IGF2 expression and β-catenin levels are increased in Frozen Shoulder Syndrome
Bibliographic record
Abstract
PURPOSE: Frozen Shoulder Syndrome is a fibrosis of the shoulder joint capsule that is clinically associated with Dupuytren's disease, a fibrosis of the palmar fascia. Little is known about any commonalities in the pathophysiology of these connective tissue fibroses. β-catenin, a protein that transactivates gene expression, and levels of IGF2 mRNA, encoding insulin-like growth factor-II, are elevated in Dupuytren's disease. The aim of this study was to determine if correlating changes in β-catenin levels and IGF2 expression are evident in Frozen Shoulder Syndrome. METHODS: Tissue from patients with Frozen Shoulder Syndrome and rotator cuff tear were obtained during shoulder arthroscopies. Total protein extracts were prepared from tissue aliquots and β-catenin immunoreactivity was assessed by Western immunoblotting. In parallel, primary fibroblasts were derived from these tissues and assessed for IGF2 expression by quantitative PCR. RESULTS: β-catenin levels were significantly increased in Frozen Shoulder Syndrome relative to rotator cuff tear when assessed by Western immunoblotting analyses. IGF2 mRNA levels were significantly increased in primary fibroblasts derived from frozen shoulder syndrome tissues relative to fibroblasts derived from rotator cuff tissues. CONCLUSIONS: As in Dupuytren's disease, β-catenin levels and IGF2 expression are elevated in Frozen Shoulder Syndrome. These findings support the hypothesis that these connective tissue fibroses share a common pathophysiology.
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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 | 0.001 | 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) | 0.002 | 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".