THz, and the number of aerosol particles was estimated to be 3.1 ± 0.6 × 104 particles/MMD. Aerosol samples were collected by MMDs three times on three successive days. DNA was extracted from aerosols collected from three different MMDs, and PCR was performed using universal primers that amplify the V3–V4 region of bacterial 16S rDNA. The amount of DNA obtained after amplification from each MMD collection was confirmed to be approximately 40 ng by measurement using Qubit. Agarose electrophoresis showed that the molecular weight of the amplified DNA fragment corresponded to the length of the V3–V4 region (about 550 bp) (Figure 5). No DNA was amplified from samples extracted in the same procedure from not used MMDs as negative controls. The average numbers of families, genera, and species identified from each OTU are summarized in Table 3. The effective sequence information for each sample collected by the low-flow-rate suction device ranged from 95,000 to 115,000 reads, and the numbers of OTUs ranged from 87 to 139. The number of OTUs tended to decrease slightly as the pore sizes of the MMDs decreased. Metagenomic data analysis was performed with QIIME2, with a comparison of α-diversity, a statistical index for phylogenetic diversity, shown in Figure 6. A larger index indicates the presence of more diverse bacteria. These results indicate that the α-diversity of microflora in aerosol particles tended to decrease as the pore size of the MMDs decreased. The total number of OTUs obtained from the metagenome analysis of the airborne microflora collected by the MMDs was 198, with genus or species identified for 118 of these OTUs. The top 10 bacteria from the OTUs collected by each MMD are summarized in Table 4. The 34 bacterial species classified as pathogenic and their contents are summarized in Table 5. Six, seven, and seven pathogenic bacteria were collected by the 4.5 μm, 1.8 μm, and 1 μm MMDs, respectively. 3.2. Detection of Mycobacterium spp. Tuberculosis, an airborne infectious disease caused by Mycobacterium spp., is highly prevalent in Kenya. This pathogen, however, was not detected in the above analyses of airborne bacteria. PCR-amplified fragments corresponding to those of Mycobacterium spp. were observed only in the flora of airborne bacteria collected by 4.5 μm pore-size MMDs. Sequence analysis showed that the 973 bp PCR product was 99% identical to a sequence of Mycobacterium obuense, a non-tuberculous Mycobacterium that causes lung disease. 4. Discussion This study describes the development of a new sampling protocol in which atmospheric aerosols were size fractionated by small collectors equipped with MMDs, followed by genetic analysis to identify airborne microflora. Conventional technologies, such as high-volume filter samplers [34] and high-flow-rate impingers [35], require the collection of 1000–100,000 L or more of air to obtain biomass sufficient for downstream analysis. The volume of air collected by this technique was about 1500 L, a volume estimated to contain 102–106 bacteria [8]. Although this amount is smaller than the amount conventionally collected, the recovery of DNA from the MMD surface is excellent, and amplified fragments of the 16S ribosomal region were obtained by conventional PCR. NGS analysis detected 87–139 OTUs in these samples. Stacking of three types of MMDs enabled the fractionation and analysis of bacterial composition and content from a smaller sample than the previously mentioned conventional techniques. The drawbacks of filtration include concerns about damage to the microorganisms caused by prolonged collection, the clogging of the pores by the particles, and the difficulty releasing particles following their attachment to the filter [11,36,37]. The pores of the MMDs described in this study have a large aperture ratio, preventing clogging of the pores until the surface is completely filled with collected particles [22,24]. Furthermore, because of the single thin-layer structure of the MMDs, the collected particles are exposed on their surfaces, making it easy to release the particles and to extract DNA from them by direct immersion in DNA extraction reagents. Stacking MMDs with pore sizes of 4.5 μm, 1.8 μm, and 1 μm resulted in the fractionation of particles with average sizes of 5.39 ± 4.9 μm, 1.4 ± 1.4 μm, and 0.97 ± 0.49 μm, respectively, indicating the effectiveness of size fractionation by MMDs. The PCR amplification of bacterial 16S rDNA from these fractionated aerosol particles revealed the presence of intrinsic bacterial flora in each aerosol fraction. The aerosol samples in this study were collected at a farm that grows a variety of crops and raises cattle, pigs, and chickens on a small scale. Livestock manure is composted and spread on the fields. Bacterial flora in the aerosols obtained from this environment were reported to have greater diversity than flora in aerosols obtained from areas in cities [38,39], a finding supported by the present results. Differences in floral diversity may have resulted from differences in propagation distance depending on particle size, in that smaller-sized particles may have collected airborne bacteria from a wider range of sources. Pseudomonas, on the other hand, was detected in all MMDs with different pore sizes. At the sampling sites, aerosols were assumed to originate from soil, livestock feed, and compost and were ejected into the atmosphere near the sampling sites. Considering the relationship between particle size and dispersal distance, it is assumed that aerosol particles fractionated in MMDs with larger pore sizes would have shorter dispersal distances and be collected from the vicinity of the collection site, while aerosols fractionated in MMDs with smaller pore sizes would have longer dispersal distances and be collected from a wider area. Pseudomonas is abundant in the environment and may be present in a wide range of aerosol particles, ranging from small to large. The α-diversity indices suggested that the unique flora in aerosols depend on the size of the particles, with smaller particle sizes resulting in a greater difference. This difference could be due to factors such as the origin, dispersal distance, and differences in the protective effects of UV light and drying among different-sized particles [40], but analyses with larger numbers of samples are required. In this study, we also assessed whether the sensitivity of detection of floating bacteria could be improved by primer selection. For example, to detect Mycobacterium tuberculosis, a highly prevalent species in Kenya, we utilized a tuberculosis-specific primer set (MYCGEN primers) [32] and attempted to detect this bacterium in the airborne bacteria collected on MMDs. Although 16S rDNA analysis did not detect M. tuberculosis, the MYCGEN primers detected M. obuense on the 4.5 μm pore-size MMDs. However, in the present study, fungal species and viruses were not targeted; therefore, further work will be required to diversify the application so that it can identify different microorganisms, including SARS-CoV-2 viruses. This study was able to identify pathogenic bacteria in plants, including Pseudomonas syringae, Clostridium disporicum, and Rhodococcus fascians, as well as bacteria associated with infectious diseases in animals, including Corynebacterium pilosum, which induces cystitis and pyelonephritis in cattle, Enterococcus cecorum, which causes bacterial infections in pigs, calves, and other species, Streptococcus equi, which induces streptococcal mastitis in cattle and acute septicemia in poultry, and Staphylococcus saprophyticus, which induces cystitis [41]. Analyses of the bacterial flora in dust from arid climates in Africa have identified several genera and species of pathogenic bacteria observed in this study [9,10,11,42]. Although most of the pathogens identified in the study were opportunistic, exposure to dust on farms with livestock has been shown to pose some risks to human health [42]. Bioaerosols have a wide particle-size distribution, ranging from 0.01 μm (viruses) to 100 μm (pollen). Bioaerosols are often found mixed with other matter, such as mineral dust or sea salt. Because many of these particles adsorb to each other to form composite particles, bioaerosols can change in size depending on their source and time course. Since the pore size of the MMDs can be strictly regulated, the size fractionation performance of the MMDs is useful in elucidating bioaerosol characteristics and particle size. One limitation is that the lower pore-size limit of current MMDs is 1 μm, which is too large to capture viruses floating alone. However, most viruses are likely to be adsorbed on the carrier particles [43], and it is thought that this limitation can be compensated for when the MMD is combined with a highly sensitive detection method. In the future, MMDs are expected to establish detection protocols for pathogenic bacteria and viruses, especially coronaviruses, which will make them useful in hospitals and workplaces as a tool for judging the effectiveness of infection prevention and control. The developed aerosol collector is compact and quiet, making it also suitable for indoor aerosol collection. This feature is attributed to the MMD’s large aperture ratio and low pressure resistance. We plan to perform further testing of the MMDs in a hospital facility specializing in tuberculosis. The aerosol collector has advantages in that it can be used in hospital rooms without stressing patients or hospital staff. 5. Conclusions The present study describes the utilization of new MMDs to analyze bacteria in air samples at a farm in the suburbs of Nairobi, Kenya. MMDs are substrate materials consisting of thin membranes with a periodic structure on smooth surfaces that can be used to detect and separate particles. Aerosol particles, including the damaging environmental pollutant PM2.5, were separated based on size and captured on MMD surfaces using a small air pump. Bacterial genomic DNA could be extracted at high yield from aerosol particles on MMDs, with NGS analysis of bacterial 16S rDNA sequences showing the bacterial constituents of these air samples. These results provided information on the bacterial biota in the local environment, including the identification of pathogenic bacteria. MMDs can be considered a simple monitoring device for the detection and quantification of airborne pathogens. Acknowledgments The authors are particularly grateful for the assistance provided by the staff of the Kenya Research Station, Institute of Tropical Medicine, Nagasaki University and the farm owner Peter A. Kamiri. Author Contributions Investigation: X.Y., K.Y., E.A.W., M.M.S. and H.S.; resources: S.K. and T.K.; data curation: A.O.; writing—original draft preparation: X.Y. and M.H.; writing—review and editing: S.K., H.S., Y.I. and M.H.; supervision: M.H.; project administration: Y.I. and M.H.; funding acquisition: M.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the Ethics Committee of KEMRI Scientific and Ethics Review Unit (SERU) (Approval Code: 2896, and Approval Date: 2 September 2014). Informed Consent Statement Not applicable. Data Availability Statement All relevant data can be found in the paper. Conflicts of Interest Takashi Kondo is an employee of Murata Manufacturing Co., Ltd. The other authors declare that they have no conflict of interest. Figure 1 Image of the metal mesh device (MMD). (A) Dimensions of a single unit cell representative of the three types of MMD. D: aperture diameter of MMD; P: period of MMD; T: thickness of MMD. (B) An MMD packaged in polyoxymethylene (POM). Figure 2 Schematic diagram showing the setup of the suction devices using stacked MMD sensors to capture aerosol particles according to size. A low-flow-rate air suction device used 4.5 µm, 1.8 µm, and 1.0 µm MMDs for collection of PM10, PM2.5, and PM1.0, respectively. Figure 3 (A) SEM images of the surfaces of MMDs on which aerosol particles were collected with the low-flow-rate air suction device. Size bar, 50 μm. (B) Distribution of the sizes of aerosol particles captured on each pore size MMD. Figure 4 (A) Spectral changes over time for the 1.8 μm MMD, showing a shift of −3.15 THz after collecting aerosol particles for 12 h. (B) The regression line of particle number vs. frequency shift for particles captured by the 1.8 μm MMD (R2, 0.8153). Figure 5 PCR results obtained universal primers for bacterial 16SrDNA amplification. Negative controls were subjected to the same procedures but without DNA extraction from MMD-captured aerosol particles. Figure 6 Boxplot of α-diversity indices, which reflect abundance and consistency, of microflora obtained from the MMDs at low- and high-flow rates. Boxes represent the interquartile range (IQR) between the first and third quartiles (25th and 75th percentiles, respectively), and the horizontal line inside each box represents the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Diversity decreased significantly as MMD pore size decreased MMD. P-values were determined by Student’s t-tests. ijerph-19-05773-t001_Table 1 Table 1 Properties of the MMDs used in this study. Aperture Diameter (D) Thickness (T) Period (P) 1.0 μm 0.8 μm 1.4 μm 1.8 μm 1.0 μm 2.6 μm 4.5 μm 1.0 μm 6.4 μm ijerph-19-05773-t002_Table 2 Table 2 Primers used in this study. Name Primer Sequence (5′–3′) 341F TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG R805 GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC MYCGEN-F AGAGTTTGATCCTGGCTCAG MYCGEN-R TGCACACAGGCCACAAGGGA ijerph-19-05773-t003_Table 3 Table 3 Metagenome analysis of 16S rDNA extracted from aerosol particles collected with the air suction devices. MMD Size Reads OTUs Family Genus Species 4.5 μm 104,884 ± 6138 121 ± 18 90 ± 16 50 ± 12 26 ± 7 1.8 μm 105,624 ± 9921 104 ± 11 83 ± 8 53 ± 7 23 ± 5 1.0 μm 112,534 ± 2784 92 ± 6 71 ± 4 53 ± 4 25 ± 2 ijerph-19-05773-t004_Table 4 Table 4 The top 10 bacterial isolates identified from air samples collected by MMDs installed in the air suction device. Content rates are mean values (n = 3) of each OTU read number for the total NGS reads. Rank Bacteria Content Rate (%) 4.5 μm MMDs 1 Pseudomonas spp. 48.896 2 Gammaproteobacteria 17.592 3 Streptophyta 5.589 4 Betaproteobacteria 4.340 5 Enterobacteriaceae 4.334 6 Actinomycetales 2.453 7 Propionibacterium spp. 1.978 8 Staphylococcus saprophyticus 1.500 9 Corynebacterium spp. 1.430 10 Enhydrobacter aerosaccus 0.582 1.8 μm MMDs 1 Pseudomonas spp. 49.908 2 Gammaproteobacteria 22.097 3 Enterobacteriaceae 10.825 4 Nostocales 1.424 5 Enhydrobacter aerosaccus 1.022 6 Betaproteobacteria 0.944 7 Pseudomonas syringae 0.899 8 Acinetobacter spp. 0.863 9 Actinomycetales 0.804 10 Staphylococcus saprophyticus 0.564 1.0 μm MMDs 1 Pseudomonas spp. 55.843 2 Gammaproteobacteria 24.476 3 Enterobacteriaceae 5.016 4 Enhydrobacter aerosaccus 1.371 5 Staphylococcus saprophyticus 1.012 6 Pseudomonas syringae 0.963 7 Actinomycetales 0.838 8 Betaproteobacteria 0.787 9 Acinetobacter spp. 0.533 10 Propionibacterium spp. 0.525 ijerph-19-05773-t005_Table 5 Table 5 Pathogenic bacteria identified from air samples collected by MMDs installed in the air suction devices. Content rates are mean values (n = 3) of each OTU read number for the total NGS reads. Content Rate (%) NO Bacteria 4.5 μm 1.8 μm 1.0 μm 1 Pseudomonas spp. 48.896 49.908 55.843 2 Staphylococcus saprophyticus 1.5 0.564 1.012 3 Propionibacterium spp. 1.978 0.553 0.525 4 Pseudomonas syringae 0.553 0.899 0.963 5 Corynebacterium spp. 1.43 0.308 0.273 6 Acinetobacter spp. 0.393 0.863 0.533 7 Streptococcus spp. 0.337 0.394 0.067 8 Elizabethkingia spp. 0.128 0.059 0.106 9 Corynebacterium pilosum 0.006 0.137 0.074 10 Peptoniphilus spp. 0 0.16 0 11 Anaerococcus spp. 0.145 0 0 12 Streptococcus equi 0.058 0.087 0 13 Bordetella ansorpii 0 0 0.126 14 Brevundimonas vesicularis 0.091 0.03 0 15 Bacillus spp. 0 0 0.116 16 Roseomonas spp. 0.112 0 0.004 17 Corynebacterium simulans 0 0.111 0 18 Haematobacter massiliensis 0 0.106 0 19 Finegoldia spp. 0 0.103 0 20 Clostridium paraputrificum 0 0 0.097 21 Enterococcus cecorum 0.055 0.035 0 22 Helicobacter spp. 0 0 0.089 23 Propionibacterium granulosum 0.072 0.01 0 24 Kocuria kristinae 0 0.071 0 25 Rhodococcus fascians 0.063 0 0 26 Rhodococcus spp. 0 0.061 0 27 Aeromonas spp. 0 0 0.044 28 Bacteroides spp. 0.043 0 0 29 Brevibacterium casei 0 0 0.035 30 Brevundimonas spp. 0 0.034 0 31 Helcobacillus massiliensis 0 0 0.022 32 Methanobrevibacter spp. 0.015 0 0 33 Bordetella spp. 0.003 0 0 34 Rothia spp. 0.002 0 0 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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==== Front Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers14092309 cancers-14-02309 Review Dissecting the Functional Role of the TRIM8 Protein on Cancer Pathogenesis Esposito Jessica Elisabetta 1 https://orcid.org/0000-0001-7479-7452 De Iuliis Vincenzo 2 https://orcid.org/0000-0001-8048-8277 Avolio Francesco 1 https://orcid.org/0000-0002-9530-8029 Liberatoscioli Eliana 1 https://orcid.org/0000-0001-8334-0577 Pulcini Riccardo 1 https://orcid.org/0000-0003-2988-1908 Di Francesco Simona 3 Pennelli Alfonso 3 Martinotti Stefano 1 Toniato Elena 14* Mosialos George Academic Editor 1 Center of Advanced Studies and Technology, Department of Innovative Technology in Medicine and Dentistry, University of Chieti, 66100 Chieti, Italy; j.elisabetta.esposito@gmail.com (J.E.E.); avolio.francesco@gmail.com (F.A.); elianaliberato.scioli@gmail.com (E.L.); riccardo.pulcini@unich.it (R.P.); smartinotti@unich.it (S.M.) 2 Department of Clinical Pathology, G. Mazzini Civil Hospital, ASL 4, 64100 Teramo, Italy; vincenzo.deiuliis@aslteramo.it 3 Department of Medical, Oral Sciences and Biotechnology, University of Chieti, 66100 Chieti, Italy; docveronica@gmail.com (S.D.F.); a.pennelli@dsb.unich.it (A.P.) 4 Department of General Pathology, UniCamillus-International Medical University in Rome, 00100 Rome, Italy * Correspondence: e.toniato@unich.it 06 5 2022 5 2022 14 9 230923 2 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/). Simple Summary The tripartite motif (TRIM) gene family is a large group of E3 ubiquitin ligase proteins that can also have proteasome-independent functions. This review summarizes the structural organization, the biological functions and the mechanisms involved in cancer pathogenesis of TRIM proteins. Furthermore, this paper focuses on TRIM8, a member of the TRIM family proteins, describing its role both as a tumor suppressor and as an oncogene. Abstract TRIM/RBCC are a large family of proteins that include more than 80 proteins, most of which act as E3 ligases and catalyze the direct transfer of Ubiquitin, SUMO and ISG15 on specific protein substrates. They are involved in oncogenesis processes and in cellular immunity. On this topic, we focus on TRIM8 and its multiple roles in tumor pathologies. TRIM8 inhibits breast cancer proliferation through the regulation of estrogen signaling. TRIM8 downregulation in glioma is involved in cell proliferation, and it is related to patients’ survival. Several studies suggested that TRIM8 regulates the p53 suppressor signaling pathway: it is involved in the NF-kB pathway (Nuclear Factor kappa light- chain-enhancer of activated B cells) and in STAT3 (Signal Transducer and Activator of Transcription 3) of the JAK-STAT pathway. In this review, we summarize how the association between these different pathways reflects a dual role of TRIM8 in cancer as an oncogene or a tumor suppressor gene. TRIM proteins TRIM8 p53 NF-kB JAK-STAT cancer University of ChietiThis project was in part supported by 60% Ateneo Grant from the University of Chieti, Italy. ==== Body pmc1. Introduction TRIM8 is a part of a huge of proteins known as Tripartite Motif proteins, in the first instance described as a glioblastoma expressed RING-finger protein (GERP) [1]. They are also known as the RING family and are a large family of proteins characterized by the presence of three characteristic domains in the high-conserved N-terminal region: RING domain, B-box domain and coiled-coil region [2,3,4]. TRIM proteins are ontogenetically preserved [5,6]. Their primary sequences demonstrate a relatively low analogy, except for a few members. In fact, exclusively the cysteine and histidine characterizing the RING and B-box domains and the hydrophobic residues of the coiled-coil region are highly preserved given that they are mandatory to sustain the scaffold structure of the proteins [7,8]. TRIM proteins are able to integrate into high molecular weight complexes through the association of coiled-coil domains. These complexes are located in particular sub-compartments, such as cytoplasmic bodies or ribbon-like structures, which can be allocated around the nucleus (e.g., TRIM13) or in the nucleus where they constitute “nuclear bodies” (e.g., TRIM8, 19, 30 and 32) or “nuclear sticks” (e.g., TRIM6). Few members (e.g., TRIM24, 28 and 33) contain the bromo domain, which in the nucleus interacts with the acetylated lysines of histones. Only some members do not have a RING domain but are still considered TRIM/RBCC proteins because they conserve all the other domains (B-boxes and coiled-coil region) in the identical sequence as the other members [9,10,11]. The C-terminal region is less conserved than N-terminal and could present different protein-protein association domains, on the basis of which they are categorized in 11 sub-groups [2,3,4,12] (Figure 1). On this topic, we firstly described TRIM proteins’ biological functions and the mechanisms and pathways implicated in cancer pathogenesis. Later, we focused on TRIM8 protein and its dual role both as an oncogene by affecting the NF-kB and JAK-STAT pathways and as a tumor suppressor by inducing TP53-dependent cell cycle arrest. 2. TRIM Proteins Biological Functions TRIM proteins are involved in distinct cellular processes, despite showing a similar structure: regulation of cellular homeostasis, cell cycle, senescence, apoptosis, differentiation, specific metabolic pathways, meiosis and protein quality control [9,13,14]. They exert their actions on transcriptional regulation, cytoskeletal remodeling, intracellular trafficking, membrane repair and oncogenesis [15,16,17,18]. Moreover, these proteins are implicated in the development and regulation of the immune system [19,20,21]. Most TRIM molecules act as E3 ligases and directly catalyze the transfer of Ub, SUMO and ISG15 on specific protein substrates [22,23,24,25]. The conjugation reaction of ubiquitin to a substrate is catalyzed by E1 ubiquitin-activating enzyme, E2 ubiquitin-conjugating enzymes and E3 ubiquitin ligases [26]. The E3 ubiquitin ligases can be divided into two major classes: the homologous to E6-AP COOH terminus (HECT) E3 ubiquitin ligase family and the RING-finger-containing E3 ubiquitin ligase family [27,28]. The high number of E3 ligases is associated with their specificity in selectively targeting protein substrates [9]. Mostly, the enzymatic activity exerted by the E3 ligases on ubiquitin and Ubiquitin-like molecules (UBL) depends on the presence in the protein structure of the RING domain [29,30]. E3 ligases transfer the ubiquitin or UBLs from E2 conjugating enzymes to the substrates, and thus they are responsible for recognizing the substrates and are determinants of target specificity [31]. In order for ubiquitination to take place, however, it is not sufficient for the RING domain to recognize the specific substrate, but specific functional protein dimers must be formed [32,33,34]. The B-box and coiled-coil domains are responsible for the dimerization of TRIM proteins [2,35]. Many TRIM proteins play a pivotal role during mitosis and cell-cycle progression. Specifically, TRIM19, TRIM22, TRIM28, TRIM37 and TRIM6 are important during prophase; TRIM19, TRIM32 and TRIM69 in prometaphase; TRIM17, TRIM36 and TRIM69 in metaphase; and TRIM17, TRIM21, TRIM47 and TRIM76 in cytokinesis. Furthermore, in the course of the bipolar spindle assembly during all phases of mitosis, TRIM8 is involved in the mitotic spindle formation through interaction with two important regulators of mitotic spindle machinery and cytoskeleton reorganization, KIF11 and KIFC1, and through localization at the mitotic spindle [36]. TRIM8 colocalizes on centrosomes with Plk1 and straight reacts to CEP170-like protein. This interaction, suppressing TRIM8 function, induces a delay of the mitosis progression with a cell accumulation in the G2/M phase. TRIM8 is also necessary for chromosomal stability. As a matter of fact, the suppressing of TRIM8 induced an increased rate of chromosomal instability leading to a significant rise of cells with less than 46 chromosomes [9,27]. TRIM proteins have the distinctive feature of exerting a large variety of different roles and activities because of their ubiquitination or ubiquitin-like function that labels the target proteins to be degraded at the proteasome level, as well as stabilize or dislocate them in various cellular compartments through such modifications. Ubiquitination is a post-transductional modification of protein substrates necessary for different biological mechanisms, such as:Regulation of the activity and stability of oncogenes and tumor suppressors [37,38]; Degradation of toxic protein aggregates [39]; Activation of specific inflammatory pathways [15,40]. The alteration of the post-transduction mechanism of ubiquitination affects the functionality of protein substrates, with consequent alteration of the biological mechanisms in which they are involved. At a macroscopic level, these alterations can lead to the development of various pathological conditions, including tumor pathologies [2,41,42]. TRIM proteins are involved in carcinogenesis. In particular, these proteins are implicated in several biological functions: DNA repair, metastasis, tumor-suppressive and oncogenic regulation [15]. Furthermore, some of the TRIM family proteins play a pivotal role in autophagy and innate immunity and regulate important cellular processes, such as intracellular signaling and transcription [27]. The down-regulation or overexpression of TRIM proteins has long been investigated in the study of oncogenesis. However, many reports showed that TRIM alterations were observed in lung cancer, breast cancer, liver cancer, colorectal cancer and prostate cancer [43,44]. Indeed, reduced expression of these proteins could reflect the suppressive role of the tumor, whereas their over-expression could reflect their contribution to the disease development and/or progression. Therefore, some TRIMs could be considered biomarkers for some kind of cancer. In particular, TRIM11, TRIM14, TRIM24, TRIM25, TRIM27, TIM28, TRIM29, TRIM33, TRIM37, TRIM44 and TRIM59 are the most associated with cancer [43]. 3. TRIM Proteins and Cancer Pathogenesis TRIM proteins could influence cancer pathogenesis through the following mechanisms:Chromosomal translocation [45]. It could generate a fusion protein without activity or with a different activity that could dysregulate some signaling pathways, leading to the generation of some tumor shapes. An example is a translocation between the TRIM19 gene (PML) on chromosome 15 and the retinoic acid receptor α (RARa) gene on chromosome 17. This translocation leads to the formation of a fusion protein that represses acid signaling retinoic and is associated with Acute Promyelocytic Leukemia [46]. Such similar examples are the following: TRIM24, TRIM27 and TRIM33 were found in translocations with the RET gene and are involved in papillary thyroid cancer, lymphoma and non-small cell lung carcinoma, respectively. Similarly, TRIM24 was found translocated with the BRAF gene in melanoma and lung cancer and with the FGFR1 gene in myeloproliferative syndrome [43]; Modulation of the activity and stability of p53. TRIM11, TRIM13, TRIM21, TRIM24, TRIM25, TRIM28, TRIM29, TRIM31, TRIM32, TRIM39 and TRIM59 can ubiquitinate the p53 protein, a fundamental macromolecule in cell development whose purpose is to promote genomic stability and induce cell cycle arrest and apoptosis if extensive DNA damage is found in the cell. The ubiquitination of this protein leads to its direct degradation or to its sequestration in the cytoplasm: since it can no longer penetrate the nucleus, the ubiquitinated protein is no longer able to detect any damage to the DNA; consequently, the cell replicates itself by transmitting the same error in the nucleic acid sequence, resulting in the possible onset of tumor forms [47]; Regulation of pathways to cancer stemness, including STAT signaling, AKT signaling, NANOGSox2-Oct-3/4 networks. Specifically, through these pathways, TRIM28 is involved in breast cancer, TRIM24 in glioblastoma and colorectal cancer, TRIMs 14 in gastric cancer and TRIM16 has been associated as a negative regulator of stemness in breast and ovarian cancer cells [43]. Stem cells (SCs) are cells with no signs of differentiation, capable of self-renewing and generating progeny capable of differentiating into different cell types. They constitute the reserve elements of human tissues; in fact, they are activated only to restore tissue damage or to ensure normal cell turnover. SCs are capable of self-renewal, are multi-potent and immortal, and are highly resistant to chemical and physical agents, all characteristics also possessed by cancer cells. Furthermore, SCs tend to maintain the ability to de-differentiate in order to return to a primitive state of development. Such cells cannot survive outside their environment or in case of deficiency of specific cytokines and growth factors. Mutated stem cells, however, despite having all the aspects of stem cells, are unable to support tissue homeostasis, favoring, instead, the onset and progression of tumor diseases. The stem characteristics common to HF and cancer cells provide the building blocks for cancer maintenance and survival, from the potential for self-renewal and differentiation to the organization of microenvironments that support stemness. Thus, cancer stem cells (CSCs) are defined as the small population of cells within tumors that possess stem properties that support cancer development, such as advanced capabilities for cloning, growth, metastasis, re-proliferation and self-renewal. CSCs exhibit remarkable organizational skills. In fact, they can educate neighboring cells to provide nutrients and collaborate in evading the immune system, thus creating an environment favorable for tumor progression [48]. CSCs give rise to heterogeneous cell populations, often with a high potential for plasticity, high resistance to stressors, such as low oxygen or nutrient levels, or the initiation of cell death by chemotherapeutic agents, and the capability for quiescence as a typical response to these factors [49]. Among the possible pathways by which TRIM proteins act on tumor stemness are the signaling of STAT, AKT (Figure 2) and the NANOGSox2-Oct-3/4 networks [50]. In fact, TRIM proteins control stem cell characteristics mostly positively by enhancing the activity of core transcription factors, induction of specific signaling pathways, epigenetic silencing of pro-differentiation genes, metabolic reprogramming and activation of the epithelium-mesenchymal transition pathway. Several members, such as TRIM24 and TRIM28, negatively regulate stem cell self-renewal, presumably by ubiquitin-mediated degradation of stem cell transcription factors or inhibition of specific signaling pathways. Furthermore, several TRIM proteins, such as TRIM8, modulate the stem cell phenotype both positively and negatively [48]. In addition, the role of TRIM proteins on autophagic processes may represent a not-well investigated mechanism involved in cancer stemness [43]. Regulation of pathways related to epithelial-mesenchymal transition (EMT) [43,51]. The epithelium-mesenchymal transition (EMT) is a biological process that allows a polarized epithelial cell, which normally reacts with the basement membrane through its basal surface, to suffer several biochemical changes that permit it to acquire a mesenchymal cell phenotype, which includes a prominent migratory ability, invasiveness, significant opposition to apoptosis and considerably raised production of components of the extracellular matrix. The achievement of an EMT is signaled by the degradation of the underlying basement membrane and the development of a mesenchymal cell that can move away from the epithelial layer where it arises [52]. The biological processes that initiate an EMT include activation of specific transcription factors, expression of cell surface proteins, reorganization and expression of cytoskeletal proteins, production of degradative enzymes and changes in the expression of specific microRNAs. Some of these factors can be used as biomarkers to establish the switch of a cell through an EMT [53]. 4. TRIM8 TRIM8 gene (Ensembl: ENSG00000171206) is situated on chromosome 10q24.32, a region that is known to show frequent deletion or loss of heterozygosity in glioblastomas [1]. Fifteen splice-variant transcripts of TRIM8 were recognized in humans. Surprising enough, three of them are uncharacterized long non-coding RNAs (lncRNAs) (Ensembl). It has been shown that TRIM8 is present in 27 human tissues considered in the Human Protein Atlas (HPA) RNA-Seq Project and produces one major transcript (Ensembl: ENST00000643721.1) of 7290-bp length that codes for the 551-amino acid (aa) TRIM8 protein with a molecular mass of 61.489 kDa (UniProtKB: Q9BZR9 TRIM8 HUMAN) [27]. The human TRIM8 is an E3 ubiquitin ligase protein and is composed of an N-terminal C3HC4-type RING-finger domain, two B-boxes (Bbox1 and Bbox2), a coiled-coil domain and a proline-rich no-domain C-terminal region with a monopartite nuclear localization signal (NLS) (Figure 1) [54]. TRIM8 is structurally classifiable under class V of TRIM-type proteins, along with TRIM19, TRIM31, TRIM40, TRIM56, TRIM73, TRIM74, RNF207, TRIM52 and TRIM61, which are also characterized by not having known domains in their C-terminal region so far [43]. The RING domain of TRIM8 plays an important role in its activity to regulate stabilization and activation of TP53, degradation of MDM2,8 and destabilization of DNp63a,9 and thus is crucial in cell proliferation. Instead, it was shown that the conserved B-box and coiled-coil domain region is relevant to mediating the interaction with SOCS1, a tumor suppressor gene. Moreover, the coiled-coil domain of TRIM8 is necessary for homodimerization and allows the formation of Nuclear Bodies (NBs) in order to regulate the activity of main cellular proteins through protein–protein interactions. Deletion of the C-terminal domain of TRIM8 can result in protein mislocalization [9,27]. TRIM8, as a whole, is considered to be among E3 ubiquitin ligases due to the presence of the RING domain. TRIM8 was shown to function as an E3 ubiquitin ligase in various relevant biological pathways, although the mechanism of its E3 ubiquitin ligase activation is not known yet. TRIM8 can carry out K63-, K6- and K33-linked polyubiquitination [55]. Specifically, TRIM8 can react with Toll/IL-1 receptor domain-containing adaptor-inducing IFN-b (TRIF) and regulates its K6- and K33-linked polyubiquitination, which promotes the disruption of the TRIF-TANK-binding kinase-1 association [56]. In addition, TRIM8 acts as an important regulator of TNF-a- and IL-1b-induced NF-kB activation through the K63-linked polyubiquitination of TGF-b-activated kinase 1 (TAK1), mediated by TNF-a and IL-1b [57]. K63-linked ubiquitination is required in regulating proteasome-independent functions, including cellular processes, such as endocytosis and inflammatory immune responses, innate immunity, protein trafficking and NF-kB signaling. Instead, K6-linked polyubiquitination is known to be related to DNA damage response and Parkin-mediated mitophagy, and K33-linked polyubiquitination is associated with TCR signaling, post-Golgi-trafficking and AMPK-related kinase signaling. Recent studies demonstrated that TRIM8 is not only involved in an E3 ubiquitin ligase-independent manner, but it can also preserve phosphorylated IRF7 (pIRF7) from proteasomal degradation through an E3 ubiquitin ligase-independent pathway by avoiding its recognition by the peptidylprolyl isomerase [27]. 5. TRIM8 and Cancer Pathogenesis TRIM8 regulates the tumor suppressor p53 [58], the NF-kB [55] (Nuclear Factor kappa light- chain-enhancer of activated B cells) and the STAT3 [59] (Signal Transducer and Activator of Transcription 3) of the JAK-STAT pathways; its association with these three pathways explains its dual role in cancer as an oncogene or as tumor suppressor protein [9]. TRIM8 was demonstrated in murine and human tissues with greater expression in the central nervous tissue, kidney and lens; it was also proved in undifferentiated embryonic stem cells, indicating that TRIM8 could play a relevant role in maintaining pluripotency. TRIM8 is involved in most tumors as a suppressor gene. In fact, its downregulation was observed in glioblastoma, clear cell renal cell carcinoma (ccRCC), larynx squamous cell carcinoma (LSCC), colorectal cancer (CRC), chronic lymphocytic leukemia (CLL), osteosarcoma cell lines and breast cancer (BC) [27]. Firstly, the role of the TRIM8 gene in tumors was described by Vincent et al. in 2000 [1]. They observed that patients affected by glioblastomas were characterized by a frequent deletion or loss of heterozygosity in the TRIM8 gene, which causes the loss of gene copy number associated with the inactivation of TRIM8 in glioblastoma cells. Indeed, deficiency in TRIM8 E3 ligase function in glioma cells might stimulate cancer development by promoting the oncogenes stabilization and/or increasing tumor suppressors degradation. Compared with cells at highest TRIM8 levels, lowest TRIM8 expression levels related to a relevant risk of death and disease development in WHO grade III tumors, indicating that a loss of TRIM8 expression may be required for the transformation to a more aggressive phenotype typical of WHO grade III gliomas. Moreover, it was shown both U87MG glioblastoma and patients’ primary glioma cell lines were characterized by the overexpression of TRIM8, which suppresses cell development and induces an important decrease in clonogenicity [60]. Moreover, in breast cancer, downregulated TRIM8 was associated with a poor prognosis. In particular, Tian et al. showed a TRIM8 downregulation in breast cancer and an inverse correlation between the protein level of TRIM8 and the estrogen receptor α (Erα). In ER-positive BC, TRIM8 reacts with the AF1 domain of estrogen receptor α through its RING domain in the cytoplasm and rises poly-ubiquitination of the ERα protein, causing degradation of ERα. TRIM8 binds ERα protein and catalyzes its K48-linked ubiquitination to block K63-linked ubiquitination, thus promoting ERα degradation, which further inhibits K63-linked poly-ubiquitination. TRIM8 may be a potential therapeutic target in the ER-positive BC treatment, as evidenced by the post-translational mechanism between ERα and TRIM8 [61]. In several cases, the expression of TRIM8 is modulated at transcriptional and post-transcriptional levels by microRNAs (miRNAs). For instance, the overexpression of miR-17-5p demonstrated in patients affected by ccRCC, CRC, Glioma and CLL results in TRIM8 downregulation that affects cell proliferation and is related to patients’ survival [62]. Micale et al. suggested that TRIM8 and miR-17 were involved in a feedback pathway implicated in glioma pathogenesis. The authors evidenced that miR-17 plays a pivotal role in glioma cell lines: the downregulation of this miRNA significantly decreases cell viability and raises apoptotic function, while the upregulation is related to advanced tumor development and poor overall survival [60]. In cell Renal Cell Carcinoma miR-17-5p, miR-106b-5p and miR-182 bind TRIM8 mRNA leading to its degradation [9]. In colorectal cancer and in anaplastic thyroid cancer (ATC), TRIM8 seems to be associated with chemoresistance of CRC and ATC cells, respectively. In particular, in CRC, TRIM8 downregulation was promoted by the overexpression of miR-17-5p and miR-106b-3p induced by N-MYC. In addition, N-MYC is negatively regulated by miR-34a, which is transactivated by p53. Silencing of miR-17-5p and miR-106b-5p leads to a raise of TRIM8 expression levels, which in turn conducts to p53 stabilization with the activation of cell cycle arrest and transcription of miR-34a that targets N-MYC for degradation. Thus, the oncogenic effect of N-MYC is suppressed by p53 through the transcription of miR-34a, linking p53 to N-MYC. TRIM8 acts as a key point in the p53/N-MYC/miR-17 pathway. CRC cells recover sensitivity to chemotherapy treatments by restoring normal TRIM8 expression levels. Finally, in anaplastic thyroid cancer (ATC), TRIM8 is a direct target of miR-182, which is upregulated in ATC tissue and cell lines. Silencing the function of TRIM8, miR-182 promotes cellular development and increases the chemoresistance of ATC cells [62]. 6. TRIM8 as Tumor Suppressor Several studies reported that TRIM8 has a key role both as an oncogene by affecting the NF-kB [55] and JAK-STAT pathways [59] and as a tumor suppressor [62]. In particular, a positive feedback loop involving TRIM8 and p53 was described. This pathway is activated in response to genotoxic stress causing p53 stabilization and activation, resulting in cell cycle arrest and decreasing in cell proliferation. TRIM8 physically reacts with p53, avoiding its association and degradation by the principal negative regulator of p53, Murine Double Minute 2 (MDM2) [9]. TRIM8 replaces p53-MDM2 binding, thus stabilizing p53 and stimulating MDM2 degradation. Finally, TRIM8 act as a promoter of cell proliferation and DNA repair through p53-dependent suppression [62]. The combined activation of TRIM8 and p53 can result in negative outcomes in response to hypoxic stress due to ischemia following a stroke or myocardial infarction. TRIM8 deficiency avoided p53 activation following drug treatments in several p53 wild-type cell lines. For example, in RCC showing wild-type p53, the loss of one copy of the gene causing downregulation of TRIM8 was shown to impair the p53-mediated cellular responses to chemotherapeutic drugs in renal cell carcinoma. TRIM8 expression recovery in RCC cell lines makes these cells sensitive to chemotherapeutic treatments following p53 pathway reactivation. As a consequence, TRIM8 could be used as a factor that improves the chemotherapy efficacy in cancers where p53 is wild-type, and its pathway is defective. Moreover, reactivation of the p53 pathway can be confined exclusively to cancer cells without affecting normal tissue, hence limiting side effects. One mechanism to reactivate p53 in tumor types harboring a wild-type p53 is to constrain the maintenance of p53 protein by releasing it from the negative control of MDM2 [63]. The TRIM8 ability to prevent the proliferation of cancer cells is also related to its effects on the stability and activity of the oncogenic transcription factor DNp63, which is included in the p53 gene family. As it is upregulated in many different tumors, DNp63 expression is associated with a poor prognosis [64]. DNp63 degradation is carried out by TRIM8 in both proteasomal and caspase-1 dependent ways, but DNp63 is able to downregulate TRIM8 transcription expression levels, thus avoiding p53 stabilization [9]. TRIM8 can perform as a tumor suppressor by inducing TP53-dependent cell cycle arrest [64]. In summary, the TRIM8 anticancer capacity has expertise in three distinct ways, in all of which TRIM8′s anti-proliferative function is affected by the TP53 functional or wild-type background:By inducing the TP53 tumor suppressor activity through a positive feedback loop formation. TRIM8, a direct target gene of TP53, promotes TP53 expression and tumor suppressor activity through a positive feedback loop-forming mechanism with TP53 during UV-instigated stress factors by triggering cell cycle arrest genes such as CDKN1A (p21) and GADD45 expression. The recovery of TRIM8 expression, downregulated in many tumors, can lead to the enhancement of efficacy of chemotherapeutic drugs by reactivating the TP53 pathway. Notably, TRIM8 silencing prevents TP53 activation after UV radiation [64]; Restoring TP53 functions by blunting N-MYC activity in chemo-resistant tumors. The inhibition of miR-17-5p and/or miR-106-5p leads to the restoration of TRIM8-mediated TP53 tumor suppressor activity and inhibits N-MYC-dependent cell proliferation through miR-34a upregulation [65]; Quenching the DNp63a oncogenic activity by forming a negative feedback loop. TRIM8 can blunt the pro-proliferative function of oncogenic DNp63a in a TP53 wild-type background [27]. The transcription factor ∆Np63α is upregulated in several tumors, and its expression level is associated with a poor prognosis. TRIM8 affected the degradation of ∆Np63α in both a proteasomal and caspase-1-dependent expertise pathway, opposing the proliferation of cancer cells [64]. 7. TRIM 8 as Oncogenic Protein TRIM8 has been shown to play a role both as an oncogene and as a tumor suppressor, thus allowing the proliferation of cancer cells. TRIM8 enables autophagic processes mediating lysosomal biosynthesis and autophagy flux in a p53-independent manner. Autophagy preserves cellular homeostasis by removing deteriorated proteins, aggregates and defective organelles and eliminating damaged DNA, which, following genotoxic stress, is transported out of the nucleus and degraded by the lysosomes. TRIM8 regulates the expression of p62, which is involved in several functions during autophagic processes such as being a cargo selector, inflammation and senescence induced by DNA damage and decreasing inflammation by promoting mitophagy. In fact, during genotoxic stress, TRIM8 can allow a proliferative advantage to cancer cells by increasing autophagy flux through lysosomal biogenesis and inactivating the cleaved Caspase-3 subunit to inhibit cell death induced by genotoxic stress. TRIM8 knockdown reduces the expression of X-linked inhibitor of apoptosis protein (XIAP), a major regulator of cell death and autophagy, whereas the enhanced expression of TRIM8 stabilizes XIAP, forming a trimeric complex with Caspase-3, inhibiting XIAP activation in the presence of etoposide. XIAP also strongly activates NF-kB via BIR (baculovirus inhibitor of apoptosis protein repeat) domain-mediated dimerization and binding to TGF-b-activated kinase 1 (MAP3K7) binding protein. This XIAP-mediated NF-kB activation also induces the expression of genes involved in autophagy, such as Beclin-1 [9,27,66]. During genotoxic stress, TRIM8-mediated XIAP stabilization can also promote the degradation of Caspase-3, one of the most important players in the apoptotic cascade. For that reason, TRIM8-mediated XIAP stabilization has the capability to lead to two important oncogenic results during the course of tumorigenesis. First, TRIM8-mediated XIAP stabilization allows the expression of genes involved in autophagy and cell proliferation through NF-kB activation. Second, TRIM8 mediated stabilized XIAP averts activation of Caspase-3, leading to the suppression of apoptosis. Therefore, TRIM8 avoids cell death during genotoxic stress and radiation therapy, suggesting that TRIM8′s highly oncogenic potential can allow survival assistance to cancer cells [27]. 7.1. TRIM8 and NF-kB The principal TRIM8 partners involved in its role in oncogenesis are NF-kB and STAT3. NF-kB consists of a family of inducible transcription factors that control the expression of numerous genes that play a pivotal role both in immune and inflammatory responses. The classical activation of NF-kB is initiated by the phosphorylation of the NF-kB inhibitor IkBα through the activated IkBα kinase complex (IKK). Phosphorylation of IkBα is followed by its consequent ubiquitin proteasomal degradation, which promotes the release of the NF-kB dimers with subsequent nuclear entry. Once inside the nucleus, NF-kB dimers modulate genes implicated in cell death inhibition and cell proliferation, thus stimulating migratory and invasive phenotypes associated with tumor progression as well as Epithelial–Mesenchymal Transition (EMT) [52]. TRIM8 can activate the NF-kB signaling pathway both in the cytoplasm and in the nucleus. In the nucleus, the translocation of PIAS3 (Protein Inhibitor of Activated STAT3) from the nucleus to the cytosol performed by TRIM8 induces PIAS degradation. In this way, PIAS3 can no longer bind the RelA (p65) subunit of NF-kB, which is free to dimerize and activate the NF-kB responsive genes. In the cytoplasm, TRIM8 enhances the activation of NF-kB triggered by TNFα, the most important activator of carcinogenesis and inflammatory diseases, and IL-1β. TRIM8 regulates the polyubiquitination of TAK1, which in turn activates the kinase IKK, which promotes IkBα phosphorylation and NF-kB activation (Figure 2). TRIM8 plays a relevant role in regulating tumor necrosis factor-alpha (TNF-a) and interleukin (IL)-1b-induced nuclear-factor kB (NF-kB) activation through the K63-linked polyubiquitination of TAK1. In fact, overexpression of TRIM8 activates NF-kB and enhances TNF-a- and IL-1b-induced activation of NF-kB, whereas knockdown of TRIM8 leads to inverse effects. TRIM8 also mediates the proliferation and migration ability of the cells through the NF-kB pathway, and the knockdown of TRIM8 in the breast cancer MCF7 cell line significantly reduces the cell proliferation and clonogenicity of cells (Figure 2) [57]. The activation of NF-kB is responsible for cell proliferation and protecting cells from initiating apoptosis. Thus, TRIM8 plays an important role as an oncogene involved in cell proliferation by positively mediating the TNF-induced NF-kB pathway [27]. 7.2. TRIM8 and STAT3 STAT3 is a transcriptional factor belonging to the STAT family of transduction signal responsive transcription factors. Similar to NF-kB, STAT3 is also retained in an inactive form in the cytoplasm of non-stimulated cells. The phosphorylation of Tyr 705 of STAT3 is necessary for its dimerization and, thus, activation. In the dimerized form, STAT3 is able to enter the nucleus and promotes the transcription of several target genes. Members of the JAK family of tyrosine kinase receptors commonly mediate STAT activation, and in the case of STAT3, the major activator is JAK1. Moreover, STAT3 activity can be optimized through a reversible acetylation mechanism, which also influences the activity of NF-KB family members [67]. TRIM8 association with SOCS-1 through the SH2 domain promotes its degradation and allows the activation of JAK-STAT induced by IFNγ (Figure 2) [17]. Both NF-kB and STAT3 are activated in response to overlapping stimuli, such as stresses and cytokines, although they are regulated by entirely different signaling mechanisms. Once activated, both NF-kB and STAT3 regulate the expression of several genes involved in pro-proliferative pathways, immune response and anti-apoptotic processes [9]. 8. Conclusions TRIM/RBCC is a large family of proteins, most of which act as E3 ligases, involved in cellular signaling, metabolism, autophagy, oncogenesis processes and in cellular immunity. The alteration of the post-transduction mechanism of ubiquitination affects the functionality of protein substrates, with consequent alteration of the biological mechanisms in which they are involved. These alterations can lead to the development of various pathological conditions, including tumor pathologies. In fact, TRIM proteins play a critical role in carcinogenesis and are involved in several biological processes, such as DNA repair, metastasis, tumor-suppressive regulation and oncogenic regulation. Furthermore, some of the TRIM family proteins are relevant factors required for autophagy and innate immunity and regulate significant cellular processes, such as intracellular signaling and transcription. The down-regulation or overexpression of TRIM proteins was described in lung cancer, breast cancer, liver cancer, colorectal cancer and prostate cancer. Indeed, reduced expression of these proteins could reflect the suppressive role of the tumor, whereas their over-expression could reflect their contribution to the disease development and/or progression. In this review, we focused on TRIM8 and its multiple roles in tumor pathologies. Specifically, TRIM8 regulates the p53 suppressor signaling pathway; it is involved in the NF-kB and in STAT3 of the JAK-STAT pathways. In this review, we also summarized how the association between these different pathways reflects a dual role of TRIM8 in cancer as an oncogene or tumor suppressor gene. However, many experiments enhance the anti-oncogenic function of the protein. In particular, it was shown that TRIM8 physically interacting with the oncosuppressor p53 protein increases its stability leading to cell cycle arrest. For these reasons, TRIM8 could be indicated as a potential target capable of enhancing the p53-mediated tumor suppressor activity. Author Contributions Conceptualization, E.T. and S.M.; methodology, J.E.E.; software, R.P.; validation, J.E.E., F.A. and E.L.; formal analysis, J.E.E.; investigation, J.E.E.; resources, A.P., S.D.F.; data curation, V.D.I.; writing—original draft preparation, J.E.E. and E.L.; writing—review and editing, V.D.I., F.A.; supervision, E.T.; project administration, F.A.; funding acquisition, S.M. 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 Classification of TRIM/RBCC proteins. The N-terminal domain (N-ter) is mostly conserved in TRIM family members and includes RING, B-box 1, B-box 2 and coiled-coil domains. A variable C-terminal domain (C-ter) classifies TRIMs into 12 different classes and includes COS box motif, ARF (ADP ribosylation factor)/SAR, PHD (Plant Homeodomain), PRY, SPRY (SPla and the RYanodine receptor), MATH (meprin and TRAF homology domain), TM (transmembrane motif), FILAMIN, NHL (NCL1/HT2A/LIN-41), Bromo domain, FN3 (FibroNectin type III motif), and a variable domain. The presence of certain domains can vary even among members of the same class, as indicated by brackets. Figure 2 TRIM8 is an oncogenic protein, with its interaction with NF-kB and STAT3 leading to cell proliferation. Pro-inflammatory cytokines (TNFα e IL-1β) promote NF-kB activation through TRIM8. 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==== Front Nutrients Nutrients nutrients Nutrients 2072-6643 MDPI 10.3390/nu14091871 nutrients-14-01871 Article An Investigation of Social Ecological Barriers to and Facilitators of WIC Farmers Market Nutrition Program Voucher Redemption Blumberg Renata 1* https://orcid.org/0000-0002-7508-2974 Fowler Emily 1 Bai Yeon 1 https://orcid.org/0000-0001-6799-3156 Lal Pankaj 2 Smolen Alyssa 1 Dubrovsky Ilana 1 Di Noia Jennifer Academic Editor 1 Department of Nutrition and Food Studies, Montclair State University, Montclair, NJ 07043, USA; emilyfowler27@gmail.com (E.F.); baiy@montclair.edu (Y.B.); smolena1@montclair.edu (A.S.); ilana.dubrovsky@gmail.com (I.D.) 2 Department of Earth and Environmental Studies, Clean Energy and Sustainability Analytics Center, Montclair State University, Montclair, NJ 07043, USA; lalp@montclair.edu * Correspondence: blumbergr@montclair.edu 29 4 2022 5 2022 14 9 187113 12 2021 24 3 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 United States, many communities lack sufficient access to fresh produce. To improve access to fresh fruits and vegetables, the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides eligible participants vouchers through the Farmers Market Nutrition Program (FMNP) that can be redeemed directly from farmers at markets or farm stands. However, FMNP voucher redemption rates in New Jersey remain lower than those in neighboring states. This article used the social ecological model to examine differences between FMNP participants who redeem vouchers (Redeemers) and those who do not (non-Redeemers) in the areas of: produce procurement practices and consumption frequency, and barriers to and facilitators of FMNP voucher redemption. This cross-sectional study included WIC FMNP participants (N = 329) in northern New Jersey, USA. Analyses were conducted using descriptive statistics, independent sample t-tests, and one-way ANOVA. Compared to Redeemers, non-Redeemers consumed fewer average daily vegetable servings, were more likely to shop at small grocery/corner stores, and encountered significant barriers to FMNP redemption, e.g., difficulty finding time to redeem vouchers. social ecological model Farmers Market Nutrition Program food access farmers’ markets local food National Institute of Food and Agriculture, US Department of Agriculture2017-70001-25994 This material is based upon work that is supported by the National Institute of Food and Agriculture, US Department of Agriculture, under award number 2017-70001-25994. ==== Body pmc1. Introduction In the United States, the prevalence of diet-related chronic diseases continues to be a problem, with higher rates found among Hispanic, African American, and low-income populations [1,2]. A troubling tendency has been the increasing incidence of Type 1 and Type 2 diabetes in youths [3]. While chronic diseases are associated with diverse causal factors, high fruit and vegetable consumption helps to reduce disease risk [4]. However, many communities across the United States lack sufficient access to fresh produce [5]. Over the years, United States federal food and nutrition programs have been modified to encourage fruit and vegetable consumption, and non-profit organizations have also initiated programs to improve access to fresh produce [6,7,8]. WIC is the third largest federal food and nutrition program in the United States, serving approximately 6.2 million individuals each month [9]. The program supports low-income women, infants, and children up to five years of age who are deemed nutritionally at-risk by a health care professional. Research demonstrates that the WIC population is at a greater risk of developing adverse health outcomes due to insufficient nutrition and inadequate dietary patterns, leading to micronutrient deficiencies among other nutrition-related health concerns [10,11]. WIC provides participants with group and individualized nutrition education, supplemental foods to increase consumption of fresh fruits and vegetables, and health care and social services referrals [12]. WIC participants also receive cash-value vouchers to purchase eligible foods from participating grocery stores and supermarkets; items include breakfast and infant cereals, fresh fruits and vegetables, whole wheat bread and other whole grains, eggs, and infant formula [13]. WIC’s objective is to provide nutrition and health care interventions early in life to improve long-term health outcomes. The WIC Farmers Market Nutrition Program (FMNP) was founded in 1992 with the mission to provide fresh produce to WIC participants and expand access to farmers’ markets [14]. In 2015, WIC FMNP supported 1.7 million families with fresh produce; the program also provided over USD 14 million to over 18,000 participating farmers [15]. To redeem produce at farmers’ markets or farm stands, participants use FMNP vouchers to purchase fresh fruits and vegetables. FMNP vouchers may be redeemed from May until November, which marks the end of the season, while other WIC vouchers may be redeemed throughout the year [16]. State agencies have the authority to determine the value of FMNP vouchers. Federal FMNP guidelines enforce that the minimum benefit level must not fall below USD 10 and may not exceed USD 30, but states may choose to provide benefits either per individual or per family unit [17,18]. For example, New Jersey WIC FMNP vouchers were historically distributed once per year in the form of two USD 10 vouchers for each eligible participant (including the year when this research was conducted), but the value recently increased to USD 25 per participant for the season [19,20]. Other states such as South Carolina provide WIC FMNP participants with five USD 5 vouchers (USD 25 total) to purchase produce at approved farmers’ markets and farm stands [21]. The FMNP enables participants to select their own fresh, unprepared fruits, vegetables, and/or herbs from participating certified farmers. Although the number of locations to redeem vouchers (e.g., farmers’ markets and other direct-to-consumer marketing channels) has increased in New Jersey, redemption rates for WIC FMNP have remained below average in the region. In 2014, the FMNP redemption rate in New Jersey was 47.9%, while rates in surrounding states such as Pennsylvania and New York were 59.1% and 56.0%, respectively [22]. General FMNP redemption barriers mirror the barriers that low-income consumers face when attempting to shop at farmers’ markets [23,24]. However, few research studies have specifically focused on farmers’ market patronage by WIC participants, or by low-income consumers and ethnic/racial minorities more broadly [25]. In a systematic review of 49 peer-reviewed articles on facilitators of and barriers to farmers’ market patronage, Freedman et al. found that only 15% of the articles focused on racial or ethnic minorities, and 39% included information on low-income consumers [25]. Because farmers’ markets are relatively inexpensive to establish and have low overhead costs, compared to retail establishments, they provide an ideal structure to serve the nutritional needs of low-income communities with low access to fresh fruits and vegetables. However, considerable barriers hamper farmers’ market patronage among low-income consumers, including accessibility; transportation constraints; perception of high prices; lack of knowledge about WIC FMNP redemption possibilities; and inconvenient opening hours [25,26]. Because barriers to and facilitators of FMNP voucher redemption include individual, organizational, community, and policy-based factors, the social ecological model (SEM) provides a useful framework with which to understand FMNP redemption dynamics. The SEM conceives of individuals as shaped by social and spatial systems, which are conceptualized as concentric levels of influence around any given individual. Evaluating redemption behaviors through the lens of the SEM enables researchers to analyze the range of factors and themes that influence fruit and vegetable consumption. Applications of the SEM in nutrition research examine the significance of the following levels: first, the individual level of knowledge, habits, and beliefs; second, the interpersonal level of social relations, such as relationships between families and groups; third, the organizational level, including formal and informal organizations; fourth, community influences; and fifth, social structures and systems, including policies at all scales [27,28,29]. This framework has been widely used in nutrition research to better understand multiple determinants of behaviors through various levels of influence [30,31]. Analyzing behaviors within an individual’s social and spatial contexts enables researchers to identify influences at each level and to determine appropriate interventions [32]. Both barriers to and facilitators of FMNP redemption may exist at any of these levels. Individuals may already have the habit of going to the farmers’ market, which would facilitate FMNP redemption. Conversely, individuals may also lack knowledge on how to cook the fresh produce that is available at the farmers’ market, presenting a critical barrier. At the interpersonal level, family members may influence FMNP redemption due to their taste preferences. At the organizational level, the farmers’ market may not have convenient opening hours. At the community level, the farmers’ market may be located too far away. Finally, at the policy level, the WIC FMNP is a federal program, but states administer the program and determine eligibility requirements for farmers as well as the value of the FMNP vouchers. Therefore, state-level policies may influence redemption. For example, at the time of this study, New Jersey farmers were required to have at least five acres in production to certify becoming WIC FMNP farmers [19,33]. In addition, other state and local policies may also be influencing redemption. For example, states or local municipalities may play an active role in supporting the creation of farmers’ markets, thereby improving redemption possibilities in their communities. Despite the existence of these documented barriers, researchers have found that farmers’ market patronage is associated with higher fruit and vegetable consumption [34,35], and participation in the FMNP program has a positive effect on vegetable consumption [36]. However, sufficient research has not been conducted to understand why many WIC participants do not redeem their FMNP vouchers. The goal of this research project was to analyze FMNP voucher redemption by WIC participants, a population that is nutritionally at-risk and low-income. In particular, we sought to identify differences between FMNP voucher recipients who redeemed their vouchers and those who received FMNP vouchers but did not redeem them. Specifically, we sought to examine differences in demographic characteristics, produce procurement and consumption practices, and self-reported FMNP redemption barriers and facilitators. We hypothesized that, in comparison to WIC participants who did not redeem their FMNP vouchers, WIC participants who redeemed their FMNP vouchers would have similar demographic and behavioral characteristics to farmers’ markets shoppers more broadly. We also hypothesized that WIC participants who did not redeem their FMNP vouchers would report more barriers to FMNP redemption at all levels of the SEM. The research presented here is part of a larger research project. The findings from the larger project have been presented in poster sessions at US conferences and are published as abstracts [37,38]. 