Bioregulation of lubricin expression by growth factors and cytokines
Bibliographic record
Abstract
Lubricin, also commonly referred to as superficial zone protein (SZP) and proteoglycan 4 (PRG4), is a multifaceted, cytoprotective glycoprotein that contributes to the boundary lubrication properties facilitating low friction levels at interfacing surfaces of articular cartilage. Biological processes effecting the gain or loss of lubricin function may therefore have important consequences relevant to joint physiology and pathology. Herein, we describe experiments conducted to extend our understanding of the influence of various cytokines and growth factors on lubricin gene expression and protein secretion in synovial tissues. Exposure of synoviocytes, chondrocytes and cartilage explants to proinflammatory cytokines such as interleukin-1 (IL-1) and tumor necrosis factor-alpha (TNF-alpha) results in a marked reduction in the expression and/or abundance of secreted lubricin, with corresponding alterations in the amounts of cartilage-associated (boundary) lubricin. Conversely, treatment with transforming growth factor-beta (TGF-beta) significantly upregulates lubricin synthesis, secretion and cartilage boundary association. Oncostatin M also appears to be capable of modulating lubricin metabolism, with the potential to induce lubricin synthesis by chondrocytes. Collectively, the results of studies on cytokine and growth factor regulation of lubricin biosynthesis and biodistribution may help provide new insights and therapeutic perspectives for promoting joint function.
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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".