The risk of breast cancer development is believed to be attributed to the alterations of a number of key biological components. Within this context, elevated levels of some chemokines that act as growth factors and can promote cancer development. The current study was designed to evaluate CXCL3 (a chemokine C-X-C Motif Ligand 3) and leptin (a peptide hormone synthesized by adipose tissue with cytokine activity) serum of Iraqi breast cancer patients in comparison to healthy controls. A total of 90 participants consisted of 60 patients diagnosed with breast cancer and 30 healthy women as control group were enrolled into this case-control study. Venous blood samples were collected from all participants to evaluate CXCL3 and leptin serum levels

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.

Objective: We hypothesized that attacking cancer cells by combining various modes of action can hinder them from taking the chance to evolve resistance to treatment. Incorporation of photodynamic therapy (PDT) with oncolytic virotherapy might be a promising dual approach to cancer treatment. Methods: NDV AMHA1 strain as virotherapy in integration with aminolaevulinic acid (ALA) using low power He-Ne laser as PDT in the existing work was examined against breast cancer cells derived from Iraqi cancer patients named (AMJ13). This combination was evaluated using Chou–Talalay analysis. Results: The results showed an increased killing rate when using both 0.01 and 0.1 Multiplicity of infection (MOI) of the virus when combined with a dose of 617

Breast cancer (BC) is one of the most frequently observed malignancy in females worldwide. Today, tamoxifen (TAM) is considered as the highly effective therapy for treatment of breast tumors. Oxidative stress has implicated strongly in the pathophysiology of malignancies. This study aimed to investigate the changes in the levels of oxidants and antioxidants in patients with newly diagnosed and TAM-treated BC. Sixty newly diagnosed and 60 TAM-treated women with BC and 50 healthy volunteers were included in this study. Parameters including total oxidant capacity (TOC), total antioxidant capacity (TAC), and catalase (CAT) activity were determined before and after treatment with TAM. The serum levels of TOC and oxidative stress index (OSI) were

MDS code is a linear code that achieves equality in the Singleton bound, and projective MDS (PG-MDS) is MDS code with independents property of any two columns of its generator matrix.   In this paper, elementary methods for modifying a PG-MDS code of dimensions 2, 3, as extending and lengthening, in order to find new incomplete PG-MDS codes have been used over . Also, two complete PG-MDS codes over  of length  and 28 have been found.

Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we

Objectives: To assess the relation between breast cancer & blood groups, identify the importance of women
age group and the relation of age with breast cancer.
Methodology: The study was performed on (115) women who were diagnosed with breast cancer in different
stages of disease and different ages. Blood samples were taken from them to demonstrate their blood groups and
(20) fresh tumor tissue samples were obtained; the tumor tissue used as a source of lectin for hemagglutinate
with erythrocyte of different blood groups. The study conducted at Baghdad Teaching Hospital and Radiation &
Nuclear Medicine Hospital from January, 2007 through June 2007.
Results: The study shows that the highest percentage of women

       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

   Deficiencies in revenue-related accounting standards, including American accounting standards as well as international accounting standards, prompted the issuance of the International Financial Reporting Standard IFRS 15 "Revenue from contracts with customers" as part of the convergence plan between the FASB and the International Accounting Standards Board (IASB) according to the requirements of The joint venture between the two councils, whereby the standard aims to define the basis for reporting useful information to the users of the financial statements about the nature, amount, timing and uncertainty about the revenues and cash flows arising from a contract with the customer, The standard is base