Epimers of Azaspiracids: Isolation, Structural Elucidation, Relative LC-MS Response, and <i>in Vitro</i> Toxicity of 37-<i>epi</i>-Azaspiracid-1
Bibliographic record
Abstract
Since azaspiracid-1 (AZA1) was identified in 1998, the number of AZA analogues has increased to over 30. The development of an LC-MS method using a neutral mobile phase led to the discovery of isomers of AZA1, AZA2, and AZA3, present at ~2-16% of the parent analogues in phytoplankton and shellfish samples. Under acidic mobile phase conditions, isomers and their parents are not separated. Stability studies showed that these isomers were spontaneous epimerization products whose formation is accelerated with the application of heat. The AZA1 isomer was isolated from contaminated shellfish and identified as 37-epi-AZA1 by nuclear magnetic resonance (NMR) spectroscopy and chemical analyses. Similar analysis indicated that the isomers of AZA2 and AZA3 corresponded to 37-epi-AZA2 and 37-epi-AZA3, respectively. The 37-epimers were found to exist in equilibrium with the parent compounds in solution. 37-epi-AZA1 was quantitated by NMR, and relative molar response studies were performed to determine the potential differences in LC-MS response of AZA1 and 37-epi-AZA1. Toxicological effects were determined using Jurkat T lymphocyte cells as an in vitro cell model. Cytotoxicity experiments employing a metabolically based dye (i.e., MTS) indicated that 37-epi-AZA1 elicited a lethal response that was both concentration- and time-dependent, with EC50 values in the subnanomolar range. On the basis of EC50 comparisons, 37-epi-AZA1 was 5.1-fold more potent than AZA1. This data suggests that the presence of these epimers in seafood products should be considered in the analysis of AZAs for regulatory purposes.
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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) | 0.000 | 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) | 0.001 | 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".