Hydrophilic interaction liquid chromatography/mass spectrometry for determination of domoic acid in Adriatic shellfish
Bibliographic record
Abstract
This paper describes a new method for sensitive, specific and direct determination of domoic acid (DA), the causative toxin of amnesic shellfish poisoning (ASP) syndrome, in shellfish. It is based on combination of hydrophilic interaction liquid chromatography with mass spectrometry (HILIC/MS). The high percentage of organic modifier in the mobile phase and the omission of ion-pairing reagents, both favoured in HILIC, result in enhanced detection limits with MS detection. The new method was set up either on an ionspray ion trap MS instrument operating in MS and MS/MS scanning acquisition modes, or on a turboionspray triple-quadrupole MS system operating in selected ion monitoring (SIM) and multiple reaction monitoring (MRM) acquisition modes. Positive and negative ion experiments were performed. MRM experiments are recommended for screening contaminated shellfish tissue and for quantitative analyses due to highest sensitivity and selectivity. The minimum detection levels for the toxin in tissue were found to be 63 and 190 ng/g in positive and negative MRM experiments, respectively, which are well below the regulatory limit for DA in tissue (20 microg/g). Application to shellfish samples collected in the Adriatic Sea (Italy) in the period 2000-2004 demonstrated for the first time in Italy the presence of DA as a new toxin that has entered the Adriatic Mytilus galloprovincialis toxin profile.
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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 | 0.001 | 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 | 0.001 |
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".