<i>In vitro</i> synergistic effect of farnesol and human gingival cells against <i>Candida albicans</i>
Bibliographic record
Abstract
Farnesol prevents the germination of yeast cells into mycelia, a fact that may be useful in eliminating C. albicans pathogenicity. Given the clinical potential of farnesol, its impact on C. albicans and host cells merited further investigation. We thus studied the effect of farnesol on C. albicans growth and filamentation and on gingival epithelial cells and fibroblasts and the synergistic effect of both gingival cells and farnesol on C. albicans filamentation. Repeated additions of farnesol reduced the growth of C. albicans. Farnesol was also effective at reducing C. albicans germ tube formation. While farnesol inhibited germ tube formation under the conditions tested, it was most effective at inhibiting C. albicans filamentation when added to the culture medium at the same time as the serum. Farnesol also had an effect on gingival cells. In a serum-free medium, farnesol reduced fibroblast adhesion and proliferation, promoted epithelial cell differentiation and reduced proliferation up to 48 h post-treatment. These effects were not seen in the presence of serum. When C. albicans, farnesol and gingival cells were present in the same culture, significantly greater inhibition of the yeast-to-hyphal transition was observed than germ tube inhibition in cultures containing only C. albicans and farnesol, suggesting a synergistic effect between the gingival cells and farnesol in inhibiting the transition. Overall, the data suggest that farnesol is effective against C. albicans and may have an effect on host cells at certain 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".