Sulfide Oxidations for LC-MS Analysis of Methionine-Containing Microcystins in <i>Dolichospermum flos-aquae</i> NIVA-CYA 656
Bibliographic record
Abstract
Microcystins are cyclic heptapeptides produced by a range of cyanobacteria. More than 150 microcystin analogues have been reported from cultures, algal blooms, or other contaminated samples. Relatively few analytical standards are available, making identification and quantitation of these toxins a challenge, even with LC-MS technology. We developed a two-step oxidative procedure that allows LC-MS identification of microcystins containing methionine and methionine sulfoxide, and reveals the oxidation state of the methionyl sulfur atom. The procedure was used in parallel with mercaptoethanol derivatization and LC-MS(2) analysis to demonstrate the presence of [Asp(3)]MC-MR (12) and MC-MR (17) in a culture of Dolichospermum flos-aquae, together with low levels of [Asp(3)]MC-M(O)R (5) and MC-M(O)R (7), as well as 20 other microcystins. Fresh culture contained only traces of sulfoxides 5 and 7, but these increased during storage or sample extraction and preparation. This suggests that microcystins containing methionine sulfoxide are primarily postextraction oxidation artifacts, rather than being produced by biosynthesis in cyanobacteria. A simple, rapid extraction under inert gas followed promptly by LC-MS analysis minimized oxidation artifacts for D. flos-aquae.
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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 | 0.000 | 0.000 |
| 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".