Correlation between the size of released titanium particles and changes in the surface of dental implants during insertion into bone blocks: an <i>in vitro</i> study
Bibliographic record
Abstract
PURPOSE: This study investigated the size and amount of titanium particles immediately released following dental implant insertion into bovine bone blocks and aimed to correlate them with the surface roughness of the implants. METHODS: Twelve bone blocks were prepared from bovine mandibles. Six tapered (group A) and 6 cylindrical (group B) dental implants were inserted into the bone blocks under water irrigation, following the standard drilling protocol. After insertion, the implants were immediately removed from the bone. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and atomic force microscopy were performed to investigate the released titanium particles and implant surface roughness, respectively. The amount of titanium ions in the irrigation water was measured using inductively coupled plasma mass spectrometry. Dynamic light scattering (DLS) was used to determine the size range of the released titanium particles. RESULTS: The percentages of titanium content on the surface of implants decreased in both groups after implantation into bone blocks. SEM-EDX analysis confirmed the presence of titanium particles embedded in the implanted bone bed. Group B implants showed significantly higher concentrations of titanium ions in the collected water than group A implants (0.868 and 0.565 µg/L, respectively). Group A implants demonstrated high pre-implantation surface roughness, which led to a much greater decrease in post-implantation surface roughness than was observed for group B implants. DLS analysis showed that the titanium particles released from group A implants were within the nano-size range, whereas those released from group B implants were within the micro-size range. CONCLUSIONS: studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".