Femur Shape Changes in Prg4‐Deficient Mice: Morphological Insights Into Joint Well‐Being
Bibliographic record
Abstract
ABSTRACT Many studies have reported on the role of Proteoglycan‐4 (PRG4, aka lubricin) in the reduction of friction between cartilage surfaces with a specific focus on chondroprotection within the joint. Disruption of the Prg4 gene in humans and mice leads to premature joint failure, hallmarked by synovial hyperplasia and premature articular cartilage fibrillation. Our group has published extensively using Prg4 knockout mice and has consistently noticed variable distal femoral morphology in these animals when compared to Prg4 +/+ wild‐types (WT). This prompted us to undertake a quantitative study examining joint element size and shape to elucidate if this phenotype was consistent in a larger sample size. High‐resolution X‐ray microscopy (XRM) images were obtained from WT and Prg4 −/− mice between 8‐ and 36 weeks of age. We then employed geometric morphometrics to characterize mouse femora shape changes, which were correlated to cross‐sectional histological findings. We find that Prg4 −/− femora vary in size and shape compared to WT controls; distal femora in Prg4 −/− mice are enlarged, extended (anteroposterior) and narrower (mediolateral), with the largest regional deviations being traced to the trochlear groove, epicondyles, and medial condyle. Additionally, quantifiable changes in condylar articular cartilage thickness were associated with abnormal compressive biomechanical properties. Collectively, these data suggest that PRG4 loss extends beyond joint homeostasis and critically impacts joint morphology.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".