Increased muscle oxidative potential following resistance training induced fibre hypertrophy in young men
Bibliographic record
Abstract
Some evidence suggests that resistance training may lower relative muscle mitochondrial content via "dilution" of the organelle in a larger muscle fibre. Such an adaptation would reduce fatigue resistance, as well as compromise oxidative ATP synthesis and the capacity for fatty-acid oxidation. We investigated the effect of resistance training on mitochondrial enzymes of the citric acid cycle (citrate synthase; CS) and beta-oxidation (beta-hydroxyacyl CoA dehydrogenase; beta-HAD), as well as markers of the potential for glucose phosphorylation (hexokinase; HK) and glycolysis (phosphofructokinase; PFK). Twelve untrained men (21.9 +/- 0.5 y; 1.79 +/- 0.03 m; 83.2 +/- 3.2 kg) participated in a 12 week progressive resistance-training program. Muscle biopsies were taken from the vastus lateralis before (PRE) and after (POST) training. Training increased mean muscle fibre cross-sectional area (p < 0.05) and the activities of CS (PRE = 4.53 +/- 0.44 mol.kg protein(-1).h(-1); POST = 5.63 +/- 0.40 mol.kg protein(-1).h(-1); p < 0.001) and beta-HAD (PRE = 2.55 +/- 0.28 mol.kg protein(-1).h(-1); POST = 3.11 +/- 0.21 mol.kg protein(-1).h(-1); p < 0.05). The activity of HK increased 42% (p < 0.05), whereas the activity of PFK remained unchanged. We conclude that resistance training provides a stimulus for improving muscle oxidative potential, as reflected by the increased activities of CS and beta-HAD following resistance training induced hypertrophy.
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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".