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The Significance Of Maternal Total Serum Homocysteine Level In Iraqi Mothers Who Had Previous Babies With Neural Tube Defects
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Background: Neural tube defects (NTDs) are said to be inherited in a multifactorial fashion, i.e. genetic-environmental interaction. Maternal nutritional deficiencies had long been reported to cause NTDs, especially folate deficiency during early pregnancy. More attention had been paid to the exact mechanism by which this deficiency state causes these defects in the developing embryo. The most significant of all researches was that connecting reduced folate and increased homocysteine level in maternal serum on one hand and the risk of developing a NTD baby on the other hand. Objectives : to determine the significance of homocysteine level in Iraqi mothers who gave birth to babies with NTDs as compared to normal controls. Patients, Materials and Methods: Fifty Iraqi women having babies born with NTDS, referred to the genetic clinic in Baghdad Teaching Hospital, were included in this study (the study group) as well as 37 healthy women having normal children (the control group). This study was conducted from November, 2002 till October, 2003. Analysis of total serum homocysteine level for all women was done using a computerized HPLC system. Results : the age of women in both groups was comparable (mean+SD in the study group was 26.2+5.14 years vs. 26.3+4.57 years in the controls). Among the study group, 4 (8%) had normal tHcy level; 44 (88%) had mildly elevated level, and only 2 (4%) had moderately elevated tHcy level, while all (100%) women in the control group had their tHcy level within normal level. This difference was statistically highly significant (p<0.001). Conclusions : Women become at an increased risk of delivering a baby with NTD when having an elevated tHcy level in their sera, and that tHcy level is an important marker in maternal serum that is associated significantly with pregnancy outcome.

Publication Date
Mon Jan 01 2024
Journal Name
Medical Research Archives
Genetic Polymorphism for the Gene Encoding Endoplasmic Reticulum Aminopeptidase-1 (ERAP-1) in Iraqi Patients with Ankylosing Spondylitis
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Ankylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis affecting primarily the spine and pelvis. This study was aimed to investigate the relationship between the rs27044 polymorphism in Endoplasmic reticulum aminopeptidase-1 (ERAP-1) with the susceptibility and severity of AS correlated with some biochemical markers such as hematological parameter (Erythrocytes sedimentation rate (ESR)) and immunological parameters (C-reactive protein (CRP), Human leukocyte antigen-B27 (HLA-B27), Interlukin-6 (IL-6) and Interlukin-23 (IL-23)), and oxidative stress parameters (Glutathione (GSH) and Malondialdehyde (MDA)) in a sample of Iraqi population. A total of 60 blood samples were collected from AS patients requited Rhe

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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Studying the genotype of Aryl Hydrocarbon Receptor-Interacting Protein (AIP) Gene (rs641081C>A) in ‎Iraqi Samples with Acromegaly Pituitary Adenoma
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Pituitary adenomas are the anterior pituitary tumors. Patients with an Aryl Hydrocarbon Receptor-Interacting Protein (AIP) mutation (AIP- mut) tend to have more aggressive tumors occurring at a younger age. Single nucleotide polymorphisms (SNPs) in many studies have been related to metabolic comorbidities in the general population. Study aims investigated the role of AIP gene SNPs with susceptibility to acromegaly pituitary- adenoma, with levels of LH, FSH, TSH, Testosterone, IGF1,GH, FT4 , Prolactin hormones and blood sugar levels.  The study ‎was conducted on a group of acromegaly patients, including 50 patients) both Genders( with ‎hyperplasia of the ends, and apparently healthy control group. Genotyping of

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Publication Date
Sun Sep 15 2024
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Olanzapine-induced Metabolic Syndrome and its Association with -759C&gt;T Polymorphism of the HTR2C Gene in Iraqi Schizophrenic Patients
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The hazardous metabolic effects of treating schizophrenia patients with olanzapine comprise serotonin 2C receptor (5-HT2C) antagonists. Metabolic side effects of antipsychotic drugs, including lipid abnormalities, disturbed glucose metabolism, and weight gain, can have a major impact on treating psychiatric patients. The intent of this study was to investigate whether there is an associated link between the genetic polymorphism at -759C&gt;T in the promoter region of the 5-hydroxytryptamine 2C receptor (HTR2C) gene and the metabolic syndrome driven by olanzapine in schizophrenia patients. A cross-sectional study that involved fifty hospitalized patients with schizophrenia. The patients were split into two groups (metabolic and non-metab

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Publication Date
Mon May 01 2017
Journal Name
Energy
Solidification enhancement in a triplex-tube latent heat energy storage system using nanoparticles-metal foam combination
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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

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Publication Date
Tue Nov 09 2021
Journal Name
Energies
Natural Convection Effect on Solidification Enhancement in a Multi-Tube Latent Heat Storage System: Effect of Tubes’ Arrangement
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The solidification process in a multi-tube latent heat energy system is affected by the natural convection and the arrangement of heat exchanger tubes, which changes the buoyancy effect as well. In the current work, the effect of the arrangement of the tubes in a multi-tube heat exchanger was examined during the solidification process with the focus on the natural convection effects inside the phase change material (PCM). The behavior of the system was numerically analyzed using liquid fraction and energy released, as well as temperature, velocity and streamline profiles for different studied cases. The arrangement of the tubes, considering seven pipes in the symmetrical condition, are assumed at different positions in the system, i

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Publication Date
Fri Mar 01 2024
Journal Name
International Communications In Heat And Mass Transfer
Accelerated charging of PCM in coil heat exchangers via central return tube and inlet positioning: A 3D analysis
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