Hiroi, Noriko



Graduate School of Media and Governance (Shonan Fujisawa)


Project Professor (Non-tenured)

Related Websites


Noriko F. Hiroi

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  • "Fate of cells dependent on intracellular inhomogeneity." My research target is mainly the phenomena happen in cellular level. Especially I am interested in what can induce localisation of signalling molecules and distribute their reaction rate, as a result, cellular shapes vary and affect their functions, fates, and the interaction manner with the other cells. I set 4 pillars for the above research object. I may classify them into 2 groups. One is about the behaviours of mobile molecules, the other is about the spatial characteristics of the intracellular space itself. The first class consists of 2 topics; the origin of force for molecular localisation, and the role of localised signalling molecules. The latter class consists of also 2 topics; the distribution of reaction rate - this is about the inhomogeneity toward the time axis of the target variable, and the last one is the distribution of reaction space - the inhomogeneity toward x-y-z axes. The total perspective is as follows. Intracellular space is inhomogeneous toward x-y-z and t. The characteristics as a reaction space does affect to the origin of force to localise signalling molecules, and bring differentiated phenotypes of the cells. Now the history of a cell is, starting from symmetry division to differentiated cells via asymmetry division, it equals to start one's life from simple proliferation and to develop with differentiating one's cellular roles to organise a multicellular individual.

Academic Background 【 Display / hide

  • 1998.04

    The University of Tokyo, Department of Medical Science, Molecular cellular Biology

    Japan, Graduate School, Completed, Doctoral course

Academic Degrees 【 Display / hide

  • 博士(医学), 東京大学, Coursework, 2002.03

    A conserved role for mammalian Rcd1 in cell differentiation


Research Areas 【 Display / hide

  • System genome science


Books 【 Display / hide

  • Kinetics of Dimension Restricted Condition

    HIROI Noriko and Akira Funahashi, Humana Press, NJ USA, 2007.07

    Scope: Chapter 14 of Introduction to Systems Biology

  • アポトーシス実験プロトコール

    HIROI Noriko, Hideharu Maruta, 秀潤社, 1999.03

Papers 【 Display / hide

  • 3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis

    Tokuoka Y., Yamada T.G., Mashiko D., Ikeda Z., Hiroi N.F., Kobayashi T.J., Yamagata K., Funahashi A.

    npj Systems Biology and Applications (npj Systems Biology and Applications)  6 ( 1 )  2020.12

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    During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To acquire quantitative criteria of embryogenesis from time-series 3D microscopic images, image processing algorithms such as segmentation have been applied. Because the cells in embryos are considerably crowded, an algorithm to segment individual cells in detail and accurately is needed. To quantify the nuclear region of every cell from a time-series 3D fluorescence microscopic image of living cells, we developed QCANet, a convolutional neural network-based segmentation algorithm for 3D fluorescence bioimages. We demonstrated that QCANet outperformed 3D Mask R-CNN, which is currently considered as the best algorithm of instance segmentation. We showed that QCANet can be applied not only to developing mouse embryos but also to developing embryos of two other model species. Using QCANet, we were able to extract several quantitative criteria of embryogenesis from 11 early mouse embryos. We showed that the extracted criteria could be used to evaluate the differences between individual embryos. This study contributes to the development of fundamental approaches for assessing embryogenesis on the basis of extracted quantitative criteria.

  • Cellular thermogenesis compensates environmental temperature fluctuations for maintaining intracellular temperature

    Yamanaka R., Shindo Y., Hotta K., Hiroi N., Oka K.

    Biochemical and Biophysical Research Communications (Biochemical and Biophysical Research Communications)  533 ( 1 ) 70 - 76 2020.11

    ISSN  0006291X

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    Temperature governs states and dynamics of all biological molecules, and several cellular processes are often heat sources and/or sinks. Technical achievement of intracellular thermometry enables us to measure intracellular temperature, and it can offer novel perspectives in biology and medicine. However, little is known that changes of intracellular temperature throughout the cell-cycle and the manner of which cells regulates their thermogenesis in response to fluctuation of the environmental temperature. Here, cell-cycle-dependent changes of intracellular temperature were reconstructed from the snapshots of cell population at single-cell resolution using ergodic analysis for asynchronously cultured HeLa cells expressing a genetically encoded thermometry. Intracellular temperature is highest at G1 phase, and it gradually decreases along cell-cycle progression and increases abruptly during mitosis. Cells easily heated up are harder to cool down and vice versa, especially at G1/S phases. Together, intracellular thermogenesis depends on cell-cycle phases and it maintains intracellular temperature through compensating environmental temperature fluctuations.

