Host Cell Prediction of Exosomes Using Morphological Features on Solid Surfaces Analyzed by Machine Learning-Reference-Cited by-同舟云学术

Host Cell Prediction of Exosomes Using Morphological Features on Solid Surfaces Analyzed by Machine Learning

Published:2018-05-17 Issue:23 Volume:122 Page:6224-6235
ISSN:1520-6106
Container-title:The Journal of Physical Chemistry B
language:en
Short-container-title:J. Phys. Chem. B

Author:

Ito Kazuki¹,Ogawa Yuta¹,Yokota Keiji¹,Matsumura Sachiko²,Minamisawa Tamiko²,Suga Kanako²,Shiba Kiyotaka²,Kimura Yasuo³,Hirano-Iwata Ayumi⁴^ORCID,Takamura Yuzuru⁵,Ogino Toshio¹⁵^ORCID

Affiliation:

1. Yokohama National University, 79-5, Tokiwadai, Hodogaya-ku, Yokohama 240-8501, Japan

2. Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo 135-8550, Japan

3. Tokyo University of Technology, 1404-1, Katakura-Cho, Hachioji 192-0914, Japan

4. Tohoku University, 2-1-1, Katahira, Aoba-ku, Sendai, Miyagi 980-8577, Japan

5. Japan Advanced Institute of Science and Technology, 1-1, Asahi-Dai, Nomi, Ishikawa 923-1292, Japan

Funder

Core Research for Evolutional Science and Technology

Japan Society for the Promotion of Science

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,Surfaces, Coatings and Films,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.8b01646

Reference68 articles.

1. Exosomes: Current knowledge of their composition, biological functions, and diagnostic and therapeutic potentials

2. Extracellular vesicles: Exosomes, microvesicles, and friends

3. Production and characterization of clinical grade exosomes derived from dendritic cells

4. Exosomes released from macrophages infected with intracellular pathogens stimulate a proinflammatory response in vitro and in vivo

5. Selective Enrichment of Tetraspan Proteins on the Internal Vesicles of Multivesicular Endosomes and on Exosomes Secreted by Human B-lymphocytes

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