Evidence map›Paper›PMID 24862329›Full record

ReviewCurrent HIV research2014

Bioinformatic analysis of HIV-1 entry and pathogenesis.

Benjamas Aiamkitsumrit, Will Dampier, Gregory Antell, Nina Rivera, Julio Martin-Garcia, Vanessa Pirrone, Michael R Nonnemacher, Brian Wigdahl

Abstract readReview
In one paragraph

Review in Current HIV research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

14 citing papers in PubMed, 24 citations in OpenAlex.

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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 at 1 institution in 1 country.

Benjamas Aiamkitsumrit
Will Dampier
Gregory Antell
Nina Rivera
Julio Martin-Garcia
Vanessa Pirrone
Michael R Nonnemacher
Brian WigdahlDepartment of Microbiology and Immunology, Drexel University College of Medicine, 245 N. 15th Street, Philadelphia, PA 19102. bwigdahl@drexelmed.edu.
Bentham Science Publishers (China) · CN

Funding

Viral Gene Editing and Bioinformatics Core for Institution # 269291P30MH092177 · NIMH · TEMPLE UNIV OF THE COMMONWEALTH · PI Ilker Kudret Sariyer · 2011 to 2026
$24.9M
Interdisciplinary And Translational Research Training In NeurohivT32MH079785 · NIMH · TEMPLE UNIV OF THE COMMONWEALTH · PI Kamel Khalili · 2008 to 2026
$5.4M
High Specificity HIV-1 Markers Predictive of Neuro-AIDSR01DA019807 · NIDA · DREXEL UNIVERSITY · PI WIGDAHL, BRIAN · 2004 to 2014
$5.1M
NEUROLOGICAL &LYMPHOID FACTORS IN HIV1 LTR ACTIVATIONR01NS032092 · NINDS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI WIGDAHL, BRIAN · 1993 to 2011
$3.9M
Co-evolution of HIV-1 Regulators in CNS DiseaseR01NS046263 · NINDS · DREXEL UNIVERSITY · PI WIGDAHL, BRIAN · 2004 to 2009
$1.8M
NIDA NIH HHS DA19807NIDA NIH HHS R01 DA019807NIMH NIH HHS 5T32MH079785NIMH NIH HHS P30 MH092177NIMH NIH HHS T32 MH079785NINDS NIH HHS NS32092NINDS NIH HHS NS46263NINDS NIH HHS R01 NS032092NINDS NIH HHS R01 NS046263
6 · The paper itself

Abstract

The evolution of human immunodeficiency virus type 1 (HIV-1) with respect to co-receptor utilization has been shown to be relevant to HIV-1 pathogenesis and disease. The CCR5-utilizing (R5) virus has been shown to be important in the very early stages of transmission and highly prevalent during asymptomatic infection and chronic disease. In addition, the R5 virus has been proposed to be involved in neuroinvasion and central nervous system (CNS) disease. In contrast, the CXCR4-utilizing (X4) virus is more prevalent during the course of disease progression and concurrent with the loss of CD4(+) T cells. The dual-tropic virus is able to utilize both co-receptors (CXCR4 and CCR5) and has been thought to represent an intermediate transitional virus that possesses properties of both X4 and R5 viruses that can be encountered at many stages of disease. The use of computational tools and bioinformatic approaches in the prediction of HIV-1 co-receptor usage has been growing in importance with respect to understanding HIV-1 pathogenesis and disease, developing diagnostic tools, and improving the efficacy of therapeutic strategies focused on blocking viral entry. Current strategies have enhanced the sensitivity, specificity, and reproducibility relative to the prediction of co-receptor use; however, these technologies need to be improved with respect to their efficient and accurate use across the HIV-1 subtypes. The most effective approach may center on the combined use of different algorithms involving sequences within and outside of the env-V3 loop. This review focuses on the HIV-1 entry process and on co-receptor utilization, including bioinformatic tools utilized in the prediction of co-receptor usage. It also provides novel preliminary analyses for enabling identification of linkages between amino acids in V3 with other components of the HIV-1 genome and demonstrates that these linkages are different between X4 and R5 viruses.

Indexed as

Computational BiologyHIV InfectionsHumansReceptors, CCR5Receptors, CXCR4Receptors, CCR5Receptors, CXCR4

Identifiers

PMID24862329
PMCPMC4382797
OpenAlexW2096047537

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.