2. Materials and Methods A cross-sectional survey for WIC participants in northern New Jersey was conducted between October 2017 and January 2018. These months were selected because they coincide with the end of the farmers’ market season. This study design enabled the researchers to investigate multiple variables (e.g., redemption barriers and facilitators) at a single point in time. A non-randomized, convenience sampling method was utilized to increase the number of responses, and because randomization would have been difficult given that we did not have contact information for all FMNP participants. The survey was conducted utilizing an electronic tablet using the Qualtrics Survey Software offline tablet application, and the survey took approximately 10 to 15 minutes to complete. To recruit participants, a plea was given to individuals in two WIC office waiting rooms during opening hours. Both the plea and survey were written in the English and Spanish languages in consideration of local demographics; Spanish is the second most prevalent language spoken in households among all New Jersey counties and provided the opportunity for greater participation in this study [39]. Furthermore, the New Jersey Department of Health’s Division of Family Health Services estimates that over 50% of the WIC population in the state are Latino/Hispanic, and the primary language spoken in 30% of WIC households is Spanish [40]. Incentives were offered to participants, including a snack, stickers for children, and an opportunity to enter a gift card draw for a local supermarket. Institutional review board approval was granted prior to beginning data collection. The survey was divided into three parts. The first section assessed fruit and vegetable procurement and consumption practices and values, such as where and how often individuals shop for fresh fruits and vegetables between the months of June and November, the time period when FMNP vouchers are valid. Another question covered the transportation modes typically used to travel to the store or market. The importance of store or market characteristics, such as opening hours, location, accessibility, and measures of convenience, were assessed on a 5-point Likert scale (1 = Very Unimportant to 5 = Very Important). Fruit and vegetable consumption was self-reported on two scales. An adapted 2-item serving screener for fruit and vegetable intake was used [41]. Sample serving sizes were described and photos were provided to illustrate different serving sizes. Average fruit and vegetable consumption was assessed on a scale of “None” or “Less than One” (calculated as 0 average daily servings), “One” (calculated as 1 average serving), “Two” (calculated as 2 average daily servings), etc. Second, the number of servings of fruits and vegetables consumed in the past 24 hours was assessed, allowing respondents to specify a specific integer (0, 1, 2, 3, etc.). Additionally, a self-reported assessment of diet quality was obtained, including rankings of Poor, Fair, Good, Very Good, and Excellent. Common barriers to fruit and vegetable procurement and consumption were presented to respondents, such as price, time to prepare, and likeability of vegetables. Subsequent sections included questions on FMNP participation in previous years. Finally, the survey assessed demographic characteristics such as age, gender, education level, race/ethnicity, and employment status. The survey tool was developed and pre-tested to elicit feedback and to estimate response rates. Upon the completion of data collection, the results were exported into IBM Statistical Package for Social Sciences (SPSS) Version 25 for analysis. Survey respondents who participated in the FMNP in the previous year (2017) were clustered into two groups based on redemption behavior: those who redeemed any or all of their vouchers (Redeemers), and those who did not redeem any vouchers at all (non-Redeemers). One-way ANOVA and independent sample t-tests were conducted to compare mean redemption rates between Redeemers and non-Redeemers, grouped by demographics, barriers, and facilitators. Open-ended comments submitted by non-Redeemers were coded for themes [42], such as the type of barrier (e.g., time, interest, or knowledge) that respondents experienced in redeeming FMNP vouchers. Some respondents listed multiple barriers. Each barrier was counted in its specific category. Qualitative coding was cross-checked by another member of the research team. In addition, the FMNP redemption rate was calculated via the self-reported total value of vouchers redeemed divided by the total value of vouchers received for each participant. For example, if an individual received two USD 10 vouchers and only redeemed one of them, that individual’s redemption rate would be calculated as 50.0%. The redemption rates were also calculated for different demographic groups and analyzed using one-way ANOVA. 3. Results A total of 333 respondents indicated that they received FMNP vouchers in 2017. Of the FMNP participants, 228 redeemed all or some of their vouchers (henceforth “Redeemers”) and 101 did not redeem any of their vouchers (henceforth, “non-Redeemers”). Four respondents did not indicate whether they redeemed or not and were therefore excluded from the analysis. A total of 152 (46.2%) respondents took the survey in English and 181 (55.0%) took the survey in Spanish. The overall FMNP redemption rate in the 2017 season was 63.2%. Survey respondents who were over the age of 35 had a higher FMNP redemption rate, with a mean redemption rate of 72.3% (see Table 1). FMNP redemption rates were lower for survey respondents aged 25 to 34 and the lowest for those under the age of 24. The differences between these age groups were statistically significant (p = 0.041). While not significantly different (p = 0.251), FMNP recipients with higher levels of education had lower redemption rates (see Table 1). FMNP recipients employed on a part-time basis had a higher redemption rate than those who were employed full-time or unemployed, although this difference was also not statistically significant (p = 0.550). Respondents were asked to report their fruit and vegetable consumption as a daily average. In addition, total servings of fruits and vegetables consumed in the last 24 hours were recorded. As a daily average, Redeemers indicated eating more servings of vegetables than non-Redeemers, at a statistically significant level (1.66 versus 1.43, p = 0.050) (see Table 2). Redeemers reported slightly higher daily average consumption of fruit, but this difference was not statistically significant (1.94 versus 1.87, p = 0.520). Redeemers were significantly more likely to agree that both fruits and vegetables are too expensive. Although non-Redeemers reported a higher level of agreement with the statement that vegetables are time-consuming to prepare, this difference was not significant. Individuals were also asked where they usually shop for fresh fruits and vegetables between the months of June and November, and they could check as many or as few retail outlets from a list of 12 options. Fewer Redeemers than non-Redeemers shopped at supermarkets for fruits (64.0% versus 70.3%) or superstores (18.9% versus 26.7%). However, a greater proportion of non-Redeemers shopped at small grocery/corner stores (30.7% versus 23.2%). In comparison to Redeemers, non-Redeemers frequented fewer types of retail outlets to purchase fresh fruits and vegetables (2.09 versus 2.46 retail outlets). Similarly, Redeemers were more likely to utilize a greater number of transportation methods to travel to the store/market, but this difference was not significant. For Redeemers, these included private cars (57.5%), walking (39.0%), public bus (19.3%), and taxi/rideshare (16.2%). In contrast, non-Redeemers relied on private cars (65.3%), walking (35.6%), taxi/rideshare (11.9%), and public bus (9.9%). Table 3 displays FMNP redemption barriers, which were averaged and compared between groups. Non-Redeemers encountered barriers to FMNP redemption at the individual level, which were significantly higher than the individual-level barriers encountered by Redeemers. Table 4 displays FMNP redemption facilitators. Redeemers were more likely to agree that they would redeem the vouchers if the value given per person was higher. In contrast, the average response reported for non-Redeemers was closer to neutral. Participants’ comfort level in redeeming the FMNP vouchers is analyzed in Table 3 and Table 4 at the interpersonal level and was found to be a statistically significant barrier to voucher redemption (p = 0.003). Participants also reported that they would redeem the vouchers if they were more comfortable in redeeming them. This was also found to be statistically significant (p = 0.016). Table 5 contains coded, open-ended comments provided by non-Redeemers, which provide insight into why they did not redeem their vouchers. High percentages of non-Redeemers encountered individual-level barriers. 4. Discussion At the individual level of the SEM, important differences in demographic characteristics, knowledge, and practices were found between FMNP Redeemers and non-Redeemers. Older respondents had higher FMNP redemption rates, which confirms findings from other studies that found that farmers’ markets attract middle-aged adults [43]. Existing research has also shown that race/ethnicity may influence farmers’ market patronage, and that women and college-educated shoppers are more likely to shop at farmers’ markets [43,44,45,46,47,48]. In contrast, our study found that FMNP redemption rates decreased in groups with higher levels of education, although these differences were not statistically significant (Table 1). Interestingly, redemption rates were higher for those who worked part-time, in comparison to those who were unemployed or worked full-time, although this difference was not statistically significant. The inability to make time in personal schedules to go to the farmers’ market or farm stand was mentioned by 23.0% of non-Redeemers as a reason for why they did not redeem the vouchers (Table 5). Another set of differences between Redeemers and non-Redeemers at the individual level includes fruit and vegetable consumption and procurement practices. Existing research on farmers’ market consumers has shown that they tend to consume more fruits and vegetables than shoppers who do not frequent farmers’ markets [35]. Other research on FMNP showed that after an intervention, individuals who redeemed the vouchers consumed more fruits and vegetables [44]. Our study found that, on average, Redeemers consumed more vegetables, but not significantly more fruit. Non-Redeemers were less likely to agree that fruits and vegetables were too expensive. Therefore, they may have fewer financial incentives to redeem the vouchers. Non-Redeemers were also more likely to report that it was difficult to find time to redeem vouchers (Table 3), and they were more likely to agree that they would redeem the vouchers if they had more time (Table 4). Other researchers studying dietary practices of low-income families have found that the perceived lack of time is a barrier to healthy eating [49,50]. Shopping strategies and transportation methods may also impact FMNP voucher redemption because low-income consumers face particular barriers when shopping for food [51]. For example, they are less likely to have access to a car than the general public [52]. Transportation has been an identified barrier in FMNP redemption as early as 1999, when the Community Food Security Coalition investigated whether transportation serves as a significant barrier to farmers’ market access [53]. In comparison to low-income American residents more broadly [51], our survey’s non-Redeemer respondents reported using a private car less often but walked more often. Faced with various barriers, low-income consumers develop shopping strategies which are highly dependent on access to different modes of transportation, including taxis [51]. Limited access to public transportation has been reported as a significant barrier for low-income consumers to accessing farmers’ markets [25,53]. In our study, most survey respondents selected more than one transportation method when asked how they usually travel to the store/market to purchase fresh fruits and vegetables. However, a minority of respondents reported using public buses, the main form of public transportation available in the surveyed communities. In comparison to Redeemers, among non-Redeemers, a higher percentage of respondents reported using a private car and a lower percentage of respondents reported walking or using a public bus. For 10.0% of non-Redeemers, transportation issues were a barrier to voucher redemption, and 8.9% explained that factors at the interpersonal level, such as having to take care of small children, influenced their transportation and shopping behavior (Table 5). Additional research demonstrates that a consumer’s proximity to farmers’ markets may influence where they shop; proximity may increase access and decrease barriers to fruit and vegetable consumption [34,54]. Furthermore, non-Redeemer responses indicated that they live further from farmers’ markets, increasing their need for alternate modes of transportation. At the interpersonal level, we found that a lack of comfort in redeeming vouchers may play a role in voucher redemption. Martin et al. analyzed redemption rates among food stamp recipients as well as those eligible to visit a food pantry or soup kitchen [55]. This study discovered that one of the primary reasons this population does not visit a pantry or soup kitchen was due to the low comfort level participating in the program. Researchers state that addressing social stigma and acceptability could help to address these barriers to program participation. At the organizational level, previous research has documented factors related to farmers’ market operations, which inhibit farmers’ market patronage by low-income consumers [25]. For example, low-income consumers may not frequent farmers’ markets because they do not offer a sufficient variety of foods or culturally appropriate food, or do not accept food stamps [25,56]. In a recent study analyzing FMNP participant barriers and behaviors in North Carolina, 76% of participants reported that variety was a primary motivator to redeeming FMNP vouchers [15]. Purchasing behaviors were also analyzed in this group and demonstrated that participants purchased over 20 different varieties of fruits and vegetables, with the most popular items being tomatoes, squash, bell peppers, and white potatoes. In our study, both Redeemers and non-Redeemers tended to disagree or have neutral opinions about statements such as: “the closest farmers’ market/farm stand lacks familiar produce” (Table 3). Our research found that although barriers at the organizational level did exist, more barriers at the individual level were found to be statistically significant. However, they may also be interrelated. For example, non-Redeemers reported significantly higher levels of agreement with the statements: “It is difficult to find time to redeem the vouchers,” and “The closest farmers’ market/farm stand is not open at convenient times.” Research conducted by Ball and colleagues also demonstrated that convenience in terms of opening hours and location is a considerable barrier for WIC FMNP participants, and reducing these barriers is critical to improving fruit and vegetable consumption in this vulnerable population [15]. Another recent study surveyed WIC FMNP participants and found that 35.65% of participants lacked knowledge of when the farmers’ market was open and 45.21% did not know of a farmers’ market in their local area [57]. Improved communication and consistency of farmers’ market opening hours and locations, as well as an increase in mobile farm usage, could be beneficial in reducing transportation and other barriers that participants face. At the community level, one WIC office was served with a weekly mobile vegetable market operated by a local non-profit organization, and the other WIC office was in a city with a weekly farmers’ market. Nevertheless, non-Redeemers expressed a high level of agreement with the statement that “the closest farmers’ market/farm stand is too far away” (Table 3). This may be because WIC participants do not necessarily reside in the same city where the WIC office and farmers’ market are located. An Oregon case study analyzed 108 participant responses and found that 21% claimed that farmers’ market distance and limited opening hours were barriers to FMNP redemption [58]. Other research has shown that projects that make farmers’ markets more accessible, such as farm-to-WIC interventions, can improve voucher redemption and can be cost effective [59]. At the policy level, non-Redeemers reported lower levels of agreement with the statement that the value of the vouchers is not high enough. Specifically, the mean response was 2.85, which was between disagree and neutral. This suggests that increasing the value of the vouchers might not be enough to encourage non-Redeemers to utilize them. This has ramifications for programs such as the new incentive initiatives that provide extra vouchers to WIC and Supplemental Nutrition Assistance Program (SNAP) recipients who shop at farmers’ markets. These programs are meant to encourage low-income consumers to shop at farmers’ markets and therefore increase access to local food. While the value of the incentive varies, often these programs will double the value of what the shopper spends at the market using their WIC Cash Value Vouchers, FMNP vouchers, or SNAP benefits. Double-value programs provide benefits to farmers and consumers who use them [60], and research suggests that these programs may attract new farmers’ market patrons [61]. Strengths and Limitations of This Study Our research found significant individual-, organizational-, and community-level barriers for non-Redeemers. Some barriers at the individual level can be addressed more easily than others. For example, because non-Redeemers were more likely to agree that it is difficult to know where to redeem the vouchers, interventions designed to address this could include publishing the list of farmers who are certified to accept FMNP vouchers in a format that is easy to navigate. The state of New Jersey has only recently begun to publish this information, but other states provide this information on easily accessible websites. Information could be provided in multiple languages, with links to websites for the farms and farmers’ markets. Although some public listings in New Jersey include information on farmers’ markets that have farmers who accept FMNP, providing information on which farmers at the market accept FMNP would make the process of redeeming vouchers easier for WIC FMNP participants. Another individual-level barrier was the lack of time, an issue faced by families of diverse socioeconomic backgrounds [62]. A related organizational-level barrier was the inconvenient opening hours of farmers’ markets or farm stands. Weekend markets may be more attractive for this population, but these markets may experience problems attracting farmers, especially if they intend to be open for long hours. Participants were less likely to report a lack of quality, variety, or familiar produce as a barrier. In addition, in the open-ended responses, language barriers were not widely reported to be a barrier. This should be investigated further. This study has several limitations. This cross-sectional study was designed to gain a large number of survey responses from WIC participants in urban areas of northern New Jersey. The goal was to provide a snapshot of redemption behaviors, rather than track participants over a period of time. In addition, surveys were conducted at only two WIC offices, and all data were self-reported. This type of study design may introduce bias. For example, it was not feasible to verify if the vouchers were, in fact, redeemed by the survey respondents. This study utilized non-randomized, convenience sampling, which may also introduce bias and limits the generalizability of the sample population. Future research could utilize other methods to track fruit and vegetable consumption and voucher redemption so that differences between Redeemers and non-Redeemers could be more accurately analyzed. Moreover, the generalizability of the findings is limited because each community will have different access to farm stands or farmers’ markets where vouchers could be redeemed. Future research could evaluate differences within the Redeemers category, such as by analyzing redemption rates among low and high Redeemers, or those that redeemed some or all of their vouchers. Barriers and facilitators can also be further analyzed to see if there are differences between groups based on their level of agreement with barriers to and facilitators of FMNP redemption. Farmer perspectives, another component of the larger issues regarding FMNP redemption, deserve further study. Finally, this study was conducted before the coronavirus pandemic, which has had a significant impact on food insecurity [63], food procurement practices [64], and local food markets [65]. These impacts and resulting changes should be considered in any future research. Despite these changes and challenges, WIC and FMNP continued operating. Farmers’ markets adapted to meet coronavirus safety procedures, such as changing operations and infrastructure to practice social distancing. However, redemption barriers still exist. Certain barriers such as cost, availability of produce, and access to fruits and vegetables may have worsened during the pandemic, as global and domestic supply chains were significantly disrupted [66]. Future research could investigate any changes to redemption barriers since the start of the coronavirus pandemic. A variety of interventions are currently being implemented to increase FMNP redemption. Mobile markets are also becoming more popular with urban agriculture organizations who want to better serve their communities. Further research could explore differences between different interventions. For our study, we did not collect the addresses of the survey respondents. As a result, we were unable to more accurately link FMNP redemption with accessibility to a farmers’ market or farm stand. Future research could also take a place-based approach to redemption barriers so that interventions to improve redemption rates could be tailored towards individual communities. 5. Conclusions According to the Centers for Disease Control and Prevention, only about 1 in 10 US adults consume the minimum amount of recommended daily fruits and vegetables [67]. The USDA WIC Farmers Market Nutrition Program was created to increase access to local produce for WIC participants [14]. The increasing use of electronic benefit transfer systems at farmers’ markets and the use of incentives have improved patronage among low-income consumers, including WIC participants, but a variety of barriers to redemption still remain [54,68,69]. Utilizing the social ecological model, this study identified FMNP redemption barriers, facilitators, and related behaviors in a population of WIC participants in the US state of New Jersey. Acknowledgments We would like to thank the students who participated in data collection for this project. We would also like to thank the WIC clinic directors who allowed us to conduct the study at their sites, and we would like to thank the survey respondents for being generous with their time. Author Contributions Conceptualization, R.B. and P.L.; methodology, R.B., Y.B., E.F. and P.L.; software, E.F.; formal analysis, Y.B. and E.F.; investigation, R.B. and E.F.; data curation, E.F.; writing—original draft preparation, R.B., E.F. and A.S.; writing—review and editing, R.B. and I.D.; visualization, E.F. and I.D.; supervision, R.B.; project administration, R.B.; funding acquisition, R.B. and P.L. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was approved by the Montclair State University Institutional Review Board IRB-FY16-17-385. 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. nutrients-14-01871-t001_Table 1 Table 1 Demographics and Redemption Rates for Survey Respondents. n Mean Redemption Rate (%) P-Value Age Under 24 years 62 54.44 0.041 25–34 years 155 62.15 Over 35 years 100 72.25 Race/Ethnicity Asian/Pacific Islander 5 90.00 0.193 Black or African American 50 62.00 Hispanic or Latino 239 64.44 Native American 1 0.00 White 13 44.87 Other 6 66.67 Highest Level of Education Less than High School 43 71.51 0.251 High School Graduate, Diploma, or Equivalent (GED) 147 66.67 Post High School Education, No Degree 88 59.75 College Degree or More 35 54.29 Employment Status Employed Full-Time 70 63.21 0.550 Employed Part-Time 40 71.25 Unemployed 208 62.78 One-way ANOVA tests were conducted to identify if there were any statistically significant differences in redemption rates between demographic groups. nutrients-14-01871-t002_Table 2 Table 2 Fruit and Vegetable Consumption. n Mean SD P-Value Average Daily Fruit Servings * Redeemers 228 1.94 0.97 0.520 Non-Redeemers 101 1.87 1.05 Average Daily Vegetable Servings * Redeemers 227 1.66 0.96 0.050 Non-Redeemers 101 1.43 0.99 24-Hour Recall: Fruit Servings * Redeemers 228 2.17 1.66 0.989 Non-Redeemers 101 2.17 1.66 24-Hour Recall: Vegetable Servings * Redeemers 228 1.80 1.50 0.893 Non-Redeemers 101 1.77 1.86 Independent samples t-tests were conducted to determine if there were significant differences in fruit and vegetable consumption between Redeemers and non-Redeemers. * 0 = Zero Servings or Less than One Serving; 1 = One Serving; 2 = Two Servings; 3 = Three Servings. nutrients-14-01871-t003_Table 3 Table 3 Barriers to FMNP Redemption. Barriers to FMNP Redemption Redeemers Non-Redeemers P-Value n = 228 n = 101 Mean (SD) Mean (SD) Individual It is difficult to... ...know where to redeem the vouchers 2.85 (1.49) 3.51 (1.50) <0.001 ...find time to redeem the vouchers 2.85 (1.45) 3.60 (1.40) <0.001 Interpersonal It is uncomfortable to redeem vouchers 2.37 (1.36) 2.87 (1.50) 0.003 Organizational The closest farmers’ market/farm stand... ...is not open at convenient times 3.56 (1.40) 3.98 (1.12) 0.010 ...lacks quality produce 2.56 (1.34) 2.87 (1.22) 0.077 ...lacks a variety of produce 3.10 (1.45) 3.12 (1.30) 0.920 ...lacks familiar produce 2.94 (1.43) 2.94 (1.28) 0.969 ...lacks produce that I or my family likes 2.90 (1.44) 2.90 (1.26) 0.979 Community The closest farmers’ market/farm stand is too far away 3.26 (1.47) 3.78 (1.28) 0.003 Policy The value of the vouchers given per person is not high enough 3.07 (1.43) 2.85 (1.36) 0.196 1 = Highly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Highly Agree. Independent samples t-tests were conducted to determine if there were significant differences in mean barriers to FMNP redemption between Redeemers and non-Redeemers. nutrients-14-01871-t004_Table 4 Table 4 Facilitators of FMNP Redemption. “I would redeem if...” Redeemers Non-Redeemers P-Value n = 228 n = 101 Mean (SD) Mean (SD) Individual I knew where to redeem the vouchers 3.46 (1.45) 4.00 (1.24) 0.002 I had more time to redeem the vouchers 3.59 (1.40) 4.04 (1.14) 0.006 Interpersonal I was more comfortable redeeming vouchers 3.35 (1.39) 3.75 (1.20) 0.016 Organizational the closest farmers’ market/farm stand... ...was open at more convenient times 3.88 (1.28) 4.25 (0.88) 0.012 ...had better quality produce 3.34 (1.46) 3.44 (1.23) 0.624 ...had a better variety of produce 3.71 (1.36) 3.54 (1.24) 0.332 ...carried more familiar produce 3.67 (1.38) 3.59 (1.19) 0.680 ...had produce that I or my family likes 3.64 (1.38) 3.61 (1.19) 0.872 Community the closest farmers’ market/farm stand was located closer 3.94 (1.22) 4.14 (0.97) 0.168 Policy the value of the vouchers given per person was higher 3.82 (1.31) 3.32 (1.38) 0.002 1 = Highly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Highly Agree. Independent samples t-tests were conducted to determine if there were significant differences in mean facilitators to FMNP redemption between Redeemers and non-Redeemers. nutrients-14-01871-t005_Table 5 Table 5 Analysis of Open-Ended Responses. Barriers to FMNP Redemption % Non-Redeemers Examples Reporting Barrier n n = 90 Individual Lack of... ...time 23 25.6% “No time to make a special trip.” “I work 7 am to 4 pm. It is impossible for me to redeem my checks if the veggie car [mobile farm stand] only comes Friday mornings.” ...interest 8 8.9% “I forgot I had them.” ...knowledge on how to redeem/difficult finding where to redeem 33 36.7% “Figuring out where to go, commuting may be difficult.” “We couldn’t find a farmers market in our area.” ...access to private car/transportation issues 9 10.0% “No ride” Other personal barrier 7 7.8% “Line too long, bags too heavy, pregnant.” Interpersonal Children limit shopping opportunities 8 8.9% “I don’t have a car; it’s not local enough for me having a 3 year old and her things to take on a bus.” Language barrier limits shopping opportunities 1 1.1% “Because I wasn’t sure of the expiration date, language barrier.” Organizational Farmers’ market/farm stand... ...is not open at convenient times 11 12.2% “Timing of the markets. Extend opening hours.” ...is not reliable (hours; produce gets sold out) 8 8.9% “[The mobile farm stand] is not reliable; at times they don’t show up.” ...lacks variety or familiar food 5 5.6% “They don’t bring enough products I’m familiar with.” Community Community lacks... ...farmers’ market/closest market is too far 27 30.0% “I have no time; the nearest market it’s far; I usually walk there.” ...adequate transportation options 8 8.9% “The places were too far; I didn’t know how to get there. Taxi charges me more than $20, more than the value of the checks.” Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Gaskin D.J. Thorpe R.J. Jr. McGinty E.E. Bower K. Rohde C. Young J.H. LaVeist T.A. Dubay L. Disparities in Diabetes: The Nexus of Race, Poverty, and Place Am. J. Public Health 2014 104 2147 2155 10.2105/AJPH.2013.301420 24228660 2. Menke A. Casagrande S. Geiss L. Cowie C.C. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092469 jcm-11-02469 Article Safety and Efficacy of the Nit-Occlud® Coil for Percutaneous Closure of Various Sizes of PDA https://orcid.org/0000-0003-1337-563X Jung Seyong 1† https://orcid.org/0000-0001-8258-3497 Seol Jaehee 2† Choi Jaeyoung 1* Ha Keesoo 3* Dell’Amore Andrea Academic Editor 1 Division of Pediatric Cardiology, College of Medicine, Yonsei University, Seoul 03722, Korea; jung811111@yuhs.ac 2 Department of Pediatrics, Yonsei University Wonju College of Medicine, Wonju 26426, Korea; seoljh0623@gmail.com 3 Department of Pediatrics, College of Medicine, Korea University, Seoul 02841, Korea * Correspondence: cjy0122@yuhs.ac (J.C.); kissuha@naver.com (K.H.); Tel.: +82-2-2228-8280 (J.C.); +82-2-2626-1229 (K.H.) † These authors contributed equally to this work. 28 4 2022 5 2022 11 9 246931 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/). Most interventionalists use the Amplatzer Duct Occluder (ADO) or the Nit-Occlud® Coils (NOC) to close patent ductus arteriosus (PDA). Data regarding the success and effect of NOCs in the occlusion of large PDAs are insufficient. We aimed to investigate whether the PDA occlusion of large PDAs using NOC is safe and efficient for all ages. This was a retrospective study involving 361 pediatric and adult patients who underwent the transcatheter closure of PDA using NOC over the past 21 years for all PDA sizes and ages. The sizes of PDA were classified as small, moderate, and large. A comparison of the aortic pressure before and after PDA occlusion using NOC showed significant differences in terms of systolic and pulse pressures for all age groups (p < 0.05). The rate of the residual shunts of NOC was 2%, while the rate of complete occlusions of NOC was 98% at 12 months after occlusion regardless of the shape of PDA. The complication rate with PDA occlusion using NOC was 5%. PDA occlusion using NOC is as effective and safe as ADO for the occlusion of PDA of all sizes. Therefore, PDA occlusion using NOC can be a safe and feasible procedure to close various sizes and types of PDA without complications. patent ductus arteriosus therapeutic occlusion procedure This research received no external funding. ==== Body pmc1. Introduction Device procedures for the closure of patent ductus arteriosus (PDA) have increasingly been preferred over open-heart surgery due to their associated lower mortality and morbidity; however, their costs are more expensive than open surgery [1]. A number of techniques and occluders, including coils and devices, have been developed for the transcatheter closure of PDA over recent decades ever since the percutaneous closure of PDA for the first time in 1967 by Porstmann [2]. There is currently no consensus on which types of devices are more suitable for the different sizes of PDA. Nevertheless, data have shown that the Amplatzer ductal occluder (ADO) device and Nit-Occlud® coil (NOC, PFM Medical AG, Cologne, Germany) are more efficient and safer for a relatively large PDA [3]. The transcatheter closure of PDA using the NOC is a safe and simple method, which can be performed for all age groups. However, most investigations on the NOC have been limited to small or moderate PDAs [4,5,6,7]. Data regarding the safety and efficacy of NOC in the occlusion of large PDAs have not been sufficiently reported compared to those of ADO. In this study, we aimed to determine the safety and efficacy of NOC in the transcatheter closure of large PDAs for all ages, including pediatric and adult patients. 2. Materials and Methods 2.1. Patients We retrospectively investigated PDA patients who underwent PDA occlusion using NOC between April 1995 and November 2016 (21 years) at Severance Cardiovascular Hospital, Yonsei University. A total of 361 patients, including pediatric and adult patients, were enrolled in this study. The enrolled patients were divided into five pediatric age groups and one adult age group: 6 months of age to <1 year of age, 1 year of age to <6 years of age, 6 years of age to <12 years of age, 12 years of age to <18 years of age, and 18 years of age and above. The sizes of PDA were classified as small, moderate, and large, according to the scales of 2 and 4 mm (three groups). We retrospectively analyzed medical data, echocardiographic results, and angiographic findings with hemodynamic characteristics. The demographics, the sizes and types of PDA, and the size relationships between PDA and NOC were analyzed. Furthermore, the regional sizes of PDA, such as aortic ampulla (AoA), pulmonary ampulla (PuA), length, and PDA isthmus (PI), and the regional sizes of NOC, such as the distal diameter (DD) and proximal diameter (PD), were also analyzed. The size gaps between the PDA and used NOC reflect the relationship between the regional sizes of PDA and NOC; these include size gaps between the AoA of PDA and DD of NOC, and those between PuA and PD of NOC, which are anatomically related to each other. Moreover, since the size of PI of PDA is the standard for NOC selection, it is important to know the size differences (gaps) between PI and DD, and between PI and PD. Echocardiography was performed to assess the position of the NOC, the presence of residual shunts around PDA, and major or minor complications. Follow-up echocardiography analyses were conducted at the immediate time of the procedure, the next day, and at 1 month, 6 months, and 1 year after the procedures. Hemodynamic characteristics in the angiographic findings were obtained by observing the changes in blood pressure and the ratio of pulmonary blood flow to systemic blood flow (Qp/Qs) before and after PDA occlusion using NOC during cardiac catheterization. The aortograms were obtained in the right anterior oblique angle (30°) and lateral angle (90°) to confirm the positions of PDA and NOC. Additionally, the maximum diameters of the narrowest portion of the PDA (PDA isthmus, PI) were measured on frozen images. Furthermore, balloon-occlusive diameters of PDA were measured to calculate the accurate size of PDA, if needed. The residual shunts and configurations were identified within 10 to 15 min via an aortic aortogram after the implantation of NOC. Mild narrowing (peak velocity < 1.5 m/s) of the pulmonary artery (PA), mild narrowing of the aorta (peak velocity < 1.5 m/s), and transient weakness of the arterial pulse were regarded as minor complications. A peak velocity of >1.5 m/s was considered as stenosis, which indicated the presence of a major complication. The procedural success in the PDA occlusion using NOC was considered as conditions with the absence of a residual shunt, stenotic lesions of the aorta, PA, and any other serious complications. 2.2. Ethics Statement This study was approved by the Institutional Review Board of the Severance Hospital, Yonsei University Health System (4-2021-0800). The requirement for informed consent was waived due to the retrospective nature of the study. 2.3. Statistical Analysis All data were represented as mean ± standard deviation, and a p value < 0.05 was regarded as statistically significant. Statistical analyses were performed using the SPSS 20 software (IBM Corp., Armonk, NY, USA). Additionally, the values were compared among each group using a non-parametric test (Mann–Whitney U test, χ2 test, and Wilcoxon test). 3. Results The mean age and body weight of all patients, including pediatric and adult patients, were 80 months (6.7 years) and 20 kg (not shown in Table 1), respectively. The pressure differences between the pediatric and adult groups were significant in terms of the following: systole, mean, and pulse pressures in the aorta before PDA occlusion using NOC (p < 0.01), pulse pressure in the main PA before PDA occlusion using NOC (p < 0.05), systole, diastole, and mean pressure gaps between the aorta and the main PA before PDA occlusion using NOC (p < 0.01), and systole and pulse pressure in the aorta after PDA occlusion using NOC (p < 0.05) (Table 1). The size gaps between PDA and NOC showed significant differences in each pediatric and adult group. The size gaps between AoA and DD among the pediatric groups showed significant differences (p = 0.001), and their mean size gap was approximately 2 mm (1.7 ± 3.4 mm). The size gaps between PuA and PD, PI and DD, and PI and PD among the pediatric groups did not show significant differences, and their mean size gaps were approximately 0 mm (−0.3), −4 mm (−3.5), and −3 mm (−2.6), respectively. The size gaps of AoA and DD, PI and DD, and PI and PD between the pediatric and adult groups showed significant differences (p < 0.001, respectively). Additionally, their mean size gaps in the adult group were approximately 5 mm (5.1), −5 mm (−5.0), and −2 mm (−1.8), respectively. The size gaps of PuA and PD between the pediatric and adult groups did not show significant differences, and the mean size gap in the adult group was observed to be approximately 1 mm (1.3). The Qp/Qs before PDA occlusion using NOC showed significant differences not only between the pediatric and adult groups (p = 0.001), but also among the pediatric groups (p = 0.023). However, the Qp/Qs after the PDA occlusion using NOC did not show statistical differences among all age groups (Table 1; Figure 1). The most common size group of PDA was the moderate size. Additionally, age and body weight showed significant differences among the size groups of PDA (p < 0.001). The pressures among the size groups of PDA showed significant differences as follows: systolic and pulse pressure of the aorta (p < 0.001); systolic, diastolic, mean pressure of the main PA (p < 0.05); and systole pressure gaps between the aorta and main PA (p < 0.001) before PDA occlusion using NOC. However, the systole, diastole, mean, and pulse pressures of the aorta after PDA occlusion using NOC did not show significant differences among the PDA size groups. The size gaps between PDA (AoA, PuA and PI) and NOC (DD and PD) showed significant differences among the size groups of PDAs; the size gap between AoA and DD and the size gap between PI and PD showed significant differences (p < 0.001, respectively). The Qp/Qs before PDA occlusion using NOC among the different PDA size groups and Qp/Qs between before and after PDA occlusion using NOC showed significant differences (p < 0.001, respectively). The rate of residual shunts of NOC decreased from 25% to 2%, while the rate of complete occlusions of NOC increased from 75% to 98% from the immediate time of the procedure to 12 months after PDA occlusion using NOC (Table 2). The frequency order of the PDA types in the patients was as follows: A (conical) > E (elongated) > B (window) > C (tubular) > D (complex). Additionally, the one in the pediatric group was the same as those in all patients. The frequency order of PDA types in the adult group was A > B > E = C > D, although the number of adult patients was small. The frequency of type E (elongated) PDA in the pediatric group was higher than that in the adult group (p = 0.048) (Table 3). A comparison of the systole and the pulse pressure of the aorta before and after PDA occlusion using NOC showed significant differences in the total age group and pediatric age group (p < 0.05). A comparison of the Qp/Qs values before and after PDA occlusion using NOC showed significant differences in all age groups (p < 0.001, respectively) (Table 4). The most common diagnosis of congenital heart diseases (CHDs) accompanying PDA occluded by NOC was the simple PDA without other CHDs. Other common diagnoses of CHDs accompanying PDA occluded by NOC were the secundum atrial septal defect, ventricular septal defect, endocardial cushion defect, and the Taussig–Bing anomaly (Table 5). The most common complication associated with PDA occlusion using NOC was a residual shunt, followed by disturbance in the flow of PA by NOC. The total proportion of complications associated with PDA occlusion using NOC was 5% (Table 6). 4. Discussion The pressures prior to PDA occlusion using NOC showed statistical differences not only between pediatric and adult groups, but also among different pediatric age groups. However, these differences occur only due to the gradual physiological increase in normal blood pressures according to the age and body surface area [8]. Moreover, the gradual increase in the aortic ampulla, pulmonary ampulla, length, and isthmus of PDA prior to the occlusion of NOC with age occurs due to the same reasons. The occlusion of PDA has an influence on the systemic blood pressure and cerebral circulation of pediatric patients. Furthermore, it leads to an increase in the systemic systolic, diastolic, and mean pressures after the percutaneous closure of PDA [9]. The ratio of Qp/Qs after PDA occlusion using a coil showed a dramatic decrease due to the decrease in extra pulmonary blood flow compared to that before the coil occlusion of PDA [10]. These facts are consistent with our investigation and are well-known physiological characteristics observed after PDA occlusion using a coil. It was meaningful that the pressure changes before and after PDA occlusion using NOC were established basically according to chronological ages. According to the instruction manual of NOC on the PFM medical AG website (Nit-Occlud® PDA. Available Online: https://www.pfmmedical.com/productcatalogue/occluder/nit_occludr_pda/index.html (assessed on 15 March 2022)), the diameter of NOC should be selected as follows: the distal diameter of the coil (DD) should be a maximum of 2 mm larger than that of the aortic ampulla (AoA, represented as D2 in the instructions). The DD should be minimal and should be 3 to 4 mm larger than the PDA isthmus (PI, represented as D1 in the instructions). However, these instructions could be confusing or unperceivable; therefore, we created the following equations for the sizes of the PDA and NOC used based on Table 1:PuA (=PI + 3) = PD (=PI + 3) > PI < DD (= PI + 4) < AoA (=PI + 6) in children (the unit mm) PuA (=PI + 3) > PD (=PI + 2) > PI < DD (= PI + 5) < AoA (=PI + 10) in adults (the unit mm) These novel formulae are feasible and understandable and can definitely help in selecting the NOC sizes in a stable manner according to the various sizes and morphologies of PDA. The size relationships between the regions of PDA and NOC are illustrated in Figure 2 and Figure 3. Almost all previous studies reported that NOC was effective and safe for small to moderate PDAs [4,5]. Our result showed that 50 patients had large PDA, with a size ranging from 4 to 9 mm in 27 pediatric (age ≤ 6 months; 1, 7–12 months; 3, 1–6 years; 13, 7–12 years; 7, 12–18 years; 3) and 23 adult patients. The large PDA accounted for the largest proportion in the adult group, and it was the most common PDA size at the age of 1–6 years compared to all other pediatric age groups. The rate of residual shunts in the large PDA group decreased to 6% at 12 months from 26% immediately after PDA occlusion using NOC. Furthermore, the success rate in the large PDA group was 94% in 12 months after PDA occlusion using NOC. Three patients in the large PDA group had residual shunts. Among the three, one had a trivial residual shunt, while two had moderate residual shunts, which were occluded by additional NOCs. The rate of persistent residual shunts was higher in the large-sized PDA group than those in small- or moderate-sized PDA groups. However, the rate of the residual shunt in large PDA was 6%, which could be controlled and treated with additional coils or secondary devices. The complications of patients with large PDA occluded by NOCs included having two residual shunts and atrial fibrillation. The two residual shunts were treated via the implantation of extra coils, while atrial fibrillation was treated with medication. Therefore, the PDA occlusion using NOC is an effective and safe procedure for the occlusion of large PDAs in addition to small to moderate PDAs, without major complications. The geometric shapes of PDA devices were developed since angiographic classification of PDA types was established by Krichenko A et al. [11]. Some studies reported that the frequency order of PDA types, which consisted of mostly pediatric patients, was as follows: conical > elongated > tubular > window > complex or conical > tubular > elongated > window > complex [12,13]. Most studies reported that the conical type was the most common type of PDA, while the rarest one was the complex type. The frequency order of PDA types among our study patients, consisting mostly of children and a few adults, was as follows: conical > elongated > window > tubular > complex. Furthermore, the frequencies of the elongated and window types in our study were relatively higher compared with those in other studies. The frequencies of the elongated and window types in the pediatric group of our study were relatively high compared with those in the adult group of our study. The ratio of the window-type PDA was evenly distributed among small, moderate, and large PDA groups (6/101 = 6%, 16/210 = 8%, and 4/50 = 8%, respectively). The elongated-type PDA, in addition to the fetal (F)-type PDA, was relatively common in pre-term infants [14]. Our study shows that the smaller the size of the PDA and the younger the age of the patient, the higher the ratio of elongated type PDA is (small PDA group 34/101 = 34%, moderate PDA group 24/210 = 11%, and large PDA group 4/50 = 8%) (p < 0.001, small vs. moderate, small vs. large PDA, respectively). The PDA occlusion using NOC did not show significant differences in the success rate according to the types of PDA, and it showed high success rates evenly in each group classified according to the PDA type. Therefore, the PDA occlusion using NOC is an effective procedure regardless of the morphological classification of PDA. One of the characteristics of PDA hemodynamics is having a peripheral bounding pulse and wide pulse pressure in PDA patients [15]. The pulse pressure and pulmonary blood flow before and after PDA occlusion using NOC in our study showed significant decreases in the entire patient group and pediatric patient group. Moreover, this fact reflects the hemodynamic characteristics according to the presence or absence of a PDA. It has been reported that the diastolic pressure after PDA occlusion using devices increased [10]. However, our results did not show significant increases after PDA occlusion using NOC. Most studies reported that there was neither mortality in any group nor serious complications associated with PDA occlusion using NOC [16,17]. The main complications associated with NOC intervention at 12 months after the procedure, in this study, were the presence of residual shunts and flow disturbances of PA. The rate of total complications associated with PDA occlusion using NOC was as low as 5%, while the degree of complication in the large PDA group was very low at 1%. Therefore, PDA occlusion using NOC is a safe and feasible procedure in occluding large PDAs without resulting in major complications. Limitations Pressure changes in the pulmonary artery before and after PDA occlusion using NOC were not compared because of insufficient main PA pressure data after PDA occlusion using NOC. Nevertheless, the percutaneous closure of PDA decreases immediately and continues to decrease gradually [18]. 5. Conclusions In summary, the novel formulae of the size relationships between the regions of PDA and NOC are feasible and understandable. Furthermore, they can be used to select NOC sizes in a stable manner, according to the various sizes and morphologies of PDA. PDA occlusion using NOC is as effective and safe as ADO for the occlusion of large PDAs in addition to small and moderate PDAs. Moreover, PDA occlusion using NOC is a feasible procedure, regardless of the morphological classification of PDA. Therefore, PDA occlusion using NOC is a safe and effective procedure for occluding various sizes and types of PDA without prominent complications. Author Contributions Conceptualization: K.H. and J.C.; methodology: S.J. and J.S.; Software: K.H. and J.C.; Validation: J.C. and J.S.; Formal analysis: S.J. and J.S.; Investigation: K.H. and S.J.; Data curation: S.J. and J.S.; Original draft preparation: K.H.; Review and editing: K.H. and J.C.; Supervision: J.C. 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 Severance Hospital, Yonsei University Health System (4-2021-0800) for studies involving humans. Informed Consent Statement The requirement for informed consent was waived due to the retrospective nature of the study. Data Availability Statement The data underlying this article will be shared at reasonable request to the corresponding authors. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The changes in PDA sizes (A) and size gaps between PDA and NOC (B) according the chronological age groups. Ao, aorta; AoA, aortic ampulla of PDA; NOC, Nit-Occlud® coil; PDA, patent ductus arteriosus; PuA, pulmonary ampulla of PDA; PI, PDA isthmus; DD, distal diameter of NOC; PD, proximal diameter of NOC. Figure 2 Illustration of the size relationships between regions of PDA and Nit-Occlud® Coils (NOC). The schematic illustration of (A) the regions of PDA, (B) the regions of NOC, and (C) the installed coil inside PDA. PuA; pulmonary ampulla of PDA, AoA; aortic ampulla of PDA, PI; PDA isthmus, PDA; patent ductus arteriosus, PD; proximal diameter of NOC, NOC; Nit-Occlud® coil, DD; distal diameter of NOC. Figure 3 The size relationships between the regions of PDA and NOC; PI of PDA with other regions of PDA and NOC. It is useful to select the size of NOC by measuring the sizes of PI, PuA, and Ao according to chronological age. Ao; aorta, AoA; aortic ampulla of PDA, NOC; Nit-Occlud® coil, PDA; patent ductus arteriosus, PuA; pulmonary ampulla of PDA, PI; PDA isthmus, DD; distal diameter of NOC, PD; proximal diameter of NOC. jcm-11-02469-t001_Table 1 Table 1 Characteristics of subjects with PDA occluded by NOC according to the chronological age groups. Pediatrics (0–18 y) Age ≤ 6 Months Age 7–12 Months Age 1–6 Years Age 7–12 Years Age 13–18 Years p Value (Among Pediatrics) Adults (>18 y) Number 325 26 57 175 57 10 36 Age (months) 41 ± 40 4 ± 2 10 ± 2 34 ± 18 103 ± 23 178 ± 21 <0.001 451 ± 185 Body weight (kg) 16 ± 11 7.0 ± 2.6 9.0 ± 1.6 14 ± 5 30 ± 10 56 ± 13 <0.001 57 ± 9 Pre-Ao Pr (mmHg)  Systole 111 ± 17 100 ± 10 102 ± 15 112 ± 16 125 ± 21 121 ± 13 <0.001 129 ± 26  Diastole 63 ± 14 54 ± 10 54 ± 10 64 ± 13 76 ± 15 76 ± 10 <0.001 66 ± 11  Mean 83 ± 15 72 ± 10 74 ± 13 84 ± 14 96 ± 16 93 ± 15 <0.001 89 ± 11  Pulse Pr 50 ± 15 48 ± 10 49 ± 13 48 ± 10 49 ± 12 45 ± 7 0.748 67 ± 14  Pre-MPA Pr  Systole 29 ± 9 29 ± 9 26 ± 6 29 ± 7 34 ± 13 36 ± 19 0.001 30 ± 8  Diastole 12 ± 6 11 ± 6 11 ± 5 12 ± 5 15 ± 8 15 ± 12 0.012 11 ± 4  Mean 19 ± 7 18 ± 6 18 ± 5 19 ± 6 23 ± 11 24 ± 16 0.003 19 ± 6  Pulse Pr 17 ± 6 17 ± 7 15 ± 5 16 ± 5 19 ± 7 21 ± 10 0.002 19 ± 5 Pr gaps of Pre-Ao and pre-MPA  Systole 82 ± 17 71 ± 15 76 ± 14 83 ± 16 95 ± 15 84 ± 23 <0.001 100 ± 22  Diastole 50 ± 14 42 ± 13 43 ± 11 51 ± 13 64 ± 12 60 ± 11 <0.001 55 ± 11  Mean 63 ± 15 53 ± 14 56 ± 13 64 ± 14 75 ± 11 68 ± 18 <0.001 71 ± 10 Post-Ao Pr  Systole 114 ± 15 95 ± 9 113 ± 6 115 ± 15 112 ± 19 123 ± 15 0.027 140 ± 17  Diastole 67 ± 12 47 ± 10 63 ± 6 68 ± 10 72 ± 24 73 ± 10 0.027 73 ± 3  Mean 86 ± 11 67 ± 6 83 ± 3 87 ± 10 87 ± 19 93 ± 16 0.035 90 ± 10  Pulse Pr 48 ± 14 47 ± 13 50 ± 10 47 ± 13 40 ± 9 50 ± 18 0.874 64 ± 25 PDA sizes (mm)  AoA 7.9 ± 3.6 7.3 ± 1.7 7.4 ± 2.6 7.6 ± 3.4 9.8 ± 5.5 10.5 ± 4.9 0.003 14.7 ± 5.2  PuA 5.3 ± 1.7 4.9 ± 1.2 5.0 ± 0.6 5.3 ± 1.8 6.4 ± 2.3 5.5 ± 2.1 0.061 8.0 ± 2.4  Length 9.2 ± 3.5 8.3 ± 2.8 8.7 ± 3.2 8.9 ± 3.1 11.9 ± 5.1 12.1 ± 3.4 <0.001 14.8 ± 5.9  PI 2.3 ± 1.0 2.3 ± 1.2 2.1 ± 0.9 2.3 ± 0.9 2.6 ± 1.2 2.9 ± 0.8 0.023 4.4 ± 1.6 Size gaps of PDA and NOC (mm)  AoA—DD 1.7 ± 3.4 0.8 ± 3.5 1.7 ± 2.1 1.3 ± 3.1 3.9 ± 5.2 2.8 ± 4.9 0.001 5.1 ± 5.8  PuA—PD −0.3 ± 1.6 −0.5 ± 1.2 −0.4 ± 0.8 −0.4 ± 1.8 0.6 ± 1.5 −0.5 ± 2.1 0.707 1.3 ± 2.5  PI—DD −3.5 ± 1.4 −3.6 ± 1.2 −3.4 ± 1.2 −3.6 ± 1.4 −3.2 ± 1.6 −4.4 ± 1.8 0.192 −5.0 ± 2.4  PI—PD −2.6 ± 1.0 −2.7 ± 1.0 −2.6 ± 0.9 −2.6 ± 1.0 −2.2 ± 1.4 −2.6 ± 0.8 0.365 −1.8 ± 1.9 Pre-Qp/Qs 1.4 ± 1.0 1.6 ± 0.5 1.4 ± 0.4 1.3 ± 0.3 1.3 ± 0.2 1.3 ± 0.2 0.023 1.5 ± 0.4 Post-Qp/Qs 1.0 ± 0.8 1.1 ± 0.2 1.0 ± 0.1 1.0 ± 0.1 1.0 ± 0.1 1.0 ± 0.0 0.716 1.0 ± 0.0 Ao = aorta; MPA = main pulmonary artery; AoA = aortic ampulla of PDA; NOC = Nit-Occlud® coil; PDA = patent ductus arteriosus; PuA = pulmonary ampulla of PDA; PI = PDA isthmus; DD = distal diameter of NOC; PD = proximal diameter of NOC; Qp/Qs = pulmonary blood flow/systemic blood flow; Pre- = before PDA occlusion using NOC; Post- = after PDA occlusion using NOC; Pr = pressure. jcm-11-02469-t002_Table 2 Table 2 Characteristics of PDA occlusion using NOC according to the PDA size groups. Size Groups of PDA Isthmus (PI, mm) at Catheterization Small (0.5 ≤ Sizes < 2) Moderate (2 ≤ Sizes < 4) Large (4 ≤ Sizes ≤ 9) p Value Numbers (n = 361) 101 210 50 Age, m 28 ± 24 59 ± 106 202 ± 220 <0.001 Body weight, kg 13 ± 7 19 ± 16 38 ± 21 <0.001 Pre-Ao Pr, mmHg  Systole 109 ± 19 112 ± 18 123 ± 22 <0.001  Diastole 64 ± 15 62 ± 13 67 ± 13 0.191  Mean 82 ± 17 83 ± 15 88 ± 13 0.111  Pulse Pr 46 ± 11 50 ± 12 56 ± 19 <0.001  Pre-MPA Pr  Systole 27 ± 7 29 ± 8 32 ± 11 0.010  Diastole 11 ± 4 13 ± 6 14 ± 7 0.004  Mean 18 ± 5 20 ± 7 21 ± 9 0.009  Pulse Pr 16 ± 6 17 ± 6 18 ± 7 0.284 Pr gaps of Pre-Ao and pre-MPA  Systole 81 ± 19 83 ± 16 94 ± 20 <0.001  Diastole 52 ± 15 49 ± 13 54 ± 13 0.055  Mean 64 ± 17 63 ± 13 69 ± 12 0.069 Post-Ao Pr  Systole 117 ± 12 113 ± 16 124 ± 18 0.197  Diastole 63 ± 6 66 ± 11 73 ± 12 0.167  Mean 88 ± 6 85 ± 11 91 ± 12 0.270  Pulse Pr 53 ± 15 47 ± 13 51 ± 15 0.656 PDA sizes, mm  AoA 5.8 ± 2.7 8.5 ± 3.6 13.2 ± 5.2 <0.001  PuA 4.4 ± 1.5 5.2 ± 1.6 7.2 ± 2 <0.001  Length 7.8 ± 3.1 9.9 ± 3.7 13.2 ± 5.2 <0.001  PI 1.2 ± 0.3 2.6 ± 0.5 4.6 ± 1.1 <0.001 Size gaps of PDA and NOC, mm  AoA—DD 0.9 ± 2.5 2 ± 3 4 ± 6 <0.001  PuA—PD −0.3 ± 1.5 −0.4 ± 1.7 0.6 ± 1.8 0.130  PI—DD −3 ± 0.9 −4 ± 2 −4 ± 2 0.201  PI—PD −3 ± 0.6 −3 ± 1.0 −1 ± 1 <0.001 Pre-Qp/Qs * 1.4 ± 0.4 1.4 ± 0.4 1.5 ± 0.4 <0.001 Post-Qp/Qs * 1.0 ± 0.1 1.0 ± 0.9 1.0 ± 0.0 0.658 PDA types A/B/C/D/E/U, n 45/6/5/6/34/5 130/16/11/4/24/25 37/4/5/0/4/0 RS, n Total RS/COc  Immediate time 12 (12%) 65 (31%) 13 (26%) 90 (25%)/271 (75%)  1 day 11 (11%) 53 (25%) 10 (20%) 74 (20%)/287 (80%)  1 month 4 (4%) 26 (12%) 5 (10%) 35 (10%)/326 (90%)  6 months 3 (3%) 8 (4%) 4 (8%) 15 (4%)/346 (96%)  1 year 1 (1%) 4 (2%) 3 (6%) 8 (2%)/353 (98%) * The p values between pre-Qp/Qs and post-Qp/Qs were < 0.001 at small-, moderate-, and large-sized PDA groups, respectively. Ao = aorta; MPA = main pulmonary artery; AoA = aortic ampulla of PDA; COc = complete occlusion; NOC = Nit-Occlud® coil; PDA = patent ductus arteriosus; PuA = pulmonary ampulla of PDA; PI = PDA isthmus; DD = distal diameter of NOC; PD = proximal diameter of NOC; Qp/Qs = pulmonary blood flow/systemic blood flow; Pre- = before PDA occlusion using NOC; Post- = after PDA occlusion using NOC; Pr = pressure; RS = residual shunt. jcm-11-02469-t003_Table 3 Table 3 Morphological types and numbers (n) of PDA subjects according to the chronological age groups. Pediatric Ages Adults Total Ages ≤6 Months 7–12 Months 1–6 Years 7–12 Years 13–18 Years Subtotal Subtotal PDA Types n = 26 n = 57 n = 175 n = 57 n = 10 n = 325 n = 36 n = 361 A (conical) 16 (62%) 35 (60%) 115 (65%) 16 (28%) 6 (60%) 188 (58%) 21 (58%) 209 (58%) B (window) 1 (4%) 3 (4%) 12 (7%) 4 (7%) 1 (10%) 21 (6%) 5 (14%) 26 (7%) C (tubular) 1 (4%) 2 (4%) 14 (8%) 1 (2%) 1 (10%) 19 (6%) 2 (6%) 21 (6%) D (complex) 0 (0%) 2 (4%) 5 (3%) 1 (2%) 2 (20%) 10 (3%) 0 (0%) 10 (3%) E (elongated) 6 (23%) 13 (21%) 29 (17%) 8 (14%) 0 56 (17%) 2 (6%) 58 (16%) U (unclassified) 2 (7%) 2 (7%) 0 27 (47%) 0 31 (10%) 6 (16%) 37 (10%) PDA = patent ductus arteriosus. jcm-11-02469-t004_Table 4 Table 4 The pressure differences before and after PDA occlusion using NOC in aorta. Pediatrics p Adults p Before After Wilcoxon Test Before After Wilcoxon Test Systole Ao Pr 111 ± 17 114 ± 15 0.031 129 ± 26 140 ± 17 0.317 Diastole Ao Pr 63 ± 14 67 ± 12 0.130 66 ± 11 73 ± 3 0.421 Mean Ao Pr 83 ± 15 86 ± 11 0.535 89 ± 11 90 ± 10 0.125 Pulse Pr of Ao 48 ± 10 47 ± 13 0.004 67 ± 14 64 ± 25 0.321 Qp/Qs 1.4 ± 1.0 1.0 ± 0.8 <0.001 1.5 ± 0.4 1.0 ± 0.0 <0.001 Ao = aorta; NOC = Nit-Occlud® coil; PDA = patent ductus arteriosus; Pr = pressure (mmHg); Qp/Qs = pulmonary blood flow/systemic blood flow. jcm-11-02469-t005_Table 5 Table 5 Various comorbidities of congenital heart disease (CHD) accompanying PDA occlusion using NOC. The CHDs Accompanying PDA Numbers (n = 361) Simple patent ductus arteriosus 329 Secundum atrial septal defect 11 Ventricular septal defect 8 Double outlet right ventricle with sub-pulmonary ventricular septal defect (Taussig-Bing anomaly) 3 Endocardial cushion defect 3 Pulmonary atresia with intact ventricular septum 2 Total anomalous pulmonary venous return, pulmonary atresia with complete endocardial cushion defect 1 Ebstein anomaly 1 Partial fusion of right coronary cusp and non-coronary cusp without significant aortic stenosis 1 Pulmonary valve stenosis 1 Hypertrophic cardiomyopathy 1 NOC = Nit-Occlud® coil; PDA = patent ductus arteriosus. jcm-11-02469-t006_Table 6 Table 6 Complications with PDA occlusion using NOC at 1 year after the procedure. 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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/ijerph19095728 ijerph-19-05728 Article Effects of Stepwise Temperature Shifts in Anaerobic Digestion for Treating Municipal Wastewater Sludge: A Genomic Study https://orcid.org/0000-0002-9267-9799 Sudiartha Gede Adi Wiguna 12 https://orcid.org/0000-0002-8891-0564 Imai Tsuyoshi 1* https://orcid.org/0000-0002-2472-7357 Hung Yung-Tse 3 Tchounwou Paul B. Academic Editor 1 Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Yamaguchi 755-8611, Japan; adiwiguna.sudiartha@unud.ac.id 2 Environmental Engineering Study Program, Faculty of Engineering, Udayana University, Bali 80361, Indonesia 3 Department of Civil and Environmental Engineering, Cleveland State University, FH 112, 2121 Euclid Ave, Cleveland, OH 44115, USA; y.hung@csuohio.edu * Correspondence: imai@yamaguchi-u.ac.jp 08 5 2022 5 2022 19 9 572823 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/). In wastewater treatment plants (WWTP), anaerobic digester (AD) units are commonly operated under mesophilic and thermophilic conditions. In some cases, during the dry season, maintaining a stable temperature in the digester requires additional power to operate a conditioning system. Without proper conditioning systems, methanogens are vulnerable to temperature shifts. This study investigated the effects of temperature shifts on CH4 gas production and microbial diversity during anaerobic digestion of anaerobic sewage sludge using a metagenomic approach. The research was conducted in lab-scale AD under stepwise upshifted temperature from 42 to 48 °C. The results showed that significant methanogen population reduction during the temperature shift affected the CH4 production. With 70 days of incubation each, CH4 production decreased from 4.55 L·g−1-chemical oxygen demand (COD) at 42 °C with methanogen/total population (M·TP−1) ratio of 0.041 to 1.52 L·g−1 COD (M·TP−1 ratio 0.027) and then to 0.94 L·g−1 COD ( M·TP−1 ratio 0.026) after the temperature was shifted to 45 °C and 48 °C, respectively. Methanosaeta was the most prevalent methanogen during the thermal change. This finding suggests that the Methanosaeta genus was a thermotolerant archaea. Anaerobaculum, Fervidobacterium, and Tepidanaerobacter were bacterial genera and grew well in shifted-up temperatures, implying heat-resistant characteristics. anaerobic digestion biogas production genomic analysis shifted-up temperature sludge treatment and disposal thermotolerant bacteria This research received no external funding. ==== Body pmc1. Introduction Water resources and environmental protection policies worldwide have mandated thorough treatment of wastewater prior to discharge into water bodies [1]. Activated sludge treatment is a common wastewater treatment method [2]. However, the main issue regarding this type of treatment is sludge generated from primary sedimentation (PS) and activated sludge (AS). Sludge produced from wastewater treatment plants (WWTP) is produced in large volumes worldwide with up to 8910, 6510, 2960, 650, 580, 550, and 370 thousand metric tons of dry sludge produced annually by EU countries, the United States, China, Iran, Turkey, Canada, and Brazil, respectively [3]. Considering the substantial volumes of waste production, it is not surprising that WWTP sludge management and disposal have become an area of significant concern globally [4]. As a result of its high water content, low dewaterability, and rigorous regulations for sludge reuse and disposal, sludge management is a demanding and complicated issue in wastewater treatment plants [5]. In some countries, landfill is the most favorable disposal method [6]. However, due to the volume of sludge produced and the availability of the land area, attention has shifted to the development of other potential usable products. Currently, the wastewater treatment paradigm has shifted to an environmentally friendly process to reduce the volume of sludge disposed and convert it into a bioenergy source. The dry bulk of WWTP sludge contains organic components that can be utilized to generate a significant quantity of biomass energy [7]. Anaerobic digestion (AD) is one of the most reliable and promising technologies [8], with several biological wastewater treatment plants applying it as an end-treatment for sewage sludge, primary sludge, and waste-activated sludge [9,10,11]. In Japan, especially in Ube wastewater treatment plants, sludge generated in PS and AS is dewatered and delivered to an anaerobic digester. AD has several benefits compared to other biological processes, such as effortless operation, potentially creating an organic by-product that may be utilized in agriculture and managed to provide an appropriate treatment process [12,13]. During anaerobic digestion, organic compounds are hydrolyzed into soluble fermentable substrates, which are subsequently fermented to acetate, carbon dioxide (CO2), and hydrogen gas (H2) by acetogenic and acidogenic bacteria. These products are then consumed by methanogens to generate methane (CH4) [9]. Silva et al. [14] investigated the CH4 and biohydrogen production from a mixture of food waste, anaerobic sewage sludge, and glycerol. The maximum yield of CH4 and biohydrogen obtained from the mixture was 342.0 mL CH4·g−1 vs. and 179.3 mL H2·g−1 VS, respectively. Without any substrate addition, anaerobic sludge was also capable of generating biogas at 230 ± 29 mL·L−1·d−1 with CH4 production of 153 mL·L−1·d−1 [15]. There are several temperature conditions where anaerobic digestion frequently occurs at psychrophilic (<30 °C), mesophilic (30–40 °C), and thermophilic (50–60 °C) [16]. Recent studies have attempted to investigate the potential of biogas production from anaerobic sludge at various temperatures. Mirmasoumi et al. [17] investigated the biogas production of anaerobic sludge under two different conditions: mesophilic condition (37 °C) and thermophilic condition (55 °C). Under mesophilic conditions, the maximum CH4 produced was 0.246 m3 CH4·m−3 per digester per day. Meanwhile, a greater CH4 productivity was obtained under thermophilic conditions, up to 0.64 m3 CH4/m3 per digester per day. Kasinski [18] also found higher CH4 yields under thermophilic conditions than under mesophilic conditions (0.56 L CH4·g−1 vs. −0.70 L CH4·g−1 VS and 0.25 L CH4·g−1 vs. −0.32 L CH4·g−1 vs., respectively). These findings suggest that biogas production using anaerobic digestion generally favors high temperatures. However, in a large-scale WWTP, maintaining thermophilic conditions in the reactor during anaerobic digestion will require significant energy, which will lead to higher operational expenses, especially in four-seasoned countries. In some cases, fermentation failure can occur owing to transient temperature increases caused by power outages, mechanical faults, or human errors during the fermentation process [19]. This motivates further extensive studies of thermotolerant microorganisms for the anaerobic digestion process. Thermotolerant microorganisms are microbial consortia that are robustly adapted to harsh conditions during industrial applications [20]. Thermotolerant microorganisms are mostly mesophilic, with optimum growth temperatures of 35–45 °C, which are 5–10 °C higher than typical mesophilic strains of the same genus [21,22,23,24]. These strains cannot be classified as thermophilic microorganisms, which are characterized by an optimum growth temperature greater than 50 °C [19]. Few studies have examined the potential of thermotolerant microorganisms during anaerobic digestion. Suksong et al. [25] studied the gas production potential of thermotolerant microorganisms from the anaerobic digestion of oil palm empty fruit bunches. The maximum CH4 yields identified for Clostridiaceae and Lachnospiraceae with prehydrolysis empty fruit bunches were 252 mL CH4·g−1 vs. and 349 mL CH4·g−1 VS, respectively. Su et al. [20] discovered the potential of a thermotolerant methanotrophic consortium for producing methanol from biogas. To date, there have been no reports on the potential of thermotolerant microorganisms to produce biogas from the anaerobic digestion of anaerobic sludge. Notably, investigation of biogas production and genomic analysis from the anaerobic digestion process under shifted-up temperatures has not been performed to date. Therefore, there is an urgent need to expand our understanding of this field. Owing to the heat-resistant characteristics and possible benefits of AD in WWTP-scale applications, further research regarding thermotolerant microorganisms needs to be performed, especially to investigate their potential for biogas production. Therefore, the objectives of this study were to investigate the potential of biogas production (especially CH4) and to identify the most biogas-producing microorganisms among the cultures after being shifted to several temperature levels. 