Quantification of Cells Expressing Mesenchymal Stem Cell Markers in Healthy and Osteoarthritic Synovial Membranes
Bibliographic record
Abstract
OBJECTIVE: To quantify cells expressing mesenchymal stem cell (MSC) markers in synovial membranes from human osteoarthritic (OA) and healthy joints. METHODS: Synovial membranes from OA and healthy joints were digested with collagenase and the isolated cells were cultured. Synovial membrane-derived cells were phenotypically characterized for differentiation experiments using flow cytometry to detect the expression of mesenchymal markers (CD29, CD44, CD73, CD90, CD105, CD117, CD166, and STRO-1) and hematopoietic markers (CD34 and CD45). Chondrogenesis was assessed by staining for proteoglycans and collagen type II, adipogenesis by using a stain for lipids, and osteogenesis by detecting calcium deposits. Coexpression of CD44, CD73, CD90, and CD105 was determined using immunofluorescence. RESULTS: Cells expressing MSC markers were diffusely distributed in OA synovial membranes; in healthy synovial membrane these cells were localized in the subintimal zone. More numerous MSC markers in OA synovial membranes were observed in cells also expressing the CD90 antigen. FACS analysis showed that more than 90% of OA synovial membrane-derived cells were positive for CD44, CD73, and CD90, and negative for CD34 and CD45. OA synovial membrane-derived cells were also positive for CD29 (85.23%), CD117 (72.35%), CD105 (45.5%), and STRO-1 (49.46%). Micropellet analyses showed that the culture of cells with transforming growth factor-ß3 stimulated proteoglycan and collagen type II synthesis. CONCLUSION: Synovial membranes from patients with OA contain more cells positive for CD44, CD90, and CD105 antigens than those from joints with undamaged cartilage.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".