中药新药与临床药理2026，Vol.37Issue(3)：520-530,11.DOI:10.19378/j.issn.1003-9783.2026.03.014
基于数据挖掘分析肺纤维化动物模型的特点及构建药效指标评价体系
Data Mining-Based Analysis of Characteristics of Animal Models of Pulmonary Fibrosis and Construction of an Efficacy Indicator Evaluation System
摘要
Abstract
Objective To summarize the characteristics of animal models of pulmonary fibrosis and establish an efficacy indicator evaluation system using data mining methods.Method Literature related to pharmacological studies of pulmonary fibrosis in animals was retrieved from databases including China National Knowledge Infrastructure(CNKI),Wanfang,VIP,PubMed,Web of Science,and Embase.The modeling methods,intervention drugs,and other aspects of animal models of pulmonary fibrosis were summarized and analyzed.The types and methods of detection indicators were statistically analyzed to form an efficacy indicator system for animal studies of pulmonary fibrosis.Results A total of 1 174 articles were included.Common inducing factors for animal modeling included antineoplastic drugs,environmental/occupational exposure particles,and physical factors.C57 BL/6 mice and SD rats were the main research subjects.Among these,bleomycin-induced pulmonary fibrosis models via non-invasive tracheal drip were the most common.Common intervention drugs in animal efficacy studies of pulmonary fibrosis included chemical drugs,inhibitors/agonists,natural products,and traditional Chinese medicine compounds.Detection indicators in animal efficacy studies of pulmonary fibrosis were categorized into seven types:general condition,pulmonary function,histopathology,extracellular matrix,epithelial-mesenchymal transition(EMT),cytokines,and oxidative stress.General condition indicators primarily included body weight,lung coefficient,and survival analysis.Pulmonary function indicators mainly included forced vital capacity,dynamic lung compliance,and tidal volume.Common lung histopathological staining methods included hematoxylin-eosin(HE)staining,Masson staining,and Sirius red staining.Extracellular matrix detection indicators mainly included type Ⅰ collagen,hydroxyproline,and fibronectin.EMT indicators included α-smooth muscle actin(α-SMA),E-cadherin,and vimentin.Cytokine detection indicators mainly included transforming growth factor-β1(TGF-β1),tumor necrosis factor-α(TNF-α),and interleukin-6(IL-6).Oxidative stress detection indicators mainly included malondialdehyde(MDA),superoxide dismutase(SOD),and glutathione(GSH).Based on detection indicators with a frequency≥200 times,strongly recommended indicators for animal efficacy studies of pulmonary fibrosis were identified as:general condition(body mass,lung coefficient),lung pathology(HE staining,Masson staining,etc.),extracellular matrix(hydroxyproline,type Ⅰ and Ⅲ collagen,fibronectin),EMT(α-SMA),and cytokines(TNF-α,IL-6/IL-1β,TGF-β1).Conclusion This study provides additional references for the construction of animal models of pulmonary fibrosis and the establishment of an efficacy indicator evaluation system.关键词
肺纤维化/数据挖掘/动物模型/应用分析/药效指标Key words
pulmonary fibrosis/data mining/animal model/application analysis/therapeutic indicators分类
医药卫生引用本文复制引用
杨帆,谢云云,彭云鹏,梁莹玉,田燕歌,李建生..基于数据挖掘分析肺纤维化动物模型的特点及构建药效指标评价体系[J].中药新药与临床药理,2026,37(3):520-530,11.基金项目
国家自然科学基金区域联合重点项目(U23A20503) （U23A20503）
河南省科技研发计划联合基金(优势学科培育类)重点项目(232301420020). （优势学科培育类）
