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Genetic polymorphisms associated with diabetic foot ulcer: A review article
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Diabetic foot ulcer (DFU) or Lower limb ulcers are one of the major complications caused by diabetes mellitus especially when patients fail to maintain tight glycemic control. DFU is linked to multiple risk factors along with the genetic factors and ethnicity which play a significant role in the development of DFUs through their effects on multiple aspects of the pathophysiological process. This narrative review aimed to summarize all the previous studies within the last ten years associating gene polymorphism and DFU. Polymorphism associated with vascular endothelial growth factor (rs699947), the G894T polymorphism of the endothelial nitric oxide synthase gene, interleukin-6–174 G>C gene polymorphism, heat shock protein 70 gene polymorphism, the apolipoprotein E gene polymorphism, Sirtuin 1 (sirt1) polymorphisms (rs12778366 and rs3758391), hypoxia-inducible factor -1 alpha exon 12 mutation, toll-like receptor gene (thr399ile polymorphism), the effect of both monocyte chemoattractant protein-1 (MCP-1) –2518A/G and the vascular endothelial growth factor (VEGF) –634g/c polymorphisms were summarized in this review. The results of all these studies indicating that screening for Polymorphisms might be helpful for early screening and prevention of DFU through their regulatory function on the transcription activity of the genes. Additional studies should be conducted in larger and different populations and ethnic regions to confirm the results of all previous studies mentioned in this review.

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Publication Date
Thu Jun 02 2016
Journal Name
Ashrae Transactions
Melting of PCM with nanoparticles in a triplex-tube thermal energy storage system
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Publication Date
Sat Dec 30 2017
Journal Name
International Journal Of Heat And Technology
Optimization of a rectangular pin fin using rectangular perforations with different inclination angles
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Publication Date
Sat Feb 19 2022
Journal Name
Intelligent Service Robotics
Dynamic performance of a series elastic actuator with variable stiffness logarithmic spiral spring
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Publication Date
Tue Jun 30 2015
Journal Name
Al-kindy College Medical Journal
Familial Pulmonary Alveolar Microlithiasis: A Rare Case Report with Emphasis on Imaging Findings
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ABSTRACT Pulmonary alveolar microlithiasis is rare infiltrative pulmonary disease characterized by intra-alveoli deposition of microliths. We present a familial case of an adult female with complaint of progressive shortness of breath on exertion. Chest radiograph showed innumerable tiny dense nodules, diffusely involving both lungs mainly the lower zones. High-resolution CT scan illustrated widespread intra-alveolar microliths, diffuse ground-glass attenuation areas and septal thickening predominantly in the basal regions. Chest radiograph is all that is needed for the diagnosis of this case but CT scan was done to demonstrate the extent and severity of this disease

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Publication Date
Thu Mar 20 2025
Journal Name
Osol Journal Of Medical Sciences (ojms)
Thyroid Function Variations in Critically Ill Neonates A Comparative Study with Healthy Controls
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Normal thyroid function is essential for neonatal growth and brain development. In a newborn infant with severe disease, endocrine regulation of hormones can be affected by abnormal metabolism. The assessment of thyroid parameters results in the recognition of a dysfunction and its association with disease severity

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Publication Date
Tue Feb 01 2011
Journal Name
Biochemical Engineering Journal
Elicitation of Streptomyces coelicolor with E. coli in a bioreactor enhances undecylprodigiosin production
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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Mechanical Science And Technology
Optimization of a rectangular pin fin using elliptical perforations with different inclination angles
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Publication Date
Thu Jun 29 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications (ijnaa)
Applying a suitable approximate-simulation technique of an epidemic model with random parameters
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

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Publication Date
Thu Jan 30 2014
Journal Name
Al-kindy College Medical Journal
Orbital Hydatid Disease: A case study of young patients with primary orbital lesion
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Background:This is a prospective study of three children presented to us in the Orbital clinic in AL ShahidGazi Al Hariri Hospital with painless proptosiswith suspension of Hydatid disease.Objectives: : Orbital hydatid disease is a rare lesion accounting for less than 1% of the total lesions of the body (1, 2). Orbital cysts presented as a primary lesion in our study which is rare to have such lesion without involvement of other organs (3). Humans represent the intermediate host where the commonly affected organ are liver and the lung (10-15%) (4). Methods:This is a prospective study of three Children presented to us in the Orbital clinic in Al Shahid Ghazi Alhariri Hospital with painless proptosis with suspension of Hydatid disease, dep

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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