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Optoelectronics Global Conference (OGC)

作者： Hanyu Zhang Linjie Zhou Liangjun Lu Jianping Chen B. M. A. Rahman Shanghai Institute for Advanced Communication and Data Science Shanghai Key Lab of Navigation and Location Services State Key Laboratory of Advanced Optical Communication Systems and Networks SJTU Shanghai China Department of Electrical and Electronic Engineering University of London London U.K.

We present a non-volatile optical switch based on a directional coupler comprising a silicon-Ge2Sb2Te5 (GST) hybrid waveguide. The non-volatility of GST makes it attractive for reducing static power consumption in optical switching. Experimental results show that the optical switch has an extinction ratio of >20 dB in the bar state and >25 dB in the cross state around 1578 nm wavelength. The insertion loss is 2 dB and 7 dB for the bar and cross states, respectively.

关键词： Optical waveguides Silicon Optical switches Directional couplers Optical refraction Optical variables control Photonics

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First characterization of the emission behavior of Mrk421 from radio to VHE gamma rays with simultaneous X-ray polarization measurements

arXiv

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arXiv 2023年

作者： Abe, S. Abhir, J. Acciari, V.A. Agudo, I. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Baxter, J. Becerra González, J. Bednarek, W. Bernardini, E. Bernete, J. Berti, A. Besenrieder, J. Bigongiari, C. Biland, A. Blanch, O. Bonnoli, G. Bošnjak, Ž. Burelli, I. Busetto, G. Campoy-Ordaz, A. Carosi, A. Carosi, R. Carretero-Castrillo, M. Castro-Tirado, A.J. Ceribella, G. Chai, Y. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D'Ammando, F. D'Amico, G. D'Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. de Menezes, R. Del Popolo, A. Delgado, J. Delgado Mendez, C. Di Pierro, F. Di Venere, L. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Escudero, J. Fariña, L. Fattorini, A. Foffano, L. Font, L. Fröse, S. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Gradetzke, T. Grau, R. Green, D. Green, J.G. Günther, P. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Imazawa, R. Inada, T. Ishio, K. Jiménez Martínez, I. Jormanainen, J. Kerszberg, D. Kluge, G.W. Kobayashi, Y. Kouch, P.M. Kubo, H. Kushida, J. Láinez Lezáun, M. Lamastra, A. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Mang, N. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Martínez-Chicharro, M. Mas-Aguilar, A. Mazin, D. Menchiari, S. Mender, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molero González, M. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, D. Nakamori, T. Nanci, C. Nava, L. Neustroev, V. Nickel, L. Nievas Rosillo, M. Nigro, C. Nikolić, L. Nilsson, K. Nishijima, K. Njoh Ekoume, T. Noda, K. Nozaki, S. The University of Tokyo Chiba Kashiwa277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Instituto de Astrofísica de Andalucía CSIC Glorieta de la As-tronomía s/n Granada18008 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Com-plutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Departament de Física CERES IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Department for Physics and Technology University of Bergen Norway INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento In-terateneo di Fisica Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Faculty of Physics Rijeka51000 Croatia Technische Universität Dortmund DortmundD-44221 Germany University of Geneva Chemin d'Ecogia 16 VersoixCH-1290 Switzerland Japanese MAGIC Group: Physics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima739-8526 Japan ZeuthenD-15738 Germany Armenian MAGIC Group: ICRANet-Armenia Yerevan0019 Armenia Split21000 Croatia Universität Würzburg Würzb

Aims. We perform the first broadband study of Mrk 421 from radio to TeV gamma rays with simultaneous measurements of the X-ray polarization from IXPE. Methods. The data were collected within an extensive multiwavelength campaign organized between May and June 2022 using MAGIC, FermiLAT, NuSTAR, XMM-Newton, Swift, and several optical and radio telescopes to complement IXPE. Results. During the IXPE exposures, the measured 0.2-1 TeV flux is close to the quiescent state and ranges from 25% to 50% of the Crab Nebula without intra-night variability. Throughout the campaign, the VHE and X-ray emission are positively correlated at a 4σ significance level. The IXPE measurements unveil a X-ray polarization degree that is a factor of 2-5 higher than in the optical/radio bands;that implies an energy-stratified jet in which the VHE photons are emitted co-spatially with the X-rays, in the vicinity of a shock front. The June 2022 observations exhibit a rotation of the X-ray polarization angle. Despite no simultaneous VHE coverage being available during a large fraction of the swing, the Swift-XRT monitoring unveils an X-ray flux increase with a clear spectral hardening. It suggests that flares in high synchrotron peaked blazars can be accompanied by a polarization angle rotation, as observed in some flat spectrum radio quasars. Finally, during the polarization angle rotation, NuSTAR data reveal two contiguous spectral hysteresis loops in opposite directions (clockwise and counter-clockwise), implying important changes in the particle acceleration efficiency on ∼hour timescales. Copyright © 2023, The Authors. All rights reserved.

