Randomized split‐mouth clinical trial comparing osteoblastic activity and osteogenic potential of autogenous particle harvesting during implant surgery without irrigation and with irrigation
Bibliographic record
Abstract
OBJECTIVE: To compare the osteoblastic activity and osteogenic potential of autogenous particle harvesting during implant surgery using low-speed drilling without irrigation and high-speed drilling with irrigation. MATERIALS AND METHODS: Thirty patients with bilateral missing teeth of 3.6 and 4.6 were randomized into two groups (Group 1: low-speed drilling without irrigation and Group 2: high-speed drilling with irrigation) and 60 single dental implants were placed. The temperature at the tip of each drill was recorded and the harvested bone was weighed; particle size and Ca and P levels were also analyzed. After osteoblast culture, cell viability, cell cycle assay, cell migration, vascular endothelial growth factor (VEGF) concentration, and mineralized nodule formation were assessed. RESULTS: Although the temperature of the drills was slightly higher in Group 1, no statistically significant differences were observed (p ≤ 0.05); however, the amount of harvested bone was higher (p < 0.001) and the size of the particles was higher (p = 0.019). In relation to osteoblastic activity and osteogenic potential, higher cell proliferation, higher number of cells in G2/M and S phases, higher cell migration capacity, higher VEGF concentration, and higher amount of mineralized nodule formation were observed in Group 1. CONCLUSIONS: Low-speed drilling without irrigation does not result in a significant increase in bone temperature compared to conventional drilling. However, a greater amount of bone is obtained; in addition, osteoblastic activity and osteogenic potential are higher with this technique, but further clinical studies are necessary.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".