Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 292

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Differentiation of multipotent vascular stem cells contributes to vascular diseases

Open access
Tang, Zhenyu, Wang, Aijun, Yuan, Falei, Yan, Zhiqiang, Liu, Bo, Chu, Julia S., Helms, Jill A., Li, Song·2012·Nature Communications

Abstract

It is generally accepted that the de-differentiation of smooth muscle cells, from the contractile to the proliferative/synthetic phenotype, has an important role during vascular remodelling and diseases. Here we provide evidence that challenges this theory. We identify a new type of stem cell in the blood vessel wall, named multipotent vascular stem cells. Multipotent vascular stem cells express markers, including Sox17, Sox10 and S100β, are cloneable, have telomerase activity, and can differentiate into neural cells and mesenchymal stem cell-like cells that subsequently differentiate into smooth muscle cells. On the other hand, we perform lineage tracing with smooth muscle myosin heavy chain as a marker and find that multipotent vascular stem cells and proliferative or synthetic smooth muscle cells do not arise from the de-differentiation of mature smooth muscle cells. In response to vascular injuries, multipotent vascular stem cells, instead of smooth muscle cells, become proliferative, and differentiate into smooth muscle cells and chondrogenic cells, thus contributing to vascular remodelling and neointimal hyperplasia. These findings support a new hypothesis that the differentiation of multipotent vascular stem cells, rather than the de-differentiation of smooth muscle cells, contributes to vascular remodelling and diseases. De-differentiation and proliferation of vascular smooth muscle cells is thought to have a dominant role in vascular remodelling. Here, Tanget al. identify a new type of multipotent vascular stem cell in the blood vessel wall that contributes to this process, thereby challenging the established hypothesis.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/ncomms1867

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 292

Metadata

Authors
Tang, Z., Wang, A., Yuan, F., Yan, Z., Liu, B., Chu, J. S., Helms, J. A., & Li, S.
Venue
Nature Communications
Published
2012-06-06
Volume
3
Issue
1
Pages
875-875
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2059893788
Cited by
292
References
4
FWCI
12.91
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.