Evidence map›Paper›PMID 37038777›Full record

ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2023

Comparison of cell subsets in chronic obstructive pulmonary disease and controls based on single-cell transcriptome sequencing.

Li An, Hong Xia, Weiying Zheng, Lin Hua

Open access · bronzeAbstract read
In one paragraph

Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2023. 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
0.2field-weighted citation impact, top 32% 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. Review
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

4 authors at 1 institution in 1 country.

Li AnDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Hong XiaSchool of Biomedical Engineering, Capital Medical University, Beijing, China.
Weiying ZhengSchool of Biomedical Engineering, Capital Medical University, Beijing, China.
Lin HuaSchool of Biomedical Engineering, Capital Medical University, Beijing, China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrently, chronic obstructive pulmonary disease (COPD) significantly impacts patients' quality of life and survival as it has a high morbidity and mortality rate. COPD progression is associated with infiltration of adaptive inflammatory immune cells that form lymphatic follicles into the lung.

objectiveThe rapid development of single-cell RNA sequencing technology (scRNA-seq) provided us with powerful tools for studying the classification of cell subtypes. Additionally, it is known that COPD is closely related to the abnormal function of long-chain non-coding RNAs (lncRNAs), and scRNA-seq can help to study the expression of lncRNA from a single cell level.

methodsWe reanalyzed the scRNA-seq data of peripheral blood mononuclear cells of COPD patients downloaded from Gene Expression Omnibus (GEO) database, and performed the mRNA-based and lncRNA-based single cell clustering to compare the cell subsets in COPD and controls without COPD. Furthermore, we performed Gene Ontology (GO) enrichment analysis for the top ranked differentially expressed genes and target genes of differentially expressed lncRNAs in different cell subtypes for COPD and controls respectively.

resultsDifferences in cell subtypes were found between COPD and controls.

conclusionThis study may help us to further understand the mechanism of the human adaptive immune cell response of COPD.

Indexed as

Pulmonary Disease, Chronic ObstructiveRNA, Long NoncodingGene Expression ProfilingHumansLeukocytes, MononuclearQuality of LifeTranscriptomeRNA, Long NoncodingCOPDimmunelncRNAsSingle-cell

Identifiers

PMID37038777
PMCPMC10200138
OpenAlexW4362701922

What OpenQuestion holds

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LicenceCC BY-NC
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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.