Involvement of CD44 in induction of matrix metalloproteinases by a COOH‐terminal heparin‐binding fragment of fibronectin in human articular cartilage in culture
Bibliographic record
Abstract
OBJECTIVE: To investigate the mechanism of induction of matrix metalloproteinases (MMPs) by a 40-kd COOH-terminal heparin-binding fibronectin fragment (HBFN-f) containing III12-14 and IIICS domains in human articular cartilage in culture. METHODS: Human articular cartilage was removed from macroscopically normal femoral heads and cultured with HBFN-f. MMP secretion into conditioned media was analyzed by immunoblotting (MMPs 1 and 13) and by gelatin zymography (MMPs 2 and 9). Type II collagen cleavage by collagenase was monitored in culture by immunoassay. Involvement of specific peptide-binding domains in HBFN-f and the involvement of CD44 were assessed with synthetic peptides and an anti-CD44 antibody. Immunofluorescence histochemistry was performed using fluorescein isothiocyanate-conjugated anti-CD44 antibody. RESULTS: HBFN-f stimulated production of MMPs 1, 2, 9, and 13 in association with type II collagen cleavage by collagenase in human articular cartilage. Peptide V (WQPPRARI) of HBFN-f, which can bind cell surface heparan sulfate proteoglycan (HSPG), blocked MMP induction by HBFN-f, while the scrambled peptide V (RPQIPWAR) had no effect. Peptide CS-1 of 25 amino acids in IIICS of HBFN-f caused no significant effect. Treatment of cartilage with anti-CD44 antibody or HSPG resulted in significant inhibition of HBFN-f-stimulated MMP production. Preincubation with peptide V blocked binding of the anti-CD44 antibody to chondrocytes in cartilage. CONCLUSION: Interaction of the peptide V sequence in HBFN-f with glycosaminoglycans, such as those in CD44, plays an important role in HBFN-f-stimulated MMP production in articular cartilage. Because CD44 is up-regulated in osteoarthritic and rheumatoid arthritic cartilage, the role of the interaction between CD44 and HBFN-f in these pathologies should be of relevance and should be studied further.
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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 | 0.000 | 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) | 0.001 | 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".