Chemical Form Matters: Differential Accumulation of Mercury Following Inorganic and Organic Mercury Exposures in Zebrafish Larvae
Bibliographic record
Abstract
Mercury, one of the most toxic elements, exists in various chemical forms each with different toxicities and health implications. Some methylated mercury forms, one of which exists in fish and other seafood products, pose a potential threat, especially during embryonic and early postnatal development. Despite global concerns, little is known about the mechanisms underlying transport and toxicity of different mercury species. To investigate the impact of different mercury chemical forms on vertebrate development, we have successfully combined the zebrafish, a well-established developmental biology model system, with synchrotron-based X-ray fluorescence imaging. Our work revealed substantial differences in tissue-specific accumulation patterns of mercury in zebrafish larvae exposed to four different mercury formulations in water. Methylmercury species not only resulted in overall higher mercury burdens but also targeted different cells and tissues than their inorganic counterparts, thus revealing a significant role of speciation in cellular and molecular targeting and mercury sequestration. For methylmercury species, the highest mercury concentrations were in the eye lens epithelial cells, independent of the formulation ligand (chloride versusl-cysteine). For inorganic mercury species, in absence of l-cysteine, the olfactory epithelium and kidney accumulated the greatest amounts of mercury. However, with l-cysteine present in the treatment solution, mercuric bis-l-cysteineate species dominated the treatment, significantly decreasing uptake. Our results clearly demonstrate that the common differentiation between organic and inorganic mercury is not sufficient to determine the toxicity of various mercury species.
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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".