US Develops Mathematical Models to Predict Immune Response to Influenza Viruses in the Body

Researchers at the University of Rochester in the United States published a report in the new issue of the American Journal of Virology that they have developed a mathematical model that can predict the body's immune response to influenza A viruses such as the H1N1 influenza virus. This result will help researchers find effective antiviral therapy.

When the human body is infected with the influenza virus, its immune system responds immediately - the antigen-presenting cell that serves as a "scoop" will present the virus "looking" to special white blood cells, such as T cells. On the one hand, T cells directly attack and eliminate virus-infected cells, and they also assist other immune cells such as B cells to produce antibodies that specifically deal with viruses.

A mathematical model developed by researchers at the University of Rochester in the United States can simulate a variety of immune responses, including the pathogenicity of the influenza virus in the lungs and lymph glands, the number of T and B cells responding, the role of antigen-presenting cells, etc. . Researchers learned from this mathematical model that infection with influenza viruses for a long time can affect the production of T cells and inhibit the function of antigen-presenting cells. The mathematical model also confirms that antiviral therapy is the most effective way to slow the virus's continued transmission within two days after infection by the virus.