ABSTRACT Background: Nonalcoholic fatty pancreatic disease (NAFPD) is an increase of fat in the pancreas, and has an important association with insulin resistance (IR) and type 2 diabetes mellitus. Research has confirmed that the triglyceridemia/glycemia (TyG) index determines IR as much as does the hyperinsulinemic-euglycemic clamp assessment as the homeostasis model testing of IR (HOMA-IR). Objective: To evaluate the association between degree of NAFPD and TyG index. Methods: In 72 patients undergoing ultrasound of abdomen with a diagnosis of NAFPD, insulin, glucose, and triglycerides levels were evaluated. The HOMA-IR and TyG indexes were used as a reference for IR. The degrees of NAFPD and the TyG index were presented through the receiver operating characteristics (ROC) curves in order to evaluate the association between different degrees of NAFPD, and the correlation of NAFPD with HOMA-IR was also evaluated. Results: There was a statistically significant correlation between the degree of NAFPD and the TyG index. The AUROC curve for the TyG index for predicting the degree of NADPD was 0.855 (0.840-0.865). The intensity-adjusted probabilities of the degree of NAFPD were more strongly associated with TyG values when compared with HOMA-IR. Conclusion: In this study the TyG index correlated positively with the degree of NAFPD, performing better than HOMA-IR.

RESUMO Contexto: A doença pancreática gordurosa não alcoólica (DPGNA) é um aumento de gordura pancreática, e tem uma importante associação com a resistência à insulina (RI) e com diabetes mellitus tipo 2. Pesquisas confirmaram que o índice triglicérides/glicemia (TyG) determina a RI tanto quanto a avaliação da clamp hiperinsulinêmico-euglicêmico como o teste do modelo de homeostasia da RI (HOMA-IR). Objetivo: Avaliar a associação entre o grau de DPGNA e o índice TyG. Métodos: Em 72 pacientes submetidos a ultrassonografia do abdome com diagnóstico de DPGNA, foram avaliados os níveis de insulina, glicose e triglicérides. Os índices HOMA-IR e TyG foram usados como referência para RI. Os graus de DGPNA e o índice TyG foram apresentados através da curva ROC com o objetivo de avaliar a associação entre diferentes graus de DPGNA, e a correlação do DGPNA com o HOMA-IR também foi avaliada. Resultados: Houve uma correlação estatisticamente significativa entre o grau de DPGNA e o índice TyG. A curva AUROC para o índice TyG para prever o grau do NADPD foi 0,855 (0,840-0,865). As probabilidades ajustadas de intensidade do grau de NAFPD foram mais fortemente associadas aos valores de TyG quando comparadas com o HOMA-IR. Conclusão: Neste estudo, o índice TyG correlacionou-se positivamente com o grau de DPGNA, tendo um desempenho melhor que o índice HOMA-IR.

Bile acids (BAs) are steroid molecules that have a hydrophilic and a hydrophobic end, and are synthesized exclusively in the liver, being end product of cholesterol catabolism. Type 2 diabetes mellitus (DM2) is a chronic degenerative disease, with a pathophysiology characterized by insulin resistance (IR), insulin deficiency due to insufficient production of pancreatic ß-cells, and elevated serum glucose levels leading to multiple complications. BAs are related to several metabolic alterations, including metabolic syndrome and DM2. It is currently known that BAs act as a ligand for the nuclear farnesoid X receptor, a receptor with an important role in glucose metabolism, lipids and cellular energy production, as well as in the regulation of production, elimination and mobilization of BAs. BAs have also been reported to act as a signaling pathway through of Takeda G protein-coupled receptor 5. In this manuscript, we describe the interface between BAs and metabolic disorders, in particular DM2, including discussing possibilities in the development of therapeutic procedures targeting BAs as an optional pathway in the treatment of DM2.

ABSTRACT Objective: To define the mathematical relationship between fructosamine levels and average glucose values. Subjects and methods: The study comprised laboratory data of 1,227 patients with type 1 or 2 diabetes mellitus. Fructosamine levels measured at the end of a 3-week period were compared against the average blood glucose levels of the previous 3 weeks. Average glucose levels were determined by the weighted average of the daily fasting capillary glucose results performed during the study period, and the plasma glucose measured in the same sample collected for fructosamine measurement. Results: In total, 9,450 glucose measurements were performed. Linear regression analysis between fructosamine levels and average glucose levels showed that for each 1.0 µmol/L increase in fructosamine level there was a 0.5 mg/dL increase in average glucose level, as estimated by the equation Mean glucose level = (0.5157 x Fructosamine) – 20. The coefficient of determination (r2 = 0.353492, p < 0.006881) allowed the calculation of the estimated average glucose based on fructosamine level. Conclusion: Our study demonstrated a linear correlation between fructosamine level and mean blood glucose level, suggesting that fructosamine levels can be a proxy for the average glucose level in assessing the metabolic control of patients with diabetes.

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)) nbsp;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.