Faculty Profiles - KATO, Ryuji

Papers - KATO, Ryuji

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Collection of Data Variation Using a High-Throughput Image-Based Assay Platform Facilitates Data-Driven Understanding of TRPA1 Agonist Diversity Reviewed Open Access

Terada Yuko, Tanaka Kenjiro, Matsuyama Minami, Fujitani Masaya, Shibuya Masatoshi, Yamamoto Yoshihiko, Kato Ryuji, Ito Keisuke

APPLIED SCIENCES Vol. 12 ( 3 ) 2022.2

Morphological heterogeneity description enabled early and parallel non-invasive prediction of T-cell proliferation inhibitory potency and growth rate for facilitating donor selection of human mesenchymal stem cells Reviewed Open Access

Imai Yuta, Kanie Kei, Kato Ryuji

INFLAMMATION AND REGENERATION Vol. 42 ( 1 ) page： 8 2022.1

Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning Reviewed Open Access

Yoshida Kazunori, Kawai Shun, Fujitani Masaya, Koikeda Satoshi, Kato Ryuji, Ema Tadashi

SCIENTIFIC REPORTS Vol. 11 ( 1 ) page： 11883 2021.6

Predicting quality decay in continuously passaged mesenchymal stem cells by detecting morphological anomalies.  Reviewed

Takemoto Yuto, Imai Yuta, Kanie Kei, Kato Ryuji

JOURNAL OF BIOSCIENCE AND BIOENGINEERING Vol. 131 ( 2 ) page： 198 - 206 2021.2

Development of Carbon Concentration Prediction Technology from Microstructure Images of Carburizing Heat Treatment Products using Machine Learning Reviewed Open Access

YACHI Yoshiki, HATTORI Kiyoyuki, KATO Ryuji

NETSUSHORI Vol. 61 ( 5 ) page： 257 - 263 2021

Language：Japanese Publisher：The Japan Society for Heat Treatment

<p>Carburizing, quenching and tempering heat treatments are widely used as surface hardening, and it is known that their performances are changed depending on the carbon concentration. We had verified the effectiveness of the technique for predicting the carbon concentration from the microstructure images after heat treatment by using image recognition technologies and machine learning technologies that were focused in recent years. These technologies extracted the black and white objects of the image, and then machine learning of each shape information and brightness information as a features．Based on these technologies, we succeeded in predicting 0.78 mass％ of microstructure in the range of 0.75 mass％ to 0.79 mass％ by using regression models according to the characters of microstructure images.</p>

DOI： 10.14940/netsushori.61.257

Open Access

CiNii Research

身近となった画像解析とAI Open Access

加藤竜司

生物工学会誌 Vol. 99 ( 8 ) page： 432 - 435 2021

Screening of FFAR1-activating peptides by molecular structural analysis Reviewed

Yoshioka Keitaro, Yamashita Haruki, Fujitani Masaya, Kato Ryuji, Shimizu Kazunori, Honda Hiroyuki

KAGAKU KOGAKU RONBUNSHU Vol. 47 ( 3 ) page： 64 - 68 2021

Language：Japanese Publisher：The Society of Chemical Engineers, Japan

<p>To find FFAR1-activating peptides consisting of natural amino acid residues, molecular structure analysis was performed by hierarchical clustering using extraction of physicochemical parameters. When 3 mer to 6 mer peptide libraries were prepared and the molecular structure of each was compared with 5 chemical agonists, 12 peptides with high correlation coefficients of physicochemical parameters were found from the 6 mer peptide library. These peptides were then synthesized by Fmoc solid phase synthesis, and their activity was assessed by TGFα shedding assay using FFAR1-expressing HEK293. As a result, two peptides, GCGGSS and GASGCC, were identified as peptide agonists with relatively high activity. Although these peptides showed approximately one fifth of the activity of chemical agonist GW9508, they are the first examples that we know of FFAR1-activating peptides consisting of natural amino acid residues.</p>

DOI： 10.1252/kakoronbunshu.47.64

Web of Science

Scopus

CiNii Research

Machine learning-based amino-acid substitution of short peptides: Acquisition of peptides with enhanced inhibitory activities against α-amylase and α-glucosidase. Reviewed

Yamashita Haruki, Fujitani Masaya, Shimizu Kazunori, Kanie Kei, Kato Ryuji, Honda Hiroyuki

ACS BIOMATERIALS SCIENCE & ENGINEERING Vol. 6 ( 11 ) page： 6117 - 6125 2020.11

In vitro model of human skeletal muscle tissues with contractility fabricated by immortalized human myogenic cells. Reviewed

