Anti-Microbial Activity of Hempseed Oil and Sage Oil against Streptococcus mutans and Candida albicans: An In-Vitro Study
Bibliographic record
Abstract
Objective: To assess the anti-microbial activity of sage oil and hempseed oil against Streptococcus mutans and Candida albicans. Material and Methods: The sage oil and hempseed oil in pure extract form were collected from an authorized government organization. The anti-microbial activity from the oils was assessed by Kirby-Bauer disc diffusion method. Standard antibiotics Vancomycin and Fluconazole were taken as a positive control for Streptococcus mutans and Candida albicans, respectively. The mean zone of inhibition (ZOI) was measured at 24 hours, 48 hours and 72 hours by HI-MEDIAs antibiotic zone scale. One-way Analysis of variance with Tukey’s Post Hoc was applied for statistical analysis. Results: The mean zone of inhibition of sage oil and hempseed oil at 24 hours, 48 hours and 72 hours against Streptococcus mutans was (7.0 ± 4.24, 9.1 ± 3.71 and 8.4 ± 3.02) and (0.0, 3.2 ± 0.75, 1.9 ± 1.24) respectively. The zone of inhibition against Candida albicans 24 hours, 48 hours and 72 hours for sage oil (2.80 ± 1.151, 6.70 ± 1.30 and 6.30 ± 1.44), hempseed oil (0.0, 3.80 ± 0.75, 3.10 ± 0.41). Sage oil presented potential anti-microbial activity against Streptococcus mutans and Candida albicans. Comparing the anti-microbial efficacy, standard antibiotic (Vancomycin/Fluconazole) was more effective than test oils. Conclusion: Test oils showed anti-bacterial and anti-fungal activity against Streptococcus mutans and Candida albicans. Among these, sage oil showed efficacy at 24 hours, while hempseed oil did not show any effect at this time point. Further studies are needed to affirm the same and test their efficacy in different forms and concentrations.
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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 | 0.000 | 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".