Cutaneous leishmaniasis is a disease caused by Leishmania tropica parasite. Current treatments for this parasite are undesirable because of their toxicity, resistance, and high cost. Macrophages are key players against pathogens. Nitric oxide (NO), a molecule produce by immune cells, controls intracellular killing of pathogens during infection. Silver nanoparticles (Ag NPs) demonstrated broad-spectrum activity against various types of infectious diseases. It has the ability to stimulate oxygen species production. This study aims to analyze the macrophages activation through NO production and estimate the cytotoxicity based on the lactate dehydrogenase (LDH) release upon exposure to L. tropica and Ag NPs. Serially concentrations of Ag NPs were used under two conditions during and following macrophages exposure to L. tropica. MTT assay was used to determine the cytotoxicity of Ag NPs on L. tropica amastigotes during infection of macrophages in vitro. The results showed that by increasing the Ag NPs concentrations, the viability percentage of L. tropica amastigotes decreased and reached to 21.7 ± 0.64 % during infection compared with the control. The 50% inhibitory concentration of Ag NPs on amastigotes was 2.048µg/ml during infection. Moreover, post-phagocytosis study involved the assessment of NO and LDH release by macrophages upon exposure to L. tropica. It have shown that untreated macrophages released low levels of NO while in the presence of Ag NPs, macrophages were activated to produce higher levels of NO under all experimental conditions. On the other hand, macrophages were capable of controlling cytotoxicity and decreasing LDH levels during phagocytosis of L. tropica amastiogotes. Taking together, these findings suggest that Ag NPs can enhance macrophages NO production which provides a method for the identification of Ag NPs ligands with microbicidal and anti-cytotoxic properties against L. tropica pathogens.
This paper presents the results of experimental investigation carried out on concrete model piles to study the behaviour of defective piles. This was achieved by employing non-destructive tests using ultrasonic waves. It was found that the reduction in pile stiffness factor is found to be about (26%) when the defect ratio increased from (5%) to (15%). The modulus of elasticity reduction factor as well as the dynamic modulus of elasticity reduction factor increase with the defect ratio
Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately de
... Show MoreThe present investigation is concerned for the purification of impure zinc oxide (80-85 wt %) by using petroleum coke
(carbon content is 76 wt %) as reducing agent for the impure zinc oxide to provide pure zinc vapor, which will be
oxidized later by air to the pure zinc oxide.
The operating conditions of the reaction were studied in detail which are, reaction time within the range (10 to 30 min),
reaction temperature (900 to 1100 oC), air flow rate (0.2 to 1 l/min) and weight percentage of the reducing agent
(petroleum coke) in the feed (14 to 30 wt %).
The best operating conditions were (30 min) for the reaction time, (1100 oC) for the reaction temperature, (1 l/min) for
the air flow rate, and (30 wt %) of reducing
A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
Pure SnSe thin film and doped with S at different percentage (0,3,5,7)% were deposited from alloy by thermal evaporation technique on glass substrate at room temperature with 400±20nm thickness .The influences of S dopant ratio on characterization of SnSe thin film Nano crystalline was investigated by using Atomic force microscopy(AFM), X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), Hall Effect measurement, UV-Vis absorption spectroscopy to study morphological, structural, electrical and optical properties respectively .The XRD showed that all the films have polycrystalline in nature with orthorhombic structure, with preferred orientation along (111)plane .These films was manufactured of very fine crystalline size in the ra
... Show MoreA Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.