FULL-THICKNESS SUPRASPINATUS TEARS DEMONSTRATE SIGNIFICANT DETERIORATION OF MUSCLE REGENERATIVE POTENTIAL
Bibliographic record
Abstract
Introduction Rotator cuff tendinopathy is a significant source of musculoskeletal disability. Accompanying muscle changes may be important determinants of the prognosis. The aim of this study was to compare histological muscle changes in partial-thickness to full-thickness tears of the supraspinatus tendon. Methods Muscle biopsies of nine partially torn and 15 fully torn supraspinatus tendons were compared histologically. H&E staining was performed to assess degenerative changes. Immunohistochemistry was used to assess slow and fast myosin heavy chains (type I and II fibres; Anti-slow skeletal myosin heavy chain antibody and Anti-fast skeletal myosin heavy chain antibody), satellite cells (CD56), proliferation (Ki67) and apoptotic cells (activated caspase-3; Asp175). Results Full-thickness tears demonstrated significant atrophy of both slow (type I) and fast (type II) myosin heavy chains compared to partial tears. The area ratio of type II to type I was doubled in full-thickness tears. Partial thickness tears revealed significantly more satellite cells and proliferative activity than full-thickness tears. There was no detectable apoptosis using an antibody recognising active caspase-3. Discussion Progression of rotator cuff tendinopathy is accompanied by a change in muscle fibre phenotype from endurance type I fibres to type II fibres more prone to fatigue, illustrating an aspect of muscle disuse. The rotator cuff muscle's ability to regenerate appears to be reduced when a full-thickness tear is established. Apoptosis does not appear to be of importance in muscle changes accompanying 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 | 0.000 |
| 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) | 0.004 | 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".