Effects of Aire on perforin expression in BMDCs via TLR7/8 and its therapeutic effect on type 1 diabetes

Repolarizing Tumor-Associated Macrophages and inducing immunogenic cell Death: A targeted liposomal strategy to boost cancer immunotherapy

Cancer immunotherapy has shown promise in treating various malignancies. However, the presence of an immunosuppressive tumor microenvironment (TME) triggered by M2 tumor-associated macrophages (TAMs) and the limited tumor cell antigenicity have hindered its broader application. To address these challenges, we developed DOX/R837@ManL, a liposome loaded with imiquimod (R837) and doxorubicin (DOX), modified with mannose-polyethylene glycol (Man-PEG). DOX/R837@ManL employed a mannose receptor (MRC1)-mediated targeting strategy, allowing it to accumulate selectively at M2 Tumor associated macrophages (TAMs) and tumor sites. R837, an immune adjuvant, promoted the conversion of immunosuppressive M2 TAMs into immunostimulatory M1 TAMs, and reshaped the immunosuppressive TME. Simultaneously, DOX release induced immunogenic cell death (ICD) in tumor cells and enhanced tumor cell antigenicity by promoting dendritic cells (DCs) maturation. Through targeted delivery, the synergistic action of R837 and DOX activated innate immunity and coordinated adaptive immunity, enhancing immunotherapy efficacy. In vivo experiments have demonstrated that DOX/R837@ManL effectively eliminated primary tumors and lung metastases, while also preventing tumor recurrence post-surgery. These findings highlighted the potential of DOX/R837@ManL as a promising strategy for cancer immunotherapy.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.