Improved Isolation Procedures for Okadaic Acid Group Toxins from Shellfish (Mytilus edulis) and Microalgae (Prorocentrum lima)
Bibliographic record
Abstract
Okadaic acid (OA) group toxins may accumulate in shellfish and can result in diarrhetic shellfish poisoning when consumed by humans, and are therefore regulated. Purified toxins are required for the production of certified reference materials used to accurately quantitate toxin levels in shellfish and water samples, and for other research purposes. An improved procedure was developed for the isolation of dinophysistoxin 2 (DTX2) from shellfish (M. edulis), reducing the number of purification steps from eight to five, thereby increasing recoveries to ~68%, compared to ~40% in a previously reported method, and a purity of >95%. Cell densities and toxin production were monitored in cultures of Prorocentrum lima, that produced OA, DTX1, and their esters, over ~1.5 years with maximum cell densities of ~70,000 cells mL−1 observed. Toxin accumulation progressively increased over the study period, to ~0.7 and 2.1 mg L−1 of OA and DTX1 (including their esters), respectively, providing information on appropriate harvesting times. A procedure for the purification of OA and DTX1 from the harvested biomass was developed employing four purification steps, with recoveries of ~76% and purities of >95% being achieved. Purities were confirmed by LC-HRMS, LC-UV, and NMR spectroscopy. Additional stability observations led to a better understanding of the chemistry of these toxins.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".