Objectives: The aim of this study was to assess the possible the association between +3061 (G>A, rs1143676) missense mutation in exon 24 of the integrin α-4 subunit (ITGA-4) gene and the response to natalizumab in a sample of Iraqi multiple sclerosis patients. Methods: A sample of 59 patients with multiple sclerosis (16 males and 43 females; mean age of 32 years; age range of 15 to 52 years) receiving natalizumab for at least 12 consecutive months were involved in the study between March and August/ 2022. The sample was categorized into two groups according to their response to natalizumab treatment (responders and non-responders). Polymerase chain reaction and Sanger’s sequencing for the extracted deoxyribonucleic acid was pe

Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

Consider a simple graph   on vertices and edges together with a total  labeling . Then ρ is called total edge irregular labeling if there exists a one-to-one correspondence, say  defined by  for all  where  Also, the value  is said to be the edge weight of . The total edge irregularity strength of the graph G is indicated by  and is the least  for which G admits   edge irregular h-labeling.  In this article,   for some common graph families are examined. In addition, an open problem is solved affirmatively.

Background and Objectives: Wound healing is a complex process with overlapping phases haemostasis, inflammation, proliferation and maturation/matrix remodeling. Each phase of wound healing requires different management strategies, and inappropriate treatment can delay wound healing. The aim of the present study was to evaluate the efficacy of topical application of calmodulin as a significant augmentation of the granulation tissue production process of wound healing and to express of genes CaMKK2, MaP2K6 and CXCR4 at site of wound defect, that have versatile effects on the body and they belong to Ca/camodulin related genes. Material and Methods: In this study thirty albino male rats, weighting (300-400) gram, aged (6-8) months, wil

: Cigarette smoking is a lifestyle behavior that causes significant adverse health effects. Cigarette smoke contains chemicals, many of which are lead to the production of reactive oxygen species (ROS), which can lead to apoptosis and autophagy. To estimate the association of Cigarette smoking with the autophagy and immunity, technology of real time polymerase chain reaction (RTPCR) for gene expression of (LC3A, LC3B, LC3C, myd88) was used. Enzyme-linked immunosorbent assay (ELISA) technique was utilized to measurement the amount of TNF-α protein. The ratios of LC3A/LC3B and LC3B/LC3C were calculated to estimate the autophagy flux. The results indicate the expression of LC3B, LC3C and Myd88 genes in smokers is increased significantly (p

Abortion is categorized as the termination of conception caused by the failure or removal of the embryo from the uterus before the conclusion of pregnancy. Microorganisms and genetic factors are two of the many factors associated with abortion. Cytomegalovirus is a widespread congenital virus infection pathogen that affects a wide variety of people. The prothrombin gene is one of the essential causes that trigger blood clotting and the function of abortion women, therefore the aim of the study is to detect and associate Cytomegalovirus and prothrombin gene mutation (Gene ID: 14061 in NCBI) with abortion through genetic and immunological methods. Five ml of whole blood was collected from an intravenous puncture and divided into two tubes,

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

Abstract Background: Timely diagnosis of periodontal disease is crucial for restoring healthy periodontal tissue and improving patients’ prognosis. There is a growing interest in using salivary biomarkers as a noninvasive screening tool for periodontal disease. This study aimed to investigate the diagnostic efficacy of two salivary biomarkers, lactate dehydrogenase (LDH) and total protein, for periodontal disease by assessing their sensitivity in relation to clinical periodontal parameters. Furthermore, the study aimed to explore the impact of systemic disease, age, and sex on the accuracy of these biomarkers in the diagnosis of periodontal health. Materials and methods: A total of 145 participants were categorized into three groups based