Composition and antimicrobial activity of the essential oil of Thymus fontanesii

The yield of oil isolated by hydrodistillation from aerial parts of Thymus fontanesii Boiss. et Reut. (Lamiaceae) growing wild in Djelfa (Algeria) was 0.9%. Analysis of the oil by gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS) revealed the identification of 47 components accounting for 98.5% of the total oil. The oil was found to be rich in monoterpenes (91.5%) with major constituents being thymol (29.3%), γ-terpinene (21.7%), p-cymene (15.9%), and thymol methyl ether (11.4%), while a smaller amount of linalool (4.8%) and β-caryophyllene (2.9%) were detected. According to the antimicrobial study using the disk diffusion method and the agar dilution assay-minimal inhibitory concentration (MIC), the oil showed strong in vitro growth inhibition activity against Gram-negative bacteria and antifungal activity. The oil exhibited the maximum antifungal activity against Mucor ramaniamus (MIC = 0.2 μL/mL). © 2006 Informa Healthcar

Studies on the essential oil composition and antimicrobial activity of Thymus algeriensis Boiss

Many species of Thymus have been widely used in Algerian folk medicine as astringent, expectorant and cicatrising agents. This study was designed to investigate for the first time the essential oil of the aerial parts of wild growing Thymus algeriensis endemic in North Africa. The volatile oil obtained by hydrodistillation was characterized by the physico-chemical properties, GC and GC/MS techniques. The yield of the oil was 1.13% (w/w), based on dry weight. Fifty-five components, representing 94.3% of the total oil, were identified. The oil was distinguished by its high content of oxygenated monoterpenes (79.5%) and was found to possess the following major components: linalool (47.3%), thymol (29.2%) and p-cymene (6.8%). Furthermore, the oil was tested for antimicrobial activity against four bacteria, two fungi and two yeasts. This oil exhibited a significant in vitro antimicrobial activity against Bacillus subtilis (MIC = 0.5 μL/mL), as well as against all yeast and all filamentous fungi tested (MIC = 0.5 and 1.0 μL/mL). © 2006 Elsevier Ltd. All rights reserve

Chemical composition of the essential oil of Salvia officinalis from Algeria

Sage (Salvia spp.), belonging to the Lamiaceae family, is an aromatic plant and includes about 900 species that grow in several regions all over the world [1]. This genus showed a very high variability of both morphological and cariological characters [2]. Since ancient times, this genus has been used in folk medicine and as a flavoring agen

Adsorption d’un tensio-actif cationique sur électrode à mercure

L'objectif de ce travail est d'étudier l'adsorption d'un tensioactif cationique le DTAB (dodécyltriméthylammonium bromure), en présence d'un sel NaBr, en utilisant comme surface modèle l'électrode à mercure. Les essais ont montré que ce cationique forme une bi- couche. Ce résultat diffère de celui trouvé antérieurement avec un détergent anionique de même longueur de chaîne aliphatique, le SDS ou dodécylsulfate de sodium en présence de NaCl, mais semblable à celui des détergents cationiques le CTAC (cétyltriméthyl ammonium chlorure) ou le CTAB (cétyltriméthyl-ammonium bromure) en présence respectivement de KCl et KBr. Les courbes isopotentielles ont permis de délimiter les valeurs de la CMC (concentration micellaire critique). L'addition de sels diminue la CMC. Il apparaît que pour le DTAB, ces variations sont liées non seulement à un effet de couche diffuse mais aussi à un effet de relargage

A Transfer Learning Approach to Classify the Brain Age from MRI Images

Predicting brain age from Magnetic Resonance Imaging (MRI) can be used to identify neurological disorders at an early stage. The brain contour is a biomarker for the onset of brain-related problems. Artificial Intelligence (AI) based Convolutional Neural Networks (CNN) is used to detect brain related problems in MRI images. However, conventional CNN is a complex architecture and the time to process the image, large data requirement and overfitting are some of its challenges. This study proposes a transfer learning approach using InceptionV3 to classify brain age from the MRI images in order to improve the brain age classification model. Models are trained on an augmented OASIS (Open Access Series of Imaging Studies) dataset which contains 411 raw and 411 masked MRI images of different people. The models are evaluated using testing accuracy, precision, recall, and F1 Scores. Results demonstrate that InceptionV3 has a testing accuracy of 85%. This result demonstrates the potential for InceptionV3 to be used by medical practitioners to detect brain age and the potential onset of neurological disorders from MRI images

Synthesis, crystal structure and antibacterial activity of new highly functionalized ionic compounds based on the imidazole nucleus

International audienceSeveral new highly functionalized imidazolium derivatives were synthesized, via appropriate synthetic routes, using imidazole, 1-methylimidazole and 2-phenyl-1-methylimidazole as key intermediates. The antibacterial activity of the prepared compounds was evaluated against: Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Salmonella thipymurium using disk-diffusion and MIC methods. Crystal X-ray structures are reported for six compounds

Automatic depletion with Spectra Optia allows a safe 16% reduction of red blood cell pack consumption in exchanged sickle cell anemia patients

International audienc