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Ikuro Suzuki

Showing results (1-10 of 34) with videos related to

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Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|March 2, 2025
[The potential of neural microphysiological systems (MPS)]Ikuro Suzuki
Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|September 4, 2020
[Approach to drug efficacy and safety assessment based on functions of a human iPSC-derived neuronal network]Ikuro Suzuki
Current Pharmaceutical Biotechnology|November 30, 2019
Approach to Neurotoxicity using Human iPSC Neurons: Consortium for Safety Assessment using Human iPS CellsTakafumi Shirakawa, Ikuro Suzuki
Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|September 4, 2020
[Evaluation methods for drug-induced seizure by microelectrode array recording using human iPS cell-derived neurons]Takafumi Shirakawa, Ikuro Suzuki
The Journal of Toxicological Sciences|October 2, 2022
Responses to antibiotics in human iPSC-derived neurons based on the clinical antibiotic-associated encephalopathy classificationYuto Ishibashi, Shingo Kimura, Ikuro Suzuki
Lab on a Chip|April 26, 2013
Control of neural network patterning using collagen gel photothermal etchingAoi Odawara, Masao Gotoh, Ikuro Suzuki
Biosensors & Bioelectronics|June 21, 2025
Development of a microelectrode array system for simultaneous measurement of field potential and glutamate release in brain slicesAiko Hasegawa, Naoki Matsuda, Ikuro Suzuki
Frontiers in Neuroscience|January 27, 2023
Detection of astrocytic slow oscillatory activity and response to seizurogenic compounds using planar microelectrode arrayTaeko Kuroda, Naoki Matsuda, Yuto Ishibashi, et al.
Frontiers in Neuroscience|September 2, 2025
Advanced neural activity mapping in brain organoids via field potential imaging with ultra-high-density CMOS microelectrode arraysRemi Yokoi, Naoki Matsuda, Yuto Ishibashi, et al.
Toxics|November 26, 2024
Development of a Novel Microphysiological System for Peripheral Neurotoxicity Prediction Using Human iPSC-Derived Neurons with Morphological Deep LearningXiaobo Han, Naoki Matsuda, Makoto Yamanaka, et al.
Pageof 4

Showing results (1-10 of 34) with videos related to

Sort By:
Pageof 4
Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|March 2, 2025
[The potential of neural microphysiological systems (MPS)]Ikuro Suzuki
Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|September 4, 2020
[Approach to drug efficacy and safety assessment based on functions of a human iPSC-derived neuronal network]Ikuro Suzuki
Current Pharmaceutical Biotechnology|November 30, 2019
Approach to Neurotoxicity using Human iPSC Neurons: Consortium for Safety Assessment using Human iPS CellsTakafumi Shirakawa, Ikuro Suzuki
Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|September 4, 2020
[Evaluation methods for drug-induced seizure by microelectrode array recording using human iPS cell-derived neurons]Takafumi Shirakawa, Ikuro Suzuki
The Journal of Toxicological Sciences|October 2, 2022
Responses to antibiotics in human iPSC-derived neurons based on the clinical antibiotic-associated encephalopathy classificationYuto Ishibashi, Shingo Kimura, Ikuro Suzuki
Lab on a Chip|April 26, 2013
Control of neural network patterning using collagen gel photothermal etchingAoi Odawara, Masao Gotoh, Ikuro Suzuki
Biosensors & Bioelectronics|June 21, 2025
Development of a microelectrode array system for simultaneous measurement of field potential and glutamate release in brain slicesAiko Hasegawa, Naoki Matsuda, Ikuro Suzuki
Frontiers in Neuroscience|January 27, 2023
Detection of astrocytic slow oscillatory activity and response to seizurogenic compounds using planar microelectrode arrayTaeko Kuroda, Naoki Matsuda, Yuto Ishibashi, et al.
Frontiers in Neuroscience|September 2, 2025
Advanced neural activity mapping in brain organoids via field potential imaging with ultra-high-density CMOS microelectrode arraysRemi Yokoi, Naoki Matsuda, Yuto Ishibashi, et al.
Toxics|November 26, 2024
Development of a Novel Microphysiological System for Peripheral Neurotoxicity Prediction Using Human iPSC-Derived Neurons with Morphological Deep LearningXiaobo Han, Naoki Matsuda, Makoto Yamanaka, et al.
Pageof 4