Evidence map›Paper›PMID 42215988›Full record

ArticleBiology direct2026

Single-cell transcriptomic analysis deciphers heterogeneity and transcriptional regulatory programs of sepsis with different prognosis.

Yuanming Yang, Yiwei Hua, Suyi Yang, Nan Liu, Jun Li

Abstract read
In one paragraph

Article in Biology direct, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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

5 authors.

Yuanming YangThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China. 20212120217@stu.gzucm.edu.cn.
Yiwei HuaSchool of Food and Health, Guangzhou City Polytechnic, Guangzhou, 511370, China.
Suyi YangThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China.
Nan LiuThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China.
Jun LiThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China. lijun@gzucm.edu.cn.

Funding

2024 Scientific Research and Development Cultivation Project of Guangdong Provincial Laboratory of Traditional Chinese Medicine HQL2024PZ004National Interdisciplinary Innovation Team for Traditional Chinese Medicine ZYYCXTD-D202406National Natural Science Foundation of China 82474409
6 · The paper itself

Abstract

Sepsis has a high mortality rate, yet the cellular heterogeneity and transcriptional regulatory programs associated with divergent clinical outcomes remain incompletely understood. Here, we integrated two peripheral blood single-cell RNA-seq cohorts to explore prognosis-associated immune remodeling patterns in sepsis. Using reference-based annotation, pySCENIC-inferred regulon activity, pathway enrichment, and CellChat based ligand-receptor inference, we observed broad differences in cell composition, transcriptional programs, and intercellular communication between survivors and non-survivors. Non-survivors exhibited relative decrease of monocytes, B-cells, NK cells, and CD4/CD8 T cells, together with relative platelet expansion. cDC2 and plasmablasts showed relatively large transcriptional disturbance compared to other cell types. In cDC2, poor outcome was associated with increased TNF-α and NF-κB related regulon activity, which linked to AP-1 transcription factors (JUN, FOSL2, CEBPB, NFIL3, KLF6, and FOSB), together with reduced STAT1 and STAT2-associated interferon signaling. Gene regulatory network analysis highlighted cell type-specific transcription factor and target gene relationships. CellChat suggested that cDC2 may occupy a more connected position in survivors, whereas connectivity appeared reduced in non-survivors. Independent bulk transcriptomic validation supported increased FOSL2 and CEBPB expression, and a multivariable eight-transcription-factor model showed preliminary discriminatory performance. Overall, this study suggests that poor-outcome sepsis may be associated with altered cDC2 regulatory states and reduced cDC2 centered intercellular coordination.

Indexed as

Gene Expression RegulationGene Regulatory NetworksSepsisTranscriptomeGene Expression ProfilingHumansPrognosisSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisGene regulatory networksHeterogeneityPrognosisscRNA-seqSepsisTranscription factor

Identifiers

PMID42215988
PMCPMC13435497

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Registered trials

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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 OpenQuestion graph.