論文

査読有り 国際誌
2018年9月20日

Intelligent Image-Activated Cell Sorting.

Cell
  • Nao Nitta
  • Takeaki Sugimura
  • Akihiro Isozaki
  • Hideharu Mikami
  • Kei Hiraki
  • Shinya Sakuma
  • Takanori Iino
  • Fumihito Arai
  • Taichiro Endo
  • Yasuhiro Fujiwaki
  • Hideya Fukuzawa
  • Misa Hase
  • Takeshi Hayakawa
  • Kotaro Hiramatsu
  • Yu Hoshino
  • Mary Inaba
  • Takuro Ito
  • Hiroshi Karakawa
  • Yusuke Kasai
  • Kenichi Koizumi
  • SangWook Lee
  • Cheng Lei
  • Ming Li
  • Takanori Maeno
  • Satoshi Matsusaka
  • Daichi Murakami
  • Atsuhiro Nakagawa
  • Yusuke Oguchi
  • Minoru Oikawa
  • Tadataka Ota
  • Kiyotaka Shiba
  • Hirofumi Shintaku
  • Yoshitaka Shirasaki
  • Kanako Suga
  • Yuta Suzuki
  • Nobutake Suzuki
  • Yo Tanaka
  • Hiroshi Tezuka
  • Chihana Toyokawa
  • Yaxiaer Yalikun
  • Makoto Yamada
  • Mai Yamagishi
  • Takashi Yamano
  • Atsushi Yasumoto
  • Yutaka Yatomi
  • Masayuki Yazawa
  • Dino Di Carlo
  • Yoichiroh Hosokawa
  • Sotaro Uemura
  • Yasuyuki Ozeki
  • Keisuke Goda
  • 全て表示

175
1
開始ページ
266
終了ページ
276
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.cell.2018.08.028

A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.

リンク情報
DOI
https://doi.org/10.1016/j.cell.2018.08.028
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/30166209
ID情報
  • DOI : 10.1016/j.cell.2018.08.028
  • ISSN : 0092-8674
  • PubMed ID : 30166209

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