A structural model of EFL teachers' physical activity, emotion regulation, and competence for online teaching.

BACKGROUND: The COVID-19 pandemic has prompted a rapid shift to online teaching, placing unprecedented demands on educators' physical and mental well-being. However, the relationship between English as a Foreign Language (EFL) teachers' physical activity, emotion regulation, and competence for online teaching remains underexplored. OBJECTIVES: This study aimed to investigate the interplay between EFL teachers' physical activity, emotion regulation strategies, and competence for online teaching. RESULTS: Structural equation modeling revealed significant direct and indirect effects, indicating that physical activity positively influences emotion regulation, which, in turn, enhances teachers' competence for online instruction. Furthermore, emotion regulation was found to mediate the relationship between physical activity and online teaching competence. CONCLUSIONS: These findings underscore the importance of promoting physical activity among EFL teachers as a means to enhance their emotion regulation skills and competence for online teaching, particularly in the context of the COVID-19 pandemic. IMPLICATIONS: The study highlights the need for targeted interventions aimed at supporting EFL teachers' well-being and professional development, with implications for educational policies, teacher training programs, and institutional support structures in the digital learning landscape.

RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality.

RNA is a complex macromolecule that plays central roles in the cell. While it is well known that its structure is directly related to its functions, understanding and predicting RNA structures is challenging. Assessing the real or predictive quality of a structure is also at stake with the complex 3D possible conformations of RNAs. Metrics have been developed to measure model quality while scoring functions aim at assigning quality to guide the discrimination of structures without a known and solved reference. Throughout the years, many metrics and scoring functions have been developed, and no unique assessment is used nowadays. Each developed assessment method has its specificity and might be complementary to understanding structure quality. Therefore, to evaluate RNA 3D structure predictions, it would be important to calculate different metrics and/or scoring functions. For this purpose, we developed RNAdvisor, a comprehensive automated software that integrates and enhances the accessibility of existing metrics and scoring functions. In this paper, we present our RNAdvisor tool, as well as state-of-the-art existing metrics, scoring functions and a set of benchmarks we conducted for evaluating them. Source code is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr.

Exploring the effect of the structural model of active aging on the self-assessment of quality of life among older people: A cross-sectional and analytical study.

BACKGROUND: Although studies have examined the relationship between variables associated with active aging and quality of life (QoL), no studies have been identified to have investigated the effect of a structural model of active aging on QoL in a representative sample of older people in the community. OBJECTIVE: To measure the domains and facets of QoL in older people and identify the effect of the structural model of active aging on the self-assessment of QoL. DESIGN AND SETTING: This cross-sectional analytical study included 957 older people living in urban areas. Data were collected from households using validated instruments between March and June 2018. Descriptive, confirmatory factor, and structural equation modeling analyses were performed. RESULTS: Most older people self-rated their QoL as good (58.7%), and the highest mean scores were for the social relationships domain (70.12 ± 15.4) and the death and dying facet (75.43 ± 26.7). In contrast, the lowest mean scores were for the physical domains (64.41 ± 17.1) and social participation (67.20 ± 16.2) facets. It was found that active aging explained 50% of the variation in self-assessed QoL and directly and positively affected this outcome (λ = 0.70; P < 0.001). CONCLUSION: Active aging had a direct and positive effect on the self-assessment of QoL, indicating that the more individuals actively aged, the better the self-assessment of QoL.

Structural models of genome-wide covariance identify multiple common dimensions in autism.

Common genetic variation has been associated with multiple phenotypic features in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous phenotypic spectrum is limited. Here, we developed and implemented a structural equation modelling framework to directly model genomic covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent with a case-only design. We identified three independent genetic factors most strongly linked to language performance, behaviour and developmental motor delay, respectively, studying an autism community sample (N = 5331). The three-factorial structure was largely confirmed in independent ASD-simplex families (N = 1946), although we uncovered, in addition, simplex-specific genetic overlap between behaviour and language phenotypes. Multivariate models across cohorts revealed novel associations, including links between language and early mastering of self-feeding. Thus, the common genetic architecture in ASD is multi-dimensional with overarching genetic factors contributing, in combination with ascertainment-specific patterns, to phenotypic heterogeneity.

