ObjectiveTo systematically assess the public health governance capacity in Zhejiang Province, to conduct an in-depth analysis of its strengths and weaknesses, so as to provide scientific basis and strategic recommendations for further enhancement. MethodsA systematic collection of policy documents, public information reports, and research literature related to public health governance capacity in Zhejiang Province from 2002 to 2023 was conducted (encompassing a total of 1 263 policy documents, 138 pieces of information reports and 631 research articles). Based on the evaluation criteria suitable for public health systems previously developed by the research team, the basic status and magnitude of change in public health governance capacity in Zhejiang Province was evaluated. Additionally, normative gap analyses were employed to identify the strengths and weaknesses. ResultsZhejiang Province ranked 4th nationwide in terms of public health governance capacity with a score of 733.4 points (1 000.0-point maximum). The province has effectively implemented the principle of health first (scoring 698.5 points in the assessment of health-first strategy implementation) and attached sufficient importance to health-related goals (scoring 658.2 points in the scientific rationality of goal setting). However, the implementation of inter-departmental coordination and incentive mechanisms only scored 178.7 points, the feasibility of management and monitoring mechanisms scored even lower at only 144.0 points, and the coverage of incentive mechanisms scored 286.0 points. ConclusionZhejiang Province has effectively implemented its health first strategy and attached great importance to health targets, but still needs to strengthen cross-departmental coordination mechanisms and health-oriented incentives.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Objective: To analyze the implementation status and challenges of sex education in special education schools, so as to provide a scientific basis for formulating effective promotion strategies. Methods: From November 2023 to January 2024, a census survey was conducted among 120 in service teachers from 7 special education schools in Luzhou. The questionnaire covered the current status of sex education in schools, teachers attitudes and knowledge toward sex education, and their coping methods for students inappropriate sexual behaviors. Results: About 77.5% of teachers reported having provided sex education to students, but 93.2% indicated a lack of specialized sex education textbooks for special children, 90.4% reported no full time teachers for sex education, and the methods of sex education were relatively limited (50.0% mainly based on lecture method). Nearly 95.8% of teachers held a positive attitude toward sex education, with 98.3% supporting its implementation. Only 26.7% of teachers demonstrated a good grasp of sex education knowledge, with the best understood topic being "recognition and protection of private parts" (21.6%). When dealing with students inappropriate sexual behaviors, the active response rate of teachers was 23.9%, with the highest active response rate observed for "intentionally hugging or kissing the opposite sex" (39.7%). Conclusions The special education schools in Luzhou lack comprehensive sex education curricula, teaching materials and full time teachers, sufficient knowledge among teachers, and adequate proactive responses to students inappropriate sexual behaviors. Greater emphasis should be placed on sex education for special children, including the training of dedicated teachers, to provide comprehensive and high quality sex education services for special children.

ObjectiveTo systematically evaluate the public health governance capacity of 40 cities in Jiangsu, Zhejiang, and Anhui Provinces, providing a scientific evaluation basis for building a "Healthy Yangtze River Delta". MethodsA comprehensive collection of policy documents, public information reports, and research literature related to public health governance capacity in Jiangsu, Zhejiang, and Anhui Provinces was conducted, totaling 6 920 policy documents, 1 720 information reports, and 1 200 literature pieces. Based on the evaluation standards for an appropriate public health system established by the research team, the basic status of public health governance capacity was assessed to identify the strengths and weaknesses of the 40 cities. ResultsIn 2022, the public health governance capacity score for the 40 cities in Jiangsu, Zhejiang, and Anhui Provinces was (562.5±38.0) points. In terms of specific areas, the emergency response field received the highest score of (791.4±49.7) points, while the chronic disease prevention and control field received the lowest score of (368.2±29.6) points. The Jiangsu-Zhejiang-Anhui region has largely achieved the strategic priority of health, gradually improved public health legal regulations, and established a basic organizational framework with a solid foundation for information and data infrastructure. However, challenges still need to be addressed, such as unstable government funding for public health, unclear departmental responsibilities, and barriers to information interoperability. ConclusionThe public health governance capacity of the 40 cities in Jiangsu, Zhejiang, and Anhui Province has been at a moderate level, but disparities have still existed across regions and fields. In the future, while continuing to deepen existing advantages, it is essential to accurately identify the causes of problems, establish a long-term and stable investment mechanism, enhance information connectivity mechanisms, further clarify departmental responsibilities, and promote the achievement of the "Healthy Yangtze River Delta" goal.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

