Comparison of Different Solid-Phase Cleanup Methods Prior to the Detection of Ciguatoxins in Fish by Cell-Based Assay and LC-MS/MS
Bibliographic record
Abstract
Ciguatera poisoning (CP) is the most reported food poisoning associated with fish consumption. Ciguatoxins (CTXs) are produced by microalgae and metabolized in fish; even low levels of these toxins in fish can lead to CP. To date, there is no unique validated methodology for their study, and demonstrating their presence in fish tissues is an analytical challenge. The main techniques used are cell-based assay and liquid chromatography, which may present different matrix effect interferences; thus, purification protocols are necessary. Six cleanup strategies for fish extracts, assessing the principal analogues found in fish in different parts of the world (CTX1B/CTX3C/C-CTX1), are compared here. Cleaned-up extracts are evaluated by cell-based assay and chromatography. All protocols are suitable for recovering the analogues of CTXs. Two of them, those that used polystyrene-divinylbenzene and silica cartridges, achieve the most adequate results showing toxicity in their fractions over 53% and chromatography efficiencies over 79% for CTX1B/CTX3C, proving to be the most versatile clean-ups for the study of the different CTX analogues.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".