Abnormalities in the Lipid and lipoprotein levels are common in the general population and are considered as very important risk- factors for cardiovascular disease .In this context the effect of cholesterol, which is one of the most clinically relevant lipids is very important. Aim of the present study was to determine the levels of GLP-1 and GPCR in non- diabetic dyslipidaemic patients and compare the results with the control group, which may be used as a novel biomarker to predict heart disease in these patients. The study was also aimed to find the relationship between GLP-1 and GPCR with lipid profile and glucagon in the patient group. The study involved 90 non-diabetic dyslipidaemia patients, with 90 healthy controls. The subjects were matched by age (35-50 years) and body mass index (BMI) (28 kg/m2). Blood samples were collected from healthy controls and dyslipidaemic patients after 12-14 hours of fasting. The study was conducted between January 2015– September 2015 in the Ibn- Al Naphes hospital in Baghdad province / Iraq .Diabetic patients were exclusion from this study. BMI were determined for all student groups.FBG, Lipid Profile ,glucagon, GLP-1, GPCR was determined in the control and patient groups. The results are expressed as mean ± SEM. Student ̓s t-test was used to compare the significance of the variation between dyslipidaemia and control groups. Results showed nonsignificant elevations in BMI, FBS, and HbA1c levels in the patient group compared with the control group. There was a significant elevation in TC, TG, LDL-c, and VLDL-c levels in the patient group compared with the control group, while a significant decrease was noticed in HDL-c level in the patient group compared with the control group .There was also a significant elevation in glucagon, while a highly significant elevation in GLP-1 and GPCR levels in the patient group when compared with the control group. A significant correlation was observed between GLP-1 with TC, TG, HDL-c, and GPCR in the patient group. There was also a significant correlation between GPCR with TC, TG and HDL-c in the patient group. From this study, it is concluded that a significant increase in GLP-1and GPCR levels, in addition to their correlation with TC, TG, HDL-c and glucagon in the patient group, compared to the control group indicate that these parameters could be used as a novel biomarker to predict heart disease in these patients in future.
Communities seek to achieve the economic growth through the optimal use of resources. The human resource is considered the most important of those resources where the insurance institutions take the larger role in the protection of this resource and reducing the impact caused by dangers realization that endures. The general Iraqi insurance company is considered the leading in the field of life insurance since it was founded, and until now.
This research is based on an analyzing the relation between premiums and compensations of life insurance, for individual and the group insurance, and a reality of the
... Show MoreThe purpose of this research is to demonstrate the impact of banking compliance in combating money laundering and terrorist financing through banks. The phenomenon of money laundering and terrorist financing has received wide attention in the countries of the world and international organizations because of the negative effects this phenomenon has on the global economy as a result of exploiting developments and modern banking operations to pass Money laundering and terrorist financing operations in order to legitimize illegal funds and obliterate their criminal sources, which obliged the banking sector to increase control measures in order to reduce these operations, which conceal money laundering thr
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... Show MoreGroupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff
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