The roles of matrix molecules in mediating chondrocyte aggregation, attachment, and spreading
Bibliographic record
Abstract
The most abundant macromolecules in cartilage are hyaluronan, collagen, aggrecan, and link protein, which are believed to play roles in maintaining a unique three-dimensional network for a functional joint. This study was designed to investigate the roles of the major extracellular molecules in mediating chondrocyte-matrix interactions. We employed specific approaches to remove components individually or in combination: hyaluronan was digested with hyaluronidase; type II collagen was digested with collagenase; aggrecan expression was inhibited with antisense and beta-xyloside approaches; and link protein expression was inhibited with antisense oligonucleotides. Digestion of hyaluronan induced chondrocyte attachment to tissue culture plates, collagen-coated plates, and fibroblast-like chondrocyte cultures, and induced chondrocyte aggregation. Treated chondrocytes exhibited a fibroblast-like morphology, and the effects of hyaluronidase were dose-dependent. Conversely, the effect of collagenase on chondrocyte adhesion and aggregation was far less pronounced. Treatment with Arg-Gly-Asp peptide inhibited chondrocyte-collagen interaction. Chondrocyte attachment was enhanced by antisense oligonucleotides complementary to aggrecan and link protein and by beta-xyloside treatment. Nevertheless, hyaluronan seems to predominate over the other molecules in mediating chondrocyte-matrix interactions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".