<scp>ABA</scp> inhibits entry into stomatal‐lineage development in <scp>A</scp>rabidopsis leaves
Bibliographic record
Abstract
The number and density of stomata are controlled by endogenous and environmental factors. Despite recent advances in our understanding of stomatal development, mechanisms which prevent stomatal-lineage entry remain unclear. Here, we propose that abscisic acid (ABA), a phytohormone known to induce stomatal closure, limits initiation of stomatal development and induces enlargement of pavement cells in Arabidopsis cotyledons. An ABA-deficient aba2-2 mutant had an increased number/proportion of stomata within a smaller cotyledon, as well as reduced expansion of pavement cells. This tendency was reversed after ABA application or in an ABA over-accumulating cyp707a1cyp707a3 doublemutant. Our time course analysis revealed that aba2-2 shows prolonged formation of meristemoids and guard mother cells, both precursors of stoma. This finding is in accordance with prolonged gene expression of SPCH and MUTE, master regulators for stomatal formation, indicating that ABA acts upstream of these genes. Only aba2-2 mute, but not aba2-2 spch double mutant showed additive phenotypes and displayed inhibition of pavement cell enlargement with increased meristemoid number, indicating that ABA action on pavement cell expansion requires the presence of stomatal-lineage cells.
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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 | 0.001 |
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".