Susceptibility to the pandemic coronavirus disease 2019 (COVID-19) has recently been associated with ABO blood groups in patients of different ethnicities. This study sought to understand the genetic association of this polymorphic system with risk of disease in Iraqi patients. Two outcomes of COVID-19, recovery and death, were also explored. ABO blood groups were determined in 300 hospitalized COVID-19 Iraqi patients (159 under therapy, 104 recovered, and 37 deceased) and 595 healthy blood donors. The detection kit for 2019 novel coronavirus (2019-nCoV) RNA (PCR-Fluorescence Probing) was used in the diagnosis of disease.

A simple and rapid high performance liquid chromatographic with fluorescence detection method for the determination of the aflatoxin B1, B2, G1 and G2 in peanuts, rice and chilli was developed. The sample was extracted using acetonitrile:water (90:10, v/v%) and then purified by using ISOLUTE multimode solid phase extraction. After the pre-column derivatisation, the analytes were separated within 3.7 min using Chromolith performance RP-18e (100–4.6 mm) monolithic column. To assess the possible effects of endogenous components in the food items, matrix-matched calibration was used for the quantification and validation. The recoveries of aflatoxins that were spiked into food samples were 86.38–104.5% and RSDs were <4.4%. The method was

       The purpose of this study was to measure the radon concentration of some dried fruit and grain samples which were consumed as a meal. This is performed by counting the alpha tracks emitted from radon by exposing the CR-39 detector. Measurements indicated that the highest concentration of radon in dried fruit samples was in dried coconut sample 69.89247 Bq/m³, and the lowest concentration of radon was in figs 50.40323 Bq/m³, while the highest concentration of radon was in grain samples in oats was 61.82796 Bq/m³, The lowest concentration of radon was in Iraqi bulgur was 48.3871 Bq/m³, These results are due to the type and characteristics of the soil. Also sho

Background: Periodontitis is an infection attributable to multiple infectious; it causes an interrelated cellular and humoral host immune responses. Recent reports have indicated that human cytomegalovirus (HCMV) may contribute to pathogenesis of periodontitis. The HCMV can stimulate the release of cytokines from inflammatory and non-inflammatory cells and weaken the periodontal immune defense. This study aimed to reveal the presence of anti-CMV IgG, and determine the levels of IL‐6 and TNF-α and to correlate the presence of cytomegalovirus (CMV) with cytokines levels. Materials and Methods: Forty patients with chronic periodontitis and 40 healthy control subjects (their age and sex were matched with the patients) were involved

    Osteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA usin