Discovery of new analogs of the marine biotoxin azaspiracid in blue mussels ( <i>Mytilus edulis</i> ) by ultra‐performance liquid chromatography/tandem mass spectrometry
Bibliographic record
Abstract
Azaspiracids (AZAs) are a group of lipophilic marine biotoxins that were first discovered in blue mussels harvested in 1995 in Killary Harbour on the west coast of Ireland. At least eight people fell ill after the consumption of contaminated mussels and developed symptoms of nausea, stomach cramps, vomiting and severe diarrhoea. Until now, eleven different analogs of these toxins have been described, with a twelfth one theoretically postulated. This paper describes the detection and identification of twenty new analogs of azaspiracid, including dihydroxy-AZAs and carboxy-AZAs, using state-of-the-art techniques including ultra-performance liquid chromatography (UPLC) and tandem mass spectrometry (MS/MS). Blue mussels (Mytilus edulis) from a toxic event of the northwest coast of Ireland in 2005 were extracted and analysed using LC/MS. The mass spectra obtained from different instruments enabled identification of previously unknown analogs of azaspiracid with additional hydroxyl and carboxyl substituents. Mass fragmentation patterns of the dihydroxy-AZAs indicated the positions of these substituents to be at the C3 and C23 position. The previously theoretically postulated AZA12 was also observed in this study. Product ion spectra showed the presence of a unique fragment ion at m/z 408 for all C23-hydroxylated analogs. This fragmentation competes with the fragmentation leading to m/z 362, a fragment ion that has shown to be present in all AZAs. The novel analogs have not been seen in plankton or water samples and are believed to be metabolites of AZAs formed in mussels. All the new AZA analogs were present at low concentrations in the shellfish and it is probably safe to assume that they do not pose a risk for the shellfish consumer.
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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".