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Central fatigue assessment following high-intensity exercise performed in human dorsiflexor muscles

2025· article· en· W4411879793 on OpenAlexaff
Andrew J. Richards, Rohin Malekzadeh, Sarva Saeid, Robert Laham, Arthur J. Cheng

Bibliographic record

VenuePhysiology · 2025
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsYork University
Fundersnot available
KeywordsMedicinePhysical medicine and rehabilitationMuscle fatigueIntensity (physics)Physical therapyElectromyographyPhysics

Abstract

fetched live from OpenAlex

Background: Central fatigue (CF) is defined as a progressive exercise-induced failure in the voluntary activation (VA) of the muscle. Muscle afferent III and IV neurons are proposed to be major contributors to central fatigue development by detecting increases in intramuscular metabolite accumulation that leads to inhibition of descending neural drive during voluntary contractions. Yet, during high-intensity exercise, few studies show evidence of central fatigue using the interpolated twitch technique. These results contradict the current hypotheses regarding the inhibitory function of group III/IV afferents on the voluntary activation of muscles. Objective: 1) To develop a method to better evaluate central fatigue during high-intensity interval exercise (HIIE). 2) To investigate the proposed influence of group III/IV metabolite receptors on central fatigue development during HIIE. Hypothesis: It was hypothesized that voluntary activation failure would be evident following metabolically-demanding HIIE by assessing central fatigue during a 60 s sustained maximal effort contraction that stresses the neural activation of muscle. Methods: Ten healthy, recreationally active adult human participants (7 M; 3 F) performed six sets of 30 s all-out isokinetic concentric dorsiflexion at 160°/s. Each bout was followed by a 60 s sustained maximal voluntary contraction (MVC) whereby twitch interpolation was performed every 10 s during the MVC to measure voluntary activation. Each set was followed by a 2-min rest. Results: Minimal central fatigue was observed during the 60 s sustained MVC following each set of high-intensity interval exercise. Relative to the pre-exercise set, some voluntary activation failure was observed at the following sets and timepoints (VA%): Post set-1 at 20 s (93%, p <0.05), post set-3 at 0 s and 20 s (93% and 89%, respectively p <0.05), and post set-5 at 10 s (93%, p <0.05). Mean VA% at post-exercise sets 3 (92%, p <0.01), 5 (92%, p <0.001), and 6 (92%, p <0.05) revealed minimal voluntary activation failure following HIIE. Conclusion: Our study revealed that the human dorsiflexor muscles are resilient against central fatigue development during metabolically-demanding high-intensity exercise. Funded by NSERC Discovery and American Physiology Society SURF program. This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.268
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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