Optimal delivery of endothelial progenitor cells in a rat model of critical‐size bone defects
Bibliographic record
Abstract
Nonunion and segmental bone defects are complex issues in orthopedic trauma. The use of endothelial progenitor cells (EPCs), as part of a cell-based therapy for bone healing is a promising approach. In preclinical studies, culture medium (CM) is commonly used to deliver EPCs to the defect site, which has the potential for immunogenicity in humans. The goal of this study was to find an effective and clinically translatable delivery medium for EPCs. Accordingly, this study compared EPCs delivered in CM, phosphate-buffered saline (PBS), platelet-poor plasma (PPP), and platelet-rich plasma (PRP) in a rat model of femoral critical-size defects. Fischer 344 rats (n = 35) were divided into six groups: EPC+CM, EPC+PBS, EPC+PPP, EPC+PRP, PPP alone, and PRP alone. A 5 mm mid-diaphyseal defect was created in the right femur and stabilized with a miniplate. The defect was filled with a gelatin scaffold impregnated with the corresponding treatment. Radiographic, microcomputed tomography and biomechanical analyses were performed. Overall, regardless of the delivery medium, groups that received EPCs had higher radiographic scores and union rates, higher bone volume, and superior biomechanical properties compared to groups treated with PPP or PRP alone. There were no significant differences in any outcomes between EPC subgroups or between PPP and PRP alone. These results suggest that EPCs are effective in treating segmental defects in a rat model of critical-size defects regardless of the delivery medium used. Consequently, PBS could be the optimal medium for delivering EPCs, given its low cost, ease of preparation, accessibility, noninvasiveness, and nonimmunogenic properties.
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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 | 0.000 |
| 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 | 0.001 |
| 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".