The need to improve predictive analytics in healthcare demands strong frameworks that would be able to interpret the complicated physiological signals well. In this study, the researcher presents a complex multi-modal emotion recognition architecture of mental health care based on EEG, ECG, and GS Rrecordings with aGPT-based NLP interface to understand brief clinical text input and self-reported emotional responses. The framework com bines sophisticated preprocessing and synchronization can be performed using cross-correlation, noise reduction using discrete wavelet transform, and event segmentation then feature extraction can be done using wavelet scattering transform and statistics. The dimensionality reduction is through two-dimensional bidirectional principal component collaborative projection as well as the use of canonical correlation analysis to make sure that fusion of features is effective. According to the experimental assessment, provision of contextual embeddings produced by GPT results in a better interpretability score and contributes to clinical reasoning, which in turn improves the healthcare decision-making. Optimized WOA-KELM model performs significantly better than the traditional classifiers like SVM, k-NN, and XGBoost as well as the standard KELM with high valence and arousal classification rates of 96.93 and 99.05 respectively. Valence and arousal are treated as binary classification tasks for emotion recognition. The GPT module is used only for post-classification interpretation and does not influence the classification performance. Also, the GPT component demonstrates the possibilities of optimized, multi-model solutions to facilitate predictive healthcare analytics meaningfully and provide credible applications in emotion-aware diagnostics, mental health monitoring, adaptive human-computer interaction, and future ways of providing real-time and personalized healthcare solutions.

Problematic internet use (PIU) and problematic social-media use have been associated with depressive symptoms and suicidal behaviors among university students, with limited Mediterranean evidence. This study examined their associations with stressful life events, depressive symptoms, and suicidal behaviors.

A cross-sectional anonymous online survey conducted among undergraduates at the Cyprus University of Technology. Participants completed Internet Addiction Test-20 (IAT-20) to assess PIU risk, Bergen Social Media Addiction Scale (BSMAS) to assess problematic social-media use, Center for Epidemiologic Studies Depression Scale (CES-D) to assess depressive symptoms, Life Events Scale for Students (LESS-36) to assess stressful life events, and Suicidal Behaviors Questionnaire-Revised (SBQ-R) to assess suicidal behaviors. Correlation and multivariable linear regression analyses examined associations with depressive symptoms and suicidal behaviors.

1002 students completed the survey (45% response rate); 67.7% were female. PIU risk was minimal (51.1%), mild (38.6%), and moderate (10.3%). BSMAS and LESS-36 scores correlated with depressive symptoms (ρ = 0.47; ρ = 0.30) and suicidal behaviors (ρ = 0.24; ρ = 0.31; all p < 0.001). Adjusted analyses showed depressive symptoms were associated with female gender, mild-moderate PIU, problematic social-media use, and stressful life events. Suicidal behaviors were associated with male gender, non-Cypriot nationality, family history of mental illness, screen time, mild-moderate PIU, stressful life events, and depressive symptoms.

Problematic internet and social-media use and stressful life events were associated with depressive symptoms and suicidal behaviors; longitudinal research is needed to clarify temporal relationships.

Traumatic events produce enduring memories that may be attenuated through extinction learning. Previous work has identified neuronal mechanisms underlying extinction learning that involve the remodeling or inhibition of neuronal ensembles (or engrams) that support the original fear memory. Here we identify a role for microglia in extinction learning in mice. We show that, during extinction, microglia are recruited to the soma and dendritic processes of fear engram neurons in the dentate gyrus. Interactions between microglia and somata mediate transient silencing of engram neurons. Inhibition of microglial recruitment to somata attenuated extinction-induced reductions in engram reactivity and slowed extinction. By contrast, interactions between microglia and dendritic processes promote engulfment of engram synapses and remodeling of engram neurons. Blocking complement signaling in engram neurons prevented extinction-induced engram neuron remodeling and slowed extinction. Together, these findings identify microglia as key regulators of fear engram expression and remodeling during extinction learning.

This study provides prevalence estimates of gaming disorder (GD) risk among Polish adolescents and validates a Polish translation of the Gaming Motivation Inventory (GMI). Moreover, it explores the role of introjected regulation in GD using a comprehensive motivational model. A representative sample of 1060 adolescents (930 gamers) completed measures of GD symptoms, gaming motivation, and involvement. GD risk ranged from 7.7% to 10.8%, higher among boys (8.9%-12.2%) than girls (6.5%-7.5%). The Polish GMI demonstrated strong psychometric properties, supporting its use in assessing gaming motivations among Polish adolescents. Introjected regulation, escape and identity were among the motivations most strongly associated with GD symptoms, with introjected regulation emerging as the strongest predictor.

