Low-Dose Radiation Exposure and Atherosclerosis in<i>ApoE</i><sup>−/−</sup>Mice
Bibliographic record
Abstract
The hypothesis that single low-dose exposures (0.025-0.5 Gy) to low-LET radiation given at either high (about 150 mGy/min) or low (1 mGy/min) dose rate would promote aortic atherosclerosis was tested in female C57BL/6J mice genetically predisposed to this disease (ApoE⁻/⁻). Mice were exposed either at an early stage of disease (2 months of age) and examined 3 or 6 months later or at a late stage of disease (8 months of age) and examined 2 or 4 months later. Changes in aortic lesion frequency, size and severity as well as total serum cholesterol levels and the uptake of lesion lipids by lesion-associated macrophages were assessed. Statistically significant changes in each of these measures were observed, depending on dose, dose rate and disease stage. In all cases, the results were distinctly non-linear with dose, with maximum effects tending to occur at 25 or 50 mGy. In general, low doses given at low dose rate during either early- or late-stage disease were protective, slowing the progression of the disease by one or more of these measures. Most effects appeared and persisted for months after the single exposures, but some were ultimately transitory. In contrast to exposure at low dose rate, high-dose-rate exposure during early-stage disease produced both protective and detrimental effects, suggesting that low doses may influence this disease by more than one mechanism and that dose rate is an important parameter. These results contrast with the known, generally detrimental effects of high doses on the progression of this disease in the same mice and in humans, suggesting that a linear extrapolation of the known increased risk from high doses to low doses is not appropriate.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".