Evidence map›Paper›PMID 26447881›Full record

ArticlePloS one2015

Tumor Necrosis Factor Alpha and Insulin-Like Growth Factor 1 Induced Modifications of the Gene Expression Kinetics of Differentiating Skeletal Muscle Cells.

Swanhild U Meyer, Stefan Krebs, Christian Thirion, Helmut Blum, Sabine Krause, Michael W Pfaffl

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 31% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Building Haplotype-Resolved 3D Genome Maps of Chicken Skeletal Muscle.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Inhibition ofFrontiers in cell and developmental biology · 2021
    Article
  12. Article
  13. Neuromuscular Diseases and Bone.Frontiers in endocrinology · 2019
    Review
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 at 2 institutions in 1 country.

Swanhild U MeyerPhysiology Weihenstephan, ZIEL Research Center for Nutrition and Food Sciences, Technische Universität München, Freising, Germany.
Stefan KrebsLaboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Ludwig-Maximilians-Universität München, München, Germany.
Christian ThirionSIRION Biotech GmbH, Martinsried, Germany.
Helmut BlumLaboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Ludwig-Maximilians-Universität München, München, Germany.
Sabine KrauseFriedrich-Baur-Institute, Department of Neurology, Ludwig-Maximilians-Universität München, München, Germany.
Michael W PfafflPhysiology Weihenstephan, ZIEL Research Center for Nutrition and Food Sciences, Technische Universität München, Freising, Germany.
Ludwig-Maximilians-Universität München · DETechnical University of Munich · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTNF-α levels are increased during muscle wasting and chronic muscle degeneration and regeneration processes, which are characteristic for primary muscle disorders. Pathologically increased TNF-α levels have a negative effect on muscle cell differentiation efficiency, while IGF1 can have a positive effect; therefore, we intended to elucidate the impact of TNF-α and IGF1 on gene expression during the early stages of skeletal muscle cell differentiation. METHODOLOGY/PRINCIPAL

findingsThis study presents gene expression data of the murine skeletal muscle cells PMI28 during myogenic differentiation or differentiation with TNF-α or IGF1 exposure at 0 h, 4 h, 12 h, 24 h, and 72 h after induction. Our study detected significant coregulation of gene sets involved in myoblast differentiation or in the response to TNF-α. Gene expression data revealed a time- and treatment-dependent regulation of signaling pathways, which are prominent in myogenic differentiation. We identified enrichment of pathways, which have not been specifically linked to myoblast differentiation such as doublecortin-like kinase pathway associations as well as enrichment of specific semaphorin isoforms. Moreover to the best of our knowledge, this is the first description of a specific inverse regulation of the following genes in myoblast differentiation and response to TNF-α: Aknad1, Cmbl, Sepp1, Ndst4, Tecrl, Unc13c, Spats2l, Lix1, Csdc2, Cpa1, Parm1, Serpinb2, Aspn, Fibin, Slc40a1, Nrk, and Mybpc1. We identified a gene subset (Nfkbia, Nfkb2, Mmp9, Mef2c, Gpx, and Pgam2), which is robustly regulated by TNF-α across independent myogenic differentiation studies.

conclusionsThis is the largest dataset revealing the impact of TNF-α or IGF1 treatment on gene expression kinetics of early in vitro skeletal myoblast differentiation. We identified novel mRNAs, which have not yet been associated with skeletal muscle differentiation or response to TNF-α. Results of this study may facilitate the understanding of transcriptomic networks underlying inhibited muscle differentiation in inflammatory diseases.

Indexed as

AnimalsCell DifferentiationCell LineGene Expression Regulation, DevelopmentalInsulin-Like Growth Factor IMiceMyoblasts, SkeletalOligonucleotide Array Sequence AnalysisPrincipal Component AnalysisRNA, MessengerTranscriptomeTumor Necrosis Factor-alphaInsulin-Like Growth Factor IRNA, MessengerTumor Necrosis Factor-alpha

Identifiers

PMID26447881
PMCPMC4598026
OpenAlexW2149714879

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.