Evidence map›Paper›PMID 27683580›Full record

ArticleFrontiers in immunology2016

Tr1-Like T Cells - An Enigmatic Regulatory T Cell Lineage.

Anna Malgorzata White, David C Wraith

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
5.0field-weighted citation impact, top 3% 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

45 citing papers in PubMed, 74 citations in OpenAlex.

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  15. hPMSCs inhibit the expression of PD-1 in CD4Stem cell research & therapy · 2021
    Article
  16. Review
  17. Understanding LAG-3 Signaling.International journal of molecular sciences · 2021
    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

2 authors at 1 institution in 1 country.

Anna Malgorzata WhiteSchool of Cellular and Molecular Medicine, University of Bristol , Bristol , UK.
David C WraithSchool of Cellular and Molecular Medicine, University of Bristol, Bristol, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK.
University of Bristol · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The immune system evolved to respond to foreign invaders and prevent autoimmunity to self-antigens. Several types of regulatory T cells facilitate the latter process. These include a subset of Foxp3(-) CD4(+) T cells able to secrete IL-10 in an antigen-specific manner, type 1 regulatory (Tr1) T cells. Although their suppressive function has been confirmed both in vitro and in vivo, their phenotype remains poorly defined. It has been suggested that the surface markers LAG-3 and CD49b are biomarkers for murine and human Tr1 cells. Here, we discuss these findings in the context of our data regarding the expression pattern of inhibitory receptors (IRs) CD49b, TIM-3, PD-1, TIGIT, LAG-3, and ICOS on Tr1-like human T cells generated in vitro from CD4(+) memory T cells stimulated with αCD3 and αCD28 antibodies. We found that there were no differences in IR expression between IL-10(+) and IL-10(-) T cells. However, CD4(+)IL-10(+) T cells isolated ex vivo, following a short stimulation and cytokine secretion assay, contained significantly higher proportions of TIM-3(+) and PD-1(+) cells. They also expressed significantly higher TIGIT mRNA and showed a trend toward increased TIM-3 mRNA levels. These data led us to conclude that large pools of IRs may be stored intracellularly; hence, they may not represent ideal candidates as cell surface biomarkers for Tr1-like T cells.

Indexed as

CD4+ T cellIL-10inhibitory receptorsperipheral toleranceTr-1 T cells

Identifiers

PMID27683580
PMCPMC5021682
OpenAlexW2520354143

What OpenQuestion holds

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Registered trials

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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.