Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 393

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Eccentric Muscle Contractions: Risks and Benefits

Open access
Hody, Stéphanie, Croisier, Jean-Louis, Bury, Thierry, Rogister, Bernard, Leprince, Pierre·2019·Frontiers in Physiology

Abstract

Eccentric contractions, characterized by the lengthening of the muscle-tendon complex, present several unique features compared with other types of contractions, which may lead to unique adaptations. Due to its specific physiological and mechanical properties, there is an increasing interest in employing eccentric muscle work for rehabilitation and clinical purposes. However, unaccustomed eccentric exercise is known to cause muscle damage and delayed pain, commonly defined as "Delayed-Onset Muscular Soreness" (DOMS). To date, the most useful preventive strategy to avoid these adverse effects consists of repeating sessions involving submaximal eccentric contractions whose intensity is progressively increased over the training. Despite an increased number of investigations focusing on the eccentric contraction, a significant gap still remains in our understanding of the cellular and molecular mechanisms underlying the initial damage response and subsequent adaptations to eccentric exercise. Yet, unraveling the molecular basis of exercise-related muscle damage and soreness might help uncover the mechanistic basis of pathological conditions as myalgia or neuromuscular diseases. In addition, a better insight into the mechanisms governing eccentric training adaptations should provide invaluable information for designing therapeutic interventions and identifying potential therapeutic targets.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3389/fphys.2019.00536

Cites

14 of 14 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 393

Metadata

Authors
Hody, S., Croisier, J.-L., Bury, T., Rogister, B., & Leprince, P.
Venue
Frontiers in Physiology
Published
2019-05-03
Volume
10
Pages
536-536
ISSN
1664-042X (ISSN-L)
OpenAlex
W2272991862
Cited by
393
References
14
FWCI
24.17
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.