Objective: To assess the effect of 12-year-old children s pit and fissure sealants on the health of first permanent molars, so as to provide evidence for optimizing caries prevention strategies among children. Methods: In March 2025, a cluster random sampling method was used to conduct oral examinations on 965 students aged 12 from Chengdu s 2021 Comprehensive Intervention Program for Pediatric Oral Diseases. Data from the Comprehensive Intervention System for Children s Oral Diseases were referenced. Participants were divided into a sealed group ( n =755) and an unsealed group ( n =210) based on whether they had received sealants on their first permanent molars. Chi square test or analysis of variance were used to compare indicators such as caries incidence, new caries detection rate, and new caries mean (DMFT increment) between the two groups Results: The sealed group showed significantly lower caries incidence, new caries detection rate, and new caries mean (33.38%, 17.65%, 0.59±1.00) compared to the unsealed group (43.81%, 24.70%, 0.87±1.22)( χ 2/F =7.79, 18.26, 9.55, all P <0.05). However, no significant difference was found in the filled teeth ratio between the two groups (20.38% , 20.16%; χ 2=0.01, P =0.94). In girls, the sealed group exhibited significantly lower caries incidence, new caries detection rate, and new caries mean (36.78%, 20.99%, 0.69± 1.10 ) than the unsealed group (57.55%, 33.52%, 1.15±1.29) ( χ 2/F =14.42, 23.76, 10.92, all P <0.05), whereas no significant differences were observed between boys in the sealed (30.47%, 14.85%, 0.50±0.89) and unsealed groups (29.81%, 16.18%, 0.59± 1.08) ( χ 2/F =0.02, 0.41, 0.74, all P >0.05). Boys had significantly lower new caries detection rates and new caries means than girls in both groups ( χ 2/F =16.20, 6.94; 29.93, 11.84, all P <0.05). In urban areas, the sealed group had lower new caries detection rates and new caries means (19.37%, 0.68±1.04) than the unsealed group (24.66%, 0.90±1.20) ( χ 2/F =6.86, 3.94, both P <0.05). In suburban areas, all indicators for the sealed group (24.71%, 13.77%, 0.42±0.87) were significantly lower than those for the unsealed group (38.81%, 24.77%, 0.82±1.28) ( χ 2/F =5.28, 15.36, 6.00, all P <0.05). Indicators from specialized dental institutions (11.25%, 4.81%, 0.16±0.56) were significantly lower than those from county level or above general hospitals (33.33%, 19.11%, 0.38±1.00) and primary healthcare institutions (37.59%, 19.24%, 0.67±1.05) ( χ 2/F =20.99, 34.31, 21.08 , all P <0.01). Conclusions The 12-year-old children s pit and fissure sealants effectively reduce the caries incidence in first permanent molars, particularly showing significant effectiveness in girls and suburban children. Intervention strategies should be optimized according to gender.

Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

OBJECTIVE To investigate the efficacy and safety of Wuling capsules combined with fluoxetine in the treatment of adolescents with first-episode moderate-to-severe depressive disorder accompanied by insomnia. METHODS The clinical data of 476 adolescents with first-episode moderate-to-severe depression accompanied by insomnia admitted to our hospital from June 2022 to May 2025， were retrospectively collected. According to the initial treatment regimen， patients were divided into a control group （241 cases， treated with fluoxetine alone） and an observation group （235 cases， treated with Wuling capsules combined with fluoxetine）. The depression severity （Hamilton Depression Rating Scale-17 Item and the Self-Rating Depression Scale scores）， sleep quality （Pittsburgh Sleep Quality Index score， sleep latency， wake after sleep onset， total sleep time， sleep efficiency）， serum neuroendocrine indicator （cortisol） and inflammatory markers （C-reactive protein， interleukin-6） were compared between the two groups before treatment and at 4th and 8th weeks of treatment. The effective rate at 8th weeks and the occurrence of adverse drug reactions （ADRs） were also compared between the two groups. RESULTS Before treatment， there were no significant differences in depression severity， sleep quality， serum neuroendocrine indicator， and inflammatory markers between the two groups （ P ＞0.05）. At 4th and 8th weeks， both groups showed significant improvement in these indicators compared to those before treatment， with the observation group demonstrating significantly greater improvement than the control group at the corresponding time points （ P ＜0.05）. At 8th week， the eff ective rate of the observation group was 90.21%， significantly higher than 80.50% in the control group （ P ＜0.05）. The incidence of nausea， headache， fatigue， dry mouth， and palpitations， as well as the total incidence of ADRs， did not differ significantly between the two groups （ P ＞0.05）. CONCLUSIONS Wuling capsules combined with fluoxetine can significantly improve the effective rate in adolescents with first-episode moderate-to-severe depression accompanied by insomnia， accelerate the relief of depressive symptoms， improve sleep quality， and reduce serum neuroendocrine indicator and inflammatory markers， with a favorable safety profile.

