Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 973

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

DAMPening Inflammation by Modulating TLR Signalling

Open access
Piccinini, A. M., Midwood, K. S.·2010·Mediators of Inflammation

Abstract

Damage-associated molecular patterns (DAMPs) include endogenous intracellular molecules released by activated or necrotic cells and extracellular matrix (ECM) molecules that are upregulated upon injury or degraded following tissue damage. DAMPs are vital danger signals that alert our immune system to tissue damage upon both infectious and sterile insult. DAMP activation of Toll-like receptors (TLRs) induces inflammatory gene expression to mediate tissue repair. However, DAMPs have also been implicated in diseases where excessive inflammation plays a key role in pathogenesis, including rheumatoid arthritis (RA), cancer, and atherosclerosis. TLR activation by DAMPs may initiate positive feedback loops where increasing tissue damage perpetuates pro-inflammatory responses leading to chronic inflammation. Here we explore the current knowledge about distinct signalling cascades resulting from self TLR activation. We also discuss the involvement of endogenous TLR activators in disease and highlight how specifically targeting DAMPs may yield therapies that do not globally suppress the immune system.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1155/2010/672395

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 25 references

Cited by

See all 973

Metadata

Authors
Piccinini, A. M., & Midwood, K. S.
Venue
Mediators of Inflammation
Publisher
Wiley
Published
2010
Volume
2010
Pages
1-21
ISSN
  • 0962-9351 (ISSN-L)
  • 1466-1861
OpenAlex
W1983419107
Cited by
973
References
25
FWCI
21.78
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: DAMPening Inflammation by Modulating TLR Signalling. https://app.cochat.ai/papers/10.1155/2010/672395
The paper
Piccinini, A. M., & Midwood, K. S. (2010). DAMPening Inflammation by Modulating TLR Signalling. Mediators of Inflammation. https://doi.org/10.1155/2010/672395

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.