Evidence map›Paper›PMID 39162976›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Quantifying Muscle Regeneration: Activated Muscle Satellite Cells and New Regenerated Myofibers in Chronic and Acute Degeneration Models.

Antonio Fernando Ribeiro Junior, Brandow Willy Souza, Mariz Vainzof

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Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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.

Antonio Fernando Ribeiro JuniorHuman Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, SP, Brazil.
Brandow Willy SouzaHuman Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, SP, Brazil.
Mariz VainzofHuman Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, SP, Brazil. mvainzof@usp.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Regeneration is a remarkable characteristic of the skeletal muscle. Triggered by common lesions, regeneration is stimulated resulting in muscle fiber repair and restoration of muscle homeostasis in normal muscle. In genetic dystrophic muscle, the cycle of degeneration/regeneration is an endless loop that leads to impaired regeneration and substitution of muscle fibers by connective and adipose tissue, causing muscle weakness. Identification and characterization of muscle regeneration steps can help discover potential therapy targets for muscle diseases and aging. Muscle regeneration markers such as the number of satellite cells in the muscle, the proportion of activated satellite cells, and the quantity of regenerating muscle fiber can be quantified using immunolabeling.Here we are presenting a quantitative method to measure muscle regeneration that can be applied to different proposals. To demonstrate the protocol applicability, we used models for acute and chronic muscle injuries. As model of acute degeneration, a wild-type C57BL6 mice with muscle injury induced by electroporation was used, and the muscle was analyzed after 5 and 10 days post-injury. DMD

Indexed as

Muscle Fibers, SkeletalMuscle, SkeletalRegenerationSatellite Cells, Skeletal MuscleAnimalsChronic DiseaseDisease Models, AnimalElectroporationMiceMice, Inbred C57BLDevelopmental myosinElectroporationImmunofluorescenceMuscle regenerationMuscular dystrophiesNeuromuscular diseasePAX7Satellite cellsSkeletal muscle

Identifiers

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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.