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Cytokine profile in COVID-19 infection: focus on interleukin-13, interleukin-33, and tumor necrosis factor-α as immunological markers
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COVID-19 is a pandemic disease that has a wide spectrum of symptoms from asymptomatic to severe fatal cases due to hyperactivation of the immune system and secretion of pro-inflammatory cytokines. This study aimed to assess the level and impact of interleukin (IL)-13, IL-33, and tumor necrosis factor (TNF)-α cytokines on immune responses in mild and moderate COVID-19-infected Iraqi patients. A prospective case-control study was conducted from January 2023 to January 2024; it included 80 patients infected with moderate COVID-19 infection who consulted in different private clinics and 40 healthy controls. The serum of both groups was tested for quantification of serum IL-13, IL-33, and TNF-α using the human enzyme-linked immunosorbent assay method. The mean age of the moderate COVID-19 patient group was 43.67±1.85 years, while the mean age of the healthy control group was 34.45±3.12 years with a statistically significant (p=0.0081), but there was no statistically significant difference in IL-13, IL-33, and TNF-α levels between the patients and control groups. This study highlights the importance of age, gender, and body mass index as risk factors associated with COVID-19 infection. There were no significant differences in IL-13, IL-33, and TNF-α levels between moderate COVID-19 patients and healthy controls. The receiver operating characteristic curve analysis of IL-13, IL-33, and TNF-α shows moderate potential (non-significant) as a biomarker for predicting mild and moderate COVID-19. Pearson correlation analysis showed a strong potential correlation between IL-13, IL-33, and TNF-α.

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Realizing the personality traits of Bisha University Employees during the Covid-19 pandemic
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The post-Corona Covid-19 world is not the world before it, the problem of perception of personality traits with two axes: the characteristics of psychological and social compatibility, and the second aspect the mental disorder during the pandemic, and the accompanying precautions and prohibitions during the academic year 2020 AD. The aim of the research is to reveal the perception of the personal characteristics of Bisha University employees (students and faculty) during the Corona Covid-19 pandemic, and to reveal statistically significant differences in the perception of the personality traits of Bisha’s members during the Covid 19 according to the scientific qualification variables (female students -faculty members),  marital st

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Image And Graphics
Normalized-UNet Segmentation for COVID-19 Utilizing an Encoder-Decoder Connection Layer Block
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The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
The Role of Interleukine-33 in Inflammatory Bowel Disease
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The inflammatory bowel disease (IBD), Crohn’s disease (CD) and ulcerative colitis (UC) are heterogenous chronic inflammatory disorders of the gastrointestinal tract. The most widely accepted etiopathogenic hypothesis for these disorders suggests an immune mediated process.
Objective: This study was performed to evaluate the role of interleukine-33 in pathogenesis of inflammatory bowel disease and to correlate their levels with the disease activity and/or severity.
Methods: Fifty five subjects with inflammatory bowel disease (41 ulcerative colitis patients and 14 Crohn’s disease patients) their ages range from 16-65 years and 25 apparently healthy volunteers their ages and sexes were matched with the patients were participated i

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Publication Date
Mon Dec 02 2024
Journal Name
International Journal Of Science Academic Research
EFFECT OF ORAL ADMINISTRATION OF ETHYL ACETATE EXTRACT OF ROSMARINUS OFFICINALIS L. ON SERUM ENZYMES IN RATS AND EVALUATION OF α‐AMYLASE AND α-GLUCOSIDASE INHIBITORY ACTIVITY
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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
The Scientific Contribution of the Al-Kindy College Medical Journal to the World Literature on the COVID-19 Pandemic
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The beginning of COVID-19 in Wuhan, China in late December 2019 and its worldwide transmission has led the World Health Organization to formally address the pandemic. The pandemic has imposed influential impacts on different environmental, economic, social, health, and living aspects. Publishing in scholastic journals was not immune from these impacts.

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Publication Date
Sun Mar 01 2009
Journal Name
Baghdad Science Journal
Study of ELISA and antibiotic sensitivity test for Salmonella enteritidis as experimental infection in mice
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Salmonella enteritidis one of more important as epidemiological bacteria between other salmonella types. It is very important pathologically that cause food poising and gastrointestinal tract infections. This study includes some of immunological changes that appear by ELISA test and antibiotic sensitivity test against these bacteria in mice. ELISA test results appears high immunological response happen after 3 days of inoculation, mean titration readings beginning 0.198 and the maximum mean titration after 15 days of inoculation 1.538 and begin to decrease after this time slowly to remain about 0.297 after 40 days of inoculation. An antibiotics sensitivity test result appears, this bacteria sensitive to Chloramphenicol, Ceftriaxone,

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Fri Mar 04 2022
Journal Name
Environmental Science And Pollution Research
Geographically weighted regression model for physical, social, and economic factors affecting the COVID-19 pandemic spreading
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Abstract<p>This study aims to analyze the spatial distribution of the epidemic spread and the role of the physical, social, and economic characteristics in this spreading. A geographically weighted regression (GWR) model was built within a GIS environment using infection data monitored by the Iraqi Ministry of Health records for 10 months from March to December 2020. The factors adopted in this model are the size of urban interaction areas and human gatherings, movement level and accessibility, and the volume of public services and facilities that attract people. The results show that it would be possible to deal with each administrative unit in proportion to its circumstances in light of the factors that appe</p> ... Show More
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