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Σάββατο 1 Δεκεμβρίου 2018

Development and validation of mathematical models for testing antifungal activity of different essential oils against Candida species

Publication date: Available online 1 December 2018

Source: Archives of Oral Biology

Author(s): Mirjana Perić, Katarina Rajković, Aleksandra Milić Lemić, Rade Živković, Valentina Arsić Arsenijević

Abstract
Objective

The upward trend in using plant materials introduced essential oils (EOs) as a valuable, novel, bioactive antifungal agent and as an alternative to standard treatment protocol of denture stomatitis caused by Candida species. Therefore, the aim was to evaluate the antifungal activity of different EOs and to present the response surface methodology (RSM) and artificial neural network (ANN) as possible tools for optimizing and predicting EOs antifungal activity.

Methods

Minimum inhibitory concentration (MIC) and Minimum fungicidal concentration (MFC) of the EOs against 3 species Candida spp. (C. albicans, C. tropicalis, C. glabrata) isolated in patients with DS were determined, together with optimization and prediction based on non-terpene and terpene content in EOs, using two mathematical models RSM and ANN-GA.

Results

The highest concentrations of EO M. alternifolia inhibited (1.6 – 2.8 μg/ml) and fungicided (3.5 – 6.0 μg/ml) all three investigated Candida spp. while the lowest concentrations of EO C. limon inhibited (0.2 – 0.5 μg/ml) and fungicided (0.6 - 1.1 μg/ml).Among the three types of Candida, C. glabrata was the most sensitive. The RSM modelling proved that MICs and MFCs statistically depend on non-terpene and terpene content in different EOs (<0.0001). Both models showed that a citrus oil (EO C. limon) with 89% content of terpenes and limonene as major constituent was more antifungal efficient.

Conclusions

The investigated EOs showed a broad spectrum of anticandidal activity, also confirmed using the RSM and ANN-GA models. Since EOs can be cytotoxic in higher concentrations, models may be used for qualitative and quantitative dosage predictions of the antifungal activity of EOs.



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