Chronological Changes in the Ultrastructure of Titanium‐Bone Interfaces: Analysis by Light Microscopy, Transmission Electron Microscopy, and Micro‐Computed Tomography
Bibliographic record
Abstract
PURPOSES: The objectives of this study were to chronologically examine the titanium-bone interfaces and to clarify the process of osseointegration using light microscopy, transmission electron microscopy (TEM), and micro-computed tomography (CT). MATERIALS AND METHODS: Experimental implants (Ti-coating plastic implants) were placed into tibiae of 8-week-old rats. Animals were sacrificed at 1 to 28 days after implant placement and prepared tissue specimens for a light microscope, a TEM, and micro-CT. RESULTS: New bone formation began 5 days after implant placement, and osseointegration was obtained by 14 days after implant placement. Osseointegration was well developed by 28 days after implant placement. DISCUSSION: TEM and quantitative computer tomography (QCT) results indicated that bone formation in osseointegration of titanium implants did not occur from the surfaces of the implant or preexisting bone, but it was likely that bone formation progressed at a site a small distance away from the surface. The bone formation took place in a scattered manner. Small bone fragments adhered to each other and transformed into reticular-shaped bone, and finally these bones became lamellar bone. CONCLUSION: Comparative analysis of the titanium-bone interfaces using light microscopy, TEM, and QCT by micro-CT revealed the precise process of osseointegration.
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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 | 0.000 |
| 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".