Evidence map›Paper›PMID 37153747›Full record

ArticleTheranostics2023

Multilineage commitment of Sca-1

Zhichao Ni, Lingxia Lyu, Hui Gong, Luping Du, Zuoshi Wen, Hua Jiang, Hao Yang, Yanhua Hu, Bohuan Zhang, Qingbo Xu and 2 more

Open access · goldAbstract read
In one paragraph

Article in Theranostics, 2023. 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
0.9field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
  3. CD34Theranostics · 2025
    Article
  4. Article
  5. Resident vascular Sca1iScience · 2024
    Article
  6. Article
  7. Stem cell antigen-1Cellular and molecular life sciences : CMLS · 2023
    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

12 authors at 2 institutions in 1 country.

Zhichao NiDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Lingxia LyuDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Hui GongDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Luping DuDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Zuoshi WenDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Hua JiangDepartment of kidney disease center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, PR China.
Hao YangDepartment of kidney disease center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, PR China.
Yanhua HuDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Bohuan ZhangDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Qingbo XuDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Xiaogang GuoDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Ting ChenDepartment of Cardiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Zhejiang University · CNFirst Affiliated Hospital Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vein graft failure remains a significant clinical problem. Similar to other vascular diseases, stenosis of vein grafts is caused by several cell lines; however, the sources of these cells remain unclear. The objective of this study was to investigate the cellular sources that reshape vein grafts. By analyzing transcriptomics data and constructing inducible lineage-tracing mouse models, we investigated the cellular components of vein grafts and their fates. The sc-RNAseq data suggested that Sca-1+ cells were vital players in vein grafts and might serve as progenitors for multilineage commitment. By generating a vein graft model in which the venae cavae from C57BL/6J wild-type mice were transplanted adjacent to the carotid arteries of Sca-1(Ly6a)-CreERT2; Rosa26-tdTomato mice, we demonstrated that the recipient Sca-1+ cells dominated reendothelialization and the formation of adventitial microvessels, especially at the perianastomotic regions. In turn, using chimeric mouse models, we confirmed that the Sca-1+ cells that participated in reendothelialization and the formation of adventitial microvessels all had a non-bone-marrow origin, whereas bone-marrow-derived Sca-1+ cells differentiated into inflammatory cells in vein grafts. Furthermore, using a parabiosis mouse model, we confirmed that non-bone-marrow-derived circulatory Sca-1+ cells were vital for the formation of adventitial microvessels, whereas Sca-1+ cells derived from local carotid arteries were the source of endothelium restoration. Using another mouse model in which venae cavae from Sca-1 (Ly6a)-CreERT2; Rosa26-tdTomato mice were transplanted adjacent to the carotid arteries of C57BL/6J wild-type mice, we confirmed that the donor Sca-1+ cells were mainly responsible for smooth muscle cells commitment in the neointima, particularly at the middle bodies of vein grafts. In addition, we provided evidence that knockdown/knockout of Pdgfrα in Sca-1+ cells decreased the cell potential to generate SMCs

Indexed as

VeinsVenae CavaeAnimalsMiceMice, Inbred C57BLNeointimaTunica Intima

Identifiers

PMID37153747
PMCPMC10157743
OpenAlexW4364321961

What OpenQuestion 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 OpenQuestion graph.