Evidence map›Paper›PMID 36853713›Full record

ArticleSTAR protocols2023

Quantitative analysis of myofiber type composition in human and mouse skeletal muscles.

Tooba Abbassi-Daloii, Salma El Abdellaoui, Hermien E Kan, Erik van den Akker, Peter A C 't Hoen, Vered Raz, Lenard M Voortman

Open access · goldAbstract read
In one paragraph

Article in STAR protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 11 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

7 authors at 2 institutions in 2 countries.

Tooba Abbassi-DaloiiHuman Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
Salma El AbdellaouiHuman Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
Hermien E KanC.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; Duchenne Center Netherlands, the Netherlands.
Erik van den AkkerMolecular Epidemiology, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands; Leiden Computational Biology Center, Leiden University Medical Center, 2333 ZC Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, 2628 XE Delft, the Netherlands.
Peter A C 't HoenHuman Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, 6525 GA Nijmegen, the Netherlands.
Vered RazHuman Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. Electronic address: v.raz@lumc.nl.
Lenard M VoortmanCell and Chemical Biology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. Electronic address: l.m.voortman@lumc.nl.
Leiden University Medical Center · NLRadboud University Nijmegen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscles are composed of different myofiber types characterized by the expression of myosin heavy chain isoforms, which can be affected by physical activity, aging, and pathological conditions. Here, we present a step-by-step high-throughput semi-automated approach for performing myofiber type quantification of entire human or mouse muscle tissue sections, including immunofluorescence staining, image acquisition, processing, and quantification. For complete details on the use and execution of this protocol, please refer to Abbassi-Daloii et al. (2022).

Indexed as

AgingMuscle, SkeletalAnimalsHumansMiceHigh-Throughput ScreeningMicroscopy

Identifiers

PMID36853713
PMCPMC9898062
OpenAlexW4318428348

What OpenQuestion holds

Textmetadata
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.