This study has been carried out to evaluate the expression level of beta 2 microglobulin gene on patients infected by hepatitis C virus before and after treatment with interferon. The study included 117 hepatitis C patients comprising as 63 pre-treated patients, the range of age was between 20-65 year with a mean age of 48.12 ± 16.1 and 54 post-treated patients with age range was between 23-63 year with the mean of 46.1 ± 18.1. Also it was found that more than half of patients were located within third and fourth decade i.e. 30-49 year, with a percentage of 52.4% and 55.6 % for pre-treatment and post-treatment patients respectively. Moreover , regarding both groups, males are more than females with the ratio of ( 3.2:1) among pre-treatment group and 2:1 among post-treatment group. Further , It has been found that the concentration of ?2 microglobulin was (3.425±0.943mg/L) among pre-treatment group and (1.860±0.723 mg/L) among post-treatment group with significant correlation (P=0.05). Besides that , in the present study ,It has been found the concentration of ?2 microglobulin was decrease after treatment from (3.425±0.943 mg/L) to (1.860±0.723mg/L) which was statistically significant (P=0.05) , Thus ?2 microglobulin can be used as a supporting marker of responsiveness to treatment with interferon in hepatitis C patients as well as indicator for monitoring the disease progression.
Cranberry (Vaccinium macrocarpon) is a North American natural fruit. consumed as food and used for health promotion and prevention of various diseases. Aim. The present study was designed to evaluate the protective effect of cranberry fruit extract on nephrotoxicity induced by cisplatin in mice by measuring selected oxidative stress markers. Methods. Twenty-eight male albino mice were used in this study. The animals were divided into 4 groups as follows: Group I [Negative Control]/orally-administered normal saline for 7 successive days; Group II [Orally-administered cranberry fruit extract alone (200 mg/kg) for 7 successive days; Group III/Mice IP injection with cisplatin (12mg/kg) on day 7 and; Group IV [Orally-administered cr
... Show MoreNitrogen dioxide NO2 is one of the most dangerous contaminant in the air, its toxic gas that cause disturbing respiratory effects, most of it emitted from industrial sources especially from the stack of power plants and oil refineries. In this study Gaussian equations modelled by Matlab program to state the effect of pollutant NO2 gas on area around Durra refinery, this program also evaluate some elements such as wind and stability and its effect on stacks height. Data used in this study is the amount of fuel oil and fuel gas burn inside refinery at a year 2017. Hourly April month data chosen as a case study because it’s unsteady month. After evaluate emission rate of the all fuel and calculate exit velocity from
... Show MoreThroughout this paper, a generic iteration algorithm for a finite family of total asymptotically quasi-nonexpansive maps in uniformly convex Banach space is suggested. As well as weak / strong convergence theorems of this algorithm to a common fixed point are established. Finally, illustrative numerical example by using Matlab is presented.
Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.
... Show MoreArtificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit