Evidence map›Paper›PMID 28747624›Full record

ArticleScientific reports2017

Number of infection events per cell during HIV-1 cell-free infection.

Yusuke Ito, Azaria Remion, Alexandra Tauzin, Keisuke Ejima, Shinji Nakaoka, Yoh Iwasa, Shingo Iwami, Fabrizio Mammano

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. HIV-1 Infection of Primary CD4Journal of virology · 2018
    Article
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.

Yusuke ItoDepartment of Biology, Faculty of Sciences, Kyushu University, Fukuoka, 819-0395, Japan.
Azaria RemionINSERM, U941, 75010, Paris, France.
Alexandra TauzinINSERM, U941, 75010, Paris, France.
Keisuke EjimaSchool of Public Health, University of Alabama at Birmingham, Alabama, 35294-0011, USA.
Shinji NakaokaPRESTO, JST, Saitama, 332-0012, Japan.
Yoh IwasaDepartment of Biology, Faculty of Sciences, Kyushu University, Fukuoka, 819-0395, Japan.ORCID 0000-0003-0691-1852
Shingo IwamiDepartment of Biology, Faculty of Sciences, Kyushu University, Fukuoka, 819-0395, Japan. siwami@kyushu-u.org.
Fabrizio MammanoINSERM, U941, 75010, Paris, France. fabrizio.mammano@inserm.fr.ORCID 0000-0002-9193-7696

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

HIV-1 accumulates changes in its genome through both recombination and mutation during the course of infection. For recombination to occur, a single cell must be infected by two HIV strains. These coinfection events were experimentally demonstrated to occur more frequently than would be expected for independent infection events and do not follow a random distribution. Previous mathematical modeling approaches demonstrated that differences in target cell susceptibility can explain the non-randomness, both in the context of direct cell-to-cell transmission, and in the context of free virus transmission (Q. Dang et al., Proc. Natl. Acad. Sci. USA 101:632-7, 2004: K. M. Law et al., Cell reports 15:2711-83, 2016). Here, we build on these notions and provide a more detailed and extensive quantitative framework. We developed a novel mathematical model explicitly considering the heterogeneity of target cells and analysed datasets of cell-free HIV-1 single and double infection experiments in cell culture. Particularly, in contrast to the previous studies, we took into account the different susceptibility of the target cells as a continuous distribution. Interestingly, we showed that the number of infection events per cell during cell-free HIV-1 infection follows a negative-binomial distribution, and our model reproduces these datasets.

Indexed as

Models, TheoreticalCD4-Positive T-LymphocytesCell LineHIV-1Humans

Identifiers

PMID28747624
PMCPMC5529392

What OpenQuestion holds

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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.