Seasonal variation in the essential oil composition of Origanum majorana L. cultivated in Egypt

Antioxidant Activity and Molecular Docking Study of Volatile Constituents from Different Aromatic Lamiaceous Plants Cultivated in Madinah Monawara, Saudi Arabia

A comparative study of volatile constituents, antioxidant activity, and molecular docking was conducted between essential oils from Mentha longifolia L., Mentha spicata L., and Origanum majorana L., widely cultivated in Madinah. The investigation of volatile oils extracted by hydrodistillation was performed using Gas Chromatography-Mass Spectrometry (GC-MS). A total number of 29, 42, and 29 components were identified in M. longifolia, M. spicata, and O. majorana representing, respectively, 95.91, 94.62, and 98.42, of the total oils. Pulegone (38.42%), 1,8-cineole (15.60%), menthone (13.20%), and isopulegone (9.81%) were the dominant compounds in M. longifolia oil; carvone (35.14%), limonene (27.11%), germacrene D (4.73%), and β-caryophyllene (3.02%) were dominant in M. spicata oil; terpin-4-ol (42.47%), trans-sabinene hydrate (8.52%), γ-terpinene (7.90%), α-terpineol (7.38%), linalool (6.35%), α-terpinene (5.42%), and cis-sabinene hydrate (3.14%) were dominant in O. majorana oil. The antioxidant activity, assessed using DPPH free radical–scavenging and ABTS assays, was found to be the highest in O. majorana volatile oil, followed by M. spicata and M. longifolia, which is consistent with the differences in total phenolic content and volatile constituents identified in investigated oils. In the same context, molecular docking of the main identified volatiles on NADPH oxidase showed a higher binding affinity for cis-verbenyl acetate, followed by β-elemene and linalool, compared to the control (dextromethorphan). These results prove significant antioxidant abilities of the investigated oils, which may be considered for further analyses concerning the control of oxidative stress, as well as for their use as possible antioxidant agents in the pharmaceutical industry.

Deep learning model for classification and bioactivity prediction of essential oil-producing plants from Egypt

Reliance on deep learning techniques has become an important trend in several science domains including biological science, due to its proven efficiency in manipulating big data that are often characterized by their non-linear processes and complicated relationships. In this study, Convolutional Neural Networks (CNN) has been recruited, as one of the deep learning techniques, to be used in classifying and predicting the biological activities of the essential oil-producing plant/s through their chemical compositions. The model is established based on the available chemical composition’s information of a set of endemic Egyptian plants and their biological activities. Another type of machine learning algorithms, Multiclass Neural Network (MNN), has been applied on the same Essential Oils (EO) dataset. This aims to fairly evaluate the performance of the proposed CNN model. The recorded accuracy in the testing process for both CNN and MNN is 98.13% and 81.88%, respectively. Finally, the CNN technique has been adopted as a reliable model for classifying and predicting the bioactivities of the Egyptian EO-containing plants. The overall accuracy for the final prediction process is reported as approximately 97%. Hereby, the proposed deep learning model could be utilized as an efficient model in predicting the bioactivities of, at least Egyptian, EOs-producing plants.

Atividade in vitro do óleo essencial de Origanum vulgare L. em isolados clínicos de Aspergillus spp

RESUMO Aspergillus fumigatus, A. flavus e A. niger são os mais importantes agentes etiológicos da aspergilose, relevante micose aviária, com tratamento ineficaz e altas taxas de mortalidade. Em vista da importância da aspergilose, da necessidade de prospectar novos fármacos e do potencial terapêutico do óleo essencial de Origanum vulgare L. (OEO), o orégano, objetivou-se avaliar a sensibilidade in vitro de isolados clínicos de Aspergillus spp. em relação ao OEO. O óleo foi obtido por hidrodestilação em Clevenger, e a análise química realizada por cromatografia de massa (GC/MS). Observaram-se 15 diferentes compostos ativos, sendo 4-terpineol, hidrato de sabinene e timol os majoritários. Nos testes de microdiluição em caldo (Reference..., 2008), todos os isolados (n= 23) foram sensíveis ao OEO: A. fumigatus teve CIM entre 28,125mg/mL (0,1875%) e 450mg/mL (3,0%), A. flavus entre 112,5mg/mL (0,75%) e 450mg/mL, e A. niger 112,5mg/mL. CFM variou de 112,5mg/mL a 450mg/mL nos isolados de A. fumigatus, de 225mg/mL (1,5%) a 450mg/mL em A. flavus, e foi de 450mg/mL em A. niger. CIM e CFM foram idênticos em 6/14 isolados, o que demonstra que o óleo com a mesma concentração pode ter capacidade fungistática e fungicida. CIM 90 correspondeu à CIM máxima. Os resultados demonstram a atividade anti-Aspergillus do OEO, com CIM 90 de 450mg/mL (3%).

Chemical composition and repellency of essential oils from four medicinal plants against Ixodes ricinus nymphs (Acari: Ixodidae)

In our search for effective tick repellents from plant origin, we investigated the effect of essential oils of four medicinal and culinary plants belonging to the family Lamiaceae on nymphs of the tick Ixodes ricinus (L.). The essential oils of the dry leaves of Rosmarinus officinalis (Rosemary) (L.), Mentha spicata (Spearmint) (L.), Origanum majorana (Majoram) (L.), and Ocimum basilicum (Basil) (L.) were isolated by steam distillation and 15 microg/cm2 concentration of oils was tested against ticks in a laboratory bioassay. The oils of R. officinalis, M. spicata, and O. majorana showed strong repellency against the ticks 100, 93.2, and 84.3%, respectively, whereas O. basilicum only showed 64.5% repellency. When tested in the field, the oils of R. officinalis and M. spicata showed 68.3 and 59.4% repellency at a concentration of 6.5 microg/cm2 on the test cloths. The oils were analyzed by gas chromatography mass spectrometry and the major compounds from the most repellent oils were 1,8-cineole, camphor, linalool, 4-terpineol, borneol, and carvone.