Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Work–Family Conflict on Burnout during the COVID-19 Pandemic: The Effect of Teleworking Overload

If there is any field that has experienced changes as a result of the COVID-19 pandemic, it is work, primarily due to the implementation of teleworking and the effort made by workers and families to face new responsibilities. In this context, the study aims to analyze the impact of work–family conflict on burnout, considering work overload, in teleworkers during the COVID-19 pandemic. To evaluate the hypotheses, we used data collected during the last week of July 2020 using an online survey. Work–family conflict and burnout were measured using the Gutek et al. (1991) and Shirom (1989) scales. We tested the hypotheses using a structural equation model (SEM). The results indicated, between other findings, that there was a positive relationship between work–family conflict and family–work conflict and all the dimensions of burnout. However, there was no effect of teleworking overload in the work–family conflict and burnout relationship. This article is innovative because it highlights the importance of the economic and regulatory conditions that have surrounded the modality of teleworking during the pandemic, and their influence on wellbeing and psychosocial risks in workers.
Psychological Distress, Dental Health, and Dental Fear among Finnish University Students: A National Survey

The aim of this study was to investigate the association between dental fear, psychological distress, and perceived symptoms of teeth controlled for age, gender, educational sector, and tobacco use. The data from the Finnish University Student Health Survey 2016 targeting students (n = 10,000) of academic universities and universities of applied sciences were used. Psychological distress was measured with the Clinical Outcomes in Routine Evaluation 10 (CORE-10) and the General Health Questionnaire 12 (GHQ-12) and dental fear with the question ‘Do you feel scared about receiving dental care? ’. The study included 3110 students. In logistic regression analyses those with psychological distress (measured with CORE-10 and GHQ-12) and those reporting teeth-related symptoms were more likely than their counterparts to have high dental fear. In gender-specific analyses men with psychological distress (measured with CORE-10) and women with teeth-related symptoms were more likely to have high levels of dental fear. Finnish university students with psychological distress and teeth-related symptoms were more likely to experience higher levels of dental fear than their counterparts were. The results of this study support possible common vulnerability factors that dental fear and other psychological disorders may share.
A Survey of Autoencoder Algorithms to Pave the Diagnosis of Rare Diseases

Rare diseases (RDs) concern a broad range of disorders and can result from various origins. For a long time, the scientific community was unaware of RDs. Impressive progress has already been made for certain RDs; however, due to the lack of sufficient knowledge, many patients are not diagnosed. Nowadays, the advances in high-throughput sequencing technologies such as whole genome sequencing, single-cell and others, have boosted the understanding of RDs. To extract biological meaning using the data generated by these methods, different analysis techniques have been proposed, including machine learning algorithms. These methods have recently proven to be valuable in the medical field. Among such approaches, unsupervised learning methods via neural networks including autoencoders (AEs) or variational autoencoders (VAEs) have shown promising performances with applications on various type of data and in different contexts, from cancer to healthy patient tissues. In this review, we discuss how AEs and VAEs have been used in biomedical settings. Specifically, we discuss their current applications and the improvements achieved in diagnostic and survival of patients. We focus on the applications in the field of RDs, and we discuss how the employment of AEs and VAEs would enhance RD understanding and diagnosis.
A Method for Assaying of Protein Kinase Activity In Vivo and Its Use in Studies of Signal Transduction in Strawberry Fruit Ripening

Strawberry (Fragaria × ananassa) fruit ripening is regulated by a complex of cellular signal transduction networks, in which protein kinases are key components. Here, we report a relatively simple method for assaying protein kinase activity in vivo and specifically its application to study the kinase, FaMPK6, signaling in strawberry fruit. Green fluorescent protein (GFP)-tagged FaMPK6 was transiently expressed in strawberry fruit and after stimuli were applied to the fruit it was precipitated using an anti-GFP antibody. The precipitated kinase activity was measured in vitro using 32P-ATP and myelin basic protein (MBP) as substrates. We also report that FaMPK6 is not involved in the abscisic acid (ABA) signaling cascade, which is closely associated with FaMPK6 signaling in other plant species. However, methyl jasmonate (MeJA), low temperature, and high salt treatments were all found to activate FaMPK6. Transient manipulation of FaMPK6 expression was observed to cause significant changes in the expression patterns of 2749 genes, of which 264 were associated with MeJA signaling. The data also suggest a role for FaMPK6 in modulating cell wall metabolism during fruit ripening. Taken together, the presented method is powerful and its use will contribute to a profound exploration to the signaling mechanism of strawberry fruit ripening.
Predicting Future Geographic Hotspots of Potentially Preventable Hospitalisations Using All Subset Model Selection and Repeated K-Fold Cross-Validation

