ObjectiveTo observe the effects of Yangjing Zhongyutang （YJZYT） on mitochondrial biogenesis and oxidative stress damage mediated by the silent information regulator 1 （SIRT1）/peroxisome proliferator-activated receptor gamma coactivator-1alpha （PGC-1α） signaling pathway in cyclophosphamide （CTX）-induced rats with diminished ovarian reserve （DOR）， and to explore its mechanism in improving ovarian reserve function and follicular development. MethodsForty-two 8-week-old female SD rats with normal estrous cycles were randomly divided into a blank control group （n=7） and a model group （n=35）. Rats in the model group received a single intraperitoneal injection of CTX （90 mg·kg^-1） to establish the DOR model. After modeling， estrous cycles were monitored for 7 consecutive days， and model success was confirmed based on criteria for estrous cycle disruption. After successful modeling， rats were divided into groups for intervention： estradiol valerate group （0.09 mg·kg^-1）， and YJZYT high-， medium-， and low-dose groups （19.98， 9.99， 5.00 g·kg^-1）. The blank control group and model group were given an equal volume of distilled water by gavage. All groups received daily gavage once for 4 consecutive weeks. The general state， body weight， and ovarian wet weight of rats were observed and recorded， and the ovarian organ index was calculated. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， estradiol （E₂）， anti-Müllerian hormone （AMH）， superoxide dismutase （SOD）， and glutathione peroxidase （GSH-Px）. Hematoxylin-eosin （HE） staining was performed to observe ovarian histomorphological changes and follicular development status. Immunofluorescence was used to detect reactive oxygen species （ROS） expression levels. Colorimetric assays were employed to measure adenosine triphosphate （ATP） and malondialdehyde （MDA） content in ovarian tissues. Quantitative Real-time polymerase chain reaction （Real-time PCR） was used to detect mitochondrial DNA （mtDNA） copy number and the mRNA expression levels of key genes including SIRT1， PGC-1α， nuclear respiratory factor 1 （NRF1）， and mitochondrial transcription factor A （TFAM）. Western blot was performed to detect the protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM. ResultsCompared with the blank group， rats in the model group exhibited disrupted estrous cycles， obviously reduced body weight， and decreased ovarian index （P<0.05）. Ovarian histopathology revealed cortical thinning， loose structure， and a significant reduction in both primordial and growing follicles （P<0.01）. Serum FSH and LH levels were significantly elevated （P<0.01）， while E₂ and AMH levels were obviously reduced （P<0.05， P<0.01）. ATP content and mtDNA copy number decreased in ovarian tissue （P<0.01）， ROS expression increased， MDA levels rose， while SOD and GSH-Px activities obviously decreased （P<0.05， P<0.01）， mRNA and protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM were obviously downregulated （P<0.05， P<0.01）. After treatment， compared with the model group， body weight and ovarian index obviously recovered in rats administered various doses of YJZYT （P<0.05）， serum E₂ and AMH levels increased， while FSH and LH levels obviously decreased （P<0.05， P<0.01）， ovarian tissue ATP content and mtDNA copy number were up-regulated， ROS and MDA levels decreased， and antioxidant enzymes SOD and GSH-Px activity obviously increased （P<0.05， P<0.01）， Gene and protein expression levels related to the SIRT1/PGC-1α /NRF1/TFAM signaling pathway were obviously up-regulated compared to the model group （P<0.05， P<0.01）， HE staining revealed that ovarian structure gradually recovered to integrity in all treatment groups， with a obviously increase in the number of primordial and growing follicles （P<0.05， P<0.01）. Granulosa cells were neatly arranged， indicating marked improvement in ovarian function. ConclusionYJZYT may improve ovarian function and follicular development in rats with diminished ovarian reserve by activating the SIRT1/PGC-1α signaling pathway， promoting mitochondrial biogenesis， enhancing mitochondrial function， and alleviating oxidative stress damage.

Objective: To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents. Methods: A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model. Results: The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05). Conclusion The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.

