Chitosan inhibits platelet-mediated clot retraction, increases platelet-derived growth factor release, and increases residence time and bioactivity of platelet-rich plasma <i>in vivo</i>
Bibliographic record
Abstract
Platelet-rich plasma (PRP) has been used to treat different orthopedic conditions, however, the clinical benefits of using PRP remain uncertain. Chitosan (CS)-PRP implants have been shown to improve meniscus, rotator cuff and cartilage repair in pre-clinical models. The purpose of this current study was to investigate in vitro and in vivo mechanisms of action of CS-PRP implants. Freeze-dried formulations containing 1% (w/v) CS (80% degree of deacetylation and number average molar mass 38 kDa), 1% (w/v) trehalose as a lyoprotectant and 42.2 mM calcium chloride as a clot activator were solubilized in PRP. Gravimetric measurements and molecular/cellular imaging studies revealed that clot retraction is inhibited in CS-PRP hybrid clots through physical coating of platelets, blood cells and fibrin strands by chitosan, which interferes with platelet aggregation and platelet-mediated clot retraction. Flow cytometry and ELISA assays revealed that platelets are activated and granules secreted in CS-PRP hybrid clots and that cumulative release of platelet-derived growth factor (PDGF-AB) and epidermal growth factor is higher from CS-PRP hybrid clots compared to PRP clots in vitro. Finally, CS-PRP implants resided for up to 6 weeks in a subcutaneous implantation model and induced cell recruitment and granulation tissue synthesis, confirming greater residency and bioactivity compared to PRP in vivo.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".