Effects of low-load resistance exercise with blood flow restriction on intramuscular hemodynamics, oxygenation level and water content
Bibliographic record
Abstract
BACKGROUND: Muscle metabolism during and after low-load blood flow restriction (BFR) exercise should be further investigated to clarify the mechanism by which the exercise leads to muscle hypertrophy, and increases strength and endurance. We aimed to investigate the effects of low-load resistance exercise with BFR on intramuscular hemodynamics, oxygenation level, and water content. METHODS: Seven men performed ankle plantar flexion exercise (120 repetitions, 30% one repetition maximum) using a custom-made device with and without BFR inside a magnetic resonance scanner. Changes in the total hemoglobin/myoglobin concentration and Tissue Oxygenation Index (TOI) within the medial gastrocnemius were evaluated before, during, and after exercise using near-infrared spectroscopy. Intramuscular water content was evaluated before and after exercise by calculating an apparent diffusion coefficient (ADC) using magnetic resonance diffusion-weighted imaging. RESULTS: The TOI significantly decreased during BFR and non-restricted exercises, and significantly increased after BFR exercise; compared to the non-restricted condition, the BFR condition showed significantly greater changes in the TOI during and after exercise. The total hemoglobin/myoglobin concentration significantly increased during and after exercise in both exercise conditions; the BFR condition temporarily showed significantly greater values during and after exercise. Although the ADC values significantly elevated after BFR and non-restricted exercises, the elevation was significantly greater in the BFR condition. CONCLUSIONS: Compared to non-restricted exercise, low-load BFR exercise exposes an exercising muscle to greater hypoxic and hyperemic environments. Moreover, BFR exercise not only elevates muscle oxygenation level, but also results in greater muscle swelling and reactive hyperemia than those observed after non-restricted 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 | 0.000 |
| 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".