Assessing Muscle Protein Synthesis Rates In Vivo in Humans: The Deuterated Water (2H2O) Method
Bibliographic record
Abstract
Skeletal muscle tissue is in a constant state of turnover, with muscle tissue protein synthesis and breakdown rates ranging between 1% and 2% across the day in vivo in humans. Muscle tissue remodeling is largely controlled by the up- and down-regulation of muscle tissue protein synthesis rates. Research studies generally apply stable isotope-labeled amino acids to assess muscle protein synthesis rates in vivo in humans. Following labeled amino acid administration in a laboratory setting, muscle tissue samples are collected over several hours to assess the incorporation rate of these labeled amino acids in muscle tissue protein. To allow quantification of bulk muscle protein synthesis rates over more prolonged periods, the use of deuterated water methodology has regained much interest. Ingestion of daily boluses of deuterium oxide results in 2 H enrichment of the body water pool. The available 2 H-atoms become incorporated into endogenously synthesized alanine primarily through transamination of pyruvate in the liver. With 2 H-alanine widely available to all tissues, it becomes incorporated into de novo synthesized tissue proteins. Assessing the increase in tissue protein-bound 2 H-alanine enrichment in muscle biopsy samples over time allows for the calculation of muscle protein synthesis rates over several days or even weeks. As the deuterated water method allows for the assessment of muscle tissue protein synthesis rates under free-living conditions in nonlaboratory settings, there is an increasing interest in its application. This manuscript describes the theoretical background of the deuterated water method and offers a comprehensive tutorial to correctly apply the method to determine bulk muscle protein synthesis rates in vivo in humans.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".