Miracle-dz/UniFAR-FTUs huggingface dataset:
Major depression, temperament, and social support as psychosocial mechanisms of the intergenerational transmission of parenting styles

Abstract In this three-generation longitudinal study of familial depression, we investigated the continuity of parenting styles, and major depressive disorder (MDD), temperament, and social support during childrearing as potential mechanisms. Each generation independently completed the Parental Bonding Instrument (PBI), measuring individuals’ experiences of care and overprotection received from parents during childhood. MDD was assessed prospectively, up to 38 years, using the semi-structured Schedule for Affective Disorders and Schizophrenia (SADS). Social support and temperament were assessed using the Social Adjustment Scale – Self-Report (SAS-SR) and Dimensions of Temperament Scales – Revised, respectively. We first assessed transmission of parenting styles in the generation 1 to generation 2 cycle (G1→G2), including 133 G1 and their 229 G2 children (367 pairs), and found continuity of both care and overprotection. G1 MDD accounted for the association between G1→G2 experiences of care, and G1 social support and temperament moderated the transmission of overprotection. The findings were largely similar when examining these psychosocial mechanisms in 111 G2 and their spouses (G2+S) and their 136 children (G3) (a total of 223 pairs). Finally, in a subsample of families with three successive generations (G1→G2→G3), G2 experiences of overprotection accounted for the association between G1→G3 experiences of overprotection. The results of this study highlight the roles of MDD, temperament, and social support in the intergenerational continuity of parenting, which should be considered in interventions to “break the cycle” of poor parenting practices across generations.
Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning–based ECG analysis

Significance The use of artificial intelligence (AI) in medicine, particularly deep learning, has gained considerable attention recently. Although some works boast superior capabilities compared to clinicians, actual deployments of AI systems in the clinic are scarce. We describe four important gaps on the machine-learning side responsible for this discrepancy by first formulating them in a way that is actionable by AI researchers and then systematically addressing these needs. Aiming beyond the search for better model architectures or improved accuracy, we focus directly on the challenges of clinical usefulness as stated by medical professionals in the literature. Our results show that deep-learning systems can be robust, trustworthy, explainable, and transparent while retaining the superior level of performance these algorithms are known for. Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically meaningful terms, handling the presence of unknown medical conditions, and transparency regarding the system’s limitations, both in terms of statistical performance as well as recognizing situations for which the system’s predictions are irrelevant. We articulate these unmet clinical needs as machine-learning (ML) problems and systematically address them with cutting-edge ML techniques. We focus on electrocardiogram (ECG) analysis as an example domain in which AI has great potential and tackle two challenging tasks: the detection of a heterogeneous mix of known and unknown arrhythmias from ECG and the identification of underlying cardio-pathology from segments annotated as normal sinus rhythm recorded in patients with an intermittent arrhythmia. We validate our methods by simulating a screening for arrhythmias in a large-scale population while adhering to statistical significance requirements. Specifically, our system 1) visualizes the relative importance of each part of an ECG segment for the final model decision; 2) upholds specified statistical constraints on its out-of-sample performance and provides uncertainty estimation for its predictions; 3) handles inputs containing unknown rhythm types; and 4) handles data from unseen patients while also flagging cases in which the model’s outputs are not usable for a specific patient. This work represents a significant step toward overcoming the limitations currently impeding the integration of AI into clinical practice in cardiology and medicine in general.
Dyadic coping and coparenting among couples after their child’s recent autism diagnosis

This study explores how parenting couples use their relationship to support each other after their child’s autism diagnosis by assessing the role of dyadic coping and parenting sense of competence as predictors of their coparenting quality. Mothers and fathers raising a child on the spectrum (N = 70 couples) individually completed self-report questionnaires measuring stress appraisal, dyadic coping, parenting sense of competence, and coparenting. Parents were recruited 1–36 months after their child’s autism diagnosis and data were analyzed using the actor-partner interdependence model. Parents’ dyadic coping and sense of competence were related to their level of coparenting. Partner effects were found as mothers’ dyadic coping was positively linked to fathers’ coparenting and a higher sense of competence among fathers predicted mothers’ coparenting. Further research is needed to understand how these effects evolve throughout the child’s development stages. Lay abstract We investigated how couples support each other after their child’s autism diagnosis and whether this affects the way they work together to raise their child. We recruited 70 couples raising a child on the autism spectrum. Both partners were asked to complete the same questionnaires measuring how they perceived the experience of having a child on the autism spectrum, how they used their relationship to support each other during stressful situations, how competent they felt completing their parenting tasks, and the coparenting relationship to explore how they worked together as a team when parenting their child. Parents participated in the study 1–36 months after their child’s autism diagnosis. We used statistical techniques that allowed us to see the impact mothers and fathers had on each other. Overall, parents who felt more competent and supported by their partner worked better as a team to raise their child on the spectrum. Fathers invested in the coparenting relationship more when mothers felt more supported by fathers. Mothers invested in the coparenting relationship more when fathers felt more competent parenting their child. Further research is needed to better understand how we can support couples as their child gets older.
IMU-Based Deep Neural Networks: Prediction of Locomotor and Transition Intentions of an Osseointegrated Transfemoral Amputee

