Effect of autotaxin inhibition in a surgically-induced mouse model of osteoarthritis
Bibliographic record
Abstract
Objective: Osteoarthritis (OA) is a degenerative joint disease with no approved disease modifying therapy. The enzyme autotaxin (ATX) converts lysophoshatidylcholine analogues to lysophosphatidic acid. Systemic inhibition of ATX reduces pain in animal models of OA; however, OA disease-modifying effects associated with ATX inhibition remain unknown. Here, we sought to determine whether local (knee joint) injection of an ATX inhibitor attenuates surgically-induced OA in mice. Methods: ATX expression was evaluated in human knee OA cartilage. Ten-week-old mice were subjected to surgically-induced OA. ATX inhibitor (PF-8380, 2.5ng/joint) was injected intra-articularly either at three and five weeks post-surgery or at two, four, six and eight weeks post-surgery and knee joints were evaluated by histopathology and immunohistochemistry to study the expression of catabolic and cell death markers. mRNA sequencing of human OA chondrocytes treated with/without ATX inhibitor was performed to identify differentially expressed transcripts, followed by pathway enrichment analysis. Results: ATX expression was elevated in severely degenerated cartilage compared to less degenerated human OA cartilage. In surgically-induced OA mice, intra-articular injection of ATX inhibitor at three and five weeks post-surgery partially protected knee joints from cartilage degeneration. Interestingly, earlier and more frequent ATX inhibitor injections did not confer significant protection. Immunohistochemical analysis showed decreased expression of catabolic and apoptotic markers with two ATX inhibitor injections. mRNA sequencing followed by pathway analysis identified pathways related to cholesterol analogue metabolism and cell-cycle that could be modulated by ATX inhibition in human OA chondrocytes. Conclusion: Local delivery of ATX inhibitor partially attenuates surgically-induced OA in mice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".