高齢化社会が抱える健康課題に対するデータ科学の応用

学位プログラム名: 京都大学大学院思修館京都大学新制・課程博士博士(総合学術)甲第25457号総総博第33号京都大学大学院総合生存学館総合生存学専攻(主査)准教授 水本 憲治, 教授 齋藤 敬, 教授 今中 雄一学位規則第4条第1項該当Doctor of PhilosophyKyoto UniversityDFA

Community Structure and Its Stability on a Face-to-Face Interaction Network in Kyoto City

As social behavior plays an essential role in people’s lives, the features of face-to-face interaction networks must be examined to understand people’s social behavior. In this study, we focused on the stable community structure of a face-to-face interaction network because it explains the persistent communities caused by the stationary communication patterns of citizens and visitors in a city. We regarded citizens and visitors as two kinds of particles and the community as a phase and theorized the stability of the community structure using the equilibrium conditions among communities. We formulated the chemical potentials of the communities and examined whether they were in equilibrium under the assumption of a canonical ensemble. We estimated the chemical potentials of persistent communities and found that these values matched within approximately 10% error for each day. This result indicates that the cause of persistent communities is the stability of community structure

Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan

The aging world population requires a sustainable and high-quality healthcare system. To examine the efficiency of medical cooperation, medical provider and physician networks were constructed using patient claims data. Previous studies have shown that these networks contain information on medical cooperation. However, the usage patterns of multiple medical providers in a series of medical services have not been considered. In addition, these studies used only general network features to represent medical cooperation, but their expressive ability was low. To overcome these limitations, we analyzed the medical provider network to examine its overall contribution to the quality of healthcare provided by cooperation between medical providers in a series of medical services. This study focused on: i) the method of feature extraction from the network, ii) incorporation of the usage pattern of medical providers, and iii) expressive ability of the statistical model. Femoral neck fractures were selected as the target disease. To build the medical provider networks, we analyzed the patient claims data from a single prefecture in Japan between January 1, 2014 and December 31, 2019. We considered four types of models. Models 1 and 2 use node strength and linear regression, with Model 2 also incorporating patient age as an input. Models 3 and 4 use feature representation by node2vec with linear regression and regression tree ensemble, a machine learning method. The results showed that medical providers with higher levels of cooperation reduce the duration of hospital stay. The overall contribution of the medical cooperation to the duration of hospital stay extracted from the medical provider network using node2vec is approximately 20%, which is approximately 20 times higher than the model using strength

First Demonstration Experiment for Energy-Trading System EDISON-X Using the XRP Ledger

Proceedings of Blockchain Kaigi 2022 (BCK22), August 4-5, 2022, Sendai, JapanWe developed a blockchain-based energy-trading system called EDISON-X to manage the buying and selling of electricity usage rights (i.e., tokens). Students buy UPX and SPX tokens to use electricity supplied from the utility company’s distribution lines and solar PV panels installed on the roof of the school building, respectively. In July 2022, 17 students from our school dormitory participated in an experiment to validate the operation of the EDISON-X system. Based on the results of this experiment, we describe an energy-trading system using blockchain technology for the effective usage of renewable energy. We developed topology and network science methodologies to understand the characteristics of energy trading. This study examined the hypothesis that market transactions become less active when “cavities” appear using topological data analysis. The preliminary results suggest that this hypothesis is plausible

Domain Growth Kinetics in a Cell-sized Liposome

We investigated the kinetics of domain growth on liposomes consisting of a ternary mixture (unsaturated phospholipid, saturated phospholipid, and cholesterol) by temperature jump. The domain growth process was monitored by fluorescence microscopy, where the growth was mediated by the fusion of domains through the collision. It was found that an average domain size r develops with time t as r ~ t^0.15, indicating that the power is around a half of the theoretical expectation deduced from a model of Brownian motion on a 2-dimensional membrane. We discuss the mechanism of the experimental scaling behavior by considering the elasticity of the membrane

Glycine-alanine dipeptide repeat protein contributes to toxicity in a zebrafish model of C9orf72 associated neurodegeneration

