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Association of HLA-DRB1/DQB1 Alleles and Genetic Susceptibility to Type 1 Diabetes Mellitus
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Objective: This study was conducted to identify the association of HLA-DRB1/DQB1 genes with the susceptibility or resistance to type 1 diabetes mellitus (T1D) among patients between the ages of five and eighteen.

Subjects and Methods: The study included 200 Sudanese participants, ages ranging from 5 to 18. One hundred participants were healthy non-diabetic as the control group and 100 with T1D as the case group. The investigation was carried out in Khartoum state. The selection of patients with T1D was from diabetic centers and hospitals. The allele-specific-refractory mutation system-polymerase chain reaction (ARMS-PCR) technique was applied to identify the HLA gene polymorphism.

Results: There was a significant difference in genotype frequency across the groups in the current investigation (Kruskal-Wallis, p-value= 0.021). Whereas CG was not substantially different across groups (Chi-square, p-value=0.116), the CC genotype was considerably greater (46.0%) in patients (Chi-square Adjusted p-value0.001).

Conclusion: This study found that patients' genotypes and allele frequencies are significantly correlated when compared to those of healthy participants.

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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Comparison study of Interleukin-1 alpha between Unstable Angina and Acute Myocardial Infarction patients
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Multiple studies support a role for inflammation in the pathogenesis of coronary atherosclerosis and unstable cardiac syndromes. However, of the known pro-inflammatory cytokines, only elevated plasma levels of interleukin-6(IL-6) have been linked to Unstable Angina. We sought to examine the plasma levels of other major proinflammatory cytokines in similar clinical settings patients with unstable angina and acute myocardial infarction and the relationship extent between them. This study aimed to investigate and compare the level of IL-1 in Unstable Angina and Acute Myocardial Infarction patients. Thirty patients with unstable angina and thirty patients with Acute Myocardial Infarction, also thirty healthy individual as control were included

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Publication Date
Sun Dec 20 2020
Journal Name
Journal Of Global Pharma Technology
Synthesis, Characterization, Antibacterial and Antifungal Activity of Some Bis (1, 3, 4-oxadiazole) Polymer
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Pyridine-2, 6-dicarbohydrazide comp (2) was synthesized from ethanolic solution of diethyl pyridine-2, 6- dicarboxylate comp (1) with excess of hydrazine hydrate. Newly five polymers (P1-P5) were synthesized from reaction of pyridine-2, 6-dicarbohydrazide comp (2) with five different di carboxylic acid in the presence of poly phosphoric acid (PPA). The antibacterial activity of the synthesized polymers was screened against some gram positive and gram negative bacteria. Antifungal activity of these polymers was evaluated in vitro against some yeast like fungi such as albicans (candida albicans). Polymers P3, P4 and P5 exhibited highest antibacterial and antifungal against all microorganisms under test.

Publication Date
Wed Sep 30 2015
Journal Name
Journal Of Natural Sciences Research
Study the levels of GPCR, GLP-1 and related hormones controlled and uncontrolled in diabetic patient's.
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The aim of the present study is to evaluate the change in the levels of glucagon, GLP-1 and GPCR in diabetic patient's and diabetic with dyslipidemia as metabolic syndrome. The study included 75 male aged ranged (30-50) years and with BMI (25-29) kg/m2 which divided into three groups as follows: group one (G1): consist of 25 subjects as healthy control group. Group two (G2): consist of 25 patient's with diabetes mellitus and group three (G3): consist of 25 patient's with diabetic and dyslipidemia as metabolic syndrome. Serum was used in determination of FBG, lipid profile, insulin, glucagon, GLP-1 and GPCR. Whole blood was determination of HbA1c. The results revealed significant elevation in FBG and HbA1c in G2 and G3 comparing to G1. While

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Publication Date
Thu Jun 27 2024
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Impact of Gliclazide Modified Release or Glimepiride as Add-on Therapy to Metformin on Glycemic and Oxidative Stress Parameters in Type 2 Diabetic Patients
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Background: Type 2 diabetes mellitus is a condition characterized by an elevation of oxidative stress, which has been implicated in diabetic progression and its vascular complications. Aim: Assessing the impact of gliclazide modified release (MR) versus glimepiride on oxidative stress markers, glycemic indices, lipid profile, and estimated glomerular filtration rate in uncontrolled type 2 diabetic patients on metformin monotherapy. Methods: This was an observational comparative study conducted in Thi-Qar specialized diabetic, endocrine, and metabolism center. Sixty-six patients were randomized into two groups based on the addition of the sulfonylureas (SUs). Group 1 (33 patients) was on gliclazide MR, whereas Group 2 (33 patients)

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Statistical
Evaluating the performance of introduced varieties of maize (Zea Mays L.) and estimating some genetic parameters
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sci.
Evaluating the performance of introduced varieties of Maize (Zea mays L.) And estimating some genetic parameters
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Publication Date
Sun Dec 01 2019
Journal Name
Indian Journal Of Ecology
Evaluation of maize hybrids, their inbred lines and estimation of genetic divergence based on cluster analysis
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Publication Date
Mon Jan 01 2018
Journal Name
Iraqi Journal Of Agricultural Sciences, 2018, 49(2), Pp. 179–187
Estimation of some genetic parameters for grain yield and its components of maize under watered and water stress
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Publication Date
Fri Apr 01 2016
Journal Name
Nurse Education Today
Diabetes knowledge of nurses in different countries: An integrative review
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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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