Evaluation of Mesial Root Canals of Mandibular Molars Obturated with Gutta-Percha and Resilon Techniques
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate the obturation of mesial root canals of mandibular first molars performed with different filling techniques and materials (gutta-percha and resilon). METHODS: Seventy-eight mesial root canals of human mandibular first molars were prepared using the K3 rotary system, and the apical preparation was set up to size 35.04. The root canals were obturated with single cone, System B, Thermafil and Real Seal 1 techniques using either gutta-percha/ThermaSeal Plus (n=13) or Resilon/Real Seal SE (n=13). Rhodamine B dye was incorporated into the sealers. Each specimen was horizontally sectioned at 2 milimeters (mm), 4 mm and 6 mm from the apex, and the samples were examined under a stereomicroscope to evaluate the presence and type of isthmuses and the percentage areas of gutta-percha/Resilon, sealer and voids. Confocal laser scanning microscopy (CLSM) was used to evaluate the sealer penetration into dentinal tubules. The Kruskal-Wallis and Dunn's tests were used to analyse the stereomicroscope data, while the ANOVA and Tukey tests were used to analyse the CLSM data (P<0.05). RESULTS: Thermafil and Real Seal 1 fillings showed more gutta-percha/Resilon and less sealer (P<0.05) at the 2 mm level, but the percentage of voids was similar in all groups (P>0.05). At the 4 mm level, more sealer (P<0.05) was found in the single cone groups using both materials. The System B groups exhibited better performance at the 6 mm level. The percentage of sealer penetration showed no statistically significant differences among the obturation techniques for all evaluated levels. Similar results (P>0.05) were found for both material/sealers. CONCLUSION: None of the materials or techniques completely filled the mesial root canals of mandibular molars, but the plasticised techniques were more efficient. The obturations using both materials and sealers were similar.
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 | 0.000 | 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) | 0.002 | 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".