PPARγ deficiency results in severe, accelerated osteoarthritis associated with aberrant mTOR signalling in the articular cartilage
Bibliographic record
Abstract
OBJECTIVES: We have previously shown that peroxisome proliferator-activated receptor gamma (PPARγ), a transcription factor, is essential for the normal growth and development of cartilage. In the present study, we created inducible cartilage-specific PPARγ knockout (KO) mice and subjected these mice to the destabilisation of medial meniscus (DMM) model of osteoarthritis (OA) to elucidate the specific in vivo role of PPARγ in OA pathophysiology. We further investigated the downstream PPARγ signalling pathway responsible for maintaining cartilage homeostasis. METHODS: Inducible cartilage-specific PPARγ KO mice were generated and subjected to DMM model of OA. We also created inducible cartilage-specific PPARγ/mammalian target for rapamycin (mTOR) double KO mice to dissect the PPARγ signalling pathway in OA. RESULTS: Compared with control mice, PPARγ KO mice exhibit accelerated OA phenotype with increased cartilage degradation, chondrocyte apoptosis, and the overproduction of OA inflammatory/catabolic factors associated with the increased expression of mTOR and the suppression of key autophagy markers. In vitro rescue experiments using PPARγ expression vector reduced mTOR expression, increased expression of autophagy markers and reduced the expression of OA inflammatory/catabolic factors, thus reversing the phenotype of PPARγ KO mice chondrocytes. To dissect the in vivo role of mTOR pathway in PPARγ signalling, we created and subjected PPARγ-mTOR double KO mice to the OA model to see if the genetic deletion of mTOR in PPARγ KO mice (double KO) can rescue the accelerated OA phenotype observed in PPARγ KO mice. Indeed, PPARγ-mTOR double KO mice exhibit significant protection/reversal from OA phenotype. SIGNIFICANCE: PPARγ maintains articular cartilage homeostasis, in part, by regulating mTOR pathway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".