ArticleFrontiers in public health2022
Bulk RNA Sequencing With Integrated Single-Cell RNA Sequencing Identifies BCL2A1 as a Potential Diagnostic and Prognostic Biomarker for Sepsis.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Construction of Diagnostic Model for Regulatory T Cell-Related Genes in Sepsis Based on Machine Learning.Biomedicines · 2025Article
- Single-Cell Landscape of Bronchoalveolar Lavage Fluid Identifies Specific Neutrophils during Septic Immunosuppression.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Development of a Starvation Response-Based Model and Its Application in Prognostic Assessment of Liver Hepatocellular Carcinoma.Mediators of inflammation · 2025Article
- Multi-omics analysis reveals that low cathepsin S expression aggravates sepsis progression and worse prognosis via inducing monocyte polarization.Frontiers in cellular and infection microbiology · 2025Article
- Single-cell analysis reveals the loss of FABP4-positive proliferating valvular endothelial cells relates to functional mitral regurgitation.BMC medicine · 2024Article
- Acetylation of TIR domains in the TLR4-Mal-MyD88 complex regulates immune responses in sepsis.The EMBO journal · 2024Article
- Contribution of A1 to macrophage survival in cooperation with MCL-1 and BCL-XCell death & disease · 2024Article
- ADAR1 Inhibits Macrophage Apoptosis and Alleviates Sepsis-induced Liver Injury Through miR-122/BCL2A1 Signaling.Journal of clinical and translational hepatology · 2024Article
- Correlation between the gut microbiota characteristics of hosts with severe acute pancreatitis and secondary intra-abdominal infection.Frontiers in medicine · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Sepsis is one of the leading causes of morbidity and mortality worldwide in the intensive care unit (ICU). The prognosis of the disease strongly depends on rapid diagnosis and appropriate treatment. Thus, some new and accurate sepsis-related biomarkers are pressing needed and their efficiency should be carefully demonstrated. Methods: Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were applied to detect sepsis and monocyte/macrophage-related genes. Least absolute shrinkage and selection operator (LASSO) and random forest regression analyses were used in combination to screen out prognostic genes. Single-cell RNA sequence profiling was utilized to further verify the expression of these genes on a single cell level. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were also applied to verify the diagnostic value of the target biomarkers. Results: The intersections of the genes detected by differential expression and WGCNA analyses identified 141 overlapping candidate genes that were closely related to sepsis and macrophages. The LASSO and random forest regression analyses further screened out 17 prognostic genes. Single-cell RNA sequencing analysis detected that Conclusions: It was revealed that
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