Effectiveness of light-emitting diode exposure on photodynamic therapy against Enterococcus faecalis: in vitro study
Bibliographic record
Abstract
Background: A successful root canal treatment eliminates pathogenic bacteria from infected root canals. The most common bacteria in root canal infections is Enterococcus faecalis (E. faecalis), due to its resistance to medicament and root canal irrigation. A photodynamic therapy (PDT) is a method of root canal disinfection that uses a combination of photosensitisers and light activation to eliminate bacteria in the root canal. The duration of the PDT irradiation results in the production of singlet oxygen and reactive oxygen species (ROS) to eliminate the E. faecalis bacteria. Purpose: To analyse the differences in the duration exposure of photodynamic therapy against the E. faecalis bacteria. Methods: The E. faecalis bacteria culture was divided into seven eppendorf tubes. Group I was a control group, and group II, III, IV, V, VI and VII were treated using PDT consisting of Toluidine Blue O (TBO) photosensitiser and light source irradiation for ten, 20, 30, 40, 50 and 60 seconds, respectively. After incubation, the number of bacteria was calculated by the Quebec Colony Counter and analysed using the Kruskal–Wallis test and the Mann–Whitney test (p <0.05). Results: There was a significant difference between the number of E. faecalis bacteria colonies in each treatment group (p <0.05). Group VI and VII, which had a longer exposure to PDT, showed a smaller amount of E. faecalis bacteria. Conclusion: The longer exposure of PDT results in a smaller amount of E. faecalis bacteria. The light irradiation of 50 seconds is the most effective to eliminate E. faecalis bacteria.
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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) | 0.001 | 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) | 0.002 | 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".