Objective To explore the shared mechanisms of genes related to three common chronic diseases non-alcoholic fatty liver disease(NAFLD),type 2 diabetes mellitus(T2DM)and atherosclerosis(AS)with ageing as well as potential therapeutic agents by using bioinformatics analysis,machine learning algorithms and molecular docking methods and techniques.Methods Ageing-related genes were collected and organized from AgeingAtlas,CellAge,GenAge,and MSigDB databases.After taking the intersection of genes related to NAFLD,T2DM and AS obtained from databases such as CTD,DisGeNET,GeneCards,OMIM,PharmGKB,and TTD and the gene sets obtained based on the GEO differential gene analysis,we obtained the set of related disease genes for these three common chronic diseases.The KEGG pathway enrichment analysis was performed on the ageing gene set and the three disease-related gene sets using the clusterProfiler package,and the intersection was taken.The enriched genes in the KEGG pathway were merged and imported into the STRING database;the PPI network was constructed.We analyzed the core sub-modules in the PPI network using the MCODE tool and calculated the essential values of Nim and Cim for each node and module.Meanwhile,three machine learning models were used to screen the feature genes:the Lasso regression model,the Boruta algorithm,and the random forest model.The HIT2.0 database was utilized to find the targeted TCM small molecules related to the key feature genes.Small molecules were evaluated and analyzed by ADMET using SwissADME and ADMETlab 3.0 online system.The molecular docking method was utilized to dock the key action targets and screen small molecules.Results A total of 1 325,616,78,and 597 genes related to ageing,NAFLD,T2DM,and AS were obtained.The KEGG pathway enrichment analysis results for ageing and the three diseases were taken to intersect to get two shared intersecting pathways containing 243 genes.The PPI network was constructed,and Cluster 2 had the highest Cim value among the three core submodules.According to the results of signature gene screening,combined with PPI network module analysis results,four signature genes related to ageing were found:CDK6,CDKN1A,MYC,and PTEN.These four targets have 94 potential TCM small molecule candidates,among which resveratrol(RSV)is a TCM small molecule common to these four targets.The ADMET evaluation showed that it had good drug-forming properties.The PTEN target had a high Nim value,and molecular docking of RSV with PTEN showed good binding stability.Conclusion A potential herbal small molecule,RSV,was identified from the perspective of ageing,which may prevent and treat three common chronic diseases,namely,NAFLD,T2DM and AS,by regulating the key gene PTEN.

Objective To explore the shared mechanisms of genes related to three common chronic diseases non-alcoholic fatty liver disease(NAFLD),type 2 diabetes mellitus(T2DM)and atherosclerosis(AS)with ageing as well as potential therapeutic agents by using bioinformatics analysis,machine learning algorithms and molecular docking methods and techniques.Methods Ageing-related genes were collected and organized from AgeingAtlas,CellAge,GenAge,and MSigDB databases.After taking the intersection of genes related to NAFLD,T2DM and AS obtained from databases such as CTD,DisGeNET,GeneCards,OMIM,PharmGKB,and TTD and the gene sets obtained based on the GEO differential gene analysis,we obtained the set of related disease genes for these three common chronic diseases.The KEGG pathway enrichment analysis was performed on the ageing gene set and the three disease-related gene sets using the clusterProfiler package,and the intersection was taken.The enriched genes in the KEGG pathway were merged and imported into the STRING database;the PPI network was constructed.We analyzed the core sub-modules in the PPI network using the MCODE tool and calculated the essential values of Nim and Cim for each node and module.Meanwhile,three machine learning models were used to screen the feature genes:the Lasso regression model,the Boruta algorithm,and the random forest model.The HIT2.0 database was utilized to find the targeted TCM small molecules related to the key feature genes.Small molecules were evaluated and analyzed by ADMET using SwissADME and ADMETlab 3.0 online system.The molecular docking method was utilized to dock the key action targets and screen small molecules.Results A total of 1 325,616,78,and 597 genes related to ageing,NAFLD,T2DM,and AS were obtained.The KEGG pathway enrichment analysis results for ageing and the three diseases were taken to intersect to get two shared intersecting pathways containing 243 genes.The PPI network was constructed,and Cluster 2 had the highest Cim value among the three core submodules.According to the results of signature gene screening,combined with PPI network module analysis results,four signature genes related to ageing were found:CDK6,CDKN1A,MYC,and PTEN.These four targets have 94 potential TCM small molecule candidates,among which resveratrol(RSV)is a TCM small molecule common to these four targets.The ADMET evaluation showed that it had good drug-forming properties.The PTEN target had a high Nim value,and molecular docking of RSV with PTEN showed good binding stability.Conclusion A potential herbal small molecule,RSV,was identified from the perspective of ageing,which may prevent and treat three common chronic diseases,namely,NAFLD,T2DM and AS,by regulating the key gene PTEN.

In order to solve the problems in traditional health management experimental teaching, such as high cost, safety and difficult repeatability, a virtual simulation experimental teaching platform for health management combined with Traditional Chinese Medicine (TCM) characteristics has been constructed by using virtual simulation, multimedia, and human-computer interaction technologies, which comprises TCM constitution identification, TCM health management and health management service process. Through the combination of virtual simulation and reality situation, the platform has formed an online and offline model of experimental teaching, which has improved the innovation and practice ability of students and enhanced the teaching quality.

Objective:To explore the design of an evaluation index system with feasibility and appropriateness, and to conduct cloud model evaluation, in order to provide reference for the high-quality development of public traditional Chinese medicine(TCM) medical institutions in China.Methods:The Delphi method and analytic hierarchy process were used to construct an evaluation index system for public TCM medical institutions and calculate the index weights. Then the cloud model theory was applied to comprehensively evaluate the index system.Results:The index system of TCM medical institutions including 5 primary indicators and 12 secondary indicators of " external governance" module and 9 primary indicators and 62 secondary indicators of " internal management" module was constructed. The cloud model of the index system was(4.608, 1.022, 0.151), and the cloud rank was in the range of " very good" .Conclusions:The indicator system constructed in this study is relatively objective, scientific, and reasonable. While ensuring the accuracy and credibility of the evaluation results, it also adds evaluation information, which has certain guiding significance for promoting the high-quality development of public TCM medical institutions.

OBJECTIVE: A method based on dubious condition of information entropy was introduced and applied to discuss a complexity problem in the analysis of correlation between traditional Chinese medicine (TCM) syndrome and season. METHODS: Eight hundred and seventy one cases of chronic virus hepatitis B (hepatitis B) with TCM clinical data were analyzed by information entropy method. RESULTS: It was found that hepatitis B with Yin deficiency of liver and kidney happened more often in summer than in other seasons. CONCLUSION: It is inferred that the difference of seasons may influence the variation of TCM syndromes.