[Animal modeling] - Application analysis of asthma animal model based on data mining

  Objective To analyze the modeling factors of asthma animal models, and to provide methodological reference for improving the success rate of modeling and effectively evaluating the tested drugs.

  Methods With asthma and animal models as the subject words, search the relevant journals and literatures of CNKI (January 2009 to August 2019), collect the types of experimental animals, excitation methods, sensitization methods, detection indicators, etc., establish a database, and conduct statistical analysis.

  Results 118 articles were included in the standard journals, of which BALB/c mice (43 times, 36.4%) and SD rats (42 times, 35.5%) were the most frequently used animals, aerosol challenge (102 times, 86.4%) was the most frequently used method, and ovalbumin (OVA) sensitization (107 times, 90.6%) was the most frequently used method, The most frequently detected indicators were 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%), and alveolar lavage fluid supernatant biochemical indicators (39 times, 33.1%).

  Conclusion When establishing asthma animal model, BALB/C mice or SD rats are used as experimental animals, aerosol sensitization is conducted by means of aerosol stimulation, and OVA is used as sensitization antigen, which can improve the success rate of the model. It is suggested to select lung tissue pathology, biochemical indicators in serum, classification and counting of alveolar lavage fluid cells to effectively evaluate the tested drugs, so as to provide a basis for better experimental research on asthma animals.