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 explore the the possibility and potential mechanism of Coptis chinensis in treating caries based on network pharmacology and molecular docking technology.Methods:The active ingredients of Coptis chinensis and the targets of the active in-gredients and caries were obtained through a variety of databases.The intersection targets of Coptis chinensis and caries were obtained by VENNY.Based on the target of the intersection,the protein-protein interaction(PPI)networks relationship diagram was formed on the STRING platform.The core target diagram was formed through the Cytoscape software,and the Coptis chinensis-active ingre-dient-target network diagram was constructed.The intersection targets are analyzed by GO and KEGG.The core targets of Coptis chinensis active ingredients in treating caries was analyzed by molecular docking.Results:The 11 Coptis chinensis active ingredi-ents,465 targets of Coptis chinensis active ingredients and 1 160 targets of caries were obtained from the database.After analysis,71 targets of Coptis chinensis-caries intersection and 12 core targets were obtained.The potential therapeutic effect of Coptis chinensis on caries involved relaxin,phosphatidylinositol 3-kinase-protein kinase B(PI3K-Akt),mitogen activated protein kinase(MAPK),ras-re-lated protein 1(RAP1)and other signaling pathways.Berberine,one of the main active components of Coptis chinense,had strong binding activity on epidermal growth factor receptor(EGFR),matrix metalloproteinase 9(MMP9)and other core targets.Coptis chinen-sis and its active components can play a role in the treatment of caries through EGFR,MMP9 and PI3K-AKT,MAPK and other path-ways.Conclusion:Coptis chinensis and its active components can regulate several targets and signaling pathways such as EGFR,MMP9,PI3K-AKT and MAPK.Coptis chinensis may play a role in the prevention and treatment of caries through multiple pathways.

Objective To investigate the expression of calumenin(CALU)in gastric cancer and its effect on metastasis and invasion of gastric cancer,and analyze its relationship with the prognosis of gastric cancer patients.Methods The Cancer Genome Atlas(TCGA)database was used to analyze the expression level of CALU in gastric cancer and its impact on patient prognosis.A total of 102 pairs of gastric cancer and paracancerous tissue samples were collected from 189 gastric cancer patients who underwent partial gastrectomy in First Affiliated Hospital of Army Medical University from January 2018 to December 2022.The expression of CALU in gastric cancer and paracancerous tissues was detected by immunohistochemical assay,and the relationship of its expression with clinicopathological parameters was statistically analyzed.After gastric cancer cells with CALU knockdown and overexpression were constructed,and the efficiencies of knockdown and overexpression were evaluated by Western blotting as well as RT-qPCR.Transwell assay was applied to determine the effect of CALU on the migration and invasion abilities of gastric cancer cells.Results Bioinformation analysis found that CALU was significantly highly expressed in gastric cancer tissues(P<0.05),and its expression level was negatively correlated with the prognosis of patients(P<0.05).Immunohistochemical results showed that the expression level of CALU was obviously highly in gastric cancer tissues than the paracancerous tissues(P<0.01),and its level was positively correlated with the depth of infiltration(P<0.01),lymph node metastasis(P<0.01),and TNM stage(P<0.05).Statistical analysis revealed that the clinical data of 102 patients showed that CALU expression was positively correlated with the TNM stage(P=0.021)and T stage(P<0.001)and N stage(P=0.028).CALU knockdown significantly inhibited the migration and invasion abilities of gastric cancer cells(P<0.01),while over-expression obtained the opposite results.Conclusion CALU is highly expressed in gastric cancer tissues and promotes metastasis and invasion of gastric cancer and thus leads to poor prognosis in patients.

