Application analysis of asthma animal model based on data mining

  Objective   Analyze the elements of asthma animal model modeling, and provide a methodological reference for improving the success rate of modeling and effectively evaluating the tested drugs. Methods Using asthma and animal models as the subject terms, searching the relevant journals of China HowNet (January 2009 to August 2019), collecting experimental animal types, excitation methods, sensitization methods, detection indicators, etc., establishing a database and performing statistics analysis. Results 118 articles of journals meeting the criteria were included. Among them, the most used experimental animal types were BALB/c mice (43 times, 36.4%) and SD rats (42 times, 35.5%), and the most used challenge method For nebulization excitation (102 times, 86.4%), the most used sensitization method is ovalbumin (OVA) sensitization (107 times, 90.6%), and the most detected index is lung tissue pathology (92 times) , 77.9%), serum biochemical indicators (49 times, 41.5%), alveolar lavage fluid cell classification count (42 times, 35.6%), lung tissue immunohistochemistry (40 times, 33.9 %), biochemical indicators in the supernatant of alveolar lavage fluid (39 times, 33.1%), etc. Conclusion When establishing an animal model of asthma, using BALB/C mice or SD rats as experimental animals, nebulizing sensitization by nebulization, and using OVA as the sensitizing antigen can improve the success rate of the model. It is recommended to select lung Histopathology, serum biochemical indicators, cell classification and counts in alveolar lavage fluid can effectively evaluate the tested drugs and provide a basis for better animal experimental research on asthma.