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  1. Article: Three-year update outcomes of the first chimeric antigen receptor-T therapy for children and young adults with relapsed/refractory acute lymphoblastic leukemia.

    Nakayama, Hideki

    Translational pediatrics

    2024  Volume 13, Issue 4, Page(s) 535–536

    Language English
    Publishing date 2024-04-08
    Publishing country China
    Document type Editorial ; Comment
    ZDB-ID 2901309-4
    ISSN 2224-4344 ; 2224-4344 ; 2224-4336
    ISSN (online) 2224-4344
    ISSN 2224-4344 ; 2224-4336
    DOI 10.21037/tp-23-535
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Late surgical intervention after childhood cancer treatment.

    Nakayama, Hideki

    Translational pediatrics

    2023  Volume 12, Issue 12, Page(s) 2093–2094

    Language English
    Publishing date 2023-12-22
    Publishing country China
    Document type Editorial ; Comment
    ZDB-ID 2901309-4
    ISSN 2224-4344 ; 2224-4344 ; 2224-4336
    ISSN (online) 2224-4344
    ISSN 2224-4344 ; 2224-4336
    DOI 10.21037/tp-23-367
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online: Pixel to Binary Embedding Towards Robustness for CNNs

    Kishida, Ikki / Nakayama, Hideki

    2022  

    Abstract: There are several problems with the robustness of Convolutional Neural Networks (CNNs). For example, the prediction of CNNs can be changed by adding a small magnitude of noise to an input, and the performances of CNNs are degraded when the distribution ... ...

    Abstract There are several problems with the robustness of Convolutional Neural Networks (CNNs). For example, the prediction of CNNs can be changed by adding a small magnitude of noise to an input, and the performances of CNNs are degraded when the distribution of input is shifted by a transformation never seen during training (e.g., the blur effect). There are approaches to replace pixel values with binary embeddings to tackle the problem of adversarial perturbations, which successfully improve robustness. In this work, we propose Pixel to Binary Embedding (P2BE) to improve the robustness of CNNs. P2BE is a learnable binary embedding method as opposed to previous hand-coded binary embedding methods. P2BE outperforms other binary embedding methods in robustness against adversarial perturbations and visual corruptions that are not shown during training.

    Comment: Accepted to ICPR2022
    Keywords Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2022-06-13
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Metabolic engineering of high-salinity-induced biosynthesis of γ-aminobutyric acid improves salt-stress tolerance in a glutamic acid-overproducing mutant of an ectoine-deficient

    Zou, Ziyan / Kaothien-Nakayama, Pulla / Ogawa-Iwamura, Junpei / Nakayama, Hideki

    Applied and environmental microbiology

    2023  Volume 90, Issue 1, Page(s) e0190523

    Abstract: A moderately halophilic eubacterium, ...

    Abstract A moderately halophilic eubacterium,
    MeSH term(s) Salt Tolerance ; Glutamic Acid/metabolism ; Halomonas/genetics ; Metabolic Engineering ; Salinity ; Sodium Chloride/metabolism ; Amino Acids, Diamino ; Carbon/metabolism ; Nitrogen/metabolism ; gamma-Aminobutyric Acid/metabolism
    Chemical Substances ectoine (7GXZ3858RY) ; Glutamic Acid (3KX376GY7L) ; Sodium Chloride (451W47IQ8X) ; Amino Acids, Diamino ; Carbon (7440-44-0) ; Nitrogen (N762921K75) ; gamma-Aminobutyric Acid (56-12-2)
    Language English
    Publishing date 2023-12-19
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 223011-2
    ISSN 1098-5336 ; 0099-2240
    ISSN (online) 1098-5336
    ISSN 0099-2240
    DOI 10.1128/aem.01905-23
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.B 201: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: E3 Ubiquitin Ligase Riplet Is Expressed in T Cells and Suppresses T Cell-Mediated Antitumor Immune Responses.

    Iwamoto, Asuka / Tsukamoto, Hirotake / Nakayama, Hideki / Oshiumi, Hiroyuki

    Journal of immunology (Baltimore, Md. : 1950)

    2022  Volume 208, Issue 8, Page(s) 2067–2076

    Abstract: The E3 ubiquitin ligase Riplet mediates retinoic acid-inducible gene-I polyubiquitination and is essential for viral-induced expression of type I IFNs in dendritic cells and macrophages. The function of Riplet in innate immunity has been well ... ...

