1. Animal models of chronic obstructive pulmonary disease: a systematic review
- Author
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Tiantian Feng, Juan Cao, Xiaoting Ma, Xinhua Wang, Xiaolong Guo, Na Yan, Chunling Fan, Shisan Bao, and Jingchun Fan
- Subjects
COPD ,animal models ,modelling method ,review–systematic ,smoke + LPS ,Medicine (General) ,R5-920 - Abstract
ObjectiveExperimental animal models have been used for decades to study the development and progression of chronic obstructive pulmonary disease (COPD). However, there is a lack of methods for constructing animal models of COPD for optimal modelling. This systematic literature review (SLR) aimed to assess the various methods used to establish COPD animal models, highlight their advantages and limitations, and explore more optimized approaches for establishing such models.MethodsA systematic search was performed in four English databases (PubMed, Embase, Web of Science, and the Cochrane Library) and four Chinese databases (Chinese Biomedical Literature Database, China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Database). Of the 8,015 retrieved full-text manuscripts, 453 were selected.ResultsSmoking (n = 140), smoking combined with lipopolysaccharide (LPS) (n = 275), smoking combined with protease drip (PPE) (n = 10), smoking combined with bacteria (n = 23), and smoking combined with particulate matter (PM2.5) (n = 5) were the most used methods for establishing animal models of COPD. Rats and mice were the most frequently selected experimental animals, with male animals accounting for 79.47% of the total. A total of 92.49 and 29.14% of the articles reviewed considered lung pathology of experimental animals only and lung pathology and lung function tests, respectively.ConclusionOur review suggests that the best way to establish an animal model of COPD is to combine smoking with LPS. Although findings from animal models of COPD cannot be directly extrapolated to human COPD, they could provide useful tools for further investigation into human COPD disease.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023407555, Identifier PROSPERO CRD42023407555.
- Published
- 2024
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