The effect of blood flow on tibialis anterior motor unit firing rates during sustained low-intensity isometric contractions
Bibliographic record
Abstract
Low-intensity contractions with blood flow occlusion (BFO) result in neuromuscular adaptations comparable with high-intensity (>70% maximal voluntary contraction, MVC) exercise. Because BFO exercise can only be applied to limb muscles, it is of interest to explore whether muscles proximal to the occlusion site are affected. Therefore, the purpose of this study was to assess neural activation of the tibialis anterior (TA) when flow is occluded proximal and distal to the active muscle. Five males completed three protocols to observe the effect of BFO on motor unit firing rates (MUFR) of the TA at a fatiguing contraction intensity of ∼15% MVC. Two occlusion protocols, one proximal (BFOprox) to and one distal (BFOdis) to the TA, were compared with a control (free-flow) protocol time-matched to BFOdis. MVC was significantly reduced following the BFOprox (∼41%; P < 0.001) and BFOdis (∼27%, P < 0.001), but not following the control protocol (∼15%; P = 0.13). Surface electromyography (EMG) during BFOdis and BFOprox increased ∼14% and ∼28%, respectively, but was not different among protocols. MUFRs for BFOdis and BFOprox were significantly reduced (by ∼33% and ∼23%, respectively; P < 0.01) at task failure. Results indicate that although BFOprox results in the largest reductions of MUFRs, BFOdis shows greater impairments compared with the free-flow control condition. Novelty Effects on motor unit firing rates of proximal versus distal blood flow occlusion were compared during low-intensity fatiguing task. Proximal occlusion results in greatest fatigue and reduction in motor unit rates, but distal occlusion elicits more fatigue and rate reduction than a control task.
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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) | 0.001 | 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".