关键词： Gamma rays

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Author Correction: Genetic effects on the timing of parturition and links to fetal birth weight

引用

Nature genetics 2023年第7期55卷 1250页

作者： Pol Solé-Navais Christopher Flatley Valgerdur Steinthorsdottir Marc Vaudel Julius Juodakis Jing Chen Triin Laisk Abigail L LaBella David Westergaard Jonas Bacelis Ben Brumpton Line Skotte Maria C Borges Øyvind Helgeland Anubha Mahajan Matthias Wielscher Frederick Lin Catherine Briggs Carol A Wang Gunn-Helen Moen Robin N Beaumont Jonathan P Bradfield Abin Abraham Gudmar Thorleifsson Maiken E Gabrielsen Sisse R Ostrowski Dominika Modzelewska Ellen A Nohr Elina Hypponen Amit Srivastava Octavious Talbot Catherine Allard Scott M Williams Ramkumar Menon Beverley M Shields Gardar Sveinbjornsson Huan Xu Mads Melbye William Lowe Luigi Bouchard Emily Oken Ole B Pedersen Daniel F Gudbjartsson Christian Erikstrup Erik Sørensen Rolv T Lie Kari Teramo Mikko Hallman Thorhildur Juliusdottir Hakon Hakonarson Henrik Ullum Andrew T Hattersley Line Sletner Mario Merialdi Sheryl L Rifas-Shiman Thora Steingrimsdottir Denise Scholtens Christine Power Jane West Mette Nyegaard John A Capra Anne H Skogholt Per Magnus Ole A Andreassen Unnur Thorsteinsdottir Struan F A Grant Elisabeth Qvigstad Craig E Pennell Marie-France Hivert Geoffrey M Hayes Marjo-Riitta Jarvelin Mark I McCarthy Deborah A Lawlor Henriette S Nielsen Reedik Mägi Antonis Rokas Kristian Hveem Kari Stefansson Bjarke Feenstra Pål Njolstad Louis J Muglia Rachel M Freathy Stefan Johansson Ge Zhang Bo Jacobsson Department of Obstetrics and Gynaecology Sahlgrenska Academy Institute of Clinical Science University of Gothenburg Gothenburg Sweden. pol.sole.navais@gu.se. Department of Obstetrics and Gynaecology Sahlgrenska Academy Institute of Clinical Science University of Gothenburg Gothenburg Sweden. deCODE genetics/Amgen Reykjavik Iceland. Center for Diabetes Research Department of Clinical Science University of Bergen Bergen Norway. Division of Biomedical Informatics Cincinnati Children's Hospital Medical Center Cincinnati OH USA. Department of Pediatrics University of Cincinnati College of Medicine Cincinnati OH USA. Estonian Genome Centre Institute of Genomics University of Tartu Tartu Estonia. Department of Biological Sciences Vanderbilt University Nashville TN USA. Novo Nordisk Foundation Center for Protein Research University of Copenhagen Copenhagen Denmark. Department of Obstetrics and Gynaecology Copenhagen University Hospital Hvidovre Hvidovre Denmark. Methods and Analysis Statistics Denmark Copenhagen Denmark. K.G. Jebsen Center for Genetic Epidemiology Department of Public Health and Nursing Norwegian University of Science and Technology Trondheim Norway. Department of Epidemiology Research Statens Serum Institut Copenhagen Denmark. MRC Integrative Epidemiology Unit University of Bristol Bristol UK. Population Health Sciences Bristol Medical School University of Bristol Bristol UK. Department of Genetics and Bioinformatics Health Data and Digitalization Norwegian Institute of Public Health Oslo Norway. Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK. Genentech South San Francisco CA USA. Department of Epidemiology and Biostatistics MRC-PHE Centre for Environment and Health School of Public Health Imperial College London London UK. Department of Dermatology Medical University of Vienna Vienna Austria. Northwestern University Feinberg School of Medicine Chicago IL USA. Department of Population Medicine Harvard M

