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Correlation between paraoxonase-1 arylesterase activities and clopidogrel drug in patients with coronary artery disease
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Background: Coronary artery disease (CAD) is one of the leading causes of death worldwide. Clopidogrel, antiplatelet drug, has been widely used for management of CAD. Arylesterase, the activity of Paraoxonase-1 (PON-1), is mainly contributed in the biotransformation of clopidogrel to its active thiol form. The purpose of this study was to investigate the effect of receiving clopidogrel drug on the arylesterase activities in CAD patients. The effect of receiving clopidogrel drug on the antioxidant activity of arylesterase was also monitored by determination of malondialdehyde (MDA) level. Methods: One hundred CAD patients, who were followed-up for 5 days after reciving clopidogrel, and 50 healthy volunteers were included in our study. The activities of arylesterase using two (phenyl acetate and p-nitrophenyl acetate) substrates, lipid profile, MDA, and total protein concentration (Tp) were determined spectrophotometrically. Results: PON-1 arylesterase activities, HDL-C, and Tp were significantly decreased (P<0.0001) in patients with CAD before receiving clopidogrel drug (CAD-pre-Clp) compared to baseline (non-CAD) and the levels of these parameters were returned to baseline (P>0.05) after 5 days of receiving clopidogrel (CAD-post-Clp). 

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Pre-operative serum TSH level estimation for predicting malignant nodular thyroid disease
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Publication Date
Thu Nov 09 2023
Journal Name
Biomedicine
Role of immunological and biochemical markers in bone turnover in type I diabetic patients in Karbala province, Iraq
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Introduction & Aim: Long-term diabetes mellitus (DM) is known to have a deleterious impact on bone health, resulting in change in bone mineral density, bone turnover, and bone quality, all of which increase the risk of fractures. The aim of. this study was to link immunological and pro-inflammatory cytokine (I.L-6, I.L-1, and TNF-alpha) markers in patients.with type 1 diabetes to Their connection to bones formation (sPINP) and bone resorption parameters (sCTX).   Materials & Methods: This study included 80 patients suffering from T1DM in the age range of 20-45 years. The patients were assayed for their biochemical (Vitamin D and HbA1c), Immunological (IL-6, IL-1 and TNF-alpha) parameters, as well as bone formation and resor

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Publication Date
Sun Apr 01 2018
Journal Name
Al–bahith Al–a'alami
Investment of Propaganda in Al-Rafidain and Al- Sharqiya News Channels: Content Analysis of News Bulletins from 1/12/2016 to 29/2/2016
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The technological developments in the field of communication have witnessed considerable impact in the variables which exist in following up and conveying the events which link it’s meaning to political implications. This makes a number of satellite channels depend on the techniques of propaganda and use them in the news bulletins to achieve political aims and ends related to its formational directives where those channels allotted a considerable time in its programming transmission map to concentrate on the security and political status to complete the image of the informational scene according to the logic of its propaganda and styles in processing news for daily events.The technological developments in the field of communication hav

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Publication Date
Sun Nov 01 2015
Journal Name
Iosr Journal Of Dental And Medical Sciences (iosr-jdms)
A Comparative Study of a Topical Active Lotion Containing Triethyl Citrate and Ethyl Linoleate and Clindamycin Solution 1% in the Treatment of Mild to Moderate Acne Vulgaris
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DAIRMD Professor Hayder R. Al-Hamamy, **Professor Adil A. Noaimi, **Dr. Ihsan A. Al-Turfy, IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2015

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
EFFICACY ASSESSMENT OF BLACK PEPPER AND CLOVE EXTRACTS AGAINST SUNFLOWER SEEDS BLACK ROT DISEASE CAUSED BY ASPERGILLUS SPP.
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Positive Definiteness of Symmetric Rank 1 (H-Version) Update for Unconstrained Optimization
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Several attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of  Hessian matrix (second derivative of the objective function). There are many unconstrained optimization methods that do not generate positive definiteness of the inverse of Hessian matrix. One of those methods is the symmetric rank 1( H-version) update (SR1 update), where this update satisfies the quasi-Newton condition and the symmetric property of inverse of Hessian matrix, but does not preserve the positive definite property of the inverse of Hessian matrix where the initial inverse of Hessian matrix is positive definiteness. The positive definite prope

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