ENSA and ARPP19 differentially control cell cycle progression and development
Bibliographic record
Abstract
Greatwall (GWL) is an essential kinase that indirectly controls PP2A-B55, the phosphatase counterbalancing cyclin B/CDK1 activity during mitosis. In Xenopus laevis egg extracts, GWL-mediated phosphorylation of overexpressed ARPP19 and ENSA turns them into potent PP2A-B55 inhibitors. It has been shown that the GWL/ENSA/PP2A-B55 axis contributes to the control of DNA replication, but little is known about the role of ARPP19 in cell division. By using conditional knockout mouse models, we investigated the specific roles of ARPP19 and ENSA in cell division. We found that Arpp19, but not Ensa, is essential for mouse embryogenesis. Moreover, Arpp19 ablation dramatically decreased mouse embryonic fibroblast (MEF) viability by perturbing the temporal pattern of protein dephosphorylation during mitotic progression, possibly by a drop of PP2A-B55 activity inhibition. We show that these alterations are not prevented by ENSA, which is still expressed in Arpp19Δ/Δ MEFs, suggesting that ARPP19 is essential for mitotic division. Strikingly, we demonstrate that unlike ARPP19, ENSA is not required for early embryonic development. Arpp19 knockout did not perturb the S phase, unlike Ensa gene ablation. We conclude that, during mouse embryogenesis, the Arpp19 and Ensa paralog genes display specific functions by differentially controlling cell cycle progression.
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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 | 0.001 |
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".