RANK-RANKL-OPG in Hemophilic Arthropathy: From Clinical and Imaging Diagnosis to Histopathology
Bibliographic record
Abstract
OBJECTIVE: Hemarthrosis triggers hemophilic arthropathy, involving the target joints. The histopathogenesis of blood-induced joint damage remains unclear. The triad of receptor activator of nuclear factor-κB (RANK), RANK ligand (RANKL), and osteoprotegerin (OPG; RANK-RANKL-OPG) controls bone turnover. Our aim was to evaluate RANK-RANKL-OPG expression in the synovium of hemophilic patients with severe arthropathy. METHODS: Synovial biopsies were obtained from 18 patients with hemophilic arthropathy and 16 with osteoarthritis (OA) who were undergoing total knee replacement and synovectomy. The severity of hemophilic arthropathy was evaluated according to ultrasonography score, the World Federation of Hemophilia (WFH) orthopedic joint scale, and the radiographic Pettersson score. RANK-RANKL-OPG expression was examined by immunohistochemistry and Western blotting. Serum levels of soluble RANKL (sRANKL) and OPG from an extended group of 67 patients with hemophilic arthropathy and 30 healthy controls were measured by ELISA. RESULTS: The mean ultrasonography, WFH orthopedic joint scale, and Pettersson scores in patients with hemophilic arthropathy indicated severe arthropathy. A decreased expression of OPG was found in hemophilic arthropathy synovium compared with patients with OA. RANK and RANKL immunopositivity was strong in the lining and sublining layers in hemophilic arthropathy synovial tissue. Western blotting confirmed the immunohistological findings. Serum levels of sRANKL and OPG in patients with hemophilia were lower than in healthy controls. CONCLUSION: In hemophilic arthropathy, the synovium highly expressed RANK and RANKL, whereas OPG immunopositivity decreased, suggesting an osteoclastic activation. Low tissue expression of OPG paralleled the serum levels of this protein and the severity of hemophilic arthropathy assessed by ultrasonography, Pettersson, and WFH orthopedic joint scale scores.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".