Chronic Internal Exposure to Low Dose 137Cs Induces Positive Impact on the Stability of Atherosclerotic Plaques by Reducing Inflammation in ApoE-/- Mice
Bibliographic record
Abstract
After Chernobyl and Fukushima Daï Chi, two major nuclear accidents, large amounts of radionuclides were released in the environment, mostly caesium 137 (137Cs). Populations living in contaminated territories are chronically exposed to radionuclides by ingestion of contaminated food. However, questions still remain regarding the effects of low dose ionizing radiation exposure on the development and progression of cardiovascular diseases. We therefore investigated the effects of a chronic internal exposure to 137Cs on atherosclerosis in predisposed ApoE-/- mice. Mice were exposed daily to 0, 4, 20 or 100 kBq/l 137Cs in drinking water, corresponding to range of concentrations found in contaminated territories, for 6 or 9 months. We evaluated plaque size and phenotype, inflammatory profile, and oxidative stress status in different experimental groups. Results did not show any differences in atherosclerosis progression between mice exposed to 137Cs and unexposed controls. However, 137Cs exposed mice developed more stable plaques with decreased macrophage content, associated with reduced aortic expression of pro-inflammatory factors (CRP, TNFα, MCP-1, IFNγ) and adhesion molecules (ICAM-1, VCAM-1 and E-selectin). Lesions of mice exposed to 137Cs were also characterized by enhanced collagen and smooth muscle cell content, concurrent with reduced matrix metalloproteinase MMP8 and MMP13 expression. These results suggest that low dose chronic exposure of 137Cs in ApoE-/- mice enhances atherosclerotic lesion stability by inhibiting pro-inflammatory cytokine and MMP production, resulting in collagen-rich plaques with greater smooth muscle cell and less macrophage content.
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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 | 0.001 | 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) | 0.000 | 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".