Tooth Discoloration Induced by Endodontic Phenothiazine Dyes in Photodynamic Therapy
Bibliographic record
Abstract
OBJECTIVE: This study sought to assess if discoloration of tooth structures occurs after photodynamic therapy (PDT) and to determine the efficacy of a protocol to remove the photosensitizers. BACKGROUND DATA: PDT has been used in root canal treatment to enhance cleaning and disinfection of the root canal system. PDT uses a low power laser in association with a dye as a photosensitizer. Photosensitizers can induce staining of the dental structures, resulting in an unaesthetic appearance. METHODS: Forty teeth were randomly divided into four groups according to the photosensitizer used and pre-irradiation time: 0.01% methylene blue for 5 min (MB5); 0.01% methylene blue for 10 min (MB10); 0.01% toluidine blue for 5 min (TB5); and 0.01% toluidine blue for 10 min (TB10). Specimens were irradiated with a 660 nm diode laser with a 300 μm diameter optical fiber, at 40 mW power setting for 3 min. Immediately after, the photosensitizers were removed with Endo-PTC cream+2.5% sodium hypochlorite (NaOCl). The shade was measured by a Vita Easyshade spectrophotometer based on the CIELAB color system (L*a*b* values) at three different experimental times: before PDT (T0), immediately after PDT (T1), and after removal of the photosensitizer (T2). RESULTS: The results showed a decrease in the averages of the L*a*b* coordinate values after PDT (T1) in all the groups, when compared with the number at T0, with a significant statistical difference in group MB10. After photosensitizer removal (T2), all the values of the coordinates increased with significant statistical differences (p<0.05) between T1 and T2 in L* and a*. CONCLUSIONS: It can be concluded that both methylene blue and toluidine blue dyes cause tooth discoloration, and that Endo-PTC cream associated with 2.5% NaOCl effectively remove these dyes, regardless of the pre-irradiation time used for PDT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".