Search Results (48,072)

Background/Objectives: Against the background of the rapid aging of the population, the symptoms of depression are a major health problem for middle-aged and older adults. This study analyzes the relationship between social participation and the trajectory of depressive symptoms and whether this association varies by gender. Methods: The data comes from five rounds of surveys conducted by the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, including a total of 5796 participants aged 45 or above. The depressive symptoms of each wave are measured using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10). Social participation was defined as the number of reported activities (0, 1, or ≥2). The development trajectory of depressive symptoms was analyzed through Group-Based Trajectory Modeling (GBTM), and their links with social participation level were subsequently quantified using multinomial logistic regression. Gender differences were assessed via interaction tests and stratified models. Results: GBTM identified four distinct depressive symptom trajectories: low (29.71%), moderate (42.72%), increasing (22.07%), and high (5.50%). Compared with no participation, engaging in one activity was linked to lower odds of falling into the moderate, increasing, and high trajectories; the association was stronger for ≥2 activities. Gender-stratified analyses revealed substantial heterogeneity (all interaction p < 0.01). Among women, single-activity participation was associated with lower odds across all three adverse trajectories. Among men, similar associations required ≥2 activities, with single-activity participation linked only to lower odds of the high trajectory. Conclusions: Higher levels of social participation have significantly reduced the depressive symptoms of middle-aged and older adults, and the gender differences are pronounced. Interventions should improve access to social participation for older women and promote activity diversity for older men. Full article

Background/Objectives: Vaccine hesitancy is a complex and growing phenomenon worldwide, posing a serious threat to public health achievement in disease control and prevention. This study aimed to assess willingness to uptake and factors linked to shifts between different categories of willingness and uptake regarding the COVID-19 and influenza vaccines. Methods: Prospective cohort study with a representative sample of 1400 individuals aged ≥60 years residing in mainland Portugal, randomly selected. Two telephone surveys were conducted: one at the start of the 2023/2024 vaccination campaign, assessing patients’ characteristics and willingness for vaccination (using an 11-point Likert scale), and another at the end, assessing vaccination status and reasons for uptake/non-uptake. Results: Shifts were observed among both acceptance and refusal groups—12.93% of the individuals within these categories shifted to an opposite decision. Hesitancy presents divergent attitudes: for the COVID-19 vaccine, 56.50% declined vaccination, while for the influenza vaccine, non-uptake was only 30.60%. Age, presence of chronic disease, level of education, household dimension, and previous uptake of booster doses are significantly associated with shifting attitudes, playing different roles for each category of willingness and uptake outcome. For the acceptance category, non-uptake relates to confidence factors. For hesitancy, non-uptake is mainly due to complacency. For refusal, the decision is influenced by all domains. Conclusions: Vaccine hesitancy remains an important public health concern in the Portuguese population and appears to differ between COVID-19 and influenza vaccination. Attitudes toward COVID-19 and influenza vaccines can vary in all directions over a short period. Acceptance does not guarantee uptake, and refusal can shift towards uptake. These findings highlight the importance of reinforcing public health strategies and interventions for uptake across a population, taking into consideration the specificities of each willingness group. Full article

Background/Objectives: Type 2 diabetes (T2D) remission can be defined as a return to a HbA1c < 6.5% (<48 mmol/mol) sustained without ongoing treatment for at least 3 months. Prevalence estimates and factors associated remain unknown for LMIC and resource-limited settings. Methods: We conducted a retrospective observational analysis of electronic medical records from 8463 adults who received multidisciplinary care at Mexico’s primary care specialized units (UNEMES-EC) between 2015 and 2019 and who were referred for inadequate metabolic control. Remission was defined per 2021 ADA criteria as HbA1c <6.5% sustained for ≥3 months without glucose-lowering medications. After estimating the prevalence of T2D remission, logistic regression models were used to evaluate its sociodemographic and clinical predictors, with particular attention to weight change and baseline adiposity interactions. Results: RT2D prevalence was 0.87% (95% CI: 0.68–1.10) over a median 393-day follow-up. Weight loss ≥10% (adjusted OR 2.75; 95% CI: 1.21-6.27) and systolic blood pressure (tertile 3 vs tertile 1: OR 2.49; 95% CI: 1.17–5.26) were positively associated with RT2D, while elevated baseline HbA1c (tertile 3 vs. tertile 1: OR 0.09; 95% CI: 0.02–0.33), triglyceride levels (tertile 3 vs. tertile 1: OR 0.49; 95% CI: 0.24–0.98) and intensive pharmacotherapy were inversely associated with RT2D. No associations with HDL and total cholesterol were found. Age, sex, educational attainment, and income demonstrated no independent associations with remission. Among lifestyle-treated patients achieving ≥5% weight loss, remission prevalence reached approximately 11%. No significant interaction between baseline BMI and weight change was detected (p = 0.60). Conclusions: This first large-scale Mexican study establishes RT2D as an achievable endpoint in patients with poor baseline metabolic control. The findings suggest that remission could be achieved with equity-focused, weight-centered interventions even in resource-constrained health systems and populations. Full article

