Some things get better with age: differences in salicylic acid accumulation and defense signaling in young and mature Arabidopsis
Bibliographic record
Abstract
In Arabidopsis, much of what we know about the phytohormone salicylic acid (SA) and its role in plant defense comes from experiments using young plants. We are interested in understanding why young plants are susceptible to virulent strains of Pseudomonas syringae, while mature plants exhibit a robust defense response known as age-related resistance (ARR). SA-mediated signaling is important for defense in young plants, however, ARR occurs independently of the defense regulators NPR1 and WHY1. Furthermore, intercellular SA accumulation is an important component of ARR, and intercellular washing fluids from ARR-competent plants exhibit antibacterial activity, suggesting that SA acts as an antimicrobial agent in the intercellular space. Young plants accumulate both intracellular and intercellular SA during PAMP- and effector-triggered immunity, however, virulent P. syringae promotes susceptibility by suppressing SA accumulation using the phytotoxin coronatine. Here we outline the hypothesis that mature, ARR-competent Arabidopsis alleviates coronatine-mediated suppression of SA accumulation. We also explore the role of SA in other mature-plant processes such as flowering and senescence, and discuss their potential impact on ARR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".