Evidence mapPaperPMID 35958408Full record

ReviewFrontiers in cardiovascular medicine2022

Advances in application of single-cell RNA sequencing in cardiovascular research.

Yue Hu, Ying Zhang, Yutong Liu, Yan Gao, Tiantian San, Xiaoying Li, Sensen Song, Binglong Yan, Zhuo Zhao

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 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
field-weighted citation impact
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.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. 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

9 authors.

Yue HuDepartment of Cardiology, Jinan Central Hospital, Shandong University, Jinan, China.
Ying ZhangDepartment of Cardiology, Central Hospital Affiliated Shandong First Medical University, Jinan, China.
Yutong LiuDepartment of Cardiology, Jinan Central Hospital, Shandong University, Jinan, China.
Yan GaoDepartment of Research Center of Translational Medicine, Central Hospital Affiliated Shandong First Medical University, Jinan, China.
Tiantian SanDepartment of Cardiology, Jinan Central Hospital, Shandong University, Jinan, China.
Xiaoying LiDepartment of Research Center of Translational Medicine, Central Hospital Affiliated Shandong First Medical University, Jinan, China.
Sensen SongDepartment of Cardiology, Central Hospital Affiliated Shandong First Medical University, Jinan, China.
Binglong YanDepartment of Cardiology, Central Hospital Affiliated Shandong First Medical University, Jinan, China.
Zhuo ZhaoDepartment of Cardiology, Jinan Central Hospital, Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) provides high-resolution information on transcriptomic changes at the single-cell level, which is of great significance for distinguishing cell subtypes, identifying stem cell differentiation processes, and identifying targets for disease treatment. In recent years, emerging single-cell RNA sequencing technologies have been used to make breakthroughs regarding decoding developmental trajectories, phenotypic transitions, and cellular interactions in the cardiovascular system, providing new insights into cardiovascular disease. This paper reviews the technical processes of single-cell RNA sequencing and the latest progress based on single-cell RNA sequencing in the field of cardiovascular system research, compares single-cell RNA sequencing with other single-cell technologies, and summarizes the extended applications and advantages and disadvantages of single-cell RNA sequencing. Finally, the prospects for applying single-cell RNA sequencing in the field of cardiovascular research are discussed.

Indexed as

cardiovascularheart developmentprecision medicinesingle-cell RNA sequencingstem cells

Identifiers

PMID35958408
PMCPMC9360414

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.