Research Progress on Fusarium Mycotoxins in Plant and Pathogen Interactions
Bibliographic record
Abstract
Fusarium is one of the most important plant pathogens in the world, affecting plant growth and development and posing a serious threat to global food security and biodiversity. Almost all Fusarium species produce fungal toxins, which are diverse and highly toxic. On the one hand, they can participate in the pathogenic process of Fusarium as one of the pathogenic factors, and on the other hand, they can contaminate food and feed, leading to related diseases in humans and animals. Previous studies have shown that different types of mycotoxins produced by Fusarium infection not only poison plant cells and cause necrosis of plant tissues, but also accelerate the infection of pathogenic fungi. At the same time, in response to the mycotoxins produced by pathogenic fungi, plants activate defense enzymes and initiate the expression of defense related genes, or convert the pathogenic factors into non-toxic or low toxic substances and transport them out of the cell, or directly inhibit the biosynthesis of pathogenic mycotoxins by secreting secondary metabolites. To comprehensively analyze the role of Fusarium mycotoxin in pathogen infection of plants and improve their resistance to pathogens, this article reviews the types, toxicity mechanisms, and roles of mycotoxins in the interaction between plants and pathogens in Fusarium. It also discusses the defense response strategies of plants to mycotoxins, with an aim to provide references for future research on the pathogenic mechanism and pathogen control strategies of Fusarium mycotoxins.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".