Background: The anticancer impact of Epigallocatechin gallate (EGCG) the highly active polyphenol of green tea was abundantly studied.  Though, the exact mechanism of its cytotoxicity is still under investigation. Objectives: Hence, the current study designed to investigate the molecular target of EGCG in HepG2 cells on thirteen autophagy- and/or apoptosis- related genes. Methods: The apoptosis detection analyses such as flow cytometry and dual apoptosis assay were used. The genes expression profile was explored by the real-time quantitative-PCR. Results: EGCG increases G0/G1 cell cycle arrest and the real-time apoptosis markers proteins leading to stimulate apoptos

Experimental study has been conducted for laminar natural convection heat transfer of air flow through a rectangular enclosure fitted with vertical partition. The partition was oriented parallel to the two vertical isothermal walls with different temperatures, while all the other surfaces of the enclosure were insulated. In this study a test rig has been designed and constructed to allow studying the effect of Rayleigh number, aperture height ratio, partition thickness, the position of aperture according to the side walls and according to the height, the position of the partition according to the hot wall, and partition inclination. The experiments were carried out with air as the working fluid for Rayleigh number range (5*107 – 1.3*10

Type-1 diabetes is defined as destruction of pancreatic beta cell, virus and bacteria are some environmental factor for this disease. The study included 25 patients with type-1 diabetes mellitus aged between 8 – 25 years from Baghdad hospital and 20 healthy persons as control group. Anti-rubella IgG and IgM, anti-Chlamydia pneumonia IgG and IgM were measured by ELISA technique while anti-CMV antibody were measured by immunofluorescence technique. The aim of current study was to know the trigger factor for type-1 diabetes. There were significant differences (P<0.05) between studied groups according to parameters and the results lead to suggest that Chlamydia pneumonia, CMV and rubella virus may trigger type-1 diabetes mellitus in Iraqi pat

Many isolated rural communities are located in regions where there is an abundant and reliable supply of solar energy, but where the distance to the nearest power station is many tens or even hundreds of kilometre. It is therefore mainly in these areas that rural electrification is now being provided by PV generators. since Stand-Alone PV generator can offer the most cost-effective and reliable option for providing power needed in remote places. Accordingly these isolated rural canters are fitted with PV for lighting, a refrigerator, a television and socket to supply kitchen appliances

2-amino-4-(4-chloro phenyl)-1,3-thiazole (1) was synthesized by refluxing thiourea with para-chloro phenacyl bromide in absolute methanol. The condensation of amine compound (1)  with phenylisothiocyanate in the presence of pyridine will  produce 1-(4-(4-chlorophenyl)thiazol-2-yl)-3-phenylthiourea(2), which is  upon treatment with 2,4 dinitrophenyl hydrazine by conventional method, afforded 1- ( 4 - ( 4 – chlorophenyl ) thiazol – 2 – yl ) – 3 - phenylhydrazonamide,N' - ( 2 , 4 -dinitrophenyl) ,(3).The characterization of the titled compounds were performed utilizing FTIR spectroscopy, ¹HNMR and CHNS elemental analysis, and by me

Background: Job satisfaction remains as an important concern for both employer and employee. A high-quality teaching staff is the cornerstone of a successful educational system. One step in developing a high quality faculty understands the factors associated with teaching quality and retention. One of these factors is job satisfaction, which has been studied widely by organizational researchers.Objectives: To evaluate the extent of job satisfaction of teaching staff working at AL-Kindy College of medicine and to identify some work-related factors associated with job satisfaction.Methods: A cross- sectional study was carried out. A convenient sample of 50 teaching staff, who had a teaching job at different scientific departments at AL-Kin

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise