Objective: To analyse seasonal influenza epidemic situation in 2006, and to analyse the genetic and antigenic characteristics of viral hemagglutinin (HA) gene.
Methods: The single-way hemagglutination inhibition (HI) tests were used to test the antigenic characteristics of these viruses from influenza surveillance network, and the HA1 genes were sequenced based on the antigenic test results according to different isolation times and sites.
Results: The influenza virus types A and B co-circulated in 2006. influenza A H1N1 subtype and Victoria-like B influenza circulated preponderantly during this epidemic season. The HA1 gene sequence of H1N1 viruses showed that 192, 193, 196, 198 positions (located at antigenic site B) have an amino acid substitute, compared with the last circulating strain A/Hubeihongshan/53/2005(H1N1). Two amino acid changes at 142 and 144 positions compared with A/Yunnan/1145/2005 (H3N2). There was no change in influenza B viruses either Victoria-like B or Yamagata-like B virus, i.e . antigenic characteristics is analogous to B/shenzhen/155/2005 and B/tianjin/144/2005, respectively.
Conclusion: The H1N1 and H3N2 influenza viruses had changing antigenic and genetic characteristics in 2006. Influenza virus types B did not change in 2006.
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Cell Rep
January 2025
Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA. Electronic address:
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Chemistry of Natural and Microbial Products Department, Pharmaceutical and Drug Industries Research Institute, National Research Centre, 33 El Buhouth St, Dokki-Giza, Egypt.
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State Key Laboratory of NBC Protection for Civilian, Beijing, 102205, China. Electronic address:
Significant efforts were currently being made worldwide to develop a tool capable of distinguishing between various harmful viruses through simple analysis. In this study, we utilized fluorescence excitation-emission matrix (EEM) spectroscopy as a rapid and specific tool with high sensitivity, employing a straightforward methodological approach to identify spectral differences between samples of respiratory infection viruses. To achieve this goal, the fluorescence EEM spectral data from eight virus samples was divided into training and test sets, which were then analyzed using random forest and support vector machine classification models.
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Ōmura Satoshi Memorial Institute, Kitasato University, 5-9-1 Shirokane, Minato-Ku, Tokyo, 108-8641, Japan.
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