Exposure to Low to Moderate Doses of Ionizing Radiation Induces A Reduction of Pro-Inflammatory Ly6chigh Monocytes and a U-Curved Response of T Cells in APOE -/- Mice
Bibliographic record
Abstract
Low dose ionizing radiation (LDIR) is known to have a protective effect on atherosclerosis in rodent studies, but how it impacts different cells types involved in lesion formation remains incompletely understood. We investigated the immunomodulatory response of different doses and dose-rates of irradiation in ApoE -/- mice. Mice were exposed to external γ rays at very low (1.4 mGy.h -1 ) or low (50 mGy.h -1 ) dose-rates, with cumulative doses spanning 50 to 1000 mGy. Flow cytometry of circulating cells revealed a significant decrease in pro-inflammatory Ly6C Hi monocytes at all cumulative doses at low dose-rate, but more disparate effects at very low dose-rate with reductions in Ly6C Hi cells at doses of 50, 100 and 750 mGy only. In contrast, Ly6C Lo monocytes were not affected by LDIR. Similarly, proportions of CD4 + T cell subsets in the spleen did not differ between irradiated mice and non-irradiated controls, whether assessing CD25 + FoxP3 + regulatory or CD69 + activated lymphocytes. In the aorta, gene expression of cytokines such as IL-1 and TGF-ß and adhesion molecules such as E-Selectin, ICAM-1, and VCAM-1 were reduced at the intermediate dose of 200 mGy. These results suggest that LDIR may reduce atherosclerotic plaque formation by selectively reducing blood pro-inflammatory monocytes and by impairing adhesion molecule expression and inflammatory processes in the vessel wall. In contrast, splenic T lymphocytes were not affected by LDIR. Furthermore, some responses to irradiation were nonlinear; reductions in aortic gene expression were significant at intermediate doses, but not at either highest or lowest doses. This work furthers our understanding of the impact of LDIR with different dose-rates on immune system response in the context of atherosclerosis.
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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 | 0.000 |
| 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 | 0.001 | 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".