Antimicrobial effects of chlorhexidine gel associated with hyaluronic acid or cetylpyridinium chloride in a multispecies biofilm
Bibliographic record
Abstract
Chlorhexidine (CHX) and cetylpyridinium chloride (CPC) are commonly used as mouthwashes due to their antimicrobial effect. More recently, hyaluronic acid (HA) has also been associated to oral health products aiming to improve their anti-inflammatory and antimicrobial effects. This study aimed to evaluate the effect of three different CHX-based commercially available products on the subgingival microbial composition and metabolic activity using a multispecies biofilm model. A biofilm model composed of 33 bacterial species with 7 days of maturation on a Calgary plate device was used. The multispecies biofilm was treated with CHX 0.2% (positive control), CHX 0.2% + CPC (test 1), CHX 0.2% + HA 1% (test 2), and culture medium (negative control). The metabolic activity of the multispecies biofilm was measured using a spectrophotometric assay and the microbial composition by checkerboard DNA-DNA hybridization. The studied groups were compared using ANOVA and post hoc Bonferroni tests. The significance level was established at 5%. The CHX+CPC gel was more effective than the other treatments in reducing proportions of red complex species and increasing bacterial species associated with periodontal health (p<0.05). A reduction of approximately 54% was observed in the microbial metabolic activity of biofilms treated with CHX and CHX + CPC, and 26% in biofilms treated with CHX+HA. The CHX+CPC gel seems to have a superior antibacterial potential when compared to a gel containing CHX only, or CHX+HA, in an in vitro multispecies biofilm model.
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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) | 0.001 | 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".