This paper focuses on the design and comparison of different deep neural networks for the real-time prediction of locomotor and transition intentions of one osseointegrated transfemoral amputee using only data from inertial measurement units. The deep neural networks are based on convolutional neural networks, recurrent neural networks, and convolutional recurrent neural networks. The architectures’ input are features in both the time domain and the time-frequency domain, which are derived from either one inertial measurement unit (placed above the prosthetic knee) or two inertial measurement units (placed above and below the prosthetic knee). The prediction of eight different locomotion modes (i.e., sitting, standing, level ground walking, stair ascent and descent, ramp ascent and descent, walking on uneven terrain) and the twenty-four transitions among them is investigated. The study shows that a recurrent neural network, realized with four layers of gated recurrent unit networks, achieves (with a 5-fold cross-validation) a mean F1 score of 84.78% and 86.50% using one inertial measurement unit, and 93.06% and 89.99% using two inertial measurement units, with or without sitting, respectively.
Effect of fulvic acid on gastric mucosa damage caused by chronic water avoidance stress

ABSTRACT We investigated the antioxidant and anti-ulcerogenic effects of fulvic acid (FA) on oxidative damage caused by water avoidance stress (WAS) in rat gastrointestinal mucosa. Three experimental groups were established: control (C), chronic stress (CS), and chronic stress + FA (CS + FA). After WAS, a single dose of FA was administered for 10 days to the CS + FA group. Samples of the pyloric region of the stomach were stained with hematoxylin and eosin (H & E) and periodic acid-Schiff (PAS). Immunohistochemical staining was performed for inducible nitric oxide synthase (iNOS) and endothelial nitric oxide synthase (eNOS). Total antioxidant status (TAS), total oxidant status (TOS), oxidative stress index (OSI), superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase (CAT) levels were measured biochemically. By light microscopy, we observed loss of gastric epithelial cells and greater polymorphonuclear cell migration into the mucosa in the CS group compared to the C group. We found intact epithelial cell structure and a thick superficial mucus layer in the CS + FA group compared to the CS group. These findings in the CS + FA group were similar to those for group C. iNOS staining was stronger in the CS group compared to the C group. TOS and OSI levels in the CS + FA group were decreased compared to the CS group, but TAS, SOD, GPx and CAT levels were increased. We found that WAS caused damage to epithelium and connective tissue of the stomach mucosa and that this damage was prevented by FA. Therefore, administration of FA appears to prevent stress induced damage to rat stomach.
Acyl-CoA synthetase 6 is required for brain docosahexaenoic acid retention and neuroprotection during aging

The omega-3 fatty acid docosahexaenoic acid (DHA) inversely relates to neurological impairments with aging; however, limited nondietary models manipulating brain DHA have hindered a direct linkage. We discovered that loss of long-chain acyl-CoA synthetase 6 in mice (Acsl6–/–) depletes brain membrane phospholipid DHA levels, independent of diet. Here, Acsl6–/– brains contained lower DHA compared with controls across the life span. The loss of DHA- and increased arachidonate-enriched phospholipids were visualized by MALDI imaging predominantly in neuron-rich regions where single-molecule RNA in situ hybridization localized Acsl6 to neurons. ACSL6 is also astrocytic; however, we found that astrocyte-specific ACSL6 depletion did not alter membrane DHA because astrocytes express a non–DHA-preferring ACSL6 variant. Across the life span, Acsl6–/– mice exhibited hyperlocomotion, impairments in working spatial memory, and increased cholesterol biosynthesis genes. Aging caused Acsl6–/– brains to decrease the expression of membrane, bioenergetic, ribosomal, and synaptic genes and increase the expression of immune response genes. With age, the Acsl6–/– cerebellum became inflamed and gliotic. Together, our findings suggest that ACSL6 promotes membrane DHA enrichment in neurons, but not in astrocytes, and is important for neuronal DHA levels across the life span. The loss of ACSL6 impacts motor function, memory, and age-related neuroinflammation, reflecting the importance of neuronal ACSL6-mediated lipid metabolism across the life span.
DNA damage checkpoint activation affects peptidoglycan synthesis and late divisome components in Bacillus subtilis

