Does lower oxidative capacity influence the relative contributions of ATP-producing pathways during muscular work in aging?
Bibliographic record
Abstract
Although the capacity of skeletal muscle to produce ATP via oxidative phosphorylation may decrease in some muscles in older age, the influence of a lower capacity on relative use of oxidative and non-oxidative ATP production pathways in vivo during contractions is unclear. To test the hypothesis that lower oxidative capacity would yield greater non-oxidative ATP production, 19 young (10F) and 17 older (9F) adults performed knee extensor muscle contractions in a 3-tesla magnetic resonance system. Phosphorus metabolites were used to calculate oxidative capacity (rate constant of phosphocreatine recovery; kPCr, s-1) and estimate the maximal rate of oxidative ATP production (Vmax, mM·s-1) following a 24-s dynamic contraction protocol. Next, ATP production (mM·s-1) by the creatine kinase reaction (ATPCK), glycolysis (ATPGLY), and oxidative phosphorylation (ATPOX) was determined during 4 min of dynamic muscle contractions. Proton spectroscopy of deoxymyoglobin was also acquired in a subset (n = 12) and used to calculate the cytosolic partial pressure of oxygen (PO2). Young muscle had a greater kPCr (0.023 ± 0.005 s-1, mean ± SD) than older muscle (0.020 ± 0.003 s-1, P = .033). ATPCK, ATPGLY, and ATPOX were not different by group (P ≥ .129), but ATPOX as %Vmax was lower in younger than older muscle (55 ± 14%, 71 ± 10%, respectively, P < .001). Intracellular oxygen availability (PO2) was not different by group (young: 2.4 ± 0.7 Torr, n = 7; older: 3.2 ± 1.6 Torr, n = 5, P = .371). These new findings suggest a bioenergetic rigidity in older muscle, such that it adapts to the energetic demand by using oxidative ATP production at a greater percentage of capacity rather than switching to an increased use of non-oxidative ATP production.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".