Background: The altered status of some essential trace elements observed in diabetes could have deleterious influences on the health of the diabetics. Objectives: To estimate and study the potential role of serum Selenium in type 1, type 2 diabetics and healthy subjects; and its relation with lipid profile and glycemic index. Methods: A case control designed study was carried out at the National Diabetes Center (NDC) / Al-Mustansiria University; on a total of 94 participants formed of 32 type 1 diabetics, 32 type 2 diabetics and 30 healthy control participants. Data collected about age, sex and BMI; also, blood samples examined for FPG, HbA1C, serum total cholesterol, HDL cholesterol, non-HDL cholesterol, serum triglyceride and sera were examined for Selenium by using atomic absorption technique. Results: Type 1 and type 2 diabetic groups show respectively 75% and 65% decrement in S. Selenium, <70 µg/L. The mean of S. Selenium, age, BMI, waist/hip ratio, FPG, HbA1c, total cholesterol, triglyceride, HDL, Non-HDL and atherogenic index (total cholesterol/HDL cholesterol) for the type 1 and type 2 diabetics shows statistically significant differences from control group. Type 1 diabetics versus type 2 diabetics shows statistically insignificant differences between mean of the S.Selenium, total cholesterol, HDL cholesterol and atherogenic index (t-test, P > 0.05) while the mean of FPG, HbA1c and triglyceride show highly statistical significant differences (t-test, < 0.001).Simple linear correlation and regression analysis of FPG, HbA1c, total cholesterol, triglyceride, HDL, Non-HDL and atherogenic index of the studied groups shows weak to moderate correlation with their serum Selenium levels. Conclusions: The inverse relationship between Selenium status and glucose tolerance suggest the potential role of Selenium in diabetics. Serum Selenium levels show high statistically significant differences from healthy subjects; while the differences between type1 and type 2 diabetic groups’ shows no statistically significant differences. Inverse correlations and regression were noticed between S.Selenium levels of all studied groups with their FPG, HbA1c, total cholesterol, triglyceride, HDL, Non-HDL and atherogenic index. Low S.Selenium and HDL-cholesterol plus an increase in total cholesterol, non-HDL and atherogenic index enhance risk of cardiovascular diseases progression among the diabetics.
Breast cancer is a disease in which cells in the breast grow out of control. CD200 is a cell surface glycoprotein expressed on many cells, it belongs to the immunoglobulin family (Ig) and have a great role in the regulation of inflammation in autoimmunity. CD200 is the ligand for CD200R1 receptor. To determine if serum level of CD200 and its receptor CD200R1 can be used as a diagnostic and prognostic marker in patients with breast cancer.This case control study was carried out at Oncology Teaching Hospital – Medical city in Baghdad. Six groups were enrolled, four groups were confirmed with breast cancer stage (I, II, III and IV), fifth group (benign) and sixth group was control (healthy individual). Serum is divided to me
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Background: Anti-oxidants are used as supplements to counteract the over production of free radicals in periodontal disease.Co-Q10 functions as an intercellular antioxidant by acting as a primary scavenger of free radicals (FRs) and reactive oxygen species (ROS), this study aimed to evaluate the effect of intra pocket application of perio Q gel (coenzyme Q10) alone and as adjunct to scaling and root planing on the periodontal clinical parameters in the treatment of patients with chronic periodontitis and compare the better improvement on the clinical periodontal parameters among different treatment modalities at 3 and 6 weeks. Materials and methods: A total of 323 sites with pocket depth (5-8) mm in patients with chronic periodontitis were
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The Growth Differentiation Factor -15 (GDF-15) is a member of the transforming growth factor β superfamily. İt represents an example of the stress response cytokines. It's mostly found in cardiac myocytes, adipocytes, macrophages, endothelial cells, and vascular endothelial cells, whether they're generated normally or not. GDF-15 levels have increased and are associated with cardiovascular risk. Aim of the study: To investigate the correlation between angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor blockers (ARBs) with the level of plasma GDF-15 in a group of hypertensive patients. Materials and methods: A case-control study involved 90 individuals, 60 hypertensive patients (36 on ACE inhibitors and 24 on ARBs)
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Background: Human leukocyte antigen-G (HLA-G)and Toll-like receptor-9 (TLR-9)play a role in the regulation of autoimmune diseases and inflammatory processes. Aim of the study: To detect the HLA-G + 3142G > C gene polymorphism that associated with the susceptibility to SLE patients and associated with Hepatitis B infection and TLR-9 serum level. Patients and methods: This study was done on 75 SLE patients and 75 healthy control groups. Genotyping of HLA-G + 3142G > C were detected by PCR and PCR-RFLP methods. In addition to the estimation of Hepatitis B surface (HBs)antigen status by immunochromatography technique and TLR-9 serum level by ELISA technique. Results: The HLA-G + 3142G > C gene polymorphism between the SLE patients and controls
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Prostate cancer is an important and potentially fatal disease in humans. Both genetic and environmental risk factors are associated with increased risk of prostate cancer among Asian pop
Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
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