Evidence map›Paper›PMID 37122356›Full record

ArticleJHEP reports : innovation in hepatology2023

Time-resolved single-cell transcriptomics reveals the landscape and dynamics of hepatic cells in sepsis-induced acute liver dysfunction.

Gan Chen, Chao Ren, Yao Xiao, Yujing Wang, Renqi Yao, Quan Wang, Guoxing You, Mingzi Lu, Shaoduo Yan, Xiaoyong Zhang and 3 more

Open access · goldAbstract read
In one paragraph

Article in JHEP reports : innovation in hepatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

16 citing papers in PubMed, 17 citations in OpenAlex.

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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

13 authors at 4 institutions in 1 country.

Gan ChenInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Chao RenTranslational Medicine Research Center, Fourth Medical Center and Medical Innovation Research Division of the Chinese PLA General Hospital, Beijing, China.
Yao XiaoInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Yujing WangInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Renqi YaoTranslational Medicine Research Center, Fourth Medical Center and Medical Innovation Research Division of the Chinese PLA General Hospital, Beijing, China.
Quan WangInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Guoxing YouInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Mingzi LuBeijing Science and Technology Innovation Research Center, Beijing, China.
Shaoduo YanInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Xiaoyong ZhangInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Jun ZhangInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Yongming YaoTranslational Medicine Research Center, Fourth Medical Center and Medical Innovation Research Division of the Chinese PLA General Hospital, Beijing, China.
Hong ZhouInstitute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Beijing, China.
Academy of Military Medical Sciences · CNChinese PLA General Hospital · CNBeijing Advanced Sciences and Innovation Center · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background & Aims: Sepsis-induced acute liver dysfunction often occurs early in sepsis and can exacerbate the pathology by triggering multiple organ dysfunction and increasing lethality. Nevertheless, our understanding of the cellular heterogeneity and dynamic regulation of major nonparenchymal cell lineages remains unclear. Methods: Here, single-cell RNA sequencing was used to profile multiple nonparenchymal cell subsets and dissect their crosstalk during sepsis-induced acute liver dysfunction in a clinically relevant polymicrobial sepsis model. The transcriptomes of major liver nonparenchymal cells from control and sepsis mice were analysed. The alterations in the endothelial cell and neutrophil subsets that were closely associated with acute liver dysfunction were validated using multiplex immunofluorescence staining. In addition, the therapeutic efficacy of inhibiting activating transcription factor 4 (ATF4) in sepsis and sepsis-induced acute liver dysfunction was explored. Results: Our results present the dynamic transcriptomic landscape of major nonparenchymal cells at single-cell resolution. We observed significant alterations and heterogeneity in major hepatic nonparenchymal cell subsets during sepsis. Importantly, we identified endothelial cell (CD31 Conclusions: These results elucidate the potential mechanisms and subsequent therapeutic targets for the prevention and treatment of sepsis-induced acute liver dysfunction and other liver-related diseases. Impact and Implications: Sepsis-induced acute liver dysfunction often occurs early in sepsis and can lead to the death of the patient. Nevertheless, the pathogenesis of sepsis-induced acute liver dysfunction is not yet clear. We identified the major cell types associated with acute liver dysfunction and explored their interactions during sepsis. In addition, we also found that ATF-4 inhibition could be invoked as a potential therapeutic for sepsis-induced acute liver dysfunction.

Indexed as

Activating transcription factor 4Acute liver dysfunctionSepsisSingle-cell RNA sequencing

Identifiers

PMID37122356
PMCPMC10130477
OpenAlexW4322621421

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.