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Pancreatic Stone Protein/ regenerating Protein (PSP/reg) as a Biochemical Marker for prediction of Microvascular Complications of Type 2 Diabetes Mellitus
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Background: Type 2 diabetes mellitus (T2DM) characterized by insulin resistance (IR) and progressive decline in functional beta (β) cell mass partially due to increased β cell apoptosis rate. Pancreatic stone protein /regenerating protein (PSP/reg) is produced mainly by the pancreas and elevated drastically during pancreatic disorder. Beta cells are experiencing apoptosis that stimulate the expression of PSP/reg gene in surviving neighboring cells, and that PSP/reg protein is subsequently secreted from these cells which could play a role in their regeneration.

Objectives: To analyze serum levels of PSP/reg protein in T2DM patients and evaluate its correlation with the microvascular complications of the disease.

Subjects and Methods: One hundred fifty participants (64 males, 86 females; aged 40–70 years) include T2DM patients with and without microvascular complications as well as healthy controls were enrolled in this study. Biochemical parameters like random blood glucose (RBG), glycated hemoglobin (HbA1c), lipid profile, urea and creatinine (Cr) were measured. Serum values of PSP/reg protein were measured by enzyme- linked immunosorbent assay (ELISA).

Results: Serum levels of PSP/reg protein were found significantly elevated in T2DM patients with microvascular complications compared with those of controls (p<0.001) and T2DM patients without microvascular complications (p< 0.001).PSP/reg protein is correlated with type 2 DM duration (p<0.001), RBG (p<0.001), and HbA1c (p<0.001). The area under the curve (AUC) for the presence of microvascular complications was 0.973.

Conclusion: PSP/reg protein may be used as biochemical marker to predict microvascular complications of T2DM.

 

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Thu Jan 30 2020
Journal Name
Al-kindy College Medical Journal
Satisfaction of Patients with Type II Diabetes on Health Service in Specialized Center for Endocrinology and Diabetes /Baghdad 2019
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Background: Patient satisfaction is of increasing importance and widely recognized as an important indicator of quality of the medical care. There was no homogeneous definition of patient satisfaction, since satisfaction concerns different aspects of care or settings, as well as care given by various professions.

Objective: The objective of this study is to assess the patients’ level of satisfaction with diabetes care and to identify the underlying factors influencing it.

Methods: This cross-sectional study had been conducted in the Specialized Center for Diabetes and Endocrinology in Baghdad Al- Rusafa 2018. Where150 type two diabetic patients attending their follow-up

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
The Detection of Silent Celiac Disease In patients With Type 1 Diabetes Mellitus by the use of Anti Tissue Transglutaminase Antibodies
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Objective: Detection the presumptive prevalence of silent celiac disease in patients with type 1 diabetes mellitus with determination of which gender more likely to be affected.
Methods: One hundred twenty asymptomatic patients [75 male , 45 female] with type 1 diabetes mellitus with mean age ± SD of 11.25 ± 2.85 year where included in the study . All subjects were serologically screened for the presence of anti-tissue transglutaminase IgA antibodies (anti-tTG antibodies) by Enzyme-Linked Immunosorbent Assay (ELISA) & total IgA was also measured for all using radial immunodiffusion plate . Anti-tissue transglutaminase IgG was selectively done for patients who were expressing negative anti-tissue transglutaminase IgA with low tot

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
The Detection of Silent Celiac Disease In patients With Type 1 Diabetes Mellitus by the use of Anti Tissue Transglutaminase Antibodies
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Objective: Detection the presumptive prevalence of
silent celiac disease in patients with type 1 diabetes
mellitus with determination of which gender more
likely to be affected.
Methods: One hundred twenty asymptomatic patients
[75 male , 45 female] with type 1 diabetes mellitus
with mean age ± SD of 11.25 ± 2.85 year where
included in the study . All subjects were serologically
screened for the presence of anti-tissue transglutaminase
IgA antibodies (anti-tTG antibodies) by Enzyme-
Linked Immunosorbent Assay (ELISA) & total IgA
was also measured for all using radial
immunodiffusion plate . Anti-tissue transglutaminase
IgG was selectively done for patients who were
expressing negative anti-

