Mizutani Laboratory

Dept of Bioengineering, Tokai University

Home - Movies/3D models - Publications - Schizophrenia AIjump - MCTracejump - RecViewjump - 3D test patterns - Japanese

Interests

Our research in collaboration with SPring-8/JASRI and Advanced Photon Source (APS) of Argonne National Laboratory involves a number of studies. We have performed X-ray microtomographic (micro-CT) and nanotomographic (nano-CT) analyses of biological soft tissues, including human, mouse, and fruit fly brains. Cellular and subcellular structures, such as neurons, neurites, and dendritic spines have been visualized at micrometer to nanometer resolution using synchrotron radiation X-ray sources. More details are...

HumanNeurons Human mentality develops with age and is altered in psychiatric disorders, though their underlying mechanism is unknown. We analyzed nanometer-scale three-dimensional structures of brain tissues of the anterior cingulate cortex from eight schizophrenia and eight control cases. The distribution profiles of neurite curvature of the control cases showed a trend depending on their age, resulting in an age-correlated decrease in the standard deviation of neurite curvature (Pearson's r = -0.80, p = 0.018). In contrast to the control cases, the schizophrenia cases deviate upward from this correlation, exhibiting a 60% higher neurite curvature compared with the controls (p = 0.00078). The neurite curvature also showed a correlation with a hallucination score (Pearson's r = 0.80, p = 0.00018), indicating that neurite structure is relevant to brain function. This study is based on our 3D analysis of human brain tissues over a decade and is unprecedented in terms of the number of cases. We suggest that neurite curvature plays a pivotal role in brain aging and can be used as a hallmark to exploit a novel treatment of schizophrenia. Original paper. Our related study ( Transl.Psychiatry 2019 2021 ) was news released from Argonne National Lab and widely mentioned in the news media. It's featured in the APS highlights and ranked top 5 percentile with Altmetrics. YouTube: 3D image - Network. We also found that brain capillary structures correlate with neuron structures: DOI YouTube

FlyBrain We have also reported a three-dimensional analysis of the brain network of the fruit fly Drosophila melanogaster by synchrotron-radiation nanotomography. A skeletonized wire model of the left half of the brain network was built by tracing the 3D image of the brain network. The obtained models of neuronal processes were classified into groups on the basis of their structures. The model structure indicated that the Drosophila brain is composed of networks with different complexity and extensity depending on the brain regions. Simple networks in the optic lobe should be appropriate for relaying information straightforwardly while intricate and widespread networks mainly in the central brain can integrate information from a number of brain regions. These structures of the reconstructed networks provide a basis for understanding how the Drosophila brain works. An article reviewing this study appeared in MIT Technology Review. DOI PubMed arXiv YouTube

TestPattern Spatial resolution is the fundamental parameter in structural sciences. We developed a method for estimating the spatial resolution of real images from a logarithmic intensity plot in the Fourier domain. The logarithmic intensity plots of test images indicated that the full width at half maximum of a Gaussian point spread function can be estimated from the images themselves. The spatial resolution of imaging X-ray nanotomography using Fresnel zone-plate optics was estimated with this method. A cross section of a test object visualized with the nano-CT indicated that square-wave patterns up to 120-nm pitch were resolved. The logarithmic intensity plot was calculated from a nano-CT cross section of brain tissue. The full width at half maximum of the point spread function estimated from the plot coincided with the resolution determined from the test object. These results indicated that the logarithmic intensity plot in the Fourier domain provides an alternative measure of the spatial resolution without explicitly defining a noise criterion. DOI PubMed arXiv


Recently, our interests have been focused on (1) three-dimensional structural analysis of biological soft tissues, including brain tissues of schizophrenia cases (original paper), and (2) evaluation of the spatial resolution of real sample images.

