Gao Jie, Wang Kang, Ding Tao, Zhu Shanshan
School of Science, Jiangnan University, Wuxi, 214122, China.
Key laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
BMC Syst Biol. 2017 Sep 21;11(Suppl 4):85. doi: 10.1186/s12918-017-0460-y.
Influenza A virus is prone to mutation and susceptible to human beings and spread in the crowds when affected by the external environment or other factors. It is very necessary to forecast influenza A pandemic outbreak.
This paper studies the different states of influenza A in the method of dynamical network biomarkers. Through establishing protein dynamical network biomarkers of influenza A virus protein, a composite index is ultimately obtained to forecast influenza A pandemic outbreak.
The composite index varies along with the state of pandemic influenza virus from a relatively steady state to critical state before outbreak and then to the outbreak state. When the composite index continuous decreases for 2 years and increases of more than o.1 suddenly, it means the next year is normally in the outbreak state. Therefore, we can predict and identify whether a certain year is in the critical state before influenza A outbreak or outbreak state by observing the variation of index value. Meanwhile, through data analysis for different countries influenza A pandemic outbreak in different countries can also be forecasted.
This indicates the composite index can provide significant warning information to detect the stage of influenza A, which will be significantly meaningful for the warning and prevention of influenza A pandemic.
甲型流感病毒易于突变，易感染人类，并在受到外部环境或其他因素影响时在人群中传播。预测甲型流感大流行的爆发非常必要。
本文采用动态网络生物标志物的方法研究甲型流感的不同状态。通过建立甲型流感病毒蛋白的蛋白质动态网络生物标志物，最终获得一个综合指数来预测甲型流感大流行的爆发。
综合指数随着大流行性流感病毒的状态而变化，从相对稳定状态到爆发前的临界状态，再到爆发状态。当综合指数连续两年下降且突然增加超过0.1时，意味着下一年通常处于爆发状态。因此，我们可以通过观察指数值的变化来预测和识别某一年是否处于甲型流感爆发前的临界状态或爆发状态。同时，通过数据分析，还可以预测不同国家甲型流感大流行的爆发情况。
这表明综合指数可以为检测甲型流感的阶段提供重要的预警信息，这对于甲型流感大流行的预警和预防具有重要意义。