Background: Dynamic risk stratification is fundamental to the modern management of pulmonary arterial hypertension (PAH). However, data on the impact of sequential add-on therapy in patients with Group 1.4 PAH—particularly in Latin American populations—remains limited. This study evaluated changes in risk classification using COMPERA 2.0 and REVEAL Lite 2 scores in patients treated with endothelin receptor antagonist (ERA) and phosphodiesterase type 5 inhibitor (PDE5i) combination therapy (macitentan + sildenafil) at a referral center in Mexico. Methods: In this single-center, retrospective cohort study, 25 patients with a confirmed diagnosis of PAH between 1st January 2022 and 31st December 2024 were evaluated at baseline and after 24 weeks of treatment. Clinical, functional, and biochemical parameters were recorded. Within-patient changes were analyzed using the Wilcoxon signed-rank test, and agreement between risk assessment tools was assessed using Spearman’s correlation coefficient. Results: At 24 weeks, patients demonstrated significant improvement in World Health Organization functional class (p = 0.002) and a significant reduction in brain natriuretic peptide levels (p = 0.003). Both COMPERA 2.0 and REVEAL Lite 2 scores showed a consistent shift toward lower-risk categories. A strong concordance between the two tools was observed. Conclusions: Sequential add-on ERA + PDE5i therapy was associated with meaningful improvement in risk stratification among patients with Group 1.4 PAH. These findings support the clinical utility of simplified, noninvasive risk assessment tools in real-world settings, particularly in resource-constrained environments. Full article

While individual determinants of students’ well-being are well established, less is known about the association with the institutional context. This study evaluates institutional-level factors associated with students’ mental health while controlling for individual characteristics. The cross-sectional analysis used data from 12 German institutions (n = 13,715) collected in the StudiBiFra survey on study conditions and student mental health. Individual-level variables included gender, age, study subject group, and four mental health variables (general well-being, depressiveness, cognitive stress, and exhaustion). Institution-level variables comprised institution type, excellence status, multi-campus structure, size, and satisfaction with the quality of health promotion services. Multilevel binary logistic regression models were applied to examine associations between institutional characteristics and mental health outcomes, adjusting for individual factors. Students enrolled at universities of applied sciences showed a lower likelihood of reporting depressiveness and exhaustion. Higher levels of depressiveness and cognitive stress were observed among students at medium-sized institutions compared to small ones. Students not enrolled at institutions with excellence status had lower risks of depressiveness, stress, and exhaustion. Additionally, higher satisfaction with institutional health promotion services was associated with reduced odds of depressiveness. Institutional factors are related to students’ mental health beyond individual characteristics, highlighting the need for a holistic, setting-based approach. Full article

Background: Physical activity is a key modifiable factor influencing healthy aging, yet data on activity patterns and their physiological correlates in older adults from Central Asia remain limited. Understanding these relationships is essential for informing region-specific health promotion strategies. Objectives: This study assessed physical activity levels among urban-dwelling older adults in Astana, Kazakhstan, and examined associations between activity level, body composition, visceral fat accumulation, metabolic indicators, and muscle strength. Methods: A cross-sectional study was conducted among 608 adults aged ≥60 years (median age: 68 years; 82.1% women). Physical activity was measured using the validated Physical Activity Scale for the Elderly (PASE). Anthropometric and body composition indicators, including BMI, total and visceral fat, skeletal muscle mass, and handgrip strength, were evaluated. Spearman correlation and linear regression analyses were applied. The analyses were exploratory and did not include adjustment for potential confounders such as sex, chronic disease burden, or socioeconomic status; therefore, the observed associations should be interpreted with caution. Results: The median PASE score was 55.55, with 61.8% of participants demonstrating moderate activity levels, primarily through walking and household tasks. In analyses without adjustment for potential confounding factors, PASE scores showed weak inverse associations with visceral fat (ρ = −0.214; p < 0.001) and waist-to-hip ratio (ρ = −0.154; p < 0.001), as well as weak positive associations with handgrip strength. Across the reported significant associations, correlation coefficients ranged from |ρ| = 0.103 to 0.235, and the explanatory capacity of the regression models was low, with R² values ranging from 0.6% to 8.2%. Conclusions: Higher habitual physical activity may be linked to selected bioelectrical impedance parameters, WHR, and handgrip strength among urban older adults. Given the cross-sectional design, causal interpretation should be approached with caution. These findings provide meaningful regional baseline evidence for future longitudinal and intervention studies on physical activity and healthy aging in Central Asia. Full article

