To analyse the epidemiological trends, influencing factors, and dynamic changes of central obesity among adults in Guizhou Province from 2004 to 2023, providing evidence for formulating targeted prevention and control strategies.

Data from the China Health and Nutrition Survey (CHNS) were selected for Guizhou Province in 2004, 2006, 2009, 2011, 2015, 2018, and 2023. A stratified cluster random sampling method was employed, selecting adult residents aged≥18 years as study subjects. Central obesity was defined according to the WS/T 428-2013 standard (waist circumference ≥90 cm for males, ≥85 cm for females). The χ² test was employed to compare rates between groups, while the Cochran-Armitage trend test analysed trends in central obesity rates across years and age groups. To examine changes in influencing factors, the study period has been divided into an early phase (2004-2011) and a recent phase (2015—2023), and multivariate logistic regression models have been constructed for each phase for comparison.

A total of 6 101 survey subjects was included. The central obesity rate increased from 16.55% in 2004 to 39.15% in 2023（χ²=237.663, P<0.001). Period-specific multivariate logistic regression analysis revealed significant changes in the influencing factors: 2004-2011 (OR=1.46, 95%CI:1.23-1.74), whereas excessive cereal and tuber consumption became the dominant risk factor during 2015-2023 (OR=1.23, 95%CI:1.01-1.49) and alcohol consumption (OR=1.39, 95%CI: 1.10-1.77) became predominant risk factors. Concurrently, the risk among individuals with lower educational attainment increased significantly in recent years (OR=1.56, 95%CI:1.06-2.30).

Between 2004 and 2023, the prevalence of central obesity among adults in Guizhou Province rose sharply, with the primary risk factors shifting from excessive consumption of animal-based foods in the early years to an unbalanced staple food diet, alcohol consumption and low educational attainment in recent years. Prevention and control strategies need to be dynamically adjusted; in the immediate term, the focus should be on optimising the composition of staple foods, restricting alcohol consumption and strengthening health interventions targeting people with low educational attainment.

To construct a predictive model for frailty risk among older adults living alone, identify key influencing factors, and provide scientific evidence for early screening and intervention of frailty.

Using data from the 2018 China Health and Retirement Longitudinal Study, 1 758 individuals aged 60 years and older living alone were enrolled. The dataset was divided into a training set (n=1 230) and a validation set (n=528) at a 7:3 ratio. The Frailty Index was constructed to assess frailty. Predictor variables were identified using a health ecology model, and LASSO regression and multivariable logistic regression were employed to select predictors influencing frailty in older adults living alone, thereby constructing a risk prediction model. Model performance was evaluated using metrics such as the area under the ROC curve, calibration curves and decision-making analysis curves.

The frailty detection rate among older adults living alone was 24.6%. LASSO regression identified six potential predictors. Multivariate logistic regression revealed that advanced age, female gender, and poor sleep quality were risk factors for frailty among older adults living alone, while exercise and social engagement served as protective factors. In model validation, the area under the ROC curve was 0.822 for the training set and 0.767 for the validation set, and Hosmer-Lemeshow test value P > 0.05. Decision curve analysis indicated that the model demonstrated significantly superior net benefit compared to extreme scenarios within the 0.1-0.75 interval.

The frailty risk prediction model developed for older adults living alone in this study exhibits good predictive performance and clinical applicability, providing a reference for primary healthcare workers to conduct frailty screening among key populations.

To investigate the causal relationship between plasma arginine (Arg) levels and colorectal cancer (CRC) risk using a bidirectional two-sample mendelian randomization (MR) approach, thereby providing genetic evidence for this association.

Based on publicly available large-scale Genome-Wide Association Study (GWAS) data, bidirectional MR analysis was conducted with Arg and CRC. In the forward analysis, genetic variants associated with plasma Arg levels were used as instrumental variables to estimate their causal effect on CRC risk. The reverse analysis assessed the effect of genetic predisposition to CRC on Arg levels. The primary causal estimate, derived via the inverse-variance weighted (IVW) method, was supplemented by the weighted median (WM) and MR-Egger approaches for sensitivity analyses. Robustness was evaluated through heterogeneity tests (Cochran Q), assessments of horizontal pleiotropy (MR-Egger intercept), and leave-one-out sensitivity analyses.

The forward MR analysis revealed an inverse causal association between genetically predicted plasma Arg levels and CRC risk (OR=0.762, 95%CI: 0.589-0.986, P=0.039). Sensitivity analyses showed no significant heterogeneity (Cochran QP=0.222) or evidence of horizontal pleiotropy (MR-Egger intercept P=0.991). In the reverse direction, MR analysis found no significant causal effect of genetic liability for CRC on plasma Arg levels (P>0.05).

Genetically elevated plasma arginine levels are causally associated with a reduced risk of colorectal cancer, suggesting a potential protective role. No reverse causal relationship was found. This provides genetic evidence for further exploration of the potential role of arginine in the prevention or intervention of colorectal cancer.

To identify a novel plasma protein biomarker panel for predicting mild cognitive impairment (MCI) and Alzheimer’s disease (AD) using machine learning algorithms, and to provide evidence for early diagnosis of AD.

A total of 566 eligible participants were enrolled from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, and baseline plasma proteomic data were collected. Random forest, Lasso regression, and support vector machine were applied to screen plasma proteins that effectively discriminate MCI and AD. Correlation analyses with cerebrospinal fluid biomarkers and cognitive scales, and Mendelian randomization analysis were conducted. The model was validated in the GEO and UK Biobank databases.

