Evidence map›Paper›PMID 35811838›Full record

ArticleComputational and structural biotechnology journal2022

Tracing the cell-type-specific modules of immune responses during COVID-19 progression using scDisProcema.

Anyao Li, Jihong Yang, Jingyang Qian, Xin Shao, Jie Liao, Xiaoyan Lu, Xiaohui Fan

Open access · goldAbstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2022. 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
0.1field-weighted citation impact, top 58% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  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

7 authors at 2 institutions in 1 country.

Anyao LiCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Jihong YangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Jingyang QianCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Xin ShaoCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Jie LiaoCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Xiaoyan LuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Xiaohui FanCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Yangtze University · CNZhejiang Lab · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has caused severe threats to lives and damage to property worldwide. The immunopathology of the disease is of particular concern. Currently, researchers have used gene co-expression networks (GCNs) to deepen the study of molecular mechanisms of immune responses to COVID-19. However, most efforts have not fully explored dynamic changes of cell-type-specific molecular networks in the disease process. This study proposes a GCN construction pipeline named single-cell Disease Progression cellular module analysis (scDisProcema), which can trace dynamic changes of immune system response during disease progression using single-cell data. Here, scDisProcema considers changes in cell fate and expression patterns during disease development, identifying gene modules responsible for different immune cells. The hub genes are screened for each module by the specific expression level and the intercellular connectivity of modules. Based on functional items enriched by each gene module, we elucidate the biological processes of different cells involved in disease development and explain the molecular mechanisms underlying the process of cell depletion or proliferation caused by disease. Compared with traditional WGCNA methods, scDisProcema can make more convenient use of the heterogeneity information provided by scRNA-seq data and has great potential in exploring molecular changes during disease progression and organ development.

Indexed as

COVID-19Disease progressionscRNA-seqWGCNA

Identifiers

PMID35811838
PMCPMC9250167
OpenAlexW4283767949

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.