Spontaneous progression of ligatured induced peri‐implantitis at implants with different surface characteristics. An experimental study in dogs II: histological observations
Bibliographic record
Abstract
AIM: The aim of the present study was to analyze tissue reactions to plaque formation following ligature removal in experimental peri-implantitis at commercially available implants in dogs. MATERIAL AND METHODS: Mandibular premolars and the three anterior premolars in both sides of the maxilla were extracted in six Labrador dogs. After 3 months, four implants representing four different implant systems--groups A (turned), B (TiOblast), C (SLA), D (TiUnite)--were placed in a randomized order in the right side of the mandible. Three months after implant installation, experimental peri-implantitis was initiated by placement of ligatures and plaque formation. The ligatures were removed when about 40-50% of the supporting bone was lost. After the subsequent 24-week period of continued plaque accumulation, block biopsies containing implants and their surrounding tissues were obtained and prepared for histological analysis. RESULTS: All types of implants exhibited extensive inflammatory cell infiltrates and large associated crater-formed osseous defects. The lesions were consistently characterized by insufficient encapsulation of pus and biofilm layers and the inflammatory cell infiltrates extended apical of the pocket epithelium. The presence of numerous osteoclasts indicated active tissue destruction. The vertical dimension and the overall surface area of the infiltrated connective tissue (ICT) were larger at implants of group D than at other implant types. CONCLUSION: It is suggested that spontaneous progression of peri-implantitis is associated with severe inflammation and tissue destruction.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".