Comparative Evaluation of the Antibacterial Efficacy of Metronidazole, Chlorhexidine, and Normal Saline as Laser- and Sonic-Activated Intracanal Irrigants Against Enterococcus faecalis: In Vitro Study Protocol
Bibliographic record
Abstract
Background: The persistence of Enterococcus faecalis is a significant challenge in endodontic therapy, due to its ability to form biofilms and penetrate the dentinal tubules, frequently leading to treatment failures. Therefore, despite the proven antimicrobial activity of metronidazole (MTR) and chlorhexidine (CHX), the resilience of E. faecalis necessitates integrating activation techniques. Laser and sonic activation methods show promise in enhancing the antibacterial performance of irrigants. However, studies on the activation-enhanced efficacy of MTR, CHX, and saline remain limited. Objective: This study aimed to compare the antibacterial efficacy of MTR, CHX, and normal saline as intracanal irrigants when activated by laser and sonic techniques against E. faecalis in extracted human mandibular premolars. Methods: It is a laboratory-based in vitro experimental study involving extracted human teeth. Ninety freshly extracted single-rooted mandibular premolars will be obtained, decoronated, and biomechanically prepared. Canals will be inoculated with E. faecalis (ATCC 29212) and incubated for 7 days to allow biofilm formation. The teeth will then be randomly divided into 3 main groups ([MTR], [CHX], and saline), each subdivided based on the activation method used (laser or sonic). Irrigation protocols will be standardized, and pre- and postirrigation bacterial samples will be collected on paper points and cultured on brain heart infusion agar. Colony-forming units will be counted to evaluate antibacterial efficacy. Results: As of June 2025, ethical approval for the study has been obtained. Sample collection of extracted human teeth commenced in July 2025, and 90 extracted teeth have been collected as of January 2026, corresponding to the planned sample size. Laboratory procedures and data analysis have not yet commenced. Conclusions: This study aims to provide evidence-based insights into optimizing root canal disinfection protocols by evaluating and comparing the synergistic effects of antimicrobial agents and advanced activation techniques. The findings could contribute significantly to improving endodontic treatment outcomes and reducing the incidence of persistent infections caused by E. faecalis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".