Magnetic Amino-Modified Multiwalled Carbon Nanotube (MWCNT) Based Magnetic Dispersive Solid-Phase Extraction (m-dSPE) for the Determination of Paralytic Shellfish Toxins in Bivalve Mollusks with Hydrophilic Interaction Liquid Chromatography–Tandem Mass Spectrometry (HILIC-MS/MS)
Bibliographic record
Abstract
A sensitive and efficient magnetic amino modified multi-walled carbon nanotubes (m-MWCNT-NH2)-based magnetic dispersive solid-phase extraction (m-dSPE) coupled with hydrophilic interaction liquid chromatography–tandem mass spectrometry (HILIC-MS/MS) strategy is reported for the simultaneous determination of 13 paralytic shellfish toxins (PSTs) in bivalve mollusks. The samples were extracted twice with 1% acetic acid and purified using optimized m-dSPE procedures with Fe3O4 coated MWCNT-NH2 composites as magnetic adsorbents. The adsorbed PSTs on the m-MWCNT-NH2 adsorbents were separated using a Ni-coated neodymium magnet and subsequently eluted with 2 mL water–acetonitrile–acetic acid (80:20:1, v/v/v) and analyzed by HILIC-MS/MS. The correlation coefficients (r) of the targeted toxins obtained in matrix-matched external standard curves were from 0.997 to 0.999. The PSTs were acquired and quantified in the multiple reaction-monitoring mode and the limits of detection and quantitation in bivalve mollusks were 1.10 to 4.51 μg/kg and 3.67 to 13.5 μg/kg, respectively. Spiked recoveries at three concentrations in negative samples were from 73.4% to 92.5% with precision less than 10.6%. The method validation was in accordance with 2002/657/EC guidelines and method application in commercial bivalve mollusk samples. The developed method was rapid, convenient and economical for the determination of the targeted toxins.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".