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 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 | 0.000 |
| 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".