Aim: To find any association between specific ABO blood groups and FUT2 secretory status and COVID-19 in a sample of Iraqi dentists. Materials and Methods: For each participant, a questionnaire including demography, COVID-19 status, blood grouping, and RH factor, with chemo-sensitive symptoms was recorded. The saliva samples were collected and DNA was extracted from leukocytes. Sequencing of molecular detection of the FUT2 gene by real-time PCR and the data was done, whilst drawing the phylogenetic tree. Results: Out of 133, most of the dentists were female 61%, most were just under 35 years of age. The most participants in this study were predominantly with blood group O (40%), followed by B, A, and AB, with (90%) of them were RH+. All blood grouping and RH factor were high significantly associated with COVID-19 infection and its frequency (p<0.001). A significant association between smell dysfunction and infected blood group A and RH+ (p =0.044, 0.038) while taste dysfunction was negatively and significantly correlated with AB group (r=-0.73; p=0.008). The FUT2 secretor showed a significant association with COVID-19 infection and frequency. The majority of COVID-19-infected participants experienced a significant loss of both smell and taste with fast recovery within 2 weeks. Conclusions: The COVID-19 infection susceptibility and reinfection are associated with FUT2 secretory status and greatly associated to olfactory and gustatory sense loss.
BACKGROUND: COVID-19 is resulted from severe acute respiratory syndrome coronavirus 2, which initiated in China in December 2019. Parasites are efficient immune modulators because their ability to stimulate an immune response in infected persons. AIM: This study aims to detect if there is a probable relationship between intestinal parasitic infections and COVID-19. METHODS: Ninety patients consulted at Al-Kindy Teaching Hospital (Al-Shifa center) from October 2020 till April 2021, confirmed infection with COVID-19 by PCR. Stool examination was done for detecting intestinal parasites. RESULTS: From 90 patients, males were 63 (70%), with median age 32 years, while females were 27 (30%), with age 24–44 years. Asymptomatic pati
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat
... Show MoreBackground: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.
Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.
Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol
... Show MoreBackground: Coronavirus disease 2019 (COVID-19) is
one of the updated challenges facing the whole world.
Objective: To identify the characteristics risk factors that
present in humans to be more liable to get an infection
than others.
Methods: A cross-sectional study was conducted for
positively confirmed 35 patients with polymerase chain
reaction in Wasit province at AL-Zahraa Teaching
Hospital from the period of March 13th till April 20th. All
of them full a questionnaire regarded by risk factors and
other comorbidities. Data were analyzed by SPSS version
23 using frequency tables and percentage. For numerical
data, the median, and interquartile range (IQR) were used.
Differences between categoric
At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat
... Show MoreBy March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy
... Show MoreAfter 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
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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
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