Books 【 display / non-display 】

Books 【 display / non-display 】

• Sustainable Catalysis: Challenges and Practices for the Pharmaceutical and Fine Chemical Industries

  Editors-in-chief Peter J. Dunn, K. K. (Mimi) Hii. Michael J. Krische. Michael T. Williams (H. Gotoh, Y. Hayashi.)（ Role： Joint author ,  Diarylprolinol Silyl Ethers: Development and Application as Organocatalysts）

  John Wiley & Sons, Inc. 

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  Language：Japanese Book type：Scholarly book

Thesis for a degree 【 display / non-display 】

Thesis for a degree 【 display / non-display 】

• プロリン及びシステイン由来の有機触媒を用いた不斉反応の開発

  五東　弘昭

  2009.3

  Doctoral Thesis   Single Work  

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  東京理科大学　工学研究科
  プロリンおよびシステインから単段階で合成可能な有用な有機触媒を開発し、それを用いることにより、これまでの不斉触媒反応の改良を行った。さらに、これまで不斉触媒的に行えなかった反応を開発した有機触媒を用いることにより進行させ、有用な光学活性化合物を合成した。

• システイン誘導体有機触媒を用いた分子内不斉マイケル反応

  五東　弘昭

  2006.3

  Master Thesis   Single Work  

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  東京理科大学 工学研究科
  システインから簡単に合成できる新規有機触媒が分子内不斉マイケル反応に優れていることを示し、光学活性な５および５，６員環を高ジアステレオかつ高エナンチオ選択的に合成した。

Papers 【 display / non-display 】

Papers 【 display / non-display 】

• Predicting Substrate Reactivity in Oxidative Homocoupling of Phenols Using Positive and Unlabeled Machine Learning

  Nishii Takafumi, Ichizawa Kaname, Nagano Haruka, Mukai Hiroya, Sakaguchi Daimon, Gotoh Hiroaki

  ACS Omega   10 ( 42 )   49805 - 49815   2025.10

  CiNii Research

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  Language：English   Publishing type：Research paper (scientific journal)   Publisher：American Chemical Society   Joint Work  

  A positive and unlabeled machine learning (PU learning) model was trained to predict substrate reactivity in the oxidative homocoupling of phenols under different conditions. We demonstrated its effectiveness by conducting validation using two descriptor sets: 28-dimensional descriptors considered to influence reactivity and extended-connectivity fingerprints. We performed parameter tuning of the model using our experimental data and determined that the optimized parameters provided excellent prediction accuracy for the existing experimental data, regardless of the reaction conditions. Furthermore, the prediction results obtained using 30 types of unlabeled data matched the experimental results for approximately 83.3–86.7% of substrates, and the prediction accuracy of the PU learning model was shown to be superior to that of a model trained with both positive and negative reactivity data. Because negative data are not required to train a PU learning model, it can be applied to reactions reported in many previous studies, informing the cost-effective synthesis of molecules based on model-predicted results.

• Silyloxy-substituted anthraquinones as Type I photoinitiators for visible light-induced radical polymerization

  Eunseok Lee, Takuya Sekizawa, Yuki Kobayashi-Miyajima, Takaya Hirose, Shunichi Himori, Akihiko Yama … Show more authors

  Polymer Journala   57   513 - 526   2025.1  [Reviewed]

  DOI

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  Authorship：Last author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Single Work  

  Other Link： https://www.nature.com/articles/s41428-024-01001-9

• Three-dimensional radiation dosimetry of carbon ion beams using surfactant hydrogels: Fundamental investigation

  Toyohara, M; Kusano, Y; Kobayashi, N; Gotoh, H; Wada, S; Shimono, Y

  MEDICAL PHYSICS   52 ( 1 )   454 - 470   2025.1

  DOI Web of Science PubMed Repository

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  Language：English   Publishing type：Research paper (scientific journal)   Publisher：American Association of Physicists in Medicine   Joint Work  

