An enzymatic approach to lactate production in human skeletal muscle during exercise
Bibliographic record
Abstract
PURPOSE: This paper examines the production of lactate in human skeletal muscle over a range of power outputs (35-250% VO2max) from an enzymatic flux point of view. The conversion of pyruvate and NADH to lactate and NAD in the cytoplasm of muscle cells is catalyzed by the near-equilibrium enzyme lactate dehydrogenase (LDH). As flux through LDH is increased by its substrates, pyruvate and NADH, the factors governing the production of these substrates will largely dictate how much lactate is produced at any exercise power output. In an attempt to understand lactate production, flux rates through the enzymes that regulate glycogenolysis/glycolysis, the transfer of cytoplasmic reducing equivalents into the mitochondria, and the various fates of pyruvate have been measured or estimated. RESULTS: At low power outputs, the rates of pyruvate and NADH production in the cytoplasm are low, and pyruvate dehydrogenase (PDH) and the shuttle system enzymes (SS) metabolize the majority of these substrates, resulting in little or no lactate production. At higher power outputs (65, 90, and 250% VO2max), the mismatch between the ATP demand and aerobic ATP provision at the onset of exercise increases as a function of intensity, resulting in increasing accumulations of the glycogenolytic/glycolytic activators (free ADP, AMP, and Pi). The resulting glycolytic flux, and NADH and pyruvate production, is progressively greater than can be handled by the SS and PDH, and lactate is produced at increasing rates. Lactate production during the onset of exercise and 10 min of sustained aerobic exercise may be a function of adjustments in the delivery of O2 to the muscles, adjustments in the activation of the aerobic ATP producing metabolic pathways and/or substantial glycogenolytic/glycolytic flux through a mass action effect.
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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 | 0.001 | 0.001 |
| 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".