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  1. Book: Mammalian cell engineering

    Kojima, Ryosuke

    methods and protocols

    (Methods in molecular biology ; 2312 ; Springer protocols)

    2021  

    Author's details edited by Ryosuke Kojima
    Series title Methods in molecular biology ; 2312
    Springer protocols
    Collection
    Keywords Animal cell biotechnology ; Mammals/Cytology ; Genetic engineering
    Subject code 660.6
    Language English
    Size xi, 330 Seiten, Illustrationen, Diagramme, 26 cm
    Publisher Humana Press
    Publishing place New York, NY
    Publishing country United States
    Document type Book
    HBZ-ID HT020995493
    ISBN 978-1-0716-1440-2 ; 9781071614419 ; 1-0716-1440-1 ; 107161441X
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    Zs A 7042 -2312- verfügbar in Königswinter Königswinter

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  2. Article ; Online: Bridging endoscopic pancreatic stenting for disconnected pancreatic duct syndrome using a rendezvous technique from a walled-off necrosis cavity.

    Mukai, Shuntaro / Itoi, Takao / Sofuni, Atsushi / Tsuchiya, Takasyoshi / Tanaka, Reina / Tonozuka, Ryosuke / Kojima, Hiroyuki

    Endoscopy

    2024  Volume 56, Issue S 01, Page(s) E29–E30

    MeSH term(s) Humans ; Pancreas ; Abdomen ; Endoscopy ; Pancreatic Ducts/surgery
    Language English
    Publishing date 2024-01-09
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 80120-3
    ISSN 1438-8812 ; 0013-726X
    ISSN (online) 1438-8812
    ISSN 0013-726X
    DOI 10.1055/a-2219-2672
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 669: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MO 162: Show issues

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  3. Article ; Online: Functional vagal paraganglioma developing 15 years after resection of a retroperitoneal paraganglioma.

    Kojima, Fumiya / Ohno, Kazuchika / Fushimi, Naoki / Takahashi, Ryosuke / Tasaki, Akihisa / Asakage, Takahiro

    Auris, nasus, larynx

    2024  Volume 51, Issue 3, Page(s) 425–428

    Abstract: The patient, a 40-year-old woman, was diagnosed as having a functional right vagal paraganglioma (PGL) 15 years after undergoing resection for a retroperitoneal PGL. ...

    Abstract The patient, a 40-year-old woman, was diagnosed as having a functional right vagal paraganglioma (PGL) 15 years after undergoing resection for a retroperitoneal PGL.
    Language English
    Publishing date 2024-03-22
    Publishing country Netherlands
    Document type Case Reports
    ZDB-ID 604552-2
    ISSN 1879-1476 ; 0385-8146
    ISSN (online) 1879-1476
    ISSN 0385-8146
    DOI 10.1016/j.anl.2023.12.002
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    ab Jg. 2022: Lesesaal (EG)

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  4. Article ; Online: Network-based prediction approach for cancer-specific driver missense mutations using a graph neural network.

    Hatano, Narumi / Kamada, Mayumi / Kojima, Ryosuke / Okuno, Yasushi

    BMC bioinformatics

    2023  Volume 24, Issue 1, Page(s) 383

    Abstract: Background: In cancer genomic medicine, finding driver mutations involved in cancer development and tumor growth is crucial. Machine-learning methods to predict driver missense mutations have been developed because variants are frequently detected by ... ...

    Abstract Background: In cancer genomic medicine, finding driver mutations involved in cancer development and tumor growth is crucial. Machine-learning methods to predict driver missense mutations have been developed because variants are frequently detected by genomic sequencing. However, even though the abnormalities in molecular networks are associated with cancer, many of these methods focus on individual variants and do not consider molecular networks. Here we propose a new network-based method, Net-DMPred, to predict driver missense mutations considering molecular networks. Net-DMPred consists of the graph part and the prediction part. In the graph part, molecular networks are learned by a graph neural network (GNN). The prediction part learns whether variants are driver variants using features of individual variants combined with the graph features learned in the graph part.
    Results: Net-DMPred, which considers molecular networks, performed better than conventional methods. Furthermore, the prediction performance differed by the molecular network structure used in learning, suggesting that it is important to consider not only the local network related to cancer but also the large-scale network in living organisms.
    Conclusions: We propose a network-based machine learning method, Net-DMPred, for predicting cancer driver missense mutations. Our method enables us to consider the entire graph architecture representing the molecular network because it uses GNN. Net-DMPred is expected to detect driver mutations from a lot of missense mutations that are not known to be associated with cancer.
    MeSH term(s) Humans ; Mutation, Missense ; Neural Networks, Computer ; Neoplasms/genetics ; Machine Learning
    Language English
    Publishing date 2023-10-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-023-05507-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book ; Online: ReactionT5

    Sagawa, Tatsuya / Kojima, Ryosuke

    a large-scale pre-trained model towards application of limited reaction data

    2023  

    Abstract: Transformer-based deep neural networks have revolutionized the field of molecular-related prediction tasks by treating molecules as symbolic sequences. These models have been successfully applied in various organic chemical applications by pretraining ... ...