Barriers and Implications of 5G Technology Adoption for Hospitals in Western China: Integrated Interpretive Structural Modeling and Decision-Making Trial and Evaluation Laboratory Analysis.

BACKGROUND: 5G technology is gaining traction in Chinese hospitals for its potential to enhance patient care and internal management. However, various barriers hinder its implementation in clinical settings, and studies on their relevance and importance are scarce. OBJECTIVE: This study aimed to identify critical barriers hampering the effective implementation of 5G in hospitals in Western China, to identify interaction relationships and priorities of the above-identified barriers, and to assess the intensity of the relationships and cause-and-effect relations between the adoption barriers. METHODS: This paper uses the Delphi expert consultation method to determine key barriers to 5G adoption in Western China hospitals, the interpretive structural modeling to uncover interaction relationships and priorities, and the decision-making trial and evaluation laboratory method to reveal cause-and-effect relationships and their intensity levels. RESULTS: In total, 14 barriers were determined by literature review and the Delphi method. Among these, "lack of policies on ethics, rights, and responsibilities in core health care scenarios" emerged as the fundamental influencing factor in the entire system, as it was the only factor at the bottom level of the interpretive structural model. Overall, 8 barriers were classified as the "cause group," and 6 as the "effect group" by the decision-making trial and evaluation laboratory method. "High expense" and "organizational barriers within hospitals" were determined as the most significant driving barrier (the highest R-C value of 1.361) and the most critical barrier (the highest R+C value of 4.317), respectively. CONCLUSIONS: Promoting the integration of 5G in hospitals in Western China faces multiple complex and interrelated barriers. The study provides valuable quantitative evidence and a comprehensive approach for regulatory authorities, hospitals, and telecom operators, helping them develop strategic pathways for promoting widespread 5G adoption in health care. It is suggested that the stakeholders cooperate to explore and solve the problems in the 5G medical care era, aiming to achieve the coverage of 5G medical care across the country. To our best knowledge, this study is the first academic exploration systematically analyzing factors resisting 5G integration in Chinese hospitals, and it may give subsequent researchers a solid foundation for further studying the application and development of 5G in health care.

Psychological Dimensions That Explain Integrity in Older Adults: Examination of a Structural Model.

OBJECTIVES: The aim of this research was to confirm whether internal coping strengths, depressive symptomatology and gratitude disposition are significant predictors of integrity in older adults. METHODS: Participated 394 Ecuadorian older adults with ages between 60 and 91 years old. Self-report were applied to assess the different variables under study. Specifically, integrity, coping, resilience, self-efficacy, mood and gratitude were assessed. RESULTS: A confirmatory model was estimated to predict ego-integrity. A personal adjustment factor composed of problem-focused coping strategies, resilience and self-efficacy, and gratitude showed positive and significant relationships with ego-integrity, whereas negative mood negatively predicted integrity. CONCLUSIONS: Integrity is a key variable to strengthen a coherent view of one's life history and highly relevant during ageing. Having personal strengths and dispositions that facilitate adaptation to ageing and maintaining a positive mood predicts the attainment of integrity. CLINICAL IMPLICATIONS: Integrity is an adjustment factor that facilitates adaptation to the stressors of ageing and to major life changes and loss of control indifferent areas of life.

The structural model of mother-infant bonding in the first pregnancy based on the mother's attachment style and parenting style: the mediating role of mentalization and shame.

INTRODUCTION: This study aimed to evaluate the relationship between the mother's attachment style and parenting style and mother-infant bonding in the first pregnancy considering the mediating role of mentalization and shame. METHODS: This was a descriptive-correlational study. The sample population included the women who had gone through their first pregnancy and were referred to the health centers in Neyshabur, Iran in 2022. In total, 330 women were selected by convenience sampling. To collect data, we used a demographic questionnaire, the Attachment Style Questionnaire, the Parenting Style Questionnaire, the Mother-Infant Bonding Scale, the Reflective Functioning Questionnaire, and the Guilt and Shame Proneness Scale. Data analysis was conducted using descriptive indices, correlation coefficients, and pass analysis. RESULTS: Overall, the findings showed that the studied model adequately fits the data. Further, the obtained results confirmed the mediating role of mentalization and shame in the relationship between the mother's attachment style and parenting style and mother-infant bonding. A significant correlation was also observed between attachment styles, parenting styles, and mother-infant bonding (p < 0.01). CONCLUSION: Mother-infant bonding is correlated with the mother's attachment style/parenting style, shame, and mentalization. Thus, we can help vulnerable mothers by improving the quality of psychological care before the first pregnancy or during pregnancy.

