Search Results (27,448)

Background/Objectives: Sleep stage analysis is considered to be the key factor for understanding and diagnosing various sleep disorders, as it provides insights into sleep quality and overall health. Methods: Traditional methods of sleep stage classification, such as manual scoring and basic machine learning approaches, often suffer from limitations including subjective biases, limited scalability, and inadequate accuracy. Existing deep learning models have improved the accuracy of sleep stage classification but still face challenges such as overfitting, computational inefficiencies, and difficulties in handling imbalanced datasets. To address these challenges, we propose the Sleep Stage Analysis with Multilayer Perceptron (SLA-MLP) model. Results: SLA-MLP leverages advanced deep learning techniques to enhance the classification of sleep stages from EEG signals. The key steps of this approach include data collection, where diverse and high-quality EEG data are gathered; preprocessing, which involves signal cropping, spectrogram conversion, and normalization to prepare the data for analysis; data balancing, where class weights are adjusted to address any imbalances in the dataset; feature extraction, utilizing Temporal Convolutional Networks (TCNs) to extract meaningful features from the EEG signals; and final classification, applying a Multilayer Perceptron (MLP) to accurately predict sleep stages. Conclusions: SLA-MLP demonstrates superior performance compared to traditional methods by effectively addressing the limitations of existing models. Its robust preprocessing techniques, advanced feature extraction, and adaptive data balancing strategies collectively contribute to obtaining more accurate results, having an accuracy of 97.23% for the S-DSI, 96.23 for the S-DSII and 97.23% for the S-DSIII dataset. This model offers a significant advancement in the field, providing a more precise tool for sleep research and clinical applications. Full article

Background: This study aims to assess the demographic, lifestyle, and clinical characteristics associated with varying levels of triglycerides (TGs) in a large population sample. Methods: This cross-sectional study utilized data from a nationwide health screening program in Mongolia. A total of 125,330 participants (mean age: 43.8 ± 15.3 years) were included. TG levels were categorized into normal, borderline high, high, and very high. Due to the small number of participants in the very high TG group, they were combined with the high TG category for analysis. Multivariate logistic regression was performed to identify independent predictors of elevated TG levels. Results: The majority of participants (80.3%) had normal TG levels, while 10.3% had borderline high, 8.7% had high, and 0.7% had very high TG levels. Significant predictors of elevated TG levels included age (OR 1.013, 95% CI 1.012–1.014), male (OR 2.328, 95% CI 2.251–2.408), obesity (OR 1.920, 95% CI 1.855–1.987), central obesity (OR 1.866, 95% CI 1.801–1.933), smoking (OR 1.399, 95% CI 1.347–1.453), alcohol use (OR 1.233, 95% CI 1.176–1.292), and non-regular exercise (OR 1.144, 95% CI 1.118–1.171). Sex-specific analysis revealed that elevated TG levels were more prevalent among males, regardless of other risk factors such as obesity and smoking. Conclusions: Male sex, obesity, and smoking were the strongest predictors of elevated TG levels. Full article

This research aims to find an optimal balance between privacy and performance in forecasting mental health sentiment. This paper investigates federated learning (FL) augmented with a novel data obfuscation (DO) technique, where synthetic data is used to "mask" real data points. Bidirectional Encoder Representations from Transformer (BERT) is used for sentiment analysis, forming a new framework, FL-BERT+DO, that addresses the privacy-performance trade-off. With FL, data remains decentralized, ensuring that user-sensitive information is retained on local devices rather than being shared with the FL server. The integration of BERT gives our system an enhanced feature of context sense-making from text conduct, and our model is extremely proficient in emotion categorization tasks. The experiments were performed on combined (real and replica synthetic) datasets containing emotions and showed significant enhancements compared to baseline methods. The proposed FL-BERT+DO framework shows the following metrics: prediction accuracy, $82.74\%$; precision, $83.30\%$; recall, $82.74\%$; F1-score, $82.80\%$. Further, we assessed its performance in the adversarial setup using membership inference and linkage attacks to ensure the privacy-preserved performance did not suffer deeply. It demonstrates that, even for large datasets, providing privacy-preserving prediction is possible and can significantly improve existing methods of addressing personal issues, like mental health support. Based on the results of our work, we can propose the development of secure decentralized learning systems that are capable of providing high accuracy of sentiment analysis and meeting strict privacy constraints. Full article