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Author Correction: Inferring structural variant cancer cell fraction

引用

Nature communications 2022年第1期13卷 7568页

作者： Marek Cmero Ke Yuan Cheng Soon Ong Jan Schröder Niall M Corcoran Tony Papenfuss Christopher M Hovens Florian Markowetz Geoff Macintyre Department of Surgery Division of Urology Royal Melbourne Hospital and University of Melbourne Parkville VIC 3050 Australia. cmerom@unimelb.edu.au. The Epworth Prostate Centre Epworth Hospital Richmond VIC 3121 Australia. cmerom@unimelb.edu.au. Department of Computing and Information Systems University of Melbourne Parkville VIC 3010 Australia. cmerom@unimelb.edu.au. Bioinformatics Division The Walter and Eliza Hall Institute of Medical Research Parkville VIC Australia. cmerom@unimelb.edu.au. Murdoch Children's Research Institute Parkville VIC 3052 Australia. cmerom@unimelb.edu.au. School of Computing Science University of Glasgow Sir Alwyn Williams Building Glasgow G12 8RZ UK. Cancer Research UK Cambridge Institute University of Cambridge Cambridge CB2 0RE UK. Electrical and Electronic Engineering University of Melbourne Parkville VIC 3010 Australia. Machine Learning Research Group Data61 Canberra ACT 2601 Australia. Research School of Computer Science Australian National University Canberra ACT 2601 Australia. Bioinformatics Division The Walter and Eliza Hall Institute of Medical Research Parkville VIC Australia. Department of Surgery Division of Urology Royal Melbourne Hospital and University of Melbourne Parkville VIC 3050 Australia. The Epworth Prostate Centre Epworth Hospital Richmond VIC 3121 Australia. Department of Computing and Information Systems University of Melbourne Parkville VIC 3010 Australia. geoff.macintyre@cruk.cam.ac.uk. Cancer Research UK Cambridge Institute University of Cambridge Cambridge CB2 0RE UK. geoff.macintyre@cruk.cam.ac.uk.

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Stochastic Proximal Gradient Consensus over Random Networks

Stochastic Proximal Gradient Consensus over Random Networks

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作者： Hong, Mingyi Chang, Tsung-Hui Department of Industrial and Manufacturing Systems Engineering Iowa State University AmesIA50021 United States School of Science and Engineering Chinese University of Hong Kong Shenzhen518172 China Shenzhen Research Institute of Big Data Shenzhen China

We consider solving a convex optimization problem with possibly stochastic gradient, and over a randomly time-varying multiagent network. Each agent has access to some local objective function, and it only has unbiased estimates of the gradients of the smooth component. We develop a dynamic stochastic proximal-gradient consensus algorithm, with the following key features: 1) it works for both the static and certain randomly time-varying networks;2) it allows the agents to utilize either the exact or stochastic gradient information;3) it is convergent with provable rate. In particular, the proposed algorithm converges to a global optimal solution, with a rate of \mathcal O(1/r) [resp. \mathcal O(1/r) when the exact (resp. stochastic) gradient is available, where r is the iteration counter. Interestingly, the developed algorithm establishes a close connection among a number of (seemingly unrelated) distributed algorithms, such as the EXTRA, the PG-EXTRA, the IC/IDC-ADMM, the DLM, and the classical distributed subgradient method. © 2017 IEEE.

关键词： Time varying networks

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Publisher Correction: An international perspective on the future of systemic sclerosis research

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Nature reviews. Rheumatology 2025年第4期21卷 249页

