Evidence map›Paper›PMID 35980286›Full record

ArticleDatabase : the journal of biological databases and curation2022

SC2sepsis: sepsis single-cell whole gene expression database.

Yinjiaozhi Li, Ruoming Tan, Yang Chen, Zhaojun Liu, Erzhen Chen, Tingting Pan, Hongping Qu

Open access · goldAbstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

7 citing papers in PubMed, 5 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

7 authors at 1 institution in 1 country.

Yinjiaozhi LiDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No.197 Ruijin Er Road, Shanghai CN 200025, China.
Ruoming TanDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No.197 Ruijin Er Road, Shanghai CN 200025, China.
Yang ChenDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No.197 Ruijin Er Road, Shanghai CN 200025, China.
Zhaojun LiuDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No.197 Ruijin Er Road, Shanghai CN 200025, China.
Erzhen ChenDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No.197 Ruijin Er Road, Shanghai CN 200025, China.
Tingting PanDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No.197 Ruijin Er Road, Shanghai CN 200025, China.
Hongping QuDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No.197 Ruijin Er Road, Shanghai CN 200025, China.ORCID 0000-0002-2116-5125
Ruijin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis, one of the major challenges in the intensive care unit, is characterized by complex host immune status. Improved understandings of the phenotypic changes of immune cells during sepsis and the driving molecular mechanisms are critical to the elucidation of sepsis pathogenesis. Single-cell RNA sequencing (scRNA-seq), which interprets transcriptome at a single-cell resolution, serves as a useful tool to uncover disease-related gene expression signatures of different cell populations in various diseases. It has also been applied to studies on sepsis immunopathological mechanisms. Due to the fact that most sepsis-related studies utilizing scRNA-seq have very small sample sizes and there is a lack of an scRNA-seq database for sepsis, we developed Sepsis Single-cell Whole Gene Expression Database Website (SC2sepsis) (http://www.rjh-sc2sepsis.com/), integrating scRNA-seq datasets of human peripheral blood mononuclear cells from 45 septic patients and 26 healthy controls, with a total amount of 232 226 cells. SC2sepsis is a comprehensive resource database with two major features: (i) retrieval of 1988 differentially expressed genes between pathological and healthy conditions and (ii) automatic cell-type annotation, which is expected to facilitate researchers to gain more insights into the immune dysregulation of sepsis. DATABASE URL: http://www.rjh-sc2sepsis.com/.

Indexed as

SepsisSingle-Cell AnalysisGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansLeukocytes, MononuclearSequence Analysis, RNASoftwareTranscriptome

Identifiers

PMID35980286
PMCPMC9387141
OpenAlexW4292209017

What OpenQuestion holds

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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.