SA-ABA antagonism in defense responses
Bibliographic record
Abstract
Until recently, phytohormones were mostly studied separately. However, recent studies have suggested that the signaling pathways involved are highly interconnected. We recently reported the antagonistic effects of salicylic acid (SA) and abscisic acid (ABA) in the lesion mimic mutants, cpr22 and ssi4. After shifting these mutants from high humidity, where the lesion mimic phenotype is suppressed to permissive low humidity condition, both SA and ABA pathways were up-regulated. However, the increased levels of SA were able to block downstream ABA responses even though ABA signaling genes and endogenous ABA were elevated. Furthermore, these lesion mimic mutants displayed a partial ABA insensitivity with respect to germination, guard cell opening, and water loss. This increased water loss in detached mutant plants could also be mimicked by treating wild type plants with SA. An active SA analog, 5-chloro-salicylic acid also induced enhanced water loss, while an inactive analog, 4-hydroxy-benzoic acid, did not. Here, we report that the biological analogs of SA, the systemic acquired resistance (SAR) activators, BTH (benzo-(1,2,3)-thiadiazole-7-carbothioic acid S-methyl ester) and BIT (1,2-benzisothiazol-3(2H)-one1,1-dioxide), did not have the same effect as SA, suggesting that SA may have additional roles to defense, and that SAR activators may not mimic all SA effects.
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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) | 0.002 | 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".