Ionizing Radiation Induces Delayed Hyperrecombination in Mammalian Cells
Bibliographic record
Abstract
Exposure to ionizing radiation can result in delayed effects that can be detected in the progeny of an irradiated cell multiple generations after the initial exposure. These effects are described under the rubric of radiation-induced genomic instability and encompass multiple genotoxic endpoints. We have developed a green fluorescence protein (GFP)-based assay and demonstrated that ionizing radiation induces genomic instability in human RKO-derived cells and in human hamster hybrid GM10115 cells, manifested as increased homologous recombination (HR). Up to 10% of cells cultured after irradiation produce mixed GFP(+/-) colonies indicative of delayed HR or, in the case of RKO-derived cells, mutation and deletion. Consistent with prior studies, delayed chromosomal instability correlated with delayed reproductive cell death. In contrast, cells displaying delayed HR showed no evidence of delayed reproductive cell death, and there was no correlation between delayed chromosomal instability and delayed HR, indicating that these forms of genome instability arise by distinct mechanisms. Because delayed hyperrecombination can be induced at doses of ionizing radiation that are not associated with significantly reduced cell viability, these data may have important implications for assessment of radiation risk and understanding the mechanisms of radiation carcinogenesis.
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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) | 0.000 | 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) | 0.002 | 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".