日時：	2025年5月9日（金）13：30～14：30
場所：	医生物学研究所 医生研１号館１階会議室（134室）
演者：	Takao Yogo, M.D., Ph.D. Researcher Division of Cell Regulation The Institute of Medical Science, The University of Tokyo
演題：	Prediction of hematopoietic stem cell diversity using quantitative phase imaging

講演要旨

Cells undergo continual transformations, never retaining their original state. Hematopoietic stem cells (HSCs), at the apex of the hematopoietic hierarchy, are not exempt from this dynamic process. Foundational research on HSCs has progressed in tandem with the development of innovative identification technologies. Given that the functional quality of HSCs is critically linked to the safety and efficacy of stem cell therapies, there is a pressing need to accurately identify high-quality HSCs. However, conventional approaches predominantly relied on snapshot evaluations at single time points, thereby overlooking the inherent temporal variability of these dynamic cells. In this study, we integrated an ex vivo HSC expansion system with quantitative phase imaging (QPI) and machine learning to noninvasively predict the functional quality of murine HSCs. Single-cell QPI tracking during culture revealed diverse HSC dynamics that were undetectable using conventional snapshot analysis. By performing multidimensional analyses of cellular features extracted from QPI data, we achieved accurate prediction of HSC functional quality. Moreover, incorporating time information from continuous QPI datasets into machine learning models significantly enhanced predictive accuracy. Observations of similar dynamic behavior in human HSCs further support the potential of this new framework for functionally predicting HSC quality based on temporal dynamics.

20250509_Dr.Yogo_flyer

Host:
医生物学研究所　ナノ生物工学分野
新宅　博文　Hirofumi Shintaku,
shintaku[@]infront.kyoto-u.ac.jp