Consistent changes in muscle metabolism underlie dive performance across multiple lineages of diving ducks
Bibliographic record
Abstract
Diving animals must sustain high activity with limited O 2 stores to successfully capture prey. Studies suggest that increasing body O 2 stores supports breath-hold diving, but less is known about metabolic specializations that underlie underwater locomotion. We measured maximal activities of 10 key enzymes in locomotory muscles (gastrocnemius and pectoralis) to identify biochemical changes associated with diving in pathways of oxidative and substrate-level phosphorylation and compared them across three groups of ducks—the longest diving sea ducks (eight spp.), the mid-tier diving pochards (three spp.) and the non-diving dabblers (five spp.). Relative to dabblers, both diving groups had increased activities of succinate dehydrogenase and cytochrome c oxidase, and sea ducks further showed increases in citrate synthase (CS) and hydroxyacyl-CoA dehydrogenase (HOAD). Both diving groups had relative decreases in capacity for anaerobic metabolism (lower ratio of lactate dehydrogenase to CS), with sea ducks also showing a greater capacity for oxidative phosphorylation and lipid oxidation (lower ratio of pyruvate kinase to CS, higher ratio of HOAD to hexokinase). These data suggest that the locomotory muscles of diving ducks are specialized for sustaining high rates of aerobic metabolism, emphasizing the importance of body O 2 stores for dive performance in these species.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".