The Covid-19 virus disease has been shown to affect numerous organs and systems including the liver. The study aimed to compare lipid profiles and liver enzyme levels in individuals who had recovered from Covid-19 infection. To achieve the study objectives, liver Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT), Alkaline phosphatase (ALP),  Random Blood Sugar (RBS) and Lipid profile which include cholesterol, High-Density Lipoprotein (HDL), Triglycerides (T.G), Low-Density Lipoprotein (LDL), and Very low-density Lipoprotein (VLDL) were determined.

One hundred twenty serum samples were obtained, of which fifty samples were utilized as the control healthy persons (not affected by COVID) and seventy samples came f

This study aims to identify maternal death cases caused by Coronavirus infection 2019 pneumonia, including disease progression, fetal consequences, and the fatality cause.

Patients and methodology: A retrospective case collection of Iraqi pregnant women in their second and third trimesters diagnosed with COVID-19 pneumonia and died due to it.

The four cases were all of a young age, had a brief complaint period, and had no comorbidities. Fever, dyspnea, and fatigue were the most common symptoms. Hypoxia was present in all cases and was the cause of mortality in three cases, with thromboembolism being a potential cause in the fourth. Prelabour membrane breakup, fetal growth restriction, and fetal death are al

Abstract: Coronavirus disease 2019 (COVID-19) is an infectious disease with severe acute respiratory syndrome and first recognized in Wuhan, China, and it has since spread to the world, resulting in the coronavirus pandemic to 2020. The present study aimed to evaluate Molecular study of some types of vaginal fungi isolated from recovered women from Covid-19 in Baghdad governorate. The study was conducted on 213 samples collected between December 2021 and March 2022, where the number of positive samples reached 188 with percentage 88.26%, while the number of negative samples reached 25 with percentage 11.73% by taking vaginal swabs from various female patients in Al- Kadhimiya Teaching Hospital. Three of Candida spp. were isolated: Candida a

Abstract

The pressures of life have become a tangible phenomenon in all societies in varying degrees. This disparity determines several factors, including the nature of societies, the level of their urbanization, the intensity of interaction, the intensity of conflict, and the increasing rate of change in those societies. many people name The modern era in which we live the “era of pressures", where one of the most important of these changes is the “new Coronavirus 19-COVID”, which has spread widely throughout the world, as the pandemic, has affected all aspects of daily life, including the educational and academic process, academic activities have been suspended in universities, which caused sudden change

Since its start spreed "Severe acute respiratory syndrome coronavirus 2" was discovered in Wuhan, China.that is chargeable COVID-19, a pandemic virus, has end up a widespread fitness hassle everywhere in the global Over 2.1 million people have been affected. We analyze serum concentration of CD4 marker and CD8 marker depend in COVID-19 sufferers, and to make clear a relationship between these variables and disorder Progression and severity For those purpose, (158) sufferers with COVID-19 (showed with the aid of using polymerase chain reaction) and (22) seemingly wholesome human beings have been protected withinside the present day examine and taken into consideration as a manipulate group. All examine population (sufferers and manipulate) h

     In this paper, a novel coronavirus (COVID-19) model is proposed and investigated. In fact, the pandemic spread through a close contact between infected people and other people but sometimes the infected people could show two cases; the first is symptomatic and the other is asymptomatic (carrier) as the source of the risk. The outbreak of Covid-19 virus is described by a mathematical model dividing the population into four classes. The first class represents the susceptible people who are unaware of the disease. The second class refers to the susceptible people who are aware of the epidemic by media coverage. The third class is the carrier individuals (asymptomatic) and the fourth class represents the infected ind

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

      The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc :  COVID-19 patients ( without vaccine ) , Gp₁: COVID-19 patients took one dose of Pfizer Biontech, Gp₂ : COVID-19 patients took two doses of Pfizer Biontech, Ga₁ : patients took one dose of AstraZeneca Oxford vaccine , Ga₂: patients took two doses of AstraZeneca Oxford vaccine , Gs₁ : patients took one dose of Sinopharm vaccine and Gs₂:

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