• Elucidating the Origins of π-Facial Selectivity in Nucleophilic Reactions through Quantitative Evaluation of Electronic States

  Sakaguchi, D; Gotoh, H

  JOURNAL OF COMPUTER CHEMISTRY-JAPAN   24 ( 1 )   A18 - A24   2025

  DOI Web of Science

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  Language：Japanese   Publishing type：Research paper (scientific journal)   Joint Work  

• Three-dimensional radiation dosimetry of carbon ion beams using surfactant hydrogels: Fundamental investigation

  Toyohara Masumitsu, Kusano Yohsuke, Kobayashi Norihisa, Gotoh Hiroaki, Wada Satoshi

  Medical Physics   Early Access   2024.10

  CiNii Research

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  Language：English   Publishing type：Research paper (scientific journal)   Publisher：American Association of Physicists in Medicine   Joint Work  

  Background
  In carbon ion radiotherapy, accurate measurement of the three-dimensional (3D) absorbed dose distribution is critical for effectively targeting tumors. Although micellar gel dosimeters exhibit considerable potential for measuring 3D absorbed dose distributions, few studies have focused on radiotherapy using carbon ion beams.
  
  Purpose
  This study investigated the applicability of the surfactant hydrogel dosimeter (SHD), a micellar gel dosimeter, to measuring a 3D dose absorbed through carbon ion beam irradiation.
  
  Methods
  A cubic target region of 34 mm per side was established at a depth of 46 mm below the upper surface of an SHD specimen. Scanning irradiation was performed using a pencil beam of carbon ions at the Ion-beam Radiation Oncology Center in Kanagawa (“i-ROCK”), Japan, under irradiation conditions set by the treatment planning system (“Monaco for Carbon”, Ver. 5.20, Elekta AB, Sweden) to create a spread-out Bragg peak within the target. The physical dose was set to 10 Gy at the isocenter, situated at the center of the target. The SHD responsiveness was measured twice using optical computed tomography (CT) (“Vista 15”, Modus Medical Devices, Canada) for three irradiated specimens, and six types of measured optical attenuation coefficient (OAC) were obtained. To assess whether the OAC represented the absorbed dose expected in the treatment plan, we compared the relative distribution of the OAC and that of the absorbed dose. Relative fraction (RF) was used to measure the difference between the relative value of the OAC and that of the absorbed dose. Moreover, the distribution of OH radical (•OH) concentration obtained by Monte Carlo simulation (“PHITS” ver. 3.24 JAEA, Japan) and that of the OAC were compared.
  
  Results
  In the direction of beam travel, the relative distribution of the OAC was lower than that of the absorbed dose. This discrepancy could be attributed to a decrease in the concentration of •OH produced by irradiation owing to the recombination reaction, which does not accurately reflect the absorbed dose. By contrast, the distributions in the plane perpendicular to the beam travel were consistent. The RF increased from ± 3% to ± 13% along the beam travel direction. The small RF in the plane perpendicular to the beam travel could be attributed to the constant distribution of linear energy transfer, regardless of the irradiation position, and the generation of radicals proportionally to the absorbed dose. The increase in RF along the beam travel direction was ascribed to ring artifacts in the irradiated region.
  
  Conclusion
  The measurement of the absorbed dose distribution in the beam travel direction should be improved. The observed discrepancy is attributed to the reduced reactivity of the SHD due to a high liner energy transfer near the Bragg peak. However, the absorbed dose distribution can be effectively evaluated in the plane perpendicular to the direction of beam travel.

