Evidence map›Paper›PMID 39609860›Full record

ArticleBiomarker research2024

CardioAtlas: deciphering the single-cell transcriptome landscape in cardiovascular tissues and diseases.

Tiantongfei Jiang, Xiaoyan Jin, Yueying Gao, Weiwei Zhou, Jinyang Yu, Yongsheng Li, Juan Xu, Benzhi Cai

Abstract readLetter
In one paragraph

Article in Biomarker research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Tiantongfei Jiang *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China.
Xiaoyan Jin *Department of Pharmacy, The Second Affiliated Hospital, Department of Pharmacology, College of Pharmacy, (The Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), Harbin Medical University, Harbin, 150081, China.
Yueying Gao *School of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin, 150081, China.
Weiwei Zhou *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China.
Jinyang YuHainan Provincial Key Laboratory for Human Reproductive Medicine and Genetic Research, Department of Reproductive Medicine, Hainan Provincial Clinical Research Center for Thalassemia, Key Laboratory of Reproductive Health Diseases Research and Translation, College of Biomedical Information and Engineering, Hainan Medical University, Ministry of Education, The First Affiliated Hospital of Hainan Medical University, Haikou, 571199, China.
Yongsheng LiSchool of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin, 150081, China. liyongsheng@ems.hrbmu.edu.cn.
Juan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China. xujuanbiocc@ems.hrbmu.edu.cn.
Benzhi CaiDepartment of Pharmacy, The Second Affiliated Hospital, Department of Pharmacology, College of Pharmacy, (The Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), Harbin Medical University, Harbin, 150081, China. caibz@ems.hrbmu.edu.cn.

Funding

National Natural Science Foundation of China 32170676National Natural Science Foundation of China 32322020Natural Science Foundation of Heilongjiang Province (Key Program) ZD2023C007
6 · The paper itself

Abstract

Increasing scRNA-seq data in cardiovascular research have substantially improved our knowledge on the development of the cardiovascular system and the mechanisms underlying cardiovascular diseases. However, the single-cell transcriptome datasets were dispersed in literature and no resource for cardiovascular systems and diseases. Here, we constructed an organized resource CardioAtlas, which provides comprehensive analysis results for > 1,929,000 cells in 27 human data sets and > 1,088,000 cells in 39 mouse data sets. Through large-scale literature retrieval and manual annotation, we constructed 12 and 15 scRNA-seq reference atlas for common human and mouse cardiovascular systems and diseases, covering 43 and 39 cell types. In particular, CardioAtlas provides five analytic modules, including cell-type prediction, identification of marker genes, functional enrichment analysis, identification of cell-type-specific transcription regulons, and cell-cell communication analysis. In addition, users can upload scRNA-seq data for personalized analysis. CardioAtlas is available at http://bio-bigdata.hrbmu.edu.cn/CardioAtlas . CardioAtlas provides the first comprehensive and well-crafted reference atlas of cardiovascular systems and diseases and describes in detail previously unrecognized cell populations across a large number of humans and mice.

Identifiers

PMID39609860
PMCPMC11606023

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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.