2. Materials and Methods 2.1. Inoculum and Substrates The inoculum (I) originated from anaerobically digested sludge obtained from a municipal sewage treatment plant located in Ube City, Yamaguchi Prefecture, Japan. The inoculum characteristics are listed in Table 1. The inoculum samples were then mixed with the substrate (S) solution before being placed in an incubator and exposed to gradually elevated temperature conditions. The substrate used for biogas production in this research was a glucose-based synthetic wastewater consisting of 1.5 g·L−1 glucose, 2 mg·L−1 NaHCO3, 2 mg·L−1 K2HPO4, 1 g·L−1 yeast extract, 0.7 g·L−1 (NH4)2HPO4, 0.75 g·L−1 KCl, 0.85 g·L−1 NH4Cl, 0.42 g·L−1 FeCl3·6H2O, 0.82 g·L−1 MgCl2·6H2O, 0.25 g·L−1 MgSO4·7H2O, 0.018 g·L−1 CoCl2·6H2O, and 0.15 g·L−1 CaCl2·2H2O. Glucose was chosen as the ideal carbon source for microbial metabolic transformations in the fermentation process, and is also a readily biodegradable substance abundantly found in municipal wastewater [26,27]. To obtain the maximum CH4 potential, the appropriate ratio between the microorganisms and substrate must be determined [28]. The CH4 yield, in theory, is independent of the inoculum to substrate ratio (I·S−1), and the I·S−1 ratio should influence only the kinetics of CH4 production [29]. In contrast, previous studies have demonstrated that the I·S−1 ratio can impact both the CH4 yield and production rate, as significant evidence suggested that the ratio directly influences the microorganism growth pattern [30,31,32]. Referring to the German Standard VDI4630, the I·S−1 ratio should be adjusted to more than two [33]. Other studies have discovered that a higher I·S−1 ratio generates more biogas on a consistent basis during the AD process, while a lower I·S−1 ratio produces less biogas due to the lower pH and accumulation of volatile fatty acids (VFAs) [34,35]. In this study, the I·S−1 ratio maintained at approximately 3.0, which indicates that 1 mL of substrate was added for every 3 mL of inoculum. 2.2. Experimental Procedures Laboratory-scale anaerobic digester containers were later defined as vials. A total volume of 160 mL was prepared. To ensure obligate anaerobic conditions, the vial was filled with pure nitrogen gas to flush the remaining oxygen. Subsequently, the vials were capped with butyl rubber stoppers and aluminum caps. Since the laboratory-scale vials were used as the reactor in this research, there were some potential risks that may emerge, such as lower capacity to contain total biogas production, low sample provision to perform several monitoring parameters, and possibility that the sensitivities and instabilities in the laboratory scale reactors do not represent that in the full-scale digesters [36]. This research was divided into two categories: temperature shifted-up (shift-up) and controlled temperature condition. For the shift-up research, in phase 1, batch experiments were performed by adding 110 mL of sludge as inoculum to a vial mixed with 40 mL of substrate. The mixture was then incubated at 42 °C with shaking at 50 rpm for the first two weeks. This action was intended to enhance the growth of microorganisms and ensure the availability of nutrients during acclimatization. After the first two weeks, phase 2 was initiated. Every time gas production declined sharply, up to 2 mL of substrate with a chemical oxygen demand (COD) of 2000 mg·L−1 was injected into the vial. This treatment altered the reactor system from a batch reactor to a fed-batch reactor system. The incubation was continued for 70 days of incubation period in the fed-batch reactor system. Every 70 days, the temperature was increased by 3 °C for the shift-up research until it reached 45 °C and 48 °C. Meanwhile, the controlled temperature research was carried out at 45 °C and 48 °C from the beginning of incubation without any temperature shifts. This study was intended to compare the biogas production and microbial communities among the shifted condition and stabilized condition. During the fermentation period, the total gas volume and composition were measured daily using gas chromatography. A glass syringe was used to measure the volume of the biogas produced. The gas composition of the samples, such as H2, N2, CH4, and CO2, was determined using gas chromatography (GC-8APT/TCD; Shimadzu Co., Kyoto, Japan) with 60/80 activated charcoal mesh column (1.5 m × 3.0 mm internal diameter) and argon gas as the carrier gas. During operation, the temperatures of the injector, column, and detector were adjusted to 50 °C, 60 °C, and 50 °C, respectively. 2.3. Deoxyribonucleic Acid (DNA) Extraction and Sequencing DNA was extracted according to the NucleoSpin® soil manual. Sludge samples were prepared using an MN Bead Tube Type A (MACHEREY-NAGEL GmbH & Co., Düren, Germany). KG was mixed with lysis buffer SL1 and lysed using Enhancer SX. Contaminants were precipitated using lysis buffer SL3, and the lysate was filtered using a NucleoSpin® Inhibitor Removal Column. Subsequently, the binding conditions were adjusted using Binding Buffer SB. DNA was bound by loading 550 µL sample on the NucleoSpin® Soil Column. After the binding phase, the silica membrane was washed with binding buffer SB, wash buffer SW1, and SW2. Finally, the DNA was eluted using SE elution buffer. DNA samples were then delivered to the Faculty of Medicine, Yamaguchi University, Japan, for next-generation sequencing. Next generation sequencing (NGS) was performed to acquire a broad range of genes or gene regions from phylum to genus using the 16 s ribosomal ribonucleic acid (RNA) gene amplicons for the Illumina MiSeq System, wherein DNA or RNA are sequenced using hybrid capture or amplicon-based approaches (previously transcribed into complementary DNA). Using these approaches, the genome (all 3 billion base pairs), all coding genes (exome; 1% of the genome or 30 million base pairs—that is 20,000 genes made of 180,000 exons), all RNA produced from genes (transcriptome), and any subset of these can be sequenced [37]. 2.4. Microbial Diversity Analysis Diversity index analysis was conducted to determine possible changes in the microbial communities during the anaerobic digestion process. A diversity index is a numerical measure of how many distinct types (such as species) are present in a dataset (a community), as well as the evolutionary relationships among individuals dispersed throughout those types, such as richness, divergence, and evenness [38]. In this study, Simpson’s diversity index, Shannon’s diversity index, and Shannon’s equitability index were utilized. 3. Results 3.1. Biogas Production under Shifted-Up Temperature The fluctuation in daily CH4 production and cumulative CH4 production during the first incubation at 42 °C is shown in Figure 1. During the batch anaerobic digestion period, biogas production increased gradually with the cumulative volume of biogas generated being up to 316.5 mL on day 14, with cumulative CH4 production being up to 120.76 mL CH4. The CH4 content in the biogas increased rapidly in the first 8 days, reaching 69% on the 8th day, and 64.7% on average until day 13. Cumulative CH4 production increased gradually in the first 3 days, and then showed a substantial increase on day 7 (66.59 mL CH4). On the final day of the batch period, the cumulative methane production reached 120.76 mL CH4 which was equal to 1.43 L·g−1 COD feed. Theoretically, the energy recovery (expressed as CH4 production) from digested wastewater sludge through anaerobic process was 0.38 L·g−1 COD [39]. From this study, it took approximately four days of anaerobic digestion to exceed the theoretical CH4 production with the aforementioned inoculum and substrates, with an I·S−1 ratio of 2.75. However, on the 14th day, methane production sharply decreased to 0 mL. Declining CH4 production indicates a dead phase of methanogenic activity [40]. This drawdown in CH4 production may also be linked to a decrease in pH caused by the interaction of VFAs with other fragmented precursors during oxidative processes [41]. To maintain CH4 production, 2 mL of the substrate was injected into the vial when CH4 production started diminishing due to the scarcity of nutrients. As illustrated in Figure 1a, substrate injection led to a spike in CH4 production as the activity of methanogenic microorganisms increased due to the availability of glucose as a carbon source and other nutrients that expedited microbial growth. Consequently, as shown in Figure 1a*, the cumulative volume of methane produced increased significantly after substrate addition. At the end of the incubation period at 42 °C, the cumulative CH4 production was observed to increase to 454.5 mL CH4, with a yield of 4.55 L·g−1 COD feed. After incubation for 70 days at 42 °C, the incubation temperature was shifted to 45 °C with the same treatment conditions and hydraulic retention times. Even though the same sample was utilized, the cumulative CH4 calculation was restarted from 0 mL CH4. As presented in Figure 1b, the daily CH4 production peaked at 17.2 mL CH4 which was obtained on day 60 after receiving the 4th feed. From the Figure 1b*, the cumulative CH4 produced and yield after 70 days of incubation was 152.2 mL CH4 and 1.52 L·g−1 COD feed, respectively. This was less than the volume of CH4 produced during incubation at 42 °C by a factor of three. There was also a significant difference in CH4 production behavior after the temperature was increased to 45 °C, e.g., a shorter period required to shift from peak days to trough days, which denotes faster methanogenesis and death phase for methanogenic bacteria. This shorter methanogenesis phase can be attributed to the higher concentration of CO2 produced during the incubation period. As shown in Figure 1c, CH4 production decreased further when the temperature was increased to 48 °C. After 70 days of incubation, only 86.57 mL of CH4 was produced, with a CH4 yield of 0.94 L·g−1 COD feed. The CH4 production trend after the 3rd feed at shifted-up 45 °C is a good illustration of the potential inhibition of methanogenic bacterial activity by the presence of high CO2 levels (Figure 2). The high CO2 levels indicated the occurrence of acetoclastic methanogenesis in the AD process, which later led to the abundant presence of VFAs, particularly acetic acid [42]. The decrease in CH4 was also parallel to the decrease in overall biogas production consisting of H2, N2, CH4 and CO2, which is illustrated in Figure 3a. The total biogas production decreased from 1161.93 mL (11.61 L·g−1 COD feed) at 42 °C to 672 mL (6.7 L·g−1 COD feed) and then to 505 mL (5.49 L·g−1 COD feed) after the temperature was shifted to 45 °C and 48 °C, respectively. The decreasing CH4 production volume after being shifted-up to the higher temperature at 45 °C and 48 °C was followed by the decline in CH4 content in biogas compositions as seen in Figure 3b–d. At the end of incubation period, the concentration of COD, total suspended solids (TSS), volatile suspended solids (VSS), and pH were measured for each temperature condition. As seen in Table 2, the concentration of COD was increasing up to 3-fold, in contrast to TSS and VSS that significantly decreased every temperature shift. This finding indicates that the number of microbial communities (represented by VSS) declined every upshifted thermal condition and subsequently causing a depletion on microbial activity, which eventually resulted in the lower organic matter consumed by microorganisms in the reactor. The pH is another parameter that affects digestion process. The pH increased substantially from 7.64 at 42 °C to 8.20 and 8.33 when the temperature was shifted-up to 45 °C and 48 °C, respectively. Subsequently, the biogas production decreased along with the rising pH. This finding supports a research study from Kouzi et al. [43] who discovered that the optimum pH range for sewage sludge AD was 7.0, while the biogas production was considerably lower in the reactors with higher pH of 8.0, 9.0, and 10.0. 3.2. Alpha Diversity Analysis To study the changes in microbial diversity at the upshift temperature, samples from the reactor were used for DNA isolation for bioinformatic analysis using NGS. For comparison, several samples from other fed-batch reactors with controlled temperatures of 42 °C, 45 °C, and 48 °C were examined for their microbial diversity. This action was intended to elucidate the differences among microbial communities and compositions that matured under controlled and shifted-up temperatures. The Shannon diversity index (SDI) and Simpson index were used to measure and compare the richness of the microbiota at a certain temperature, while the Shannon equitability index (SEI) was assigned to approximate the evenness of the microbiota diversity. As illustrated by Figure 4a,b, the index value for both richness and evenness of the microbiota communities spread within the range 3.2–3.7 and 0.46–0.54, respectively. The Simpson index, as seen in Figure 4c, ranged from 0.89 to 0.96, indicating high diversity for all sample conditions. The deviation of the diversity index between the shifted-up temperature conditions and controlled temperature conditions was not significantly discerned, which signifies that each reactor has a close similarity of microbiota abundance and species to each other. However, compared to the controlled temperature conditions, the shifted-up temperature conditions showed a significant drop in microbiota diversity, with an increase in temperature. The diversity index value declined from 3.72 at 42 °C to 3.22 at 48 °C. This indicated that several bacteria communities were vanished during the temperature shift. This was also confirmed by the decrease in the equitability index value; however, since the equitability values were greater than 0.1, some microorganism colonies managed to acclimatize to this chaotic condition and experienced massive growth while the other colonies became extinct. The effects of temperature on diversity were confirmed using analysis of variance (ANOVA), with significance of p < 0.05. The probability value (p-value) for all diversity indices (SDI, SEI, and Simpson index) was p < 0.001, which signified that there were statistically significant differences in relative abundances and diversity indices between several temperature conditions. 3.3. Microbial Community Structure Overall, the number of methanogens decreased sharply when the temperature was shifted from 42 °C to 45 °C, as shown in Figure 5. Methanosaeta was the most dominant methanogenic archaea that existed during incubation at 42 °C, shifted up to 45 °C, subsequently shifted up to 48 °C, and also abundant during incubation atcontrolled temperatures of 45 °C and 48 °C. This result implied that Methanosaeta is a thermotolerant methanogen. The relative abundances of methanogens at the order level at various temperatures are shown in Figure 6a. The composition of methanogens in both shifted-up temperature and controlled temperature conditions was dominated by the orders Methanobacteriales, Methanomicrobiales, and Methanosarcinales. Among the three methanogens, Methanosarcinales was the most abundant (86.89% at 42 °C, 88.84% at shifted-up 45 °C, 59.14% at shifted-up 48 °C, 85.56% at controlled 45 °C, and 78.54% at controlled 48 °C). At the family level, as illustrated in Figure 6b, the methanogen communities were composed of Methanosaetaceae, Methanomicrobiaceae, Methanoregulaceae, Methanobacteriaceae, Methanosarcinaceae, and Methanospirillaceae. The Methanosaetaceae family was abundant, with relative abundances of 85.01% at 42 °C, 88.05% at shifted-up 45 °C, 56.52% at shifted-up 48 °C, 84.76% at controlled 45 °C, and 51.14% at controlled 48 °C. In this study, Methanosaeta was the only descendant of the Methanosaetaceae family. At the genus level, Methanoculleus, Methanolinea, Methanobacterium, Methanobrevibacter, Methanosarcina, Methanothermobacter, Methanofollis, Methanosalsum, Methanogenium, and Methanolobus were detected at all temperatures (Figure 6c). However, during the incubation at a controlled temperature of 48 °C, the dominance of Methanosaeta was lower than under shifted-up temperature (84% of the total methanogens at shifted-up 48 °C and 51% at controlled 48 °C) while Methanosarcina genes were detected up to 27% of the total methanogens. These findings confirmed the results of Figeac et al. [44] who discovered that the family Methanosarcinaceae was the most abundant acetotrophic archaea in the initial thermophilic inoculum, whereas the Methanosaetaceae family was mostly found in the initial mesophilic inoculum. Therefore, the population of Methanosaeta with an initial temperature of 48 °C was considerably lower than that in the upshift condition that was initially acclimatized under mesophilic conditions (at 42 °C). Apart from acetotrophic methanogens, hydrogenotrophic methanogens, such as members of genera Methanobacterium, Methanobrevibacter, and Methanothermobacter, started to grow significantly after the reactor temperature was shifted up to 48 °C. Hydrogenotrophic methanogens favor thermophilic conditions, whereas acetotrophic methanogens cannot resist high temperatures [45]. Methanobacterium communities grew from 2.5% to 7.4% of the total methanogen population, and Methanobrevibacter population ranged from 0.76% to 1.64% at a shifted-up temperature of 42–48 °C. This finding contradicts previous research reporting that Methanobacterium genera were mostly found at lower mesophilic temperature (24–35% at 35 °C and 32–45% at 37 °C) and eradicated with increasing the temperature to 55 °C [44,46]. Methanobrevibacter genera were also found to be the dominant methanogens at 24 °C and 35 °C and vanished at 55 °C [44]. However, the researchers did not examine the existence of Methanobrevibacter genera at higher mesophilic temperatures (42–48 °C). Judging from the results of previous studies that showed Methanobacterium and Methanobrevibacter were abundant in the lower mesophilic conditions, our research reported a significant spike in the population of those methanogens after shifting up temperatures to higher mesophilic conditions, signifying that Methanobacterium and Methanobrevibacter genera potentially have heat-resistant characteristics that allow them to compromise the staggering increase in temperature conditions. Lastly, Methanothermobacter population increased from 0.17% to 0.24% relative abundance at 42–48 °C. This is not surprising as Methanothermobacter genera is a thermophilic methanogen that dominated methanogenesis at temperatures of 50 °C and higher [47,48,49,50]. The distribution of non-methanogenic bacteria is also an important factor for determining the influence of several bacteria on CH4 production. As seen in Figure 7a, Clostridia and Synergistia were the most abundant bacteria at the order level, with respective relative abundances of 31.11% and 18.50% at 42 °C, 42.98% and 20.88% at shifted-up 45 °C, 24.38% and 34.83% at shifted-up 48 °C, 23.43% and 30.49% at 45 °C, and 27.88% and 28.17% at 48 °C. Clostridia was found to be dominant at both mesophilic (this research) and thermophilic temperatures (at 52 °C) [51], indicating that the Clostridia order belongs to thermotolerant bacteria. According to the experimental results, Synergistia were found at higher mesophilic temperatures, but in some cases, were also found abundantly at low temperatures of 20 °C [52]. This suggested that Synergistia was resistant to both low-and high-temperature environments, leading to the conclusion that temperature had a responsive connection with the microbial community structure. At the family level, Anaerobaculaceae, Clostridiaceae, and Thermoanaerobacterceae dominated the microbial communities, as shown in Figure 7b. At the genus level (see Figure 7c), Anaerobaculum, Fervidobacterium, Tepidanaerobacter, Clostridium, Moorella, Aminiphilus, Carboxydocella, and Methanosaeta are some microorganism genera that exhibited noteworthy growth during the temperature shift. Anaerobaculum and Tepidanaerobacter from the Thermoanaerobacterales family are syntrophic bacteria that have an essential role in converting short-chain fatty acids to methanogenic components such as acetate, H2, and formate [53]. Moorella has been identified as an acidogenic bacterium [54], whereas Clostridium is a hydrogen-producing bacterium that plays a key role in the hydrolysis process [46]. Compared to the other types of microorganisms, methanogenic archaea were shown to have the least portion of the population among the microbial communities. The decrease in the methanogen population accelerated faster in shifted-up temperature conditions than in controlled temperature conditions. However, the number of methanogen populations is unlikely to affect CH4 production. The cumulative CH4 production decreased along with the decline in the methanogen:total population (M·TP−1) ratio during the shifted-up temperature period. This result contradicts the outcome of the controlled temperature, in which the cumulative CH4 production increased conspicuously despite the fluctuation in the M·TP−1 ratio (Figure 8a). To date, no particular ratio has been found to be effective in understanding the influence of the microbial ratio (the existence of a particular microorganism) on biogas production. The closest ratio was that of sulphate-reducing bacteria (SRB) to methanogens (SRB·M−1). Previous research has stated that the existence of SRBs in the AD process may inhibit CH4 production as it would compete with methanogens for convenient H2, acetate, propionate, and butyrate [55]. From the shifted-up temperature experiment, the SRB·M−1 ratio showed harmony with the statement of previous research. The higher the SRB·M−1 ratio, the lower the CH4 production as the SRB emulated the methanogens in consuming available H2 (Figure 8b). Nevertheless, the results from the controlled temperature experiments showed that the SRB·M−1 ratio was also ineffective in determining the relationship between the ratio and CH4 production. At controlled 48 °C, the maximum CH4 volume production was observed despite the low M·TP−1 ratio and high SRB·M−1 ratio. Under these conditions, the populations of Methanosarcina and Methanoculleus genera were the most abundant. Methanosarcina genera are known to be the major contributors to CH4 production [56] and manage to perform all methanogenesis pathways (hydrogenotrophic, acetoclastic, and methylotrophic) that help them survive in food competition [57]. In contrast to other methanogens, Methanosarcina was capable of growing significantly under high concentrations of VFAs and ammonia, which are the foremost inhibitors in biogas production [58]. Methanoculleus, in contrast, has been reported to increase in abundance along with elevated sulfate concentration [59]. Thus, both Methanosarcina and Methanoculleus acclimatized well and were attributed to high CH4 production under high inhibitor concentrations. These findings may explain the phenomenon of increasing CH4 production at a controlled temperature of 48 °C. The influence of Methanosarcina and Methanoculleus on CH4 production was demonstrated by considering the decreasing volume of CH4 production parallel to the decrease in Methanosarcina and Methanoculleus abundance during shifts in temperature. Methanosarcina abundances decreased from 2% to 0.75% and 0.59%, parallel to the Methanoculleus population that declined from 6.52% to 4.96% and 3.81% during the incubation at temperature of 42 °C, shifted up to 45 °C, and shifted up to 48 °C, respectively. 4. Discussion In AD processes, temperature has a significant influence on biogas production and microbial ecology [60,61]. There has been a number of research that examined the effects of temperature in mesophilic and thermophilic conditions [18,62,63]. However, to the best of our knowledge, the assessment of biogas production (especially CH4) and microbial community adaptation under multiple rising temperature conditions in a fed-batch reactor has not been widely studied. We expected instability in microbial communities (especially methanogens) and decreased CH4 production, along with the temperature shift process owing to perturbations caused by sudden temperature changes. Among the three temperature conditions, there was a noticeable decrease in CH4 production when the temperature was increased. The cumulative CH4 production decreased from 454 mL at 42 °C to 152 mL after increasing the temperature to 45 °C and to 86.57 mL after increasing the temperature to 48 °C. This result is consistent with previous findings for the shifted-up temperature [51,64]. Each temperature shift was conducted after 70-day incubation periods in order to allow a period of acclimatization for methanogens and other bacteria. The total methanogen abundance in shifted-up 45 °C and 48 °C were close to that in controlled 45 °C and 48 °C after 70 days operation. Previous studies showed potential steadier operation condition in term of CH4 production after acclimatization for 100–140 days, yet the risks of instability still exists [51,65]. Beale et al. [64] investigated the effect of upshift temperature shock from 37 °C to 42 °C on the biogas production volume of anaerobically digested sludge. Similarly, the biogas generated after the temperature was increased to 42 °C was persistently lower than that from the controlled digester at 37 °C during the first 32 days of operation. Identical results were also reported by Ziembinska-Buczynska et al. [66] who found a significant decrease in the biogas production rate from 70.5 L·day−1 to 28.6 L·day−1 along with an increase in temperature from 38 °C to 55 °C. Researchers also discovered that there was a decrease in microbiota diversity as the temperature of the digester influenced the evolution from mesophilic to thermophilic conditions. Some methanogens cannot survive at higher temperatures (heat unresistant), e.g., Methanobrevibacter (37–39 °C), Methanogenium (20–25 °C), or Methanobacterium (37–45 °C) [67]. However, our research contradicts the findings of Bouskova et al. [68] who discovered higher CH4 production after the temperature was shifted from 42 °C to 47 °C, 51 °C, and 55 °C. A possible reason for the observed discrepancies was the characteristics and ratio of the inoculum and substrates. The researchers used an inoculum with TS of 31.24 g·L−1 and vs. of 14.48 g·L−1. Meanwhile in our study, the inoculum consisted of 8 g·L−1 TS and 3 g·L−1 VS. Previous researchers also utilized a mixture of primary sludge and waste activated sludge as substrates which also contained seeds of microorganisms that maintained the longevity of biogas production. We also found that the presence of excessive CO2 in the reactor may have led to lower methane production. Methanogenic bacteria require CO2 and H2 to produce CH4, which indicates that if the CO2 volume was greater than CH4 after substrate feeding, this signifies the failure of these bacteria to consume sufficient quantities of CO2 and H2, which consequently would lead to the accumulation of VFAs, lower CH4 yield, and low pH [69,70]. Low pH is a serious concern as it inhibits methanogenic bacteria due to the increase in the concentration of free acid molecules, which is harmful for microorganisms and impacts enzymatic activity [71]. It has been suggested that microbiota composition and methanogenic pathways are altered when encountering an immediate low pH and high acetate crisis (pH 5.5–6.5, completely hindered at pH 5.0) [72]. Temperature shifts also affected the microbial communities in the reactor, especially the methanogens. The number of methanogens decreased significantly after the temperature was shifted from 42 °C to 45 °C and then stabilized at 48 °C, as shown in Figure 4. This instability supported the study by Westerholm et al. [51] who found that immense perturbation occurred in the interval of 40–44 °C, signifying that the 40–44 °C temperature range had a significant impact on both mesophilic and thermophilic microbial populations. The only conceivable interpretation for this phenomenon is that the temperature range may be greater than the upper threshold for the growth of mesophiles but not sufficiently high for the growth of thermophiles [73]. Because our reactor was initially developed using mesophilic anaerobic sludge, this potentially limits the abundance of thermophilic microorganisms. Tian et al. [74] omitted the 40–44 °C area and still found a transitory decrease in total methanogen concentration after the temperature was shifted (37–55 °C), but then recovered quickly on day 11. Among all the methanogens, Methanosaeta (Methanosaetaceae family) was the most abundant under all temperature conditions in this study. This finding contradicts the findings of Kim et al. [75] who reported that the Methanosaetaceae family started to dominate the microbial structure only at temperatures above 45 °C. A plausible explanation for this difference is that the researchers started cultivation at 35 °C, which was more favorable to the growth of Methanomicrobiales order than Methanosarcinales (the ancestor of Methanosaetaceae). The instability of methanogen populations in anaerobic digestion also led to an increase in some types of bacteria that contributed to H2 and VFAs consumption, such as SRBs. As illustrated in Figure 7b, our research shows that the increasing SRB/methanogen ratio has a considerable influence on the decrease in CH4 production under the shifted-up temperature conditions. This result supports the idea from previous studies that reported that sulfide generation by SRBs inhibits methanogenesis, with the latter being the leading rival of methanogens for electron donors and substrates [65,76]. In addition, Beale et al. [64] emphasized that even a small amount of SRBs was enough to inhibit biogas production, as methanogens were vulnerable to the toxicity caused by metabolic products of SRBs. Although this study characterized the behavior of some microorganisms and their influence on CH4 production during the shifted-up temperature, there are still several unidentified factors that can potentially affect the outcome of the AD process. Further studies are needed to determine and characterize the mechanism by which shifted temperature may affect the abundance of microorganisms, especially methanogenesis-related microbiota (e.g., methanogens, SRB, methanotrophs, hydrogenotrophs, acetotrophs, nitrogen-fixing bacteria, and sulfate-oxidizing bacteria) and the influence on CH4 production. Other microbial communities with syntrophic and fermentative behaviors, as well as their metabolic networks, merit study. Minimizing the number of unknown microorganisms may also provide a clearer insight into the relationship between the abundance of microorganisms and CH4 production, as in this study, we detected a large number of unknown bacteria. 5. Conclusions Treating wastewater sludge using anaerobic digestion does not eliminate the risk of temperature instability. Consequently, the effects of shifting the temperature during anaerobic digestion of anaerobic sludge were investigated in this study. The results showed a considerable reduction in the CH4 cumulative gas production, from 454 mL (4.55 L·g−1 COD) to 152 mL (1.52 L·g−1 COD) then to 86.57 mL (0.94 L·g−1 COD) when the temperature of the reactor was increased from 42 °C to 45 °C and subsequently to 48 °C, respectively. Several factors have been attributed to the decrease in CH4 production under the shifted-up temperature, such as the decreasing methanogen population (expressed as the M·TP−1 ratio) due to intense food competition, increasing SRB populations over methanogens, and low abundance of major CH4 producers (e.g., Methanosarcina and Methanoculleus). Methanosaeta was the most dominant methanogen in this study, while Anaerobaculum and Tepidanaerobacter were the most abundant syntrophic bacteria, and Clostridium which are known as hydrogen-producing bacteria. Overall, the diversity of the anaerobic microbial consortium observed in this study altered slightly during the shift in the thermal conditions. This indicated that the majority of the communities belonged to thermotolerant microorganisms. Acknowledgments The first author would like to thank the Japanese Ministry of Education, Culture, Sports, Science and Technology (Monbukagakusho) for the full support through the Doctoral Degree Scholarship Program. Author Contributions G.A.W.S.: Conceptualization, methodology, formal analysis, investigation, data curation, writing—original draft, and visualization. T.I.: conceptualization, methodology, resources, writing—review and editing, supervision, project administration, and funding acquisition. Y.-T.H.: conceptualization, methodology, writing—review and editing. 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 that they have no conflict of interest, no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Figure 1 Daily (without *) and cumulative (with *) methane production of anaerobic sludge at (a,a*) 42 °C, (b,b*) shifted-up to 45 °C, and (c,c*) shifted-up to 48 °C. Figure 2 The production of CO2 after the 3rd feed compared to CH4 production in 12 consecutive days. Figure 3 Total biogas production (H2, N2, CH4, and CO2) of anaerobic sludge during the shifted-up temperature conditions (a) and biogas composition at 42 °C (b), shifted-up to 45 °C (c), and shifted-up to 48 °C (d). Figure 4 The richness and evenness index of the total microorganisms’ communities on each reactor: (a) Shannon-Wiener Diversity Index; (b) Shannon Equitability Index; and (c) Simpson Diversity Index. Note: (*) signs the shifted-up temperature. Figure 5 Methanogens total number of genes hit by NGS during anaerobic digestion process in several temperature conditions. Note: (*) signs the shifted-up temperature. Figure 6 Methanogens distribution in shifted-up temperature (*) and controlled temperature: (a) order level; (b) family level; and (c) genus level. Figure 7 Bacteria (non-methanogens) community distribution in shifted-up temperature (*) and controlled temperature: (a) order level; (b) family level; and (c) genus level. Figure 8 Comparison between cumulative CH4 production and M·TP−1 ratio (a) and sulphate-reducing bacteria (SRB) to methanogen ratio (b). Note: (*) signs the shifted-up temperature. ijerph-19-05728-t001_Table 1 Table 1 Characteristics of anaerobic sludge as inoculum. Parameters Anaerobic Sludge Units pH 7.09 pH = −log10[a(H+)] Total Solid (TS) 8000 mg/L Volatile Solid (VS) 3000 mg/L Fixed Solid (FS) 5000 mg/L VS/TS ratio 0.37 - ijerph-19-05728-t002_Table 2 Table 2 Effluent quality in each temperature condition after incubation period. Temperature (°C) pH Total Suspended Solids (TSS) in mg·L−1 Volatile Suspended Solids (VSS) in mg·L−1 VSS.TSS−1 Chemical Oxygen Demand (COD) in mg·L−1 42 °C 7.64 7300 4675 0.64 498.72 45 °C 8.20 6860 4105 0.60 1911.76 48 °C 8.33 6880 3465 0.50 3690.52 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Nika C.E. Gusmaroli L. Ghafourian M. Atanasova N. Buttiglieri G. Katsou E. Nature-Based Solutions as Enablers of Circularity in Water Systems: A Review on Assessment Methodologies, Tools and Indicators Water Res. 2020 183 115988 10.1016/j.watres.2020.115988 32683049 2. Cayetano R.D.A. Kim G.B. Park J.H. Lee M.J. Kim S.H. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095086 ijms-23-05086 Article A General Use QSAR-ARX Model to Predict the Corrosion Inhibition Efficiency of Drugs in Terms of Quantum Mechanical Descriptors and Experimental Comparison for Lidocaine Beltran-Perez Carlos 1 Serrano Andrés A. A. 1 Solís-Rosas Gilberto 1 Martínez-Jiménez Anatolio 2 https://orcid.org/0000-0002-1983-2806 Orozco-Cruz Ricardo 3 Espinoza-Vázquez Araceli 3* https://orcid.org/0000-0002-7992-3718 Miralrio Alan 1* Kim Dongho Academic Editor 1 Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico; carlos.beltran@tec.mx (C.B.-P.); andres.serrano@tec.mx (A.A.A.S.); gilsolisr@gmail.com (G.S.-R.) 2 Departamento de Ciencias Básicas, División de CBI (Ciencias Básicas e Ingeniería), Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Área de Física Atómica Molecular Aplicada, San Pablo 180, Ciudad de México 02200, Mexico; amartinez@azc.uam.mx 3 Unidad Anticorrosión, Instituto de Ingeniería, Universidad Veracruzana, Boca del Río 94292, Mexico; rorozco@uv.mx * Correspondence: araespinoza@uv.mx (A.E.-V.); miralrio@tec.mx (A.M.) 03 5 2022 5 2022 23 9 508619 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 study of 250 commercial drugs to act as corrosion inhibitors on steel has been developed by applying the quantitative structure-activity relationship (QSAR) paradigm. Hard-soft acid-base (HSAB) descriptors were used to establish a mathematical model to predict the corrosion inhibition efficiency (IE%) of several commercial drugs on steel surfaces. These descriptors were calculated through third-order density-functional tight binding (DFTB) methods. The mathematical modeling was carried out through autoregressive with exogenous inputs (ARX) framework and tested by fivefold cross-validation. Another set of drugs was used as an external validation, obtaining SD, RMSE, and MSE, obtaining 6.76%, 3.89%, 7.03%, and 49.47%, respectively. With a predicted value of IE% = 87.51%, lidocaine was selected to perform a final comparison with experimental results. By the first time, this drug obtained a maximum IE%, determined experimentally by electrochemical impedance spectroscopy measurements at 100 ppm concentration, of about 92.5%, which stands within limits of 1 SD from the predicted ARX model value. From the qualitative perspective, several potential trends have emerged from the estimated values. Among them, macrolides, alkaloids from Rauwolfia species, cephalosporin, and rifamycin antibiotics are expected to exhibit high IE% on steel surfaces. Additionally, IE% increases as the energy of HOMO decreases. The highest efficiency is obtained in case of the molecules with the highest ω and ΔN values. The most efficient drugs are found with pKa ranging from 1.70 to 9.46. The drugs recurrently exhibit aromatic rings, carbonyl, and hydroxyl groups with the highest IE% values. corrosion inhibition lidocaine QSAR tight binding ARX model FROLS algorithm lidocaine Tecnologico de MonterreyThe APC was funded by Tecnologico de Monterrey through the grants for scientific papers publication fund. ==== Body pmc1. Introduction 1.1. Corrosion Inhibition and QSAR Fundamentals Amongst the metals, steel is the most used iron alloy for industrial applications [1], such as oil, food, energy, chemical, and construction industries. Being highly ductile, durable, and resistant, steel is highly appreciated for its mechanical properties. Furthermore, the several different alloys obtained at a considerable low-cost increase the variety of properties exhibited. Unfortunately, corrosion is probably the most common phenomenon that leads to weakening metals; this originates from the electrochemical interaction of metallic surfaces with a corrosive environment. Furthermore, the sulfates, oxides, and other compounds produced from these interactions modify the inherent properties of the metal surface, leading to undesired behaviors [2]. From the above, the most common corrosion inhibition strategies are dedicated to steel [3,4,5], although copper and aluminum alloys are studied to a lesser extent [6,7,8,9,10,11,12]. According to the National Association of Corrosion Engineers (NACE), through its “International Measures of Prevention, Application and Economics of Corrosion Technology” study, the Global cost of the damages produced by corrosion in 2013 was US$2.5 trillion. This massive amount of resources represented 3.4% of the Global Gross Domestic Product (GDP) in 2013 [13]. Thus, providing novel solutions to reduce the undesired effects of corrosion on metals is a global priority. The most recurrent strategy to reduce the corrosion on metals is to employ corrosion inhibitors on their surface [3,14,15,16]. A corrosion inhibitor is a substance that, added in small amounts to the metal surface, reduces the action of the corrosive media on the metal by forming a protective film. These organic species could bond strongly to the metal surface through intermolecular interactions, from the inhibitor molecule to neighboring metal atoms [2]. Electrostatic interactions, London dispersion forces, and even covalent bonding could be exhibited. Mostly, these organic compounds contain nitrogen, oxygen, and sulfur. Moreover, organic molecules rich in π-electrons, associated with either triple, double, or conjugated bonds and aromatic rings, are recurrently found to act as corrosion inhibitors [2,3,4,5,17]. Several organic compounds acting as corrosion inhibitors have been evaluated in recent years—for instance, plant extracts [14,17,18,19,20,21,22,23] and commercial drugs [3,4,5,6,7,8,10,24,25,26,27,28,29,30]. However, the massive amounts of phytochemicals and drugs that can be tested as corrosion inhibitors need intelligent strategies for their study [31,32,33]. In pharmacology, the evaluation and prediction of biological activities and properties for massive amounts of potential drugs have been assessed for a long time by the quantitative structure-activity/property relationship (QSAR/QSPR) paradigm [34,35,36,37]. QSAR/QSPR proposes predicting a given activity/property of quantifiable descriptors. These values can be extracted from existing databases, experiments, theoretical calculations, or simulations. Consequently, data curation, descriptors selection, and mathematical modeling join the problem proposed by the QSAR/QSPR approach [38]. Besides, the QSAR/QSPR modeling in the corrosion field is scarce. The ground-breaking work of Zhang et al. proposes QSAR linear models correlating parameters, obtained mainly by quantum-chemical calculations, such as polarizability, dipole moment, frontier orbital energies, and others, to predict the corrosion inhibition efficiency (IE%) of 18 inhibitors on steel, obtaining average deviations of about 9.82%. Another relevant and quite elegant QSAR linear model is the one reported by Keshavarz and coworkers [39], given the number of nitrogen atoms, amino groups, and other structural parameters. This QSAR model accounts for root mean squared deviation (RMSD), mean absolute error, and maximum errors of about 6.15%, 4.93%, and 12.0%, respectively. Moreover, recent reports on QSAR/QSPR studies applied to predict IE% of organic corrosion inhibitors on metal surfaces borrow tools from data science. For instance, Liu and coworkers used support vector machine (SVM) models with 11 top descriptors to characterize 20 benzimidazole derivatives [40]. The root mean square error (RMSE) reported is about 4.45%. On the other hand, Ser et al. reported that the corrosion inhibition efficiency of pyridines and quinolines on iron surfaces had been evaluated utilizing machine learning-based QSPR relationships [41]. The authors obtained the mathematical model by genetic algorithm-artificial neural network methods, leading to linear and nonlinear models, with RMSE of about 16.5% and 8.8%, respectively. In this case, the models considered up to nine variables, mainly obtained from DFT calculations. 1.2. QSAR Paradigm and HSAB Descriptors This work proposes modeling the quantitative structure-activity relationship (QSAR) paradigm using several empirical and theoretical descriptors to predict organic molecule corrosion inhibition efficiency. Since these descriptors are almost any quantitative values that can be measured by experiments or determined by theoretical calculations, this work proposes a set of empirical and theoretical descriptors. The QSAR descriptors determine a drug’s biological activity, looking for specific behaviors. For instance, as proposed by Hansch and Muir, the log P octanol-water partition coefficient was correlated with the biological activity 1/C [35]. The log P descriptor is massively used to study potential drugs since it determines a substance’s concentrations between a hydrophobic phase and a hydrophilic phase. Other QSAR descriptors commonly used in drug design are the solubility coefficient log S, pKa, molecular weight, polar surface area, polarizability, and H-bond acceptor and donor counts [35]. Some common QSAR descriptors are defined within Pearson’s HSAB [42] theory. These descriptors are based on the vertical ionization energy (I) and the vertical electron affinity (A). By Koopmans’ theorem, both can be calculated by I = −EHOMO and A = −ELUMO, where EHOMO and ELUMO are the energies of the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), respectively. According to the HSAB principle, two species will interact easily if either hard or soft [42]. A molecule’s global hardness (η) can be calculated by η = (I − A)/2. Other helpful properties are the absolute electronegativity χ = (I + A)/2 and the global electrophilicity ω = μ2/2η [43]. The first one determines the “ability” of a given molecule to attract electrons from the environment, whereas the second is related to the energetic stabilization a species gains by obtaining an additional electron. Lastly, the fraction of electrons transferred (ΔN) is a valuable property to elucidate the behavior of the organic molecule interacting with the metal surface. This value can be calculated by ΔN = (χMetal − χInhibitor)/[2(ηMetal + ηInhibitor)], where the electronegativities and harnesses of the metal species and the corrosion inhibitor molecule are used. Lukovits and coworkers reported that the higher ΔN value, the higher the corrosion inhibition efficiency [44]. Additionally, isosurfaces of frontier molecular orbitals and electrostatic potential arise to describe the active sites and the electrostatic interactions [45]. This work elucidated the contribution to the corrosion inhibition properties in terms of these HSAB descriptors. In addition, the most common QSAR descriptors listed in the previous subsection were studied for completeness. Since DFT calculations require massive computational resources, third-order density-functional tight binding (DFTB) method with Lennard-Jones (LJ) dispersion-correction was used to obtain the quantum chemical descriptors. Thus, the method, hereafter labeled as DFTB3-LJ, was used as implemented in the DFTB+ 21.2 quantum chemistry package [46,47] (more details in Supplementary Materials). From all the above, this work aims to obtain a QSAR model to predict common commercial drugs to act as high-performance corrosion inhibitors. Thus, this work is divided into four subsections shown as follows. Firstly, the QSAR model is rationalized. Secondly, we describe how the corrosion inhibition efficiency behaves in terms of the descriptors chosen. Then, we discuss the characterization of the high-performance corrosion inhibitors by a quantum-chemical study, and lastly, we provide a theoretical-experimental evaluation of lidocaine as a corrosion inhibitor on steel. 2. Theoretical and Experimental Methods 2.1. NARMAX System Identification Approach Nonlinear autoregressive moving averages with exogenous inputs, NARMAX, system identification methodology [48] is used to build models smartly using historical data from the inputs, outputs, and other components. Some relevant applications of these techniques are stock prices [49] and weather [50] prediction, speech recognition [51], pattern classification [52], and aircraft dynamics [53]. As a model, the autoregressive with exogenous inputs (ARX) model is more straightforward (and easier to solve) than other more complex models such as NARMAX. This simplicity is because the ARX model does not require more detailed information about the system to be identified, such as nonlinear elements, which is why it is considered convenient for engineering applications where sufficient data in terms of representativeness is attainable as monitoring or diagnosis [54]. The NARMAX system identification methodology builds first a dictionary or matrix D composed of the system descriptors and corresponding observations. At that point, the forward regression orthogonal least squares (FROLS) algorithm [55,56] and the error reduction ratio (ERR) estimator [57] process the D matrix to produce an iterative feature selection that is capable of building a compact but representative model. The ARX model in the system identification context has been successfully applied in various areas, such as troubleshooting and diagnostics for cooling dehumidifiers [54], fault analysis modeling for variable air volume [58], monitoring of buildings’ energy consumption [59], interstitial glucose prediction during human physical activity [60], to predict the global magnetic disturbance in near-Earth space [61], the variability of the Atlantic meridional circulation [62], the Artemia population swimming motion [63], Drosophila photoreceptor responses [64], and EEG signal identification in the neuroscience field [65]. 2.2. ARX Theoretical Model The solution method for obtaining the prediction model presented in this work consists of two stages. The first one seeks to place the descriptor data for each drug in the form of a matrix according to the ARX model. In the second part, the descriptors that best explain the IE% are selected in an iterative process to identify the final model. 2.2.1. Arrangement of Candidate Terms In the first step, it is required to arrange the commercial drug’s data within rows and their corresponding chemical descriptors data into columns, aiming to produce an arrangement analogous to the ARX mathematical model structure, where only linear terms are included. Hence, the drug’s regression representation remains as follows:yi = ΣMj=1 βj xi,j∀ i ∈ N(1) The previous series can also be expressed as:yi = β1 xi,1 + β2 xi,2 + … + βM xi,M ∀ I ∈ N(2) where yi is the maximum corrosion inhibition efficiency (IE%) for the ith commercial drug contained within the database (for i = 1, …, N), xi,j is the jth chemical descriptor value for the ith commercial drug (for j = 1, …, M), and β1, …, βM is a set of adjusted weights to be computed once the final model has been identified by the FROLS algorithm. The goal of generating this series of N equations is to pack them together to produce an N × 1 vector array on the left side, namely y, and an N × M matrix arrangement on the right side, namely X, containing N rows of commercial drugs and M columns of chemical descriptors. In this stage, each column in X represents a model term that is viewed as a candidate that can be included (or not) in the final ARX prediction model, as will be explained in the next section. 2.2.2. FROLS and ERR Algorithms for Model Structure Selection The second stage of the solution methodology aims to identify a final ARX prediction model for accurately predicting the corrosion inhibition efficiency. We incorporated the FROLS algorithm to achieve this end, designed to select a subset of candidate terms that best explains the corrosion inhibition efficiencies contained in vector y. In the final model selection, the FROLS algorithm compares each candidate column in X with the column vector y to incorporate step by step into the model the terms/features that primarily reduce the error prediction of y. Such a process continues iteratively until the selected descriptors collectively reach a minimum value for the sum of error reduction ratio (SERR) [48]. Finally, to complete the system’s mathematical model, it is necessary to obtain the weights or parameters of the descriptors previously selected by the FROLS algorithm. The weights are easy to calculate thanks to the fact that the new model has a linear-in-the-parameters representation:y = β Z(3) where y is the response vector, Z is the matrix of selected descriptors, and β is the vector of weights obtained from the model. Thus, to compute the vector of linear weights, we only need to clear the vector β as follows:β = y Z−1(4) 2.2.3. Cross-Validation Cross-validation is a standard procedure when the dataset on hand has too few observations for data splitting. In the case of the current study, fivefold cross-validation was employed to seek a reliable model creation; hereafter, such a method is described [66,67]. Firstly, a database of 250 chemical compounds is elaborated as described in Section 3. Secondly, all compounds containing an experimental value of IE% are promoted to the training/validation set. The remaining compounds, those with no available experimental IE%, are set aside. Then, for each ARX/FROLS simulation run, the training/validation set is further randomly divided into five groups. In the first iteration, the first group is treated as a validation subset, and the remaining four groups are designated as the training subset, over which the ARX model and FROLS algorithm are run. The mean squared error (MSE) is computed on the first validation set. This procedure is repeated five times; each time, a different group of observations is treated as a validation subset. This process results in 5 different linear models with five distinct MSE estimates of the test error. The model with the lowest MSE value is promoted to predict the IE% of the remaining compounds. Other metrics were employed to analyze the model’s performance: Mean absolute percentage error (MAPE), standard deviation (SD), mean square error, and root mean square error (RMSE). These metrics, discussed throughout the manuscript, are defined now: MAPE = (1/n) Σni=1|(yi − ŷi)/yi| × 100%, SD = [(1/n − 1)Σni=1 (ŷ − yi)2]1/2, MSE = (1/n) Σni=1 (yi − ŷi)2, and RMSE = [(1/n) Σni=1 (yi − ŷi)2]1/2. Where yi is the experimental value of IE% for compound i, ŷi is the estimated value of IE% for compound i provided by the model, and y is the average IE% within a sample of compounds of size n. 2.3. Experimental Details 2.3.1. Solution Preparation Different concentrations of the lidocaine compound (Figure 1) were prepared and obtained in an injectable solution from “Farmacias del Ahorro” pharmacy. The initial solution concentration was 0.01 M, dissolved in ethanol, to make later solutions of 0, 10, 20, 50, and 100 parts per million (ppm). The corrosive solution is NaCl 3% (100 mL). 2.3.2. Electrochemical Evaluation The standard three-electrode system was used for the electrochemical evaluation at room temperature. The API 5L X70 sample was the working electrode, a saturated Ag/AgCl electrode was the reference electrode, and a graphite bar was the counter electrode. The test sequence was performed on a piece of Gill-AC equipment as follows: (a) Open circuit potential (OCP) was measured for 1800 s; (b) Electrochemical impedance spectroscopy (EIS) was employed using 10−2–104 Hz with an amplitude of ±10 mV. The exposure area of experimentally used samples was 0.78 cm2. The electrochemical tests were performed in triplicate. After the EIS measurements, potentiodynamic polarization curves of the inhibitor at different concentrations were performed, measured from −300 mV to 300 mV in relation to the open circuit potential (OCP), with the speed of 60 mV/min using the ACM Analysis software for data interpretation. 2.3.3. Characterization by Atomic Force Microscopy (AFM) The morphology of the steel sample surface after immersion in the corrosive media, in the presence and absence of the Lidocaine inhibitor, was characterized by atomic force microscopy (AFM) using digital instruments scanning probe microscope with a nanoscope IIIa controller. The AFM was operated in tapping mode using an etched silicon cantilever with a length of 125 µm, with a nominal tip radius of approximately 10 nm. 3. Results and Discussion In order to predict the corrosion inhibition efficiency of drugs on steel surfaces, a database with 250 commercial drugs containing common QSAR descriptors and those formulated within Pearson’s HSAB theory was used to obtain a linear mathematical model by an ARX analysis. The ARX methodology was also used to exclude the variables that do not contribute to the prediction of IE%. In addition, a more sophisticated method for data analysis, IBM’s Watson artificial intelligence [68], will be implemented to compare it with the ARX model and ensure the proper performance of the linear function. Thus, this work is divided into four subsections. Firstly, the model’s determination is discussed and compared briefly with the privative AI model. Secondly, the main tendencies exhibited by the linear model are discussed. Then, species predicted as highly efficient corrosion inhibitors are studied and, for extension, correlated with their families. Lastly, the prediction of IE% for lidocaine was compared with its experimental counterpart. 3.1. Model Determination This section explains how an ARX model was estimated to predict the iron corrosion inhibition of different compounds through a system identification methodology based on the FROLS algorithm. First, we narrate the data processing of the stated problem into a linear input-output system, followed by a term selection process to reach the final prediction model. 3.1.1. Data Processing into an ARX Linear System As stated, system identification aims to find a model that reveals the distinctive elements of a system by processing the history of its interactions with the environment. Here, we took the system to be identified as the corrosion inhibition efficiency on steel, IE%, explained by ten candidate quantum chemical descriptors. We studied the previous interaction through instances collected from 42 commercial chemical substances. The input-output model determination problem implies a suitable selection of the variables (descriptors) present in the following simple ARX linear model:y = β1 x1 + β2 x2 + β3 x3 + β4 x4 + β5 x5 + β6 x6 + β7 x7 + β8 x8 + β9 x9 + β10 x10(5) where y is an output term plus ten input terms composed of candidate descriptors, as labeled in Table 1, and a corresponding parameter value or weight βi. The list of the ten candidate descriptors and their corresponding index number is listed in Table 1. Each drug’s molecular weight (MW) was considered a size-dependent parameter. Additionally, the negative base-10 logarithm of the acid dissociation constant of a solution, pKa = −logKa, was included to determine the strength of an acid in the solution. Additionally, the octanol-water partition coefficient, log P, is a descriptor associated with the concentration of a given substance in the aqueous phase of a two-phase octanol-water mix. Similarly, the log S descriptor is directly related to the water solubility of a substance employing a base-10 logarithm. Besides, the polar surface area (PSA) is the molecular surface associated with heteroatoms and polar hydrogen atoms, giving a quantitative amount related to charge accumulation. In addition, polarizability, α, denotes the tendency of a particular molecule to acquire an electric dipole moment in the presence of an external electric field. As described previously, energies of HOMO and LUMO orbitals can be related, through Koopman’s theorem, to ionization energy and the electron affinity of a given molecular species, respectively. In addition, electrophilicity, ω, relates to the change in energy of an electrophile when it comes in contact with a perfect nucleophile, being a measure of the tendency to react between electrophile and nucleophile species. Finally, the fraction of electrons shared, ΔN, was selected since it relates to the amount of charge transferred from one species to another (Table 1). Unlike nonlinear models with second or third-order expansions, linear regression models are simpler to solve as they have precisely the same number of variables and model terms. A final critical point in data processing is the determination of the partition of the samples in testing and training data sets. Here, we divided data at random, where 80% of the data was used for training and 20% for validation. 3.1.2. Term Selection through FROLS and ERR In the term selection stage, we consider the linear model in Equation (5) and the training set as entry points to the FROLS algorithm, which can easily detect the most relevant terms in first-order expansions [48]. At the first step, the ERR values of each candidate m included in the D dictionary, where D = {p1, p2, …, pM}, are determined:ERRm = (yTpm/pTmpm)2(pTmpm)/yTy(6) The ERR value helps determine the final subset of the model’s terms because these indicate each one’s contribution to the prediction error reduction. The first term selected from the D dictionary is always the one with the highest ERR. The descriptor with the highest ERR was x7, with an ERR of 97.82% in our testing. The selection process takes only the remaining unselected terms from dictionary D and introduces orthogonal transformations via the Gram–Schmidt algorithm from step two onwards. The orthogonalization process prevents the following candidates from being included from containing information already provided by the descriptors already selected, thus each new term contributes independently to the model’s accuracy. Finally, the selection procedure ends when the error-to-signal ratio (ESR) decreases below a predetermined threshold, where:ESR = 1 − ΣMoi=1 ERRi ≤ ρ(7) where ρ is a very small value, for instance, in this work, ρ = 0.005 and M0 is the number of unselected candidate variables. The terms included in the final model and the ERR values for each can be consulted in Table 1. The final calculation involved the estimation of the parameters β, as it is shown in Section 2.2.1, thus the final ARX model, derived from the initial linear formulation in (5), can be stated as follows:ŷ = 812.1748 x7 + 33.1669 x10 + 823.4630 x8 + 6579.0080 x9 + 0.5287 x2(8) Consequently, the linear ARX model obtained accurate and precise results compared to the testing set, as evidenced by the computed mean absolute percentage error and standard deviation. The testing set included aspirin, cephapirin, ascorbic acid, imidazole, trimethoprim, clindamycin, phenobarbital, and doxycycline data, obtaining MAPE, SD, RMSE, and MSE of about 5.18, 2.51, 4.87, and 23.80%, respectively. In addition, another set of drugs was collected to verify the generalization power of the ARX model. Additional data for streptomycin [73], fexofenadine [74], quinoline [75] N, N-dimethylformamide [76], and mycophenolic acid [25] was used to compute the MAPE, SD, RMSE, and MSE, obtaining 6.76%, 3.89%, 7.03%, and 49.47%, respectively. These values are fully comparable to those obtained with the testing set, pointing to a correct prediction of IE% values for drugs relatively different from those in the original database. IBM’s Watson artificial intelligence platform was also used to obtain a private and highly hyperparametrized model. In this case, the five variables (pKa, EHOMO, ELUMO, ω, and ΔN) in the ARX model were included in the AutoAI Watson’s routine to fit the experimental IE% values [77]. Additionally, 80% of the data was used for the training set and the remaining 20% for validation. Finally, four different experiments, pipelines, were done by the extra trees regressor algorithm. The model obtained improved the external comparison only to 5.44%, 2.91%, 5.35%, 28.59% for MAPE, SD, RMSE, and MSE, respectively. Thus, the ARX model (obtained through FROLS), a linear function that depends only on five descriptors, obtained results close to a highly hyperparametrized, non-portable, and nonlinear alternative. Other QSAR models have been proposed recently. Thus, it is pertinent to compare our linear ARX model with those found in the literature regarding standard evaluation metrics. For instance, Quadri and coworkers reported several multiple linear regression and artificial neural network (ANN) models adjusted to twenty pyridazine derivatives. The best ANN model yielded a lower MAPE value, of about 10.2362%, whereas the RMSE and MSE achieved were 10.5637 and 111.5910%, respectively [78]. In comparison, Li and colleagues obtained a QSAR model by a support vector machine approach to predict the performance of benzimidazole derivatives. In this case, the nonlinear model achieved an RMSE of about 6.79% [79]. More recently, they updated the model, improving the RMSE up to 4.45% [40]. In addition, Al-Fakih and coworkers reported QSAR models for furan derivatives, obtained with sparse multiple linear regression using ridge penalty and sparse multiple linear regression using an elastic net, achieving MSE of about 7.75 and 2.34%, respectively [80]. The ARX approach obtained similar metrics compared to those obtained with alternative methods, as reported by other authors. A brief discussion is included below to identify the extent and perspectives of the ARX linear model. In principle, corrosion inhibition is a multifactorial phenomenon since drug solubility, pH, temperature, concentration, corrosive medium, dynamic conditions, the employed alloy, and even experimental technique used to determine IE% could influence the results [2]. Thus, it is possible to assume that a 5-parameters model such as that introduced above is not enough to catch the variety of conditions experimentally used. However, to the best of our knowledge, these experimental variables are not recurrently considered, possibly by the scare IE% values measured with the same experimental design, hindering the formulation of mathematical models. Nevertheless, work conditions are naturally occurring variables that should be considered for robust predictive models. Finally, although linear models to predict IE% are the most common approach [78], nonlinear formulations can also be suitable. A nonlinear version of ARX comes to be the NARMAX model in the current case. According to Gu et al., nonlinear models performed better than linear ones in a study about cortical responses. Nevertheless, the linear terms had larger weights than those in the resulting NARMAX models [81]. In addition, NARMAX approaches are known to identify mathematical models for nonlinear systems, which prevail in nature. This is the case of the solar wind coupling analysis reported by Boynton and coworkers [82] or the peak air pollution levels forecasted by Pisoni et al. [83]. Thus, it is expected that a NARMAX approach to the corrosion inhibition problem may well determine whether the phenomenon is nonlinear in terms of the proposed descriptors. However, as suggested by Boynton, a high number of possible monomials resulting from the polynomial expansion can be a challenging situation. The above stems from the need for a final parsimonious NARMAX model with fewer monomials selected out of a vast majority with no or minimal influence on the phenomenon. In principle, such as in the ARX approach used here, the FROLS algorithm could lead to a small set of monomials within the selected allowable model order [84]. 