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Review Papers 【 display / non-display 】

Review Papers 【 display / non-display 】

• Substrate Scope in Organic Reactions: Comparison of Fingerprint-Based and Reactivity-Based Similarity Metrics

  Ichizawa, K; Nishii, T; Gotoh, H

  Journal of Chemical Information and Modeling   66 ( 7 )   3878 - 3891   2026.4

  DOI Web of Science PubMed

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  Language：The in addition, foreign language   Publishing type：Article, review, commentary, editorial, etc. (bulletin of university, research institution)   Joint Work  

• DPPH Measurement for Phenols and Prediction of Antioxidant Activity of Phenolic Compounds in Food

  Kato, R; Tada, C; Yamauchi, M; Matsumoto, Y; Gotoh, H

  Current Issues in Molecular Biology   48 ( 1 )   2025.12

  DOI Web of Science PubMed

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  Language：The in addition, foreign language   Publishing type：Article, review, commentary, editorial, etc. (bulletin of university, research institution)   Joint Work  

• Predicting Substrate Reactivity in Oxidative Homocoupling of Phenols Using Positive and Unlabeled Machine Learning

  Nishii, T; Ichizawa, K; Nagano, H; Mukai, H; Sakaguchi, D; Gotoh, H

  ACS Omega   10 ( 42 )   49805 - 49815   2025.10

  DOI Web of Science PubMed Repository

  　More details

  Language：The in addition, foreign language   Publishing type：Article, review, commentary, editorial, etc. (bulletin of university, research institution)   Publisher：American Chemical Society   Joint Work  

  A positive and unlabeled machine learning (PU learning) model was trained to predict substrate reactivity in the oxidative homocoupling of phenols under different conditions. We demonstrated its effectiveness by conducting validation using two descriptor sets: 28-dimensional descriptors considered to influence reactivity and extended-connectivity fingerprints. We performed parameter tuning of the model using our experimental data and determined that the optimized parameters provided excellent prediction accuracy for the existing experimental data, regardless of the reaction conditions. Furthermore, the prediction results obtained using 30 types of unlabeled data matched the experimental results for approximately 83.3–86.7% of substrates, and the prediction accuracy of the PU learning model was shown to be superior to that of a model trained with both positive and negative reactivity data. Because negative data are not required to train a PU learning model, it can be applied to reactions reported in many previous studies, informing the cost-effective synthesis of molecules based on model-predicted results.

• Analysis of Asymmetric Reduction of Ketones Using Three-Dimensional Electronic States

  Sakaguchi, D; Shimono, M; Gotoh, H

  The Journal of Physical Chemistry A   129 ( 39 )   8945 - 8958   2025.10

  DOI Web of Science PubMed

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  Language：The in addition, foreign language   Publishing type：Article, review, commentary, editorial, etc. (bulletin of university, research institution)   Joint Work  

• Kinetic and thermodynamic evaluation of antioxidant reactions: factors influencing the radical scavenging properties of phenolic compounds in foods

  Yamauchi, M; Kitamura, Y; Tada, C; Kato, R; Gotoh, H

  Journal of the Science of Food and Agriculture   105 ( 14 )   8186 - 8195   2025.7

  DOI Web of Science PubMed

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  Language：The in addition, foreign language   Publishing type：Article, review, commentary, editorial, etc. (bulletin of university, research institution)   Joint Work  

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Awards 【 display / non-display 】

Awards 【 display / non-display 】

• 優秀講演賞

  2024.12   第47回ケモインフォマティクス討論会 実行委員会   電子状態を評価する分子場解析法を用いたケトンの不斉還元反応のエナンチオ選択性の予測と解釈

  Individual or group name of awards：⚪坂口 大門, 下野 真輝, 五東 弘昭

Grant-in-Aid for Scientific Research 【 display / non-display 】

Grant-in-Aid for Scientific Research 【 display / non-display 】

• 抗酸化性を示す食品成分の解明と網羅的予測

  Grant number：24K08785  2024.4 - 2027.3

  Grant-in-Aid for Scientific Research(C)

  Investigator(s)：五東弘昭

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  Authorship：Principal investigator  Grant type：Competitive

• 重粒子線スキャニング照射のための3次元ゲル線量計の開発とその臨床応用

  Grant number：21K07696  2021.4 - 2024.3

  Grant-in-Aid for Scientific Research(C)

  Investigator(s)：五東弘昭

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  Authorship：Principal investigator  Grant type：Competitive