Ten core plasma biomarkers, including apolipoprotein AII, apolipoprotein E, transthyretin (TTR), were consistently identified by the three algorithms and showed strong correlations with cerebrospinal fluid biomarkers and cognitive scores. Mendelian randomization indicated an inverse association between TTR and AD risk. The area under the curve (AUC) of the tenbiomarker panel was 0.929 for predicting MCI and 0.932 for AD. The panel achieved an AUC of 0.871 in the GEO dataset. When combined with age, sex and APOE ε4 status, the panel yielded an AUC of 0.856 for predicting incident AD over an average of 14 years in the UK Biobank.

The newly identified plasma protein panel can effectively predict the occurrence of MCI and AD, providing a noninvasive tool for early screening and prevention of AD.

To explore factors influencing suicidal behavior in patients with severe mental disorders.

Using cohort data from a western region of China (2006-2018), 332 298 patients were included. A multilevel logistic regression model was used to analyze factors associated with suicidal behavior (suicide death and suicide attempts).

Among 332 298 individuals, 3 358 experienced the outcome event, with an incidence of 1.01%. Multilevel logistic regression showed that female sex (OR=1.142, 95%CI: 1.058-1.234), other ethnicities (OR=1.609, 95%CI: 1.220-2.122), and non married status (OR=1.169, 95%CI: 1.064-1.285) were associated with higher risk, while age ≥46 years (46-60: OR=0.754, 95%CI: 0.669-0.849; 61-90: OR=0.708, 95%CI: 0.615-0.814) was associated with lower risk. When analyzing suicide attempts and suicide death separately, gender, ethnicity, and marital status were associated only with suicide attempt, whereas urban/rural residence and family history were associated only with suicide death. Follow-up time showed opposite effects on the two outcomes.

Prevention efforts should target high-risk populations, including those with risk assessment levels 3-5, other ethnicities, adverse drug reactions, ongoing pharmacotherapy, and higher education levels. Maintaining follow-up and establishing an integrated prevention network combining clinical and social factors is essential.

To explore the differences in the composition and function of intestinal microbiota among healthy individuals, patients with diabetes, and those with diabetic nephropathy, and to analyze the characteristics of intestinal flora imbalance in patients with advanced diabetic nephropathy, providing references for the mechanism research and prevention and treatment strategy formulation of this disease.

A total of 32 patients with advanced diabetic nephropathy, 79 patients with diabetes mellitus and 55 healthy controls were enrolled from the West China Fourth Hospital and Southwest China natural population cohort. Clinical data were collected and fecal samples were subjected to metagenomic sequencing. Linear discriminant analysis was used to screen for differentially abundant species and functional pathways. Linear regression analysis was performed to investigate the correlation between population phenotypes and differentially abundant species. Random forest and SPIEC-EASI algorithms were used to establish species classifiers and interaction networks, respectively.

There were significant differences in the β-diversity of the intestinal microbiota among the three groups, but no statistically significant differences were observed in the α-diversity. In the advanced stage of diabetic nephropathy patients, the intestines were enriched with various opportunistic pathogenic bacteria (such as Eggerthella lenta, Clostridium innocuum, Hungatella hathewayi, etc.) and harmful pathways such as anaerobic energy metabolism and L-histidine degradation, and were significantly correlated with renal function indicators. The intestines of diabetic patients were characterized by the enrichment of opportunistic pathogenic bacteria (such as Escherichia coli and Klebsiella pneumoniae) and the activation of glycolytic pathways. The random forest model performed best in differentiating the diabetic nephropathy group from the healthy control group (AUC=0.920). The co-abundance network analysis further revealed that the intestinal microbial interaction network of diabetic nephropathy patients was significantly sparser and the topological parameters changed, suggesting that there was an imbalance in the microbial ecological network during the disease process.

From diabetes to the advanced stage of diabetic nephropathy, the intestinal microbiota shows a progressive functional disorder, with an increase in the abundance of harmful bacterial species and metabolic pathways, which is closely related to the progression of the disease.

To investigate the prevalence of comorbidity status of hypertension, diabetes mellitus and dyslipidemia (commonly referred to as the “Three Highs”), to identify factors influencing this comorbidity among community-dwelling residents aged 35–75 years in two districts of Jinan City, and to provide scientific evidence to inform targeted and precise management and intervention strategies for local patients with these metabolic comorbidities.

From September 2016 to June 2022, stratified cluster sampling was used to select residents aged 35–75 years in Licheng District and Zhangqiu District of Jinan. Questionnaire surveys, physical examinations, and blood tests were conducted. R 4.2.1 software was used for chi-square test, trend chi-square test, and binaryl logistic regression analysis to explore the influencing factors of “three highs” comorbidity.

A total of 30 214 participants were included, with 12 185 males (40.33%) and 18 029 females (59.67%), and a mean age of (57.97±9.55) years. The standardized prevalence rate of hypertension is 45.39%, that of diabetes mellitus is 22.54%, and that of dyslipidemia is 27.31%. Among them, the standardized comorbidity rate of the “three highs” stands at 5.95%. The highest standardized comorbidity rate is observed in patients with both hypertension and hyperlipidemia, reaching 9.75%. Binary logistic regression analysis showed that the following factors were risk factors for “three highs” comorbidity (all P<0.05): male (OR=1.121 95%CI: 1.028-1.222), older age groups (OR≥1.992 in all age groups); administrative/professional and technical personnel (OR=1.551 95%CI: 1.120-1.989), retired/unemployed/household workers (OR=1.174 95%CI: 1.041-1.324), private business owners/other personnel (OR=1.427 95%CI: 1.101-1.850); history of cardiovascular and cerebrovascular diseases (OR=1.943 95%CI:1.620-2.332); overweight (OR=1.624 95%CI: 1.418-1.859); obesity (OR=2.016 95%CI: 1.766-2.404); and central obesity (OR=1.931 95%CI:1.733-2.152).

