Methylmercury Targets Photoreceptor Outer Segments
Bibliographic record
Abstract
Human populations experience widespread low level exposure to organometallic methylmercury compounds through consumption of fish and other seafood. At higher levels, methylmercury compounds specifically target nervous systems, and among the many effects of their exposure are visual disturbances, including blindness, which previously were thought to be due to methylmercury-induced damage to the visual cortex. Here, we employ high-resolution X-ray fluorescence imaging using beam sizes of 500 × 500 and 250 × 250 nm(2) to investigate the localization of mercury at unprecedented resolution in sections of zebrafish larvae ( Danio rerio ), a model developing vertebrate. We demonstrate that methylmercury specifically targets the outer segments of photoreceptor cells in both the retina and pineal gland. Methylmercury distribution in both tissues was correlated with that of sulfur, which, together with methylmercury's affinity for thiolate donors, suggests involvement of protein cysteine residues in methylmercury binding. In contrast, in the lens, the mercury distribution was different from that of sulfur, with methylmercury specifically accumulating in the secondary fiber cells immediately underlying the lens epithelial cells rather than in the lens epithelial cells themselves. Since methylmercury targets two main eye tissues (lens and photoreceptors) that are directly involved in visual perception, it now seems likely that the visual disruption associated with methylmercury exposure in higher animals including humans may arise from direct damage to photoreceptors, in addition to injury of the visual cortex.
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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) | 0.000 | 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) | 0.001 | 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 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".