Selenium and mercury in organisms: Interactions and mechanisms
Bibliographic record
Abstract
This paper reviews the growing literature dealing with the antagonistic effect of selenium (Se) compounds on the toxicity of mercury (Hg) compounds in higher animals and organisms present in the aquatic environment. It covers both laboratory and field studies and summarizes the possible mechanisms that explain the protective action of Se compounds on mercuric mercury (Hg2+) and methylmercury (CH3Hg+) toxicity. The review is subdivided according to the molecular form of Hg and the organisms in which the antagonism has been studied. Many authors suggest that the protective effect of selenite on the toxicity of Hg2+in mammals is due mainly to the in vivo formation of mercuric selenide (HgSe), a stable and biologically inert complex. The detection of HgSe has been confirmed in several studies in support of this mechanism. Possible mechanisms that may be involved in the antagonism between Se compounds and CH3Hg+in mammals and aquatic organisms are also presented. The possibility of adding Se compounds to contaminated lakes and reservoirs as a remediation technique to limit the bioaccumulation of Hg2+and CH3Hg+is critically discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".