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.
It was aimed to understand the interleukin-4 (IL-4) role in etio-pathogenesis of rheumatoid arthritis (RA). Two approaches were adopted. In the first one, a quantitative expression of IL4 gene was assessed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and such findings were correlated with some demographic, clinical and laboratory parameters, which included gender, duration of disease, disease activity score (DAS-28), rheumatoid factors (RFs), C-reactive protein (CRP) and anti-cyclic citrullinated peptide (ACCP) antibodies. In the second approach, a single nucleotide polymorphism (SNP) of IL4 gene (rs2243250) was inspected by DNA sequencing using specific primers. Fifty-one Iraqi RA patients (22 males and 29 fem
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This study was conducted in Al-Salam station for Dairy cattle/private sector, for the period from 1-11-2016 to 1-11-2017, to determine the association between BTN1A1 gene polymorphism and reproductive efficiency indicator and heat tolerance in 50 Holstein cows. The results of BTN1A1 gene analysis showed a highly significant Different (P<0.01) between genotypes of BTN1A1 gene’s genotypes AA, AB the percentage were 72.00, 28.00 % respectively. Results showed that services per conception and days open was significantly (P<0.05) affected by polymorphism of BTN1A1 gene and for cows with AA genotype, there was also a significant difference (P<0.05) between the genotypes of BTN1A1 gene for IgG concentration in calves blood who belong to mother
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
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Background: Type 2 diabetes mellitus (T2DM) is a chronic disorder that constitutes a major health problem worldwide. Toxoplasma gondii is an intracellular parasite that may infect any nucleated cell. Toxoplasmosis is becoming a worldwide health threat, infecting 30–50% of the world’s human population. The studies that have been undertaken to investigate the link between T. gondii infection and diabetes have shown contradictory fi ndings. This research aimed to look at the possible link between T2DM and T. gondii infection. Methods and Subjects: The enzyme-linked immunosorbent assay (ELISA) approach was used to screen for T. gondii IgM and IgG antibodies in 69 patients with T2DM and 92 seemingly healthy persons as controls. Resul
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We examine 10 hypothetical patients suffering from some of the symptoms of COVID 19 (modified) using topological concepts on topological spaces created from equality and similarity interactions and our information system. This is determined by the degree of accuracy obtained by weighing the value of the lower and upper figures. In practice, this approach has become clearer.
The objective of this study was to assess the impact of the COVID-19 pandemic on healthcare providers (HCPs) at personal and professional levels.
This was a cross-sectional descriptive study. It was conducted using an electronic format survey through Qualtrics Survey Software in English. The target participants were HCPs working in any healthcare setting across Iraq. The survey was distributed via two professional Facebook groups between 7 April and 7 May 2020. The survey items were adopted with modifications from three previous studies of Severe Acute Respiratory Syndrome (SARS) and Avia
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121
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The objective of this study was to assess the impact of the COVID-19 pandemic on healthcare providers (HCPs) at personal and professional levels.
This was a cross-sectional descriptive study. It was conducted using an electronic format survey through Qualtrics Survey Software in English. The target participants were HCPs working in any healthcare setting across Iraq. The survey was distributed via two professional Facebook groups between 7 April and 7 May 2020. The survey items were adopted with modifications from three previous studies of Severe Acute Respiratory Syndrome (SARS) and Avia
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