作者： David J Abraham Carol M Black Christopher P Denton Jörg H W Distler Robyn Domsic Carol Feghali-Bostwick Pravitt Gourh Monique Hinchcliff Fred Kolling Masataka Kuwana Robert Lafyatis Ulf Landegren J Matthew Mahoney Javier Martin Marco Matucci-Cerinic Zsuzsanna H McMahan Ana L Mora Luc Mouthon Marlene Rabinovitch Mauricio Rojas Kristofer Rubin Maria Trojanowska John Varga Michael L Whitfield Armando Gabrielli Thomas Krieg Department of Inflammation and Rare Diseases UCL Centre for Rheumatology UCL Division of Medicine Royal Free Hospital Campus London UK. david.abraham@ucl.ac.uk. Department of Inflammation and Rare Diseases UCL Centre for Rheumatology UCL Division of Medicine Royal Free Hospital Campus London UK. Department of Rheumatology University Hospital Düsseldorf Medical Faculty of the Heinrich-Heine University Düsseldorf Germany. Hiller Research Center University Hospital Düsseldorf Medical Faculty of Heinrich Heine University Düsseldorf Germany. Division of Rheumatology Department of Internal Medicine University of Pittsburgh Pittsburgh PA USA. Department of Medicine Division of Rheumatology and Immunology Medical University of South Carolina Charleston SC USA. Scleroderma Genomics and Health Disparities Unit National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of Health Bethesda MD USA. Division of Rheumatology Allergy and Immunology Department of Internal Medicine Yale School of Medicine New Haven CT USA. Geisel School of Medicine at Dartmouth Hanover NH USA. Department of Allergy and Rheumatology. Nippon Medical School Graduate School of Medicine Tokyo Japan. Division of Rheumatology and Clinical Immunology. University of Pittsburgh School of Medicine Pittsburgh PA USA. Department of Immunology Genetics and Pathology Research programme: Molecular Tools and Functional Genomics Uppsala University Uppsala Sweden. The Jackson Laboratory Bar Harbour ME USA. Department of Cell Biology and Immunology Institute of Parasitology and Biomedicine López-Neyra CSIC Granada Spain. Unit of Immunology Rheumatology Allergy and Rare Diseases and Inflammation fibrosis and aging Initiative IRCCS Ospedle San Raffaele and Vita Salute University San Raffaele Milan Italy. Department of Internal Medicine Division of Rheumatology UTHealth Houston Houston TX USA. Division of Pulmonary Critical Care and Sleep Medicine Davis Heart and Lung r

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Ensuring data confidentiality via plausibly cdeniable encryption and secure deletion-a survey

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网络空间安全科学与技术（英文版） 2018年第1期1卷 25-44页

作者： Qionglu Zhang Shijie Jia Bing Chang Bo Chen Data Assurance and Communication Security Research Center Chinese Academy of Sciences Beijing China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of SciencesBeijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Data Assurance and Communication Security Research Center Chinese Academy of Sciences Beijing China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of SciencesBeijing China School of Information Systems Singapore Management University Singapore Singapore Department of Computer Science Michigan Technological University Houghton USA

Ensuring confidentiality of sensitive data is of paramount importance,since data leakage may not only endanger data owners' privacy,but also ruin reputation of businesses as well as violate various regulations like HIPPA and Sarbanes-Oxley *** provide confidentiality guarantee,the data should be protected when they are preserved in the personal computing devices (i.e.,confidentiality during theirlifetime);and also,they should be rendered irrecoverable after they are removed from the devices (i.e.,confidentiality after their lifetime).Encryption and secure deletion are used to ensure data confidentiality during and after their lifetime,*** work aims to perform a thorough literature review on the techniques being used to protect confidentiality of the data in personal computing devices,including both encryption and secure *** for encryption,we mainly focus on the novel plausibly deniable encryption (PDE),which can ensure data confidentiality against both a coercive (i.e.,the attacker can coerce the data owner for the decryption key) and a non-coercive attacker.

关键词： data confidentiality Plausibly deniable encryption Secure deletion

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Not just privacy: Improving performance of private deep learning in mobile cloud

arXiv

引用

arXiv 2018年

作者： Wang, Ji Zhang, Jianguo Bao, Weidong Zhu, Xiaomin Cao, Bokai Yu, Philip S. College of Systems Engineering National University of Defense Technology Changsha China Department of Computer Science University of Illinois at Chicago Chicago United States College of Systems Engineering State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Facebook Inc. Menlo Park United States Department of Computer Science University of Illinois at Chicago Chicago United States Institute for Data Science Tsinghua University Beijing China

