Integration of metabolomics and in vitro metabolism assays for investigating the stereoselective transformation of triadimefon in rainbow trout
Bibliographic record
Abstract
Triadimefon is a systemic agricultural fungicide of the triazole class whose major metabolite, triadimenol, also a commercial fungicide, provides the majority of the actual fungicidal activity, i.e., inhibition of steroid demethylation. Both chemicals are chiral: triadimefon has one chiral center with two enantiomers while its enzymatic reduction to triadimenol produces a second chiral center and two diastereomers with two enantiomers each. All six stereoisomers of the two fungicides were separated from each other using a chiral BGB-172 column on a GC-MS system so as to follow stereospecificity in metabolism by rainbow trout hepatic microsomes. In these microsomes the S-(+) enantiomer of triadimefon was transformed to triadimenol 27% faster than the R-(-) enantiomer, forming the four triadimenol stereoisomers at rates different from each other. The most fungi-toxic stereoisomer (1S,2R) was produced at the slowest rate; it was detectable after 8 h, but below the level of method quantitation. The triadimenol stereoisomer ratio pattern produced by the trout microsomes was very different from that of the commercial triadimenol standard, in which the most rat-toxic pair of enantiomers (known as "Diastereomer A") is about 85% of the total stereoisomer composition. The trout microsomes produced only about 4% of "Diastereomer A". Complementary metabolomic studies with NMR showed that exposure of the separate triadimefon enantiomers and the racemate to rainbow trout for 48 h resulted in different metabolic profiles in the trout liver extracts, i.e., different endogenous metabolite patterns that indicated differences in effects of the two enantiomers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".