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PubMed2026

Polygenic risk scores in major depressive disorder: A systematic review across diagnostic, treatment, course/severity, and subtype domains.

BACKGROUND: Major depressive disorder (MDD) is heterogeneous across diagnostic, treatment-related, course/severity, and subtype domains. Polygenic risk score (PRS) studies have examined these domains, but differences in PRS sources, samples, methods, and endpoint definitions have fragmented the evidence. We synthesised findings and examined potential contributors to heterogeneity. METHODS: PubMed/MEDLINE, Embase, PsycINFO, and Web of Science were searched for studies published from January 2016 through 25 November 2025. Result records were synthesised using SWiM, and certainty was assessed with an adapted GRADE framework. RESULTS: Sixty studies contributed 493 retained records; 450 were descriptively classified as positive, null, or reverse, although records were not independent. Positive findings accounted for 44/56 diagnostic, 61/273 treatment-related, 64/100 course/severity, and 14/21 subtype records. For MDD/depression-derived PRSs and case-control MDD status, all 10 contributing studies showed higher liability in cases (exploratory exact sign test p = 0.002; FDR q = 0.004). The same PRS group showed positive findings for overall depressive symptom severity (14/18), although the study-level test was imprecise (5/5 studies; p = 0.063). Pharmacological response/remission findings for these PRSs were mostly null or directionally mixed (10 positive, 18 null, and 9 reverse). Treatment-resistant depression (TRD) findings differed by operational definition. Atypical and psychotic subtype signals arose mainly from single-study PRS and endpoint contrasts. CONCLUSIONS: PRS evidence was clearest for MDD diagnostic status and showed a tentative pattern for overall symptom burden. Treatment and subtype findings were less consistent or less replicated. Larger, ancestrally diverse studies with standardised endpoints and transparent PRS methods are needed.

Humans↗

PubMed2026

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans↗

PubMed2026

Atopic dermatitis and the risk of osteoporosis and fractures: a meta-analysis of cohort studies.

BACKGROUND: This meta-analysis aims to evaluate the risk of osteoporosis and fractures in patients with atopic dermatitis (AD) by synthesizing data from cohort studies. We also provide a comprehensive analysis of fracture risks across different severities of AD and anatomical sites. METHODS: Following the PRISMA 2020 guidelines, a systematic search was conducted in PubMed, Embase, and the Cochrane Library up to May 30, 2025. Studies that investigated the relationship between AD and osteoporosis or fractures were included in the analysis. Data extraction and screening were performed independently by two reviewers. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was applied, alongside sensitivity and subgroup analyses. Publication bias was evaluated using funnel plots and Egger's test. RESULTS: Ten cohort studies, involving 368 to over 2 million AD patients, were included. NOS scores ranged from 7 to 8, indicating generally high study quality. The pooled analysis revealed a 56% increased risk of osteoporosis (OR = 1.56, 95% CI: 1.14-2.13; I2 = 99.9%, p < 0.0001) and an 8% increased risk of all-cause fractures (OR = 1.08, 95% CI: 1.05-1.10; I2 = 82.1%, p < 0.0001) in AD patients. Subgroup analyses demonstrated a progressive increase in fracture risk with the severity of AD. Specific risks were significantly higher for vertebral fractures (OR = 1.14, 95% CI: 1.08-1.20; I2 = 67.3%, p = 0.009) and lower limb fractures (OR = 1.11, 95% CI: 1.08-1.13; I2 = 65.0%, p = 0.014). Sensitivity analyses confirmed the robustness of these findings, and no significant publication bias was detected (p = 0.316). CONCLUSION: AD is associated with an increased risk of osteoporosis and fractures, particularly among patients with severe AD and those experiencing vertebral or lower limb fractures. These findings highlight the importance of targeted bone health monitoring in the clinical management of AD patients.Registration: (PROSPERO: CRD420251066550).

Humans↗

PubMed2026

Suicidality risk of cancer caregivers: a systematic review and meta-analysis of observational studies.