A Structural Model for the Core Nup358-BicD2 Interface.

Dynein motors facilitate the majority of minus-end-directed transport events on microtubules. The dynein adaptor Bicaudal D2 (BicD2) recruits the dynein machinery to several cellular cargo for transport, including Nup358, which facilitates a nuclear positioning pathway that is essential for the differentiation of distinct brain progenitor cells. Previously, we showed that Nup358 forms a "cargo recognition α-helix" upon binding to BicD2; however, the specifics of the BicD2-Nup358 interface are still not well understood. Here, we used AlphaFold2, complemented by two additional docking programs (HADDOCK and ClusPro) as well as mutagenesis, to show that the Nup358 cargo-recognition α-helix binds to BicD2 between residues 747 and 774 in an anti-parallel manner, forming a helical bundle. We identified two intermolecular salt bridges that are important to stabilize the interface. In addition, we uncovered a secondary interface mediated by an intrinsically disordered region of Nup358 that is directly N-terminal to the cargo-recognition α-helix and binds to BicD2 between residues 774 and 800. This is the same BicD2 domain that binds to the competing cargo adapter Rab6, which is important for the transport of Golgi-derived and secretory vesicles. Our results establish a structural basis for cargo recognition and selection by the dynein adapter BicD2, which facilitates transport pathways that are important for brain development.

An evaluation method for HMI of deep-sea manned submersible based on human reliability.

Improving the human reliability of the human-machine interface (HMI) of deep-sea manned submersible is of great importance for the development of the deep-sea field. Based on the SHEL (Software S, Hardware H, Environment E, Liveware L) model, this study classifies the performance shaping factors (PSF) that affect the human reliability of submersible HMIs and builds a PSF system. The interpretative structural model (ISM) is used to matrix the interactions between the elements that make up the system of PSF. A multi-level recursive structure is obtained by building the corresponding adjacency matrix. The Noisy-OR model is introduced to construct a Bayesian network in order to build a new HMI evaluation method. A real case of Bayesian network causal inference verifies the validity of the built method. This study proposes a set of HMI human reliability evaluation methods applicable to deep-sea manned submersible, which provides a new idea for human reliability assessment.

Expanding the repertoire of human tandem repeat RNA-binding proteins.

Protein regions consisting of arrays of tandem repeats are known to bind other molecular partners, including nucleic acid molecules. Although the interactions between repeat proteins and DNA are already widely explored, studies characterising tandem repeat RNA-binding proteins are lacking. We performed a large-scale analysis of human proteins devoted to expanding the knowledge about tandem repeat proteins experimentally reported as RNA-binding molecules. This work is timely because of the release of a full set of accurate structural models for the human proteome amenable to repeat detection using structural methods. The main goal of our analysis was to build a comprehensive set of human RNA-binding proteins that contain repeats at the sequence or structure level. Our results showed that the combination of sequence and structural methods finds significantly more tandem repeat proteins than either method alone. We identified 219 tandem repeat proteins that bind RNA molecules and characterised the overlap between repeat regions and RNA-binding regions as a first step towards assessing their functional relationship. We observed differences in the characteristics of repeat regions predicted by sequence-based or structure-based methods in terms of their sequence composition, their functions and their protein domains.

Structural Insights of the SARS-CoV-2 Nucleocapsid Protein: Implications for the Inner-workings of Rapid Antigen Tests.

