Evidence map›Paper›PMID 29963043›Full record

ReviewFrontiers in immunology2018

New Genetically Manipulated Mice Provide Insights Into the Development and Physiological Functions of Invariant Natural Killer T Cells.

Yue Ren, Etsuko Sekine-Kondo, Midori Tateyama, Thitinan Kasetthat, Surasakadi Wongratanacheewin, Hiroshi Watarai

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 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
0.3field-weighted citation impact, top 45% 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, 6 citations in OpenAlex.

  1. Review
  2. Protective effects ofFrontiers in pharmacology · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. T Cells in Adipose Tissue in Aging.Frontiers in immunology · 2018
    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

6 authors at 4 institutions in 3 countries.

Yue RenDivision of Stem Cell Cellomics, Center for Stem Cell Biology and Regenerative Medicine, Institute of Medical Science, University of Tokyo, Tokyo, Japan.
Etsuko Sekine-KondoDivision of Stem Cell Cellomics, Center for Stem Cell Biology and Regenerative Medicine, Institute of Medical Science, University of Tokyo, Tokyo, Japan.
Midori TateyamaDivision of Stem Cell Cellomics, Center for Stem Cell Biology and Regenerative Medicine, Institute of Medical Science, University of Tokyo, Tokyo, Japan.
Thitinan KasetthatDivision of Stem Cell Cellomics, Center for Stem Cell Biology and Regenerative Medicine, Institute of Medical Science, University of Tokyo, Tokyo, Japan.
Surasakadi WongratanacheewinDepartment of Microbiology, Khon Kaen University, Khon Kaen, Thailand.
Hiroshi WataraiDivision of Stem Cell Cellomics, Center for Stem Cell Biology and Regenerative Medicine, Institute of Medical Science, University of Tokyo, Tokyo, Japan.
Khon Kaen University · THThe University of Tokyo · JPJiangxi Provincial People's Hospital · CNTokyo University of Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invariant natural killer T (iNKT) cells are a unique T cell subset that exhibits characteristics of both innate immune cells and T cells. They express Vα14-Jα18 (

Indexed as

AnimalsAntigens, CD1dCell DifferentiationDisease SusceptibilityHumansMiceMice, KnockoutMice, TransgenicNatural Killer T-CellsReceptors, Antigen, T-CellThymus GlandAntigens, CD1dReceptors, Antigen, T-Celladipose tissueCD1dcloned miceinvariant natural killer T cellsiPSCobesitythymic differentiationTraj18

Identifiers

PMID29963043
PMCPMC6010523
OpenAlexW2804437686

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.