Long-term future prediction of geographic areas with high rates of potentially preventable hospitalisations (PPHs) among residents, or “hotspots”, is critical to ensure the effective location of place-based health service interventions. This is because such interventions are typically expensive and take time to develop, implement, and take effect, and hotspots often regress to the mean. Using spatially aggregated, longitudinal administrative health data, we introduce a method to make such predictions. The proposed method combines all subset model selection with a novel formulation of repeated k-fold cross-validation in developing optimal models. We illustrate its application predicting three-year future hotspots for four PPHs in an Australian context: type II diabetes mellitus, heart failure, chronic obstructive pulmonary disease, and “high risk foot”. In these examples, optimal models are selected through maximising positive predictive value while maintaining sensitivity above a user-specified minimum threshold. We compare the model’s performance to that of two alternative methods commonly used in practice, i.e., prediction of future hotspots based on either: (i) current hotspots, or (ii) past persistent hotspots. In doing so, we demonstrate favourable performance of our method, including with respect to its ability to flexibly optimise various different metrics. Accordingly, we suggest that our method might effectively be used to assist health planners predict excess future demand of health services and prioritise placement of interventions. Furthermore, it could be used to predict future hotspots of non-health events, e.g., in criminology.
Criminal Behavior and Psychosocial Risk Factors in Brazilian Adolescent Offenders: An Exploratory Latent Class Analysis

Considering that adolescent offenders are quite a heterogeneous group in terms of behavioral and psychosocial variables, it is considered that a typological approach can assist in the systematization of these differences, aiming at a better understanding of the phenomenon and at clearer guidance in terms of interventions. Therefore, this study aimed to identify the behavioral and psychosocial profiles of male adolescent offenders, based on empirical data collected in a Brazilian sociocultural context. The profiles were made with a sample of 400 adolescent offenders to perform an exploratory latent classes analysis. The instruments used in data collection were the Youth Behavior Questionnaire (Questionário de Comportamentos Juvenis, QCJ) and the Brazilian Jesness Inventory—Revised (Inventário Jesness-Revisado-Brasileiro, IJ-R-Br). The most appropriate model was that of four classes, with the profiles found indicating differences between the adolescent offenders both in relation to psychological functioning and criminal pattern, as well as the psychosocial risk/protective factors associated with each of the profiles. These findings, in addition to contributing to understanding the phenomenon, may help to reflect on the assessments required to assist in judicial decision-making processes and the customized proposal of psychosocial interventions.
Sequential Application of Calcium Phosphate and ε-Polylysine Show Antibacterial and Dentin Tubule Occluding Effects In Vitro

In this study, ε-polylysine and calcium phosphate precipitation (CPP) methods were employed to induce antibacterial effects and dentin tubule occlusion. Antibacterial effects of ε-polylysine were evaluated with broth dilution assay against P. gingivalis. CPP solution from MCPM, DCPD, and TTCP was prepared. Four concentrations of ε-polylysine(ε-PL) solutions (0.125%, 0.25%, 0.5%, 1%) were prepared. Dentin discs were prepared from recently extracted human third molars. Dentin discs were incubated with P. gingivalis (ATCC 33277) bacterial suspension (ca. 105 bacteria) containing Brain Heart Infusion medium supplemented with 0.1 g/mL Vitamin K, 0.5 mg/mL hemin, 0.4 g/mL L-cysteine in anaerobic jars (37 °C) for 7 days to allow for biofilm formation. P. g–infected dentin specimens were randomly divided into four groups: CPP + 0.125% ε-PL, CPP + 0.25% ε-PL, CPP + 0.5% ε-PL, CPP + 1% ε-PL. On each dentin specimen, CPP solution was applied followed by polylysine solution with microbrush and immersed in artificial saliva. Precipitate formation, antibacterial effects, and occlusion of dentinal tubules were characterized in vitro over up to 72 h using scanning electron microscopy. ε-PL showed 34.97% to 61.19% growth inhibition levels against P. gingivalis (P. g) after 24 h of incubation. On P. g-infected dentin specimens, DCPD + 0.25% ε-PL, and DCPD + 0.5% ε-PL groups showed complete bacterial inhibition and 78.6% and 98.1% dentin tubule occlusion, respectively (p < 0.001). The longitudinal analysis on fractured dentin samples in DCPD and TTCP groups revealed deeply penetrated hydroxyapatite-like crystal formations in dentinal tubules after 72 h of incubation in artificial saliva.
Workplace Cognitive Failure among Nurses during the COVID-19 Pandemic