The nucleocapsid (N) protein is an abundant component of SARS-CoV-2 and a key analyte for lateral-flow rapid antigen tests. Here, we present new structural insights for the SARS-CoV-2 N protein using cryo-electron microscopy (EM) and molecular modeling tools. Epitope mapping based on structural data supported host-immune interactions in the C-terminal portion of the protein, while other regions revealed protein-protein interaction sites. Complementary modeling results suggested that N protein structures from known variants of concern (VOC) are nearly 100% conserved at specific antibody-binding sites. Collectively, these results suggest that rapid tests that target the nucleocapsid C-terminal domain should have similar accuracy across all VOCs. In addition, our combined structural modeling workflow may guide the design of immune therapies to counter viral processes as we plan for future variants and pandemics.

Structure-Based Modeling of Sigma 1 Receptor Interactions with Ligands and Cholesterol and Implications for Its Biological Function.

The sigma 1 receptor (S1R) is a 223-amino-acid-long transmembrane endoplasmic reticulum (ER) protein. The S1R plays an important role in neuronal health and it is an established therapeutic target for neurodegenerative and neuropsychiatric disorders. Despite its importance in physiology and disease, the biological function of S1R is poorly understood. To gain insight into the biological and signaling functions of S1R, we took advantage of recently reported crystal structures of human and Xenopus S1Rs and performed structural modeling of S1R interactions with ligands and cholesterol in the presence of the membrane. By combining bioinformatics analysis of S1R sequence and structural modelling approaches, we proposed a model that suggests that S1R may exist in two distinct conformations-"dynamic monomer" (DM) and "anchored monomer" (AM). We further propose that equilibrium between AM and DM conformations of S1R is essential for its biological function in cells, with AM conformation facilitating the oligomerization of S1R and DM conformation facilitating deoligomerization. Consistent with experimental evidence, our hypothesis predicts that increased levels of membrane cholesterol and S1R antagonists should promote the oligomeric state of S1R, but S1R agonists and pathogenic mutations should promote its deoligomerization. Obtained results provide mechanistic insights into signaling functions of S1R in cells, and the proposed model may help to explain neuroprotective effects of S1R modulators.

A marginal structural model analysis for the effect modification by education on the association between cancer diagnosis history and major depressive symptoms: Findings from Midlife Development in the U.S. (MIDUS).

BACKGROUND: Limited research has employed a longitudinal approach to investigate the role of education level as an effect modifier on the relationship between cancer diagnosis history and the experience of major depressive disorder (MDD) with a nationally representative sample. METHODS: We harnessed data from three installments of the MIDUS Longitudinal study (n = 7108). A Marginal Structural Model facilitated the investigation of associations between a history of cancer diagnosis, MDD, and potential modifying effects of education level. Inverse probability weighting helped manage confounding factors. RESULTS: Findings indicated that a cancer diagnosis made one year prior was linked with 3.741 times greater odds of experiencing MDD (95 % CI: 1.411-9.918, p < 0.01). This connection was absent for diagnoses made two years earlier. Among individuals with education up to high school, a recent cancer diagnosis significantly increased the likelihood of MDD in the subsequent wave by 3.45 times (95 % CI: 1.31-9.08, p < 0.05). This pattern was not apparent among better-educated individuals. LIMITATIONS: As the exposure variable was dependent on self-reported questionnaires, recall bias could be a potential limitation. Moreover, unaccounted variables like genetic factors could introduce confounding. CONCLUSIONS: A recent cancer diagnosis, particularly among less educated individuals, correlated with an increased probability of MDD, while the impact was not observed for older diagnoses. These findings emphasize that the timing of a cancer diagnosis and education level need consideration in the mental health assessment of cancer survivors.

A Structural Model of Organization and Clinician Factors Associated with Standardized Measure Use in a National Survey of Youth Mental Health Providers.

Standardized assessment measures are important for accurate diagnosis of mental health problems and for treatment planning and evaluation. However, little is known about youth mental health providers' typical use of standardized measures across disciplines and outside the context of evidence-based practice initiatives. A multidisciplinary national survey examined the frequency with which 674 youth mental health providers administer standardized and unstandardized measures, and the extent to which organizational (i.e., implementation climate, rigid hierarchical organizational structure) and provider (i.e., attitudes toward standardized assessment measures, highest degree, practice setting) characteristics are associated with standardized measure use. Providers used unstandardized measures far more frequently than standardized measures. Providers' perceptions (a) that standardized measures are practical or feasible, (b) that their organization supports and values evidence-based practices, and (c) that their organization has a rigid hierarchical structure predicted greater use of standardized measures. Working in schools predicted less frequent SMU, while working in higher education and other professional settings predicted more frequent SMU. Standardized measures were not routinely used in this community-based sample. A rigid hierarchical organizational structure may be conducive to more frequent administration of standardized measures, but it is unclear whether such providers actually utilize these measures for clinical decision-making. Alternative strategies to promote standardized measure use may include promoting organizational cultures that value empirical data and encouraging use of standardized measures and training providers to use pragmatic standardized measures for clinical decision making.

