Background: Repeated blood transfusion is the main therapeutic option for transfusion-dependent anaemias with consequent iron overload and organ damage .Therefore iron chelating agents are important protective measures for these patients. The aim of this study was to investigate the efficiency and safety of Desferroxamine in paediatrics population subjected to iron overload as a consequence of repeated transfusion in a group of Sudanese children Subjects & Methods: This was a descriptive cross-sectional hospital based study. Conducted in two main paediatric reference hospitals in, Sudan. Within the period between November 2017 and April 2018 (6 months duration). The two centres were JaafarI bn- Oaf hospital and Albulk hospital. The study population included all patients of transfusion dependent anaemia who received desferrioxamine within the study period. Hundred patients were enrolled in the study. The study variables were demographic data, number of blood transfusions , serum ferritin pre and post blood transfusion and treatment of desferrioxamin Results: Sixty percent (60%) of the studied cases were males and 40% were females ,46% were thalassemic, 46% were sicklers, 5% aplastic anemia and 3% with red cell aplasia .The mean serum ferritin level before starting desferoxamine was 2.14 and after dessferoxamine was 2.48, P –value was highly significant. The most common side effect encountered was skin rash (36%) |
Combining different treatment strategies successively or simultaneously has become recommended to achieve high purification standards for the treated discharged water. The current work focused on combining electrocoagulation, ion-exchange, and ultrasonication treatment approaches for the simultaneous removal of copper, nickel, and zinc ions from water. The removal of the three studied ions was significantly enhanced by increasing the power density (4–10 mA/cm2) and NaCl salt concentration (0.5–1.5 g/L) at a natural solution pH. The simultaneous removal of these metal ions at 4 mA/cm2 and 1 g NaCl/L was highly improved by introducing 1 g/L of mordenite zeolite as an ion-exchanger. A remarkable removal of heavy metals was reported
... Show MoreCdO:NiO/Si solar cell film was fabricated via deposition of CdO:NiO in different concentrations 1%, 3%, and 5% for NiO thin films in R.T and 723K, on n-type silicon substrate with approximately 200 nm thickness using pulse laser deposition. CdO:NiO/n-Si solar cell photovoltaic properties were examined under 60 mW/cm2 intensity illumination. The highest efficiency of the solar cell is 2.4% when the NiO concentration is 0.05 at 723K.
A field experiment was conducted at Abu-Ghrib during 2013- 2014 season to study the effect of harrowing systems on the decomposition and fermentation on organic matter(OM) when added and mixed with the soil under special technology, as well as its effect on the growth parameters and productivity of (Zea mays L. 5018). The experiment was laid out using factorial randomized complete block design (RCBD) in split-split design with three replications in SCL bare soil with a percent of moisture ranged from 16 – 18 %. The main plots were designated to the two systems of harrowing (Rotary Harrowand Disc Harrow ). The sub main plots were specified for two organic matters ( Sheep manure ,cow manure ) . Data were statistically analyzed, and
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The current study deals with the effect of N-Diethylnitrosamine (DEN) induced traumatic brain injury on male albino rats, as well as the outcome results of treatment with paclitaxel nanoparticles for a period of 8 weeks with two-week intervals is the concern of the present study. Mean body weight, as well as brain weight, was considered as the main parameters whereas a detailed immunohistochemical study on rat brain sections was performed. Astrocytic biomarkers for the diagnosis of astrocytes by fibrillary glial acidic protein (GFAP). Neuronal GFAP staining used for various broke sections were forwarded. Comparison and Contrast of all these parameters in all steps of the experiment had been discussed. The
... Show MoreThe use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
... Show MoreInvestment drives the wheel of the development of different developed and developing countries. Sudan is a model for a developing country facing a lot of difficulties in the field of both local and foreign investment. The present study was focused on the problem of poor diversification and efficiency of both local and foreign investment in Sudan. Also, it clarified the important role of administrative supervision to strengthen the efficiency of investment, taking the experience of the Sudan as a model. The researchers used the well-known descriptive and analytical tools (questionnaire, interview, observation) to complete this study. A well designed questionnaire was used. It included all questions that could cover all aspects of
... Show MoreIn this paper, our aim is to study variational formulation and solutions of 2-dimensional integrodifferential equations of fractional order. We will give a summery of representation to the variational formulation of linear nonhomogenous 2-dimensional Volterra integro-differential equations of the second kind with fractional order. An example will be discussed and solved by using the MathCAD software package when it is needed.
Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.
Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are
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