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.
A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network
... Show MorePseudomonas aeruginosa is a common and major opportunistic human pathogen, its causes many and dangersinfectious diseases due to death in some timesex: cystic fibrosis , wounds inflammation , burns inflammation , urinary tract infection , other many infections otitis external , Endocarditis , nosocomial infection and also causes other blood infections (Bacteremia). thereforebecomes founding fast and exact identification of P. aeruginosafrom samples culture very important.However, identification of this species may be problematic due to the marked phenotypic variabilitydemonstrated by samples isolates and the presence of other closely related species. To facilitate species identification, we used 16S ribosomal DNA(rRNA) sequence data
... Show MoreThe study was conducted at research station A, department of field crops, college of agricultural engineering sciences, university of Baghdad during summer 2021 to evaluate the effect of boron and some growth regulators on some growth criteria and yield of soybean crop (cv. shimaa). The experiment was carried out according to split plots by using randomized complete block design with three replications. The main plots included three concentrations of boron (75, 150 and 225) mg.L-1, the sub-plots included three levels of growth regulators, spraying kinetin (100 mg. L-1), spraying ethrel (200 mg.L-1) and spraying kinetin (100 mg.L-1) + spraying ethrel (200 mg.L-1) as
... Show MoreThe current research was aimed at the following:
1. Measurement of Personality Type Observer of the University students.
2. Identify the differences in Personality Type Observer among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary)
3. Measurement of Withdrawal of the University students.
4. Identify the differences in Withdrawal among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary).
5. Identify the relationship between Personality Type Observer and Withdrawal.
To achieve this aims of the research, the researchers set up the instrument is scale