| Title |
HIV-1 diversity in infected individuals in Suzhou and Suqian, China
|
|---|---|
| Published in |
SpringerPlus, June 2016
|
| DOI | 10.1186/s40064-016-2378-z |
| Pubmed ID | |
| Authors |
Chenhao Qin, Ping Zhang, Weiguang Zhu, Fangyuan Hao, Aiping Gu, Ping Fen, Xueming Zhu, Hong Du |
| Abstract |
Jiangsu is one province with severe HIV-1 epidemic in China. However, the molecular epidemiological characterizations of HIV-1 in many cities of Jiangsu remain unclear. A molecular epidemiological investigation was performed based on 38 HIV-positive samples collected from Suzhou and Suqian during 2011-2013. Five HIV-1 genomic fragments, p17, pol, vif-vpr, vpr-env, and C2V3 were amplified and sequenced from these samples. HIV-1 group M subtype of each sample was determined by phylogenetic analyses with the standard reference sequences. Among these infected individuals, 81.6 % (31/38) self-reported to be infected via sexual contacts, including 50.0 % (19/38) via heterosexual contact and 31.6 % (12/38) via homosexual contact. Among 34 samples with available pol or vif-env sequence, 19 (55.9 %) CRF01_AE, 7 (20.6 %) CRF07_BC, 3 (8.8 %) CRF08_BC, and 5 (14.7 %) inter-subtype recombinants were identified. No pure B, B' and C subtypes were found in this cohort. The five recombinants contain one B/C, three CRF01/B and one CRF01/B/C recombinants. These results suggest that CRF01_AE was the most predominant HIV-1 group M subtype and CRF01_AE-involved recombinants were the major recombinant forms. Comparison showed that there was no obvious difference in HIV-1 group M subtype distribution between Jiangsu (including Suzhou and Suqian) and the surrounding provinces (e.g., Shanghai, Anhui, and Shandong). CRF01_AE and CRF07_BC were the top two predominant HIV-1 genotypes in Jiangsu, and less and/or no pure subtype B and C was currently circulating here. We predicted that more CRF01/CRF07 recombinants, but fewer B/C recombinants will be generated in Jiangsu in future. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
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 | 4 | 44% |
| Researcher | 1 | 11% |
| Professor | 1 | 11% |
| Unknown | 3 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 2 | 22% |
| Biochemistry, Genetics and Molecular Biology | 1 | 11% |
| Computer Science | 1 | 11% |
| Economics, Econometrics and Finance | 1 | 11% |
| Medicine and Dentistry | 1 | 11% |
| Other | 0 | 0% |
| Unknown | 3 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 August 2016.
All research outputs
#14,268,160
of 22,880,230 outputs
Outputs from SpringerPlus
#773
of 1,851 outputs
Outputs of similar age
#201,761
of 352,733 outputs
Outputs of similar age from SpringerPlus
#110
of 237 outputs
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