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Cited by 303

The DOI matches its Crossref record; 142 of the 142 references it cites were found in a registry or an index.

Insights into the Secretome of Mesenchymal Stem Cells and Its Potential Applications

Open access
Eleuteri, Sharon, Fierabracci, Alessandra·2019·International Journal of Molecular Sciences

Abstract

Mesenchymal stem cells (MSCs) have regenerative, immunoregulatory properties and can be easily isolated and expanded in vitro. Despite being a powerful tool for clinical applications, they present limitations in terms of delivery, safety, and variability of therapeutic response. Interestingly, the MSC secretome composed by cytokines, chemokines, growth factors, proteins, and extracellular vesicles, could represent a valid alternative to their use. It is noteworthy that MSC-derived extracellular vesicles (MSC-EVs) have the same effect and could be advantageous compared to the parental cells because of their specific miRNAs load. MiRNAs could be useful both in diagnostic procedures such as “liquid biopsy” to identify early pathologies and in the therapeutic field. Not only are MSC-EVs’ preservation, transfer, and production easier, but their administration is also safer, hence some clinical trials are ongoing. However, much effort is required to improve the characterization of EVs to avoid artifacts and guarantee reproducibility of the studies.

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Crossref · 10.3390/ijms20184597

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Metadata

Authors
Eleuteri, S., & Fierabracci, A.
Venue
International Journal of Molecular Sciences
Publisher
MDPI AG
Published
2019-09-17
Volume
20
Issue
18
Pages
4597
ISSN
1422-0067 (ISSN-L)
OpenAlex
W2973263520
Cited by
303
References
142
FWCI
17.02
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Insights into the Secretome of Mesenchymal Stem Cells and Its Potential Applications. https://app.cochat.ai/papers/10.3390/ijms20184597
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Eleuteri, S., & Fierabracci, A. (2019). Insights into the Secretome of Mesenchymal Stem Cells and Its Potential Applications. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms20184597

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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.