miRNAs regulate protein abundance and control diverse aspects of cellular processes and biological functions in metabolic diseases, such as obesity and diabetes. Lethal-7(Let-7) miRNAs specifically target genes associated with diabetes and have a role in the regulation of peripheral glucose metabolism. The present study aimed to describe the gene expressions of the let-7a gene with the development of diabetes in Iraq and the difference in the expression of this gene in patients with diabetes and healthy individuals. The association between age and gender with the development of diabetes was studied in this study and the results were compared with those of healthy individuals in the group of control. Based on the obtained results, there was a lack in the mean of gene expression level (ΔCt) in patients, compared to controls. Moreover, the gene expression folding (2-ΔΔCt) of the let-7a reflects significant differences in terms of gene expression between groups of patients and controls, and the level of let-7a expression was reported to be 12.97 in patients with diabetes. On the other hand, significant difference was observed in terms of age and gender between diabetic patients and controls. The findings suggest that diabetes can affect individuals in all age groups and occur regardless of gender in both males and females. Based on the obtained results in this study, the gene expression level of miRNA let-7a was lower in diabetic patients compared to healthy individuals in the group of control. This also reflects differences in the gene expression fold (2-ΔΔCt) of gene let-7a between both groups of patients and controls. Keywords: Gene expression, Diabetes, Micrornalet-7a
This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr
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Background: Recent studies suggest that chronic periodontitis (CP) and type2 diabetes mellitus (T2DM) are bidirectionally associated. Analysis of saliva as a mirror of oral and systemic health could allow identification of α amylase (α-Am) and albumin (A1) antioxidant system markers to assist in the diagnosis and monitoring of both diseases. The present study aims at comparing the clinical periodontal parameters in chronic periodontitis patients with poorly or well controlled Type 2Diabetes Mellitus, salivary α-Am, A1, flow rate (FR) and pH then correlate between biochemical, physical and clinical periodontal parameters of each study and control groups. Materials and Methods: 80 males, with an age range of (35-50) years were divide
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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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For the period from February 2014 till May 2014, one hundred and nine lactose fermenter clinical isolates from different samples (urine, stool, wound swab, blood, and sputum) were collected from Alyarmok, Alkadimiya, and Baghdad teaching hospitals at Baghdad governorate. Identification of all Klebsiella pneumoniae isolates were carried out depending on macroscopic, microscopic characterizations, conventional biochemical tests, and Api 20E system. Fifty-three (48.62%) isolates represented K. pneumoniae; however, 51.73% represented other bacteria. Susceptibility test was achieved to all fifty-three K. pneumoniae isolates using five antibiotic disks (Ceftazidime, Ceftriaxone, Cefotaxime, Imipenem, and Meropenem). Most of tested isolates (90
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The study was conducted at the ruminant research station of the general commission for agricultural research/Ministry of Agriculture, as well as the laboratory of genetic resources of the department of livestock/Ministry of Agriculture and the laboratory of the college of agriculture engineering science, with the aim of determine the genotypic of the expression region (intron 2 and part of exon 3) of the LHX3 gene And its relationship to the fertility rate in local and Shami goats. For this purpose, the RFLP technique was used, and the percentages of genotypes for the LHX3 gene in the local goat sample were 29.17, 50.00, 20.83 for the TT, AT, and AA genotypes, respectively, while in the Shami goa
... Show MoreBackground: Oral lichen planus (OLP) is a chronic immunologic disease. The etiology of OLP is unknown, viral antigens (for example EBV) have been proposed as etiologic agents. OLP may get transformation to malignancy so research on the presence of these in OLP lesions seems to be necessary. The aim of this study was to evaluate EBV expression immunohistochemically in OLP. Materials and Methods: Tissue specimens of 30 formalin fixed, paraffin-embedded tissue Blocks histologically diagnosed oral lichen planus was performed to evaluate EBV expression. Results: Expression of EBV was detected in epithelium of (46.6%) in the study samples in (OLP). no statistically significant correlation was found with clinical parameters except for a significan
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Trigeminal Neuralgia (TN) is one of the most commonly painful cranial neuralgia characterized by paroxysmal attacks as short lasting facial pain along the trigeminal nerve branches. The aim of the present study is to innovate a biochemical relationship between (melatonin, GALNT12 and Zn) and TN and also to examine the biochemical action of tegretol (carbamazepine) as a treatment on the above biochemical parameters. Blood samples were collected from fifty four (54) trigeminal neuralgia patients diagnosed by magnetic radiation image (MRI). Patients were classified into four groups: G3 (40- 70) years composed of (12) diagnosed male (without treatment), G4 (48- 75) years composed of (12) diagnosed female (without treatment), G5 (34- 76)
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