In Jinan City, the comorbidity prevalence of hypertension, diabetes, and dyslipidemia is relatively high, with hypertension combined with dyslipidemia being the most common comorbidity pattern. Priority interventions should be targeted at males, the elderly, sedentary occupational groups, individuals with a history of cardiovascular and cerebrovascular diseases, and overweight/obese individuals.

To retrospectively analyze the epidemiological characteristics and treatment outcomes of patients with recurrent pulmonary tuberculosis in Shaanxi Province from 2011 to 2024, so as to provide a scientific basis for the prevention and control of recurrent pulmonary tuberculosis and the formulation of relevant strategies in Shaanxi Province.

The medical records of all patients with recurrent pulmonary tuberculosis registered in the Tuberculosis Information Management System (TIMS) of Shaanxi Province from 2011 to 2024 were collected. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of the subjects, chi-square test was used for inter-group comparison, and Joinpoint regression model was applied for time trend analysis.

A total of 11 715 patients with recurrent pulmonary tuberculosis were cumulatively reported in Shaanxi Province from 2011 to 2024. The registration rate of recurrent pulmonary tuberculosis in the province decreased from 3.94/100 000 population in 2011 to 1.46/100 000 population in 2024, showing an overall significant downward trend (AAPC=-8.6%, P<0.05). The composition of patient detection sources underwent a fundamental shift: the dominant detection route changed from “direct consultation” (accounting for 52.45% in 2011) to “referral”(with the proportion peaking at 73.13% in 2020). During the study period, the cumulative etiologically positive rate of recurrent patients was 56.18%, which was significantly higher than 35.91% of all notified pulmonary tuberculosis patients in the general population, with a statistically significant difference (χ²=1 983.846, P<0.05). The demographic characteristics showed that patients with recurrent pulmonary tuberculosis were predominantly concentrated in male farmers aged 40-64 years, accounting for a cumulative 36.46% of all enrolled subjects. Meanwhile, although the average annual consultation delay rate of recurrent patients was 56.93%, it showed a significant continuous downward trend during the study period (AAPC=-2.50%, P<0.05). Treatment outcome analysis showed that the cumulative treatment success rate of patients with recurrent pulmonary tuberculosis from 2011 to 2024 was 82.41%, while Joinpoint regression indicated a significant downward trend of this rate (AAPC=-1.43%, P<0.05).

The epidemic of recurrent pulmonary tuberculosis in Shaanxi Province has shown an overall downward trend, but the etiologically positive rate is significantly higher than that of all notified pulmonary tuberculosis patients, and the composition of patient detection sources has changed dramatically. Recurrent patients are concentrated in middle-aged and elderly male farmers, and the treatment success rate is on a downward trend, suggesting that there are still weak links in the treatment and management of recurrent patients. It is recommended to strengthen active screening and health management for high-risk groups such as farmers, optimize the referral network to reduce consultation delay, and improve the quality of treatment and management for recurrent patients to increase the treatment success rate.

To investigate the mechanism by which reduced degradation of Bcl-2/adenovirus E1B-19-kDa interacting protein 3 (BNIP3) mediated by neural precursor cell expression developmental downregulation protein 4 (NEDD4) and proteasome β5 subunit (PSMB5) contributes to impaired autophagy flux and cellular damage in arsenic-induced human hepatocellular carcinoma cells (HepG2).

The cytotoxic effects of different doses of sodium arsenite (NaAsO₂) treated HepG2 cells over varying time periods were evaluated by analyzing cell morphology, ultrastructure, cell viability, and hepatic injury enzyme levels (ALT, AST). Immunoprecipitation blotting (Western blot) was used to detect the expression levels of NEDD4, PSMB5, BNIP3, and autophagy-related proteins. Co-immunoprecipitation (Co-IP) experiments were conducted to analyze the interactions among NEDD4, PSMB5, and BNIP3. Specific inhibitors including cycloheximide (CHX), chloroquine (CQ), and proteasome inhibitor (MG132) were employed to inhibit protein synthesis, lysosomal function, and the ubiquitin-proteasome pathway, respectively, to investigate the roles of the ubiquitin-proteasome pathway and autophagy in arsenic-induced HepG2 cell damage.

As the concentration and duration of NaAsO₂ exposure increased, the viability of HepG2 cells decreased and morphogenesis exhibited significant changes. Additionally, autophagy flux was impaired, and cellular damage worsened in a dose- and time-dependent manner. Different concentrations and durations of NaAsO₂ exposure down - regulated NEDD4 and PSMB5 protein expression while up - regulating BNIP3, Beclin-1, P62, and LC3II/LC3I protein expression, showing time - effect and dose - effect relationships (P<0.05). CQ intervention exacerbated NaAsO₂ - induced autophagy flux obstruction and cellular damage (P<0.05). Co-IP and CHX experiments demonstrated that NaAsO₂ exposure reduced the interaction between NEDD4 and PSMB5 with BNIP3, thereby decreasing BNIP3 degradation (P<0.05). MG132 intervention downregulated PSMB5 protein expression and up - regulated BNIP3, P62, Beclin-1, and LC3II/LC3I protein expression, with all differences being statistically significant (P<0.05).

NaAsO₂ exposure can reduce the expression of NEDD4 and PSMB5 in HepG2 cells in a time - and dose - dependent manner, pregulate BNIP3 protein levels, and impair autophagy flux, ultimately leading to cellular damage. The mechanism may involve reduced binding of NEDD4 and PSMB5 to BNIP3, leading to decreased BNIP3 degradation and consequent cumulative accumulation.

