Distribution of selenium in zebrafish larvae after exposure to organic and inorganic selenium forms
Bibliographic record
Abstract
Selenium is an essential micronutrient for many organisms, and in vertebrates has a variety of roles associated with protection from reactive oxygen species. Over the past two decades there have been conflicting reports upon human health benefits and detriments arising from consumption of selenium dietary supplements. Thus, early studies report a decrease in the incidence of certain types of cancer, whereas subsequent studies did not observe any anti-cancer effect, and adverse effects such as increased risks for type 2 diabetes have been reported. A possible contributing factor may be that different chemical forms of selenium were used in different studies. Using larval stage zebrafish (Danio rerio) as a model organism, we report a comparison of the toxicities and tissue selenium distributions of four different chemical forms of selenium. We find that the organic forms of selenium tested (Se-methyl-l-selenocysteine and l-selenomethionine) show considerably more toxicity than inorganic forms (selenite and selenate), and that this appears to be correlated with the level of bioaccumulation. Despite differences in concentrations, the tissue specific pattern of selenium accumulation was similar for the chemical forms tested; selenium was found to be highly concentrated in pigment (melanin) containing tissues especially for the organic selenium treatments, with lower concentrations in eye lens, yolk sac and heart. These results suggest that pigmented tissues might serve as a storage reservoir for selenium.
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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 | 0.001 |
| 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".