【Animal Modeling】-Asthma animal model based on data mining

  Purpose: Analyze the elements of asthma animal model modeling, improve the success rate of the model, and provide a methodological reference for the effective evaluation of the tested drugs.

  Methods: Use asthma and animal models as the subject headings to search for journal documents related to China Knowledge Network (January 2009 to August 2019) to find the types of experimental animals, methods of excitability and sensitization, and methods of collection , Testing indicators, etc. Establish a database and perform statistical analysis.

  Result: included in 118 journal articles that meet the criteria. Among them, the most used experimental animals are BALB/c mice (43 times, 36.4%) and SD rats (42 times, 35.5%). The excitation method is aerosol excitation (102 times, accounting for 86.4%), the most commonly used sensitization method is ovalbumin (OVA) sensitization (107 times, accounting for 90.6%), and the most frequently detected index is lung tissue Pathology (92 times), accounting for 77.9%. ). Serum biochemical index (49 times, 41.5%), number of cells in alveolar lavage fluid (42 times, 35.6%), lung tissue immunohistochemistry (40 times, 33.9%), biochemistry in the supernatant of alveolar lavage fluid Index chemical index (39 times, 33.1)%), etc.

  Conclusion: When establishing an asthma animal model, use BALB/C mice or SD rats as experimental animals, and use sprays to stimulate allergies. Using OVA as a sensitizing antigen can increase the success rate of the model. Index selection recommends that the lungs should select histopathology, serum biochemical indexes, cell classification and the number of alveolar lavage fluids to effectively evaluate the tested drugs and provide a basis for better asthma animal research.