Muscle mass and inspired oxygen influence oxygen extraction at maximal exercise: Role of mitochondrial oxygen affinity
Bibliographic record
Abstract
Abstract Aim We examined the Fick components together with mitochondrial O2 affinity (p50mito) in defining O2 extraction and O2 uptake during exercise with large and small muscle mass during normoxia (NORM) and hyperoxia (HYPER). Methods Seven individuals performed 2 incremental exercise tests to exhaustion on a bicycle ergometer (BIKE) and 2 on a 1‐legged knee extension ergometer (KE) in NORM or HYPER. Leg blood flow and VO2 were determined by thermodilution and the Fick method. Maximal ADP‐stimulated mitochondrial respiration (OXPHOS) and p50mito were measured ex vivo in isolated mitochondria. Mitochondrial excess capacity in the leg was determined from OXPHOS in permeabilized fibres and muscle mass measured with magnetic resonance imaging in relation to peak leg O2 delivery. Results The ex vivo p50mito increased from 0.06 ± 0.02 to 0.17 ± 0.04 kPa with varying substrate supply and O2 flux rates from 9.84 ± 2.91 to 16.34 ± 4.07 pmol O2·s−1·μg−1 respectively. O2 extraction decreased from 83% in BIKE to 67% in KE as a function of a higher O2 delivery and lower mitochondrial excess capacity. There was a significant relationship between O2 extraction and mitochondrial excess capacity and p50mito that was unrelated to blood flow and mean transit time. Conclusion O2 extraction varies with mitochondrial respiration rate, p50mito and O2 delivery. Mitochondrial excess capacity maintains a low p50mito which enhances O2 diffusion from microvessels to mitochondria during 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 | 0.001 |
| 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".