Hormonal Responses to Susceptible, Intermediate, and Resistant Interactions in the Brassica napus–Leptosphaeria maculans Pathosystem
Bibliographic record
Abstract
Hormone signaling plays a pivotal role in plant–microbe interactions. There are three major phytohormones in plant defense: salicylic acid (SA), jasmonic acid (JA), and ethylene (ET). The activation and trade-off of signaling between these three hormones likely determines the strength of plant defense in response to pathogens. Here, we describe the allocation of hormonal signaling in Brassica napus against the fungal pathogen Leptosphaeria maculans. Three B. napus genotypes (Westar, Surpass400, and 01-23-2-1) were inoculated with two L. maculans isolates (H75 8-1 and H77 7-2), subsequently exhibiting three levels of resistance: susceptible, intermediate, and resistant. Quantitative analyses suggest that the early activation of some SA-responsive genes, including WRKY70 and NPR1, contribute to an effective defense against L. maculans. The co-expression among factors responding to SA/ET/JA was also observed in the late stage of infection. The results of conjugated SA measurement also support that early SA activation plays a crucial role in durable resistance. Our results demonstrate the relationship between the onset patterns of certain hormone regulators and the effectiveness of the defense of B. napus against L. maculans.
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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".