Constitutive Activation of β-Catenin in Differentiated Osteoclasts Induces Bone Loss in Mice
Bibliographic record
Abstract
BACKGROUND/AIMS: Activation of the Wnt/β-catenin signalling pathway has been widely investigated in bone biology and shown to promote bone formation. However, its specific effects on osteoclast differentiation have not been fully elucidated. Our study aimed to identify the role of β-catenin in osteoclastogenesis and bone homeostasis. METHODS: In the present study, exon 3 in the β-catenin gene (Ctnnb1) allele encoding phosphorylation target serine/threonine residues was flanked by floxP sequences. We generated mice exhibiting conditional β-catenin activation (Ctsk-Cre;Ctnnb1flox(exon3)/+, designated CA-β-catenin) by crossing Ctnnb1flox(exon3)/flox(exon3) mice with osteoclast-specific Ctsk-Cre mice. Bone growth and bone mass were analysed by micro-computed tomography (micro-CT) and histomorphometry. To further examine osteoclast activity, osteoclasts were induced from bone marrow monocytes (BMMs) isolated from CA-β-catenin and Control mice in vitro. Osteoclast differentiation was detected by tartrate-resistant acid phosphatase (TRAP) staining, immunofluorescence staining and reverse transcription-quantitative PCR (RT-qPCR) analysis. RESULTS: Growth retardation and low bone mass were observed in CA-β-catenin mice. Compared to controls, CA-β-catenin mice had significantly reduced trabecular bone numbers under growth plates as well as thinner cortical bones. Moreover, increased TRAP-positive osteoclasts were observed on the surfaces of trabecular bones and cortical bones in the CA-β-catenin mice; consistent results were observed in vitro. In the CA-β-catenin group, excessive numbers of osteoclasts were induced from BMMs, accompanied by the increased expression of osteoclast-associated marker genes. CONCLUSION: These results indicated that the constitutive activation of β-catenin in osteoclasts promotes osteoclast formation, resulting in bone loss.
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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 | 0.000 | 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 | 0.001 |
| 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".