Efficacy of a propolis solution for cleaning complete dentures.
Bibliographic record
Abstract
PURPOSE: The efficacy of a propolis solution against denture biofilm was evaluated by means of an in vitro assessment and a cross-over randomized clinical trial. METHODS: Acrylic resin specimens were contaminated by Staphylococcus aureus, Streptococcus mutans, Escherichia coli, Candida albicans, Candida glabrata, Candida parapsilosis, immersed in a (A) propolis solution, (B) saline or (C) alkaline peroxide, applied onto Petri plates with culture medium and after incubation the number of colonies was counted. For the clinical trial, 30 complete denture wearers were randomly assigned to groups (A) propolis solution, and (B) saline, following one of the sequences (I)A/B or (II) B/A. After each intervention, biofilm was quantified by means of digital photos taken from the intaglio surface and a microbiological quantification of Candida spp. and mutans streptococci was conducted. RESULTS: Both propolis solution and alkaline peroxide reduced the microbial counts for S. mutans and C. albicans with significant and greater effect for group C (P< 0.05). However, no difference was found clinically between the interventions. The propolis solution showed an intermediate antimicrobial effect against S. mutans and C. albicans. Also, it did not exert an immediate effect on denture biofilm. CLINICAL SIGNIFICANCE: A commercially available propolis-based cleanser solution was evaluated in vitro and clinically for the treatment of denture stomatitis. Although an immediate effect on denture biofilm was not observed after a single application, It showed antimicrobial effect against S. mutans and C. albicans.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".