Objective: This study proposes a clustering framework for Chinese materia medica (CMM) based on a large language model (LLM), aiming to explore potential compatibility patterns among CMMs from the semantic perspective of CMM property theory. Methods: First, a CMM property knowledge base was constructed based on Chinese Materia Medica, including 567 commonly used CMMs characterized by four properties, five flavors, and meridian tropism. Then, 49 CMMs derived from 10 prescriptions for Zangdu (脏毒, pathogenic toxins) recorded in Waike Zhengzong (《外科正宗》, Orthodox Manual of External Medicine) and Yangke Xinde Ji (《疡科心得集》, Collected Insights on Ulcer Medicine) were selected as the experimental dataset. Five semantic representation methods—One-Hot, Word2Vec, Bidirectional Encoder Representations from Transformers (BERT), Beijing Academy of Artificial Intelligence General Embedding (BGE), and Qwen—were applied to encode CMM property information into vector representations. Subsequently, t-distributed Stochastic Neighbor Embedding (t-SNE) was used for nonlinear dimensionality reduction on high-dimensional semantic vectors, followed by k-means clustering (k = 7). Clustering performance was evaluated using the Silhouette Score (SS), Davies-Bouldin Index (DBI), and Calinski-Harabasz Index (CHI). Results: The Qwen-based clustering method, CMM-EmbedCluster, achieved the highest SS (0.607 4) and CHI (158.057 2), as well as the lowest DBI (0.499 5), indicating improved cluster separation and compactness compared with other methods. Visualization of CMM clustering results showed that the clusters were well separated in the low-dimensional space, with strong inter-cluster discrimination and high intra-cluster functional consistency. Further interpretability analysis of CMM clustering results revealed stable structural differences among clusters in terms of four properties, five flavors, and meridian tropism, forming functional partitions consistent with CMM property theory. Conclusion CMM-EmbedCluster utilizes an LLM to achieve semantic-level representation and clustering of CMMs within the framework of CMM property theory, providing support for exploring potential compatibility patterns among CMMs from the perspective of CMM property semantics.

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.

Traditional Chinese medicine （TCM）， through its multi-target and systematic regulatory effects， has demonstrated unique advantages in the treatment of gastric precancerous lesions （GPL）. At present， TCM theoretical research on GPL is mainly reflected in three aspects， the integration of macroscopic syndrome differentiation， the inflammation-carcinoma transformation mechanism， as well as the systematization and scientization of theoretical inheritance from famous TCM practitioners. High-quality evidence-based research findings serve as the foundation for clinical practice guidelines on GPL， and TCM has gained international academic recognition in the field of GPL prevention and treatment. Research on TCM mechanisms has yielded a series of important outcomes in the aspects of signaling pathways， gene expression regulation， cellular epigenetics， histone modification， and intestinal microecology. It is proposed that future research on GPL should focus on four key directions， establishing multi-omics data， exploring targeted intervention strategies on key regulatory nodes， advancing the standardization process of integrated traditional Chinese and western medicine prevention and treatment technologies， and constructing stratified screening and intervention platforms. The in-depth integration of TCM microcosmic mechanism of action with its macroscopic syndrome differentiation and treatment system， coupled with interdisciplinary research， will provide valuable references for the clinical treatment and scientific research of GPL.

