Evidence for involvement of jasmonic acid in the induction of leaf senescence by potassium deficiency in <i>Arabidopsis</i>
Bibliographic record
Abstract
Potassium (K + ) deficiency induces leaf senescence, and jasmonic acid (JA) plays a role in the regulation of leaf senescence; however, there is no direct evidence that JA has a role in the induction of leaf senescence by K + deficiency. Here, we determined that JA is involved in the induction of leaf senescence by K + deficiency. Leaf senescence was induced by K + deficiency, as indicated by both the induction of expression of two senescence-associated genes, SAG12 and SAG13, and a decline in chlorophyll concentration; whereas inhibitors of JA biosynthesis, aspirin and salicylate, abolished the induction of leaf senescence by K + deficiency. The JA concentration was threefold higher in the leaves of plants with K + deficiency than it was in the leaves of control plants. In addition, transcript levels of two JA-responsive genes, PDF1.2 and Thi2.1, were higher in the leaves of plants with K + deficiency than in the leaves of control plants. Our studies provide evidence that K + deficiency induces leaf senescence, at least in part, via a JA-dependent pathway.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 teacher head, 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".