    Abstract Transformer-based deep neural networks have revolutionized the field of molecular-related prediction tasks by treating molecules as symbolic sequences. These models have been successfully applied in various organic chemical applications by pretraining them with extensive compound libraries and subsequently fine-tuning them with smaller in-house datasets for specific tasks. However, many conventional methods primarily focus on single molecules, with limited exploration of pretraining for reactions involving multiple molecules. In this paper, we propose ReactionT5, a novel model that leverages pretraining on the Open Reaction Database (ORD), a publicly available large-scale resource. We further fine-tune this model for yield prediction and product prediction tasks, demonstrating its impressive performance even with limited fine-tuning data compared to traditional models. The pre-trained ReactionT5 model is publicly accessible on the Hugging Face platform.
    Keywords Physics - Chemical Physics ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2023-11-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Network-based prediction approach for cancer-specific driver missense mutations using a graph neural network

    Narumi Hatano / Mayumi Kamada / Ryosuke Kojima / Yasushi Okuno

    BMC Bioinformatics, Vol 24, Iss 1, Pp 1-

    2023  Volume 15

    Abstract: Abstract Background In cancer genomic medicine, finding driver mutations involved in cancer development and tumor growth is crucial. Machine-learning methods to predict driver missense mutations have been developed because variants are frequently ... ...

    Abstract Abstract Background In cancer genomic medicine, finding driver mutations involved in cancer development and tumor growth is crucial. Machine-learning methods to predict driver missense mutations have been developed because variants are frequently detected by genomic sequencing. However, even though the abnormalities in molecular networks are associated with cancer, many of these methods focus on individual variants and do not consider molecular networks. Here we propose a new network-based method, Net-DMPred, to predict driver missense mutations considering molecular networks. Net-DMPred consists of the graph part and the prediction part. In the graph part, molecular networks are learned by a graph neural network (GNN). The prediction part learns whether variants are driver variants using features of individual variants combined with the graph features learned in the graph part. Results Net-DMPred, which considers molecular networks, performed better than conventional methods. Furthermore, the prediction performance differed by the molecular network structure used in learning, suggesting that it is important to consider not only the local network related to cancer but also the large-scale network in living organisms. Conclusions We propose a network-based machine learning method, Net-DMPred, for predicting cancer driver missense mutations. Our method enables us to consider the entire graph architecture representing the molecular network because it uses GNN. Net-DMPred is expected to detect driver mutations from a lot of missense mutations that are not known to be associated with cancer.
    Keywords Driver mutation prediction ; Cancer missense mutation ; Graph neural network ; Molecular interaction ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
    Subject code 006
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Intracellular Unnatural Catalysis Enabled by an Artificial Metalloenzyme.

    Okamoto, Yasunori / Kojima, Ryosuke

    Methods in molecular biology (Clifton, N.J.)

    2021  Volume 2312, Page(s) 287–300

    Abstract: Artificial metalloenzymes, constructed by incorporating a synthetic catalyst into the internal spaces of a protein scaffold, can perform noncanonical chemical transformations that are not possible using natural enzymes. The addition of cell-permeable ... ...

    Abstract Artificial metalloenzymes, constructed by incorporating a synthetic catalyst into the internal spaces of a protein scaffold, can perform noncanonical chemical transformations that are not possible using natural enzymes. The addition of cell-permeable modules to artificial metalloenzymes allows for noncanonical catalysis to be implemented as a function of mammalian cells. In this chapter, we describe a protocol for controlling cellular function through a cascade consisting of an artificial metalloenzyme and a gene-circuit engineered via synthetic biology.
    MeSH term(s) Biotin/chemistry ; Catalysis ; Cell Culture Techniques ; Cell Engineering ; Enzymes/genetics ; Enzymes/metabolism ; Gene Expression Regulation, Enzymologic ; HEK293 Cells ; Humans ; Metalloproteins/genetics ; Metalloproteins/metabolism ; Protein Engineering ; Streptavidin/chemistry ; Substrate Specificity ; Synthetic Biology ; Transfection
    Chemical Substances Enzymes ; Metalloproteins ; Biotin (6SO6U10H04) ; Streptavidin (9013-20-1)
    Language English
    Publishing date 2021-07-06
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-1441-9_17
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: A migrated novel biliary stent penetrating the duodenal wall in a patient with ampullary adenoma after endoscopic papillectomy.

