Evidence map›Paper›PMID 38903589›Full record

ArticleFrontiers in public health2024

Molecular network characteristics and drug resistance analysis of 392 newly reported MSM HIV/AIDS cases in Chongqing, China.

Chongyang Bai, Tianyu Tan, Long Li, Rongrong Lu, Wei Zhang, Ling Ouyang, Guohui Wu, Chao Zhou

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chongyang Bai *Chongqing Center for Disease Control and Prevention, Chongqing, China.
Tianyu Tan *Chongqing Center for Disease Control and Prevention, Chongqing, China.
Long LiChongqing Center for Disease Control and Prevention, Chongqing, China.
Rongrong LuChongqing Center for Disease Control and Prevention, Chongqing, China.
Wei ZhangChongqing Center for Disease Control and Prevention, Chongqing, China.
Ling OuyangChongqing Center for Disease Control and Prevention, Chongqing, China.
Guohui WuChongqing Center for Disease Control and Prevention, Chongqing, China.
Chao ZhouChongqing Center for Disease Control and Prevention, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To comprehensively investigate the molecular transmission patterns of HIV-1 genotypes among men who have sex with men (MSM) in Chongqing, we employed 392 pol sequences of MSM to construct a phylogenetic tree and gene transmission network. Among the viral subtypes, CRF07_BC accounted for 73.2% (287/392) and CRF01_AE accounted for 20.7% (81/392), emerging as the predominant subtypes in this investigation. Additionally, we observed the presence of CRF55_01B, subtype B, CRF08_BC and other circulating recombinant forms. The HIV-1 molecular network was constructed with a gene distance threshold of 1.5%, resulting in an entry rate of 61.4% (241/392). Within the network, we identified a total of 23 molecular clusters, with the largest cluster being the CRF07_BC molecular cluster comprising 148 node values. Transmitted drug-resistance (TDR) mutations were found in 4.34% of the cases, with 1.79% associated with protease inhibitors (PIs), 0.51% with nucleoside reverse transcriptase inhibitors (NRTIs), and 2.55% with non-nucleoside reverse transcriptase inhibitors (NNRTIs). Statistical analysis indicated a higher enrollment rate in the HIV-1 molecular network among infected individuals with the CRF07_BC subtype, those identifying with same-sex sexual roles as "vers," and individuals with higher education levels. This suggests the need for strengthened investigation and intervention in this population to prevent the formation of larger transmission clusters. Furthermore, continuous monitoring of the HIV-1 molecular dynamics network is necessary to promptly and accurately track changes in molecular epidemic characteristics.

Indexed as

Drug Resistance, ViralHIV-1HIV InfectionsHomosexuality, MalePhylogenyAcquired Immunodeficiency SyndromeAdultChinaGenotypeHumansMaleMiddle AgedMutationHIV-1molecular networkMSMsubtypetransmitted drug-resistance

Identifiers

PMID38903589
PMCPMC11187242

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.