Evidence map›Paper›PMID 34217135›Full record

ReviewCurrent opinion in virology2021

Natural killer cells and unconventional T cells in COVID-19.

Niklas K Björkström, Andrea Ponzetta

Open access · hybridAbstract readReview
In one paragraph

Review in Current opinion in virology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

29 citing papers in PubMed, 39 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. NK Cells: A Powerful Squad Versus SARS-CoV-2.International journal of molecular sciences · 2025
    Review
  5. Review
  6. Article
  7. The causal effect of natural killer cells on COVID-19 infection, hospitalization and severity.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025
    Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Invariant natural killer T cells in lung diseases.Experimental & molecular medicine · 2023
    Review
  13. Article
  14. Article
  15. Impact of SARS-CoV-2 infection on the profiles and responses of innate immune cells after recovery.Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi · 2022
    Article
  16. Review
  17. Adaptive Immunity to Viruses: What Did We Learn from SARS-CoV-2 Infection?International journal of molecular sciences · 2022
    Review
  18. Article
  19. Editorial overview: Viral pathogenesis.Current opinion in virology · 2022
    Article
  20. Innate and Innate-like Effector Lymphocytes in Health and Disease.Journal of immunology (Baltimore, Md. : 1950) · 2022
    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

2 authors at 2 institutions in 1 country.

Niklas K BjörkströmCenter for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden; Department of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden. Electronic address: niklas.bjorkstrom@ki.se.
Andrea PonzettaCenter for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden.
Karolinska Institutet · SEKarolinska University Hospital · SE

Funding

European Research Council 948692
6 · The paper itself

Abstract

NK cells and diverse populations of unconventional T cells, such as MAIT cells, γδ T cells, invariant NKT cells, and DNT

Indexed as

COVID-19CytokinesHumansKiller Cells, NaturalLungMucosal-Associated Invariant T CellsNatural Killer T-CellsReceptors, ImmunologicSARS-CoV-2T-LymphocytesCytokinesReceptors, Immunologic

Identifiers

PMID34217135
PMCPMC8214213
OpenAlexW3173484100

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.