Rosemary essential oil and its components 1,8-cineole and α-pinene induce ROS-dependent lethality and ROS-independent virulence inhibition in Candida albicans
Bibliographic record
Abstract
The essential oil from Rosmarinus officinalis L., a composite mixture of plant-derived secondary metabolites, exhibits antifungal activity against virulent candidal species. Here we report the impact of rosemary oil and two of its components, the monoterpene α-pinene and the monoterpenoid 1,8-cineole, against Candida albicans, which induce ROS-dependent cell death at high concentrations and inhibit hyphal morphogenesis and biofilm formation at lower concentrations. The minimum inhibitory concentrations (100% inhibition) for both rosemary oil and 1,8-cineole were 4500 μg/ml and 3125 μg/ml for α-pinene, with the two components exhibiting partial synergy (FICI = 0.55 ± 0.07). At MIC and 1/2 MIC, rosemary oil and its components induced a generalized cell wall stress response, causing damage to cellular and organelle membranes, along with elevated chitin production and increased cell surface adhesion and elasticity, leading to complete vacuolar segregation, mitochondrial depolarization, elevated reactive oxygen species, microtubule dysfunction, and cell cycle arrest mainly at the G1/S phase, consequently triggering cell death. Interestingly, the same oils at lower fractional MIC (1/8-1/4) inhibited virulence traits, including reduction of mycelium (up to 2-fold) and biofilm (up to 4-fold) formation, through a ROS-independent mechanism.
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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".