Cells deficient in oxidative DNA damage repair genes Myh and Ogg1 are sensitive to oxidants with increased G 2 /M arrest and multinucleation
Bibliographic record
Abstract
Oxidative stress generated from endogenous and exogenous sources causes oxidative DNA damage. The most frequent mutagenic base lesion 7,8-dihydro-8-oxoguanine and the resulting mismatched adenine are removed by OGG1 and MYH in mammals. Deficiencies in human MYH or mouse MYH and OGG1 result in tumor predisposition but the underlying molecular mechanism is not fully understood. To facilitate the study of the roles of MYH and OGG1 in the protection against oxidative stress, we generated mouse embryonic fibroblast cell lines deficient in these genes. Myh and Ogg1 double knockout cells were more sensitive than wild type to oxidants (hydrogen peroxide and t-butyl hydroperoxide), but not to cis-platinum or gamma-irradiations. The low dosage oxidative stress resulted in more reduction of S phase and increase of G(2)/M phase in Myh(-/-)Ogg1(-/-) cells than in wild-type cells, but a similar level of cell death in both cells. The oxidants also induced more multinucleated cells in Myh(-/-)Ogg1(-/-) cells than in wild-type, accompanied by centrosome amplification and multipolar spindle formation. Thus, under oxidative stress, Myh and Ogg1 are likely required for normal cell-cycle progression and nuclear division, suggesting multiple roles of Myh and Ogg1 in the maintenance of genome stability and tumor prevention.
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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) | 0.001 | 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".