Progranulin regulation of autophagy contributes to its chondroprotective effect in osteoarthritis
Bibliographic record
Abstract
Progranulin (PGRN) is a multifunctional growth factor involved in many physiological processes and disease states. The apparent protective role of PGRN and the importance of chondrocyte autophagic function in the progression of osteoarthritis (OA) led us to investigate the role of PGRN in the regulation of chondrocyte autophagy. PGRN knockout chondrocytes exhibited a deficient autophagic response with limited induction following rapamycin, serum starvation, and IL-1β-induced autophagy. PGRN-mediated anabolism and suppression of IL-1β-induced catabolism were largely abrogated in the presence of the BafA1 autophagy inhibitor. Mechanistically, during the process of OA, PGRN and the ATG5-ATG12 conjugate form a protein complex; PGRN regulates autophagy in chondrocytes and OA through, at least partially, the interactions between PGRN and the ATG5-ATG12 conjugate. Furthermore, the ATG5-ATG12 conjugate is critical for cell proliferation and apoptosis. Knockdown or knockout of ATG5 reduces the expression of ATG5-ATG12 conjugate and inhibits the chondroprotective effect of PGRN on anabolism and catabolism. Overexpression of PGRN partially reversed this effect. In brief, the PGRN-mediated regulation of chondrocyte autophagy plays a key role in the chondroprotective role of PGRN in OA. Such studies provide new insights into the pathogenesis of OA and PGRN-associated autophagy in chondrocyte homeostasis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".