Effect of Bleaching Treatment on Fatigue Resistance and Flexural Strength of Bovine Dentin
Bibliographic record
Abstract
PURPOSE: To determine the effects of bleach on dentin fatigue resistance and flexural strength. MATERIALS AND METHODS: Eighty bovine dentin specimens (2 × 2 × 17 mm) were treated with: placebo or 10% carbamide peroxide bleach. Treatment was applied for 6 hours/day for 2 or 8 weeks. After treatment, 10 specimens per group were subjected to fatigue testing (10(6) cycles) whereas the other 10 were stored in artificial saliva as fatigue controls. The specimens undergoing fatigue were checked daily for visible signs of fracture and excluded from subsequent flexural strength tests if fractured. Fatigue control and surviving fatigued specimens were subjected to flexural strength testing. Chi-square, Kruskal-Wallis, factorial analysis of variance (p < 0.05) and Mann-Whitney (p < 0.002) tests were performed. RESULTS: There were significant differences in fatigue resistance (p = 0.003) and flexural strength rank scores (p < 0.0001) among the groups. None of the specimens in the "8-week bleach" group survived the fatigue testing. Fatigue (p = 0.005) and interaction of time and treatment (p = 0.039) were significant factors in the flexural strength results. Fatigued specimens had lower flexural strength than nonfatigued and "8-week bleach" had lower flexural strength than placebo and "2-week bleach" groups. CONCLUSIONS: Prolonged direct bleaching of bovine dentin reduces its fatigue resistance and flexural strength in vitro. Further research is needed in this area. CLINICAL SIGNIFICANCE: It remains prudent to advise patients to limit their exposure to tooth bleaching materials by avoiding direct application of bleach to exposed dentin and by minimizing the duration of bleach treatment.
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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 | 0.001 |
| 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 | 0.001 | 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".