Arsenic bioaccumulation and biotransformation in aquatic organisms
Bibliographic record
Abstract
Arsenic exists universally in freshwater and marine environments, threatening the survival of aquatic organisms and human health. To elucidate arsenic bioaccumulation and biotransformation processes in aquatic organisms, this review evaluates the dissolved uptake, dietary assimilation, biotransformation, and elimination of arsenic in aquatic organisms and discusses the major factors influencing these processes. Environmental factors such as phosphorus concentration, pH, salinity, and dissolved organic matter influence arsenic absorption from aquatic systems, whereas ingestion rate, gut passage time, and gut environment affect the assimilation of arsenic from foodstuffs. Arsenic bioaccumulation and biotransformation mechanisms differ depending on specific arsenic species and the involved aquatic organism. Although some enzymes engaged in arsenic biotransformation are known, deciphering the complicated synthesis and degradation pathway of arsenobetaine remains a challenge. The elimination of arsenic involves many processes, such as fecal excretion, renal elimination, molting, and reproductive processes. This review facilitates our understanding of the environmental behavior and biological fate of arsenic and contributes to regulation of the environmental risk posed by arsenic pollution.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".