Debunking the Myth of <i>Fusarium poae</i> T-2/HT-2 Toxin Production
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Fusarium poae is commonly detected in field surveys of Fusarium head blight (FHB) of cereal crops and can produce a range of trichothecene mycotoxins. Although experimentally validated reports of F. poae strains producing T-2/HT-2 trichothecenes are rare, F. poae is frequently generalized in the literature as a producer of T-2/HT-2 toxins due to a single study from 2004 in which T-2/HT-2 toxins were detected at low levels from six out of forty-nine F. poae strains examined. To validate/substantiate the observations reported from the 2004 study, the producing strains were acquired and phylogenetically confirmed to be correctly assigned as F. poae; however, no evidence of T-2/HT-2 toxin production was observed from axenic cultures. Moreover, no evidence for a TRI16 ortholog, encoding a key acyltransferase shown to be necessary for T-2 toxin production in other Fusarium species, was observed in any of the de novo assembled genomes of the F. poae strains. Our findings corroborate multiple field-based and in vitro studies on FHB-associated Fusarium populations which also do not support the production of T-2/HT-2 toxins with F. poae and therefore conclude that F. poae should not be generalized as a T-2/HT-2 toxin producing species of Fusarium .
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".