Exposure to Moderate Arsenic Concentrations Increases Atherosclerosis in ApoE−/− Mouse Model
Bibliographic record
Abstract
Arsenic is a widespread environmental contaminant to which millions of people are exposed worldwide. Exposure to arsenic is epidemiologically linked to increased cardiovascular disease, such as atherosclerosis. However, the effects of moderate concentrations of arsenic on atherosclerosis formation are unknown. Therefore, we utilized an in vivo ApoE(-/-) mouse model to assess the effects of chronic moderate exposure to arsenic on plaque formation and composition in order to facilitate mechanistic investigations. Mice exposed to 200 ppb arsenic developed atherosclerotic lesions, a lower exposure than previously reported. In addition, arsenic modified the plaque content, rendering them potentially less stable and consequently, potentially more dangerous. Moreover, we observed that the lower exposure concentration was more atherogenic than the higher concentration. Arsenic-enhanced lesions correlated with several proatherogenic molecular changes, including decreased liver X receptor (LXR) target gene expression and increased proinflammatory cytokines. Significantly, our observations suggest that chronic moderate arsenic exposure may be a greater cardiovascular health risk than previously anticipated.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".