Objective:To explore the effectiveness of the"full-chain"integrated medical and elderly care service model in addressing key issues in medical-nursing services such as weak medical support capacity and insufficient provision of community-and home-based medical-nursing services.Methods:The development pathway for the"full-chain"integrated medical-elderly care service standardization system,encompassing core components such as operational mechanisms,smart platforms,policy documents,and quality control systems was systematically outlined.Effectiveness based on dimensions including service coverage,quality improvement,talent development,and social benefits was evaluated.With standardization as the core driver,the'1234567'management model was innovatively implemented.Results:The model leveraged the downward allocation of high-quality resources from tertiary general hospitals to strengthen subdistrict community health service centers.By collaborating with subdistrict elderly-care service centers,it established"subdistrict medical-elderly care and wellness service centers".These centers enhanced the capabilities of"community-embedded elderly-care complexes",including community daytime care centers,established two-way referral channels between medical and elderly care services,aligned with healthcare demands to provide elderly individuals with reliable medical support.It reduced the burden on families and society,stimulated market vitality,boosted domestic demand,promoted the development of integrated medical-elderly care and wellness initiatives,thereby advancing the silver economy.With provincial government endorsement,the model had been applied to 203 communities across 37 counties by the end of 2024.Conclusion:The established"full-chain"integrated medical-elderly care service model facilitates regional high-quality development in integrated care by consolidating healthcare group resources and seamlessly connecting the service chain across hospitals,nursing homes,community institutions,and home-based settings,thereby creating a practical paradigm for comprehensive elderly care service delivery.

Objective To investigate the metabolic characteristics of patients with early-onset type 2 diabetes mellitus(T2DM)and to develop a risk prediction model for microvascular complications.Methods A retrospective study was conducted on 980 T2DM patients admitted for treatment between April 2020 and April 2024.Based on age at diagnosis,the patients were divided into two groups,an early-onset T2DM group(age at diagnosis<40 years,n=265)and a late-onset T2DM group(age at diagnosis≥40 years,n=715).Differences in metabolic indicators between the two groups were compared.Patients in the early-onset group were further divided into a complication subgroup(n=142)and a non-complication subgroup(n=123)based on the presence or absence of microvascular complications.Data on baseline characteristics,metabolic parameters,and laboratory indicators were collected and compared between the two groups.Multivariate logistic regression analysis was used to identify independent risk factors for microvascular complications,and a nomogram prediction model was constructed.The model's discriminative performance was assessed using receiver operating characteristic(ROC)curves,and its calibration was evaluated using calibration curves and the Hosmer-Lemeshow test.Decision curve analysis(DCA)was also performed to assess the model's clinical utility.Results Compared with the late-onset group,patients in the early-onset group exhibited more pronounced metabolic abnormalities,including higher body mass index(BMI),proportion of family history of diabetes mellitus,glycated hemoglobin(HbA1c)levels,total cholesterol(TC),triglycerides(TG),low-density lipoprotein cholesterol(LDL-C),triglyceride-glucose index(TyG),and lactate dehydrogenase(LDH)levels(all P<0.05),along with a shorter disease duration and lower levels of high-density lipoprotein cholesterol(HDL-C)(P<0.05).According to a multivariate analysis,systolic blood pressure(SBP),total bilirubin(TBIL),HDL-C,LDL-C,TyG,and LDH were identified as independent risk factors for microvascular complications in patients with early-onset T2DM.A predictive model based on these factors was established as the follows,Log(P)=-19.915+0.017×SBP-0.136×TBIL-1.241×HDL-C+0.684×LDL-C+0.769×TyG+0.050×LDH.The area under the ROC curve(AUC)was 0.864(95%CI,0.820-0.907),and the Hosmer-Lemeshow test indicated good model fit(χ2=10.286,P=0.246).The slope of the DCA curve was also close to 1.Conclusion The nomogram prediction model based on SBP,TBIL,HDL-C,LDL-C,TyG,and LDH demonstrates good predictive performance for microvascular complications and can provide a reference for clinical risk stratification and individualized intervention.

