<i>AREB/ABF/ABI5</i> transcription factors in plant defense: regulatory cascades and functional diversity
Bibliographic record
Abstract
Basic leucine zipper transcription factors (TFs), also known as ABRE-BINDING PROTEINs/ABRE BINDING FACTORs (AREBs/ABFs), and ABA INSENSITIVE 5 (ABI5), show a great potential for the regulation of gene expressions in different crops under unfavorable conditions. These factors are involved in phytohormone signaling pathways, developmental metabolism, and growth regulation under environmental stresses. ABI5 functions alongside ABREs to regulate gene expression, with their promoter regions composed of the receptors PYR/PYL/RCAR, kinases (sucrose non-fermenting-1-related protein kinase 2) and phosphatases (PROTEIN PHOSPHATASE 2 C). These TFs participate in signaling pathways that regulate key genes and control numerous morphological, physiological, biochemical, and molecular processes under stressful environments. In this review, we studied ABFs/AREBs/ABI5s TFs, the phytohormone signaling pathways and their crosstalk, which play critical roles in regulating responses to abiotic stresses. The key TFs discussed in this work regulate various metabolic pathways and are promising candidates for the development of stress-resilient crops via CRISPR/CRISPR-associated protein technology to address threats to food security and sustainability in agriculture.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".