Treatment of periodontal disease with guided tissue regeneration technique using a hydroxyapatite and polycaprolactone membrane
Bibliographic record
Abstract
ABSTRACT The aim of this study was to evaluate the use of a malleable membrane composed of hydroxyapatite (60%) and polycaprolactone (40%) as treatment of periodontal disease experimentally induced in dogs. A bone defect of standardized dimensions was created between the roots of the third and fourth premolar of 12 dogs for periodontal disease induction. Six dogs had the defect covered by the membrane and six dogs received only standard treatment for periodontal disease, also applied to dogs in the treated group. The animals were clinically monitored during the experiment. Radiographs were taken after surgery and at 60 days after treatment initiation. Clinical attachment level was also assessed in those moments. On the 60th day, dental sample of all animals, containing tooth, defect and periodontal tissues, were harvested, fixed in formalin and analyzed by microtomography and histology. During the experimental period, the animals showed no pain and purulent discharge, however, there was dehiscence in 50% of animals and membrane exposure in five out of six animals in the treated group. Clinical attachment level showed no difference between groups. Radiographs showed radiopacity equal to the alveolar bone in both groups. The microtomography revealed that the control group had higher bone volume in the defect compared to the treated group; however, the furcation was not filled by new alveolar bone in any animal. Histological analysis revealed that junctional epithelium invasion was lighter in the control group. New bone was only observed in the apical edge of the defect in both groups. Although the composite is biocompatible and able to keep the space of the defect, it did not promote periodontal tissue regeneration within 60 days of observation.
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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 | 0.000 | 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".