Sanhuang Xiexintang （SHXXT）， originating from the Synopsis of the Golden Chamber （Jin Gui Yao Lue）， comprises three medicinal herbs： Rhei Radix et Rhizoma， Coptidis Rhizoma， and Scutellariae Radix. Renowned for its effects of purging fire， detoxifying， drying dampness， and draining heat， SHXXT primarily treats syndromes characterized by internal excess heat， dampness-heat stagnation， and reckless blood movement due to heat. Because of the concise formulation and remarkable efficacy of this formula， modern research has extensively explored the chemical composition， clinical applications， and pharmacological mechanisms of SHXXT， yielding significant advancements. As a modern derivative of SHXXT， Yiqing granules exemplify the transformation of classical formulas into convenient and precise applications， embodying the paradigm of modern development of classical formulas. This systematic review synthesizes recent research progress in SHXXT. Chemical analyses reveal that the active components—anthraquinones， alkaloids， and flavonoids—of SHXXT exert holistic therapeutic effects through multi-component synergy. Clinical studies demonstrate broad utility of this formula in managing digestive disorders， endocrine diseases， urinary tract infections， dermatological conditions， and systemic inflammatory diseases， highlighting its multi-system regulatory potential. Mechanism investigations elucidate its multi-target mechanism of action， including antimicrobial， anti-inflammatory， metabolic-regulatory， hepatoprotective， and gastrointestinal-modulating effects， reflecting an integrated multi-component， multi-target， multi-pathway mode of action. This review systematically summarizes the modern research progress in SHXXT， providing a theoretical foundation for deciphering the scientific essence of classical formulas and advancing their precision application in clinical practice.

Abstract To clarify the service targets, service contents, and safeguard mechanisms of the basic public service program for student vision health management, the study grounded in the current status of child and adolescent myopia prevention and control in China and integrated with the practical experience and innovative practices of Wuhan National Demonstration Area for Student Vision Health Management, takes education as the main thread and schools as the base, consolidating resources from multiple stakeholders including education administrative departments, schools, families, and professional technical service institutions. Centering on four core components—vision health education, monitoring and record keeping, risk prevention and control, and dynamic management, the study constructs a multi tiered basic public service system for vision health management of primary and secondary school students. It further proposes the use of an intelligent management platform and a "three tier color coded early warning" mechanism (red, yellow, blue) to prevent and control student myopia at the source, providing schools with replicable and operable implementation pathways to enhance the level of student vision health management.

Objective: To assess the status of sexual behaviors, HIV/AIDS knowledge awareness, and novel synthetic drug use among school attending young students in Guangdong Province, so as to provide evidence base for formulating targeted intervention strategies. Methods: From September to December 2024, a convenience sampling method was employed to conduct an anonymous online survey among 41 119 students from 20 higher education institutions and vocational colleges in Guangdong Province. Chi square test was utilized for rate comparisons and univariate analysis, and a multivariate Logistic regression model was applied to analyze factors associated with novel synthetic drug use. Results: The self reported rate of sexual behavior was 5.2%. Among sexually active students, the rates of unprotected sexual intercourse, having temporary sexual partners, and having commercial sexual partners were 32.4%, 34.5%, and 26.3%, respectively. The awareness rate of HIV related knowledge was 75.7%. The overall use rate of novel psychoactive substances(NPS) was 1.0%, and among sexually active students it was 6.5%. Multivariate Logistic regression analysis showed that students with sexual experience ( OR =4.15) and those with HIV testing history ( OR =9.38) had higher risks of NPS use; among sexually active students, those with unprotected sexual intercourse ( OR =6.83) and those with commercial sexual partners ( OR = 4.68 ) had higher risks of NPS use (all P <0.05). Conclusions The HIV/AIDS knowledge level among surveyed students needs further improvement, and high risk sexual behaviors are cross linked with novel synthetic drug use. It is recommended to carry out integrated health education for all students and implement comprehensive targeted interventions for sexually active students.

Objective To introduce the calculation of the DISO index in multi-dimensional data ranking for disease surveillance, and evaluate its applicability. Methods Using the data from the quality supervision and inspection of infectious disease reporting in Jingzhou City in a certain year as an example, the DISO index was used to rank 16 investigated medical institutions and compared with the TOPSIS method. The consistency between the two evaluation results was analyzed using Spearman correlation. Then, The DISO index from different medical institutions was used to evaluate the ranking of 8 counties (cities, districts). The evaluation indicators for the supervision and inspection included six items: report rate, timely report rate, completeness of report card filling, accuracy of report card filling, consistency rate with network information report, and completeness of valid ID number filling. Results Among the 16 medical institutions, 8 institutions had all six evaluation indicators at 100%. Using the two methods to rank the 16 medical institutions, the two methods showed that the 8 medical institutions with all six evaluation indicators at 100% were ranked first. There was a strong correlation between the rankings of the 16 medical institutions using the two methods (r_s=0.992, P=0.000). The three counties (cities, districts) with all six evaluation indicators at 100% were all ranked first, while country G was ranked seventh and country E was ranked eighth. Conclusion The results of the DISO index and the TOPSIS method were similar in one-dimensional ranking. DISO can be used for multi-dimensional ranking of disease surveillance data and deserves to be promoted and applied.