BACKGROUND: The increase in the number of global cancer cases is expected to lead to a greater caregiving burden. However, few studies have investigated the risk of suicidality among cancer caregivers. OBJECTIVE: The aim of this systematic review was to explore the risk of suicidality among cancer caregivers. METHODS: For this systematic review, a comprehensive search of the PubMed, Embase, Cochrane, Web of Science databases, PsycINFO and Scopus databases was conducted from inception to 16 July 2025. A meta-analysis was performed to determine the odds ratios (ORs) for case-control and cross-sectional studies and the adjusted hazard ratios (aHRs) for cohort studies. RESULTS: Seven studies were included (four cohort studies, one case-control study and two cross-sectional studies), and 638,188 study subjects and 4,203,957 nonexposed subjects. The meta-analyses revealed that the ORs was 1.91 (95% confidence interval [CI]: 1.46-2.49) in the case-control study, cross-sectional studies, and one cohort study which reported ORs, and the aHRs was 1.32 (95% CI: 1.16-1.50) in the three cohort studies. Caregivers of patients with highly aggressive cancers had a greater risk of suicidality (aHR = 1.66; 95% CI: 1.48-1.86). Within the first 7 years following a patient's cancer diagnosis, the risk of suicidality among caregivers remained elevated (aHR = 1.42; 95% CI: 1.04-1.94). CONCLUSION: The results indicate the need for both clinical and societal awareness to reduce the risk of suicidality among cancer caregivers, especially those with highly aggressive cancers. TRIAL REGISTRATION: Registered prospectively in PROSPERO (https://www.crd.york.ac.uk/prospero/) with the registration number (PROSPERO CRD420251011926) and date of registration(15/03/2025).

Humans↗

PubMed2026

Microplastic contamination in South Asian commercially important seafood: A comprehensive assessment of occurrence, source, and human health risk.

Seafood is a cornerstone of global food security and human nutrition, serving as the primary source of animal protein for more than one-fourth of the global population, with South Asia representing one of the world's fastest-growing seafood-consuming regions. However, escalating microplastic (MP) pollution in marine ecosystems poses an emerging threat to seafood safety and human health, yet a comprehensive regional assessment of MP contamination in South Asian seafood remains lacking. This study presents the first region-wide systematic synthesis of the literature on MP contamination in commercially important seafood across South Asia, integrating occurrence patterns, human exposure assessment, polymer-specific hazard evaluation, and bibliometric analysis to address this critical knowledge gap. The meta-analysis estimated an average microplastic exposure of 145 particles/person/day through seafood consumption in South Asia, with fish contributing the highest intake (121 particles/person/day). The detected polymers were classified into PHI hazard levels I-IV, with polyvinyl chloride (PVC), polyurethane (PU), and polyacrylamide (PAM) representing the highest hazard categories. The mean pollution load index (PLI) was 7.71 (Category I), with crustaceans exhibiting the highest contamination (PLI = 10.07). Polypropylene was the predominant polymer, whereas fragments and blue particles were the most frequently reported microplastic characteristics. These findings provide the first regional baseline for assessing microplastic contamination, polymer-associated hazards, and human exposure through seafood consumption in South Asia, underscoring the need for standardized monitoring and targeted mitigation strategies to safeguard seafood safety and public health.

Animals↗

PubMed2026

Alcohol use disorder and childhood adversity in the association between polygenic risk and suicidality.

OBJECTIVE: Suicidal ideation (SI) and suicide attempt (SA) are both influenced by genetic, behavioral, and environmental factors. Alcohol use disorder (AUD) and adverse childhood experiences (ACEs) may mediate or moderate the effects of genetic liability for suicidality. METHODS: Using data from 10,275 participants (43.8% female; 47.2% African-like genetic ancestry [AFR], 52.8% European-like genetic ancestry [EUR]), we tested whether polygenic scores (PGS) for SI and SA predicted lifetime suicidality outcomes. We evaluated whether AUD partially accounted for these associations and ACEs moderated the direct and indirect associations. RESULTS: The SA PGS was significantly associated with SA (AFR: b = 0.36, SE = 0.01; EUR: b = 0.17, SE = 0.01; both ps < 2e-16), but the SI PGS was not associated with SI (p > 0.55). AUD statistically mediated the association between the SA PGS and SA, accounting for approximately 2% of the total association in AFR individuals and 10% in EUR individuals (both ps < 2e-16). Notably, the proportion of the association that was accounted for by AUD decreased as ACEs exposure increased, from 4.30% to 0.54% in AFR individuals and from 13.31% to 3.44% in EUR individuals. In contrast, there was only very modest mediation and no moderated mediation for SI. CONCLUSIONS: Particularly among individuals with lower ACEs exposure, AUD accounted for a meaningful proportion of the association between genetic liability to SA and lifetime SA. These findings highlight different correlates across suicidality phenotypes and suggest potential clinical relevance for AUD in the association between genetic liability and SA.

