Fractionated, Low-Dose-Rate Ionizing Radiation Exposure and Chronic Ulcerative Dermatitis in Normal and<i>Trp53</i>Heterozygous C57BL/6 Mice
Bibliographic record
Abstract
The influence of low-dose-rate chronic radiation exposure and adaptive responses on non-cancer diseases is largely unknown. We examined the effect of low-dose/low-dose-rate fractionated or single exposures on spontaneous chronic ulcerative dermatitis in Trp53 normal or heterozygous female C57BL/6 mice. From 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, and other Trp53+/- mice were exposed to a single dose of 10 mGy (0.5 mGy/min) at 20 weeks of age. The 90-week exposure produced an adaptive response, decreasing both disease frequency and severity in Trp53+/+ mice and extending the life span of older animals euthanized due to severe disease. The 30- or 60-week exposures had no significant protective or detrimental effect. In contrast, the chronic, fractionated exposure for 30 or 60 weeks significantly increased the frequency and severity of the disease in older Trp53+/- mice, significantly decreasing the life span of the animals required to be euthanized for disease. Similarly, the single 10-mGy exposure also increased disease frequency in older animals. However, the chronic, fractionated exposure for 90 weeks prevented these detrimental effects, with disease frequency and severity not different from unexposed controls. We conclude that very low-dose fractionated exposures can induce a protective adaptive response in both Trp53 normal and heterozygous mice, but that a lower threshold level of exposure, similar in both cases, must first be passed. In mice with reduced Trp53 functionality, doses below the threshold can produce detrimental 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".