Local policy makers increasingly have implemented nutrition standards for municipal programs to advance population health and climate change goals. Yet little is known about the impact of these policies. In 2008, New York City established nutrition standards for food purchased and served by city agencies, and in 2022, it revised the standards to limit meat and increase plant-based options. Using menu data from four agencies serving 77 percent of all city meals, we examined changes in their entrée offerings, as well as greenhouse gas and nutrition content associated with their total menu offerings, from fiscal year 2019 through fiscal year 2024. All agencies reduced the frequency of beef entrées offered on menus and increased the frequency of vegetarian entrées. Changes in total menu offerings were associated with an estimated reduction of 0.64 kilograms of carbon dioxide equivalent in greenhouse gas emissions per portion across all agencies and programs, while the nutrition content generally remained consistent. These findings suggest that municipal food standards can support greenhouse gas reductions without compromising nutrition, and they offer a model for other jurisdictions seeking to advance both population and environmental health goals.

Tobacco endgame strategies aim to reduce smoking prevalence to minimal levels (<5%) through measures that expand traditional tobacco control approaches. Although some countries have set endgame targets, most still report prevalence rates >15%, and practical guidance on how to assess readiness for endgame implementation remains limited. This study aims to synthetise the key determinants of jurisdictions' readiness for tobacco endgame and proposes a self-assessment tool to evaluate it.

A narrative review of peer-reviewed and grey literature published between January 2010 and September 2025 was conducted. Publications were identified through targeted searches of academic databases and relevant organisational websites. A thematic synthesis of evidence on political, social and structural determinants of readiness was undertaken to identify recurring domains, which were later used to inform the development of a self-assessment tool.

Nine readiness domains were identified: relatively low smoking prevalence; advanced implementation of WHO Framework Convention on Tobacco Control measures; robust enforcement infrastructure; social denormalisation of smoking; broad public understanding and support for ending tobacco use; a positive political climate and strong political will and leadership; a cohesive tobacco control community and civil society; minimal tobacco industry interference with strong protective mechanisms; and sufficient resources to implement tobacco endgame action plan. These domains guided the development of an evidence-informed self-assessment tool to help jurisdictions evaluate readiness, identify gaps and prioritise strategic actions.

The Assessment of Readiness for Tobacco Endgame tool offers an evidence-informed framework to assess tobacco endgame readiness, helping jurisdictions assess capacities, identify gaps and guide strategic decision-making.

Stigmatizing attitudes toward individuals with mental disorders represent a major barrier to treatment, recovery, and social inclusion. The present research introduces and psychometrically evaluates the German-language Stigma Toward People with Mental Disorders scale (SToP-MD) across three independent studies with distinct samples.In study 1 (N = 266), an initial item pool was developed and refined based on theoretical frameworks and exploratory factor analysis. In study 2 (N = 448), confirmatory factor analysis supported a two-factor structure comprising prejudiced stigmatization (SToP-MD-PS) and assumption of problems (SToP-MD-AP). The model demonstrated adequate fit according to conventional indices (CFI = 0.97, TLI = 0.96, SRMR = 0.07), although robust indices indicated only moderate fit (robust CFI = 0.91, robust RMSEA = 0.13). Internal consistency was good for the PS subscale (ω = 0.83) but limited for the AP subscale (ω = 0.51). In study 3 (N = 266), the scale's sensitivity to short-term change was examined following exposure to differently framed media content.As hypothesized, the SToP-MD subscales were positively associated with depression stigma (DSS) and social distance (SDI), and negatively correlated with openness and agreeableness (NEO-FFI), supporting convergent validity. Discriminant validity was partially confirmed by low or non-significant correlations with attitudes toward physically disabled individuals (ATDP), suicide-related cognitions (CCSS), and socially desirable responding (BIDR).Across all three studies, the SToP-MD demonstrated preliminary yet consistent evidence of structural and construct validity, as well as change sensitivity. It captures both overt prejudices and implicit burden assumptions, offering a nuanced assessment of public stigma toward mental disorders. The scale can serve as a valuable tool in stigma research, public health monitoring, and evaluation of interventions. Future research should extend validation to more diverse samples and test predictive and longitudinal utility.

