The effect of oral essential amino acids on incretin hormone production in youth and ageing
Bibliographic record
Abstract
Abstract Background The effect of substantive doses of essential amino acids (EAA) on incretin and insulin production, and the impact of age upon this effect, is ill‐defined. Methods A 15‐g oral EAA drink was administered to young (N = 8; 26 ± 4.4 years) and older (N = 8; 69 ± 3.8 years) healthy volunteers. Another group of younger volunteers (N = 9; 21 ± 1.9 years) was given IV infusions to achieve equivalent plasma amino acids (AA) profiles. Plasma AA, insulin, glucagon‐like peptide‐1 (GLP‐1) and glucose‐dependent insulinotropic peptide (GIP) were quantified over 2 hours. Results In younger recruits, EAA‐induced rapid insulinaemia and aminoacidaemia with total amino acids(AA), EAA and branched chain amino acids (BCAA) matched between oral and IV groups. Insulin peaked at 39 ± 29 pmol L−1 at 30 minutes following oral feeding compared to 22 ± 9 pmol L−1 at 60 minutes following IV feeding (P: NS). EAA peaked at 3395 μmol L−1 at 45 minutes during IV infusion compared to 2892 μmol L−1 following oral intake (Feeding effect: P < 0.0001. Oral vs IV feeding: P: NS). There was an 11% greater increase in insulin levels in the 120 minutes duration of the study in response to oral EAA as opposed to IV EAA. GIP increased following oral EAA (452 pmol L−1 vs 232 pmol L−1, P < 0.05). Age did not impact insulin or incretins production. Conclusion Postprandial rises in EAA levels lead to rapid insulinaemia which is higher with oral compared with IV EAA, that is attributed more to GIP and unaffected by age. This finding supports EAA, on their own or as part of high‐protein meal, as nutritive therapeutics in impaired glycaemia and ageing.
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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 | 0.001 |
| 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".