ObjectiveTo observe the therapeutic effect of Erchentang on depression in obese mice and explore the therapeutic mechanism. MethodsC57BL/6J mice were randomized into the control， model， metformin （0.65 g·kg^-1）， and low-， medium-， and high-dose （3.35， 6.7， and 13.4 g·kg^-1， respectively） Erchentang groups. Gavage was initiated simultaneously with modeling and continued for 28 days. The therapeutic effects of Erchentang were evaluated through behavioral tests， liver and brain indices， liver function， lipid indicators， and histopathological changes in the liver and brain tissue. RNA-seq technology was used to conduct transcriptomic analysis of mouse liver tissue， and differentially expressed genes were screened and subjected to Kyoto Encyclopedia of Genes and Genomes （KEGG） analysis. Key genes were further verified by Western blot and Real-time polymerase chain reaction（Real-time PCR）. ResultsBehavioral tests， liver function， lipid indicators， and histopathological changes in the liver and brain tissue all demonstrated that Erchentang had therapeutic effects on depression in obese mice. KEGG pathway enrichment analysis of transcriptomic data indicated that Erchentang treated depression in obese mice mainly through the peroxisome proliferator-activated receptor （PPAR） signaling pathway. Western blot and Real-time PCR results showed that compared with the model group， the low-， medium-， and high-dose Erchentang groups exhibited downregulated expression of fatty acid-binding protein （FABP） 1 （P<0.01） and upregulated expression of acyl-CoA oxidase （ACOX） 1， PPARα， cholesterol 7α-hydroxylase （CYP7A） 1， and phosphoenolpyruvate carboxy kinase （PCK） 1 （P<0.05） in the liver tissue. ConclusionErchentang exerts therapeutic effects on obesity-associated depression by regulating the PPAR signaling pathway and the expression of related genes FABP1， ACOX1， PPARα， CYP7A1， and PCK1.

Driven by the"Big Health"concept,chronic disease management has gradually shifted from single-treatment approaches to comprehensive health maintenance.This paper analyzes the challenges in the development of community-based re-habilitation for chronic diseases in China,including workforce shortages,policy support gaps,funding constraints,and health ed-ucation deficiencies.Implementation pathways are proposed,such as strengthening rehabilitation teams,improving community re-habilitation management systems,diversifying funding sources,and promoting health education.Future directions include con-structing a multimodal collaborative"hospital-community-pharmacy"network,advancing integrated healthcare and prevention models,emphasizing scientific multi-morbidity management,and adopting AI-driven medical technologies.These strategies aim to optimize service models,enhance the overall effectiveness of community-based chronic disease rehabilitation,and support the implementation of the Healthy China initiative.

OBJECTIVE T o explore the value of targeted next-generation sequencing(t-NGS)in diagnosis of respir-atory tract pathogens through meta-analysis so as to provide reference for clinical application.METHODS PubMed database,Web of Science database,Wanfang database,CNKI database and Sinomed database were retrieved,and the time period of retrieval ranged from Jan.2010 to May 2024.The literatures were screened out based on the es-tablished standards.The quality was assessed by QU ADAS-2,the risk of bias graph was drawn by Revman 5.4,and the statistical analysis was performed by Stata 16.0.RESULTS A total of 9 literatures were included in the study.The result of meta-analysis showed that the heterogeneity test Q for sensitivity was 268.21,P＜0.01,I2=97.02％,with the heterogeneity test Q for specificity 210.04,P＜0.01,I2=96.19％,the combined sensitivity 0.88(95％CI:0.62 to 0.97),combined specificity 0.68(95％CI:0.41 to 0.86),combined positive likelihood ratio 2.72(95％CI:1.44 to 5.15),combined negative likelihood ratio 0.18(95％CI:0.06 to 0.53),combined diagno-sis score 2.74(95％CI:1.68 to 3.80),and combined diagnostic odds ratio 15.44(95％CI:5.34 to 44.66).The area under synthesize receiver operating characteristic(SROC)curve(AUC)was 0.85(95％CI:0.82 to 0.88).The result of Deeks funnel plot showed that P was 0.99,indicating that there was no obvious publication bias.CONCLUSIONS The sensitivity of tNGS is high in detection of the pathogens causing acute respiratory tract infection,the specificity needs to be improved,but its comprehensive ability is satisfactory.It has certain val-ue in early clinical diagnosis.

