The severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) or 2019 novel coronavirus (2019-nCoV) is quickly spreading to the rest of the world, from its origin in Wuhan, Hubei Province, China. And becoming a global pandemic that affects the world's most powerful countries. The goal of this review is to assist scientists, researchers, and others in responding to the current Coronavirus disease (covid-19) is a worldwide public health contingency state. This review discusses current evidence based on recently published studies which is related to the origin of the virus, epidemiology, transmission, diagnosis, treatment, and all studies in Iraq for the effect of covid-19 diseases, as well as provide a reference for future research

At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

ABSTRACT: In dental practice there are many wrong habits that should be recognized and treated. One of them is the irrational antibiotic (AB) administration by patient. This indeed created an important issue in dental clinics first of all drug resistance and super infection. This was analyzed in our study and then the causes were identified and a plan suggested in recommendation hope that it will minimize the outcomes. Results: all those patients were finally subjected to be clinically diagnosed and treated this lead to only one fact, these antibiotics are not effective in one way or another since they are not prescribed by dentist

Orthodontic tooth movement is characterized by tissue reactions, which consist of an inflammatory response in periodontal ligament and followed by bone remodeling in the periodontium depending on the forces applied. These processes trigger the secretion of various proteins and enzymes into the saliva. The purpose of this study was to evaluate the activity of the lactate dehydrogenase (LDH) in saliva during orthodontic tooth movement using different magnitude of continuous orthodontic forces. Thirty orthodontic patients (12 males and 18 females) with ages 17-23 years with class II division I malocclusion all requiring bilateral maxillary first premolar extractions. Those patients were randomly divided into 3 groups according to the magnitude

Background: Dental erosion is a common oral condition which results due to consumption of high caloric and low pH acidic food such as carbonated drinks and fruit juices. It is expected that these food types can cause irreversible damage to dental hard tissues and early deterioration of the dental restorations. So, this study aimed to evaluate and compare the erosive potential effects of orange fruit juice and Miranda orange drink on the microhardness of an orthodontic composite material. Materials and methods: Thirty discs with a thickness of 2 mm and a diameter of 10 mm were prepared from orthodontic bonding composite. The prepared discs were equally divided into three groups (n=10). Microhardness analysis was carried out both prior to

Objectives: The objectives of the present study are to identify both, the rate of urinary tract infections (UTI) in medical
and surgical wards in Baghdad Teaching Hospital and the common types of microorganisms that cause this type of NIs,
study the resistance of isolated microorganisms to several types of antibiotic and the effect of some disinfection
material like Iodine, chlorhexidine and septicin on the growth of these isolates.
Methodology: This is descripƟve study carried out from 1\6\2009 to 1\11\2009. A total of 200 paƟents were admiƩed
to medical and surgical wards in Baghdad teaching hospital, paƟents were divided into two group 100 paƟents, in
surgical ward and 100 paƟents in medical ward. Some of impor

Objective: Comprehending microbial diversity and antibiotic resistance patterns is essential for efficient treatment protocols. This study sought to determine the incidence of bacterial and fungal pathogens responsible for burn and wound infections and their antibiotic susceptibility profiles. Methods: This cross-sectional study involved 140 patients with burn or wound infections. Sterile swabs and pus aspiration were employed to collect samples, which were subsequently processed using standard microbiological procedures. Antibiotic resistance was determined using the Kirby-Bauer disc diffusion method, following Clinical and Laboratory Standards Institute (CLSI) guidelines. Data was analysed using IBM SPSS version 25.0, and the Chi-

Biomarkers such as Interleukin-6 (IL-6), Procalcitonin (PCT), C-reactive protein (CRP) and Neutrophil-Lymphocyte Ratio (NLR) have a role in the pathogenesis of severe coronavirus disease 2019 (COVID-19). The aim of this study was to explore the differences between serum levels of such biomarkers in severe and non-severe COVID-19 cases and compare them with normal people and to evaluate the sociodemographic variables and chronic diseases effect on the severity of COVID-19. The study included 160 subjects, divided into two groups, a case group of 80 patients, and a control group of 80 normal persons. The case group was divided into two subgroups: 40 severe COVID-19 patients and 40 patients with non-severe disease. Blood IL-6 was asses