• 有機分子触媒を用いた環境に優しいラジカル的カップリング反応の開発

  Grant number：26810055  2014.4 - 2016.3

  科学研究費補助金  Grant-in-Aid for Young Scientists(B)

  Investigator(s)：五東弘昭

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  Grant type：Competitive

Presentations 【 display / non-display 】

Presentations 【 display / non-display 】

• Fusion of transition state analysis and data-driven approach for stereoselectivity prediction in asymmetric ketone reduction

  ○Daimon Sakaguchi, Masaki Shimono, Hiroaki Gotoh

  Pacifichem 2025 

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  Event date： 2025.12

  Language：English   Presentation type：Poster presentation  

• Fingerprint embeddings from molecular structures and descriptions by natural language processing and their evaluation of interpretability and extrapolability

  ○Matsumoto Yuto, Koide Yuya, Gotoh Hiroaki

  Pacifichem 2025 

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  Event date： 2025.12

  Language：English   Presentation type：Poster presentation  

• Analysis of Asymmetric Reduction of Ketones Using Three-Dimensional Electronic States

  ○Daimon Sakaguchi, Masaki Shimono, Hiroaki Gotoh

  第9回ケモインフォマティクス秋の学校 

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  Event date： 2025.11

  Language：English   Presentation type：Poster presentation  

• Fingerprint-Informed Doc2Vec for Activity Prediction and Interpretation

  ○Matsumoto Yuto, Koide Yuya, Gotoh Hiroaki

  第9回ケモインフォマティクス秋の学校 

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  Event date： 2025.11

  Language：English   Presentation type：Poster presentation  

• Compound Embeddings from Textual Data and. Fingerprints by Doc2Vec and Classification and. Interpretability Using Them

  ○Matsumoto Yuto, Koide Yuya, Gotoh Hiroaki

  CBI学会2025年大会 

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  Event date： 2025.10

  Language：English   Presentation type：Poster presentation  

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Preferred joint research theme 【 display / non-display 】

Preferred joint research theme 【 display / non-display 】

Charge of on-campus class subject 【 display / non-display 】

Charge of on-campus class subject 【 display / non-display 】

• 2026   Basic Laboratory for Chemistry, Chemical Engineering and Life Science 1

  College of Engineering Science

• 2026   Chemistry, Chemical Engineering and Life Science: Exercise A

  College of Engineering Science

• 2026   Basic and Practice of Artificial Intelligence

  College of Engineering Science

• 2026   Basis and Practice of Data Science

  College of Engineering Science

• 2026   化学データサイエンス

  College of Engineering Science

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Committee Memberships 【 display / non-display 】

Committee Memberships 【 display / non-display 】

• 日本化学会関東支部

  2018.3 - 2019.2  幹事

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  Committee type：Other 

Social Contribution(Extension lecture) 【 display / non-display 】

Social Contribution(Extension lecture) 【 display / non-display 】

• 第38回「化学クラブ研究発表会」コメンテーター・審査員

  Role(s)： Commentator

  日本化学会関東支部  2021.3

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  Audience： Junior high school students,　High school students

  Type：Volunteer

• 重粒子線がん治療装置の高度化に向けて産官学連携で共同研究を加速

  Role(s)： Official expert

  横浜国立大学研究・学術情報部 産学・地域連携課  YNUプレスリリース  2020.6

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  Audience： University students,　Graduate students,　Researchers,　General public,　Company,　Government agency,　Media

  Type：Newspaper, magazine

  横浜国立大学(国立大学法人）、神奈川県立病院機構(地方独立行政法人)、東芝エネルギーシステムズ(株)の3者で2017年度に共同研究講座を設立し研究を進め開発。2020年4月1日より契約更新しさらなる研究を開始した。研究期間は3年を予定。
  掲載：2020年6月11日
  【契約掲載されているWEBサイトの例】
  https://www.excite.co.jp/news/article/Prtimes_2020-06-12-32322-90/
  https://www.jaif.or.jp/journal/japan/3444.html