Looking into a whale’s heart: investigating a genetic basis for cardiomyopathy in a non-model species
Bibliographic record
Abstract
Understanding the pathogenesis of complex diseases can benefit from multi-species comparative studies. Yet these studies rarely include natural populations of non-model species. Here, we focused on the cause of a heart muscle disease, cardiomyopathy (CM), affecting multiple mammalian species including humans, cats, dogs, and certain species of whales. Mutations in genes coding for sarcomeric proteins have been identified as a leading cause for CM in humans, and some were also revealed to be responsible for CM in cats. We investigated whether similar mutations could be detected in the deep-diving pygmy sperm whale (Kogia breviceps), which is one of two cetacean species known to display CM. We sequenced portions of two candidate genes (MYH7: 3153 bp and MYBPC3: 3019 bp) in 55 whales including affected and unaffected individuals. Mutation screening revealed six nonsynonymous substitutions that were predicted to have an effect on protein function. However, the etiology of CM is likely complex and probably multi-factorial as three of these mutations were observed in unaffected individuals from our control group. This incomplete penetrance could be partly age-related and could also be due to the influence of environmental factors on the development of CM, as seen in humans.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".