The Application Of Cell Array For Detecting The Central Nervous System Infectious Disease

As the incidence of an infectious disease and the complicated pathogeny, it is necessary to establish a clinical method to detect the pathogenic microbiology to get effective therapy. There have been some research and commercial products to detect the infection due to pathogenic microbiology, but in China there is no products used to clinical detection. The research bases on the plateform of cell array and chooses 10 high-incidence viruses as our research object, which can result in central nervous system infectious disease. The aim is to establish a rapid, high-throught method to detect the pathogenic microbiology of the central nervous system infectious disease.The research used the ATCC standard viruses and the CCTCC cell line, applied the classical cell culturing method to ensure the best condition of infection. At the same time, the research prepared the diagnosis of central nervous system infectious disease diagnostic cell array, applied the indirect immunofluorescence technique as the detecting method and the commercial mono-antibody as the quality control, and made the positive detecting standard and typical fluorescent model. According to the detecting standard, we detected the positive serum samples as quality control, the results are effective and accurate.Comparing the central nervous system infectious disease diagnostic cell array and the similar products, the result of the both method is almost same. The accurate dectection rate of our method (20/20) is little higher than others (18/20). By contrast experiment, it is proved that the method is simpler, the combination of pathogenic microbiology is more pertinent, and the detection is also more objective.We choose 100 clinical samples ( 85 of them are positive, 15 of them are negative) to classify the virus which cause the central nervous system infectious disease, applying the established dectecting method in our research. We detected that 78 samples were positive, the result matched the clinical, and the 15 negative samples were also detected without false positive result. So it is significant to the rapid disease detection.