Evidence map›Paper›PMID 36405762›Full record

ArticleFrontiers in immunology2022

Integrating bulk and single-cell sequencing reveals the phenotype-associated cell subpopulations in sepsis-induced acute lung injury.

Fuquan Wang, Ming Chen, Jiamin Ma, Chenchen Wang, Jingxu Wang, Haifa Xia, Dingyu Zhang, Shanglong Yao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
5.3field-weighted citation impact, top 3% of its field
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

30 citing papers in PubMed, 36 citations in OpenAlex.

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  19. Review
  20. Decoding IL-1 receptor 1 and 2 expression profiles across organs in sepsis.Frontiers in cell and developmental biology · 2025
    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

8 authors at 2 institutions in 1 country.

Fuquan WangDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ming ChenDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jiamin MaDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chenchen WangDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jingxu WangDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Haifa XiaDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Dingyu ZhangDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Shanglong YaoDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Huazhong University of Science and Technology · CNUnion Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dysfunctional immune response and multiple organ injury in sepsis is a recurrent theme impacting prognosis and mortality, while the lung is the first organ invaded by sepsis. To systematically elucidate the transcriptomic changes in the main constituent cells of sepsis-injured lung tissue, we applied single-cell RNA sequencing to the lung tissue samples from septic and control mice and created a comprehensive cellular landscape with 25044 cells, including 11317 immune and 13727 non-immune cells. Sepsis alters the composition of all cellular compartments, particularly neutrophils, monocytes, T cells, endothelial, and fibroblasts populations. Our study firstly provides a single-cell view of cellular changes in septic lung injury. Furthermore, by integrating bulk sequencing data and single-cell data with the Scissors-method, we identified the cell subpopulations that are most associated with septic lung injury phenotype. The phenotypic-related cell subpopulations identified by Scissors-method were consistent with the cell subpopulations with significant composition changes. The function analysis of the differentially expressed genes (DEGs) and the cell-cell interaction analysis further reveal the important role of these phenotype-related subpopulations in septic lung injury. Our research provides a rich resource for understanding cellular changes and provides insights into the contributions of specific cell types to the biological processes that take place during sepsis-induced lung injury.

Indexed as

Acute Lung InjurySepsisAnimalsLungMiceNeutrophilsPhenotypecellular landscapelung injuryScissors-methodsepsissingle-cell sequencing

Identifiers

PMID36405762
PMCPMC9666384
OpenAlexW4307991362

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.