Training intensity modulates changes in PGC‐1α and p53 protein content and mitochondrial respiration, but not markers of mitochondrial content in human skeletal muscle
Why this work is in the frame
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Bibliographic record
Abstract
Exercise training has been associated with increased mitochondrial content and respiration. However, no study to date has compared in parallel how training at different intensities affects mitochondrial respiration and markers of mitochondrial biogenesis. Twenty-nine healthy men performed 4 wk (12 cycling sessions) of either sprint interval training [SIT; 4-10 × 30-s all-out bouts at ∼200% of peak power output (WPeak)], high-intensity interval training (HIIT; 4-7 × 4-min intervals at ∼90% WPeak), or sublactate threshold continuous training (STCT; 20-36 min at ∼65% WPeak). The STCT and HIIT groups were matched for total work. Resting biopsy samples (vastus lateralis) were obtained before and after training. The maximal mitochondrial respiration in permeabilized muscle fibers increased significantly only after SIT (25%). Similarly, the protein content of peroxisome proliferator-activated receptor γ coactivator (PGC)-1α, p53, and plant homeodomain finger-containing protein 20 (PHF20) increased only after SIT (60-90%). Conversely, citrate synthase activity, and the protein content of TFAM and subunits of the electron transport system complexes remained unchanged throughout. Our findings suggest that training intensity is an important factor that regulates training-induced changes in mitochondrial respiration and that there is an apparent dissociation between training-induced changes in mitochondrial respiration and mitochondrial content. Moreover, changes in the protein content of PGC-1α, p53, and PHF20 are more strongly associated with training-induced changes in mitochondrial respiration than mitochondrial content.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it