An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns

Nobuyuki Tanaka, Tadahiro Yamashita, Asako Sato, Viola Vogel, Yo Tanaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The importance of collaborative studies between the fields of biology and engineering are increasing. Technological innovation is a primary driver of advances in molecular and cellular biology. Unfortunately, most cutting-edge technologies are difficult to practically apply to biology. In embryogenesis, biological systems show a high degree of spatially controlled differentiation patterns. To understand underpinning mechanisms of spatial differentiation patterns of human mesenchymal stem cells (hMSCs) quantitatively in an in vitro system, both advanced micro-fabrication and image analysis technologies are required. hMSC differentiation patterns induced here by the cultivation of cells in confined space and by exposing them to differentiation induction media. This paper discusses an ensemble of nonadhesive agarose micro cell-culture wells (microwells) confining cells on adhesive substrates and artificial intelligence (AI) to understand why hMSC do not differentiate homogeneously, but in patterns, from the viewpoint of usability of our technological advances in actual high throughput screening experiments.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages64-67
Number of pages4
ISBN (Electronic)9781538631942
DOIs
Publication statusPublished - 2017 Jul 2
Externally publishedYes
Event2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017 - Beijing, China
Duration: 2017 Oct 172017 Oct 19

Publication series

Name2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
Volume2018-January

Other

Other2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
CountryChina
CityBeijing
Period17/10/1717/10/19

Keywords

  • agarose
  • image processing
  • machine learning
  • mesenchymal stem cell
  • micro-structure
  • patterned differentiation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization

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  • Cite this

    Tanaka, N., Yamashita, T., Sato, A., Vogel, V., & Tanaka, Y. (2017). An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns. In 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017 (pp. 64-67). (2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBS.2017.8266068