Impaired Efferocytosis by Synovial Macrophages in Patients With Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Osteoarthritis (OA) exposes all joint tissues to physiologic stresses, increasing the need to clear apoptotic cells from tissues, including the synovium. We undertook this study to assess the burden of apoptotic cells in synovial tissue in patients with late-stage knee OA and to investigate whether OA impairs the macrophage-mediated clearance of apoptotic cells via efferocytosis. METHODS: Synovial tissue was collected from individuals with healthy knees and patients with late-stage knee OA during arthroplasty. Synovial apoptotic cell burden was assessed by immunofluorescence for cleaved caspase 3. Efferocytosis of apoptotic Jurkat cells by CD14+ synovial tissue macrophages and peripheral blood-derived macrophages was quantified using immunofluorescence microscopy. Effects of OA on macrophage-mediated efferocytosis were modeled by stimulating blood-derived macrophages with synovial fluid collected from individuals with healthy knees and patients with early- or late-stage knee OA. RESULTS: Patients with late-stage knee OA had more apoptotic synovial cells compared to healthy individuals. There was a marked reduction in the fraction of synovial tissue macrophages engaging in efferocytosis and the quantity of material efferocytosed by individual macrophages in OA patients. Blood-derived macrophages exposed to synovial fluid from patients with knee OA recapitulated the defective efferocytosis, with the greatest effect from patients with early-stage knee OA and higher disease activity (pain and inflammation). CONCLUSION: Apoptotic cells accumulate in the synovium of patients with late-stage knee OA. Our results suggest that OA impairs critical homeostatic functions of synovial macrophages, leading to accumulation of apoptotic cells.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".