Validation of a New Sensitive Method for the Detection and Quantification of R and S-Epimers of Ergot Alkaloids in Canadian Spring Wheat Utilizing Deuterated Lysergic Acid Diethylamide as an Internal Standard
Bibliographic record
Abstract
Ergot sclerotia effect cereal crops intended for consumption. Ergot alkaloids within ergot sclerotia are assessed to ensure contamination is below safety standards established for human and animal health. Ergot alkaloids exist in two configurations, the R and S-epimers. It is important to quantify both configurations. The objective of this study was to validate a new ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method for quantification of six R and six S-epimers of ergot alkaloids in hard red spring wheat utilizing deuterated lysergic acid diethylamide (LSD-D3) as an internal standard. Validation parameters such as linearity, limit of detection (LOD), limit of quantification (LOQ), matrix effects, recovery and precision were investigated. For the 12 epimers analyzed, low LOD and LOQ values were observed, allowing for the sensitive detection of ergot epimers. Matrix effects ranged between 101–113% in a representative wheat matrix. Recovery was 68.3–119.1% with an inter-day precision of <24% relative standard deviation (RSD). The validation parameters conform with previous studies and exhibit differences between the R and S-epimers which has been rarely documented. This new sensitive method allows for the use of a new internal standard and can be incorporated and applied to research or diagnostic laboratories.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".