3.2. Main Tendencies This subsection aims to elucidate the main tendencies exhibited by the predictions, carried out on 250 commercial drugs by the ARX model detailed previously, of the corrosion inhibition efficiency IE%. Thus, five variables contained in the ARX mathematical model (EHOMO, ELUMO, ΔN, ω, and pKa) and molecular weight were used to illustrate the predicted IE% values. In addition, five drugs were excluded from the following analyses due to their unrealistic IE% values predicted above 100%. These species are sulfadiazine (106.31%), methacycline (111.72%), glycine (124.03%), ethosuximide (158.88%), and hexetidine (259.25%). First of all, Figure 2 shows that corrosion inhibition efficiency IE% increases as the energy of HOMO decreases. Consequently, by Koopman’s theorem, the most efficient drug molecules to act as corrosion inhibitors are those with the lowest ionization potential. The above can be rationalized by the necessity of the metal surface atoms to fill their vacant d-orbitals with electrons, coming from the corrosion inhibition molecule in the current case. Consequently, the easier it is to remove valence electrons from the organic molecule, the higher corrosion inhibition performance exhibited. On the other hand, ELUMO splits the IE% values into two sets (Figure 2). The first set of drugs, with ELUMO values below 2.0 eV, shows a tendency similar to that exhibited by EHOMO since the most efficient corrosion inhibitors are those with the most negative ELUMO values and consequently the highest electron affinities. Thus, it is expected that high-performance corrosion inhibitor molecules can catch electrons from the environment and donate them, leading to shared electrons as in covalent interactions. However, the other set of molecules with moderate performance, with ELUMO values above 4.5 eV, offers another route to produce the corrosion inhibition effect (Figure 3). Since up to 14 species are obtained with low and even positive ELUMO values and intermediate EHOMO energies, ranging from −6.5 to −5.0 eV, they are expected to donate charge to the metal surface and handle mostly electrostatic interactions with it. These intermediate efficiency corrosion inhibitors are, in order of increasing IE%, the following ones: cyclopentamine (84.92%), methenamine (85.56%), triethylamine (86.74%), gentamicin (87.12%), mecamylamine (88.32%), kanamycin (88.66%), diethylamine (90.00%), diethanolamine (90.75%), ethambutol (91.46%), amantadine (92.43%), ethanolamine (92.57%), tromethamine (92.59%), tuaminoheptane (92.99%), and ethylamine (94.12%). In the case of IE% as a function of the electrophilicity and the fraction of electrons shared, the efficiency shows two sets of compounds. The highest IE% values are obtained in the molecules with the highest ω and ΔN values (see Figure 3). The above can be related to the previous assumptions about how the electrons behave between the corrosion inhibitor molecule and the metal surface. Thus, a highly effective corrosion inhibitor molecule is expected to donate a considerable number of electrons to the metal surface, as denoted by the ΔN values calculated for the specific case of an iron surface. Additionally, according to the ARX model, a highly efficient corrosion inhibitor molecule is expected to behave as an electrophile with high power to attract electrons to itself. Besides, the other set of molecules is composed precisely of those drugs named above. Drugs with intermediate performance, with IE% efficiency ranging from 84.92% to 94.12%, cannot donate large amounts of charge to the metal surface and neither to attract it. Thus, the fourteen species with moderate performance are expected to interact by electrostatic interactions. Lastly, the heat map obtained for IE% as a function of the molecular weight and pKa shows more smoothly dispersed values without the two sets obtained previously (see Figure 4). It is noticeable that the highest efficiency is obtained for species with molecular weight ranging from 415 to 823 Da. Additionally, all the high-performance molecules are predicted for those species with positive pKa, ranging from 5 to 10. Thus, weak acids are expected to behave as potential corrosion inhibitors, whereas strong acids are not helpful for this application. Although light molecules are not particularly prominent by their corrosion inhibition efficiencies, values above 90% are easily reached. In the case of these light species, with a molecular weight below 400 Da, the IE% increases as the pKa increases. Since the commercial drugs must exhibit high corrosion inhibition efficiencies, above 90% according to international standards for industrial applications, the following subsection aims to deep into the species predicted by the ARX models as highly efficient corrosion inhibitors. 3.3. High-Efficiency Corrosion Inhibitors In order to produce reliable predictions for highly efficient commercial drugs to act as corrosion inhibitors, species with IE% estimated above 95% are studied as follows. The value 95% was chosen to take into account MAPE and SD values computed for the mathematical model of about 5.18% and 2.51%, respectively. This way, it is expected that efficiencies measured under experimental conditions must fall into the regime required for industrial applications, with inhibition efficiencies above 90%. The drugs fulfilling these conditions, shown in Table 2, are minocycline (97.58%), deserpidine (95.29%), daunorubicin (96.67%), dipyridamole (97.28%), doxorubicin (97.40%), amphotericin B (97.55%), acepromazine (97.73%), cephaloridine (98.57%), mercaptopurine (98.66%), and rifampicin (98.71%). Being weak acids, the most efficient drugs are found with pKa ranging from 1.70 to 9.46. Moreover, EHOMO values are found in a tight range, from −5.87 to −4.34 eV. Conversely, ELUMO values are exhibited in a broader range, from −4.01 to −1.83 eV. Electrophilicity ranges from 0.77 to 1.23 eV, whereas ΔN ranges from 1.12 to 1.55. Thus, all the above is consistent with previous observations about general tendencies. There are no significant similarities among all the high-efficient species; however, some functional groups are recurrently exhibited by these species. In addition, invoking the similarity principle, drugs belonging to the same family are suitable to be presumed as corrosion inhibitors with efficiencies comparable to those obtained for the species shown in Table 2. For instance, minocycline is a tetracycline antibiotic, with multiple dimethylamino, hydroxyl, and carbonyl groups, obtained as a highly efficient corrosion inhibitor, with an IE% predicted value of 97.58% (Table 2). Other tetracycline antibiotics are presumed to be obtained as suitable corrosion inhibitors. Doxycycline and oxytetracycline are predicted as efficient CIs, with 91.89% and 93.95% IE% values, respectively. Deserpidine is an example of an ester alkaloid drug, exhibiting multiple methoxyl and carbonyl groups, used for their antihypertensive and antipsychotic properties. Although alkaloids predicted to act as corrosion inhibitors cover a wide range of structural motifs, the most prominent by their structural similarity to deserpidine and predicted IE% value of about 94.55% is reserpine, another alkaloid that can be obtained from Rauwolfia species (Table 2). By extension, yohimbine is another alkaloid presumed to act as a suitable corrosion inhibitor. Finally, daunorubicin and doxorubicin are two examples of anthracycline class drugs for cancer treatments [85], with predicted IE% values of about 96.67% and 97.40%. Similar to the previous cases, these species exhibit several hydroxyl and carbonyl groups, presumed to be covalent-polar and dative bonds with iron surface atoms, respectively [86,87]. Additionally, multiple π-electrons coming from their aromatic rings can be donated to the iron surface. Furthermore, amphotericin B is another drug that is predicted to act as a highly efficient corrosion inhibitor, with IE% estimated as 97.55%. This drug belongs to macrolides and the same class of antibiotics, including erythromycin, roxithromycin, azithromycin, and clarithromycin. In particular, Amphotericin B does not contain several aromatic rings, such as those exhibited by the species previously discussed. Thus, this drug, exhibiting eleven hydroxyl groups and two carbonyl ones, is expected to interact mainly with the metal surface by their functional groups. Erythromycin is another macrolide expected to work as a suitable corrosion inhibitor, with IE% estimated as 90.11% (Table 2) according to NRF-005-2009. This decrement in the corrosion inhibition efficiency can be rationalized by the few functional groups in erythromycin capable of interacting with the metal surface compared to amphotericin B. On the other hand, acepromazine heads the phenothiazine family of antipsychotics, accounting for an estimated corrosion inhibition efficiency of about 97.73%. This molecule’s interactions can be explained by the π electrons available in its aromatic rings in addition to a carbonyl group. Other members of the phenothiazine family, promazine and levomepromazine, lack that carbonyl group. These drugs achieve lower corrosion inhibition efficiencies of 91.19 and 91.81% (Table 2). Another relevant drug is cefaloridine, being part of the cephalosporin class, a large group of antibiotics derived from the fungus acremonium. Aromatic rings and carbonyl groups are the most relevant structural motifs constituting cefaloridine. However, several cephalosporin drugs were also studied but achieved lower efficiencies. These drugs are cephapirin (85.72%), cephalexin (85.87%), cephalothin (86.06%), cefazolin (86.24%), and cephradine (86.68%). In this case, it is unclear why cefaloridine is so efficient since all cephalosporin exhibits similar functional groups. Thus, it is necessary to deepen the corrosion inhibition effect of cefaloridine and other cephalosporin drugs. According to these measurements, cephapirin (82.5%) and cephalexin (76.9%) achieve lower corrosion inhibition efficiencies in comparison with the predicted values, whereas cephalothin (92.0%), cefazolin (93.9%), and cephradine (95%) are closer to the value predicted for cephaloridine of about 98.57% (see Supplementary Materials). It is plausible that the ARX model does not well describe the cephalosporin family. Dipyridamole and mercaptopurine are two drugs without relatives in the current study. With high corrosion inhibition efficiencies of about 97.28 and 98.66%, respectively, dipyridamole and mercaptopurine are presumed to strongly interact by their double bonds and polar functional groups. Finally, rifampicin is part of the rifamycins class, a group of antibiotics, with IE% estimated as 98.71% (Table 2). Interestingly, rifampicin is the only of these highly efficient corrosion inhibitor molecules, with an experimental measure of its IE% of about 94.7% (see Supplementary Materials). Furthermore, this species exhibits several functional groups, such as carbonyl and hydroxyl groups and heteroatoms and π-electrons, thus suggesting that rifampicin could interact with the metal surface by covalent, dative bonds, or electrostatic interactions. Thus, the whole rifamycin family could be evaluated as corrosion inhibitors. The above discussion points out the highly efficient corrosion inhibition properties expected for ten commercial drugs, with IE% values ranging from 95.29 to 98.71% (Table 2). In comparison, other drugs experimentally evaluated exhibited similar or lower corrosion inhibition efficiencies. For instance, losartan, a drug commonly used for hypertension treatment, obtained a maximum IE%, by EIS technique, of only 92.0% [88]. Additionally, salbutamol, a commonly used treatment for asthma, was obtained with a maximum IE%, determined by EIS measurement, of about 84% [89]. Similarly, Anadebe and coworkers collected the maximum IE% achieved by several recently reported commercial drugs, ranging from 80% to 95% [89]. Drugs applied to carbon steel were tobramycin (80%) [90], metformin (90%) [91], metolazone (92%) [92], and nifedipine (94%) [93]. Additionally, species applied on mild steel surfaces were: dexamethasone (83%) [94], rosuvastatin (90%) [95], ambroxol (94%) [96], and dapsone (95%) [97]. Additionally, Abeng, et al. reported the IE% on carbon steel achieved by moxifloxacin (88.2%), nifedipine (89.6%), metolazone (92.8%), and levofloxacin (94.1%) [98]. Even more, the recently evaluated drugs, mycophenolic acid [25] and fluconazole [24], obtained moderate efficiencies of about 90%. Clearly, all these recently studied drugs obtained values below the threshold assumed in this work. However, other drugs were comparable to those expected for the molecules analyzed in this subsection. This is the case of pyrazinamide, isoniazid, and rifampicin, which achieved maximum IE% values of about 95.86%, 97.89%, and 97.06%, respectively [99]. Thus, the predictions and tendencies discussed could be the object of study and further confirmation. 3.4. Experimental Verification (a) Open circuit potential (OCP) The variations of the OCP without and with the corrosion inhibitor lidocaine reached a steady state at 600 s (Figure 5). It is evident that when a corrosion inhibitor is present, the potential considerably decreases, indicating a drop in the corrosion process. (b) Concentration effect of lidocaine by EIS The equivalent electric circuits employed to fit the experimental data of the Nyquist diagrams are shown in Figure 6. A Randles circuit in the case of the sample of Figure 6a was used without inhibitor (Blank). A parallel circuit with two constant phase elements (Figure 6b) for the samples with inhibitor. Where Rs is the solution resistance, Rct is the charge transfer resistance, CPEinh is the constant phase element of the inhibitor, and CPERct is the constant phase element associated with the double layer. The inhibitor efficiency IE% was calculated by the equation [100]:IE% = 100 [(Rp blank−1 − Rp inh−1)/Rp blank−1)](9) where Rp blank−1 is the polarization resistance of blank and Rp in−1 is the polarization resistance of sample with inhibitor. The polarization resistance (Rp) was calculated with:Rp = Rct + RF(10) where Rct is charge transference resistance and RF film resistance, in Ω cm2. The electrochemical double-layer capacitance (Cdl) was calculated through the next equation [101]:Cdl = Y01/n (Rs−1 + Rct−1) (n − 1)/n(11) where Y0 is the constant phase element, Rs is the solution resistance (Ω cm2), and Rct is the charge transfer resistance (Ω cm2). For the description of a frequency-independent phase shift between an applied AC potential and its current response, a constant phase element (CPE) is used, defined in the impedance representation as:ZCPE = Y0−1(jω)−n(12) where Y0 is the CPE constant, n is the CPE exponent that can be used as a gauge of the heterogeneity or roughness of the surface, j = −1 is an imaginary number, and ω is the angular frequency in rad s−1. Depending on n, CPE can represent a resistance (ZCPE = R, n = 0), a capacitance (ZCPE = C, n = 1), and a Warburg impedance (ZCPE = W, n = 0.5), or inductance (ZCPE = L, n = −1). The correct equation to convert Y0 into CF is given by [102] CF = Y0 (ω′)n−1(13) where CF is the film capacitance (µF/cm2) and ω′ is the angular frequency at which Zreal is maximum. Figure 7a shows the Nyquist diagram of API 5L X52, called “blank”. A semicircle that is not entirely close was observed, attributed to charge transfer resistance. On the other hand, the Nyquist diagram in Figure 7b in all concentrations showed two processes: one attributed to inhibitor film and the charge transfer resistance [103]. Table 3 shows the electrochemical parameters obtained after fitting with the equivalent electric circuits of Figure 6. At 100 ppm, the highest value of Rct was reached (1522 Ω cm2). This behavior could be attributed to the high adsorption process of the organic compound on the metallic surface. On the other hand, the Cdl and CF values decreased because the surface is protected by the inhibitor at the metal/solution interface [104]. (c) Polarization curves The polarization curves of the API 5L X70 steel, immerse in 3% NaCl with and without lidocaine, are shown in Figure 8. The polarization parameters are enlisted in Table 4: corrosion potential (Ecorr), current density (icorr), tafel slopes (ba and bc), and the inhibition efficiency (IE%) was determined by:IE% = [1 − icorr/icorr blank] × 100(14) where icorr and icorr blank are the current density with and without inhibitor. Figure 8 shows that the curve shifts to the left due to the corrosion current density decreasing when the concentration increases due to the adsorption of the inhibitor. The electrochemical parameters by this technique show that the corrosion current density (icorr) value decreased in the presence of the lidocaine inhibitor, being attributed to the protected metal surface (Table 4). This phenomenon implies that the inhibitor might suppress the anodic reaction of the metal dissolution and the detachment of cathodic hydrogen [105], while the inhibition efficiency by this technique shows similar results to the other technique (EIS), and the best concentration was 20 ppm with 92.6% to protect the metal surface. Finally, according to corrosion potential (Ecorr), at a concentration of 20 ppm, the lidocaine behaved as an anodic inhibitor, while at 10, 50, and 100 ppm, the behavior was cathodic. (d) Adsorption process The corrosion inhibition displaces the water molecules and replaces them with the inhibitor molecules on the metal surface. Nevertheless, the superficial coverage (θ) for the different lidocaine concentrations as corrosion inhibitors in this system was evaluated by EIS using IE%:θ = (1/100) IE%(15) Using the Langmuir isotherm, a good fit is obtained, and according to the value of the free energy of adsorption of Gibbs (Equation (17)), the combined process continues [106]. C/θ = kads−1 + C(16) ΔG0ads = − 55.5 RT ln kads(17) where C is the concentration, θ is the coating coverage, kads is the adsorption constant, R is the ideal gas constant, and T is the temperature. In some reports, the ΔG0ads will indicate which adsorption mechanism follows the organic compound; if it is lower than −20 kJ/mol, it can be considered a physisorption process. If it is higher than −40 kJ/mol (ΔG0ads > −40 kJ/mol), then it is a chemisorption process, but if it is in the middle of −20 kJ/mol and −40 kJ/mol, the type of process that is taking place is called “combined”. Figure 9 shows a good fit, having a correlation coefficient (R2) of 0.9996. The equation obtained is C/θ = 1.0534 C + 8 × 10−6, obtaining a ΔG0ads = −38.39 kJ/mol due to a combined type process. (e) AFM analysis Figure 10 shows AFM images recorded on the surfaces of steel samples, and Table 5 shows the roughness values; both Ra (the mean roughness or arithmetic average of the absolute values of the roughness profile ordinates) and Rq (root mean square roughness or the root mean square average of the roughness profile ordinates) are reported. After exposure to the corrosive media for 24 h in the absence (Figure 10a) and in the presence of 50 ppm of lidocaine (Figure 10b), it can be noted that the roughness values of the steel sample that was not protected with lidocaine are notorious compared with that of the sample that was protected with lidocaine or that which was not exposed to the corrosive media, Figure 10c, such notable rugosity is due to the different corrosion products formed in each case. 4. Conclusions A QSAR relationship constructed through a linear ARX model was used to predict the corrosion inhibition efficiency of 250 commercial drugs on steel. The ARX treatment found the five most important descriptors to predict IE%, reducing by half the number of variables used in the linear model. These variables, obtained mostly from quantum chemical calculations of gas-phase molecules at the DFTB3-LJ level, are the pKa, electrophilicity, HOMO and LUMO energies, and the fraction of electrons transferred to bulk iron. The ARX model obtained a MAPE and SD of about 5.18 and 2.51%, respectively, compared to the testing set. Another five drugs not included in the original database were used as an external validation set for which the computed MAPE and SD were approximately 6.76% and 3.89%, respectively, thus confirming the previous predictions. In addition, a fivefold model, obtained by IBM’s Watson AI extra trees regressor algorithm, was used to compare it with the ARX one. In this case, IBM’s Watson model improved the external comparison only to 5.44% and 2.91% for MAPE and SD, respectively. Thus, the linear ARX model is competitive compared to highly hyperparametrized and privative alternatives. Overall, there are several tendencies of IE% as a function of the selected variables. For instance, IE% increases as the energy of HOMO decreases. Additionally, the highest IE% values are obtained in the case of the molecules with the highest ω and ΔN values. The most efficient drugs are found with pKa ranging from 1.70 to 9.46. The drugs recurrently exhibit aromatic rings, carbonyl, and hydroxyl groups with the highest IE% values. Ten drugs are predicted with IE% above 95%—those are: minocycline (97.58%), deserpidine (95.29%), daunorubicin (96.67%), dipyridamole (97.28%), doxorubicin (97.40%), amphotericin B (97.55%), acepromazine (97.73%), cephaloridine (98.57%), mercaptopurine (98.66%), and rifampicin (98.71%). Alkaloids from Rauwolfia species, macrolides, cephalosporin, and rifamycin antibiotics are expected to exhibit high IE% on steel surfaces. Lastly, lidocaine was predicted and experimentally tested for the first time. At 100 ppm concentration, the lidocaine showed IE% of about 92.5% using electrochemical impedance spectroscopy and 87.4% by polarization curves; in comparison, the ARX model predicted 87.51%. The thermodynamic analysis showed that the lidocaine follows a mixed adsorption process in the API 5L X70 surface. This linear model proposed to deepen the use of commercial and reused drugs to act as corrosion inhibitors on steel. Acknowledgments A.E.-V., A.M., and R.O.-C. wish to acknowledge the SNI for the distinction of its membership and the stipend received. A.E.-V. and R.O.-C. express their gratitude to the Instituto de Ingeniería of the Universidad Veracruzana (UV). A.M. thanks to Laboratorio de Supercomputo del Bajio and Hasso Plattner Institute for the supercomputer resources received. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23095086/s1. Click here for additional data file. Author Contributions Conceptualization, A.E.-V., C.B.-P., A.A.A.S. and A.M.; methodology, A.E.-V., C.B.-P., A.A.A.S. and A.M.; software, C.B.-P. and A.M.; validation, A.E.-V., C.B.-P., A.A.A.S. and A.M.; formal analysis, A.E.-V., C.B.-P., A.A.A.S., R.O.-C., A.M.-J. and A.M.; investigation, A.E.-V., C.B.-P., A.A.A.S., G.S.-R., R.O.-C., A.M.-J. and A.M.; resources, A.E.-V., C.B.-P., R.O.-C., A.M.-J. and A.M.; data curation, A.E.-V., C.B.-P., A.A.A.S., G.S.-R., R.O.-C., A.M.-J. and A.M.; writing—original draft preparation A.E.-V., C.B.-P., A.A.A.S. and A.M.; writing—review and editing, A.E.-V., C.B.-P., A.A.A.S., G.S.-R., R.O.-C., A.M.-J. and A.M.; supervision, A.E.-V. and A.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 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 Lidocaine molecule experimentally used to validate the ARX model. Figure 2 Corrosion inhibition efficiency, predicted by the ARX model, as a function of EHOMO and ELUMO. Variables calculated at the DFTB3-LJ level of theory. Figure 3 Corrosion inhibition efficiency, predicted by the ARX model, as a function of electrophilicity, ω, the fraction of electrons transferred, ΔN. Variables calculated at the DFTB3-LJ level of theory. Figure 4 Corrosion inhibition efficiency, predicted by the ARX model, as a function of molecular weight and pKa. Figure 5 Variation of OCP at different concentrations of Lidocaine in API 5L X70 steel. Figure 6 Equivalent electrical circuits. (a) A Randles circuit in the case of the sample was used without inhibitor (Blank). (b) A parallel circuit with two constant phase elements for the samples with inhibitor. Figure 7 Nyquist plots (a) without inhibitor and (b) different concentrations of lidocaine in API 5L X70 immersed in NaCl 3%. Figure 8 Polarization curves of different concentrations of lidocaine in API 5L X70 steel immersed in 3% NaCl. Figure 9 Langmuir isotherm at different concentrations of lidocaine in API 5L X70 steel immersed in NaCl 3%. Figure 10 AFM images (2D and 3D formats) were recorded on the surface of API 5L X70 steel samples after 24 h immersion in NaCl 3%: (a) in the absence and (b) in the presence of 50 ppm lidocaine. The image in (c) corresponds to the as-polished steel sample not immersed in the corrosive media. ijms-23-05086-t001_Table 1 Table 1 List of variables included, in the database, used to obtain the QSAR model, symbols, units, and references of their use in QSAR studies for corrosion inhibition. Additionally, parameters and ERR were obtained by the FROLS algorithm after processing the model of Equation (5) for the final model. x i Descriptor Symbol Units Reference Parameter ERR (%) x 1 Molecular weight MW Da [69,70] - - x 2 Acid dissociation constant pKa - - 0.5287 0.0600 x 3 Octanol-water partition coefficient log P - [71,72] - - x 4 Water solubility log S - - - - x 5 Polar surface area PSA Å2 [38,71,72] - - x 6 Polarizability α Å3 [72] - - x 7 Energy of HOMO E HOMO eV [38,69,71,72] 812.1748 97.8259 x 8 Energy of LUMO E LUMO eV [38,69,71,72] 823.4630 0.1034 x 9 Electrophilicity ω eV [44,72] 6579.0080 0.0688 x 10 The fraction of electrons shared ΔN - [44,70,72] 33.1669 1.3933 Sum of ERR 99.4514 ijms-23-05086-t002_Table 2 Table 2 Descriptor values, common use, and structure of drugs predicted as corrosion inhibitors with efficiency above 95%. Drug pKa E HOMO E LUMO ω ΔN IE% Common Use 2D Structure Deserpidine 6.68 −4.92 −2.42 0.92 1.33 95.29 Antihypertensive and antipsychotic Daunorubicin 8.20 −5.87 −4.01 1.23 1.11 96.67 Cancer treatment Dipyridamole 6.40 −4.34 −1.83 0.77 1.55 97.28 Anticoagulant Doxorubicin 9.46 −5.86 −4.00 1.23 1.12 97.40 Cancer treatment Amphotericin B 3.58 −5.27 −3.29 1.07 1.37 97.55 Antibiotic and fungicide Minocycline 2.30 −5.32 −3.42 1.09 1.38 97.58 Antibiotic Acepromazine 9.30 −4.92 −2.53 0.93 1.37 97.73 Antipsychotic Cephaloridine 3.40 −5.31 −3.43 1.09 1.40 98.57 Antibiotic Mercaptopurine 7.80 −5.03 −2.83 0.98 1.40 98.66 Cancer treatment Rifampicin 1.70 −4.86 −2.81 0.96 1.55 98.71 Antibiotic ijms-23-05086-t003_Table 3 Table 3 Electrochemical parameters at different concentrations of lidocaine in API 5L X70 immersed in NaCl 3%. C (ppm) Rs (Ω cm2) n Cdl (µF/cm2) Rct (Ω cm2) CF (µF/cm2) n2 Rmol (Ω cm2) Rtotal (Ω cm2) IE% (%) 0 6 0.800 2960 127 - - - - - 10 8.24 0.80 181.3 102.00 4034.0 0.8 28.70 130.70 3.2 20 10.53 0.77 187.5 404.10 622.2 0.52 337.90 742.00 83.0 50 24.66 0.85 90.3 1493.00 40.7 0.49 151.70 1644.70 92.3 100 24.29 0.84 51.9 1522.00 26.0 0.48 157.00 1679.00 92.5 ijms-23-05086-t004_Table 4 Table 4 Polarization parameters for lidocaine in API 5L X70 immersed in NaCl 3%. C (ppm) Ecorr (mV) vs. Ag/AgCl sat icorr (µA/cm2) ba (mV/dec) −bc (mV/dec) IE% (%) 0 −804.7 67.4 159.5 173 - 10 −909.7 65.0 146.6 161.5 3.4 20 −709.6 4.9 104.5 204.1 92.6 50 −907.7 7.4 170.5 60.3 89.0 100 −916.5 8.2 187.8 68.2 87.4 ijms-23-05086-t005_Table 5 Table 5 Roughness values calculated from the AFM images shown in Figure 10. AFM image Ra (nm) Rq (nm) a 142 181 b 30.5 45 c 3.4 4.3 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. 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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/ijerph19095762 ijerph-19-05762 Article Management of Breast Abscess during Breastfeeding https://orcid.org/0000-0002-3569-0780 Pileri Paola 12* Sartani Alessandra 3 Mazzocco Martina Ilaria 1 https://orcid.org/0000-0002-4890-6915 Giani Sofia 2 Rimoldi Sara 4 Pietropaolo Gaia 3 Pertusati Anna 3 Vella Adriana 5 Bazzi Luca 5 https://orcid.org/0000-0002-9217-3034 Cetin Irene 12 Orczyk-Pawiłowicz Magdalena Academic Editor Tchounwou Paul B. Academic Editor 1 Department of Woman, Child and Neonate, Buzzi Children Hospital, ASST Fatebenefratelli Sacco, Via L. Castelvetro 32, 20154 Milan, Italy; martina.mazzocco@libero.it (M.I.M.); irene.cetin@unimi.it (I.C.) 2 Departmental Breast Unit, ASST Fatebenefratelli Sacco, University of Milan, Via G.B. Grassi 74, 20157 Milan, Italy; sofigiani@gmail.com 3 Department of Biomedical and Clinical Sciences, University of Milan, Via G.B. Grassi 74, 20157 Milan, Italy; alessandra.sartani@asst-fbf-sacco.it (A.S.); gaia.pietropaolo@asst-fbf-sacco.it (G.P.); annapertusati@gmail.com (A.P.) 4 Laboratory of Clinical Microbiology, Virology and Diagnostics of Bioemergencies, ASST Fatebenefratelli Sacco, University of Milan, Via G.B. Grassi 74, 20157 Milan, Italy; sara.rimoldi@asst-fbf-sacco.it 5 Department of Radiology, “Luigi Sacco” University Hospital, Via G.B. Grassi 74, 20157 Milan, Italy; adriana.vella@asst-fbf-sacco.it (A.V.); luca.bazzi@asst-fbf-sacco.it (L.B.) * Correspondence: paola.pileri14@gmail.com 09 5 2022 5 2022 19 9 576231 1 2022 07 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/). (1) Background: Breast abscess (BA) is a condition leading in the majority of cases to breastfeeding interruption. Abscesses are commonly treated with antibiotics, needle aspiration or incision and drainage (I&D), but there is still no consensus on the optimal treatment. Since there are no well-defined clinical guidelines for abscess management, we conducted a retrospective, observational study with the aim of assessing ultrasound (US)-guided management of BA without surgery, regardless of the BA size. The secondary objective was the microbiologic characterization and, in particular, the S. aureus methicillin resistance identification. (2) Methods: our population included 64 breastfeeding mothers with diagnosis of BA. For every patient, data about maternal, perinatal and breastfeeding features were collected. All patients underwent office US scans and 40 out of 64 required a more detailed breast diagnostic ultrasound performed by a radiologist. In all cases, samples of milk or abscess material were microbiologically tested. All patients received oral antibiotic treatment. We performed needle aspiration, when feasible, even on abscesses greater than 5 cm. (3) Results: most of the women developed BA during the first 100 days (68.8% during the first 60 days) after delivery and 13 needed hospitalization. Four abscesses were bilateral and 16 had a US major diameter greater than 5 cm. All patients were treated with antibiotic therapy according to our clinical protocol and 71.9% (46/64) underwent fine needle aspiration. None of them required I&D. The average duration of breastfeeding was 5 months (IR 2; 9.5) and 40.6% of women with BA continued to breastfeed for more than 6 months. Only 21 mothers interrupted breastfeeding before 3 months. (4) Conclusions: our observational data suggest, regardless of the size and the clinical features of the BA, a conservative approach with antibiotic therapy targeted at the Methicillin-Resistant Staphilococcus aureus (MRSA) identified and needle aspiration, if feasible. In our experience, treatment with needle aspiration is a cost- effective method. Unlike drainage, it is an outpatient procedure, easily repeatable, with no cosmetic damage. In addition, it has lower risk of recurrences since, differently from surgical incision, it does not cause interruption of the ducts. Moreover, needle aspiration is less painful, does not require the separation of the mother-child dyad and allows for a quicker, if not immediate, return to breastfeeding. breast abscess breastfeeding needle aspiration surgery This research received no external funding. ==== Body pmc1. Introduction Breastfeeding is the earliest form of communication between mother and child and breast milk is the best food for infants, species-specific, recommended by major societies, such as WHO [1], UNICEF [2], American College of Obstetricians and Gynecologists (ACOG) [3] and American Academy of Pediatrics (AAP) [4]. It has positive effects on mothers and their breastfed babies, enduring throughout life [5]. It provides all the nutrients needed in the first phase of life and contains bioactive and immunological substances that are not found in artificial substitutes. It promotes mother–child bonding, contributing to the increase in the intellectual quotient (IQ) and, through oxytocin production, stimulates the natural uterine contractions, reducing post-partum bleeding [4,5,6,7,8]. These are the reasons why the World Health Organization (WHO) recommends exclusive breastfeeding for the first 6 months of the infant’s life, and continued breastfeeding up to 2 years and beyond [1]. In a study performed by our group in 2014–2016, we found that breastfeeding support and promotion are the most significant factors that could affect breastfeeding outcomes [9]. During breastfeeding, problems or diseases may arise that may compromise its success if not promptly and appropriately treated. If during breastfeeding the mother reports pain, the presence of breastfeeding breast disease should be suspected and the most frequent causes are mastitis and breast abscesses. Breast abscess (BA) is a serious condition, related to severe morbidity in lactating women leading in the majority of cases to breastfeeding interruption with all its consequences. BA are defined as localised areas of infection with a walled-off collection of pus [10]. It may or may not be associated with mastitis, which represents its most severe complication. BA develops in 3% to 11% of women with mastitis with reported incidence of 0.1% to 3% in breastfeeding women. Cases due to Staphylococcus aureus are the most common and the majority of isolated strains are resistant to penicillins [11]. A progressive increase of breast infections due to Methicillin-resistant Staphylococcus aureus (MRSA) is reported, but few data are available regarding its real incidence. It varies among different countries in the world (e.g., <5% in UK, 60% in United States) [12,13]. In 2019, Rimoldi et al. published a study conducted in Italy where MRSA strains were responsible for 50% of breast abscesses in lactating women [14]. Less common are cases due to coagulase-negative staphylococci and streptococci [11]. Risk factors for BA are: advanced maternal age at delivery, primiparity, gestational age greater than 41 weeks, previous mastitis, cracked nipples, breastfeeding difficulties during hospital stays and working mothers [15]. The diagnosis of breast abscess is clinical and is confirmed by ultrasound [16]. Ultrasonography is the baseline radiologic technique to diagnose a BA, which results in a hypoechoic or anechoic mass surrounded by a hyperechoic area due to edema [17,18]. Abscesses are commonly treated with antibiotics, ultrasound-guided needle aspiration or incision and drainage (I&D), but there is still no consensus on the optimal treatment. When I&D is performed, the abscess is cut open with a scalpel to release the infected fluid, while treatment by needle aspiration is less invasive. Using ultrasound (US) guidance, a needle (18–19 Gauge) is inserted into the cavity of the breast abscess and a syringe is used to draw out the infected fluid [19]. Several authors have reported surgical incision with drainage as the first-line therapy for abscesses with a size greater than 3–5 cm or multilocular [20,21,22]. However, surgery necessitates local or general anesthesia, separation of the mother from her baby, and is a major risk of ending breastfeeding and scarring with its cosmetic outcomes. Moreover, scars in the breast tissue represent a major risk for further BA. A proper I&D must be performed in the operating room and requires hospitalization, with consequent higher costs [23,24]. Many recent studies support the treatment of lactational breast abscesses with needle aspiration, with or without US guidance [23,25,26]. A timely diagnosis and adequate treatment are essential, as mastitis and abscess represent one of the main reasons that lead to early weaning, with the loss of the benefits that derive from this practice for mother and child. Furthermore, if inadequately treated, they can lead to the development of sepsis and occasionally be fatal [27,28,29]. For a better management of these pathologies we created, in our II level medical center in Milan (ASST Fatebenefratelli—Sacco), a multidisciplinary team, composed of gynaecologists, breast surgeons, radiologists, pediatricians, microbiologists, midwives and nurses. Given that abscess management is still controversial, we conducted this retrospective observational study with the aim of assessing US-guided management of BA without surgery, regardless of BA size. A secondary objective was the microbiologic characterization and, in particular, the S. aureus methicillin resistance identification. 2. Materials and Methods This retrospective, observational study was performed at the Azienda Socio Sanitaria Territoriale (ASST) Fatebenefratelli—Sacco in Milan, between January 2016 and December 2019. Our population included 64 breastfeeding mothers with breast abscesses. The diagnosis of lactational breast abscess was made in the presence of clinical inflammatory signs (pain, redness, inflammatory skin) and often a localized, pulpable breast lump was present. The clinical picture was associated with an ultrasound finding of a localised area of infection with a walled-off collection of pus. All our patients underwent office ultrasound for the diagnosis of BA performed by a gynecologist or a breast surgeon. Forty out of the 64 patients required a more detailed breast diagnostic ultrasound performed by a radiologist to better characterize the lesion and understand if it was a drainable abscess cavity. All patients were followed by the multidisciplinary team according to the therapeutic diagnostic protocol in force. Every woman signed an informed consent for invasive procedures. For every patient recruited, data about maternal, perinatal and breastfeeding features were collected. We obtained information on breastfeeding outcomes by means of telephone interviews carried out after six months from the childbirth. Follow up was not possible for 5 mothers. The BA size was measured by ultrasound when performed by the radiologist. We established 5 cm as a cut off to distinguish between small and large abscesses. This parameter was chosen since many authors claimed that abscesses larger than 5 cm should be treated with I&D [11,16,22]. In all cases, samples of milk or abscess material, or both, were sent for microbiological testing in the laboratory. According to the Academy of Breastfeeding Medicine’s (ABM) clinical protocol, milk samples were collected by manual pressing of the breast following the cleansing of the skin, the nipple, the areola, and the operators’ hands [10]. An intermediate milk sample was collected for a total of 5–10 cc. The abscess purulent material was collected by needle aspiration or surgical drainage of the affected area. Needle aspiration was carried out after adequate disinfection of the skin, preparation of a sterile field, and local anesthesia with Lidocaine spray, using an 18 Gauge needle and a 20 cc syringe. I&D is a procedure that involves the injection of anesthetic into the intradermal tissues with a 25- or 30-Gauge needle followed by an incision directly over the center of the abscess. The goal is to allow sufficient space to introduce hemostats, to break up loculations and to place internal packing material. The wounds drain spontaneously but sometimes require gentle pressing to empty the residual content. Samples were collected in a sterile urine culture container, transferred by a sterile syringe to the BacT/ALERT blood culture bottle for Anaerobics (BioMérieux, Marcy L’Etoile, France) and sent to the Laboratory of Clinical Microbiology, Virology and Bioemergecy of the ASST. The samples were analysed with the automated BacT/ALERT microbial detection system, and the positive ones were grown in selective agar plates. The identification of the microbial species was carried out by mass spectrometry with MALDI-TOF technology (BioMérieux, Marcy L’Etoile, France), and the antibiogram was performed with the Vitek 2.0 automatic analyser (BioMérieux, Marcy L’Etoile, France), according to the EUCAST (European Committee on Antimicrobial Susceptibility Testing) breakpoints. Since a high prevalence of MRSA in BA was found, as demonstrated by a previous study from the same group, all patients infected with this bacterium received oral antibiotic treatment (Clindamycin 300 mg 4 times a day for 10–14 days), based on the antibiogram [14]. When feasible, abscesses greater than 5 cm were also treated by needle aspiration using the same procedure described for performing the culture examination on the purulent material. To evaluate the feasibility of performing such a procedure, we considered the ultrasound characteristics of the abscess (mainly liquid content) and the clinical examination (perception on palpation). Whenever possible, such a procedure was preferred because of the immediate benefit to the patient and the potential of a faster resolution. However, the dimensions of 3 cm were maintained as a cut off for surgical treatment, as described in literature [20,21,22] whenever the characteristics described above were not considered as fully met. All the analyses were performed using the statistical software SPSS. The qualitative characteristics were described using the absolute frequencies in each category. The quantitative characteristics were described using mean and standard deviation (SD) or median and the interquartile range. The significance of the differences between the study groups was calculated with a Student’s t-test for continuous variables and with the χ2 test for categorical variables. Two-tailed p-values < 0.05 were considered statistically significant. The success of the needle aspiration treatment was estimated by the proportion of abscesses that recovered without resorting to surgical drainage and by the proportion of patients who did not stop breastfeeding. 3. Results The socio-demographic and obstetrical data of the population included in this study are listed in Table 1. Primiparity and vaginal birth were an important feature in this population. Exclusive breastfeeding at diagnosis was present in 51.6% while 54.7% of women used breastfeeding aids at diagnosis. Most of the women developed BA during the first 100 days (68.8% in the first 60 days) after delivery and 13 needed hospitalization. Thirty-four women had fissures, 4 had bilateral abscesses and 16 BA had a US major diameter greater than 5 cm (Table 2). Women with BA < 5 cm and >5 cm were similar in the characteristics analysed (Table 3). In addition, no significant differences in socio-demographic characteristics of patients between the analysed groups were observed (data not shown). All the BA > 5 cm were S. aureus positive; among these, 56% were methicillin-resistant. All patients were treated with antibiotic therapy according to our clinical protocol and 71.9% (46/64) underwent fine needle aspiration. None of them required I&D. The average duration of breastfeeding was 5 months (IR 2; 9.5) and 40.6% of the women continued to breastfeed for more than 6 months (Table 4). The most common microorganism identified was Staphylococcus aureus (n = 58): 55.2% were Methicillin-sensitive Staphylococcus aureus (MSSA) (n = 32) and 44.8% were MRSA (n = 26). Among women who had a cesarean section, the proportion of patients with MRSA infection was significantly greater than MSSA (38.5% vs. 9.4%, p < 0.05), confirmation that recent surgery is a risk factor for MRSA infection, as stated in the WHO “MRSA surviving network” [30]. There were no other differences between the two groups, regarding socio-demographic, clinical and obstetrical features (Table 5 and Table 6). 4. Discussion This is the first Italian observational study about the management of breast abscesses during breastfeeding by a multidisciplinary team. According to previous studies, the primiparity and recent surgery appear to be associated with the development of breast abscesses [15]. The difficulty to start breastfeeding after surgery and the prevalence of microorganisms with antibiotic resistance during the hospitalization were the probable factors of BA occurring during the puerperal period [30]. The difficulty in breastfeeding also resulted in the use of breastfeeding aids by 54.6% of the lactating mothers. Antibiotics and I&D were considered as standard management of breast abscesses up until the early 1990s, after which US-guided interventions became the preferred approach, but there is still no consensus in literature regarding the optimal management of large and multilocular BA. A prospective study, published in Breast, regarding 45 women with lactational BA who were randomly treated with either needle aspiration or I&D, showed that all I&D patients were treated successfully, but 70% of them were not satisfied with the cosmetic outcome. On the other side, in the needle aspiration group, 41% of women did not heal following the procedure and an abscess size larger than 5 cm was identified as a risk factor for failure of the procedure [16]. In another prospective study conducted in 30 women with breast abscesses treated by needle aspiration of pus, oral antibiotics, and repeated aspiration (if necessary), 18 patients required only a single aspiration, 9 patients required multiple aspirations, and 6 patients required incision and drainage (overall cure rate, 82%). The patients in whom needle aspiration was successful had a significantly smaller volume of pus on initial aspiration (4.0 mL versus 21.5 mL, p = 0.002) [31]. However, consistent data and randomized trials in the literature are limited and a Cochrane review published in 2014 stated that there was insufficient evidence to determine whether needle aspiration is a more effective option than I&D for lactational breast abscesses [19]. In addition, BMJ Best Practice published in 2017 suggests that incision and drainage should be reserved for patients in whom aspiration failed and/or for large abscesses (>5 cm in diameter) [11]. However, some recent studies have suggested that the treatment of BA with needle aspiration should be preferred to surgery, regardless of the BA size. A Cameroonian study, published in 2020, enrolled 28 patients diagnosed with lactational breast abscesses, treating them with aspiration and oral antibiotics, and eventually with instillation of ceftriaxone. The study showed that 76% of the patients continued breastfeeding after abscess treatment [25]. In our population, 64.3% of patients continued breastfeeding for more than 3 months. Moreover, Colin et al. published a study reporting that US-guided percutaneous management was successful in 96% of the cases (101/105), regardless of BA size, and allowed continued breastfeeding [23]. Results from a recent retrospective pilot study, published in 2021, including 28 patients with diagnosis of lactational BA and managed by US guided aspiration as first line therapy, showed that a single aspiration was sufficient in 64.3% of the cases, that there were no differences in size of abscesses between patients receiving needle aspiration alone and those who have undergone surgery (p = 0.97), that patients who had been managed by needle aspiration continued breastfeeding after the treatment and 40% of the patients were still breastfeeding at 6 months [32]. Moreover, in the largest single study published, which evaluated 151 breast abscesses (lactational and non- lactational) treated with US-guided drainage, 86 (97%) out of 89 patients with puerperal abscesses recovered after the first round of ultrasound-guided drainage [33]. In our study, all patients were treated with safe oral antibiotics during breastfeeding and 71.9% underwent fine needle aspiration. None of them required I&D. The average duration of breastfeeding was 5 months (IR 2; 9.5) and 40.6% of women with BA continued to breastfeed for more than 6 months (64.3% for more than 3 months). We confirm that the main pathogen was S. aureus (90%) with a methicillin-resistance in 56% of BA > 5 cm. Recurrences occurred in nine patients treated with antibiotics and needle-aspiration. There were 6 primiparous and 4 of them needed hospitalization. In addition, 50% of them were due to MRSA, the other 50% to MSSA. These BA developed in women previously treated for mastitis with an inadequate antibiotic therapy or in women in whom breastfeeding was inadequately suspended. This suggests that there could be a correlation between these factors and BA, but this needs to be further investigated. In the clinical practice, we do not recommend interrupting breastfeeding during the acute phase in order not to worsen the clinical condition and not to favour relapses. Following our results, regardless of size and clinical features of BA, we suggest a conservative and multidisciplinary approach with antibiotic therapy based on the MRSA prevalence and needle aspiration, if necessary. Our study reports the data collected from a relatively significant number of cases, and the execution of microbiological tests based on bacterial cultures allowed us to perform targeted antibiotic therapy in all our patients. This kind of diagnostic-therapeutic approach promotes healing and above all allows mothers to continue breastfeeding, as demonstrated by the fact that more than 40% of the women in our study continued to breastfeed for more than 6 months. On the other hand, an important limit of the study is that we have not standardized the clinical and ultrasound parameters for evaluating a breast abscess. This is in part due to the fact that often they are “emergency-urgency” situations in which ultrasound tests were carried out by the medical personnel attending the patient and not by radiologists. The US were performed in the emergency department with an office ultrasound equipment in order to rapidly assess the need to be drained. Other limitations of the study are the fact that it is a retrospective study and that we lost some patients in the follow up. In addition, a limitation of the study is that we could not analyse the correlation between the time point at which BA occurred with socio-demographic and obstetrical data (no data available). This could be an interesting aim for a future study because exploring this relationship could be helpful for prediction. However, our retrospective study has suggested that needle aspiration may be performed, regardless of the BA size and characteristics, in more patients than previously thought and avoid the surgical procedure of I&D. It also allowed us to check accurately the microorganisms in the abscess material aspirated and target the antibiotic therapy. Such preliminary observations would require a confirmation by a controlled study. 5. Conclusions In our experience, treatment with needle aspiration of BA in breastfeeding women is a cost-effective method for many reasons. Unlike incision and drainage, it is an outpatient procedure, easily repeatable, with no cosmetic damage and potentially lower risk of recurrences. In addition, it is cheaper because it does not require the use of operating rooms and hospitalization. Moreover, needle aspiration is less painful, does not require the separation of the mother–child dyad and allows a quicker, if not immediate, restart of breastfeeding. In addition, it is advisable to treat breast abscesses in referral centers, where patients are managed by a multidisciplinary team. Acknowledgments The authors thank the staff at the study site for their continuous support. Author Contributions Conceptualization, P.P. and A.S.; Formal analysis, M.I.M. and S.G.; Investigation, M.I.M., S.G., G.P., A.P., A.V., L.B. and S.R.; Methodology, P.P. and A.S.; Software, M.I.M. and S.G.; Validation, P.P., I.C. and A.S.; Writing—original draft, M.I.M.; Writing—review and editing, M.I.M., A.S. and S.G. 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 hospital rules after obtaining consent for privacy. No biological material has been stored. 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 privacy. Conflicts of Interest The authors declare no conflict of interest. ijerph-19-05762-t001_Table 1 Table 1 Socio-demographic and obstetrical characteristics. Population (n = 64) Age (years) 33.07 ± 6.99 Smoking (%) (n) 1.6 (1) BMI (kg/m2) 22.2 ± 3.9 Marital status - Married (%) (n) - Unmarried (%) (n) - Unknown (%) (n) 50 (32) 26.6 (17) 23.4 (15) Educational qualification: - Degree (%) (n) - High school diploma (%) (n) - Secondary school diploma (%) (n) - Unknown 46.9 (30) 23.4 (15) 7.8 (5) 21.9 (14) Parity - Primiparous (%) (n) - Multiparous (%) (n) 81.2 (52) 18.8 (12) Gestational age at birth (weeks) 39.3 ± 1.4 Pregnancy onset - Spontanous (%) (n) - ART (Assisted Reproductive Technology) (%) (n) 93.7 (60) 6.3 (4) Mode of delivery - Cesarean section (%) (n) - Vaginal birth (%) (n) 23.4 (15) 76.6 (49) Birthweight (g) 3241.5 ± 421.5 Sex of newborn - F (%) (n) - M (%) (n) 51.6 (33) 48.4 (31) Breastfeeding at birth - Exclusive (%) (n) - Complementary (%) (n) - Unknown (%) (n) 53.1 (34) 21.9 (14) 25 (16) Breastfeeding at diagnosis - Exclusive (%) (n) - Complementary (%) (n) - Unknown (%) (n) 51.6 (33) 40.6 (26) 7.8 (5) Use of breastfeeding aids at diagnosis (breast pump, nipple shilds) 54.7 (35) Data expressed as mean ± SD and %. ijerph-19-05762-t002_Table 2 Table 2 Clinical characteristics. Population (n = 64) Days between birth and diagnosis (n) 35 [25.25; 58.75] BA developed in the first 60 days (%) (n) 68.8 (44) Fissures (%) (n) 53.1 (34) Concurrent diseases (candidiasis, vasospasm) (%) (n) 6.3 (4) Hospitalization (%) (n) 20.3 (13) Bilateral abscesses (%) (n) 6.3 (4) Abscesses > 5 cm (%) (n) 25 (16) Data expressed as median and IQR and %. ijerph-19-05762-t003_Table 3 Table 3 Clinical and microbiological characteristics of patients compared by the size of abscess. Abscess < 5 cm (n = 24) Abscess > 5 cm (n = 16) Days between delivery and diagnosis (n) 34.5 [25; 58.25] 35 [25.25; 58.75] Fissures (%) (n) 58.3 (14) 43.7 (7) Concurrent patologies (vasospasm, candidiasis) (%) (n) 4.5 (1) 6.2 (1) Hospitalization (%) (n) 8.3 (2) 43.7 (7) Bilateral abscesses (%) (n) 8.3 (2) 12.5 (2) Fine needle aspiration (%) (n) 62.5 (15) 87.5 (14) Culture examination—Bacteria - S. aureus (%) (n) - Not S. aureus (%) (n) 79.2 (19) 20.8 (5) 100 * (16) 0 (0) Antimicrobial resistances - MRSA (%) (n) - MSSA (%) (n) - Others (%) (n) - No resistences (%) (n) 37.5 (9) 37.5 (9) 12.5 (3) 12.5 (3) 56.2 (9) 37.5 (6) 0 (0) 6.3 (1) Note: data expressed as median and IQR and %. Significance: Student’s t-test and ꭓ2 analysis; * p < 0.05. ijerph-19-05762-t004_Table 4 Table 4 Follow up—breastfeeding duration. Population (n = 64) Lost at follow up 5 n = 59 Breastfeeding duration - <3 months (%) (n) - 3–6 months (%) (n) - >6 months (%) (n) - >12 months (%) (n) 35.7 (21) 23.7 (14) 20.3 (12) 20.3 (12) Breastfeeding duration (months) 5 [2; 9.5] Weaning (months) 5.355 ± 2.09 Recurrences (%) (n) 15.2 (9) Data expressed as median and IQR, mean ± SD and %. ijerph-19-05762-t005_Table 5 Table 5 Socio-demographic and obstetric features of patients with S. aureus infection. MSSA (n = 32) MRSA (n = 26) Age (years) 32.3 ± 5.1 33.5 ± 9.0 Smoking (%) (n) 0 (0) 3.8 (1) BMI (kg/m2) 22.5 ± 4.1 22.3 ± 4.5 Mode of delivery - Vaginal birth (%) (n) - Cesarean section (%) (n) 90.6 (29) 9.4 (3) 61.5 (16) 38.5 * (10) Exclusive breastfeeding at birth (%) (n) 71.9 (23) 42.3 (11) Breastfeeding at diagnosis - Exclusive (%) (n) - Complementary (%) (n) - No breastfeeding (%) (n) 65.6 (21) 31.2 (10) 3.2 (1) 46.1 (12) 38.5 (10) 15.4 (4) Use of breastfeeding aids (breast pump, nipple shilds) (%) (n) 50 (16) 57.7 (15) Data expressed as mean ± SD and %. Significance: Student’s t-test and ꭓ2 analysis; * p < 0.05. ijerph-19-05762-t006_Table 6 Table 6 Clinical features of patients with S. aureus infection. MSSA (n = 32) MRSA (n = 26) Days between birth and diagnosis (n) 34 [25; 54] 34.5 [25.25; 56] Fissures (%) (n) 59.4 (19) 42.3 (11) Concurrent diseases (vasospasm, candidiasis) (%) (n) 3.1 (1) 3.8 (1) Hospitalization (%) (n) 21.9 (7) 23.1 (6) Bilateral abscesses (%) (n) 6.2 (2) 7.7 (2) Abscesses > 5 cm (%) (n) 21.9 (7) 34.6 (9) Data expressed as median and IQR and %. Significance: Student’s t-test and ꭓ2 analysis. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. WHO Global Strategy for Infant and Young Child Feeding 2003 Available online: https://www.who.int/nutrition/topics/global_strategy/en/ (accessed on 22 December 2021) 2. UNICEF Breastfeeding. A Mother’s Gift, for Every Child 2018 Available online: https://www.healthynewbornnetwork.org/resource/breastfeeding-a-mothers-gift-for-every-child/ (accessed on 20 June 2019) 3. ACOG Committee Opinion No. 756. Optimizing Support for Breastfeeding as Part of Obstetric Practice Obstet. Gynecol. 2018 132 E187 E196 10.1097/AOG.0000000000002890 30247365 4. American Academy of Pediatrics Breastfeeding and the Use of Human Milk Pediatrics 2012 129 E827 E841 10.1542/peds.2011-3552 22371471 5. Victora C.G. Bahl R. Barros A.J. França G.V.A. Horton S. Krasevec J. Murch S. Sankar M.J. Walker N. Nigel C.R. Breastfeeding in the 21th century: Epidemiology, mechanisms, and lifelong effect Lancet 2016 387 475 490 10.1016/S0140-6736(15)01024-7 26869575 6. Chung M. Raman G. Chew P. Magula N.P. Breastfeeding and maternal and infant health outcomes in developed countries Evid. Rep. Technol. Assess. 2007 153 1 186 7. UNICEF WHO Tracking Progress for Breastfeeding Policies and Programmes 2017 Available online: https://www.ennonline.net/nex/9/trackingbfpoliciesprogrammes (accessed on 14 July 2019) 8. Abedi P. Jahanfar S. Namvar F. Lee J. Breastfeeding or nipple stimulation for reducing postpartum haemorrhage in the third stage of labour Cochrane Database Syst. Rev. 2016 2016 CD010845 10.1002/14651858.CD010845.pub2 26816300 9. Pileri P. di Bartolo I. Mazzocco M.I. Casazza G. Giani S. Cetin I. Savasi V.M. Breastfeeding: Biological and Social Variables in Different Modes of Conception Life 2021 11 110 10.3390/life11020110 33535450 10. Amir L.H. The Academy of Breastfeeding Medicine Protocol Committee ABM Clinical Protocol #4: Mastitis, Revised March 2014 Breastfeed. Med. 2014 9 239 243 24911394 11. BMJ Best Practice Mastitis and breast abscess Br. Med. J. 2017 Available online: https://bestpractice.bmj.com/topics/en-gb/1084 (accessed on 20 May 2019) 12. Dabbas N. Chand M. Pallett A. Royle G.T. Sainsbury R. Have the organisms that cause breast abscess changed with time?—Implications for appropriate antibiotic usage in primary and secondary care Breast J. 2010 16 412 415 10.1111/j.1524-4741.2010.00923.x 20443790 13. 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Ruolo della Mammografia, dell’Ecografia e della RM nella diagnosi delle Lesioni Mammarie in Gravidanza ed Allattamento: Revisione della letteratura e nostra esperienza G. Ital. Di Radiol. Med. 2015 2 853 863 19. Irusen H. Rohwer A.C. Steyn D.W. Young T. Treatments for breast abscesses in breastfeeding women Cochrane Database Syst. Rev. 2015 8 CD010490 10.1002/14651858.CD010490.pub2 20. Benson E. Management of breast abscesses World J. Surg. 1989 13 753 756 10.1007/BF01658428 2696229 21. Son E.J. Oh K.K. Kim E.K. Pregnancy-Associated Breast Disease: Radiologic Features and Diagnostic Dilemmas Yonsei Med. J. 2006 47 34 42 10.3349/ymj.2006.47.1.34 16502483 22. Lam E. Chan T. Wiseman S. Breast abscess: Evidence based management recommendations Expert Rev. Anti. Infect 2014 12 753 762 10.1586/14787210.2014.913982 23. Colin C. Colin C. Breast abscesses in lactating women: Evidences for ultrasound-guided percutaneous drainage to avoid surgery Emerg. 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Causes and Mangaement World Health Organization Geneva, Switzerland 2000 29. World Health Organization Statement on Maternal Sepsis World Health Organization Geneva, Switzerland 2017 30. MRSA Survivors Network Available online: https://mrsasurvivors.org (accessed on 17 December 2021) 31. Schwarz R.J. Shrestha R. Needle aspiration of breast abscesses Am. J. Surg. 2001 182 117 119 10.1016/S0002-9610(01)00683-3 11574080 32. Rigourd V. Benoit L. Paugam C. Driessen M. Charlier C. Bille E. Pommeret B. Leroy E. Murmu M.S. Guyonnet A. Management of lactating breast abscesses by ultrasound-guided needle aspiration and continuation of breastfeeding: A pilot study J. Gynecol. Obstet. Hum. Reprod. 2022 51 102214 10.1016/j.jogoh.2021.102214 34469779 33. Christensen A.F. Al-Suliman N. Nielsen K.R. Vejborg I. Severinsen N. Christensen H. Nielsen M.B. Ultrasound-guided drainage of breast abscesses: Results in 151 patients Br. J. Radiol. 2005 78 186 188 10.1259/bjr/26372381 15730981

