Wnt5a induces homodimerization and activation of Ror2 receptor tyrosine kinase
Bibliographic record
Abstract
Wnts are secreted glycoproteins that control vital biological processes, including embryogenesis, organogenesis and tumorigenesis. Wnts are classified into several subfamilies depending on the signaling pathways they activate, with the canonical subfamily activating the Wnt/beta-catenin pathway and the non-canonical subfamily activating a variety of other pathways, including the Wnt/calcium signaling and the small GTPase/c-Jun NH2-terminal kinase pathway. Wnts bind to a membrane receptor Frizzled and a co-receptor, the low-density lipoprotein receptor related protein. More recently, both canonical and non-canonical Wnts were shown to bind the Ror2 receptor tyrosine kinase. Ror2 is an orphan receptor that plays crucial roles in skeletal morphogenesis and promotes osteoblast differentiation and bone formation. Here we examine the effects of a canonical Wnt3a and a non-canonical Wnt5a on the signaling of the Ror2 receptor. We demonstrate that even though both Wnt5a and Wnt3a bound Ror2, only Wnt5a induced Ror2 homo-dimerization and tyrosine phosphorylation in U2OS human osteoblastic cells. Furthermore, Wnt5a treatment also resulted in increased phosphorylation of the Ror2 substrate, 14-3-3beta scaffold protein, indicating that Wnt5a binding causes activation of the Ror2 signaling cascade. Functionally, Wnt5a recapitulated the Ror2 activation phenotype, enhancing bone formation in the mouse calvarial bone explant cultures and potentiating osteoblastic differentiation of human mesenchymal stem cells. The effect of Wnt5a on osteoblastic differentiation was largely abolished upon Ror2 down-regulation. Thus we show that Wnt5a activates the classical receptor tyrosine kinase signaling cascade through the Ror2 receptor in cells of osteoblastic origin.
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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) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".