Both Hyaluronan and Collagen Type II Keep Proteoglycan 4 (Lubricin) at the Cartilage Surface in a Condition That Provides Low Friction during Boundary Lubrication
Bibliographic record
Abstract
Wear resistant and ultralow friction in synovial joints is the outcome of a sophisticated synergy between the major macromolecules of the synovial fluid, e.g., hyaluronan (HA) and proteoglycan 4 (PRG4), with collagen type II fibrils and other non-collagenous macromolecules of the cartilage superficial zone (SZ). This study aimed at better understanding the mechanism of PRG4 localization at the cartilage surface. We show direct interactions between surface bound HA and freely floating PRG4 using the quartz crystal microbalance with dissipation (QCM-D). Freely floating PRG4 was also shown to bind with surface bound collagen type II fibrils. Albumin, the most abundant protein of the synovial fluid, effectively blocked the adsorption of PRG4 with HA, through interaction with C and N terminals on PRG4, but not that of PRG4 with collagen type II fibrils. The above results indicate that collagen type II fibrils strongly contribute in keeping PRG4 in the SZ during cartilage articulation in situ. Furthermore, PRG4 molecules adsorbed very well on mimicked SZ of absorbed HA molecules with entangled collagen type II fibrils and albumin was not able to block this interaction. In this last condition PRG4 adsorption resulted in a coefficient of friction (COF) of the same order of magnitude as the COF of natural cartilage, measured with an atomic force microscope in lateral mode.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".