Evidence map›Paper›PMID 29912167›Full record

ReviewViruses2018

Neutralizing Antibody-Based Prevention of Cell-Associated HIV-1 Infection.

Matthew S Parsons, Roger Le Grand, Stephen J Kent

Open access · goldAbstract readReview
In one paragraph

Review in Viruses, 2018. 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
0.7field-weighted citation impact, top 34% 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, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
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  6. 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

3 authors at 3 institutions in 2 countries.

Matthew S ParsonsDepartment of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria 3000, Australia. mattp@unimelb.edu.au.
Roger Le GrandCEA, Université Paris Sud 11, INSERM u1184, Immunology of Viral Infections and Autoimmune Diseases, IDMIT Department, IBFJ, Fontenay-aux-Roses 92265, France. roger.le-grand@cea.fr.
Stephen J KentDepartment of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria 3000, Australia. skent@unimelb.edu.au.
Infectious Disease Models and Innovative Therapies · FRPeter Doherty Institute · AUUniversity of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improved vaccine-mediated protection against HIV-1 requires a thorough understanding of the mode of HIV-1 transmission and how various immune responses control transmission. Cell-associated HIV-1 is infectious and contributes to HIV-1 transmission in humans. Non-human primate models of cell-associated SIV infection demonstrate that cell-associated SIV is more infectious than cell-free SIV. In a recently described chimeric simian⁻human immunodeficiency virus (SHIV) macaque model, it was demonstrated that an occult infection with cell-associated SHIV can be established that evades passive protection with a broadly neutralizing antibody (bnAb). Indeed, considerable in vitro data shows that bnAbs have less efficacy against cell-associated HIV-1 than cell-free HIV-1. Optimizing the protective capacity of immune responses such as bnAbs against cell-associated infections may be needed to maximize their protective efficacy.

Indexed as

AnimalsAntibodies, NeutralizingDisease Models, AnimalDisease Transmission, InfectiousHIV-1HIV AntibodiesHIV InfectionsImmunization, PassiveMacacaAntibodies, NeutralizingHIV Antibodiesbroadly neutralizing antibodycell-associated virusHIV-1simian–human immunodeficiency virus

Identifiers

PMID29912167
PMCPMC6024846
OpenAlexW2808396374

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.