Antibiotic resistance is the major growing threat facing the pharmacological treatment of bacterial infections. Therefore, bioprospecting the medicinal plants could provide potential sources for antimicrobial agents. Mimusops, the biggest and widely distributed plant genus of family Sapotaceae, is used in traditional medicines due to its promising pharmacological activities. This study was conducted to elucidate the antimicrobial effect of three unexplored Mimusops spp. (M. kummel, M. laurifolia and M. zeyheri). Furthermore, the mechanisms underlying such antibacterial activity were studied. The Mimusops leaf extracts revealed significant antibacterial activities against the five tested bacterial strains with a maximum inhibition zone diameter of 22.0 mm against B. subtilis compared with standard antibiotic ciprofloxacin. The minimal inhibitory and bactericidal concentration values against tested Gram-positive and Gram-negative bacterial strains ranged from 3.15-12.5 µg/ml. However, weak antifungal effect was recorded against Candida albicans with MIC value ˃25 µg/ml. The 1, 1-diphenyl-2-picrylhydrazyl (DPPH) assay showed that M. caffra was the best antioxidant (IC50=14.75±0.028 µg/ml), while M. laurifolia was the least one (IC50=34.22±0.014 µg/ml). The phenolics in plant leaves extracts were identified and quantified by high performance liquid chromatography (HPLC) which revealed the presence of seven phenolic acids and four flavonoids. The abundant phenolic compounds were rutin (5.216±0.067 mg/g dried wt.) and gallic acid (0.296±0.068 mg/g) followed by myricetin (0.317±0.091 mg/g) then kaempferol (0.113±0.049 mg/g) as flavonoids. The antibacterial mechanism of M. laurifolia extract, as a representative species, induces ultrastructural changes in the model bacterium Staphylococcus aureus with cell wall and plasma membrane lysis as revealed by transmission electron microscopy. Overall, Mimusops species (M. laurifolia, M. kummel and M. zeyheri) are promising natural alternative sources for antimicrobial agents.
Eight new complexes with the general formula [M(L)2(H2O)2] were prepared resulting from the reaction of the new Schiff base ligand [(E)-5- ((2-hydroxybenzylidene)amino)-2-phenyl-2,4-dihydro-3H-pyrazol-3- one(L)] with metal ions [manganese, cadmium, zinc, copper, nickel, cobalt, Mercury Bivalent and tetravalent platinum. This ligand was derived from the reaction of the amine (5-amino-2-phenyl-2,4-dihydro3H-pyrazol-3-one) with Salicylaldehyde, which is linked to the metal ions via two atoms. The nitrogen is the isomethene group, and the oxygen is the hydroxide group of the pyrazoline ring. The prepared compounds were characterized using infrared spectroscopy, nuclear magnetic resonance spectroscopy, and ultraviolet spectroscopy, and from the
... Show MoreWater quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor
... Show MoreWater quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin
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Globalisation and rapid environmental change have created many challenges for public and private organisations across Iraq as a developing country, particularly in the higher education sector. This includes, for example, decreases in government funding; increased demand for higher education; a need for economic transformation, and related competitiveness of organizations. Such challenges require exceptional leaders and strategic planning in order to take action to improve. In Iraq, the higher education sector is still one of the main foundations in progressing the knowledge economy. Studies into leadership style, strategic planning processes, and the importance of leadership and organisational culture to an organisation’s success have bee
... Show MoreThe chemical additives used to enhance the properties of drilling mud cause damage to humans and the environment. Therefore, it is necessary to search for alternative additives to add them to the drilling mud. Thus, this study investigates the effects of pomegranate peel and grape seed powders as natural waste when added to un-weighted water-based mud. The test includes measurements of the rheological properties and filtration, as well as the alkanity and density of the drilling mud. The results showed a decrease in PH values with an increase in the concentrations of pomegranate peel or grapeseed, and a decrease in mud density with an increase in powders of pomegranate peel and grape seed concentrations that resulted f
... Show MoreObjective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.
Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are
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