To investigate the therapeutic efficacy and underlying mechanism of ZSP1603, a novel independently developed small-molecule tyrosine kinase inhibitor, against lung tissue injury in silicotic mice, so as to provide an experimental basis for clinical research on the treatment of silicosis.

Based on the molecular toxicological network induced by silica dust, molecular docking was performed to predict the potential targets and mechanisms of ZSP1603 in alleviating silica dust-mediated respiratory toxicities. A silica-induced mouse silicosis model was established. Pathological staining, immunohistochemistry and multi-omics analyses were comprehensively applied to evaluate the protective effects and molecular mechanisms of ZSP1603 on silica-associated silicosis-like lesions in mice.

A total of 50 intersecting genes were identified between the pharmacological targets of ZSP1603 and the toxicity-related genes triggered by silica dust, which were mainly enriched in signaling pathways associated with inflammation, oxidative stress and fibrosis. Long-term administration of ZSP1603 at the experimental dose (60 mg/kg) significantly ameliorated silica-induced pulmonary inflammation, lung tissue damage and collagen deposition (at 12 weeks, the Szapiel and Ashcroft scores in the ZSP1603 group were significantly lower than those in the model group, P<0.01), and downregulated the expression of proteins related to silica toxicity (the expression levels of Collagen I, Collagen III, α-SMA, FN, TNF-α, IL-6, and IL-1β were significantly downregulated compared to the model group, P<0.001). Moreover, ZSP1603 effectively corrected the gut microbiota dysbiosis in silicotic mice. In addition, no obvious systemic in vivo toxicity was observed following treatment with the experimental dose of ZSP1603.

The novel tyrosine kinase inhibitor ZSP1603 alleviates silicosis-related inflammation and fibrosis in a mouse silicosis model. These findings provide a reference for the research and development of therapeutic agents for the secondary and tertiary prevention and clinical intervention of silicosis.

To identify the main chemical occupational hazard factors and their exposure levels associated with condensate oil in natural gas exploitation, and to explore occupational health risk assessment methods for chemical hazards in this industry, so as to provide a basis for accurately preventing occupational hazards and protecting the health of occupational populations.

Based on occupational health surveys, condensate oil component analysis and continuous monitoring of chemical occupational hazards, the occupational health risks of condensate oil exposure in natural gas exploitation were assessed using the comprehensive index method, ICMM quantitative assessment method and occupational hazard risk index method.

The main occupational hazard factors of condensate oil in natural gas exploitation were benzene, toluene, xylene, n-hexane and cyclohexane. Their time-weighted average concentrations (C_TWA) ranged within 1%-50% of the occupational exposure limits (OELs). Among the 10 gas production well stations, only xylene concentration showed statistical significance (P<0.001), while concentrations of the other four chemical toxicants were generally consistent (P>0.05). Short-term exposure concentrations (C_STEL) of all five typical chemical toxicants were detected in the gas field water treatment station, with generally consistent concentrations (P>0.05). Analysis of occupational health risk levels showed that according to the comprehensive index method, benzene was rated as extremely high risk in both gas production stations and gas field water treatment stations, toluene, n-hexane and cyclohexane as high risk, and xylene as medium risk. According to the occupational hazard risk index method, benzene was moderate risk in the gas field water treatment station and mild risk in gas production stations, while all other factors were assessed as no risk. In the ICMM quantitative assessment method, only benzene in the gas field water treatment station was rated as intolerable risk, and all other factors were rated as tolerable risk. The Kruskal-Wallis test showed significant differences in the rating distributions among the three methods (P<0.05), indicating that different assessment systems varied in their ability to discriminate risk levels of hazardous factors.

Benzene, toluene, xylene, n-hexane and cyclohexane should be the key occupational hazards concerned in condensate oil exposure in the natural gas exploitation industry. The improved ICMM quantitative assessment is a suitable method for occupational health risk assessment of condensate oil in natural gas exploitation.

To explore the impact of early life factors on the initial establishment of infant gut microbiota and their association with allergic diseases in infancy.

A nested case-control study was conducted involving 82 samples from the maternal-infant cohorts established at West China Second University Hospital and Chengdu Women’s and Children’s Central Hospital.

In the vaginal delivery group, the incidence of allergic diseases in infants (30.30%) was lower than that in the cesarean section group (51.02%), with no statistically significant difference; in the breastfeeding group, the incidence (31.81%) was lower than that in the mixed feeding group (55.26%), and the difference was statistically significant (P=0.063; P=0.032). On day 0, the Simpson index in the allergic group was significantly higher than that in the healthy group (P<0.05). By day 30, the healthy group exhibited more favorable microbial richness-related indices of the gut microbiota. On day 7, the relative abundance of Bdellovibrionota in the allergic mixed-fed group was significantly higher than that in other groups (P<0.05). The relative abundance of Bifidobacterium in feces was significantly higher in the healthy group than in the allergic group on day 7 (P<0.05), and the abundance of Bifidobacterium in breast milk of the healthy group remained higher than that of the allergic group from day 0 to day 30.

Vaginal delivery is conducive to maintaining the diversity of gut microbiota in early infancy and establishing a gut microbiota pattern dominated by Bifidobacterium. Meanwhile, breastfeeding promotes the colonization of probiotics such as Bifidobacterium, thereby reducing the long-term risk of allergies in infants.

To explore the dynamic relationship between physical exercise and early adolescent insomnia disorder, and to examine the longitudinal mediating role of depressive symptoms in this relationship, providing scientific evidence for promoting the physical and mental health of adolescents.