    Yamamoto, Kenjiro / Tsuchiya, Takayoshi / Tonozuka, Ryosuke / Kojima, Hiroyuki / Minami, Hirohito / Nakatsubo, Ryosuke / Itoi, Takao

    Journal of hepato-biliary-pancreatic sciences

    2022  Volume 30, Issue 8, Page(s) e56–e57

    MeSH term(s) Humans ; Ampulla of Vater/diagnostic imaging ; Ampulla of Vater/surgery ; Endoscopy ; Adenoma/diagnostic imaging ; Adenoma/surgery ; Stents ; Common Bile Duct Neoplasms/diagnostic imaging ; Common Bile Duct Neoplasms/surgery ; Treatment Outcome ; Retrospective Studies ; Sphincterotomy, Endoscopic
    Language English
    Publishing date 2022-11-15
    Publishing country Japan
    Document type Case Reports ; Research Support, Non-U.S. Gov't
    ZDB-ID 2536236-7
    ISSN 1868-6982 ; 1868-6974
    ISSN (online) 1868-6982
    ISSN 1868-6974
    DOI 10.1002/jhbp.1264
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4024: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  9. Article ; Online: Foraging predicts the evolution of warning coloration and mimicry in snakes.

    Kojima, Yosuke / Ito, Ryosuke K / Fukuyama, Ibuki / Ohkubo, Yusaku / Durso, Andrew M

    Proceedings of the National Academy of Sciences of the United States of America

    2024  Volume 121, Issue 11, Page(s) e2318857121

    Abstract: Warning coloration and Batesian mimicry are classic examples of Darwinian evolution, but empirical evolutionary patterns are often paradoxical. We test whether foraging costs predict the evolution of striking coloration by integrating genetic and ... ...

    Abstract Warning coloration and Batesian mimicry are classic examples of Darwinian evolution, but empirical evolutionary patterns are often paradoxical. We test whether foraging costs predict the evolution of striking coloration by integrating genetic and ecological data for aposematic and mimetic snakes (Elapidae and Dipsadidae). Our phylogenetic comparison on a total of 432 species demonstrated that dramatic changes in coloration were well predicted by foraging strategy. Multiple tests consistently indicated that warning coloration and conspicuous mimicry were more likely to evolve in species where foraging costs of conspicuous appearance were relaxed by poor vision of their prey, concealed habitat, or nocturnal activity. Reversion to crypsis was also well predicted by ecology for elapids but not for dipsadids. In contrast to a theoretical prediction and general trends, snakes' conspicuous coloration was correlated with secretive ecology, suggesting that a selection regime underlies evolutionary patterns. We also found evidence that mimicry of inconspicuous models (pitvipers) may have evolved in association with foraging demand for crypsis. These findings demonstrate that foraging is an important factor necessary to understand the evolution, persistence, and diversity of warning coloration and mimicry of snakes, highlighting the significance of additional selective factors in solving the warning coloration paradox.
    MeSH term(s) Humans ; Phylogeny ; Biological Mimicry ; Vision, Low
    Language English
    Publishing date 2024-03-04
    Publishing country United States
    Document type Journal Article
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.2318857121
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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  10. Article ; Online: A novel technique for one-step dilation followed by bile aspiration using an ultra-tapered bougie dilator with side holes to minimize bile leakage during EUS-guided hepaticogastrostomy.

    Mukai, Shuntaro / Itoi, Takao / Tsuchiya, Takayoshi / Tanaka, Reina / Tonozuka, Ryosuke / Yamamoto, Kenjiro / Nagai, Kazumasa / Matsunami, Yukitoshi / Kojima, Hiroyuki / Sofuni, Atsushi

    Journal of hepato-biliary-pancreatic sciences

    2024  

    Language English
    Publishing date 2024-01-08
    Publishing country Japan
    Document type Case Reports
    ZDB-ID 2536236-7
    ISSN 1868-6982 ; 1868-6974
    ISSN (online) 1868-6982
    ISSN 1868-6974
    DOI 10.1002/jhbp.1413
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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