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ND2 Gene Sequencing of Sub fertile Patients Recovered from COVID-19 in Association with Toxoplasmosis
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A total of (90) blood samples were collected from male patients infected with Toxoplasmosis who recovered from COVID- 19 and attended Kamal Alsamiraai Hospital from 15 January to 15 September 2021. We measured anti-Toxoplasma antibodies (IgG and IgM) detected by ELISA, whereas Anti-COVID-19 antibodies (IgG and IgM) were estimated using Elisa and Afilias. The semen characteristics were also studied among fertile, healthy individuals (control group) and sub-fertile patients. Results showed that the mean sperm count was high among the control group (40.5±1.3x 106/ml) compared with that of the sub-fertile patients (10.3±1.75 and 8.8±1.9 x 106/ml for oligozoospermia, and oligoasthenozoospermia respectively), and it was the highest (44.7±1.4 x 106/ml) among asthenozoospermia patients. Compared to the control group, there were highly significant differences between anti-Toxoplasma IgG antibodies and anti-COVID-19 IgG antibodies (P<0.001). The mean level of Toxoplasma IgM was (11.74±8.90) and for control was (0.05±0.10), while the mean level of COVID-19 IgM was (1.91±1.06) and for control was (0.04±0.03) in sub-fertile patients. The mutation occurred in IL-IB gene A to G transgene at site 4514 of the IL-IB gene (sample code, 6383) and in the case of an invalid sample code, 2409 and 5097. In the alanine codon, the GCA codon has mutated into GCG. Also, G to A transgene occurred at site 4514 of the IL-IB gene. (sample code, 6750) In the case of an invalid sample code, it happened in 010081 and 009593. In the alanine codon, the ATG codon has mutated into ATA.

Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Clinical Course and Disease`s Outcome Aspects of COVID-19 Pediatric Patients in Ibn Al-Khateeb Isolation Hospital
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Background: Corona virus disease 2019 (COVID-19) is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, leading to an ongoing pandemic.

Aim of study: to review the clinical, lab investigation and imaging techniques, in pediatric age group affected COVID-19 to help medical experts better understand and supply timely diagnosis and treatment.

Subjects and methods: this study is a retrospective descriptive clinical study. The medical records of patients were analyzed. Information’s recorded include demographic data, exposure history, symptoms, signs, laboratory findin

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Gene Expression and Methylation Levels of PCSK9 Gene in Iraqi Patients with Coronary Artery Disease
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The expression of the Proprotein Convertase Subtilisin/Kexin Type 9 gene (PCSK9) is inextricably related to lipid levels and a risk of atherosclerotic coronary artery disease (ASCAD). The present study aims to measure the quantity of PCSK9 gene expression and the effect of methylation on its expression level taking part in the pathogenesis of acute coronary artery disorder.

A current study included 150 subjects from the Iraqi population, 100 ASCAD patients and 50 healthy controls. The concentration of PCSK9 in each serum sample was determined by the ELISA technique, the expression levels of the PCSK9 gene in whole blood were estimated by RT-qPCR – Quantitative Reverse Transcription PCR method, and DNA

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Levels of Some Blood Clotting Factors in COVID-19 Patients: Comparative Study Before and After Pfizer- BioNTech Vaccinations
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One of the health issues that a coronavirus can induce is blood clotting. Coronavirus can be prevented in a number of ways. Vaccination is one of the critical methods for preventing illness or lessening its impact. This study seeks to estimate a few blood coagulation variables. 147 samples were collected from the Baghdad Governorate in the autumn of 2021. The samples were split into three groups: COVID-19 patients, healthy individuals before and after receiving the (Pfizer-BioNTech) vaccine, and healthy individuals only. Prothrombin Time (PT), Partial Thromboplastin Time (PTT), Protein C (PTN-C), Protein S (PTN-S), and International Normalized Ratio (INR) for 49 samples were measured and computed for each group. The results have shown th

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Publication Date
Sun Oct 23 2022
Journal Name
Baghdad Science Journal
Comparison Between Deterministic and Stochastic Model for Interaction (COVID-19) With Host Cells in Humans
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In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Modeling Extreme COVID-19 Data in Iraq
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     This paper considers the maximum number of weekly cases and deaths caused by the COVID-19 pandemic in Iraq from its outbreak in February 2020 until the first of July 2022. Some probability distributions were fitted to the data. Maximum likelihood estimates were obtained and the goodness of fit tests were performed. Results revealed that the maximum weekly cases were best fitted by the Dagum distribution, which was accepted by three goodness of fit tests. The generalized Pareto distribution best fitted the maximum weekly deaths, which was also accepted by the goodness of fit tests. The statistical analysis was carried out using the Easy-Fit software and Microsoft Excel 2019.

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Publication Date
Sat Sep 30 2023
Journal Name
Al–bahith Al–a'alami
The Iraqi Journalistic Treatment of COVID-19 pandemic
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This research aims to investigate the approaches adopted by Iraqi newspapers in addressing the COVID-19 pandemic crisis. Employing a descriptive methodology and survey technique, the study conducts content analysis on articles published in three prominent newspapers: Al-Sabah, Al-Mada, and Tareeq Al-Shaab. A multi-stage sampling method was employed, encompassing 260 issues of the aforementioned newspapers. Data collection involved the use of a content analysis questionnaire, with the "How it was said?" method utilized to determine analysis categories.
The results showed that Al-Sabah newspaper adopted a positive approach in addressing COVID-19-related topics, while Al-Mada newspaper remained neutral, and Tare

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Statistical Analysis of COVID-19 Data in Iraq
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The analysis of COVID-19 data in Iraq is carried out. Data includes daily cases and deaths since the outbreak of the pandemic in Iraq on February 2020 until the 28th of June 2022. This is done by fitting some distributions to the data in order to find out the most appropriate distribution fit to both daily cases and deaths due to the COVID-19 pandemic. The statistical analysis includes estimation of the parameters, the goodness of fit tests and illustrative probability plots. It was found that the generalized extreme value and the generalized Pareto distributions may provide a good fit for the data for both daily cases and deaths. However, they were rejected by the goodness of fit test statistics due to the high variability of the data.<

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Deep Convolutional Neural Network Architecture to Detect COVID-19 from Chest X-Ray Images
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      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

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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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