A total of 1 162 students from four junior high schools in Xiangxi Tujia and Miao Autonomous Prefecture, Hunan Province were selected using cluster convenience sampling and participated in three follow-up surveys. The research tools included the Insomnia Severity Index (ISI), the Physical Activity Rating Scale (PARS-3), and the Patient Health Questionnaire-9 (PHQ-9) for assessing depressive symptoms. Cross-lagged panel modeling (CLPM) was used to analyze the dynamic relationship between physical exercise and insomnia disorder, and to test the longitudinal mediating effect of depressive symptoms.

The detection rates of depressive symptoms were 50.5%, 55.4%, and 48.1%, while those of insomnia disorder were 48.3%, 46.6%, and 50.1% at the three time points. Physical exercise significantly negatively predicted subsequent insomnia disorder (T1→T2:β=-0.087; T1→T3: β=-0.245, allP<0.001). Insomnia disorder also significantly negatively predicted subsequent physical exercise (T1→T2:β=-0.168; T2→T3:β=-0.213, allP<0.001). Depressive symptoms partially mediated the relationship between physical exercise and insomnia disorder (T1 physical exercise→T2 depressive symptoms:β=-0.150, P<0.001; T2 depressive symptoms→T3 insomnia disorder:β=0.110, P<0.001; indirect effect:β=-0.016, 95%CI=-0.025- -0.010, P<0.001). Physical exercise could indirectly affect insomnia disorder through multiple pathways(total indirect effect:β=-0.117,P<0.001).

There is a long-term bidirectional predictive relationship between physical exercise and early adolescent insomnia disorder, and physical exercise can indirectly influence the development of insomnia disorder through depressive symptoms. It is important to emphasize the cultivation of regular physical exercise habits and intervention of depressive symptoms in early adolescence to improve insomnia disorder and promote the physical and mental health development of adolescents.

To explore the prevalence of comorbidity of myopia and overweight/obesity among junior high school students in Handan and its association with sleep patterns, in order to provide scientific evidence for developing effective prevention measures.

From October to November 2025, a stratified cluster random sampling method was used to select 8 384 junior high school students from 18 counties (cities, districts) in Handan. Participant underwent physical examinations and complete questionnaire. Multivariate Logistic regression model was used to analyze the association between sleep and comorbidity of myopia and overweight/obesity, and restricted cubic spline model was used to clarify the dose-response relationship.

The detection rate of comorbidity of myopia and overweight/obesity among junior high school students in Handan was 16.78%. The median daily sleep duration was 8.42 hours, and the sleep sufficiency rate was 34.03%. Students with light in the sleep environment had a higher risk of comorbidity (OR=1.14, 95%CI:1.01-1.28). Taking the “early to bed and normal wake-up” mode as the reference, junior high school students with “early to bed and early wake-up” mode and “late to bed and normal wake-up” mode had a higher risk of comorbidity (OR=1.27, 95%CI:1.03-1.55; OR=1.33, 95%CI:1.08-1.65). The dose-response relationship between sleep duration and comorbidity risk was an inverted “J” shape. When the sleep duration was longer than 8.1h/d, the comorbidity risk gradually decreased with the extension of sleep duration.

The comorbidity of myopia and overweight/obesity among junior high school students in Handan is a serious issue. Sleep insufficiency is a widespread phenomenon highly associated with an increased risk of comorbidity with myopia and overweight/obesity, indicating that sleep health is a weak link in the current health management of students.

To examine the temporal relationship between the peak velocity of physical fitness development and peak height velocity (PHV) in children and adolescents, and to explore sex differences in this relationship.

This longitudinal study included 13 513 primary and secondary school students from Shiyan, China, with six consecutive years of complete measurements between 2015 and 2024, yielding 101 969 observations. Annual height growth velocity and physical fitness development velocity were calculated. Locally weighted regression was used to identify peak ages and to compute the temporal difference between peak physical fitness velocity and PHV. Linear mixed-effects models were applied to evaluate the effects of fitness type and sex on the temporal difference.

The mean age at PHV was 12.07±1.46 years for boys, significantly later than 11.07±1.46 years for girls (P<0.001). The peak ages of physical fitness development velocity were mainly concentrated between 12 and 13 years, and all occurred after PHV (all P<0.001). Linear mixed-effects modeling indicated that girls exhibited an overall delay of 0.598 years compared with boys (95%CI: 0.511-0.685, P<0.001). The peak velocities of physical fitness development were delayed relative to PHV by approximately 0.52-0.64 years in boys and 1.13-1.22 years in girls, with statistically significant differences (all P<0.001).

Peak physical fitness development velocity generally lags behind PHV in children and adolescents, with a significantly greater delay observed in girls than in boys.

To construct a framework for social work services in elderly palliative care, providing a scientific basis for enhancing the professionalism and effectiveness of social work in palliative care.

A preliminary framework for service content was developed through literature analysis and field research. The Delphi method and Analytic Hierarchy Process (AHP) were used to determine the weights of the indicators and conduct analysis.

A total of 11 experts were consulted, with an average working experience of (20.82±11.09) years, and 7 (63.64%) held deputy senior titles or above. The response rate of valid questionnaires in both rounds of consultation was 100%, with an expert authority coefficient of 0.932 and Kendall’s coefficients of concordance (W) of 0.150 and 0.166, respectively. The final framework for service content includes 3 first-level indicators, 12 second-level indicators, and 41 third-level indicators. At the first-level indicator level, the comprehensive weight of services for patients and their families is the highest, reaching 0.731. At the second-level indicator level, the comprehensive weight of psychological-social intervention is the highest, reaching 0.243. At the third-level indicator level, the comprehensive weight of psychological-emotional adjustment and crisis intervention services for patients and their families is the highest, reaching 0.085.

