INCREASED LEVELS OF APOPTOSIS AND P53 IN PARTIAL-THICKNESS SUPRASPINATUS TENDON TEARS
Bibliographic record
Abstract
Introduction The role of apoptosis in the progression of rotator cuff tendinopathy is poorly understood. The primary aim of this study was to quantify the amount of apoptosis in supraspinatus tendons presenting partial-thickness tears and matched intact subscapularis tendons. Methods 9 partially torn supraspinatus tendons and matched intact subscapularis tendons were biopsied and compared to 10 reference subscapularis tendon samples. Immunohistochemistry was used to assess apoptotic cells (activated caspase-3; Asp175), proliferation (Ki67) and p53 (M7001), a key protein involved in regulating cell death. The Bonar scale was used to evaluate tendon degeneration. Results The partially torn supraspinatus tendons and matched subscapularis tendons demonstrated a significant increase in the density of apoptotic cells and p53 expression. The Bonar score revealed significant tendon degeneration in the partially torn supraspinatus tendon compared to both matched and reference subscapularis tendon. The number of proliferating tendon cells was higher in the partially torn supraspinatus than in the matched or reference subscapularis tendons. Discussion The presence of increased apoptosis and p53 in partial-thickness tears of the supraspinatus tendon is accompanied by features of both degeneration as well as ongoing repair. Apoptosis may be a relatively early feature in the continuum of rotator cuff tendinopathy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".