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==== Front Sensors (Basel) Sensors (Basel) sensors Sensors (Basel, Switzerland) 1424-8220 MDPI 10.3390/s22093257 sensors-22-03257 Article Study of Model Uncertainties Influence on the Impact Point Dispersion for a Gasodynamicaly Controlled Projectile https://orcid.org/0000-0002-7173-0890 Jacewicz Mariusz https://orcid.org/0000-0002-8866-7293 Lichota Piotr https://orcid.org/0000-0003-0109-7265 Miedziński Dariusz * https://orcid.org/0000-0002-2389-7653 Głębocki Robert Savkin Andrey V. Academic Editor Division of Mechanics, Institute of Aeronautics and Applied Mechanics, Warsaw University of Technology, Nowowiejska 24, 00-665 Warsaw, Poland; mariusz.jacewicz@pw.edu.pl (M.J.); piotr.lichota@pw.edu.pl (P.L.); robert.glebocki@pw.edu.pl (R.G.) * Correspondence: dariusz.miedzinski2.dokt@pw.edu.pl; Tel.: +48-22-234-5814 24 4 2022 5 2022 22 9 325723 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/). The article presents the analysis of the impact point dispersion reduction using lateral correction thrusters. Two types of control algorithms are used and four sources of uncertainties are taken into account: aerodynamic parameters, thrust curve, initial conditions and IMU errors. The Monte Carlo approach was used for simulations and Circular Error Probable was used as a measure of dispersion. Generic rocket mathematical and simulation model was created in MATLAB/Simulink 2020b environment. Results show that the use of control algorithms greatly reduces the impact point dispersion. flight simulation dispersion analysis rocket pulse jet control ==== Body pmc1. Introduction Determining and lowering the impact point dispersion of an artillery projectile is an important factor when determining its usefulness and effectiveness. Due to the imperfections of modelling of the flight of such objects, unknowns, simplifications, and uncertainties in model parameters, it is important to take into account the various possibilities of scenarios and determine and quantify the dispersion of possible landing points. Key factors influencing the flight of the object, and the hardest to obtain accurately for modelling, are the aerodynamic characteristics, thrust curve, and initial conditions. To maximize the accuracy of the projectile, various types of control methods, algorithms, and target detection methods are utilized, such as H∞ guidance law [1], proportional navigation guidance and its modifications [2,3], various optimal control methods [4,5,6,7] or model predictive approach [8]. In [9,10] the impact point dispersion of a lateral pulse jet controlled rocket following a reference trajectory and its robustness to the effects of the measurement noise were studied. Launch conditions’ uncertainties were studied in [11,12]. In [13,14] the impact point dispersion due to manufacturing errors using Monte Carlo method was studied. In [15] the effects of launch condition variability, atmospheric factors, and IMU errors on the guidance accuracy were investigated. The influence of missile initial conditions’ uncertainties and IMU errors on the impact point dispersion using lateral thrusters for control were investigated in [16] and the influence of uncertainties in rocket parameters on the performance of a cold launch were analyzed in [17]. IMU errors and noise impact on the guidance were also investigated in [18,19]. The analysis of the robustness of the control algorithm with respect to uncertainty regarding the launch environment and rocket conditions was presented in [20,21]. Monte Carlo analysis of the impact point dispersion due to the missile parameters and atmospheric conditions’ uncertainties was performed in [22] and the impact point dispersion reduction due to high spin motion was analyzed in [23]. In this paper, the analysis of the impact point dispersion caused by model uncertainties is presented. The uncertainties in the aerodynamic parameters, thrust curve, and initial conditions, as well as the uncertainties caused by the Inertial Measurement Unit model and its errors are analyzed. Two types of control algorithms were tested, Multi-Condition Control Algorithm (MCCA) and modified Proportional Navigation Guidance (mPNG). The analysis was performed using the Monte Carlo approach. The prepared article is organised as follows: in Section 2 the mathematical model of the rocket is presented in the Section 2.1 with used assumptions and coordinate systems. The dynamic equations of motion, followed by additional kinematic equations are shown in that section. The external loads comprised of aerodynamics, gravity, propulsion, and correction thrusters are presented, and this is followed by the description of inertial parameters, atmosphere, and Inertial Measurement Unit modelling approach. At last, the used control algorithms are shown. In Section 2.2 the simulational model created in MATLAB/Simulink R2020b is presented. Section 3 presents the simulational study and its results, followed by the discussion and interpretation. The paper finishes with a short summary of the conclusions shown in Section 4. The novelty in this paper is the comparison of the IMU errors’ influence on the accuracy of the two control algorithms utilizing lateral pulse jet control. The developed numerical simulation might be used in design process of new sensors intended for projectile navigation. This tool might be used for fast prototyping of control schemes that reduces the overall system design process and costs. 2. Materials and Methods 2.1. Mathematical Model 2.1.1. Assumptions For creating a mathematical and simulational model of a generic rocket, several assumptions were made. The rocket is modelled as a rigid body with six degrees of freedom and variable inertial parameters. It is controlled by a set of solid rocket motor thrusters, which use does not change the inertial and aerodynamic parameters of the rocket. Atmosphere model is taken from the International Standard Atmosphere [24]. Earth rotation and eccentricity are not modelled, the gravitational acceleration is constant and consistent with WGS-84 model [25]. The mathematical model includes the Inertial Measurement Unit (IMU) comprised of accelerometers and gyroscopes triades, modelled as second-order dynamical systems, with their disturbances that include noise, bias, scale factor and cross coupling as well as g-dependent factor for gyroscopes. 2.1.2. Coordinate Systems The coordinate systems used are presented in Figure 1:The navigational coordinate system Onxnynzn is a right-handed, Cartesian coordinate system fixed to earth. Its origin is located at any point and the Onxnyn plane is tangent to the surface of the earth. The Onxn axis points in the direction of a launch rail, Onzn axis in the direction of the gravitational acceleration and Onyn axis completes the right-handed coordinate system. The gravitational coordinate system Ogxgygzg is a right-handed, Cartesian moving coordinate system fixed with the rocket. Its origin is located at the center of mass of the rocket and the whole system remains parallel to the navigational system during the whole flight of the rocket. The body coordinate system Obxbybzb is a right-handed Cartesian coordinate system. Its origin is located at any point of the rocket. The Obxb axis is parallel to the rockets longitudinal axis and points forward, Obyb axis points at the right wing and Obzb axis completes the right-handed coordinate system. Orientation of the body coordinate system with respect to the gravitational coordinate system is described by the Euler angles of yaw Ψ, pitch Θ and roll Φ. The measuring coordinate system Oexeyeze is a right-handed, Cartesian coordinate system fixed with the airflow. Its origin is located at any point of the Obybzb symmetry plane and the position of that point with respect to the Obxbybzb coordinate system is defined by the vector re. The Oexe axis lies in the direction of the airflow, Oeze axis points upwards and the Oeye axis points to the right. The aerodynamic coordinate system Oaxayaza is the right-handed Cartesian coordinate system fixed with the airflow. The Oaxa axis points in the opposite direction that the airflow, Oaza axis points downwards and the Oaya completes the right-handed coordinate system. 2.1.3. Dynamic Equations of Motion For developing the dynamic equations of motion, the linear and angular momentum change theorems for the rigid body were used. In the non-inertial frame Obxbybzb with the origin not located at the center of mass, they are given as [26,27]:(1) δ˜Πδ˜t+Ω×Π=Fb (2) δ˜K0δ˜t+Ω×K0+Vb×Π=Mb where Vb=UVWT is the velocity vector, Ω=PQRT is the angular velocity vector, Fb=XbYbZbT is the vector of external forces acting on the object, Mb=LbMbNbT is the vector of external torques with respect to point Ob and δ˜δ˜t is the local derivative. Linear and angular momentum for a rigid body are [26]:(3) Π=mVb+Ω×rC (4) K0=IΩ+rC×mVb where m is the instantaneous mass of the rocket, I is the instantaneous moment of inertia tensor and rC is the center of mass position with respect to Ob. The dynamic equations of motion can be written as:(5) mV˙b+Ω˙×S+Ω×mVb+Ω×Ω×S=Fb (6) IΩ˙+S×V˙b+I˙Ω+Ω×IΩ+Ω×S×Vb+Vb×Ω×S=Mb where S=mrC is the first moment of mass. It must be noted that the propulsion terms resulting from expelling of the propellant by the main motor is included on the right side of above-mentioned equations. In the moments equations the jet damping effect was also omitted because for rocket artillery projectiles it is rather small when compared to aerodynamic damping. After changing cross-products to matrix multiplication, using the skew-symmetric matrix notation, []x, this can be written as:(7) m1−[S]x[S]xIV˙bΩ˙+000I˙VbΩ+[Ω]x0[Vb]x[Ω]xm1−[S]x[S]xIVbΩ=FbMb where 0 is the zero matrix and 1 is the unit matrix. In the short form this is:(8) Ax˙+A˙x+ωAx=FB where the state vector has the form x=UVWPQRT. This equation can be then numerically integrated to obtain the state vector. 2.1.4. Orientation For determining object orientation, the quaternion algebra was used. Quaternion describes the orientation of the object in terms of rotation around a specific axis and is written as [28,29]:(9) e=e0+e1i+e2j+e3k where e0,e1,e2,e3 are the real numbers and i,j,k are the axes versors. The real parts of the quaternion can be written in terms of rotation axes direction cosines Ex,Ey,Ez and rotation angle δE and are presented in Equations (10)–(). (10) e0=cosδE2 (11) e1=ExsinδE2 (12) e2=EysinδE2 (13) e3=EzsinδE2 The kinematic equation for the rate of change of the quaternion is given as [29,30]:(14) e˙0e˙1e˙2e˙3=−120PQR−P0−RQ−QR0−P−R−QP0e0e1e2e3−kEe0e1e2e3 where k is the feedback coefficient and E is the bounding equation violation coefficient E=|e|2−1. It was assumed that k=1. Quaternions can be used to calculate the transformation matrix from the body to the navigation coordinate system as [29]:(15) Λ=e02+e12−e22−e322(e1e2−e0e3)2(e0e2+e1e3)2(e0e3+e1e2)e02−e12+e22−e322(e2e3−e0e1)2(e1e3−e0e2)2(e0e1+e2e3)e02−e12−e22+e32 and orientation angles of roll, pitch, and yaw, given as [29,30]: (16) Φ=arctan2(e0e1+e2e3)e02−e12−e22+e32 (17) Θ=arcsin2(e0e2−e1e3) (18) Ψ=arctan2(e0e3+e1e2)e02+e12−e22−e32 Using the transformation matrix from (15) can be used in the second kinematic equation bounding linear velocities in On coordinate system with velocities in Ob coordinate system. (19) x˙ny˙nz˙n=ΛUVW The initial quaternion can be determined from the initial orientation angles by means of equations [29,30,31]: (20) e0=cosΦ2cosΘ2cosΨ2+sinΦ2sinΘ2sinΨ2 (21) e1=sinΦ2cosΘ2cosΨ2−cosΦ2sinΘ2sinΨ2 (22) e2=cosΦ2sinΘ2cosΨ2+sinΦ2cosΘ2sinΨ2 (23) e3=cosΦ2cosΘ2sinΨ2−sinΦ2sinΘ2cosΨ2 2.1.5. External Loads The motion of the object is caused by the external forces and torques from aerodynamics Fa and Ma, gravity Fg and Mg, thrust Fs and Ms and reaction thrusters Fsk and Msk [16]: (24) Fb=Fa+Fg+Fs+Fsk (25) Mb=Ma+Mg+Ms+Msk 2.1.6. Aerodynamics Aerodynamic force and moment vectors are given with respect to point Oe, so with respect to point Ob they are given as:(26) Fa=XaYaZa (27) Ma=LaMaNa=Ma,Oe+re×Fa where re=rwe−rwC+rC is the vector describing the location of point Oe with respect to point Ob, rwe is the position of point Oe with respect to rocket’s base and rwC is the position of point Ob with respect to the rocket’s base. Aerodynamic force and moment are given as:(28) Fa=12ρ|Vb|2SCX(α,β,Ma)CY(α,β,Ma)CZ(α,β,Ma) (29) Ma,Oe=12ρ|Vb|2SdCl(α,β,Ma)Cm(α,β,Ma)Cn(α,β,Ma) where ρ is the air density, S is the rocket’s cross section area and d is the rocket’s diameter. Aerodynamic incidence angles are given as [29,30]: (30) α=arctanWU (31) β=arcsinV|Vb| (32) Ma=|Vb|a where α is the angle of attack, β is the sideslip angle, and Ma is the Mach number given in (), where a is the local speed of sound. The aerodynamic coefficients are [9,32]:(33) CX=(CXbase0+CXbaseα2α2+CXbaseβ2β2)+(CXeng0+CXengα2α2+CXengβ2β2)δengCY=CY0+CYββCZ=CZ0+CZααCl=Cl0+(Clp0+Clpα2α2+Clpβ2β2)Pd2|Vb|Cm=Cm0+CmααCn=Cn0+Cnββ where CX0 is zero-longitudinal axial force coefficient, CYβ is side force with angle of sideslip derivative, CZα is normal force with respect to angle of attack derivative, Cl0 is spin driving rolling moment coefficient and Clp is spin damping derivative. Cmα is pitching moment with respect to angle of attack derivative, Cnβ is yawing moment derivative with respect to sideslip angle. Cmq is pitching moment coefficient derivative with pitch rate and Cnr is yawing moment coefficient derivative with yaw rate. δe is the parameter that describes the main motor state (δe=0 for active phase of flight and δe=1 after main motor burnout, for gliding flight). When the main motor operates the projectile base drag is lower than after main motor burnout. CX0 was obtained for two system configurations (main motor on/off) and δe is used in a simulation to switch between aerodynamic data tables. Aerodynamic coefficients were obtained using commercially available software PRODAS (Projectile Rocket Ordnance Design & Analysis System). These coefficients were implemented into the Simulink model using Lookup-Table methodology. The aerodynamic coefficients are presented in Figure 2. 2.1.7. Gravity Gravitational acceleration vector in the gravitational coordinate system is given as g=00g0T. Gravitational acceleration is assumed constant and consistent with WGS-84 reference model [25], i.e., g0=9.80665 m/s2. Gravitational force and torques are given as:(34) Fg=Tbgm00g0 (35) Mg=rC×Fg where Tbg is the transformation matrix from gravitational to body coordinate system, given as:(36) Tgb=cosΘcosΨcosΘsinΨ−sinΘsinΦsinΘcosΨ−cosΦsinΨsinΦsinΘsinΨ+cosΦcosΨsinΦcosΘcosΦsinΘcosΨ+sinΦsinΨcosΦsinΘsinΨ−sinΦcosΨcosΦcosΘ 2.1.8. Thrust Thrust vector, which can deviate from the rocket’s longitudinal axis by angle ΘT in pitch plane and ΨT in the yaw plane, is given as [16]:(37) Fs=Fp(t)cosΘTcosΨTcosΘTsinΨT−sinΨT where Fp(t) is the instantaneous value of the thrust force. Torque from the thrust force with respect to Ob is given as:(38) Ms=(−rwC+rC)×Fs 2.1.9. Correction Thrusters For the gasodynamic control system comprised of a set of identical correction thrusters placed radially in a set of parallel layers, the thrust and torque from the thrusters are given as:(39) Fski,j=Fpsk(t)0sinΦi,j−cosΦi,j (40) Mski,j=rski,j−rwC+rC×Fski,f where Fpsk(t) is the instantaneous thrust force of the thruster, index i=1,⋯,M is the layer number, index j=1,⋯,N is the number of a thruster in a particular layer, Φi,j is the azimuth angle of a thruster is a particular layer, rski,j is the vector describing the position of the layer with respect to the rocket’s base, measured from the base in the direction of the rocket’s axis. The total force and torque generated by the gasodynamic control system is given as: (41) and (42) (41) Fsk=∑i=1M∑j=1NFski,j (42) Msk=∑i=1M∑j=1NMski,j For the simulation purposes it was assumed that the projectile is equipped in a modular unit (Figure 3) composed from 32 solid propellant lateral thrusters and placed before the center of mass of the missile. These thrusters are set into a 4 arrays with 8 motors in each layer. Each of the thrusters might by used only once. The mass of the propellant in the single motor is approximately 0.005 kg so it is reasonable to assume that the ignition does not influence the mass and inertia projectile properties. The aerodynamic interference effects of the thrusters with the external flow were also omitted. 2.1.10. Inertial Parameters The instantaneous mass of the rocket is given as:(43) m(t)=m0−mpIc∫t0tFp(t)dt where m0 is the starting mass of the rocket at time t0, mp is the mass of the propellant and Ic is the total impulse given as:(44) Ic=∫t0tkFp(t)dt where tk is the time of propellant burnout. During the powered flight, the rocket’s mass center position vector rwC measured from the rocket’s base is changing according to:(45) rwC=xcg(t)=xcg0−xcg0−xcgkIc∫t0tfp(t)dt00 where xcg0 is the center of mass position on the Obxb axis during launch and xcgk is the center of mass position on the Obxb axis after the propellant burnout. The change of moments of inertia can be express as:(46) Iij(t)=Iij0−Iij0−IijkIc∫t0tFp(t)dt where Iij0 is the moment of inertia tensor component during launch and Iijk is the moment of inertia tensor component after the propellant burnout. 2.1.11. Atmosphere Model The air density, temperature, and the speed of sound are calculated according to the International Standard Atmosphere model [24]. (47) ρ=ρ01−h443004.256 (48) T=T0−0.0065h (49) a=a0T288 The reference values of these thermodynamic parameters are taken for the troposphere: ρ0=1.225 kg/m3, T0=288.15 K, a0=340.3 m/s and h=−zn is the height in meters. It was assumed that the flight take place in the steady state atmosphere (wind speed was set to 0 m/s). 2.1.12. Inertial Measurement Unit Model It was assumed that the rocket’s is equipped with the strapdown Inertial Measurement Unit with the three-axis accelerometer and three-axis gyroscope, and these are the only sources of information about rocket position, velocity and orientation. Abovementioned design requirements are quite difficult to fullfill due to errors. Pure inertial navigation has a tendency due to drift. These drift errors might be reduced using integration with GPS receivers. Also, additional sensors like might be used to improve the system acccuracy. Magnetometers measurement are imprecise because the projectile and launcher structure are made from steel alloys. The IMU is intended for a projectile that spins about the longitudinal axis of symmetry. Photodiode sensors could be used to measure the projectile roll rate. An example of IMU that is suitable for the considered application is Micro-Electro-Mechanical-Systems based HG1930. The mass of this device is approximately 0.16 kg and power consumption less than 3 W. The operating temperature range is from −54°C up to +85°C. The gyroscopes ranges are up to 7200 deg/s in the X axis and 1440 deg/s in the Y and Z axes (X axis range must be significanlty higher than Y and Z due to projectile axial spin). Accelerometers operating range is up to 85 g in the X axes and 35 g in the Y and Z axes. High measurement range for X axis results from acceleration caused by main motor. This device requires supply voltage of 5 V. The IMU might be connected with the central onboard computer using military standard RS-422 serial interface. The maximum rate of data transmission for control purposes is 600 Hz. This measurement device is placed in front of the missile center of mass (between main motor unit and lateral thrusters module). Accelerometers model The acceleration of the rocket’s center of mass in Obxbybzb coordinate system is:(50) a=axayaz=Fbm In the general case, the accelerometer position need not to coincide with the center of mass of the rocket. Therefore, the center of mass acceleration must be recalculated to the point of accelerometers’ mounting:(51) aIMU=a+Ω×Ω×rwz+Ω˙×rwz−g where rwz=rwC−rIMU is the position of the IMU with respect to center of mass and rIMU is the IMU position with respect to the rocket’s base. As a next step, the model of the sensor’s errors was included, which is comprised of scale factors sx,sy,sz, cross-coupling cxy,cxz,cyz and biases bx,by,bz:(52) a^IMU=sx−cxycxzcxysy−cyz−cxzcyzszaIMU+bxbybz Accelerometer is treated as a second-order dynamic system:(53) ameas=ωnacc2s2+2ξaccωnaccs+ωnacc2a^IMU where ξacc is the accelerometer damping coefficient and ωnacc is the accelerometer natural frequency (ξacc=0.707 and ωnacc=7600). The last step was to include the sensor noise, assumed as white noise with known standard deviation and zero mean, and output saturation. Gyroscopes Model The gyroscope output does not depend on the gyroscopes’ position inside the rocket. Therefore, there is no need to transform its output to the center of mass. The gyroscope errors’ model includes scale factor, cross-coupling, bias, and sensitivity to accelerations, given by the gyroscopes’ sensitivity matrix G:(54) ΩIMU=sx−cxycxzcxysy−cyz−cxzcyzszΩ+bxbybz+Gaxayaz Gyroscope is also treated as a second-order system:(55) Ωmeas=ωngyro2s2+2ξgyroωngyros+ωngyro2ΩIMU where ξgyro is the gyroscope damping coefficient and ωngyro is the gyroscope natural frequency (it was assumed that ξgyro=0.356 and ωngyro=7600 Hz). The last step, as with accelerometers, was to include the sensor noise and output saturation. The values of ameas and Ωmeas are sampled with the sensor sample frequency. From the measured angular velocity, the rocket’s orientation is calculated. To obtain the rocket’s velocity, the measured accelerations are firstly recalculated back to the center of mass position:(56) ameas,CG=ameas+Ωmeas×Ωmeas×rwz+Ω˙meas×rwz and then the velocity vector can be obtained by numerical integration:(57) V˙b,meas=ameas,CG−Ωmeas×Vb,meas+Λ00g0T where Vb,meas=[Umeas,Vmeas,Wmeas]T. Velocity vector is expressed in body frame Obxbybzb so it must be transformed to the navigational coordinate system Onxnynzn. The rocket’s position in the navigational coordinate system is calculated by numerical integration of velocity components:(58) x˙n,measy˙n,measz˙n,meas=ΛUmeasVmeasWmeas In order to solve the mentioned earlier navigation equations the initial attitude, velocity and position of the projectile must be known. It was assumed that these parameters are perfectly estimated using initial alignment procedure before the flight. 2.1.13. Control Algorithms Projectiles equipped in solid propellant lateral motors often have very low control authority. It means that the maneuverability of such objects is small. This fact makes the guidance process challenging. For the tests of landing dispersion analysis, two algorithms were created: Multi-Condition Control Algorithm (MCCA) and modified Proportional Navigation Guidance (mPNG). The guidance algorithm used in the MCCA is based on the reference trajectory tracking. This algorithm is discussed in detail in [33]. The main idea behind MCCA is to use the reference trajectory to minimize the hitting error just and the end of flight. Due to limited number of lateral motors it is difficult to track the trajectory along the full flight path. In MCCA approach the position error between reference trajectory and the actual projectile position is minimized after trajectory vertex, during the descending flight. It is assumed that the reference trajectory is calculated prior to launch, so the position of the target is known a priori, and implemented in the rocket’s control system prior to launch. The reference trajectory is calculated for unguided projectile in such a way the missile hits perfectly the target (miss distance at the end of nominal trajectory is 0 m). The guidance algorithm used in the mPNG algorithm is the classical Proportional Navigation Guidance [34] modified by the term accounting for the trajectory bending due to gravity. Both algorithms use the same thrusters’ ignition logic that is presented in [12,16]. Due to the rocket’s high roll angular velocity during the flight, the correction thrusters must be ignited in the right moment, which means when the rocket achieves a certain roll angle. At any moment, only one correction thruster can be ignited. The set of conditions of thrusters’ ignition, common for both algorithms are:Correction thruster was not used already (solid motor thrusters are single-use motors) The time between the last thruster ignition tlast is greater than some limit value τ∈(0;∞) (59) t−tlast>τ The correction thruster must be ignited so that the resultant thrust force was in the direction of the desired lateral displacement [35,36], which means that the absolute value of the difference between the error phase γ and thruster azimuth angle Φi,j diminished by the control prediction times τd and τsk multiplied by the roll angular velocity was lower than some limit value γt. (60) γ−Φi,j−π−P(τd+τsk)≤γt The rocket’s pitch angle must be lower or equal the threshold value Θg and the time of flight must be at least equal to the threshold value tg (61) Θ≤Θg∧t≥tg Additional conditions for the MCCA algorithm:The distance between the rocket’s center of mass and the reference trajectory Γ, measured perpendicular, is greater than some limit value Γt (62) Γ>Γt Additional conditions for the mPNG algorithm:the norm of the commanded value of the lateral acceleration acmd must be greater than the threshold value acmd,g (63) acmd≥acmd,g The parameters of the control laws were determined using the expert method and parametric study: τ=0.2 s, τd=0.001 s, τsk=0.015 s, γt=2.5 deg, Θg=−10 deg (the guidance process starts after trajectory vertex), tg=15 s, Γt=1 m, acmd,g=3 m/s2. 2.2. Simulation Model The mathematical model described in Section 2.1 was implemented in MATLAB/ Simulink 2020b environment. The main Simulink block model of the system is presented in Figure 4. The program simulates the flight of the gasodynamically controlled rocket, calculates the loads from gravity, aerodynamics, thrust, and correction thrusters. It solves the set of ordinary differential equations for the rigid body with 6 degrees of freedom and variable mass. It includes the models of International Standard Atmosphere and Inertial Measurement Unit as well as the inertial navigation equation for determining the rocket’s position, orientation, and velocity. The equations of motion of the projectile were integrated using fixed step, third order Bogacki-Shampine method. The step size was set to 0.0001 s. Simulations were realized using Simulink build in option “Accelerator mode”. Marsenne-Twister algorithm [37] was used to generate in a pseudorandom way the disturbances for the Monte-Carlo simulation. The model was optimized to make the run time as short as possible. The simulation might be realized in a batch mode from the external MATLAB script. 3. Results and Discussion 3.1. Input Data for the Simulation Study A generic rocket model was used for the simulations, which general data are provided in Table 1. The missile is stabilized with four trapezoidal fins. The maximum flight velocity of this projectile is 605 m/s and maximum roll rate 4700 deg/s (these values are obtained in 3 s of flight). The missile was fired at elevation angle 25 deg. Initial velocity was set to 42 m/s and initial roll rate 1073 deg/s. Projectile was fired from the initial position (0, 0, 0) m. The reference trajectory of the projectile (unguided flight) is presented in Figure 5. 3.2. Initial Verification of Control Algorithms As a first step, five deterministic cases were evaluated to test if the prepared control algorithms work as intended: no control, mPNG algorithm with and without IMU model, and MCCA algorithm with and without IMU model. To intentionally introduce aiming error it was assumed that the launch tube is not perfectly aligned with the demanded shoot direction. The initial heading error angle equaled 2 degrees. The position coordinates of the stationary target were set to (9296.54,−7.29,0) m. Table 2 presents the results of the performed cases. The first column describes the used algorithm, with the information whether the IMU model was on. The next columns present the error between the x and y components of the rocket’s and reference trajectories at the impact point, and the distance between the rocket’s landing point and the target position given as ΔR=ΔX2+ΔY2. The results shown in Table 2 indicate that the largest error was obtained for the uncontrolled flight. The projectile landed 324.5 m from the desired point and it is obvious that the target was not achieved (typical radius of destruction for rocket artillery projectiles is order of 20–40 m). Both algorithms work properly and that the mPNG control algorithm lowers the miss distance by about 92% and MCCA algorithm by about 75% on average. The IMU model errors slightly increase the miss distance for both algorithms. 3.3. Monte-Carlo Simulations Next, to test the influence of various uncertainties on the performance of control algorithms and the resulting landing dispersion, a few sets of simulations were performed. Tested were uncertainties in aerodynamic data, thrust parameters, and initial conditions. For every uncertainty, again five cases were simulated: no control, mPNG algorithm with and without IMU model, and MCCA algorithm with and without IMU model. Every case took 1000 runs, using the Monte Carlo method, giving a total of 15 thousand runs. As a merit of accuracy, the Circular Error Probable CEP was used. It gives information about the radius of a circle inside which 50% of landing points are located. 3.3.1. Aerodynamic Parameters Uncertainties The first set of Monte Carlo simulations consisted of uncertainties in aerodynamic data. It was assumed that the normal distribution standard deviation of all aerodynamic parameters was equal to σ=0.2. Next, the maps of impact points were obtained. The Figure 6 presents the results of the performed simulations. On the horizontal axis there is crossrange and on the vertical axis range of the projectile. In the not controlled case, the CEP was equal to 231.14 m. Ideal case of mPNG and MCCA algorithms (IMU model off) achieved 85.6% and 83.1% miss distance reduction respectively and with the IMU model on 84.5% for mPNG and 82.4% for MCCA. Much bigger dispersion is observed along the rocket’s flight path, because the drag coefficient uncertainties have the biggest influence on the range. Small directional dispersion is mostly caused by the IMU model errors. The achieved miss distance reduction for both algorithms were very similar. 3.3.2. Thrust Curve Uncertainties The next set of simulations consisted of uncertainties in the thrust data. For simplicity, it was assumed that the thrust curve can be approximated by the quadrilateral comprised of four characteristic pairs of points, time-thrust, presented in Figure 7. Every point was randomly chosen, using a uniform distribution, between the maximum and minimum allowable values, with additional constraints that the 4th time had to be larger that the 3rd time and that the total impulse of the thrust should lie in between allowable values. The values of the uncertainties are presented in Table 3. In this way a set of pseudorandom thrust curves was obtained as input data for the Monte-Carlo simulations (in each simulation run a different thrust curve was used). The Figure 8 presents the results of the performed simulations. Again, the largest dispersion of the impact points was observed for the uncontrolled projectile. The uncontrolled flight case resulted in CEP of 66.90 m. It means, that thrust uncertainties produce smaller dispersion than uncertainties in aerodynamic parameters. This dispersion is reduced significantly in controlled shoots. Results for mPNG and MCCA algorithms without IMU achieved 92.1% and 89.2% miss distance reduction respectively and with the IMU model on 89.2% for mPNG and 86.7% for MCCA. Again, a bigger dispersion is observed in the longitudinal direction, which thrust uncertainties affect the most. Directional dispersion is a bit lower for the mPNG algorithm. Again, the results for both algorithms lied very close. 3.3.3. Initial Condition Uncertainties The last set of simulations consisted of uncertainties in the initial conditions. The values of the initial linear velocity vector, angular velocity vector, and orientation angles were chosen randomly, using a normal distribution, using set values of standard deviation. The Figure 9 presents the results of the performed simulations. The uncontrolled case resulted in CEP of 67.09 m and the longitudinal and directional dispersion were the same. This is a typical dispersion pattern that is obtained for rocket artillery projectiles at medium elevation angles. Results for mPNG and MCCA algorithms without IMU achieved 95.2% and 80.3% miss distance reduction respectively and with the IMU model on 93.7% for mPNG and 79.1% for MCCA. In this scenario, the miss distance reduction is in favour of the mPNG algorithm with around 10% difference in results. Directional dispersion is more affected by control than the longitudinal, which may arise from the difference in longitudinal and lateral velocity of the rocket. Several new aspects brought by the paper might be mentioned. First, the influence of measurement errors on the resulting projectile miss distance was investigated. Second, two different guidance methods intended for lateral thrusters controlled missiles were compared for idealized and realistic case. From the obtained results it might be concluded that it is possible to achieve CEP order of several meters but to realize this goal the missile must be equipped in high-accuracy IMU. 4. Conclusions Precision guided munition become more and more important in modern military conflicts. To achieve a high direct hit probability the influence of various factors on the resulting dispersion must be understood in detail. In the article, the impact point dispersion, caused by the uncertainties in aerodynamic parameters, thrust curve, initial conditions, and on-board measuring devices, for two types of control algorithms, was presented. Monte Carlo approach was used in the simulations and as the merit of dispersion the CEP was utilized. The results showed that the use of control algorithms greatly reduces the miss distance by more than 80% in most simulated cases. From the simulations it might be concluded that there is possible to achieve CEP smaller than 8 m. For modern guided munition this is quite a realistic result (for example, 160 mm ACCULAR projectile has declared CEP < 10 m). It means that equipping the projectile with control module composed from lateral thrusters allows effectively reduce the impact points dispersion. The uncontrolled projectile might land even 200 m from the intended location in the worst-case scenario. This issue is very important in modern military applications due to the requirement of minimizing the collateral damage. The IMU model causes a slight increase in the dispersion of about 3% in every case. The mPNG algorithm proved to be better for all simulated cases, the greatest difference between the two algorithms was observed in the initial condition case dispersion. The developed numerical simulation might be used in the design of new measurement systems intended for missile navigation. Parametric model allows on rapid implementation of data for other missiles and IMU-s and investigate the dispersion as a function of measurement uncertainties. In this way the overall time and cost of the projectile design might be reduced. Further works might concentrate on flight tests of the real ground-to-ground projectile and validating the model. Also wind tunnel measurements of the missile could be evaluated to obtain the aerodynamic data for a wide range of flight conditions. The influence of wind on the projectile dispersion might be also explored in detail. Hardware-in-the-loop simulation might be also considered to investigate the influence of sensor errors on the projectile hitting accuracy. Author Contributions Conceptualization, R.G. and P.L.; methodology, M.J. and P.L.; software, M.J. and D.M.; validation, M.J. and P.L.; formal analysis, R.G.; investigation, D.M.; resources, D.M. and M.J. and P.L.; data curation, D.M.; writing—original draft preparation, D.M., R.G. and P.L.; writing—review and editing, P.L.; visualization, D.M.; supervision, R.G. and P.L.; project administration, P.L.; funding acquisition, P.L. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by National Centre for Reaserch and Development grant number DOB-SZAFIR/03/B/002/01/2021. 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 Definition of measuring and aerodynamic coordinate systems, and navigational, gravitational and body coordinate systems. Figure 2 Aerodynamic coefficients. Figure 3 Configuration of the lateral thrusters module. Figure 4 Top level architecture of the Simulink simulational model. Figure 5 Projectile trajectory. Figure 6 Results of landing point dispersion with uncertainties of aerodynamic data: (a) no control, (b) mPNG, (c) mPNG + IMU, (d) MCCA, (e) MCCA + IMU. Figure 7 Thrust curve. Figure 8 Results of landing point dispersion with uncertainties of thrust data: (a) no control, (b) mPNG, (c) mPNG + IMU, (d) MCCA, (e) MCCA + IMU. Figure 9 Results of landing point dispersion with uncertainties of initial conditions: (a) no control, (b) mPNG, (c) mPNG + IMU, (d) MCCA, (e) MCCA + IMU. sensors-22-03257-t001_Table 1 Table 1 Generic rocket’s parameters. Parameter Value Unit diameter 122 mm length 1.58 m initial mass 22.14 kg propellant mass 5.83 kg initial moment of inertia Ixx 0.0422 kg·m2 final moment of inertia Ixx 0.0326 kg·m2 initial moment of inertia Iyy 11.223 kg·m2 final moment of inertia Iyy 9.513 kg·m2 initial moment of inertia Izz 11.223 kg·m2 final moment of inertia Izz 9.513 kg·m2 maximum thrust 7277.5 N average thrust 3383.2 N burn time 3.31 s total impulse 13,529 N correction thruster’s thrust 200 N correction thruster’s burn time 0.03 s number of correction thrusters per layer 8 - number of correction thrusters’ layers 4 - sensors-22-03257-t002_Table 2 Table 2 The errors in landing point components. Algorithm ΔX[m] ΔY[m] ΔR[m] None −5.4 324.4 324.5 mPNG −12.3 19.7 23.2 mPNG + IMU −15.3 20.1 25.3 MCCA −32.1 69.8 76.8 MCCA + IMU −32.0 75.2 81.8 sensors-22-03257-t003_Table 3 Table 3 Thrust curve uncertainties. Point Value Time t [s] Thrust T [N] 1 min 0 0 1 max 0 0 2 min 0 3600 2 max 0.15 4400 3 min 1.9 6900 3 max 2.5 8700 4 min 2.1 0 4 max 2.7 0 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Liu L.J. Shen Y. Three-Dimension H∞ Guidance Law and Capture Region Analysis Trans. Aerosp. Electron. Syst. 2012 48 419 429 2. Budiyono A. Rachman H. Proportional Guidance and CDM Control Sythesis for a Short-Range Homing Surface-to-Air Missile J. Aerosp. Eng. 2012 25 168 177 10.1061/(ASCE)AS.1943-5525.0000104 3. Guo Y. Li X. Zhang H. Cai M. He F. Data-Driven Method for Impact Time Control Based on Proportional Navigation Guidance J. Guid. Control. Dyn. 2020 43 955 966 10.2514/1.G004669 4. Chen X. Wang J. Optimal Control Based Guidance Law to Control Both Impact Time and Impact Angle Aerosp. Sci. Technol. 2018 84 454 463 10.1016/j.ast.2018.10.036 5. He S. Lee C.H. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23094963 ijms-23-04963 Article Mono-Sized Anion-Exchange Magnetic Microspheres for Protein Adsorption Wang Zhe 12 Wang Wei 1 Meng Zihui 1 Xue Min 1* Yadav Raghvendra Singh Academic Editor Serrano-Aroca Ángel Academic Editor 1 School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 102488, China; wangzhe@bit.edu.cn (Z.W.); wangwei2020_ripp@126.com (W.W.); mengzh@bit.edu.cn (Z.M.) 2 Academy of National Food and Strategic Reserves Administration, Beijing 100037, China * Correspondence: minxue@bit.edu.cn 29 4 2022 5 2022 23 9 496314 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/). In this study, mono-sized anion-exchange microspheres with polyglycidylmethacrylate were engineered and processed to introduce magnetic granules by penetration–deposition approaches. The obtained magnetic microspheres showed a uniform particle diameter of 1.235 μm in average and a good spherical shape with a saturation magnetic intensity of 12.48 emu/g by VSM and 12% magnetite content by TGA. The magnetic microspheres showed no cytotoxicity when the concentration was below 10 μg/mg. The magnetic microspheres possess respective adsorption capacity for three proteins including Bovine albumin, Hemoglobin from bovine blood, and Cytochrome C. These magnetic microspheres are also potential biomaterials as targeting medicine carriers or protein separation carriers at low concentration. magnetic microspheres surface embedding magnetic separation protein adsorption Natural Science Foundation of China21874009 This research was funded by the Natural Science Foundation of China, grant number 21874009. ==== Body pmc1. Introduction The purified proteins play a crucial role in the research of protein on life activities, such as catalytic metabolic reactions and growth control. However, current separation and purification methods are tedious and time-consuming [1,2,3], such as affinity chromatography, dialysis, salting, and ultrafiltration. Magnetic separation technology has potential in protein purification due to its advantages of easy operation and rapid separation [4,5,6]. Magnetic microspheres are composite material particles [6,7] consisting of both inorganic magnetic materials providing magnetism and organic active functional groups carrying affinity ligand to target on the surface. Magnetic microspheres have been successfully used for the separation of proteins [8,9,10] based on the interaction between protein and functional groups or special ligands on the microspheres, including electrostatic adsorption and specific adsorption. Moreover, magnetic microspheres modified with affinity ligands may have high selectivity to the target proteins, but the available ligands are limited and relative expensive [11,12]. Some commercial magnetic beads modified with monoclonal antibodies were successfully used for target substances identification, especially in diagnosis. However, the high cost, the tedious modification process, and the difference in separation effect severely limit their widespread application. Magnetic polymer microspheres could be synthesized by several methods. The embedding method [13] is typically applied in the preparation of magnetic microspheres with a magnetic shell, which is simple and easy to carry out, but results in the magnetic particles with irregular shapes and polydisperse states. The emulsion polymerization method [14] provides monodispersed magnetic microspheres, but the small grain size beads below l.0 μm that exhibit higher separation efficiency under magnetic field are hard obtain. An in situ method [15] is a way to obtain the magnetic nanocomposite materials by binding nanoscale magnetic materials on the pre-synthetic polymer surface. During the magnetization process, the particle size and distribution of the monodisperse polymer microspheres could be maintained. Each microsphere, containing the same concentration of magnetic particles, ensures that it has uniform magnetic response in the magnetic field. In this study, two kinds of anion-exchange microspheres were prepared by an in situ method and applied for protein adsorption study. A novel method for modification of amino-microsphere to carboxyl-microsphere by EDC, NHS, and sodium carboxymethyl cellulose was proposed. The particle size, functional groups, and magnetic properties of the resultant magnetic particles were characterized. The maximum binding capacity was relatively high compared with similar research [16,17,18]. 2. Results and Discussion 2.1. Synthesis of Anion-Exchange Magnetic Microspheres The functional magnetic microspheres were synthesized by an in situ synthesis method with moderate size and functional group beneficiation on the surface for further modification. Glycidyl methacrylate (GMA) was selected as the basic monomer to structure monodisperse polymeric microspheres. The PGMA microsphere surface was rich in amino group after reacting with EDA (Figure 1a). The amino group is a strong polar group, which can form an ionic bond and a complex coordinate bond with a metal ion, thereby reducing the probability of collision between the particles and preventing excessive aggregation of the particles. Magnetic microspheres were prepared when Fe3O4 nanoparticles were precipitated in the surface and the internal of PGMA microspheres through the interfacial stripping precipitation method (see Figure 1b). Furthermore, a novel method in which carboxymethyl cellulose was bonded to the surface of magnetic microspheres by the EDC method was applied to prepare carboxyl magnetic microspheres (Figure 1c). 2.2. Characterization of the Magnetic Microspheres The morphologies of microspheres were studied by SEM. It could be observed that the PGMA microspheres were mono-sized microspheres with very smooth surfaces, while the magnetic microspheres were relatively rough on the surface (Figure 2). The average diameter of the magnetic microspheres was 1.235 ± 0.017 μm according to the 100 microspheres selected from SEM images randomly, and the diameter of the Fe3O4 particles coated by sodium carboxymethyl cellulose on the microspheres was 30~50 nm. The size of these magnetic microspheres is relatively smaller compared with a similar polymerization method [19]. Generally, smaller diameter means larger specific surface area and greater adsorption capacity for the target. The presence of the functional groups of PGMA and amino-PGMA microspheres was verified by FT-IR in Figure 3. PGMA microspheres were obtained by the polymerization of GMA monomer with DVB as cross-linker; therefore, epoxy groups and carbonyl group should distribute throughout the microspheres surface. The strong adsorption peak at 1727 cm−1 corresponds to C=O stretching vibration. Compared with Figure 3a, the characteristic bands at 848 cm−1, 908 cm−1, and 1250 cm−1 belong to the epoxy group which disappeared in Figure 3b, indicating that the epoxy groups transformed into an amino group after the amino modification. Controlling the magnetite content of the microspheres is important for realizing the rapid response to external magnetic fields for efficient adsorption. TGA measurement showed that the main weight loss of all microspheres was in the range of 200~450 °C, indicating that the microspheres should have stable thermal performance in the adsorption condition (Figure 4A). By comparing the residual mass after full burning, it can be calculated that the magnetite content of amino magnetic spheres and carboxyl magnetic spheres is about 12%. The magnetic properties of the carboxyl magnetic microspheres were measured by vibrating sample magnetometry (VSM). The magnetization curve shows that the saturation magnetization of the microspheres reached 12.48 emu/g, while the residual magnetism and coercive force were almost zero (Figure 4B). It means the magnetic microspheres are of high enough magnetism such that they can be separated from a suspension quickly. Moreover, they are superparamagnetic, which could disperse in the solution uniformly when there is no magnetic field. Compared with previous reports, magnetic intensity lowering of sodium carboxymethyl cellulose coated magnetic decrease may be caused by the embedding of the coating. The density of amino groups and carboxyl groups on corresponding microspheres measured by the titration method was 2.75 mmol/g and 1.32 mmol/g respectively. It could be inferred from the result that amino groups incompletely reacted with carboxymethyl cellulose, so both amino groups and carboxyl groups exist on the surface of carboxyl magnetic microspheres. Investigation of the biological safety of magnetic microspheres is critical for biomolecular separation medium. Herein, human pulmonary epithelial cells were used to study the in vitro cytotoxicity of carboxyl magnetic microspheres solution and its supernatant measured using a water-soluble tetrazolium cell proliferation assay. It could be inferred from Figure 5 that the supernatant of suspension showed no cytotoxicity to the cell, and the carboxyl magnetic microspheres showed no cytotoxicity when their concentrations were lower than 10 μg/mg. Therefore, it could be said that the magnetic microspheres are potential targeting medicine carriers or cell separation carriers at low concentrations. 2.3. Binding Capability of Magnetic Microspheres The adsorption capability of magnetic microspheres to proteins is mainly affected by the properties of the protein, the functional groups content on the surface of the microspheres, and the adsorption conditions. Generally, proteins are more likely to precipitate around their isoelectric point. It is comprehensible that pH value has a great effect on the adsorption of proteins by the microspheres. The maximum adsorption capacity of three proteins to amino magnetic microspheres is in close proximity to the isoelectric point (pI) in Figure 6a. Amino magnetic microspheres were positively charged while BSA was negatively charged at pH 5, which means BSA (pI 4.6) would be more easily absorbed on the magnetic surface of the microspheres due to its electrostatic interaction. The absorption mechanism of Hb (pI 7.0) was similar to BSA with the optimal amount of adsorption at pH 7. However, the adsorption for Cyt C (pI 10.65) was not very significant and the adsorption amount differences between each pH value were slight. The carboxyl magnetic microsphere was negatively charged on the protein surface. Due to electrostatic adsorption, binding capacities of Hb to the microspheres were greater when the pH value was below 7. Since there were both carboxyl groups and amino groups existing on the carboxyl magnetic microsphere surface, the adsorption of carboxyl magnetic microspheres was more complicated than the adsorption of amino magnetic microspheres. Binding experimental results (Figure 6b) suggested the overall adsorption of BSA was not much with the maximum adsorption when the pH value was close to its isoelectric point; greater adsorption of Hb is observed in an acidic environment; maximum absorption of Cyt C is also near the isoelectric point. According to our experiment, the optimal adsorption conditions Hb, BSA, and Cyt C are pH 5, pH 7, and pH 9 for amino microspheres, pH 4, pH 3, and pH 11 for the carboxyl microspheres, respectively. The adsorption of Hb was also recorded in the concentration ranging from 0 to 10 mg/mL at 25 °C (Figure 7). With the increase of the initial concentration of Hb, the equilibrium adsorption amount generally increased and eventually became saturated. The adsorption capacities of several magnetic microsphere adsorption materials were compared in Table 1. We can see that the adsorption capacity of the prepared microspheres is comparable to that of the magnetic microspheres prepared by the in situ method. Meanwhile, they have the advantages of simple preparation and low cost. The immunoaffinity magnetic microspheres are highly specific to the target protein, however, sacrificing part of the adsorption capacity. The magnetic microspheres prepared by the imprinting technology have ordered imprinting pores and excellent specificity for target protein, realizing an efficient adsorption rate, which is higher than immunomagnetic microspheres. In addition, the surface mesoporous structure and the enrichment effect of metal particles are also considered to be the factors that improve the ability to adsorb proteins. The adsorption isotherm describes the distribution of the adsorbed molecules between the liquid phase and the solid phase when the adsorption process reaches equilibrium. To study the adsorption mechanism of amino magnetic microspheres and carboxyl magnetic microspheres to Hb, whose adsorption capacity is larger than that of other proteins, the isotherm data were analyzed based on the Langmuir and Freundlich models respectively. The expressions, adsorption constantsm and correlation coefficients of the Langmuir and Freundlich models at 25 °C were calculated and are presented in Table 2. Where ce is the equilibrium concentration (mg/L), qe is the adsorption amount at equilibrium (mg/g), K is the Langmuir adsorption equilibrium constant, qm is the Langmuir constant, which represents the saturated monolayer adsorption capacity (mg/g), KF is a Freundlich constant related to the adsorption capacity (mg/g), and n is a Freundlich adsorption equilibrium constant relevant to the adsorption intensity. Comparing the adsorption constants and correlation coefficients (R2) of the Langmuir and Freundlich isotherms, it is suggested that the adsorption of the magnetic microspheres to Hb is in accordance with the Langmuir equation and the adsorption process is chemical monolayer adsorption. In Langmuir model, the maximum capacity q_mof the carboxyl microspheres in the Langmuir constant monolayer was 215.74 mg/g at 25 °C, indicating that the carboxyl magnetic microspheres have better adsorption capacity than the amino magnetic microspheres. The kinetic curves (Figure 8) showed that the adsorption of the microspheres saturated quickly in 15 min. It is because electrostatic force between magnetic microspheres and proteins occurs mainly on the surface of the magnetic microspheres without the inward diffusion phenomenon. In the initial stage, there are a large number of active sites on the surface of the magnetic microspheres, and proteins were easily adsorbed. As the adsorption increases, the surface active sites of the magnetic microspheres decrease, and the adsorption becomes slower. Therefore, the microspheres would be more efficient for protein purification. The adsorption data of the microspheres to Hb were respectively fitted to the pseudo first-order and pseudo-second-order kinetic models (Table 3). The correlation coefficients of the pseudo second-order kinetic model for amino magnetic microspheres and carboxyl magnetic microspheres were 0.9981 and 0.9911, and the maximum adsorption amounts obtained were 119.05 mg/g and 172.41 mg/g, respectively, which are consistent with the experimental results. It is suggested that the adsorption process is a pseudo second-order kinetic adsorption, which is consistent with the mentioned adsorption mechanism above. Where qe and qt signify the amount adsorbed at equilibrium and at any time t, k is a Lagergren constant. 3. Materials and Methods 3.1. Materials Glycidyl methacrylate (GMA) was obtained from TCI Company (Shanghai, China). Divinylbenzene was obtained from J&K chemical (Beijing, China). 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide hydrochloride (EDC·HCl) and N-Hydroxysuccinimide (NHS) were purchased from Shanghai Medpep corporation (Shanghai, China). Bovine albumin (BSA), Hemoglobin from bovine blood (Hb), Cytochrome C (Cyt C) were obtained from Aladdin chemical corporation (Shanghai, China). Polyvinyl pyrrolidone (PVP K-30), 2,2′-azobis-(isobutyronitrile) (AIBN), ethylenediamine (EDA), anhydrous morpholine ethanesulfonic acid, and other chemicals were received from Beijing Chemical Factory (Beijing, China). Cell Counting Kit-8 (CCK-8) was received from Dojindo Laboratories, Kumamoto, Japan. Human pulmonary epithelial cells were purchased from InvivoGen (San Diego, CA, USA) and grown in Dulbecco’s modified Eagle’s medium (Sigma-Aldrich, St. Louis, MO, USA) containing 10% (v/v) fetal bovine serum, 50 units/mL penicillin, 50 mg/L streptomycin, 100 μg/mL normocin, and 10 μg/mL blasticidin. All chemicals were used without further treatment. Deionized water used in polymerization and characterization was distilled and purified by Aqua Pro (Chongqing, China). 3.2. Synthesis of PGMA Microspheres PGMA microspheres are fabricated by dispersion polymerization method [24]. The polymerization was carried out under nitrogen in the three-necked flask equipped with a condenser. PVP K-30 (2.4 g) and GMA (8.0 g) dissolved in ethanol (67.0 g) was stirred at 300 rpm under nitrogen at room temperature for 15 min. After the initiator AIBN (0.16 g/5 g ethanol) was added, the polymerization was carried out at 70 °C for 2 h. Thereafter, Divinylbenzene (DVB, 0.24 g) was added into the flask smoothly, keeping the reaction going on for 5 h. Then the microspheres were centrifuged and washed with ethanol and water several times and dried under vacuum. 3.3. Synthesis of Amino Magnetic Microspheres The amino magnetic microspheres were synthesized according to the reported method [15]. The dry PGMA microspheres (2.0 g) were added into a mixture of ethylene diamine (EDA, 50 mL) and water (50 mL) while stirring at 80 °C for 6 h. The microspheres were centrifuged and washed with water, and then dried under vacuum. The EDA functionalized microspheres (1.0 g) were added into water (100 mL), which was cooled to 0 °C under nitrogen for 30 min. Afterwards, FeCl3·6H2O (0.41 g) and FeSO4·7H2O (0.24 g) dissolved in water (10 mL) were added to the mixture respectively, and stirred for 3 h below 5 °C. After adding the ammonia solution (10 mL) smoothly, the ice bath was removed and the temperature was raised to 80 °C for 1.5 h. The resulting microspheres were centrifuged and washed with 0.5 M HCl three times and followed by pure water. The magnetic microspheres were dried by lyophilization and reserved. 3.4. Synthesis of Carboxyl Magnetic Microspheres The amino magnetic microspheres were modified with sodium carboxymethyl cellulose to the synthesis of the amino-microspheres. EDC (1.94 g) and NHS (0.58 g) were dissolved in MES solution (100 mL, 0.1 M) together with sodium carboxymethyl cellulose solution (100 mL, 2.5 g/L). Then the dry amino magnetic microspheres (1.0 g) were added and stirred at room temperature for 2 h. Finally, the microspheres were washed with pure water and dried by lyophilization. 3.5. Characterizations of the Magnetic Microspheres The morphology of magnetic microspheres was observed by scanning electron microscopy (SEM, S-4800, HITACHI, Tokyo, Japan). The sample powders were sputter-coated with gold before examination. The magnetic properties of magnetic microspheres were measured by a vibrating sample magnetometer (VSM, 9600-1, LDJ Electronics, Troy, MI, USA) at room temperature. TGA was performed with a thermal gravimetric analyzer (DTG-60H, Shimadzu, Kyoto, Japan) in the temperature range from room temperature to 800 °C with a scanning rate of 10 °C/min under nitrogen stream. The presence of certain functional groups was detected by Fourier Transform infrared spectrometer (FT-IR, ALPHA, Bruker, Billerica, MD, USA). The densities of amino groups and carboxyl groups on the microspheres were measured by a titration method. 3.6. Cytotoxicity Test of the Carboxyl Magnetic Microspheres The cytotoxicity of the carboxyl magnetic microspheres was investigated using a CCK-8 method in vitro. The 96-well plates were seeded with a suspension of 5000 human pulmonary epithelial cells for 24 h to allow the cells to adhere. Then serial dilutions of carboxyl magnetic microspheres solution, the supernatant and medium alone (control) were added into the wells. After incubation at 37 °C for 24 h in an atmosphere of 5% CO2, 10 μL CCK-8 solution was added to each well and the cells were incubated for another three hours. Absorbance at 450 nm was determined using a microplate reader using a microplate reader (MTP-880 Lab, Corona Electric, Ibaraki, Japan). Cytotoxicity was expressed as a percentage of viable cells compared with untreated control ones. 3.7. Binding Experiment The binding properties of magnetic anion-exchange microspheres to the proteins were studied by HPLC with a diode array detector and the C8 column at 40 °C. The standard curves and adsorption capability for the proteins were measured with the corresponding conditions. For BSA, the mobile phase was acetonitrile/water (2/8–8/2, v/v), using a linear gradient elution at the wavelength of 280 nm, and the injection volume was 10 μL. For Hb, the mobile phase was acetonitrile/water (5/5, v/v), using isocratic elution at the wavelength of 400 nm, and the injection volume was 20 μL. For Cyt C, the mobile phase was acetonitrile/water (3/7–5/5, v/v), using linear gradient elution at the wavelength of 400 nm, and the injection volume was 20 μL. The adsorption of proteins by magnetic microspheres was carried out in phosphate buffers (100 mM) of different pH values ranging from 3–11, adjusted with phosphoric acid solution or sodium hydroxide solution. The following experiment was performed in triplicate. The dry magnetic polymer microspheres (5 mg) were dispersed in 1 mL buffer solution followed by the adsorption experiment while the initial concentration of protein was determined from 0 to 10 mg/mL and the equilibrium time was 60 min. In the adsorption kinetics experiment, protein solution with initial concentration (BSA 5 mg/mL, Hb 5 mg/mL, Cyt C 1 mg/mL) was added, and the mixture was incubated at 25 °C for different times (0~60 min) respectively. Then the tubes were placed in the magnetic separation rack for 2 min, and the supernatant was extracted carefully for HPLC detection. The protein binding quantity q (mg/g) of magnetic microspheres could be calculated from Formula (1). (1) q=C0−C×VW where C0 and C are the protein concentrations (mg/mL) before and after adsorption; V is the volume of protein solution (mL); W is the weight of magnetic microspheres (g). 4. Conclusions A new process to obtain the carboxymethyl cellulose surface-coated magnetic polymer microspheres by EDC method was performed in this study. The superparamagnetism and no significant cytotoxicity of the magnetic microspheres attribute to their potential application in vivo. The adsorption capacity of three proteins (BSA, Hb, and Cyt C) on amino magnetic microspheres and carboxyl magnetic microspheres was evaluated, wherein maximum adsorption capacity of Hb on carboxyl magnetic microspheres reached 215.74 mg/g within sufficient binding time at appropriate pH value. However, further studies based on the increase of the stability of magnetic microspheres, specific adsorption of a certain protein, and desorption of protein are required. This paper provides an idea for the preparation of magnetic microspheres for protein separation, which is expected to be a fast and efficient new way of protein separation in the future. Acknowledgments We are grateful for the support of the SEM test from Analysis &Testing Center in Beijing Institute of Technology and cytotoxicity test from National Institute for Materials Science (NIMS), Japan. Author Contributions Original draft writing and validation, Z.W.; methodology, W.W.; conceptualization, Z.M.; supervision, review, and editing, M.X. 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 Schematic diagram of the preparation of magnetic anion-exchanged microspheres. (a) Preparation and amino modification of PGMA Polymer Microspheres. (b) Synthesis of amino magnetic microspheres. (c) Carboxyl coating on the surface of amino magnetic microspheres. Figure 2 SEM images of microspheres. (a) PGMA microspheres. (b) Carboxyl magnetic microspheres. (c) The close-up of carboxyl magnetic microspheres. Figure 3 IR spectrum of microspheres. (a) PGMA microspheres. (b) Amino microspheres. Figure 4 (A) TGA of (a) PGMA microspheres, (b) Amino microspheres, (c) Amino magnetic microspheres, and (d) Carboxyl magnetic microspheres. (B) Hysteresis curve of carboxyl magnetic microspheres. The inset shows photos of the carboxyl magnetic microsphere in aqueous solution without (left) and with (right) a magnet. Figure 5 Relation curve of cell viability with the concentration of magnetic microspheres. Figure 6 Adsorption capacity of three proteins to magnetic microspheres with different pH values. (a) Amino magnetic microspheres. (b) Carboxyl magnetic microspheres. Figure 7 Adsorption isotherm of magnetic microspheres on Hb at 25 °C. Figure 8 Adsorption kinetics of three proteins to magnetic microspheres. (a) Amino magnetic microspheres. (b) Carboxyl magnetic microspheres. ijms-23-04963-t001_Table 1 Table 1 Comparison of the adsorption capacity of several magnetic microspheres for proteins. Magnetic Microspheres Protein Maximum Adsorption Capacity (mg/g) Thepreparedmagnetmicrospheres Hb 217 Chitosan-based magnetic beads byin situmethod [20] BSA 240.5 Cu2+-cooperated magnetic imprinted nanomaterial [21] Hb 116.3 surface-imprinted polyvinyl alcohol microspheres [22] papain 44 magnetic immunoaffinity beads by dispersion polymerization [23] Anti-Tf 2.0 Fe3O4@PMAA@Ni microspheres with flower-like Ni nanofoams [7] Hb 2660 ijms-23-04963-t002_Table 2 Table 2 The adsorption isotherm parameters of Hb by amino magnetic microspheres and carboxyl magnetic microspheres. Adsorbents Langmuir Adsorption Isotherm ceqe=ceqm+1Kqm Freundlich Adsorption Isotherm lnqe=lnKF+lncen qm (mg/g) K R 2 KF (mg/g) 1/n R 2 amino magnetic microspheres 131.27 1.4837 0.9966 52.55 0.5342 0.9427 carboxyl magnetic microspheres 215.74 0.4282 0.9997 48.41 0.6603 0.9750 ijms-23-04963-t003_Table 3 Table 3 Adsorption kinetics parameters of HB by amino magnetic microspheres and carboxyl magnetic microspheres. Amino Magnetic Microspheres Carboxyl Magnetic Microspheres k qe/(mg/g) R2 k qe/(mg/g) R 2 Lagergren first-order rate kinetics lnqe−qt=lnqe−kt 0.2660 166.05 0.9209 0.1143 153.33 0.9767 Lagergren second-order rate kinetics tqt=1kqe2+tqe 2.352 119.05 0.9981 0.0010 172.41 0.9911 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Schmelter C. Funke S. Treml J. Beschnitt A. Perumal N. Manicam C. Pfeiffer N. Grus F. 