Identification of two populations of osteoarthritic osteoblasts according to the 1,25[OH] <sub>2</sub> vitamin D <sub>3</sub> potency to stimulate osteocalcin
Bibliographic record
Abstract
INTRODUCTION: Few studies have tried to discriminate a differential behavior between osteoarthritic (OA) osteoblasts (Obs). Based on osteocalcin level, we aimed, in the present study, to evaluate the capacity of OA Obs for producing molecules of the Wnt/β-catenin signaling pathway. METHODS: Human primary OA Obs (n=11) were exposed or not to 50 nM of 1,25 dihydroxyvitamin D3 (VitD3) for 24 h. Osteocalcin (OCN), TGF-β1, Dickkopf-related protein 2 (DKK2), R-spondin 2 (Rspo2), Wnt5b, and low density lipoprotein related-receptor 1 (LRP1) were evaluated by real time RT-PCR. RESULTS: All samples responded to VitD3 as validated by the increase in OCN expression. However two populations of Obs were discriminated; one called "high responders" whose OCN stimulation was higher than 100 fold (mean 881 fold, p<0.01, n=5) and the second one whose stimulation was inferior to 100 fold (mean 47 fold, p<0.01, n=6), namely "low responders". In fact, high responders have a weaker basal expression of OCN. With regards to these two cell populations and in absence of VitD3 challenge, the expression level of TGF-β1 (15 fold, p<0.001), DKK2 (2.5 fold, p<0.002) and Wnt5b (5.5 fold, p<0.003) was higher in "high responders", meanwhile Rspo2 and LRP1 expression was unchanged. VitD3 exacerbated this pattern but corrected OCN expression and favored Wnt agonist expression. CONCLUSION: We identified 2 populations of OA Obs according to the OCN expression under the control of VitD3. In addition under basal conditions, these 2 populations expressed differently TGF-β1, Wnt5b, DKK2, suggesting a heterogeneous differentiation and phenotype in Obs among OA patients.
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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) | 0.002 | 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".