Intestinal oxidative stress severely compromises the health and growth of weaned piglets. The fly maggot-derived antioxidant peptide FMP was previously identified, but its protective mechanisms remain unclear. Here, we explored how FMP alleviates oxidative intestinal injury. In IPEC-J2 cells, FMP pretreatment significantly attenuated H₂O₂-induced cytotoxicity, ROS accumulation, and apoptosis, while enhancing antioxidant enzyme activities and activating Nrf2 signaling (p < 0.05). Co-treatment with the Nrf2 inhibitor ML385 abolished FMP-mediated mitophagy enhancement and cytoprotection, revealing that FMP enhances PINK1/Parkin-dependent mitophagy via Nrf2 activation. In diquat-challenged weaned piglets, oral FMP administration restored serum SOD and GSH-Px activities, reduced MDA and DAO levels (p < 0.05), upregulated jejunal tight junction proteins, and enriched Lactobacillus populations. These findings demonstrate that FMP targets the Nrf2-mitophagy axis to protect against intestinal oxidative damage, supporting its application as a green feed additive. Full article

Global agriculture faces a dual imperative: increase food production to meet rising demand while simultaneously reducing environmental impacts and resource inefficiencies. Addressing this challenge requires repositioning ruminant nutrition as the intelligent nexus linking crop and livestock production within Integrated Crop–Livestock Systems (ICLS). In this role, nutrition becomes central to restoring ecological, nutritional, and economic synergies that have been fragmented by decades of agricultural specialization. While ICLS provides the ecological foundation, Precision Livestock Farming delivers the technological and analytical infrastructure necessary to operationalize integration at the individual-animal level. Real-time sensing, Internet of Things platforms, and Artificial Intelligence (AI) enable dynamic monitoring of animal physiology, behavior, and environmental interactions across scales. A key advancement in this evolution is the development of Hybrid Intelligent Mechanistic Models (HIMM), which integrate biologically grounded mechanistic models with data-driven AI approaches. By combining interpretability with adaptive learning, HIMM enhances predictive accuracy, extrapolative capacity, and decision transparency, enabling the creation of digital twins that simulate biological responses before management interventions are implemented. Such architectures extend precision nutrition beyond feed efficiency and methane mitigation to include nutrient density and product quality, thereby linking different ecosystem processes directly to human dietary needs. Integrating nutrition with advanced modeling and monitoring tools can help livestock systems move beyond static “net-zero” benchmarks toward sustainable strategies that are responsive to local production contexts. In this reframed paradigm, nutrition is not merely a production input but the central analytical framework that computationally links biological mechanisms, environmental stewardship, technological innovation, and human health within sustainable ruminant systems. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by β-amyloid (Aβ) accumulation and a breakdown of mitochondrial homeostasis. Vitamin K2 (VK2) has emerged as a potential neuroprotective agent, yet the specific molecular cascades linking its intervention to the restoration of mitochondrial integrity remain poorly understood. This study utilizes an AD Drosophila model to investigate the efficacy of VK2 and elucidates its multidimensional regulatory mechanisms. Behavioral analysis showed that VK2 significantly rescued locomotor impairments, improving both vertical climbing and horizontal walking performance. Crucially, VK2 intervention achieved a systemic rescue of mitochondrial health: transmission electron microscopy (TEM) confirmed the preservation of mitochondrial ultrastructure and cristae density, while biochemical assays demonstrated a robust recovery of bioenergetic markers, including ATP levels and the NAD⁺/NADH ratio. Furthermore, VK2 treatment stabilized the mitochondrial membrane potential (MMP) and effectively attenuated the accumulation of reactive oxygen species (ROS). To identify the molecular drivers of this recovery, an unbiased integration of human clinical transcriptomic data and network pharmacology prioritized the EGFR-Ras-ERK signaling axis as a central hub. In vivo validation confirmed that VK2 suppresses the pathological overactivation of this cascade. VK2 reduced EGFR phosphorylation in parallel with the effects observed for the EGFR inhibitor Gefitinib. Collectively, our findings show that VK2 ameliorates locomotor deficits and mitochondrial dysfunction in Aβ42-expressing flies and that these effects are associated with suppression of the EGFR-Ras-ERK signaling axis. Further studies are required to establish direct target engagement and pathway causality. Full article