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==== Front Materials (Basel) Materials (Basel) materials Materials 1996-1944 MDPI 10.3390/ma15093266 materials-15-03266 Article Hygrothermal Performance of Salt (NaCl) for Internal Surface Applications in the Building Envelope https://orcid.org/0000-0002-7318-1821 Pungercar Vesna * Musso Florian Torgal F. Pacheco Academic Editor Department of Architecture, School of Engineering and Design, Technical University of Munich, 80333 Munich, Germany; musso@tum.de * Correspondence: vesna.pungercar@tum.de; Tel.: +49-89-28922302; Fax: +49-89-28922356 02 5 2022 5 2022 15 9 326610 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/). Salt (NaCl), as a by-product from the potash and desalination industry, can be the solution to the scarcity of building materials and might replace more energy-consuming materials. However, salt carries the risk of deliquescence in humid environments. This study conducted fundamental research on the hygrothermal performance of salt for internal surface applications in the building envelope in six different climate conditions. In addition, salt’s performance was also compared with that of gypsum in similar applications. The simulation models (using WUFI®Pro, WUFI®Plus) and in situ measurements were applied to investigate the hygrothermal consequences of the incorporation of salt on the thermal envelope, indoor environment, and energy consumption. Our studies revealed that salt provided the best hygrothermal responses without Heating, Ventilation, and Air Conditioning (HVAC) in very hot-dry and the worst in very hot-humid climates. With an energy-efficient thermal envelope and HVAC, salt can also find an indoor application in temperate, continental, and subpolar climates. In comparison to gypsum, salt has a slightly higher energy demand (heating, cooling, and dehumidification) due to its higher thermal conductivity and moisture resistance. This study fills the knowledge gap on salt’s hygrothermal performance and shows the potential in its utilization. salt gypsum hygrothermal performance experiment WUFI simulation This research received no external funding. ==== Body pmc1. Introduction Newly built or retrofitted buildings are expected to be energy efficient [1,2], provide comfortable indoor room conditions for living [3], and be durable [1]. While new requirements are improving buildings’ energy efficiency with higher airtightness and more insulation of the building envelope, the moisture content inside the buildings is increasing [1,4,5,6]. Too much moisture in the building envelope or too high relative humidity in the room air provide ideal conditions for mould growth [1], deterioration of the materials [7], as well as unsuitable indoor room conditions [3]. Various different strategies [8] have already been implemented in research and practice to counteract the moisture challenge, including energy-efficient building envelopes, controlled HVAC systems, improvement of occupant behaviour, and innovative building constructions [9]. In addition to these strategies, the selection of materials is an area of great interest, especially now, when the world population is growing [10] and the demand for building materials is increasing [11]. It is thus essential to identify new building materials that can substitute rare, expensive or energy-consuming materials that can contribute to better living conditions [12]. One of those potential materials is salt (NaCl), which is a by-product from the potash and desalination industries in a quantity of up to 3 billion m3 per year [13,14]. Typically, salt waste is discharged directly into the environment where it causes negative impacts (change in salinity, increase in temperature, and loss of biodiversity) [15,16,17,18,19,20,21,22,23,24,25,26,27,28]. However, salt can have advantages as a building material in increasing resource efficiency; it is also antibacterial [19] and inflammable [19], has no odour [20], and can store humidity and heat [19,21,22]. In terms of health, salt caves and salt rooms across Europe have been shown to positively affect human lung cancer cells, depression, respiratory, and skin-related diseases [23,24,25,26,27,28,29,30,31,32,33,34]. Salt has already been used as a building material in the past [35,36,37,38,39,40,41,42,43,44]. Initially, buildings were built from solid salt blocks cut from nearby salt-rich lakes [35,36,37]. The Romans diversified the use of salt in construction, for example, by mixing seawater, volcanic ash, and lime to create a strong concrete [38,45]. In the last 60 years, salt has entered a new round of innovation including technological developments in compressing salt under pressure [46,47,48,49], 3D printing with salt [41,42,43,50], and using natural crystallization for new products (shading system or salt plates) [51,52]. In recent years, salt blocks from the Himalayas are starting to get more attention in the construction industry due to their high salt content (up to 98.30% [44]), workability, easy fixing systems, and translucency and have already been used in several restaurants and spas worldwide [53,54]. However, in contrast with more commonplace building materials, salt must be used with caution unless in very hot-dry climates or controlled indoor conditions [44]. Limitations in the use of salt stem from the solubility of salt crystals in water and at high relative humidities (more than 75.0%) [19,22], its corrosive action on steel [55], and its detrimental and efflorescent effects on bricks [56]. Salt can be incorporated into a wide range of materials and components [39,40,41,45] and limited studies on the use of salt in the field of construction have already been undertaken [21,39,57,58]. Most of the studies have been dedicated to studying the mechanical [39,58,59] or hygrothermal [21] properties of salt mixtures such as: karshif stone (salt and clay) and salt concrete (salt and concrete). Karshif stone is a material that can be still found in Siwa Oasis in Egypt [57,60]. It was designed by collecting salt pieces from the nearby salt sea, connected by salt–clay mortar, and under very dry climate conditions over many years formed into a stone [57]. Makhlouf and his team [21] examined the hygrothermal properties of this karshif stone (a salt block composed of up to 95.0% salt and enriched with clay and sand) and compared it with sandstone and limestone. They discovered that karshif stone can buffer moisture better than sandstone and limestone. The Deutsche Gesellschaft zum Bau und Betrieb von Endlagern für Abfallstoffe mbH (DBE, Peine, Germany) has defined the mechanical and thermal material properties of salt concrete mixture (54.0% salt and 46.0% concrete) for the safe disposal of radioactive waste in Morsleben, Germany [39]. The specific heat capacity (C) and heat conductivity (λ) of salt concrete were within a range of values for concrete and salt rock. However, the porosity was higher, and permeability and compressive strength lower, in comparison with commonly used concrete. A similar research project was conducted by Czaikowski and his team [58], who investigated the chemical–hydraulic behaviour of salt concrete in contact with saturated NaCl solution. Their experimental study of sealing systems for disposal of nuclear waste in Germany resulted in more or less identical material properties as those defined by DBE. There are very few scientific studies about salt as a building material and usually, these have focused only on salt’s material properties. Salt applications on the thermal envelope interior and hygrothermal characterization have not yet been explored. Applying salt as an interior finish to the building envelope can modify the hygrothermal performance of the exterior wall, which might result in a number of hygrothermal risks [1,3,61]. The increased water content in the wall construction and in the interior surface of salt material may exceed the critical relative humidity and water content of salt. The critical hygrothermal conditions found in the literature for salt are characterized by a water content of over 0.5% (5 kg/m3) at relative humidity greater than 75.0% [55,56,57]. As long as the water content (moisture) and relative humidity in the pore system of salt remain above these critical values, condensation will occur and the salt crystals will dissolve [19,22]. Additionally, salt’s higher vapour diffusion resistance factor (in comparison with gypsum) [62,63,64] might lower the temperature of the wall structure and change the drying time of the wall. Lastly, salt’s potential influence on the indoor air quality (air relative humidity and air temperature) should be investigated since it can affect the comfort and health of building occupants. 2. Materials and Methods The key aims of our study are to evaluate the moisture and heat performance of salt blocks for internal surface applications in the building envelope and to investigate their influence on room temperature and humidity in different climatic regions. To achieve this, we conducted hygrothermal simulations and on-site measurements. In the hygrothermal simulation, the relevant hygrothermal properties of the salt block were firstly defined, used as input values in the simulation, and compared with gypsum. On-site measurements were typically taken for 5 months to evaluate salt behaviour in real-life situations. Our research contributes to filling the knowledge gap on the risks and benefits of using salt in the thermal envelope, which helps to understand salt’s potential as a building material and how it ages. 2.1. Hygrothermal Simulation 2.1.1. Objective The transport of heat and moisture in the thermal envelope under natural weather conditions were simulated with WUFI®Pro, while the influences on the indoor air temperature and relative humidity were monitored with WUFI®Plus for 6 different climates. To compare the hygrothermic behaviour of the salt plate with that of a more typical interior finish, a sample with an internal gypsum plaster cladding was also studied. The WUFI®Pro simulation investigated the frequency of overstepping the critical boundaries and the impact on the hygrothermal process in the wall assembly/the interior surface of salt material in different climatic zones. WUFI®Plus simulations were carried out to define energy demand (cooling, heating, dehumidification, and humidification) and indoor air quality (see Figure 1). 2.1.2. External Condition—Climate Parameters External conditions (Table 1, Figure 2) were chosen across six different climate zones in Europe and North America, according to the Köppen climate classification. These locations were selected to investigate the most appropriate climatic conditions for salt materials. Meteorological data were defined in WUFI®Programs and consisted of annual outdoor air temperature, annual outdoor relative humidity, mean wind speed, solar radiation sum, and rainfall sum. 2.1.3. Internal Conditions—Indoor Parameters The internal simulation conditions in WUFI®Pro were obtained by standard values from the WUFI database. The indoor conditions in WUFI®Plus varied: at first, the HVAC was turned off to evaluate the influence of the climate zone and construction on the indoor temperature and relative humidity. In the next step, the HVAC was turned on, to maintain the indoor air quality standards and to evaluate the energy demand (annual heating and cooling, humidification, and dehumidification). Table 2 lists the various hygrothermal impact indicators. 2.1.4. Boundary Condition—Exterior Wall The simulation models used a masonry construction typical in Germany with different thicknesses of external thermal insulation composite system (ETICS) (Table 1). The ETICS thickness was defined according to the locally permitted maximal heat transfer coefficient U-value of the specific climate zone (see Table 3). The simulation model (exterior wall) comprised of four main layers: (1) an outdoor render, (2) a thermal insulation, (3) a brick construction, and (4) an indoor plaster (salt or gypsum). Salt was always simulated and compared with the gypsum for a better understanding of the salt’s performance. The salt material analysed was Himalayan salt rock [53,65], which is the most common salt material in the construction industry, fixed in place with various techniques (glued on interior walls, hung on a secondary mesh construction, or connected with steel profiles) [54]. The hygrothermal properties of this salt rock could not be found in the literature and were, therefore, for the goals of this research, analysed at Fraunhofer Institut IBF, Germany in 2020 [62,63]. The relevant properties for the hygrothermal simulation of all other materials, used as input data in WUFI®Pro and WUFI®Plus, are presented in Table 3. 2.2. Experimental Measurements 2.2.1. Objective We took experimental measurements to investigate the hygrothermal impact of salt, gypsum, and salt–gypsum in a temperate climate. The relative humidity and the materials’ temperatures were tested over five months in Munich, Germany. The measured results were then compared with the simulation models. 2.2.2. The Testing Room The monitoring was carried out in a room in a typical existing 1980s residential building in Munich, Germany (48°10’ N, 11°32’ E) [9]. The room has three internal and one external walls (Figure 3). The investigated part of the room was the external wall, composed of a brick wall with poor thermal insulation, almost no wind exposure, and southwest orientation. This existing wall is made up of four layers (Figure 2) and during the day is shaded 70.0% of the time by vegetation, balconies, and surrounding buildings in the summer and 80.0% of the daytime in the winter. Four people live in the apartment, but the test room was mostly used by just two. The room’s interior conditions are not totally controlled and represent rather typical living conditions of a family with varying room occupancy, with heating in winter and shading in summer, together with influences from other rooms. 2.2.3. The Test Materials One test panel (Figure 4) comprised of three different materials was placed on the indoor surface of the exterior wall. It consists of a 29.0 cm × 78.0 cm timber frame filled with samples of the three materials of 20 cm × 20 cm × 2.5 cm size. From the top down, these materials are: pink rock salt, gypsum, and salt–gypsum. The material characteristics of the salt plate and gypsum are shown in Table 3. Boundary condition (construction of the exterior walls with the material properties). The salt–gypsum sample is a mixture of 70.0% gypsum and 30.0% salt: however, its material properties were not tested. The joints between the test materials and the timber frame were filled with silicone paste, while the fixing of the frame to the wall was made airtight with sealing tape. Nevertheless, we assume that the temperature difference between the internal and external surfaces of the material samples and sealing deformation cannot provide total control of moisture and temperature flow. 2.2.4. The Test Instrumentation Temperature and relative humidity from Testo were installed at the centre of each sample material surface to measure relative humidity and temperature. One sensor was installed on the centre of the outer surface facing the room, the second sensor was installed on the centre of the interface between the surface of the material and the inner surface of the external wall, and the third sensor was installed on the outer surface of the external wall (Figure 4). Indoor environment conditions were measured with temperature and relative humidity sensor 176 H1 in the middle of the room at 1.8 m height. Outdoor environment temperature and relative humidity values were taken from the real weather condition. All the sensors were calibrated by the manufacturers and the accuracy ranges are shown in Table 4. 2.2.5. The Test Protocol The duration of the monitoring was about 139 days (from 2 August 2020 till 18 December 2020), which covered the three climate conditions: hottest (summer), moderate (autumn), and coldest periods (winter). In view of the manufacturer’s recommendation for monitoring salt materials with steel sensors, their data were collected for less than 6 months. Data from the sensors on the interior wall, the test panel, and the exterior wall surface were saved every 10 min during the testing period. The interior temperature and humidity in the test room were not controlled. It changed according to its occupancy level, the heating period, the extent of shading to the window, and the infiltration of air through the doors and windows. 3. Results 3.1. Simulation WUFI®Pro Table 5 and Figure 5 show the values of the hourly simulated relative humidity (RH), temperature (T), and water content (WC) for the indoor surface (gypsum—G and salt S) and for the exterior wall construction for each climate (TR—Tropical, AR—Arid, TE—Temperate, CO—Continental, ME—Mediterranean, and SP—Subpolar). Minimum, maximum, average, and mean values of temperature, relative humidity, and water content are listed in Table 5 to show the differences in climate zones as well as the comparison between salt and gypsum. The higher the temperature and relative humidity in a climate zone, the higher the T, RH, and WC in the observed materials. Figure 5 shows the water content and RH over three years in the gypsum (G) and salt (S). The differences in RH in both materials are negligible compared to the water content. The water content in gypsum is more variable over time than in salt and shows a slight water uptake during the three years in all climate zones. 3.2. Simulation WUFI®Plus—Influence on the Indoor Air Quality and Energy Consumption Figure 6 presents the dynamically simulated data of indoor air temperature and air relative humidity for gypsum and salt without HVAC (Heating, Ventilation, and Air Conditioning). The differences in the values can be attributed to the outdoor environmental influences and material parameters. The main differences (between G and S) are in relative humidity and not in temperature. The enclosed space with salt shows, in a comparison with gypsum, the lower range and, in most of the cases, a lower average RH value. The annual energy consumption (cooling, heating, dehumidification, and humidification) with respect to outdoor environmental conditions for G and S are presented in Figure 7. These results help us understand how different surface materials influence energy consumption in various climate conditions. The result of the material influence is that in all climate zones, no energy for humidification is needed and that in most cases (13 out of 15), salt performs with a slightly higher energy demand in comparison with gypsum. 3.3. Measurements Figure 8 and Table 6 show the relative humidity and temperature of in situ measurements in the CO climate zone (Munich) for three materials (G—gypsum, S—salt, and SG—salt–gypsum). Each box shows the highest, lowest, mean, and average values. 4. Discussion Measured and simulated data for materials are discussed with respect to three topics: temperature, relative humidity, and water content, and influence on the indoor air quality and energy consumption. For a better interpretation of the performance of salt, gypsum values are set as reference models and compared with salt. 4.1. Temperature Salt (S), in comparison to gypsum (G), shows a reduction in the temperature of the surface of the internal walls. As can be seen in Table 5 and Table 6, the measured and simulated average surface temperatures of salt are, in all climate zones, slightly lower than those of gypsum. According to the simulated results for all climate zones, the average temperature decreases up to a maximum of 0.05 °C in the TR zone (from 27.73 °C to 27.68 °C). According to the measured results (S) in the CO climate zone, the indoor surface temperature decreases by 0.73 °C (from 22.3 to 21.90 °C), which is 0.01 °C higher than in the CO simulation (from 20.78 to 20.77 °C). As can be seen in Figure 8, the measured average surface temperature of the salt–gypsum (SG) of the outer surface to indoor, and of the centre of the interface between the surface of the material and the inner surface of the external wall, is between the values of salt and gypsum. In general, the T of salt (S) is found to be lower in measured and simulated results. There is a small difference in values due to different periods of examination, and indoor and outdoor boundary conditions. With the higher thermal conductivity of salt, heat in salt is more rapidly transferred (than in gypsum) and, thus, has a slightly lower surface temperature. 4.2. Humidity and Water Content In the first step, relative humidity and water content in salt and gypsum are analysed, and the frequency by which the limits specified for salt are exceeded is defined (Table 5). The annual moisture balance of the whole envelope is then analysed through simulation for three years (Figure 5). In comparison to gypsum, salt shows an increase in RH. According to the simulated results for all climate zones, the average RH in the indoor surface layer of salt increases up to a maximum of 0.36% in TR (from 69.81% to 70.17%) and at the same time exceeds the RH limits. According to the measured results for salt in the CO climate zone, the RH of the outer surface of the salt test material decreases by 4.26% (from 55.01% to 50.72%). However, the simulation values show no difference. Mixing salt with gypsum (Table 6) shows also a decrease in the moisture resistance, and the measured average relative humidity of salt–gypsum increases up to a maximum of 3.04% (in comparison to salt). Only a slight difference in the relative humidity obtained for salt and gypsum was found during the three years of the simulation period (see Figure 5). According to the simulated results for salt in all climate zones (Table 5), the average accumulated water content on the indoor surface, compared to gypsum, decreases up to a maximum of 0.12 kg/m3 in the ME zone (from 4.81 to 4.69 kg/m3) and increases up to a maximum of 0.40 kg/m3 in SP (from 3.43 to 3.83 kg/m3). Observing the results during the three-year period (see Figure 5) in different climate zones, the highest accumulated moisture content is found in salt in the TR and ME zones. The accumulated moisture content exceeds the critical limits specified for salt for 414 h in the first year, 196 h in the second year, 402 h in the third year in the TR zone, and 2 h in the first year in the ME zone. Both findings show the high risk of salt deliquescence, which is also present in the controlled indoor environment. The reason for this is the low u-value of the building envelope systems and high air humidity of this climate zone (a drying period does not occur or is too short), so the moisture remains in the material. As a general observation, it is noted that the water content values in salt in other climate zones are higher at the beginning of the period (first year) due to some initial moisture, decrease over time, and do not vary as dramatically as in gypsum, where the values fluctuate substantially with the smallest change in air RH or T. With respect to the water content in the whole building envelope, the difference between S and G is not significant (up to a maximum of 14.0% in the SP zone). Building envelopes with salt show higher average water content in CO (5.0%), TE (7.0%), and SP (14.0%) zones and lower in TR (9.6%) and AR (6.0%) zones and the same values in the ME zone. The highest average water content (2.71 kg/m2 for salt) is observed in building envelopes in the hot-humid climate zone (TR) and the lowest (9.92 kg/m2) in the hot-dry climate. Due to the lower porosity and higher vapour diffusion resistance factor of salt (in comparison to gypsum), the high water content from construction cannot be transported as quickly towards the outdoor surface and thus dry out. In general, the smaller the insulation thickness, at a lower RH/T, the lower the relative humidity and water content of the thermal envelope. Salt is most appropriate for applications in hot-dry climates due to its lowest risk for moisture-induced damage and, therefore, higher durability of the building envelope in such climates. 4.3. Influence on the Indoor Air Quality without HVAC for Enclosed Spaces The corresponding comfort range for indoor air temperature (Ti) is in the range of 21–27 °C and relative humidity (RHi) in the range of 40.0–70.0%. The simulation results (Figure 6) for a building envelope with salt with no HVAC show the average Ti as appropriate at 25 °C in the TR and 26.9 °C in the AR zones, but inappropriate at 13.09 °C in CO, 12.66 °C in TE, 19.85 °C in ME, and 19 °C in the SP zone. The average Ti with salt decreases in comparison to gypsum by up to 0.12 °C in TR (25.80 to 25.68 °C) and by 0.15 °C in ME zones (20.08 to 19.85 °C). Average Ti with salt increases in comparison to gypsum by up to 0.81 °C in AR (26.12 to 26.93 °C), 0.08 °C in CO (12.58 to 12.66 °C), 0.11 °C in TE (12.98 to 13.09 °C), and 11.27 °C in SP (7.73 to 19 °C). So, evaluating the average indoor air temperature of the enclosed space, salt shows advantages compared with gypsum in the no HVAC conditions (in four of the six climate conditions the average Ti was higher) due to the higher thermal conductivity of salt that transmits the heat quickly from outside to inside. Figure 6 shows also the average, min, max, and mean RHi for salt and gypsum in all climate zones with no HVAC. The average RHi for salt enclosed spaces is inappropriate in all climate zones (72.93% in TR, 36.45% in AR, 74.84% in TE, 74.85% in CO, 74.54% in ME, and 82.0% in SP). All climate zones with an average RHi between 70.0 and 75.0% and a maximum >75.0% in settings without HVAC are inappropriate for salt application due to the higher risk of deliquescence. Therefore, only AR climate zones with lower RHi are suitable for salt applications. The average RHi in salt enclosed spaces has lower values of the variation in comparison to gypsum, and in four of six cases also a lower average RHi. This is due to the higher water vapour diffusion resistance factor of salt (compared to gypsum) that does not absorb so much of the indoor RH and, thus, slightly reduces the humidity buffering ability of the building envelope to regulate variations in the indoor RH levels. 4.4. Influence on the Energy Consumption with HVAC for Enclosed Spaces The measured annual energy (Figure 7) use for the heating, cooling, and dehumidification presents data for the enclosed unit, both for the gypsum and salt applications. The salt enclosed space shows an annual increase in cooling demand of 4.8% in TR, 6.0% in AR, and a decrease of 6.9% in the ME zone. The annual heating demand for the salt enclosed space is higher in all zones with a maximal increase of 14.3% in the TR zone. In addition, the annual dehumidification demand for salt is higher in five of the six climate zones in comparison to gypsum. The results show that in hot-humid climate zones where there is great external heat or moisture load, the moisture and heat are transmitted through the building envelope from outdoor to indoor. In contrast, in cold climate zones with higher internal heat or moisture, the heat and moisture flow from inside to outside. The higher thermal conductivity, lower porosity, and higher bulk density of salt enable the quicker transport of heat and increase the annual demand for heating or cooling. The higher moisture resistance of salt prevents the transport of indoor humidity and increases the indoor dehumidification consumption due to interior heat gains. In future studies, it will be important to also have the real measured data for energy consumption of salt and gypsum. This would help to improve the simulation accuracy and make more accurate recommendations for salt. 4.5. Suggestions for Future Studies This research is the first-ever hygrothermal study of salt (Himalayan) as a building material for indoor application in six different climate zones. The hygrothermal performance of salt showed the potential to replace gypsum, especially in hot-dry climates. However, the knowledge gained in the study about salt’s hygrothermal behaviour is limited, as it only investigated only one salt material. Therefore, the paper gives several suggestions for future studies:- Salt mixtures with other materials for increasing resource efficiency and saving of CO2: The annual world production of cement is about 4.4 billion tons [66], of gypsum 150 million tons [67,68,69], and 1.1 billion tons of salt [70,71,72,73] is produced each around the world. The production of cement and gypsum is subject to substantial criticism because of its high energy demand [74,75] and the heavy impact of mining on landscapes [15,17,76,77,78]. Resources such as FGD gypsum, which currently supply approx. 50.0% of the gypsum requirement in Germany [69], is disappearing due to German energy strategies (the phasing out of coal combustion) [79,80]. By increasing the salt content in the composite material, natural resources (e.g., natural gypsum) will be protected, less energy will be needed for production and CO2 emissions will be reduced. Each ton of cement replaced by one ton of salt would save approximately 600 kg of CO2 [81] emissions. - Hygrothermal performance of other salt composites: The simulated and on-site measurements of different salt composites (salt and concrete, salt and gypsum, salt and clay) should be analysed in detail, comparing and evaluating the passive regulation of indoor temperature and relative humidity in different climate conditions. The inclusion of other additives should also be considered for more effective heat and moisture transport. - Durability of salt materials: Salt materials should be exposed to different humidity, temperature and different positions in the thermal envelope to investigate degradation, aging, and durability. Measured results should be compared with simulations. - Other constructive possibilities: In this research was salt analysed only as a cladding element. Different constructive possibilities, such as supporting components in 3D printing, modular prefabricated elements, or just filling material for interior walls, should be further considered and explored. 5. Conclusions This paper presents an investigation into salt’s hygrothermal performance as an indoor building component of the thermal envelope, which is compared with a reference material (gypsum) in terms of six different typical climate zones, construction types, and HVAC. A comparison between salt and gypsum shows that salt has higher bulk density, lower porosity, lower moisture storage, higher heat transport properties, and the same heat storage capacities as gypsum. As the simulation results of the building envelope (WUFI®Pro) show, the salt material layer has, in comparison to gypsum: a max. 0.05 °C decrease in the material temperature and a max. 0.36% increase in material relative humidity. Another important aspect was looking at the water content of the entire building envelope in each climate zone. We found that the building envelope containing salt shows a greater average water content of up to 13.0% in cold climate zones and lower average water content in warmer climate zones. The same influence of cold or warm climate zones on water content in the thermal envelope can reasonably be supported by the studies of Qin et al. [82] Liu et al. [83], Corrado et al. [84] and Qin et al. [85]. The highest risk of salt deliquescence is observed in TR and ME climate zones, with the lowest risk in the AR zone. Due to the limitation of the in situ measurements, only the T and RH near the indoor and outdoor surfaces of the tested materials are measured. The simulated results show good agreement with in situ measurements for salt and gypsum in the CO zone. Both results show the same tendency in values of material temperature and humidity. However, the measured temperature at the indoor surface is slightly higher and the RH slightly lower than the simulated ones, probably due to the tested materials being located near the central heating element from 26 September 2019 till 18 December 2019. Previous studies by Moujalled et al. [86] and Illomets et al. [87] have also found that in situ measurements show slightly different results as simulations due to the heating system. However, the modelling method is shown to be correct, but will have to be adapted to real living conditions such as building envelope, occupation (behaviour and density), and energy system in the future. The annual simulation for energy consumption in WUFI®Plus shows that salt has a slightly increased heat and decreased moisture transport, which leads to more cooling, heating, and dehumidification energy. However, salt has advantages in increased heat transport that reduce the indoor surface temperature, the peak of indoor air temperature, and is moreover beneficial for better indoor comfort in very hot climate zones. Decreased moisture transport in salt shows it can help to reduce the influence of the external environment RH with respect to indoor RH or it can prevent the condensed water and indoor moisture from drying out. This result correlates with other works in which the hygrothermal performance of materials in the building envelope have been studied [1,3,61,87]. The outcomes mentioned above can form the basis for some recommendations on the application of salt in internal spaces. In general, for buildings without HVAC only very dry and hot outdoor climatic environments (AR zone) are suitable as there is no risk of salt deliquescence, while the salt has a positive influence on the Ti/RHi and durability of the thermal envelope. For buildings with good thermal envelopes and controlled HVAC, the CO, TE, and SP zones might also come into consideration. Acknowledgments The authors gratefully thank Fraunhofer IBP for helping with the simulation programme WUFI 2D. Author Contributions Conceptualization, Methodology, Software, Validation, Formal Analysis, Investigation, Resources, Data Curation, Writing—Original Draft Preparation, Writing—Review and Editing, and Visualization (98.0%), V.P.; Review, Conceptualisation (2.0%), F.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. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Simulation model design with the boundary conditions and expected results. Figure 2 Six different climate zones in Europe and North America, according to the Köppen climate classification. Figure 3 Left: Ground plan of the test room. Right: Exterior wall of the testing room. Figure 4 Left: Test panel. Right: Horizontal section through the test panel installation. Figure 5 Simulated RH and water content of salt and gypsum over three years (G_RH—gypsum and relative humidity, S_RH—salt and relative humidity, G_WC—gypsum and water content, S_WC—salt and water content). Figure 6 Simulated indoor air temperature and relative humidity for 6 climate zones (TR—Tropical, AR—Arid, TE—Temperate, CO—Continental, ME—Mediterranean, SP—Subpolar) with gypsum (G-grey box) or salt (S-white box) without HVAC. Red area – area for the most comfortable T (°C) and RH (%). Figure 7 Comparison of annual cooling, heating, and dehumidification demand for gypsum and salt in six climate zones (TR—Tropical, AR—Arid, TE—Temperate, CO—Continental, ME—Mediterranean, SP—Subpolar, grey—gypsum, white—salt). Figure 8 In situ measurements of relative humidity and temperature in Munich (red colour—indoor air temperature, blue colour—outdoor air temperature, grey colour—gypsum, white colour—salt, light grey colour—salt–gypsum, In—surface to interior, Ext—surface to exterior). materials-15-03266-t001_Table 1 Table 1 Exterior weather conditions. Climate Zones—Köpper–Geiger Climate Classification City Climate Position (Latitude, Longitude) U-Value Requirements (W/m2K) TR Tropical (Am) Miami, USA Monsoon 25.80° N 80.27° W 0.857 (ASHREA 2019) AR Arid (Bwh) Phoenix, USA Dessert, hot arid 33.43° N 112.02° W 0.857 (ASHREA 2019) TE Temperate (Cfb) Hannover, Germany Humid and warm summer 52.37° N 9.37° E 0.24 (EnEV 2016) CO Continental (Dfb) Munich, Germany Fully humid, cool summer 48.13° N 11.72° E 0.24 (EnEV 2016) ME Meditterian (Csa) Palma, Spain Dry summer, hot summer 39.56° N 2.65° E 0.38 (DBHE 2019) SP Subpolar (Dfd) Karasjok, Norway Fully humid cold summer 69.47° N 25.49° E 0.22 (TEK 17) materials-15-03266-t002_Table 2 Table 2 Outdoor and indoor conditions for the simulation model. WUFI®Pro WUFI®Plus Outdoor condition (weather data) Real weather data from the WUFI®Pro/Plus programme Real weather data from the WUFI®Pro/Plus programme Indoor condition USA: ASHRAE 160 Europe: EN 15026, DIN 4108, WTA 6-2 USA: ASHRAE 160 Europe: EN 15026, DIN 4108, WTA 6-2 Component (wall/room) Thermal envelope Room (3 m × 3 m × 3 m) Calculation Period, Profiles 3 Years (time steps: 1 h) 1 year (time steps: 1 h) Orientation Wall component is oriented to north (the lowest solar radiation) No windows to evaluate the influence of the climate zones and construction Inclination 90° 90° Initial moisture and temperature in construction component RH = 70.0% T = 20 °C RH = 70.0% T = 20 °C Driving Rain Coefficients 0.07 0.07 Monitor Position Material surface In a room Number of occupants 1 person per room 1 person per room Office indoor heat and moisture load Standard program input Convective heat: 33.3 W Radiant heat: 25.2 W, Moisture 17.55 g/h, CO2: 20.79 g/h Human activity: 1.2 met Air velocity: 0.1 m/s Clothing Standard program input 0.7 clo Occupancy Period Standard program input 7.00–18.00 Energy system Only heating Depending on the climate zone (norms: EN 15026, DIN 4108, WTA 6-2, ASHRAE 160) HVAC on: Indoor air temperature 21–27 °C RH 40.0–70.0% Max CO2: 3000 ppmv Air exchange: 0.6 h−1 Heating, cooling, humidification, and dehumidification calculated HVAC off materials-15-03266-t003_Table 3 Table 3 Boundary condition (construction of the exterior walls with the material properties). The indoor material layer is gypsum or salt (dark grey). Construction from Outside to Inside (cm) U-Value (W/m2K) Mineral Plaster Mineral Insulation Board Solid Brick Masonry Gypsum Plaster Salt Wall 1: Tropical (TR) and arid (AR) climate zone 0.72 (gypsum) 1.0 3.0 24.0 2.0 0.77 (salt) 1.0 3.0 24.0 2.0 Wall 2: Temperate (TE) and continental (CO) climate zone 0.23 (gypsum) 1.0 14.0 24.0 2.0 0.24 (salt) 1.0 14.0 24.0 2.0 Wall 3: Mediterranean (ME) climate zone 0.35 (gypsum) 1.0 9.0 24.0 2.0 0.35 (salt) 1.0 9.0 24.0 2.0 Wall 4: subpolar (SP) climate zone 0.21 (gypsum) 1.0 16.0 24.0 2.0 0.22 (salt) 1.0 16.0 24.0 2.0 Material properties Bulk density (kg/m3) 1900 15 1900 850 2087 Porosity (m3/m3) 0.24 0.95 0.24 0.65 0.04 Specific Heat Capacity (J/kgK) 850 1500 850 850 850 Water Vapour Diffusion Resistance Factor (−) 25 30 10 8.3 7836 Thermal conductivity (W/mK) 0.8 0.04 0.6 0.2 2.65 Typical Build-In Moisture (kg/m3) 210 44.8 100 400 999 materials-15-03266-t004_Table 4 Table 4 Sensors. Sensors Accuracy Ranges testo 176 H1—Temperature and humidity data logger (data logger for sensors on the test materials) ±0.2 °C (−20 to +70 °C) ±1 Digit ±0.4 °C (Remaining Range) ±1 Digit dependent on probe selected (0.0 to 100.0% RH) Thin humidity/temperature probe with cable (sensors on the test materials) ±0.2 °C at 0 to +40 °C ±2.0% RH at +25 °C (2.0 to +98.0% RH) ±0.08% RH/K (k = 1), long-term stability: ±1.0% RH/year testo 175 H1—Temperature and humidity data logger (exterior and interior measurements) ±0.4 °C (−20 to +55 °C) ±1 Digit at −20 to +55 °C ±2.0% RH (2.0 to 98.0%) at +25 °C ±0.03% RH/K ±1 Digit <±1.0% RH/year drift at +25 °C materials-15-03266-t005_Table 5 Table 5 The characteristics of the simulated relative humidity, temperature, and water content in gypsum/salt and the water content in the whole exterior wall in different climate conditions: the minimum, the maximum, the average, and the mean range. TR_G TR_S AR_G AR_S CO_G CO_S TE_G TE_S ME_G ME_S SP_G SP_S Relative Humidity, Surface (%) Min 43.85 42.68 17.58 17.38 36.95 36.60 36.94 36.62 47.19 46.95 36.61 36.31 Max 89.02 99.61 71.53 73.50 68.64 70.77 68.11 69.65 74.53 76.11 66.68 68.30 Ave 69.81 70.17 38.92 39.02 54.27 54.27 54.80 54.84 61.04 61.08 46.37 46.42 Mean 70.76 70.92 38.80 38.83 53.80 53.74 54.34 54.32 62.73 62.91 45.81 45.77 Water Content, Surface (kg/m3) Min 3.95 4.95 1.33 1.66 2.82 3.64 2.91 3.79 3.69 4.29 2.72 3.07 Max 6.83 36.52 5.23 5.40 5.32 5.41 5.40 5.42 5.69 41.01 5.19 5.38 Ave 5.57 6.47 2.84 2.77 4.14 4.25 4.18 4.33 4.81 4.69 3.45 3.83 Mean 5.63 5.12 2.85 2.59 4.10 4.25 4.13 4.31 4.97 4.68 3.34 3.81 Salt (Water Content > 0.5 kg/m3 and RH > 75.0%), Gypsum (T = 5–40 °C and RH > 80.0%) (1st year, 2nd year, 3rd year) Hours 19.0, 0.0, 0.0 414.0, 196.0, 402.0 0.0, 0.0, 0.0 0.0, 0.0, 0.0 0.0, 0.0, 0.0 0.0, 0.0, 0.0 0.0, 0.0, 0.0 0.0, 0.0, 0.0 0.0, 0.0, 0.0 2.0, 0.0, 0.0 0.0, 0.0, 0.0 0.0, 0.0, 0.0 Temperature, Surface Layer (°C) Min 20.51 19.95 19.71 19.56 19.05 19.03 19.18 19.16 19.24 19.20 18.54 18.50 Max 32.43 32.40 41.47 41.43 24.88 24.88 24.82 24.83 25.20 25.23 23.99 23.95 Ave 27.73 27.68 28.20 28.17 20.78 20.77 20.77 20.75 22.56 22.55 19.66 19.65 Mean 27.86 27.79 28.14 28.13 19.65 19.64 19.70 19.69 22.88 22.85 19.43 19.42 Water content, whole construction (kg/m2) Min 2.81 2.36 0.39 0.38 1.68 1.51 1.78 1.59 2.15 1.95 1.65 1.34 Max 3.58 3.83 3.17 3.16 3.47 3.63 3.33 3.49 3.52 3.95 3.30 3.56 Ave 3.10 2.71 0.98 0.92 2.20 2.32 2.26 2.43 2.53 2.53 2.08 2.42 Mean 3.11 2.65 0.98 0.73 2.16 2.19 2.23 2.31 2.47 2.46 1.97 2.51 materials-15-03266-t006_Table 6 Table 6 In-Situ measurements of relative humidity (RH) and temperature (T) on the interior (In) and exterior (Ext) surface of three materials (S—salt, G—gypsum, SG—salt–gypsum). S_In RH S_In T S_Ext RH S_Ext T G_In RH G_In T G_Ext RH G_Ext T SG_In RH SG_In T SG_Ext RH SG_In T Min 33.46 18.90 33.31 18.40 39.93 18.91 41.24 18.57 41.97 18.84 3817 18.57 Max 70.86 24.99 68.11 24.76 72.72 25.06 68.25 24.91 73.21 24.82 69.00 24.65 Ave 50.72 21.90 49.70 21.52 55.01 22.63 54.52 23.00 55.42 21.54 52.74 21.74 Mean 50.01 21.88 49.43 21.46 54.27 22.88 53.46 23.52 54.21 21.45 52.71 21.69 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Künzel H.M. Karagiozis A. 2-Hygrothermal behaviour and simulation in buildings Materials for Energy Efficiency and Thermal Comfort in Buildings Hall M.R. Woodhead Publishing Sawston, UK 2010 54 76 2. Künzel H.M. Simultaneous Heat and Moisture Transport in Building Components: One- and Two-Dimensional Calculation Using Simple Parameters IRB Stuttgart, Germany 1995 3. Künzel H.M. Holm A. Zirkelbach D. Karagiozis A.N. 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==== Front J Clin Med J Clin Med jcm Journal of Clinical Medicine 2077-0383 MDPI 10.3390/jcm11092278 jcm-11-02278 Article The Efficacy of Single-Stage Correction by Posterior Approach for Neglected Congenital Scoliosis: Comparative Analysis According to the Age of Surgical Intervention https://orcid.org/0000-0001-6949-6954 Yang Jae Hyuk 1 https://orcid.org/0000-0002-8162-9585 Kim Hong Jin 2 https://orcid.org/0000-0001-6731-1063 Chang Dong-Gune 2*† Suh Seung Woo 3† Nam Yunjin 3 https://orcid.org/0000-0003-4948-4539 Hong Jae-Young 4 Greggi Tiziana Academic Editor Korovessis Panagiotis Academic Editor 1 Department of Orthopedic Surgery, Korea University Anam Hospital, College of Medicine, Korea University, Seoul 02841, Korea; kuspine@naver.com 2 Department of Orthopedic Surgery, Inje University Sanggye Paik Hospital, College of Medicine, Inje University, Seoul 01757, Korea; hongjin0925@naver.com 3 Department of Orthopedic Surgery, Korea University Guro Hospital, College of Medicine, Korea University, Seoul 08308, Korea; spine@korea.ac.kr (S.W.S.); nam.yunjin@gmail.com (Y.N.) 4 Department of Orthopedic Surgery, Korea University Ansan Hospital, College of Medicine, Korea University, Ansan 15355, Korea; osspine@korea.ac.kr * Correspondence: dgchangmd@gmail.com; Tel.: +82-2-950-1284 † Dong-Gune Chang and Seung Woo Suh equally contributed to this work, and should be considered as co-corresponding author. 19 4 2022 5 2022 11 9 227815 3 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/). Background: A single-stage correction for congenital scoliosis through a posterior-only approach is a commonly used surgical technique. However, there are few studies on the surgical treatment effect of posterior single-stage correction in patients with neglected congenital scoliosis. Methods: Patients who underwent a single-stage posterior correction for congenital scoliosis with a minimum follow-up of 2 years were divided into three groups based on age: Group A (7–11 years), B (12–18 years) and C (>18 years). A comparison of surgical, radiological, and clinical outcomes was performed for three groups. Results: The Cobb angle changed form 75 ± 18° to 37 ± 18° with a correction rate of 53%. Group A showed a significantly higher correction rate than Group B and C (all p < 0.001). The amount of blood loss in Groups B and C was significantly larger than that of Group A (p = 0.015). Pulmonary complications were significantly higher in Group C (p = 0.007). Conclusions: A single-stage correction with pedicle screws through a posterior-only approach achieved a significant correction with improved outcomes, even in neglected cases. However, the early correction for younger patients was still more beneficial in terms of bleeding loss, complications, and flexible curve correction. congenital scoliosis posterior approach single-stage correction osteotomy ==== Body pmc1. Introduction The treatment of congenital scoliosis focuses on early diagnosis and appropriate surgical management before the development of larger curves, since certain variants of congenital scoliosis have been known to progress more rapidly in comparison to other types of scoliosis [1,2]. Surgical treatment is usually recommended for patients with severe spinal deformity, but it is extremity challenging for the pediatric patients [1]. Early surgical intervention contributed to preventing the development of local deformities and secondary structural curves allowing normal growth in unaffected lesion of the spine [1,2,3,4,5]. Despite these recommendations, it is not uncommon to see cases of neglected congenital scoliosis, presenting in adulthood (after 18 years) [1,2]. There are several reasons for such a late presentation: a previously well-balanced deformity that was not exteriorly visible, as a result of ignorance on the part of care takers and, in some cases, due to fear of surgery [3]. It is known that, as time progresses, these curves become larger and stiffer rendering a surgical correction more challenging [4]. In addition, the deformation of costal bones frequently occurs causing secondary pulmonary insults such as restrictive lung disease and thoracic insufficiency [3]. Such larger and stiffer curves can theoretically make these patients more susceptible to higher chances of spinal cord injury during surgical interventions [4,5]. Late surgery can lead to the conducting of procedures, such as osteotomy and thoracoplasty, with associated risks [4,5,6]. In cases of severe congenital scoliosis, a combined anterior and posterior approach has been conventionally used, conducted in a sequential or staged manner to acquire flexibility by anterior release, followed by posterior corrective surgery [6,7]. In recent years, the three-column stability offered by pedicle screws allowed for a single-stage correction through a posterior-only approach [8,9,10]. However, at present, there is a dearth of research on the surgical outcome of the single-stage posterior-only approach in neglected congenital scoliosis (patients over 18 years of age). With this background, the objective of our study was to evaluate the surgical outcomes, including complication rates of single-stage posterior-only approaches to the correction of neglected congenital scoliosis. The study also aims to determine the age-related surgical efficacy of the posterior only approach for congenital scoliosis. 2. Materials and Methods 2.1. Study Design and Patients Group With the approval of an institutional review board, a retrospective chart review of all patients who underwent correction surgery for congenital scoliosis at our Scoliosis Research center from 2007 to 2012 was conducted. Among the enrolled patients, only patients who met the following conditions were primarily selected for this study: (1) Congenital scoliosis patients who were treated in a single-stage operation, (2) only a posterior surgical approach was used, and (3) minimum 2-year follow-up period. Secondarily, the following patients were excluded: (1) Revisional scoliosis surgery, (2) patients who may have had scoliosis due to other metabolic diseases, and (3) patients whose diagnosis could not be accurately identified. The selected patients were divided into 3 groups based on the age at which surgical intervention was performed. Division of the three groups was based on the growth spurt at 11 years of age and the completion of growth at the age of 18. Group A with age range of 7–11 years, Group B with age range of 12–18 years, and group C (neglected congenital scoliosis group) included patients who were over 18 years old at time of surgical intervention. The surgical results of the neglected congenital scoliosis (Group C) group were evaluated in comparison to the two control groups (Group A and B). For radiologic evaluation, whole-spine anterior–posterior (AP) and lateral radiographs were taken in all patients enrolled in this study. Through these radiographies, coronal alignment and sagittal balance were evaluated. Preoperative three-dimensional computed tomography (CT) was taken in all patients. Based on the CT results, the type of congenital scoliosis and the location of the congenital vertebrae were identified and a surgical plan was established based on these data of CT. Immediately after surgery, whole-spine AP and lateral radiographs were taken to confirm the status of the screw insertion and correction. Secondary radiographic imaging was performed 2 to 3 weeks after the operation, when the patient performed ambulation smoothly and could achieve a standing posture by themselves. To verify the maintenance of surgical correction, whole-spine AP and lateral radiographic images were taken at 3, 6 months, and 1 year after surgery and at the last follow-up. 2.2. Surgical Intervention In this study, all enrolled patients underwent spinal correction while performing spinal cord neuromonitoring using a motor-evoked potential (MEP) device. The monitoring of the spinal cord using MEP was continued until the end of the operation. The osteotomy was performed in accordance with Winter’s classification [11,12]. Single- or double-vertebral body resections, such as hemi- or block-vertebral body resections, were performed in the case of simple segmentation or formation defects by Winter’s classification. Smith-Peterson osteotomy and/or posterior multilevel crack osteotomy and/or vertebral column resection were performed with or without vertebral body resection in the case of coronal and sagittal imbalances of long segments with congenital vertebral anomaly [13]. A unilateral bar resection was also performed in the case of congenital scoliosis with unilateral bar. If the patients had a rib deformity and/or decreased flexibility of vertebral body, rib resection was also performed to obtain the flexibility of a vertebral body in the surgical process of unilateral bar resection. The 2-stage operation was performed in the case of a higher intraoperative bleeding, such as mixed-type bleeding, and/or intraoperative signal change of neuromonitoring systems, such as motor-evoked potential. 2.3. Measurements of Parameters Hospital charts were reviewed for clinical details, per-operative findings and complications. For each group, the following factors were assessed: hospital stay, intensive care unit (ICU) admission, type of congenital scoliosis, extent of spine fusion, incidence of thoracoplasty, post-operative complications such as infection, pulmonary complications (hemothorax or pneumothorax), neurological deficit, re-operation and cerebro-spinal fluid (CSF) leakage. Radiological analysis was conducted by a review of preoperative, postoperative (secondary post-operative radiography with standing posture), and last-follow-up radiographs. Coronal alignment was evaluated by Cobb angle, coronal balance (CB), T1 tilt angle (T1 angle), and T1 clavicle angle (CA). Cobb angle was used to calculate the postoperative correction rate (postoperative Cobb angle/preoperative Cobb angle × 100%). For coronal balance, left deviation from the central axis was marked as positive value, whereas right deviation was marked as negative value. For the CA and T1 angles, positive value was given for upper left area, and negative value was given for upper right area. When these values were compared to a reference value of 0, they were converted to an absolute value. In order to assess sagittal balance, sagittal vertical axis (SVA), thoracic kyphosis (TK), and lumbar lordosis (LL) were measured. SVA gave a positive value for anterior displacement and negative value for posterior displacement. This was converted to an absolute value when comparing it to the reference value of 0. All data of enrolled patients were described as median (range). 2.4. Statistical Analysis Statistical analysis was performed using the SPSS program (version 18.0; IBM, Armonk, NY, USA); the Wilcoxon signed rank test and Kruskal–Wallis test were used for comparing mean values of continuous data, and the McNemar-Browker test and Fisher’s exact test was used to analyze categorical values. Post hoc analysis was performed by Bonferroni correction. p-values < 0.05 were considered statistically significant. 3. Results From 2007 to 2012, a total of 58 patients underwent congenital scoliosis surgery. Among them, a total of 37 patients met the inclusion and exclusion criteria for the study. Control groups of Group A (Figure 1) and B (Figure 2) included 11 and 17 patients, respectively, and experimental group C (Figure 3) included 9 patients. As there was no statistically significant difference in the gender ratio of the group, type of congenital scoliosis, preoperative Cobb angle and follow-up period, the comparison between the three groups was made assuming that there were no differences between them. All cases in Group C required vertebral body osteotomy, with 5 cases (55%) needing thoracoplasty (Table 1). The preoperative Cobb angle was 75° (50–104°), and postoperatively, it was 37° (15–75°), which shows a correction rate of 53% (28–71%). In case of control groups, the Cobb angle changed from 66° (10–152°) to 15° (2–63°) and 64° (21–130°) to 27° (2–56°), in Group A and Group B, respectively. With the correction rates being 77% (55–98%) for Group A and 57% (16–100%) for Group B. The correction rate showed a statistically significant difference between the three groups (p = 0.006). In the post hoc analysis, the comparisons between group A and B, group A and C were significant (p = 0.024, and p = 0.01), but group B and C were not significant. The values of coronal factors did not show significant differences between the three groups (Table 2). Sagittal factors were as described in Table 3. On average, the SVA of Group C was corrected by 3 mm. TK was corrected from 43° (2–89°) to 35° (6–62°) and the LL from 34° (−14–73°) to 29° (−11–67°). Sagittal factors between the groups did not show statistically significant differences (Table 3). The operation time, intraoperative blood loss, length of hospitalization, ICU admission, and complications in enrolled patients were recorded and are shown in Table 4. The surgical time of Group B and C was relatively longer than that of Group A; however, it was not statistically significant (p = 0.111). The amount of blood loss in Group B and C was larger than that of Group A, where the difference was statistically significant (p = 0.015). Regarding the complications, Group C showed a higher complication rate (88.9%) than Group A (18.2%) and group B (17.6%) with a statistical significance (p < 0.005). The occurrence of pulmonary complications for pneumothorax were higher in Group C. Although not statistically significant, other complications occurred more frequently in Group C (Table 4). 4. Discussion The treatment of congenital scoliosis is focused on early diagnosis and proper surgical intervention before the development of severe deformity [1,2,3]. Some studies reported on surgical outcomes by age at the time of surgery [13,14]. However, no studies were conducted to compare the efficacy regarding the benefits and risks of a single-stage correction by a posterior approach in neglected congenital scoliosis. From our study, the surgical intervention of the patients with neglected congenital scoliosis showed a comparable correction rate but still had risks in terms of blood loss, complication rate, and difficulties in surgical correction. The age of intervention is one of the most crucial factors in the management of congenital scoliosis [14,15]. This is due to the fact that it is better to stabilize a curve when it is small, and prevent it from worsening, than to correct the deformity when the child is grown up, when the curve becomes larger and stiffer [1,12]. Additionally, curves of congenital scoliosis are characterized by a rapid progression during first five years of life and at a pubertal growth spurt [16]. Hence, for certain variants of congenital scoliosis, the surgical approach varies based on the time of intervention along the natural course of the curves [2]. For example, for patients younger than 5 years with congenital scoliosis, it is known that fusion can have deleterious effect on thoracic volume [17]. Hence, in the absence of rib fusions, the growing rod technique has replaced spinal arthrodesis as the standard of care in this age group [18]. However, instrumentation and fusion at the earliest possible age are shown to have favorable results in congenital scoliosis patients presenting in juvenile and adolescent age groups [8,9,14]. In recent years, a single-stage posterior pedicle screw-based approach has become well-established as a safe and effective method in this age group [9,10]. Nevertheless, the outcomes of surgical intervention in adults with neglected congenital scoliosis (>18 years) are yet to be elucidated. There is paucity of literature on single-stage posterior corrections for neglected congenital scoliosis. Recently, Sarlak et al. reported an isolated posterior approach in 14 congenital scoliosis patients with a mean age of 14.9 years at surgery (range: 10 to 25 years) [10]. In the study by Sarlak et al., the deformities were mainly corrected by the compression of the convex deformity side with the segmental resection of three apical ribs after pedicle screw instrumentation without any usage of osteotomy techniques, which was able to achieve a 51.6% correction rate [10]. In a more recent study, Ayvaz M et al. reported the results of single-stage posterior correction in eighteen adolescent congenital kyphoscoliosis patients with a mean age of 13.6 years (range, 11–16 years) [19]. Chevron osteotomies were performed at apical segments (three to seven levels) with concave rib osteotomies, resulting in a correction rate of 62% [19]. Our Cobb angle correction rates in Group B and Group C were similar to the results of the above studies [10,19]. In our study in Group C (the neglected congenital scoliosis group), the Cobb angle was corrected by 39° (range, 26–53°) with a correction rate of 53% (range, 28–71%), which was a similar to correction in the adolescent group, Group B. However, in our research, we also found that in patients younger than 11 years—denoted as the juvenile group, Group A—the correction rate was significantly higher than that of the adult and adolescent groups, Groups B and C (77% vs. 57% and 53%). In accordance with these results, it can be stated that, for similar Cobb angles, an earlier surgical intervention can result in a more effective correction than delayed intervention. It is possible that this difference is due to the curves becoming more rigid with age, which coincides with other studies [9,10,13,14]. Additionally, the concomitant progression of the deformation of the rib cage can add to the rigidity and the magnitude of the curve. The correction rates in Group C, point to the fact that, even though the skeletal curves become stiff with age, they can still yield to posterior-only approaches owing to the three-column stability of pedicle screws and release versatility of the available osteotomies [9]. Though not statistically significant the surgical time in Group A was shorter than in Group B and Group C. Additionally, the average intraoperative blood loss in Group A was less than that in Group B and Group C. This difference in average blood loss between Group A and Group B and C was statistically significant (p = 0.015). The following factors could be attributed to the relatively decreased blood loss: Firstly, due to their relatively young age, Group A patients required less additional osteotomy or costectomy than in Group B and C, owing to more flexible vertebrae, except at the site of deformation. Secondly, the amount of soft-tissue detachment for the approach to osteotomy or costectomy could have been smaller, obtaining flexibility during the posterior approach of vertebral body detachment. In the study by Ayvaz M et al. on neglected adolescent congenital scoliosis, the authors reported similar results at a surgical time of 292 min with average bleeding of 989 mL [19]. In a similar adolescent age group, Sarlak et al. also reported similar results for a mean operation time of 3.5 h (210 min) and a mean blood loss of 980 mL (range: 450 to 2200 mL) [10]. The incidence of surgical complications was significantly higher in Group C compared to Group A and B. The authors consider that the following are reasons for the high incidence of surgical complications in Group C: Various difficult surgical techniques are needed in the cases of neglected congenital scoliosis (Group C), which is reflected on the result of complication rate [9]. In patients with neglected congenital scoliosis (Group C), rib deformity and spontaneous fusion between the rips around the deformed spine were often accompanied by congenital spinal deformity, and the flexibility of the vertebral body was often poor. Therefore, there were many cases of rib resection in order to obtain an appropriate correction angle during corrective spine surgery (rib resection rates 9%, 41% and 55% in Groups A, B and C) [19]. Due to these reasons, the incidence of pulmonary complications such as pneumothorax and hemothorax was higher in Group C. Ayvaz et al. also reported that adolescent congenital scoliosis patients underwent rib resections during surgery and reported pulmonary complications after surgery [19]. Furthermore, in younger groups, severe thoracic deformity limits lung capacity, for which deformity correction improved pulmonary function. The improvement of thoracic cage after deformity correction permits the growth of the lungs during development [9]. However, in mature adult groups, all were fully grown, which called for more difficult surgical techniques, and more pulmonary complications appeared in limited lung capacity [9,14]. The incidence of neurological deficits in Group C was relatively higher than in Groups A and B (9%, 0%, 22% in Group A, B and C), but did not reach statistically significance (p = 0.083). We speculate that, in the process of correction of the spine, an uncontrolled traction force was transmitted to the spinal cord and dynamic instability and venous engorgement or arterial stretching around corrected deformed spine can occur. All these situations might have caused injury [20]. The risk of such injury was higher in Group C due to a decrease in the flexibility of aged spines, and the progressive deformation of vertebral body caused by neglect [17]. Rajavelu et al. reported that, when performing surgery to correct neglected congenital spinal deformity—if there is a kyphotic or kyphoscoliotic deformity in the congenitally deformed vertebra, a formational defect and mixed type of vertebral anomalies, and proximal thoracic vertebral lesions—there was a high probability of developing a neurological deficit [20]. In this study, type 1 and 3 other types of spinal deformity were relatively common in Group C (67%, 45% in Group A, 29% in Group C). The lesser complication rates in Group A of our study population were mirrored in previously published reports on the posterior correction of congenital scoliosis [21,22,23]. From our study, the surgical correction of neglected congenital scoliosis had acceptable outcomes regardless of age at surgery. However, delayed surgery in congenital scoliosis made it difficult for deformity correction due to an increased rigidity of the vertebral body and the necessity of multiple and various types of osteotomy, which showed increased postoperative complications [24,25]. Furthermore, Group C showed a higher fusion level, intraoperative bleeding, and hospital stay than Group A and B, indicating that the risk of surgery was higher in Group C. Therefore, even if single-stage correction by a posterior approach also obtained a comparable correction rate, early surgery was important for reducing complication rates because the case of neglected congenital scoliosis requires extensive surgical procedures. Our study is limited by its retrospective nature and the small number of patients, who could not be categorized based on the type of congenital scoliosis and various surgical techniques [26]. Additionally, some comparisons that showed no significant statistical significances may be due to our small sample size. However, considering the paucity of neglected congenital scoliosis patients, gathering the patient groups by homogeneity of age and type of deformity is very difficult. Additionally, no clinical satisfaction measure was assessed to study the impact of intervention on the quality of life of the patients as there is no scale or index which has been validated for the measurement of clinical outcomes in congenital scoliosis. In spite of these limitations, this study is still relevant as it enabled us to ascertain the effectiveness of a posterior-only approach for adult neglected congenital scoliosis and demonstrated the differences in outcomes of congenital scoliosis based on the age of surgical intervention. 5. Conclusions A single-stage correction with pedicle screws through a posterior-only approach achieves a significant correction with improved outcomes, even in neglected cases. However, the early correction for younger age patients is still more beneficial in terms of bleeding loss, complications rate, and flexible curve correction. Author Contributions Conceptualization, J.-Y.H., J.H.Y. and D.-G.C.; methodology, H.J.K., J.H.Y. and S.W.S.; validation, H.J.K., J.H.Y. and Y.N.; investigation, H.J.K., J.H.Y.; data curation, H.J.K.; writing—original draft preparation, J.-Y.H., J.H.Y. and D.-G.C.; writing—review and editing, H.J.K., J.H.Y. and D.-G.C.; visualization, J.H.Y. and S.W.S.; supervision, D.-G.C.; project administration, D.-G.C. and S.W.S. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by a grant of Korea University Medical College (K2209231). 