Application analysis of a chronic obstructive pulmonary disease model by data mining

doi:10. 3969 / j.issn.1671-7856. 2022. 07. 002

Home > Archive>Volume 32, Issue 7, 2022 >10-17. DOI:10. 3969 / j.issn.1671-7856. 2022. 07. 002

Application analysis of a chronic obstructive pulmonary disease model by data mining
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                        10. 3969 / j.issn.1671-7856. 2022. 07. 002
                    
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                        LI LeiLI Lei
1. Beijing University of Chinese Medicine, Beijing 100029, China. 2. the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
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WU DongliangWU Dongliang
1. Beijing University of Chinese Medicine, Beijing 100029, China. 2. the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
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LI ShangdianLI Shangdian
1. Beijing University of Chinese Medicine, Beijing 100029, China. 2. the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
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YAN Yue2YAN Yue
the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
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SHI Qi2SHI Qi
the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
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LI Chunlei2LI Chunlei
the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
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LI Youlin2LI Youlin
the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
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Affiliation:1. Beijing University of Chinese Medicine, Beijing 100029, China. 2. the 2nd Department of Pulmonary Disease, China-Japan Friendship Hospital, Key Unit of State Administration of Traditional Chinese Medicine (Pneumonopathy Chronic Cough and Dyspnea), Beijing Key Laboratory of Prevention and Treatment of Allergic Diseases with Traditional Chinese Medicine (BZ0321), Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Beijing 100029
Clc Number:R-33
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Abstract:

Objective To explore the modeling elements of an animal model of chronic obstructive pulmonary disease, which may provide a method ological reference to establish this model. Methods We searched for literature from January 2011 to July 2021 in CNKI and Wanfang databases using an animal model of chronic obstructive pulmonary disease combined with animal models as the subject words, and sorted out the animal species and model involved in the model. Then, we established a database for statistical analysis with method, cycles, detection indicators, administration time and positive control drugs. Results A total of 176 articles were included. The most commonly used animals for the COPD model were SD rats (83 times, 47. 16%), Wistar rats (59 times, 33. 52%), and C57 mice (14 times, 7. 95%), which tended to be male (140 times, 79. 55%). Most modeling method were smoke exposure combined with lipopolysaccharide (91 times, 52%) or simple smoke exposure (34 times, 19. 43%). The modeling cycle was mostly within 3 months (147, 83. 52%). The most detected indicators were lung histopathology ( 137 times, 24. 82%), lung function ( 79 times, 14. 31%), general condition (63 times, 11. 41%), and alveolar lavage fluid (56 times, 10. 14%). Conclusions Using SD/ Wistar rats or C57 mice as experimental animals under smoke exposure combined with lipopolysaccharide instillation or simple smoke exposure within 3 months effectively improves the success rate of COPD models. Model evaluation indicators suggest that the result of lung histopathology, lung function, general condition and alveolar lavage fluid should be integrated.

Key words:chronic obstructive pulmonary disease; animal model; data mining

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Received:October 13,2021
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Online: November 09,2022
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