Data from: Maladaptive phenotypic plasticity in cardiac muscle growth is suppressed in high-altitude deer mice
Bibliographic record
Abstract
How often phenotypic plasticity acts to promote or inhibit adaptive evolution is an ongoing debate among biologists. Recent work suggests that adaptive phenotypic plasticity promotes evolutionary divergence, though several studies have also suggested that maladaptive plasticity can potentiate adaptation. The role of phenotypic plasticity, adaptive or maladaptive, in evolutionary divergence remains controversial. We examined the role of plasticity in evolutionary divergence between two species of Peromyscus mice that differ in native elevations. We used cardiac mass as a model phenotype, since ancestral hypoxia-induced responses of the heart may be both adaptive and maladaptive at high-altitude. While left ventricle growth should enhance oxygen delivery to tissues, hypertrophy of the right ventricle can lead to heart failure and death. We compared left- and right-ventricle plasticity in response to hypoxia between captive-bred P. leucopus (representing the ancestral lowland condition) and P. maniculatus from high-altitude. We found that maladaptive ancestral plasticity in right ventricle hypertrophy is reduced in high-altitude deer mice. Analysis of the heart transcriptome suggests that changes in expression of inflammatory signaling genes, particularly interferon regulatory factors, contribute to the suppression of right ventricle hypertrophy. We found weak evidence that adaptive plasticity of left ventricle mass contributes to evolution. Our results suggest that selection to suppress ancestral maladaptive plasticity plays a role in adaptation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.025 |
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".