Crade extract of dried fruit piper nigrum was made by useing sexhdet for three hours.The dried material was extracted with 95% ethanol and water as solvent. A test was made to the extract effect in certain concentration to 32 Gram of negative bacterial isolates , collected from patient admitted to Ibn-AL-balade hospital . Ethanolic extract showed antibacterial activity against bacterial isolates and water extract reveled effectivnes.Such isolates showed highly sensitive to Norfacin and Impinene and less sensitve to Amoxicillin .
This research includes study of the effect of two kinds of Anthocyanin extracted , from extracted orange fruit ( Anthocyanin Evolvulus ,Methiola Violet ) on two types of pathological bacteria E.coli , staphylococcus aureus. The result shows that two kinds of extraction have nearly similar effect , and there is Inhibition zone of no growth between 10-12mm ,and the extraction (1) that has concentration of 10-3 mol./L is more effective..
Background: The beneficial gut bacterium E. coli can cause blood poisoning, diarrhoea, and other gastrointestinal and systemic disorders. Objective: This study amid to examines the antibiofilm activity of Laurus nobilis leaves extract on E. coli isolates and compares pre- and post-treatment gene expression of fimA and papC genes. Subjects and Methods: Ten isolates of E. coli were obtained from the Genetic Engineering and Biotechnology Institute, University of Baghdad, which was previously collected from Baghdad city hospitals and diagnosed by chemical tests, the diagnosis was confirmed using VITEK-2 System. The preparation of the aqueous and methanolic Laurus nobilis leaves extracts was done by using the maceration method and Soxhlet appara
... Show MoreIn this research, silver nanoparticles (AgNPs) were manufactured using aqueous extract of mushroom Pleurotus ostreatus. Anticancer potential of AgNPs was investigated versus human breast cancer cell line (MCF-7). Cytotoxic response was assessed by MTT assay. AgNPs showed inhibition effect at the following concentrations 12.5, 25, 50, 100 and 200 µg/ml versus MCF-7 cell line, and all treatments had a positive result. The MCF-7 cells were inhibited up to 85.14 % at the concentration 200 μg/ml of AgNPs which reduced cells viability to 14.86%, while 12.5 μg/ml of AgNPs caused 24.23% cells inhibition with reduction of cells viability to 75.77%.
The study was conducted to evaluate the antifungal activity of the aqueous and
alcoholic extract and the essential oil of E. incrassata leaves toward some biological
characteristics of the water mold S. ferax. Chemical analysis of the plant leaves using HPLC
showed the content of several active compounds included 1,8-Cineole, Terpineal, Citronellal,
Phellendrene and Citiric acid.
Treatment of the fungus growing on solid media containing different concentrations of
the extracts showed significant gradual decrease in radial growth with the increasing
concentration, and the effect varied with the different extracts.
Treatment of the fungus grown in distilled water on sesame seeds with different
concentratio
This study was conducted with the aim to extract and purify a polyphenolic compound “ Resveratrol†from the skin of black grapes Vitis vinifera cultivated in Iraq. The purified resveratrol is obtained after ethanolic extraction with 80% v/v solution for fresh grape skin, followed by acid hydrolysis with 10% HCl solution then the aglycon moiety was taken with organic solvent
( chloroform). Using silica gel G60 packed glass column chromatography with mobile phase benzene: methanol: acetic acid 20:4:1 a
... Show MoreCorrect grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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