Elevated Dickkopf-2 levels contribute to the abnormal phenotype of human osteoarthritic osteoblasts
Bibliographic record
Abstract
The Wnt signaling pathway is crucial for osteogenesis and regulates terminal osteoblast differentiation. Although osteoarthritic (OA) osteoblasts show an abnormal phenotype and poor in vitro mineralization, the mechanism leading to this situation still remains unknow. Recent evidence indicates that Wnt signaling may be altered in OA osteoblasts. In this study we determined whether an alteration of the Wnt/β-catenin signaling pathway is responsible for the abnormal phenotype of OA osteoblasts. Expression of the Wnt signaling antagonist Dickkopf-1 (DKK1) was similar in normal and OA osteoblasts, whereas DKK2 expression was higher in OA osteoblasts than in normal osteoblasts. OA osteoblasts showed a decrease of Wnt3a-dependent Wnt/β-catenin signaling, measured by the TOPflash reporter assay and by Western blot analysis, compared with normal osteoblasts. Correcting DKK2 levels in OA osteoblasts by siRNA techniques enhanced Wnt/β-catenin signaling. Elevated DKK2 levels could be explained by elevated transforming growth factor β1 (TGF-β1) in OA osteoblasts, and exogenous TGF-β1 increased DKK2 expression in normal osteoblasts, whereas ablating TGF-β1 expression in OA osteoblasts reduced DKK2 expression. Inhibiting TGF-β1 or DKK2 expression corrected the abnormal phenotype of OA osteoblasts. In vitro mineralization of OA osteoblasts also was increased by DKK2 siRNA. We conclude that elevated TGF-β1 levels in OA osteoblasts can stimulate DKK2 expression, which, in turn, is responsible, at least in part, for their abnormal phenotype.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".