BACKGROUND:Electromyographic biofeedback therapy has demonstrated unique advantages of non-invasive,real-time feedback,personalized treatment and promotion of neuroplasticity,and can promote the recovery of motor function in patients with spinal cord injury.OBJECTIVE:To review the current application status and therapeutic effects of electromyographic biofeedback combined with exercise therapy,robotic exoskeletons,and virtual reality technology in the recovery of motor function after spinal cord injury.METHODS:Relevant literature was retrieved from CNKI and PubMed databases up to May 2024.The search terms included"spinal cord injury,EMG biofeedback,physical therapy,robotic exoskeleton,VR,motor function,exercise"in both English and Chinese.Finally,71 articles were included for review.RESULTS AND CONCLUSION:Mechanisms by which electromyographic biofeedback therapy promotes spinal cord injury rehabilitation include promoting neural plasticity changes,strengthening neuromuscular connections and improving movement patterns.Electromyographic biofeedback,as an emerging tool for treating spinal cord injury,is often used in conjunction with other therapeutic methods,including exercise therapy,robotic exoskeletons,and VR,to promote the recovery of motor function after spinal cord injury.The effectiveness of combination therapy has been significantly improved.However,there are still some problems and challenges,such as the lack of detailed analysis of the mechanism,the lack of large-scale trials that provide strong evidence for combined efficacy,and the limited adaptability of the technology.Future research can focus on these aspects:to improve the personalization and accuracy of electromyographic biofeedback;to develop new rehabilitation equipment and expand the application areas of electromyographic biofeedback combined with more advanced technologies or engineering equipment;to apply electromyographic biofeedback to gait training systems,respiratory training systems,and limb-linkage rehabilitation systems,so as to improve the accuracy of the feedback and the effect of personalized treatment plans.At the same time,the ease of use and comfort of the equipment will be improved.

Breast cancer is the leading cause of cancer-related mortality among women worldwide and has drawn extensive research attention.Owing to its molecular heterogeneity,drug resistance,and low therapeutic response,single-modality treatments often fail to achieve satisfactory efficacy or broad applicability.Combination therapy,designed based on the pathophysiological characteristics,related signaling pathways,and biomarkers of breast cancer,has emerged as a promising approach for improving therapeutic outcomes.With the advancement of research on combination strategies,the understanding of their molecular mechanisms—particularly key signaling pathways and biomarkers—has become increasingly important.However,comprehensive reviews addressing these molecular mechanisms and synergistic strategies remain scarce.This article summarizes recent advances in combination therapy for breast cancer,providing a comprehensive review of recent combination therapies for breast cancer and their underlying molecular mechanisms,and focusing on key signaling pathways involved in combination therapy and synergistic strategies,thereby providing theoretical insights and reference for researchers,graduate students,and clinicians engaged in the development of novel combination therapeutic strategies for breast cancer and related malignancies.

BACKGROUND:Early diagnosis of pulmonary fibrosis is the foundation for timely antifibrotic drug therapy.Therefore,exploring and discovering ideal biomarkers that can be effectively used for the early diagnosis of pulmonary fibrosis is crucial for the treatment of the disease.OBJECTIVE:To conduct an in-depth analysis of key autophagy-related genes involved in the process of pulmonary fibrosis by means of bioinformatics and machine learning techniques,in order to investigate whether autophagy-related core genes of pulmonary fibrosis can be used as reliable biomarkers in the assessment of the progression of pulmonary fibrosis.METHODS:Two datasets of pulmonary fibrosis,GSE24206 and GSE110147,were downloaded from the Gene Expression Omnibus(GEO)database(a public database developed and maintained by the U.S.National Center for Biotechnology Information to store and share bioinformatics data),and the gene expression matrices of these two datasets were normalized by using the"limma"package in R software.The autophagy-related genes were extracted from GeneCards database(a database created by the U.S.National Center for Biotechnology Information,which automatically integrates gene-centric data from about 200 Web sources,including genomic,transcriptomic,proteomic,genetic,clinical,and functional information).Differential gene analysis was performed on the pulmonary fibrosis dataset,and the common genes were extracted by cross-comparing the differential genes with the autophagy genes,so as to identify autophagy genes that may play a role in the process of pulmonary fibrosis.The intersecting genes were analyzed for functional enrichment and cellular immune infiltration by gene ontology and Kyoto Encyclopedia of Genes and Genomes.Core genes of pulmonary fibrosis associated with autophagy were screened by protein-protein interactions and machine learning,and core genes were subjected to the enrichment analysis.Diagnostic models were constructed from the identified core genes.Calibration curves were used to assess the predictive ability of the line graph model.An external dataset,GSE21369,was used to perform a receiver operating characteristic curve analysis to validate the expression profiles of pulmonary fibrosis genes associated with autophagy,as well as to predict Chinese herbs associated with the genes IL6 and COL1A2 via the Coremine database.Finally,human embryonic lung fibroblasts were cultured and modelled by transforming growth factor-β1 treatment,and the relative expression of genes in the model cells was verified using qRT-PCR.RESULTS AND CONCLUSION:(1)A total of 51 pulmonary fibrosis differential genes and 25 genes intersecting with autophagy genes were obtained.Gene ontology analysis showed that the 25 intersecting genes were related to extracellular matrix tissue,collagen metabolism,collagen pro-fibroblasts,and growth factor binding,etc.The results of Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that they were mainly related to the Phosphatidylinositol 3-kinase/protein kinase B signaling pathway and the signaling pathway of the extracellular matrix-receptor interactions.(2)Immunoinfiltration analysis revealed that the expression of activated memory CD4+T cells,M0 macrophages,and resting dendritic cells was significantly elevated in the pulmonary fibrosis group(P＜0.05),showing a strong correlation.(3)Two autophagy signature genes involved in the progression of pulmonary fibrosis were identified:COL1A2 and IL6.The column-line diagram model showed that the two core genes predicted the onset of pulmonary fibrosis more accurately,and the receiver operating characteristic curve analysis showed that the two characteristic genes had diagnostic significance.COL1A2 and IL6 were related to the cell-cycle pathway,mitogen-activated protein kinase signaling pathway,Janus kinase-signal transduction and activator of transcription signaling pathway and cytokine-cytokine receptor interactions.A total of 20 Chinese herbs were predicted to be related to COL1A2 and IL6 genes,and their efficacies were mainly to clear away heat and detoxify toxins and to invigorate blood and move qi.COL1A2 and IL6 were verified to be highly expressed in pulmonary fibrosis.To conclude,COL1A2 and IL6 may be potential diagnostic biomarkers for pulmonary fibrosis,but its specificity to pulmonary fibrosis needs to be further investigated.

