A total of 70 pregnant women with toxoplasmosis were studied to evaluate of some immunological aspects. The women were distributed into three groups: 37 women were IgG positive, 18 women were IgM positive and 15 women were IgG and IgM positive as well as 25 healthy women were considered as control group. Serum samples were collected and ELISA method was employed to assess levels of interleukins 4, 6, 10, Interferon gamma-induced protein 10 (IP-10), Granulocyte-macrophage colony-stimulating factor (GM-CSF) and Vascular endothelial growth factor (VEGF). As compared with control the levels of cytokines were significantly increased in serum of three pregnant women groups with toxoplasmosis and the highest increase was observed in the IgM positi
... Show MoreThe most common cause of acquired thyroid dysfunction is autoimmune thyroid disease (AITD), which most commonly manifests as Hashimoto's thyroiditis (HT) or Graves' disease (GD). The importance of vitamin D (vit D) as an immune modulator has recently been emphasized in several types of disorders. However, its significance in thyroid illnesses is not fully understood. The purpose of this study is to investigate how vitamin D affects the pathophysiology of hyperthyroidism and hypothyroidism in Iraqi women. One hundred Iraqi women with age ranged from 18 to 60 years participate in this research, 50 of them were hypothyroidism patients, 30 were hyperthyroidism patients and the other 20 were euthyroidism served as controls. Blood samples
... Show MoreThis case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.
This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.
The study focused on the results of first paleostress from thrust fault slip data on Tertiary age of Hemrin North Structure, North of Iraq. The stress inversion was performed for fault slip data using an improved right dihedral model, and then followed by rotational optimization (Georient Software). The trend of the principal stress axes (σ1, σ2 and σ3) and the ratio of the principal stress differences (R) show the main paleostress field is NE-SW compression regime. As well as using Lisle graph and Mohr diagram to determine the magnitudes of palestress. The values paleostress of the study area were σ1=1430 bars, σ2=632 bars and σ3=166 bar. The large magnitudes of the primary stress axes could be attributed to active tecto
... Show MoreAbstract Background: The human epidermal growth factor receptor 2(HER2) proto-oncogene is overexpressed or amplified in approximately 15%-25% of invasive breast cancers. Approximately 35% of HER2-amplified breast cancers have coamplification of the topoisomerase II-alpha (TOP2A) gene encoding an enzyme that is a major target of anthracyclines. Hence, the determination of genetic alteration (amplification or deletion) of both genes is considered as an important predictive factor that determines the response of breast cancer patients to treatment. The aims of this study are to determinate TOP2A status gene amplification in a set of Iraqi patients with breast cancer that have had an equivocal (2+) and positive HER2/neu by immunohistochemistry
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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