Glutamate availability is important in intramuscular amino acid metabolism and TCA cycle intermediates but does not affect peak oxidative metabolism
Bibliographic record
Abstract
Muscle glutamate is central to reactions producing 2-oxoglutarate, a tricarboxylic acid (TCA) cycle intermediate that essentially expands the TCA cycle intermediate pool during exercise. Paradoxically, muscle glutamate drops approximately 40-80% with the onset of exercise and 2-oxoglutarate declines in early exercise. To investigate the physiological relationship between glutamate, oxidative metabolism, and TCA cycle intermediates (i.e., fumarate, malate, 2-oxoglutarate), healthy subjects trained (T) the quadriceps of one thigh on the single-legged knee extensor ergometer (1 h/day at 70% maximum workload for 5 days/wk), while their contralateral quadriceps remained untrained (UT). After 5 wk of training, peak oxygen consumption (VO2peak) in the T thigh was greater than that in the UT thigh (P<0.05); VO2peak was not different between the T and UT thighs with glutamate infusion. Peak exercise under control conditions revealed a greater glutamate uptake in the T thigh compared with rest (7.3+/-3.7 vs. 1.0+/-0.1 micromol.min(-1).kg wet wt(-1), P<0.05) without increase in TCA cycle intermediates. In the UT thigh, peak exercise (vs. rest) induced an increase in fumarate (0.33+/-0.07 vs. 0.02+/-0.01 mmol/kg dry wt (dw), P<0.05) and malate (2.2+/-0.4 vs. 0.5+/-0.03 mmol/kg dw, P<0.05) and a decrease in 2-oxoglutarate (12.2+/-1.6 vs. 32.4+/-6.8 micromol/kg dw, P<0.05). Overall, glutamate infusion increased arterial glutamate (P<0.05) and maintained this increase. Glutamate infusion coincided with elevated fumarate and malate (P<0.05) and decreased 2-oxoglutarate (P<0.05) at peak exercise relative to rest in the T thigh; there were no further changes in the UT thigh. Although glutamate may have a role in the expansion of the TCA cycle, glutamate and TCA cycle intermediates do not directly affect VO2peak in either trained or untrained muscle.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".