Investigating the role of Rubus coreanus in enhancing peri-implant bone healing in healthy and estrogen-deficient rats
Bibliographic record
Abstract
Osseointegration can be compromised by bone diseases such as osteoporosis, negatively affecting the quality of life in affected individuals. Rubus coreanus (RC) has shown potential in modulating bone metabolism. Thus, this study aimed to evaluate the impact of RC-functionalized implants on peri-implant bone healing in both healthy (SHAM) and ovariectomized (OVX) rats. The research included both in vitro and in vivo experiments. Initially, osteoblastic cell cultures were used to assess the response to functionalized discs, followed by an in vivo study with forty-eight female Wistar rats, randomly assigned to six groups: SHAM CONV, SHAM RC 200, SHAM RC 400, OVX CONV, OVX RC 200, and OVX RC 400, where CONV refers to a conventional titanium implant and 200 and 400 represent that implant coated with 200 µg and 400 µg of RC. SHAM groups underwent fictitious surgery, while OVX groups underwent ovariectomy. After 30 days, implants were placed in the tibial metaphysis, and the rats were euthanized at 28 days post-implantation. Results indicated that RC maintained cell viability without significantly altering bone microarchitecture. Immunohistochemical analysis revealed notable histological improvements and enhanced marker expression, particularly with the RC 200 surface. Ultrastructural analysis suggested that RC functionalization improves peri-implant bone healing, especially in healthy rats treated with RC 200. In conclusion, implant functionalization with RC, particularly RC 200 significantly enhances peri-implant bone healing, with the most pronounced effects observed in SHAM group.
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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 | 0.000 |
| 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".