Correlation between polymorphisms of gene and renal injury in patients with type 2 diabetes mellitus.

Objectives: Genetic factors play an important role in the pathogenesis of diabetic kidney disease (DKD). Studies have shown that gene polymorphism is associated with the pathogenesis of type 2 diabetes mellitus (T2DM), but its role in DKD remains unclear. This study aims to analyze the distribution of alleles and genotypes of gene in patients with T2DM, and investigate the association between genetic polymorphism and DKD susceptibility in T2DM patients, which may provide new ideas for the pathogenesis of DKD.

Prevalence and associated factors of MAFLD in adults with type 2 diabetes.

To estimate the prevalence and associated factors of hepatic steatosis and fibrosis in adults with type 2 diabetes (T2DM) in the United States.Data were retrieved from the 2017‒March 2020 prepandemic cycle of the National Health and Nutritional Examination and Survey (NHANES). The study population included patients with T2DM.

The Current Progress in the Quest for Vaccines Against the Semliki Forest Virus Complex.

The Semliki Forest virus (SFV) complex comprises of arboviruses that are transmitted by arthropod vectors and cause acute febrile illness in humans. In the last seven decades, re-emergence of these viruses has resulted in numerous outbreaks globally, affecting regions including Africa, Americas, Asia, Europe and the Caribbean. These viruses are transmitted to humans by the bite of infected mosquitoes.

Development of a prognostic gene signature and exploration of P4HA1 in the modulation of cuproptosis in colorectal cancer.

Cuproptosis, a newly identified form of cell death, has drawn increasing attention for its association with various cancers, though its specific role in colorectal cancer (CRC) remains unclear. In this study, transcriptomic and clinical data from CRC patients available in the TCGA database were analyzed to investigate the impact of cuproptosis. Differentially expressed genes linked to cuproptosis were identified using Weighted Gene Co-Expression Network Analysis (WGCNA).