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Atlas of Proteomic signatures of brain structure and its links to brain disorders

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Nature Communications 2025年第1期16卷 1-18页

作者： Ren, Peng Hou, Xiao-He Li, Zeyu You, Jia Li, Yuzhu Zhang, Wei Gong, Weikang Zhang, Bei Wu, Bangsheng Wang, Linbo Shen, Chun Zhao, Yujie Ma, Qing Kang, Jujiao Jiang, Yuchao Roberts, Neil Xu, Fan He, Yong Yu, Jin-Tai Wang, Meiyun Cheng, Wei Institute of Science and Technology for Brain-Inspired Intelligence State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Fudan University Shanghai China Department of Neurology Huashan Hospital Fudan University Shanghai China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) Ministry of Education Shanghai China Department of Neurology Qingdao Hospital University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital) Qingdao China School of Data Science Fudan University Shanghai China Centre for Reproductive Health (CRH) Institute for Regeneration and Repair (IRR) University of Edinburgh 4-5 Little France Drive Edinburgh EH15 4UU United Kingdom Institute of Mechanics and Computational Engineering Department of Aeronautics and Astronautics Fudan University Shanghai China State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing China Beijing Key Laboratory of Brain Imaging and Connectomics Beijing Normal University Beijing China Department of Medical Imaging Henan Provincial People’s Hospital & Zhengzhou University People’s Hospital Zhengzhou China Fudan ISTBI—ZJNU Algorithm Centre for Brain-inspired Intelligence Zhejiang Normal University Zhejiang China

Individual variation in brain structure influences deterioration due to disease and comprehensive profiling of the associated proteomic signature advances mechanistic understanding. Here, using data from 4997 UK Biobank participants, we analyzed the associations between 2920 plasma proteins and 272 neuroimaging-derived brain structure measures. We identified 5358 associations between 1143 proteins and 256 brain structure measures, with NCAN and LEP proteins showing the most associations. Functional enrichment implicated these proteins in neurogenesis, immune/apoptotic processes and neurons. Furthermore, bidirectional Mendelian randomization revealed 33 associations between 32 proteins and 23 brain structure measures, and 21 associations between nine brain structure associated proteins and ten brain disorders. Moreover, the significant associations between the identified proteins and mental health were mediated by brain volume and surface area. In summary, this study generates a comprehensive atlas mapping the patterns of association between proteome and brain structure, highlighting their potential value for studying brain disorders. © The Author(s) 2025.

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Cluster analysis methods and future time perspective groups of second-year engineering students in a major-required course 125

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Cluster analysis methods and future time perspective groups ...

125th ASEE Annual Conference and Exposition

作者： Chasmar, Justine Ehlert, Katherine M. Center for Data Mathematical and Computational Sciences Quantitative Reasoning Center Goucher College United States Engineering and Science Education Department College of Engineering Computing and Applied Sciences Clemson University United States

UNCOVER: The growth of the first massive black holes from JWST/NIRSpec – spectroscopic redshift confirmation of an X-ray luminous AGN at z=10.1

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arXiv 2023年

作者： Goulding, Andy D. Greene, Jenny E. Setton, David J. Labbe, Ivo Bezanson, Rachel Miller, Tim B. Atek, Hakim Bogdán, Ákos Brammer, Gabriel Chemerynska, Iryna Cutler, Sam E. Dayal, Pratika Fudamoto, Yoshinobu Fujimoto, Seiji Furtak, Lukas J. Kokorev, Vasily Khullar, Gourav Leja, Joel Marchesini, Danilo Natarajan, Priyamvada Nelson, Erica Oesch, Pascal A. Pan, Richard Papovich, Casey Price, Sedona H. van Dokkum, Pieter Wang, Bingjie Weaver, John R. Whitaker, Katherine E. Zitrin, Adi Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States Department of Physics and Astronomy PITT PACC University of Pittsburgh PittsburghPA15260 United States Centre for Astrophysics and Supercomputing Swinburne University of Technology MelbourneVIC3122 Australia Department of Astronomy Yale University New HavenCT06511 United States Department of Physics and Astronomy Northwestern University 1800 Sherman Ave EvanstonIL60201 United States Institut d’Astrophysique de Paris CNRS Sorbonne Université 98bis Boulevard Arago Paris75014 France Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Niels Bohr Institute University of Copenhagen Jagtvej 128 København NDK-2200 Denmark Department of Astronomy University of Massachusetts AmherstMA01003 United States Kapteyn Astronomical Institute University of Groningen Groningen9700 AV Netherlands Waseda Research Institute for Science and Engineering Faculty of Science and Engineering Waseda University 3-4-1 Okubo Shinjuku Tokyo169-8555 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo Japan Department of Astronomy The University of Texas at Austin AustinTX78712 United States Physics Department Ben-Gurion University of the Negev P.O. Box 653 Be’er-Sheva84105 Israel Kapteyn Astronomical Institute University of Groningen P.O. Box 800 Groningen9700AV Netherlands Department of Astronomy & Astrophysics The Pennsylvania State University University ParkPA16802 United States Institute for Computational & Data Sciences The Pennsylvania State University University ParkPA16802 United States Institute for Gravitation and the Cosmos The Pennsylvania State University University ParkPA16802 United States Physics and Astronomy Department Tufts University 574 Boston Ave. MedfordMA02155 United States Department of Physics Yale University New HavenCT06520 United States Black Hole Initiative

