ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Objective: To investigate the association between medium to long term PM 2.5 exposure around school areas and overweight/obesity among primary and secondary school students in Guangxi, providing data support and theoretical foundations for scientifically addressing overweight and obesity in primary and secondary school students. Methods: From September to November 2023, a stratified cluster random sampling method was employed to select 251 183 students aged 7-18 years (grade 1 to grade 12) from 14 prefecture level cities (111 districts and counties) in Guangxi. PM 2.5 mass concentration data were obtained from the Tracking Air Pollution in China (TAP) dataset. Preliminary comparative analysis was conducted using the Mann-Whitney U test, while binary Logistic regression models were applied to quantify the relationship between PM 2.5 exposure and overweight/obesity. Restricted cubic spline analysis was further utilized to examine the nonlinear association between PM 2.5 concentration and overweight/obesity risk. Results: The detection rate of overweight/obesity among Guangxi students in 2023 was 19.5%. The median PM 2.5 concentration in the year prior to the study was higher in the overweight/obesity group (23.22 μg/m 3) compared to the non overweight/obesity group (22.63 μg/m 3) ( Z=-15.66, P <0.01), and consistent trends were observed across gender (male/female) and educational stage (primary/junior/senior high school) subgroups (all P <0.01). Binary Logistic regression revealed that for every 10 μg/m 3 increase in the annual average PM 2.5 concentration, the risk of overweight/obesity increased by 12% ( OR=1.12, 95%CI=1.09- 1.15 , P <0.01). Restricted cubic spline analysis indicated a nonlinear relationship between monthly PM 2.5 levels and overweight/obesity risk ( P trend <0.01). Below 22.68 μg/m 3, PM 2.5 exposure showed no significant association with obesity risk; above the threshold, the risk increased with rising PM 2.5 levels. Conclusion Medium to long term PM 2.5 exposure around school environments is significantly associated with overweight/obesity among primary and secondary school students.

In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To develop a machine learning-based risk prediction model for postoperative acute kidney injury(AKI)and a model for mortality in obese patients admitted to intensive care unit(ICU)in order to improve early warning and prognostic evaluation to support clinical decision-making.Methods Data of obese postoperative ICU patients were retrospectively retrieved from the MIMIC-Ⅳ and eICU databases for statistical analysis.Ultimately,2 520 patients(670 from MIMIC-Ⅳ and 1 850 from eICU databases)were included to build the risk prediction models for AKI and mortality.The data included demographic information,vital signs,laboratory findings,surgical types,comorbidities,and medication use.After data cleaning and preprocessing,Boruta feature selection was applied,followed by the construction of prediction models using 7 machine learning algorithms,that is,Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),k-Nearest Neighbors(KNN),Na?ve Bayes(NB),Neural Network(NNET),Support Vector Machine(SVM),and XGBoost.Model performance was evaluated through cross-validation and external validation.Results In the risk prediction models of AKI,the SVM model achieved the highest AUC value of 0.80 in the testing set and 0.71 in the external validation test.For the risk prediction models of mortality,the GBM model outperformed others in the prediction,attaining an AUC value of 0.91 in the testing set.Conclusion Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed,and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients.

Objective To discuss the curative effect of hepatic arterial infusion chemotherapy(HAIC)combined with programmed death receptor-1(PD-1)inhibitors and anti-angiogenesis therapy for BCLC stage C hepatocellular carcinoma(HCC).Methods The patients with HCC of BCLC stage C,who received HAIC combined with PD-1 inhibitors and anti-angiogenesis therapy at the First Affiliated Hospital of Soochow University of China from January 2021 to December 2023,were collected for this study.The time from the start of treatment to complete remission(CR)of disease,the dynamic changes in alpha-fetoprotein(AFP)levels and the recurrence during follow-up period were analyzed.The relevant literature of the above triple regimen for HCC was searched from PubMed database and its curative effect was analyzed.Results Of the 214 HCC patients treated with triple therapy regimen,9(4.2％)achieved CR.The time from the start of treatment to CR was 2-10 months.The patients were followed up for 5-20 months.The time of AFP level returning to normal value was from 79 to 259 days.One patient developed recurrence 10 months after CR,and the other 8 patients maintained the CR status.A total of 12 articles were retrieved,the reported CR rates ranged from 0 to 16.5％.Conclusion A CR can be achieved in a few patients with advanced HCC treated with HAIC combined with PD-1 inhibitors and anti-angiogenesis therapy.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

The antidepressant activity and molecular mechanisms of Yueju Wan volatile oil were investigated. The Yueju Wan volatile oil was extracted by using supercritical CO_2. Gas chromatography-mass spectrometry(GC-MS) combined with network pharmacology identified 28 chemical constituents in Yueju Wan volatile oil, primarily terpenes and lactones. A total of 123 overlapping targets were associated with depression, including core targets of interleukin-1β(IL-1β), signal transducer and activator of transcription 3(STAT3), and caspase-3(CASP3). These targets were mainly involved in the prolactin, advanced glycation end products/receptor(AGE/RAGE), and phosphoinositide 3-kinase/protein kinase B(PI3K/Akt) signaling pathways. A reserpine-induced depression mouse model was established to evaluate the therapeutic effects and mechanisms of Yueju Wan volatile oil. The effects of Yueju Wan volatile oil on depression-like behavior in mice were evaluated by analyzing body mass, body temperature index, tail suspension immobility time, forced swimming immobility time, and sucrose preference. Hematoxylin-eosin(HE) staining revealed neuronal protection of Yueju Wan volatile oil in the brain of mice. Enzyme-linked immunosorbent assay(ELISA) and Western blot were employed to detect the protein expression of AGEs, IL-1β, phosphorylated PI3K(p-PI3K), Akt, phosphorylated Akt(p-Akt), nuclear factor κB(NF-κB), and brain-derived neurotrophic factor(BDNF). Behavioral evaluation showed that Yueju Wan volatile oil could effectively control the decline of body mass and body temperature of depressed mice, reduce tail suspension and swimming immobility time, and enhance their preference for sucrose. Histopathological examination showed that Yueju Wan volatile oil could alleviate the neuronal damage in CA1 and dentate gyrus(DG) of the hippocampus of mice. ELISA and Western blot results showed that Yueju Wan volatile oil could significantly increase the protein expression levels of PI3K, Akt, and BDNF and significantly decrease the protein expression levels of AGEs, IL-1β, p-PI3K, p-Akt, and NF-κB in the hippocampus of mice. Furthermore, the p-PI3K/PI3K and p-Akt/Akt ratios were significantly decreased at medium and high doses. These findings suggest that the aromatherapy of Yueju Wan volatile oil can significantly improve reserpine-induced depression-like behavior in mice, which may be related to reducing the expression of neuronal membrane protein AGEs, reducing the phosphorylation levels of PI3K and Akt, inhibiting NF-κB entry into the nucleus, and alleviating the release of pro-inflammatory factors and nerve injury.
Animals ; Antidepressive Agents/chemistry* ; Mice ; Proto-Oncogene Proteins c-akt/immunology* ; Phosphatidylinositol 3-Kinases/immunology* ; Oils, Volatile/chemistry* ; Male ; Drugs, Chinese Herbal/chemistry* ; Signal Transduction/drug effects* ; Depression/metabolism* ; Glycation End Products, Advanced/immunology* ; Humans

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*