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A human immune dysregulation syndrome characterized by severe hyperinflammation with a homozygous nonsense Roquin-1 mutation (vol 10, 4779 , 2019)

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NATURE COMMUNICATIONS 2019年第1期10卷 1-16页

作者： Tavernier, S. J. Athanasopoulos, V. Verloo, P. Behrens, G. Staal, J. Bogaert, D. J. Naesens, L. De Bruyne, M. Van Gassen, S. Parthoens, E. Ellyard, J. Cappello, J. Morris, L. X. Van Gorp, H. Van Isterdael, G. Saeys, Y. Lamkanfi, M. Schelstraete, P. Dehoorne, J. Bordon, V. Van Coster, R. Lambrecht, B. N. Menten, B. Beyaert, R. Vinuesa, C. G. Heissmeyer, V. Dullaers, M. Haerynck, F. Primary Immune Deficiency Research Lab Department of Internal Medicine and Pediatrics Centre for Primary Immunodeficiency Ghent Jeffrey Modell Diagnosis and Research Centre Ghent University Hospital Ghent Belgium VIB Center for Inflammation Research Unit of Molecular Signal Transduction in Inflammation Ghent Belgium Department of Biomedical Molecular Biology Ghent University Ghent Belgium Department of Immunology and Infectious Disease and Center for Personalised Immunology (NHMRC Centre for Research Excellence) John Curtin School of Medical Research Australian National University Canberra Australia Centre for Personalised Immunology (CACPI) Shanghai Renji Hospital Shanghai Jiao Tong University Shanghai China Department of Internal Medicine and Pediatrics Division of Pediatric Neurology and Metabolism Ghent University Hospital Ghent Belgium Institute for Immunology Biomedical Center Ludwig-Maximilians-Universität München Planegg-Martinsried Germany Research Unit Molecular Immune Regulation Helmholtz Zentrum München Munich Germany Department of Internal Medicine and Pediatrics Division of Pediatric Immunology and Pulmonology Ghent University Hospital Ghent Belgium Department of Internal Medicine and Pediatrics Ghent University Hospital Ghent Belgium Center for Medical Genetics Ghent University Hospital Ghent Belgium VIB Center for Inflammation Research Unit of Data Mining and Modeling for Biomedicine Ghent Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Gent Belgium VIB Bioimaging Core VIB Center for Inflammation Research Ghent Belgium The Australian Phenomics Facility John Curtin School of Medical Research Australian National University Canberra Australia VIB Center for Inflammation Research Ghent Belgium VIB Flow Core VIB Center for Inflammation Research Ghent Belgium Department of Internal Medicine and Pediatrics Division of Pediatric Rheumatology Ghent University Hospital Ghent Belgium Department of Inter

Hyperinflammatory syndromes are life-threatening disorders caused by overzealous immune cell activation and cytokine release, often resulting from defects in negative feedback mechanisms. In the quintessential hyperinflammatory syndrome familial hemophagocytic lymphohistiocytosis (HLH), inborn errors of cytotoxicity result in effector cell accumulation, immune dysregulation and, if untreated, tissue damage and death. Here, we describe a human case with a homozygous nonsense R688* RC3H1 mutation suffering from hyperinflammation, presenting as relapsing HLH. RC3H1 encodes Roquin-1, a posttranscriptional repressor of immune-regulatory proteins such as ICOS, OX40 and TNF. Comparing the R688* variant with the murine M199R variant reveals a phenotypic resemblance, both in immune cell activation, hypercytokinemia and disease development. Mechanistically, R688* Roquin-1 fails to localize to P-bodies and interact with the CCR4-NOT deadenylation complex, impeding mRNA decay and dysregulating cytokine production. The results from this unique case suggest that impaired Roquin-1 function provokes hyperinflammation by a failure to quench immune activation.

关键词： Disease genetics Inflammation Primary immunodeficiency disorders RNA decay

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Optomechanically Induced Birefringence and Optomechanically Induced Faraday Effect

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Physical Review Letters 2019年第2期123卷 023602-023602页

作者： Robert Duggan Javier del Pino Ewold Verhagen Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Center for Nanophotonics AMOLF Science Park 104 1098 XG Amsterdam The Netherlands Photonics Initiative Advanced Science Research Center City University of New York New York 10031 USA Physics Program Graduate Center City University of New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

We demonstrate an optomechanical platform where optical mode conversion mediated by mechanical motion enables the arbitrary tailoring of polarization states of propagating light fields. Optomechanical interactions are realized in a Fabry-Pérot resonator, which naturally supports two polarization-degenerate states while an optical control field induces rotational symmetry breaking. Applying such principles, the entire Poincaré sphere is spanned by just optical control of the driving field, realizing reciprocal and nonreciprocal optomechanically induced birefringence for linearly polarized and circularly polarized control driving. A straightforward extension of this setup also enables all-optical tunable isolation and circulation. Our findings open new avenues to exploit optomechanics for the arbitrary manipulation of light polarization.

关键词： Nonlinear optics Optomechanics

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A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks

A One-step Pruning-recovery Framework for Acceleration of Co...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Dong Wang Xiao Bai Lei Zhou Jun Zhou School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Jiangxi Research Institute Beihang University Beijing China School of Information and Communication Technology Griffith University Queensland Australia

Acceleration of convolutional neural network has received increasing attention during the past several years. Among various acceleration techniques, filter pruning has its inherent merit by effectively reducing the number of convolution filters. However, most filter pruning methods resort to tedious and time-consuming layer-by-layer pruning-recovery strategy to avoid a significant drop of accuracy. In this paper, we present an efficient filter pruning framework to solve this problem. Our method accelerates the network in one-step pruning-recovery manner with a novel optimization objective function, which achieves higher accuracy with much less cost compared with existing pruning methods. Furthermore, our method allows network compression with global filter pruning. Given a global pruning rate, it can adaptively determine the pruning rate for each single convolutional layer, while these rates are often set as hyper-parameters in previous approaches. Evaluated on VGG- 16 and ResNet-50 using ImageNet, our approach outperforms several state-of-the-art methods with less accuracy drop under the same and even much fewer floating-point operations (FLOPs).

