The Orphan Receptor Tyrosine Kinase Ror2 Modulates Canonical Wnt Signaling in Osteoblastic Cells
Bibliographic record
Abstract
Ror2 is an orphan receptor tyrosine kinase that plays crucial roles in developmental morphogenesis, particularly of the skeleton. We have identified human Ror2 as a novel regulator of canonical Wnt signaling in osteoblastic (bone-forming) cells with selective activities, enhancing Wnt1 but antagonizing Wnt3. Immunoprecipitation studies demonstrated physical interactions between human Ror2 and mammalian Wnt1 and Wnt3. Functionally, Ror2 antagonized Wnt1- and Wnt3-mediated stabilization of cytosolic beta-catenin in osteoblastic cells. However, Ror2 had opposing effects on a more distal step of canonical Wnt signaling: it potentiated Wnt1 activity but inhibited Wnt3 function as assessed by changes in Wnt-responsive reporter gene activity. Despite binding to Ror2, neither Wnt1 nor Wnt3 altered receptor activity as assessed by levels of Ror2 autophosphorylation. The ability of Ror2 to regulate canonical Wnt signaling in osteoblastic cells should have physiological consequences in bone, because Wnt signaling is known to modulate osteoblast survival and differentiation. Expression of Ror2 mRNA was highly regulated in a biphasic manner during human osteoblast differentiation, being virtually undetectable in pluripotent stem cells, increasing 300-fold in committed preosteoblasts, and disappearing again in osteocytes. Furthermore, Ror2 expression in osteoblasts was suppressed by the Wnt antagonist, secreted frizzled-related protein 1. The regulated expression of Ror2 during osteoblast differentiation, its inverse expression pattern with secreted frizzled-related protein 1, and its ability to modulate Wnt signaling in osteoblastic cells suggest that Ror2 may regulate bone formation.
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) | 0.001 | 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".