Evidence map›Paper›PMID 30621783›Full record

ArticleSkeletal muscle2019

Open-CSAM, a new tool for semi-automated analysis of myofiber cross-sectional area in regenerating adult skeletal muscle.

Thibaut Desgeorges, Sophie Liot, Solene Lyon, Jessica Bouvière, Alix Kemmel, Aurélie Trignol, David Rousseau, Bruno Chapuis, Julien Gondin, Rémi Mounier and 2 more

Open access · goldAbstract read
In one paragraph

Article in Skeletal muscle, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

51 citing papers in PubMed, 84 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

12 authors at 1 institution in 1 country.

Thibaut DesgeorgesInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
Sophie LiotInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
Solene LyonCREATIS, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5220, INSERM U1206, INSA Lyon, 69100, Villeurbanne, France.
Jessica BouvièreInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
Alix KemmelInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
Aurélie TrignolInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
David RousseauCREATIS, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5220, INSERM U1206, INSA Lyon, 69100, Villeurbanne, France.
Bruno ChapuisCIQLE, Lyon Bio Image, Univ Lyon, Université Claude Bernard Lyon 1, Structure Fédérative de Recherche santé Lyon-Est CNRS UMS3453/INSERM US7, 69008, Lyon, France.
Julien GondinInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
Rémi MounierInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France.
Bénédicte ChazaudInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France. benedicte.chazaud@inserm.fr.ORCID 0000-0002-1262-502X
Gaëtan JubanInstitut NeuroMyoGène, Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5310, INSERM U1217, 8 Avenue Rockfeller, F-69008, Lyon, France. gaetan.juban@univ-lyon1.fr.
Université Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adult skeletal muscle is capable of complete regeneration after an acute injury. The main parameter studied to assess muscle regeneration efficacy is the cross-sectional area (CSA) of the myofibers as myofiber size correlates with muscle force. CSA analysis can be time-consuming and may trigger variability in the results when performed manually. This is why programs were developed to completely automate the analysis of the CSA, such as SMASH, MyoVision, or MuscleJ softwares. Although these softwares are efficient to measure CSA on normal or hypertrophic/atrophic muscle, they fail to efficiently measure CSA on regenerating muscles. We developed Open-CSAM, an ImageJ macro, to perform a high throughput semi-automated analysis of CSA on skeletal muscle from various experimental conditions. The macro allows the experimenter to adjust the analysis and correct the mistakes done by the automation, which is not possible with fully automated programs. We showed that Open-CSAM was more accurate to measure CSA in regenerating and dystrophic muscles as compared with SMASH, MyoVision, and MuscleJ softwares and that the inter-experimenter variability was negligible. We also showed that, to obtain a representative CSA measurement, it was necessary to analyze the whole muscle section and not randomly selected pictures, a process that was easily and accurately be performed using Open-CSAM. To conclude, we show here an easy and experimenter-controlled tool to measure CSA in muscles from any experimental condition, including regenerating muscle.

Indexed as

RegenerationAnimalsHistological TechniquesImage Processing, Computer-AssistedMice, Inbred C57BLMice, Inbred mdxMuscle Fibers, SkeletalReproducibility of ResultsSoftware

Identifiers

PMID30621783
PMCPMC6323738
OpenAlexW2910310212

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.