ArticleEndocrine, metabolic & immune disorders drug targets2026
Single-Cell Profiling Identifies JUNB/SPI1-Driven Inflammatory Programs and Novel Communication Axes in Myeloid Cells of Sepsis
Article in Endocrine, metabolic & immune disorders drug targets, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
2 citing papers in PubMed.
- Serum inflammatory biomarkers can predict clinical outcomes in patients with sepsis-associated gastrointestinal dysfunction.World journal of gastrointestinal surgery · 2026Article
- Advances in the identification of novel cell signatures in benign prostatic hyperplasia and prostate cancer using single-cell RNA sequencing.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSepsis is a Systemic Inflammatory Response (SIR) caused by invading pathogens. We aimed to characterize infiltrating cells in sepsis and provide novel insight for the treatment of sepsis. MATERIALS AND
methodsWhole-blood scRNA-seq samples from four septic patients and five healthy subjects were collected from the Gene Expression Omnibus (GEO) database (GSE175453). The Seurat R package was used for quality control and cell clustering by scRNA- seq analysis. Gene set enrichment analysis (GSEA) was performed using the clusterProfiler R package for pathway enrichment analysis. Then, the SCENIC analysis was used to identify key transcriptional regulons, and the CellChat R package was used for cell communication analysis.
resultsWe mainly obtained 9 cell clusters, including myeloid cells, T cells, dendritic cells, NK T cells, B cells, plasma B cells, megakaryocytes, mast cells and erythrocytes. Notably, myeloid cells, erythrocytes and mast cells had a higher proportion in sepsis patients. Activated IL-17 and p53 pathways supported anti-infection response in myeloid cells, and JUNB and SPI1 mediated multiple inflammatory pathways, including TNF signaling and neutrophil activation. We also identified that the cell interaction mode of myeloid cells, such as MPZL1-MPZL1 and FASL-FAS, may serve as a potential target for an anti-inflammatory response in sepsis treatment. DISCUSSIONS: The scRNA-seq analysis revealed pro-inflammatory pathways (IL-17, p53) and key regulators (JUNB, SPI1) in septic myeloid cells. Receptor genes (MPZL1 and FAS) mediated cell communication, offering potential biomarkers and targets for sepsis therapy.
conclusionWe characterized the pro-inflammatory immune response pathways, transcriptional regulon and cell interaction modes of myeloid cells in the development of sepsis.
Indexed as
Identifiers
What Socratic holds
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.