Evidence map›Paper›PMID 30511955›Full record

ArticleJournal of musculoskeletal & neuronal interactions2018

Can obesity-induced inflammation in skeletal muscle and intramuscular adipose tissue accurately detect liver fibrosis?

Athina Chasapi, Kostas Balampanis, Eleni Kourea, Fotios Kalfarentzos, Vaia Lambadiari, George I Lambrou, Maria Melachrinou, Georgia Sotiropoulou-Bonikou

Open access · greenAbstract read
In one paragraph

Article in Journal of musculoskeletal & neuronal interactions, 2018. 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
1.1field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Athina ChasapiDepartment of Pathology, Medical School, University of Patras, Patras, Greece.
Kostas Balampanis
Eleni Kourea
Fotios Kalfarentzos
Vaia Lambadiari
George I Lambrou
Maria Melachrinou
Georgia Sotiropoulou-Bonikou
University of Patras · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesObesity is characterized by a chronic, low grade, systemic inflammation. However, little is known about the role of skeletal muscle, which represents an active metabolic organ whose activities need to be determined. The purpose of our study was to detect relationships between skeletal muscle and adipose tissue inflammation with nonalcoholic fatty liver disease (NAFLD) and diabetes, as well as to explore associations with clinicopathological parameters.

methodsOur study population consisted of 50 morbidly obese patients undergoing planned bariatric surgery. Biopsies were taken from visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), skeletal muscle (SM), extramyocellular adipose tissue (EMAT) and liver. The expression of CD68 and CD3 was assessed by immunohistochemistry.

resultsOur findings suggest a complex inter- and intra-tissue co-expression network that links obesity-induced inflammation in adipose depots and skeletal muscle with NAFLD. A novel finding is the intricate cross-talk between SM, EMAT and the liver and the probable correlation between SM, EMAT inflammation and the presence of liver fibrosis.

conclusionsAlthough the mechanisms of obesity-induced inflammation and its association with NAFLD and liver fibrosis are incompletely understood, our findings indicate an extensive and complex tissue network that needs to be further investigated.

Indexed as

Adipose TissueAdultFemaleHumansInflammationInflammation MediatorsLiver CirrhosisMaleMiddle AgedMuscle, SkeletalObesity, MorbidYoung AdultInflammation Mediators

Identifiers

PMID30511955
PMCPMC6313048
OpenAlexW2983427431

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.