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 Korea University Guro Hospital (IRB number: 2021GR0045), approved date: 28 January 2021. Informed Consent Statement Patient consent was waived due to retrospective design. Data Availability Statement The data collected for this study, including individual patient data, will not be made available. Conflicts of Interest The authors declare no conflict of interest. Figure 1 A 9-year-old boy patient (Group A) presented to the orthopedic clinic due to congenital scoliosis. (A) Clinical photograph. (B) the whole-spine anteroposterior view showed congenital scoliosis. The Cobb angle was 79°. (C) A hemi-vertebra resection and pedicle screw instrumentation by posterior approach were performed, and the curvature was corrected to 18° with a correction rate of 77% after the surgery. R: right-sided on radiographs. Figure 2 A 12-year-old adolescent patient (Group B) presented to the orthopedic clinic due to congenital scoliosis. (A) Clinical photograph: the whole-spine anteroposterior view, and three-dimensional computed tomography image showed congenital scoliosis. The Cobb angle was 81°. (B) Single-stage posterior correction with multiple crack osteotomies was performed, and the curvature was corrected to 29° with a correction rate of 67% after the surgery. R: right-sided on radiographs. Figure 3 A 27-year-old male patient (Group C) presented to the orthopedic clinic due to neglected congenital scoliosis. (A) Clinical photograph and the whole-spine anteroposterior view showed congenital scoliosis. The Cobb angle was 89°. (B) Single-stage posterior correction by posterior vertebral column resection and thoracoplasty were performed, and the curvature was corrected to 40° with a correction rate of 55% after the surgery. R: right-sided on radiographs. jcm-11-02278-t001_Table 1 Table 1 Demographics of enrolled patients. Factors Group A (7–11 Years) Group B (12–18 Years) Group C (Age > 18 Years) p Value Age (years) 8.8 (7–11) 13.8 (12–15) 27.3 (18–15) <0.001 Sex (male/female) 6/5 9/8 6/3 0.834 Follow-up period (month) 95.4 (53–131) 91.3 (53–137) 93.4 (60–146) 0.998 Pre-op Cobb angle (°) 66 (10–152) 64 (21–130) 75 (50–104) 0.259 Congenital scoliosis type (1/2/3) 3/6/2 3/12/2 3/3/3 0.433 Congenital vertebrae resection (hemi or block vertebral body resection) 7 8 7 0.012 Osteotomy except congenital vertebrae resection 1 7 9 - Additional osteotomy 4 9 7 0.180 Correction without osteotomy 1 2 0 - Thoracoplasty (yes/no) 1/10 7/11 5/4 0.238 Group A, B, C are neglected congenital scoliosis aged between 7 to 11 years, congenital scoliosis aged between 12 and 18 years, and neglected congenital scoliosis aged over 18, respectively. Congenital scoliosis type was differentiated to the defect of vertebral segmentation (type 1), defects of vertebral body formation (type 2) and mixed anomalies (type 3). It was also described in the same order as in this table. Additional osteotomies used for correction of spinal deformity are Smith-Peterson, Ponte, multiple crack osteotomy and vertebral column resection. Significant differences are accepted for p < 0.05. jcm-11-02278-t002_Table 2 Table 2 Coronal factors of enrolled patients. Factors Group A (7–11 Years) Group B (12–18 Years) Group C (Age > 18 Years) p Value Pre-Op Cobb angle (°) 66 (10–152) 64 (21–130) 75 (50–104) - Post-Op Cobb angle (°) 15 (2–63) 27 (2–56) 37 (15–75) - ∆ Cobb angle 51 (15–100) 38 (7–130) 39 (26–53) 0.970 Statistical significance * (Cobb angle) 0.003 <0.001 0.008 - Correction rate $ (%) 77 (55–98) 57 (16–100) 53 (28–71) 0.006 Pre-Op Coronal balance (mm) 1 (−25–44) −1 (−65–59) 6 (−17–50) - Post-Op Coronal balance (mm) 6 (−15–37) −4 (−38–36) 9 (−32–41) - ∆ Coronal balance (mm) 5 (−3–17) 9 (−31–65) 1 (−19–11) 0.348 Statistical significance * (Coronal balance) 0.575 0.438 0.678 Pre-Op T1 tilt angle (°) 0 (−15–23) −5 (−30–33) −2 (−26–33) Post-Op T1 tilt angle (°) 0 (−15–9) −1 (−14–22) 1 (−14–16) ∆ T1 tilt angle (°) 2 (−11–14) 7 (−17–28) 4 (−5–17) 0.472 Statistical significance * (T1 tilt angle) 1.00 0.271 0.173 Pre-Op T1 clavicle angle (°) 0 (−9–7) −1 (−14–9) −2 (−6–0) Post-Op T1 clavicle angle (°) 0 (−12–9) 0 (−9–8) −1 (−5–2) ∆ T1 clavicle angle (°) 0 (−8–4) 1 (−7–6) 1 (−4–4) 0.595 Statistical significance * (T1 clavicle angle) 0.477 0.232 0.161 Group A, B, C are neglected congenital scoliosis aged between 7 to 11 years, congenital scoliosis aged between 12 and 18 years, and neglected congenital scoliosis aged over 18, respectively. Statistical significance * was statistically analyzed between preoperative and postoperative variables. $ Post hoc analysis of different groups by Bonferroni test at 95% confidence level. Group A vs. Group B: p = 0.024, Group A vs. Group C: p = 0.010, and Group B vs. Group C: p = 1.00. jcm-11-02278-t003_Table 3 Table 3 Sagittal factors of enrolled patients. Factors Group A (7–11 Years) Group B (12–18 Years) Group C (Age > 18 Years) p Value Pre-Op SVA (mm) 7 (−46–105) 5 (−60–124) 27 (−27–117) Post-Op SVA (mm) 26 (−2–70) 15 (−66–104) 37 (−30–182) ∆ SVA (mm) 3 (−30–39) 9 (−68–104) 3 (−65–78) 0.910 Statistical significance * (SVA) 0.169 0.196 0.678 Pre-Op TK (°) 55 (15–119) 28 (3–70) 43 (2–89) 0.094 Post-Op TK $ (°) 41 (15–105) 20 (3–49) 35 (6–62) 0.020 Statistical significance * (TK) 0.168 0.017 0.477 Pre-Op LL (°) 49 (2–75) 47 (−26–100) 34 (14–73) 0.5 Post-Op LL (°) 46 (28–75) 42 (0–72) 29 (11–67) 0.303 Statistical significance * (LL) 0.790 0.218 0.859 Group A, B, C are neglected congenital scoliosis aged between 7 to 11 years, congenital scoliosis aged between 12 and 18 years, and neglected congenital scoliosis aged over 18, respectively. Statistical significance * was statistically analyzed between preoperative and postoperative variables. $ Post hoc analysis of different groups by Bonferroni test at 95% confidence level. Group A vs. Group B: p = 0.028, Group A vs. Group C: p = 1.00, and Group B vs. Group C: p = 0.161. SVA = sagittal vertical axis; TK = thoracic kyphosis; LL = lumbar lordosis. jcm-11-02278-t004_Table 4 Table 4 Operative factors and complications of enrolled patients. Factors Group A (7–11 Years) Group B (12–18 Years) Group C (Age > 18 Years) p Value Operation time (min) 229 (100–386) 326 (152–710) 316 (198–463) 0.111 Fusion extent 7.8 (1–13) 9.0 (1–16) 8.8 (2–15) 0.482 Bleeding loss $ (mL) 1564 (300–4000) 3271 (700–6000) 3644 (800–8000) 0.015 Hospital stay (day) 20 (11–47) 20 (12–61) 34 (13–141) 0.337 ICU stay (yes/no) 1/10 3/14 1/8 1.00 Complications 2 3 8 <0.005 Hemothorax 0 1 1 0.211 Pneumothorax 0 2 5 0.003 Infection 1 0 0 1.00 Neurologic deficit 1 0 2 0.083 CSF leakage 0 0 0 - Group A, B, C are neglected congenital scoliosis aged between 7 to 11 years, congenital scoliosis aged between 12 and 18 years, and neglected congenital scoliosis aged over 18, respectively. $ Post hoc analysis of different groups by Bonferroni test at 95% confidence level. Group A vs. Group B: p = 0.025, Group A vs. Group C: p = 0.046, and Group B vs. Group C: p = 1.00. ICU, intensive care unit; CSF, cerebro-spinal fluid. 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Musaoğlu R. Buluç L. Isolated pedicle screw instrumented correction for the treatment of thoracic congenital scoliosis J. Spinal Disord. Tech. 2010 23 525 529 10.1097/BSD.0b013e3181c2f51b 20924297 11. McMaster M.J. Ohtsuka K. The natural history of congenital scoliosis. A study of two hundred and fifty-one patients J. Bone Jt. Surg. Am. 1982 64 1128 1147 10.2106/00004623-198264080-00003 12. Winter R.B. Congenital scoliosis Clin. Orthop. Relat. Res. 1973 93 75 94 10.1097/00003086-197306000-00010 4722963 13. Yang J.H. Suh S.W. Cho W.T. Hwang J.H. Hong J.Y. Modi H.N. Effect of posterior multilevel vertebral osteotomies on coronal and sagittal balance in fused scoliosis deformity caused by previous surgery: Preliminary results Spine (Phila Pa 1976) 2014 39 1840 1849 10.1097/BRS.0000000000000555 25299167 14. Chang D.G. Suk S.-I. Kim J.-H. Ha K.-Y. Na K.-H. Lee J.-H. Surgical outcomes by age at the time of surgery in the treatment of congenital scoliosis in children under age 10 Spine J. 2015 15 1783 1795 10.1016/j.spinee.2015.04.009 25862509 15. Mohanty S.P. Kanhangad M.P. Saifuddin S. Narayana Kurup J.K. Pattern of syringomyelia in presumed idiopathic and congenital scoliosis Asian Spine J. 2021 15 791 798 10.31616/asj.2020.0216 33189109 16. Kobayashi K. Ando K. Nakashima H. Machino M. Morozumi M. Kanbara S. Ito S. Inoue T. Yamaguchi H. Mishima K. Scoliosis caused by limb-length discrepancy in children Asian Spine J. 2020 14 801 807 10.31616/asj.2019.0374 32429019 17. Fletcher N.D. Bruce R.W. Early onset scoliosis: Current concepts and controversies Curr. Rev. Musculoskelet. Med. 2012 5 102 110 10.1007/s12178-012-9116-0 22477364 18. Wang S. Zhang J. Qiu G. Wang Y. Li S. Zhao Y. Shen J. Weng X. Dual growing rods technique for congenital scoliosis: More than 2 years outcomes: Preliminary results of a single center Spine (Phila Pa 1976) 2012 37 E1639 E1644 10.1097/BRS.0b013e318273d6bf 22990366 19. Ayvaz M. Olgun Z.D. Demirkiran H.G. Alanay A. Yazici M. Posterior all-pedicle screw instrumentation combined with multiple chevron and concave rib osteotomies in the treatment of adolescent congenital kyphoscoliosis Spine J. 2014 14 11 19 10.1016/j.spinee.2012.10.016 23218976 20. Rajavelu R. Shetty A.P. Viswanathan V.K. Kanna R.M. Rajasekaran S. Analysis of risk factors and treatment outcome in patients presenting with neglected congenital spinal deformity and neurological deficit Spine Deform. 2022 10 401 410 10.1007/s43390-021-00427-y 34665447 21. Nakamura H. Matsuda H. Konishi S. Yamano Y. 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==== Front Molecules Molecules molecules Molecules 1420-3049 MDPI 10.3390/molecules27092793 molecules-27-02793 Article Application of Levan-Rich Digestate Extract in the Production of Safe-to-Use and Functional Natural Body Wash Cosmetics https://orcid.org/0000-0002-0498-6415 Wasilewski Tomasz 12 https://orcid.org/0000-0002-9916-769X Seweryn Artur 12* Pannert Dominika 2 Kierul Kinga 3 https://orcid.org/0000-0002-4001-9983 Domżał-Kędzia Marta 34 https://orcid.org/0000-0003-4038-4232 Hordyjewicz-Baran Zofia 5 https://orcid.org/0000-0002-1453-8376 Łukaszewicz Marcin 4 https://orcid.org/0000-0001-9821-8793 Lewińska Agnieszka 36* Morikawa Toshio Academic Editor 1 Department of Industrial Chemistry, Faculty of Chemical Engineering and Commodity Science, Kazimierz Pulaski University of Technology and Humanities in Radom, Chrobrego 27, 26-600 Radom, Poland; tomasz.wasilewski@uthrad.pl 2 Research and Development Department, ONLYBIO.life S.A., Jakóba Hechlińskiego 6, 85-825 Bydgoszcz, Poland; dominika.pannert@boruta-zachem.pl 3 Research and Development Department, INVENTIONBIO S.A., Jakóba Hechlińskiego 4, 85-825 Bydgoszcz, Poland; kinga.kierul@inventionbio.pl (K.K.); marta.domzal@inventionbio.pl (M.D.-K.) 4 Faculty of Biotechnology, University of Wroclaw, Joliot-Curie 14a, 50-383 Wroclaw, Polandmarcin.lukaszewicz@uwr.edu.pl (M.Ł.) 5 Lukasiewicz Research Network-Institute of Heavy Organic Synthesis “Blachownia”, Energetykow 9, 47-225 Kedzierzyn-Kozle, Poland; zofia.hordyjewicz@icso.lukasiewicz.gov.pl 6 Faculty of Chemistry, University of Wroclaw, Joliot-Curie 14, 50-383 Wroclaw, Poland * Correspondence: a.seweryn@uthrad.pl (A.S.); agnieszka.lewinska@chem.uni.wroc.pl or agnieszka.lewinska@inventionbio.pl (A.L.); Tel.: +48-48-361-7552 (A.S.); +48-71-375-7324 (A.L.) 27 4 2022 5 2022 27 9 279311 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/). The study focused on the evaluation of the possibility of using a levan-rich digestate extract in the production of safe and functional body wash cosmetics. Model shower gels were designed and formulated on the basis of raw materials of natural origin. Prepared prototypes contained various extract concentrations (16.7; 33; 50%). A gel without extract was used as a reference. The samples were evaluated for their safety in use and functionality. The results showed that the use of high-concentration levan-rich digestate extract in a shower gel resulted in a significant reduction in the negative impact on the skin. For example, the zein value decreased by over 50% in relation to the preparation without the extract. An over 40% reduction in the emulsifying capacity of hydrophobic substances was also demonstrated, which reduces skin dryness after the washing process. However, the presence of the extract did not significantly affect the parameters related to functionality. Overall, it was indicated that levan-rich digestate extract can be successfully used as a valuable ingredient in natural cleansing cosmetics. plant extracts Bacillus subtilis cosmetics safety skin irritation quality The National Centre for Research and DevelopmentPOIR.01.01.01-00-1433/19 This research was funded by The National Centre for Research and Development, Poland; grant number POIR.01.01.01-00-1433/19. ==== Body pmc1. Introduction In terms of composition, shower gels are typically formulated as aqueous solutions of anionic surfactants and additionally enriched with compounds from the groups of non-ionic and amphoteric surfactants and various additives, including preservatives, colorants, plant extracts or pH regulators. The viscosity of these formulations is usually modified by adding sodium chloride or using polymers [1,2]. In recent years, cosmetics manufacturers have been increasingly turning their interest towards the development and production of natural cosmetics. This shift has largely been driven by changing consumer expectations and the search for safe products. There have been a number of scientific studies evaluating the application of various types of plant-based raw materials [3,4] or ingredients obtained through biotechnological processes [5,6,7,8] as cosmetic components. A key aspect in evaluating the quality of cosmetics, especially the types intended for personal hygiene, is the maximum possible reduction in adverse effects on the skin surface. It is expected that the washing process leaves the skin in the best possible condition, without any undesirable effects such as skin irritation, redness or excessive dryness. Based on the current state of knowledge, measures to reduce the skin irritating effect of body wash cosmetics rely on mechanisms that minimize interactions between cosmetic ingredients and epidermal structural proteins. These mechanisms relate to changes in the structure of surfactant aggregates forming in the wash bath which contribute to the development of skin irritation as a result of additives incorporated into the cosmetic formulation. Remedial measures consist of lowering the concentration of free surfactant monomers in the solution as they are primarily responsible for interactions with skin proteins or changes in the structure of emerging micellar aggregates [9]. These effects are achieved by adding surfactants with a documented low skin irritation potential [1,10,11], polymers [2,12], divalent metal salts [13], hydrophobic substances [14] or plant extracts [3,4] to cosmetic formulations. A particularly interesting trend in the development of cosmetics is the application of plant-based raw materials and ingredients obtained in biotechnological processes, including fermentation [15,16]. The use of fermented ingredients in cosmetic formulations is becoming more and more popular in modern cosmetics. These types of ingredients increase the bioavailability of important ingredients with a cosmeceutical effect, making them stronger and more effective than normal. They facilitate the absorption of the cosmetic into the deeper layers of the skin. The fermentation process itself enables the synthesis of new substances that can positively affect the condition of the skin, and their natural production reduces the risk of irritation. These ingredients can also influence the skin microbiome, positively influencing the natural microflora and preventing excessive growth of pathogenic microflora. Fermented ingredients can enrich the finished cosmetic formulation with various anti-aging or beautifying compounds and visibly improve the condition of the skin. Compounds that can be identified in various types of fermented solutions include amino acids and peptides, vitamins, enzymes, minerals, antioxidants, etc. Extract of rice bran fermented with Aspergillus oryzae showed higher tyrosinase and elastase inhibition activity than other tested extracts [17]. Red ginseng Panax ginseng (Order: Apiales, Family: Araliaceae, Genus: Panax) fermented with Lactobacillus brevis showed greater skin whitening and anti-wrinkle activity than unfermented ginseng [18]. Bacillus subtilis is a bacterium known to synthesize various compounds for cosmetic use. One of the ingredients often found in cosmetics is Bacillus Ferment. It is used as a source of proteolytic enzymes that gently exfoliate dead cells. It can improve the penetration of various substances through the skin [19]. However, raw materials obtained by fermentation with B. subtilis may also show other properties depending on the conditions of the process carried out. It has been shown that B. subtilis natto—fermented Radix astragali, which is dried root of Astragalus membranaceus (Order: Fabales, Family: Fabaceae or Leguminosae, Genus: Astralagus L.)—had a stimulating effect on collagen synthesis in human fibroblast and keratinocyte cells [20] and also had a positive effect on the synthesis of hyaluronic acid [21]. B. subtilis is also capable of synthesizing other compounds of interest for cosmetic use, e.g., biopolymers. One of these is levan, which is a fructose polymer. Its potential in cosmetic applications has already been demonstrated [16]. The polymer itself has antioxidant properties [22], is able to increase skin hydration [23,24] and is not toxic to human cells [16]. As a polymer, it can also reduce the irritating effects of other components, in particular those of surfactants [9]. The main goal of our research was to show that fermentation ingredients are not a short-lived fashion in cosmetics but that they are an important step towards a sustainable industry, and fermentation biotechnology could become a turning point in the development of highly functional cosmetics. The aim of the presented study was to demonstrate the reduction of the irritating effect of effective ionic surfactants in the formulations of washing cosmetics with the use of ferment rich in the biopolymer levan (Bacillus Ferment Extract), based on the example of the developed model recipe. Verification of the aim required empirical tests, including the assessment of safety in use (zein value, bovine serum albumin test) and functionality (foaming ability, detergent properties, color, rheological characteristics and microbiological testing). 2. Results and Discussion 2.1. The Optimization of the Fermentation Process Focused on Obtaining Ferment Rich in Levan, Polymer and Divalent Metals Ions The type and concentration of inorganic salt can be translated into the structure of the bulk phase and the performance properties. Our previous research [25] showed that magnesium salt resulted in more favorable characteristics than sodium salt due to the surface activity of the formulations. Additionally, the formulations in which magnesium salt was used caused much less irritation compared with the formulations with monovalent ions. The ICP analysis allowed the determination of the content of monovalent and divalent ions in the obtained Bacillus-fermented supernatant. A sample of 50 g of tested fermented material contained 4.14 mg of magnesium, 69.44 mg of sodium, 96.34 mg of potassium, 2.90 of calcium, 0.078 mg of zinc, 30.83 mg of phosphorus and 8.39 mg of sulfur ions. Sodium, potassium, calcium, magnesium and phosphate are some of the components of NMF (natural moisturizing factor) [26]. These minerals are capable of restoring moisture as a result of their hygroscopic characteristics. Both calcium and magnesium ions support the induction of skin barrier repair mechanisms and improve its functions [27,28]. Calcium ions also play an important role in regulating keratinocyte differentiation [28,29]. The healing effects of sulfur waters have been known for centuries. Sulfur-containing waters have a keratolytic effect, gently exfoliating the epidermis [30]. They also show bactericidal and antifungal properties [31]. The presence of various ions is also of a utility nature. Products containing monovalent metal salts are characterized by good performance parameters, i.e., the ability to wash, foam and emulsify fat, while divalent metal salts allow to obtain products with a high degree of safety in use [13]. Polymer and surfactants often appear side by side in emulsions, suspensions and other colloidal systems in many products relevant for the food, pharmaceutical and chemical industries. Mixtures of polymer and surfactant can exhibit molecular interactions that might affect the physicochemical properties of the system and result in an influence on thickening or stabilizing. The addition of a polymers to formulations containing anionic surface-active agents reduces the irritant potential of the surfactant [9]. Spectroscopic analysis confirmed the presence of levan, a fructose polymer, in the tested material obtained after fermentation of B. subtilis natto KB1. The obtained data are comparable with those obtained previously for this bacterial strain [16]. According to the 1H NMR spectrum, seven signals of chemical shift were observed at 4.17 (H-3), 4.08 (H-4), 3.93(H-5), 3.88 (H-6a), 3.75 (H-1a), 3.64 (H-1b) and 3.55 (H-6b) ppm. The FT-IR spectrum exhibited a strong band at 3430 cm−1, which was attributed to the hydroxyl (- OH) stretching vibrations of the polysaccharide. Bands from the carbon–hydrogen (C–H) stretching vibration were around 2933 cm−1, which confirmed the existence of fructose residue. The band at 1433 cm−1 was attributed to C–H. The bands around 1075 cm−1 were attributed to stretching vibrations of the glycosidic linkage C–O–C and C–OH groups. The absorption around 951 cm−1 was attributed to the stretching vibrations of the pyran ring. The band around 1636 cm−1 was evidence of bound water. The concentration of levan in the Bacillus-fermented supernatant was 5.04 ± 0.19%. Relevant spectra are presented in Figure 1. 2.2. Antimicrobial Activity of Ferment Rich in Levan The compounds obtained through the fermentation process with the use of various species of microorganisms and their use in cosmetic products is known. Thanks to the fermentation process, compounds are formed that are often characteristic of the microorganism used, with various effects. In the case of B. subtilis fermentation, antimicrobial, prebiotic and other compounds, including proteolytic enzymes, are formed. The Bacillus-fermented supernatant was tested against pathogenic microorganisms. Its antimicrobial activity, reducing cell biofilm and preventing their adhesion to the surface, was determined. First, the antimicrobial potential (Figure 2) and the MIC values were determined (Table 1). The antimicrobial potential was initially assessed in the agar diffusion test. After incubating the pathogenic microorganisms with the Bacillus-fermented supernatant, a visible zone of inhibition was observed (Figure 2). In the further course of the study, the MIC value of each test microorganism was determined. For each pathogenic microorganism tested, the MIC value was quite high (Table 1). The highest MIC values were recorded for S. epidermidis, S. aureus and E. coli, with 412.88 mg/mL. As for the P. aeruginosa, the MIC resulted with a value of 275.25 mg/mL. In the case of C. albicans, this value was lower and amounted to 206.44 mg/mL. The obtained values were the basis for selecting the concentration of Bacillus-fermented supernatant (BFS) in the finished formulation for cosmetic use. For comparison, the extracts obtained after the fermentation of B. amyloliquefaciens showed, inter alia, the inhibitory effect of S. aureus and S. epidermidis with MIC values of 25.0 μg/mL and 12.5 μg/mL, respectively [32]. Other potential cosmetic raw materials obtained through the fermentation process also show antimicrobial activity. One example is Lactobacillus-fermented plant juices showing activity against E. coli, S. aureus, P. aeruginosa, group A Streptococcus and C. albicans [33]. In the next stage of this research, the influence of Bacillus-fermented supernatant on the formed biofilm and adhesion capacity was determined. The SEM analysis revealed reductions in biofilm for all tested microorganisms after exposure to BFS (Figure 3). The untreated biofilm was compact and the test surface was densely covered. Under the influence of BFS, a reduction in the biofilm on the plate surface could be observed. This was also confirmed by the result obtained in the experiment with crystal violet. The biofilm reduction was on the level 67.41–93.16% and the greatest reduction was recorded for S. aureus (Table 1). Both the antimicrobial activity and the reduction in the biofilm may be due to the presence of levan in the Bacillus-fermented supernatant. Ağçeli and Cihangir found that levan has an antimicrobial and antibiofilm effect on pathogenic microorganisms [34]. Antibacterial activity of levan was evaluated against bacteria and the largest zone of inhibition was observed against E. coli at a concentration of 1000 μg/mL. Antibiofilm activity of levan was also evaluated, and results shown that levan concentrations inhibited biofilm formation of P. aeruginosa ATCC 27853, S. aureus ATCC29213, Klebsiella pneumoniae ATCC 4352, and C. albicans ATCC 10231 [34]. The morphology of the untreated cells showed their normal structure and smooth surface. Cells after BFS treatment exhibited a more irregular surface and visible morphological changes. Adhesion is the process by which microorganisms can stick to other cells or surfaces. Adhesion itself is a multi-stage process, but it is also the first stage in the formation of a microbial biofilm. The effect of BFS on the adhesion capacity was also observed. The reduction in adhesion to the polystyrene plaque ranged from 53.46 to 96.97% compared to untreated cells (Table 1). 2.3. Development of Formulations and Technologies to Obtain Shower Gels Containing Digestate Extract Studies exploring the application of levan-rich digestate extract to body wash cosmetics were conducted on the basis of originally designed shower gel formulations. When selecting their composition, the authors relied on the available literature [35,36] and their own expertise in the field of cosmetic technology [1,4,10,12,37]. Different cosmetic formulations contained varying concentrations of the extract. The extract was added to the cosmetics in place of water as the primary ingredient of the product. A reference product used in the studies was a prototypical cosmetic formulated without the raw material being evaluated. A detailed list of ingredients used in different prototypical shower gels under study is given in Table 2. The cosmetic formulations were prepared by carrying out the steps of the procedure outlined below. The prototypical cosmetics were produced using an MZUTL 5 homogenizing mixer from Urliński (producer: Urlinski, Warsaw, Poland). A total of 5 L of the cosmetic formulation was obtained in a single batch. Sodium coco sulfate was dissolved in water at 95 °C. Next, mixing was commenced (at 50 rpm), and the raw materials were added in the order specified in the formulation (up to and including the parfum). The ingredients were stirred until a clear homogeneous solution was obtained. In the next step, the pH was adjusted to 5.5. Afterwards, cocamidopropyl betaine was added and mixed into the formulation. The samples were set aside at room temperature for 24 h until the system was completely deaerated. The study samples exhibited full stability during the period of storage under normal sunlight conditions and at a normal temperature. 2.4. Safety Assessment of the Shower Gels When evaluating body wash cosmetics such as shower gels, consumers increasingly take into account the safety of using cosmetic products in terms of their potential to induce skin irritation. Consumer evaluation is particularly rigorous with regard to cosmetics marketed as “natural”. Since their production process is based on certified raw materials of natural origin, they are described as being completely environmentally friendly and safe both by consumers and, to a large extent, by manufacturers themselves. In actual fact, the safety of body wash cosmetics, understood as a limited potential to produce skin irritations, is not related to the natural origin of materials used in the formulation process. The skin irritating effect induced by body wash cosmetics depends on the type (chemical structure) and concentration of surfactants and additives used to modify product characteristics to achieve improved functional properties [9]. Tests were conducted to determine the safety of the formulated prototypical body wash cosmetics in terms of the risk of skin irritation developing after their application (Figure 4, Figure 5, Figure 6 and Figure 7). The zein values determined for the shower gel prototypes ranged from 135 to 66 mgN/100 mL. The highest value was obtained for the formulation CC_1, containing no digestate extract. Partial replacement of water by the digestate extract in the prototypical body wash cosmetics leads to a decrease in the zein number to the minimum value in the formulation CC_4, in which the ingredient represented 50% of the composition. The zein number test (Figure 4) showed that the substitution of water by the digestate extract in the prototypical body wash cosmetics had the benefit of reducing the skin irritating effect of the entire cosmetic formulation. The impact of the digestate extract on the skin irritating effect elicited by the body wash cosmetics containing the extract can be evaluated by performing the bovine serum albumin (BSA) test. It is based on interactions between the cosmetic’s surface-active ingredients and the water-soluble protein albumin. Anionic surfactants—used as the primary ingredients with a cleansing effect—bind to the cationic groups on the protein, causing its denaturation. In order to neutralize the negative protein charge resulting from the predominance of anionic groups in its molecules, adsorption of protons from the solvent takes place, causing a rise in the pH of the solution. The higher the pH increase compared to the baseline (5.5), the greater the skin irritating effect of the product analyzed [1]. The test results obtained for the prototypical body wash cosmetics containing the digestate extract are shown in Figure 5. The test results (Figure 5) are consistent with the results of the zein number determination. The highest pH increase in the mixture, close to 15% compared to the baseline, was observed for the formulation CC_1. The result shows that this prototypical cosmetic was characterized by the highest skin irritating effect out of all analyzed products. Incorporating the digestate extract into cosmetic formulations results in a lower increase in pH value. The smallest pH increase in relation to the baseline was noted for the formulation CC_4, which contained the digestate extract at the highest studied concentration. Tests evaluating the skin irritating effect of the analyzed prototypical cosmetics confirm the anti-irritation effect of the digestate extract used. The observed decrease in the skin irritating effect accompanying a rise in the concentration of the digestate extract in the cosmetics results from the composition of that ingredient, as well as from potential interactions between the chemical compounds it contains and the surfactants used as the main functional ingredients in the formulated body wash cosmetics. The effect produced by the extract is probably attributable to the significant proportion of levan in its composition (Figure 1). Furthermore, the impact of the digestate extract on reducing skin irritation may arise from its wide range of other ingredients, including proteins and mineral salts. Ingredients of this type are also capable of reducing interactions between surfactants and the skin [9]. Levan is probably the adsorption site for free surfactant monomers, which effectively reduces their concentration in the bulk phase. This restricts potential interactions involving monomers and the epidermal surface, thereby decreasing the skin irritating effect of the entire formulation. In addition, the surfactant micelles forming in the solution may bind relatively permanently with levan chains, creating a polymer–surfactant complex with a beaded structure. The stability of micelles in aggregates of this type is higher than the micelles forming in the bulk phase without the involvement of macromolecular compounds. This results in an equilibrium shift in the bulk phase towards more stable micellar aggregates and a decline in the concentration of free monomers in the solution. As a consequence, the skin irritating effect of the formulation becomes significantly reduced [9,38]. The claim is corroborated by the results of the tests shown in Figure 6. Polymers and surfactants are very commonly included in many industrial products, and their mixtures can exhibit molecular interactions affecting the properties of the product. In this respect, the mechanism of interaction between a water-soluble polymer—levan and an anionic surfactant Sodium Coco Sulfate (SCS), occurring in greater quantity was investigated. The addition of SCS to the Bacillus-fermented supernatant is presented in Figure 6. There are two break points in the relation of tested surfactant and the conductivity. The first break point is related to critical aggregation concentration (cac) and the second break is for saturation point of the polymer by the surfactant (psp). The interactions between surfactant and polymer solution is visible when the cac value is reached. A linear increase in conductivity was observed when SCS was added to the Bacillus-fermented supernatant solutions, with the same slope for all solutions tested. When the cac value is reached, the slope decreases. This may suggest absorption or the formation of polymer clusters resulting in depletion of free surfactant ions in the solution. This relationship lasts until the polymer is saturated with SCS molecules, which determines the second break point or psp. Further addition of SCS results in a linear conductivity relationship and the slope of the curve is the same for all solutions. All plots show two line areas, below the cac and above the psp. Upon reaching psp, only normal surfactant micelles are formed [39]. However, this does not exclude their formation below the psp point [40]. Once the cac of the polymer is reached, the surfactant molecules begin to associate with it to form micellar structures around each polymer molecule and they remain in equilibrium with the surfactant molecules in the solution [41]. Its further addition to the polymer-containing solution results in the formation of larger micellar structures, the mobility of the ions in the solution is reduced, revealing the visible psp point [42]. The skin irritating effect of body wash cosmetics is mainly related to the interactions between basic surfactants, i.e., the primary ingredients of the formulation, and the stratum corneum, as well as the results of these interactions. In addition to potential adverse interactions with proteins building corneocytes in the stratum corneum and deactivation of enzymes known to play a role in healthy skin function [9,11,43], scientific studies analyzing the safety of cosmetics from the viewpoint of their skin effects also address the impact of cosmetic products in the context of hydrophobic components present in the epidermis [9,44,45,46]. Specifically, an excessive ability to emulsify fats in body wash cosmetics carries the risk of removing valuable lipids from the epidermal protective layer, which are proven to contribute to maintaining appropriate hydration of the epidermis and strengthening the skin’s barrier function. Such processes can disrupt the structure of the intercellular cement between corneocytes or contribute to damaging the enzymes that produce lipids in the extracellular matrix. Consequences include an increase in trans- epidermal water loss and symptoms such as dry skin, epidermal cracking or even scaling [1,46]. Increased emulsification of fatty soiling can also lead to uncontrolled removal of naturally occurring bacterial flora from the epidermal surface, inducing a change in skin pH [1,47,48]. On the other hand, the ability of cosmetic formulations to emulsify fatty soiling in the wash bath guarantees appropriate product functionality which is expected by consumers in terms of washing performance. This is because the mechanism of skin washing consists of a number of processes aimed at removing a variety of soils from the skin surface, including environmental pollutants and skin secretions (e.g., sweat or sebum), one of the key subprocesses being emulsification of soils in the wash bath solution [1,49,50]. It ensures permanent removal of soils from the skin surface. The results obtained in the evaluation of the ability of the shower gels to emulsify fatty soiling are shown in Figure 7. The ability of the studied prototypical cosmetics to emulsify fatty soiling was shown to be in the range of 31.5–21.0 g/L. The highest ability to emulsify fats was shown for the shower gel CC_1 which was formulated without the digestate extract. The addition of the extract leads to a considerable decrease in the parameter determined for the cosmetics. At the maximum studied concentration of the digestate extract (sample CC_4), the level of fatty soiling that could be emulsified in the wash bath was found to be the lowest. The results of the study show that the incorporation of the digestate extract into body wash cosmetics significantly impairs their functionality in terms of the ability to emulsify fats. On the other hand, a reduction in this parameter provides clear benefits, making cosmetics highly safe to use in terms of their interactions with epidermal lipids and potentially associated effects, such as excessively dry skin after product application. Similar findings were reported by Ananthapadmanabhana et al. [45,46,51], who evaluated the ability of model surfactant solutions to solubilize stearic acid and cholesterol. The authors assert that the documented limited capacity of some surfactants to remove hydrophobic components naturally occurring in the epidermis makes them safer for the skin. Researchers argue that the approach to the quality of body wash formulations in terms of their impact on the skin must be comprehensive, taking into account individual ingredients of the formulation but also looking at the product as a whole, with an emphasis on interactions with both epidermal proteins and lipids. Similar conclusions are reported in [1,2,51], with the authors pointing out that cosmetics formulated specifically for body washing purposes are expected to remove relatively loose soiling typically found on the skin. Consequently, an excessive ability to emulsify fatty soiling is not desirable in their case. The composition of body wash cosmetics should be adjusted appropriately. On the one hand, cosmetic products should have good cleansing properties. On the other, they should not cause excessive removal of lipids which are essential for healthy skin functioning. 2.5. Evaluation of Functional Properties Ensuring the desirable functionality of body wash cosmetics involves appropriate selection of their quantitative and qualitative composition, so that the finished product displays satisfactory performance in the eyes of consumers. In their evaluation, consumers are concerned primarily with the characteristics related to the cosmetic’s performance (cleansing action) and application (good foaming ability, and appropriate viscosity and rheological properties). With regard to cosmetics marketed as “natural”, which are free of colorants enhancing their visual appeal, consumer evaluation also includes the aspect of color. Such cosmetics are typically transparent systems, and their color results from the raw materials used for production. The section below outlines the results of studies showing how the addition of the digestate extract affects the functionality-related aspects of cosmetic quality. The analysis comprised a range of parameters including viscosity, color, foaming ability, detergent properties and rheological characteristics of prototypical shower gels. The results obtained in the assessment of foaming ability of the shower gels are shown in Figure 8. The shower gels under study are characterized by very good foaming ability. Their aqueous solutions generate between 580 and 620 cm3 of foam. Foam stability in all the cosmetics under study was found to be within a similar range of 86–89%. The concentration of the digestate extract was not shown to have an effect on the properties of the aqueous solutions of the studied body wash cosmetics. The results obtained in the evaluation of detergent properties of the shower gels are shown in Figure 9. The addition of the digestate extract has no impact on the detergent properties of the prototypical shower gels analyzed in the study. The decreases in the weight of soiling determined after the contact with the solutions of the cosmetics under study were similar and stood at around 45% of the baseline value. Since the goal was to develop products that meet the criteria of natural cosmetics, no colorants were added to the formulations. The shower gels under study are transparent systems. Colorimetric evaluation was performed to determine how the application of the digestate extract affected the natural color of the products arising from the raw materials used. The results of the colorimetric analysis are given in Table 3. The base shower gel was very light in color, with a shade close to yellow (ho value was around 93). Preparations containing extracts from the digestate also had a very light shade, similar in shade to yellow, slightly changing to green (ho range 101.9–102.6). On the basis of the determined values of ΔEshower gel with digestate extract/base shower gel, it was found that the use of digestate extracts slightly affects the color difference of individual shower gels. The calculated ΔEshower gel with digestate extract/base shower gel values were close to the range from about 1.0 to 2.0. This proves that the color difference is only slightly discernible, only by an experienced observer [52,53]. An important parameter for evaluating the quality of shower gels is viscosity. Consumers often mistakenly believe that highly viscous body wash cosmetics are rich in active substances. As a consequence, the parameter is essentially equated with product efficacy. In fact, the viscosity of cosmetics formulated as aqueous surfactant solutions is typically adjusted by adding a salt (usually NaCl) or a polymeric viscosity modifier. The measure is applied to facilitate product application. Moreover, viscosity can affect the ease of dispensing the product from the package and spreading it over the skin, and reconstitution with water to obtain a wash bath [54,55]. Concentration-dependent viscosity curves were recorded for the investigated products. The effect of adding-fermented extract at different concentrations (17, 33 and 50%) on viscosity with increasing shear rate is shown in Figure 10. The shower gels showed similar viscosity curve profiles, with an increase in viscosity upon addition of the fermented extract. The flow behavior of shower gels was also investigated as a function of shear rate (Figure 11). It was observed that the shear stress increased with increasing concentration and increased with the increase in shear rate. Calculation of the flow behavior index, n, using the power low model (Ostwald de Waele model) revealed the shear-thinning behavior of shower gel CC_1, without addition of fermented extract, with n < 1 characteristic for pseudo-plastic material. After addition of the fermented extract, it was observed that n value was close to 1, indicating the changing behavior of the shower gels towards Newtonian fluids with viscosity independent of the share rate. Increasing the concentration of fermented extract caused increases in shower gel viscosity. The product designed without extract addition exhibited the lowest viscosity. The viscosity of the shower gel (share rate 34 s−1) with addition of the 17% of extract was approximately 10 times higher than that of the CC_1 product. The viscosity of the shower gels with concentrations of 33 and 50% fermented extract were about 30 times and 40 times higher, respectively. 3. Materials and Methods 3.1. Raw Materials for Cosmetics The shower gels were made with certified raw materials of plant origin and approved for the production of natural products according to COSMOS standards: sodium coco sulfate (trade name: Sulfopon 1216G, supplier: BASF, Germany), coco glucoside (trade name: Plantacare 818, BASF, Germany), cocamidopropyl betaine (trade name: Dehyton K45, supplier: BASF, Germany), sodium benzoate and potassium sorbate as preservatives (trade name: KEM BS, supplier: Akema Fine Chemicals, Italy), Bacillus Ferment Extract (supplier: InventionBio, Poland), citric acid (trade name: citric acid, supplier: POCH Poland), sodium hydroxide (sodium hydroxide, supplier: POCH Poland), distilled water. 3.2. Fermentation Process for Levan Production with Bacillus Subtilis Natto KB1 The inoculation of Bacillus subtilis natto KB1 was carried out in a bioreactor with a total capacity of 5 L in LB medium (10 g/L bacto-tryptone, 5 g/L bacto-yeast extract, 10 g/L NaCl). The process was carried out for 24 h at the temperature of 37 °C with constant stirring (200 rpm) and aeration (1 vvm). The starting OD was 0.1. Fermentation was carried out in a dedicated medium (sucrose 50 g/L, MgSO4 × 7H2O − 0.5 g/L, NaH2PO4 × 2H2O − 3 g/L, Na2HPO4 × 12H2O − 3 g/L). During the process, the pH of the culture was controlled with 1 M NaOH and 1 M HCl. Foaming was controlled with almond oil. Upon completion of the process, the biomass was removed by centrifugation (17 000× g). The supernatant was divided into two parts and one part was freeze-dried for analytical studies and the other part was used for further application research. 3.3. Bacillus-Fermented Supernatant Analysis 3.3.1. NMR analysis 1H nuclear magnetic resonance (NMR) spectra were recorded using the AVANCE III NMR 500 MHz spectrometer (Brucker Co., Billerica, MA, USA) at 25 °C. Preparation of the samples for the study included precipitation by using ethyl alcohol in a ratio of 1: 4, centrifugation of the precipitate and its lyophilization. Then, the sample was dissolved in deuterated water (D2O). The chemical shifts (δ) were obtained as ppm. The obtained chemical shifts were compared with the previously obtained results [16] relating to the B. subtilis KB1 strain used. 3.3.2. Fourier-Transform Infrared Analysis The infrared spectra were recorded with a Bruker Vertex 70 FT-IR spectrometer. The sample precipitated after fermentation and was prepared as described above, as a KBr pellet. Sample was scanned over a wavelength range of 4000–400 cm−1. The obtained spectrum was compared with the previous data obtained for the B. subtilis KB1 strain used. 3.3.3. Determination of Levan Content The levan concentration in the post-fermentation product was determined using the Fructan Assay Kit K-FRUC (Megazyme). For determinations, a specific volume of the Bacillus-fermented supernatant sample was precipitated with 4 portions of cold 96% ethanol, left overnight, and then the pellet was centrifuged and lyophilized. The levan content was determined according to manufacturer’s protocol. The method consists of enzymatic and chemical removal of sugars, i.e., sucrose, glucose and fructose, from the sample, and then of a colorimetric determination of fructane content after its hydrolysis. Absorbance was measured at 410 nm against a reagent blank. The calculations were performed by using the downloaded Megazyme Mega-Calc for Fructan Assay Kit [56]. Maleic acid, p-hydroxybenzoic acid, sodium borohydride and sodium citrate dihydrate were purchased from Sigma. Other reagents (NaOH, CH3COOH, calcium chloride dihydrate) were of analytical grade and purchased from PoCH (Poland). 3.3.4. ICP–OES Analysis For ICP–OES analysis, the Bacillus-fermented supernatant was digested in acidic conditions. The concentration of selected elements was determined by iCAP 7400 DUO emission spectrometer (Thermo Fisher Scientific) optimized and calibrated for multielement analysis taking into account the effect of the acid matrix. Samples were analyzed in triplicate. 3.4. Conductivity Measurements Conductometric measurements were carried out at the temperature of 22 ± 1 °C in a beaker by adding the appropriate volume of a 4% solution of sodium coco sulfate anionic surfactant to 50 mL of solution obtained after fermentation with a concentration of 16.7, 33.3 and 50% (v/v). The surfactant was added until its concentration in the solution reached 3.3%. After adding each portion of the surfactant, the entire solution was mixed with a magnetic stirrer until a constant conductivity value was obtained. The conductance of the solution was measured on Elmeiron CPC-505 conductivity meter. All solutions were prepared with double distilled water of specific conductance between 1 and 2 µS/cm at 22 °C. 3.5. Antimicrobial Activity Pseudomonas aeruginosa ATCC 9027, Staphylococcus aureus ATCC 6538, Staphylococcus epidermidis ATCC 1917, Escherichia coli ATCC 8739 and Candida albicans ATCC 10231 were used for antimicrobial tests. 3.5.1. Agar Well Diffusion Test A bacterial and yeast cell suspension obtained after overnight culture was spread uniformly on the solid agar medium and left dried at room temperature. The wells were cut using sterile Pasteur pipet and the diameter of the wells was the same in each experiment (8 mm). Then, 50 µL of Bacillus-fermented supernatant was loaded and kept in chilled conditions for 2 h to allow diffusion into the agar. Then, another 50 µL of tested solution was added into the wells. PBS solution was used as a negative control. Penicillin–Streptomycin and acetic acid were used as positive controls for bacteria and yeast respectively. The agar plates were incubated at 37 °C for 24 h for S. aureus, P. aeruginosa, E. coli, S. epidermidis and C. albicans. A clear zone diameter around the well, which indicated the microbial inhibition, was measured at two perpendicular directions. All experiments were performed with three replications. 3.5.2. Minimum Inhibitory Concentration (MIC) Determination The MIC was defined as the lowest concentration of the tested compounds at which no bacterial growth occurred. The inocula were standardized to 0.5 McFarland standard. Bacterial strains of P. aeruginosa ATCC 9027, S. aureus ATCC 6538, S. epidermidis, E. coli ATCC 8739 were grown in LB medium (BioShop) with different concentrations of Bacillus-fermented supernatant for 24 h at 37 °C in 96-well plates. As for C. albicans ATCC 10231, it was incubated with the same concentration of Bacillus-fermented supernatant as for the bacteria strains, for 24 h at 28 °C in YPG medium (1% YE, peptone BioShop, 2% glucose Bioshop) in 96-well plates. After the incubation period, the optical density was measured using a microplate reader at 600 nm (ASYS UVM 340 Biogenet). Negative and growth control wells did not contain tested supernatant. 3.5.3. Effect of Bacillus-fermented Supernatant on Pathogen Cell Shape—Scanning Electron Microscopy (SEM) Selected strains were incubated in 96-wells microplates with Bacillus-fermented supernatant for 24 h at 37 °C. After this time, the wells were washed 2 times with PBS buffer and prepared for SEM analysis. First the cells were fixed with 2.5% glutaraldehyde in PBS, then dehydrated in a series of acetone washes and dried. The SEM analysis was performed on Hitachi S-3400N equipped with a tungsten cathode (magnification 80–300.000×) at operation voltage of 15 keV at room temperature. 3.5.4. Effect of Bacillus-fermented Supernatant on Pathogenic Strain Biofilm Formation The protocol was based on our previous experiments [57]. Bacterial strains were grown on LB medium at 37 °C for 24 h and C. albicans ATCC 10231 was grown in YPG medium at 30 °C for 24 h. The overnight cultures were centrifuged and washed twice with PBS buffer. Then the cells suspensions were prepared with an optical density OD600 = 1 for bacteria strains and OD600 = 0.6 for C. albicans. Then 100 µL of each suspension was added to the wells and incubated for 2 h in 37 °C on a rotary shaker (MixMate, Eppendorf, Germany) at 300 rpm. After that time, the microbial suspension was removed and wells were washed twice with PBS buffer. Then, 100 µL of Bacillus-fermented supernatant was added to each well, and for the negative control, 100 µL of PBS was used. The plate was incubated for another 2 h in 37 °C on a rotary shaker at 300 rpm. Then the wells were washed twice with PBS and the cells were stained with 0.1% crystal-violet for 5 min at room temperature and washed in triplicate with PBS. Then, 150 µL of isopropanol-0.04 N HCl and 50 μL of 0.25% SDS per well was added to solubilize the dye. The absorbance of each well was measured using a microplate reader at 590 nm (ASYS UVM 340 Biogenet). The results were expressed as a percentage of control (untreated cells). Assays were carried out twice in three replications. 3.5.5. Pre-adhesion Activity of Bacillus-Fermented Supernatant Bacterial strains were grown as it is described in Section 3.4. The protocol was adapted from [58] with some modifications. The Bacillus-fermented supernatant was tested for its pre-adhesion activity in 96-well plates (Sarsteadt, Germany). The wells were filled with 100 µL of Bacillus-fermented supernatant and incubated for 2 h at 37 °C on a rotary shaker (MixMate, Eppendorf, Germany) at 300 rpm. After 2 h, the wells were washed twice with PBS. Negative control wells contained only PBS buffer. The overnight cultures of tested strains were centrifuged, washed twice with PBS and resuspended to an optical density OD600 = 1 for bacterial and OD600 = 0.6 for C. albicans. Then, 100 µL of prepared microbial suspensions were added to the wells and incubated for another 2 h at 37 °C on a rotary shaker at 300 rpm. After that, the wells were washed in triplicate to remove nonadherent cells. The adherent cells were stained with 0.1% crystal-violet for 5 min at room temperature and then the wells were washed three times with PBS. The dye was resolubilized with 150 µL of isopropanol-0.04 N HCl and 50 μL of 0.25% SDS per well. The absorbance of each well was measured using a microplate reader at 590 nm (ASYS UVM 340 Biogenet). The results were expressed as a percentage of control (untreated cells). Assays were carried out twice in three replications. 3.6. Zein Test Irritant potential of the shower gel was measured using the zein test. The study was carried out using the automatic mineralization system Digestor 8AR and the automatic nitrogen analyzer Kjeltec 8400 (Producer FOSS, Denmark). In the zein test procedure, 2 g of protein was solubilized in 40 g solution of cosmetic sample (10% wt.). The amount of solubilized protein was determined by Kjeldahl analysis, and the result of the zein number procedure was expressed as mg of solubilized protein (calculated as nitrogen) in 100 mL of sample. The final result was the arithmetic mean of three independent measurements. The test methodology was described in more detail by Nizioł-Łukaszewska et al. [4] and Bujak et al. [2,12,38]. 3.7. pH Rise Test with Bovine Albumin Serum (BSA) The test was based on measuring the degree of protein denaturation by determining the pH level of the BSA solution in the solution of the studied cosmetic. The greater its increase, the stronger the skin irritating effect produced by the product concerned. The results were expressed as a percent increase in the pH value in relation to the level defined for normal human skin (pH = 5.5). Three independent assays were performed for each of the studied cosmetics and the results were averaged. The test methodology was described in more detail by Seweryn et al. [13] and Bujak et al. [38]. 3.8. Evaluation of Ability to Emulsify Fatty Soils The ability to emulsify fatty soils was evaluated in tests conforming to the PN-C-77003 standard. The maximum weight of rapeseed oil colored with Sudan Red (0.1 g of Sudan IV per 1000 mL of rapeseed oil) capable of being emulsified by 1 dm3 of a 1% aqueous solution of the studied cosmetics was determined. The experiments were carried out as follows: 1.4 g of rapeseed oil colored with Sudan Red (model fatty soil) and 2.0 g of the studied cosmetics were placed in a 50 mL beaker. Then the mixture was intensively stirred with a glass rod (diameter of the rod, 7 mm; rotational speed, about 200 rpm) for 5 min. The mixture obtained was transferred quantitatively into a 200 cm3 volumetric flask and brought up to volume with distilled water. The flask was closed and rotated for 5 min with rotations of 180° (one rotation per second). The resulting emulsion was placed in an incubator (45 °C) for 30 min. The flask was then taken out, and the emulsion was assessed. Separation of the oil layer in the flask’s neck or the appearance of one or more drops of colored oil in the upper part of the flask’s neck was considered to be a negative result (i.e, the liquid was not capable of emulsifying a given weight of fatty soil). When a negative result was obtained, subsequent trials were carried out in which the weight of oil was decreased by 0.2 g. If the result obtained was then positive, subsequent trials were carried out (with an increase in the oil weight of 0.2 g) until a negative result was obtained. The test consisted of determining the maximum weight of rapeseed oil which can be emulsified by 1 L of a washing bath containing 1 wt% of the evaluated formulation. The final result (mean value of three independent measurements) obtained in the test determining the ability of the evaluated formulation to emulsify fatty soils was expressed in grams of oil per liter of the evaluated formulation at the concentration of 1 wt%. The test methodology was described by Seweryn et al. [1,13]. 3.9. Evaluation of Foaming Properties The method of measurement was in line with Polish Standard PN—EN 1272. The experiments were carried out as follows: 100 cm3 of 1% aqueous solution of studied body wash cosmetic was poured into a glass cylinder. Then, the foam was whipped (time of whipping 60 s., number of full hits 60) using a perforated disc placed on a metal bar. The volume of the foam formed was read out after 10 s. Foaming ability was described as foam volume 10 s after its formation. Additionally, the percent foam stability coefficient was evaluated as a ratio of the foam volume after 10 min. The final result was the arithmetic mean of three independent measurements. 3.10. Evaluation of Detergent Properties The detergent properties were evaluated based on the methodology described in the US patent No. 4904359 [59]. A 3 g portion of fatty soiling (pork lard) was applied to a pre-weighed (with an accuracy to 0.01 g) 250 mL polypropylene beaker. After being liquefied by heating, the lard was spread evenly on the bottom of the container. Next, the beaker was placed in the refrigerator for 1 h and then brought to room temperature. The aim of this step was to fix the soiling in the container. In a separate beaker, a 250 g of portion of 0.4% aqueous solution of the study formulation was prepared and the temperature set at 46 °C. After the solution had reached the desired temperature, it was poured into the beaker containing the soiling. The beaker was placed in the incubator for 15 min and the temperature set at 46 °C to keep the temperature of the solution constant. After 15 min, the beaker was emptied, rinsed gently with distilled water using a wash bottle, and dried for 1 h in a drying oven at 46 °C to completely evaporate the solution. Following that time, the beaker was weighed again. By comparing the difference in weight between the beaker containing 3 g of lard and the empty beaker, the decrease in weight of the soiling was calculated. The final result was expressed as a percentage loss of the weight of the fatty soiling following contact with the aqueous solution of the studied formulation. 3.11. Rheological Properties The viscosity was measured at 20 °C using a Brookfield rheometer DV2TRV with Small Sample Adapter and Cylindrical Spindle SC4 (Brookfield, St. Louis, MI, USA). For each test, 8 mL of the sample was used. Different shear rates and shear stresses were applied to the sample, and the resulting rheogram was constructed to determine the rheological behavior. All measurements were carried out in triplicate. 3.12. Determination of the Color Parameters Samples of cosmetics with digestate extracts were tested at room temperature, 48 h after their preparation. A CHROMA METER CR-400 (Konica Minolta, Sensing Inc., Japan) was used to evaluate the color parameters (CIELAB coordinates). The CIELAB system was defined by the International Commission on Illumination in 1978. It is based on three color attributes: L*, a*, b*, where L* is a brightness variable proportional to the value in the Munsell system, and a* and b* are chromatic coordinates. The a* and b* coordinates indicate positions on the red/green and yellow/blue axes, respectively (+a = red, −a = green; + b = yellow, −b = blue). Based on the data obtained: L*, a* and b*, the following color parameters were calculated: chroma (C*) and hue (ho). The following equations were used:(1) C*=a*2+b*2 (2) ho=arctanb*a* General color difference (ΔEshower gel with digestate extract/base shower gel) was calculated according to the following formula:(3) ΔEshower gel with digestate extract/base shower gel*=ΔL*2+Δa*2+Δb*2 where: ΔL*, Δa*, and Δb* are the mathematical differences between shower gel with extracts L*, a*, b* and base shower gel L*, a*, b* values. 4. Conclusions The study showed that the levan-rich digestate extract was a suitable ingredient for the formulation of body wash cosmetics which are safe on the skin. The prototypical shower gels prepared for this purpose were subjected to tests evaluating their skin irritation potential and basic parameters related to functionality. The zein numbers determined for the cosmetics containing the highest analyzed concentration of the digestate extract were over 50% lower compared to the water-based reference formulation. Consistent results were obtained in the BSA test, indicating a significant reduction in skin irritation characteristics after the application of the studied ingredient to the formulation. The effect is attributed to the high content of protein and mineral salts in the extract and predominantly to the presence of levan. As shown by conductometric studies, this polymer, through its impact on anionic surfactants, successfully prevents interactions between these compounds and epidermal structural proteins, thus reducing the skin irritating effect. Evaluation of the ability to emulsify fatty soiling showed a significant decrease in the evaluated parameter accompanying an increase in the concentration of the digestate extract. A decrease in the value of this parameter may translate into reduced impact of the formulation on epidermal lipids, and thus into the improved safety of the cosmetics regarding their effect on the skin. Other studies evaluating functionality indicated that the application of the digestate extract did not affect the functional performance of the shower gels under study. Rheological analysis revealed a thickening effect of the extract, which may be due to the presence of considerable amounts of electrolytes in the composition of this raw material. Consequently, there is no need to incorporate an additional viscosity modifier into the formulation to obtain the desired viscosity level and application parameters expected by consumers. Author Contributions Conceptualization, A.S. and T.W.; methodology, A.S., T.W., D.P., M.Ł., K.K. and A.L.; software, A.S.; validation, A.S., T.W., M.Ł., Z.H.-B., K.K., M.D.-K. and A.L.; formal analysis, A.S., T.W., M.Ł., Z.H.-B., K.K., M.D.-K. and A.L.; investigation, A.S., Z.H.-B. and A.L.; resources, A.S., T.W., M.Ł., D.P. and A.L.; data curation, A.S., T.W., Z.H.-B., D.P., M.D.-K. and A.L.; writing—original draft preparation, A.S., Z.H.-B., M.D.-K. and A.L.; writing—review and editing, A.S., T.W., M.Ł., Z.H.-B., M.D.-K. and A.L.; visualization, A.S., Z.H.-B., M.D.-K. and A.L.; supervision, A.S. and T.W.; project administration, A.S. and A.L.; funding acquisition, T.W. and M.Ł. 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 are contained within 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 Spectra of levan from B. subtilis natto KB1—(A) 1H NMR, (B) IR. Figure 2 Antimicrobial activity of Bacillusfermented supernatant against bacterial and yeast pathogens; (A) P. aeruginosa, (B) C. albicans, (C) S. aureus, (D) E. coli, (E) S. epidermidis. Figure 3 SEM images of untreated biofilms and biofilms treated with (A) P. aeruginosa, (B) C. albicans, (C) S. aureus, (D) E. coli, (E) S. epidermidis. Images represent typical fields of view. Figure 4 Zein value for shower gels formulated with the digestate extract. Figure 5 Changes in pH of the mixture of bovine serum albumin solutions and shower gels containing the digestate extract. Figure 6 Plots of conductivity versus sodium coco sulfate concentration for various concentrations of Bacillus-fermented supernatant. Figure 7 Ability to emulsify fatty soiling determined for shower gels formulated with the digestate extract. Figure 8 Foaming ability of shower gels containing digestate extract. Figure 9 The evaluation of detergent properties for the shower gels. Figure 10 Shear rate dependence of viscosity for shower gel with digestate extracts. Figure 11 The flow behavior of shower gels a function of shear rate. molecules-27-02793-t001_Table 1 Table 1 Influence of Bacillus-fermented supernatant on selected pathogenic strains—inhibition zone, MIC value, biofilm formation and adhesion to the polystyrene surface. Pathogen Inhibition Zone [mm] MIC Value [mg/mL] Biofilm * [%] Adhesion * [%] P. aeruginosa ATCC 9027 4.50 ± 1.38 275.25 92.75 53.46 S. aureus ATCC 6538 2.83 ± 0.68 412.88 67.41 68.02 S. epidermidis ATCC 1917 3.42 ± 0.49 412.88 92.12 72.42 E. coli ATCC 8739 2.50 ± 0.84 412.88 93.16 96.97 C. albicans ATCC 10231 5.17 ± 0.75 206.44 76.83 70.36 * Values expressed as a percentage of untreated cells. Experiments performed in triplicate. molecules-27-02793-t002_Table 2 Table 2 Model shower gel formulations containing digestate extract. Name According to INCI 1 CC_1 CC_2 CC_3 CC_4 Aqua to 100 Sodium Coco Sulfate 3.3 Coco Glucoside 4.2 Bacillus Ferment Extract 0 16.7 33.3 50.0 Cocamidopropyl Betaine 1.5 Citric Acid/ Sodium Hydroxide do pH 5.5 Sodium Benzoate, Potassium Sorbate 0.45 Parfume 0.5 Aqua to 100 1 INCI = International Nomenclature of Cosmetic Ingredients. molecules-27-02793-t003_Table 3 Table 3 Color parameters for cosmetic (shower gel). L* a* b* C* ho ΔEshower gel with digestate extract /base shower gel CC_1 92.3 −0.29 5.47 5.5 93.0 - CC_2 93.1 −0.93 4.41 4.5 101.9 1.47 CC_3 94.0 −0.96 4.31 4.4 102.6 2.16 CC_4 93.5 −1.00 4.76 4.9 101.9 1.56 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Seweryn A. Bujak T. Application of anionic phosphorus derivatives of alkyl polyglucosides for the production of sustainable and mild body wash cosmetics ACS Sustain. Chem. Eng. 2018 6 17294 17301 10.1021/acssuschemeng.8b04711 2. Bujak T. Nizioł-Łukaszewska Z. Ziemlewska A. Amphiphilic cationic polymers as effective substances improving the safety of use of body wash gels Int. J. Biol. Macromol. 