To investigate the effects of losartan and enalapril on serum uric acid in hypertensive patients with metabolic syndrome, one hundred and twenty six newly diagnosed mild hypertensive patients, having markers of metabolic syndrome included  in the study. The patients were divided into two groups. Group 1 (60 patients) was given losartan (50 mg/ day) and group 2 (66 patients)  enalapril (20 mg/ day) for a duration of 2 months. A control group of seventy apparently healthy individuals were included. Metabolic syndrome was diagnosed according to diagnostic criteria of metabolic syndrome related to the American National Cholesterol Education Program-Adult Treatment Panel III. Serum uric acid levels were measured bef

Objective(s): The main aim of the study is to determine the level of burden on mothers toward children with anorectal malformation.
Methodology: A descriptive study was carried out at Welfare Pediatric Teaching Hospital and Central Pediatric Teaching Hospital in Baghdad City. From November 15th, 2017 to April 29th, 2018. Convenient sample comprised of (140) children mothers with anorectal malformation were interviewed for the study. The instrument of study is composed of six domains related mothers' burden toward psychosocial burden as a result of child with anorectal malformation. Validity of the study instrument was determined through a panel of experts and the reliability of the questionnaire is determined in a pilot study among (1

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

Background: In spite of all efforts, Non-small cell lung cancer (NSCLC) is a fatal solid tumor with a poor prognosis as of its high metastasis and resistance to present treatments. Tyrosine kinase inhibitors (TKI) such as erlotinib are efficient in treating NSCLC but the emergence of chemoresistance and adverse effects substantially limits their single use. Objective: in this study, the combination treatments of either 2-deoxy-D-glucose (2DG) or cinnamic acid (CINN) with erlotinib (ERL) were tested for their possible synergistic effect on the proliferation and migration capacity of NSCLC cells. Methods: In this study, NSCLC model cell line A549 was used to investigate the effects of single compounds and their combination on cell gro

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe