Wnt3‐frizzled 1 chimera as a model to study canonical Wnt signaling
Bibliographic record
Abstract
Wnt proteins initiate signaling by binding to seven transmembrane spanning receptors of the frizzled (Fz) family together with the members of the low-density lipoprotein receptor-related protein (LRP) 5 and 6. A chimera of human Wnt3 and Fz1 receptor was developed that efficiently activated the TCF-luciferase reporter. Deletion of the cytoplasmic tail and point mutations in the PDZ binding region in the chimera resulted in the loss of Wnt signaling, suggesting a critical role for the Fz cytoplasmic region in Wnt signaling. The Fz CRD is also critical for Wnt signaling, as a deletion of 29 amino acids in the 2nd cysteine loop resulted in the total loss of TCF-luciferase activation. DKK-1 protein blocks upregulation of the TCF-luciferase reporter by the Wnt3-Fz1 chimera, suggesting involvement of LRP in Wnt3-Fz1 signaling. Expression of a Wnt3-Fz1 chimera in C3H10T1/2 cells resulted in the upregulation of alkaline phosphatase activity and inhibition of adipocyte formation, demonstrating that the Wnt3-Fz1 chimera is a potent activator of differentiation of C3H10T1/2 cells into osteoblasts and an inhibitor of their differentiation into the adipocyte lineage. In summary, the Wnt-Fz chimera approach has the potential to better our understanding of the mechanism of Wnt action and its role, particularly in stem cell differentiation. In addition, this methodology can be utilized to identify inhibitors of either Wnt, Fz or interactors of the canonical pathway, which may have potential therapeutic value in the treatment of cancers and other diseases.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".