The increasing demand for on-device deep learning services calls for a highly efficient manner to deploy deep neural networks (DNNs) on mobile devices with limited capacity. The cloud-based solution is a promising approach to enabling deep learning applications on mobile devices where the large portions of a DNN are offloaded to the cloud. However, revealing data to the cloud leads to potential privacy risk. To benefit from the cloud data center without the privacy risk, we design, evaluate, and implement a cloud-based framework Arden which partitions the DNN across mobile devices and cloud data centers. A simple data transformation is performed on the mobile device, while the resource-hungry training and the complex inference rely on the cloud data center. To protect the sensitive information, a lightweight privacy-preserving mechanism consisting of arbitrary data nullification and random noise addition is introduced, which provides strong privacy guarantee. A rigorous privacy budget analysis is given. Nonetheless, the private perturbation to the original data inevitably has a negative impact on the performance of further inference on the cloud side. To mitigate this influence, we propose a noisy training method to enhance the cloud-side network robustness to perturbed data. Through the sophisticated design, Arden can not only preserve privacy but also improve the inference performance. To validate the proposed Arden, a series of experiments based on three image datasets and a real mobile application are conducted. The experimental results demonstrate the effectiveness of Arden. Finally, we implement Arden on a demo system to verify its practicality. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep neural networks

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Infinite factorial finite state machine for blind multiuser channel estimation

arXiv

引用

arXiv 2018年

作者： Ruiz, Francisco J.R. Valera, Isabel Svensson, Lennart Perez-Cruz, Fernando Department of Computer Science Columbia University in the City of New York United States Engineering Department University of Cambridge United Kingdom Department of Empirical Inference Max Planck Institute for Intelligent Systems in Tübingen Germany Department of Signal Processing and Communications University Carlos III Madrid Spain Chalmers University of Technology Gothenburg Sweden Swiss Data Science Center Zurich Switzerland

New communication standards need to deal with machine-to-machine communications, in which users may start or stop transmitting at any time in an asynchronous manner. Thus, the number of users is an unknown and time-varying parameter that needs to be accurately estimated in order to properly recover the symbols transmitted by all users in the system. In this paper, we address the problem of joint channel parameter and data estimation in a multiuser communication channel in which the number of transmitters is not known. For that purpose, we develop the infinite factorial finite state machine model, a Bayesian nonparametric model based on the Markov Indian buffet that allows for an unbounded number of transmitters with arbitrary channel length. We propose an inference algorithm that makes use of slice sampling and particle Gibbs with ancestor sampling. Our approach is fully blind as it does not require a prior channel estimation step, prior knowledge of the number of transmitters, or any signaling information. Our experimental results, loosely based on the LTE random access channel, show that the proposed approach can effectively recover the data-generating process for a wide range of scenarios, with varying number of transmitters, number of receivers, constellation order, channel length, and signal-to-noise ratio. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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Penetrance of neurodevelopmental copy number variants is associated with variations in cortical morphology

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Biological psychiatry. Cognitive neuroscience and neuroimaging 2025年