Driven by the"Big Health"concept,chronic disease management has gradually shifted from single-treatment approaches to comprehensive health maintenance.This paper analyzes the challenges in the development of community-based re-habilitation for chronic diseases in China,including workforce shortages,policy support gaps,funding constraints,and health ed-ucation deficiencies.Implementation pathways are proposed,such as strengthening rehabilitation teams,improving community re-habilitation management systems,diversifying funding sources,and promoting health education.Future directions include con-structing a multimodal collaborative"hospital-community-pharmacy"network,advancing integrated healthcare and prevention models,emphasizing scientific multi-morbidity management,and adopting AI-driven medical technologies.These strategies aim to optimize service models,enhance the overall effectiveness of community-based chronic disease rehabilitation,and support the implementation of the Healthy China initiative.

Objective:To explore the value of amide proton transfer weighted imaging (APTWI) combined with human epidermal growth factor receptor 2 (HER2) expression in predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer.Methods:The study was a cross-sectional study. Clinicopathological [estrogen receptor (ER), progesterone receptor (PR), HER2, Ki-67 status, and molecular subtypes] and imaging data were retrospectively analyzed in 100 female patients who had invasive ductal carcinoma of the breast confirmed pathologically by preoperative puncture in the Henan Cancer Hospital from May 2023 to May 2024. All patients underwent MRI, including enhanced MRI, APTWI, and diffusion-weighted imaging (DWI) before NAC. The reference enhanced MRI images were segmented into lesions using the threshold extraction method, and the three-dimensional region of interest within the tumor was automatically outlined by the software and replicated in the amide proton transfer map generated by APTWI and the apparent diffuse coefficient (ADC) map generated by DWI. The magnetization transfer ratio asymmetry (MTRasym) value and the ADC value were measured, respectively. Tumor response to NAC was assessed using the Miller-Payne grading system, where Grade 5 indicated pCR and Grades 1-4 were classified as non-pCR. Independent sample t-tests and χ2 tests were used to compare clinical pathological and imaging parameters between pCR and non-pCR patients. Statistically significant variables were included in multivariate logistic regression to identify independent predictors of pCR. The diagnostic performance of individual and combined indicators for pCR was evaluated using receiver operating characteristic curves and the area under the curve (AUC). DeLong′s test was used to compare AUCs. Results:There were 39 pCR and 61 non-pCR patients. Significant differences were observed between the pCR and non-pCR patients in molecular subtypes, ER, PR, HER2, and Ki-67 statuses ( P<0.05). Pre-treatment MTRasym values were significantly higher in the pCR patients compared to the non-pCR patients ( P=0.005), whereas ADC values showed no statistical difference ( P=0.372). Multivariate logistic regression analysis showed HER2 positivity ( OR=5.87, 95% CI 1.99-17.30, P=0.001) and MTRasym values>2.61% (OR=4.39, 95% CI 1.37-14.08, P=0.013) was independent predictors of pCR after NAC. HER2 positivity combined with MTRasym value>2.61% predicted pCR after NAC in breast cancer with AUC of 0.819, which was superior to HER2 positivity and MTRasym value alone in predicting efficacy ( Z=3.91, P<0.001; Z=2.63, P=0.009). Conclusions:The MTRasym value of pre-treatment APTWI is valuable in predicting pCR after NAC in breast cancer. APTWI combined with HER2 expression status can further enhance the predictive efficacy.

