Anabolic phenotype in cartilage-specific Mitogen-inducible gene-6 knockout mice is independent of Transforming growth factor- <i>α</i>
Bibliographic record
Abstract
Abstract Background/Objective Osteoarthritis (OA) is a whole joint disorder with no disease modifying treatment currently available. The Epidermal Growth Factor Receptor (EGFR) signaling pathway plays an important role in cartilage/bone development and its ligand transforming growth factor- α (TGl· α ) is upregulated in OA. In contrast, Mitogen-inducible gene 6 (Mig6) is a negative regulator of EGFR, and our studies demonstrate that cartilage-specific Mig-6 deletion results in anabolic effects on cartilage and formation of chondro-osseus nodules (CON). We aimed to attenuate EGFR signaling by inhibiting TGF α production in cartilage-specific Mig6 deficient mice, to test whether this would prevent the formation of CONs. Methods We generated double knockout mice by crossing cartilage-specific Mig-6 fl/fl Col2a1-Cre +/- and whole-body Tgfa +/- mice to generate experimental and control wild-type mice. Knee and elbow sections were stained with toluidine blue to examine articular cartilage thickness and cell density, and tartrate-resistant acid phosphatase for osteoclast activity. Additionally, immunohistochemistry was completed to analyze phospho-EGFR and SOX9. Results Mig-6 deficient mice display cartilage thickening and CONs at 12 weeks in both the elbow and knee joints, which is independent of TGF α ligand presence. Similarly, articular cartilage cell density is increased in Mig-6 fl/fl Col2a1-Cre +/- Tgfa -/- and Mig-6 fl/fl Col2al-Cre +/- mice, but not Tgfa -/- mice, and displays increased SOX9 and phospho-EGFR staining. Conclusion The articular cartilage displays increased thickness, increased cell density, and CON formation independent of the presence of TGF α , suggesting the anabolic phenotype in the Mig6-deficient mice is independent of TGF α /EGFR binding. The anabolic phenotype may be due to an alternative EGFR ligand activation, or perhaps due to other non-EGFR specific mechanism. More research is required to elucidate the exact pathway responsible for the anabolic effects.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".