Goat milk butter, locally known as “Dhan,” from the Sfisfa region of Algeria, holds significant cultural and economic value. This study investigates the probiotic properties of lactic acid bacteria (LAB) present in Dhan, focusing particularly on Lactobacillus strains. Molecular identification using 16S rRNA revealed a dominance of Levilactobacillus brevis and Lactiplantibacillus plantarum, forming a substantial part of the bacterial profile. Three LAB isolates (DC01-A, DC04, and DC06) were selected from fresh samples, and rigorous analyses were performed to evaluate their probiotic properties. Safety assessments confirmed the absence of gelatinase, DNase, and haemolytic activities in all isolates. The isolates demonstrated high tolerance to bile salts and acidic conditions, along with the ability to survive simulated gastrointestinal digestion. Notably, strain DC06 exhibited exceptional survival at low pH (1.5) and high bile salt concentrations (0.15–0.3%). All isolates showed substantial growth in MRS medium with 2% phenol, although growth was significantly decreased at 5% phenol. Furthermore, our strains exhibited high adhesion rates to various solvents, demonstrating their potential for strong interaction with cell membranes. Specifically, adhesion to chloroform was observed at 98.26% for DC01-A, 99.30% for DC04, and 99.20% for DC06. With xylene, the adhesion rates were 75.94% for DC01-A, 61.13% for DC04, and 76.52% for DC06. The LAB strains demonstrated impressive growth in ethanol concentrations up to 12%, but their tolerance did not exceed this concentration. They also exhibited robust growth across temperatures from 10 °C to 37 °C, with strains DC04 and DC06 able to proliferate at 45 °C, though none survived at 50 °C. Additionally, the isolates showed significant resistance to oxidative stress induced by hydrogen peroxide (H₂O₂) and displayed medium to high autolytic activity, with rates of 50.86%, 37.53%, and 33.42% for DC01-A, DC04, and DC06, respectively. The cell-free supernatant derived from strain DC04 exhibited significant antimicrobial activity against the tested pathogens, while strain DC06 demonstrated moderate antioxidant activity with the highest DPPH scavenging rate at 68.56%, compared to the probiotic reference strain LGG at 61.28%. These collective findings not only suggest the probiotic viability of LAB strains found in Dhan but also highlight the importance of traditional food practises in contributing to health and nutrition. Consequently, this study supports the potential of traditional Dhan butter as a functional food and encourages further exploration of its health benefits. Full article

Trace organic contaminants (TrOCs), including pharmaceutically active compounds (PhACs), present significant challenges for conventional water treatment processes and pose potential risks to environmental and human health. To address these issues, nanofiltration (NF) and reverse osmosis (RO) membrane technologies have gained attention. This study aims to evaluate the performance of NF and RO membranes in removing TrOCs from wastewater and develop a predictive model using the Solution Diffusion Model. Experiments were conducted using a stirred cell setup at various target concentrations, stirring speeds, and operating pressures, with acetaminophen and caffeine selected as representative pharmaceutical compounds. The results demonstrated that most of the pharmaceutical compounds were effectively removed, showing excellent performance. NF membranes exhibited high permeate flux with somewhat lower removal efficiency (average 84.17%), while RO membranes demonstrated high removal efficiency (average 99.21%), highlighting their importance in trace pharmaceutical treatment. The predictive model based on the solution diffusion model correlated well with the experimental data, suggesting its potential utility for large-scale system applications. This study confirms that NF and RO membranes are effective technologies for the removal of TrOCs from wastewater, offering a promising solution to the challenges posed by trace pharmaceutical contaminants. Full article

Clostridioides difficile (C. difficile) is a global threat and has significant implications for individuals and health care systems. Little is known about host molecular mechanisms and transcriptional changes in peripheral immune cells. This is the first gene expression study in whole blood from patients with C. difficile infection. We took blood and stool samples from patients with toxigenic C. difficile infection (CDI), non-toxigenic C. difficile infection (GDH), inflammatory bowel disease (IBD), diarrhea from other causes (DC), and healthy controls (HC). We performed transcriptome-wide RNA profiling on peripheral blood to identify diarrhea common and CDI unique gene sets. Diarrhea groups upregulated innate immune responses with neutrophils at the epicenter. The common signature associated with diarrhea was non-specific and shared by various other inflammatory conditions. CDI had a unique 45 gene set reflecting the downregulation of humoral and T cell memory functions. Dysregulation of immunometabolic genes was also abundant and linked to immune cell fate during differentiation. Whole transcriptome analysis of white cells in blood from patients with toxigenic C. difficile infection showed that there is an impairment of adaptive immunity and immunometabolism. Full article

