Growth versus metabolic tissue replacement in mouse tissues determined by stable carbon and nitrogen isotope analysis
Bibliographic record
Abstract
Stable-isotope signatures in animal tissues presumably reflect the local food web. However, that assumption may be complicated by differential nutrient routing, fractionation, and the possibility that large organisms are not in isotopic equilibrium with seasonally available food sources. Additionally, the rate at which organisms incorporate the isotopic signature of a food is largely unknown. In this study we assessed the rate of carbon- and nitrogen-isotope turnover in liver, muscle, and blood in mice (Mus musculus L., 1758) following a diet change. We report the proportion of tissue turnover caused by growth versus that caused by metabolic tissue replacement. Growth accounted for approximately 10% of observed tissue turnover in adult mice. Blood carbon had the shortest half-life (16.9 days), followed by muscle carbon (23.9 days). Liver carbon turnover, which was slower than blood and muscle carbon turnovers, was not as well described by the exponential decay equations. All tissues primarily reflect the protein carbon signature rather than the carbohydrate carbon signature. The nitrogen signature in all tissues was enriched by 3‰–5‰ over their diets' nitrogen signature, depending on tissue type, and the isotopic turnover rates of nitrogen in blood and muscle were comparable with those observed for carbon.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".