Objective: To understand the prevalence and related factors of depressive symptoms among primary and secondary school students in the in depth monitoring counties of China s Rural Compulsory Education Nutrition Improvement Program, so as to provide a basis for prevention and psychological intervention of depressive symptoms among children and adolescents in rural areas. Methods: In November 2022, a stratified random sampling method was adopted to collect height and weight data, basic personal and family information of 7 949 primary and secondary school students from grade three to grade nine through physical measurements and questionnaires in 56 key monitoring schools implementing the Student Nutrition Improvement Program in 7 in depth monitoring counties (Jalaid Banner in Inner Mongolia, Jinzhai County in Anhui, Mao Xian in Sichuan, Tiandeng County in Guangxi, Mian County in Shaanxi, Zhaozhou County in Heilongjiang and Youxi County in Fujian), and to obtain the information related to their depressive symptoms through the self assessment questionnaire on depression. Multivariate Logistic regression analysis was conducted to analyze the prevalence of depressive symptoms among primary and secondary school students, as well as their related factors. Results: The detection rate of depressive symptoms among primary and secondary school students in the in depth monitored counties was 23.5%. Logistic regression analysis showed that the probability of detecting depressive symptoms was higher among female students, middle school students, students whose video screen duration per day was >2 h, and students whose parents marital status was divorced or widowed ( OR =1.40, 1.64, 1.60, 1.24), and students whose sleep duration reached the recommended standard, whose parents usually accompanied them daily for time was 60-<120 min and ≥120 min, and students whose mothers literacy level was middle school graduation had lower probability of detecting depressive symptoms ( OR =0.85, 0.84, 0.71, 0.76) ( P < 0.05 ). Conclusion The detection rate of depressive symptoms among students in the in depth monitoring area is high, and targeted interventions need to be developed for students to reduce the risk of mental health problems.

ObjectiveTo investigate the status of tooth loss in people aged 50 and above, so as to understand their oral health status and provide scientific evidences for promoting oral health of middle-aged and elderly people. MethodsA total of 400 patients who visited the department of stomatology at Sijing Hospital in Songjiang District of Shanghai were performed oral health examinations and their information was collected according to the national epidemiological survey standards for oral health. ResultsThere were statistically significant differences in tooth loss among people aged 50 and above with different ages, educational levels, occupations, types of medical insurance and chronic diseases (P<0.05), but gender and monthly income had no statistically significant correlations with tooth loss (P>0.05). Among lifestyle factors, smoking, alcohol consumption and tea drinking had no statistically significant impacts on the number of remaining teeth (P>0.05), but toothbrushing frequency, flossing frequency, toothpick use frequency, toothbrush replacement frequency, and tooth loosening were statistically associated with the number of remaining teeth (P<0.05). Multiple linear regression analyses indicated that a total of 7 related factors including age, educational level, occupation, medical payment type, chronic disease, tooth loosening and toothpick use frequency were significantly associated with the number level of remaining teeth in individuals aged 50 and above. ConclusionAge, chronic disease, and tooth loosening were influencing factors affecting the number of teeth left in people aged 50 and above. It is recommended to strengthen oral health education and improve healthcare awareness to reduce the risk of tooth loss in people aged 50 and above.

Diabetic neuropathy(DN)is a prevalent chronic complication of diabetes,characterized by a com-plex pathogenesis involving various cell types and molecular pathways.Research indicates that microglia,serving as the innate immune cells of the central nervous system,are pivotal in the development of DN.In recent years,with the in-depth understanding of the pathogenesis of DN,targeting microglia polarization has become a new research hotspot.This article provides an overview of current research on the regulatory mechanisms of microglia polarization,the impact of mi-croglia polarization on DN,and treatment strategies that target microglia polarization to improve DN.The objective is to elucidate the pivotal role of microglia in the pathogenesis of DN,and assess the efficacy and constraints of existing and emerging treatment methods targeting microglia,in order to offer a fresh perspective for future research and clinical treat-ment of DN.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.