基于数据挖掘的糖尿病心肌病动物模型应用分析OA

Objective To establish an animal model reflecting the pathogenesis of diabetic cardiomyopathy(DCM)by analysis of key modeling elements and detection indexes involved in the construction of animal models of DCM,to provide valuable references to improve the success rate of modeling and establish a standard for DCM animal models.Methods We searched the CNKI,Wanfang,VIP,PubMed,and Web of Science databases for the past 10 years to identify relevant articles on animal experiments of DCM.We organized and summarized the data including experimental animal species,gender,age,body weight,modeling method,publication volume and quality,types of positive control drugs and administration cycles,detection indexes,and modeling standards.We then established a database and carried out a statistical analysis of the result using Excel 2021,Origin 2022,SPSS Modeler 18.0,and Cytoscape 3.10.3.Results A total of 228 papers were included in the analysis.Most of the DCM animal models were prepared in male Sprague-Dawley rats induced by a high-sugar and high-fat diet combined with streptozotocin.Modeling success was generally assessed by blood glucose and echocardiography.Western blot and hematoxylin/eosin staining were frequently used,and in studies containing positive control drugs,the most frequently used drug was metformin,followed by rosiglitazone.Conclusions DCM animal models currently lack a systematic evaluation of Chinese medicine syndrome patterns,and the modeling method and standards have not been unified.Further studies are therefore needed to improve the modeling method and evaluation system for DCM animal modes.