ArticleScientific reports2024
Neutrophil-based single-cell sequencing combined with transcriptome sequencing to explore a prognostic model of sepsis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Dysregulation of Neutrophil-Endothelial Communication in Sepsis: Mechanisms and Therapeutic Perspectives.Cells · 2026Review
- Longitudinal biomarker trajectories and their prognostic utility for 21-day mortality in burn patients with sepsis: a retrospective cohort study.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
- Advances in Single-Cell Sequencing for Infectious Diseases: Progress and Perspectives.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Multi-Dimensional Characterization of Programmed Cell Death Patterns for Prognostic Stratification and Therapeutic Insights in Sepsis.ImmunoTargets and therapy · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Sepsis is a life-threatening condition influenced by various factors. Although gene expression profiling has offered new insights, accurately assessing patient risk and prognosis remains challenging. We utilized single-cell and gene expression data of sepsis patients from public databases. The Seurat package was applied for preprocessing and clustering single-cell data, focusing on neutrophils. Lasso regression identified key genes, and a prognostic model was built. Model performance was evaluated using Receiver Operating Characteristic (ROC) curves, and further analyses, including immune cell infiltration, Gene Set Enrichment Analysis (GSEA), and clinical correlation, were conducted. Several neutrophil subtypes were identified with distinct gene expression profiles. A prognostic model based on these profiles demonstrated strong predictive accuracy. Risk scores were significantly correlated with clinical features, immune responses, and key signalling pathways. This study provides a comprehensive analysis of sepsis at the molecular level. The prognostic model shows promise in predicting patient outcomes, offering potential new strategies for diagnosis and treatment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.