Evidence map›Paper›PMID 42827606›Full record

ArticleFrontiers in aging2026

Unraveling skeletal muscle senescence in an

Kayo Moreira Bagri, Morgana Teixeira Lima Castelo-Branco, Claudia Mermelstein

Abstract read
In one paragraph

Article in Frontiers in aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Kayo Moreira BagriInstituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Morgana Teixeira Lima Castelo-BrancoInstituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Claudia MermelsteinInstituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Skeletal muscles are crucial for voluntary movement, posture, breathing, joint stability, and therefore are essential for maintaining overall health and quality of life. Aging, sarcopenia, cancer, immobilization, and several muscle pathologies can have an impact on muscle function, and muscle cell senescence is associated with these conditions. Methods: Here we aimed to develop a primary cell culture model to study skeletal muscle cell senescence. We induced cell cycle arrest in cultured embryonic chick muscle cells using a low concentration of cytosine arabinoside (Ara-C) for 9 days. Results: Our results show that Ara-C was able to induce several cellular senescence-associated bone fide characteristics, including reduced cell proliferation, increased β-galactosidase expression, increased reactive oxygen species production (ROS), increased p53 and p21 expression, increased muscle fibroblast cell size and nuclei numbers, increased lysosomal activity, decreased muscle differentiation (decreased muscle fiber size and decreased desmin expression), and increased secretion of IL-6, TNFα and TGFβ. Interestingly, inhibition of fibroblast growth factor receptor recovers the AraC-induced senescent phenotype in myogenic cells. Conclusion: This new experimental model could be used to deepen our understanding of the molecules and signaling pathways associated with the initiation and establishment of skeletal muscle senescence. Furthermore, this model could be used to test new drugs and therapeutic interventions aiming the amelioration of senescence-associated conditions.

Indexed as

cytosine arabinosidedesminFGFlysosomesmusclep53ROSsenescence

Identifiers

PMID42827606
PMCPMC13631421

What OpenQuestion holds

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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.