Background: Obesity typically results from a variety of causes and factors which contribute, genetics included, and style of living choices, and described as excessive body fat accumulation of body fat lead to excessive body, is a chronic disorder that combines pathogenic environmental and genetic factors. So, the current study objective was to investigate the of the FTO gene rs9939609 polymorphism and the obesity risk. Explaining the relationship between fat mass and obesity-associated gene (FTO) rs9939609 polymorphism and obesity in adults. Methods: Identify research exploring the association between the obesity risk and the variation polymorphisms of FTO gene rs9939609. We combined the modified odds ratios (OR) as total groups and subgro

ABSTRACT:

Objectives: The study aims to know the effectiveness of the educational program in the patient’s adherence to medication and diet and to know the relationship between the effectiveness of the education program and their demographic data related to the patient’s age, gender, marital status, education level, occupation, monthly income and residence.

Methodology: A quasi -experimental design study was performed on patient who attended to Gastroenterology and Hepatology Teaching Hospital, from March 2021 to September 2021. The non-probability sampling including 50 patients for case study and 30 patients for control group. The questionnaire consists of 3 parts, part one the socio

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

Giardia lamblia is the worldwide most common intestinal protozoan parasite. It was indicated that Giardia is the most important agent that causes acute and chronic diarrhea in infants, young children and travelers. The aim was to detect the influence of host HLA alleles on the susceptibility to infection with G. lamblia in a sample of Iraqi patients. A total of (40) patients with giardiasis aged (14-39) years were registered. All of them were symptomatic and (40) healthy individuals matched age and sexes were included as controls. All patients were prepared to stool examination to detect G. lamblia and eliminated other pathogens, as well as human leukocyte antigen (HLA) class II alleles (DRB1) typing. The most common detected alleles in pat

The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic