Arsenobetaine formation in plankton: a review of studies at the base of the aquatic food chain
Bibliographic record
Abstract
Arsenobetaine is one of the major organoarsenic compounds found in aquatic organisms, including seafood and fish meant for human consumption. It has been widely studied over the last 50 years because of its non-toxic properties, and its origin is postulated to be at bottom of the aquatic food chains. The present review focuses on arsenobetaine formation in marine and freshwater plankton, comparing the arsenic compounds found in the different plankton organisms, and the methods used to assess arsenic speciation. The main findings indicate that in the marine environment, phytoplankton and micro-algae contain arsenosugars, with the first traces of arsenobetaine appearing in herbivorous zooplankton, and becoming a major arsenic compound in carnivorous zooplankton. Freshwater plankton contains less arsenobetaine than their marine relatives, with arsenosugars dominating. The possible role and formation pathways of arsenobetaine in plankton organisms are reviewed and the literature suggests that arsenobetaine in zooplankton comes from the degradation of ingested arsenosugars, and is selectively accumulated by the organism to serve as osmolyte. Several arsenic compounds such as arsenocholine, dimethylarsinoylacetate or dimethylarsinoylethanol that are intermediates of this pathway have been detected in plankton. The gaps in research on arsenobetaine in aquatic environments are also addressed: primarily most of the conclusions are drawn on culture-based experiments, and few data are present from the natural environment, especially for freshwater ecosystems. Moreover, more data on arsenic in different zooplankton species would be helpful to confirm the trends observed between herbivorous and carnivorous organisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".