Antibacterial Activity of a Bioactive Tooth-Coating Material Containing Surface Pre-Reacted Glass in a Complex Multispecies Subgingival Biofilm
Bibliographic record
Abstract
Bioactive materials were developed with the ability to release fluoride and provide some antimicrobial potential, to be widely used in dentistry today. However, few scientific studies have evaluated the antimicrobial activity of bioactive surface pre-reacted glass (S-PRG) coatings (PRG Barrier Coat, Shofu, Kyoto, Japan) on periodontopathogenic biofilms. This study evaluated the antibacterial activity of S-PRG fillers on the microbial profile of multispecies subgingival biofilms. A Calgary Biofilm Device (CBD) was used to grow a 33-species biofilm related to periodontitis for 7 days. The S-PRG coating was applied on CBD pins from the test group and photo-activated (PRG Barrier Coat, Shofu), while the control group received no coating. Seven days after treatment, the total bacterial counts, metabolic activity, and microbial profile of the biofilms were observed using a colorimetric assay and DNA–DNA hybridization. Statistical analyses were applied; namely, the Mann–Whitney, Kruskal–Wallis, and Dunn’s post hoc tests. The bacterial activity of the test group was reduced by 25.7% compared with that of the control group. A statistically significant reduction was observed for the counts of 15 species: A. naeslundii, A. odontolyticus, V. parvula, C. ochracea, C. sputigena, E. corrodens, C. gracilis, F. nucleatum polymorphum, F. nucleatum vincentii, F. periodonticum, P. intermedia, P. gingivalis, G. morbillorum, S. anginosus, and S. noxia (p ≤ 0.05). The bioactive coating containing S-PRG modified the composition of the subgingival biofilm in vitro, thereby decreasing colonization by pathogens.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".