This study included 50 blood samples that were collected from patients with age ranged between 35-65 years. Thirty samples were collected from patients with Type 2 Diabetes Mellitus (T2DM), while 20 blood samples were collected from healthy individuals as a control sample. The polymorphism results of TGF-β1 gene in codon 10: +869*C/T position by using amplification refractory mutation system (ARMS-PCR) showed that the T allele was suggested to have a protective effect, while C allele was associated with an increased risk of T2DM. The TT and CT were suggested to have a protective effect, while CC genotype was associated with an increased risk of T2DM. The polymorphism results of TGF-β1 gene in codon 25: +915*G/C position in samples

Background: Dyslipidemia is defined as an abnormally high level of various lipids in the blood. It is considered a major risk for atherosclerosis and coronary artery disease. Genetic susceptibility can have a significant influence on the development and progression of dyslipidemia. ApoB-100 R3500Q mutation and ApoE variants are among those genetic risks for dyslipidemia. This study aims to assess the possible contribution of ApoB and ApoE variants on lipid profile among a group of early-onset ischemic heart disease (IHD) patients in comparison to a group of controls. Methods: Forty patients with dyslipidemia and early-onset IHD without chronic conditions likely to cause derangement of lipid levels were recruited to this case-control study

The study aimed to evaluating the inhibitory activity of apigenin extracted from Salvia officinalis leaves on the growth of L20B cancer cell in vitro, and through two incubation periods; 48 and 72 hours. Accordingly, eight concentrations (1.56, 3.13, 6.25, 12.5, 25.0, 50.0, 100.0 and 200.0 micromol) of apigenin and similar concentrations of vitamin C and carbon tetrachloride (CCl4) were tested. The apigenin revealed its significant inhibitory potentials against the growth of L20B cell line, especially at the low concentrations (1.56, 3.13 and 6.25 micromol) and at 72 incubation period in comparison with vitamin C and CCl4.

Tumor necrosis factor-alpha (TNF-α) antagonists’ therapy are expensive and has a non-responsive rate between 30% to 40% in rheumatoid arthritis patients. Genetic variation plays a vital role in the responsiveness to this type of therapy.The aim of this study is to investigate if the presence of genetic polymorphism in the TNF-α gene promoter region at locations -376 G/A (rs1800750), -806 C/T (rs4248158), and -1031 T/C (rs1799964) affects rheumatoid arthritis patient's tendency to be a non-responder to etanercept.

Eighty RA patients on etanercept (ETN) for at least six months were recruited from the Rheumatology Unit at Baghdad Teaching Hospital. Based on The European League Against Rheumatism response (EULAR) criteria, patient

Objective: The aim of this study is to detect the effect of continuous exposure to Sodium Nitrite on 8-oxoguanine
DNA glycosylase (OGG1) gene which responsible on DNA repairs. DNA repair play a major role in maintaining
genomic stability when DNA exposure to damage. Genomic stability is very important for keeping body cells
healthy and to prevent many types of tumor development. Many genes are responsible for this job; one of them is
OGG1 gene.
Methodology: In current study two groups of mice were chronically exposed to sodium nitrite for six months and
eighteen months while third group was used as a control. Then sizes of OGG1 were estimated.
Results: The results exhibited in the unexposed (control) mice had two dif

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p