A Lower Dose Threshold for the<i>In Vivo</i>Protective Adaptive Response to Radiation. Tumorigenesis in Chronically Exposed Normal and<i>Trp53</i>Heterozygous C57BL/6 Mice
Bibliographic record
Abstract
Low doses of ionizing radiation to cells and animals may induce adaptive responses that reduce the risk of cancer. However, there are upper dose thresholds above which these protective adaptive responses do not occur. We have now tested the hypothesis that there are similar lower dose thresholds that must be exceeded to induce protective effects in vivo. We examined the effects of low-dose/low-dose-rate fractionated exposures on cancer formation in Trp53 normal or cancer-prone Trp53 heterozygous female C57BL/6 mice. Beginning at 6 weeks of age, mice were exposed 5 days/week to single daily doses (0.33 mGy, 0.7 mGy/h) totaling 48, 97 or 146 mGy over 30, 60 or 90 weeks. The exposures for shorter times (up to 60 weeks) appeared to be below the level necessary to induce overall protective adaptive responses in Trp53 normal mice, and detrimental effects (shortened life span, increased frequency) evident for only specific tumor types (B- and T-cell lymphomas) were produced. Only when the exposures were continued for 90 weeks did the dose become sufficient to induce protective adaptive responses, balancing the detrimental effects for these specific cancers and reducing the risk level back to that of the unexposed animals. Detrimental effects were not seen for other tumor types, and a protective effect was seen for sarcomas after 60 weeks of exposure, which was then lost when the exposure continued for 90 weeks. As shown previously for the upper dose threshold for protection by low doses, the lower dose boundary between protection and harm was influenced by Trp53 functionality. Neither protection nor harm was observed in exposed Trp53 heterozygous mice, indicating that reduced Trp53 function raises the lower dose/ dose-rate threshold for both detrimental and protective tumorigenic effects.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".