Application of the COSIAM method for muscle protein turnover and skeletal muscle mass in young females: A comparison of methods for body composition assessment
Bibliographic record
Abstract
Evaluating rates of myofibrillar protein synthesis (MyoPS) and breakdown (MyoPB) is essential for understanding muscle protein turnover, which underpins changes in skeletal muscle mass (SMM). For the first time, we applied the Combined Oral Stable Isotope Assessment of Muscle (COSIAM) method in a group of young, healthy females. This protocol allows simultaneous measurement of MyoPS, MyoPB, and SMM using deuterium oxide, D 3 -3-methylhistidine, and methyl-D 3 -creatine (D3-Cr), respectively. Additionally, we evaluated the agreement between D3-Cr-derived SMM and several SMM proxies, to determine the bias of each method relative to D3-Cr-derived SMM. Using the three-day COSIAM protocol, we assessed MyoPS, MyoPB and SMM in a cohort of twenty-one healthy, females (age: 22 ± 2 years, BMI: 24.7 ± 3.5 kg/m 2 ). Bioelectrical impedance (BIA), DXA and BodPod were used to estimate SMM, lean mass (LM), and fat-free mass (FFM), respectively. BIA, DXA, and ultrasound (US) were also used to assess appendicular lean mass (ALM), while US was additionally used to measure vastus lateralis cross-sectional area. Rates of MyoPS (1.97 ± 0.29 %/d) and MyoPB (rate constant [k] of 0.045) aligned with previous literature. DXA-derived LM, BIA-derived SMM, and BodPod-derived FFM overestimated D3-Cr-derived SMM by 20.1 ± 3.6 kg, 4.0 ± 2.2 kg, and 22.8 ± 4.1 kg, respectively. Conversely, DXA, BIA, and US-derived ALM uniformly underestimated D3-Cr-derived SMM by approximately 2.50 kg. Our findings suggest that the COSIAM method is a viable approach for assessing muscle protein turnover in young, healthy females, and provides reference values for future research. Additionally, this study reveals the degree to which commonly used proxy measures of SMM, overestimate or underestimate D3-Cr-derived SMM. These insights support the application of COSIAM in future female-focused research and advance our understanding of biases in body composition assessments for young females.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".