Sepsis-associated acute respiratory distress syndrome (SA-ARDS) is a severe disease with high morbidity and mortality. Emerging evidence indicates that ferroptosis plays a critical role in the development of SA-ARDS. However, the key regulatory targets and underlying molecular mechanisms remain to be further elucidated. Weighted gene co-expression network analysis (WGCNA) was performed based on the GSE66890 dataset to identify SA-ARDS-related gene modules. Candidate genes were screened by intersecting WGCNA module genes with ARDS-related targets from the GeneCards database and ferroptosis-related genes from FerrDb. An in vitro SA-ARDS model was established in HuLEC-5a cells using lipopolysaccharide (LPS). Cell viability, inflammatory cytokine levels, apoptosis, and ferroptosis-related parameters, including ROS, MDA, 4-HNE, and Fe2+ levels, were evaluated using MTT, ELISA, flow cytometry, and corresponding assay kits. The mRNA and protein expression levels were determined by RT-qPCR and Western blot. The transcriptional regulation of topoisomerase II alpha (TOP2A) by GATA binding protein 2 (GATA2) was verified using JASPAR prediction, chromatin immunoprecipitation (ChIP), and dual-luciferase reporter assays. All cellular experiments were performed using three independent biological replicates. WGCNA identified the salmon and cyan modules as significantly associated with SA-ARDS. Intersection analysis identified TOP2A as a key ferroptosis-related gene in SA-ARDS. TOP2A was significantly upregulated in LPS-induced HuLEC-5a cells. Knockdown of TOP2A markedly alleviated LPS-induced cellular injury, as evidenced by enhanced cell viability, reduced levels of inflammatory cytokines (IL-6, IL-8, TNF-α), decreased apoptosis rate, and lowered ROS and Fe2+ accumulation, reduced MDA and 4-HNE levels, restored GPX4 and SLC7A11 expression, and decreased ACSL4 expression, along with increased expression of endothelial barrier-related proteins. GATA2 directly bound to the TOP2A promoter and activated its transcription. TOP2A overexpression reversed the protective effects of GATA2 knockdown in LPS-induced HuLEC-5a cells. GATA2 transcriptionally activated TOP2A expression, which in turn promoted ferroptosis and exacerbated LPS-induced HuLEC-5a cell injury.
Background:In sepsis-induced immune dysregulation, monocytes contribute critically through their dual pro-inflammatory and immunosuppressive functions. Leading to multi-organ injury, the lungs are the most vulnerable initial target, dictating clinical outcomes. Thus, studying monocyte dynamics is essential to understand sepsis-induced acute lung injury (ALI) pathophysiology. Methods:We analyzed publicly available mouse-derived single-cell RNA sequencing (scRNA-seq) and spatial transcriptomic (ST) datasets for sepsis-induced ALI from the GEO database. Computational characterization of monocyte heterogeneity included cell-cell communication, single-cell trajectory analysis, and functional enrichment analyses to identify subtype-specific signaling and injury-related signatures. Spatial mapping further confirmed monocyte subtype localization. Experimental validation was performed in a mouse model of sepsis-induced ALI established by intraperitoneal LPS injection. Histological evaluation, immunohistochemistry, immunofluorescence, Quantitative real-time PCR, and Western blot were integrated to verify the spatial distribution of the Mono-S100A4 subset and its associated pathway molecules. Results:Clustering analysis revealed a restructured immune landscape in septic ALI, characterized by both cellular heterogeneity and prominent monocyte accumulation. Spatial transcriptomics revealed that inflammatory infiltration mediated by monocytes and other immune cells predominantly localized to bronchial and bronchiole regions. Monocyte heterogeneity analysis identified a distinct Mono-S100A4 subset, which exhibited enhanced intercellular communication capacity, influencing other subclusters through the (MIF)-(CD74+CD44) axis. KEGG and GSEA analyses of Mono-S100A4 revealed significant enrichment in the IL-17 signaling pathway and Th17 cell differentiation, suggesting a potential role in exacerbating inflammatory responses. In vivo experiments revealed a significant upregulation in both the mRNA and protein expression levels of S100A4, IL-17A, MIF, and CD74 in the lung tissue of ALI mice. Conclusion:The Mono-S100A4 subset is strongly associated with the activation of the Th17 signaling pathway via the MIF-(CD74+CD44) axis, and this correlative relationship supports a potential pathogenic role of Mono-S100A4 in sepsis-induced ALI, which forms a key hypothesis to be validated by subsequent functional experiments.
We, the publisher, are issuing an expression of concern about Binbin Han et al. (2024) Optimising Deep Neural Networks for Tumour Diagnosis Algorithms Based on Improved MRFO Algorithm. https://doi.org/10.4108/eetpht.10.5147 There is a concern over the integrity of the peer review review process and suspected manipulation of the editorial process. The investigation is ongoing and we advise scholars to exercise caution when referencing this manuscript.
