Alzheimer’s disease (AD), a chronic and progressive neurodegenerative disorder, poses a significant threat to the health of the aging population. The pathological hallmarks of AD include the accumulation of amyloid-β (Aβ) plaques and neurofibrillary tangles (NFTs) within the brain. While substantial neuronal loss has been consistently observed in AD, the precise mechanisms underlying neuronal elimination remain incompletely understood. As a distinct form of regulated cell death, the contribution of ferroptosis to AD pathogenesis and progression warrants further investigation. This review critically examines the amyloid cascade hypothesis within the context of AD, with particular emphasis on the molecular signatures of ferroptosis and their contributions to canonical AD pathogenesis and cognitive decline. We aim to provide an updated perspective on AD etiopathogenesis. Furthermore, we synthesize current therapeutic strategies targeting ferroptosis inhibition in AD, highlighting recent advances that hold significant implications for guiding present and future translational efforts.

While comorbid depression and stroke are a major concern for public health, the effect of dietary nutrient patterns on their concurrent occurrence is still largely unexplored. From NHANES, a survey of the U.S. civilian, non‐institutionalized population, we included 814 participants with complete data on diet, depression, and stroke. Of these, 140 were identified with comorbid depression and stroke. Baseline characteristics were compared between groups, and Weighted Quantile Sum (WQS) regression was used to evaluate the collective effects of nutrient mixtures. Machine learning models aimed at predicting comorbid conditions were developed, incorporating Synthetic Minority Oversampling Technique (SMOTE) for oversampling and Boruta for selecting features. The interpretability of these models was analyzed using SHapley Additive exPlanations (SHAP) and Local Interpretable Model‐agnostic Explanations (LIME). Participants with comorbidities were younger and had lower socioeconomic status, along with reduced intake of thiamin, vitamin B6, total folate, added vitamin B12, and vitamin C. Although neither WQS‐negative nor WQS‐positive indices showed statistically significant associations with comorbidity risk, specific nutrients such as alcohol, alpha‐carotene, added vitamin B12, theobromine, and vitamin E emerged as predominant contributors within the mixture models. The Random Forest classifier achieved the highest area under the receiver operating characteristic curve (AUC = 0.945) when adjusted for covariates and maintained consistently high performance in the unadjusted setting. SHAP and LIME analyses consistently identified vitamin B1, vitamin B12, zinc, vitamin C, and caffeine as influential predictors, with SHAP plots revealing mirrored feature contribution patterns depending on comorbidity status. Covariate adjustment improved directional stability and interpretability, particularly in SHAP dependence plots and waterfall visualizations. LIME explanations at the individual level corroborated these findings, showing consistent yet class‐dependent feature effects. Although the overall mixture effect was not significant, machine learning identified nutrient‐specific signals associated with comorbid depression and stroke. These results indicate that integrating dietary indicators with explainable artificial intelligence may improve transparency in risk prediction and guide future longitudinal and interventional research.

Purpose: Obstructive sleep apnea (OSA) is increasingly recognized as a systemic disorder in which inflammation plays a pivotal role in its pathophysiology and comorbidities. This study aimed to conduct the first comprehensive bibliometric analysis of global research on inflammation in OSA, in order to map knowledge structures, identify influential contributors, and highlight emerging research trends. Patients and Methods: Publications related to OSA and inflammation were retrieved from the Web of Science Core Collection (WoSCC) (1996– 2025). After exclusions, 2,075 articles and reviews were analyzed using bibliometric tools including CiteSpace, VOSviewer, and the bibliometrix R package. Citation frequencies, co-citation networks, and collaboration patterns among countries, institutions, authors, and journals were examined. Results: The number of publications has shown robust growth (annual rate 12.11%). China and the United States were the leading contributors, with Harvard University, the University of Chicago, and Institut National De La Sante Et De La Recherche Medicale (INSERM) among the most productive institutions. Influential authors included Gozal D, Kheirandish-Gozal L, and Khalyfa A. Sleep and Breathing was the most prolific journal, while Circulation and American Journal of Respiratory and Critical Care Medicine were highly co-cited sources. Highly cited works established the link between intermittent hypoxia, systemic inflammation, and cardiovascular/metabolic consequences. Thematic clusters revealed major research focuses on cardiovascular disease, metabolic syndrome, oxidative stress, neuroinflammation (including microglial activation), and therapeutic strategies such as continuous positive airway pressure (CPAP), adenotonsillectomy, and bariatric surgery. Emerging topics included gut microbiota, vitamin D, and neurodegenerative diseases. Conclusion: Research on inflammation is evolving from mechanistic insights toward clinical management and interdisciplinary exploration. Looking ahead, priority should be given to biomarker discovery and the development of anti-inflammatory therapeutic strategies. These findings provide a roadmap for targeted research and clinical translation in the field of OSA-related inflammation, ultimately improving patient outcomes.

