This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

Diabetic sarcopenia (DS) is a common but often ignored skeletal muscle complication in individuals with diabetes mellitus. It is characterized by progressive loss of skeletal muscle mass, reduced muscle strength, and impaired physical performance, which may further increase the risk of falls, disabilities, metabolic disorders, and adverse clinical outcomes. Traditionally, DS has been attributed mainly to hyperglycemia, insulin resistance, aging-related muscle decline, and chronic complications of diabetes. However, increasing evidence suggests that lipid metabolic disturbance and pathological lipid metabolic reprogramming are not merely secondary consequences of diabetes, but may actively participate in the initiation and progression of DS. Under diabetic conditions, impaired fatty acid uptake, transport, oxidation, and storage disrupt skeletal muscle metabolic homeostasis, leading to ectopic lipid deposition and accumulation of lipotoxic intermediates. These lipid-derived metabolites can aggravate insulin resistance, impair mitochondrial energy production, enhance oxidative stress, activate chronic low-grade inflammation, and disturb protein synthesis and degradation balance, thereby accelerating skeletal muscle atrophy and functional decline. Lipid metabolic dysregulation may also interact with multiple pathological processes involved in DS, including mitochondrial dysfunction, inflammatory signaling, oxidative damage, impaired autophagy, and gut microbiota imbalance. These mechanisms do not occur independently; instead, they form a complex bidirectional vicious cycle with diabetes-related metabolic disorders. Specifically, mitochondrial dysfunction reduces fatty acid oxidative capacity, which further promotes lipid accumulation and lipotoxicity. Inflammatory activation can impair insulin signaling and muscle protein metabolism, while lipid overload may in turn amplify inflammatory responses. Similarly, gut microbiota dysbiosis and altered microbial metabolites may influence systemic inflammation, lipid metabolism, and skeletal muscle homeostasis. Therefore, lipid metabolic reprogramming provides an important mechanistic perspective for understanding the progression of DS from metabolic disturbance to structural and functional muscle impairment. Exercise intervention is an effective and clinically feasible non-pharmacological strategy for the prevention and management of DS. Both aerobic exercise and resistance training have been shown to improve insulin sensitivity, enhance fatty acid oxidation, increase mitochondrial biogenesis, reduce ectopic lipid deposition, and attenuate lipotoxic metabolite accumulation. These adaptations not only improved glucose and lipid metabolism, but also increased the preservation of muscle mass, muscle strength, and physical function. Moreover, combined exercise strategies may provide complementary benefits by integrating the metabolic advantages of aerobic exercise with the anabolic and functional effects of resistance training. Based on analyses of publicly available datasets and literature evidences, this review systematically summarizes the role of lipid metabolic disorders in the pathogenesis of DS, with particular attention to the molecular mechanisms linking lipid dysregulation to insulin resistance, chronic inflammation, oxidative stress, mitochondrial dysfunction, and gut microbiota disturbance. Furthermore, this review discusses the potential mechanisms by which exercise intervention improves DS through the regulation of lipid metabolic reprogramming, and outlines exercise prescription strategies in terms of modality, intensity, frequency, and duration. Understanding the interaction between lipid metabolism and skeletal muscle dysfunction may provide new theoretical evidence for early identification, mechanistic research, and precision exercise therapy in DS. Overall, targeting pathological lipid metabolic reprogramming through exercise intervention represents a promising and clinically actionable approach for improving muscle health and prognosis in individuals with DS.

Objective: To explore the influencing factors of incident caries at age 5 among caries-free 3-year-old children in Beijing, construct a machine learning prediction model based on oral health behavioral data, and provide a scientific basis and practical tool for early risk identification, stratified prevention and control, and home-kindergarten-medical collaborative intervention of incident dental caries in preschool children. Methods: This study has been reviewed and approved by the Medical Ethics Committee, and written informed consent was obtained from the guardians of the study participants and their guardians. Children with complete baseline data at age 3 and follow-up data at age 5 from Beijing public oral health programs were included. Oral examinations were conducted according to World Health Organization diagnostic criteria, and questionnaires were completed by guardians. Risk factors were screened by Logistic regression. The total sample was randomly divided into a test set (20%) and a validation set (80%). Five-fold cross-validation was performed on the validation set for model training and tuning, and the final model performance was evaluated on the test set. Four machine learning models—decision tree, random forest, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)—were constructed. Model performance was evaluated using the area under the curve (AUC), accuracy, and specificity. Shapley Additive Explanations (SHAP) was used for model interpretation. Results: The incidence of incident caries for 3 372 5-year-old children in Beijing was 50.96%. Multivariate logistic regression showed that parental caries, sleeping with milk, frequent feeding at night, no postprandial cleaning, high sugar intake, insufficient bedtime tooth brushing, and non-fluoride toothpaste use were significant risk factors (P < 0.05). Although all four machine learning models performed well, the XGBoost model performed the best (AUC = 0.806). Feature importance and SHAP analysis indicated that the frequency of bedtime tooth brushing, the frequency of candy consumption, and parental caries status were the top three predictors. Conclusion The XGBoost model based on oral health behaviors at age 3 can accurately predict the risk of incident caries in 5-year-old children in Beijing. Bedtime tooth brushing, sugar control, and parental oral health management are key points for caries prevention in preschool children.

