DNA Hypomethylation May Contribute to Metabolic Recovery of Frozen Wood Frog Brains
Bibliographic record
Abstract
Transcriptional suppression is characteristic of extreme stress responses, speculated to preserve energetic resources in the maintenance of hypometabolism. In recent years, epigenetic regulation has become heavily implicated in stress adaptation of many animals, including supporting freeze tolerance of the wood frog (Rana sylvatica). However, nervous tissues are frequently lacking in these multi-tissue analyses which warrants investigation. The present study examines the role of DNA methylation, a core epigenetic mechanism, in the response of wood frog brains to freezing. We use immunoblot analysis to track the relative expression of DNA methyltransferases (DNMT), methyl-CpG-binding domain (MBD) proteins and ten-eleven-translocation (TET) demethylases across the freeze-thaw cycle in R. sylvatica brain, including selected comparisons to freeze-associated sub-stresses (anoxia and dehydration). Global methyltransferase activities and 5-hmC content were also assessed. The data show coordinated evidence for DNA hypomethylation in wood frog brains during freeze-recovery through the combined roles of depressed DNMT3A/3L expression driving lowered DNMT activity and increased TET2/3 levels leading to elevated 5-hmC genomic content (p < 0.05). Raised levels of DNMT1 during high dehydration were also noteworthy. The above suggest that alleviation of transcriptionally repressive 5-mC DNA methylation is a necessary component of the wood frog freeze-thaw cycle, potentially facilitating the resumption of a normoxic transcriptional state as frogs thaw and resume normal metabolic activities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".