Exploring the use of a Ruthenium complex incorporated into a methacrylate-based dental material for antimicrobial photodynamic therapy
Bibliographic record
Abstract
Objectives: To evaluate the effects of a blue light photosensitizer (PS), Ruthenium II complex (Ru), on the chemical, physical, mechanical, and antimicrobial properties of experimental dental resin blends. Methods: The experimental resin (BisEMA, TEEGDMA, HPMA, ethanol, and photoinitiator) was loaded with Ru at 0.00%, 0.07%, 0.14%, 0.28%, 0.56%, 1.12%, 1.2%, 1.5%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, or 10% w/w. Samples were evaluated for the degree of conversion (DC) after 30 and 60 s curing-time ( n = 6). Selected formulations (0.00%, 0.28%, 0.56%, 1.12%) were further tested for shear bond strength (SBS) ( n = 15); flexural strength (FS) ( n = 12); and antimicrobial properties (CFUs), in dark and light conditions. These latter tests were performed on specimens stored for 24-h or 2-month in 37°C water. Water sorption (WS) and solubility (SL) tests were also performed ( n = 12). Data were analyzed either by a one- or two-factor general linear model (α = 0.05). Results: Overall, Ru concentration above 1.2% resulted in reduced DC. In SBS results, only the 1.12%Ru resin blend samples had statistically lower values compared to the 0.00%Ru resin blend at 24-h storage ( p = 0.004). In addition, no differences in SBS were detected among the experimental groups after 2-month storage in water. Meanwhile, FS increased for all experimental groups under similar aging conditions ( p < 0.001). Antimicrobial properties were improved upon inclusion of Ru and application of light ( p < 0.001 for both) at 24-h and 2-month storage. Lastly, no detectable changes in WS or SL were observed for the Ru-added resins compared to the 0.00%Ru resin blend. However, the 0.28% Ru blend presented significantly higher WS compared to the 0.56% Ru blend ( p = 0.007). Conclusions: Stable SBS, improved FS, and sustained antimicrobial properties after aging gives significant credence to our approach of adding the Ruthenium II complex into dental adhesive resin blends intended for an aPDT approach.
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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".