A novel negative regulatory mechanism of Smurf2 in BMP/Smad signaling in bone
Bibliographic record
Abstract
Abstract Transforming growth factor-β (TGF-β) and bone morphogenetic protein (BMP) play important roles in bone metabolism. Smad ubiquitination regulatory factors (Smurfs) regulate TGF-β/BMP signaling via ubiquitination, resulting in degradation of signaling molecules to prevent excessive activation of TGF-β/BMP signaling. Though Smurf2 has been shown to negatively regulate TGF-β/Smad signaling, its involvement in BMP/Smad signaling in bone metabolism has not been thoroughly investigated. In the present study, we sought to evaluate the role of Smurf2 in BMP/Smad signaling in bone metabolism. Absorbable collagen sponges containing 3 μg of recombinant human BMP2 (rhBMP2) were implanted in the dorsal muscle pouches of wild type (WT) and Smurf2 −/− mice. The rhBMP2-induced ectopic bone in Smurf2 − /− mice showed greater bone mass, higher mineral apposition and bone formation rates, and greater osteoblast numbers than the ectopic bone in WT mice. In WT mice, the ectopic bone consisted of a thin discontinuous outer cortical shell and scant inner trabecular bone. In contrast, in Smurf2 −/− mice, the induced bone consisted of a thick, continuous outer cortical shell and abundant inner trabecular bone. Additionally, rhBMP2 - stimulated bone marrow stromal cells (BMSCs) from Smurf2 −/− mice showed increased osteogenic differentiation. Smurf2 induced the ubiquitination of Smad1/5. BMP/Smad signaling was enhanced in Smurf2 −/− BMSCs stimulated with rhBMP2, and the inhibition of BMP/Smad signaling suppressed osteogenic differentiation of these BMSCs. These findings demonstrate that Smurf2 negatively regulates BMP/Smad signaling, thereby identifying a new regulatory mechanism in bone metabolism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".