Sodium nitrate co-ingestion with protein does not augment postprandial muscle protein synthesis rates in older, type 2 diabetes patients
Bibliographic record
Abstract
The age-related anabolic resistance to protein ingestion is suggested to be associated with impairments in insulin-mediated capillary recruitment and postprandial muscle tissue perfusion. The present study investigated whether dietary nitrate co-ingestion with protein improves muscle protein synthesis in older, type 2 diabetes patients. Twenty-four men with type 2 diabetes (72 ± 1 yr, 26.7 ± 1.4 m/kg(2) body mass index, 7.3 ± 0.4% HbA1C) received a primed continuous infusion of l-[ring-(2)H5]phenylalanine and l-[1-(13)C]leucine and ingested 20 g of intrinsically l-[1-(13)C]phenylalanine- and l-[1-(13)C]leucine-labeled protein with (PRONO3) or without (PRO) sodium nitrate (0.15 mmol/kg). Blood and muscle samples were collected to assess protein digestion and absorption kinetics and postprandial muscle protein synthesis rates. Upon protein ingestion, exogenous phenylalanine appearance rates increased in both groups (P < 0.001), resulting in 55 ± 2% and 53 ± 2% of dietary protein-derived amino acids becoming available in the circulation over the 5h postprandial period in the PRO and PRONO3 groups, respectively. Postprandial myofibrillar protein synthesis rates based on l-[ring-(2)H5]phenylalanine did not differ between groups (0.025 ± 0.004 and 0.021 ± 0.007%/h over 0-2 h and 0.032 ± 0.004 and 0.030 ± 0.003%/h over 2-5 h in PRO and PRONO3, respectively, P = 0.7). No differences in incorporation of dietary protein-derived l-[1-(13)C]phenylalanine into de novo myofibrillar protein were observed at 5 h (0.016 ± 0.002 and 0.014 ± 0.002 mole percent excess in PRO and PRONO3, respectively, P = 0.8). Dietary nitrate co-ingestion with protein does not modulate protein digestion and absorption kinetics, nor does it further increase postprandial muscle protein synthesis rates or the incorporation of dietary protein-derived amino acids into de novo myofibrillar protein in older, type 2 diabetes patients.
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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) | 0.000 | 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 | 0.000 | 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".