The absorption spectrum for three types of metal ions in different concentrations has been studying experimentally and theoretically. The examination model is by Gaius model in order to find the best fitting curve and the equation controlled with this behavior. The three metal ions are (Copper chloride Cu⁺², Iron chloride Fe^+3, and Cobalt chloride Co⁺²) with different concentrations (10^-4, 10^-5, 10^-6, 10^-7) gm/m³. The spectroscopic study included UV-visible and fluorescence spectrum for all different concentrations sample. The results refer to several peaks that appear from the absorption spectrum in the high concentration of all metal ions solution.

Background: All diseases concerning bone destruction such as osteoporosis and periodontal diseases share common pattern in which the osteoclast cells are absolutely responsible for bone resorption that occurred when osteoclast activity exceeds osteoblast activity. Osteoprotegrin (OPG) considered as novel soluble decoy receptor known as “bone protector” since it prevents extreme bone resorption through inhibition of differentiation and activity of osteoclast by competing for binding site. It binds to receptor activator of nuclear factor kappa-B ligand (RANKL) and prevent its interaction with receptor activator of nuclear factor kappa-B (RANK), thus inhibits osteoclast formation. TNF-α is a pro-inflammatory cytokines having

Abstract: This study was aimed to investigate the effect of two doses of pregabalin (PGB) on hormonal level and sexual activity in female albino rats. Ninety female rats with age (9-10 weeks) and weight (200±20 g) were divided into three major groups of thirty rats. First group was considered as control G1, the second G2 and third G3 groups were exposed to PGB into two doses 150, and 300 mg/kg body weight per day respectively. Each major group was divided into three subgroups (subgroup A, B, and C of each has ten rats), the treatments last for one month for subgroup A, two months for subgroup B, and three months for subgroup C. Five rats from each subgroup were placed separately into two breeding cages with two isolated males and wait

Background: Diabetes mellitus is a chronic disease with an increasing prevalence worldwide and characterized by an increase in oxidative stress and inflammation. The most important factor that is responsible for oxidative stress and production of reactive oxygen species (ROS) is hyperglycemia. The major targets of ROS are proteins. The most common and widely used biomarker of severe oxidative protein damage is protein carbonyl content.

The study was designed to assess the serum level of protein carbonyl as a marker of protein oxidation in patients with type 2 diabetes mellitus and to evaluate the effect of age, body weight, waist circumference, diabetic control and disease duration on the level

Objective This study aims to investigate the impact of integrated training on kinematics variables and defensive accuracy in volleyball, focusing on enhancing balance and muscle tension control through proprioceptive neuromuscular facilitation (PNF) exercises. Methods The sample consisted of 14 male volleyball athletes from the first volleyball league of Al-Jaish Sports Club were divided into experimental (n=7) and control group (n=7). In the pre- and post-intervention periods, dynamic balance, muscle tension control and kinematic variables (during a lateral reaching task) as well as defensive performance accuracy upon fatigue onset of recoil laser strikes were assessed. Exposure the intervention program was carried out for six weeks, and t

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F