ABSTRACT Background: One of the challenges to use chlorhexidine is its effect on the amount of microleakage after restoration; however, use of the materials with antibacterial properties after tooth preparation and before restoration has been widespread. The objective of this, in-vitro, study was to evaluate the influence of consepsis (chlorhexidine gloconate disinfectant) application on microleakage in class II cavities restored with light cured composite using universal adhesive system; etch and rinse technique –self etch technique. Materials and Methods: Forty class II cavities were prepared on mesial and distal surfaces of 20 non-carious mandibular third molars. The cavities were divided into four groups; (n =10 for each group).

A new ligand [3(3(2chloroacetyl) thioureido)pyrazine-2-carboxyliIcacid](CPC)was synthesized by reaction of rized by imicro elmental analysis C.H.N.S.,FT-IR,UV-Vis and 1H-13CNMR spectra, some transition metals complex ofIthis ligand were Prepared and characterized byiFT-IR,UV-Vis spectra conductivity measurements magnetic susceptibility and atomic absorption. From the obtained results the molecular formula of all prepared complexes were[M(CPC)2](M+2i=Mn. Co, Ni, Cu, Zn, Cd and Hg),the proposedi geometrical structure for all complexes were as tetrahedral geometry except copper complex has square planer geometry.

     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

حضر الليكاند (L) 1-فنيل-3-بردين-2-يل مثيل-ثايويوريا من تفاعل 2-أمينو مثيل بردين مع فنيل ايزوثايوسيانيت وبنسبة 1: 1 وشخص الليكاند بواسطة التحليل الدقيق للعناصر (C, H, N), الأشعة تحت الحمراء، الأشعة فوق البنفسجية–المرئية وطيف الرنين النووي المغناطيسي كما حضرت وشخصت معقدات أملاح بعض ايونات العناصر الثنائية التكافؤ (Co, Ni, Cu, Cd and Hg). استخدمت تقنية الأشعة تحت الحمراء، الأشعه فوق البنفسجية-المرئية, التوصيلية الكهربائية و الا

The Growth Differentiation Factor -15 (GDF-15) is a member of the transforming growth factor β superfamily. İt represents an example of the stress response cytokines. It's mostly found in cardiac myocytes, adipocytes, macrophages, endothelial cells, and vascular endothelial cells, whether they're generated normally or not. GDF-15 levels have increased and are associated with cardiovascular risk. Aim of the study: To investigate the correlation between angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor blockers (ARBs) with the level of plasma GDF-15 in a group of hypertensive patients. Materials and methods: A case-control study involved 90 individuals, 60 hypertensive patients (36 on ACE inhibitors and 24 on ARBs)

The placenta is an organ between the mother and fetus necessary for fetal growth and development. Gestational diabetes mellitus (DM) is the most frequent metabolic condition detected during pregnancy. It is characterized as hyperglycemia of various severity with onset or first detection during pregnancy that does not clearly describe any form of preexisting diabetes. Urotensin II (UII), a pluripotent vasoactive peptide, is important in developing insulin resistance. This study aimed to determine the level of Urotensin II(UII) in placenta and in the serum of diabetic and nondiabetic women. Methods The blood and placenta tissue collected from 50 ladies had been enrolled in this research ( 25 females with uncomplicated), (25 women with gestati

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and