Evidence map›Paper›PMID 35604877›Full record

ArticleClinical and translational medicine2022

Targeting inflammation with collagen.

Dennis Schwarz, Marie Lipoldová, Holger Reinecke, Yahya Sohrabi

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational medicine, 2022. 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
5.2field-weighted citation impact, top 3% 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, 38 citations in OpenAlex.

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  13. [Research advances of collagen-based biomaterials in wound repair].Zhonghua shao shang yu chuang mian xiu fu za zhi · 2024
    Review
  14. Observational
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  17. Targeting inflammation with collagen.Clinical and translational medicine · 2022
    Article
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

4 authors at 2 institutions in 2 countries.

Dennis SchwarzDepartment of Cardiology I - Coronary and Peripheral Vascular Disease, Heart Failure, University Hospital Münster, Münster, Germany.
Marie LipoldováLaboratory of Signal Transduction, Institutes of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia.
Holger ReineckeDepartment of Cardiology I - Coronary and Peripheral Vascular Disease, Heart Failure, University Hospital Münster, Münster, Germany.
Yahya SohrabiDepartment of Cardiology I - Coronary and Peripheral Vascular Disease, Heart Failure, University Hospital Münster, Münster, Germany.ORCID 0000-0001-5268-238X
University Hospital Münster · DECzech Academy of Sciences, Institute of Molecular Genetics · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tissue damage caused by an infection oran autoimmune disease triggers degradation of collagen in the extracellular matrix (ECM), which further enhances inflammation. Therefore, improving ECM in aninflamed tissue can be exploited as a potential therapeutic target. A recentstudy emphasised an innovative approach against COVID-19 using polymerised type I collagen (PTIC) that improves disease severity through a hitherto unknownmechanism. In this paper, we provide an overview of potential mechanism thatmay explain the anti-inflammatory effect of collagen peptides. In addition,the paper includes a brief summary of possible side effect of collagendeposition in inflammatory diseases. Altogether, current knowledge suggeststhat collagen may potentially reduce the residual risk in inflammatorydiseases; however, the detailed mechanism remains elusive.

Indexed as

COVID-19 Drug TreatmentCollagenCollagen Type IExtracellular MatrixHumansInflammationCollagenCollagen Type IcollagenCOVID-19ECMinflammationMMPs

Identifiers

PMID35604877
PMCPMC9126324
OpenAlexW4281294320

What OpenQuestion holds

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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.