Adult↗

PubMed2026

Emerging hantavirus risks in mass gatherings: epidemiology, diagnostic challenges, and outbreak preparedness.

Hantaviruses are emerging rodent borne zoonotic pathogens of increasing global public health concern because of their high mortality, expanding ecological distribution, and potential for international dissemination. Although traditionally associated with sporadic rural outbreaks, recent ecological disruption, climate variability, urbanization, and increased global mobility have heightened concerns regarding hantavirus risks in mass gathering settings. This review critically examines the epidemiology, transmission uncertainty, diagnostic and surveillance challenges, and preparedness strategies related to hantavirus infections in the context of mass gatherings, including religious events, refugee settlements, cruise tourism, sporting events, and temporary accommodations. Particular emphasis is placed on the 2026 multinational cruise ship associated outbreak linked to the MV Hondius, which highlighted vulnerabilities related to delayed diagnosis, international passenger dispersal, and uncertainties surrounding possible human to human transmission of Andes virus. Current evidence indicates that hantavirus transmission occurs primarily through inhalation of aerosolized rodent excreta; however, controversies regarding limited interpersonal transmission, environmental persistence, and asymptomatic infections continue to complicate risk assessment and outbreak preparedness. Diagnostic limitations, underreporting, insufficient environmental surveillance, and lack of mass gathering specific preparedness frameworks remain major public health challenges, especially in resource limited settings. Strengthening proactive preparedness through integrated One Health approaches, ecological surveillance, genomic monitoring, AI driven epidemic intelligence, and coordinated international response systems is essential for mitigating future risks. The review emphasizes the urgent need for multidisciplinary research and evidence based policy development to improve global preparedness against emerging hantavirus associated threats in increasingly interconnected mass gathering environments.

Humans↗

PubMed2026

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30‑day all‑cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged ≥ 60 years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K‑Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P < 0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR = 9.752), smoking (OR = 5.171), AIP (OR = 6.691), TyG index (OR = 4.393), HALP score (OR = 2.831), and ≥ 2 comorbidities (OR = 3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC = 0.884, accuracy = 0.829, sensitivity = 0.812, specificity = 0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30‑day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans↗

PubMed2026

Microbial diversity, functional activities, and safety risks in fermented tea: a comprehensive review.

Microbial fermented teas are gaining global popularity due to their unique sensory profiles and health benefits. The quality and safety of these products are governed by complex microbial ecosystems that orchestrate the biotransformation of tea leaf components. This review addresses a critical paradox in the field: the same microbial activities that generate desirable bioactive metabolites, such as theabrownins and organic acids, also create ecological niches for mycotoxigenic fungi, posing significant health risks from contaminants like ochratoxin A, citrinin, and aflatoxins. While extensive research has cataloged the microbial diversity in these systems, a comprehensive framework linking processing environments to microbial community assembly, functional outcomes, and quantifiable safety risks remains elusive. This review systematically bridges this gap by synthesizing current knowledge on the microbial consortia-dominated by Aspergillus, Penicillium, Bacillus, and Lactiplantibacillus species-that drive tea fermentation. We critically analyze their functional roles in enhancing flavor, bioactivity, and potential probiotic activity while simultaneously evaluating the mechanisms of mycotoxin production and accumulation. By integrating microbial ecology, biochemistry, and food safety, we propose a forward-looking perspective focused on transitioning the industry from traditional, spontaneous fermentation to modern, controlled biotechnological processes. This approach, centered on the use of defined starter cultures, predictive modeling, and active biocontrol strategies, provides a roadmap for ensuring the consistent quality and safety of fermented tea products, ultimately unlocking their full potential as high-quality functional foods.

Tea↗

PubMed2026

Empagliflozin and functional aerobic capacity in individuals with increased risk of heart failure: The Empire Prevent Cardiac trial.

