Mitochondrial DNA methyltransferases and their regulation under freezing and dehydration stresses in the freeze-tolerant wood frog, <i>Rana sylvatica</i>
Bibliographic record
Abstract
Wood frogs are a few vertebrate species that can survive whole-body freezing. Multiple adaptations support this, including cryoprotectant production (glucose), metabolic rate depression, and selective changes in gene and protein expression to activate pro-survival pathways. The role of DNA methylation machinery (DNA methyltransferases, DNMTs) in regulating nuclear gene expression to support freezing survival has already been established. However, a comparable role for DNMTs in the mitochondria has not been explored in wood frogs. We examined the mitochondrial protein levels of DNMT-1, DNMT-3A, DNMT-3B, and DNMT-3L as well as mitochondrial DNMT activity in the liver and heart to assess the involvement of DNMT in the survival of freezing and dehydration stresses (cellular dehydration being a component of freezing). Our results showed stress- and tissue-specific responses to mitochondrial DNMT-1 in the liver and heart, respectively. During 24 h of freezing and whole-body dehydration, we observed an overall downregulation of mitochondrial DNMT-1, a major protein involved in maintaining methylation levels related to its role in the selective transcription of mitochondrial genes as well as antioxidant response. Tissue-specific responses of protein levels of DNMT-3A, DNMT-3B, DNMT-3L, and DNMT activity in the liver suggested a preference for a higher methylation state in the liver under both freezing and dehydration stress, but not in the heart.
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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".