Chronic Arsenic Exposure and Oxidative Stress: <i>OGG1</i> Expression and Arsenic Exposure, Nail Selenium, and Skin Hyperkeratosis in Inner Mongolia
Bibliographic record
Abstract
Arsenic, a human carcinogen, is known to induce oxidative damage to DNA. In this study we investigated oxidative stress and As exposure by determining gene expression of OGG1, which codes for an enzyme, 8-oxoguanine DNA glycosylase, involved in removing 8-oxoguanine in As-exposed individuals. Bayingnormen (Ba Men) residents in Inner Mongolia are chronically exposed to As via drinking water. Water, toenail, and blood samples were collected from 299 Ba Men residents exposed to 0.34-826 microg/L As. RNA was isolated from blood, and mRNA levels of OGG1 were determined using real-time polymerase chain reaction. OGG1 expression levels were linked to As concentrations in drinking water and nails, selenium concentrations in nails, and skin hyperkeratosis. OGG1 expression was strongly associated with water As concentrations (p < 0.0001). Addition of the quadratic term significantly improved the fit compared with the linear model (p = 0.05) . The maximal OGG1 response was at the water As concentration of 149 microg/L. OGG1 expression was also significantly associated with toenail As concentrations (p = 0.015) but inversely associated with nail Se concentrations (p = 0.0095) . We found no significant differences in the As-induced OGG1 expression due to sex, smoking, or age even though the oldest group showed the strongest OGG1 response (p = 0.0001) . OGG1 expression showed a dose-dependent increased risk of skin hyperkeratosis in males (trend analysis, p = 0.02) , but the trend was not statistically significant in females. The results from this study provide a linkage between oxidative stress and As exposure in humans. OGG1 expression may be useful as a biomarker for assessing oxidative stress from As exposure.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".