Structure Elucidation and Toxicity Analysis of the Degradation Products of Deoxynivalenol by Gaseous Ozone
Bibliographic record
Abstract
Fusarium Head Blight (FHB) or scab is a fungal disease of cereal grains. Wheat scab affects the yield and quality of wheat and produces mycotoxins such as deoxynivalenol (DON), which can seriously threaten human and animal health. In this study, gaseous ozone was used to degrade DON in wheat scab and the degradation products of ozonolysis were analyzed by ultra-performance liquid chromatography quadrupole-orbitrap mass spectrometry (UHPLC Q-Orbitrap). Toxicology analyses of the degradation products were also studied using structure-activity relationships. Ozone (8 mg L−1 concentration) was applied to 2 μg mL−1 of DON in ultrapure water, resulted in 95.68% degradation within 15 s. Ten ozonized products of DON in ultrapure water were analyzed and six main products (C15H18O7, C15H18O9, C15H22O9, C15H20O10, C15H18O8, and C15H20O9) were analyzed at varying concentrations of ozone and DON. Structural formulae were assigned to fragmentation products generated by MS2 and Mass Frontier® software. According to structure-activity relationship studies, the toxicities of the ozonized products were significantly decreased due to de-epoxidation and the attack of ozone at the C9-10 double bond in DON. Based on the results of the study above, we can find that gaseous ozone is an efficient and safe technology to degrade DON, and these results may provide a theoretical basis for the practical research of detoxifying DON in scabby wheat and other grains.
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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".