In vitro activity of essential oils extracted from plants used as spices against fluconazole-resistant and fluconazole-susceptible Candida spp.
Bibliographic record
Abstract
In the present study, the antifungal activity of selected essential oils obtained from plants used as spices was evaluated against both fluconazole-resistant and fluconazole-susceptible Candida spp. The Candida species studied were Candida albicans, Candida dubliniensis, Candida tropicalis, Candida glabrata, and Candida krusei. For comparison purposes, they were arranged in groups as C. albicans, C. dubliniensis, and Candida non-albicans. The essential oils were obtained from Cinnamomum zeylanicum Breyn, Lippia graveolens HBK, Ocimum basilicum L., Origanum vulgare L., Rosmarinus officinalis L., Salvia officinalis L., Thymus vulgaris L., and Zingiber officinale. The susceptibility tests were based on the M27-A2 methodology. The chemical composition of the essential oils was obtained by gas chromatography-mass spectroscopy and by retention indices. The results showed that cinnamon, Mexican oregano, oregano, thyme, and ginger essential oils have different levels of antifungal activity. Oregano and ginger essential oils were found to be the most and the least efficient, respectively. The main finding was that the susceptibilities of fluconazole-resistant C. albicans, C. dubliniensis, and Candida non-albicans to Mexican oregano, oregano, thyme, and ginger essential oils were higher than those of the fluconazole-susceptible yeasts (P<0.05). In contrast, fluconazole-resistant C. albicans and Candida non-albicans were less susceptible to cinnamon essential oil than their fluconazole-susceptible counterparts (P<0.05). A relationship between the yeasts' susceptibilities and the chemical composition of the essential oils studied was apparent when these 2 parameters were compared. Finally, basil, rosemary, and sage essential oils did not show antifungal activity against Candida isolates at the tested concentrations.
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.
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) | 0.000 | 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".