Objective:To explore the risk factors for bronchiolitis obliterans (BO) after Mycoplasma pneumoniae bronchiolitis in children. Methods:A retrospective cohort study was conducted on 122 children diagnosed with Mycoplasma pneumoniae bronchiolitis in Department No.2 of Respiratory Medicine of Beijing Children′s Hospital, Capital Medical University, from March 2017 to December 2024. Clinical data, including general information, clinical manifestations, imaging findings, laboratory tests, and outcomes, were analyzed. Patients were divided into BO and non-BO groups based on the presence of BO. Differences between groups were assessed using Mann-Whitney U test, χ2 test, or Fisher exact test. Logistic regression and receiver operating characteristic (ROC) curve analysis were employed to identify risk factors and evaluate predictive performance. Results:Among 122 children (73 males, 49 females), the age at onset was 5.0 (2.4, 7.1) years. The BO group included 21 patients, and the non-BO group 101. The BO group exhibited significantly longer durations of persistent high fever and higher peak levels of C-reactive protein, lactate dehydrogenase, and D-dimer compared to the non-BO group (9 (7, 11) vs. 4 (2, 6) d, 19 (7, 35) vs. 10 (7, 18) mg/L, 438 (337, 498) vs. 315 (274, 351) U/L, 0.36 (0.27, 0.91) vs. 0.21 (0.15, 0.29) mg/L, U=295.00, 743.50, 463.50, 470.50, all P<0.05). The BO group also had higher proportions of resting oxygen saturation <0.95 on room air (100.0% (21/21) vs. 43.6% (44/101)), inspiratory retractions (57.1% (12/21) vs. 18.8% (19/101), χ2=11.53), and adenovirus co-infection (38.1% (8/21) vs. 5.0% (5/101)) (all P<0.05). Multivariate Logistic regression identified prolonged high fever ( OR=1.83, 95% CI 1.31-2.58, P<0.001), inspiratory retractions ( OR=10.48, 95% CI 1.72-63.85, P=0.011), and adenovirus co-infection ( OR=42.47, 95% CI 4.04-446.87, P=0.002) as independent risk factors for BO. ROC curve analysis revealed that a fever duration cutoff of 7.5 days predicted BO with 0.71 sensitivity and 0.92 specificity. Conclusions:Prolonged high fever (≥7.5 days), inspiratory retractions, and adenovirus co-infection are significant predictors of BO after Mycoplasma pneumoniae bronchiolitis in children, which are helpful for early clinical identification.

OBJECTIVE T o explore the value of targeted next-generation sequencing(t-NGS)in diagnosis of respir-atory tract pathogens through meta-analysis so as to provide reference for clinical application.METHODS PubMed database,Web of Science database,Wanfang database,CNKI database and Sinomed database were retrieved,and the time period of retrieval ranged from Jan.2010 to May 2024.The literatures were screened out based on the es-tablished standards.The quality was assessed by QU ADAS-2,the risk of bias graph was drawn by Revman 5.4,and the statistical analysis was performed by Stata 16.0.RESULTS A total of 9 literatures were included in the study.The result of meta-analysis showed that the heterogeneity test Q for sensitivity was 268.21,P＜0.01,I2=97.02％,with the heterogeneity test Q for specificity 210.04,P＜0.01,I2=96.19％,the combined sensitivity 0.88(95％CI:0.62 to 0.97),combined specificity 0.68(95％CI:0.41 to 0.86),combined positive likelihood ratio 2.72(95％CI:1.44 to 5.15),combined negative likelihood ratio 0.18(95％CI:0.06 to 0.53),combined diagno-sis score 2.74(95％CI:1.68 to 3.80),and combined diagnostic odds ratio 15.44(95％CI:5.34 to 44.66).The area under synthesize receiver operating characteristic(SROC)curve(AUC)was 0.85(95％CI:0.82 to 0.88).The result of Deeks funnel plot showed that P was 0.99,indicating that there was no obvious publication bias.CONCLUSIONS The sensitivity of tNGS is high in detection of the pathogens causing acute respiratory tract infection,the specificity needs to be improved,but its comprehensive ability is satisfactory.It has certain val-ue in early clinical diagnosis.

Objective: To assess the presence of vector-borne pathogens [including Zika virus (ZIKV), dengue virus (DENV), chikungunya virus (CHIKV), and Plasmodium (PLAS)] among voluntary blood donors in Wenshan Zhuang and Miao Autonomous Prefecture (referred to as Wenshan), so as to provide a basis for formulating blood safety-related strategies. Methods: Blood samples from voluntary blood donors in Wenshan from June to August 2022 to 2024 were selected. Real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to test 20 426 samples for ZIKV RNA, DENV RNA, and CHIKV RNA; and 19 765 samples were tested for PLAS DNA. Results: All 20 426 samples tested for ZIKV RNA, DENV RNA, and CHIKV RNA were negative; similarly, all 19 765 samples tested for PLAS DNA were negative. Conclusion: The risk of ZIKV, DENV, CHIKV, and PLAS infection among voluntary blood donors in Wenshan is relatively low. Routine surveillance for these pathogens as endemic diseases is not currently warranted. It is recommended to adjust the screening strategy based on the dynamic situation of local epidemiology control and prevention.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.