Stability and Recovery of Palytoxin and Ovatoxin-a
Bibliographic record
Abstract
spp., respectively. Several documented events have resulted in human exposure to aerosolized toxins that led to significant respiratory distress. It has been reported that processing of samples containing palytoxin and ovatoxin during analysis can lead to significant analyte recovery issues due to a variety of parameters. In this study, systematically designed experiments, monitored by LC-MS/MS, were used to evaluate palytoxin and ovatoxin-a stability and recovery, and the effects of pH, solvent composition, and vial contact surface. Significant losses of palytoxin and ovatoxin-a were observed when drying highly aqueous solutions in glass, which were reduced with the use of a polypropylene contact surface and the addition of bovine serum albumin and phosphate-buffered saline. The results showed that palytoxin analogues should be maintained in solutions containing greater than 50% organic solvent, such as methanol, and in a pH range of 5-8 in order to minimize losses or degradation. The recovery of ovatoxin-a was lower than for palytoxin in several experiments, indicating that the structural differences between these analogues may affect solubility or stability. This work provides insight into palytoxin and ovatoxin-a handling, and will help improve analytical measurements, handling during toxicology studies, and minimize losses during isolation protocols for the development of reference materials.
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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) | 0.000 | 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) | 0.001 | 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 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".