Contribution of reversible histone acetylation to freeze tolerance and recovery in wood frog kidneys
Bibliographic record
Abstract
The wood frog (Rana sylvatica) possesses remarkable adaptation mechanisms that ensures it survival in extreme environmental conditions, including enduring whole body freezing. The present study investigates the epigenetic mechanisms, specifically histone lysine acetylation and deacetylation, which are critical for regulating gene expression and conserving energy, underlying the wood frog's ability to endure whole-body freezing. We investigated the expression patterns of lysine acetyltransferases (KATs) and lysine deacetylases (HDACs) in wood frog kidney over the freeze-thaw cycle. Our results reveal a significant downregulation of KATs in kidneys of frozen frogs, with specific KATs showing considerable reductions. This suggests that histone acetylation may play a vital role in suppressing gene expression and conserving energy during freezing. Furthermore, histone acetylation marks, including H2AK5ac, H2BK5ac, H3K9ac, H3K23ac, H3K27ac, and H3K56ac, showed repression under frozen and thawed conditions, indicating a role in silencing specific genes. HDACs exhibited dynamic regulation, with HDAC3 and HDAC11 showing significant repression in frozen frog kidneys, while HDAC5, p-HDAC4, and p-HDAC8 were downregulated during the recovery phase, suggesting their involvement in the thawing process. This research provides crucial insights into the epigenetic control of freeze tolerance in wood frog kidneys and offers a foundation for further exploration of epigenetic modifications that mediate the wood frog's remarkable adaptations for freezing survival.
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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 | 0.000 | 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".