Antifungal Activity of Ocimum tenuiflorum and Ocimum gratissimum Herbal Formulation-Based Oral Rinse Against Candida albicans
Bibliographic record
Abstract
Background Candida albicans is a common fungal pathogen responsible for oral infections, posing significant health challenges. Traditional antifungal treatments often come with side effects and resistance issues, highlighting the need for effective natural alternatives. O. tenuiflorum and Ocimum gratissimum are known for their medicinal properties, including antifungal activity. Objective This study aimed to evaluate the antifungal effectiveness of an O. tenuiflorum and O. gratissimum herbal formulation-based oral rinse against C. albicans. Methods Antifungal activity was measured using agar well diffusion, time-kill curve assays, and analyses of cytoplasmic and protein leakage. The herbal rinse was tested at concentrations of 25 µg/mL, 50 µg/mL, and 100 µg/mL, and compared to a commercial oral rinse. Results The herbal rinse demonstrated strong antifungal effects that increased with concentration. At 100 µg/mL, it produced a 13 mm zone of inhibition, outperforming the commercial rinse's 11 mm. The time-kill assay revealed that the 100 µg/mL concentration reduced fungal counts to 103 CFU/mL within 5 hours, on par with the commercial rinse. Cytoplasmic leakage analysis showed an optical density of 0.42 at 100 µg/mL, close to the commercial rinse's 0.45. Protein leakage analysis indicated an optical density of 0.52 at 100 µg/mL, slightly higher than the commercial rinse's 0.51. Conclusion The O. tenuiflorum and O. gratissimum herbal formulation-based oral rinse exhibit potent antifungal activity against C. albicans, rivaling and even surpassing commercial rinses at higher concentrations. This study underscores the potential of this natural oral rinse as a powerful alternative for managing oral fungal infections, meriting further research and clinical trials to confirm its long-term safety and efficacy.
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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) | 0.000 | 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".