Aim: Self-stigma represents a major barrier to recovery among individuals with severe mental illness (SMI). This review aimed to identify and synthesize the available evidence on the effectiveness of non-pharmacological interventions for reducing self-stigma in adults with SMI, while also exploring physical appearance care as a potentially relevant but under-researched area. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines and the Cochrane Handbook recommendations. The review protocol was registered in PROSPERO (CRD420251013333). Data Sources: A comprehensive search was conducted across multiple databases, including the Virtual Health Library, PubMed, Web of Science, the Cochrane Library, and EBSCOhost databases. A snowball search of reference lists was also performed. Studies published in English or Spanish within the past ten years were included. Review Methods: Two independent reviewers screened titles, abstracts, and full texts according to predefined criteria. Methodological quality was assessed using the Critical Appraisal Skills Programme España (CASPe). A qualitative synthesis was conducted for all included studies, and a random-effects meta-analysis was performed for studies providing sufficient quantitative data. Standardized mean differences and heterogeneity statistics were calculated. Results: Twenty-eight studies were included in the qualitative synthesis, and twelve were eligible for meta-analysis. Multicomponent interventions integrating psychoeducation, cognitive restructuring, narrative approaches, and social support showed the most consistent effects across the evaluated outcome domains. Meta-analytic findings indicated small-to-moderate reductions in self-stigma and improvements in hope, with low levels of statistical heterogeneity across outcomes. Effects on self-esteem, quality of life, self-efficacy, and psychiatric symptomatology were limited or inconsistent across studies. No studies specifically evaluated interventions focused on physical appearance care. Conclusions: Non-pharmacological interventions appear to produce modest but potentially meaningful reductions in self-stigma among individuals with SMI, particularly when delivered through multicomponent psychosocial approaches that integrate psychoeducation, cognitive restructuring, narrative techniques, and social support. Full article

The health system is now more complex, uncertain, interdependent, and dynamically interconnected than ever, making traditional planning decisions based on static, reductionist models increasingly impracticable. Systems analytics approaches such as system dynamics, agent-based modeling, and network analysis are often deployed in isolation and fail to capture cross-level interactions and emergent system behavior. This study proposes an integrated multi-layer systems analytics framework that combines these analytical paradigms within a unified architecture to support adaptive health systems planning under uncertainty. The proposed framework introduces an Adaptive Policy Intelligence Layer (APIL), which enables continuous feedback-driven policy adaptation through dynamic monitoring, scenario evaluation, and real-time adjustment mechanisms. The model is evaluated under multiple simulation scenarios, including baseline conditions, demand shocks, resource constraints, and digital transformation environments. The findings provide strong quantitative and analytical evidence of improved system performance and resilience. More specifically, the digital transformation scenario achieved the lowest mean system pressure (0.128) and the highest resilience index (0.887), while the demand shock scenario produced the highest peak system pressure (0.306). The results demonstrate enhanced system resilience, more efficient resource deployment, and superior policy responsiveness compared with traditional single-method approaches. The originality of this study lies in integrating multi-level systems analytics with adaptive policy intelligence into a unified, feedback-driven decision-support framework for resilient health systems governance. The study contributes to systems analytics literature by advancing a synergistic and adaptive modeling paradigm capable of supporting policymakers in navigating complex and unstable healthcare environments. Full article

Antibiotic-resistant bacteria are widely distributed and threaten public health. Photocatalytic antimicrobial technology can effectively inactivate multidrug-resistant bacteria without readily inducing resistance. We previously showed that oxygen-rich vacancy Bi₂MoO₆ (OBM) exhibits excellent activity against methicillin-resistant Staphylococcus aureus (MRSA), but the underlying molecular mechanisms remain poorly understood. Here, we employed integrated transcriptomics and metabolomics, with qRT-PCR validation, to systematically elucidate the antibacterial mechanism of OBM against MRSA. OBM treatment induced profound transcriptional and metabolic alterations: 231 differentially expressed genes and 206 differentially abundant metabolites were identified. Functional enrichment analysis revealed cooperative involvement in multiple critical pathways, including inhibition of amino acid biosynthesis and protein translation, disruption of cell wall and membrane integrity, induction of oxidative stress, collapse of energy metabolism (suppression of oxidative phosphorylation and impaired ATP synthesis), and imbalance in nucleotide metabolism (down-regulation of DNA helicase and mismatch repair genes, dysregulation of purine/pyrimidine metabolism). These findings demonstrate that OBM photocatalytically inactivates MRSA through a multi-target systemic attack at both the transcriptional and metabolic levels, providing a novel theoretical foundation for the development of photocatalytic materials aimed at controlling MRSA and other drug-resistant bacteria. Full article

