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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
Fri Apr 02 2021
Journal Name
New Trends In Information And Communications Technology Applications: 4th International Conference, Ntict 2020, Baghdad, Iraq, June 15, 2020, Proceedings 4
Iris recognition using localized Zernike features with partial iris pattern
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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
Sun Feb 01 2026
Journal Name
Bulletin Of Pharmaceutical Sciences Assiut University
Synthesis and Characterization a New Schiff Base Ligand Derived from O-vanillin with Some Transition Metal Complexes and Study of Antimicrobial Activity
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Publication Date
Tue Jun 17 2025
Journal Name
Baghdad Science Journal
Synthesis and Biological Study of Schiff–Mannich Base Derived from 2-Mercaptobenzimidazole as Chelated Tridentate Ligand with Some Transition Metal Ions Complexes
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To prepare a new ligand, many compounds were used to synthesize Schiff-Mannich base, such as isatin, Para chloro Aniline, 2-mercaptobenzimidazole and indole. The resulting compound 1-((2-((1H-indol-1-ylthio)-1H-benzo[d]imidazol1-yl)methyl)-3-(4-chlorophenylimino)indolin-2-one (L). (L) was used to create a series of metal ion complexes with Co (II), Ni (II), Cu (II), Pd (II), Pt (IV), and Au (III). C.H.N.S., FTIR, mass spectra UV-ViS, 1H-NMR, 13CNMR, magnetic moment, and molar conductivity were used to characterize all of these compounds. Except for the palladium(II) and gold(III) complexes, all of the produced complexes had an octahedral geometry, according to the data. The antibacterial activity of the produced compounds was tested by usin

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
The Association between Single Nucleotide Polymorphisms rs1042522 and rs1642785 in the TP53 gene and Acute Myeloid leukemia in a sample of the Baghdad/ Iraq population
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Acute myeloid leukemia (AML) represents the most prevalent type of acute leukemia in adults and is responsible for approximately 80% of all cases. The tumor suppressor gene (TP53) is a gene that has been frequently studied in cancer, and mutations in this gene account for about 50% of human cancers. This study aims to evaluate the correlation between two single nucleotide polymorphisms (SNPs) in the gene: rs1042522 and rs1642785, and a group of Iraqi patients suffering from pre-diagnostic acute myeloid leukemia (AML). Blood samples were collected from sixty patients (26 males and 34 females) and sixty controls (26 males and 34 females); these subjects were matched in gender, age, and ethnicity. Genomic DNA has been extracted fro

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Publication Date
Tue Dec 01 2020
Journal Name
Egyptian Journal Of Medical Human Genetics
Association between ABO blood groups and susceptibility to COVID-19: profile of age and gender in Iraqi patients
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Abstract<sec> <title>Background

A case-control study was performed to examine age, gender, and ABO blood groups in 1014 Iraqi hospitalized cases with Coronavirus disease 2019 (COVID-19) and 901 blood donors (control group). The infection was molecularly diagnosed by detecting coronavirus RNA in nasal swabs of patients.

Results

Mean age was significantly elevated in cases compared to controls (48.2 ± 13.8 vs. 29.9 ± 9.0 year; probability [p] < 0.001). Receiver operating characteristic anal

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Publication Date
Mon May 28 2018
Journal Name
Biology
The Effect of Overexpressed DdRabS on Development, Cell Death, Vesicular Trafficking, and the Secretion of Lysosomal Glycosidase Enzymes
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Publication Date
Fri Jul 01 2022
Journal Name
Aip Conf. Proc. 2450, 020031 (2022)
The study of the identification and association of adiponectin and Interleukin-6 and some variables. Biochemical parameters in the Iraqi cord blood of newborns
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t. The current study was conducted on the umbilical cord blood of newborns in the Banks Hospital in Baghdad, Diyala, and Khalis in Diyala, where the study included 90 samples of blood, and samples were collected for the period from the 1st of October;2020 to The first of February;2021 AD, where the study included measuring levels of interleukin-6;Adiponectin,glucose and bilirubin in the blood, comparison study between the study variables with the child's weight (greater than 3 kg),(less or equal 3 kg),the mother's age (greater than 25 years, less or equal to 25 years),the sex of the child (male, female).The results of our study showed that there were no significant differences between the variables of the current study between the two sex

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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