Background: Hypertension and dyslipidemia are
cardiovascular risk factors that commonly coexist .
Objective : To evaluate the effects of ß - blocker
(Atenolol) , ACE inhibitor (Captopril) calcium Channel
blocker (Nefidipin ) and diuretics on serum lipid profiles .
Method: Thirty untreated hypertensive and 147
hypertensive patient treated with these antihypertensive
drugs, attending different public health clinics in Basrah
pronivce were enrolled in this study .
Serum lipid profile were determined enzymaticaly using kits
from BioMerieux, France .
Result : The study has revealed that ß-blocker do not
significantly affect total cholesterol ( TC ) and LDLcholesterol , but increase significantly triglycer

ten albino male rates were orally treated daily 20% and 30% ethanol for 30 days treatment with 30%ethanol caused of hippocampuse of darckness google hospital patients

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Background: Dyslipidemia is a major cause of
cardiovascular disease, which in turn, is the most
common cause of female morbidity and mortality.
Postmenopausal women (natural and surgical) are at
higher risk of developing cardiovascular disease,
especially coronary artery atherosclerosis.
Objective: To observe the relationship between blood
lipids: total cholesterol (TC), high density lipoproteincholesterol (HDL-C), low density lipoproteincholesterol (LDL-C), triglycerides (TGs), and very low
density lipoprotein- cholesterol (VLDL-C), LDL-C/
HDL-C ratio (atherogenic index) and menopausal
status, and to determine the co-factors that may explain
this relationship
Methods: A prospective, cross-sectional st

This study included nine patients with inactive carrier states of HBV and 14 healthy control groups. The number and the percentage of T-lymphocyte (CD3+ Cells) in the peripheral blood of these groups showed no significant difference. Similar trend was observed when number and percentages of T helper cells (CD4+ cells) and T cytotoxic lymphocytes (CD8+ cells). Moreover, no significant difference in CD4+ /CD8+ cells ratio (P > 0.05) in peripheral blood of patients with inactive carrier state of HBV as compared with healthy control group. The levels of total serum bilirubin (TSB) concentration and alanine aminotransferase (ALT) activity were similar to control group. The levels of immunoglobulin concentration (IgG and IgM) in patients g

The detection for Single Escherichia Coli Bacteria has attracted great interest and in biology and physics applications. A nanostructured porous silicon (PS) is designed for rapid capture and detection of Escherichia coli bacteria inside the micropore. PS has attracted more attention due to its unique properties. Several works are concerning the properties of nanostructured porous silicon. In this study PS is fabricated by an electrochemical anodization process. The surface morphology of PS films has been studied by scanning electron microscope (SEM) and atomic force microscope (AFM). The structure of porous silicon was studied by energy-dispersive X-ray spectroscopy (EDX). Details of experimental methods and results are given and discussed

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect