Transforming growth factor α suppression of articular chondrocyte phenotype and <i>Sox9</i> expression in a rat model of osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To define the roles of transforming growth factor alpha (TGFalpha) in cartilage degradation. METHODS: Primary rat articular chondrocytes and articular osteochondral explants were cultured with TGFalpha to assess the effects of TGFalpha on chondrocyte physiology and phenotype. RESULTS: TGFalpha altered chondrocyte morphology through reorganization of the actin cytoskeleton and formation of stress fibers. Expression of anabolic genes, including aggrecan, type II collagen, and cartilage link protein, was reduced in response to TGFalpha. Proliferation of chondrocytes and formation of articular chondrocyte clusters was stimulated by TGFalpha. Expression of matrix metalloproteinase 13 and cathepsin C was increased by TGFalpha. We demonstrated the down-regulation of Sox9 messenger RNA and protein levels by TGFalpha. This was associated with reduced levels of phosphorylated and total SOX9 in cartilage explants upon TGFalpha treatment. In contrast, another growth factor identified in our microarrays, Kitl, had no effects on the chondrocyte parameters tested. To examine correlations between the increased levels of TGFalpha in experimental knee osteoarthritis (OA) with the levels of TGFalpha in humans with knee OA, a microarray analysis of mRNA from 13 normal and 12 late-stage OA cartilage samples was performed. Seven OA samples showed TGFA mRNA levels similar to those in the normal controls, but expression was markedly increased in the other 5 OA samples. These data confirm that TGFA transcript levels are increased in a subset of patients with OA. CONCLUSION: This study adds TGFalpha to the list of dysregulated cytokines present in degrading cartilage in OA. Since TGFalpha inhibits articular chondrocyte anabolic capacity, increases catabolic factors, and contributes to the development of chondrocyte clusters, TGFalpha may be a potential target for therapeutic strategies in the treatment of OA.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".