Medicinal plants contain bioactive substances that are highly bioavailable in extracts or pure molecules, making them promising for therapeutic applications and precursors for chemo-pharmaceutical semi-synthesis. Harpagophytum procumbens (Devil’s Claw) is widely recognized as one of the most potent therapeutic herbs. This study aimed to extract seeds from H. procumbens using two types of solvents and to assess both qualitative and quantitative aspects of the extracts. The two extracts were evaluated for antibacterial and anti-biofilm activities using agar well diffusion assays against four bacterial isolates and two yeast isolates. Qualitative analysis identified the presence of alkaloids, flavonoids, tannins, saponins, and terpenoids. The active components detected were: alkaloids (12.69%), flavonoids (3.25%), total phenolic compounds (24.58%), total terpenoids (8.55%), and total steroids (1.25% for methanolic and 4.55% for petroleum ether). Both methanolic and petroleum ether extracts exhibited antioxidant activities of approximately 85.33% and 74.19%, respectively, compared to ascorbic acid, which had an antioxidant effect of 67.99% at a concentration of 200 µg/ml. The extracts demonstrated a broad spectrum of activity against all tested bacteria (Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus pyogenes) and fungi (Candida albicans, C. tropicalis, C. parapsilosis). At a concentration of 1000 µg/ml, the seed extracts showed the highest bactericidal activity, with inhibition zones ranging from 10 to 22 mm. Moreover, both extracts exhibited greater anti-biofilm activity at 1000 µg/ml compared to lower concentrations. Our study found that seed extracts of H. procumbens possess significant antibacterial and antioxidant activities, particularly at a concentration of 1000 µg/ml.
The accurate extracting, studying, and analyzing of drainage basin morphometric aspects is important for the accurate determination of environmental factors that formed them, such as climate, tectonic activity, region lithology, and land covering vegetation.
This work was divided into three stages; the 1st stage was delineation of the Al-Abiadh basin borders using a new approach that depends on three-dimensional modeling of the studied region and a drainage network pattern extraction using (Shuttle Radar Topographic Mission) data, the 2nd was the classification of the Al-Abiadh basin streams according to their shape and widenings, and the 3rd was ex
... Show MoreAzo dyes like methyl orange (MO) are very toxic components due to their recalcitrant properties which makes their removal from wastewater of textile industries a significant issue. The present study aimed to study their removal by utilizing aluminum and Ni foam (NiF) as anodes besides Fe foam electrodes as cathodes in an electrocoagulation (EC) system. Primary experiments were conducted using two Al anodes, two NiF anodes, or Al-NiF anodes to predict their advantages and drawbacks. It was concluded that the Al-NiF anodes were very effective in removing MO dye without long time of treatment or Ni leaching at in the case of adopting the Al-Al or NiF-NiF anodes, respectively. The structure and surface morphology of the NiF electrode were inves
... Show MoreThe research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.
The impregnation method is used in test sample preparation, using molding by pressure presses.
All samples were exposure to (Co60) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.
The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad
... Show MoreThe current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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