Myocardial Insulin Resistance

Background: The low available of Glut-4 transporters in sarcolemma of the cardiac cells is what characterizes the myocardial insulin resistance (MIR), which is triggered separately of generalized insulin resistance. Insulin receptors are quite evident in the heart muscle and vessels, and mitochondrial activity performs a significant function in MIR preserving cellular homeostasis by cell reproduction, cells livelihoods, and energy generation. Objective: To evaluate the MIR mechanism and through the signaling pathway design. Methods: PubMed database was employed to search for reviews publications with MIR. The referenced data of the signaling pathway was chosen aggregating references of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A signaling pathway was designed based on MIR research manuscripts, where we show several mechanisms included in the MIR. The KEGG server was employed to exploit the interrelationship protein-protein, and elaborate signaling pathway diagram. The signaling pathway mapping was carried out with PathVisio software. Results: We selected 42 articles from a total of 450 articles in the PubMed database that presented a significant association between the terms "insulin resistance myocardial" AND "signaling pathway". Founded on database-validated research papers, we choose well-founded pathways and we succeeded representative description of these pathways. The reproduction contigs taken from the KEGG database designed the signaling pathway of the bio-molecules that lead to MIR. Thus, the acting among multiple mechanisms releases factors that participate of the development of MIR. Conclusion: The interaction among various mechanisms and molecular interactions are important factors in development of MIR

SARS-CoV-2 / COVID e Diabetes Mellitus Tipo 1: Uma abordagem com imunoinformática

