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

Previous studies on the synthesis and characterization of metal chelates with uracil by elemental analysis, conductivity, IR, UV-Vis, NMR spectroscopy, and thermal analysis were covered in this review article. Reviewing these studies, we found that uracil can be coordinated through the electron pair on the N1, N3, O2, or O4 atoms. If the uracil was a mono-dentate ligand, it will be coordinated by one of the following atoms: N1, N3 or O2. But if the uracil was bi-dentate ligand, it will be coordinated by atoms N1 and O2, N3 and O2 or N3 and O4. However, when uracil forms complexes in the form of polymers, coordination occurs through the following atoms: N1 and N3 or N1 and O4.

      Rheumatoid arthritis (RA) is an inflammatory condition causing joint pain and stiffness, with often debilitating and life-limiting consequences. Recently, a new B-cell secreted cytokine, IL-39, was identified in mice. The most up-to-date research indicates that although IL-39 is expressed in murine models of lupus and has a role in mediating the inflammatory response in this context, there is no solid, replicated evidence of the existence of IL-39 in humans. This study aimed to clarify the existence and role of IL-39 in the human body and to elucidate whether it plays a role in rheumatoid arthritis. Accordingly, serum samples were collected from 66 patients with rheumatoid arthritis who were under therapy and from 66 healthy c

A compact microstrip six-port reflectometer (SPR) with extended bandwidth is proposed in this paper. The design is based on using 16-dB multi-section coupled line directional couplers and a multi-section 3-dB Wilkinson power divider operating from 1 to 6 GHz. The proposed SPR employs only two calibration standards: a matched load and an open load. As compared to other dielectric substrates, fabricating the proposed SPR involves using a low-cost (FR4) substrate. A novel algorithm is also proposed to estimate the complex reflection coefficient over the frequency ranges at which the standard performance of the circuit components is not fully satisfied. The new algorithm is based on the circles’ intersection points, which have been de

Objective Thalassemic patients present with multiple immune abnormalities that may predispose them to oral Candida, however this has not been investigated. The aim of this study was to assess oral candidal colonization in a group of patients with β-thalassemia major both qualitatively and quantitatively. Study design The oral mycologic flora of 50 β-thalassemia major patients and 50 age- and sex-matched control subjects was assessed using the concentrated oral rinse technique. Candida species were identified using the germ tube test and the Vitek yeast identification system. Results Oral Candida was isolated from 37 patients (74%) and 28 healthy subjects (56%; P = .04). The mean candidal count was significantly higher in thalassemic patie

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