Evidence map›Paper›PMID 35604384›Full record

RevieweLife2022

Contractile force assessment methods for in vitro skeletal muscle tissues.

Camila Vesga-Castro, Javier Aldazabal, Ainara Vallejo-Illarramendi, Jacobo Paredes

Abstract readReview
In one paragraph

Review in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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.

Camila Vesga-CastroUniversity of Navarra, Tecnun School of Engineering, Manuel de Lardizábal, San Sebastian, Spain.ORCID 0000-0002-7234-8650
Javier AldazabalUniversity of Navarra, Tecnun School of Engineering, Manuel de Lardizábal, San Sebastian, Spain.ORCID 0000-0002-2246-5242
Ainara Vallejo-IllarramendiGroup of Neurosciences, Department of Pediatrics, UPV/EHU, Hospital Donostia - IIS Biodonostia, San Sebastian, Spain.ORCID 0000-0002-2409-8263
Jacobo ParedesUniversity of Navarra, Tecnun School of Engineering, Manuel de Lardizábal, San Sebastian, Spain.ORCID 0000-0002-0620-0770

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last few years, there has been growing interest in measuring the contractile force (CF) of engineered muscle tissues to evaluate their functionality. However, there are still no standards available for selecting the most suitable experimental platform, measuring system, culture protocol, or stimulation patterns. Consequently, the high variability of published data hinders any comparison between different studies. We have identified that cantilever deflection, post deflection, and force transducers are the most commonly used configurations for CF assessment in 2D and 3D models. Additionally, we have discussed the most relevant emerging technologies that would greatly complement CF evaluation with intracellular and localized analysis. This review provides a comprehensive analysis of the most significant advances in CF evaluation and its critical parameters. In order to compare contractile performance across experimental platforms, we have used the specific force (sF, kN/m

Indexed as

Muscle ContractionMuscle, SkeletalProspective StudiesSarcomeresTissue Engineeringcontractile forceneuroscienceskeletal musclestimulationtissue engineering

Identifiers

PMID35604384
PMCPMC9126583

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.