Background:
Background:
type 2 diabetes mellitus is a chronic disease that is accompanied by the production of free radicals which will ultimately increase the level of oxidative stress.
Diabetes mellitus (T2DM) is a multifactorial syndrome that israpidly rising in all the continents ofthe globe, causing elevated blood sugar levels in affected people. A sample of 81 Iraqi T2DM patients was investigated based on several parameters. Glycemic control parameters includedlevels of fasting blood glucose (FBG),
glycated hemoglobin (HbA1C), and insulin, along with insulin resistance (IR) and insulin sensitivity (IS). Renal function tests includedmeasuring the blood levels of urea and creatinine. Oxidative stress parameters included total antioxidant capacity (TAC) and thelevel of reactive oxygen species (ROS). The results of the present
study showed a highly significant (P˂0.01) increase in FBG, HbA1c, insulin and IR leve
Background: Diabetes mellitus consists of a group of diseases characterized by abnormally high blood glucose levels. Glycated haemoglobin (HbA1c) is a form of haemoglobin used to identify the average concentration of plasma glucose over prolonged periods of time. It is formed in a non-enzymatic pathway by normal exposure of hemoglobin to high levels of plasma glucose, The main alterations observed in the saliva of Type 1 diabetic patients are hyposalivation and alteration in its composition, particularly those related to the levels of glucose. The aim of the present study was to assess the effect of Glycated haemoglobin level on the level of salivary glucose which may have an effect on oral health condition. Materials and methods
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In this paper, we introduce and study new types of soft open sets and soft closed
sets in soft bitopological spaces (X,~ ,~ ,E) 1 2 , namely, (1,2)*-maximal soft open
sets, (1,2)*-maximal soft (1,2)*-pre-open sets, semi (1,2)*-maximal soft (1,2)*-preopen
sets, (1,2)*-maximal soft closed sets, (1,2)*-maximal soft (1,2)*-pre-closed
sets, (1,2)*-minimal soft open sets, (1,2)*-minimal soft (1,2)*-pre-open sets, (1,2)*-
minimal soft closed sets, (1,2)*-minimal soft (1,2)*-pre-closed sets, and semi (1,2)*-
minimal soft (1,2)*-pre-closed sets. Also, properties and the relation among these
concepts have been studied.
The goal of this study was to investigate the protein peroxidation role by measuring serum levels of advanced oxidation protein products (AOPP) in type 2 diabetic patients with or without retinopathy and comparing them to controls to see if circulating AOPP levels can be used as a detection biomarker for DR. And see which of the two widely used antidiabetic treatment groups had the most impact on this oxidative stress marker. The groups were divided into two subgroups: 1) 70 type 2 diabetic patients (36 male, 34 female), 35 with diabetic retinopathy (DR) and 35 with no evidence of DR, and 2) non-diabetic controls (11 male, 9 female) were chosen from Ibn AL-Haitham Hospital for Ophthalmology and a Specialized Center for Endocrinology and Dia
... Show MoreBackground: Inflammation and more specifically inflammatory cytokines are determinant in the development of microvascular diabetic complications, including neuropathy, retinopathy and nephropathy.
Objective: The aim of present study is to evaluate the relationships between high sensitive C-reactive protein, microalbuminuria and risk factors for cardiovascular disease.
Subjects and methods: the study involved (30) patients with type 1 diabetic mellitus compared to (30) healthy control. A fasting blood sample was drawn from all subjects after an overnight fasting to measure the biochemical parameters which including glycated hemoglobin, lipid profile, atherogenic index of plasma and high sensitive C-reactive protein concentration in
This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different
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