EFFICACY OF DIODE LASSER 405 NM WITH CHLOROPHYLLS AS PHOTOSENSITIZER ON Enterococcus faecalis
Bibliographic record
Abstract
Background: The presence of persistent infections in the root canals by microorganisms causes root canal failure. The most commonly found bacteria that cause persistent infection is Enterococcus faecalis. PDI / photodynamic inactivation is an in vitro approach to inactivation of microorganisms. The combination of light and photosensitivity of chlorophyll in PDI will cause photoinactivation in bacteria. Long radiation of PDT can affect the production of singlet oxygen and ROS (Reactive Oxygen Species) to kill Enterococcus faecalis bacteria. Objective: To prove the effect of 405 nm laser diode with and without chlorophyll photosensitizer and the irradiation effect of 405 nm laser diode on the number of CFU of Enterococcus faecalis bacteria. Method: This study used the Enterococcus faecalis bacteria cultur which was divided into 5 groups. Group I as control group, Group II irradiation 30 ', III chlorophyll + irradiation 30', IV irradiation 60 ', V chlorophyll + irradiation 60'. After incubation, the bacteria count was calculated with Quebec Colony Counter and analyzed by Shapiro-Wilk test, Levene test and Anova test. Results: There were significant differences (p <0.05) between the number of colonies of Enterococcus faecalis bacteria in each treatment group. Longer duration of PDT exposure (Group II and IV) with chlorophyll showed less number of Enterococcus faecalis bacteria. Conclusion: The longer the PDT irradiation, the less number of Enterococcus faecalis bacteria. The 60-second radiation with chlorophyll showed the least amount of Enterococcus 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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".