This study has constructed a framework for social work services in elderly palliative care, providing a standardized theoretical tool for clarifying professional roles, standardizing service practices, and promoting multidisciplinary collaboration. Future research should further verify its application effect and promotion value through large-sample practical studies.

To evaluate the effectiveness of community-based management program involving second-generation antipsychotic long-acting injectables (SGA-LAIs) for patients with severe mental disorders (SMD).

Based on the Sichuan Provincial Severe Mental Disorders Management System, patients enrolled in the program between April 2022 and February 2023 were selected. Clinical symptoms and social functioning were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Social Disability Screening Schedule (SDSS). Caregiver burden was measured using the Zarit Burden Interview (ZBI). A linear mixed-effects model (LMM) was applied to handle the unbalanced longitudinal data and analyze the trends of each indicator over time.

A total of 1 740 patients with severe mental disorders were included. During follow-up, the total PANSS score, its subscale scores, and the total SDSS score all showed significant decreasing trends over time (P<0.001). Age was positively correlated with both PANSS and SDSS scores (P<0.05), and female patients had more severe social functional impairment (β=0.435, P=0.009).

The community-based management program incorporating SGA-LAIs isassociated with sustained improvement in patients’ symptoms and functioning, as well as a reduction in caregiver burden. The results suggest a need for attention to personalized support for older adults and female patients. Given the study design limitations, the causal effect of the observed associations requires verification by future controlled studies.

To understand the current status of elderly care models in Liangshan Prefecture, Sichuan Province from the perspective of the residents living together, and to analyze the influencing factors.

From July to August 2023, a questionnaire survey was conducted among 699 elderly individuals in Liangshan Prefecture. Chi-square test and multinomial logistic regression analysis were used to explore the influencing factors of elderly care models, and Firth regression was employed for sensitivity analysis.

Among the 699 individuals, 373 (53.4%) lived only with their partners, 211 (30.2%) lived with their children, 82 (11.7%) lived alone, and 33 (4.7%) resided in elderly care institutions. The elderly who lived with their children had the highest satisfaction with their living arrangements (H=29.468, P<0.001). The multivariate analysis results indicated that, compared with those living with their children, elderly individuals whose children did not provide daily care were more likely to choose to live only with their partners (OR=33.96, 95%CI:10.45-110.35;the wide confidence interval indicates an exploratory finding) or to live alone or in an institution (OR=21.85, 95%CI:8.44-56.53). Similarly, those whose children did not provide financial support were also more likely to choose to live only with their partners (OR=3.03, 95%CI:1.69-5.43) or to live alone or in an institution (OR=10.99, 95%CI:4.88-24.78). Moreover, the influence of children’s provision of daily care on the elderly’s choice of living only with a partner was greater than that of financial support, as the lower bound of the 95%CI for the OR of daily care (10.45) exceeded the upper bound of the 95%CI for the OR of financial support (5.43).

The elderly care model in Liangshan Prefecture is mainly based on living with a partner or children, and the elderly who live with their children have the highest satisfaction. The daily care and financial support provided by children are important factors influencing the elderly care model in this area. The daily care provided by children has a greater impact than financial support.

To evaluate the effectiveness of the Cardiac Services Network in Chengdu, identify service-deficient areas, and to propose optimized site selection strategies for the construction of Chest Pain Treatment Units (CPUs).

Geographic Information System (GIS) techniques were applied in combination with Voronoi and the Baidu Maps route planning API to quantitatively analyze service areas and population accessibility of existing chest pain centers. Emergency service gaps were identified by simulating round-trip ambulance transfer scenarios, using a threshold of travel time exceeding 2 hours. Spatial neighborhood and overlay analyses were conducted, and primary healthcare institutions were screened for upgrading to CPUs based on a “tier-priority” principle.

The current Cardiac Services Network in Chengdu covers 99.5% of the permanent resident population; however, 54 residential settlements in remote suburban areas exhibit insufficient accessibility. Model simulations suggest that upgrading six suburban primary healthcare institutions to CPUs would reduce the average treatment time for chest pain patients in underserved areas from 95.7 minutes (95%CI: 93.76-97.48) to 32.2 minutes (95%CI: 29.12-37.36), representing a 66.4% reduction (α=0.05, P<0.001).

Although the chest pain emergency network in Chengdu has largely achieved comprehensive coverage, targeted capacity enhancement in remote suburban areas remains necessary. Spatially tiered optimization strategies can significantly shorten treatment time and provide valuable references for emergency care system planning in similar urban settings.

To analyze the changing trends and the stability of influencing factors of influenza vaccine hesitancy among university students in central and western China between 2022 and 2025, and to provide evidence for targeted interventions in universities.

Two rounds of repeat cross-sectional surveys were conducted among university students in central and western China in June 2022 and between January and February 2025. Propensity Score Matching (PSM) was used to balance baseline characteristics. Binary Logistic Regression analyses were employed to identify factors associated with vaccine hesitancy.

A total of 1 786 matched pairs were included in the analysis. From 2022 to 2025, the vaccine hesitancy rate significantly decreased from 47.65% (851/1 786) to 33.31% (595/1 786) (P<0.001). Logistic regression revealed that perceived severity of influenza (2022 OR=0.799 (0.763-0.837), 2025 OR=0.845 (0.793-0.900)), perceived necessity of vaccination (2022 OR=0.275 (0.131-0.579), 2025 OR=0.157 (0.068-0.361)), and previous influenza vaccination history (2022 OR=0.284 (0.222-0.363), 2025 OR=0.469 (0.363-0.606)) were stable protective factors against hesitancy in both years (allP<0.05). Influenza vaccine knowledge changed from a risk factor in 2022 (OR=1.118 (1.009-1.240), P=0.033) to a protective factor in 2025 (OR=0.827 (0.730-0.938), P=0.003). The protective effect of recommendations from family, classmates, or friends was significantly strengthened in 2025 (OR=0.362 (0.278-0.473), P<0.001).