  • Identification of a master transcription factor and a regulatory mechanism for desiccation tolerance in the anhydrobiotic cell line Pv11

    Yamada T.G., Hiki Y., Hiroi N.F., Shagimardanova E., Gusev O., Cornette R., Kikawada T., Funahashi A.

    PLoS ONE (PLoS ONE)  15 ( 3 )  2020.03

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    Water is essential for living organisms. Terrestrial organisms are incessantly exposed to the stress of losing water, desiccation stress. Avoiding the mortality caused by desiccation stress, many organisms acquired molecular mechanisms to tolerate desiccation. Larvae of the African midge, Polypedilum vanderplanki, and its embryonic cell line Pv11 tolerate desiccation stress by entering an ametabolic state, anhydrobiosis, and return to active life after rehydration. The genes related to desiccation tolerance have been comprehensively analyzed, but transcriptional regulatory mechanisms to induce these genes after desiccation or rehydration remain unclear. Here, we comprehensively analyzed the gene regulatory network in Pv11 cells and compared it with that of Drosophila melanogaster, a desiccation sensitive species. We demonstrated that nuclear transcription factor Y subunit gamma-like, which is important for drought stress tolerance in plants, and its transcriptional regulation of downstream positive feedback loops have a pivotal role in regulating various anhydrobiosis-related genes. This study provides an initial insight into the systemic mechanism of desiccation tolerance.

  • Neural differentiation dynamics controlled by multiple feedback loops in a comprehensive molecular interaction network

    Iwasaki T., Takiguchi R., Hiraiwa T., Yamada T.G., Yamazaki K., Hiroi N.F., Funahashi A.

    Processes (Processes)  8 ( 2 )  2020.02

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    Mathematical model simulation is a useful method for understanding the complex behavior of a living system. The construction of mathematical models using comprehensive information is one of the techniques of model construction. Such a comprehensive knowledge-based network tends to become a large-scale network. As a result, the variation of analyses is limited to a particular kind of analysis because of the size and complexity of the model. To analyze a large-scale regulatory network of neural differentiation, we propose a contractive method that preserves the dynamic behavior of a large network. The method consists of the following two steps: comprehensive network building and network reduction. The reduction phase can extract network loop structures from a large-scale regulatory network, and the subnetworks were combined to preserve the dynamics of the original large-scale network. We confirmed that the extracted loop combination reproduced the known dynamics of HES1 and ASCL1 before and after differentiation, including oscillation and equilibrium of their concentrations. The model also reproduced the effects of the overexpression and knockdown of the Id2 gene. Our model suggests that the characteristic change in HES1 and ASCL1 expression in the large-scale regulatory network is controlled by a combination of four feedback loops, including a large loop, which has not been focused on. The model extracted by our method has the potential to reveal the critical mechanisms of neural differentiation. The method is applicable to other biological events.

  • Deep learning for non-invasive determination of the differentiation status of human neuronal cells by using phase-contrast photomicrographs

    Ooka M., Tokuoka Y., Nishimoto S., Hiroi N., Yamada T., Funahashi A.

    Applied Sciences (Switzerland) (Applied Sciences (Switzerland))  9 ( 24 )  2019.12

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    Regenerative medicine using neural stem cells (NSCs), which self-renew and have pluripotency, has recently attracted a lot of interest. Much research has focused on the transplantation of differentiated NSCs to damaged tissues for the treatment of various neurodegenerative diseases and spinal cord injuries. However, current approaches for distinguishing differentiated from non-differentiated NSCs at the single-cell level have low reproducibility or are invasive to the cells. Here, we developed a fully automated, non-invasive convolutional neural network-based model to determine the differentiation status of human NSCs at the single-cell level from phase-contrast photomicrographs; after training, our model showed an accuracy of identification greater than 94%. To understand how our model distinguished between differentiated and non-differentiated NSCs, we evaluated the informative features it learned for the two cell types and found that it had learned several biologically relevant features related to NSC shape during differentiation. We also used our model to examine the differentiation of NSCs over time; the findings confirmed our model's ability to distinguish between non-differentiated and differentiated NSCs. Thus, our model was able to non-invasively and quantitatively identify differentiated NSCs with high accuracy and reproducibility, and, therefore, could be an ideal means of identifying differentiated NSCs in the clinic.

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Papers, etc., Registered in KOARA 【 Display / hide

Awards 【 Display / hide

  • コニカミノルタ画像科学奨励賞

    広井賀子, 2014.03, コニカミノルタ科学技術振興財団, 細胞内構造三次元再構成に向けた高精度測定システムの開発