Mesenchymal stem cells and platelet-rich plasma-impregnated polycaprolactone-β tricalcium phosphate bio-scaffold enhanced bone regeneration around dental implants
Bibliographic record
Abstract
BACKGROUND: Finding a material that supports bone regeneration is the concern for many investigators. We supposed that a composite scaffold of poly(ε) caprolactone and β-tricalcium phosphate (PCL-TCP) would entail desirable characteristics of biocompatibility, bioresorbability, rigidity, and osteoconductivity for a proper guided bone regeneration. Furthermore, the incorporation of mesenchymal stem cells (MSCs) and platelet-rich plasma (PRP) would boost the bone regeneration. We conducted this study to evaluate the bone regeneration capacity of PCL-TCP scaffold that is loaded with MSCs and PRP. MATERIALS AND METHODS: Five miniature pigs received 6 implants in 6 created-mandibular bony defects in the right and left lower premolar areas. The bony defects were managed according to the following three groups: the PCL-TCP scaffold loaded with MSCs and PRP (MSCs+PRP+PCL-TCP) group (n = 10), PCL-TCP scaffold loaded with PRP (PRP+PCL-TCP) group (n = 10), and PCL-TCP scaffold group (n = 10). After 12 weeks, the bone regeneration was assessed using fluorochrome bone labeling, μCT bone morphogenic analysis, and histomorphometric analysis. RESULTS: All of the three groups supported the bone regeneration around the dental implants. However, the PCL-TCP scaffold loaded with MSCs and PRP (MSCs+PRP+PCL-TCP) group showed non-significant higher bone surface, bone specific surface, and bone surface density than the other two groups as revealed by the μCT bone morphogenic analysis. Histologically, the same group revealed higher bone-implant contact ratio (BIC) (p = 0.017) and new bone height formation (NBH, mm) (p = 0.0097) with statistically significant difference compared to the PCL-TCP scaffold group. CONCLUSIONS: PCL-TCP scaffold is compatible for bone regeneration in bone defects surrounding dental implants. Moreover, the incorporation of MSCs and PRP optimized the bone regeneration process with respect to the rate of scaffold replacement, the height of the regenerated bone, and implant stability.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".