RanBP3 enhances nuclear export of active β-catenin independently of CRM1
Bibliographic record
Abstract
beta-Catenin is the nuclear effector of the Wnt signaling cascade. The mechanism by which nuclear activity of beta-catenin is regulated is not well defined. Therefore, we used the nuclear marker RanGTP to screen for novel nuclear beta-catenin binding proteins. We identified a cofactor of chromosome region maintenance 1 (CRM1)-mediated nuclear export, Ran binding protein 3 (RanBP3), as a novel beta-catenin-interacting protein that binds directly to beta-catenin in a RanGTP-stimulated manner. RanBP3 inhibits beta-catenin-mediated transcriptional activation in both Wnt1- and beta-catenin-stimulated human cells. In Xenopus laevis embryos, RanBP3 interferes with beta-catenin-induced dorsoventral axis formation. Furthermore, RanBP3 depletion stimulates the Wnt pathway in both human cells and Drosophila melanogaster embryos. In human cells, this is accompanied by an increase of dephosphorylated beta-catenin in the nucleus. Conversely, overexpression of RanBP3 leads to a shift of active beta-catenin toward the cytoplasm. Modulation of beta-catenin activity and localization by RanBP3 is independent of adenomatous polyposis coli protein and CRM1. We conclude that RanBP3 is a direct export enhancer for beta-catenin, independent of its role as a CRM1-associated nuclear export cofactor.
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) | 0.000 | 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) | 0.002 | 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".