Antimicrobial effects of chlorhexidine gel associated with hyaluronic acid or cetylpyridinium chloride in a multispecies biofilm
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it