BACKGROUND: Higher maximal oxygen consumption (VO₂ max) is associated with lower risk of developing heart failure (HF). Empagliflozin improves VO2 max in HF with reduced ejection fraction, but the effect on VO2 max in individuals at risk of HF remain unknown. OBJECTIVE: This study aimed to evaluate the effect of 180 days treatment with empagliflozin compared to placebo on VO2 max, daily physical activity level, and quality of life (QoL) in individuals with overweight or obesity and risk of HF. METHOD: This investigator-initiated, double-blinded, randomized, placebo-controlled, multicenter trial included elderly individuals with body mass index >28 kg/m2 and at least one additional risk factor for HF, including hypertension, ischemic heart disease, stroke, or chronic kidney disease. Individuals with HF or type 2 diabetes mellitus were excluded. The primary endpoint was the mean difference in change of VO2 max. The secondary outcome was objectively measured physical activity level. QoL was an explorative outcome. RESULTS: Among 191 randomized individuals (94 empagliflozin, 97 placebo), 89% had hypertension and 66% ischemic heart disease. At baseline, 69% were male, median age was 68 years, median body mass index 31.9 kg/m², mean left ventricular ejection fraction 65 ± 9%, and mean VO₂ max 18.1 ± 4.3 mL/min/kg. Empagliflozin did not change VO2 max with an estimated treatment difference of -0.2 mL/min/kg (97.5% confidence interval -1.2 to 0.8), adjusted P = 1.00. No significant treatment differences were observed for neither daily physical activity nor QoL. CONCLUSIONS: Empagliflozin did not affect VO2 max, physical activity level, or QoL in elderly individuals with overweight or obesity and risk of HF.

Humans↗

PubMed2026

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans↗

PubMed2026

The effect of monetary versus point-based rewards on effort-cost decision making in individuals at clinical high risk for psychosis.

OBJECTIVE: The dissemination of inexpensive computerized behavioral tasks indexing amotivation may enhance the assessment of clinical high risk (CHR) across settings. However, the impact of varying reward value in such tasks is unclear. If point-based rewards engage participants, this could improve the scalability of computerized assessments. We tested how point-based rewards versus money impacted effort-cost decision-making in CHR individuals. We further assessed how negative symptom severity and household income interacted with reward-type to impact behavior. METHODS: Participants completed the Effort Expenditure for Reward Task (EEfRT). Participants were randomly assigned to receive either money or points for their performance during the EEfRT. Data from a large sample of CHR (N = 233) individuals and healthy controls (HC; N = 157) were collected. RESULTS: Across diagnostic groups, we observed heightened effort expenditure when money was used as a reward (b = 0.13, p = 0.018). We did not find an interaction of CHR status (b = 0.07, p = 0.845) or negative symptoms (b = 0.01, p = 0.429) with reward-type. Within CHR individuals, heightened negative symptom severity was associated with reduced expended effort (b = -0.03, p = 0.016), regardless of reward type. In an exploratory analysis, we found that individuals in the money condition with relatively high household income expended less effort during high reward, high probability trials (b = -0.24, p = 0.046). CONCLUSIONS: Across CHR and HC individuals, individuals pursuing money expended greater effort. While we did not find a group by reward type interaction, CHR individuals with heightened negative symptom severity expended less effort across trials, replicating prior work. Present findings support further study of point-based rewards in tasks indexing amotivation.

Humans↗

PubMed2026

Nasopharyngeal Carriage Rate, Risk Factors, and Co-Resistance Patterns of Methicillin-Resistant Staphylococcus aureus in Ethiopia: Systematic Review and Meta-Analysis.

Methicillin-resistant Staphylococcus aureus (MRSA) nasopharyngeal carriage is a major global health concern linked to severe infections and transmission. However, comprehensive evidence on the burden of MRSA carriage, antimicrobial resistance, and associated risk factors in Ethiopia remains limited. This study aimed to estimate pooled prevalence, resistance pattern, and determinants of nasopharyngeal MRSA carriage. PubMed, ScienceDirect, Scopus, Web of Science, Google Scholar, and gray literature were searched for cross-sectional studies published between January 2015 and December 2025. Two groups of reviewers screened studies based on predefined criteria. The risk of bias was assessed using the Joanna Briggs Institute tool. Pooled prevalence and resistance proportions were estimated using a random-effects model, and pooled odds ratios (ORs) were calculated using the Mantel-Haenszel method. Heterogeneity and publication bias were assessed, and a sensitivity analysis was conducted. A total of 1040 records were identified, and 20 studies (6869 participants) were included. The pooled carriage prevalence was 7.3% (95% CI, 5.0-10.8), with substantial heterogeneity (I2 = 95.5%). Resistance was highest to tetracycline (55.75%) and lowest to clindamycin (12.66%). Increased odds of carriage were associated with prior hospitalization (OR, 3.49) and antibiotic use (OR, 2.35). Inconsistent variable coding across included studies limited the inclusion of other potential risk factors. Evidence of publication bias was detected, suggesting that the pooled prevalence should be interpreted with appropriate caution. The findings indicate a considerable burden of MRSA and highlight the need for strengthened antimicrobial stewardship, improved surveillance, and targeted prevention efforts in higher-risk populations. This review was registered in PROSPERO (CRD420251047192).