Numerous studies provide evidence of the physical and emotional strain experienced by nurses during the COVID-19 pandemic. However, little is known regarding the impact of this occupational strain on nurses’ cognitive function at work. The aim of this study was to identify factors associated with workplace cognitive failure in a sample of U.S. nurses during the COVID-19 pandemic. An online questionnaire was administered in May 2020 to Michigan nurses statewide via three nursing organizations (n = 695 respondents). Path analysis was conducted to test the parallel effects of frequency of contact with COVID patients and personal protective equipment (PPE) supply on workplace cognitive failure scores. Mediation effects of stress, sleep quality, secondary trauma, and work-related exhaustion were examined for each exposure. Results revealed significant indirect effects of all mediators except sleep quality of contact with COVID patients (cumulative indirect effect = 1.30, z = 6.33, p < 0.001) and PPE (cumulative indirect effect = −2.10, z = −5.22, p < 0.001) on cognitive failure. However, 58% of the PPE effect was direct. To reduce the risk of cognitive failure, healthcare organizations need to provide nurses with protective equipment and work environments that allow nurses to strengthen their resilience to extreme working conditions.
Electroencephalography as a Non-Invasive Biomarker of Alzheimer’s Disease: A Forgotten Candidate to Substitute CSF Molecules?

Biomarkers for disease diagnosis and prognosis are crucial in clinical practice. They should be objective and quantifiable and respond to specific therapeutic interventions. Optimal biomarkers should reflect the underlying process (pathological or not), be reproducible, widely available, and allow measurements repeatedly over time. Ideally, biomarkers should also be non-invasive and cost-effective. This review aims to focus on the usefulness and limitations of electroencephalography (EEG) in the search for Alzheimer’s disease (AD) biomarkers. The main aim of this article is to review the evolution of the most used biomarkers in AD and the need for new peripheral and, ideally, non-invasive biomarkers. The characteristics of the EEG as a possible source for biomarkers will be revised, highlighting its advantages compared to the molecular markers available so far.
Angiogenic Effects and Crosstalk of Adipose-Derived Mesenchymal Stem/Stromal Cells and Their Extracellular Vesicles with Endothelial Cells

Adipose-derived mesenchymal stem/stromal cells (ASCs) are an adult stem cell population able to self-renew and differentiate into numerous cell lineages. ASCs provide a promising future for therapeutic angiogenesis due to their ability to promote blood vessel formation. Specifically, their ability to differentiate into endothelial cells (ECs) and pericyte-like cells and to secrete angiogenesis-promoting growth factors and extracellular vesicles (EVs) makes them an ideal option in cell therapy and in regenerative medicine in conditions including tissue ischemia. In recent angiogenesis research, ASCs have often been co-cultured with an endothelial cell (EC) type in order to form mature vessel-like networks in specific culture conditions. In this review, we introduce co-culture systems and co-transplantation studies between ASCs and ECs. In co-cultures, the cells communicate via direct cell–cell contact or via paracrine signaling. Most often, ASCs are found in the perivascular niche lining the vessels, where they stabilize the vascular structures and express common pericyte surface proteins. In co-cultures, ASCs modulate endothelial cells and induce angiogenesis by promoting tube formation, partly via secretion of EVs. In vivo co-transplantation of ASCs and ECs showed improved formation of functional vessels over a single cell type transplantation. Adipose tissue as a cell source for both mesenchymal stem cells and ECs for co-transplantation serves as a prominent option for therapeutic angiogenesis and blood perfusion in vivo.
Phylogeny, body morphology, and trophic level shape intestinal traits in coral reef fishes

Abstract Trait‐based approaches are increasingly used to study species assemblages and understand ecosystem functioning. The strength of these approaches lies in the appropriate choice of functional traits that relate to the functions of interest. However, trait–function relationships are often supported by weak empirical evidence. Processes related to digestion and nutrient assimilation are particularly challenging to integrate into trait‐based approaches. In fishes, intestinal length is commonly used to describe these functions. Although there is broad consensus concerning the relationship between fish intestinal length and diet, evolutionary and environmental forces have shaped a diversity of intestinal morphologies that is not captured by length alone. Focusing on coral reef fishes, we investigate how evolutionary history and ecology shape intestinal morphology. Using a large dataset encompassing 142 species across 31 families collected in French Polynesia, we test how phylogeny, body morphology, and diet relate to three intestinal morphological traits: intestinal length, diameter, and surface area. We demonstrate that phylogeny, body morphology, and trophic level explain most of the interspecific variability in fish intestinal morphology. Despite the high degree of phylogenetic conservatism, taxonomically unrelated herbivorous fishes exhibit similar intestinal morphology due to adaptive convergent evolution. Furthermore, we show that stomachless, durophagous species have the widest intestines to compensate for the lack of a stomach and allow passage of relatively large undigested food particles. Rather than traditionally applied metrics of intestinal length, intestinal surface area may be the most appropriate trait to characterize intestinal morphology in functional studies.
ADSC-Based Cell Therapies for Musculoskeletal Disorders: A Review of Recent Clinical Trials

