Short-term training attenuates muscle TCA cycle expansion during exercise in women
Bibliographic record
Abstract
Muscle glycogenolytic flux and lactate accumulation during exercise are lower after 3-7 days of "short-term" aerobic training (STT) in men (e.g., Green HJ, Helyar R, Ball-Burnett M, Kowalchuk N, Symon S, and Farrance B. J Appl Physiol 72: 484-491, 1992). We hypothesized that 5 days of STT would attenuate pyruvate production and the increase in muscle tricarboxylic acid cycle intermediates (TCAI) during exercise, because of reduced flux through the reaction catalyzed by alanine aminotransferase (AAT; pyruvate + glutamate <--> 2-oxoglutarate + alanine). Eight women [22 +/- 1 yr, peak oxygen uptake (Vo2 peak) = 40.3 +/- 4.6 ml. kg-1. min-1] performed seven 45-min bouts of cycle exercise at 70% Vo2 peak over 9 days (1 bout/day; rest only on days 2 and 8). During the first and last bouts, biopsies (vastus lateralis) were obtained at rest and after 5 and 45 min of exercise. Muscle glycogen concentration was approximately 50% higher at rest after STT (493 +/- 38 vs. 330 +/- 20 mmol/kg dry wt; P <or= 0.05), and net glycogenolysis and lactate accumulation were reduced after 5 min of exercise by 59 and 49%, respectively (P <or= 0.05). The net increase in four measured TCAI was approximately 40% lower (P <or= 0.05) during exercise after training (1.68 +/- 0.60 vs. 2.71 +/- 0.44 mmol/kg dry wt), and the net decrease in glutamate concentration was attenuated (P
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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) | 0.001 | 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".