BackgroundIndividuals with chronic multimorbidity exhibit a high prevalence of sleep disturbances， which impair their physical and psychological well-being and impede chronic disease management. Although sleep quality is closely influencing with psychological functioning， empirical evidence regarding the longitudinal trajectories of sleep quality and their influencing factors in this population remains insufficient. ObjectiveTo investigate the longitudinal trajectories of sleep quality and associated factors among patients with chronic multimorbidity from hospitalization through 6 months post-discharge， aiming to facilitate the early identification of high-risk individuals and the development of personalized sleep interventions. MethodsA total of 228 inpatients with chronic multimorbidity， primarily with cardiovascular and metabolic chronic conditions， were enrolled via random sampling at The Third People's Hospital of Fuyang from January 2023 to September 2024. Baseline assessments were conducted during hospitalization using the general socio-demographic questionnaire， the Sleep Dysfunction Rating Scale （SDRS）， the Ruminative Response Scale （RRS）， and the Hospital Anxiety and Depression Scale （HADS）. Sleep quality was further evaluated using the SDRS at 1-， 3-， and 6-month post-discharge. Latent class growth model was employed to delineate trajectories of sleep quality. Multivariate logistic regression analysis was subsequently performed to identify influencing factors of sleep quality. ResultsA total of 201 patients with chronic diseases were included.Based on four predefined assessment time points （baseline， 1 month， 3 months， 6 months post-discharge）， the latent class growth model identified three distinct trajectories of sleep quality： persistent high sleep disturbance （n=72， 35.82%）， moderate sleep disturbance-progression （n=73， 36.32%）， and low sleep disturbance （n=56， 27.86%）. Multivariate logistic regression analysis revealed that， compared with the low sleep disturbance group， multiple factors increased the odds of membership in the persistent high sleep disturbance group： per capita monthly household income of <3 000 yuan （β=13.131， P<0.01） or 3 000–5 000 yuan （β=5.913， P<0.05）， aged 45–65 years （β=9.536， P<0.05）， presence of 3 （β=7.792， P<0.05） or >3 comorbid chronic conditions （β=6.626， P<0.05）， as well as higher RRS （β=0.334， P<0.01） and HADS score （β=1.628， P<0.01）. Additionally， patients aged 45–65 years （β=2.777， P<0.05）， with 3 （β=3.802， P<0.01） or >3 comorbid chronic conditions （β=2.463， P<0.01）， and with higher RRS （β=0.111， P<0.01） and HDAS scores （β=0.350， P<0.05） also demonstrated significantly increased odds of belonging to the moderate sleep disturbance–progression group. ConclusionThere is significant population heterogeneity in sleep quality trajectories among patients with chronic multimorbidity， with age， per capita household monthly income， number of comorbidities， rumination， and anxiety/depression symptoms being identify as the primary influencing factors.

Objective The causal relationship between endometriosis(EMs)and 15 trace elements including copper,calcium,carotene,folic acid,iron,magnesium,potassium,selenium,vitamin A,vitamin B12,vitamin B6,vitamin C,vitamin D,vitamin E and zinc was analyzed by double sample Mendelian randomization(MR).Methods Multiple trace elements were used as exposure factors,and the incidence risk of EMs was used as the outcome factor for two-sample MR analysis.The data were sourced from the publicly available integrative epidemiology unit open Genome-Wide Association Studies database and Finnish Genome Research Project database.Five Mendelian randomization analysis methods were employed to investigate the causal relationship between EMs and trace elements.Additionally,sensitivity analysis was carried out to evaluate the influence of heterogeneity and horizontal pleiotropy on the results of the MR analysis.Results The impact of trace elements on various types of EMs varies.The results of the inverse variance weighted(IVW)method indicated that trace element calcium(OR=1.465,95％CI:1.094-1.962)and vitamin B6(OR=1.580,95％CI:1.146-2.178)might be risk factors for ovarian EMs.Vitamin B6(OR=0.203,95％CI:0.044-0.939)may be a protective factor for tubal EMs.The above research results were not affected by heterogeneity and horizontal pleiotropy(P＞0.05).This study did not find a causal relationship between other trace elements and EMs.Conclusion The trace elements calcium and vitamin B6 predicted by genetics may play a regulatory role in the development of EMs.

Objective:To observe the clinical efficacy of combined acupuncture and medication therapy in treating cerebral infarction in the acute stage and its impact on cerebral blood flow.Methods:A total of 160 patients with cerebral infarction were divided into 4 groups using the random number table method,with 40 cases in each group.Conventional treatment was given to all groups.Besides,the Chinese medication group received Tong Shen Fu Nao Wan;the acupuncture group received Xing Nao Kai Qiao(mind-refreshing and orifice-opening)needling therapy;the acupuncture-medication group received both Tong Shen Fu Nao Wan and Xing Nao Kai Qiao needling therapy.After 4 weeks of treatment,the clinical efficacy was assessed,and changes in the traditional Chinese medicine(TCM)symptom score and hemodynamics were compared among the four groups,as well as complications and adverse reactions.Results:After treatment,the acupuncture-medication group had a higher total effective rate compared to the other three groups(P<0.05).After the intervention,the National Institutes of Health stroke scale(NIHSS)score dropped in all groups(P<0.05)and was lower in the acupuncture-medication group than in the other three groups(P<0.05);all groups showed a decrease in the TCM symptom score(P<0.05),and the acupuncture-medication group was significantly lower than the other groups(P<0.05).After treatment,the blood flow velocity of the bilateral anterior cerebral artery(ACA),middle cerebral artery(MCA),and posterior cerebral artery(PCA)increased in every group(P<0.05),and the acupuncture-medication group had higher blood flow velocities compared to the other three groups(P<0.05).The acupuncture-medication group had the fewest number of complications among the four groups(P<0.05),and there was no statistical significance when comparing the adverse reactions among the groups(P>0.05).Conclusion:Compared to the separate use,the combined use of acupuncture and medication enhances the clinical efficacy,accelerates cerebral blood circulation,and boosts the recovery in treating cerebral infarction.

Objective To construct a prognostic model of lung adenocarcinoma(LUAD)based on m5C modification-related genes and to explore its clinical value.Methods Based on the LUAD data in TCGA,GSE30219,GSE31210,and GSE50081 cohorts,prognosis-related m5C modification-related genes were screened,and the prognostic model was constructed by using univariate Cox,Lasso,and multivariate Cox regression analyses.Kaplan-Meier curve,ROC curve,and Cox regression were used to observe the robustness and prognostic performance of the model.The correlation between the prognostic model and clinico-pathologic features was further explored.Results A prognostic model consisting of eight m5C modifi-cation-related genes,including CDK1,CDKN1A,NOP2,RRM2,TCL6,TLR8,TRDMT1,and YTHDF2,was constructed.Risk score was an independent risk factor for the prognosis of patients with LUAD,and it is combined with age,T stage,and N stage to constitute a nomogram which can accurately predict the prognosis of patients.The infiltration of macrophages and CD4+/CD8+T cells was significantly reduced in high-risk patients.The risk score in LUAD tissues was significantly higher than that in normal tissues and was positively correlated with T stage and N stage.The risk score of smoking and EGFR wild-type patients was higher than that of non-smoking and EGFR-mutant patients.Conclusion The prognostic model constructed based on m5C modification-related genes has shown good accuracy and stability in predicting the prognosis of patients with LUAD,and it is closely related to clinical features,driver gene mutations,and immune infiltration,which can provide a potential basis for the treatment and prognostic assessment of LUAD.

Objective:To investigate the correlation between expressions of serum procalcitonin (PCT), T-cell immunogloblin domain, mucin domain 4 (TIM-4) and prognosis of patients with severe pneumonia (SP) treated with bronchoalveolar lavage (BAL).Methods:Data of 497 patients with SP in the Department of Respiratory and Critical Care Medicine of the Affiliated Hospital of Yan'an University from June 2021 to June 2024 were retrospectively analyzed. Patients were divided into good prognosis group [pneumonia severity index (PSI) score<90 points, 289 cases] and poor prognosis group (PSI score≥90 points, 208 cases) according to the prognosis status of patients at 30 days after admission. The clinical data [history of smoking, alcohol consumption, history of hypertension, history of diabetes mellitus, gender, age, body mass index, PSI score after 30 d of admission, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) and clinical pulmonary infection score (CPIS) after 14 days of treatment], serum PCT and TIM-4 levels were compared between both groups. Measurement data with normal distribution were expressed as xˉ± s, and t test was used for comparison between groups. Enumeration data were represented as n (%), and the composition ratio between groups was compared by χ2 test. The influencing factors of prognosis of BAL in the treatment of SP were analyzed by multivariate Logistic regression analysis. ROC curve was applied to analyze the diagnostic efficiency of serum PCT and TIM-4 on prognosis of BAL therapy. Results:Age (56.79±11.98) years, APACHEⅡscore (9.98±3.27) and CPIS score (6.54±1.81) in the good prognosis group were younger or lower than those in the poor prognosis group [(62.74±10.57) years, (13.06±4.25), (8.12±1.97)] ( t=5.734, 9.127, 9.250, respectively, P<0.001). The PCT (0.41±0.08) μg/L and TIM-4 (61.79±15.62) ng/L after treatment were higher in the poor prognosis group than those in the good prognosis group [(0.35±0.07) μg/L, (48.76±14.58) ng/L] ( t=8.876, 9.538, respectively, P<0.001). Multivariate Logistic regression analysis suggested that after excluding the interference effects of other factors, PCT ( OR=3.615, 95% CI: 1.641-7.964) and TIM-4 ( OR=4.047, 95% CI: 1.773-9.236) were influencing factors of prognosis in patients with SP receiving BAL therapy ( P=0.002, 0.001). ROC curve analysis indicated that the AUC value of PCT, TIM-4 and the combination of both in the diagnosis of prognosis of BAL therapy of SP were 0.782, 0.828 and 0.887 respectively, all of which had efficiency on predicting prognosis (all P<0.001). The sensitivity and specificity of combined prediction were 88.00% and 72.00%. Conclusion:The expressions of serum PCT and TIM-4 are closely related to the prognosis of SP patients receiving BAL. The PCT, TIM-4 and combination of both are of important reference value for prognosis prediction.

