Exacerbation of Aging‐Associated and Instability‐Induced Murine Osteoarthritis With Deletion of D Prostanoid Receptor 1, a Prostaglandin D <sub>2</sub> Receptor
Bibliographic record
Abstract
Objective D prostanoid receptor 1 (DP1), a receptor for prostaglandin D 2 , plays important roles in inflammation and cartilage metabolism. However, its role in the pathogenesis of osteoarthritis (OA) remains unknown. This study was undertaken to explore the roles of DP1 in the development of OA in murine models and to evaluate the efficacy of a DP1 selective agonist in the treatment of OA. Methods The development of aging‐associated OA and destabilization of the medial meniscus (DMM)–induced OA was compared between DP1‐deficient (DP1 −/− ) and wild‐type (WT) mice. The progression of OA was assessed by histology, immunohistochemistry, and micro–computed tomography. Cartilage explants from DP1 −/− and WT mice were treated with interleukin‐1α (IL‐1α) ex vivo, to evaluate proteoglycan degradation. The effect of intraperitoneal administration of the DP1 selective agonist BW245C on OA progression was evaluated in WT mice. Results Compared to WT mice, DP1 −/− mice had exacerbated cartilage degradation in both models of OA, and this was associated with increased expression of matrix metalloproteinase 13 and ADAMTS‐5. In addition, DP1 −/− mice demonstrated enhanced subchondral bone changes. Cartilage explants from DP1 −/− mice showed enhanced proteoglycan degradation following treatment with IL‐1α. Intraperitoneal injection of BW245C attenuated the severity of DMM‐induced cartilage degradation and bony changes in WT mice. Conclusion These findings indicate a critical role for DP1 signaling in OA pathogenesis. Modulation of the functions of DP1 may constitute a potential therapeutic target for the development of novel OA treatments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".