Muscular loading of joints triggers cellular secretion of PRG4 into the joint fluid
Bibliographic record
Abstract
We developed a novel testing system that allows quantification of joint loading and permits analysis of changes in total protein and PRG4 contents in joint fluid of intact knees in live mice. A sequence of 15 repeat, isometric muscular contractions of "low" intensity (less than 50% of the maximal isometric muscular force), and "high" intensity (greater than 55% of maximal) were applied repeatedly (up to five times with a 15 min rest between contractions) to the mouse knee. Increases in knee joint loading were accompanied with significant increases in total protein (p<0.0001) and PRG4 concentrations in the synovial fluid. Total protein and PRG4 concentrations decreased with repeated "high" intensity loading. However, the addition of cell secretion inhibitors to the knee prior to muscular loading resulted in PRG4 levels that remained below the detection limit for all loading conditions. These results suggest that changes in synovial fluid proteins and PRG4 concentrations upon joint loading are mediated by cells within the joint, and that these changes may be used as quantitative indicators for the intensity and duration of acute joint loading, and might serve as a powerful clinical tool to assess the effectiveness of rehabilitation and prevention exercise programs.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".