Oxidative stress impairs pigs’ health and production performance. This study examined the effects of level and source of methionine (Met) supplementation against the diquat-induced oxidative stress in pigs. Forty growing barrows were randomly assigned to four groups. Groups 1 and 2 received a basal diet that was adequate in energy and nutrients (Diet 1), Group 3 received a DL-Met-supplemented diet, and Group 4 received an MHA-Ca-supplemented diet. After 3 weeks of feeding (Phase 1), pigs were injected with 10 mL saline (Group 1) or 10 mg/kg-BW diquat in 10 mL saline (Groups 2, 3, and 4), and then continually fed for one week (Phase 2). During or at the end of Phase 1, there were no differences in nearly all of the growth performance and redox parameters among the four groups. During or at the end of Phase 2, however, the ADFI and ADG were lower (p < 0.01) in Group 2 than in Group 1 while the serum malondialdehyde content was higher (p < 0.05) in Group 2 than in Group 1. The serum glutathione peroxidase (GPX) activity and liver superoxide dismutase (SOD) activity were lower (p < 0.05) in Group 2 than in Group 1. The serum GPX activity, the serum total antioxidant capacity, and the liver GPX activity were higher (p < 0.05) in Group 3 than in Group 2. There were nearly no differences in these redox parameters between Groups 3 and 4. In conclusion, MHA-Ca and DL-Met, when used at an equivalent bioefficacy level, had similar effects on the pigs’ growth performance and antioxidative status. Therefore, increased Met supplementation can improve pigs’ antioxidative status. Full article

Climate change is projected to bring substantial changes to hydroclimatic extremes, which will affect natural river regimes and have wide-ranging impacts on human health and ecosystems, particularly in Central Highland Vietnam. This study focuses on understanding and quantifying the projected impacts of climate change on streamflow in the Kon-Ha Thanh River basin, using the Soil and Water Assessment Tool (SWAT) between 2016 and 2099. The study examined projected changes in streamflow across three time periods (2016–2035, 2046–2065, and 2080–2029) under two scenarios, Representative Conversion Pathways (RCPs) 4.5 and 8.5. The model was developed and validated on a daily scale with the model performance, yielding good performance scores, including Coefficient of Determination (R²), Nash-Sutcliffe Efficiency (NSE), and Root Mean Squared Error (RMSE) values of 0.79, 0.77, and 50.96 m³/s, respectively. Our findings are (1) streamflow during the wet season is projected to increase by up to 150%, particularly in December, under RCP 8.5; (2) dry season flows are expected to decrease by over 10%, beginning in May, heightening the risk of water shortages during critical agricultural periods; and (3) shifts in the timing of flood and dry seasons are found toward 2099 that will require adaptive measures for water resource management. These findings provide a scientific foundation for incorporating climate change impacts into regional water management strategies and enhancing the resilience of local communities to future hydroclimatic challenges. Full article

This study aimed to identify the relationship between the safety leadership of safety and health managers, the safety climate of the organization, and the safety behavior of workers in the electronics industry in order to develop a sustainable industrial safety and health policy. The study included 842 individuals working at electronics industry cooperators. After analyzing the correlation between safety leadership of managers, safety climate, and safety behavior using SPSS 23.0, measurement model analysis and structural equation modeling (SEM) were performed using AMOS 26.0 to evaluate their relationships. We observed that the safety leadership of managers was associated with safety climate and safety behavior. Additionally, among the sub-dimensional variables of safety climate, the management’s commitment to safety and health and the delivery and communication of safety and health information were related to safety behavior. Therefore, enhancing worker participation and behavior requires strengthening the safety leadership of managers, increasing management’s commitment to safety and health, and improving the effectiveness of safety and health information delivery and communication. Full article

The effects of music exposure on vocal performers remain relatively unknown. This study aimed to assess the immediate and long-term effects of music and singing practice on the peripheral auditory system of vocal performers using otoscopy, pure-tone audiometry, and noise dosimetry. The hearing status, sound pressure levels (SPLs), and sound doses of 12 vocal performers with normal hearing at the study’s onset were evaluated. Pre- and post-study questionnaires regarding the participants’ otologic health and music-making activities, as well as repeated hearing evaluations, were implemented. Additionally, noise dosimetry was conducted on each participant’s most vocally active day of the week. Audiometric assessments generally revealed normal hearing thresholds, with some exceptions. Half of the participants exhibited elevated low-frequency thresholds and over half of the participants displayed emerging audiometric “notches” at 6000 Hz. Noise dosimetry measurements indicated that most of the participants were consistently exposed to SPLs during music-making activities that exceeded recommended limits. Questionnaire responses highlighted that the participants often engaged in extra-curricular music-making activities, frequently with piano accompaniment, and with little to no use of hearing protection devices. A few of the participants reported histories of otologic issues and potential hearing problems. Full article

