Differences in mitochondrial efficiency explain individual variation in growth performance
Bibliographic record
Abstract
The physiological causes of intraspecific differences in fitness components such as growth rate are currently a source of debate. It has been suggested that differences in energy metabolism may drive variation in growth, but it remains unclear whether covariation between growth rates and energy metabolism is: (i) a result of certain individuals acquiring and consequently allocating more resources to growth, and/or is (ii) determined by variation in the efficiency with which those resources are transformed into growth. Studies of individually housed animals under standardized nutritional conditions can help shed light on this debate. Here we quantify individual variation in metabolic efficiency in terms of the amount of adenosine triphosphate (ATP) generated per molecule of oxygen consumed by liver and muscle mitochondria and examine its effects, both on the rate of protein synthesis within these tissues and on the rate of whole-body growth of individually fed juvenile brown trout (Salmo trutta) receiving either a high or low food ration. As expected, fish on the high ration on average gained more in body mass and protein content than those maintained on the low ration. Yet, growth performance varied more than 10-fold among individuals on the same ration, resulting in some fish on low rations growing faster than others on the high ration. This variation in growth for a given ration was related to individual differences in mitochondrial properties: a high whole-body growth performance was associated with high mitochondrial efficiency of ATP production in the liver. Our results show for the first time, to our knowledge, that among-individual variation in the efficiency with which substrates are converted into ATP can help explain marked variation in growth performance, independent of food intake. This study highlights the existence of inter-individual differences in mitochondrial efficiency and its potential importance in explaining intraspecific variation in whole-animal performance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".