Consumption of High-Leucine-Containing Protein Bar Following Breakfast Impacts Aminoacidemia and Subjective Appetite in Older Persons
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Bibliographic record
Abstract
BACKGROUND: Limited data are available examining dietary interventions for optimizing protein and leucine intake to stimulate muscle protein synthesis (MPS) in older humans. OBJECTIVES: We aimed to investigate the aminoacidemia and appetite responses of older adults after consuming breakfast, a meal frequently consumed with high-carbohydrate and below-par amounts of protein and leucine for stimulating MPS. METHODS: , fat- and bone-free mass: 63 ± 7 kg) took part in this experiment in which they consumed breakfasts with low-protein (LP = 13 ± 2 g), high-protein (HP = 32 ± 5 g), and LP followed by a protein- and leucine-enriched bar formulation 2 h later (LP + Bar = 29 ± 2 g). The LP, HP, and LP + Bar breakfast conditions contained 519 ± 86 kcal, 535 ± 83 kcal, and 739 ± 86 kcal, respectively. Blood samples were drawn for 6 h and analyzed for amino acid, insulin, and glucose concentrations. Visual analog scales were assessed for hunger, fullness, and desire to eat. RESULTS: The net AUC for essential amino acid (EAA) exposure was similar between the LP + Bar and HP conditions but greater in the HP condition compared with the LP condition. Peak leucinemia was higher in the LP + Bar condition compared with the HP, and both were greater than the LP condition. Net leucine exposure was similar between HP and LP + Bar, and both were greater than LP. Hunger was similarly reduced in LP + Bar and HP, and LP + Bar resulted in a greater hunger reduction than LP. Both LP + Bar and HP resulted in greater net fullness scores than LP. CONCLUSIONS: Consuming our bar formulation increased blood leucine availability and net exposure to EAAs to a similar degree as consuming a high-protein meal. High-protein at breakfast results in a greater net exposure to EAAs and leucine, which could support MPS in older persons. This study was registered at clinicaltrials.gov as NCT03712761.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it