Evidence map›Paper›PMID 23166585›Full record

ArticlePloS one2012

Effect of synaptic transmission on viral fitness in HIV infection.

Natalia L Komarova, David N Levy, Dominik Wodarz

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

12 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
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  8. Modeling Viral Spread.Annual review of virology · 2016
    Review
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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

3 authors at 2 institutions in 1 country.

Natalia L KomarovaDepartment of Mathematics, University of California Irvine, Irvine, California, USA. komarova@uci.edu
David N Levy
Dominik Wodarz
University of California, Irvine · USNew York University · US

Funding

Viruis Dynamics and Multiple Infection of Cells: Computational and Experimental AR01AI093998 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI LEVY, DAVID N, WODARZ, DOMINIK F · 2011 to 2014
$1.5M
NIAID NIH HHS 1R01AI093998-01A1NIAID NIH HHS R01 AI093998
6 · The paper itself

Abstract

HIV can spread through its target cell population either via cell-free transmission, or by cell-to-cell transmission, presumably through virological synapses. Synaptic transmission entails the transfer of tens to hundreds of viruses per synapse, a fraction of which successfully integrate into the target cell genome. It is currently not understood how synaptic transmission affects viral fitness. Using a mathematical model, we investigate how different synaptic transmission strategies, defined by the number of viruses passed per synapse, influence the basic reproductive ratio of the virus, R(0), and virus load. In the most basic scenario, the model suggests that R(0) is maximized if a single virus particle is transferred per synapse. R(0) decreases and the infection eventually cannot be maintained for larger numbers of transferred viruses, because multiple infection of the same cell wastes viruses that could otherwise enter uninfected cells. To explain the relatively large number of HIV copies transferred per synapse, we consider additional biological assumptions under which an intermediate number of viruses transferred per synapse could maximize R(0). These include an increased burst size in multiply infected cells, the saturation of anti-viral factors upon infection of cells, and rate limiting steps during the process of synapse formation.

Indexed as

Biological EvolutionModels, BiologicalGenetic FitnessHIV InfectionsSynapsesSynaptic TransmissionVirus Replication

Identifiers

PMID23166585
PMCPMC3499495
OpenAlexW2105607559

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.