This study included 50 blood samples that were collected from patients with age ranged between 35-65 years. Thirty samples were collected from patients with Type 2 Diabetes Mellitus (T2DM), while 20 blood samples were collected from healthy individuals as a control sample. The polymorphism results of TGF-β1 gene in codon 10: +869*C/T position by using amplification refractory mutation system (ARMS-PCR) showed that the T allele was suggested to have a protective effect, while C allele was associated with an increased risk of T2DM. The TT and CT were suggested to have a protective effect, while CC genotype was associated with an increased risk of T2DM. The polymorphism results of TGF-β1 gene in codon 25: +915*G/C position in samples

Background: Atherosclerosis is well known related to age and certain cardiovascular diseases. Aging is one reason of arteries function deterioration which can cause loss of compliance and plaque accumulation, this effect increases by the presence of certain diseases such as hypertension and diabetes disease. Aim: To investigate the reduction of blood supply to the brain in patients with diabetes and hypertension with age and the role of resistive index in the diagnosis of reduced blood flow. Method: Patients with both diseases diabetic and hypertension were classified according to their age to identify the progression of the disease and factors influencing the carotid artery blood flow. By using ultrasound and standard Doppler techniq

An experimental study was conducted to evaluate the effect of AL-coholic extract alkaloid of Cordia myxa leafs in fourth larval stage of lesser grain borer Rhyzopertha dominica. Using alkaline extracts of 8%, the study has been shown clear effect increased in mortality rate for fourth larval stage 93.3% and degressed to 66.6% at 4% concentrate to 13.3% with control treatment .Ahigher percentage of pupal mortality 16.6% at 4% concentrate has been observed, while no natural emergence carried out at concentrates of 4.6% comparing with control treatment of 86.66%, at the same time percentage of deformation has been increased to 16.66% at 4% of extracts and degressed to 6.66% at 6% while no deformation have been shown with control treatment .

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

Background: Diabetes mellitus consists of a group of diseases characterized by abnormally high blood glucose levels. Glycated haemoglobin (HbA1c) is a form of haemoglobin used to identify the average concentration of plasma glucose over prolonged periods of time. It is formed in a non-enzymatic pathway by normal exposure of hemoglobin to high levels of plasma glucose, The main alterations observed in the saliva of Type 1 diabetic patients are hyposalivation and alteration in its composition, particularly those related to the levels of glucose. The aim of the present study was to assess the effect of Glycated haemoglobin level on the level of salivary glucose which may have an effect on oral health condition. Materials and methods

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti