Pericellular Matrix Proteoglycan Content is Less Affected in The Mid-Zone Cartilage in Early Post-Traumatic Osteoarthritis
Bibliographic record
Abstract
Abstract Proteoglycan content changes in articular cartilage during post-traumatic osteoarthritis affect both chondrocyte biomechanics and tissue health. Previously, we found that four weeks after anterior cruciate ligament transection (ACLT) in rabbits, proteoglycan loss was less pronounced in the pericellular matrix (PCM) than in the extracellular matrix (ECM), resulting in a greater PCM-to-ECM proteoglycan content ratio compared to controls. Here, we investigate whether this pattern is already present two weeks post-ACLT and whether changes in the proteoglycan ratio relate to cell volumetric strain in the superficial zone during tissue loading. Unilateral ACLT was performed in eight skeletally mature rabbits. Two weeks post-surgery, cartilage from all load-bearing sites of the operated and contralateral knees were collected. Age-matched, non-operated knees from separate animals served as controls. Proteoglycan content in the chondrocyte microenvironment was analyzed in the superficial and middle zones of cartilage via digital densitometry. Volumetric strain of superficial zone cells was measured using two-photon confocal microscopy during indentation. In the superficial zone, the PCM-to-ECM proteoglycan content ratio was greater in the ACLT knees than in controls for the lateral tibial plateau ( p = 0.043). However, this was not clearly linked to changes in cell volumetric strain. Interestingly, in the middle zone, the PCM-to-ECM proteoglycan content ratio was greater in the ACLT knees than in controls for the medial femoral condyle, femoral groove, and patella ( p < 0.05). These results suggest that, in early post-traumatic osteoarthritis, proteoglycan loss is less severe in the PCM than in the ECM, especially in the middle cartilage zone.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".