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

FLI1 is a member of ETS family of transcription factors that regulate a variety of normal biologic activities including cell proliferation, differentiation, and apoptosis. The expression of FLI1 and its correlation with well-known breast cancer prognostic markers (ER, PR and HER2) was determined in primary breast tumors as well as four breast cancer lines including: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 using RT-qPCR with either 18S rRNA or ACTB (β-actin) for normalization of data. FLI1 mRNA level was decreased in the breast cancer cell lines under study compared to the normal breast tissue; however, Jurkat cells, which were used as a positive control, showed overexpression compared to the normal breast. Regarding primary breast carcinoma

Background: Colorectal cancer is the third most common cancer-related mortality worldwide, and its prevalence is increasing among many nations.  Aim of the study: Investigate the predictive value of carbohydrate antigen 242 (CA242) in comparison to the CEA biomarker and to estimate the significance of CA242 as prognosis maker in colorectal cancer patients. Methods: a case-control study with a total of 150 individuals, 100 patients (59 males, 41 females) and 50 healthy controls (26 males, 24 females). using an enzyme-linked immunosorbent (ELISA) to determine the serum levels of CA242 and CEA. The study was carried out at the gastroenterology consultation clinic of the oncology teaching hospital between November 2020 and February

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

STAG proteins, which are part of the cohesin complex and encoded by the STAG genes, are known as Irr1/Scc3 in yeast and as SA/STAG/stromalin in mammals. There are more variants as there are alternate splice sites, maybe three open reading frames (ORFs) code for three main proteins, including: SA1 (STAG1), SA2 (STAG2) and SA3 (STAG3). The cohesin protein complex has various essential roles in eukaryotic cell biology. This study compared the expression of the STAG1 gene in four different breast cancer cell lines, including: MCF-7, T-47D, MDA-MB-468, and MDA-MB-231 and normal breast tissue. RNA was extracted from these cell lines and mRNA was converted to cDNA, and then expression of the STAG1 gene was quantified by three sets of specific prim

Parkinson’s disease (PD) consider as a progressive ageing neurodegenerative disease, Parkinson’s consider as a heterogenous disease, with mainly initiate through correlation between genetic and epigenetic by inducing of different factors on some related genes, these factors like (environmental, toxicants, nutrition, heavy metals, pesticides, some drugs) and also(trauma on head ,strokes) in addition to unknown reasons which cause an idiopathic PD .Current study aims to focusing on specific related PD gene called SNCA by single nucleotides polymorphism (rs2619363) as a risk factor for PD initiation disease in PD patients in addition to study the effect of polymorphisms on random Iraqi patients with different gastrointestinal

Background: Osteoarthritis is a complicated, chronic disorder of cartilage and bone, associated with homeostasis of bio-elements. The current study aims to assess the role of serum progranulin levels among Iraqi patients with knee osteoarthritis. Patients and Methods: The study encompassed 50 patients aged 52.50 ± 3.12 years (25 males and 25 females), admitted to the at the Baghdad Medical City through the period from November 2021 to March 2022. All individuals were identified by physicians in a Rheumatology and Rehabilitation Outpatient Clinic and the clinical data was collected along with the assess¬ment of biochemical parameters. Fasting serum glucose, lipid profile, calcium, magnesium, alkaline phosphatase, vitamin D3, and p

Background: Venous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), presents an extra challenge in the management of patients with cancer, given the increase in morbidity and mortality in having both conditions. Cancer patients are well known to have a high risk of VTE; particularly; those who have had major surgery, chemotherapy and/or hormonal therapy. These groups of patients need to understand the risk factors and the prophylactic measures to prevent developing VTE. This review aims to provide an overview of the literature on cancer patients’ understanding of VTE and their experiences of cancer-associated thrombosis (CAT).

Method: A scoping review wa

ZG Abdulrazaq, MR Younus, Nasaq, 2023