Objective: In this study ,the effects of silver nanoparticles (Ag NPs)were investigated on the liver and kidney tissues. Methodology: The produced nanoparticles have an average particle size of about 30 nm. Eighteen male albino rats were used by dividing them into three groups, each group comprise 6 rats. First group(control group) given food and water like other groups by liberty. Second group was tail injected by (AgNPs) at dose of (0.4 mg/kg. body weight/day). Third group was injected by (AgNPs) at dose of (0.6 mg/kg. body weight/day) for 15 days. All animals were sacrified at the end of experiment. The liver and kidney tissues specimens were fixed in 10% formalin and histological preparations were carried out then stained with H&E. Path

The neutrophil/ lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) have the potential to be inflammatory markers that reflect the activity of many inflammatory diseases. The aim of this study was to evaluate the NLR and PLR as potential markers of disease activity in patients with ankylosing spondylitis.

         Seventy five E. coli isolates were collected from urine of patients with urinary tract infections in AL-Kadhimia and AL-Yarmook teaching hospitals in Baghdad for a period between 22/11/2009 to 15/3/2010,  from these samples twenty five isolates were selected according to their pattern of the highest resistance as these showing multi-drug resistances and tested to specify their minimum inhibitory concentration for (meropenem, gentamicin and amikacin), meropenem was found having the lowest MIC comparing with others. This study also includes in vitro effects of various combinations of three types of antimicrobials (meropenem, gentamicin and amikacin) against twenty five E. c

AW Ali T, Journal of the Faculty of Medicine, 2016 - Cited by 1

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

A study carried out to prepare Hg1-xCdxTe compound and to see the effect on increasing the percentage of x on the compound structure by using x-ray diffraction and atomic absorption for 0