Medical simulation-based assessments have emerged as a vital method for evaluating the clinical competence of healthcare professionals. These assessments provide examinees with opportunities to practice clinical skills in a controlled environment that mirrors real-life medical scenarios. However, assessment organizers must implement specific measures to ensure that these assessments yield valid and reliable results. The reliability of simulation-based assessments is a crucial component of quality assurance. This article delineates twelve practical recommendations to enhance the reliability of medical simulation-based assessments across the three key dimensions of raters, simulation environment, and assessment tools. These recommendations include ① selecting raters with relevant professional backgrounds and extensive experience in simulation-based teaching and assessment; ②providing raters with standardized training for the assessment; ③conducting mock ratings and piloting to reach consensus among raters; ④preventing excessive work hours or cognitively overload while rating; ⑤providing standardized personnel with adequate training and re-training; ⑥implementing immediate and long-term quality assurance measures for standardized patient role performance; ⑦maintaining consistent operation of simulation equipment; ⑧guaranteeing the simulation provides adequate functional fidelity for the examinees; ⑨clearly defining each element and item in assessment tools while controlling their quantity; ⑩ensuring consistency when multiple assessment tools are used; 11using assessment tools with evidence of construct validity when possible; and 12establishing systems to ensure consistency in data (scoring) collection while safeguarding data security. These strategies aim to assist medical educators in developing structured and reliable simulation-based assessment schemes.

Objective The causal relationship between endometriosis(EMs)and 15 trace elements including copper,calcium,carotene,folic acid,iron,magnesium,potassium,selenium,vitamin A,vitamin B12,vitamin B6,vitamin C,vitamin D,vitamin E and zinc was analyzed by double sample Mendelian randomization(MR).Methods Multiple trace elements were used as exposure factors,and the incidence risk of EMs was used as the outcome factor for two-sample MR analysis.The data were sourced from the publicly available integrative epidemiology unit open Genome-Wide Association Studies database and Finnish Genome Research Project database.Five Mendelian randomization analysis methods were employed to investigate the causal relationship between EMs and trace elements.Additionally,sensitivity analysis was carried out to evaluate the influence of heterogeneity and horizontal pleiotropy on the results of the MR analysis.Results The impact of trace elements on various types of EMs varies.The results of the inverse variance weighted(IVW)method indicated that trace element calcium(OR=1.465,95％CI:1.094-1.962)and vitamin B6(OR=1.580,95％CI:1.146-2.178)might be risk factors for ovarian EMs.Vitamin B6(OR=0.203,95％CI:0.044-0.939)may be a protective factor for tubal EMs.The above research results were not affected by heterogeneity and horizontal pleiotropy(P＞0.05).This study did not find a causal relationship between other trace elements and EMs.Conclusion The trace elements calcium and vitamin B6 predicted by genetics may play a regulatory role in the development of EMs.