Publications

Selected publications are:
  1. Ryuta Mizutani, Rino Saiga, Yoshiro Yamamoto, Masayuki Uesugi, Akihisa Takeuchi, Kentaro Uesugi, Yasuko Terada, Yoshio Suzuki, Vincent De Andrade, Francesco De Carlo, Susumu Takekoshi, Chie Inomoto, Naoya Nakamura, Youta Torii, Itaru Kushima, Shuji Iritani, Norio Ozaki, Kenichi Oshima, Masanari Itokawa, and Makoto Arai (2021). Structural diverseness of neurons between brain areas and between cases. Transl. Psychiatry 11, 49. DOI pdf
  2. Rino Saiga, Masato Hoshino, Akihisa Takeuchi, Kentaro Uesugi, Katsuko Naitou, Akemi Kamijo, Noboru Kawabe, Masato Ohtsuka, Shunya Takizawa, and Ryuta Mizutani (2019). Synchrotron radiation microtomography of brain hemisphere and spinal cord of a mouse model of multiple sclerosis revealed a correlation between capillary dilation and clinical score. J. Comp. Neurol. 527(13), 2091-2100. [invited] DOI arXiv PubMed
  3. *Ryuta Mizutani, Rino Saiga, Susumu Takekoshi, Chie Inomoto, Naoya Nakamura, Masanari Itokawa, Makoto Arai, Kenichi Oshima, Akihisa Takeuchi, Kentaro Uesugi, Yasuko Terada and Yoshio Suzuki (2016). A method for estimating spatial resolution of real image in the Fourier domain. J. Microscopy 261(1), 57-66. DOI arXiv PubMed
Our other publications are...

Results and resources

Movies and skeletonized models (RRID:SCR_016529)

Movies and skeletonized models of human, mouse, and fly brain networks.

MCTracejump (RRID:SCR_016532)

A GUI-based program for neuronal network model building. We use this software to convert 3D images of neurons into the 3D Cartesian coordinates of neurons to analyze the geometry of brain network.

RecViewjump (RRID:SCR_016531)

Reconstruction and image processing of micro-CT and nano-CT data taken at SPring-8 and APS Argonne. On-the-fly CT reconstruction is implemented using CUDA and SIMD assembly code up to AVX-512.

Preparation of soft tissue samplesjump

Sample preparation tips for synchrotron radiation experiments.
Preparation of capillary mount samples (YouTube).jump

Test patterns for microtomography and nanotomography

Test patterns for the estimation of spatial resolution of 3D images.

Artificial neural network mimicking schizophreniajump

Neural network layers inspired from our study on brain tissues of schizophrenia cases outperform conventional layers. Over 60% of weight parameters can be eliminated without any changes in training procedures or network configuration: original paper.

Vita of P.I.

Name: Ryuta Mizutani

Mizutani Mizutani attaching a sample on the rotation stage of the 32-ID beamline of APS, Argonne National Lab. If you use human tissue samples, your operating procedure must be approved by the institutional committee beforehand. The procedure may ask you to wear personal protective equipments.

Birth: 1967

Education:

1990 B.Sc. (Pharmaceutical Sciences) The University of Tokyo
1992 M.Sc. (Pharm Sci) The University of Tokyo
1995 Ph.D. (Pharm Sci) The University of Tokyo

Research experience:

1992-1993 Affiliate Assistant Professor, International Christian University
1993-1995 Research fellow, the Japan Society for the Promotion of Science
1995-2006 Assistant Professor, the University of Tokyo
2006-2012 Associate Professor, Tokai University
2012- Professor, Tokai University

Membership:

The Japanese Biochemical Society
Microscopy Society of America
Royal Society of Medicine (UK)
etc.

Contact

Ryuta Mizutani, Prof., Dr.
Department of Bioengineering
Department of Applied Biochemistry
School of Engineering / Graduate Sch. of Engineering / Grad. Sch. of Science and Technology
Tokai University
Kitakaname 4-1-1, Hiratsuka, Kanagawa 259-1292, Japan
Tel +81 (463) 58-1211
E-mail mizutanilaboratory(at)gmail.com
https://mizutanilab.github.io/
YouTube LinkedIn ORCID

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