Antimicrobial activity of Commercial essential oils on human pathogens
Bibliographic record
Abstract
Essential oils (EOs) are natural extracts from the seeds, stems, roots, flowers, bark and other parts of the plant prepared by steam distillation. They are complex, volatile, natural compounds formed by aromatic plants as secondary metabolites. They are known for their bactericidal, virucidal, fungicidal, sedative, anti-inflammatory, analgesic, spasmolytic and locally anesthetic properties. They are generally composed of a combination of substances like terpenes, phenolics, aldehydes or alcohols. The complex composition and different mechanisms of action of EOs may be an advantage over other antimicrobials to prevent the development of resistance of pathogenic bacteria. With this background, the aim of this study was to evaluate the antimicrobial activity of five essential oils like basil, lime, rosemary, thyme and canada balsam against 14 microbes. The effects of essential oil on the selected microbes were determined by agar well diffusion method. The zone of inhibition was observed and measured in millimeter. Essential oils which showed inhibitory diameter >15 mm were further tested to determine the minimum inhibitory concentration (MIC). S. aureus, E. coli, S. mutans, S. sanguinis, C. albicans and M. furfur were inhibited by all essential oils. K. pneumoniae, P. aeruginosa and E .faecalis were inhibited only by thyme and not by other essential oils. The MIC values ranged from 50% to 0.10%. The least MIC value of 0.10% was shown by thyme and basil to S. aureus, thyme to E.coli and all essential oils against C. albicans except lime.
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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 | 0.001 |
| 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) | 0.002 | 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".