Mitochondrial adaptations to high‐volume exercise training are rapidly reversed after a reduction in training volume in human skeletal muscle
Bibliographic record
Abstract
Increased mitochondrial content and respiration have both been reported after exercise training. However, no study has directly compared how different training volumes influence mitochondrial respiration and markers of mitochondrial biogenesis. Ten healthy men performed high-intensity interval cycling during 3 consecutive training phases; 4 wk of normal-volume training (NVT; 3/wk), followed by 20 d of high-volume training (HVT; 2/d) and 2 wk of reduced-volume training (RVT; 5 sessions). Resting biopsy samples (vastus lateralis) were obtained at baseline and after each phase. No mitochondrial parameter changed after NVT. After HVT, mitochondrial respiration and citrate synthase activity (∼40-50%), as well as the protein content of electron transport system (ETS) subunits (∼10-40%), and that of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α), NRF1, mitochondrial transcription factor A (TFAM), PHF20, and p53 (∼65-170%) all increased compared to baseline; mitochondrial specific respiration remained unchanged. After RVT, all the mitochondrial parameters measured except citrate synthase activity (∼36% above initial) were not significantly different compared to baseline (all P > 0.05). Our findings demonstrate that training volume is an important determinant of training-induced mitochondrial adaptations and highlight the rapid reversibility of human skeletal muscle to a reduction in training volume.-Granata, C., Oliveira, R. S. F., Little, J. P., Renner, K., Bishop, D. J. Mitochondrial adaptations to high-volume exercise training are rapidly reversed after a reduction in training volume in human skeletal muscle.
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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) | 0.001 | 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".