Objective:To explore the effectiveness of the"full-chain"integrated medical and elderly care service model in addressing key issues in medical-nursing services such as weak medical support capacity and insufficient provision of community-and home-based medical-nursing services.Methods:The development pathway for the"full-chain"integrated medical-elderly care service standardization system,encompassing core components such as operational mechanisms,smart platforms,policy documents,and quality control systems was systematically outlined.Effectiveness based on dimensions including service coverage,quality improvement,talent development,and social benefits was evaluated.With standardization as the core driver,the'1234567'management model was innovatively implemented.Results:The model leveraged the downward allocation of high-quality resources from tertiary general hospitals to strengthen subdistrict community health service centers.By collaborating with subdistrict elderly-care service centers,it established"subdistrict medical-elderly care and wellness service centers".These centers enhanced the capabilities of"community-embedded elderly-care complexes",including community daytime care centers,established two-way referral channels between medical and elderly care services,aligned with healthcare demands to provide elderly individuals with reliable medical support.It reduced the burden on families and society,stimulated market vitality,boosted domestic demand,promoted the development of integrated medical-elderly care and wellness initiatives,thereby advancing the silver economy.With provincial government endorsement,the model had been applied to 203 communities across 37 counties by the end of 2024.Conclusion:The established"full-chain"integrated medical-elderly care service model facilitates regional high-quality development in integrated care by consolidating healthcare group resources and seamlessly connecting the service chain across hospitals,nursing homes,community institutions,and home-based settings,thereby creating a practical paradigm for comprehensive elderly care service delivery.

Breast cancer is the leading cause of cancer-related mortality among women worldwide and has drawn extensive research attention.Owing to its molecular heterogeneity,drug resistance,and low therapeutic response,single-modality treatments often fail to achieve satisfactory efficacy or broad applicability.Combination therapy,designed based on the pathophysiological characteristics,related signaling pathways,and biomarkers of breast cancer,has emerged as a promising approach for improving therapeutic outcomes.With the advancement of research on combination strategies,the understanding of their molecular mechanisms—particularly key signaling pathways and biomarkers—has become increasingly important.However,comprehensive reviews addressing these molecular mechanisms and synergistic strategies remain scarce.This article summarizes recent advances in combination therapy for breast cancer,providing a comprehensive review of recent combination therapies for breast cancer and their underlying molecular mechanisms,and focusing on key signaling pathways involved in combination therapy and synergistic strategies,thereby providing theoretical insights and reference for researchers,graduate students,and clinicians engaged in the development of novel combination therapeutic strategies for breast cancer and related malignancies.