作者： Ana I Silva Ida E Sønderby George Kirov Abdel Abdellaoui Ingrid Agartz David Ames Nicola J Armstrong Eric Artiges Tobias Banaschewski Anne S Bassett Carrie E Bearden John Blangero Rune Boen Dorret I Boomsma Robin Bülow Nancy J Butcher Vince Calhoun Linda E Campbell Eva W C Chow Simone Ciufolini Michael C Craig Benedicto Crespo-Farroco Adam C Cunningham Shareefa Dalvie Eileen Daly Paola Dazzan Eco J C de Geus Greig I de Zubicaray Joanne L Doherty Gary Donohoe Mark Drakesmith Thomas Espeseth Vincent Frouin Hugh Garavan David C Glahn Naomi J Goodrich-Hunsaker Penny A Gowland Hans J Grabe Antoine Grigis Maria Gudbrandsen Boris A Gutman Jan Haavik Asta K Håberg Jeremy Hall Andreas Heinz Sarah Hohmann Jouke-Jan Hottenga Sébastien Jacquemont Neda Jahanshad Rachel K Jonas Derek K Jones Erik G Jönsson Sanne Koops Kuldeep Kumar Stephanie Le Hellard Herve Lemaitre Jingyu Liu Astri J Lundervold Jean-Luc Martinot Karen A Mather Donna M McDonald-McGinn Katie L McMahon Allan F McRae Sarah E Medland Clara A Moreau Kieran C Murphy Declan Murphy Robin M Murray Frauke Nees Michael J Owen Marie-Laure Paillère Martinot Diimitri Papadopoulos Orfanos Tomas Paus Luise Poustka Tiago Reis Marques David R Roalf Perminder S Sachdev Freda Scheffler J Eric Schmitt Gunter Schumann Vidar M Steen Dan J Stein Lachlan T Strike Alexander Teumer Anbupalam Thalamuthu Sophia I Thomopoulos Diana Tordesillas-Gutiérrez Julian N Trollor Anne Uhlmann Ariana Vajdi Dennis van 't Ent Therese van Amelsvoort Marianne B M van den Bree Dennis van der Meer Javier Vázquez-Bourgon Julio E Villalón-Reina Uwe Völker Henry Völzke Jacob A S Vorstman Lars T Westlye Nigel Williams Katharina Wittfeld Margaret J Wright Paul M Thompson Ole A Andreassen David E J Linden School for Mental Health and Neuroscience Department of Psychiatry and Neuropsychology Faculty of Health Medicine and Life Sciences Maastricht University Maastricht The Netherlands Neuroscience and Mental Health Innovation Institute Cardiff University Cardiff United Kingdom Center for Magnetic Resonance Research Department of Radiology University of Minnesota Minneapolis MN USA. Electronic address: silvaai@um.edu. Centre for Precision Psychiatry Institute of Clinical Medicine University of Oslo Oslo Norway Department of Medical Genetics Oslo University Hospital Oslo Norway KG Jebsen Centre for Neurodevelopmental Disorders University of Oslo Oslo Norway. Division of Psychological Medicine and Clinical Neurosciences Cardiff University Cardiff United Kingdom Centre for Neuropsychiatric Genetics and Genomics School of Medicine Cardiff University Cardiff United Kingdom. Department of Psychiatry Amsterdam UMC University of Amsterdam Amsterdam the Netherlands. Norwegian Centre for Mental Disorders Research (NORMENT) Institute of Clinical Medicine University of Oslo Oslo Norway Centre for Psychiatry Research Department of Clinical Neuroscience Karolinska Institutet & Stockholm Health Care Services Stockholm Region Stockholm Sweden Department of Psychiatric Research Diakonhjemmet Hospital Oslo Norway. University of Melbourne Academic Unit for Psychiatry of Old Age Kew Victoria Australia. Mathematics and Statistics Curtin University Perth WA Australia. Institut National de la Santé et de la Recherche Médicale INSERM U1299 "Trajectoires développementales et psychiatrie" Université Paris-Saclay Ecole Normale supérieure Paris-Saclay CNRS Centre Borelli Gif-sur-Yvette France Psychiatry Department EPS Barthélémy Durand Etampes Île-de-France France. Department of Child and Adolescent Psychiatry and Psychotherapy Central Institute of Mental Health Medical Faculty Mannheim University of Heidelberg Mannheim Germany. Clinical Genetics Research Program Centre for

BACKGROUND:Copy number variants (CNVs) increase risk for neurodevelopmental conditions. The neurobiological mechanisms linking these high-risk genetic variants to clinical phenotypes are largely unknown. An important question is whether brain abnormalities in individuals carrying CNVs are associated with their degree of penetrance. METHODS:We investigated if increased CNV-penetrance for schizophrenia and other developmental disorders was associated with variations in cortical and subcortical morphology. We pooled T1-weighted brain magnetic resonance imaging and genetic data from 22 cohorts from the ENIGMA-CNV consortium. In the main analyses, we included 9,268 individuals (aged 7 to 90 years, 54% females), from which we identified 398 carriers of 36 neurodevelopmental CNVs at 20 distinct loci. A secondary analysis was performed including additional neuroimaging data from the ENIGMA-22q consortium, including 274 carriers of the 22q11.2 deletion and 291 non-carriers. CNV-penetrance was estimated through penetrance scores that were previously generated from large cohorts of patients and controls. These scores represent the probability risk to develop either schizophrenia or other developmental disorders (including developmental delay, autism spectrum disorder and congenital malformations). RESULTS:For both schizophrenia and developmental disorders, increased penetrance scores were associated with lower surface area in the cerebral cortex and lower intracranial volume. For both conditions, associations between CNV-penetrance scores and cortical surface area were strongest in regions of the occipital lobes, specifically in the cuneus and lingual gyrus. CONCLUSIONS:Our findings link global and regional cortical morphometric features with CNV-penetrance, providing new insights into neurobiological mechanisms of genetic risk for schizophrenia and other developmental disorders.

关键词： autism neuroimaging psychiatric disorders schizophrenia structural imaging

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