The influenza vaccine hesitancy rate among university students in central and western China decreased significantly between 2022 and 2025, primarily driven by improved vaccine knowledge, enhanced positive social norms, and heightened risk perception. Further efforts to reduce hesitancy should focus on optimizing knowledge dissemination, leveraging social networks, and strengthening guidance from authoritative sources.

To systematically investigate the genetic association and shared biological mechanisms between weekly alcohol consumption (DrnkWk) and estimated heel bone mineral density (eBMD) in adults.

Leveraging large-scale genome-wide association study (GWAS) summary statistics from the UK Biobank and the GSCAN consortium, we integrated linkage disequilibrium score regression (LDSC), local genetic correlation analysis (SUPERGNOVA), cross-trait meta-analysis (PLEIO), gene-based association analysis (MAGMA), and bidirectional two-sample Mendelian randomization (MR) to comprehensively assess global and local genetic correlations, pleiotropic loci, and causal relationships between DrnkWk and eBMD.

No significant genome-wide genetic correlation was observed (r_g=-0.018, 95%CI: -0.050-0.014, P=0.26); while SUPERGNOVA identified 3 genomic regions with significant local genetic correlations. PLEIO revealed 35 pleiotropic loci (including 9 novel loci), and MAGMA implicated 30 shared genes. Bidirectional MR provided no evidence of a causal effect (forward MR:β=-0.051, P=0.12; reverse MR:β=-0.009, P=0.08).

The epidemiological association between alcohol consumption and bone density is likely driven by shared biological pathways and pleiotropic genetic architecture rather than direct causality, offering new insights for genetic risk stratification and targeted prevention strategies for osteoporosis.

To identify key microRNAs involved in idiopathic pulmonary fibrosis (IPF) and investigate the underlying mechanisms.

Analysis of miRNA expression in lung tissues from IPF patients revealed a significant upregulation of miR-205 (logFC=1.91, adj. P. Value<0.05). In vitro experiments confirmed that miR-205 directly targets and suppresses NKD1 expression, thereby modulating the Wnt/β-Catenin signaling pathway and influencing epithelial-mesenchymal transition (EMT), which in turn regulates cell migration and fibrotic progression. Lipid nanoparticles encapsulating a miR-205 inhibitor (i205-LNP) were formulated and evaluated for therapeutic efficacy in a mouse model of pulmonary fibrosis. Following intratracheal administration, i205-LNP significantly upregulated NKD1 expression by approximately 4.05-fold compared to the model group (P<0.05) and reduced the levels of fibrosis-related markers, including α-SMA (approximately 15%, P<0.001), and Col1a1 (approximately 25%, P<0.001) in lung tissues. Consequently, pulmonary inflammation and fibrosis were alleviated, accompanied by attenuated body weight loss and improved survival rates in treated mice.

miR-205 promotes the pathogenesis of idiopathic pulmonary fibrosis by suppressing its target gene NKD1 via the Wnt-EMT signaling pathway.

To analyze the temporal trends and driving factors of the burden of leukemia attributable to smoking in China from 1990 to 2023, and to provide evidence for prevention and control strategies.

Based on the Global Burden of Disease Study 2023 database, data on leukemia deaths and disability-adjusted life years (DALYs) attributable to smoking in China were extracted. The Joinpoint regression model was used to analyze the temporal trends of standardized rates. Decomposition analysis was employed to explore the impacts of population growth, aging, and epidemiological changes on the disease burden.

From 1990 to 2023, the number of leukemia deaths attributable to smoking in China increased from 4 200 to 8 200 (an increase of 96.82%), and DALYs increased from 118 300 to 203 600 person-years (an increase of 72.13%). The age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR) showed downward trends (with average annual percent changes of -0.97% and -1.13%, respectively, P<0.001). Decomposition analysis indicated that population growth and aging were the main driving forces for the increase in the absolute value of the disease burden.

Although the age-standardized burden of leukemia attributable to smoking in China showed a declining trend from 1990 to 2023, the absolute burden continued to increase under the influence of factors such as population aging, and significant sex disparities were observed. Males and older adults should be prioritized in prevention and control efforts, and tobacco control interventions should be further strengthened to curb the growing burden.

To analyze the trends of diabetes burden and Quality of Care Index (QCI) in China from 1990 to 2023.

Data on diabetes incidence, prevalence and mortality were extracted. The estimated annual percentage change (EAPC) was used to evaluate the burden trends. QCI was constructed using principal component analysis. Differences in QCI by age, sex and diabetes type were compared. Long-term temporal trends in QCI from 1990 to 2023 were further analyzed.

The total prevalence and age-standardized incidence increased significantly (EAPC=0.79%, 95%CI: 0.62%-0.97%), while age-standardized mortality decreased significantly (EAPC=-0.68%, 95%CI: -0.87%- -0.48%). Trends in type 2 diabetes mellitus (T2DM) were consistent with the overall pattern. The first principal component explained 86.0% of the total variance. QCI generally decreased with age, with no statistically significant sex difference. QCI differed significantly among type 1 diabetes mellitus (T1DM), T2DM and overall diabetes (adjusted P<0.001). During the period from 1990 to 2023, T1DM demonstrated a consistent gradual decline in QCI; in contrast, T2DM displayed an initial decline followed by a subsequent increase.