Ethiopia↗

PubMed2026

Extreme Temperature and Incident Diabetes Risk Among Middle-Aged and Older Adults in China: A National Longitudinal Cohort Study.

BACKGROUND AND AIMS: The metabolic consequences of extreme temperature exposure in nondiabetic populations remain poorly understood. This study aimed to examine associations between heatwave and coldwave exposure and incident diabetes mellitus (DM) and impaired glucose tolerance (IGT) in middle-aged and older Chinese adults. METHODS: A total of 1803 China Health and Retirement Longitudinal Study participants aged ≥45 years with normoglycemia at baseline were followed from Wave 1 (2011) to Wave 3 (2015). Eighteen extreme-temperature indicators were derived from city-level fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis data. Outcomes were classified according to American Diabetes Association criteria. Generalized linear mixed-effects models (GLMMs) were pooled across five imputed datasets, with Bonferroni correction for multiple comparisons (α = 0.0028) and sensitivity analysis adjusting for individual follow-up duration. RESULTS: All nine heatwave indicators showed odds ratios (ORs) < 1.0 for DM and IGT. HT9 (≥97.5th percentile, ≥4 consecutive days) was the sole Bonferroni-significant result: OR = 0.845 (95% confidence interval [CI]: 0.802-0.890). Coldwave indicators showed no consistent associations. Age significantly modified the HT9 effect (P-interaction = 0.004): adults aged 65-84 showed a stronger inverse association (OR = 0.616) than those aged < 65 (OR = 0.921). CONCLUSION: Prolonged heatwave exposure was consistently associated with reduced diabetes risk, with pronounced age heterogeneity. Replication in larger prospective studies is warranted.

Humans↗

PubMed2026

Risk factors for loss of skeletal muscle mass in patients with chronic kidney disease on a low-protein diet.

OBJECTIVES: A low-protein diet (LPD) is recommended for patients with chronic kidney disease (CKD) to prevent a further decline in renal function. However, its impact on muscle mass in these patients remains unclear. This study investigated the risk factors for loss of muscle mass in patients with CKD on an LPD. METHODS: Eighty-four patients with predialysis CKD (59 men, mean age 61.9 ± 11.5 y) who participated in a multicenter randomized controlled trial initiated in 2014 were retrospectively reviewed. We collected data on baseline blood and urine tests, body composition, and dietary records at the start and end of the observation period. We evaluated muscle mass using the skeletal muscle index (SMI) and analyzed risk factors for a decrease in SMI during the 24-wk observation period, using logistic regression analysis. Variables with an association (P < 0.1) in univariate analysis, as well as age, sex, use of low-protein rice, and changes in protein intake, were subjected to multivariate analysis. RESULTS: SMI decreased in 50 patients (59.5%) during the observation period. Multivariate analysis identified significant associations of the SMI with serum albumin at baseline (odds ratio 0.11, 95% confidence interval 0.02-0.52, P = 0.004) and changes in energy intake while on the LPD (odds ratio 3.39, 95% confidence interval 1.00-11.43, P = 0.049). CONCLUSIONS: Risk factors for reduced SMI in patients with CKD on an LPD were malnutrition when initiating the LPD and reduced energy intake during its implementation. Clinicians should optimize nutritional status before initiation of an LPD and ensure adequate energy intake throughout treatment.

Humans↗

PubMed2026

Association of lipoprotein-associated phospholipase A2 with recurrence risk and its predictive value in large artery atherosclerotic stroke.

OBJECTIVE: To investigate the association of lipoprotein-associated phospholipase A2 (Lp-PLA2) with large artery atherosclerotic (LAA) stroke and its predictive value for recurrence. METHODS: We consecutively enrolled 412 acute LAA stroke patients. Using a cutoff of 200 ng/mL, patients were divided into high and low Lp-PLA2 groups, and into recurrence and non‑recurrence groups based on 1‑year follow‑up. Baseline characteristics, lipid profiles, National Institutes of Health Stroke Scale (NIHSS) scores, and vascular stenosis degree were compared. Binary logistic regression and Receiver Operating Characteristic (ROC) analysis were used to identify independent risk factors and evaluate predictive value. RESULTS: The high Lp-PLA2 group had significantly higher low-density lipoprotein cholesterol (LDL-C), small dense low-density lipoprotein cholesterol (sdLDL-C), prevalence of severe stenosis (≥70%), and proportion of NIHSS > 15 (all P < 0.05). The recurrence group showed elevated Lp-PLA2, higher LDL‑C and sdLDL-C, more severe neurological deficits, and more severe stenosis (all P < 0.001). Multivariable regression identified elevated Lp-PLA2 (per 10 ng/mL: OR = 1.139, 95% CI: 1.089-1.191), moderate (OR = 3.145) and severe (OR = 11.663) neurological deficits, and severe stenosis (OR = 9.390) as independent risk factors for recurrence (all P < 0.05). The Area Under the Curve (AUC) of Lp-PLA2 was 0.75 (95% CI: 0.69-0.82), with an optimal cutoff of 208.95 ng/mL. CONCLUSION: Elevated Lp-PLA2 is associated with adverse lipid profiles, more severe neurological deficits, and greater vascular stenosis in LAA stroke patients, and independently predicts 1‑year recurrence. Lp-PLA2 shows moderate predictive value, supporting its potential for risk stratification.

