Plasma and Urine Levels of Glycosaminoglycans in Patients with Systemic Sclerosis and Their Relationship to Selected Interleukins and Marker of Early Kidney Injury

Screening core genes for minimal change disease based on bioinformatics and machine learning approaches

Based on bioinformatics and machine learning methods, we conducted a study to screen the core genes of minimal change disease (MCD) and further explore its pathogenesis. First, we obtained the chip data sets GSE108113 and GSE200828 from the Gene Expression Comprehensive Database (GEO), which contained MCD information. We then used R software to analyze the gene chip data and performed functional enrichment analysis. Subsequently, we employed Cytoscape to screen the core genes and utilized machine learning algorithms (random forest and LASSO regression) to accurately identify them. To validate and analyze the core genes, we conducted immunohistochemistry (IHC) and gene set enrichment analysis (GSEA). Our results revealed a total of 394 highly expressed differential genes. Enrichment analysis indicated that these genes are primarily involved in T cell differentiation and p13k-akt signaling pathway of immune response. We identified NOTCH1, TP53, GATA3, and TGF-β1 as the core genes. IHC staining demonstrated significant differences in the expression of these four core genes between the normal group and the MCD group. Furthermore, GSEA suggested that their up-regulation may be closely associated with the pathological changes in MCD kidneys, particularly in the glycosaminoglycans signaling pathway. In conclusion, our study highlights NOTCH1, TP53, GATA3, and TGF-β1 as the core genes in MCD and emphasizes the close relationship between glycosaminoglycans and pathogenesis of MCD.

Glycosaminoglycans: Participants in Microvascular Coagulation of Sepsis

Sepsis represents a syndromic response to infection and frequently acts as a common pathway leading to fatality in the context of various infectious diseases globally. The pathology of severe sepsis is marked by an excess of inflammation and activated coagulation. A substantial contributor to mortality in sepsis patients is widespread microvascular thrombosis-induced organ dysfunction. Multiple lines of evidence support the notion that sepsis induces endothelial damage, leading to the release of glycosaminoglycans, potentially causing microvascular dysfunction. This review aims to initially elucidate the relationship among endothelial damage, excessive inflammation, and thrombosis in sepsis. Following this, we present a summary of the involvement of glycosaminoglycans in coagulation, elucidating interactions among glycosaminoglycans, platelets, and inflammatory cells. In this section, we also introduce a reasoned generalization of potential signal pathways wherein glycosaminoglycans play a role in clotting. Finally, we discuss current methods for detecting microvascular conditions in sepsis patients from the perspective of glycosaminoglycans. In conclusion, it is imperative to pay closer attention to the role of glycosaminoglycans in the mechanism of microvascular thrombosis in sepsis. Dynamically assessing glycosaminoglycan levels in patients may aid in predicting microvascular conditions, enabling the monitoring of disease progression, adjustment of clinical treatment schemes, and mitigation of both acute and long-term adverse outcomes associated with sepsis.