Interlaboratory Evaluation of Multiple LC–MS/MS Methods and a Commercial ELISA Method for Determination of Tetrodotoxin in Oysters and Mussels
Bibliographic record
Abstract
BACKGROUND: Given the recent detection of tetrodotoxin (TTX) in bivalve molluscs but the absence of a full collaborative validation study for TTX determination in a large number of shellfish samples, interlaboratory assessment of method performance was required to better understand current capabilities for accurate and reproducible TTX quantitation using chemical and immunoassay methods. OBJECTIVE: The aim was to conduct an interlaboratory study with multiple laboratories, using results to assess method performance and acceptability of different TTX testing methods. METHODS: Homogenous and stable mussel and oyster materials were assessed by participants using a range of published and in-house detection methods to determine mean TTX concentrations. Data were used to calculate recoveries, repeatability, and reproducibility, together with participant acceptability z-scores. RESULTS: Method performance characteristics were good, showing excellent sensitivity, recovery, and repeatability. Acceptable reproducibility was evidenced by HorRat values for all LC-MS/MS and ELISA methods being less than the 2.0 limit of acceptability. Method differences between the LC-MS/MS participants did not result in statistically different results. Method performance characteristics compared well with previously published single-laboratory validated methods and no statistical difference was found in results returned by ELISA in comparison with LC-MS/MS. CONCLUSION: The results from this study demonstrate that current LC-MS/MS methods and ELISA are on the whole capable of sensitive, accurate, and reproducible TTX quantitation in shellfish. Further work is recommended to expand the number of laboratories testing ELISA and to standardize an LC-MS/MS protocol to further improve interlaboratory precision. HIGHLIGHTS: Multiple mass spectrometric methods and a commercial ELISA have been successfully assessed through an interlaboratory study, demonstrating excellent performance.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".