The James Webb Space Telescope is now detecting early black holes (BHs) as they transition from "seeds" to supermassive BHs. Recently, Bogdan et al. (2023) reported the detection of an X-ray luminous supermassive BH, UHZ-1, with a photometric redshift at z > 10. Such an extreme source at this very high redshift provides new insights on seeding and growth models for BHs given the short time available for formation and growth. Harnessing the exquisite sensitivity of JWST/NIRSpec, here we report the spectroscopic confirmation of UHZ-1 at z = 10.073±0.002. We find that the NIRSpec/Prism spectrum is typical of recently discovered z ≈ 10 galaxies, characterized primarily by star-formation features. We see no clear evidence of the powerful X-ray source in the rest-frame UV/optical spectrum, which may suggest heavy obscuration of the central BH, in line with the Compton-thick column density measured in the X-rays. We perform a stellar population fit simultaneously to the new NIRSpec spectroscopy and previously available photometry. The fit yields a stellar mass estimate for the host galaxy that is significantly better constrained than prior photometric estimates (M* ∼ 1.4+0−034 × 108 M☉). Given the predicted BH mass (MBH ∼ 107 − 108 M☉), the resulting ratio of MBH/M* remains two to three orders of magnitude higher than local values, thus lending support to the heavy seeding channel for the formation of supermassive BHs within the first billion years of cosmic evolution. Copyright © 2023, The Authors. All rights reserved.

关键词： Black holes

The Obscured Fraction of Quasars at Cosmic Noon

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arXiv 2022年

作者： Vijarnwannaluk, Bovornpratch Akiyama, Masayuki Schramm, Malte Ueda, Yoshihiro Matsuoka, Yoshiki Toba, Yoshiki Sawicki, Marcin Gwyn, Stephen Pflugradt, Janek Astronomical Institute Tohoku University Aoba-ku Aramaki Miyagi Sendai980-8578 Japan Graduate School of Science and Engineering Saitama University 255 Shimo-Okubo Sakura-ku Saitama Saitama City338-8570 Japan Department of Astronomy Kyoto University Kitashirakawa-Oiwake-cho Sakyo-ku Kyoto606-8502 Japan Research Center for Space and Cosmic Evolution Ehime University 2-5 Bunkyo-cho Ehime Matsuyama790-8577 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Tokyo Mitaka181-8588 Japan Institute for Computational Astrophysics Department of Astronomy and Physics Saint Mary's University HalifaxNSB3H 3C3 Canada Canadian Astronomy Data Centre NRC-Herzberg 5071 West Saanich Road VictoriaBCV9E 2E7 Canada

Statistical studies of X-ray selected Active Galactic Nuclei (AGN) indicate that the fraction of obscured AGN increases with increasing redshift, and the results suggest that a significant part of the accretion growth occurs behind obscuring material in the early universe. We investigate the obscured fraction of highly accreting X-ray AGN at around the peak epoch of supermassive black hole growth utilizing the wide and deep X-ray and optical/IR imaging datasets. A unique sample of luminous X-ray selected AGNs above z > 2 was constructed by matching the XMM-SERVS X-ray point-source catalog with a PSF-convolved photometric catalog covering from u∗to 4.5μm bands. Photometric redshift, hydrogen column density, and 2-10 keV AGN luminosity of the X-ray selected AGN candidates were estimated. Using the sample of 306 2-10 keV detected AGN at above redshift 2, we estimate the fraction of AGN with log NH(cm-2) > 22, assuming parametric X-ray luminosity and absorption functions. The results suggest that 76-3+4% of luminous quasars (log LX(erg s-1) > 44.5) above redshift 2 are obscured. The fraction indicates an increased contribution of obscured accretion at high redshift than that in the local universe. We discuss the implications of the increasing obscured fraction with increasing redshift based on the AGN obscuration scenarios, which describe obscuration properties in the local universe. Both the obscured and unobscured z > 2 AGN show a broad range of SEDs and morphology, which may reflect the broad variety of host galaxy properties and physical processes associated with the obscuration. © 2022, CC BY.

