Ionizing radiation‐induced long‐term expression of senescence markers in mice is independent of p53 and immune status
Bibliographic record
Abstract
Exposure to IR has been shown to induce the formation of senescence markers, a phenotype that coincides with lifelong delayed repair and regeneration of irradiated tissues. We hypothesized that IR-induced senescence markers could persist long-term in vivo, possibly contributing to the permanent reduction in tissue functionality. Here, we show that mouse tissues exposed to a sublethal dose of IR display persistent (up to 45 weeks, the maximum time analyzed) DNA damage foci and increased p16(INK4a) expression, two hallmarks of cellular senescence and aging. BrdU-labeling experiments revealed that IR-induced damaged cells are preferentially eliminated, at least partially, in a tissue-dependent manner. Unexpectedly, the accumulation of damaged cells was found to occur independent from the DNA damage response modulator p53, and from an intact immune system, as their levels were similar in wild-type and Rag2(-/-) gammaC(-/-) mice, the latter being deficient in T, B, and NK cells. Together, our results provide compelling evidence that exposure to IR induces long-term expression of senescence markers in vivo, an effect that may contribute to the reduced tissue functionality observed in cancer survivors.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".