ObjectiveTo explore the association between metabolic score for visceral fat（METS-VF） and cardiometabolic multimorbidity（CMM） as well as cognitive function in the elderly population， revealing the role of METS-VF as an assessment tool in this population， and providing evidence and new perspectives for the early screening and intervention strategies of CMM and cognitive function. MethodsThis study is based on cross-sectional data from the Hubei memory and aging cohort study（HMACS）， which includes elderly individuals aged 60 and above. The METS-VF index was calculated and divided into quartiles（Q1-Q4）. CMM was assessed through a questionnaire， defining CMM as the coexistence of at least two of the following conditions： diabetes， heart disease， and stroke. Standardized cognitive tests were used to evaluate overall cognition， memory， language， executive function， and attention. Logistic and Linear regression analysis was performed to explore the association between METS-VF and the risk of CMM as well as cognitive function. A restricted cubic spline was used to test the dose-response relationship， and subgroup analysis was conducted to assess the variation of METS-VF in different populations. Additionally， multinomial unordered logistic regression was used to evaluate the performance of METS-VF in predicting CMM morbidity patterns. ResultsA total of 3 790 elderly participants aged 60 and above were included. After adjusting for confounding factors， compared with the lowest quartile（Q1）， the Q4 group of METS-VF was associated with a higher risk of CMM ［OR=3.00，95%CI （2.18， 4.16）］， and with lower scores in overall cognition ［b=-0.12， 95%CI （-0.21，-0.04）］， attention ［b=-0.14， 95%CI （-0.24，-0.05）］， and executive function ［b=-0.10， 95%CI （-0.20，-0.00）］. Dose-response analysis did not show a nonlinear relationship between METS-VF and either CMM or cognitive function （P for nonlinear > 0.05）. Subgroup analysis revealed that the male group with higher METS-VF had lower overall cognitive scores， while the female group showed lower executive function scores （P for interaction ＜ 0.05 for both）. Multinomial unordered logistic regression analysis indicated that the METS-VF index was associated with an increased risk of diabetes with coronary heart disease ［OR=2.62，95%CI （1.66， 4.15）］ or concomitant stroke ［OR=2.66，95%CI （1.73， 4.09）］， especially in the group with both diabetes and stroke and coronary heart disease， where the association between METS-VF and the risk was strongest. ConclusionsAn increased METS-VF is associated with a higher risk of CMM and lower scores in overall cognition， attention， and executive function in the elderly population. Diabetes may be a key driving factor in the multimorbidity model. The METS-VF index can serve as a dual-purpose tool for screening cardiovascular metabolic risks and assessing cognitive function.

Abstract The World Health Organization (WHO) emphasizes that tuberculosis preventive treatment is a key measure for ending the tuberculosis epidemic. In 2023, Huzhou City initiated the construction of Zero Tuberculosis City based on the pilot program of Zero Tuberculosis Communities in Zhejiang Province, and established a three-level tuberculosis preventive treatment system for latent tuberculosis infection (LTBI) at the municipal, county (district), and township (subdistrict) levels. Strategies including formulating standards and norms, promoting preventive treatment clinics at all levels, improving staffing and clarifying work responsibilities were implemented to strengthen active intervention and management of LTBI and improve the standardization of preventive treatment. From 2023 to 2024, a total of 27 535 individuals tested positive for Mycobacterium tuberculosis (MTB) in Huzhou City. The acceptance rate of preventive treatment was 34.82%, and the completion rate was 57.89%. During follow-up, the incidence density of active pulmonary tuberculosis among MTB-positive individuals who did not receive preventive treatment was 393.83/105 person-years, while that among individuals who received preventive treatment but interrupted treatment was 293.83/105 person-years, and that among individuals who received and completed preventive treatment was 46.08/105 person-years. Practices have shown that the LTBI preventive treatment system constructed in Huzhou City features strong accessibility and high operability, which has effectively expanded the coverage of interventions for high-risk groups, significantly reduced the risk of active pulmonary tuberculosis among MTB-positive individuals, and provided a replicable and promotable practical paradigm for LTBI prevention and control nationwide. In the future, Huzhou City will continue to rely on the primary medical and health network to optimize the whole-process standardized management of LTBI, leverage smart prevention and control technologies, optimize diagnosis and treatment services and cross-regional linkage mechanisms, continuously consolidate the achievements of the Zero Tuberculosis City initiative, steadily reduce the regional tuberculosis epidemic, and contribute to the achievement of the strategic goal of ending the tuberculosis epidemic.

