The Heterochromatic Barrier to DNA Double Strand Break Repair: How to Get the Entry Visa
Bibliographic record
Abstract
Over recent decades, a deep understanding of pathways that repair DNA double strand breaks (DSB) has been gained from biochemical, structural, biophysical and cellular studies. DNA non-homologous end-joining (NHEJ) and homologous recombination (HR) represent the two major DSB repair pathways, and both processes are now well understood. Recent work has demonstrated that the chromatin environment at a DSB significantly impacts upon DSB repair and that, moreover, dramatic modifications arise in the chromatin surrounding a DSB. Chromatin is broadly divided into open, transcriptionally active, euchromatin (EC) and highly compacted, transcriptionally inert, heterochromatin (HC), although these represent extremes of a spectrum. The HC superstructure restricts both DSB repair and damage response signaling. Moreover, DSBs within HC (HC-DSBs) are rapidly relocalized to the EC-HC interface. The damage response protein kinase, ataxia telangiectasia mutated (ATM), is required for HC-DSB repair but is dispensable for the relocalization of HC-DSBs. It has been proposed that ATM signaling enhances HC relaxation in the DSB vicinity and that this is a prerequisite for HC-DSB repair. Hence, ATM is essential for repair of HC-DSBs. Here, we discuss how HC impacts upon the response to DSBs and how ATM overcomes the barrier that HC poses to repair.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".