Optimizing the measurement of mitochondrial protein synthesis in human skeletal muscle
Bibliographic record
Abstract
The measurement of mitochondrial protein synthesis after food ingestion, contractile activity, and/or disease is often used to provide insight into skeletal muscle adaptations that occur in the longer term. Studies have shown that protein ingestion stimulates mitochondrial protein synthesis in human skeletal muscle. Minor differences in the stimulation of mitochondrial protein synthesis occur after a single bout of resistance or endurance exercise. There appear to be no measurable differences in mitochondrial protein synthesis between critically ill patients and aged-matched controls. However, the mitochondrial protein synthetic response is reduced at a more advanced age. In this paper, we discuss the challenges involved in the measurement of human skeletal muscle mitochondrial protein synthesis rates based on stable isotope amino acid tracer methods. Practical guidelines are discussed to improve the reliability of the measurement of mitochondrial protein synthesis rates. The value of the measurement of mitochondrial protein synthesis after a single meal or exercise bout on the prediction of the longer term skeletal muscle mass and performance outcomes in both the healthy and disease populations requires more work, but we emphasize that the measurements need to be reliable to be of any value to the field.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".