Evidence map›Paper›PMID 21331081›Full record

ReviewNature reviews. Immunology2011

MicroRNAs: the fine-tuners of Toll-like receptor signalling.

Luke A O'Neill, Frederick J Sheedy, Claire E McCoy

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Immunology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 474 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
474citing papers in PubMed, 1 pooled it
32.6field-weighted citation impact, top 1% 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

474 citing papers in PubMed, 1 synthesis or guideline pooled it, 850 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Time to Heal: MicroRNA Temporal Dysregulation in Diabetic Foot Ulcers.International journal of molecular sciences · 2026
    Review
  5. Non-Coding RNAs in Oral Diseases: From Pathogenesis to Clinical Translation.International journal of molecular sciences · 2026
    Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

414 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 3 countries.

Luke A O'NeillSchool of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland. laoneill@tcd.ie
Frederick J Sheedy
Claire E McCoy
Monash Institute of Medical Research · AUNew York University · USTrinity College Dublin · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toll-like receptor (TLR) signalling must be tightly regulated to avoid excessive inflammation and to allow for tissue repair and the return to homeostasis after infection and tissue injury. MicroRNAs (miRNAs) have emerged as important controllers of TLR signalling. Several miRNAs are induced by TLR activation in innate immune cells and these and other miRNAs target the 3' untranslated regions of mRNAs encoding components of the TLR signalling system. miRNAs are also proving to be an important link between the innate and adaptive immune systems, and their dysregulation might have a role in the pathogenesis of inflammatory diseases.

Indexed as

3' Untranslated RegionsAdaptive ImmunityAnimalsCytokinesForecastingGene Expression RegulationHost-Pathogen InteractionsHumansImmunity, InnateInflammationMicroRNAsModels, ImmunologicalRNA, MessengerSignal TransductionToll-Like ReceptorsTranscription Factors3' Untranslated RegionsCytokinesMicroRNAsRNA, MessengerToll-Like ReceptorsTranscription Factors

Identifiers

PMID21331081
OpenAlexW2124957695

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.