Postsynaptic structure formation of human iPS cell-derived neurons takes longer than presynaptic formation during neural differentiation in vitro.

Autor: Togo, Kazuyuki^1,2 (AUTHOR), Fukusumi, Hayato² (AUTHOR), Shofuda, Tomoko² (AUTHOR), Ohnishi, Hiroshi³ (AUTHOR), Yamazaki, Hiroyuki^4,5 (AUTHOR), Hayashi, Mariko Kato^6,7 (AUTHOR), Kawasaki, Nana⁸ (AUTHOR), Takei, Nobuyuki⁹ (AUTHOR), Nakazawa, Takanobu^10,11 (AUTHOR), Saito, Yumiko¹² (AUTHOR), Baba, Kousuke¹ (AUTHOR), Hashimoto, Hitoshi^{10,13,14,15,16} (AUTHOR), Sekino, Yuko¹⁷ (AUTHOR), Shirao, Tomoaki⁴ (AUTHOR), Mochizuki, Hideki¹ (AUTHOR), Kanemura, Yonehiro^18,19 (AUTHOR) kanemura.yonehiro.hk@mail.hosp.go.jp

Publikováno v: Molecular Brain. 10/10/2021, Vol. 14 Issue 1, p1-17. 17p.

Additional file 1 of Postsynaptic structure formation of human iPS cell-derived neurons takes longer than presynaptic formation during neural differentiation in vitro

Autor: Togo, Kazuyuki, Fukusumi, Hayato, Shofuda, Tomoko, Ohnishi, Hiroshi, Yamazaki, Hiroyuki, Hayashi, Mariko Kato, Kawasaki, Nana, Takei, Nobuyuki, Nakazawa, Takanobu, Saito, Yumiko, Baba, Kousuke, Hashimoto, Hitoshi, Sekino, Yuko, Shirao, Tomoaki, Mochizuki, Hideki, Kanemura, Yonehiro

Additional file 1: Table 1. Primers for SYBR Green-based qRT-PCR.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a6fb7617be56cfa8eb86e9f100768d2

Additional file 4 of Postsynaptic structure formation of human iPS cell-derived neurons takes longer than presynaptic formation during neural differentiation in vitro

Autor: Togo, Kazuyuki, Fukusumi, Hayato, Shofuda, Tomoko, Ohnishi, Hiroshi, Yamazaki, Hiroyuki, Hayashi, Mariko Kato, Kawasaki, Nana, Takei, Nobuyuki, Nakazawa, Takanobu, Saito, Yumiko, Baba, Kousuke, Hashimoto, Hitoshi, Sekino, Yuko, Shirao, Tomoaki, Mochizuki, Hideki, Kanemura, Yonehiro

Additional file 4: Figure S1. Gene expression analysis of pre- and postsynaptic markers during the neuronal differentiation of hiPSC-NPCs in the absence and presence of NGF. Dot and box plots showing the expression of postsynaptic markers (drebrin A+

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::055f6206882dcf038a34baf4383aa76f

Nonlinear Control System Using Universal Learning Network with RBF and RasVal

Autor: Shao, Ning, Hirasawa, Kotaro, Ohbayashi, Masanao, Murata, Junichi, Togo, Kazuyuki, Hu, Jinglu

Publikováno v: 九州大学大学院システム情報科学紀要. 2(2):197-212

In this paper, we present a new control method firstly for nonlinear systems using Universal Learning Network(ULN) with radial basis function(RBF). ULN can model and control the large scale complicated systems such as industrial plants, economic, soc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=jairo_______::5e6f0e0f732b372f20952e0cf3e65696
http://hdl.handle.net/2324/1522391

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