Diabetes mellitus (DM) is a chronic metabolic disease that is considered a major worldwide healthcare problem. Multiple studies have revealed that people with DM are more likely to acquire oral problems, such as periodontal diseases, because the oral microbiota plays a major role in oral health and may affect the saliva composition. This study aimed to characterize the oral microbiota of a sample of DM patients and its association with some demographic factors, such as smoking habits and gender. A total of 91 specimens, including 51 DM patients and 40 apparently healthy individuals, were enrolled in this study, which was carried out from November 2021 to February 2022. Whole saliva was collected in a sterile tube, and oral swabs were obtained from both patients and the control groups. The results of the present study show there was no significant difference between both genders in DM hits. As well, a smoking habit is considered a predisposing habit that may increase the risk of oral diseases in DM patients. The acidic pH of saliva recorded higher values between patients and control subjects than other pH items. On the other hand, the most prevalent bacterial isolates found in oral DM patients were Staphylococcus spp. (37.12%), E.coli (12.9%), Klebsiella spp. (10.60%), Pseudomonas spp. (9.84%), Enterobacter (8.33%), both Streptococcus spp. and Acinetobacter spp. (5.30%), Corynebacterium spp. and Proteus spp. (3.8%), Neisseria spp. and Haemophilus Influenza was 1.51%. These percentages were significantly different from those in the control group, which were Staphylococcus spp. (43.4%), Klebsiella spp. (25.0%), Enterobacter (7.89%), E.coli (6.58%), Bacillus spp. (5.2%), Acinetobacter spp. (3.9%), Pseudomonas spp., Streptococcus spp., and Proteus spp. (2.7%).
Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them. Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 normal healthy f
... Show MoreObjective: Atorvastatin therapy is now recommended for reduction of cardiovascular risk in type 2 diabetic patients (T2DM), based on convincing evidence of reductions in mortality and vascular events in major clinical outcome trials. The aim is to evaluate the effects of atorvastatin on proinflammatory markers (TNF-α, IL-6), HbA1c andleptin in obese patients with type 2 diabetes. Methods: Sixty fivenewly diagnosed T2DM patients were randomly allocated into 2 groups; group I treated with metformin only; in group II atorvastatin was added with metformin. Twenty healthy subjects were enrolled as control group. While maintaining their usual eating habits, fasting blood samples were collected at baseline and after 12 weeks of treatment. Results
... Show MoreAim of the study is to find any correlation between obesity (insulin resistance) and type I diabetes in children. Obesity and diabetes mellitus are the common health problems, and obesity is common cause of the insulin resistance. The results revealed marked increased in glucose, insulin, HbAlc and insulin resistance in obese diabetic type I patients comparing to control group they were obese and non-obese found to be within normal values for glucose, insulin, FIbAlc , and insulin resistance.
Background: Type I diabetes mellitus is an autoimmune disorder characterized by destruction of insuline producing.
In order to investigate the levels of reduced glutathione GSH and α1-antitrypsine in the sera of 20 type 2 diabetic patients and 10 healthy subjects, were enrolled in this study. A significant reduction in GSH level was found in the patient group compared with control. On the other hand a significant elevation in α1-antitrypsine in patient compared with control was observed. Correlation between α1-antitrypsine and reduced glutathion was found to be positive (+Ve) for diabetes mellitus type2 patients and negative (-Ve) for healthy control with r values 0.257 and – 0.339 respectively. In conclusion the depletion of GSH as antioxidant defense insured higher free radical generation in diabetic patients
... Show MoreBackground: Diabetes mellitus type 2 has been known for many years as the most common endocrine metabolic disorder that affect the oral cavity and cause many oral diseases including candidiasis. In this study, the incidence of Candida spp. in the saliva of controlled and uncontrolled diabetic patients were determined and compared with non diabetic group. Material and method: The sample consists of 200 subjects: 100 diabetic patients [57 (28.5%) uncontrolled diabetes, 43 (21.5%) controlled diabetes] and 100 (50%) non diabetic groups. Saliva samples was obtained from the subjects and cultured on selective media using appropriate microbiological method to observe the presence of Candida spp. Results: The results revealed a significant associat
... Show MoreThis study included 50 blood samples collected from children with mean age 8-12 years. Thirty five blood samples were collected from children with Type 1 Diabetes Mellitus (T1D) with mean age 9.4±0.34 years, and 15 blood samples collected from healthy children as a control sample with mean age 10.9±0.38 years. Immunogenetic study was done on collected blood samples. Concentrations of IFN-γ were estimated from T1D patient and control samples by using Elisa instrument. The concentration of this interferon was 1.575 pg/ml in T1D patient sample in comparison with 0.921 pg/ml in control sample. Significant differences of this interferon concentration were found between T1D patient and control samples when Mann-Whitney U test was used
... Show MoreRheumatoid arthritis is a chronic inflammatory autoimmune disease its etiology is unknown. The classical autoimmune diseases, have adaptive immune genetic associations with autoantibodies and major histocompatibility complex (MHC) class II such as rheumatoid arthritis (RA), diabetes mellitus type two (DM II). Serum of99 males suffering from RA without DMII as group (G1), 45 males suffering from RA with DM II as group (G2) and 40 healthy males as group (G3) were enrolled in this study to estimation of alkaline phosphates (ALP), C-reactive protein (CRP) and Pentraxin-3(PTX). Results showed a highly significant increase in PTX3 levels in G1 and G2 compared to G3 and a significant decrease in G1comparing to G2. Results also revealed a significa
... Show MoreBackground: Diabetes and periodontitis are considered as chronic diseases with a bidirectional relationship between them. This study aimed to determine and compare the severity of periodontal health status and salivary parameters in diabetic and non-diabetic patients with chronic periodontitis. Materials and Methods: Seventy participants were enrolled in this study. The subjects were divided into three groups: Group I: 25 patients had type 2 diabetes mellitus with chronic periodontitis, Group 2: 25 patients had chronic periodontitis and with no history of any systemic diseases, Group 3: 20 subjects had healthy periodontium and were systemically healthy. Unstimulated whole saliva was collected for measurement of salivary flow rate and pH.
... Show MoreDiabetes is a disease caused by high sugar levels. Currently, diabetes is one of the most common diseases in the number of people with diabetes worldwide. The increase in diabetes is caused by the delay in establishing the diagnosis of the disease. Therefore, an initial action is needed as a solution that requires the most appropriate and accurate data mining to manage diabetes mellitus. The algorithms used are artificial neural network algorithms, namely Restricted Boltzmann Machine and Backpropagation. This research aims to compare the two algorithms to find which algorithm can produce high accuracy, and determine which algorithm is more accurate in detecting diabetes mellitus. Several stages were involved in this research, including d
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