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Prediction of the next highly pathogenic avian influenza pandemic that can cause illness in humans

Overview of attention for article published in Infectious Diseases of Poverty, November 2015
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Title
Prediction of the next highly pathogenic avian influenza pandemic that can cause illness in humans
Published in
Infectious Diseases of Poverty, November 2015
DOI 10.1186/s40249-015-0083-8
Pubmed ID
Authors

Zhong-Wei Zhang, Ting Liu, Jian Zeng, Yang-Er Chen, Ming Yuan, Da-Wei Zhang, Feng Zhu, Shu Yuan

Abstract

In recent years, avian influenza viruses (AIVs) have seriously threatened human health. Questions such as: why do AIVs infect humans?, how quickly can an AIV become pandemic?, and which virus is the most dangerous? cannot be sufficiently answered using current bioinformatic studies. Secondary structures and energies of representative 5'-untranslated region (UTR) of the HA gene were calculated. Then their secondary structures and energies were re-calculated after one or two nucleotide substitutions were introduced into the HA 5'-UTR. Phylogenetic trees on the basis of hemagglutinin (HA) and polymerase basic protein 2 (PB2) amino acid sequences and HA 5'-UTR nucleotide sequences were constructed. The connection between the energy and translation efficiency of 5'-UTR was confirmed by in vitro coupled transcription/translation assay. The simplicity of the secondary structure of the 5'-UTR of the HA gene determines the overall virus replication rate and transmission potential. Point mutation assays show that the 5'-UTR sequences of the HA gene in the influenza subtypes H2N2, H3N2, and H7N9 have greater variation potentials than other virus subtypes. Some high-virulent strains of avian influenza might emerge in the next two to three years. The H2N2 subtype, once disappeared in humans, may stage a comeback. The current outbreak of H7N9 may become pandemic and cause even more deaths, if one or two bases are substituted in the 5'-UTR sequence of the HA gene.

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Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 28%
Student > Ph. D. Student 6 24%
Student > Bachelor 3 12%
Student > Master 2 8%
Professor 1 4%
Other 1 4%
Unknown 5 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 28%
Biochemistry, Genetics and Molecular Biology 5 20%
Medicine and Dentistry 2 8%
Veterinary Science and Veterinary Medicine 2 8%
Environmental Science 1 4%
Other 3 12%
Unknown 5 20%