Effectiveness of Photodynamic Therapy Against <i>Enterococcus faecalis,</i> With and Without the Use of an Intracanal Optical Fiber: An <i>In Vitro</i> Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Photodynamic therapy (PDT) is a new technique introduced in endodontics that combines the action of a photosensitizer (dye) and a low intensity light source. Currently, there are no PDT studies evaluating the microbial disinfection of root canals in order to compare the effects of light delivery systems in the photosensitizer activation. The aim of this study was to evaluate the PDT effectiveness in reducing Enterococcus faecalis, with and without the aid of an intracanal optical fiber. METHODS: Extracted single-rooted teeth were selected, instrumented, inoculated with E. faecalis and divided into six groups: one control group (untreated), one conventionally-treated group (1% NaOCl irrigation) and four PDT-treated groups. Irradiation (diode laser) was performed with (OF) or without an intracanal optical fiber (NOF) using two different irradiation times: 1 min and 30 sec (IT(90)) or 3 min (IT(180)). Samples were collected before and after testing procedures and CFU/mL was determined. RESULTS: The greatest reduction of E. faecalis (99.99%) was achieved with irrigation with 1% NaOCl. PDT also significantly reduced E. faecalis in the following decreasing order: OF/IT(180), NOF/IT(180), OF/IT(90) and NOF/IT(90), with no significant statistical difference among the groups. CONCLUSIONS: These results suggest that PDT was effective against E. faecalis, regardless of the use of an intracanal optical fiber.
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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) | 0.000 | 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 | 0.000 | 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".