Evidence map›Paper›PMID 37223430›Full record

ArticleNano research2023

Comparison of extruded cell nanovesicles and exosomes in their molecular cargos and regenerative potentials.

Xianyun Wang, Shiqi Hu, Dashuai Zhu, Junlang Li, Ke Cheng, Gang Liu

Open access · bronzeAbstract read
In one paragraph

Article in Nano research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
7.1field-weighted citation impact, top 2% 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

26 citing papers in PubMed, 46 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Xianyun WangDepartment of Cardiology, The First Hospital of Hebei Medical University, Shijiazhuang, 050000 China.
Shiqi HuDepartment of Molecular Biomedical Science, North Carolina State University, Raleigh, North Carolina 27607 USA.
Dashuai ZhuDepartment of Molecular Biomedical Science, North Carolina State University, Raleigh, North Carolina 27607 USA.
Junlang LiDepartment of Molecular Biomedical Science, North Carolina State University, Raleigh, North Carolina 27607 USA.
Ke ChengDepartment of Molecular Biomedical Science, North Carolina State University, Raleigh, North Carolina 27607 USA.
Gang LiuDepartment of Cardiology, The First Hospital of Hebei Medical University, Shijiazhuang, 050000 China.
North Carolina State University · USFirst Affiliated Hospital of Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular vesicles (EVs) generated from mesenchymal stem cells (MSCs) play an essential role in modulating cell-cell communication and tissue regeneration. The clinical translation of EVs is constrained by the poor yield of EVs. Extrusion has recently become an effective technique for producing a large scale of nanovesicles (NVs). In this study, we systematically compared MSC NVs (from extrusion) and EVs (from natural secretion). Proteomics and RNA sequencing data revealed that NVs resemble MSCs more closely than EVs. Additionally, microRNAs in NVs are related to cardiac repair, fibrosis repression, and angiogenesis. Lastly, intravenous delivery of MSC NVs improved heart repair and cardiac function in a mouse model of myocardial infarction. Electronic Supplementary Material: Supplementary material (Figs. S1-S4) is available in the online version of this article at 10.1007/s12274-023-5374-3.

Indexed as

cardiac repairexosomesextracellular vesicles (EVs)mesenchymal stem cells (MSCs)myocardial infarction (MI)nanovesicles (NVs)

Identifiers

PMID37223430
PMCPMC9971669
OpenAlexW4322775728

What OpenQuestion holds

Textmetadata
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.