An integrated method for studying the biodegradation of benzo[a]pyrene by Citrobacter sp. HJS-1 and interaction mechanism based on the structural model of the initial dioxygenase.

A bacterial strain Citrobacter sp. HJS-1 was discovered from the sludge in a drainage canal of a coal mine. Firstly, its biodegradation capacity for benzo[a]pyrene (BaP) was detected under different concentrations. The results proved that the strain possessed excellent biodegradation capacity for BaP with high-efficiency degradation rates ranging from 78.9 to 86.8%. The highest degradation rate was observed in the low-concentration sample, and the high-concentration BaP had a slight influence on the biodegradation capacity due to the potential toxicity of BaP and its oxygen-containing derivatives. Meanwhile, the degradation test for the other five aromatic hydrocarbons (2- to 4-ring) proved that the strain had a comprehensive degradation potential. To clarify the biodegradation mechanism of BaP, a dioxygenase structure was constructed by homology modeling. Then, the interactions between dioxygenase and BaP were researched by molecular simulation. Combined with the identification of the vital BaP-cis-7,8-dihydrodiol intermediate and the interaction analysis, the initial oxidation mode and the binding site of BaP were revealed in the dioxygenase. Taken together, this study has offered a way to understand the biodegradation process of BaP and its interaction mechanism based on experimental and theoretical analysis.

Structural Model for Factor X Inhibition of IgM and Complement-Mediated Neutralization of Adenovirus.

Adenovirus has strong therapeutic potential as an oncolytic virus and gene therapy vector. However, injecting human species C serotype 5 adenovirus, HAdv-C5, into the bloodstream leads to numerous interactions with plasma proteins that affect viral tropism and biodistribution, and can lead to potent immune responses and viral neutralization. The HAdv/factor X (FX) interaction facilitates highly efficient liver transduction and protects virus particles from complement-mediated neutralization after intravenous delivery. Ablating the FX interaction site on the HAdv-C5 capsid leaves the virus susceptible to neutralization by natural IgM followed by activation of the complement cascade and covalent binding of complement components C4b and C3b to the viral capsid. Here we present structural models for IgM and complement components C1, C4b, and C3b in complex with HAdv-C5. Molecular dynamics simulations indicate that when C3b binds near the vertex, multiple stabilizing interactions can be formed between C3b, penton base, and fiber. These interactions may stabilize the vertex region of the capsid and prevent release of the virally encoded membrane lytic factor, protein VI, which is packaged inside of the viral capsid, thus effectively neutralizing the virus. In a situation where FX and IgM are competing for binding to the capsid, IgM may not be able to form a bent conformation in which most of its Fab arms interact with the capsid. Our structural modeling of the competitive interaction of FX and IgM with HAdv-C5 allows us to propose a mechanistic model for FX inhibition of IgM-mediated virus neutralization. According to this model, although IgM may bind to the capsid, in the presence of FX it will likely retain a planar conformation and thus be unable to promote activation of the complement cascade at the virus surface.

Does antibiotic awareness campaigns exposure decrease intention to demand antibiotic treatment? Testing a structural model among parents in Western Australia.