    Abstract The E3 ubiquitin ligase Riplet mediates retinoic acid-inducible gene-I polyubiquitination and is essential for viral-induced expression of type I IFNs in dendritic cells and macrophages. The function of Riplet in innate immunity has been well demonstrated; however, its role in adaptive immunity during the antitumor immune response is unclear. In this study, we examined the role of Riplet in the T cell-mediated antitumor immune response. Riplet was expressed in T cells and upregulated in CD8
    MeSH term(s) Adaptive Immunity/immunology ; Animals ; CD8-Positive T-Lymphocytes/immunology ; Dendritic Cells ; Immunity, Innate/immunology ; Mice ; Mice, Inbred C57BL ; Mice, Knockout ; T-Lymphocytes/immunology ; T-Lymphocytes, Cytotoxic/immunology ; Th1 Cells/immunology ; Ubiquitin-Protein Ligases/biosynthesis ; Ubiquitin-Protein Ligases/immunology
    Chemical Substances Rnf135 protein, mouse (EC 2.3.2.27) ; Ubiquitin-Protein Ligases (EC 2.3.2.27)
    Language English
    Publishing date 2022-04-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 3056-9
    ISSN 1550-6606 ; 0022-1767 ; 1048-3233 ; 1047-7381
    ISSN (online) 1550-6606
    ISSN 0022-1767 ; 1048-3233 ; 1047-7381
    DOI 10.4049/jimmunol.2100096
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    Ud II Zs.37: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)
    Zs.MG 28: Show issues

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  6. Article ; Online: Radiation Therapy Oncology Group 8502 "QUAD shot" regimen using volumetric modulated arc therapy for incurable head and neck cancer.

    Toya, Ryo / Fukugawa, Yoshiyuki / Saito, Tetsuo / Matsuyama, Tomohiko / Yoshida, Ryoji / Murakami, Daizo / Orita, Yorihisa / Nakayama, Hideki / Oya, Natsuo

    Oral oncology

    2024  Volume 151, Page(s) 106752

    Abstract: Objectives: We aimed to evaluate the outcomes of the Radiation Therapy Oncology Group 8502 "QUAD shot" regimen using volumetric modulated arc therapy (VMAT) for incurable head and neck cancer (HNC).: Materials and methods: We included 105 patients ... ...

    Abstract Objectives: We aimed to evaluate the outcomes of the Radiation Therapy Oncology Group 8502 "QUAD shot" regimen using volumetric modulated arc therapy (VMAT) for incurable head and neck cancer (HNC).
    Materials and methods: We included 105 patients with HNC in the study, undergoing at least one QUAD shot regimen cycle. We planned the radiotherapy using VMAT with 6 MV photons. One QUAD shot cycle included 14.8 Gy in 4 fractions with at least 6-hour intervals over 2 consecutive days, repeated every 3-6 weeks up to 3 cycles.
    Results: We completed 1, 2, and 3 cycles in 11 (10 %), 17 (16 %), and 77 (73 %) patients, respectively. We concurrently performed systemic therapy in 13 (12 %) patients. Tumor response was observed in 92 (88 %) patients and at least one symptom relief in 51 (71 %) of 72 patients. We observed an overall response (tumor response or symptom relief) in 98 (93 %) patients with all patients who completed 3 cycles achieving it. The median overall survival (OS) was 6.8 months. Our multivariate analysis revealed that non-squamous cell carcinoma (p < 0.001), T category of 0-2 (p = 0.021), and 3 QUAD shot cycles (p < 0.001) were independent prognostic factors of better OS. We observed Grade 3 toxicity in 2 (2 %) patients while no ≥ Grade 4 acute or ≥ Grade 3 late toxicity.
    Conclusions: The QUAD shot regimen using VMAT exerts appropriate palliative effect in patients with incurable HNC. Treatment with higher QUAD shot cycle number would be recommended for better treatment outcomes.
    MeSH term(s) Humans ; Radiotherapy, Intensity-Modulated/adverse effects ; Head and Neck Neoplasms/radiotherapy ; Head and Neck Neoplasms/etiology ; Treatment Outcome ; Radiotherapy Dosage ; Dose Fractionation, Radiation ; Radiotherapy Planning, Computer-Assisted
    Language English
    Publishing date 2024-03-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 1120465-5
    ISSN 1879-0593 ; 0964-1955 ; 1368-8375
    ISSN (online) 1879-0593
    ISSN 0964-1955 ; 1368-8375
    DOI 10.1016/j.oraloncology.2024.106752
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4869: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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    Zs.A 456: 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)

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  7. Book ; Online: Balancing Reconstruction and Editing Quality of GAN Inversion for Real Image Editing with StyleGAN Prior Latent Space

    Katsumata, Kai / Vo, Duc Minh / Liu, Bei / Nakayama, Hideki

    2023  

    Abstract: The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quality remains an open problem. In this study, we revisit StyleGANs' ... ...