关键词： Active Galactic Nuclei

Multi-scale simulations of electron and ion dynamics in self-irradiated silicon

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arXiv 2020年

作者： Lee, Cheng-Wei Stewart, James A. Foiles, Stephen M. Dingreville, Rémi Schleife, André Department of Materials Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Center for Integrated Nanotechnologies Sandia National Laboratories AlbuquerqueNM87185 United States Computational Materials and Data Science Department Sandia National Laboratories AlbuquerqueNM87185 United States Materials Research Laboratory University of Illinois at Urbana-Champaign UrbanaIL61801 United States National Center for Supercomputing Applications University of Illinois at Urbana-Champaign UrbanaIL61801 United States

The interaction of energetic ions with the electronic and ionic system of target materials is an interesting but challenging multi-scale problem and understanding of the early stages after impact of heavy, initially charged ions is particularly poor. At the same time, energy deposition during these early stages determines later formation of damage cascades. We address the multi-scale character by combining real-time time-dependent density functional theory for electron dynamics with molecular dynamics simulations of damage cascades. Our first-principles simulations prove that core electrons affect electronic stopping and have an unexpected influence on the charge state of the projectile. We show that this effect is absent for light projectiles, but dominates the stopping physics for heavy projectiles. By parameterizing an inelastic energy loss friction term in the molecular dynamics simulations using our first-principles results, we also show a qualitative influence of electronic stopping physics on radiation-damage cascades. Copyright © 2020, The Authors. All rights reserved.

关键词： Projectiles

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Skater’s dilemma

arXiv 2020年

作者： Ichinose, Genki Miyagawa, Daiki Ito, Junji Masuda, Naoki Department of Mathematical and Systems Engineering Shizuoka University 3-5-1 Johoku Naka-ku Hamamatsu432-8561 Japan Skating Club Yamanashi Gakuin University 2-4-5 Sakaori Kofu Yamanashi400-8575 Japan Department of Mathematics University at Buffalo State University of New York BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

In some athletic races, such as cycling and types of speed skating races, athletes have to complete a relatively long distance at a high speed in the presence of direct opponents. To win such a race, athletes are motivated to hide behind others to suppress energy consumption before a final moment of the race. This situation seems to produce a social dilemma: players want to hide behind others, whereas if a group of players attempts to do so, they may all lose to other players that overtake them. To support that speed skaters are involved in such a social dilemma, we analyzed video footage data for 14 mass start skating races to find that skaters that hid behind others to avoid air resistance for a long time before the final lap tended to win. Furthermore, the finish rank of the skaters in mass start races was independent of the record of the same skaters in time-trial races measured in the absence of direct opponents. The results suggest that how to strategically cope with a skater’s dilemma may be a key determinant for winning long-distance and high-speed races with direct *** Codes 91A80 Copyright © 2020, The Authors. All rights reserved.

关键词： Game theory

Correction: The Effect of Co-Culture of Two Coral Species on Their Bacterial Composition Under Captive Environments

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Marine biotechnology (New York, N.Y.) 2022年第6期24卷 1176页

作者： Keigo Ide Yoshikatsu Nakano Michihiro Ito Yohei Nishikawa Hiroyuki Fujimura Haruko Takeyama Department of Life Science and Medical Bioscience Waseda University Tokyo Japan. Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL) National Institute of Advanced Industrial Science and Technology Tokyo Japan. Tropical Biosphere Research Center University of the Ryukyus Tokyo Japan. Marine Science Section Research Support Division Okinawa Institute of Science and Technology Graduate University Okinawa Japan. Research Organization for Nano and Life Innovation Waseda University Tokyo Japan. Department of Chemistry Biology and Marine Science University of the Ryukyus Okinawa Japan. Department of Life Science and Medical Bioscience Waseda University Tokyo Japan. haruko-takeyama@waseda.jp. Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL) National Institute of Advanced Industrial Science and Technology Tokyo Japan. haruko-takeyama@waseda.jp. Research Organization for Nano and Life Innovation Waseda University Tokyo Japan. haruko-takeyama@waseda.jp. Institute for Advanced Research of Biosystem Dynamics Waseda Research Institute for Science and Engineering Tokyo Japan. haruko-takeyama@waseda.jp.

