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.

ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

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.

Objective: To analyze the school tuberculosis (TB) outbreaks and preventive treatment in Hefei from 2022 to 2024, so as to provide reference for TB prevention and control in schools. Methods: Data were collected on all school based TB outbreaks occurring during 2022-2024 in Hefei, defined as ≥2 epidemiologically linked TB cases within the same school during a single semester. Statistical analyses were performed using the Chi square test. Results: Close contacts exhibited significantly higher TB incidence (2.88%) and latent mycobacterium tuberculosis infection (LTBI) rates (13.80%) in the school TB outbreaks, compared to non close contacts (0.12% and 2.63%, respectively). Among close contacts, secondary school students showed lower TB incidence (0.48%) and LTBI prevalence (3.42%) than both primary school or younger children (0.68%, 6.95%) and college students ( 0.78% , 6.50%), with statistically significant differences ( χ 2=360.91, 6.37; 791.71, 102.03, all P <0.05). The proportion of LTBI individuals recommended for preventive therapy was higher in primary school or younger groups (98.59%) than in secondary (95.25%) or college students (86.34%) ( χ 2=25.86, P <0.01). However, among those recommended, close contacts had higher uptake (85.82%) and completion rates (87.25%) of preventive therapy than non close contacts (69.63% and 70.57%); similarly, secondary school students demonstrated higher uptake (91.21%) and completion rates (86.45%) compared to primary school or younger (88.57%, 83.87%) and college students (57.28%, 64.08%) ( χ 2=30.52, 26.72; 125.17, 38.84, all P <0.01). Subsequent TB incidence among LTBI close contacts (13.30%) and among those who did not complete preventive therapy (22.73%) were significantly higher than among non close contacts (2.80%, 2.41%), respectively ( χ 2=32.19, 13.87, both P <0.05). Conclusions In school TB outbreaks, close contacts face higher LTBI prevalence and subsequent TB risk than non close contacts. College students show notably low adherence to preventive therapy. It is necessary to take targeted measures to improve the compliance of preventive measures among students.

The development of the rare disease discipline is a crucial pathway for enhancing the diagnosis and treatment of rare diseases, cultivating specialized professionals, and fostering technological innovation. Currently, China' rare disease discipline is accelerating its development driven by both policy and demand. However, it still faces multi-dimensional challenges, including an incomplete clinical management mechanism, a shortage of interdisciplinary talents, a weak scientific research system, and limited outreach capacity. To address these challenges, this paper proposes and constructs an integrated development system with clinical diagnosis and treatment as the foundation, talent cultivation as the engine, scientific research as the support, and disciplinary outreach capacity as the extension. Specific strategies include: enhancing clinical management through artificial intelligence-assisted diagnosis systems and multidisciplinary collaboration platforms; strengthening the talent pool through textbooks, curricula, and hierarchical training mechanisms; bolstering research collaboration and translational outcomes by leveraging international data-sharing platforms, national rare disease medical centers, the State Key Laboratory of Complex Severe and Rare Diseases, and the National Key Scientific Infrastructure for Translational Medicine; and expanding grassroots outreach and public awareness through the National Rare Disease Diagnosis and Treatment Collaboration Network, the National Rare Disease Quality Control Center, and integrated media communication channels. In the future, the rare disease discipline should further deepen the integration of medicine and engineering, expand international cooperation, focus on the translational closed loop, improve the regional collaboration network, so as to build a more resilient and dynamic disciplinary ecosystem, and ultimately achieve a comprehensive improvement in the diagnosis and treatment of rare diseases.

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.

Objective : To analyze the epidemiological characteristics and spatial clustering of brucellosis in Shanxi Province from 2019 to 2023, so as to provide a reference for formulating prevention and control measures of brucellosis. Methods: The case data of brucellosis in Shanxi Province from 2019 to 2023 were collected through the Infectious Disease Surveillance System of the Chinese Disease Prevention and Control Information System. The seasonal distribution, population distribution, and region distribution of brucellosis cases were described. Spatial autocorrelation analysis was applied to explore the spatial clustering characteristics of brucellosis. Results: A total of 21 241 human brucellosis cases were reported in Shanxi Province from 2019 to 2023, with an average annual reported incidence of 11.87/100 000, showing an upward trend (P<0.05). The peak incidence period was from March to August, with 14 163 cases reported cumulatively, accounting for 66.68% of the total. There were 16 336 male cases and 4 905 female cases, with a male-to-female ratio of 3.33:1. The high-incidence age group was 40-<70 years, with 15 675 cases accounting for 73.80%. The majority of patients were farmers, with 17 926 cases accounting for 84.39%. Spatial autocorrelation analysis showed that there was spatial clustering in the incidence of brucellosis from 2019 to 2023 (all Moran's I>0, P<0.05). The high-high clustering areas were mainly Datong City, and Shuozhou City in northern Shanxi, and Linfen City in the southern Shanxi. The low-low clustering areas were mainly Taiyuan City and Yangquan City in central Shanxi, and Changzhi City and Jincheng City in southeastern Shanxi. Conclusions From 2019 to 2023, the reported incidence of brucellosis in Shanxi Province showed an upward trend. The incidence peaked from March to August, and males, middle-aged and elderly people and farmers were the high-risk groups. There was spatial clustering and the high-high clustering areas gradually expanded from northern Shanxi to southern Shanxi.