The overlapping symptoms between bipolar disorder (BD) and major depressive disorder (MDD) pose a challenge in diagnosis and treatment. A prevailing hypothesis suggests that mood dysregulation may be linked to impairments in the reward system, but the neurocomputational differences between BD and MDD remain elusive. This study investigates whether atypical reward processing affects subjective mood in adolescents with BD and MDD. Our research aims to elucidate the behavioral and neural differences between the two groups, facilitating more accurate and timely diagnosis and intervention.

Forty-five adolescents (aged ≤ 19 years) diagnosed with BD-II in depressed mood states (N = 25) or MDD (N = 20) completed a risky gambling task while their brain responses were recorded using functional magnetic resonance imaging (fMRI). Several computational models were constructed to uncover the associations between various reward components (e.g. reward prediction errors, RPE) and trial-wise fluctuations in subjective mood during the task.

Adolescents with BD exhibited a lower best choice rate and a higher uncertain choice rate compared to those with MDD. Computational modeling and mediation analysis suggested a tripartite mediating relationship between RPE-mood association, decision rationality, and symptom severity. Using fMRI, we observed significant RPE-related activation in the ventral striatum, which showed a slight positive correlation with the RPE-mood association. We also noted subtle differences in several brain regions (i.e. medial orbitofrontal cortex) between the BD and MDD groups. These differences were further associated with manic symptoms.

Decision rationality mediated the association between RPE-mood association and symptom severity. Relative to adolescents with MDD, those with BD showed decreased decision rationality, along with modest but distinct reward-related neural patterns on fMRI. These findings highlight the crucial role of reward processing in mood regulation and provide preliminary neurocomputational evidence that may inform future diagnostic biomarker development.

Little research has elucidated the effects of maternal autistic traits (MATs) on children's anxiety in normal populations, and their underlying mechanisms. The present study aimed to test this relationship and the mediating role of maternal negative meta-emotional philosophy (MEP) and children's emotional instability among Chinese people.

This study recruited 590 mother-child dyads. These mothers have no other children with autism, and they completed the Autism Spectrum Quotient, Maternal Meta-Emotion Philosophy, Emotion Regulation Checklists, and the Chinese version of the Spence Children's Anxiety Scale. The chain mediation model was tested using SPSS software.

(1) There are significantly positive correlations among MATs and children's anxiety. (2) Children's anxiety was affected by MATs through 3 different pathways: the mediating role of maternal MEP (dysfunction and noninvolvement emotional philosophy), the mediating role of children's emotional lability, and the chain mediating role of both MEP and children's emotional lability.

This cross-sectional study demonstrates that MATs predict child anxiety through the sequential mediation of mothers' negative MEP and children's emotional instability. These findings deepen our understanding of the adverse effects of subclinical autistic traits within the general population. Furthermore, they suggest that early interventions for families with mothers exhibiting high autistic traits should focus not solely on the traits themselves, but on improving maternal MEP. Such a focus would help children develop adaptive emotion regulation strategies, thereby reducing the risk of anxiety. A primary limitation of this study is its cross-sectional design, which precludes causal inferences. Future longitudinal research is needed to clarify the temporal dynamics and long-term effects among these variables.

Background/Objectives: Wildfires are increasing in frequency and intensity worldwide, leading to widespread exposure to wildfire smoke and associated environmental stressors. While the respiratory and cardiovascular effects of wildfire smoke are well established, the potential neurological and mental health consequences have received growing attention. This narrative review synthesizes evidence from animal and human studies examining the effects of wildfire exposure on neurological function, behavior, and mental health, and explores the potential role of epigenetic mechanisms. Methods: A structured literature search was conducted using PubMed to identify original research articles examining wildfire exposure in relation to neurological, behavioral, mental health, or epigenetic outcomes. Both human and animal studies were included. Results: Experimental animal studies suggest that wildfire smoke exposure can induce neuroinflammation, blood-brain barrier disruption, metabolic alterations, and behavioral changes. Human studies conducted in wildfire-affected populations frequently report an elevated prevalence of depression, anxiety, post-traumatic stress disorder (PTSD), and sleep disturbances. However, many of these studies reflect mental health outcomes associated with wildfire disaster exposure, including evacuation and psychosocial stress, whereas only a subset of studies quantify wildfire smoke or PM_2.5 exposure. Emerging evidence from both animal models and human studies indicates that wildfire exposure may be associated with changes in epigenetic regulation, including alterations in DNA methylation and miRNA expression. Conclusions: Current evidence suggests that wildfire exposure may influence neurological and mental health outcomes through biological and psychosocial pathways. However, the literature remains heterogeneous, and the independent effects of wildfire smoke exposure are often difficult to disentangle from disaster-related stressors. In addition, human evidence linking wildfire exposure to epigenetic changes remains limited, restricting causal inference. Further longitudinal and mechanistic studies integrating exposure assessment, neurological outcomes, and molecular profiling are needed to clarify these relationships.

