Induction of apoptosis by high linear energy transfer radiation: role of p53
Bibliographic record
Abstract
The involvement of the tumor suppressor p53 gene in the sensitivity of many cell types towards low linear energy transfer (LET) radiation is now well established. However, little information is available on the relationship between p53 status of tumor cells and their ability to undergo apoptosis following exposure to high-LET radiation. Here we present the results of experiments carried out with the human lymphoblastoid cell line TK6 and its p53 knock-out counterpart NH32. Cells were irradiated at doses ranging from 0.25 to 8 Gy with fast neutrons (65 MeV), carbon ions (95 MeV/nucleon), and X rays (15 MV). For both cell lines, the occurrence of apoptosis, determined by the quantification of hypodiploid particles as well as the activation of several caspases, was compared with their sensitivity towards high-LET radiation. Results indicate that p53 is involved in the response of TK6 cells to fast neutrons and carbon ions, as measured by cell proliferation and occurrence of apoptosis. However, p53-deficient cells are still able to undergo apoptosis following irradiation. This suggests that heavy ions and fast neutrons induce cellular damage that is not under the control of p53. The involvement of executioner caspases in high-LET radiation induced apoptosis was also evaluated by use of specific inhibitors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.004 | 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 teacher head, 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".