Introduction: Cardiovascular diseases are the main cause of death among type 2 diabetic patients. Higher levels of plasminogen activator urokinase receptor have been found to predict morbidity and mortality across acute and chronic diseases in the common populace. This study aims to explore the role of serum plasminogen activator urokinase receptor levels as a cardiometabolic risk factor among type 2 diabetic Iraqi patients. Methods: Seventy type 2 diabetic patients (40 male and 30 female) (mean age: 46.20±7.56 years) participated in this study; 35 patients were with cardiovascular disease and 35 were without cardiovascular disease; their ages range was 40-55 years. In addition, 30 individuals who apparently healthy were selected a

Endophytic fungi live inside plants or any part of them without creating any visible pathogenic signs. Endophytic fungi are found within medicinal plants and have shown strong biologic activity, such as anticancer and antioxidant activities, as well as producing extracellular enzymes. In this study, different fungal strains were isolated from the leaves of the medicinal plant Ziziphus spina, including Aspergillus flavus, Aspergillus fumigatus, Aspergillus niger, Cladosporium sp., Rhizopus sp., and Mucor sp. Extracellular enzymes have been quantified using agar plate-based methods in which fungi were grown in specified growth media to detect the enzymes produced. The results showed that A. niger has the highest ability to produce amy

Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

Type 2 diabetes mellitus is often characterized by hyperglycemia as a result of increased insulin resistance in hepatic/peripheral tissues and pancreactic B-cell dysfunction. Approximately 92% of patients with type 2 diabetes mellitus demonstrate insulin resistance, however hyperglycemia is always a consequence of insulin deficiency. This study was done on 120 patients newly diagnosed diabetes type 2 characterized by dyslipidemia that is increased triglycerides and decreased HDL. Hypoglycemia and weight gain are common problem with oral sulfonyl urea drugs. In this work three different oral hypoglycemic drugs repaglinide and glibenclamide (insulin secretagogues) and rosiglitazone (insulin sensitizer) were used for treatment of patients w

The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

The work includes synthesis of 1,2,3-triazoles via click conditions and using the microwave irradiation starting from two synthesized azides: 2,3,4,6-tetra-O-acetyl-β-D-glucopyranosyl azide (5) and perfluorobutylethyl azide (10) and different terminal alkynes. It also includes microwave enhanced synthesis of tetrazoles via the reaction of two synthesized azides i.e., perfluorobutylethyl azide (10) and 1,5-diazidopentane (13) with benzoyl cyanide. Most of the prepared compounds have been characterized by: TLC, FT-IR, 1H NMR, 13C NMR, LC-MS and microelemental analysis

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

      The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe