A comparative histological evaluation of the biocompatibility of materials used in apical surgery
Bibliographic record
Abstract
AIM: To evaluate the biological properties of a variety of materials that could be used in apical surgery. METHODOLOGY: The intraosseous implant technique recommended by the FDI (1980) and ADA (1982) was used to test the following materials: zinc oxide-eugenol (ZOE), mineral trioxide aggregate (MTA), and Z-100 light-cured composite resin. Thirty guinea-pigs, 10 for each material, divided into experimental periods of 4 and 12 weeks, received one implant on each side of the lower jaw symphysis. The connective tissue response alongside the lateral wall outside the cup served as a negative control for the technique. At the end of the observation periods, the animals were killed and the specimens prepared for routine histological examination to evaluate their biocompatibility. RESULTS: The reaction of the tissue to the materials diminished with time. The ZOE cement was highly toxic during the 4-week experimental period, but this profile changed significantly after 12 weeks, when it showed biocompatible characteristics. MTA and Z-100 showed biocompatibility in this test model at both time periods. CONCLUSIONS: MTA and Z-100 composite were biocompatible at 4 and 12 weeks in this experimental model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".