Evidence map›Paper›PMID 42162552›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Gene Expression Analysis on Single Myofibers from Mouse Edl and Soleus Muscles.

Amairani Cancino-Bello, Mauricio Hernández-Somilleda, Estela G García-González, J Manuel Hernández-Hernández

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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

4 authors.

Amairani Cancino-BelloLaboratorio de Epigenética de la Regeneración Muscular, Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de México, México, 07360.
Mauricio Hernández-SomilledaLaboratorio de Epigenética de la Regeneración Muscular, Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de México, México, 07360.
Estela G García-GonzálezLaboratorio de Epigenética de la Regeneración Muscular, Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de México, México, 07360.
J Manuel Hernández-HernándezLaboratorio de Epigenética de la Regeneración Muscular, Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de México, México, 07360. jose.hernandezh@cinvestav.mx.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscle is composed of different myofiber types with specific transcriptomic, proteomic, and metabolic identities. As such, skeletal muscle represents a valuable model to study cell differentiation and gene expression regulation. However, many molecular analyses of skeletal muscle are performed on whole muscle, with the caveat that many different cell types that constitute this organ contribute to the experimental results. Here, we describe a method to efficiently isolate individual myofibers from two muscle types and provide a guide to perform quantitative gene expression analysis of representative myosin heavy chain genes.

Indexed as

Gene Expression ProfilingMuscle Fibers, SkeletalMuscle, SkeletalAnimalsMiceMyosin Heavy ChainsSingle-Cell Gene Expression AnalysisMyosin Heavy ChainsEene expressionExtensor digitorum longusMyh4Myh7Myofibers isolationqPCRSkeletal muscleSoleus

Identifiers

PMID42162552

What OpenQuestion holds

Textmetadata
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.