During normal DNA replication, all cells encounter damage to their genetic material. As a result, organisms have developed response pathways that provide time for the cell to complete DNA repair before cell division occurs. In Bacillus subtilis, it is well established that the SOS‐induced cell division inhibitor YneA blocks cell division after genotoxic stress; however, it remains unclear how YneA enforces the checkpoint. Here, we identify mutations that disrupt YneA activity and mutations that are refractory to the YneA‐induced checkpoint. We find that YneA C‐terminal truncation mutants and point mutants in or near the LysM peptidoglycan binding domain render YneA incapable of checkpoint enforcement. In addition, we develop a genetic method which isolated mutations in the ftsW gene that completely bypassed checkpoint enforcement while also finding that YneA interacts with late divisome components FtsL, Pbp2b, and Pbp1. Characterization of an FtsW variant resulted in considerably shorter cells during the DNA damage response indicative of hyperactive initiation of cell division and bypass of the YneA‐enforced DNA damage checkpoint. With our results, we present a model where YneA inhibits septal cell wall synthesis by binding peptidoglycan and interfering with interaction between late arriving divisome components causing DNA damage checkpoint activation.
Perspectives of patients with chronic pain about a pain science education video

ABSTRACT Purpose Patients have responded in variable ways to pain science education about the psychosocial correlates of pain. To improve the effectiveness of pain education approaches, this study qualitatively explored participants’ perceptions of and responses to pain science education. Methods We conducted a qualitative content analysis of interviews with fifteen, adult patients (73.3% female) who had recently attended a first visit to a chronic pain clinic and watched a pain science educational video. Results Participants thought it was important to improve their and healthcare providers’ understanding of their pain. They viewed the video favorably, learned information from it, and thought it could feasibly facilitate communication with their healthcare providers, but, for many participants, the video either did not answer their questions and/or raised more questions. Participants’ responses to the video included negative and positive emotions and were influenced by their need for confirmation that their pain was real and personal relevance of the pain science content. Conclusion Study results support the feasibility and value of delivering pain science education via video and increase our understanding of patients’ perceptions of and responses to pain science education. The video’s triggering of emotional responses warrants additional research.
Transmission of Seed and Soil Microbiota to Seedling

Seed microbiota can have a crucial role for crop installation by modulating dormancy, germination, seedling development, and recruitment of plant symbionts. Little knowledge is available on the fraction of the plant microbiota that is acquired through seeds. ABSTRACT The seed microbial community constitutes an initial inoculum for plant microbiota assembly. Still, the persistence of seed microbiota when seeds encounter soil during plant emergence and early growth is barely documented. We characterized the encounter event of seed and soil microbiota and how it structured seedling bacterial and fungal communities by using amplicon sequencing. We performed eight contrasting encounter events to identify drivers influencing seedling microbiota assembly. To do so, four contrasting seed lots of two Brassica napus genotypes were sown in two soils whose microbial diversity levels were manipulated by serial dilution and recolonization. Seedling root and stem microbiota were influenced by soil but not by initial seed microbiota composition or by plant genotype. A strong selection on the seed and soil communities occurred during microbiota assembly, with only 8% to 32% of soil taxa and 0.8% to 1.4% of seed-borne taxa colonizing seedlings. The recruitment of seedling microbiota came mainly from soil (35% to 72% of diversity) and not from seeds (0.3% to 15%). Soil microbiota transmission success was higher for the bacterial community than for the fungal community. Interestingly, seedling microbiota was primarily composed of initially rare taxa (from seed, soil, or unknown origin) and intermediate-abundance soil taxa. IMPORTANCE Seed microbiota can have a crucial role for crop installation by modulating dormancy, germination, seedling development, and recruitment of plant symbionts. Little knowledge is available on the fraction of the plant microbiota that is acquired through seeds. We characterize the encounter between seed and soil communities and how they colonize the seedling together. Transmission success and seedling community assemblage can be influenced by the variation of initial microbial pools, i.e., plant genotype and cropping year for seeds and diversity level for soils. Despite a supposed resident advantage of the seed microbiota, we show that transmission success is in favor of the soil microbiota. Our results also suggest that successful plant-microbiome engineering based on native seed or soil microbiota must include rare taxa.
A quantitative analysis of bone lamellarity and bone collagen linearity induced by distinct dosing and frequencies of teriparatide administration in ovariectomized rats and monkeys

Abstract The lamellar structure of bone, which endows biomechanical rigidity to support the host organism, is observed in mammals, including humans. It is therefore essential to develop a quantitative analysis to evaluate the lamellarity of bone, which would especially be useful for the pharmacological evaluation of anti-osteoporotic drugs. This study applied a current system for the semi-automatic recognition of fluorescence signals to the analysis of un-decalcified bone sections from rat and monkey specimens treated with teriparatide (TPTD). Our analyses on bone formation pattern and collagen topology indicated that TPTD augmented bone lamellarity and bone collagen linearity, which were possibly associated with the recovery of collagen cross-linking, thus endowing bone rigidity.
Cyberbullying, student nurses’ ethical awareness and the Covid-19 pandemic

