The<i>Drosophila</i>F-box protein dSkp2 regulates cell proliferation by targeting Dacapo for degradation
Bibliographic record
Abstract
Cell cycle progression is controlled by a complex regulatory network consisting of interacting positive and negative factors. In humans, the positive regulator Skp2, an F-box protein, has been a subject of intense investigation in part because of its oncogenic activity. By contrast, the molecular and developmental functions of its Drosophila homologue, dSkp2, are poorly understood. Here we investigate the role of dSkp2 by focusing on its functional relationship with Dacapo (Dap), the Drosophila homologue of the cyclin-dependent kinase inhibitors p21(cip1)/p27(kip1)/p57(kip2). We show that dSkp2 interacts physically with Dap and has a role in targeting Dap for ubiquitination and proteasome-mediated degradation. We present evidence that dSkp2 regulates cell cycle progression by antagonizing Dap in vivo. dSkp2 knockdown reduces cell density in the wing by prolonging the cell doubling time. In addition, the wing phenotype caused by dSkp2 knockdown resembles that caused by dap overexpression and can be partially suppressed by reducing the gene dose of dap. Our study thus documents a conserved functional relationship between dSkp2 and Dap in their control of cell cycle progression, suggesting the possibility of using Drosophila as a model system to study Skp2-mediated tumorigenesis.
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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) | 0.001 | 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 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".