Corneal endothelial dysfunction is a major cause of global blindness, with an estimated 12.7 million patients awaiting corneal transplantation, and the severe shortage of donor grafts underscores the urgent need for non-surgical therapies. Gene therapy offers a promising alternative, but is hindered by the limitations in existing delivery systems and the scarcity of validated molecular targets capable of reversing core pathophysiology. To address this, we first employed multi-omics analysis and identified FOXO1 as a central and under-explored therapeutic target for corneal endothelial dysfunction. In vivo FOXO1 overexpression effectively improved corneal endothelial function by preserving mitochondria-associated endoplasmic reticulum membrane integrity and mitochondrial Ca^{2 +} homeostasis, yet its therapeutic potential was limited by low transfection efficiency. To overcome this, we engineered an AAV-Foxo1 delivery system using a viscous choline chloride-fructose-based deep eutectic solvent (DES) as the carrier. The DES-AAV-Foxo1 delivery system exhibited good biocompatibility, significantly prolonged anterior chamber retention, and enhanced transfection efficiency in corneal endothelial cells compared to conventional AAV delivery. Animal experiments confirmed that it effectively improved corneal endothelial pump activity and mitigates endothelial dysfunction in type 1 diabetes mellitus and Fuchs endothelial corneal dystrophy mouse models. Our findings demonstrated the therapeutic potential of DES-AAV-Foxo1 delivery system for corneal endothelial disorders.

To synthesize and evaluate current evidence on the responsiveness, interpretability (MID/MIC), and clinical utility of validated health-related quality of life (HRQoL) patient-reported outcome (PRO) instruments used in adults with head and neck cancer (HNC).

A systematic search of PubMed, Scopus, Web of Science, Embase, and Cochrane Library (Central) identified studies published from January 2015 to July 2025. The review was registered in PROSPERO (CRD420251128978) and followed PRISMA 2020 guidelines. Observational and interventional studies assessing HRQoL using validated HNC instruments (EORTC QLQ-C30, QLQ-H&N35/H&N43, UW-QOL, FACT-H&N or MDADI) were included. Eligible studies reported responsiveness (ability to detect meaningful change) or clinical applicability. Methodological quality was evaluated using the COSMIN Risk of Bias checklist, and results were narratively synthesized due to methodological heterogeneity.

Thirteen studies involving 8,075 patients met the inclusion criteria. The EORTC QLQ-C30 and H&N35/43, UW-QOL, FACT-H&N, and MDADI exhibited consistent responsiveness, capturing expected HRQoL deterioration during treatment and partial recovery within 6-12 months. Reported minimal important difference (MID) and minimal important change (MIC) values typically ranged from 4 to 15 points for improvement and 10-20 points for deterioration, supporting the interpretability of change scores. Several patient-reported outcome measures (PROMs) also demonstrated prognostic relevance, with early HRQoL changes associated with survival or recurrence.

Validated HRQoL questionnaires in HNC demonstrate robust responsiveness and meaningful clinical applicability, supporting their integration into routine oncology practice. Their use may enhance early detection of complications, guide rehabilitative interventions, and facilitate more individualized, patient-centered care.

This study aimed to identify subgroups of health-related quality of life (HRQoL) and examine predictors of latent class membership among low- and high-income cancer survivors using latent class analysis (LCA).

We analyzed data from the Korea National Health and Nutrition Examination Survey (2013-2020), including 1075 cancer survivors. HRQoL patterns were identified using LCA based on the EuroQol five-dimension questionnaire. Analyses were conducted separately for low- and high-income groups to examine income-stratified HRQoL patterns. Sociodemographic characteristics and chronic disease status were included as covariates in the latent class models to examine predictors of class membership within each income group.

Income-stratified LCAs suggested differential HRQoL patterns. Three latent HRQoL classes were identified in the low-income group: Good HRQoL, Pain and Mobility Impairment, and Poor HRQoL. In the high-income group, two classes were identified: Good HRQoL and Pain and Mobility Impairment. While education was a common predictor in both groups, other predictors varied by income level. In the low-income group, older age, unemployment, and multimorbidity were significantly associated with impaired HRQoL classes, whereas female sex predicted membership in the Pain and Mobility Impairment class in the high-income group.

These findings highlight differences in HRQoL patterns and associated factors across income-stratified groups of cancer survivors, underscoring the limitations of relying solely on average HRQoL scores in survivorship care. Survivorship strategies should be tailored to the differential HRQoL patterns and associated predictors identified within each income group, thereby promoting more targeted and equitable care for cancer survivors.