Cinnamon Leaf and Clove Essential Oils Are Potent Inhibitors of Candida albicans Virulence Traits
Bibliographic record
Abstract
Plant-based essential oils are promising anti-virulence agents against the multidrug-resistant opportunistic pathogen Candida albicans. Gas chromatography–mass spectrometry of Cinnamomum zeylanicum (cinnamon) leaf and Eugenia caryophyllus (clove) flower bud essential oils revealed eugenol (73 and 75%, respectively) as their major component, with β-caryophyllene, eugenyl acetate, and α-humulene as common minor components. Cinnamon leaf and clove essential oils had minimum inhibitory concentrations of 600 and 500 µg/mL, respectively against the C. albicans RSY150 reference strain and 1000 and 750 µg/mL, respectively for the clinical reference strain ATCC 10231. The combined oils are additive (FICI = 0.72 ± 0.16) and synergistic (0.5 ± 0.0) against RSY150 and the clinical reference strain, respectively. Mycelial growth was inhibited by sublethal concentrations of either essential oil, which abolished colony growth. At half of the lowest combined lethal concentration for the two oils, the yeast-to-hyphal transition and mycelial growth was potently inhibited. Mutant strains als1Δ/Δ, als3Δ/Δ, hwp1Δ/HWP1+, and efg1Δ/Δ were sensitive to either or both oils, especially efg1Δ/Δ. In conclusion, oils of cinnamon leaf and clove and their combination significantly impact C. albicans virulence by inhibiting hyphal and mycelial growth.
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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) | 0.000 | 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".