Background: Arylesterase activity of Paraoxonase-1 (ARE-PON-1) exhibits an antioxidant role which protects lipoprotein from oxidation. It is known that ARE-PON-1 antioxidant activity associated with high density lipoprotein cholesterol (HDL-C) reduces the oxidative damage mediated by low density lipoprotein cholesterol (LDL-C). The present study was aimed to examine the level of serum ARE-PON1 in Iraqi patients with β-thalassemia minor and its relationship with lipid profile (total cholesterol (TC), HDL-C, very low density lipoprotein (VLDL-C), and LDL-C) and hematologic changes as a part of antioxidant system action. Methods: In the present study, the ARE-PON-1 activity was investigated in serum of patients with β-thalassemia minor. Resu

The poly(ethylene oxide) polymer (PEO) is doped with fine powder of MnCl₂ salt and thin films of thickness (50–150 mm) with salt content (0, 5, 10, 15, and 20 wt%) are obtained. The AC electrical conductivity and dielectric constants are studied as a function of temperature through an impedance technique. It is found that AC conductivity increases and the calculated activation energy decreases with increasing temperature due to enhancement of the ionic conduction in the film bulk. The dielectric constants of the doped membranes increase with temperature. It is found that the peak value of the tanloss is shifted to a higher frequency at higher temperatures. The dielectric behavior is explained on the basis of

Background: Differentiation between malignant and benign vertebral compression fracture is often problematic. This is precisely difficult in elderly who are predisposed to benign compression caused by osteoporosis .Establishing correct diagnosis is of great importance in determining the treatment andprognosis.A study was performed to determine which magnetic resonance imaging findings are useful in discrimination between metastatic and acute osteoporotic compression fractures of the spine. Recently MRI is being increasingly used for evaluation of these fractures.Objectives: The aim of this study is to establish the correct diagnosis of malignant and benign compression vertebral fracture by MRI to determine treatment and prognosis.Methods

Oscillation criteria are obtained for all solutions of the first-order linear delay differential equations with positive and negative coefficients where we established some sufficient conditions so that every solution of (1.1) oscillate. This paper generalized the results in [11]. Some examples are considered to illustrate our main results.

To determine the seroprevalence of hepatitis B markers in chronic hepatitis B patients, 75 patients with chronic hepatitis B virus of ages (8-70) years have been investigated and compared with 50 apparently healthy individuals. All the studied groups were carried out to measure (HBsAg), (HBsAb), (HBeAg), (HBeAb), and (Total HBcAb) by Enzyme linked immunosorbent assay (ELISA) technique. The percentage distribution of HBsAg was (86.67%) and HBsAb was (1.33%) in sera of CHB patients and there were a highly significant differences (P<0.01) when compared between studied groups, while, the percentage distribution of HBeAg was (22.67%) in sera of CHB patients and the significant represent the difference in distribution of HBeAg as infection but no

Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class