Patients with renal failure in the final stages undergo the treatment by hemodialysis. Hemodialysis is used to reinstate the intracellular and extracellular fluid environment, by propagation of molecules in solution through a semipermeable membrane along an electrochemical concentration gradient. Blood catching in the dialysis machine and the recurrent phlebotomy may lead to losing about 1-3 g of iron per year. Prohepcidin hormone is an acute phase protein (type II) that plays a major role in the systemic iron irregularities as it is a mediator of anemia in inflammation and regulator of iron metabolism. This study aims to evaluate the effect of hemodialysis on iron hemostasis and its relationship with prohepcidin as an inflammatory marker. This study includes forty four adult male patients with end-stage renal failure (in pre and post –treated) by means of chronic hemodialysis-HD with mean age (53.27 ± 13.76 years). The following biochemical investigations have been studied: Prohepcidin, Iron, Ferritin, Transferrin, Total Iron-Binding Capacity (TIBC), The Unsaturated Total Iron Binding Capacity (UIBC), and transferrin saturation (TAST).Decrement of Prohepcidin level on hemodialysis patients in post dialysis with non-significantly compared to pre dialysis, while iron and ferritin was increment in post treated than pre- treated with non-significantly.Hemodialysis affects Prohepcidin levels as it was long duration and Glomerular Filtration rate GFR (cock croft equation) and prohepcidin level affect the iron profile related with the iron store depletion.
KE Sharquie, A Noaimi, W Al-Janabi, American Journal of Dermatology and Venereology, 2014 - Cited by 4
Statistics has an important role in studying the characteristics of diverse societies. By using statistical methods, the researcher can make appropriate decisions to reject or accept statistical hypotheses. In this paper, the statistical analysis of the data of variables related to patients infected with the Coronavirus was conducted through the method of multivariate analysis of variance (MANOVA) and the statement of the effect of these variables.
KE Sharquie, AA Noaimi, AA Hajji, Journal of Cosmetics, Dermatological Sciences and Applications, 2014 - Cited by 5
Ankylosing spondylitis is a complex debilitating disease because its pathogenesis is not clear. This study aims at detecting some pathogenesis factors that lead to induce the disease. Chlamydia pneumoniae is one of these pathogenesis factors which acts as a triggering factor for the disease. The study groups included forty Iraqi Ankylosing spondylitis patients and forty healthy persons as a control group. Immunological and molecular examinations were done to detect Chlamydia. pneumoniae in AS group. The immunological results were performed by Enzyme-Linked Immunosorbent Assay (ELISA) to detect anti-IgG and anti-IgM antibodies of C. pneumoniae revealed that five of forty AS patients' samples (12.5%) were positive for anti-IgG and IgM C. pneu
... Show MoreObjective: Geographic differences in clinical and pathological aspects of ameloblastoma have been suggested, therefore the purpose of this study was to analyze cases of ameloblastoma in terms of clinical and radiographic manifestations, histopathological types, treatment modalities and recurrence rate and compare them with reports from other parts of the world. Methods: The medical reports of patients diagnosed with ameloblastoma were reviewed and the data concerning the age, gender, chief complaint, the anatomical site of the lesion, radiographic appearance, histopathological diagnosis, treatment approach and recurrence were retrieved. Surgical treatment consisted of either enucleation with curettage and peripheral ostectomy or resection;
... Show MoreBackground: Lung cancer is responsible for the most
cancer deaths in both men and women throughout the
world. Deaths from lung cancer (160,440 in 2004,
according to the National Cancer Institute) exceed the
number of deaths from four other major cancers combined
(breast, colon, pancreatic and prostate).
Objective: To assess the behavior and the approaches of
lung cancer in a sample of Iraqi patients.
Methods: This descriptive retrospective study was
performed using the records of 390 patients proved to have
lung cancer that had attending the Thoracic Surgery
Department of Surgical Specialties Hospital-Medical City
\Baghdad for the period from January, 1st
, 2001 to
December, 31st
,2002.
Res
Land use change, particularly the expansion of urban areas and associated human activities at the expense of natural and semi-natural areas, is a major ecological issue in urban areas around the world. Climate change being a very strong additional driver for changing the temperature and habitat in the cities. This also applies to Baghdad, Iraq, where urbanisation and climate change exerts a major pressure on the natural habitats of the city, and thus may affect the ability of city planners to adapt to future climate change scenarios. Here we present evidence of substantial growth in urban areas, increases in temperature, and degradation of natural vegetation within Baghdad city by using Remote Sensing techniques and an assessment for the
... Show MoreMost studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for