Background/Objectives: Food insecurity affects college students at nearly twice the rate of US households, with documented impacts on student academic performance, physical and mental health, and socialization. While frameworks exist to conceptualize general food insecurity and food insecurity in specific contexts, researchers and practitioners lack resources to guide system-level responses to food insecurity on college and university campuses and assess those responses. In this study, we aimed to develop and validate a simple yet comprehensive framework for assessing food insecurity responses within the context of higher education. Methods: We adapted an eight-phase process for framework development: (1) map selected data sources within the multidisciplinary literature, (2) read and categorize selected sources, (3) identify and name concepts, (4) deconstruct and categorize concepts based on their features, (5) group similar concepts together, (6) synthesize concepts into a framework, (7) validate the framework using expert panel review, and (8) revise as necessary. Results: The developed Campus Food Aid Self-assessment (CFAS) framework consists of six dimensions: Student Services and Supports; Involvement; Advocacy; Awareness and Culture Efforts; Education and Training; and Research, Scholarship, and Creative Works. Expert panelists (n = 7) reviewed the proposed framework and confirmed the clarity, comprehensiveness, and representativeness of the proposed dimensions, conceptual definitions, and operational variables. Conclusions: With a comprehensive yet accessible structure, the CFAS framework supports the development, coordination, and improvement of campus-based strategies to address food insecurity and support positive student outcomes.

Low-value care (LVC) research originates predominantly from Western healthcare systems. This narrative review offers the first synthesis of LVC patterns, determinants and reduction initiatives across six diverse Asian countries (Japan, Singapore, South Korea, China, Malaysia and India), comparing them with Western models to inform context-specific de-implementation strategies and identify key priorities for further research.

This is a narrative review of 132 English and non-English literature (2000-2025) from academic databases, grey literature, and policy documents across the six countries that was analysed using a novel framework examining LVC landscapes (healthcare challenges and measurement), determinants (structural, organisational, clinician, patient) and reduction initiatives.

Asian systems mirror Western pressures from demographic shifts, escalating costs and a growing burden of non-communicable diseases, underscoring the urgency of reducing LVC. Despite this, systematic measurement of LVC in Asia remains limited. Common LVC determinants include fee-for-service incentives, medicolegal concerns and a 'more is better' cultural perception, though further research, particularly on cross-country comparisons and from the patient's perspective, is needed. LVC reduction initiatives are still emerging in Asia, with existing approaches shaped by local cultural norms and resource constraints, suggesting that Western strategies provide valuable insights but require adaptation for successful local de-implementation.

This multicountry review establishes a foundation for further collaborative LVC research in Asia via a holistic framework linking country-specific contexts to tailor de-implementation strategies. Key priorities for LVC research in Asia include systematic LVC quantification, development of contextualised evidence-based recommendations and implementation of contextualised multicomponent interventions, supported by further research and regional collaboration.

Socio-economic and demographic variables have been identified as determinants of transmission of, and susceptibility to, COVID-19. In this study, we analyse the heterogeneous impacts of non-pharmaceutical interventions on the socio-economic and demographic (SED) variables driving COVID-19 incidence in Toronto during the 2nd, 3rd and 4th waves of the pandemic. Spatial autoregressive models were used to explore associations between COVID-19 incidence and SED variables at neighborhood scale, accounting for vaccination levels. This approach helps clarify how SED factors and vaccine coverage drive COVID-19 incidence and how non-pharmaceutical interventions (NPIs) modulate these factors at neighborhoods' level, while taking into account the pervious nature of boundaries at these scales to disease transmission due to population mobility, although without directly informing on behaviours, exposure, or vulnerability at individual level. Three distinct models were considered for each of the second, third and fourth COVID-19 waves, from late 2020 to late 2021. Associations highlighted by the models were interpreted with reference to the NPIs implemented. Level of scholarity, income, proportion of the population living alone, average number of children in families, and the proportion of the population whose mother tongue is not an official language showed significant relationships with COVID-19 incidence. Model results were different for each wave, reflecting the unequal impacts of NPIs at different time points, and for different population groups, depending on the nature of interventions and the SED determinants considered. Prioritization of population groups for testing, unequal gathering restrictions, selective closure of economic activities or work-from-home policies led to heterogenous impacts on incidence. The results highlight the unequal burden of the pandemic across populations and likely disparities in occupational exposure driven by SED factors, as well as their evolution with the implementation and lifting of NPIs. Populations with the lowest income and scholarity cumulate the highest risks of exposure and the highest risks of severe disease outcomes. Our results support the development of knowledge based public health surveillance programs integrating both non-communicable and infectious diseases cases, beyond their acute occurrences, along with their socio-economic characteristics.