Antimicrobial resistance (AMR) is one of the key public health concerns the world is facing today. The effect of antibiotic awareness campaigns (AACs) on consumer behaviour has been documented in the literature with mixed results. Understanding the mechanism for how AACs affect target populations is vital in designing effective and tailored campaigns. Using structural equation modelling our study examined the relationships among people's exposure to antibiotic awareness campaigns, knowledge of AMR prevention, AMR risk perception, and intention to seek antibiotic treatment. This study also tested the moderating effect of anxiety and societal responsibility on preventing AMR, and on their intention to demand antibiotic treatment mediated by knowledge of AMR prevention and risk-perception. Primary data was generated using an online survey of 250 Western Australian parents. We tested our hypotheses using reliability and validity tests and structural equation modelling. Our results show that exposure to AACs alone may not be enough to change parental intention to demand antibiotic prescription for their children. Parental risk perception of AMR and parental anxiety affect intention to demand antibiotics, and the view that AMR is a social responsibility has a moderating effect on intention to demand antibiotics. These factors could be considered and combine messaging strategies in designing future antibiotic awareness campaigns.

Comparison of the predictive power of two models of cortico-cortical connections in primates: the distance rule model and the structural model.

Synaptic tract-tracing studies in macaques have provided a wealth of data about cortico-cortical connections that have been used to identify regularities and propose models and theories to explain cortical connectivity. The two most relevant of these models are the distance rule model (DRM) and the structural model (SM). They relate the strength and laminar pattern of cortico-cortical connections to two different factors: Euclidean distance (according to the DRM) and cortical type distance (according to the SM). If both predictive factors were correlated, the DRM and the SM would be compatible, but quite often, two cortical areas of similar cortical type are far apart from each other. In the present article, we have performed a conceptual analysis of the DRM and the SM to obtain predictions from each of the two models about strength and laminar pattern of cortico-cortical connections. We then tested the predictive power of each model with analyses of several cortico-cortical connectivity databases to check which of them provide the most accurate predictions. We conclude that the DRM and the SM capture the decrease in connection strength with increasing Euclidean and cortical type distances, respectively; but, for laminar pattern, type distance is a better predictor than Euclidean distance.

Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models.

Longitudinal observational data on patients can be used to investigate causal effects of time-varying treatments on time-to-event outcomes. Several methods have been developed for estimating such effects by controlling for the time-dependent confounding that typically occurs. The most commonly used is marginal structural models (MSM) estimated using inverse probability of treatment weights (IPTW) (MSM-IPTW). An alternative, the sequential trials approach, is increasingly popular, and involves creating a sequence of "trials" from new time origins and comparing treatment initiators and non-initiators. Individuals are censored when they deviate from their treatment assignment at the start of each "trial" (initiator or noninitiator), which is accounted for using inverse probability of censoring weights. The analysis uses data combined across trials. We show that the sequential trials approach can estimate the parameters of a particular MSM. The causal estimand that we focus on is the marginal risk difference between the sustained treatment strategies of "always treat" vs "never treat." We compare how the sequential trials approach and MSM-IPTW estimate this estimand, and discuss their assumptions and how data are used differently. The performance of the two approaches is compared in a simulation study. The sequential trials approach, which tends to involve less extreme weights than MSM-IPTW, results in greater efficiency for estimating the marginal risk difference at most follow-up times, but this can, in certain scenarios, be reversed at later time points and relies on modelling assumptions. We apply the methods to longitudinal observational data from the UK Cystic Fibrosis Registry to estimate the effect of dornase alfa on survival.

A structural model of the iRhom-ADAM17 sheddase complex reveals functional insights into its trafficking and activity.

Several membrane-anchored signal mediators such as cytokines (e.g. TNFα) and growth factors are proteolytically shed from the cell surface by the metalloproteinase ADAM17, which, thus, has an essential role in inflammatory and developmental processes. The membrane proteins iRhom1 and iRhom2 are instrumental for the transport of ADAM17 to the cell surface and its regulation. However, the structure-function determinants of the iRhom-ADAM17 complex are poorly understood. We used AI-based modelling to gain insights into the structure-function relationship of this complex. We identified different regions in the iRhom homology domain (IRHD) that are differentially responsible for iRhom functions. We have supported the validity of the predicted structure-function determinants with several in vitro, ex vivo and in vivo approaches and demonstrated the regulatory role of the IRHD for iRhom-ADAM17 complex cohesion and forward trafficking. Overall, we provide mechanistic insights into the iRhom-ADAM17-mediated shedding event, which is at the centre of several important cytokine and growth factor pathways.