Effect of pretreatment of root dentin surface with cold atmospheric plasma on improving the bond strength of fiber post and resin cement: In vitro study
Bibliographic record
Abstract
INTRODUCTION: Achieving stable adhesion between fiber post and interradicular dentin is a challenging process in the restoration of endodontically treated teeth. This study was conducted to investigate the effect of surface pretreatment with cold atmospheric plasma (CAP) on improving the bond strength between them. MATERIALS AND METHODS: Forty-eight single-canal mandibular premolars were cut 1 mm above the cementoenamel junction to keep the root length of 14 mm or more. After endodontic treatment and preparation of the post space, the teeth were divided into four groups regarding the pretreatment of dentin surfaces, including normal saline, ethylenediaminetetraacetic acid (EDTA), CAP, and CAP + EDTA groups. The data were analyzed using paired and independent t-test and one-way analysis of variance and the significance level was set at p < .05. RESULTS: The bond strength was significantly higher in the coronal third than in the apical third in all the groups. Moreover, the bond strength was significantly higher in the CAP + EDTA-treated group. The bond strength increased significantly in the CAP group compared to the normal saline group. In addition, the bond strength increased significantly in the CAP or EDTA groups compared to the control group. The lowest bond strength belonged to the control group (normal saline). CONCLUSION: The surface pretreatment with CAP (alone or in combination with EDTA) played a significant role in improving the bond strength of fiber post and root canal dentin.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".