2020 147 973 979 10.1016/j.ijbiomac.2019.10.064 31678103 3. Amberg N. Fogarassy C. Green consumer behavior in the cosmetics market Resources 2019 8 137 10.3390/resources8030137 4. Nizioł-Łukaszewska Z. Osika P. Wasilewski T. Bujak T. 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==== Front Int J Mol Sci Int J Mol Sci ijms International Journal of Molecular Sciences 1422-0067 MDPI 10.3390/ijms23095256 ijms-23-05256 Review The Structure and Function of Next-Generation Gingival Graft Substitutes—A Perspective on Multilayer Electrospun Constructs with Consideration of Vascularization https://orcid.org/0000-0001-5501-1338 Webb Brian C. W. 12 Glogauer Michael 1 Santerre J. Paul 12* Kawase Tomoyuki Academic Editor Shirakata Yoshinori Academic Editor 1 Faculty of Dentistry, University of Toronto, 124 Edward St, Toronto, ON M5G 1G6, Canada; b.webb@mail.utoronto.ca (B.C.W.W.); michael.glogauer@dentistry.utoronto.ca (M.G.) 2 Institute of Biomedical Engineering, University of Toronto, 164 Collage St Room 407, Toronto, ON M5S 3G9, Canada * Correspondence: Paul.Santerre@dentistry.utoronto.ca 09 5 2022 5 2022 23 9 525609 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/). There is a shortage of suitable tissue-engineered solutions for gingival recession, a soft tissue defect of the oral cavity. Autologous tissue grafts lead to an increase in morbidity due to complications at the donor site. Although material substitutes are available on the market, their development is early, and work to produce more functional material substitutes is underway. The latter materials along with newly conceived tissue-engineered substitutes must maintain volumetric form over time and have advantageous mechanical and biological characteristics facilitating the regeneration of functional gingival tissue. This review conveys a comprehensive and timely perspective to provide insight towards future work in the field, by linking the structure (specifically multilayered systems) and function of electrospun material-based approaches for gingival tissue engineering and regeneration. Electrospun material composites are reviewed alongside existing commercial material substitutes’, looking at current advantages and disadvantages. The importance of implementing physiologically relevant degradation profiles and mechanical properties into the design of material substitutes is presented and discussed. Further, given that the broader tissue engineering field has moved towards the use of pre-seeded scaffolds, a review of promising cell options, for generating tissue-engineered autologous gingival grafts from electrospun scaffolds is presented and their potential utility and limitations are discussed. electrospinning gingival tissue material substitutes functional materials porous materials vascularization Natural Science and Engineering Research Council360520 Training Program in Organ-on-a-Chip Engineering and EntrepreneurshipN/A This research was funded by Natural Science and Engineering Research Council (NSERC) Discovery (RGPIN-2018-04424), grant number #2018-04424 and The Training Program in Organ-on-a-Chip Engineering and Entrepreneurship (TOeP). ==== Body pmc1. Introduction Gingival recession with tooth root exposure affects half of the adult U.S. population [1,2]. A more efficient and less painful solution to the current treatment standard could have a widespread impact, improving the lives of millions. Loss of gingival coverage around the tooth at the tooth–tissue margin is referred to as gingival recession and results in the exposure of the tooth’s root surface. This root exposure can lead to tooth sensitivity when eating, increased risk of biofilm accumulation and further tissue loss and aesthetic compromise. Tissue loss is primarily caused by inflammation associated with periodontitis (initiated from agents produced within plaque/biofilm) and mechanical trauma [3]. Not only does gingival recession yield challenges for the patients’ esthetic appearance, but it can also expose the roots surface of the tooth to cariogenic supragingival microbiota leading to an increased risk of dental caries and in the extreme case loss of tooth [3]. The current treatment for the soft tissue defect of gingival recession is primarily autologous soft tissue grafts, usually harvested from the patient’s palate [4]. However, material substitutes can be used in isolation, or with autologous grafts, and are available on the market, such as the Geistlich Fibro-Gide® bovine-collagen-based material [5]. This material still has limitations when compared to the gold standard of care (autologous grafts) [6], while several other more innovative materials that are now being studied and are discussed here. However, the field of tissue material substitutes [7], and tissue-engineered solutions is still in its infancy in this application area. The pain and length of recovery and the time to carry out the procedures could be greatly reduced, when compared to the standard-of-care-associated procedures, if superior scaffold material substitutes and/or pre-vascularized tissue-engineered constructs could be translated into the clinical realm [8,9]. Vascularized tissue-engineered substitutes hold the potential to provide the cells needed for tissue regeneration and anastomosis, and deliver novel scaffolding materials to promote their proliferation and phenotype expression towards successful tissue regeneration outcomes [10]. One promising processing method for fabricating materials for regenerating and/or engineering gingival tissue is electrospinning. The method enables the production of fiber and fibril features that are on the scale of those of host extracellular matrices (ECM). Despite its mention in a recent systematic review looking at engineering vascularized oral tissue (mainly gingiva and alveolar bone), the article provided no insight into the use of layered electrospun scaffolds, which is gaining interest by many tissue engineering groups attempting to replicate the ECM form and niche residence conditions for related cells to the tissue being grown [11]. It should be noted that while other examples of layered scaffolds for periodontal regeneration have been previously reported, none have addressed the potential use of electrospun elastomeric polymers [7]. Thus, the goal of the current review is to provide focused insight on understanding the relationship between structure and function applied to new innovative electrospun-material-based approaches for gingival tissue engineering and regeneration. Specifically, functional electrospun materials are discussed in addition to a method for generating 3D electrospun constructs and providing perspectives on promising cell options for engineering pre-vascularized gingival tissue. 2. Physiology and Disease of the Periodontium and Gingival Tissues: Defining Structure Requirements The periodontium is comprised of four main tissue types: the alveolar bone, periodontal ligaments (connective tissue which allows for the attachment between the alveolar bone and root of the tooth), cementum, which is a mineralized tissue connecting the alveolar bone and the root of the tooth via periodontal ligaments, and gingival tissue which is the mucosal tissue that seals and protects the tooth from bacterial or physical threats as illustrated in Figure 1A [12]. The gingiva has two distinct layers, the epithelial tissue layer and the connective tissue layer (lamina propria) which make up approximately 30% and 70% of the gingiva, respectively [13,14]. The lamina propria can further be described as having two layers, the papillary layer, and the reticular layer [14]. The recession of gingival tissue is primarily caused by prolonged inflammation of periodontal tissue, periodontal treatment, and occlusal trauma [15]. Factors that could predispose an individual to gingival recession include a decrease in the thickness of the alveolar or buccal bone [15]. Healthy gingiva is comprised mostly of collagens [17], elastin [18], laminin [13], and fibronectin [13,19]. Of the collagens found in the gingiva, collagen type I and type III make up 99% of this protein family in human gingival tissue [17]. The remaining 1% is accounted for by collagen type IV, with the presence of collagen type V only increasing during the initial stages of healing. The presence of collagen type V is thought to guide endothelial cells (ECs), facilitating angiogenesis [17]. The major function of the remaining collagen molecules is primarily to provide strength to the lamina propria [17]. The ultra-structure of these collagens and ECM can be found in Figure 1B,C. Within the lamina propria, human gingival fibroblasts (HGFs) are responsible for synthesizing and maintaining the ECM [20]. Gingival fibroblasts are present in the lamina propria at a concentration of 200 million cells/cm3 [14]. The collagen fibrils produced by HGFs are approximately 50–100 nm in diameter [21]. Both the papillary and reticular components contain a dense network of vasculature, consisting of terminal capillary loops in the papillary component and the gingival plexus which is made up of postcapillary venules [14]. The papillary layer contains approximately 50–60 loops/mm2 [14]. The natural gingiva has approximately 10 microvessel lumens/mm2 [22,23], with defined diameters depending on locations and depth as outlined in Table 1. Having the blueprint of the vasculature within gingival tissue is fundamental to its engineering from the standpoint of understanding what is required for the native tissue to function. There are however notable differences in vasculature structure from person to person [25]. How and to what variation blood flow is being supplied to the lamina propria is of relevance when considering how important the anastomosis of pre-vascularized constructs will be. By prohibiting blood flow from certain areas of the papilla, previous literature has demonstrated that some individuals have greater blood flow horizontally or vertically [25]. This is thought to be related to the abundance of blood vessels supplying the gingival area [25]. The differences may also be explained by changes in arteriole-to-arteriole connections (<100 µm in diameter) [24,25,26]. It is also well recognized that males have better blood flow recovery, and quicker anastomosis of coronally advanced flaps than females, which may suggest key factors that can be targeted to enhance the anastomosis of a graft [27]. Characterizing the differences in gingival vasculature is ongoing and will be critical to the application of pre-vascularized tissue engineering to the periodontium. Based on the physiology and anatomy of gingival tissue, it is evident that to prepare a construct resembling the native gingiva, modulating vasculature formation is going to be critical to graft integration and healing. 3. Current Material Options for Gingival Recession Treatment The current treatment for gingival recession is typically autologous soft tissue grafts [4]. Additionally, material substitutes are available on the market, which have some reports on their efficacy. The two most common types of autologous grafts are connective tissue grafts (CTG) and free gingival grafts (FGG). CTGs involve harvesting connective tissue and grafting it such that root coverage and improved thickness of the gingival tissue are provided, as seen in Figure 2. An FGG entails harvesting connective tissue with surface epithelial tissue and placing it on the defect to cover the exposed root of the tooth and increase keratinized tissue [28]. Some of the major disadvantages of autologous gingival grafting are the increase in morbidity due to the harvest site, interindividual differences in terms of tissue availability, the time associated with the tissue harvesting (FGG takes ~25 min longer than using material substitutes) [29], donor infection, and bleeding from the harvest site [5,30]. To avoid some of the downsides of autologous grafting, material substitutes can and have been introduced in an attempt to address these issues, however, the standard of care remains the autologous graft, which highlights the limitations of the current alternatives, some of which will be discussed later in this review. Based on two systematic reviews, the general consensus is that FGGs provide additional efficacy in terms of generating keratinized tissue when compared to material substitutes [6,32]. One of the most popular metrics of efficacy is the width of keratinized tissue [32]. Although the differences between autografts and material substitutes might not be large enough to negate the use of material substitutes given their benefits, autologous grafts remain the “gold standard” due to their ability to provide a greater area of keratinized tissue [6,32]. Taken all together autologous grafts remain the engineering benchmark, in large part due to their superior efficacy quantified by keratinized tissue. During the differentiation of epithelial cells to keratinocytes, the composition of the underlying connective tissue dictates the subsequent occupancy of the epithelium, due to the keratinocyte interactions with components of the ECM, such as collagen type I [33,34]. Keratinocytes are also involved in the complex processes of healing the underlying connective tissue [35]. Further, changes in epithelial cell integrin binding are associated with changes in the activity of matrix metalloproteinases (MMPs), which participate in tissue remodeling and the migration of keratinocytes [33,36]. The interactions between the underlying connective tissue and the epithelial layer are mediated by integrins such as beta1-integrins [37]. The interactions that epithelial cells, such as keratinocytes, have with such integrins dictate cellular differentiation and survival [37,38]. Additionally, the secretion of paracrine factors such as hepatocyte growth factor from the underlying connective tissue contributes to the formation of keratinocytes [39]. Due to the available supply and lower morbidity associated with using material substitutes, the field is pushing towards their greater adoption. However, their adoption is in part hampered by the lack of efficacy to establish a keratinized structured layer, as discussed above, when compared to the traditional autologous graft. In considering keratinized tissue dependence in relation to their composition and interactions with the underlying connective tissue, it will be important that de novo material substitutes try to facilitate the formation of healthy gingival tissue more rapidly, as in this instance more keratinized tissue can be produced, thus improving the clinical efficacy of the graft. Currently, the most common types of material substitutes being reported on and used in the clinic appear to be xenogenic scaffolds such as the Geistlich Fibro-Gide® [5], or allogenic grafts such as Alloderm® [40,41]. Their benefits mainly reflect their unlimited supply relative to autografts and lower associated morbidity relative to other material subsitutes [42]. Geistlich Fibro-Gide® by volume is 96% porous and is comprised of 60–96% (w/w) porcine collagen (type I and III) and 4–40% (w/w) elastin [43,44]. A similar product is Mucograft®, which has two layers, one of which is compact, and one which is spongy architecture for supporting cell ingrowth [43]. The compact outer layer can be left exposed to the oral environment and can aid in gaining keratinized tissue, suggesting that having a multilayered structure wherein different layers provide different functions is being used in the clinic [43]. Mucoderm® is a similar product to Mucograft® however is only comprised of a single layer [43]. Alloderm® or decellularized human dermal tissue are used clinically, however, they have been shown to have inferior clinical outcomes when compared to FGGs [45,46,47]. These material substitutes are currently the leading commercial substitutes that are widely available but are clearly still in need of improvement [5]. These material substitutes lack many of the features discussed early in this review and that would be essential for successful grafting and define the field as being in its infancy. 4. Electrospinning Biomaterial Features for Gingival Tissue Engineering Electrospun scaffolds offer several of the characteristics necessary to foster and modulate soft tissue regeneration [48], while closely resembling the physical fiber features of native ECM [49]. Electrospinning facilitates the formation of fibers/fibrils by extruding a polymer solution through an electrostatic field that is generated through a capillary needle with a high voltage that is met by a grounded collection mandrel at a defined distance [50]. Fibers between a few nanometers and greater than 1 µm can be formed using this process [50,51,52]. With a multitude of parameters (illustrated in Figure 3) influencing the electrospinning process such as voltage, the polymeric solution properties, and flow rate, the electrospinning process almost always requires optimization of parameters when one material is changed to the next. It is also these fabrication parameters that allow for diverse scaffold morphologies to be achieved [53]. Lastly, the electrospinning process is rapid and cost-effective [49]. Specifically, it does not require extensive purification steps, enables low-cost processing steps, and reduces production time. The latter overcomes several shortcomings associated with obtaining decellularized tissue for example. The range in fiber membrane properties that can be achieved allows for the application of this process to produce fibers for engineering different tissue types. As discussed in a previous review the phenotype of cells seeded on electrospun scaffolds can be modulated by altering the defined nanotopography of the fiber membranes [48]. Gene expression involved in cellular behavior and signaling pathways can even be modulated by altering factors such as pore size [54]. In a 2009 study [55], the authors reported on a paradigm shift from the use of porous foams towards electrospun fibers for guided periodontal regeneration; however, this was not discussed specifically in the context of gingival tissue and its vascularization. The function of using aligned electrospun fibers for culturing HGFs for gingival tissue engineering has been presented [56]. The addition of cells offers promising phenotypic character to enhance the function of electrospun scaffolds for gingival tissue engineering. Of relevance to gingival tissue specifically, an increase in the production of collagen type I has previously been shown to be achieved with HGFs on aligned versus random fibers [57]. With collagen being the main component of the lamina propria’s ECM [17], using an aligned fiber may offer a convenient alternative to begin engineering tissue that could be more representative of the native tissue. Other authors investigating fiber alignment in the context of gingival tissue regeneration found an increase in HGF proliferation, collagen type I, focal adhesion kinase, and fibronectin on aligned versus random electrospun poly-ε-Caprolactone (PCL) scaffolds [56]. Although in this example PCL fibers were used, the benefit of using aligned fibers could be applied to electrospinning any material. This suggests that based on alignment only, the cells seeded on aligned electrospun scaffolds may offer greater gingival fibroblast proliferation, and collagen type I production when compared to non-aligned material substitutes. Interestingly, the Geistlich collagen-based scaffolds (e.g., Fibro-Gide®, Mucograft®, and Mucoderm®) currently on the market have a randomly aligned structure, suggesting that their function could be improved. When evaluating material substitutes as potential grafting materials, pore size and percent porosity are critical considerations as they dictate factors such as cellular and vascular ingrowth, and transportation of oxygen, waste, and nutrients [58]. Pore size has previously been altered/tuned by using sacrificial polymers which are initially included in the electrospinning process and then washed away with water [59,60]. Small pore sizes can inhibit vascular ingrowth (needed for the diffusion of nutrients, oxygen, and waste) [50]. A general range of pore size which has been shown to allow for cellular infiltration is in the range of 100–500 µm [61,62]. Electrospun poly-L-lactic acid (PLLA) scaffolds have previously been fabricated for skin tissue engineering with an average pore size of 132.7 µm and porosity of ~92%, with the higher porosity scaffolds showing an increase in cell migration, infiltration, and collagen deposition [58]. The high porosity and tissue infiltration are consistent with the Geistlich scaffolds (e.g., Fibro-Gide®, Mucograft®, and Mucoderm®) which have a porosity of ~93% by volume [44]. Electrospinning facilitates the formation of fibers with diameters in the same range as that of the collagen and other relevant supporting fibers such as elastin. Collagen type I and other fibril forming collagen fibrils have a diameter ranging from ~25–400 nm [63]. Elastin fibers and fibrils have diameters of 1 µm and 0.2 µm, respectively [64]. These are well within the diameter range of what can be electrospun [50,51,52]. The underlying importance and significance of having fiber diameters recapitulating those observed in native tissue are complex and likely reliant on if the material is intended to be pre-seeded with cells or be used as a substitute acellular material. Further, the optimal characteristics of the material may be different depending on if the material is intended to be pre-seeded with cells or be used as a substitute acellular material, however, a direct comparison is still needed. For example, previously it has been concluded that a larger fiber diameter (4.83 µm versus fiber diameters ranging from 1.64–3.37 µm) resulted in human umbilical vein endothelial cells (HUVECs) having significantly greater scaffold infiltration, viability, and CD31 expression [53]. Another study seeded vascular smooth muscle cells (VSMC) on PCL fiber membranes with varying diameters (0.5, 0.7, 1, 2, 2.5, 5, 7, and 10 µm) and concluded that a larger diameter (7 and 10 µm) allowed for greater VSMC and macrophage infiltration when compared to the lower fiber diameter scaffolds [65]. One paper published in 2021 supported that the cellular phenotype of seeded cells is modulated by the fibers’ electrical charge (piezoelectric properties) which were also shown to be influenced by fiber diameter [66]. A previous review has covered recent literature regarding how different electrospun fiber characteristics affect immune response [67]. Although the literature offers a range of porosities and fiber diameters that influence cellular phenotype, there still appears to be no defined standard for gingival tissue engineering. When comparing the current relative benchmark grafting materials structure to electrospun materials, we do see similarities in structure. It is no surprise that Geistlich scaffolds (Fibro-Gide’s®, Mucograft®, and Mucoderm®) structure resembles the collagen fibrils found in the native gingiva because it is made from bovine-derived collagen. In addition to having a fiber structure that resembles the native tissue (similar to the Geistlich materials), electrospun materials allow for many other factors to be controlled (e.g., porosity, fiber diameter, etc.) [49]. The scientific field appears to be moving towards materials with much more function and modulatory features, targeted at enhancing tissue development, and tissue engraftment beyond what is offered by a simple collagen scaffold. 5. Layered Structures in Electrospun Constructs It is well established that electrospun scaffolds can be designed to closely resemble that of the native ECM [49]; however, using a single layer electrospun membrane does not enable the engineering or regeneration of tissues with considerable thicknesses and the appropriate defined cellular densities that are needed. Thus the use of layered electrospun scaffolds has become more evident in the literature [7]. The use of layered scaffolds for the broader concept of periodontal regeneration has been noted and reviewed by authors previously and described as a burgeoning concept [7]. However, the literature is relatively limited with respect to articles that have reviewed the use of layered electrospun scaffolds, specifically for regenerating and engineering gingival tissue. Given the tissue-specific dependence of tissue engineering methods on the different cell phenotypes, vascular bed density generated, and ECM composition/production as discussed above, it is relevant to provide the field with particular attention to such design considerations. Gingival tissue could be considered as having layers in both the horizontal (transverse) and vertical (longitudinal) axes. As illustrated in Figure 4A, the native gingiva consists of layers that are vertically stacked in the free gingiva, with these defined layers taking on a honeycomb structure in the attached gingiva [68]. Figure 4B illustrates layered electrospun scaffolds which have structural similarities to native gingival tissue. In the horizontal direction, gingival tissue is composed of three main layers, an epithelium composed of many layers of keratinocytes with complex and diverse functionality [7,69], the basement membrane, and the lamina propria which consists of a papillary and reticular layer containing gingival fibroblasts, vasculature, and collagen-rich ECM [13,14,17]. Therefore, it is supported that the use of layered electrospun scaffolds, which architecturally mimic the divergent aspects of the native gingiva, could be generated. 5.1. Horizontal Layers The complete biological function of tissue forming layers appears to be quite complex and likely is not fully understood. However, some specific examples can help us understand its potential relevance for gingival tissue engineering. The engineering or regeneration of full-thickness gingival tissue requires the consideration of three main tissue layers in the horizontal direction [13]. Most proximal to the alveolar bone or tooth, the stratified squamous epithelium must be present to protect the tissue from both bacterial and mechanical threats [71]. The next layer is the basement membrane which is critical in separating the lamina propria and epithelium [13]. The basement membrane consists of anchoring fibers, integrins, laminin, and collagen type IV, which are necessary for the attachment of cells in the lamina propria and epithelium [13]. Not only does the basement membrane dictate cellular attachment but is also involved with cellular differentiation and phenotype [72]. In an in vitro model, it has been understood that the behavior of epithelial cell layers (which function to protect the tooth from bacterial and mechanical threats) is modulated by/through adherens junctions, which facilitate the formation of epithelial cells into a layer above a sheet of fibroblasts [73]. Further, the connection between the epithelial cell sheet layer and the underlying fibroblast layer is important such that they are required to prevent apoptosis [74]. These adhesions between the epithelial and fibroblast layer play a role in mechanically stabilizing the cell sheet, cell migration, reorganization, and random cell movement [73,75]. Additionally, the keratinocytes, found within the epithelium of the gingiva, form layers themselves with functional differences [13,76]. Thus, engineering gingival tissue in sheets or layers may offer a method for recapitulating this interaction. 5.2. Vertical Layers In the vertical or longitudinal direction within the lamina propria, we also observe layers of tissue. In vitro when gingival fibroblasts are grown on cementum they form sheets (qualitatively resembling an electrospun scaffold) [21,77,78]. Additionally, when fibroblasts are cultured in the presence of transforming growth factor-β they form sheets [79,80]. Transportation and diffusion of oxygen, nutrients, waste, and bioactive molecules are anticipated to be a function of the tissue layers. The movement of these molecules throughout a tissue is critical for tissue remodeling and regeneration. The characteristics of electrospun scaffolds such as porosity have exciting implications for engineering layered tissue, as these parameters could control the diffusion of bioactive molecules and can be optimized for factors such as cellular ingrowth, cellular proliferation, and diffusion of cellular waste, nutrients, and oxygen between layers [81]. Bovine-collagen-derived materials currently used, do not allow for the optimization of all these parameters. A previous study showed that the layering of electrospun scaffolds (polycaprolactone and polycaprolactone/collagen), with the layers being seeded with either ECs or fibroblasts, facilitated the formation of vessels in an in vivo rat model, with red blood cells being found in the middle of a three-layer construct after just one week [82]. Interestingly, the formation of vasculature was dependent on the number of electrospun scaffold layers, and the presence of endothelial cell layers. This supports that layered electrospun scaffolds can facilitate the formation of vasculature in a way that would be expected to permit the movement of waste, oxygen, and nutrients, supporting tissue regeneration. In vivo after one week of implantation, red blood cells were found at the center of a three-layered construct. This study provides strong support that electrospun multilayered constructs seeded with ECs and fibroblasts provide an adequate environment for the formation of vasculature [82]. Considering that vasculature in the native gingiva is present (10 lumens/mm2 [22], with the diameters outlined in Table 1), potential material or tissue-engineered substitutes must support the formation of vasculature, which layered electrospun scaffolds have directly been shown to facilitate. More comprehensive pre-clinical animal models will be needed to evaluate multilayered constructs in a gingival tissue-specific in vivo environment. To further improve the function of the layered electrospun scaffolds, micron-sized laser-cut ablations have previously been made through layers of an electrospun poly (l-lactic acid) scaffold, a cross-section of which can be seen in Figure 4B [70]. The approximately 300 µm in diameter laser-cut pores enhanced the proliferation, and viability of seeded human adipose-derived stem cells (ASCs), compared to non-ablated scaffolds [70]. Further, the ablations helped to prevent the separation of the scaffold layers and maintain the multilayered structure [70]. Collagen type I was also pipetted onto the scaffold before layering, to improve the attachment between the cell-seeded scaffold layers [70]. The use of laser-cut ablations may offer a method to decrease the separation of scaffold layers, and improve cell viability and proliferation [70]. The conclusion is that there is in vivo evidence for multilayered electrospun constructs facilitating the formation of vascularized tissue, but future work should continue to pursue the use of layered electrospun scaffolds for specifically gingival tissue engineering, as an alternative to the Fibro-Gide®, Mucograft®, and Mucoderm® materials. Vertical and horizontal gingival tissue-engineered layers could later be combined, to closely recapitulate the native gingival tissue. Although layering electrospun materials appears to provide a potentially viable architecture for gingival tissue engineering, another important consideration is the material itself. 6. Conventional Material Approaches There are three types of scaffolding materials that are relevant to the gingival tissue engineering application: natural polymers, synthetic polymers, and hybrid/composites [83]. All three of these latter groups are most appropriate and popular for soft tissue engineering due to their ability to recapitulate several physical/biochemical aspects, function, and architecture of the native tissue [84]. In general, natural scaffolds have fast and inconsistent degradation with poor mechanical properties [85,86]. Specifically, the limitations of the collagen matrices are that degradation and tissue integration must be balanced with mechanical properties. As the degree of crosslinking is increased within the matrix, there is also an increase in mechanical stability and degradation resistance, but tissue integration is decreased [43]. Many crosslinking methods have drawbacks which include inflammatory responses to the reagents and the foreign nature of the crosslinked structures [43,87]. Additionally, the proportion of collagen to elastin can be altered to change the scaffold’s mechanical properties and degradation (although degradation was not directly studied by the referenced authors) [88]. However, this is limited by the innate characteristics of the biomolecules used [88]. Fibro-Gide® (seen in Figure 4C) has a porosity of ~93%, increases in volume by ~25% when wetted [43], and an elastic modulus of ~5.9 × 10−3 Mpa [89], with the elastic modulus of native gingival tissue being ~37.4 Mpa [90]. When the Fibro-Gide® membranes are implanted in vivo, most of the material appears to degrade within 90 days, with some elastin still present thereafter [91]. Even after 90 days, there does appear to be tissue remodeling [91]. The use of decellularized human tissue or Alloderm® for gingival tissue engineering has also been explored and used clinically, however, the material has limited cell infiltration, inconsistent degradation, and a high cost compared to their competition [40,41,45,46,47]. Thus, likely explains the material’s inferior clinical performance when compared to FGGs [45,46,47], and limited uptake by clinicians. Polyurethane-based materials have also been used clinically, such as Artelon®, a porous polycaprolactone-based polyurethane urea scaffold. One study showed the material can allow for a marketable improvement in volume for buccal soft tissue augmentation [92,93]. Few studies have investigated the use of this material for gingival tissue engineering, with the longest reported follow-up being only 6 months [92,94]. The potential downside to the material is its relatively slow degradation of approximately 6 years, which may hamper tissue integration and the formation of functional gingival tissue [92,93]. The potential concern with lacking functional tissue development is the inability for the required cellular interactions to occur between keratinized tissue and the underlying tissue [38]. Synthetic materials such as expanded polytetrafluorethylene (ePTFE), polylactic acid (PLA), and PLA-polyglycolic acid (PLA-PGA) have been evaluated clinically for treating gingival recession and previously reviewed [95]. The use of ePTFE has major drawbacks, as a second follow-up appointment is needed to remove the non-degradable material. When comparing ePTFE to PLA no significant difference was detected in terms of keratinized tissue 6 months post-surgery [95]. Further as reviewed previously [95], an alarming reaction, characterized by swelling and a large foreign body reaction including multinucleated giant cells, is associated with the use of PLA as a gingival grafting material. PGA [96], and the slower degrading poly(glycolide-co -L-lactic acid) or PGLA, have also been investigated for gingival tissue engineering applications [97,98]. PGLA has inferior fibroblast attachment and proliferation with poor epithelial morphogenesis when compared to natural scaffolds [85,99,100]. Compared to natural polymers synthetic scaffolds are generally considered to have superior mechanical properties, are more reproducible, and are more economical [101]. Pros and cons exist for both natural and synthetic scaffolds, however, the cons may be able to be negated by using a more complex approach that exploits the pros of each material type to negate their respective cons. 7. Current Direction in Material Development The criteria and future directions of material substitutes for gingival tissue engineering are that they be: non-infectious, biocompatible, allow for rapid tissue integration, facilitate the efficient formation of vascularization, maintain volumetric form over time, have mechanical characteristics that allow for practical clinical handling, and are economical [102]. Although all design features may be improved by using novel material substitutes, the area that likely warrants the greatest improvement is the time towards tissue integration and vascularization, while not compromising mechanical stability. To overcome some of the challenges and improve upon the conventional material approaches the development of new materials for gingival tissue engineering appears to be leaning towards the use of blended or composite/hybrid biomaterials, constituting multiple natural and/or synthetic polymers, with or without added bioactive molecules. This allows for a scaffold with greater function. While the use of composites has been previously alluded to in relation to the use of electrospun polymer blends for fabricating more functional scaffolds [103,104], the approach applied to the specific context of gingival tissue engineering is lacking in the literature. Of particular relevance, are the unique criteria that are needed for gingival tissue engineering which might be best met by using blended or composite biomaterials. Previously the use of such hybrid scaffolds has allowed for the control and tuning of a scaffold’s relevant physical properties. A blend of gelatin and PLA was electrospun and characterized [105]. The combination of natural and synthetic polymers facilitated the fabrication of scaffolds with unique fiber diameters, hydrophilicities, and porosities; this could be optimized for gingival tissue engineering. The combination of a synthetic material such as PLA, which is hydrophobic, slowly degrading, and has good mechanical properties can be well complemented with a hydrophilic natural-based material, which has excellent cell adhesion, has timely degradation, but limited mechanical properties (e.g., gelatin). Essentially the materials address each other’s downsides, resulting in a more optimal and functional material for gingival tissue engineering. Although the example of the PLA/gelatin scaffold [105], and a previous review on electrospun polymer blends for fabricating more functional scaffolds were looked at through a broader tissue engineering lens [103,104], the underlying fundamental relation between the structure and function of the electrospun fiber materials also has promise for engineering gingival tissue material substitutes. In 2019, an electrospun scaffold with varying ratios of PCL and dicalcium phosphate dihydrate (DCPD) was investigated for bone tissue engineering [106]. The addition of the DCPD structure to the PCL scaffold improved the material’s hydrophilicity and fluid absorption in addition to improving the cell viability of HGFs, a relevant cell type for gingival tissue engineering [106]. The improvement in function is likely explained by the increase in surface roughness, changes in fiber diameter, and hydrophilic properties [106]. Poly(vinyl alcohol) and sodium alginate (PVA/SA) scaffolds have previously been electrospun at 10 wt% and 3.5 wt%, 4 wt% and 5 wt%, respectively [107]. The growth of HGFs on each scaffold was then investigated [107]. The structure provided by using a 4 wt% PVA/SA solution was determined to have the highest biocompatibility with electrochemical properties, suggesting that mature cell interactions were occurring between HGFs [107]. The authors suggested that it was the function provided by the dielectric properties specific to the 4 wt% PVA/SA scaffold that is enabling a scaffold with improved biocompatibility, determined by a greater HGF density, and coverage of the scaffold [107]. Cons to the use of PVA are that it is non-hydrolyzable, and has a history of being a complement system activator [108], which can negatively impact wound healing [109]. Previously aligned PCL, basic fibroblast growth factor (bFGF)-loaded electrospun membranes coated with self-polymerized dopamine conjugated with heparin, have been investigated as a material substitute for gingival tissue grafting [110]. In this study, seeded NIH-3T3 cells adhesion, and adhesion morphology was improved in the coated and loaded group, with a synergistic effect being detected in fibroblast proliferation in the aligned, coated, and loaded group [110]. The addition of a polydopamine coating and heparin immobilization changed the water contact angle of the material from 120° to 30°, essentially making a hydrophobic scaffold hydrophilic [110]. The combination of both a bioactive molecule (bFGF) and fiber alignment is reported to synergistically enhance tissue regeneration [110]. This is likely due to the aligned fibers, and the presence of bFGF recapitulating structural and molecular (bioactive molecules) factors that are seen in native tissue. This is a great example of how the field is pushing to generate more functional material substitutes when compared to the currently used Fibro-Gide®, Mucograft®, and Mucoderm® materials. To improve cellular/tissue infiltration sacrificial polymers have previously been used in the electrospinning process. Previously, a polyvinylpyrrolidone (PVP) and collagen solution were co-electrospun with poly(L-lactide-co-ε-caprolactone) (PLLCL). Post-electrospinning the PVP was removed by rinsing with water [59]. In another example, poly(desamino tyrosyl-tyrosine carbonate) (PDTEC) was electrospun with poly(ethylene glycol) (PEG) [60]. The PEG was used as a sacrificial polymer which once removed, increased the porosity of the scaffold facilitating the infiltration of cells [60]. This approach offers another potential strategy to modulate mechanical properties, degradation, and cellular infiltration. A number of electrospun fibers with antibacterial properties have also been previously prepared [111,112]. Some of the antibacterial agents that have previously been introduced into electrospun scaffolds for periodontal engineering are bismuth subsalicylate [113], ampicillin [111], and ciprofloxacin-based additives [114]. The current relative benchmark grafting materials do not explicitly use antibacterial additives, suggesting that the incorporation of antibacterial molecules into material substitutes may be advantageous. Although, the actual rate of infection with scaffolds such as Fibro-Gide® appears to be lacking from the literature. Thus, making it difficult to evaluate what impact the use of antimicrobial biomaterials could have. Further, if infection did occur this can be treated with oral antibiotics. Silk is a material that has previously been used for oral mucosal tissue engineering [115,116]. One example which exemplifies the use of multi-functional electrospun scaffolds for oral mucosa regeneration was published in 2020. Silk electrospun fibers were modified with the addition of surface-aminated liposomes which were encapsulating leptin (NH2-LIPs) [116]. Polydopamine (PDA) was also synthesized onto the surface of the silk fibers. The catechol groups on the PDA can then react with the amino groups on the NH2-LIP, facilitating the fabrication of a silk fiber modified with PDA and NH2-LIP [116]. The addition of PDA and/or NH2-LIP led to the water contact angle of the material falling from 64 degrees to ~0 degrees [116]. The leachate from the scaffold with PDA and NH2-LIP resulted in human umbilical vein endothelial cells (HUVECs) forming a greater area of tubular structures or meshes after 10 h in culture, compared to the leachate of the non-functionalized silk fibers and silk fibers coated with only PDA [116]. In vivo, the electrospun scaffolds with PDA and NH2-LIP accelerated wound closure in an oral defect rabbit model. The scaffolds may be improved by using aligned electrospun fibers rather than random fiber arrangements. The functionality of electrospun scaffolds for gingival tissue regeneration has previously been improved upon in a recent study (2021) where polycaprolactone (PCL) fibers were enriched with vitamin E and hyaluronic acid, and seeded with HGFs [117]. It was reported that HGFs seeded on the fibers with vitamin E and hyaluronic acid had statistically greater proliferation and gene expression, which induced a phenotype conducive to collagen deposition [117]. Vitamin E and hyaluronic acid inclusion may offer a relatively easy approach to enhancing cellular proliferation and gene expression of HGFs which could be implemented in future material substitutes. Although the use of synthetic polymers such as PCL are popular in the literature, likely due to them being economical, well studied, and approved by the Food and Drug Administration (FDA), they have some major drawbacks. Specifically, PCL has limited recognition sites for cells, is hydrophobic [118], and has been shown to elicit a major immune response when used as a material substitute [95]. However, improvements are being made by producing composite materials, and thus, it is the latter compositions that include PCL that may have a place for gingival tissue engineering, rather than the PCL fibers themselves. One must consider that if the secondary composite components are leachable, then at some time the PCL will be left alone for an extended period of time given its slow degradation rate, and hence the above shortcomings re-emerge later in the implant life, which could be problematic. One potential limitation of using composite/blended polymer electrospinning is the necessity for a solvent that is suitable for electrospinning and solvates all the included polymers. This consideration has been previously reviewed [103] and may require modifications and optimization to be made for the electrospinning process of gingival tissue constructs. Degradation of Scaffold Materials and Mechanical Properties When considering the optimization of materials for gingival tissue engineering, one major relationship of importance is the association between the mechanical properties of a material and the degradation of the material. We have seen both ends of this spectrum used, with synthetic-based materials having appropriate mechanical properties but relatively slow degradation, and natural materials such as Fibro-Gide® (bovine-collagen-based) having relatively quick degradation and weak mechanical properties, but superior biocompatibility [43]. The approach of improving the mechanical properties of natural polymers by adding a synthetic material with superior mechanical characteristics has been extensively reported in previous literature [119]. The native gingival tissue has an elastic modulus and tensile strength that are approximately 37.4 MPa and 3.8 MPa, respectively [90]. However, human buccal mucosa, which has been used for autologous grafting to treat gingival recession, has an elastic modulus and tensile strength of approximately 8.3 MPa and 1.5 MPa, respectively, which was found to be significantly different than human gingival tissue [90]. Therefore, the mechanical properties of a tissue-engineered gingival graft could better reflect that of the native gingival tissue when compared to the current grafting tissue. This difference in mechanical properties suggests that a material substitute or engineered construct may only need to have a modulus within the range of what is seen in oral soft tissues. The mechanical characteristics of a material for gingival tissue engineering become important when you consider the mechanical stressors that the material or engineered tissue would be subjected to; this occurs during or from speech, mastication, orthodontic movement, and during wound healing (e.g., blood flow and sutures) [120]. A bioreactor has previously been developed to screen potential cell-seeded material substitutes for oral soft tissue grafting [120]. The bioreactor determines and controls the shear force and pressure exerted on the cell-seeded material and allows for the subsequent observation of the material’s responses to different forces and pressures. This could be a potential tool for screening engineered gingival tissue constructs [120], however, a limitation is that there are still relatively minimal data available for quantifying the actual forces that occur in vivo [120]. Another mechanical property consideration of a potential material substitute for gingival tissue repair is the suture pull-out strength, as materials need to withstand the shear stress of a suture. The current standard for suture retention or pull-out strength is 2N, and would likely need to be a criterion for any material substitutes to be considered for translation [121,122]. When considering the degradation rate of a potential substitute material, generally the material needs to degrade fast enough for the host or seeded cells to integrate into the material. Though, slow enough to not leave the cells without a scaffold to adhere to, and for the graft to retain its volume. The use and clinical comparison of ePTFE (sold by Gore®) and a PLA membrane (sold by Guidor®) has previously been made in a canine model [123]. The non-resorbable ePTFE material does not degrade and must be removed after grafting, typically after 4–6 weeks. Thus, non-degradable materials are not intended for regenerating the gingiva through cellular infiltration, which would be required to form functional gingival tissue. The importance of regenerating the gingival tissue rather than only filling in the volume cannot be underscored enough, as the literature suggests that the underlying connective tissue facilitates and modulates epithelial growth and cellular differentiation [124,125]. If a material was to be implanted that degrades too quickly (>16 weeks), loss of volume would occur with poor or no tissue development [126]. When considering a material such as tetrapolymer PTFE-polyvinylidene fluoride (PVDF)-Polypropylene (PP) tetrapolymer or Artelon® which breaks down over years [127], minimal tissue infiltration is observed and the regeneration of functional tissue (cellular interactions with the basement membrane vasculature, etc.), is not formed. Looking at the degradation of the Gesitlich Fibro-Gide® material substitute [89], it is observed that after 3 months in vivo, tissue remodeling/healing is still occurring, with blood vessels formed in the material and some of the material still being present. However, the majority of material degradation has occurred [91], and thus, the degraded Fibro-Gide® material has typically lost its physical form too early and presents properties on the lower end of what would be efficacious. One way by which the mechanical properties of an electrospun scaffold can be modulated is by decreasing the material’s fiber diameter, which is typically proportional to an increased fiber density, providing greater mechanical stability. In a specific example using PCL/PEG fibers, it was found that as the proportion of PEG was increased, the mean fiber diameter decreased and the modulus of the material increased [118]. A Young’s modulus of 8.91MPa and 25–26MPa was determined with the PCL and PCL/PEG fibers, respectively [118]. Another related method for modulating electrospun fiber’s mechanical properties is through the use of sacrificial polymers. By using sacrificial polymers such as those described in the previous section [59,60], the fiber density and thus the mechanical properties can be adjusted, based on the fiber density of an electrospun membrane being proportional to the material’s Young’s modulus [128]. Previously, blends of defined ratios of PLA and PLGA have been fabricated [129]. In phosphate-buffered saline (PBS), PLGA and PLA scaffold degraded ~30% and ~15%, respectively with blends of the materials degrading 15–30% over 10 weeks [129]. This would then be expected to be a slower degradation rate compared to most natural scaffolds, however, the degradation product is lactic acid, which is known to interact with oral Streptococcus mutans (S. mutans), potentially leading to unfavorable outcomes such as S. mutans death, and changes in pH below that which is needed for the formation of caries [130]. In terms of mechanical properties, the pure PLGA and PLA scaffolds have a Young’s modulus from ~2 MPa to ~5 MPa, respectively, with the blends having moduli between 2 and 5 MPa [129]. Although the mechanical properties and degradation properties might be expected to be superior for gingival tissue regeneration to natural collagen-based scaffolds, the large immune response elicited by the materials, and their hydrophobic character are significant drawbacks, likely preventing the material’s adoption in the clinic [95]. Thus, the inferior biocompatibility must be offset with the partial substitution of natural polymers or the use of a new material entirely. Exploring electrospun blends of PCL and gelatin [131], PLA and gelatin [132], and many other blends of synthetic and natural polymers [103], have been previously reported on for tissue engineering and may offer promise for gingival tissue engineering [131]. As discussed in the previous section, the use of silk electrospun scaffolds with PDA and NH2-LIP shows promise. The addition of PDA and NH2-LIP to silk fibers increased the tensile strength from 1.95MPa to 2.87MPa [116]. Mechanical properties in this range seem reasonable considering native gingival tissue has a tensile strength of 3.8 MPa and buccal mucosa has a tensile strength of 1.5MPa [90]. Further, through a tissue engineering lens, we would expect the modulus of the materials to increase once seeded with cells [133]. Electrospun silk scaffolds have previously been shown to degrade in vivo within 8 weeks [134], which may be too quick to allow for the required anastomosis and tissue remodeling to occur, for the grafted volume to be retained and for the material to provide adequate efficacy. However, data do provide the support that vascularization of the silk fibers with PDA and NH2-LIP does occur in the oral cavity of a rabbit 14 days post-implantation [116]. A next step may be towards determining the in vivo efficacy of the material and/or pre-vascularized tissue constructs and comparing it to the Fibro-Gide®, Mucograft®, and Mucoderm® materials. Determining the material’s suture pull-out strength could also be useful for evaluating the material’s handleability. Another biomaterial that has been explored for the regeneration of several tissues, including gingival tissue, is segmented polyurethanes [135,136,137,138,139]. The soft and hard segments of these versatile biomaterials allow for control of the material’s mechanical and degradation properties. The degradation and mechanical properties can be used to strengthen and prolong the support provided for a scaffold by blending them with natural or other rapid-degrading polymers with weak mechanical characteristics. We have seen this achieved with some success in the treatment of wounds. For example, a blend of polyurethane and gelatin has previously been employed with the rationale of increasing degradation resistance and improving the mechanical properties of the material [135]. Using a 20% polyurethane and 80% gelatin material, in a collagenase/MMP-1 solution, the replacement of 20% gelatin for polyurethane resulted in the material degrading in 14 days versus within just 3 h in the 100% gelatin group [135]. While these specific formulations degrade too fast, there is much room for adjusting the ratios of natural polymers to polyurethanes, as well as the nature of the natural polymers and polyurethanes themselves. Further, investigators have previously suggested that efforts should be made to improve the degradation resistance of the Geistlich® collagen-based matrices to enzymatic digestion, such as that from collagenase [43]. The addition of polyurethanes to natural scaffolds may offer the needed temporal degradation resistance to collagenase. The efficacy of the material innovations that have been discussed here could be further improved through the addition of cells, which can be accomplished via a pre-seeding step to kick start the tissue formation process prior to implantation. The addition of cells to a material takes a step towards developing tissue in vitro which when used as a graft can decrease the time to engraftment [11], consequently leading to better efficacy. 8. Cell Options for Use with Electrospun Scaffolds Previously, the application of pre-vascularized constructs for oral tissue grafting has been reviewed [11]. The review concluded that in vivo pre-vascularized implants had quicker integration with the host’s vasculature [11]. One main consideration when assessing engineering pre-vascularized constructs is the cell source itself. During periodontal tissue regeneration, HGFs play a fundamental role in establishing the needed ECM required to achieve integration between the relevant tissues [33] and support ECs that contribute to enabling angiogenesis [140]. Thus, a co-culture of ECs and support cells such as fibroblast-like cells, and vice-versa, should provide the required biological cues for the formation of vasculature and gingival tissue regeneration [141]. With the aim of regenerating the buccal tissue, a triculture with epithelial cells was seeded on one side of either a Geistlich Bio-Gide® or Bio-Gide® Pro (further crosslinked) scaffold with fibroblasts from the gingiva, and microvascular endothelial cells from human juvenile foreskin (in a 1:1 ratio) being seeded on the other side [142]. After 10 days of subcutaneous implantation in a mouse, the seeded pre-vascularized constructs had evidence of red blood cells present within the constructs. Based on these findings and the previously mentioned review [11], the efficacy and shift towards the use of pre-vascularized constructs appear to be occurring. The use of clinically convenient and practically sourced cells to be obtained from the patient to allow for the generation of an autologous graft still appears to remain a challenge. The use of adipose tissue may be of particular interest as both fibroblast-like human adipose-derived stem cells (ASCs) and human adipose-derived microvascular endothelial cells (HAMVECs) can be obtained from a single tissue sample [143]. ASCs are a heterogeneous group of fibroblast-like cells [144], which are phenotypically indistinguishable from fibroblasts [145]. Only 5% of genes are uniquely expressed between HGFs and human dermal fibroblasts, with their fundamental characteristics being the same [146]. This suggests that gingival-specific fibroblasts may not be necessary for gingival tissue grafting. However, a functional comparison is lacking in the literature. Adipose tissue may provide an inexpensive, practical, and autologous source of fibroblast-like cells and ECs. Due to the reciprocal interaction of the soft tissue underlying the basement membrane and keratinized tissue, the use of a cell type that can either form a basement membrane or an epithelium would be expected to be advantageous for the support of keratinized tissue. More specifically, it is beta1-integrins and other integrins found in the ECM of the underlying connective tissue that regulates and dictate cellular differentiation, detachment, apoptosis, and other cellular behaviors [38]. Previously, ASCs have been shown to produce an epithelium with a basement membrane not fully developed compared to a culture of HGFs [124]. ASCs have also been shown to be able to differentiate into keratinocytes [147]. Adipose tissue appears to offer a practical and convenient source of microvasculature cells, fibroblast-like cells, and keratinocytes [147], which accounts for the majority of the cellular components comprising gingival tissue [13,17]. Determining the efficacy of the novel acellular materials and cell-seeded materials discussed here will also need to be accompanied by the development of new pre-clinical animal models. There are recent reports on the use of an oral defect rabbit model, however, the latter model does have limitations, including the observation that the experiment was only carried out 14 days post-operation [116]. With the rabbit defect model being reported in 2020 the field will likely continue to build and improve on the model. Pre-clinical models for oral reconstructive therapies have previously been reviewed [148], with no reports of rodent animal models specifically targeted for evaluating the efficacy of tissue-engineered implants for gingival recession. Such consideration is an area of critical development needed for early pre-clinical assessment in the future. This will contribute to advancing the new materials and specifically cell-seeded constructs, before moving to larger animal models which are more costly, and ultimately clinical trials. It should be noted that a limitation of this review is the lack of in vivo data directly comparing the novel materials and electrospun layered constructs to the family of Geistlich materials (Fibro-Gide®, Mucograft®, and Mucoderm®). Hence, this represents an area of future growth. Having said this, there is in vivo evidence that multilayered electrospun constructs facilitate the formation of vascularized tissue [82], and we are beginning to see gingival-specific pre-clinical animal models. The field will now need to work towards evaluating novel constructs using gingival-specific in vivo models and compare them to the current material standards. 9. Conclusions With the field of gingival tissue engineering being in its infancy, the use of layered electrospun composite materials appears to offer the versatility needed to generate structured materials and constructs with function towards the regeneration of gingival tissue. The literature offers a number of specific strategies for modulating a scaffold’s function that can be used to optimize materials for the treatment of gingival recession. Specifically, significant work is being directed towards blended synthetic/natural material substitutes and autologous pre-vascularized cell-seeded grafts. A material with multiple optimized functional design features, such as degradation, porosity, potential to vascularize, and loading with bioactive molecules, is likely to have the most promise for clinical success. Future work will need to focus on evaluating the ability of the prepared materials or constructs to support the development of healthy functional gingival tissue and its relevant cells. Acknowledgments We would like to thank Sakshee Trivedi for kindly providing images for this work. Author Contributions Conceptualization, B.C.W.W., J.P.S. and M.G.; resources, J.P.S.; writing—original draft preparation, B.C.W.W.; writing—review and editing, B.C.W.W., J.P.S. and M.G.; supervision, J.P.S.; project administration, J.P.S.; funding acquisition, J.P.S. 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. 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 (A) The periodontal tissue anatomy. Created with BioRender.com. (B,C) Decellularized human gingival tissue adapted from previous literature reproduced under terms of the CC-BY license [16]. Copyright 2012, Nasser Mahdavishahri, Maryam Moghatam Matin, Masoud Fereidoni, Zahra Yarjanli, Seyed Ali Banihashem Rad, and Saeedeh Khajeh Ahmadi, published by Iranian Journal of Basic Medical Sciences. Created with BioRender.com, accessed on 8 April 2022. Figure 2 The workflow and potential complications that can occur with a connective tissue graft. The string of green dots represents bacteria. Created with BioRender.com with images from Dr. Michael Glogauer (University of Toronto) and images reproduced with permission under terms of the CC-BY license [31]. Copyright 2014, Sakshee Trivedi, Neeta Bhavsar, Kirti Dulani, and Rahul Trivedi published by the Journal of Clinical and Experimental Dentistry. Created with BioRender.com, accessed on 8 April 2022. Figure 3 The electrospinning process with a scanning electron microscopy image of an electrospun scaffold taken by the author. Created with BioRender.com, accessed on 8 April 2022. Figure 4 Scanning electron microscopy images of different gingival tissue and previously reported constructs. (A) Scanning electron microscopy images of native gingival tissue. FG: free gingival, AG: attached gingiva. Reproduced with permission [68]. Copyright 1981, published by the Journal of Periodontal Research. (B) Scanning electron microscopy images of layered poly(l-lactic acid) electrospun scaffolds with adipose-derived stem cells and collagen. The white arrow indicates delamination of the scaffold layers. Reproduced with permission [70]. Copyright 2010, published by the Tissue Engineering—Part C: Methods. (C) Scanning electron microscopy images of a Geistlich® Fibro-Gide® matrix. 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