Role of Apoptosis in Low-Dose Hyper-radiosensitivity
Bibliographic record
Abstract
Little is known about the mode of cell killing associated with low-dose hyper-radiosensitivity, the radiation response that describes the enhanced sensitivity of cells to small doses of ionizing radiation. Using a technique that measures the activation of caspase 3, we have established a relationship between apoptosis detected 24 h after low-dose radiation exposure and low-dose hyper-radiosensitivity in four mammalian cell lines (T98G, U373, MR4 and 3.7 cells) and two normal human lymphoblastoid cell lines. The existence of low-dose hyper-radiosensitivity in clonogenic survival experiments was found to be associated with an elevated level of apoptosis after low-dose exposures, corroborating earlier observations (Enns et al., Mol. Cancer Res. 2, 557-566, 2004). We also show that enriching populations of MR4 and V79 cells with G(1)-phase cells, to minimize the numbers of G(2)-phase cells, abolished the enhanced low-dose apoptosis. These cell-cycle enrichment experiments strengthen the reported association between low-dose hyper-sensitivity and the radioresponse of G(2)-phase cells. These data are consistent with our current hypothesis to explain low-dose hyper-radiosensitivity, namely that the enhanced sensitivity of cells to low doses of ionizing radiation reflects the failure of ATM-dependent repair processes to fully arrest the progression of damaged G(2)-phase cells harboring unrepaired DNA breaks entering mitosis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".