The Effect of Hierarchical Micro/Nanotextured Titanium Implants on Osseointegration Immediately After Tooth Extraction in Beagle Dogs
Bibliographic record
Abstract
BACKGROUND: Owing to simplify the operation and shorten the overall duration of treatment, immediate implantation earned much satisfactory from patients and dentists. The results of immediate implantation determined by osseointegration, we fabricated a micro/nanotextured titanium implants to improve osseointegration immediately after tooth extraction. PURPOSE: The aim of this study was to investigate the effect of hierarchical micro/nanotextured titanium implant on osseointegration immediately after tooth extraction. MATERIAL AND METHODS: The micro/nanotextured titanium implants were fabricated by etching with 0.5 wt% hydrofluoric (HF) acid followed by anodization in HF electrolytes. Implants with a machined surface as well as implants a microtextured surface prepared by 0.5 wt% HF etching served as control groups. The machined, microtextured, and micro/nanotextured implants were inserted into fresh sockets immediately after tooth extraction in beagle dogs. Twelve weeks after implantation, the animals were sacrificed for micro-CT scanning, histological analysis and biomechanical test. RESULTS: The micro-CT imaging revealed that the bone volume/total volume (BV/TV) and trabecular thickness (Tb.Th) in the micro/nanotextured group was significantly higher than that in the machined group and microtextured group, and the trabecular separation (Tb.Sp) in the micro/nanotextured group was significantly lower than that in the other groups. For the histological analysis, the bone-to-implant contact in the machined, micro and micro/nanotextured groups were 47.13 ± 6.2%, 54.29 ± 4.18%, and 63.38 ± 7.63%, respectively, and the differences significant. The maximum pull-out force in the machined, micro, and micro/nanotextured groups were 216.58 ± 38.71 N, 259.42 ± 28.93 N, and 284.73 ± 47.09 N, respectively. CONCLUSIONS: The results indicated that implants with a hierarchical micro/nanotextured can promote osseointegration immediately after tooth extraction.
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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 | 0.001 |
| 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 | 0.001 | 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".