Mitochondrial oxygen affinity increases after sprint interval training and is related to the improvement in peak oxygen uptake
Bibliographic record
Abstract
Abstract Aims The body responds to exercise training by profound adaptations throughout the cardiorespiratory and muscular systems, which may result in improvements in maximal oxygen consumption (VO2peak) and mitochondrial capacity. By convenience, mitochondrial respiration is often measured at supra‐physiological oxygen levels, an approach that ignores any potential regulatory role of mitochondrial affinity for oxygen (p50mito) at physiological oxygen levels. Methods In this study, we examined the p50mito of mitochondria isolated from the Vastus lateralis and Triceps brachii in 12 healthy volunteers before and after a training intervention with seven sessions of sprint interval training using both leg cycling and arm cranking. The changes in p50mito were compared to changes in whole‐body VO2peak. Results We here show that p50mito is similar in isolated mitochondria from the Vastus (40 ± 3.8 Pa) compared to Triceps (39 ± 3.3) but decreases (mitochondrial oxygen affinity increases) after seven sessions of sprint interval training (to 26 ± 2.2 Pa in Vastus and 22 ± 2.7 Pa in Triceps, both P < .01). The change in VO2peak modelled from changes in p50mito was correlated to actual measured changes in VO2peak (R2 = .41, P = .002). Conclusion Together with mitochondrial respiratory capacity, p50mito is a critical factor when measuring mitochondrial function, it can decrease with sprint interval training and should be considered in the integrative analysis of the oxygen cascade from lung to mitochondria.
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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) | 0.002 | 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".