Publications by authors named "Yasuaki Hiraoka"

While the intestinal epithelium has the highest cellular turnover rates in the mammalian body, it is also considered one of the tissues most resilient to aging-related disorders. Here, we reveal an innate protective mechanism that safeguards intestinal stem cells (ISCs) from environmental conditions in the aged intestine. Using in vivo phenotypic analysis, transcriptomics, and in vitro intestinal organoid studies, we show that age-dependent activation of interferon-γ (IFN-γ) signaling and inactivation of extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK) signaling are responsible for establishing an equilibrium of Lgr5 ISCs-between active and quiescent states-to preserve the ISC pool during aging.

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Background: Time-series scRNA-seq data have opened a door to elucidate cell differentiation, and in this context, the optimal transport theory has been attracting much attention. However, there remain critical issues in interpretability and computational cost.

Results: We present scEGOT, a comprehensive framework for single-cell trajectory inference, as a generative model with high interpretability and low computational cost.

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Article Synopsis
  • Understanding disordered structures in materials is challenging due to limited experimental data, but this study combines diffraction and simulations to analyze oxygen packing and network topology in various MgO-SiO systems.
  • The research reveals that oxygen packing is larger in glass forms than in liquid forms, and suggests that the similarity in topology between certain crystalline and glass forms indicates low glass-forming ability (GFA), whereas unique topologies correspond to high GFA.
  • It concludes that the GFA of MgO-SiO is primarily influenced by atomic structure and network topology, rather than electronic structure.
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Single-cell RNA sequencing (scRNA-seq) can determine gene expression in numerous individual cells simultaneously, promoting progress in the biomedical sciences. However, scRNA-seq data are high-dimensional with substantial technical noise, including dropouts. During analysis of scRNA-seq data, such noise engenders a statistical problem known as the curse of dimensionality (COD).

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Article Synopsis
  • * The research reveals that during epigenetic reprogramming, while chromatin becomes more open and accessible, there are protective mechanisms in place to maintain proper gene expression, which later undergoes further changes for spermatogonial development.
  • * The findings indicate that issues in the development and organization of the chromatin can lead to reduced fertility, highlighting how specific chromatin structures are crucial for the formation of gametes in both males and females.
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Topological data analysis is an emerging concept of data analysis for characterizing shapes. A state-of-the-art tool in topological data analysis is persistent homology, which is expected to summarize quantified topological and geometric features. Although persistent homology is useful for revealing the topological and geometric information, it is difficult to interpret the parameters of persistent homology themselves and difficult to directly relate the parameters to physical properties.

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Understanding the protein-folding process is an outstanding issue in biophysics; recent developments in molecular dynamics simulation have provided insights into this phenomenon. However, the large freedom of atomic motion hinders the understanding of this process. In this study, we applied persistent homology, an emerging method to analyze topological features in a data set, to reveal protein-folding dynamics.

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The purpose of this study is to evaluate the accuracy for classification of hepatic tumors by characterization of T1-weighted magnetic resonance (MR) images using two radiomics approaches with machine learning models: texture analysis and topological data analysis using persistent homology. This study assessed non-contrast-enhanced fat-suppressed three-dimensional (3D) T1-weighted images of 150 hepatic tumors. The lesions included 50 hepatocellular carcinomas (HCCs), 50 metastatic tumors (MTs), and 50 hepatic hemangiomas (HHs) found respectively in 37, 23, and 33 patients.

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Macroscopic phenomena, such as fracture, corrosion, and degradation of materials, are associated with various reactions which progress heterogeneously. Thus, material properties are generally determined not by their averaged characteristics but by specific features in heterogeneity (or 'trigger sites') of phases, chemical states, etc., where the key reactions that dictate macroscopic properties initiate and propagate.

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We apply a persistent homology analysis to investigate the behavior of nanovoids during the crazing process of glassy polymers. We carry out a coarse-grained molecular dynamics simulation of the uniaxial deformation of an amorphous polymer and analyze the results with persistent homology. Persistent homology reveals the void coalescence during craze formation, and the results suggest that the yielding process is regarded as the percolation of nanovoids created by deformation.

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This article proposes a topological method that extracts hierarchical structures of various amorphous solids. The method is based on the persistence diagram (PD), a mathematical tool for capturing shapes of multiscale data. The input to the PDs is given by an atomic configuration and the output is expressed as 2D histograms.

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The characterization of the medium-range (MRO) order in amorphous materials and its relation to the short-range order is discussed. A new topological approach to extract a hierarchical structure of amorphous materials is presented, which is robust against small perturbations and allows us to distinguish it from periodic or random configurations. This method is called the persistence diagram (PD) and introduces scales to many-body atomic structures to facilitate size and shape characterization.

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