The Effect of Cryopreservation on the Bone Healing Capacity of Endothelial Progenitor Cells in a Bone Defect Model
Bibliographic record
Abstract
ABSTRACT Endothelial progenitor cells (EPCs) have proven to be a highly effective cell therapy for critical‐sized bone defects. Cryopreservation can enable long‐term storage of EPCs, allowing their immediate availability on demand. This study compares the therapeutic potential of EPCs before and after cryopreservation in a small animal critical‐sized bone defect model. Five‐millimeter segmental defects were created in the right femora of Fischer 344 rats, followed by stabilization with a miniplate and screws. The animals received 2 × 106 fresh EPCs (n = 7) or 2 × 106 cryopreserved EPCs (n = 9) delivered on a gelatin scaffold. Cryopreserved EPCs were stored for 7 days at −80°C prior to thawing and loading onto the gelatin scaffold. Biweekly radiographs were taken until the animals were euthanized 10 weeks after surgery. The operated femora were then evaluated using microscopic‐computed tomography (micro‐CT) and biomechanical testing. All animals treated with fresh (n = 7/7) or cryopreserved (n = 9/9) EPCs achieved radiographic union at 10 weeks. Animals treated with fresh EPCs had statistically significant higher radiographic scores at 2 weeks (p < 0.05) but showed no statistically significant differences thereafter (p > 0.05). Micro‐CT analysis showed no statistically significant differences between the groups in bone volume (BV) or BV normalized to total volume (p > 0.05), with excellent bone formation in both groups. Finally, there were no differences in biomechanical outcomes between the groups (p > 0.05). These results demonstrate that cryopreserved EPCs are highly effective and equivalent to fresh EPCs for healing critical‐sized bone defects in a rat model of nonunion.
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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 | 0.000 | 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".