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

In the age of information and communication revolution, education as one of life
aspects has influenced with that revolution by integrating technology in education, which
have become as an important learning tools of the whole educational process . Technology,
when used appropriately, can help make science classroom a site of active learning and
critical thinking, furthering student inquiry and connections with different materials. It is
necessary to develop human rights education programs and materials for discretionary and
extracurricular activities as it provide them with the skills and tools so that they are
empowered to take action to realize their rights. Human rights education is a critical means of
instill

Breast tumors patients generally have more oxidative stress than normal females. This was clear from a highly significant elevation (P<0.05) in malondialdehyde level in RBCs, serum and tissue of all patients groups with breast cancer as compared with control group. In this study we had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the MDA might be used as a marker for prognosis of the disease.

Objectives: The current work aimed to reveal the impact of gentamicin on the fibronectin binding proteins (fnbp) gene expression and its relation to biofilm and agr type in Staphylococcus aureus. Materials and Methods: A total of 25 S. aureus isolates were enrolled in this study previously isolated from different specimens. Identification confirmation and methicillin resistance were achieved by amplification of 16SrRNA and mecA. Multiplex polymerase chain reaction (PCR) based assay was employed to evaluate the agr typing. The gene expression of fnbA and fnbB genes was tested by real-time PCR technique. Minimum inhibitory concentration was estimated by micro broth dilution methodology. Microtiter plate method was performed to determine the a

Background: Breast cancer is a complex, multifaceted disease encompassing a great variety of entities that show considerable variation in clinical, morphological and molecular attributes.
Objective: The aim of this study to evaluate patients’ molecular profile (Estrogen receptor, Progesterone receptor, HER2/neu and Ki-67).
Patients & Methods: This is a cross-sectional descriptive study was done in Baghdad oncology teaching hospital from December 2015 to April 2016, carried on 100 breast cancer female patients with their age range from 27 to 73 years old and with their histopathology reports and (IHC) results.
Results: The highest incidence of breast cancer among patients in 5th (40-49 years) and 6th (50-59 years) decades o

The present study was undertaken in order to investigate the role of gentamicin in the gene expression of toxA in Pseudomonas aeruginosa isolated from cow mastitis. A total of ten P. aeruginosa strains originally isolated from cows infected with mastitis. Agar dilution methodology was performed to determine the minimal inhibitory concentration of gentamicin, all of which developed resistance toward gentamicin. The findings presented here demonstrated that all these strains harboured toxA depending on PCR-based assay. Nonetheless, RT-PCR technique revealed a wide variation in expression of toxA. Moreover, the cultivation of P. aeruginosa in the presence of gentamicin, significantly (P< 0.05), induced the expression of toxA, in addition to th

 Background: Breast cancer composed of several biologic subtypes that have response to hormonal therapy. Tamoxifen is  hormonal therapy  with tissue- pecific antagonistic or agonist effects, the latter being responsible for multiple  effects on lipid metabolism in women .

Objective: This study was designed to determine the impact of Tamoxifen on the serum lipid profile in breast cancer women. 

Patients and methods: Prospective observation cohort study conducted at Oncology Teaching Hospital, Medical city complx.starting from October 2015 to October 2016. A total number of 40 premenopausal women with breast cancer   were enrolled in this