The prevalence burden of diabetes in China continues to increase, while mortality risk has decreased. Quality of care varies by diabetes type and age. Targeted optimization of diabetes care resource allocation is needed in the future, with emphasis on the extreme age groups and improvement of care quality for patients with T1DM.

To analyze the trends in disease burden of HIV/AIDS in China from 1990 to 2023 and conduct a death attribution analysis, providing evidence for refining national HIV prevention and control strategies.

Utilizing data from the Global Burden of Disease Study 2023, the age-standardized incidence rate, mortality rate and disability-adjusted life years (DALYs) rate were applied to assess the disease burden of HIV/AIDS in China. The Joinpoint regression model was used to calculate the annual percent change (APC) and average annual percent change (AAPC). The age-period-cohortmodel was applied to examine the effects of age, period, and birth cohort in disease burden. Death attribution analyses were performed for comorbidities such as tuberculosis (TB).

The age-standardized incidence rate of HIV/AIDS in China increased from 0.69 per 100 000 in 1990 to 2.36 per 100 000 in 2023, with an AAPC of 3.78%. The age-standardized mortality rate rose from 0.14 per 100 000 in 1990 to 1.65 per 100 000 in 2023, with an AAPC of 7.71%. The age-standardized DALYs rate increased from 6.81 per 100 000 in 1990 to 78.21 per 100 000 in 2023, with an AAPC of 7.70%. Age-period-cohort model analysis revealed a “bimodal” age distribution in incidence, with peaks among the 20-34 and over-70 age groups. Compared with the period 2004-2008, the risk of incidence showed a declining trend after 2008, while the risk of mortality and DALYs increased. All indicators showed higher risks in males than in females. Compared with 1955-1959 birth cohort, the highest incidence risk was observed in the 1930-1934 birth cohort, while individuals born after 1960 showed increasing risks of death and DALYs. In terms of death attribution, deaths due to other diseases caused by HIV increased from 55.38% in 1990 to 93.33% in 2023. TB-related deaths continued to decline, predominantly involving HIV-drug-susceptible tuberculosis (HIV-DS-TB), with a higher proportion among males.

From 1990 to 2023, the disease burden of HIV/AIDS in China showed an upward trend. Young adults aged 20-34 yearsandthe elderly are key priority populations. Non-tuberculosis-related-diseases have become the leading cause of death. Future prevention and control strategies in China should focus on interventions targeting sexual transmission, early detection and treatment for young adults, the elderly, and male populations, as well as enhanced surveillance and management of non-tuberculosis-related-diseases.

To investigate the prognostic value of different deep learning models constructed using integrated multi-omics data for patients with cervical squamous cell carcinoma and to compare their predictive performance.

Using preprocessed multi-omics data from the The Cancer Genome Atlas (TCGA) database for cervical squamous cell carcinoma (CESC), three prognostic prediction models—AutoSurv, DeepSurv, and Cox-nnet—were constructed. The predictive performance of the models was evaluated using the C-index, time-dependent area under the receiver operating characteristic curve (AUC), and the P-value of the log-rank test. The AutoSurv model, which demonstrated superior predictive capability, was selected for interpretability analysis using DeepSHAP to identify mRNAs and miRNAs that help distinguish high-risk from low-risk patients.

The C-index, 1-year AUC, 3-year AUC, and 5-year AUC values for the different model test sets showed that the AutoSurv model had the best predictive performance (C-index: 0.78 (95%CI: 0.75-0.81), AUC (1-year): 0.84 (95%CI: 0.81-0.87), AUC (3-year): 0.78 (95%CI: 0.76-0.85), AUC (5-year): 0.77 (95%CI: 0.75-0.81). The Log-rank test of the Kaplan-Meier survival curves indicated that the survival difference between the high- and low-risk groups classified by the AutoSurv model was statistically significant (P=0.013). The AutoSurv model outperformed the DeepSurv and Cox-nnet models in predicting the prognosis of patients with cervical squamous cell carcinoma. After quantifying the mRNAs and miRNAs that significantly influence the prediction results using DeepSHAP, multiple variables associated with the prognosis of cervical squamous cell carcinoma were identified, including POLR2H, FN1, FYN, UBA52, and RPS27A, among others, which were enriched in molecular signaling pathways such as DNA damage repair and NF-κB.

The AutoSurv model can accurately predict survival risk in CESC patients (C-index: 0.78 (95%CI: 0.75-0.81)). Combined with the DeepSHAP method, it provides valuable interpretability analysis, identifies key predictive variables influencing the prognosis of cervical squamous cell carcinoma, and reveals underlying biological mechanisms. This provides a scientific basis for clinicians to develop personalized treatment strategies and offers a research direction for targeted cancer therapy.

To investigate the efficacy of role-playing in enhancing students’ practical capabilities for responding to public health emergencies, grounded in situated learning theory.

Employing the Delphi expert consultation method (n=12), the practical course content was systematically developed. A role-playing teaching approach based on the five-act scenario play Campus Defence was implemented with 120 students from the School of Public Health at a medical university.

Experts reached high consensus on core modules such as “contingency planning” and “case reporting,” providing scientific rationale for scenario development. Quantitative analysis revealed that post-intervention scores (70.94±18.83) significantly exceeded pre-intervention scores (54.43±19.11) (t=12.52, P<0.001), with a substantial effect size (Cohen’s d=1.16). Senior students, female cohorts, and those of intermediate academic standing demonstrated particularly marked improvements.

By establishing a “community of practice,” role-playing effectively facilitated students’ construction of practical knowledge within authentic scenarios. This approach provides theoretical support and a replicable pathway for bridging the knowledge-practice gap in public health education.