Evidence map›Paper›PMID 39843498›Full record

ArticleScientific reports2025

Identification of prognostic biomarkers of sepsis and construction of ceRNA regulatory networks.

Guihong Chen, Wen Zhang, Chenglin Wang, Muhu Chen, Yingchun Hu, Zheng Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. Article
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

6 authors.

Guihong ChenDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Wen ZhangDepartment of Endocrinology and Metabolism, The Traditional Chinese Medicine Hospital of Luzhou City, Luzhou, Sichuan, China.
Chenglin WangDepartment of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Muhu ChenDepartment of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Yingchun HuDepartment of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Zheng WangDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China. zheng.wang11@mail.xjtu.edu.cn.

Funding

the Southwest Medical University [2018] 6 (2017-ZRQN-009)
6 · The paper itself

Abstract

Sepsis is a life-threatening severe organ dysfunction, and the pathogenesis remains uncertain. Increasing evidence suggests that circRNAs, mRNAs, and microRNAs can interact to jointly regulate the development of sepsis. Identifying the interaction between ceRNA regulatory networks and sepsis may contribute to our deeper understanding of the pathogenesis of sepsis, bring new insights into early recognition and treatment of sepsis. Blood samples from sepsis patients in the Affiliated Hospital of Southwest Medical University were collected. RNA sequencing (mRNA/circRNA) was performed on Survivor group (n = 26) and Non-survivor group (n = 6), then quality control and differential expression analysis were performed. Subsequently, GO analysis was performed on the differential expression genes; Meta-analysis was used to screen for prognostic related genes; 10 × Single-cell RNA sequencing was used to annotate the cell distribution of core genes. Finally, combined with base complementary pairing and intergroup correlation analysis, a sepsis-associated circRNA-miRNA-mRNA regulatory network was constructed. Differential expression analysis screened 28 mRNAs and 16 circRNAs. GO results showed that differential expression genes were mainly involved in membrane raft, actin cytoskeleton, regulation of immune response, negative regulation of cAMP-dependent protein kinase activity, etc. Meta-analysis screened 2 core genes, GSPT1 and NPRL3, which are associated with sepsis prognosis. 10 × Single-cell RNA sequencing showed that GSPT1 and NPRL3 were widely localized in immune cells, mainly macrophages and T cells. A ceRNA network consisting of 4 circRNA, 26 miRNA, and 2 mRNA was constructed. GSPT1 and NPRL3 were lowly expressed in the sepsis Survivor group, compared with Non-survivor group, which may become novel prognostic biomarkers for sepsis. A sepsis-related ceRNA networks, which consists of 4 circRNA, 26 miRNA, and 2 core gene, may guide mechanistic studies.

Indexed as

BiomarkersGene Regulatory NetworksRNA, CircularSepsisAgedFemaleGene Expression ProfilingGene Expression RegulationHumansMaleMicroRNAsMiddle AgedPrognosisRNA, Competitive EndogenousRNA, MessengerBiomarkersMicroRNAsRNA, CircularRNA, Competitive EndogenousRNA, Messenger

Identifiers

PMID39843498
PMCPMC11754875

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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.