Nagashima Takunori, Hadiwidjaja Stacy, Ohsumi Saki, Murata Akari, Hisada Takumi, Kato Ryuji, Okada Yohei, Honda Hiroyuki, Shimizu Kazunori

ADVANCED BIOSYSTEMS Vol. 4 ( 11 ) page： e2000121 2020.11

Reproducible production and image-based quality evaluation of retinalpigment epithelium sheets from human induced pluripotent stem cells. Reviewed Open Access

Ye Ke, Takemoto Yuto, Ito Arisa, Onda Masanari, Morimoto Nao, Mandai Michiko, Takahashi Masayo, Kato Ryuji, Osakada Fumitaka

SCIENTIFIC REPORTS Vol. 10 ( 1 ) page： 14387 2020.9

The importance of scoring recognition fitness in spheroid morphological analysis for robust label -free quality evaluation Reviewed

Shirai Kazuhide, Kato Hirohito, Imai Yuta, Shibuta Mayu, Kanie Kei, Kato Ryuji

REGENERATIVE THERAPY Vol. 14 page： 205 - 214 2020.6

Performance of a biodegradable compositewith hydroxyapatite as a scaffold in pulp tissue repair. Reviewed Open Access

Okamoto Motoki, Matsumoto Sayako, Sugiyama Ayato, Kanie Kei, Watanabe Masakatsu, Huang Hailing, Ali Manahil, Ito Yuki, Miura Jiro, Hirose Yujiro, Uto Koichiro, Ebara Mitsuhiro, Kato Ryuji, Yamawaki-Ogata Aika, Narita Yuji, Kawabata Shigetada, Takahashi Yusuke, Hayashi Mikako

POLYMERS (BASEL) Vol. 12 ( 4 ) page： 937 - 941 2020.4

Novel cannabis flavonoid, cannflavin A displays both a hormetic and neuroprotective profile against amyloid β-mediatedneurotoxicity in PC12 cells: Comparison with geranylated flavonoids, mimuloneand diplacone. Reviewed International coauthorship

Eggers Carly, Fujitani Masaya, Kato Ryuji, Smid Scott

BIOCHEMICAL PHARMACOLOGY Vol. 169 page： 113609 2019.8

Effect of mechanical vibration stress in cell culture on human inducedpluripotent stem cells. Reviewed Open Access

Kanie Kei, Sakai Teppei, Imai Yuta, Yoshida Kei, Sugimoto Ayako, Makino Hodaka, Kubo Hirotsugu, Kato Ryuji

REGENERATIVE THERAPY Vol. 12 page： 27 - 35 2019.6

Quantitative analysisof operators' flow line in the cell culture for controlled manual operation. Reviewed Open Access

Kanie Kei, Sasaki Hiroto, Ikeda Yurika, Tamada Masaki, Togawa Fumio, Kato Ryuji

REGENERATIVE THERAPY Vol. 12 page： 43 - 54 2019.5

Identification of an early cell fate regulator bydetecting dynamics in transcriptional heterogeneity and co-regulation duringastrocyte differentiation. Reviewed Open Access

Ando Tatsuya, Kato Ryuji, Honda Hiroyuki

NPJ SYSTEMS BIOLOGY AND APPLICATIONS Vol. 5 ( 1 ) page： 18 2019.5

Numerical investigation of particle dispersion in the preprocessing stage for a staticcell cultivation. Reviewed

Sekimoto Atsushi, Kanemaru Yoshiki, Okano Yasunori, Kanie Kei, Kato Ryuji, Kino-oka Masahiro

REGENERATIVE THERAPY Vol. 12 ( 83 ) page： 87 2019.4

Activation of cancer-related and mitogen-activated protein kinase signaling pathways in human mature osteoblasts isolated from patients with type 2 diabetes. Reviewed Open Access

Kuroiwa Tomoyuki, Matsumoto Megumi, Kato Ryuji, Nimura Akimoto, Yoshii Toshitaka, Okawa Atsushi, Fujita Koji

BONE REPORTS Vol. 10 page： 100199 2019.2

Time-course colony tracking analysis for evaluating induced pluripotent stem cellculture processes. Reviewed Open Access

Yoshida Kei, Okada Mai, Nagasaka Risako, Sasaki Hiroto, Kanie Kei, Kato Ryuji

JOURNAL OF BIOSCIENCE AND BIOENGINEERING Vol. 128 ( 2 ) page： 209 - 217 2019.2

Morphology-based analysis of myoblasts for prediction of myotube formation. Reviewed Open Access

Ishikawa Kiyoshi, Yoshida Kei, Kanie Kei, Omori Kenji, Kato Ryuji

SLAS DISCOVERY Vol. 24 ( 1 ) page： 47 - 56 2019.1

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Papers - KATO, Ryuji