Selenium and Mercury in the Brazilian Amazon: Opposing Influences on Age-Related Cataracts
Bibliographic record
Abstract
BACKGROUND: Age-related cataracts (ARCs) are an important cause of blindness in developing countries. Although antioxidants may be part of the body's defense to prevent ARC, environmental contaminants may contribute to cataractogenesis. In fish-eating populations of the lower Tapajós region, elevated exposure to mercury (Hg) has been reported, and blood levels of selenium (Se) range from normal to very high (> 1,000 microg/L). OBJECTIVES: We examined ARCs in relation to these elements among adults (> or = 40 years of age) from 12 riverside communities. METHODS: Participants (n = 211) provided blood samples and underwent an extensive ocular examination. Inductively coupled plasma mass spectrometry was used to assess Hg and Se in blood and plasma. RESULTS: One-third (n = 69; 32.7%) of the participants had ARC. Lower plasma Se (P-Se; < 25th percentile, 110 microg/L) and higher blood Hg (B-Hg; > or = 25th percentile, 25 microg/L) were associated with a higher prevalence odds ratio (POR) of ARC [adjusted POR (95% confidence interval), 2.69 (1.11-6.56) and 4.45 (1.43-13.83), respectively]. Among participants with high P-Se, we observed a positive but nonsignificant association with high B-Hg exposure, whereas among those with low B-Hg, we observed no association for P-Se. However, compared with the optimum situation (high P-Se, low B-Hg), the POR for those with low P-Se and high B-Hg was 16.4 (3.0-87.9). This finding suggests a synergistic effect. CONCLUSION: Our results suggest that persons in this population with elevated Hg, the cataractogenic effects of Hg may be offset by Se. Because of the relatively small sample size and possible confounding by other dietary nutrients, additional studies with sufficient power to assess multiple nutrient and toxic interactions are required to confirm these findings.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".