Dysregulated Handling of Dietary Protein and Muscle Protein Synthesis After Mixed-Meal Ingestion in Maintenance Hemodialysis Patients
Bibliographic record
Abstract
Introduction Skeletal muscle loss is common in patients with renal failure who receive maintenance hemodialysis (MHD) therapy. Regular ingestion of protein-rich meals are recommended to help offset muscle protein loss in MHD patients, but little is known about the anabolic potential of this strategy. Methods Eight MHD patients (age: 56 ± 5 years; body mass index [BMI]: 32 ± 2 kg/m 2 ) and 8 nonuremic control subjects (age: 50 ± 2 years: BMI: 31 ± 1 kg/m 2 ) received primed continuous L-[ ring - 2 H 5 ]phenylalanine and L-[1- 13 C]leucine infusions with blood and muscle biopsy sampling on a nondialysis day. Participants consumed a mixed meal (546 kcal; 20-g protein, 59-g carbohydrates, 26-g fat) with protein provided as L-[5,5,5- 2 H 3 ]leucine-labeled eggs. Results Circulating dietary amino acid availability was reduced in MHD patients (41 ± 5%) versus control subjects (61 ± 4%; P = 0.03). Basal muscle caspase-3 protein content was elevated ( P = 0.03) and large neutral amino acid transporter 1 (LAT1) protein content was reduced ( P = 0.02) in MHD patients versus control subjects. Basal muscle protein synthesis (MPS) was ∼2-fold higher in MHD patients (0.030 ± 0.005%/h) versus control subjects (0.014 ± 0.003%/h) ( P = 0.01). Meal ingestion failed to increase MPS in MHD patients (absolute change from basal: 0.0003 ± 0.007%/h), but stimulated MPS in control subjects (0.009 ± 0.002%/h; P = 0.004). Conclusions MHD patients demonstrated muscle anabolic resistance to meal ingestion. This blunted postprandial MPS response in MHD patients might be related to high basal MPS, which results in a stimulatory ceiling effect and/or reduced plasma dietary amino acid availability after mixed-meal ingestion.
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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) | 0.000 | 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) | 0.001 | 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".