High‐intensity sprint training inhibits mitochondrial respiration through aconitase inactivation
Bibliographic record
Abstract
Intense exercise training is a powerful stimulus that activates mitochondrial biogenesis pathways and thus increases mitochondrial density and oxidative capacity. Moderate levels of reactive oxygen species (ROS) during exercise are considered vital in the adaptive response, but high ROS production is a serious threat to cellular homeostasis. Although biochemical markers of the transition from adaptive to maladaptive ROS stress are lacking, it is likely mediated by redox sensitive enzymes involved in oxidative metabolism. One potential enzyme mediating such redox sensitivity is the citric acid cycle enzyme aconitase. In this study, we examined biopsy specimens of vastus lateralis and triceps brachii in healthy volunteers, together with primary human myotubes. An intense exercise regimen inactivated aconitase by 55-72%, resulting in inhibition of mitochondrial respiration by 50-65%. In the vastus, the mitochondrial dysfunction was compensated for by a 15-72% increase in mitochondrial proteins, whereas H2O2 emission was unchanged. In parallel with the inactivation of aconitase, the intermediary metabolite citrate accumulated and played an integral part in cellular protection against oxidative stress. In contrast, the triceps failed to increase mitochondrial density, and citrate did not accumulate. Instead, mitochondrial H2O2 emission was decreased to 40% of the pretraining levels, together with a 6-fold increase in protein abundance of catalase. In this study, a novel mitochondrial stress response was highlighted where accumulation of citrate acted to preserve the redox status of the cell during periods of intense 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) | 0.000 | 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 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".