Postprandial plasma amino acid and appetite responses to a low protein breakfast supplemented with whey or pea protein in middle-to-older aged adults
Bibliographic record
Abstract
Abstract The addition of low-dose protein to low protein-containing meals in middle-to-older aged adults may promote greater postprandial plasma aminoacidemia and mitigate declines in muscle health but may be dependent on the source and quality of protein consumed. This single-blind randomised study investigated postprandial plasma aminoacidemia and appetite regulatory responses to a typical lower protein-containing (∼0.07 g·kg body mass[BM]−1) mixed breakfast supplemented with ∼0.13 g·kg BM− 1 of whey protein concentrate (MB + WPC) or pea protein isolate (MB + PPI) in middle-to-older aged adults. Venous blood samples were collected whilst fasted and over a 180-min postprandial period to determine plasma amino acid and appetite hormone concentrations. Perceived appetite ratings were measured using Visual Analogue Scales. Plasma total amino acids and essential amino acids increased over time (both P < 0.05) with no between-group differences or overall availability over 180 min (incremental area under the curve (iAUC)). Plasma leucine concentrations increased over time (both P < 0.05) with greater peak concentrations (P = 0.032) and iAUC (P = 0.012) in MB + WPC compared with MB + PPI. Plasma total-ghrelin and total-GLP-1 concentrations and perceived ratings of hunger, fullness, and satiety were transiently altered following MB + WPC and MB + PPI (P < 0.05 for all), with no differences between groups. In middle-to-older aged adults, co-ingesting a small bolus of whey protein alongside a typical lower protein-containing breakfast elicits greater plasma leucinemia than co-ingestion of pea protein, with no differential impact on appetite regulation. Whether the addition of low-dose whey protein to typical meals of middle-to-older aged adults can enhance muscle anabolism without adversely affecting appetite remains to be determined.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".