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Publication Date
Mon Apr 01 2024
Journal Name
Egyptian Journal Of Immunology
The role of C-reactive protein, procalcitonin, interleukin-6 and neutrophil / lymphocyte ratio as a laboratory biomarker in COVID-19
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Biomarkers such as Interleukin-6 (IL-6), Procalcitonin (PCT), C-reactive protein (CRP) and Neutrophil-Lymphocyte Ratio (NLR) have a role in the pathogenesis of severe coronavirus disease 2019 (COVID-19). The aim of this study was to explore the differences between serum levels of such biomarkers in severe and non-severe COVID-19 cases and compare them with normal people and to evaluate the sociodemographic variables and chronic diseases effect on the severity of COVID-19. The study included 160 subjects, divided into two groups, a case group of 80 patients, and a control group of 80 normal persons. The case group was divided into two subgroups: 40 severe COVID-19 patients and 40 patients with non-severe disease. Blood IL-6 was asses

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Publication Date
Wed Mar 15 2023
Journal Name
Journal Of The Turkish-german Gynecological Association
Obstetric and neonatal complications in large for gestational age pregnancy with late gestational diabetes
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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
Study ABO/Rh system with Endothelial Inflammatory Factors in Iraqi Arab Female with Diabetes Mellitus Type II
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Diabetes mellitus type II is a disorder of metabolism and complex diseases affected by genetic environmental factors and associated with inflammation. The symptoms of type II diabetes develop gradually, which are associated with increased blood concentration of marker of the endothelial inflammatory factors. The expression of adhesion molecules, including E-selectin, intracellular adhesion molecule-1(ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) on the surface of vascular endothelial cells to help leukocyte stick to other surrounding tissues. Many researchers have made attempts to determine the significance of particular ABO phenotype for the susceptibility to diseases. Many reports show a strong association with the ABO blood grou

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Publication Date
Mon Oct 24 2022
Journal Name
Plant Archives
USE OF APRICOT KERNELS PROTEIN ISOLATE IN BURGER INDUSTRY
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The current study was conducted with the aim of fortifying meat burger with the protein isolate extracted from defatted sweetened and unsweetened apricot kernels. The antimicrobial activity of defatted apricot kernels and protein isolates of sweetened and unsweetened kernels against some pathogenic microbes was studied, and it was characterized by its effect on gram-positive bacteria more than gram-negative bacteria. As for its effect on yeast, the inhibition diameter was 4.5 mm at a concentration of 200 mg for the unsweetened protein isolate. As for its effect on mold, the inhibition percentage was between 56.05 65.21% for all samples at a concentration of 100 mg. The sweetened and unsweetened protein isolate was used in the manufact

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Publication Date
Sun Jul 01 1990
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MEDIUM OPTIMIZATION FOR BIOMASS PRODUCTION AND PROTEIN CONTENT OF CANDIDA UTILES K50
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Molasse medium containing different concentrations of (NH4)2 SO4, (NH4)3 PO4, urea, KCI, and P2O5 were compared with the medium used for commercial production of C. utilis in a factory south of Iraq. An efficient medium, which produced 19. 16% dry wt. and 5. 78% protein, was developed. The effect of adding various concentrations of micronutrients (FeSO4, 7T20, MnSO4. 7H20, ZnSO4. 7E20) was also studied. Results showed that FeSo4. 7H20 caused a noticeable increase in both dry wt. and protein content of the yeast.

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Clinical and Sonographic Changes of Parotid Gland in Patients with Type I and Type II Diabetes Mellitus and Its Effect on Physical Properties of Saliva
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Background: Sialosis described as a specific consequence of diabetes. In diabetic sialosis, the increased volume of the glands is due to the infiltration of adipose in the parenchyma. The B-scan ultrasonography is a generally accepted tool for determining parotid gland enlargement. Oral health is, to a greater extent, dependent on quality and quantity of saliva, both of which may be altered in diabetics. This study was established to detect the enlargement of parotid gland in diabetic patient and study the changes in physical properties of saliva and its relation with the salivary gland enlargement. Subjects, Materials and Methods: A cross-sectional study with highly specified criteria with ages ranged (20-65) years, male and female subject

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