Contact with viruses which have an aminoacid (AA) sequence simile to that of the auto-antigens can lead to autoimmune diseases in genetically susceptible individuals. SARS-CoV-2 has been implied as a possible causer of new-onset type 1 diabetes mellitus (DM1), however, no consistent evidence yet that SARS-CoV-2 take to DM1 on your own initiative. Objective: Evaluate the possible similarity between the AA sequences of human insulin and human glutamic acid decarboxylase-65 (GAD65) with SARS-CoV-2/COVID proteins, to explain the possible trigger of DM1. Methods: AA sequences of the human insulin (4F0N), GAD65 (2OKK), and SARS-CoV-2 (SARS-Cov2 S protein at open state (7DDN), SARS-Cov2 S protein at close state (7DDD), SARS CoV-2 Spike protein (6ZB5), Crystal structure of SARS-CoV-2 nucleocapsid protein N-terminal RNA binding domain (6M3M), Crystal structure of SARS-CoV-2 nucleocapsid protein C-terminal RNA binding domain (7DE1), Crystal Structure of NSP1 from SARS-CoV-2 (7K3N), and SARS-CoV-2 S trimer (7DK3)) available in the Protein Data Bank were compared using the Pairwise Structure Alignment. Results: Sequence identity percentage (SI%) and sequence similarity percentage (SS%) were found among the 4F0N, 2OKK and SARS-CoV-2. The SI% between the 4F0N and SARS-CoV-2 ranged from 4.76% to 14.29% and SS% ranged from 5.00% to 45.45%, distributed like this: 4F0N and 7DDN = SI% 4.76 and SS% 28.57; 4F0N and 7DDD = SI% 14.39 and SS% 23.81; 4F0N and 6ZB5 = SI% 4.76 and SS% 28.57; 4F0N and 6M3M = SI% 5.00 and SS% 5;00; 4F0N and 7DE1 = SI% 4.76 and SS% 9.21; 4F0N and 7K3N = SI% 9.09 and SS% 45.45; 4F0N and 7DK3 = SI% 4.76 and SS% 28.57. The SI% between the between the 2OKK and SARS-CoV-2 ranged from 3.19% to 6,70% and SS% ranged from 10.45 % to 22.22%, distributed like this: 2OKK and 7DDN = SI% 6.70 and SS% 15.64; 2OKK and 7DDD = SI% 7.53 and SS% 18.84; 2OKK and 6ZB5 = SI% 6.68 and SS% 17.38; 2OKK and 6M3M = SI% 4.48 and SS% 10.45; 2OKK and 7DE1 = SI% 6.67 and SS% 22.22; 2OKK and 7K3N = SI% 3.19 and SS% 15.97; 2OKK and 7DK3 = SI% 3.95 and 17.98. Conclusion: Immunoinformatics data suggest a potential pathogenic link between DM1 and SARS-CoV-2/COVID. Thus, by means of molecular mimicking we check that sequences similarity among SARS-CoV-2/COVID and human insulin and human glutamic acid decarboxylase-65 may lead to production of an immune cross-response to self-antigens, with breakage of self-tolerance that can trigger DM1.O contato com vírus que têm uma sequência de aminoácidos (AA) semelhante à dos autoantígenos podem desencadear doenças autoimunes em indivíduos geneticamente suscetíveis. SARS-CoV-2 foi sugerido como um possível causador de diabetes mellitus tipo 1 de início recente (DM1), no entanto, não há evidências consistentes de que o SARS-CoV-2 possa desencadear DM1. Objetivo: Avaliar a possível semelhança entre as sequências AA da insulina humana e da descarboxilase-65 do ácido glutâmico humano (GAD65) com as proteínas SARS-CoV-2 / COVID, para explicar o possível desencadeamento do DM1. Métodos: Sequências de AA da insulina humana (4F0N), GAD65 (2OKK) e SARS-CoV-2 SARS-Cov2 S protein at open state (7DDN), SARS-Cov2 S protein at close state (7DDD), SARS CoV-2 Spike protein (6ZB5), Crystal structure of SARS-CoV-2 nucleocapsid protein N-terminal RNA binding domain (6M3M), Crystal structure of SARS-CoV-2 nucleocapsid protein C-terminal RNA binding domain (7DE1), Crystal Structure of NSP1 from SARS-CoV-2 (7K3N), and SARS-CoV-2 S trimer (7DK3))  disponíveis no Protein Data Bank foram comparadas utilizando o Pairwise Structure Alignment. Resultados: O percentual de identidade de sequências (SI%) e o percentual de similaridade de sequências (SS%) foram encontrados entre o 4F0N, 2OKK e o SARS-CoV-2. O SI% entre o 4F0N e o SARS-CoV-2 variou de 4,76% a 14,29% e o SS% variou de 5,00% a 45,45%, assim distribuídos: 4F0N e 7DDN = SI% 4,76 e SS% 28,57; 4F0N e 7DDD = SI% 14,39 e SS% 23,81; 4F0N e 6ZB5 = SI% 4,76 e SS% 28,57; 4F0N e 6M3M = SI% 5,00 e SS% 5; 00; 4F0N e 7DE1 = SI% 4,76 e SS% 9,21; 4F0N e 7K3N = SI% 9,09 e SS% 45,45; 4F0N e 7DK3 = SI% 4,76 e SS% 28,57. O SI% entre o 2OKK e o SARS-CoV-2 variou de 3,19% a 6,70% e o SS% variou de 10,45% a 22,22%, assim distribuídos: 2OKK e 7DDN = SI% 6,70 e SS% 15,64; 2OKK e 7DDD = SI% 7,53 e SS% 18,84; 2OKK e 6ZB5 = SI% 6,68 e SS% 17,38; 2OKK e 6M3M = SI% 4,48 e SS% 10,45; 2OKK e 7DE1 = SI% 6,67 e SS% 22,22; 2OKK e 7K3N = SI% 3,19 e SS% 15,97; 2OKK e 7DK3 = SI% 3,95 e 17,98. Conclusão: Os dados de imunoinformática sugerem uma potencial ligação patogênica entre SARS-CoV-2 / COVID e o DM1. Assim, por meio de mimetização molecular, verificamos que a similaridade das sequências de AA entre SARS-CoV-2 / COVID e insulina humana e a descarboxilase-65 do ácido glutâmico humano pode levar à produção de uma resposta cruzada imunológica para autoantígenos, com quebra de auto-tolerância, podendo desencadear o DM1

