Evidence map›Paper›PMID 26862570›Full record

ArticleData in brief2016

Frequent detection of CXCR4-using viruses among Brazilian blood donors with HIV-1 long-standing infection and unknown clinical stage: Analysis of massive parallel sequencing data.

Rodrigo Pessôa, Sabri S Sanabani

Open access · goldAbstract read
In one paragraph

Article in Data in brief, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 92% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

2 authors at 1 institution in 1 country.

Rodrigo PessôaDepartment of Pathology, Hospital das Clínicas, School of Medicine, University of São Paulo, São Paulo, Brazil.
Sabri S SanabaniDepartment of Pathology, Hospital das Clínicas, School of Medicine, University of São Paulo, São Paulo, Brazil.
Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The determination of viral tropism is critically important and highly recommended to guide therapy with the CCR5 antagonist, which does not inhibit the effect of X4-tropic viruses. Here, we report the prevalence of HIV-1×4 HIV strains in 84 proviral DNA massively parallel sequencing "MPS" data from well-defined non-recently infected first-time Brazilian blood donors. The MPS data covering the entire V3 region of the env gene was extracted from our recently generated HIV-1 genomes sequenced by a paired-end protocol (Illumina). Of the 84 MPS data samples, 63 (75%) were derived from donors with long-standing infection and 21 (25%) were lacking stage information. HIV-1 tropism was inferred using Geno2pheno (g2p) [454] algorithm (FPR=1%, 2.5%, and 3.75%). Among the 84 data samples for which tropism was defined by g2p2.5%, 13 (15.5%) participants had detectable CXCR4-using viruses in their MPS reads. Mixed infections with R5 and X4 were observed in 11.9% of the study subjects and minority X4 viruses were detected in 7 (8.3%) of participants. Nine of the 63 (14.3%) subjects with LS infection were predicted by g2p 2.5% to harbor proviral CXCR4-using viruses. Our findings of a high proportion of blood donors (15.5%) harboring CXCR4-using viruses in PBMCs may indicate that this phenomenon is common. These findings may have implications for clinical and therapeutic aspects and may benefit individuals who plan to receive CCR5 antagonists.

Indexed as

Human immunodeficiency virus type 1Massively parallel sequencingViral tropism

Identifiers

PMID26862570
PMCPMC4706613
OpenAlexW2210481497

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.