Evidence map›Paper›PMID 41114487›Full record

ArticleEndocrine, metabolic & immune disorders drug targets2026

Single-Cell Profiling Identifies JUNB/SPI1-Driven Inflammatory Programs and Novel Communication Axes in Myeloid Cells of Sepsis

Liyao Liu, Lin Zhao, Jixiang Tan

Abstract read
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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.

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2citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Liyao LiuDepartment of Emergency, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, Chinaa.
Lin ZhaoDepartment of Emergency, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Jixiang TanDepartment of Emergency, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Cell CommunicationInflammation MediatorsMyeloid CellsSepsisSingle-Cell AnalysisTranscription FactorsFemaleGene Expression ProfilingHumansInflammationMaleMiddle AgedInflammation MediatorsTranscription Factorscell communication.GSEAinflammationmyeloid cellsSepsissingle cell RNA-seq

Identifiers

PMID41114487
PMCPMC13523166

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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.