Development and validation of mathematical models for testing antifungal activity of different essential oils against Candida species
Само за регистроване кориснике
2019
Аутори
Perić, MirjanaRajković, Katarina
Milić-Lemić, Aleksandra
Živković, Rade
Arsić-Arsenijević, Valentina
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
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 mu g/ml) and fungicided (3.5-6.0 mu g/ml) all three investigated Candida spp, while the lo...west concentrations of EO C. Limon inhibited (0.2-0.5 mu g/ml) and fungicided (0.6-1.1 mu g/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 ( lt 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.
Кључне речи:
Candido species / Essential oils / Response surface methodology / Artificial neural networkИзвор:
Archives of Oral Biology, 2019, 98, 258-264Издавач:
- Pergamon-Elsevier Science Ltd, Oxford
Финансирање / пројекти:
- Значај доказивања раних лабораторијских биомаркера за исход инвазивних гљивичних инфекција код нас (RS-MESTD-Basic Research (BR or ON)-175034)
DOI: 10.1016/j.archoralbio.2018.11.029
ISSN: 0003-9969
PubMed: 30530237
WoS: 000457664000036
Scopus: 2-s2.0-85057870829
Колекције
Институција/група
Stomatološki fakultetTY - JOUR AU - Perić, Mirjana AU - Rajković, Katarina AU - Milić-Lemić, Aleksandra AU - Živković, Rade AU - Arsić-Arsenijević, Valentina PY - 2019 UR - https://smile.stomf.bg.ac.rs/handle/123456789/2470 AB - 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 mu g/ml) and fungicided (3.5-6.0 mu g/ml) all three investigated Candida spp, while the lowest concentrations of EO C. Limon inhibited (0.2-0.5 mu g/ml) and fungicided (0.6-1.1 mu g/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 ( lt 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. PB - Pergamon-Elsevier Science Ltd, Oxford T2 - Archives of Oral Biology T1 - Development and validation of mathematical models for testing antifungal activity of different essential oils against Candida species VL - 98 SP - 258 EP - 264 DO - 10.1016/j.archoralbio.2018.11.029 ER -
@article{ author = "Perić, Mirjana and Rajković, Katarina and Milić-Lemić, Aleksandra and Živković, Rade and Arsić-Arsenijević, Valentina", year = "2019", 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 mu g/ml) and fungicided (3.5-6.0 mu g/ml) all three investigated Candida spp, while the lowest concentrations of EO C. Limon inhibited (0.2-0.5 mu g/ml) and fungicided (0.6-1.1 mu g/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 ( lt 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.", publisher = "Pergamon-Elsevier Science Ltd, Oxford", journal = "Archives of Oral Biology", title = "Development and validation of mathematical models for testing antifungal activity of different essential oils against Candida species", volume = "98", pages = "258-264", doi = "10.1016/j.archoralbio.2018.11.029" }
Perić, M., Rajković, K., Milić-Lemić, A., Živković, R.,& Arsić-Arsenijević, V.. (2019). Development and validation of mathematical models for testing antifungal activity of different essential oils against Candida species. in Archives of Oral Biology Pergamon-Elsevier Science Ltd, Oxford., 98, 258-264. https://doi.org/10.1016/j.archoralbio.2018.11.029
Perić M, Rajković K, Milić-Lemić A, Živković R, Arsić-Arsenijević V. Development and validation of mathematical models for testing antifungal activity of different essential oils against Candida species. in Archives of Oral Biology. 2019;98:258-264. doi:10.1016/j.archoralbio.2018.11.029 .
Perić, Mirjana, Rajković, Katarina, Milić-Lemić, Aleksandra, Živković, Rade, Arsić-Arsenijević, Valentina, "Development and validation of mathematical models for testing antifungal activity of different essential oils against Candida species" in Archives of Oral Biology, 98 (2019):258-264, https://doi.org/10.1016/j.archoralbio.2018.11.029 . .