Background: The global COVID-19 pandemic has increased cyber communication, causing nursing students’ clinical practice to be held in cyberspace. Thus, it is essential to ensure that nursing students develop comprehensive cyber ethics awareness. Moreover, cyberbullying is becoming more widespread and is an increasingly relevant new concept. Objectives: This study aimed to assess the experiences of cyberbullying among nursing students during clinical practice and determine the effects of cyberbullying victimization and cyber environments on their cyber ethics awareness. Research design: Data for this descriptive cross-sectional study were collected in July 2020 using a self-reported questionnaire and analyzed using hierarchical regression. Participants and research context: The study included data from 291 nursing students with more than 6 months of clinical experience who were enrolled in two nursing universities in two cities in South Korea. Ethical considerations: This study was conducted after obtaining approval from the Institutional Review Board of G University. Written, informed consent was obtained from all participants. Results: Cyberbullying victimization experiences during clinical practice were few. The most common cyberbullies of work- and person-related cyberbullying were nurses and classmates, respectively. Discussion: Cyber ethics awareness was affected by cyber anonymity and the perceived seriousness of cyberbullying; cyberbullying related to clinical practices was a new factor that significantly affected cyber ethics awareness. Conclusions: Hospitals and nursing universities should develop a multi-dimensional, comprehensive, and effective nursing intervention education program to be integrated into the nursing curriculum to enhance cyber ethics awareness and reduce cyberbullying of nursing students.
Bucket hydrokinesiotherapy in hospitalized preterm newborns: a randomized controlled trial

ABSTRACT Objective To examine the effects of hydrokinesiotherapy in a bucket on physiological parameters and clinical outcomes of hospitalized preterm newborns. Methods In this randomized controlled trial, 34 preterm newborns with low birth weight were randomly allocated into experimental (EG) or control (CG) groups and were assessed four times on two alternate days: pre-intervention, post-intervention, 15 min after the intervention, 30 min after post-intervention. On both days, between pre-and post-intervention, the EG underwent hydrokinesiotherapy in a bucket for 10 min and the CG only had the diaper changed. Physiological parameters and body weight gain were considered primary outcomes. Behavioral state and degree of respiratory distress were secondary outcomes. Results Newborns in the EG presented transitory changes in heart and respiratory rates after the intervention. Oxygen saturation was higher in the EG compared to the CG at post-intervention and up to at least 15 min after post-intervention on both days. The EG was in a more active state than the CG at post-intervention on both days. These changes occurred within normal ranges. Body temperature, degree of respiratory distress, and body weight gain did not differ between groups. Conclusion The hydrokinesiotherapy caused isolated changes in the physiological parameters and led to a more active behavioral state in hospitalized preterm newborns with low birth weight. These changes did not affect the newborns’ clinical conditions. The technique was safe, but clinical outcomes, including body weight gain, were not improved.
Lower and upper motor neuron involvement and their impact on disease prognosis in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a fatal neurodegenerative disease characterized by progressive muscle wasting, breathing and swallowing difficulties resulting in patient’s death in two to five years after disease onset. In amyotrophic lateral sclerosis, both upper and lower motor neurons of the corticospinal tracts are involved in the process of neurodegeneration, accounting for great clinical heterogeneity of the disease. Clinical phenotype has great impact on the pattern and rate of amyotrophic lateral sclerosis progression and overall survival prognosis. Creating more homogenous patient groups in order to study the effects of drug agents on specific manifestations of the disease is a challenging issue in amyotrophic lateral sclerosis clinical trials. Since amyotrophic lateral sclerosis has low incidence rates, conduction of multicenter trials requires certain standardized approaches to disease diagnosis and staging. This review focuses on the current approaches in amyotrophic lateral sclerosis classification and staging system based on clinical examination and additional instrumental methods, highlighting the role of upper and lower motor neuron involvement in different phenotypes of the disease. We demonstrate that both clinical and instrumental findings can be useful in evaluating severity of upper motor neuron and lower motor neuron involvement and predicting the following course of the disease. Addressing disease heterogeneity in amyotrophic lateral sclerosis clinical trials could lead to study designs that will assess drug efficacy in specific patient groups, based on the disease pathophysiology and spatiotemporal pattern. Although clinical evaluation can be a sufficient screening method for dividing amyotrophic lateral sclerosis patients into clinical subgroups, we provide proof that instrumental studies could provide valuable insights in the disease pathology.