Antimicrobial photodynamic therapy against a dual-species cariogenic biofilm using a ruthenium-loaded resin-based dental material
Bibliographic record
Abstract
BACKGROUND: Streptococcus mutans and Candida albicans are associated with caries recurrence. Therefore, this study evaluated the combination of a Ru(II)-loaded resin-based dental material (RDM) and antimicrobial photodynamic therapy (aPDT) against a dual-species biofilm of S. mutans and C. albicans. METHODS: ) at different energy densities (0.00, 6.25, 20.25, 40.50 J/cm2). This evaluation involved singlet oxygen quantification and determination of minimum inhibitory concentration (MIC) and minimum bactericidal/fungicidal concentration (MBC/MFC). The biofilm was grown (72 h) on resin disks prepared with Ru(II)-doped RDM (0.00, 0.56, or 1.12 %) and samples were exposed to aPDT or dark conditions. The biofilm was then harvested to analyze cell viability (CFU counts) and formation of soluble and insoluble exopolysaccharides. RESULTS: ); therefor, this energy density was chosen for aPDT. Although incorporation of Ru(II) into RDM reduced the biofilm growth compared to Ru(II)-free RDM for both species in dark conditions (p < 0.05), aPDT combined with an Ru(II)-loaded RDM (0.56 or 1.12 %) potentialized CFU reductions (p < 0.05). Conversely, only 1.12 % Ru(II) with LED irradiation showed lower levels of both soluble and insoluble exopolysaccharides compared to Ru(II)-free samples in dark conditions (p < 0.05). CONCLUSIONS: When the Ru(II)-loaded RDM was associated with blue LED, aPDT reduced cell viability and lower soluble and insoluble exopolysaccharides were found in the cariogenic dual-species biofilm.
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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".