Tissue-Resident Memory T Cells in Allergy.

Tissue-resident memory T (TRM) cells constitute a distinct subset within the memory T cell population, serving as the vanguard against invading pathogens and antigens in peripheral non-lymphoid tissues, including the respiratory tract, intestines, and skin. Notably, TRM cells adapt to the specific microenvironment of each tissue, predominantly maintaining a sessile state with distinctive phenotypic and functional attributes. Their role is to ensure continuous immunological surveillance and protection. Recent findings have highlighted the pivotal contribution of TRM cells to the modulation of adaptive immune responses in allergic disorders such as allergic rhinitis, asthma, and dermatitis. A comprehensive understanding of the involvement of TRM cells in allergic diseases bears profound implications for allergy prevention and treatment. This review comprehensively explores the phenotypic characteristics, developmental mechanisms, and functional roles of TRM cells, focusing on their intricate relationship with allergic diseases.

Comprehensive analysis of mitophagy-related genes in diagnosis and heterogeneous endothelial cells in chronic rhinosinusitis: based on bulk and single-cell RNA sequencing data.

Background: Chronic rhinosinusitis (CRS) is a complex inflammatory disorder affecting the nasal and paranasal sinuses. Mitophagy, the process of selective mitochondrial degradation via autophagy, is crucial for maintaining cellular balance. However, the role of mitophagy in CRS is not well-studied. This research aims to examine the role of mitophagy-related genes (MRGs) in CRS, with a particular focus on the heterogeneity of endothelial cells (ECs). Methods: We employed both bulk and single-cell RNA sequencing data to investigate the role of MRGs in CRS. We compiled a combined database of 92 CRS samples and 35 healthy control samples from the Gene Expression Omnibus (GEO) database and we explored the differential expression of MRGs between them. A logistic regression model was built based on seven key genes identified through Random Forests and Support Vector Machines - Recursive Feature Elimination (SVM-RFE). Consensus cluster analysis was used to categorize CRS patients based on MRG expression patterns and weighted gene co-expression network analysis (WGCNA) was performed to find modules of highly correlated genes of the different clusters. Single-cell RNA sequencing data was utilized to analyze MRGs and EC heterogeneity in CRS. Results: Seven hub genes-SQSTM1, SRC, UBA52, MFN2, UBC, RPS27A, and ATG12-showed differential expression between two groups. A diagnostic model based on hub genes showed excellent prognostic accuracy. A strong positive correlation was found between the seven hub MRGs and resting dendritic cells, while a significant negative correlation was observed with mast cells and CD8+ T cells. CRS could be divided into two subclusters based on MRG expression patterns. WGCNA analysis identified modules of highly correlated genes of these two different subclusters. At the single-cell level, two types of venous ECs with different MRG scores were identified, suggesting their varying roles in CRS pathogenesis, especially in the non-eosinophilic CRS subtype. Conclusion: Our comprehensive study of CRS reveals the significant role of MRGs and underscores the heterogeneity of ECs. We highlighted the importance of Migration Inhibitory Factor (MIF) and TGFb pathways in mediating the effects of mitophagy, particularly the MIF. Overall, our findings enhance the understanding of mitophagy in CRS, providing a foundation for future research and potential therapeutic developments.