Growth factor release by vesicular phospholipid gels: in-vitro results and application for rotator cuff repair in a rat model
Bibliographic record
Abstract
BACKGROUND: Biological augmentation of rotator cuff repair is of growing interest to improve biomechanical properties and prevent re-tearing. But intraoperative single shot growth factor application appears not sufficient to provide healing support in the physiologic growth factor expression peaks. The purpose of this study was to establish a sustained release of granulocyte-colony stimulating factor (G-CSF) from injectable vesicular phospholipid gels (VPGs) in vitro and to examine biocompatibility and influence on histology and biomechanical behavior of G-CSF loaded VPGs in a chronic supraspinatus tear rat model. METHODS: G-CSF loaded VPGs were produced by dual asymmetric centrifugation. In vitro the integrity, stability and release rate were analyzed. In vivo supraspinatus tendons of 60 rats were detached and after 3 weeks a transosseous refixation with G-CSF loaded VPGs augmentation (n = 15; control, placebo, 1 and 10 μg G-CSF/d) was performed. 6 weeks postoperatively the healing site was analyzed histologically (n = 9; H&E by modified MOVIN score/Collagen I/III) and biomechanically (n = 6). RESULTS: In vitro testing revealed stable proteins after centrifugation and a continuous G-CSF release of up to 4 weeks. Placebo VPGs showed histologically no negative side effects on the healing process. Histologically in vivo testing demonstrated significant advantages for G-CSF 1 μg/d but not for G-CSF 10 μg/d in Collagen III content (p = 0.035) and a higher Collagen I/III ratio compared to the other groups. Biomechanically G-CSF 1 μg/d revealed a significant higher load to failure ratio (p = 0.020) compared to control but no significant differences in stiffness. CONCLUSIONS: By use of VPGs a continuous growth factor release could be obtained in vitro. The in vivo results demonstrate an improvement of immunohistology and biomechanical properties with a low dose G-CSF application via VPG. The VPG itself was well tolerated and had no negative influence on the healing behavior. Due to the favorable properties (highly adhesive, injectable, biocompatible) VPGs are a very interesting option for biologic augmentation. The study may serve as basis for further research in growth factor application models.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".