Journal of Epigenetics
Volume:3 Issue: 1, Winter 2022

Retinitis pigmentosa (RP) is the most common type of inherited progressive photoreceptor cells degeneration causing night blindness, progressive reduction of visual field, loss of retinal pigment epithelial function, and ultimately tubular vision and blindness. Retinitis pigmentosa is most commonly inherited in three ways: autosomal dominant, autosomal recessive, or X-linked, although mitochondrial inheritance also occurs. Mutations in the RHO gene are the most widely associated reason with Retinitis pigmentosa (20-30%). This study aims to find Retinitis pigmentosa likely pathogenic mutation in order to Whole Exome sequencing and Sanger confirmation.

 The patient is an 8-year-old child who presented to a physician following reduced vision in low light, decreased night vision, decreased peripheral vision, and blurred vision. Considering the symptoms of Retinitis pigmentosa, which were observed mildly in their paternal grandparents and severely in aunts; the patient's DNA was extracted and used for molecular studying and sequencing.

In the present study, we report a novel likely pathogenic mutation c.50C>G/ p.Thr17Arg in one affected child of a consanguineous family, which occurs in the coding region of RHO. The autosomal dominant inheritance pattern was confirmed by Sanger since the father of our proband was heterozygous for the mutation.

Since date, c.50C>G/ p.Thr17Arg likely pathogenic variant has not been observed or reported globally. This mutation disrupts the function of the RHO protein and impairs the translocation of this transmembrane protein, causing symptoms of Retinitis pigmentosa. According to family history and molecular studies, the inheritance of the gene in the family is AD, and these findings will be very significant for subsequent pregnancies in this family.

The main purpose of this study was to work out the relationship between different polymorphisms of PAI (Plasminogen Activator Inhibitor type 1) 4G/5G and XIII Val34Leu genes in women with first-semester recurrent miscarriage (RM) syndrome. Recurrent miscarriage (RM) is an obstetric challenge. Polymorphisms of factor XIII (FXIII)and plasminogen activator inhibitor-1 (PAI-1) may cause an imbalance between coagulation and fibrinolysis that can end in RM.  This case-control study enclosed 48 women with at least two or three abortions and 50 women with at least one pregnancy as a control.  DNA molecule was extracted from peripheral blood samples by the phenol-chloroform methodology. Different variants of the two genes were amplified by Amplification Refractory Mutation System - Polymerase chain reaction (ARMS-PCR) method. Finally, we analyzed allele frequencies and genotypes, Odd Ratios, Chi-square, Fisher's and Students T-test for the data. During this study, it has been found that 50% of the case population have the normal genotype for the PAI-1 (rs1799762) gene, 31.25% had a heterozygous genotype and 18.75% had a mutant homozygote. The frequency of the mutated allele in the patient population compared to the controls have p-values <0.001 and it is statistically significant for this allele (OR = 0.068, p-values <0.001, CI = 0.014-0.322). In contrast, no significant results were observed for the factor XIII (rs5985) gene and this variant was considered in this population as an ineffective polymorphism on recurrent miscarriage syndrome (p-values = 0.238). Finally, it is suggested that other variants of the given gene should be examined in Golestan.

The existence of bacterial proteins was proved in the gut of animals. Many proteins with bacterial origin were reported from the alimentary canal in the invertebrate animals. Insects, as the largest group of animals, have known serious pests in agricultural ecosystems. Feeding and nutrition are the main ways that caused damages to economic crops. Identification of digestive proteins in the gut of insects is the first step in the clearance of biochemical degradation of food particles. Proteomics is a powerful tool to identify effective proteins in the physiological systems in animal and plants. Digestive proteins in the gut of insects have originated from innate cells and microorganisms like bacteria. In this research, for the first time, gut proteins of Nezara viridula were extracted. These proteins were visualized and identified with two-dimensional polyacrylamide gel electrophoresis and mass spectrometry, respectively. Eight proteins with bacteria origins were accumulated in the gut of adults. Identified proteins were phospho pyruvate dehydratase, amino acid –N-acetyl transferase, hypothetical protein, glycerol-3 phosphate dehydrogenases, ribulose-phosphate 3-epimerase, pyruvate kinase, chitinase, and catalase. Results suggest that the interaction of bacteria and lumen of Hemiptera has a high level of efficacy; hence, the nutrition process can be used as a new target for selecting proper inhibitors to use in the integrated pest management.

In recent years, congenital hypothyroidism (CH) has been reported as the most prevalent endocrine disorder and most common cause of preventable mental retardation  in many parts of the world, especially in Asia. Delays in early diagnosis and treatment of CH can lead to growth retardation, as well as neurological and psychological disorders. Many genetic defects along with their molecular mechanisms based on pathophysiology have not been identified in many babies with congenital hypothyroidism. This study aimed to evaluate the expression of GLI3A and LATS2, MOB1A genes in patients with congenital hypothyroidism. In this study, the expression pattern of GLI3A, LATS2, and MOB1A genes after RNA extraction and converted to cDNA from the blood of 20 patients and 20 control samples were examined by the Real-time quantitative PCR (qRT-PCR). The obtained data were analyzed using Spss software and Mann-Whitney statistical method. Statistical analysis of findings has shown significant differences in the expression of GLI3A gene in two groups of patients and control. However, in the study on the expression of two genes LATS2 and MOB1A, there was no significant difference, so it can be assumed that expression of GLI3A gene may play a role in risk of congenital hypothyroidism while changes in expression of LATS2 and MOB1A genes are not involved in this disease. Results of the present study demonstrated that GLI3A gene expression could be a genetic risk factor for congenital hypothyroidism. In the present study, LATS2 and MOB1A gene expression did not show significant risk for susceptibility CH disease.

Breast cancer is the most common cancer among women and is the second leading cause of death. There is currently no efficient way to prevent breast cancer, but its detection in early stages can increase the patient's chances of being cured and surviving. Computer-aided diagnosis (CAD) systems, based on image processing techniques, can provide a more reliable interpretation of mammographic images to detect microcalcifications and have been able to identify and classify benign and malignant tumors. If we are dealing with a massive number of images, this system increases the ability and accuracy of detection. Also, in cases where the number of images is not large, CAD systems can significantly improve the image quality. In addition, a CAD system can identify suspicious areas to provide radiologists with a visual aid to interpret mammograms. Deep learning and convolutional neural networks have recently shown significant performance for visual applications. Convolutional neural networks have also been used efficiently to analyze medical images and diagnose mammograms. In this paper, a CAD system based on convolutional neural networks (Mask R-CNN) with multi-task learning to detect breast cancer and segment mammogram images is proposed. The Mask-RCNN technique is one of the strongest and most flexible deep grids ever designed for machine vision. In this article, multitask learning with the integration of two tasks of classification and segmentation is used to diagnose breast cancer. R-CNN convolution neural network is used to diagnose cancerous mass. This system consists of two main stages, including the production of pseudo-color image and segmentation-detection based on convolutional neural networks (R-CNN Mask). The INbreast dataset is employed for evaluation of the proposed method.