Glutamate ingestion: the plasma and muscle free amino acid pools of resting humans
Bibliographic record
Abstract
Monosodium glutamate (MSG) ingestion is known to increase plasma glutamate concentration, and MSG infusion stimulates insulin secretion. We investigated the impact of MSG ingestion on both the plasma and intramuscular amino acid pools. Nine postprandial adults ingested MSG (150 mg/kg) and rested for 105 min. Venous blood was sampled preingestion and then every 15 min; vastus lateralis muscle biopsies were taken preingestion and at 45, 75, and 105 min postingestion. Venous plasma glutamate and aspartate concentrations increased (P </= 0.05) approximately 700-800 and 300-400%, respectively, after 30-45 min. Although several other plasma amino acids increased modestly, the rise in glutamate accounted for approximately 80% of the increase in total plasma amino acids. In addition, plasma insulin increased threefold after 15 min; this occurred before a significant increase in plasma glutamate, indicating a feed-forward stimulation from the gastrointestinal tract. The intramuscular amino acid pool was remarkably constant, with only glutamate increasing (P </= 0.05) by 3.56 mmol/kg dry wt. By 105 min, the plasma and muscle amino acids had returned to resting concentrations. This increase in muscle glutamate concentration could account for approximately 40% of the MSG ingested; we propose that resting skeletal muscle is a major sink for the glutamate and metabolizes it to aspartate.
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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 | 0.001 | 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".