Author Correction: Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision

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Nature methods 2025年第2期22卷 448页

作者： Marieke Vromman Jasper Anckaert Stefania Bortoluzzi Alessia Buratin Chia-Ying Chen Qinjie Chu Trees-Juen Chuang Roozbeh Dehghannasiri Christoph Dieterich Xin Dong Paul Flicek Enrico Gaffo Wanjun Gu Chunjiang He Steve Hoffmann Osagie Izuogu Michael S Jackson Tobias Jakobi Eric C Lai Justine Nuytens Julia Salzman Mauro Santibanez-Koref Peter Stadler Olivier Thas Eveline Vanden Eynde Kimberly Verniers Guoxia Wen Jakub Westholm Li Yang Chu-Yu Ye Nurten Yigit Guo-Hua Yuan Jinyang Zhang Fangqing Zhao Jo Vandesompele Pieter-Jan Volders OncoRNALab Cancer Research Institute Ghent (CRIG) Department of Biomolecular Medicine Ghent University Ghent Belgium. Department of Molecular Medicine University of Padova Padova Italy. Genomics Research Center Academia Sinica Taipei City Taiwan. Institute of Crop Science and Institute of Bioinformatics Zhejiang University Zhejiang China. Department of Biomedical Data Science and of Biochemistry Stanford University Stanford CA USA. Klaus Tschira Institute for Integrative Computational Cardiology Department of Internal Medicine III University Hospital Heidelberg German Center for Cardiovascular Research (DZHK) Heidelberg Germany. School of Basic Medical Science Department of Medical Genetics Wuhan University Wuhan China. EMBL-EBI Hinxton UK. Collaborative Innovation Center of Jiangsu Province of Cancer Prevention and Treatment of Chinese Medicine School of Artificial Intelligence and Information Technology Nanjing University of Chinese Medicine Nanjing China. Computational Biology Group Leibniz Institute on Aging - Fritz Lipmann Institute (FLI) Jena Germany. Biosciences Institute Faculty of Medical Sciences Newcastle University Newcastle UK. Translational Cardiovascular Research Center University of Arizona - College of Medicine Phoenix Phoenix AZ USA. Sloan Kettering Institute New York NY USA. Bioinformatics Group Department of Computer Science and Interdisciplinary Center for Bioinformatics Universität Leipzig Leipzig Germany. Data Science Institute I-Biostat Hasselt University Hasselt Belgium. State Key Laboratory of Bioelectronics School of Biological Sciences and Medical Engineering Southeast University Nanjing China. Department of Biochemistry and Biophysics National Bioinformatics Infrastructure Sweden Science for Life Laboratory Stockholm University Stockholm Sweden. Center for Molecular Medicine Children's Hospital Fudan University and Shanghai Key Laboratory of Medical Epigenetics International Laboratory of Medical Epigenetics and Metab

Modeling temporal networks with bursty activity patterns of nodes and links

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Physical Review Research 2020年第2期2卷 023073-023073页

作者： Takayuki Hiraoka Naoki Masuda Aming Li Hang-Hyun Jo Department of Computer Science Aalto University Espoo 00076 Finland Asia Pacific Center for Theoretical Physics Pohang 37673 Republic of Korea Department of Mathematics University at Buffalo State University of New York Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York Buffalo New York 14260-5030 USA Department of Zoology University of Oxford Oxford OX1 3PS United Kingdom Department of Biochemistry University of Oxford Oxford OX1 3QU United Kingdom Department of Physics The Catholic University of Korea Bucheon 14662 Republic of Korea

The concept of temporal networks provides a framework to understand how the interaction between system components changes over time. In empirical communication data, we often detect non-Poissonian, so-called bursty behavior in the activity of nodes as well as in the interaction between nodes. However, such reconciliation between node burstiness and link burstiness cannot be explained if the interaction processes on different links are independent of each other. This is because the activity of a node is the superposition of the interaction processes on the links incident to the node, and the superposition of independent bursty point processes is not bursty in general. Here we introduce a temporal network model based on bursty node activation, and we show that it leads to heavy-tailed interevent time distributions for both node dynamics and link dynamics. Our analysis indicates that activation processes intrinsic to nodes give rise to dynamical correlations across links. Our framework offers a way to model competition and correlation between links, which is key to understanding dynamical processes in various systems.

关键词： Collective behavior in networks Dynamics of networks Scaling laws of complex systems Social systems Communication networks Multiple time scale dynamics Networks & random structures Social networks Evolving network models Network Models Non-Markovian processes Time series analysis