Urolithiasis, a prevalent urological disorder, is associated with significant morbidity and economic burden. Despite the Global Burden of Disease (GBD) data, regional specificity for urolithiasis burden in North Africa and Middle East (NAME) remains limited. This study aims to fill this gap by analyzing the burden of urolithiasis in the NAME region from 1990 to 2021.

Data from the GBD 2021 study were used to evaluate key health measures, including incidence, prevalence, mortality, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life years (DALYs). Age-standardized rates (ASRs) and absolute numbers were assessed across 21 NAME countries, stratified by sex, age, and sociodemographic index (SDI). Results were presented with 95% uncertainty intervals.

In 2021, the overall incidence reached 5.3 million (95% uncertainty intervals: 4.2-6.8) cases, compared to 2.0 million (1.6-2.5) in 1990. Prevalence rose from about 76,000 (61,000-96,000) cases in 1990-201,000 (160,000-257,000) in 2021. The number of deaths increased considerably from 142.1 (79.8-194.5) to 394.2 (182.4-509.5), and the DALYs rose from 10,814.0 (7,970.0-13,932.3) to 25,213.3 (17,943.5-33,787.7) from 1990 to 2021. ASRs for all burden measures remained stable and females consistently exhibited lower rates compared to males. There was a positive correlation between SDI and rates of incidence, prevalence, and YLDs; however, deaths, YLLs, and DALYs exhibited no significant correlation with SDI.

Urolithiasis imposes a growing health and economic burden in the NAME region, particularly among middle-aged populations and high-SDI countries. Targeted interventions and region-specific policies are crucial to address the rising disease burden effectively.

Given the high prevalence of type 2 diabetes and its significant renal complications, which can ultimately lead to renal failure and require patients to undergo hemodialysis, this study was designed and conducted to examine the association between health literacy and hemodialysis in diabetic patients. This case-control study examined 291 patients: 97 were diabetic hemodialysis patients, and 194 were non-hemodialysis diabetic patients. Data were collected using a standard adult health literacy questionnaire. Additionally, a 19-item demographic questionnaire was used to collect information on the patients' personal characteristics. Independent t-tests and analyses of variance at the 95% level of statistical significance were used to compare mean health literacy scores based on demographic variables. A multivariable logistic regression model at a 5% significance level was used to determine the relationship between health literacy scores and factors associated with type 2 diabetes requiring hemodialysis. All analyses were performed using Stata 17 statistical software. The mean age of the patients in this study was 62.3 ± 9.72 years. Health literacy had an inverse association with hemodialysis outcomes for diabetic patients, and for each unit increase in health literacy score, the odds of hemodialysis for diabetic patients (HFDP) decreased by 15% (OR = 0.85, 95% CI: 0.82, 0.88, P-value < 0.01).Income level also had an inverse association with hemodialysis outcomes in diabetic patients; those with middle socioeconomic status had 77% lower odds of requiring hemodialysis compared to those from low socioeconomic backgrounds (odds ratio: 0.23, 95% CI: 0.09, 0.56, p = 0.001). Physical activity was also inversely associated with hemodialysis outcomes, i.e. as weekly physical activity increased, the odds of HFDP decreased by 23%. (Odds Ratio: 0.77, 95% CI: 0.64, 0.94, p = 0.011). The results indicated that health literacy, income level, and physical activity are inversely associated with hemodialysis dependence. In addition, underlying health conditions are a contributing factor to the increased likelihood of diabetic patients requiring hemodialysis.

To assess the efficacy and safety of T cell-targeted immunotherapy in patients with newly diagnosed type 1 diabetes (T1D).

A comprehensive search of PubMed, Embase, CENTRAL, Web of Science, Scopus and ClinicalTrials.gov up to 6 March 2026 was performed. Randomised controlled trials comparing T cell-targeted immunotherapeutic agents with placebo in patients with newly diagnosed T1D were included. The primary outcome was change in the area under the curve (AUC) of C-peptide, whereas the secondary outcomes included change in glycated haemoglobin (HbA1c) levels, change in daily insulin dose, and adverse events.

Twenty-one trials involving 1970 participants were included in this study. Compared with the control treatment, T cell-targeted immunotherapy significantly increased the C-peptide AUC, with SMDs of 0.38 (95% CI: 0.19-0.57; p < 0.001) at 6 months, 0.41 (95% CI: 0.12-0.69; p = 0.005) at 12 months, 0.48 (95% CI: 0.32-0.65; p < 0.001) at 18 months, and 0.49 (95% CI: 0.32-0.65; p < 0.001) at 24 months. Consistently, this therapy also reduced HbA1c levels and daily insulin dose at all time points (all p < 0.05). Subgroups with younger age (< 18 years), worse baseline metabolic status, and single-blind or open-label design showed greater efficacy in the early phase of therapy. The risks of total and serious adverse events were comparable between the intervention and control groups.

T cell-targeted immunotherapy provides sustained preservation of β-cell function and improvements in HbA1c levels and insulin requirements for at least 24 months in patients with newly diagnosed T1D.