Both type 1 diabetes and type 2 diabetes have a genetic component, with over 60 chromosomal regions related to type 1 diabetes and over 200 connected with type 2 diabetes at significant genome-wide levels. Numerous single nucleotide polymorphisms in the RETN gene and genetic variables can account for up to 70% of the variations in circulating resistin levels. The RETN polymorphism has been linked in numerous studies to obesity, insulin sensitivity, type 2 diabetes, and cerebrovascular illness. Our objective is to compare this RETN gene 3ʹ-untranslated region polymorphism in type 1 diabetes and type 2 diabetes Iraqi patients. We choose 51 type 1 diabetes and 52 type 2 diabetes patients against 50 healthy subjects (control group) to investigate the comparative RETN gene polymorphisms in patients with type 1 diabetes and type 2 diabetes, using conventional polymerase chain reaction. The present study revealed statistically there was no significant increase in CC, CG, and GG genotypes (with Odd Ratio 1.43, 0.82, and 0.62 respectively) in type 1 diabetes, and statistically there was no significant increase in CC, CG, and GG genotypes (with Odd Ratio 0.68, 1.02 and 1.97 respectively) in type 2 diabetes as compared to the control group. Also, we found statistically there was no significant increase in C and G alleles in type 1 diabetes and type 2 diabetes groups as compared to the control group. The findings suggest that the CC genotype and C allele in RETN gene 3ʹ-untranslated region polymorphism rs1862513 increase the risk of type 1 diabetes compared to CG and GG genotypes, and the G allele in this gene increases the risk of type 2 diabetes in Iraqi patients.
<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
... Show MoreWater supply and distribution networks play an important role in our daily activities. They make a substantial contribution to public health by providing potable water for public consumption and non-potable applications such as firefighters and other purposes such as irrigation. This study used ArcMap 10.8 and WaterGEMS CONNECT Edition update 1 version to create a hydraulic network model to simulate the pipes’ network. Detailed network information, including pipe lengths, layouts, and diameters, was given by the Baghdad Water Department. The TUF-2000H Handheld digital ultrasonic flow meter has been used to measure the water flows in the network’s source nodes. In eight junctions,
Background: This study aimed to determine the cephalometric values of tetragon analysis on a sample of Iraqi adults with normal occlusion. Material and methods: Forty digital true lateral cephalometric radiographs belong to 20 males and 20 females having normal dental relation were analyzed using AutoCAD program 2009. Descriptive statistics and sample comparison with Fastlicht norms were obtained. Results: The results showed that maxillary and mandibular incisors were more proclined and the maxillary/mandibular planes angle was lower in Iraqi sample than Caucasian sample. Conclusion: It's recommended to use result from this study when using tetragon analysis for Iraqis to get more accurate result.
Yersinia enterocolitica has ranked a third among the pathogens that most frequently cause gastrointestinal disorders transmitted to humans through food materials, especially contaminated meats. The meat infected with Yersinia enterocolitica had no change in apparent texture or smell. The aim of this research is to survey the frequency of Y. enterocolitica in ovine meat, compare their ratio of infection between the season, To carry out this study (125) samples of local ovine meat were collected by random sampling from the middle region of Iraq. The samples were divided into two groups steak and mince, then many microbiological tests (culture, & staining, biochemical Tests Api 20E, Vitik 2 and species-specific PCR amplicon for 16S RNA gene) w
... Show MoreThis study examines the species composition, biodiversity, zoogeography, and ecology of freshwater gastropods of 12 springs in Andijan region of Uzbekistan. The study used generally accepted malacological, faunistic, ecological, analytical, and statistical methods. As a result of research in the springs, 14 species of freshwater gastropods belonging to 2 subclasses, 5 families, and 10 genera were recorded. 7 of them are endemic to Central Asia. When indicators of biodiversity of mollusks were analyzed according to the Shannon index, it was found that the highest value was recorded in the springs besides the hills. According to the biotope of distribution and bioecological features, they were divided into cryophilic, phytophilic, pelophil
... Show MoreBackground: Orthodontic tooth movement is characterized by tissue reactions, which consist of an inflammatory response in periodontal ligament and followed by bone remodeling in the periodontium depending on the forces applied. These processes trigger the secretion of various proteins and enzymes into the saliva.The purpose of this study was to evaluate the activity of alkaline phosphatase (ALP) in saliva during orthodontic tooth movement using different magnitude of continuous orthodontic forces. Materials and Methods: Thirty orthodontic patients (12 males and 18 females) aged 17-23 years with class II division I malocclusion all requiring bilateral maxillary first premolar extractions were randomly divided into three groups according to t
... Show More
Mixed convection heat transfer to air inside an enclosure is investigated experimentally. The bottom wall of the enclosure is maintained at higher temperature than that of the top wall which keeps in oscillation motion, whereas the left and right walls are well insulated. The differential temperature of the bottom and top walls changed several times in order to accurately characterize the temperature distribution over a considerable range of Richardson number. Adjustable aspect ratio box was built as a test rig to determine the effects of Richardson number and aspect ratio on the flow behavior of the air inside the enclosure. The flow fields and the average Nusselt number profiles were presented in this wo
... Show MoreWas appointed acid steady disintegration of organic EkandThe results proved that organic Allicand acting and Konnh solid baseBy Tgrav Pearson has possible account Maamat hardness and softness of organic Ekand
The complexes of the 2-hydroxy-4-Nitro phenyl piperonalidene with metal ions Cr(III), Ni(II), Pt(IV) and Zn(II) were prepared in ethanolic solution. These complexes were characterized by spectroscopic methods, conductivity, metal analyses and magnetic moment measurements. The nature of the complexes formed in ethanolic solution was study following the molar ratio method. From the spectral studies, monomer structures proposed for the nickel (II) and Zinc (II) complexes while dimeric structures for the chromium (III) and platinum (IV) were proposed. Octahedral geometry was suggested for all prepared complexes except zinc (II) has tetrahedral geometry, Structural geometries of these compounds were also suggested in gas phase by using
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show More