Liquid Chromatography/Mass Spectrometry of Domoic Acid and Lipophilic Shellfish Toxins with Selected Reaction Monitoring and Optional Confirmation by Library Searching of Product Ion Spectra
Bibliographic record
Abstract
LC/MS methodology for the analysis of domoic acid and lipophilic toxins in shellfish was developed using a hybrid triple quadrupole linear ion trap mass spectrometer. For routine quantitation a scheduled selected reaction monitoring (SRM) method for the analysis of domoic acid, okadaic acid, dinophysistoxins, azaspiracids, pectenotoxins, yessotoxins, gymnodimines, spirolides, and pinnatoxins was developed and validated. The method performed well in terms of LOD, linearity, precision, and trueness. Taking advantage of the high instrument sensitivity, matrix effects were mitigated by reducing the amount of sample introduced to the mass spectrometer. Optionally, samples can be analyzed using information dependent acquisition (IDA) methods, either in positive or negative mode, which can provide an extra level of confirmation by matching the full product ion spectra acquired for a sample with those from a specially constructed spectral library. Methods were applied to the analysis df a new certified reference material and Canadian mussels (Mytilus edulis) implicated in a 2011 diarrhetic shellfish poisoning (DSP) incident. The scheduled SRM method enabled the screening and quantitation of multiple phycotoxins. As DSP had not previously been observed in this area of Canada, positive identification of putative toxins was accomplished using the IDA and spectral search method. Analysis of the 2011 toxic mussel samples revealed the presence of high levels of dinophysistoxin-1, which explained the DSP symptoms, as well as pectenotoxins, yessotoxins, and variety of cyclic imines.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".