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
Volume2018-January
ISBN (Electronic)9781538631942
DOIs
Publication statusPublished - 2018 Jan 19
Externally publishedYes
Event2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017 - Beijing, China
Duration: 2017 Oct 172017 Oct 19

Other

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

Fingerprint

Cell Differentiation
Cell Culture
Stem Cells
Stem cells
Cell culture
Artificial intelligence
Artificial Intelligence
Ensemble
Biology
Cytology
Molecular biology
Microfabrication
Biological systems
Screening Experiment
High-throughput Screening
Embryogenesis
Image analysis
Adhesives
Cell
Screening

Keywords

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

ASJC Scopus subject areas

  • Control and Optimization
  • Artificial Intelligence

Cite this

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

An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns. / Tanaka, Nobuyuki; Yamashita, Tadahiro; Sato, Asako; Vogel, Viola; Tanaka, Yo.

2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 64-67.

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

Tanaka, N, Yamashita, T, Sato, A, Vogel, V & Tanaka, Y 2018, An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns. in 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 64-67, 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017, Beijing, China, 17/10/17. https://doi.org/10.1109/CBS.2017.8266068
Tanaka N, Yamashita T, Sato A, Vogel V, Tanaka Y. An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns. In 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 64-67 https://doi.org/10.1109/CBS.2017.8266068
Tanaka, Nobuyuki ; Yamashita, Tadahiro ; Sato, Asako ; Vogel, Viola ; Tanaka, Yo. / An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns. 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 64-67
@inproceedings{1a1ca42d96f04f958ef8692086ff24c4,
title = "An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns",
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.",
keywords = "agarose, image processing, machine learning, mesenchymal stem cell, micro-structure, patterned differentiation",
author = "Nobuyuki Tanaka and Tadahiro Yamashita and Asako Sato and Viola Vogel and Yo Tanaka",
year = "2018",
month = "1",
day = "19",
doi = "10.1109/CBS.2017.8266068",
language = "English",
volume = "2018-January",
pages = "64--67",
booktitle = "2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - An ensemble of agarose microwells and AI for understanding hMSC differentiation patterns

AU - Tanaka, Nobuyuki

AU - Yamashita, Tadahiro

AU - Sato, Asako

AU - Vogel, Viola

AU - Tanaka, Yo

PY - 2018/1/19

Y1 - 2018/1/19

N2 - 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.

AB - 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.

KW - agarose

KW - image processing

KW - machine learning

KW - mesenchymal stem cell

KW - micro-structure

KW - patterned differentiation

UR - http://www.scopus.com/inward/record.url?scp=85050528437&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85050528437&partnerID=8YFLogxK

U2 - 10.1109/CBS.2017.8266068

DO - 10.1109/CBS.2017.8266068

M3 - Conference contribution

AN - SCOPUS:85050528437

VL - 2018-January

SP - 64

EP - 67

BT - 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -