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bijps-362
Formulation and Evaluation of Ezetimibe Nanoparticles
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The aim of this study is to formulate and evaluate ezetimibe nanoparticles using solvent antisolvent technology. Ezetimibe is a practically water-insoluble drug which acts as a lipid lowering drug that selectively inhibits the intestinal absorption of cholesterol and related phytosterols. Ezetimibe prepared as nano particles in order to improve its solubility and dissolution rate.

Thirty formulas were prepared and different stabilizing agents were used with different concentrations such as poly vinyl pyrrolidone (PVPK-30), poly vinyl alcohol (PVA), hydroxy propyl methyl cellulose E5 (HPMC), and poloxamer. The ratios of drug to stabilizers used to prepare the nanoparticles were 1: 2, 1:3 and 1:4.

The prepared nanoparticles were evaluated for particle size, entrapment efficiency, dissolution study, Fourier transform infrared spectroscopy, differential scanning calorimetry, and atomic force microscopy. The percentage of drug entrapment efficiency of F1-F30 was ranged from 85% ± 1 to 98 % ± 1. On the other hand dissolution rate increasing as the particle surface area is increase due to reduction of particle size to the nano range.

The results showed that poly vinyl pyrrolidone (PVPK-30) was found to be the best stabilizer.

 Keywords: Ezetimibe, Nanoparticles, Particle Size, poly vinyl alcohol.

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Correlation between Serum and Tissue Markers in Breast Cancer Iraqi Patients
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Breast cancer is the most prevalent malignancy among women worldwide, in Iraq it ranks the first among the population and the leading cause of cancer related female mortality. This study is designed to investigate the correlations between serum and tissue markers in order to clarify their role in progression or regression breast cancer. Tumor Markers are groups of substances, mainly proteins, produced from cancer cell or from other cells in the body in response to tumor.  The study was carried out from April 2018 to April 2019 with total number of 60 breast cancer women. The blood samples were collected from breast cancer women in postoperative and pretherapeutic who attended teaching oncology hospital of the medical city in Baghdad and

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Publication Date
Thu Sep 01 2016
Journal Name
Current Pharmaceutical Design
Dry Eye Disease: Present Challenges in the Management and Future Trends
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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Energy management and storage systems on electric vehicles: A comprehensive review
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Publication Date
Sat Dec 01 2018
Journal Name
Fuel
Biodiesel from batch and continuous oleic acid esterification using zeolite catalysts
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Publication Date
Mon Feb 20 2017
Journal Name
Proceedings Of The 5th International Conference On Communications And Broadband Networking
Bit precision and Cyclic prefix effect on OFDM Power Consumption Estimation
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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Image encryption algorithm based on the density and 6D logistic map
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One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are genera

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Publication Date
Fri Jun 04 2021
Journal Name
Oral Surgery
Calcifying epithelial odontogenic tumour series with unique clinical and histopathological features
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Abstract<sec><title>Background and aims

Calcifying epithelial odontogenic tumour (CEOT) is a benign odontogenic neoplasm of epithelial origin that secretes an amyloid‐like protein tending towards calcification. This study aims to describe a case series from Iraq of one of the rarest odontogenic tumours.

Materials and methods

Clinical and histopathological analysis of Calcifying epithelial odontogenic tumour cases that are archived at the oral pathology laboratory of the college of dentistry (Baghdad University) from 2000 to 2019.

Results

Six cases of CEOT were regi

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Publication Date
Mon Mar 06 2023
Journal Name
Rheumatology (bulgaria)
Tenascin-C and Interleukin-17 Up-regulation in Axial Spondyloarthritis Patients
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Background: Axial spondyloarthritis (axSpA) is an inflammatory, systemic rheumatic condition that mostly affects the axial skeleton. Tenascin-C (TN-C) is a hexameric glycoprotein of considerable size, upregulated in many inflammatory conditions, while Interleukin-17 (IL-17) a cytokine that plays an important role in SpA symptoms. Objective: to investigate the upregulation between the serum levels of TN-C and IL-17 in Iraqi axSpA patients and the disease characteristics. Patients and Methods: Seventy-four axSpA patients and 28 matched controls were studied. Fifty-four patients received a tumor necrosis factor inhibitor (TNFi) and 20 did not. Serum TN-C and IL-17 concentrations were determined using the ELISA technique. The Bath Ankyl

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Publication Date
Fri Mar 12 2021
Journal Name
Sensors
A Robust Handwritten Numeral Recognition Using Hybrid Orthogonal Polynomials and Moments
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Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in </p> ... Show More
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