The effect of 2% chlorhexidine iontophoresis on dentin sealing ability of etch-and-rinse adhesive: An in vitro study
Bibliographic record
Abstract
Iontophoresis could enhance the delivery of chlorhexidine into oral tissue. This study aimed to determine the effect of 2% chlorhexidine iontophoresis (CHI) on the sealing ability of etch-and-rinse adhesive in human dentin using hydraulic conductance (HD) measurement, scanning electron microscopy and energy dispersive x-ray spectroscopy (SEM-EDS). Thirty-nine sound dentin specimens were prepared from 39 extracted intact third molars. Thirty specimens were used for HD measurement and randomly divided into 3 equal-sized groups; (1) No chlorhexidine treatment (control), (2) passive chlorhexidine treatment (CHT) and (3) CHI on acid-etched dentin. Each dentin surface was treated with etch-and-rinse adhesive. HD of each specimen was measured before treatment, after immediate bonding and after 14 days. The other 9 specimens were subjected to SEM-EDS analysis of the acid-etched dentin and the dentin treated with CHT and CHI. ANOVA test and Student-Newman-Keuls method were used for statistical analysis. After bonding, there was no significant difference in percentage decrease of HD among the treatment groups (P > 0.05). After 14 days, CHI and CHT groups had greater percentage decrease of HD than the control (P < 0.001 and P = 0.009, respectively). Under SEM-EDS analysis, acid-etched dentin with CHI presented opened dentinal tubule orifices and more chlorhexidine precipitates on dentin than the dentin with CHT, which strongly related to a higher percentage of chloride ions on the CHI dentin surface (P < 0.001). The use of CHI on acid-etched dentin had a positive effect on dentin sealing ability of etch-and-rinse adhesive.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".