Molecular Basis of the Core Regulatory Network in ABA Responses: Sensing, Signaling and Transport
Bibliographic record
Abstract
ABA is a major phytohormone that regulates a broad range of plant traits and is especially important for adaptation to environmental conditions. Our understanding of the molecular basis of ABA responses in plants improved dramatically in 2009 and 2010, banner years for ABA research. There are three major components; PYR/PYL/ RCAR (an ABA receptor), type 2C protein phosphatase (PP2C; a negative regulator) and SNF1-related protein kinase 2 (SnRK2; a positive regulator), and they offer a double negative regulatory system, [PYR/PYL/RCAR-| PP2C-| SnRK2]. In the absence of ABA, PP2C inactivates SnRK2 by direct dephosphorylation. In response to environmental or developmental cues, ABA promotes the interaction of PYR/PYL/RCAR and PP2C, resulting in PP2C inhibition and SnRK2 activation. This signaling complex can work in both the nucleus and cytosol, as it has been shown that SnRK2 phosphorylates basic-domain leucine zipper (bZIP) transcription factors or membrane proteins. Several structural analyses of PYR/PYL/RCAR have provided the mechanistic basis for this 'core signaling' model, by elucidating the mechanism of ABA binding of receptors, or the 'gate-latch-lock' mechanism of interaction with PP2C in inhibiting activity. On the other hand, intercellular ABA transport had remained a major issue, as had intracellular ABA signaling. Recently, two plasma membrane-type ABC transporters were identified and shed light on the influx/efflux system of ABA, resolving how ABA is transported from cell to cell in plants. Our knowledge of ABA responses in plants has been greatly expanded from intracellular signaling to intercellular transport of ABA.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".