From 2020 to 2023, the coronavirus-19 (COVID-19) pandemic exposed children to a variety of adverse childhood events, including parental loss, abuse, and disruption in services, and it exacerbated societal inequities. Studies evaluating the mental health of older children and adolescents reported increases in depression and anxiety symptoms, but no reviews have addressed the effects of the pandemic on preschool children. This systematic review and meta-analysis is the first to explore these effects. The goal was to analyze and synthesize longitudinal cohort studies to determine impact of the COVID-19 pandemic on the development and mental health of young children. Searches of multiple databases were performed for studies published between 2018 and 2023 with pre- and post-pandemic evaluations of the mental health or development of preschool children (aged 0–6 years) using objective measures and according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Cohen’s d effect sizes were calculated for each study that utilized the Strengths and Difficulties Questionnaire (SDQ), Ages and Stages Questionnaire (ASQ), or the Child Behavior Checklist (CBCL). Random-effects mixed models combined the estimates of effect sizes to calculate the overall mean effect size. The meta-analyses included 22,348 children from 16 countries. The analyses showed small increases in emotional symptoms and conduct problems, as well as increases in emotional reactivity, anxiety/depression, withdrawal symptoms, attention problems, and aggressive behaviors. A decrease in fine motor and personal–social skills was noted. Studies not included in these meta-analyses also showed negative effects on language and executive function. This systematic review characterizes the detrimental effects of the COVID-19 pandemic on the mental health and development of preschool children across the world. Our results suggest the vulnerability of early childhood to pandemic-related disruptions, although the heterogeneity in study design and child characteristics may limit some of these conclusions. Full article

Marginalized groups in Manitoba, Canada, especially females and people who inject drugs, are overrepresented in new HIV diagnoses and disproportionately affected by HIV and structural disadvantages. Informed by syndemic theory, our aim was to understand people living with HIV’s (PLHIV) gendered and intersecting barriers and facilitators across the cascade of HIV care before and during the COVID-19 pandemic. This study was co-designed and co-led alongside people with lived experience and a research advisory committee. We employed semi-structured interviews with thirty-two participants and three questionnaires. Interviews were audio-recorded, transcribed, and coded, and descriptive statistics were performed on the first two questionnaires. Qualitative data analysis used thematic analysis and focused on identifying categories (individual, healthcare, and social/structural) related to the barriers and facilitators to HIV care. A total of 32 PLHIV completed this study and over 70% of females and 50% of males reported severe and moderate sexual abuse among other traumatic childhood experiences. Barriers to accessing or continuing in the cascade of HIV care included navigating the initial shock of receiving an HIV diagnosis, mental health challenges and inaccessible supports, substance use, violence (including intimate partner), internalized and enacted compounded stigma related to houselessness and substance use, discrimination by primary care service providers and social networks, lack of preventative and social supports, lack of accessible housing, and programmatic issues. COVID-19 increased mental health problems and disrupted relationships with HIV service providers and peers living with HIV. Facilitators to HIV care included stopping substance use, caring service providers particularly during HIV diagnosis, welcoming healthcare environments, social opportunities and integrated supports, and supportive social networks. Women, men, and non-binary PLHIV experience interconnected factors complicating their experiences with HIV care. Interventions should consider holistic, person-centered, and trauma-informed care options to address the barriers found in this research and appropriately serve PLHIV. Full article

