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SINGLE NUCLEOTIDE POLYMORPHISMS (SNPS) IN EXON 3 AND 7 OF ESTROGEN RECEPTOR BETA (ESR2) GENE IN WOMEN WITH BREAST CANCER FROM IRAQ.
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This study was aimed to determine the mutations and single nucleotide polymorphisms (SNPs) in exon 3 and 7 of estrogen receptor beta (ESR2) gene in women with breast cancer from Iraq. Different samples (blood, fresh tissue with blood from same patient, and formalin fixed paraffin embedded, FFPE) were collected from women with breast cancer. Molecular analysis exon 3 and 7 in ESR2 has been studied by using PCR. It was found exon 3 and 7 in ESR2 were revealed as a single band with size 151 and 157 bp, respectively. There was no SNP in exon 3 has been identified. While three novel polymorphisms (ACT, AGG and GCA) were detected in exon 7, the type of those polymorphisms deletion for ACT and AGG while substitution polymorphism for GCA. From this study, it can be concluded that some single nucleotide polymorphism in ESR1 and ESR2 may effect gene expression.

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Publication Date
Wed Jun 09 2021
Journal Name
Design Engineering
The Impact of Transforming the Educational System in Iraq from 6-3-3 to 4-4-4 on Educational Planning Standards and the Deficiency of School Buildings (Primary and Secondary Education)
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        Educational services in Iraq face many problems that have reduced the efficiency of the educational process, as a result of the difficult conditions experienced by educational services in Iraq. This led to the accumulation of these problems and their exacerbation significantly over the years, as there was no fundamental solution to these problems. The study proposes a planning method for managing the educational system in Iraq, especially for the primary and secondary levels, where these negative phenomena are very prominent, especially the deficit in school buildings and the phenomenon of overcrowding in classrooms.      &am

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Evaluation of the cytotoxic effects of the colchicine compound isolated from the leaves of Calotropis procera (Ait) against MCF-7 and SK-GT-4 cancer cell lines.
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Alkaloids are regarded as important nitrogen-containing chemical compounds that serve as a rich source for discovering and developing new drugs where most plant-origin alkaloids have antiproliferation effects on different kinds of cancers. Alkaloids’ continence of Calotropis procera leaves are detected by two biochemical alkaloid reagents. Also GC-MS analysis for leaf alkaloid extract was done that showed the existence of one type of alkaloid compound at retention time12.8min detected as colchicine (C22H25N06( by comparing it with colchicine standard reference (Sigma Aldrich) with M.wt 399g/mol and percentage area 7.1%. Furthermore, identification, separation, and purification

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Publication Date
Mon Apr 01 2024
Journal Name
Iraqi Postgraduate Medical Journal
7 SMAS Plasty in Face Lift with Fat Graft: Evaluation of Aesthetic Outcomes
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ABSTRACT: BACKGROUND: The main goal of facelift surgery is to reduce the effect of aging by reposition of face soft tissue in to more youthful orientation. There are many methods for SMAS plication which had different design and vector of pull. AIM OF STUDY: To evaluate the effectiveness and longitivity of 7 shaped SMAS plication in facelift. PATIENT AND METHODS: From January 2020 to march 2021, 10 female patients with age (45-60) years were presented with facial sagging, those patients were subjected to subcutaneous facelift with 7 shaped SMAS plication with fat greft in Al-Shaheed Ghazi Al-Harri Hospital and Baghdad burn medical center at Baghdad medical complex. RESULTS: The average follow up period was 6 to 12 months. The mean operative

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Publication Date
Thu Aug 31 2023
Journal Name
Oncology And Radiotherapy
The role of breath holding technique on minimizing cardiac dose in left breast cancer irradiation in the adjuvant setting
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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Mon Aug 31 2015
Journal Name
Ibn Al-haitham Jour.for Pure & Appl.sci.
Isolation and Partial Purifiction of Arginase from Sera of Women with Uterine Fibroids
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The first aim of the present study was performed to assay the activity of arginase in sera of women with uterine fibroid.. This study consisted of(50) women with uterine fibroid as patient's group and (30) healthy women as control group. The age ranged between (30-55) years for the two groups. The results showed that highly significant increase (P< 0.0001) in the arginase activity in sera of women with uterine fibroid (7.99± 0.23) I.U/L is found when compared with healthy group (0.52±0.02) I.U/L. The second aim was performed to isolate arginase from sera of women with uterine fibroids. The purification is done by addition of ammonium sulfate, dialysis, gel filtration chromatography by using sephadex G-50 and ion exchange chromatography

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Publication Date
Thu Mar 16 2017
Journal Name
Ibn Al-haitham J. For Pure & Appl. Sci.
Isolation and Partial Purifiction of Arginase from Sera of Women with Uterine Fibroids
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The first aim of the present study was performed to assay the activity of arginase in sera of women with uterine fibroid.. This study consisted of(50) women with uterine fibroid as patient's group and (30) healthy women as control group. The age ranged between (30-55) years for the two groups. The results showed that highly significant increas (P< 0.0001) in the arginase activity in sera of women with uterine fibroid (7.99± 0.23) I.U/L is found when compared with healthy group (0.52±0.02) I.U/L. The second aim was performed to isolate arginase from sera of women with uterine fibroids. The purification is done by addition of ammonium sulfate, dialysis, gel filtration chromatography by using sephadex G-50 and ion exchange chromatography by

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Publication Date
Wed May 01 2024
Journal Name
Biology
Lysophosphatidylcholine Acetyltransferase 2 (LPCAT2) Influences the Gene Expression of the Lipopolysaccharide Receptor Complex in Infected RAW264.7 Macrophages, Depending on the E. coli Lipopolysaccharide Serotype
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Escherichia coli (E. coli) is a frequent gram-negative bacterium that causes nosocomial infections, affecting more than 100 million patients annually worldwide. Bacterial lipopolysaccharide (LPS) from E. coli binds to toll-like receptor 4 (TLR4) and its co-receptor’s cluster of differentiation protein 14 (CD14) and myeloid differentiation factor 2 (MD2), collectively known as the LPS receptor complex. LPCAT2 participates in lipid-raft assembly by phospholipid remodelling. Previous research has proven that LPCAT2 co-localises in lipid rafts with TLR4 and regulates macrophage inflammatory response. However, no published evidence exists of the influence of LPCAT2 on the gene expression of the LPS receptor complex induced by smooth or rough b

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Fri May 25 2018
Journal Name
Open Public Health Journal
Comparative Study on the Clinicopathological Profiles of Breast Cancer Among Iraqi and British Patients
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Background: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b

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