Analysis of ciguatoxins in fish with a single-step sandwich immunoassay
Bibliographic record
Abstract
• Simplified immunoassays for ciguatoxins (CTXs) were designed. • The single-step assay was selected as the best strategy. • The simplified assay only takes 40 min, compared to >2 hours of the original one. • The immunoassay detects CTXs at the FDA safety guidance level. • Analysis of fish extracts demonstrated the viability of the approach. Ciguatoxins (CTXs) are the primary cause of ciguatera poisoning (CP), one of the most prevalent non-bacterial seafood-borne illnesses worldwide. With no cure available beyond palliative treatments to alleviate symptoms, effective CP management relies on prevention. However, the detection of CTXs in seafood poses significant analytical challenges due to their typically low concentrations in specimens and the high variability among CTX congeners, many of which remain poorly characterized. These challenges have led to a growing demand for the development of rapid, sensitive, and user-friendly bioanalytical tools for CP surveillance. In this study, several simplified sandwich immunoassay strategies were evaluated for the detection of Pacific CTXs in fish. Among them, the single-step strategy was identified as the most promising, as it enables the detection of Pacific CTXs in complex fish matrixes within only 40 min at levels as low as 0.01 µg CTX1B equivalents/kg of fish, aligned with the safety guidance level proposed by the United States Food and Drug Administration (FDA). Unlike traditional sandwich immunoassays, which require several sequential incubation steps, the single-step strategy involves a simultaneous incubation of all components with the sample, uniquely followed by a washing and substrate incubation step prior to signal measurement. This approach significantly reduces both the complexity and time required for analysis, positioning this immunoassay as a highly promising tool for CP risk assessment and management.
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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 | 0.002 |
| 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) | 0.004 | 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".