Azaspiracid-59 accumulation and transformation in mussels (Mytilus edulis) after feeding with Azadinium poporum (Dinophyceae)
Bibliographic record
Abstract
Azaspiracid-59 (AZA-59) was detected in plankton in coastal waters of the Pacific Northwest USA. Given that bivalves metabolize and transform accumulated phycotoxins, a strain of Azadinium poporum isolated from the coast of Washington State that is a known producer of AZA-59 was used in a controlled feeding experiment with mussels ( Mytilus edulis ) to assess AZA-59 accumulation rates and transformation into shellfish metabolites. Mussels started feeding immediately after the addition of A. poporum . Mussels were generally healthy during the entire experimental exposure of 18 days with prevailingly high rates of clearance (approx. 100 mL per mussel per hour) and ingestion. Mussels were extracted after different exposure times and were analyzed by liquid chromatography coupled with low- and high-resolution mass spectrometry. In the course of the experiment a number of putative AZA-59 metabolites were detected including hydroxyl and carboxy analogues that corresponded with previously reported mussel metabolites of AZA-1. A significant formation of 3-OH fatty acid acyl esters relative to free AZAs was observed through the time course of the study, with numerous fatty acid ester variants of AZA-59 confirmed. These results illustrate the potential for metabolism of AZA-59 in shellfish and provide important information for local AZA monitoring and toxicity testing along the Northern Pacific US coast. • AZA-59 is metabolized by mussels as AZA-1/2, but additional unreported mussel metabolites of AZA-59 were detected. • Seven novel AZA variants were detected and characterized by mass spectrometry. • Content of various 3-OH fatty acid esters was higher relative to free AZAs. • During 18 days, unesterified AZAs plateaued whereas a constant increase of AZA-59 esters was observed.
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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 | 0.000 |
| 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 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".