Application of <sup>2</sup> H <sub>2</sub> O to quantify red blood cell protein synthesis rates in young trained and untrained males and females
Bibliographic record
Abstract
ABSTRACT Aim Compare the fractional synthetic rate (FSR) of hemoglobin in trained and untrained humans (Hb FSR). Methods We employed deuterated water ( 2 H 2 O) to measure Hb FSR in young males (n=10) and females (n=10) who were aerobically trained (n=5 per sex) and untrained (n=5 per sex). Overall, participants had a mean of 49.8 [SD: 10.9] mL/kg/min, hemoglobin mass of 775 [180] g, and red blood cell volume of 2370 [550] mL. After an initial loading dose, participants ingested 2 H 2 O daily for 28 days to maintain a stable 2 H body water enrichment (∼0.9 atom percent deuterium (APD)), as measured in saliva samples collected every 2-3 days. 2 H-enriched alanine was measured in RBC protein using gas chromatography combustion isotope ratio mass spectrometry. Results The increase in APD for Hb protein was nonlinear for the first two weeks, but stabilized from day 14 to day 28, with mean APD reaching 0.033 [0.005] % on day 28. Hb FSR calculated over this 2-week period was 0.84 [0.15] %/day, which equated to an Hb absolute synthetic rate of 6.5 [2.2] g/day and a lifespan of 126 [30] days. Hb FSR was not different trained (0.83 [0.19] %/day) and untrained (0.86 [0.24] %/day, P=0.81) individuals or between males (0.80 [0.25] %/day) and females (0.88 [0.17] %/day), P=0.24). Conclusion Habitual endurance training does not appear to affect Hb FSR, but the use of 2 H 2 O to measure Hb FSR in humans has potential applications to many experimental and clinical scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".