Implementing the reform of outpatient mutual-aid is a crucial measure to improve China's medical security system.Based on the policy diffusion theory,we took 228 prefecture-level cities across the country as the research objects and used the event history method to analyze the diffusion mode and influencing factors of the general outpatient pooling policy for employees'basic medical insurance,and divided into three types:the type of reducing the stock of Medical Savings Accounts(MSA),the welfare increment type I and type II for separate analysis.We found that the diffusion of the general outpatient pooling policy presented an"S"-shaped curve over time,and was mainly horizontally diffused in space,with a neighboring effect and a regional demonstration effect.The type of reducing the stock of MSA policy diffuses horizontally;the welfare increment type I is mainly horizontal diffusion,supplemented by vertical diffusion;the welfare increment type II is not affected by the pressure from higher-level governments,and mainly adopts the horizontal diffusion mode.In terms of the influencing factors of policy diffusion,the diffusion of the general outpatient pooling policy was affected by multiple factors such as policy issues,legitimacy,and government capacity.The diffusion of the type of reducing the stock of MSA policy was not affected by the pressure from higher-level governments,but was influenced by policy issues and government capacity.The diffusion of the welfare increment type I policy was most affected by policy issues,and the welfare increment type II was most affected by government capacity.

Aim To clarify the mechanism by which Qishen Yixin Granules improved microcirculation vas-cular endothelial dysfunction(VED)in mice,through activating the Nrf2/HO-1 signaling pathway to regulate oxidative stress.Methods C57 mice were randomly divided into six groups:blank group,model group,pos-itive drug group,and low-,medium-,and high-dose groups of Qishen Yixin Granules.The VED model was established by long-term infusion of Ang Ⅱ combined with a high-fat diet.Each treatment group received the corresponding drug intervention.After four weeks of drug intervention,cardiac function was assessed by echocardiography.Carstairs staining was used to ob-serve the formation of microthrombi in myocardial tis-sue.The micro vascular ischemia was evaluated by Hei-denhain staining.The ultrastructure of endothelial cells was observed by electron microscopy.The levels of EMPs,ROS,NO,ET-1,TF,TM,VWF,and TXA2 in serum were measured by ELISA.The expression levels of MDA,SOD,and GSH-Px in mouse heart tissue were determined by chemical methods.Cardiac microvascu-lar density and the expression of Nrf2,Keap1,and HO-1 proteins were detected by Immunohistochemical stai-ning.The protein expressions of Keap1,cytoplasmic Nrf2,nuclear Nrf2,and HO-1 in myocardial tissue were detected by Western blot.Results Qishen Yixin Granules could effectively improve the cardiac function of mice,alleviate the damage of endothelial cells and endothelial function.They could up-regulate serum NO levels and the activities of antioxidant enzymes SOD and GSH-Px,while down-regulating the expression of ROS and vascular inflammatory injury factors such as ET-1,VWF,TXA2,TF,TM,and EMPs.Qishen Yixin Granules also increased the positive counts of CD34,Nrf2,and HO-1,as well as microvessel density.Fur-thermore,they inhibited the expression of MDA,Keap1,and cytoplasmic Nrf2 protein in myocardial tis-sue,while increasing the expression of nuclear proteins HO-1 and Nrf2.Conclusions Qishen Yixin Granules may inhibit oxidative stress and inflammatory response by regulating the Nrf2/HO-1 signaling pathway,thereby improving vascular endothelial damage and cardiac function in VED mice.

Objective To establish a rapid on-site detection method for methamphetamine(MA)based on surface-enhanced Raman spectroscopy(SERS).Methods Laboratory-synthesized colloidal silver nanoparticles(AgNPs)were employed as SERS substrates to rapidly detect methamphetamine in typical crime scene matrices,including beer,cigarette ash,and plastic containers.Results The method requires no sample pretreatment,is simple to operate,and offers high sensitivity with fast detection speed.The limit of detection(LOD)reached 10 ppb(signal-to-noise ratio,S/N＞3).The qualitative results of methamphetamine analysis from forensic case samples were highly consistent with gas chromatography-mass spectrometry(GC-MS)findings.Conclusion Methamphetamine is frequently encountered in illicit settings and criminal activities.This study achieved rapid detection of methamphetamine in complex matrices(beer,cigarette ash,and plastic containers),demonstrating good application prospects in practice and providing important value for law enforcement,public safety,and criminal investigation.

Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.