Peroxidase is a class of oxidation-reduction reaction enzyme that is useful for accelerating many oxidative reactions that protect cells from the harmful effects of free radicals. Peroxidase is found in many common sources like plants, animals and microbes and have extensive uses in numerous industries such as industrial, medical and food processing. In this study, P. aeruginosa was harvested to utilize and study its peroxidases. P. aeruginosa was isolated from a burn patient, and the isolate was verified as P. aeruginosa using staining techniques, biochemical assay, morphological, and a sensitivity test. The gram stain and biochemical test result show rod pink gram-negative bacteria, and ensure that the isolate was that of P. aeruginosa. Optimization for bacterial growth were done by used more than pH (5,7,9) and temperatures (32,35,37°C), and it was found that the best growth conditions were at pH 5.5, producing (4.5x108cells), and a temperature of 37°C, with (5.25x108cells) being produced. Intracellular enzymes were extracted by ultra-sonication that used frequencies of ultrasound 30 kHz for 20 min in 4 °C, and was centrifuged at 13000×g for 5min. The supernatant was then re-used as a crude enzymatic extract and the cell pellet was discarded. Purification of peroxidase was accomplished by using salt precipitation, dialysis, gel filtrations and ion exchange chromatographic techniques. The result shows that gel filtration has optimal specific activity and purification fold at (61 U/ml), purification fold 6 times and then the improvement enzyme was applied as H2O2 scavenging activity antioxidant by used three concentration of enzyme (10,40,60 µg/ml), and show higher scavenging activity at 60 µg/ml, which reached to 45% scavenging activity. The enzyme was also used as anticancer agent, which was verified by using three concentration of enzyme (10,15,20 µg/ml) which show a significant kill for Mcf-7cells at (15µg/ml), with cytotoxicity activity reaching (45%).
Abstract
The purpose of our study was to develop Dabigatran Etexilate loaded nanostructured lipid carriers (DE-NLCs) using Glyceryl monostearate and Oleic acid as lipid matrix, and to estimate the potential of the developed delivery system to improve oral absorption of low bioavailability drug, different Oleic acid ratios effect on particle size, zeta potential, entrapment efficiency and loading capacity were studied, the optimized DE-NLCs shows a particle size within the nanorange, the zeta potential (ZP) was 33.81±0.73mV with drug entrapment efficiency (EE%) of 92.42±2.31% and a loading capacity (DL%) of 7.69±0.17%. about 92% of drug was released in 24hr in a controlled manner, the ex-vivo intestinal p
... Show MoreThe aim of this article is to solve the Volterra-Fredholm integro-differential equations of fractional order numerically by using the shifted Jacobi polynomial collocation method. The Jacobi polynomial and collocation method properties are presented. This technique is used to convert the problem into the solution of linear algebraic equations. The fractional derivatives are considered in the Caputo sense. Numerical examples are given to show the accuracy and reliability of the proposed technique.
The study was carried out to determine the cytotoxic, antioxidant and gastro-protective effect of ethyl-4-[(3,5-di-tert-butyl-2-hydroxybenzylid ene)amino] benzoate (ETHAB) in rats.
Abstract
This research aims to analyze the reality of the production process in an assembly line Cars (RUNNA) in the public company for the automotive industry / Alexandria through the use of some Lean production tools, and data were collected through permanence in the company to identify the problems of the line in order to find appropriate to adopt some Lean production tools solutions, and results showed the presence of Lead time in some stations, which is reflected on the customer's waiting time to get the car, as well as some of the problems existing in the car produced such as high temperature of the car, as the company does not take into account customer preferences,
... Show MoreThis paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi