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An in vitro microfluidic culture device for peripheral neurotoxicity prediction at low concentration based on deep learning

Xiaobo Han, Naoki Matsuda, Kazuki Matsuda, Makoto Yamanaka, Ikuro Suzuki
doi: https://doi.org/10.1101/2022.11.09.515778
Xiaobo Han
1Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
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Naoki Matsuda
1Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
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Kazuki Matsuda
1Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
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Makoto Yamanaka
2Ushio Inc.
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Ikuro Suzuki
1Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
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  • For correspondence: i-suzuki@tohtech.ac.jp
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Abstract

In this study, a microfluidic culture device was developed including related evaluation methods using deep learning for the purpose of constructing a rapid assessment platform for peripheral neuropathy caused by compounds. Primary rodent dorsal root ganglion was cultured in the microfluidic culture device that could separate the cell body and neurites, and the neurites’ morphological changes were analyzed by immunofluorescence images. Separated neurites successful culture in the microfluidic device for more than 1 month indicated that a series of test processes from culture to drug stimulation and fluorescence observation is possible. Additionally, cultured samples were treated with several anticancer drugs known to cause peripheral neurotoxicity (i.e., vincristine, oxaliplatin, and paclitaxel) and analyzed the neurites’ morphological changes by deep learning for image analysis. After training, artificial intelligence (AI) could identify neurite morphological changes caused by each compound and precisely predicted the toxicity positivity, even at low concentrations. For testing compounds, AI could also precisely detect toxicity negative and positive based on neurite images, even at low concentrations. Therefore, this microfluidic culture system is supposed to be useful for in vitro toxicity assessment.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted November 10, 2022.
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An in vitro microfluidic culture device for peripheral neurotoxicity prediction at low concentration based on deep learning
Xiaobo Han, Naoki Matsuda, Kazuki Matsuda, Makoto Yamanaka, Ikuro Suzuki
bioRxiv 2022.11.09.515778; doi: https://doi.org/10.1101/2022.11.09.515778
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An in vitro microfluidic culture device for peripheral neurotoxicity prediction at low concentration based on deep learning
Xiaobo Han, Naoki Matsuda, Kazuki Matsuda, Makoto Yamanaka, Ikuro Suzuki
bioRxiv 2022.11.09.515778; doi: https://doi.org/10.1101/2022.11.09.515778

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