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 - 2017/7/2
Y1 - 2017/7/2
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
T3 - 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
SP - 64
EP - 67
BT - 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
Y2 - 17 October 2017 through 19 October 2017
ER -