High-throughput and label-free isolation of senescent murine mesenchymal stem cells.


Journal

Biomicrofluidics
ISSN: 1932-1058
Titre abrégé: Biomicrofluidics
Pays: United States
ID NLM: 101293825

Informations de publication

Date de publication:
May 2020
Historique:
received: 03 02 2020
accepted: 30 04 2020
entrez: 2 6 2020
pubmed: 2 6 2020
medline: 2 6 2020
Statut: epublish

Résumé

Under internal or external insults such as aging and oxidative stresses, cells are induced into a senescent state and stop cellular division permanently. As senescent cells (SnCs) accumulate, the regeneration capacity of biological tissue would be compromised, which has been found to be associated with a plethora of age-related disorders. Therefore, isolating SnCs becomes necessary. To address the lack of effective surface markers for SnCs isolation, a label-free microfluidic device was proposed in this paper, in which a spiral microchannel was deployed to isolate SnCs based on their size differences. We adopted a well-received cellular senescence model by exerting excessive oxidative stress to murine mesenchymal stem cells. This model was then validated through a series of SnCs characterizations including size measurement, p16INK4a expression level, senescence-associated beta-galactosidase, and doubling time. The senescence chip demonstrated an efficiency of 75% and viability over 85% at a flow rate of 5 ml/min. The average cell size from the inner outlet was 5 

Identifiants

pubmed: 32477445
doi: 10.1063/5.0011925
pii: 5.0011925
pmc: PMC7244328
doi:

Types de publication

Journal Article

Langues

eng

Pagination

034106

Informations de copyright

Copyright © 2020 Author(s).

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Auteurs

Zhengkun Chen (Z)

Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China.

Kuan Jiang (K)

Mechanobiology Institute, National University of Singapore, Singapore 117411.

Zhou Zou (Z)

Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China.

Xiaohe Luo (X)

Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China.

Chunyi Wen (C)

Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China.

Classifications MeSH