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The Association Between Immune-Histochemical Expressions of Program Death Ligand with some Aggressive Features of Prostate Cancer
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Prostate cancer (PC), accounts for more than one-fourth of all cancer diagnoses, and the most frequently diagnosed cancer among men in 2022. The immunoglobulin (IG) Program death ligand-1(PD-1) cell surface receptor is predominantly expressed on the surface of many cells. The purpose of this study was to demonstrate the relationship between Program death ligand expression and some aggressive features of prostate cancer including perineural invasion, vascular invasion and necrosis. Thirty cases of prostate cancer with age range from 60 to 80 year old and 30 cases of normal prostate tissue with age under 25 year old were separated into two groups in a retrospective case-control research that encompassed 60 cases. All malignant cases were examined by consultant pathologists for the diagnosis of prostate carcinoma, and each block of tissue was divided into two slides, one for hematoxylin and eosin (H&E) staining and the other for immunoglobulin (IHC) staining of PDL-1. The expression pattern of Program Death Ligand was investigated in these samples and its relationship to particular clinic-pathological characteristics. Despite it was not expressed in healthy prostatic tissue, program death ligand demonstrated to be positive in prostate cancer with vascular invasion, perineural invasion, and necrosis, while it was negative in healthy prostatic tissue. High expression of Program death ligand was correlated with poor differentiation, neural invasion, and vascular invasion; these criteria indicate that the expression of Program death ligand is associated with high grade and aggressive tumors. The current study confirms that perineural invasion, vascular invasion, and necrosis are all accompanied by a rise in Program death ligand expression regardless their grade and stage

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Publication Date
Thu Apr 01 2021
Journal Name
Biochem Cell Arch
Histological and Histochemical Observations of the Vesicular Gland in Adult Indigenous Bull, Bos Indicus
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Publication Date
Sun Dec 01 2019
Journal Name
Saudi Medical Journal
The diagnostic power of circulating micro ribonucleic acid 34a in combination with cancer antigen 15-3 as a potential biomarker of breast cancer
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Publication Date
Tue Jan 01 2019
Journal Name
Annals Of Tropical Medicine And Public Health
ASSOCIATION BETWEEN AUTOPHAGIC FLUX AND INFLAMMATION MARKERS IN RHEUMATOID ARTHRITIS PATIENTS RECEIVING METHOTREXATE AND INFLIXIMAB
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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The Correlation of P53 and MSI Immune Markers in Gastric Adenocarcinoma
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العلاقة بين تعبير المعلمات المناعية ل (P53) وعدم استقرار الساتل الميكروي  (MSI) مع العوامل السريرية المرضية لسرطان المعدة الغدي باستخدام الكيمياء النسيجية المناعية. الخلاصة الخلفية: يحدث سرطان المعدة الغدي بسبب عدم استقرار الكروموسومات، وطفرات TP53، واختلال الصيغة الصبغية، والانتقالات، والجينات الورمية الأولية، والتغيرات الجينية المثبطة للورم.عدم استقرار الساتل الميكروي(MSI)  يسبب فشل إصلاح عدم تطابق الحم

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Recognition of Human Facial Expressions Using DCT-DWT and Artificial Neural Network
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Facial expressions are a term that expresses a group of movements of the facial fore muscles that is related to one's own human emotions. Human–computer interaction (HCI) has been considered as one of the most attractive and fastest-growing fields. Adding emotional expression’s recognition to expect the users’ feelings and emotional state can drastically improves HCI. This paper aims to demonstrate the three most important facial expressions (happiness, sadness, and surprise). It contains three stages; first, the preprocessing stage was performed to enhance the facial images. Second, the feature extraction stage depended on Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) methods. Third, the recognition stage w

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Feature Extraction of Human Facail Expressions Using Haar Wavelet and Neural network
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One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural networ

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Publication Date
Sat Jan 23 2021
Journal Name
Neural Computing And Applications
Multi-objectives TLBO hybrid method to select the related risk features with rheumatism disease
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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Enhancing audit procedures in accordance with the international assurance standard through the implementation of a proposed program
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Abstract:             

                  The research seeks to identify the role of the International Assurance Standard (3402) in the auditor's procedures, as the importance of the research stems from providing assurance services for control tools through reports that are prepared according to this standard, which contribute to strengthening audit procedures through a proposed assurance program. Many conclusions were reached, the most important of which The assurance operations are considered among the operations with a special assignme

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Expressions of CD274 (PD-L1) and CD47 rReceptors on the sSurface of bBlast cCells in AML pPatients
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     Acute myeloid leukemia (AML) is a genetically heterogeneous clonal disease defined by the proliferation and accumulation of immature hematopoietic cells in the bone marrow and blood. This study aimed to evaluate the CD47 and CD274 (PD-L1) expression in Iraqi AML patients and its role in the disease and evasion of malignant cells from immune system. The study was conducted on 85 patients diagnosed with leukemia, 25 of them were excluded as they had taken chemotherapy for less than a week and because the proportion of tumor cells was less than 20%. Virtually, it was conducted on 60 patients with AML and 20 healthy individuals as a control group.  The expression of CD47 and CD274 (PD-L1) was evaluated using flow cytometry in the p

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Measuring Positive and Negative Association of Apriori Algorithm with Cosine Correlation Analysis
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This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

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