Metabolic reprogramming plays a central role in tumors. However, the key drivers modulating reprogramming of gluconeogenesis/lipogenesis are poorly understood. Here, we try to identify the mechanism by which histone acetyltransferase 1 (HAT1) confers reprogramming of gluconeogenesis/lipogenesis in liver cancer. Diethylnitrosamine (DEN)/carbon tetrachloride (CCl₄)-induced hepatocarcinogenesis was hardly observed in HAT1-knockout mice. Multi-omics identified that HAT1 modulated gluconeogenesis and lipogenesis in liver. Protein phosphatase 2 scaffold subunit alpha (PPP2R1A) promoted gluconeogenesis and inhibited lipogenesis by phosphoenolpyruvate carboxykinase 1 (PCK1) serine 90 dephosphorylation to suppress the tumor growth. HAT1 succinylated PPP2R1A at lysine 541 (K541) to block the assembly of protein phosphatase 2A (PP2A) holoenzyme and interaction with PCK1, resulting in the depression of dephosphorylation of PCK1. HAT1-succinylated PPP2R1A contributed to the remodeling of gluconeogenesis/lipogenesis by PCK1 serine 90 phosphorylation, leading to the inhibition of gluconeogenic enzyme activity and activating sterol regulatory element-binding protein 1 (SREBP1) nuclear accumulation-induced lipogenesis gene expression, which enhanced the tumor growth. In conclusion, succinylation of PPP2R1A lysine 541 by HAT1 converses the role in modulation of gluconeogenesis/lipogenesis remodeling through PCK1 S90 phosphorylation to support liver cancer. Our finding provides new insights into the mechanism by which post-translational modifications (PTMs) confer the conversion of tumor suppressor function to oncogene.

OBJECTIVES: To compare the anti-inflammatory, antibacterial and analgesic effects of Yinqiao Powder (YQS) formulated granules and decoction. METHODS: We first evaluated the anti-inflammatory effects of the two dosage forms of YQS in a LPS-induced RAW 264.7 cell model using RT-qPCR and Western blotting. We further constructed zebrafish models of inflammation by copper sulfate exposure, caudal fin transection, or LPS and Poly (I:C) microinjection, and evaluated anti-inflammatory effects of YQS granules and decoction by examining neutrophil aggregation and HE staining findings. In a mouse model of acute lung injury (ALI) induced by intratracheal LPS instillation, the effects of YQS gavage at 10, 15, and 20 g/kg on lung pathologies were evaluated by calculating lung wet-dry weight ratio and using HE staining, ELISA and Western blotting. The microbroth dilution method was used to evaluate the antibacterial effect of YQS. Mouse pain models established by hot plate and intraperitoneal injection of glacial acetic acid were used to evaluate the analgesic effects of YQS at 10, 15, and 20 g/kg. RESULTS: Both YQS granules and decoction significantly reduced TNF-α, IL-6, and IL-1β expressions and p-STAT3 (Tyr 705) phosphorylation level in LPS-induced RAW 264.7 cells, and obviously inhibited neutrophil aggregation in the zebrafish models. In ALI mice, YQS granules and decoction effectively ameliorated lung injury, lowered lung wet-dry weight ratio, and reduced p-STAT3 (Tyr 705) expression and TNF-α and IL-6 levels. YQS produced obvious antibacterial effect at the doses of 15.63 and 31.25 mg/mL, and significantly reduced body torsion and increased pain threshold in the mouse pain models. CONCLUSIONS The two dosage forms of TQS have similar anti-inflammatory, antibacterial and analgesic effects with only differences in their inhibitory effect on TNF-α, IL-6 and IL-1β mRNA expressions in LPS-induced RAW 264.7 cells.
Animals ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Anti-Inflammatory Agents/pharmacology* ; Analgesics/pharmacology* ; RAW 264.7 Cells ; Zebrafish ; Anti-Bacterial Agents/pharmacology* ; Powders ; Tumor Necrosis Factor-alpha/metabolism* ; Acute Lung Injury/drug therapy* ; Interleukin-6/metabolism* ; Lipopolysaccharides

