Association Between Arsenic Exposure From Drinking Water and Plasma Levels of Cardiovascular Markers
Bibliographic record
Abstract
The authors conducted a cross-sectional study to assess the relation between arsenic exposure from drinking water and plasma levels of markers of systemic inflammation and endothelial dysfunction (matrix metalloproteinase-9, myeloperoxidase, plasminogen activator inhibitor-1, soluble E-selectin, soluble intercellular adhesion molecule-1 (ICAM-1), and soluble vascular adhesion molecule-1 (VCAM-1)) using baseline data from 668 participants (age, >30 years) in the Health Effects of Arsenic Longitudinal Study in Bangladesh (2007-2008). Both well water arsenic and urinary arsenic were positively associated with plasma levels of soluble VCAM-1. For every 1-unit increase in log-transformed well water arsenic (ln μg/L) and urinary arsenic (ln μg/g creatinine), plasma soluble VCAM-1 was 1.02 (95% confidence interval: 1.01, 1.03) and 1.04 (95% confidence interval: 1.01, 1.07) times greater, respectively. There was a significant interaction between arsenic exposure and higher body mass index, such that the increased levels of plasminogen activator inhibitor-1 and soluble VCAM-1 associated with arsenic exposure were stronger among people with higher body mass index. The findings indicate an effect of chronic arsenic exposure from drinking water on vascular inflammation and endothelial dysfunction that could be modified by body mass index and also suggest a potential mechanism underlying the association between arsenic exposure and cardiovascular disease.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.004 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".