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Automated Cell Mechanical Characterization by On-Chip Sequential Squeezing: From Static to Dynamic.
Li, Pengyun; Liu, Xiaoming; Kojima, Masaru; Huang, Qiang; Arai, Tatsuo.
Afiliação
  • Li P; Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing Advanced Innovation Center for Intelligent Robots and Systems, and School of Mechatronical Engineering, Beijing Institute of Technology, Beijing
  • Liu X; Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing Advanced Innovation Center for Intelligent Robots and Systems, and School of Mechatronical Engineering, Beijing Institute of Technology, Beijing
  • Kojima M; Department of Materials Engineering Science, Osaka University, Osaka 560-8531, Japan.
  • Huang Q; Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing Advanced Innovation Center for Intelligent Robots and Systems, and School of Mechatronical Engineering, Beijing Institute of Technology, Beijing
  • Arai T; Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing Advanced Innovation Center for Intelligent Robots and Systems, and School of Mechatronical Engineering, Beijing Institute of Technology, Beijing
Langmuir ; 37(27): 8083-8094, 2021 07 13.
Article em En | MEDLINE | ID: mdl-34171189
ABSTRACT
The mechanical properties of cells are harmless biomarkers for cell identification and disease diagnosis. Although many systems have been developed to evaluate the static mechanical properties of cells for biomedical research, their robustness, effectiveness, and cost do not meet clinical requirements or the experiments with a large number of cell samples. In this paper, we propose an approach for on-chip cell mechanical characterization by analyzing the dynamic behavior of cells as they pass through multiple constrictions. The proposed serpentine microfluidic channel consisted of 20 constrictions connected in series and divided into five rows for tracking cell dynamic behavior. Assisted by computer vision, the squeezing time of each cell through five rows of constrictions was automatically collected and filtered to evaluate the cell's mechanical deformability. We observed a decreasing passage time and increasing dynamic deformability of the cells as they passed through the multiple constrictions. The deformability increase rate of the HeLa cells was eight times greater than that of MEF cells. Moreover, the weak correlation between the deformability increase rate and the cell size indicated that cell recognition based on measuring the deformability increase rate could hardly be affected by the cell size variation. These findings showed that the deformability increase rate of the cell under on-chip sequential squeezing as a new index has great potential in cancer cell recognition.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microfluídica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microfluídica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article