Evidence map›Paper›PMID 25976210›Full record

ReviewImmunology2015

Invariant natural killer T cells and their ligands: focus on multiple sclerosis.

Joan O'Keeffe, Maria Podbielska, Edward L Hogan

Abstract readReview
In one paragraph

Review in Immunology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Invariant natural killer T cells in lung diseases.Experimental & molecular medicine · 2023
    Review
  6. Article
  7. Review
  8. The frequencies of peripheral blood CD5Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2022
    Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. License to Kill: When iNKT Cells Are Granted the Use of Lethal Cytotoxicity.International journal of molecular sciences · 2020
    Review
  14. Article
  15. Article
  16. Article
  17. 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.

Joan O'KeeffeDepartment of Life and Physical Sciences, School of Science, Galway-Mayo Institute of Technology, Galway, Ireland.
Maria PodbielskaDepartment of Neurology, Institute of Molecular Medicine and Genetics, Georgia Regents University, Augusta, GA, USA.
Edward L HoganDepartment of Neurology, Institute of Molecular Medicine and Genetics, Georgia Regents University, Augusta, GA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invariant natural killer T (iNKT) cells are an innate population of T cells identified by the expression of an invariant T-cell receptor and reactivity to lipid-based antigens complexed with CD1d. They account for a small percentage of lymphocytes, but are extremely potent and play central roles in immunity to infection, in some cancers, and in autoimmunity. The list of relevant stimulatory lipids and glycolipid antigens now includes a range of endogenous self-antigens including the myelin-derived acetylated galactosylceramides. Recent progress in studies to identify the nature of lipid recognition for iNKT cells in autoimmune diseases like multiple sclerosis is likely to foster the development of therapeutic strategies aimed at harnessing iNKT cell activity.

Indexed as

AnimalsAntigens, CD1dAutoantigensGalactosylceramidesHumansMultiple SclerosisNatural Killer T-CellsNeoplasmsAntigens, CD1dAutoantigensCD1D protein, humanGalactosylceramidesautoimmunityhumaninnate lymphoid cellsneuroimmunology

Identifiers

PMID25976210
PMCPMC4515127

What OpenQuestion holds

Textmetadata
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.