Inflammatory bowel disease (IBD) poses a significant global health burden with rising incidence, particularly in Asia. This study employed an integrative network pharmacology approach combined with molecular docking to elucidate the therapeutic mechanism of ganoderic acid A (GAA) against IBD. Potential GAA targets were retrieved from pharmacogenomic databases, while IBD-related genes were curated from OMIM and GeneCards databases. Weighted gene co-expression network analysis of IBD transcriptomic datasets (GSE38713, GSE126124) identified disease-associated modules, with the yellow module exhibiting the strongest positive correlation. Functional enrichment analyses demonstrated significant involvement of overlapping targets in lipid metabolism, the inflammatory response, and the mitogen-activated protein kinase (MAPK) signaling cascade pathway. We identified 14 IBD-GAA-ferroptosis-related genes and 54 key module genes. Intersection analysis revealed 5 overlapping targets, including tumor necrosis factor-α(TNF-α), peroxisome proliferators-activated receptor γ (PPARγ), MAPK14, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic α (PIK3CA), and Caspase 3 (CASP3). Molecular docking confirmed high-affinity binding of GAA to these targets, with binding energies ranging from −7.3 to −10 kcal/mol. Crucially, experimental evaluation demonstrated the pivotal role of GAA in alleviating disease pathology. GAA treatment suppressed the significantly elevated levels of TNF-α and p-MAPK14 in the organoids using a cytokine/LPS-induced IBD model. These findings collectively suggest a potential involvement of GAA in pathways associated with ferroptosis regulation, although direct experimental evidence for ferroptosis markers remains to be established. The observed multi-target effects on immune regulation and cellular proliferation/differentiation provide a foundation for further mechanistic investigation. Full article

Anxiety disorders pose an increasing challenge to the mental health of individuals, particularly in regions with limited healthcare access. This study investigated the potential of integrating a brain–computer interface for processing electroencephalography (EEG) data with deep learning models to accurately classify anxious and non-anxious states. In the first phase, a convolutional neural network (CNN) was developed and validated on the public GAMEEMO dataset, achieving a classification accuracy of 95.72%. In the second phase, we conducted a separate experimental validation with seven participants (aged 18–60 years) using a within-subjects design. The protocol comprised a custom Stroop test to elicit acute cognitive stress and anxiety-related arousal, followed by a guided 4–7–8 breathing exercise to induce relaxation. EEG data from this experiment were used to classify anxious versus non-anxious states with the same CNN architecture after domain adaptation. On this self-collected dataset, the CNN achieved an accuracy of 86.58%. These results demonstrate proof-of-concept transferability while highlighting the performance gap between controlled benchmark data and real-world, small-sample recordings. The deep learning model can subsequently be coupled with neurofeedback techniques to manage anxiety levels. Overall, the findings support the potential of the developed automated system for detecting stress-induced anxious states, with possible future integration into neurofeedback-based management systems. Full article

The increasing interest in plant-based diets has driven the demand for sustainable legumes such as lupins. However, their broader utilization is limited by the presence of quinolizidine alkaloids (QAs), secondary metabolites toxic to human health. Despite severe health risks, European legislation lacks harmonized maximum levels, necessitating comprehensive market surveillance. This study evaluates the occurrence of 14 specific QAs across 28 commercial samples collected from the Italian market using a validated LC-MS/MS method. Concurrently, the impact of a laboratory-scale debittering process was examined on a subset of eight dried seed samples to monitor toxin reduction efficiency. The total alkaloid content exhibited significant variability across food categories. Dried lupins samples showed the highest concentration (mean: 13,676 mg/kg), whereas lower levels were detected in lupin flours (mean: 253 mg/kg), brined lupins (mean: 86.1 mg/kg), and ready-to-use products (mean: 70.3 mg/kg), with lupanine being the predominant alkaloid across most matrices. Data on finished lupin-based products confirm the efficacy of industrial processing techniques in significantly reducing the alkaloid content. In parallel, laboratory debittering process demonstrated high QA reduction efficiency, ranging between 94% and 99%. Nevertheless, if initial QA levels were high, most of the debittered lupin seeds still retained residual alkaloid levels exceeding commonly accepted safety thresholds. This highlights the importance of establishing harmonized regulatory limits within the European Union and implementing continuous analytical monitoring programs, both at the field level and on commercial products, to guarantee consumer safety. Full article