Concurrent Pain Effects On Exercise Tolerance, Neuromuscular Fatigue And Perceptual Responses, Preliminary Data.
Bibliographic record
Abstract
Exercise-induced fatigue and pain negatively affect exercise tolerance; however, the influence of these sensations on regulation of neuromuscular (NM) and perceptual responses during locomotor exercise has yet to be determined. PURPOSE: To investigate the effects of one leg exercise-induced fatigue and pain on the contralateral leg exercise tolerance, NM and perceptual responses. METHODS: Nine healthy young men (age: 26±7 years) performed right leg sustained contraction at 25% of isometric maximal voluntary contraction (25%IMVC) to task failure. In three testing sessions, the 25%IMVC protocol was preceded by one of the three left leg interventions including: i) 6 min rest (CON) ii) cycling to exhaustion at 80% of peak power output (CYCL) and iii) CYCL immediately followed by blood flow occlusion to right leg task failure (OCCL). The experimental sessions were selected randomly. NM function was characterized by assessing IMVC and voluntary activation (VA) using twitch interpolated technique. Right leg pain and rating of perceived exertion (RPE) were also recorded during sustained contraction. RESULTS: 25%IMVC to task failure was longer in CON (221 ± 106 s) than CYCL (141 ± 67 s) and OCCL (119 ± 51 s) (p < 0.05). Relative to baseline, the drop on IMVC was similar for CON (-40±10%), CYCL (-36 ± 18%) and OCCL (-32 ± 17%) (p = 0.09). VA drop was also similar for CON (-6 ± 12 %), CYCL (-9 ± 11%) and OCCL (-15 ± 18%) (p > 0.05). The potentiated twitch force decline was lower for OCCL (-44 ± 25 %) when compared to CYCL (-53 ± 24 %) and CON (-51 ± 23 %) (p < 0.05). During the 25%IMVC, RPE at the onset was lower for CON (7 ± 2) compared to CYCL (13 ± 3) and OCCL (14 ± 3) (p < 0.001) but no difference was observed between the three conditions at the task failure (18 ± 2, 19 ± 1 and 19 ± 1, respectively) (p > 0.05). Right leg pain increased from onset to exhaustion for CON (2 ± 2 and 9 ± 1), CYCL (2 ± 2 and 9 ± 1) and OCCL (2 ± 1 and 9 ± 1) (p < 0.05). Left leg pain decreased from the onset of the right leg exercise to task failure for CYCL (6 ± 1 and 3 ± 2) (p < 0.05) however it stayed high during OCCL (9 ± 1 and 9 ± 1) (p < 0.05). CONCLUSION: Our preliminary data suggest that one leg exercise-induced fatigue and pain decreased the contralateral leg exercise tolerance, exacerbated perceptual pain and RPE, and blunted peripheral fatigue during subsequent exercise.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.004 | 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".