The effects of pain induced by blood flow occlusion in one leg on exercise tolerance and corticospinal excitability and inhibition of the contralateral leg in males
Bibliographic record
Abstract
Experiencing pain in one leg can alter exercise tolerance and neuromuscular fatigue (NMF) responses in the contralateral leg; however, the corticospinal modulations to nonlocal experimental pain induced by blood flow occlusion remain unknown. In three randomized visits, 13 male participants performed 25% of isometric maximal voluntary contraction (25%IMVC) to task failure with one leg preceded by (i) 6-min rest (CON), (ii) cycling at 80% of peak power output until task failure with the contralateral leg (CYCL), or (iii) CYCL followed by blood flow occlusion (OCCL) during 25%IMVC. NMF assessments (IMVC, voluntary activation [VA], and potentiated twitch [Qtw]) were performed at baseline and task failure. During the 25%IMVC, transcranial magnetic stimulations were performed to obtain motor-evoked potential (MEP), silent period (SP), and short intracortical inhibition (SICI). 25%IMVC was the shortest in OCCL (105 ± 50s) and shorter in CYCL (154 ± 68 s) than CON (219 ± 105 s) ( p < 0.05). IMVC declined less after OCCL (–24 ± 19%) and CYCL (–27 ± 18%), then CON (–35 ± 11%) ( p < 0.05). Qtw declined less in OCCL (–40 ± 25%) compared to CYCL (–50 ± 22%) and CON (–50 ± 21%) ( p < 0.05). VA was similar amongst conditions. MEP and SP increased and SICI decreased throughout the task, while SP was longer for OCCL compared to CYC condition ( p < 0.05). The results suggest that pain in one leg diminishes contralateral limb exercise tolerance and NMF development and modulate corticospinal inhibition in males. Novelty: Pain in one leg diminished MVC and twitch force decline in the contralateral limb. Experimental pain induced by blood flow occlusion may modulation corticospinal inhibition of the neural circuitries innervating the contralateral exercise limb.
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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) | 0.000 | 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) | 0.002 | 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".