Biotransformation of Arsenate to the Tetramethylarsonium Ion in the Marine Polychaetes <i>Nereis diversicolor</i> and <i>Nereis virens</i>
Bibliographic record
Abstract
Arsenic compounds in aqueous extracts of the marine polychaetes Nereis diversicolor and Nereis virens were determined by HPLC-ICP-MS. Both polychaetes contained most of their water-soluble arsenic as arsenobetaine (approximately 60%), and the tetramethylarsonium ion was also a significant arsenic constituent (approximately 20% in N. diversicolor and approximately 30% in N. virens). Trimethylarsoniopropionate and arsenosugars were present in the Nereis species as minor constituents, and traces of arsenocholine, trimethylarsine oxide, and arsenate were also detected. When N. diversicolor and N. virens were exposed in laboratory experiments to different concentrations of arsenate in seawater (10, 50, 100, 500, and 1000 microg of As L(-1)), both species accumulated arsenic in a dose-dependent manner. Atthe highest exposure level, they achieved mean arsenic concentrations (dry mass) of approximately 70 mg of As kg(-1) (N. virens) and 90 mg of As kg(-1) (N. diversicolor), which represented about a 5-fold increase when compared with the control animals. The arsenic taken up by the polychaetes was readily methylated, and the major metabolite was the tetramethylarsonium ion (up to approximately 85% of the accumulated arsenic). Two other products of arsenic methylation, methylarsonate and trimethylarsine oxide, were also produced to a small extent; however, dimethylarsinate, another likely intermediate in the formation of the tetramethylarsonium ion, could not be detected in these experiments. The remaining accumulated arsenic was present as unchanged arsenate. This is the first report of significant biomethylation of arsenic to the tetramethyl stage and provides a ready explanation for the widespread occurrence of tetramethylarsonium ion in marine animals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".