Background: Toll-like receptors (TLRs) play a significant role in the activation of adaptive immunity and may have an essential role in the development of rheumatoid arthritis (RA). Objectives: To assess the gene expression of TLR4 in individuals with RA compared to healthy individuals. Methods: From July to December 2022. A total of 100 individuals were encompassed in the study, consisting of 50 individuals diagnosed with RA, of whom 42 were females and 8 were males, with an average age of 45.22 years. Additionally, there were 50 healthy control participants, 40 of whom were females and 10 were males, with an average age of 45.64 years. To assess the TLR4 transcript levels, blood samples were collected from each participant, and RN

Background: Coronary Artery Disease (CAD) is one of the largest causes of mortality worldwide. Clopidogrel, antiplatelet drug, has been widely used for management of CAD. The current study aimed to investigate the effect of clopidogrel on the oxidative stress in CAD patients. Methods: One hundred CAD patients, who were followed-up for 5 days after receiving clopidogrel, and 50 healthy volunteers were included in this study. Parameters include catalase (CAT), total antioxidant capacity (TAC), total oxidant capacity (TOC), total protein, albumin, and globulins were determined before and after treatment with clopidogrel. Results: CAT, TAC, and Tp were significantly decreased (P<0.0001) in CAD patients compared to healthy control and

Chronic kidney disease (CKD) is a permanent loss of kidney function which is diagnosed when the glomerular filtration rate (GFR) is under 60 ml\min\1.73m2 for more than three months. The present study was conducted at Kidney Transplant and Dialysis Center in the Medical City in Baghdad from October 2018 to April 2019. Sixty CKD patients with an age ranged of 40 to 65 years and 25 healthy subjects were involved in this study. Blood samples were collected to evaluate the levels of kidney function parameters and thyroid hormones. The levels of urea, creatinine and uric acid showed highly significant (p ≤ 0.01) increases in CKD patient in comparison with the control group, while the values of GFR and creatinine clearance showed highly

Celiac disease (CD) is the most common genetically - based disease in correlation with food intolerance. The aim of this study is to measure the activity of ALT enzyme and purify enzyme from sera women with celiac disease. Alanine aminotransferase (ALT) activity has been assayed in (30) women serum samples with celiac disease, age range between (20-40) year and (30) serum of healthy women as control group, age range between (22-38) year. In the present study, the mean value of ALT activity was significantly higher in patients with celiac disease than healthy group (p<0.01). The ALT enzyme was partial purified from sera women with celiac disease by dialysis, gel filtration using Sephadex G- 50 and ion exchange chromatography using DEAE- cell

Celiac disease (CD) is the most common genetically - based disease in correlation with food intolerance. The aim of this study is to measure the activity of ALT enzyme and purify enzyme from sera women with celiac disease. Alanine aminotransferase (ALT) activity has been assayed in (30) women serum samples with celiac disease, age range between (20-40) year and (30) serum of healthy women as control group, age range between (22-38) year. In the present study, the mean value of ALT activity was significantly higher in patients with celiac disease than healthy group (p<0.01). The ALT enzyme was partial purified from sera women with celiac disease by dialysis, gel filtration using Sephadex G- 50 and ion exchange chr

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac