Catechin-incorporated dental copolymers inhibit growth of Streptococcus mutans
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To test the inhibitory growth activity of green tea catechin incorporated into dental resins compared to resins containing the broad-spectrum antimicrobial compound chlorhexidine against Streptococcus mutans in vitro. MATERIAL AND METHODS: The minimum inhibitory concentrations (MICs) of epigallocatechin-gallate (EGCg) and chlorhexidine (CHX) were determined according to the microdilution method. Resin discs (5 mm × 3 mm) were prepared from Bis-GMA/TEGDMA (R1) and Bis-GMA/CH3Bis-GMA (R2) comonomers (n=9) containing: a) no drug, b) EGCg, c) CHX. Two concentrations of each drug (0.5× MIC and 1× MIC) were incorporated into the resin discs. Samples were individually immersed in a bacterial culture and incubated for 24 h at 37°C under constant agitation. Cell viability was assessed by counting the number of colonies on replica agar plates. Statistical analysis was performed using one-way ANOVA, Tukey and Student t-tests (α=0.05). RESULTS: Both resins containing EGCg and CHX showed a significant inhibition of bacterial growth at both concentrations tested (p<0.05). A significantly higher inhibition was observed in response to resins containing CHX at 0.5× MIC and 1× MIC, and EGCg at 1× MIC when compared to EGCg at 0.5× MIC. Also, EGCg at 0.5× MIC in R1 had a significantly higher growth inhibition than in R2. CONCLUSIONS: Both EGCg and CHX retained their antibacterial activity when incorporated into the resin matrix. EGCg at 1× MIC in R1 and R2 resins significantly reduced S. mutans survival at a level similar to CHX. The data generated from this study will provide advances in the field of bioactive dental materials with the potential of improving the lifespan of resin-based restorations.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it