Evidence map›Paper›PMID 37713400›Full record

ArticlePloS one2023

Copper infused fabric attenuates inflammation in macrophages.

Safoura Zangiabadi, Khalil P Chamoun, Khang Nguyen, Yitian Tang, Gary Sweeney, Ali A Abdul-Sater

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Review
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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

6 authors.

Safoura ZangiabadiSchool of Kinesiology and Health Science, Muscle Health Research Centre (MHRC), York University, Toronto, Canada.
Khalil P ChamounSchool of Kinesiology and Health Science, Muscle Health Research Centre (MHRC), York University, Toronto, Canada.
Khang NguyenDepartment of Biology, York University, Toronto, Ontario, Canada.
Yitian TangSchool of Kinesiology and Health Science, Muscle Health Research Centre (MHRC), York University, Toronto, Canada.
Gary SweeneyDepartment of Biology, York University, Toronto, Ontario, Canada.
Ali A Abdul-SaterSchool of Kinesiology and Health Science, Muscle Health Research Centre (MHRC), York University, Toronto, Canada.ORCID 0000-0002-0022-0930

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While inflammation is an important immune response for protection from infections, excessive or prolonged inflammation can lead to a variety of debilitating diseases including skin disease, diabetes, heart disease, stroke, autoimmune diseases and cancer. Inflammation is a graded response that is typically initiated when resident macrophages sense the presence of pathogens or damage in the tissue and produce inflammatory cytokines and chemokines to kill the pathogen, clear debris and dead tissue, and initiate tissue repair. Here we show that copper-infused fabrics can prevent inflammation by blocking the production of inflammatory cytokines from macrophages after being exposed to LPS, a component of bacterial cell wall. Mechanistically, we show that copper-infused fabrics can significantly reduce the NF-κB and IRF3 activation in LPS-stimulated macrophages. Given the importance of excessive inflammation in diabetes, we show that copper can reduce insulin resistance mediated by inflammatory cytokines in muscle cells. Our data show that copper infused fabrics may be useful to reduce excessive inflammation in macrophages and improve insulin sensitivity in skeletal muscles.

Indexed as

CopperInsulin ResistanceCytokinesHumansInflammationLipopolysaccharidesMacrophagesCopperCytokinesLipopolysaccharides

Identifiers

PMID37713400
PMCPMC10503751

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.