Lubricin/Proteoglycan 4 Binding to CD44 Receptor: A Mechanism of the Suppression of Proinflammatory Cytokine–Induced Synoviocyte Proliferation by Lubricin
Bibliographic record
Abstract
OBJECTIVE: To evaluate the binding of recombinant human proteoglycan 4 (rhPRG4) to CD44 receptor and its consequences on cytokine-induced synoviocyte proliferation. METHODS: The binding of rhPRG4 to CD44 and competition with high molecular weight (HMW) hyaluronic acid (HA) was evaluated using a direct enzyme-linked immunosorbent assay (ELISA) and surface plasmon resonance. Sialidase A and O-glycosidase digestion of rhPRG4 was performed, and CD44 binding was evaluated using ELISA. Rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS) were stimulated with interleukin-1β (IL-1β) or tumor necrosis factor α (TNFα) for 48 hours in the presence or absence of rhPRG4 or HMW HA at 20, 40, and 80 μg/ml, and cell proliferation was measured. The contribution of CD44 was assessed by coincubation with a CD44 antibody (IM7). The antiproliferative effect of rhPRG4 was investigated following treatment of PRG4(-/-) mouse synoviocytes with IL-1β or TNFα in the presence or absence of IM7. RESULTS: Recombinant human PRG4 bound CD44 and interfered with the binding of HMW HA to CD44. Removal of sialic acid and O-glycosylations significantly increased CD44 binding by rhPRG4 (P < 0.001). Both rhPRG4 and HMW HA at 40 and 80 μg/ml significantly suppressed IL-1β-induced proliferation of RA FLS (P < 0.05). Recombinant human PRG4 at 20, 40, and 80 μg/ml significantly suppressed TNFα-induced RA FLS proliferation (P < 0.05). CD44 neutralization reversed the effect of rhPRG4 on IL-1β- and TNFα-stimulated RA FLS and the effect of HMW HA on IL-1β-stimulated RA FLS. Recombinant human PRG4 inhibited cytokine-induced proliferation of PRG4(-/-) synoviocytes, which could be prevented by blocking CD44. CONCLUSION: PRG4 (lubricin) is a novel putative ligand for CD44 and may control synoviocyte overgrowth in inflammatory arthropathies via a CD44-mediated mechanism.
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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) | 0.001 | 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) | 0.002 | 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".