Cardiovascular diseases (CVD) pose a significant global health challenge, requiring innovative therapeutic strategies. Vasodilators, which are central to vasodilation and blood pressure reduction, play a crucial role in cardiovascular treatment. This study integrates quantitative structure– (QSAR) modeling and molecular dynamics (MD) simulations to predict the biological activity and interactions of vasodilatory compounds with the aim to repurpose drugs already known and estimateing their potential use as vasodilators. By exploring molecular descriptors, such as electronegativity, softness, and highest occupied molecular orbital (HOMO) energy, this study identifies key structural features influencing vasodilatory effects, as it seems molecules with the same mechanism of actions present similar frontier orbitals pattern. The QSAR model was built using fifty-four Food Drugs Administration-approved (FDA-approved) compounds used in cardiovascular treatment and their activities in rat thoracic aortic rings; several molecular descriptors, such as electronic, thermodynamics, and topographic were used. The best QSAR model was validated through robust training and test dataset split, demonstrating high predictive accuracy in drug design. The validated model was applied on the FDA dataset and molecules in the application domain with high predicted activity were retrieved and filtered. Thirty molecules with the best-predicted pKI50 were further analyzed employing molecular orbital frontiers and classified as angiotensin-I or β1-adrenergic inhibitors; then, the best scoring values obtained from molecular docking were used to perform a molecular dynamics simulation, providing insight into the dynamic interactions between vasodilatory compounds and their targets, elucidating the strength and stability of these interactions over time. According to the binding energies results, this study identifies novel vasodilatory candidates where Dasabuvir and Sertindole seem to have potent and selective activity, offering promising avenues for the development of next-generation cardiovascular therapies. Finally, this research bridges computational modelling with experimental validation, providing valuable insight for the design of optimized vasodilatory agents to address critical unmet needs in cardiovascular medicine. Full article

Background/Objectives: Cancer patients undergoing chemotherapy often face challenges that reduce their physical function and quality of life. Technological resources offer innovative solutions for physical rehabilitation, but the extent of their application in this context remains unclear. This scoping review aims to explore and map the various technological tools used to support physical rehabilitation in cancer patients during chemotherapy, focusing on their potential to improve outcomes and enhance patient care. Methods: A scoping review was conducted following the Joanna Briggs Institute (JBI) guidelines and the PRISMA-ScR framework. Comprehensive searches were performed in the MEDLINE, CINAHL, Scopus, SPORTDiscus, and COCHRANE databases. The included studies focused on the technological resources used in physical rehabilitation for cancer patients undergoing chemotherapy. Data extraction followed the World Health Organization’s “Classification of Digital Health Interventions v1.0” to categorize the technologies. Results: A total of 32 studies met the inclusion criteria. The most commonly used technologies included wearable devices (16 studies), web-based platforms and telerehabilitation systems (7 studies), mHealth applications (6 studies), virtual reality (2 studies), and exergaming (3 studies). These tools were designed to enhance physical function, manage treatment-related symptoms, and improve overall quality of life. Wearable devices were particularly effective for monitoring physical activity, while web-based platforms and mHealth applications supported remote rehabilitation and patient engagement. Conclusions: Technological resources offer significant opportunities for personalized rehabilitation interventions in cancer patients undergoing chemotherapy. However, further research is needed to evaluate the long-term effectiveness, cost-efficiency, and clinical integration of these tools to ensure broader accessibility and sustainable impact. Full article

Background/Objectives: Chronic diarrhea in dogs is a prevalent condition that significantly impacts canine health, often leading to weight loss, dehydration, and malnutrition. Diagnosing and treating chronic diarrhea is challenging due to its multifactorial nature, necessitating collaboration among veterinarians across various specialties. Measuring cobalamin and folate levels is a crucial diagnostic step for all dogs with chronic diarrhea. The role of these vitamins in erythropoiesis is well-documented in human medicine, where deficiencies are linked to erythropoietic disorders and megaloblastic anemia. This study explores the relationship between cobalamin and folate concentrations with hematologic parameters in dogs with chronic diarrhea to develop novel diagnostic methods that facilitate timely decision making. Methods: Forty-seven adult dogs with a history of chronic diarrhea (2019–2023) were included in the study. Upon presentation, complete blood count and measurement of cobalamin and folate concentrations were performed. The correlation of cobalamin and folate levels with erythrocytic parameters, including hematocrit (HCT), hemoglobin concentration (HGB), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), and reticulocyte count, as well as morphological changes in the blood smear were examined. Results: Serum cobalamin was significantly correlated with RBC (p = 0.032), HGB (p = 0.006), HCT (p = 0.005), and MCV (p = 0.022). Anisocytosis was significantly correlated with hypocobalaminemia (p = 0.002), while acanthocytosis correlated with normal cobalamin levels (p = 0.046). No correlation was found between serum folate and erythrocytic parameters or morphological changes. Conclusions: These findings emphasize cobalamin’s potential role in canine erythropoiesis, highlighting the need for routine evaluation and supplementation when necessary. Conversely, the lack of association with folate suggests it plays a less significant role in this species. These results underscore the importance of complete blood count in the diagnostic investigation of dogs with chronic diarrhea. Full article