Background: In advanced diabetes mellitus, serum levels of the most hormones are altered due to several interplaying mechanisms. Objective: To assess the relation of serum leptin and lipid profile in type 2 diabetic nephropathy. Patients and Method: Serum leptin levels and its relation to lipid profile were estimated in 62 patients with type 2 diabetic nephropathy attending the National Diabetes Center in Al- Mustansiriya University, and (26) healthy individuals considered as control group. The diabetic patients were classified into three groups, (24) pathients with normoalbuminuria (21) patients with microalbuminuria and (17) patients with macroalbuminuria. Fasting plasma glucose, serum creatinine, Hb A1c %, lipid profile (Total cholesterol, LDL- Cholesterol, HDL- Cholesterol and Triglyceride) and urinary albumin, were measured to establish the possibility of using these biomarkers as a supplementary to serum leptin to be a diagnostic test for type 2 diabetic nephropathy. Results: Serum leptin levels showed a significant elevation in microalbuminuria (20.08± 4.50 ng/ml) and macroalbuminuria groups (22.35± 6.89 ng/ml) as compared to nondiabetic normal control group (10.64 ± 3.17 ng/ml). There was no significant differences observed in serum leptin levels between the normoalbuminuria group (13.96 ± 5.73 ng/ml) and healthy controls, but a significant positive differences were noticed in the levels of fasting plasma glucose, serum creatinine, Hb A1c% and lipid profile in the three patient groups in comparison with the control group. While no significant correlation was observed between these biomarkers levels and serum leptin values. Conclusion: It might be concluded that serum leptin levels were elevated in type 2 diabetic patients with microalbuminuria and macroalbuminuria, suggesting that renal leptin degradation is impaired in early stage of kidney damage and this impairment increase with the progression of this disease. Leptin hormone may consider according to these results as a risk factor for progression of kidney disease in diabetic patients.
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The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode
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Abstract:
The models of time series often suffer from the problem of the existence of outliers that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of
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The purpose of this paper is to identify environmental awareness under the Corona pandemic among students of the Faculty of Physical Education and Sports Sciences at the University of Kufa. and comparison of environmental awareness under the Corona pandemic between students of the Faculty of Physical Education and Sports Sciences at the University of Kufa. The two researchers used the descriptive approach in the style of the survey and comparisons to identify the research community in the students of the College of Physical Education and Sports Sciences at the University of Kufa for the academic year 2020-2021, who numbered (210) students, then a sample of (80) students was chosen randomly, with a percentage of (38.09%) from the research co
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