Postprandial plasma aminoacidemia and indices of appetite regulation following pea-rice blend, pea isolate and whey protein ingestion in healthy young adults
Bibliographic record
Abstract
Abstract Plant-derived proteins are often deficient in essential amino acids and have lower rates of digestibility than animal-derived proteins. Blending different plant-derived proteins could compensate for these deficiencies and may augment postprandial aminoacidemia over single-source plant proteins. This study assessed plasma amino acids and appetite hormones, appetite sensations and ad libitum energy intake following ingestion of a pea-rice protein blend (BLEND), compared with pea-only (PEA) and whey (WHEY) protein. In a randomised, double-blind, crossover design, ten healthy adults (M n 4, F n 6; mean (sd) age 22 (sd 3) years; BMI 24 (sd 3) kg·m2) ingested 0·3 g·kg·body mass–1 of BLEND, PEA or WHEY. Arterialised venous blood samples and appetite ratings were obtained in the fasted state and over 240 min postprandially. Energy intake was measured via an ad libitum buffet-style test meal. Mean plasma essential amino acid incremental AUC was higher in WHEY, compared with PEA (P < 0·01; mean diff (95 % CI): 44 218 (15 806, 72 631) μmol·240 min·l–1) and BLEND (P < 0·01; 14 358 (16 031, 101 121) μmol·240 min·l–1), with no differences between PEA and BLEND (P = 0·67). Plasma ghrelin and glucagon-like peptide-1, appetite ratings and ad libitum energy intake responses did not differ between treatments (P > 0·05 for all). Ingestion of a pea-rice protein blend did not augment postprandial aminoacidemia above pea protein, perhaps attributable to marginal differences in essential amino acid composition. No between-treatment differences in appetite or energy intake responses were apparent, suggesting that the influence of protein ingestion on perceived appetite ratings and orexigenic hormonal responses may not be solely determined by postprandial plasma aminoacidemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| 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".