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Molecular linkage tracing of HIV-1 transmission events in seroconcordant couples in Guangxi Province, Southeastern China

Overview of attention for article published in SpringerPlus, November 2016
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Title
Molecular linkage tracing of HIV-1 transmission events in seroconcordant couples in Guangxi Province, Southeastern China
Published in
SpringerPlus, November 2016
DOI 10.1186/s40064-016-3578-2
Pubmed ID
Authors

Nidan Wang, Zhenzhu Tang, Yijia Li, Peiyan Xie, Yiming Shao

Abstract

Guangxi Province in Southeastern China has one of the highest HIV-1 infection and transmission rates in stable couples. However, the mode of transmission at the molecular level has seldom been reported amongst this group. It is important to investigate this issue to support the treatment-as-prevention approach and for efficient interventions. HIV-1 subgenomic regions (1.2 kb of pol and a 660-bp env C2V5 fragment) were sequenced in 42 couples. A couple linkage assessment was performed by phylogenetic analysis of sequences and Bayesian analysis of genetic distances. A subset of pairs was selected for single-genome amplification. Thirty-five pairs (83.3 %, 35/42) were identified as linked, 3 pairs (7.1 %, 3/42) were identified as indeterminate, and 4 pairs (9.5 %) were identified as unlinked. The predominant intra-couple-transmitted HIV-1 subtype was CRF01_AE (80 %, 28/35). The median genetic distance of linked couples was 0.5 %. The majority of HIV-1 transmission events in this study occurred within the partnership, and the predominant HIV-1 subtype was CRF01_AE. Further research on the mode of HIV transmission in other locations is needed.

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Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 25%
Student > Doctoral Student 1 13%
Student > Bachelor 1 13%
Unknown 4 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 13%
Nursing and Health Professions 1 13%
Agricultural and Biological Sciences 1 13%
Medicine and Dentistry 1 13%
Unknown 4 50%