Peroxisome proliferator-activated receptor gamma in osteoarthritis
Bibliographic record
Abstract
Osteoarthritis (OA) is among the most prevalent chronic human health disorders and the most common form of arthritis. It is a leading cause of disability in developed countries. This disease is characterized by cartilage deterioration, synovitis, and remodeling of the subchondral bone. There is not yet a satisfactory treatment to stop or arrest this disease process. Although several candidates for therapeutic approaches have been put forward, recent studies suggest that activation of the transcription factor peroxisome proliferator-activated receptor gamma (PPARγ) is an interesting target for this disease. PPARγ is a ligand-activated transcription factor and member of the nuclear receptor superfamily. Agonists of PPARγ inhibit inflammation and reduce synthesis of cartilage degradation products both in vitro and in vivo, and reduce the development/progression of cartilage lesions in OA animal models. This review will highlight the recent experimental studies on the presence of PPARγ in articular tissues and its effect on inflammatory and catabolic responses in chondrocytes and synovial fibroblasts, as well as the protective effects of PPARγ ligands in arthritis experimental models. Finally, the role of PPARγ polymorphism in the pathogenesis of OA and related musculoskeletal diseases will also be discussed.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".