Heavy-Intensity Priming Exercise Attenuates the Rate of Quadriceps Muscle Fatigue and Improves Time-to-Task Failure during Severe-Intensity Cycling
Bibliographic record
Abstract
BACKGROUND: Prior high-intensity exercise (priming) has been shown to accelerate the oxygen uptake (V̇O 2 ) kinetics, as well as improve exercise tolerance during subsequent high-intensity exercise, yet the mechanisms underpinning the performance changes are unclear. In theory, a reduced reliance on non-oxidative energy input afforded by the faster V̇O 2 response may improve subsequent performance by delaying muscle fatigue; however, this effect has yet to be conclusively shown. PURPOSE: Our purpose was to explore the impact of priming exercise on the energetic response, exercise tolerance, and the kinetics of muscle fatigue during severe-intensity cycling exercise. METHODS: Fourteen participants completed constant power cycling trials in the severe domain, preceded by either a bout of heavy intensity or an equivalent duration cycling at 20 W. Muscle fatigue was assessed in real time via femoral nerve stimulation while pedaling, and energetic contributions were assessed via V̇O 2 and changes in blood lactate concentration. Quadriceps oxygenation and surface electromyography (EMG) were also measured. RESULTS: Priming improved time-to-task failure (450 ± 74 s) compared with control (391 ± 92 s) ( P = 0.008). Relative oxidative contributions increased following priming ( P = 0.001), whereas the non-oxidative glycolytic contribution was reduced ( P < 0.0001), and this was accompanied by a reduction in the rate of quadriceps twitch force decline ( P = 0.041). Vastus lateralis EMG root mean square amplitude and M-wave amplitude increased across the trial similarly in both conditions, but priming resulted in a relative "downshift" in both measures ( P ≤ 0.027). CONCLUSIONS: Priming exercise resulted in an improvement in exercise tolerance, attenuation in muscle fatigue, and reduction in EMG and M-wave amplitude. We speculate that these effects may arise in part from the interaction between a reduction in metabolite accumulation and altered sarcolemmal excitability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".