3-keto-DON, but Not 3-epi-DON, Retains the in Planta Toxicological Potential after the Enzymatic Biotransformation of Deoxynivalenol
Bibliographic record
Abstract
Deoxynivalenol (DON) is a secondary fungal metabolite that is associated with many adverse toxicological effects in agriculture as well as human/animal nutrition. Bioremediation efforts in recent years have led to the discovery of numerous bacterial isolates that can transform DON to less toxic derivatives. Both 3-keto-DON and 3-epi-DON were recently shown to exhibit reduced toxicity, compared to DON, when tested using different cell lines and mammalian models. In the current study, the toxicological assessment of 3-keto-DON and 3-epi-DON using in planta models surprisingly revealed that 3-keto-DON, but not 3-epi-DON, retained its toxicity to a large extent in both duckweeds (Lemna minor L.) and common wheat (Triticum aestivum L.) model systems. RNA-Seq analysis revealed that the exposure of L. minor to 3-keto-DON and DON resulted in substantial transcriptomic changes and similar gene expression profiles, whereas 3-epi-DON did not. These novel findings are pivotal for understanding the environmental burden of the above metabolites as well as informing the development of future transgenic plant applications. Collectively, they emphasize the fundamental need to assess both plant and animal models when evaluating metabolites/host interactions.
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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 | 0.001 |
| 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".