Macrophage-Related Gene Signatures for Predicting Prognosis and Immunotherapy of Lung Adenocarcinoma by Machine Learning and Bioinformatics.

Background: In recent years, the immunotherapy of lung adenocarcinoma has developed rapidly, but the good therapeutic effect only exists in some patients, and most of the current predictors cannot predict it very well. Tumor-infiltrating macrophages have been reported to play a crucial role in lung adenocarcinoma (LUAD). Thus, we want to build novel molecular markers based on macrophages.

Identifying the critical oncogenic mechanism of LDHA based on a prognostic model of T-cell synthetic drivers.

Background: Despite its early success, immunotherapy focused on removing T-cell inhibition does not achieve the desired effect in most patients. New strategies that target antigen-driven T-cell activation are needed to improve immunotherapy outcomes. However, a comprehensive analysis of synthetic drivers of T-cells is greatly lacking in lung adenocarcinoma (LUAD) and other types of tumors.

Exploring the role and mechanism of gut microbiota in methamphetamine addiction using antibiotic treatment followed by fecal microbiota transplantation.

Recently, the role of the gut microbiota in the context of drug addiction has attracted the attention of researchers; however, the specific effects and underlying mechanisms require further exploration. To accomplish this, C57BL/6 mice were firstly treated with methamphetamine (MA). Conditioned place preference (CPP) behavior changes, gut permeability and function, microglial activation, and inflammatory cytokine expression were systematically analyzed in antibiotics-treated mice with microbiota depletion and in fecal microbiota transplantation mice with microbiota reconstitution.