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Development of an Influenza Rapid Diagnostic Kit Specific for the H7 Subtype

Overview of attention for article published in Frontiers in Microbiology, June 2018
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Title
Development of an Influenza Rapid Diagnostic Kit Specific for the H7 Subtype
Published in
Frontiers in Microbiology, June 2018
DOI 10.3389/fmicb.2018.01346
Pubmed ID
Authors

Kiyoko Iwatsuki-Horimoto, Jianzhong Shi, Xiurong Wang, Yuko Sakai-Tagawa, Mutsumi Ito, Kazushi Murakami, Tiago J. da Silva Lopes, Kazunari Nakaishi, Seiya Yamayoshi, Satoshi Watabe, Hualan Chen, Yoshihiro Kawaoka

Abstract

Since the spring of 2013, human infections with H7N9 viruses have been detected in China. Some of these viruses have become highly pathogenic. Highly and low pathogenic avian influenza H7N9 viruses are currently co-circulating with the seasonal influenza A viruses H3N2 and H1N1pdm09. Prompt identification and isolation of H7N9 patients is one measure to prevent the spread of H7N9 virus and help prevent a pandemic. The majority of commercially available point-of-care rapid influenza diagnostic kits can differentiate between influenza A and B viruses, but cannot distinguish between H7N9 viruses and seasonal influenza A viruses. Accordingly, we have developed a rapid diagnostic kit specific for the H7 subtype that is accessible, easy to use. Although the detection limit of this H7 kit is one-tenth lower than that of a commercially available rapid influenza A and B diagnostic kit of similar design, except for the specificity of the monoclonal antibodies used, this kit is highly specific, detecting only H7-subtype influenza viruses, including the recent highly pathogenic H7N9 viruses from humans, and does not show any non-specific reactions with other HA subtypes. This H7 kit will be of value for the early detection of H7N9-infected patients.

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Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 33%
Student > Ph. D. Student 2 22%
Other 1 11%
Researcher 1 11%
Professor > Associate Professor 1 11%
Other 0 0%
Unknown 1 11%
Readers by discipline Count As %
Immunology and Microbiology 3 33%
Biochemistry, Genetics and Molecular Biology 2 22%
Agricultural and Biological Sciences 1 11%
Veterinary Science and Veterinary Medicine 1 11%
Unknown 2 22%