Enhancing Osseointegration With <scp>LNP</scp> ‐Delivered <scp>mRNA</scp> –Encoded <scp>BMP</scp> ‐2: An Experimental In Vivo Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of lipid nanoparticle (LNP)-encapsulated N1-methylpseudouridine-modified mRNA encoding BMP-2 (BMP-2 mRNA-LNP) on enhancing osseointegration and bone regeneration around titanium implants in rat femur defects. METHODS: A total of 48 rat femurs were examined in this study. BMP-2 mRNA-LNP (5 μg and 15 μg), recombinant human BMP-2 protein (4 μg), or dPBS (control) were randomly injected in a single dose into distal rat femurs (n = 6). Titanium wires were implanted, and bone formation was evaluated at 3 and 6 weeks post treatment using micro-computed tomography, histology, and immunohistochemistry analysis. Data were analyzed using the Kruskal-Wallis test, followed by the Dunn-Bonferroni test and the Wilcoxon signed-rank test with 95% confidence intervals (CIs). p-values < 0.05 were considered statistically significant. RESULTS: Micro-computed tomography analysis of bone volume, bone volume fraction, trabecular number, trabecular thickness, and bone-to-implant contact at both time points indicated a trend toward greater bone formation in the mRNA groups compared to the other groups. Significant differences were observed between the 15 μg BMP-2 mRNA-LNP group and the dPBS group at 6 weeks (p < 0.05). The 15 μg BMP-2 mRNA-LNP group also exhibited the most intense positive bone sialoprotein and osteocalcin staining compared to the other groups at 3 weeks and 6 weeks, respectively. Interestingly, histomorphometry at 6 weeks revealed a significantly higher bone area around the implants in both 5 μg and 15 μg BMP-2 mRNA-LNP groups compared to the rhBMP-2 and dPBS groups. CONCLUSION: This preclinical study highlights the potential of BMP-2 mRNA-LNP for promoting bone regeneration around dental implants.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".