Atrophy, inducible satellite cell activation, and possible denervation of supraspinatus muscle in injured human rotator-cuff muscle
Bibliographic record
Abstract
The high frequency of poor outcome and chronic pain after surgical repair of shoulder rotator-cuff injury (RCI) prompted this study to explore the potential to amplify muscle regeneration using nitric oxide (NO)-based treatment. After preoperative magnetic resonance imaging (MRI), biopsies of supraspinatus and ipsilateral deltoid (as a control) were collected during reparative surgery for RCI. Muscle fiber diameter, the pattern of neuromuscular junctions observed with alpha-bungarotoxin staining, and the γ:ε subunit ratio of acetylcholine receptors in Western blots were examined in tandem with experiments to determine the in vitro responsiveness of muscle satellite cells to activation (indicated by uptake of bromodeoxyuridine, BrdU) by the NO-donor drug, isosorbide dinitrate (ISDN). Consistent with MRI findings of supraspinatus atrophy (reduced occupation ratio and tangent sign), fiber diameter was lower in supraspinatus than in deltoid. ISDN induced a significant increase over baseline (up to 1.8-fold), in the proportion of BrdU+ (activated) Pax7+ satellite cells in supraspinatus, but not in deltoid, after 40 h in culture. The novel application of denervation indices revealed a trend for supraspinatus muscle to have a higher γ:ε subunit ratio than deltoid (P = 0.13); this ratio inversely with both occupancy ratio (P < 0.05) and the proportion of clusters at neuromuscular junctions (P = 0.05). Results implicate possible supraspinatus denervation in RCI and suggest NO-donor treatment has potential to promote growth in atrophic supraspinatus muscle after RCI and improve functional outcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".