Evidence map›Paper›PMID 26194760›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2015

The challenges of modelling antibody repertoire dynamics in HIV infection.

Shishi Luo, Alan S Perelson

Open access · greenAbstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Evolution during primary HIV infection does not require adaptive immune selection.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  2. Article
  3. Modeling the immune response to HIV infection.Current opinion in systems biology · 2018
    Article
  4. Review
  5. Article
  6. The evolution within us.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015
    Review
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 2 institutions in 1 country.

Shishi LuoDepartment of Electrical Engineering and Computer Science, UC Berkeley, Berkeley, CA 94110, USA Department of Statistics, UC Berkeley, Berkeley, CA 94110, USA.
Alan S PerelsonLos Alamos National Laboratory, Theoretical Biology and Biophysics Group, Los Alamos, NM 87545, USA asp@lanl.gov.
Los Alamos National Laboratory · USUniversity of California, Berkeley · US

Funding

Virus biology scientific research support componentUM1AI100645 · NIAID · DUKE UNIVERSITY · PI HAYNES, BARTON F. · 2012 to 2018
$204.7M
Modeling Viral and T Lymphocyte DynamicsR01OD011095 · OD · TRIAD NATIONAL SECURITY, LLC · PI PERELSON, ALAN S · 2012 to 2024
$5.0M
Immune System Modeling/HIVR01AI028433 · NIAID · UNIVERSITY OF CALIF-LOS ALAMOS NAT LAB · PI PERELSON, ALAN S · 1990 to 2021
$3.7M
NIAID NIH HHS R01 AI028433NIAID NIH HHS R01-AI028433NIAID NIH HHS UM1 AI100645NIAID NIH HHS UM1-AI100645NIH HHS R01 OD011095NIH HHS R01-OD011095
6 · The paper itself

Abstract

Antibody affinity maturation by somatic hypermutation of B-cell immunoglobulin variable region genes has been studied for decades in various model systems using well-defined antigens. While much is known about the molecular details of the process, our understanding of the selective forces that generate affinity maturation are less well developed, particularly in the case of a co-evolving pathogen such as HIV. Despite this gap in understanding, high-throughput antibody sequence data are increasingly being collected to investigate the evolutionary trajectories of antibody lineages in HIV-infected individuals. Here, we review what is known in controlled experimental systems about the mechanisms underlying antibody selection and compare this to the observed temporal patterns of antibody evolution in HIV infection. We describe how our current understanding of antibody selection mechanisms leaves questions about antibody dynamics in HIV infection unanswered. Without a mechanistic understanding of antibody selection in the context of a co-evolving viral population, modelling and analysis of antibody sequences in HIV-infected individuals will be limited in their interpretation and predictive ability.

Indexed as

Models, ImmunologicalAnimalsAntibodies, NeutralizingAntibody AffinityAntibody DiversityB-LymphocytesEvolution, MolecularGerminal CenterHIV AntibodiesHIV AntigensHIV InfectionsHumansMiceModels, GeneticSomatic Hypermutation, ImmunoglobulinAntibodies, NeutralizingHIV AntibodiesHIV AntigensevolutionHIVimmunology

Identifiers

PMID26194760
PMCPMC4528423
OpenAlexW2231538836

What OpenQuestion holds

Textmetadata
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.