OBJECTIVE To investigate the actual construction and operation status of established and under-construction centralized （cloud） prescription review centers （shortened for “prescription review center”） of close-knit county-level medical consortium in a certain city， so as to provide reference for improving the construction quality of the prescription review center. METHODS An online questionnaire survey was conducted to collect the data from 51 established and under-construction prescription review center in the city， covering basic information， funding sources， talent management， system construction， review rule maintenance， prescription review practices， prescription evaluation， data utilization， and current challenges. The collected data were summarized and analyzed. RESULTS A total of 51 valid questionnaires were retrieved， covering 32 established and 19 under-construction prescription review center. Among the 32 established prescription review centers， the main funding sources for their construction came from government financial allocations， accounting for 56.25%. Only 25.00% of prescription review center had review pharmacists who fully met national qualification requirements， and just 55.00% updated more than 10 review rule entries per month on average. Outpatient prescription verification realized full coverage， but 37.50% of prescription review centers only supported rationality verification of single prescriptions， and 50.00% could not retrieve laboratory and examination results to assist in prescription review. Additionally， 40.62% of prescription review center had not regularly conducted prescription evaluations for primary care institutions. The data from prescription review center was mainly used to support medication monitoring. Among the 19 prescription review centers currently in the planning stage， 63.16% had no identified funding sources. CONCLUSIONS The operation and construction of prescription review center in the city face challenges， such as funding shortages， absence of collaborative incentive mechanisms， and insufficient manpower.It is suggested that the state should issue a unified standard for the construction of the prescription review center as soon as possible， and local health administrative departments should formulate supporting policies and clarify assessment indicators in combination with the actual situation of the region.

Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

ObjectiveTo predict the in-hospital mortality risk among patients with ischemic stroke combined by dysphagia using interpretable machine learning methods, so as to provide more evidence-based support for the prognosis prediction of patients with ischemic stroke combined by dysphagia. MethodsMedical record of 308 patients diagnosed with ischemic stroke combined by dysphagia in the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) (2.0) in the United States were retrospectively analyzed. Features of the research data were screened based on the least absolute shrinkage and selection operator, and which were randomly divided into a training set and a test set at a ratio of 7∶3. Then ten models, including logistic regression, random forest, K-nearest neighbor, linear discriminant analysis, naive bayes (NB), neural network, quadratic discriminant analysis, recursive partitioning tree, extreme gradient boosting tree, and support vector machine, etc. were constructed. The predictive effect was measured by calculating the area under the curve (AUC) of receiver operating characteristics. In addition, the calibration curve and Brier score were used to evaluate the calibration degree of the model, and the decision curve was drawn to reflect the clinical net benefit. The Shapley additive explanation method was used to analyze the interpretability of the black box model and explore the important decision-making factors. ResultsThe NB model in the test set showed better predictive ability compared with other models (AUC=0.85, 95%CI: 0.83‒0.88). After interpretability analysis, it was found that blood urea nitrogen (BUN), age, sequential organ failure assessment, bicarbonate, chloride, and hypertension were important risk factors for in-hospital mortality in patients with ischemic stroke combined by dysphagia. ConclusionThe comprehensive performance of the NB model is better than that of the other nine models in predicting the risk of in-hospital mortality in patients with ischemic stroke combined by dysphagia. The interpretability of the model can help clinicians better understand the reasons behind the results and take further reasonable intervention measures for risk factors to improve the survival probability of patients.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.

Traditional four examinations of traditional Chinese medicine （TCM） are based on the symptoms and signs of patients， which are the advantages of TCM but also have shortcomings. Chronic kidney disease has the characteristics of insidiousness， long-term， deficiency and variability during its onset， which are difficult to be intervened in time based on only symptoms， therefore it is necessary to extend the application of the four examinations in the diagnosis and treatment process of chronic kidney disease. Based on the background of the continuous development of TCM syndrome differentiation techniques， this article proposed the extension and application strategies of the traditional four examinations in chronic kidney disease， including the incorporation of microscopic syndrome differentiation to identify the causes of kidney disease and prevent symptom deterioration； the utilization of accurate examination information enhanced by artificial intelligence for controlling development of existing disease； the integration of disease differentiation and syndrome differentiation to summarize clinical rules towards using constant to measure variation； and the establishment of a kidney disease database for the storage of four examinations information to prevent recurrence after recovery. The four above extension and application strategies can be used to achieve the long-term management and treatment effects of timely and early diagnosis， dynamic observation of the condition， accurate application of intervention， and strengthened prognosis assessment in the diagnosis and treatment of chronic kidney disease， and expand the advantages of TCM in the prevention and treatment of chronic kidney disease.

OBJECTIVE To explore the pathogenesis， diagnosis and treatment of drug reaction with eosinophilia and systemic symptoms （DRESS） caused by cross-allergy between cephalosporins and carbapenems， and provide reference for safe clinical medication. METHODS Clinical pharmacists participated in the diagnosis and treatment process of a patient with severe pneumonia whose DRESS caused by suspected cross-allergy between cephalosporins and carbapenems in our hospital. At the same time， relevant studies on the pathogenesis， diagnosis， treatment， and cross-allergy between cephalosporins and carbapenems were retrieved for analysis. Based on the clinical manifestations and treatment process of this patient， the possible mechanisms of cross- allergy between cephalosporins and carbapenems and the treatment strategies for DRESS were discussed. RESULTS The RegiSCAR score of this patient was 6 points， confirming the diagnosis of DRESS. There may be β-lactam ring-specific human leucocyte antigen alleles or T-cell receptors， which led to suspected cross-allergic reactions between cephalosporins and carbapenems. The clinical pharmacists suggested discontinuing cephalosporins and carbapenems and using methylprednisolone combined with immunoglobulin for treatment. The physician adopted the pharmacist’s suggestion， and the patient did not have fever again and the rash gradually subsided. CONCLUSIONS There is a possibility of cross-allergy between cephalosporins and carbapenems causing DRESS. For patients with DRESS， it is recommended to promptly investigate the suspected drugs and discontinue them. The combination of glucocorticoids and immunoglobulin is a feasible treatment option. Medical institutions with conditions should conduct herpesvirus screening and treatment.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.