Evidence map›Paper›PMID 31141185›Full record

ArticleScandinavian journal of immunology2019

Defining a novel subset of CD1d-dependent type II natural killer T cells using natural killer cell-associated markers.

Avadhesh Kumar Singh, Sara Rhost, Linda Löfbom, Susanna L Cardell

Abstract read
In one paragraph

Article in Scandinavian journal of immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. 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

4 authors.

Avadhesh Kumar SinghDepartment of Microbiology and Immunology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden.ORCID https://orcid.org/0000-0002-6027-1553
Sara RhostDepartment of Microbiology and Immunology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden.
Linda LöfbomDepartment of Microbiology and Immunology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden.
Susanna L CardellDepartment of Microbiology and Immunology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden.ORCID https://orcid.org/0000-0002-7665-6781

Funding

Adlerbertska StiftelsernaCancerfonden 180622Stiftelserna Wilhelm och Martina LundgrensVetenskapsrådet 2017-01821
6 · The paper itself

Abstract

Natural killer T (NKT) cells are αβ T cell receptor (TCR) expressing innate-like T cells that display natural killer (NK) cell markers. Based on TCR characteristics, they are divided into two groups restricted to the MHC class I-like molecule CD1d. Type I NKT cells, most extensively studied, are identified by a semi-invariant Vα14-Jα18 (mouse, Vα24-Jα18 in humans) TCR reactive to the prototypic ligand α-galactosylceramide presented on CD1d. In contrast, type II NKT cells display diverse TCR reacting to different CD1d-presented ligands. There are no reagents that identify all type II NKT cells, limiting their exploration. Here, we searched for novel type II NKT cells by comparing Jα18

Indexed as

AnimalsAntigens, CD1dBiomarkersFemaleGalactosylceramidesInterferon-gammaKiller Cells, NaturalLymphocyte ActivationMaleMiceMice, Inbred C57BLNatural Killer T-CellsNK Cell Lectin-Like Receptor Subfamily KPromyelocytic Leukemia Zinc Finger ProteinReceptors, Antigen, T-Cell, alpha-betaT-Lymphocyte Subsetsalpha-galactosylceramideAntigens, CD1dBiomarkersCD1d antigen, mouseGalactosylceramidesInterferon-gammaNK Cell Lectin-Like Receptor Subfamily KPromyelocytic Leukemia Zinc Finger ProteinReceptors, Antigen, T-Cell, alpha-betacytokinesexperimental animalsnatural killer T cellstranscription factors

Identifiers

PMID31141185
PMCPMC6851763

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.