Freeze-Dried Chitosan-Platelet-Rich Plasma Implants for Rotator Cuff Tear Repair: Pilot Ovine Studies
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Bibliographic record
Abstract
Rotator cuff tears are a very common shoulder pathology. Different suturing techniques have been used for surgical cuff repair, but failure of healing remains a significant clinical challenge. The objective of this study was to establish and compare chronic and acute ovine rotator cuff tear models in our laboratory and investigate the feasibility of using chitosan (CS)-platelet-rich plasma (PRP) implants in conjunction with suture anchors to treat rotator cuff tears in large animal models. Repair with suture anchors only was used as control. In two preliminary pilot studies, unilateral full-thickness tears were created in the infraspinatus (ISP) tendon of mature female Texel-cross sheep. In the chronic model (n = 4 sheep), the tendons were capped with silicon and allowed to retract for 6 weeks, leading to degenerative changes, whereas the tendons were immediately repaired in the acute model (n = 4 sheep). Transected ISP tendons were reattached with suture anchors and, in the case of treated shoulders, implants composed of freeze-dried CS solubilized in autologous PRP were additionally applied to the tendon–bone interface and on top of the repaired site. The chronic defect model induced significant tendon degeneration and retraction, which made repair more challenging than in the acute defect model. Half the tendons in the chronic repair model were found to be irrepairable at 6 weeks. In the other half, the tendons could not be reattached to the footprint due to significant retraction, which made this a model of tissue formation in a gap. In contrast, the acute tendon repair model was executed easily. Extensive bone remodeling and tissue ingrowth at the tendon-bone interface were observed in the case of treatment with anchors + CS-PRP in both models, suggesting that CS-PRP implants could potentially modulate rotator cuff healing processes in large animal models.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it