慢性腎不全における成長障害: 成長ホルモン-インスリン様成長因子系の異常に関する研究

取得学位 : 博士（医学）, 学位授与番号 : 医博甲第1053号, 学位授与年月日：平成4年3月25日,学位授与年：199

Volcanic magma reservoir imaged as a low-density body beneath Aso volcano that terminated the 2016 Kumamoto earthquake rupture

Additional file 2: Figure S2. Calculated density contrast models beneath Aso volcano in horizontal slices at depths of 3.1, 4.9, and 8.2 km: (a), (b), (c), (d), (e), and (f) correspond to density contrasts of ±0.15, ±0.20 ±0.25, ±0.30, ±0.35, and ±0.40 g/cm3, respectively (Additional file 5: Table S1)

Development of Algorithms for Estimating Apartment Rents in Metropolitan Area Based on a Combined Micro-Macro Approach

Information about the rental costs of the large apartment buildings is asymmetric in that thereal estate companies tend to disclose such information to a customer only for the large apartmentbuildings of potential interest to the customer, and any information irrelevant to the ongoing businesswould be sealed. This information imbalance prevents the market to be transparent, and theeconomic market principles are often ignored. In order to overcome this pitfall, this paper aims atdeveloping a numerical algorithm for estimating the unit rent of a large apartment building based ona set of real data in the metropolitan Tokyo. The algorithm is based on the combined micro-macroapproach, where the local information such as the nearest rail station, the distance to it, and the likewould be used first to estimate the unit rent through the micro approach. For the macro approach,the linear regression is employed based on the real data, and the resulting estimation formula wouldyield the second estimate. The two estimates would then be linearly combined, where the optimalweighting factor would be determined so as to minimize the discrepancy between the combinedestimated values and the unit rents obtained from the real data

Pushing property limits in materials discovery via boundless objective-free exploration

Materials chemists develop chemical compounds to meet often conflicting demands of industrial applications. This process may not be properly modeled by black-box optimization because the target property is not well defined in some cases. Herein, we propose a new algorithm for automated materials discovery called BoundLess Objective-free eXploration (BLOX) that uses a novel criterion based on kernel-based Stein discrepancy in the property space. Unlike other objective-free exploration methods, a boundary for the materials properties is not needed; hence, BLOX is suitable for open-ended scientific endeavors. We demonstrate the effectiveness of BLOX by finding light-absorbing molecules from a drug database. Our goal is to minimize the number of density functional theory calculations required to discover out-of-trend compounds in the intensity–wavelength property space. Using absorption spectroscopy, we experimentally verified that eight compounds identified as outstanding exhibit the expected optical properties. Our results show that BLOX is useful for chemical repurposing, and we expect this search method to have numerous applications in various scientific disciplines

Effective-mononuclear cell (E-MNC) therapy alleviates salivary gland damage by suppressing lymphocyte infiltration in Sjögren-like disease

Introduction: Sjögren syndrome (SS) is an autoimmune disease characterized by salivary gland (SG) destruction leading to loss of secretory function. A hallmark of the disease is the presence of focal lymphocyte infiltration in SGs, which is predominantly composed of T cells. Currently, there are no effective therapies for SS. Recently, we demonstrated that a newly developed therapy using effective-mononuclear cells (E-MNCs) improved the function of radiation-injured SGs due to anti-inflammatory and regenerative effects. In this study, we investigated whether E-MNCs could ameliorate disease development in non-obese diabetic (NOD) mice as a model for primary SS.Methods: E-MNCs were obtained from peripheral blood mononuclear cells (PBMNCs) cultured for 7 days in serum-free medium supplemented with five specific recombinant proteins (5G culture). The anti-inflammatory characteristics of E-MNCs were then analyzed using a co-culture system with CD3/CD28-stimulated PBMNCs. To evaluate the therapeutic efficacy of E-MNCs against SS onset, E-MNCs were transplanted into SGs of NOD mice. Subsequently, saliva secretion, histological, and gene expression analyses of harvested SG were performed to investigate if E-MNCs therapy delays disease development.Results: First, we characterized that both human and mouse E-MNCs exhibited induction of CD11b/CD206-positive cells (M2 macrophages) and that human E-MNCs could inhibit inflammatory gene expressions in CD3/CD28- stimulated PBMNCs. Further analyses revealed that Msr1-and galectin3-positive macrophages (immunomodulatory M2c phenotype) were specifically induced in E-MNCs of both NOD and MHC class I-matched mice. Transplanted E-MNCs induced M2 macrophages and reduced the expression of T cell-derived chemokine-related and inflammatory genes in SG tissue of NOD mice at SS-onset. Then, E-MNCs suppressed the infiltration of CD4-positive T cells and facilitated the maintenance of saliva secretion for up to 12 weeks after E-MNC administration.Discussion: Thus, the immunomodulatory actions of E-MNCs could be part of a therapeutic strategy targeting the early stage of primary SS

De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning

Designing fluorescent molecules requires considering multiple interrelated molecular properties, as opposed to properties that straightforwardly correlated with molecular structure, such as light absorption of molecules. In this study, we have used a de novo molecule generator (DNMG) coupled with quantum chemical computation (QC) to develop fluorescent molecules, which are garnering significant attention in various disciplines. Using massive parallel computation (1024 cores, 5 days), the DNMG has produced 3643 candidate molecules. We have selected an unreported molecule and seven reported molecules and synthesized them. Photoluminescence spectrum measurements demonstrated that the DNMG can successfully design fluorescent molecules with 75% accuracy (n = 6/8) and create an unreported molecule that emits fluorescence detectable by the naked eye