    Abstract The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quality remains an open problem. In this study, we revisit StyleGANs' hyperspherical prior $\mathcal{Z}$ and $\mathcal{Z}^+$ and integrate them into seminal GAN inversion methods to improve editing quality. Besides faithful reconstruction, our extensions achieve sophisticated editing quality with the aid of the StyleGAN prior. We project the real images into the proposed space to obtain the inverted codes, by which we then move along $\mathcal{Z}^{+}$, enabling semantic editing without sacrificing image quality. Comprehensive experiments show that $\mathcal{Z}^{+}$ can replace the most commonly-used $\mathcal{W}$, $\mathcal{W}^{+}$, and $\mathcal{S}$ spaces while preserving reconstruction quality, resulting in reduced distortion of edited images.

    Comment: 5 pages, 9 figures, AI4CC Workshop at CVPR 2023
    Keywords Computer Science - Computer Vision and Pattern Recognition
    Subject code 004
    Publishing date 2023-05-31
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: A-CAP

    Vo, Duc Minh / Luong, Quoc-An / Sugimoto, Akihiro / Nakayama, Hideki

    Anticipation Captioning with Commonsense Knowledge

    2023  

    Abstract: Humans possess the capacity to reason about the future based on a sparse collection of visual cues acquired over time. In order to emulate this ability, we introduce a novel task called Anticipation Captioning, which generates a caption for an unseen ... ...

    Abstract Humans possess the capacity to reason about the future based on a sparse collection of visual cues acquired over time. In order to emulate this ability, we introduce a novel task called Anticipation Captioning, which generates a caption for an unseen oracle image using a sparsely temporally-ordered set of images. To tackle this new task, we propose a model called A-CAP, which incorporates commonsense knowledge into a pre-trained vision-language model, allowing it to anticipate the caption. Through both qualitative and quantitative evaluations on a customized visual storytelling dataset, A-CAP outperforms other image captioning methods and establishes a strong baseline for anticipation captioning. We also address the challenges inherent in this task.

    Comment: Accepted to CVPR 2023
    Keywords Computer Science - Computer Vision and Pattern Recognition
    Publishing date 2023-04-13
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Book ; Online: Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data

    Katsumata, Kai / Vo, Duc Minh / Harada, Tatsuya / Nakayama, Hideki

    2023  

    Abstract: Label-noise or curated unlabeled data is used to compensate for the assumption of clean labeled data in training the conditional generative adversarial network; however, satisfying such an extended assumption is occasionally laborious or impractical. As ... ...

    Abstract Label-noise or curated unlabeled data is used to compensate for the assumption of clean labeled data in training the conditional generative adversarial network; however, satisfying such an extended assumption is occasionally laborious or impractical. As a step towards generative modeling accessible to everyone, we introduce a novel conditional image generation framework that accepts noisy-labeled and uncurated unlabeled data during training: (i) closed-set and open-set label noise in labeled data and (ii) closed-set and open-set unlabeled data. To combat it, we propose soft curriculum learning, which assigns instance-wise weights for adversarial training while assigning new labels for unlabeled data and correcting wrong labels for labeled data. Unlike popular curriculum learning, which uses a threshold to pick the training samples, our soft curriculum controls the effect of each training instance by using the weights predicted by the auxiliary classifier, resulting in the preservation of useful samples while ignoring harmful ones. Our experiments show that our approach outperforms existing semi-supervised and label-noise robust methods in terms of both quantitative and qualitative performance. In particular, the proposed approach is able to match the performance of (semi-) supervised GANs even with less than half the labeled data.

    Comment: 10 pages, 13 figures
    Keywords Computer Science - Computer Vision and Pattern Recognition
    Subject code 006
    Publishing date 2023-07-17
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book ; Online: Revisiting Latent Space of GAN Inversion for Real Image Editing

    Katsumata, Kai / Vo, Duc Minh / Liu, Bei / Nakayama, Hideki

    2023  

    Abstract: The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quality remains an open problem. In this study, we revisit StyleGANs' ... ...

    Abstract The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quality remains an open problem. In this study, we revisit StyleGANs' hyperspherical prior $\mathcal{Z}$ and combine it with highly capable latent spaces to build combined spaces that faithfully invert real images while maintaining the quality of edited images. More specifically, we propose $\mathcal{F}/\mathcal{Z}^{+}$ space consisting of two subspaces: $\mathcal{F}$ space of an intermediate feature map of StyleGANs enabling faithful reconstruction and $\mathcal{Z}^{+}$ space of an extended StyleGAN prior supporting high editing quality. We project the real images into the proposed space to obtain the inverted codes, by which we then move along $\mathcal{Z}^{+}$, enabling semantic editing without sacrificing image quality. Comprehensive experiments show that $\mathcal{Z}^{+}$ can replace the most commonly-used $\mathcal{W}$, $\mathcal{W}^{+}$, and $\mathcal{S}$ spaces while preserving reconstruction quality, resulting in reduced distortion of edited images.

    Comment: 10 pages, 12 figures. arXiv admin note: substantial text overlap with arXiv:2306.00241
    Keywords Computer Science - Computer Vision and Pattern Recognition
    Publishing date 2023-07-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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