Topical Application of Melatonin and Growth Hormone Accelerates Bone Healing around Dental Implants in Dogs
Bibliographic record
Abstract
BACKGROUND: Growth hormone (GH) and melatonin belong to the group of growth factors. These substances have been proposed to improve and accelerate osseous healing using topical applications. PURPOSE: The aim of this study was to evaluate the effect of the topical administration of GH and melatonin on osseointegration of dental implants in Beagle dogs 2, 5, and 8 weeks after their insertion. MATERIALS AND METHODS: Twelve adult Beagle dogs and 48 implants were used in the study. The maxillary and mandibular premolars and molars were extracted. Each mandible received cylindrical screw implants of 3.25 mm in diameter and 10 mm in length. Prior to implanting, 4 IU of recombinant human GH and 1.2 mg of lyophilized powdered melatonin was applied to one osteotomy at each side of the mandible. None was applied at the control sites. The implants were retrieved at 2, 5, and 8 weeks for light microscopic examination, energy-dispersive x-ray microanalysis, and histomorphometric measurements in ground sections. RESULTS: At week 2, BIC was significantly higher in the melatonin-growth hormone group than in the implant control one (34.20 vs 25.05%; p = .010). The M-GH group also increased significantly the peri-implant bone area (64.72 vs 53.20%; p = .038) and interthread bone area (35.62 vs 25.08%; p = .02). At weeks 5 and 8, BIC and bone density around implants were similar to both groups. Significant differences were detected in bone neoformation at 8 weeks in ML-GH group (9.04 vs 7.53%; p = .05). Regarding the mineral composition, in ML-GH group increments in concentrations of phosphorus (10.70 vs 10.34; p = .013) were observed at 2 weeks and of magnesium (0.29 vs 0.25; p = .019) 5 weeks after implantation. CONCLUSION: The present study confirms that GH and melatonin synergistically enhance new bone formation around titanium implants in early stages of healing.
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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) | 0.001 | 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".