An epigenetic code for DNA damage repair pathways?
Bibliographic record
Abstract
Exposure of living cells to intracellular or external mutagens results in DNA damage. Accumulation of DNA damage can lead to serious consequences because of the deleterious mutation rate resulting in genomic instability, cellular senescence, and cell death. To counteract genotoxic stress, cells have developed several strategies to detect defects in DNA structure. The eukaryotic genomic DNA is packaged through histone and nonhistone proteins into a highly condensed structure termed chromatin. Therefore the cellular enzymatic machineries responsible for DNA replication, recombination, and repair must circumvent this natural barrier in order to gain access to the DNA. Several studies have demonstrated that histone/chromatin modifications such as acetylation, methylation, and phosphorylation play crucial roles in DNA repair processes. This review will summarize the recent data that suggest a regulatory role of the epigenetic code in DNA repair processes. We will mainly focus on different covalent reversible modifications of histones as an initial step in early response to DNA damage and subsequent DNA repair. Special focus on a potential epigenetic histone code for these processes will be given in the last section. We also discuss new technologies and strategies to elucidate the putative epigenetic code for each of the DNA repair processes discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".