Evidence map›Paper›PMID 34571909›Full record

ReviewCells2021

Anti-Viral Pattern Recognition Receptors as Therapeutic Targets.

Conor Hennessy, Declan P McKernan

Open access · goldAbstract readReview
In one paragraph

Review in Cells, 2021. 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
2.4field-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

17 citing papers in PubMed, 39 citations in OpenAlex.

  1. Immunomodulatory Effects ofInternational journal of molecular sciences · 2026
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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

2 authors at 1 institution in 1 country.

Conor HennessyPharmacology & Therapeutics, School of Medicine, Human Biology Building, National University of Ireland Galway, H91 TK33 Galway, Ireland.
Declan P McKernanPharmacology & Therapeutics, School of Medicine, Human Biology Building, National University of Ireland Galway, H91 TK33 Galway, Ireland.ORCID 0000-0002-9691-1671
Ollscoil na Gaillimhe – University of Galway · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pattern recognition receptors (PRRs) play a central role in the inflammation that ensues following microbial infection by their recognition of molecular patterns present in invading microorganisms but also following tissue damage by recognising molecules released during disease states. Such receptors are expressed in a variety of cells and in various compartments of these cells. PRR binding of molecular patterns results in an intracellular signalling cascade and the eventual activation of transcription factors and the release of cytokines, chemokines, and vasoactive molecules. PRRs and their accessory molecules are subject to tight regulation in these cells so as to not overreact or react in unnecessary circumstances. They are also key to reacting to infection and in stimulating the immune system when needed. Therefore, targeting PRRs offers a potential therapeutic approach for chronic inflammatory disease, infections and as vaccine adjuvants. In this review, the current knowledge on anti-viral PRRs and their signalling pathways is reviewed. Finally, compounds that target PRRs and that have been tested in clinical trials for chronic infections and as adjuvants in vaccine trials are discussed.

Indexed as

AnimalsAntiviral AgentsHumansReceptors, Pattern RecognitionVirus DiseasesVirusesAntiviral AgentsReceptors, Pattern Recognitionanti-viral drugspattern recognition receptorsRIG-like receptorstoll-like receptorsvaccine adjuvantviral infection

Identifiers

PMID34571909
PMCPMC8466445
OpenAlexW3197544992

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.