Metabolic dysregulation and obesity are associated with many metabolic alterations, including impairment of insulin sensitivity and dyslipidemia. Recent studies highlight the key role of phosphatidylinositol 3,4,5-triphosphate-dependent Rac exchange proteins (PREX proteins) in the pathogenesis of obesity, advocating further elucidation of their potential therapeutic implications. The present study aimed to estimate the serum level of PREX proteins and its potential association with insulin resistance markers and plasma lipids level in obese and overweight non-diabetic patients. The study included 30 persons classified as obese, 30 as overweight, and 30 healthy individuals of similar age and gender. The levels of PREX1 and PREX2 were

Consequence of thermal and concentration convection on peristaltic pumping of hyperbolic tangent nanofluid in a non‐uniform channel and induced magnetic field is discussed in this article. The brief mathematical modeling, along with induced magnetic field, of hyperbolic tangent nanofluid is given. The governing equations are reduced to dimensionless form by using appropriate transformations. Exact solutions are calculated for temperature, nanoparticle volume fraction, and concentration. Numerical technique is manipulated to solve the highly non‐linear differential equations. The roll of different variables is graphically analyzed in terms of concentration, temperature, volume fraction of nanoparticles, axial induced magnetic fie

Background: Neutrophils destroy pathogens via phagocytosis. Neutrophils are effective innate and acquired immunity phagocytes. Low-density neutrophils are distinct neutrophil phenotypes linked to several systemic and infectious diseases. To our knowledge, low-density neutrophil phagocytosis in periodontitis has not been examined. Opsonized and non-opsonized fluorescent beads mixed with low-density neutrophils were gated and analyzed by flow cytometry to count cells that consumed at least one bead.

Aims of the Study: To estimate the potential impact of antibody (Ab)-labeled and non-labeled phagocytosis capacity of low-d

Foreign trade is very important in global economies because of its impact on the sustainability of economic growth by stimulating economic activity, creating jobs and expanding production . On the other side , this policy is a major obstacle to many developing countries and the reason is due to the nature of the economies of those countries because they rely mostly on one or a few economic resources, which makes them rely mostly on exports to that resource while they import most of the needs of their  local market Which makes them in a spiral of underdevelopment ,  dependence and economic exposure, which requires them to break that cycle and the launch of economic development Perhaps one of the most important means to a

Rudimentary non-communicating functional uterine horn with unicornuate uterus, originating from anomalous embryological development of one Mullerian duct, is prone to different complications either at the gynecological or obstetrical level such as chronic pelvic pain, hematometra, subfertility and decreased quality of life. This unique case report presents a 14-year-old female with a history of severe chronic pelvic pain. She was diagnosed with Familial Mediterranean Fever (FMF) and had an appendectomy for suspected appendicitis within the symptoms’ interval. Ultrasound showed a right 5*6 cm right complex cystic mass assuming ovarian in place. She underwent a suspected endometrioma cystectomy operation and was diagnosed with left unico

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

 Abstract

The study of oxygen mass transfer was conducted in a laboratory scale 5 liter stirred bioreactor equipped with one Rushton turbine impeller. The effects of superficial gas velocity, impeller speed, power input and liquid viscosity on the oxygen mass transfer were considered. Air/ water and air/CMC systems were used as a liquid media for this study. The concentration of CMC was ranging from 0.5 to 3 w/v. The experimental results show that volumetric oxygen mass transfer coefficient increases with the increase in the superficial gas velocity and impeller speed and decreases with increasing liquid viscosity. The experimental results of k_la were correlated with a mathematical correlation des

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration