Functions, regulation and cellular localization of plant cyclin‐dependent kinase inhibitors
Bibliographic record
Abstract
The cell cycle is regulated by the cyclin-dependent kinase (CDK), and CDK inhibitors can bind to CDKs and inhibit their activities. This review examines plant CDK inhibitors, with particular emphasis on their molecular and cellular functions, regulation and cellular localization. In plants, a family of ICK/KRP CDK inhibitors represented by ICK1 is known and another type of CDK inhibitor represented by the SIMESE (SIM) has recently been reported. Considerable understanding has been gained with the ICK/KRP CDK inhibitors. These plant CDK inhibitors share only limited sequence similarity in the C-terminal region with the KIP/CIP family of mammalian CDK inhibitors. The ICK/KRP CDK inhibitors thus provide good tools to understand the basic machinery as well as the unique aspects of the plant cell cycle. The ICK/KRP CDK inhibitors interact with D-type cyclins or A-type CDKs or both. Several functional regions and motifs have been identified in ICK1 for CDK inhibition, nuclear localization and protein instability. Clear evidence shows that ICK/KRP proteins are important for the cell cycle and endoreduplication. Preliminary evidence suggests that they may also be involved in cell differentiation and cell death. Results so far show that plant CDK inhibitors are exclusively localized in the nucleus. The molecular sequences regulating the localization and functional significance will be discussed.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".