Evidence map›Paper›PMID 30181915›Full record

ReviewImmune network2018

Damage-Associated Molecular Patterns in Inflammatory Diseases.

Jong Seong Roh, Dong Hyun Sohn

Open access · bronzeAbstract readReview
In one paragraph

Review in Immune network, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 751 papers.

0numbers the graph read from it
0cells of the map it votes in
751citing papers in PubMed
31.6field-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

751 citing papers in PubMed, 1,168 citations in OpenAlex.

  1. Article
  2. Review
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  10. The theory of the inflammatory ecosystem.Science China. Life sciences · 2026
    Review
  11. Article
  12. Article
  13. Article
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  15. Review
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  17. Exosomes in precision dermatology: From biomarkers to targeted therapeutics in personalized care.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026
    Review
  18. Review
  19. Review
  20. [Advances in innate immune-mediated neuroinflammatory mechanisms of migraine].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2026
    Review

691 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

2 authors at 1 institution in 1 country.

Jong Seong RohDepartment of Microbiology and Immunology, Pusan National University School of Medicine, Yangsan 50612, Korea.
Dong Hyun SohnDepartment of Microbiology and Immunology, Pusan National University School of Medicine, Yangsan 50612, Korea.
Pusan National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Damage-associated molecular patterns (DAMPs) are endogenous danger molecules that are released from damaged or dying cells and activate the innate immune system by interacting with pattern recognition receptors (PRRs). Although DAMPs contribute to the host's defense, they promote pathological inflammatory responses. Recent studies have suggested that various DAMPs, such as high-mobility group box 1 (HMGB1), S100 proteins, and heat shock proteins (HSPs), are increased and considered to have a pathogenic role in inflammatory diseases. Here, we review current research on the role of DAMPs in inflammatory diseases, including rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, atherosclerosis, Alzheimer's disease, Parkinson's disease, and cancer. We also discuss the possibility of DAMPs as biomarkers and therapeutic targets for these diseases.

Indexed as

Damage-associated molecular patternsInflammationInflammatory diseasesPattern recognition receptors

Identifiers

PMID30181915
PMCPMC6117512
OpenAlexW2887043640

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.