Evidence map›Paper›PMID 37554834›Full record

ArticleHeliyon2023

Insights gained from single-cell RNA analysis of murine endothelial cells in aging hearts.

Zhong Liu, Yanjing Huang, Dongliang Wang, Mengke Li, Qikai Zhang, Caineng Pan, Yuheng Lin, Yuanting Luo, Zhuoxing Shi, Ping Zhang and 1 more

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Neurovascular interactions in the ageing heart.Nature reviews. Cardiology · 2026
    Review
  3. Review
  4. Article
  5. Article
  6. 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

11 authors.

Zhong LiuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Yanjing HuangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Dongliang WangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Mengke LiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Qikai ZhangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Caineng PanState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Yuheng LinState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Yuanting LuoState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Zhuoxing ShiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Ping ZhangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Yingfeng ZhengState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging is the strongest risk factor for cardiovascular disease, with progressive decline in the function of vascular endothelial cells (ECs) with age. Systematic analyses of the effects of aging on different cardiac EC types remain limited. Here, we constructed a scRNA atlas of EC transcriptomes in young and old mouse hearts. We identified 10 EC subclusters. The multidimensionally differential genes (DEGs) analysis across different EC clusters shows molecular changes with aging, showing the increase in the overall inflammatory microenvironment and the decrease in angiogenesis and cytoskeletal support capacity of aged ECs. And we performed an in-depth analysis of 3 special ECs, Immunology, Proliferating and Angiogenic. The Immunology EC seems highly associated with some immune regulatory functions, which decline with aging at different degrees. Analysis of two types of neovascular ECs, Proliferating, Angiogenic, implied that Angiogenic ECs can differentiate into multiple EC directions after initially originating from proliferating ECs. And aging leads to a decrease in the ability of vascular angiogenesis and differentiation. Finally, we summarized the effects of aging on cell signaling communication between different EC clusters. This cardiac EC atlas offers comprehensive insights into the molecular regulations of cardiovascular aging, and provides new directions for the prevention and treatment of age-related cardiovascular disease.

Indexed as

AgingECscRNA-seq

Identifiers

PMID37554834
PMCPMC10404962

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.