Combining Glycine Powder Air‐Polishing and Ultrasonic Scaling for Bone Regeneration Around Infected Dental Implants
Bibliographic record
Abstract
OBJECTIVES: In vitro studies were conducted to evaluate the effectiveness of combining glycine powder air-polishing (AP) and ultrasonic scaling (US) in surgical bone reconstructive therapy for peri-implantitis. MATERIALS AND METHODS: Twenty clinically failed implants and 60 pristine implants were treated in vitro with AP and/or US by using stainless steel, titanium, or carbon fiber tips. Implant surface topography, contaminant distribution, elemental proportion, and composition were analyzed using scanning electron microscopy and energy-dispersive X-ray spectroscopy. RESULTS: AP effectively removed bacterial plaques but was unable to eliminate calcified deposits involving calculi and bone fragments. Conversely, US exhibited a high capacity for removing calcified deposits but inevitably altered implant surface topography and the atomic percentages of oxygen (O) and titanium (Ti) regardless of the ultrasonic tip used. AP showed minimal effects on the implant surface and even alleviated the adverse effects of US on the surface topography and the atomic percentages of O, Ti, and even carbon. A sequential protocol involving AP followed by US, with a final AP step, effectively removed contaminants from infected implants while minimally affecting the original surface features. CONCLUSIONS: The combined application of AP and US in surgical peri-implantitis therapy may be a preferred and effective approach for obtaining bone regeneration around infected dental implants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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".