OBJECTIVES: To explore the effects of exogenous trigger (hCG/GnRHa) versus endogenous LH surge in natural cycle IVF/ICSI (NC-IVF/ICSI) for patients with diminished ovarian reserve (DOR). METHODS: A retrospective analysis was conducted on 1,118 NC-IVF/ICSI cycles from two reproductive centers between 2013 and 2024. Propensity score matching (PSM) and multivariate logistic regression were used to adjust for confounding factors. The trigger-day hormone threshold was determined using receiver operating characteristic (ROC) curve analysis. Outcome measures included oocyte retrieval rate, 2PN fertilization rate, clinical available embryo rate, high-quality embryo rate, fresh cycle clinical pregnancy rate (CPR), and live birth rate (LBR). RESULTS: After adjusting for confounders via PSM and logistic regression, the exogenous trigger group demonstrated significantly better outcomes across all the evaluated parameters (oocyte retrieval rate, 2PN fertilization rate, transferable embryo rate, high-quality embryo rate, fresh cycle CPR, and LBR) than the endogenous LH surge group (P<0.05). Age-stratified analysis revealed that for the entire cohort, exogenous triggering significantly increased the number of transferable embryos and high-quality embryos (P<0.001). In the 35-39 years old subgroup, exogenous triggering showed significant advantages in oocyte yield, high-quality embryo rate, CPR, and LBR (P<0.05) and resulted in the most pronounced improvement in LBR (OR=6.25, 95% CI: 1.34-29.23). ROC analysis established a decision-day LH threshold of 19.055 mIU/mL (AUC=0.945, specificity=93.3%) for precise stratification of the clinical pathways. CONCLUSIONS For DOR patients undergoing NC-IVF/ICSI, exogenous triggering comprehensively improves the treatment outcomes, particularly providing significant live birth benefits for women aged 35-40 years. An individualized protocol incorporating the LH threshold (19.055 mIU/mL) effectively enhances embryonic developmental potential and live birth rates.
Humans ; Female ; Ovarian Reserve ; Pregnancy ; Propensity Score ; Retrospective Studies ; Fertilization in Vitro ; Sperm Injections, Intracytoplasmic ; Chorionic Gonadotropin ; Pregnancy Rate ; Logistic Models ; Ovulation Induction/methods* ; Gonadotropin-Releasing Hormone ; Adult ; Oocyte Retrieval

This report presents a case of a 9-year-old child with a complicated crown-root fracture of the maxillary central incisor, accompanied with a root fracture. The treatment strategy was minimally invasive, focusing on vital pulp preservation, root fracture recovery, and crown restoration. The fractured crown was reattached using resin short posts to enhance retention, resulting in aesthetic and functional restoration of the anterior teeth. A 2-year follow-up revealed favorable clinical and radiographic outcomes.
Humans ; Child ; Tooth Fractures/therapy* ; Tooth Root/injuries* ; Incisor/injuries* ; Tooth Crown/injuries* ; Post and Core Technique ; Dental Restoration, Permanent/methods* ; Maxilla

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surgical intervention remains the primary treatment option for early-stage lung cancer, and video-assisted thoracoscopic surgery (VATS) has become a common approach due to its minimal invasiveness and rapid recovery. However, post-discharge recovery remains incomplete, underscoring the importance of postoperative care. Traditional follow-up methods, lack standardization, consume significant medical resources, and increase the burden of the patients. Artificial intelligence (AI)-driven disease management platforms offer a novel solution to optimize postoperative follow-up. This study followed 463 lung cancer surgery patients using an AI-based platform, aiming to identify common postoperative issues, propose solutions, improve quality of life, reduce recurrence-related costs, and promote AI integration in healthcare. METHODS: Using the AI disease management platform, this study integrated educational videos, collaboration between healthcare teams and AI assistants, daily health logs, health assessment forms, and personalized interventions to monitor postoperative recovery. The postoperative rehabilitation status of the patients was assessed by the Leicester Cough Questionnaire (LCQ-MC). Two independent t-test and one-way ANOVA were used to analyze the causes of postoperative cough in lung cancer. RESULTS: Most issues occurred within 7 d post-discharge, significantly declined on 14 d post-discharge. Factors such as gender, smoking history, and surgical approaches were found to influence cough recovery. The incidence of cough on 7 d post-discharge in females was higher than that in males (P<0.01), while the incidence of cough on 14 d post-discharge in elderly patients was lower than that in young patients (P=0.03). The AI-based platform effectively addressed cough, pain, and sleep disturbances through phased interventions. CONCLUSIONS The AI-based platform significantly enhanced postoperative management efficiency and the self-care capabilities of the patients, particularly in phased cough management. Future integration with wearable devices could enable more precise and personalized postoperative care, further advancing the application of AI technology across multidisciplinary healthcare domains.
Humans ; Lung Neoplasms/rehabilitation* ; Male ; Female ; Middle Aged ; Aged ; Patient Discharge ; Artificial Intelligence ; Adult ; Postoperative Care ; Postoperative Period ; Disease Management ; Quality of Life