High in vivo levels of adipsin lead to increased knee tissue degradation in osteoarthritis: data from humans and animal models
Bibliographic record
Abstract
Objective: This study explored the role of the adipokine adipsin in OA. Methods: Control and OA articular tissues, cells and serum were obtained from human individuals. Serum adipsin levels of human OA individuals were compared with cartilage volume loss as assessed by MRI at 48 months. Human adipsin expression was determined by PCR, its production in tissues by immunohistochemistry, and in SF and serum by a specific assay. OA was surgically induced in wild-type (Df+/+) and adipsin-deficient (Df-/-) mice, and synovial membrane and cartilage processed for histology and immunohistochemistry. Results: Adipsin levels were significantly increased in human OA serum, SF, synovial membrane and cartilage compared with controls, but the expression was similar in chondrocytes, synoviocytes and osteoblasts. Multivariate analysis demonstrated that human serum adipsin levels were significantly associated (P = 0.045) with cartilage volume loss in the lateral compartment of the knee. Destabilization of the medial meniscus-Df-/- mice showed a preservation of the OA synovial membrane and cartilage lesions (P ⩽ 0.026), the latter corroborated by the decreased production of cartilage degradation products and proteases (P ⩽ 0.047). The adipsin effect is likely due to a deficient alternative complement pathway (P ⩽ 0.036). Conclusion: In human OA, higher serum adipsin levels were associated with greater cartilage volume loss in the lateral compartment, and adipsin deficiency led to a preservation of knee structure. Importantly, we documented an association between adipsin and OA synovial membrane and cartilage degeneration through the activation of the complement pathway. This study highlights the clinical relevance of adipsin as a valuable biomarker and potential therapeutic target for OA.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".