Repair of DNA–polypeptide crosslinks by human excision nuclease
Bibliographic record
Abstract
DNA-protein crosslinks are relatively common DNA lesions that form during the physiological processing of DNA by replication and recombination proteins, by side reactions of base excision repair enzymes, and by cellular exposure to bifunctional DNA-damaging agents such as platinum compounds. The mechanism by which pathological DNA-protein crosslinks are repaired in humans is not known. In this study, we investigated the mechanism of recognition and repair of protein-DNA and oligopeptide-DNA crosslinks by the human excision nuclease. Under our assay conditions, the human nucleotide excision repair system did not remove a 16-kDa protein crosslinked to DNA at a detectable level. However, 4- and 12-aa-long oligopeptides crosslinked to the DNA backbone were recognized by some of the damage recognition factors of the human excision nuclease with moderate selectivity and were excised from DNA at relatively efficient rates. Our data suggest that, if coupled with proteolytic degradation of the crosslinked protein, the human excision nuclease may be the major enzyme system for eliminating protein-DNA crosslinks from the genome.
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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 | 0.000 |
| 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 | 0.001 |
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".