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KI-67 as a predictive indicator of papillary thyroid cancer in Iraqi patients
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BACKGROUND. KI-67 (MKI-67 in humans) is a protein able to bind to DNA which contributes to cell growth and cell proliferation. KI-67 is currently considered as a biomarker that is widely utilized as prognostic indicator for evaluating cell proliferation, diagnosing diseases, and conducting research. Several different kinds of cancer have high Ki-67 expression, which simplifying the choice of treatment for individuals with various cancer types.AIM. The objective was to evaluate the expression of KI67 in patients suffering papillary thyroid cancer (PTC) also the association between patients age and gender and KI67 expression.MATERIALS AND METHODS. To undertake an in-depth investigation of KI67 in malignant and normal tissues, we used thyroid tissue sections to analyze KI67 expression in 70 samples, 50 different PTC (44 female and 6 male), and 20 normal types (10 for each gender). Each group’s average age is between 20 and 60.RESULTS. The analysis of the data revealed a substantial difference in the expression of ki67 between the patients and control groups. Ki67 expression and either gender or age did not significantly correlate.CONCLUSION. This study suggest that KI67 may be a crucial marker for assessing the aggressiveness of tumors and inflammatory diseases.

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Publication Date
Wed Oct 01 2008
Journal Name
Journal
Acanthosis Nigricans in Iraqi Patients Clinical, Histopathological and Theraputic Study
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KE Sharquie, AA Noaimi, AH Muhammad Ali, 2008 - Cited by 3

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Hypothyroidism and Leptin in Iraqi Patients with Chronic Kidney Disease
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The present study aims at assessing the effects of chronic kidney disease (CKD) on thyroid hormone and leptin by evaluating the level of: leptin hormone along with thyroid hormone in CKD patients. The study has been conducted on  70 subjects, 50 patients with an age range between 20-50 years (25  males and 25 females) who were diagnosed to have CKD stage-5, and 20 normal controls whose ages ranged between 20-48 years (10  males and 10 females), who attended  the Nephrology and Transplant Center in Medical City of Baghdad- Iraq from April  2018  to July  2018. The study showed a highly significant (P<0.01) increase in TSH level in CKD patients in comparison with controls. While T3 and T4 levels observed highly significant decrea

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Hypothyroidism and AMH in Iraqi Patients with Chronic Kidney Disease
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This study was conducted to investigate thyroid function and Anti-Müllerian hormone (AMH) in (Chronic kidney disease) CKD patients by evaluating their levels in CKD patients, 50 patients were diagnosed to have CKD stage-5, their ages ranged between 20-50 years (25 males and 25 females) who attended the Nephrology and Transplant Center in Medical City of Baghdad- Iraq, they were recruited from April 2018 to July 2018 and were enrolled into the study. The control group consisted of 20 healthy individuals, their ages ranged between 20-48 years (10 males and 10 females). The study showed non-significant (p>0.05) increase in AMH level in CKD patients compared to the control group. On the other hand, TSH was recorded a highly significant (

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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
HLA Typing in Iraqi Patients with Obesity and Primary Osteoarthritis.
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Background: Osteoarthritis (OA) is a degenerative joint disease. It is one of the major causes of disability in developed and developing countries. Human leukocyte antigen (HLA) as part of immune system has a role in the disease process.Objectives: To investigate whether there is an association between HLA class II-DRB and OA.Methods: A case control study with 26 patients with osteoarthritis and 22 apparently healthy obese control persons matching in ethnicity were enrolled in this study during the period between October 2012 till March 2013. Direct interview was done with each patient and HLA typing was done by molecular method using Sequence Specific Primer (PCR-SSP) method using One Lambda Kit-USA. Results: The results showed that fem

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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
Developing a Predictive Model and Multi-Objective Optimization of a Photovoltaic/Thermal System Based on Energy and Exergy Analysis Using Response Surface Methodology
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
COMPARISON OF SOME NONPARAMETRIC METHODS TO DETERMINE THE NUMBER OF RADIATION DOSES FOR BREAST CANCER PATIENTS
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Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
The micronucleated erythrocytes in speeies of Iraqi fish as indieator of dilution
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The micronucleated erythrocytes in fish was used to detect water pollution by genotoxic agents. Fish belonging to different species were collected from three regions from Baghdad during three months (December/2000,January and February/2001 ).The micronucleated erythrocytes was observed in all the specimens. It was concluded that the genotoxic activity' in one region was less than in die other two regions.?

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Publication Date
Thu Apr 01 2021
Journal Name
Biochem. Cell. Arch
STUDY ON THE MUTATION OF ASXL1 IN ACUTE MYELOID LEUKEMIA IN IRAQI PATIENTS
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The present study was designed to shed light on the molecular effects caused by acute myeloid leukemia (AML). It was also aimed to investigate ASXL1 point mutations in newly AML patients as compared to healthy control. The study comprised of 43 AML Iraqi patients and their ages ranged between 16-75 years. It included 23 females and 20 males compared with 20 healthy controls. Results revealed that the extracted DNA from 30 AML patients and amplified by PCR to obtain ASXL1 gene from exon 12 showed larger bands (479). Among forty three patients, two of them displayed point mutations of deletion and substitution, while the others were normal since no mutations were detected. The total of mutations in two mutated patients was 27 mutations, the m

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Publication Date
Fri Oct 11 2019
Journal Name
Open Access Macedonian Journal Of Medical Sciences
Immunohistochemical Expression of Epidermal Growth Factor Receptor in Astrocytic Tumors in Iraqi Patients
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BACKGROUND: Diffuse astrocytomas constitute the largest group of primary malignant human intracranial tumours. They are classified by the World Health Organization (WHO) into three histological malignancy grades: diffuse astrocytomas (grade II), anaplastic astrocytomas (grade III) and glioblastoma (grade IV) based on histopathological features such as cellular atypia, mitotic activity, necrosis and microvascular proliferation. Epidermal growth factor receptor (EGFR) is a 170-kDa transmembrane tyrosine kinase receptor expressed in a variety of normal and malignant cells regulating critical cellular processes. When activated, epidermal growth factor receptor (EGFR) triggers several signalling cascades leading to increased proliferatio

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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