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Prolonged Low‐frequency Force Depression is Underestimated When Assessed with Doublets Compared to Trains

2018· article· en· W3154061412 on OpenAlexafffund
Christina D. Bruce, Luca Ruggiero, Paul D. Cotton, Gabriel U. Dix, Chris J. McNeil

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan Campus
FundersNatural Sciences and Engineering Research Council of CanadaBritish Columbia Knowledge Development FundCummings Foundation
KeywordsIsometric exerciseEccentricAnklePhysical medicine and rehabilitationPlantar flexionStimulationMuscle contractionMedicineChemistryCardiologyPhysical therapyPhysicsInternal medicineAnatomy

Abstract

fetched live from OpenAlex

Unaccustomed eccentric exercise induces muscle damage, which leads to an impairment of force or torque that can last for several days. A common indirect measure of muscle damage is a greater depression of the force response to low‐frequency (e.g., 10Hz) compared to high‐frequency (e.g., 100Hz) stimulation; i.e., a post‐exercise reduction in the 10:100Hz ratio. This phenomenon is termed, prolonged low‐frequency force depression (PLFFD). Historically, trains of stimuli (e.g., 1s) have been used to evoke tetanic responses for the ratio. More recently, some authors have used only paired stimuli to evoke doublets. However, it is unknown if the PLFFD indicated by doublet responses is equivalent to the value derived from the traditional tetanic responses. Hence, the purpose of this study was to compare the magnitude of PLFFD determined by doublet vs. tetanic responses. We hypothesized that the doublet ratio (DR) would indicate significantly less PLFFD than the train ratio (TR). Eight participants (four females) performed 200 eccentric maximal voluntary contractions (4 sets of 50 repetitions, 1s rest between repetitions and 1 min rest between sets) of the dorsiflexors to induce muscle damage. Eccentric contractions were performed at 60°/s, started at a neutral ankle position, and finished at 30° of plantar flexion. Before the fatiguing protocol, baseline neuromuscular function was measured by a sequence of isometric contractions evoked by supramaximal electrical stimulation of the fibular nerve (paired stimuli at 10 and 100Hz, and 1s trains at 10 and 100Hz, each separated by 1s rest). This neuromuscular function test was repeated three times prior to fatigue and 2 min, 3 min, 5 min, 10 min and 48h after the fatiguing protocol. Using the peak torque of each response, 10:100Hz ratios were calculated at all time points; post‐exercise values were expressed as a percentage of the respective baseline ratio. At baseline, the DR was greater than TR (0.81 ± 0.04 vs. 0.48 ± 0.09; P < 0.01). PLFFD was observed by 2 min for TR (73 ± 12%) and 3 min for DR (83 ± 9%), continued to develop over the acute recovery phase (at 10 min, DR = 73 ± 9%; TR = 51 ± 11%), and recovered by 48h (DR = 98 ± 6%; TR = 91 ± 12%). The TR was reduced more than the DR at all acute recovery time points (P < 0.05), but not 48h. With DR and TR revealing different levels of PLFFD following damaging eccentric contractions, our results indicate that these techniques should not be used interchangeably. Whenever possible, trains of stimuli should be used to indicate the true extent of PLFFD. In cases where the reproducibility of the tetanic force response may be problematic (e.g., femoral nerve stimulation) or a train is deemed prohibitively uncomfortable, it should be acknowledged that paired stimuli will underestimate PLFFD. Support or Funding Information Supported by NSERC, CFI and BCKDF This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.246
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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