Evidence map›Paper›PMID 27706164›Full record

ArticlePLoS biology2016

Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics.

Katrina A Lythgoe, François Blanquart, Lorenzo Pellis, Christophe Fraser

Open access · goldAbstract read
In one paragraph

Article in PLoS biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-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

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Elevated HIV viral load is associated with higher recombination ratebioRxiv : the preprint server for biology · 2023
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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

4 authors at 3 institutions in 1 country.

Katrina A LythgoeDepartment of Zoology, Tinbergen Building, University of Oxford, Oxford, United Kingdom.
François BlanquartDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, St. Mary's Campus, London, United Kingdom.
Lorenzo PellisMathematics Institute, Zeeman Building, University of Warwick, Coventry, United Kingdom.ORCID http://orcid.org/0000-0002-3436-6487
Christophe FraserDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, St. Mary's Campus, London, United Kingdom.ORCID http://orcid.org/0000-0003-2399-9657
University of Oxford · GBImperial College London · GBUniversity of Warwick · GB

Funding

European Research Council 339251Wellcome Trust
6 · The paper itself

Abstract

The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical, and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body's viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation.

Indexed as

Viral LoadHIV-1HumansModels, TheoreticalMosaicismT-Lymphocytes, CytotoxicVirulenceVirus Replication

Identifiers

PMID27706164
PMCPMC5051940
OpenAlexW2528130990

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.