Covid-19 is a respiratory disease similar to pneumonia that results from an infection with SARS-CoV-2, a recently identified virus that became a global pandemic in 2020. The severe cases of the disease show a cytokine storm, which is excessive, uncontrolled production of pro inflammatory cytokines. MicroRNA-155 is an epigenetic microRNA that has the ability to control pro-inflammatory responses in many diseases. We aim to determine the relationship between microRNA-155 expression and some cytokines (interleukin-6, interleukin-8, and interleukin-1β) in severe covid-19 cases. A case-control study of 235 samples was collected from 120 patients with severe covid-19 and 115 of mild covid-19 cases and healthy individuals of different sexes and ages. After RNA extraction and conversion to cDNA, RT-PCR was performed on both studied groups. The levels of studied interleukins were determined for 50 severe covid-19 patients and 40 control individuals (mild and healthy). A substantial elevation in the expression of microRNA-155 was seen in severe COVID-19 patients compared to its expression in the control group consisting of mild cases and healthy individuals. Interleukin-6, interleukin-8, and interleukin-1β also show elevated levels in severe covid-19 serum than control individuals. This investigation revealed a strong and statistically significant correlation between the expression of microRNA-155 and interleukin-6, as well as a substantial correlation between the expression of microRNA-155 and interleukin-1β. MicroRNA-155 might have a role in inducing some pro-inflammatory interleukins that leads to cytokine storm.
‎ Since the first outbreak in Wuhan, China, in December 31, 2019, COVID-19 pandemic ‎has been spreading to many countries in the world. The ongoing COVID-19 pandemic has caused a ‎major global crisis, with 554,767 total confirmed cases, 484,570 total recovered cases, and ‎‎12,306 deaths in Iraq as of February 2, 2020. In the absence of any effective therapeutics or drugs ‎and with an unknown epidemiological life cycle, predictive mathematical models can aid in ‎the understanding of both control and management of coronavirus disease. Among the important ‎factors that helped the rapid spread of the ep
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Background: Helicobacter pylori (H. pylori) infection is associated with gastritis and may induce atrophic gastritis have specific circulating immunoglobulin G (IgG) antibodies.
Aim of the study: To confirm the correlation between Helicobacter pylori infection and gastric atrophy.
Patient and Method: A study was conducted in the period between December 2005 and March 2006 on 25 patients with atrophic gastritis attending Gastroenterology and Hepatology Teaching Hospital in Baghdad, and 25 healthy volunteers who agreed to donate blood. Sera were tested for H. pylori IgG Ab by ELISA test.
Results and Conclusions: detection of H. pylori IgG Ab were applied to each individual, showed that (92 %) of patie
The internet has been a source of medical information, it has been used for online medical consultation (OMC). OMC is now offered by many providers internationally with diverse models and features. In OMC, consultations and treatments are available 24/7. The covid-19 pandemic across-the-board, many people unable to go to hospital or clinic because the spread of the virus. This paper tried to answer two research questions. The first one on how the OMC can help the patients during covid-19 pandemic. A literature review was conducted to answer the first research question. The second one on how to develop system in OMC related to covid-19 pandemic. The system was developed by Visual Studio 2019 using software object-oriented approach. O
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Background: Asthma is one of the most common chronic respiratory diseases in the world, standing for the most frequent cause for hospitalization and emergency cases. Respiratory viruses are the most triggering cause. Aim: To assess the role of viral infections, especially COVID-19, in the pathogenesis of asthma initiation and exacerbations. Method: Electronic search was done for the manuscripts focusing on asthma as a risk factor for complications after COVID-19 infection. The outcomes were titles, materials, methods and classified studies related or not related to the review study. Three hundred publications were identified and only ten studies were selected for analysis. Seven studies were review, one retrospective, one longitudin
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This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.
This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.
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Background: Medical educators’ dissatisfaction may cause them to leave the practice of teaching, where it is often hard to replace those who have left. In addition, medical teaching staff dissatisfaction may indicate adverse quality for institution/ university organizations.
Objectives: To assess teaching staff satisfaction with online learning during the COVID pandemic at Al-Nahrain University /College of Medicine, Baghdad/Iraq.
Methodology: A cross-sectional study included a convenient sample of 50% of the teaching staff participating in the online academic year 2020-2021. The faculty satisfaction questionnaire was taken from the "Bolliger and Halupa" study, based on th
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This research aims to numerically solve a nonlinear initial value problem presented as a system of ordinary differential equations. Our focus is on epidemiological systems in particular. The accurate numerical method that is the Runge-Kutta method of order four has been used to solve this problem that is represented in the epidemic model. The COVID-19 mathematical epidemic model in Iraq from 2020 to the next years is the application under study. Finally, the results obtained for the COVID-19 model have been discussed tabular and graphically. The spread of the COVID-19 pandemic can be observed via the behavior of the different stages of the model that approximates the behavior of actual the COVID-19 epidemic in Iraq. In our study, the COV
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The current research aims to identify the degree to which a sample of managers in public organizations appreciated the level of application of the service leadership style from their point of view, and its relationship to the customer satisfaction index in light of the (Covid-19) pandemic, to achieve this, the researcher followed the experimental approach by applying a questionnaire that included two axes, The first: to measure the level of service leadership according to the scale (D. Van Dierendonck and I. Nuijten, 2011), which includes (8) dimensions (empowerment, stand back, accountability, courage, forgiveness, Authenticity, humility, stewardship). The second axis: to measure the level of customer satisfaction according to (Askim, 2004
... Show MoreBackground: Colorectal is a worldwide health problem. Tumors stimulate the ground of host blood vessels, a process called angiogenesis, which is essential for supplying nutrients of the tumor, also stimulate the lymphatic vessels for metasatasis.
This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being 0.66975075, 0.470
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