GRADING SCALE OF VISCERAL ADIPOSE TISSUE THICKNESS AND THEIR RELATION TO THE NONALCOHOLIC FATTY LIVER DISEASE

ContextThe mesenteric fat is drained by the portal system, being related to the metabolic syndrome which is an impor­tant risk factor for non-alcoholic fatty liver disease (NAFLD).ObjectivesGraduate of visceral fat thickness and correlate with the NAFLD degree through ultrasonography method.MethodsWe studied 352 subjects for age, gender, measures of subcutaneous fat thickness and visceral fat thickness as well as the presence and degree of liver fatty. Was analyzed the independent relationship between visceral fat thickness and NAFLD, and linear regression analysis was used in order to predict the visceral fat thickness from subcutaneous fat thickness.ResultsThe mean age of 225 women (63.9%) and 127 men (36.1%) was 47.5 ± 14.0 (18-77) years, 255 subjects had normal examinations, 97 had NAFLD thus distributed, 37 grade 1, 32 grade 2, and 28 grade 3. The subcutaneous fat thickness ranged from 0.26 to 3.50 cm with a mean of 1.3 ± 0.6 cm and visceral fat thickness ranged from 0.83 to 8.86 cm with a mean of 3.6 ± 1.7 cm. Linear regression showed that for every increase of 1 cm in subcutaneous fat thickness the visceral fat thickness will increase 0.9 cm.ConclusionsThe visceral fat thickness measured by ultrasonography is a useful and seems to be able to help estimate the risk of NAFLD

3D-Structural Characterization of MicroRNA Expressed in Leprosy : 3D-Structural Characterization of MicroRNA Expressed in Leprosy

Introduction: Hansen's disease, or leprosy is caused by Mycobacterium leprae, is a major public health problem in developing countries, and affecting the skin and peripheral nerves. However, M. leprae can also affect bone tissue, mucous membranes, liver, eyes, and testicles, producing a variety of clinical phenotypes. MicroRNAs (miRNAs) have been expressed in the various clinical forms of leprosy and could potentially be used for its diagnosis. Objective: In silico design of the molecular structure of miRNAs expressed in leprosy. Method: We performed a nucleotide sequence search of 17 miRNAs expressed in leprosy, designing in silico the molecular structure of the following miRNAs: miRNA-26a, miRNA-27a, miRNA-27b, miRNA-29c, miRNA-34c, miRNA-92a-1, miRNA-99a-2, miRNA-101-1, miRNA-101-2, miRNA-125b-1, miRNA-196b, miRNA-425-5p, miRNA-452, miRNA-455, miRNA-502, miRNA-539, and miRNA-660. We extracted the nucleotides were from the GenBank of National Center for Biotechnology Information genetic sequence database. We aligned the extracted sequences with the RNA Folding Form, and the three-dimensional molecular structure design was performed with the RNAComposer. Results: We demonstrate the nucleotide sequences, and molecular structure projection of miRNAs expressed in leprosy, and produces a tutorial on the molecular model of the 17 miRNAs expressed in leprosy through in silico projection processing of their molecular structures. Conclusion: We demonstrate in silico design of selected molecular structures of 17 miRNAs expressed in leprosy through computational biology.Introdução: a doença de Hansen, ou hanseníase é causada pelo Mycobacterium leprae (M. leprae), é um grande problema de saúde pública nos países em desenvolvimento e afeta, a pele e os nervos periféricos. Entretanto, o M. leprae também pode comprometer o tecido ósseo, membranas mucosas, fígado, olhos e testículos, produzindo uma variedade de fenótipos clínicos. MicroRNAs (miRNAs) têm sido expressos nas várias formas clínicas da hanseníase e podem ser potencialmente utilizados para seu diagnóstico. Objetivo: objetivou-se com esse experimento modelar computacionalmente a estrutura molecular dos miRNAs expressos na hanseníase.  Metedologia: realizou-se como metodologia uma pesquisa das sequências nucleotídicas de 17 miRNAs expressos na hanseníase, desenhando em modelo computacional a estrutura molecular dos seguintes miRNAs: miRNA-26a, miRNA-27a, miRNA-27b, miRNA-29c, miRNA-34c, miRNA-92a-1, miRNA-99a-2, miRNA-101-1, miRNA-101-2, miRNA-125b-1, miRNA-196b, miRNA-425-5p, miRNA-452, miRNA-455, miRNA-502, miRNA-539, e miRNA-660. Extraiu-se os nucleotídeos do banco de dados do GenBank of National Center for Biotechnology Information . Alinhou-se as sequências extraídas com o RNA Folding Form, e o projeto da estrutura molecular tridimensional foi realizado com o RNAComposer. Resultados: demonstrou-se como resultados as sequências dos nucleotídeos e a projeção da estrutura molecular dos miRNAs expressos na hanseníase, e produzimos um tutorial sobre o modelo molecular dos 17 miRNAs expressos em hanseníase através do processamento de suas estruturas moleculares em projeção computacional. Conclusão: foi demonstrado computacionalmente o projeto de estruturas moleculares selecionadas de 17 miRNAs expressos em hanseníase através da biologia computacional.