Evidence map›Paper›PMID 40641871›Full record

ReviewFrontiers in microbiology2025

Multi-omics decodes host-specific and environmental microbiome interactions in sepsis.

Jiamin Lu, Wen Zhang, Yuzhou He, Mei Jiang, Zhankui Liu, Jirong Zhang, Lanzhi Zheng, Bingzhi Zhou, Jielian Luo, Chenming He and 5 more

Abstract readReview
In one paragraph

Review in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  6. Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
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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

15 authors.

Jiamin Lu *Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Wen Zhang *Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yuzhou He *The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Mei JiangTianjin University of Traditional Chinese Medicine, Tianjin, China.
Zhankui LiuInstitute of Acute and Critical Care, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Jirong ZhangLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Lanzhi ZhengThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Bingzhi ZhouThe Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Jielian LuoLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Chenming HeLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yunan ShanSchool of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Wuhan, China.
Runze ZhangLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
KaiLiang FanThe Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
Bangjiang FangLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Chuanqi WanLonghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, and its pathogenesis involves complex interactions between the host and the microbiome. The integration of multi-omics has important value in revealing the mechanism of host-microbiome interaction. It is a key tool for promoting accurate diagnosis and guiding dynamic treatment strategies in sepsis. However, multi-omics data integration faces technical challenges, such as data heterogeneity and platform variability, as well as analytical hurdles, such as the "curse of dimensionality." Fortunately, researchers have developed two integration strategies: data-driven and knowledge-guided approaches, which employ various dimensionality reduction techniques and integration methods to handle multi-omics datasets. This review discusses the applications of multi-omics technologies in host-microbiome interactions in sepsis, highlighting their potential in identifying novel diagnostic biomarkers and developing personalized and dynamic treatment strategies. It also summarizes commonly used systems biology resources and computational tools for data integration; the review outlines the challenges in this field and proposes potential directions for future studies.

Indexed as

bioinformatics toolscomparative genome analysismicrobiomemulti-omicssepsis

Identifiers

PMID40641871
PMCPMC12241168

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.