The Effects of Naproxen on Chondrogenesis of Human Mesenchymal Stem Cells
Bibliographic record
Abstract
Currently, there are no established treatments to prevent, stop, or even retard the degeneration of articular cartilage in osteoarthritis (OA). Biological repair of the degenerating articular cartilage would be preferable to surgery. There is no benign site where autologous chondrocytes can be harvested and used as a cell source for cartilage repair, leaving mesenchymal stem cells (MSCs) as an attractive option. However, MSCs from OA patients have been shown to constitutively express collagen type X (COL-X), a marker of late-stage chondrocyte hypertrophy. We recently found that naproxen (Npx), but not other nonsteroidal anti-inflammatory drugs, can induce collagen type X alpha 1 (COL10A1) gene expression in bone marrow-derived MSCs from healthy and OA donors. In this study, we determined the effect of Npx on COL10A1 expression and investigated the intracellular signaling pathways that mediate such effect in normal human MSCs during chondrogenesis. MSCs were cultured in standard chondrogenic differentiation media supplemented with or without Npx. Our results show that Npx can regulate chondrogenic differentiation by affecting the gene expression of both Indian hedgehog and parathyroid hormone/parathyroid hormone-related protein signaling pathways in a time-dependent manner, suggesting a complex interaction of different signaling pathways during the process.
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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 | 0.000 | 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) | 0.002 | 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".