Antibacterial Coatings on Titanium Surfaces: A Comparison Study Between <i>in Vitro</i> Single-Species and Multispecies Biofilm
Bibliographic record
Abstract
Dental plaque is a biofilm that causes dental caries, gingivitis, and periodontitis. Most of the studies in antibacterial coatings have been conducted by in vitro single-species biofilm formation, but oral biofilm involves more than 700 different bacterial species that are able to interact. Therefore, new studies are focused on in vitro multispecies biofilm models that mimic in vivo biofilms. The aim of the present work was to study different antibacterial coatings onto titanium surfaces and evaluate the in vitro antimicrobial properties of the surfaces on two different bacterial species and an oral biofilm. The lactate dehydrogenase assay determined that treated samples did not affect fibroblast viability. In addition, the viability of microorganisms on modified samples was evaluated by a LIVE/DEAD BacLight bacterial viability kit. Although a decrease in viable bacteria onto treated samples was obtained, the results showed differences in effectiveness when single-biofilm and oral plaque were tested. It confirms, as we expected, the distinct sensitivities that bacterial strains have. Thus, this multispecies biofilms model holds a great potential to assess antibacterial properties onto samples for dental purposes.
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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 | 0.001 |
| 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) | 0.001 | 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".