Background: The most frequent genetic cause of frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) is the expansion of a GGGGCC hexanucleotide repeat in a non-coding region of the chromosome 9 open reading frame 72 (C9orf72) locus. The pathological hallmarks observed in C9orf72 repeat expansion carriers are the formation of RNA foci and deposition of dipeptide repeat (DPR) proteins derived from repeat associated non-ATG (RAN) translation. Currently, it is unclear whether formation of RNA foci, DPR translation products, or partial loss of C9orf72 predominantly drive neurotoxicity in vivo. By using a transgenic approach in zebrafish we address if the most frequently found DPR in human ALS/FTLD brain, the poly-Gly-Ala (poly-GA) protein, is toxic in vivo. Method: We generated several transgenic UAS responder lines that express either 80 repeats of GGGGCC alone, or together with a translation initiation ATG codon forcing the translation of GA80-GFP protein upon crossing to a Gal4 driver. The GGGGCC repeat and GA80 were fused to green fluorescent protein (GFP) lacking a start codon to monitor protein translation by GFP fluorescence. Results: Zebrafish transgenic for the GGGGCC repeat lacking an ATG codon showed very mild toxicity in the absence of poly-GA. However, strong toxicity was induced upon ATG initiated expression of poly-GA, which was rescued by injection of an antisense morpholino interfering with start codon dependent poly-GA translation. This morpholino only interferes with GA80-GFP translation without affecting repeat transcription, indicating that the toxicity is derived from GA80-GFP. Conclusion: These novel transgenic C9orf72 associated repeat zebrafish models demonstrate poly-GA toxicity in zebrafish. Reduction of poly-GA protein rescues toxicity validating this therapeutic approach to treat C9orf72 repeat expansion carriers. These novel animal models provide a valuable tool for drug discovery to reduce DPR associated toxicity in ALS/FTLD patients with C9orf72 repeat expansions

A switchable controlled-NOT gate in a spin-chain NMR quantum computer

A method of switching a controlled-NOT gate in a solid-stae NMR quantum computer is presented. Qubits of I=1/2 nuclear spins are placed periodically along a quantum spin chain (1-D antiferromagnet) having a singlet ground state with a finite spin gap to the lowest excited state caused by some quantum effect. Irradiation of a microwave tuned to the spin gap energy excites a packet of triplet magnons at a specific part of the chain where control and target qubits are involved. The packet switches on the Suhl-Nakamura interaction between the qubits, which serves as a controlled NOT gate. The qubit initialization is achieved by a qubit initializer consisting of semiconducting sheets attached to the spin chain, where spin polarizations created by the optical pumping method in the semiconductors are transferred to the spin chain. The scheme allows us to separate the initialization process from the computation, so that one can optimize the computation part without being restricted by the initialization scheme, which provides us with a wide selection of materials for a quantum computer.Comment: 8 pages, 5 figure

Coordinated optimization of visual cortical maps (I) Symmetry-based analysis

In the primary visual cortex of primates and carnivores, functional architecture can be characterized by maps of various stimulus features such as orientation preference (OP), ocular dominance (OD), and spatial frequency. It is a long-standing question in theoretical neuroscience whether the observed maps should be interpreted as optima of a specific energy functional that summarizes the design principles of cortical functional architecture. A rigorous evaluation of this optimization hypothesis is particularly demanded by recent evidence that the functional architecture of OP columns precisely follows species invariant quantitative laws. Because it would be desirable to infer the form of such an optimization principle from the biological data, the optimization approach to explain cortical functional architecture raises the following questions: i) What are the genuine ground states of candidate energy functionals and how can they be calculated with precision and rigor? ii) How do differences in candidate optimization principles impact on the predicted map structure and conversely what can be learned about an hypothetical underlying optimization principle from observations on map structure? iii) Is there a way to analyze the coordinated organization of cortical maps predicted by optimization principles in general? To answer these questions we developed a general dynamical systems approach to the combined optimization of visual cortical maps of OP and another scalar feature such as OD or spatial frequency preference.Comment: 90 pages, 16 figure

Dissipative Electron Transport through Andreev Interferometers

We consider the conductance of an Andreev interferometer, i.e., a hybrid structure where a dissipative current flows through a mesoscopic normal (N) sample in contact with two superconducting (S) "mirrors". Giant conductance oscillations are predicted if the superconducting phase difference $\phi$ is varied. Conductance maxima appear when $\phi$ is on odd multiple of $\pi$ due to a bunching at the Fermi energy of quasiparticle energy levels formed by Andreev reflections at the N-S boundaries. For a ballistic normal sample the oscillation amplitude is giant and proportional to the number of open transverse modes. We estimate using both analytical and numerical methods how scattering and mode mixing --- which tend to lift the level degeneracy at the Fermi energy --- effect the giant oscillations. These are shown to survive in a diffusive sample at temperatures much smaller than the Thouless temperature provided there are potential barriers between the sample and the normal electron reservoirs. Our results are in good agreement with previous work on conductance oscillations of diffusive samples, which we propose can be understood in terms of a Feynman path integral description of quasiparticle trajectories.Comment: 24 pages, revtex, 12 figures in eps forma