Humans↗

PubMed2026

"Abrazos, no Balazos": Intensity of Risk for Exposure to Violence and Armed Conflict Trajectories for Adolescents and Young Adults in México 2018-2024.

PURPOSE: "Abrazos, no balazos" (Hugs, not gunshots) is the approach to violence used by the Federal Mexican government from 2018 to 2024. This study identifies distinct conceptually useful latent class growth trajectories in the annual intensity of risk for exposure to events and fatalities from violence against civilians and battles for adolescents and young adults (AYAs) in México from 2018 to 2024. METHODS: Data are from the Armed Conflict Location and Event Data project. Latent class growth analyses were conducted with four longitudinal dependent variables assessed in seven sequential years (2018-2024). RESULTS: In most of the Mexican states, AYAs experienced low intensity-flat trajectories (p >.096) in the annual intensity of risk for exposure to events and fatalities from violence against civilians and battles. AYAs who lived in states with extremely, markedly, or moderately elevated 2018 intensities of risk for exposure to violence experienced decreasing trajectories (p =.000). One latent class with a mildly elevated-increasing trajectory (p =.000) in the annual intensity of risk for exposure to violence was identified for each of the four longitudinal dependent variables. DISCUSSION: During the time that the Federal Mexican government used the "Abrazos, no balazos" approach, AYAs in the majority of the states in México had intensity of risk for exposure to violence and armed conflict trajectories that were consistent with the goals of primary and secondary violence prevention. Violence prevention efforts should be augmented in states with unfavorable trajectories.

Humans↗

PubMed2026

The impact of supernormal lung function on mortality risk in adults with and without sleep-disordered breathing.

BACKGROUND: In the general population, supernormal lung function is associated with a lower risk of all-cause mortality. RESEARCH QUESTION: It remains unclear whether sleep-disordered breathing (SDB) affects this relationship. METHODS: This cohort analysis included 4,839 adults. Lung function was categorised as supernormal (FEV1 > ULN), normal (LLN ≤ FEV1 ≤ ULN), and below normal (FEV1 < LLN). SDB severity was classified using apnoea-hypopnoea index categories: no SDB (<5 events/hour), mild SDB (5-<15 events/hour), moderate SDB (15-<30 events/hour), and severe SDB (≥30 events/hour). The association between lung function and all-cause mortality was assessed using Cox proportional hazards models with subgroup analyses according to SDB severity and formal testing for interaction. Analyses were repeated using FVC-defined lung function groups as an alternative definition of supernormal lung function. RESULTS: Among the included participants, 4,068 (84.1%) had normal lung function, 369 (7.6%) had supernormal lung function, and 402 (8.3%) had below normal lung function. During 52 421.5 person-years of follow-up (median 11.72 years; IQR, 10.46-12.56), 1,188 deaths occurred. Compared with the normal lung function group, the supernormal lung function group had a lower prevalence of baseline hypertension and cardiovascular disease. The association between lung function and all-cause mortality varied across SDB severity strata (P for interaction = 0.034). A lower mortality risk associated with supernormal lung function was observed in participants without SDB (HR: 0.24, 95% CI: 0.06-0.97), whereas this association was not statistically significant in the mild, moderate, or severe SDB strata. Below normal lung function was generally associated with an increased all-cause mortality risk. Sensitivity analyses using FVC-defined lung function groups yielded broadly consistent findings. CONCLUSION: Supernormal lung function was associated with lower all-cause mortality primarily among individuals without SDB. These findings underscore the importance of considering SDB severity when assessing the health implications of lung function.

Humans↗