A Short Review of Anti-Rust Fungi Peptides: Diversity and Bioassays
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pucciniales are fungal pathogens of plants that cause devastating rust diseases in agriculture. Chemically-synthesized pesticides help farmers to control rust epidemics, but governing bodies aim at limiting their use over the next decade. Defense peptides with antimicrobial activities may help to innovate a next generation of phytosanitary products for sustainable crop protection. This review comprehensively inventories the proteins or peptides exhibiting a biochemically-demonstrated antifungal activity toward Pucciniales ( i.e. , anti-rust proteins or peptides; hereafter ‘ARPs’), and also analyses the bioassays used to characterize them. In total, the review scrutinizes sixteen publications, which collectively report 35 ARPs. These studies used either in vitro or in planta bioassays, or a combination of both, to characterize ARPs; mostly by evaluating their ability to inhibit the spore germination process in vitro or to inhibit fungal growth and rust disease development in planta . Also, the manuscript shows that almost no mode of action against rust fungi was elucidated, although some might be inferred from studies performed on other fungi. This short review may serve as a knowledge and methodological basis to inform future studies addressing ARPs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it