Modulation of lubricin biosynthesis and tissue surface properties following cartilage mechanical injury
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of injurious compression on the biosynthesis of lubricin at different depths within articular cartilage and to examine alterations in structure and function of the articular surface following mechanical injury. METHODS: Bovine cartilage explants were subdivided into level 1, with intact articular surface, and level 2, containing middle and deep zone cartilage. Following mechanical injury, lubricin messenger RNA (mRNA) levels were monitored by quantitative reverse transcriptase-polymerase chain reaction, and soluble or cartilage-associated lubricin protein was analyzed by Western blotting and immunohistochemistry. Cartilage morphology was assessed by histologic staining, and tissue functionality was assessed by friction testing. RESULTS: Two days after injury, lubricin mRNA expression was up-regulated approximately 3-fold for level 1 explants and was down-regulated for level 2 explants. Lubricin expression in level 1 cartilage returned to control levels after 6 days in culture. Similarly, lubricin protein synthesis and secretion increased in response to injury for level 1 explants and decreased for level 2 cartilage. Histologic staining revealed changes in the articular surface of level 1 explants following injury, with respect to glycosaminoglycan and collagen content. Injured level 1 explants displayed an increased coefficient of friction relative to controls. CONCLUSION: Our findings indicate that increased lubricin biosynthesis appears to be an early transient response of surface-layer cartilage to injurious compression. However, distinct morphologic changes occur with injury that appear to compromise the frictional properties of the tissue.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".