Heatwave resilience of juvenile white sturgeon is associated with epigenetic and transcriptional alterations
Bibliographic record
Abstract
Abstract Heatwaves are increasing in frequency and severity, posing a significant threat to organisms globally. In aquatic environments, heatwaves are often associated with low environmental oxygen, which is a deadly combination for fish. However, surprisingly little is known about the capacity of fishes to withstand these interacting stressors. This issue is particularly critical for species of extreme conservation concern such as sturgeon. We assessed the tolerance of juvenile white sturgeon from an endangered population to heatwave exposure and investigated how this exposure affects tolerance to additional acute stressors. We measured whole-animal thermal and hypoxic performance and underlying epigenetic and transcriptional mechanisms. Sturgeon exposed to a simulated heatwave had increased thermal tolerance and exhibited complete compensation for the effects of acute hypoxia. These changes were associated with an increase in mRNA levels involved in thermal and hypoxic stress (hsp90a, hsp90b, hsp70 and hif1a) following these stressors. Global DNA methylation was sensitive to heatwave exposure and rapidly responded to acute thermal and hypoxia stress over the course of an hour. These data demonstrate that juvenile white sturgeon exhibit substantial resilience to heatwaves, associated with improved cross-tolerance to additional acute stressors and involving rapid responses in both epigenetic and transcriptional mechanisms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.012 |
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".