Synergistic Antifungal Effects of Alcoholic Pomegranate Extract and Chlorhexidine Against Oral Candida albicans
Bibliographic record
Abstract
Compared to synthetic chemicals, which often pose risks to human health, natural plantbased antimicrobials are gaining increasing attention due to their lower toxicity and biocompatibility.Among these, pomegranate extract has emerged as a promising plantderived antimicrobial agent for controlling oral pathogens.The aim of this work was to study the effect of pomegranate alcoholic extract and analyze its synergistic effects with chlorhexidine on oral Candida albicans isolates from the mouths of diabetic patients.Ten isolates of Candida albicans were evaluated for the antifungal effect of pomegranate alcoholic extract at different concentrations (10, 25, 50, 75, and 100%), compared to chlorhexidine at 0.22%.The well diffusion and tube dilution methods were used to determine the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC), and to evaluate the synergistic effect of pomegranate alcoholic extract combined with chlorhexidine as an anti-Candida agent.The results indicate that the 100% concentration recorded the highest antifungal activity compared to the other tested concentrations, except for the 10% which did not record any effect.The minimum inhibitory concentration (MIC) and minimum fungicide concentration (MFC) were 12.5% and 25%, respectively, for the pomegranate alcoholic extract.There were also highly statistically significant differences (p<0.001) in the synergistic effect between chlorhexidine and the lowest lethal concentration of alcoholic pomegranate extract, where the inhibition zone was recorded at 2.8 cm compared to what was recorded by both chlorhexidine 2 cm and alcoholic pomegranate extract 1.7 cm.Effective treatment of oral Candida albicans could help prevent conditions such as oral candidiasis and other systemic infections, especially in people with compromised immunity or chronic diseases.This synergistic formula offers a natural alternative to traditional antifungals, with a reported 40% increase in effectiveness, reducing reliance on synthetic agents.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".