Addition of glutamine to essential amino acids and carbohydrate does not enhance anabolism in young human males following exercise
Bibliographic record
Abstract
We examined the effect of a post-exercise oral carbohydrate (CHO, 1 g.kg(-1).h(-1)) and essential amino acid (EAA, 9.25 g) solution containing glutamine (0.3 g/kg BW; GLN trial) versus an isoenergetic CHO-EAA solution without glutamine (control, CON trial) on muscle glycogen resynthesis and whole-body protein turnover following 90 min of cycling at 65% VO2 peak. Over the course of 3 h of recovery, muscle biopsies were taken to measure glycogen resynthesis and mixed muscle protein synthesis (MPS), by incorporation of [ring-2H5] phenylalanine. Infusion of [1-13C] leucine was used to measure whole-body protein turnover. Exercise resulted in a significant decrease in muscle glycogen (p < 0.05) with similar declines in each trial. Glycogen resynthesis following 3 h of recovery indicated no difference in total accumulation or rate of repletion. Leucine oxidation increased 2.5 fold (p < 0.05) during exercise, returned to resting levels immediately post-exercise,and was again elevated at 3 h post-exercise (p < 0.05). Leucine flux, an index of whole-body protein breakdown rate, was reduced during exercise, but increased to resting levels immediately post-exercise, and was further increased at 3 h post-exercise (p < 0.05), but only during the CON trial. Exercise resulted in a marked suppression of whole-body protein synthesis (50% of rest; p < 0.05), which was restored post-exercise; however, the addition of glutamine did not affect whole-body protein synthesis post-exercise. The rate of MPS was not different between trials. The addition of glutamine to a CHO + EAA beverage had no effect on post-exercise muscle glycogen resynthesis or muscle protein synthesis, but may suppress a rise in whole-body proteolysis during the later stages of recovery.
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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".