We intended to investigate the correlation of the geriatric nutritional risk index (GNRI) and the risks of all-cause and cardiovascular mortality in elderly patients with osteoarthritis (OA). This study included 2,922 OA patients aged ≥ 60 years from National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. GNRI was obtained using serum albumin and body weight, with participants stratified into high (≥ 98) and low (< 98) GNRI groups. Cox regressions, survival analysis, and restricted cubic spline (RCS) regression have been utilized to assess mortality risks. Nonlinear threshold effects were evaluated using piecewise regression. Moreover, subgroup analyses have also been completed based on demographic, lifestyle, and clinical features. Participants with low GNRI had significantly higher risks of all-cause mortality (adjusted HR = 1.494, 95% CI: 1.192–1.872, P < 0.001) and cardiovascular mortality (adjusted HR = 1.592, 95% CI: 1.142–2.219, P = 0.006). RCS analysis presented with a nonlinear J-shaped relationship, with optimal GNRI around 120. Subgroup analyses confirmed consistent associations across age, sex, race, and comorbidity strata. Lower GNRI could independently lead to increased all-cause and cardiovascular mortality in OA patients, highlighting the importance of nutritional assessment in OA management. As a result, GNRI could serve as a valuable prognostic indicator for identifying high-risk individuals who could benefit from targeted nutritional interventions.

Background: This systematic review and meta-analysis aimed to quantify the association between environmental and occupational lead exposure and the risk of various hypertension subtypes. We further evaluated this relationship through a dose–response analysis to provide a scientific basis for targeted public health interventions. Methods: Observational studies on lead exposure and hypertension were searched from Chinese/English databases (inception to June 9, 2025). Two researchers independently screened studies, extracted data, and assessed bias risk. Random-effects meta-analysis calculated pooled ORs (95% CIs); meta-regression/subgroup analyses explored heterogeneity. Egger’s test evaluated publication bias, sensitivity analyses verified result robustness, and dose–response analysis was applied to multi-level exposure data. Result: 24 studies (181,500 participants) were included. Lead exposure correlated significantly with hypertension (pooled OR = 1.27, 95% CI: 1.20–1.34) with high heterogeneity (I ² = 91.4%, p < 0.001). Stronger associations were found for blood lead (OR = 1.32), essential hypertension (OR = 1.31), and resistant hypertension (OR = 1.36); no significant associations for bone lead or gestational hypertension. Hypertension risk rose sharply at blood lead ≥ 0.107 μg/dl, reaching OR = 4.85 at 8.435 μg/dl. Potential publication bias existed, but sensitivity analyses confirmed robustness. Conclusion: Lead exposure is a hypertension risk factor with a clear dose–response relationship. It is recommended to include blood lead in hypertension risk assessment and set a blood lead action level of < 0.107 μg/dl for high-risk groups to reduce hypertension burden from lead pollution. Systematic review registration: https://inplasy.com/inplasy-2025-9-0008/ .

Background: Exercise is a non-pharmacological strategy for enhancing cognitive function among various populations. The aim of our systematic review was to synthesise evidence of the effects of exercise on cognitive function in children and adolescents with overweight or obesity. Methods: A comprehensive search of four databases (Web of Science, PubMed, Scopus, EMBASE was conducted from each database inception through 1 April, 2025. This review investigates the impact of exercise intervention on the cognitive function of children and adolescents with overweight or obesity through randomized controlled trials (RCTs). The quality of the included studies was evaluated using the Cochrane Risk of Bias Tool 2, and the treatment effects were analyzed through random-effects or fixed-effects models, with Hedges’ g serving as the metric for effect size estimation. I ² statistics assessed heterogeneity, and leave-one-out analysis verified result stability. Subgroup analyses were conducted based on the FITT principle, including exercise frequency, intensity, and time. Results: The meta-analysis of 15 RCTs, including 1,210 children and adolescents with overweight or obesity revealed that exercise significantly improved executive function ( g = 0.39, 95% CI:0.12 to 0.66, p = 0.0043). No significant effects were observed for other aspects of attention and memory ( p >0.05). Subgroup analysis identified that exercise with a frequency of >3 sessions per week (g = 0.39, p = 0.0257), moderate-to-vigorous intensity ( g = 0.50, p = 0.0132), exercise interventions ≥10 weeks ( g = 0.41, p = 0.0184), single session duration >30 min ( g = 0.41, p = 0.0139), and weekly exercise volume > 120 min ( g = 0.28, p = 0.00236) had higher effect sizes in improving executive function in children and adolescents with overweight or obesity. Subgroup analyses revealed that exercise frequencies 15 weeks ( g = 0.98) significantly enhanced attention ( p < 0.05). Conclusion: This study demonstrates that exercise interventions significantly improve executive function and attention in children and adolescents with overweight or obesity. In particular, moderate-intensity aerobic exercise performed more than three times per week, for over 30 min per session, and sustained for at least 10 weeks appears to represent the optimal training parameters for improving executive function. These findings support the use of exercise as a cognitive enhancement strategy. However, larger-scale studies are needed to confirm its effects on other cognitive domains. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251078572 , Identifier: CRD420251078572.