中村敬宇の思想 : 幕末・明治初期における儒学的「道」の展開

学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 三谷 博, 東京大学教授 黒住 真, 東京大学教授 苅部 直, 東京大学准教授 石井 剛, 法政大学教授 渡辺 浩University of Tokyo(東京大学

Depression research: where are we now?

Extensive studies have led to a variety of hypotheses for the molecular basis of depression and related mood disorders, but a definite pathogenic mechanism has yet to be defined. The monoamine hypothesis, in conjunction with the efficacy of antidepressants targeting monoamine systems, has long been the central topic of depression research. While it is widely embraced that the initiation of antidepressant efficacy may involve acute changes in monoamine systems, apparently, the focus of current research is moving toward molecular mechanisms that underlie long-lasting downstream changes in the brain after chronic antidepressant treatment, thereby reaching for a detailed view of the pathophysiology of depression and related mood disorders. In this minireview, we briefly summarize major themes in current approaches to understanding mood disorders focusing on molecular views of depression and antidepressant action

Probing of Triply Coordinated Oxygen in Amorphous Al₂O₃

Although anomalous melt properties have been attributed to the presence of triply coordinated oxygen (^[3]O), the presence of ^[3]O in covalent amorphous oxides has not been revealed experimentally; such verification is the Holy Grail in the study of the physics and chemistry of glasses. We report the first ¹⁷O NMR spectrum for amorphous Al₂O₃ and reveal the hidden nature of ^[3]O. The detailed NMR characteristics of the oxygen tricluster are distinct from those estimated for the crystalline analogs, thus indicating its unique structure. This unambiguous evidence of the presence of ^[3]O allows us to microscopically constrain its glass-forming ability and unique two-step crystallization paths of amorphous Al₂O₃ through the annihilation of glassy ^[3]O with multiple ^[5]Al species

Control of the Drying Patterns for Complex Colloidal Solutions and Their Applications

The uneven deposition at the edges of an evaporating droplet, termed the coffee-ring effect, has been extensively studied during the past few decades to better understand the underlying cause, namely the flow dynamics, and the subsequent patterns formed after drying. The non-uniform evaporation rate across the colloidal droplet hampers the formation of a uniform and homogeneous film in printed electronics, rechargeable batteries, etc., and often causes device failures. This review aims to highlight the diverse range of techniques used to alleviate the coffee-ring effect, from classic methods such as adding chemical additives, applying external sources, and manipulating geometrical configurations to recently developed advancements, specifically using bubbles, humidity, confined systems, etc., which do not involve modification of surface, particle or liquid properties. Each of these methodologies mitigates the edge deposition via multi-body interactions, for example, particle–liquid, particle-particle, particle–solid interfaces and particle–flow interactions. The mechanisms behind each of these approaches help to find methods to inhibit the non-uniform film formation, and the corresponding applications have been discussed together with a critical comparison in detail. This review could pave the way for developing inks and processes to apply in functional coatings and printed electronic devices with improved efficiency and device yield

Automatic Classification Service System for Citrus Pest Recognition Based on Deep Learning

Plant diseases are a major cause of reduction in agricultural output, which leads to severe economic losses and unstable food supply. The citrus plant is an economically important fruit crop grown and produced worldwide. However, citrus plants are easily affected by various factors, such as climate change, pests, and diseases, resulting in reduced yield and quality. Advances in computer vision in recent years have been widely used for plant disease detection and classification, providing opportunities for early disease detection, and resulting in improvements in agriculture. Particularly, the early and accurate detection of citrus diseases, which are vulnerable to pests, is very important to prevent the spread of pests and reduce crop damage. Research on citrus pest disease is ongoing, but it is difficult to apply research results to cultivation owing to a lack of datasets for research and limited types of pests. In this study, we built a dataset by self-collecting a total of 20,000 citrus pest images, including fruits and leaves, from actual cultivation sites. The constructed dataset was trained, verified, and tested using a model that had undergone five transfer learning steps. All models used in the experiment had an average accuracy of 97% or more and an average f1 score of 96% or more. We built a web application server using the EfficientNet-b0 model, which exhibited the best performance among the five learning models. The built web application tested citrus pest disease using image samples collected from websites other than the self-collected image samples and prepared data, and both samples correctly classified the disease. The citrus pest automatic diagnosis web system using the model proposed in this study plays a useful auxiliary role in recognizing and classifying citrus diseases. This can, in turn, help improve the overall quality of citrus fruits

Use of behavioral analysis in animal models for schizophrenia research

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HnRNP Q suppresses polyglutamine aggregation by reducing Vaccinia-related kinase 2 mRNA stability

Huntington’s disease (HD) is a progressive neurodegenerative disorder caused by a CAG trinucleotide repeat expansion in the huntingtin (HTT) gene, which encodes a polyglutamine tract in the HTT protein. Misfolding of proteins containing abnormal expansions of polyglutamine (polyQ) repeats is associated with cytotoxicity in HD. We have previously shown that vaccinia-related kinase 2 (VRK2) downregulates chaperonin TRiC protein levels through the ubiquitin-proteasome system by recruiting the E3 ligase COP1 and by destabilizing USP25 which is deubiquiting enzyme. Here we found that basal level of VRK2 in neuronal cells is regulated by post-transcriptional regulation. HnRNP Q specifically binds to 3’UTR of VRK2 mRNA in neuronal cells and reduces its stability. We report a dramatic increase polyglutamine aggregation by reducing hnRNP Q level. Thus, our results demonstrate that decreased brain hnRNP Q contributes to HD neurological phenotype and open new novel prognostic marker of HD.1

Enhancing Mixing Performance in a Rotating Disk Mixing Chamber: A Quantitative Investigation of the Effect of Euler and Coriolis Forces

Lab-on-a-CD (LOCD) is gaining importance as a diagnostic platform due to being low-cost, easy-to-use, and portable. During LOCD usage, mixing and reaction are two processes that play an essential role in biochemical applications such as point-of-care diagnosis. In this paper, we numerically and experimentally investigate the effects of the Coriolis and Euler forces in the mixing chamber during the acceleration and deceleration of a rotating disk. The mixing performance is investigated under various conditions that have not been reported, such as rotational condition, chamber aspect ratio at a constant volume, and obstacle arrangement in the chamber. During disk acceleration and deceleration, the Euler force difference in the radial direction causes rotating flows, while the Coriolis force induces perpendicular vortices. Increasing the maximum rotational velocity improves the maximum rotational displacement, resulting in better mixing performance. A longer rotational period increases the interfacial area between solutions and enhances mixing. Mixing performance also improves when there is a substantial difference between Euler forces at the inner and outer radii. Furthermore, adding obstacles in the angular direction also passively promotes or inhibits mixing by configuration. This quantitative investigation provides valuable information for designing and developing high throughput and multiplexed point-of-care LOCDs

Transcriptional regulation of dopamine D1 receptor by DISC1-DRRF repressor complex

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