Recently published clinical trials involving the use of adipose-derived stem cells (ADSCs) indicated that approximately one-third of the studies were conducted on musculoskeletal disorders (MSD). MSD refers to a wide range of degenerative conditions of joints, bones, and muscles, and these conditions are the most common causes of chronic disability worldwide, being a major burden to the society. Conventional treatment modalities for MSD are not sufficient to correct the underlying structural abnormalities. Hence, ADSC-based cell therapies are being tested as a form of alternative, yet more effective, therapies in the management of MSDs. Therefore, in this review, MSDs subjected to the ADSC-based therapy were further categorized as arthritis, craniomaxillofacial defects, tendon/ligament related disorders, and spine disorders, and their brief characterization as well as the corresponding conventional therapeutic approaches with possible mechanisms with which ADSCs produce regenerative effects in disease-specific microenvironments were discussed to provide an overview of under which circumstances and on what bases the ADSC-based cell therapy was implemented. Providing an overview of the current status of ADSC-based cell therapy on MSDs can help to develop better and optimized strategies of ADSC-based therapeutics for MSDs as well as help to find novel clinical applications of ADSCs in the near future.
Sorption and Micro-Scale Strength Properties of Coals Susceptible to Outburst Caused by Changes in Degree of Coalification

Coals from the south-western part of the Upper Silesian Coal Basin have a strong outburst susceptibility. The objective of this study was to identify the influence of coalification degree on methane sorption and micro scale strength properties of 24 coals from Jastrzębie Zdrój. Coal samples showed a reflectance Ro between 0.98 and 1.25%. Sorption measurements were carried out by gravimetric method. Sorption capacities were determined at mean deposit temperature of 35 °C. Using the unipore model and solution of Fick’s second law, the effective diffusion coefficients of methane in the studied coals were obtained. The Vickers method was used to study the microhardness and the modulus of elasticity. It has been shown that the increase in the coalification degree reduces the sorption capacity of coal and also reduces the rate of methane emission. Coals the most susceptible to outbursts, were the most brittle. With the increase in Ro, the methane seam pressure p increased as well as desorbable methane content DMC, both due to the reduction in the sorption capacity of coal. The increased dp index is a warning sign indicating an increased total methane content of coal seam, an increased seam pressure or an alternation of coal structure.
Risk Stratification of Patients with Acute Coronary Syndrome

Defining the risk factors affecting the prognosis of patients with acute coronary syndrome (ACS) has been a challenge. Many individual biomarkers and risk scores that predict outcomes during different periods following ACS have been proposed. This review evaluates known outcome predictors supported by clinical data in light of the development of new treatment strategies for ACS patients during the last three decades.
Favoring recruitment as a conservation strategy to improve the resilience of long‐lived reptile populations: Insights from a population viability analysis

Abstract In long‐lived species, although adult survival typically has the highest elasticity, temporal variations in less canalized demographic parameters are the main drivers of population dynamics. Targeting recruitment rates may thus be the most effective strategy to manage these species. We analyzed 1,136 capture–recapture histories collected over 9 years in an isolated population of the critically endangered Lesser Antillean iguana, using a robust design Pradel model to estimate adult survival and recruitment rates. From an adult population size estimated at 928 in 2013, we found a yearly decline of 4% over the 8‐year period. As expected under the canalization hypothesis for a long‐lived species, adult survival was high and constant, with little possibility for improvement, whereas the recruitment rate varied over time and likely drove the observed population decline. We then used a prospective perturbation analysis to explore whether managing the species’ immature cohorts would at least slow the population decline. The prospective perturbation analysis suggested that a significant and sustained conservation effort would be needed to achieve a recruitment rate high enough to slow the population decline. We posit that the high recruitment rate achieved in 2014—likely due to the maintenance in 2012 of the main nesting sites used by this population—would be sufficient to slow this population's decline if it was sustained each year. Based on the results of diverse pilot studies we conducted, we identified the most likely threats targeting the eggs and immature cohorts, stressing the need to improve reproductive success and survival of immature iguanas. The threats we identified are also involved in the decline of several reptile species, and species from other taxa such as ground‐nesting birds. These findings on a little‐studied taxon provide further evidence that focusing on the immature life stages of long‐lived species can be key to their conservation.