Food ingestion in an upright sitting position increases postprandial amino acid availability when compared with food ingestion in a lying down position
Bibliographic record
Abstract
Dietary protein digestion and absorption kinetics determine the postprandial increase in muscle protein synthesis. We recently demonstrated that body position during feeding can modulate the postprandial rise in plasma amino acid availability. Here we investigated whether protein ingestion in an upright sitting body position accelerates gastric emptying and improves dietary protein digestion and subsequent amino acid absorption compared with feeding in a supine lying body position. In a crossover design, 8 young males (age, 26 ± 1 years; body mass index, 24.0 ± 0.9 kg·m−2) ingested 20 g intrinsically l-[1-13C]-phenylalanine–labeled milk protein plus 1.5 g paracetamol while sitting in an upright position or lying down in a supine position. Blood samples were collected frequently during a 5-h postprandial period. Gastric emptying rates and dietary protein digestion and absorption were assessed using plasma paracetamol and amino acid concentrations as well as plasma l-[1-13C]-phenylalanine enrichments. Peak plasma leucine concentrations were higher when protein was ingested in an upright sitting versus lying position (213 ± 15 vs 193 ± 12 μmol·L−1, P < 0.05), which was accompanied by a trend for a greater overall leucine response (13 989 ± 720 vs 11 875 ± 1073 AU, respectively; P = 0.05). Peak plasma paracetamol concentrations were higher in the sitting versus lying treatment (11.6 ± 0.5 vs 9.3 ± 0.6 mg·L−1, P < 0.05). Protein ingestion in an upright sitting position accelerates gastric emptying and increases the postprandial rise in plasma amino acid availability by increasing protein digestion and amino acid absorption rates. Therefore, feeding in an upright body position as opposed to a lying position is an important prerequisite to allow proper postprandial muscle protein accretion.
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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) | 0.001 | 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 | 0.000 | 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".