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Giant Chern number of a Weyl nodal surface without upper limit

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Physical Review B 2022年第11期105卷 115118-115118页

作者： J.-Z. Ma S.-N. Zhang J. P. Song Q.-S. Wu S. A. Ekahana M. Naamneh M. Radovic V. N. Strocov S.-Y. Gao T. Qian H. Ding K. He K. Manna C. Felser N. C. Plumb O. V. Yazyev Y.-M. Xiong M. Shi Department of Physics City University of Hong Kong Kowloon Hong Kong China Photon Science Division Paul Scherrer Institute CH-5232 Villigen PSI Switzerland City University of Hong Kong Shenzhen Research Institute Shenzhen China Hong Kong Institute for Advanced Study City University of Hong Kong Kowloon Hong Kong China Institute of Physics École Polytechnique Fédérale de Lausanne CH-10 15 Lausanne Switzerland National Center for Computational Design and Discovery of Novel Materials MARVEL École Polytechnique Fédérale de Lausanne (EPFL) CH-1015 Lausanne Switzerland Anhui Key Laboratory of Condensed Matter Physics at Extreme Conditions High Magnetic Field Laboratory HFIPS Anhui Chinese Academy of Sciences Hefei 230031 China University of Science and Technology of China Hefei Anhui 230026 China Department of Physics Ben-Gurion University of the Negev Beer-Sheva 84105 Israel Beijing National Laboratory for Condensed Matter Physics and Institute of Physics Chinese Academy of Sciences Beijing 100190 China Songshan Lake Materials Laboratory Dongguan Guangdong China CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing 100049 China Department of Physics Tsinghua University Beijing 100084 China Max Planck Institute for Chemical Physics of Solids Dresden D-01187 Germany Department of Physics Indian Institute of Technology Delhi Hauz Khas New Delhi 110016 India Department of Physics School of Physics and Optoelectronics Engineering Anhui University Hefei 230601 China

Weyl nodes can be classified into zero-dimensional (0D) Weyl points, 1D Weyl nodal lines, and 2D Weyl nodal surfaces (WNS), which possess finite Chern numbers. Up to date, the largest Chern number of WPs identified in Weyl semimetals is 4, which is thought to be a maximal value for linearly crossing points in solids. On the other hand, whether the Chern numbers of nonzero-dimensional linear crossing Weyl nodal objects have one upper limit is still an open question. In this work, combining angle-resolved photoemission spectroscopy with density-functional theory calculations, we show that the chiral crystal AlPt hosts a cube-shaped charged WNS which is formed by the linear crossings of two singly degenerate bands. Different from conventional Weyl nodes, the cube-shaped nodal surface in AlPt is enforced by nonsymmorphic chiral symmetries and time-reversal symmetry rather than accidental band crossings, and it possesses a giant Chern number |C|=26. Moreover, our results and analysis prove that there is no upper limit for the Chern numbers of such kind of 2D Weyl nodal object.

关键词： Electronic structure First-principles calculations Symmetry protected topological states Topological materials Weyl semimetal Angle-resolved photoemission spectroscopy Density functional calculations

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Matching for the israeli 'mechinot' gap-year programs: Handling rich diversity requirements

arXiv

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arXiv 2019年

作者： Gonczarowski, Yannai A. Kovalio, Lior Nisan, Noam Romm, Assaf Einstein Institute of Mathematics Rachel and Selim Benin School of Computer Science and Engineering Fe-dermann Center for the Study of Rationality Hebrew University of Jerusalem Israel Microsoft Research Rachel and Selim Benin School of Computer Science and Engineering Hebrew University of Jerusalem Israel Federmann Center for the Study of Rationality Hebrew University of Jerusalem Israel Department of Economics Federmann Center for the Study of Rationality Hebrew University of Jerusalem Israel

We describe our experience with designing and running a matching market for the Israeli "Mechinot" gap-year programs. The main conceptual challenge in the design of this market was the rich set of diversity considerations, which necessitated the development of an appropriate preference-specification language along with corresponding choice-function semantics, which we also theoretically analyze to a certain extent. This market was run for the first time in January 2018 and matched 1,607 candidates (out of a total of 2,580 candidates) to 35 different programs, and has been adopted by the Joint Council of the "Mechinot" gap-year programs for the foreseeable future. Copyright © 2019, The Authors. All rights reserved.

关键词： Specification languages

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Search for an isotropic gravitational-wave background with the Parkes Pulsar Timing Array

arXiv

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arXiv 2023年

作者： Reardon, Daniel J. Zic, Andrew Shannon, Ryan M. Hobbs, George B. Bailes, Matthew Di Marco, Valentina Kapur, Agastya Rogers, Axl F. Thrane, Eric Askew, Jacob Ramesh Bhat, N.D. Cameron, Andrew Curylo, Malgorzata Coles, William A. Dai, Shi Goncharov, Boris Kerr, Matthew Kulkarni, Atharva Levin, Yuri Lower, Marcus E. Manchester, Richard N. Mandow, Rami Miles, Matthew T. Nathan, Rowina S. Oslowski, Stefan Russell, Christopher J. Spiewak, Renée Zhang, Songbo Zhu, Xing-Jiang Centre for Astrophysics and Supercomputing Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia OzGrav: The Australian Research Council Centre of Excellence for Gravitational Wave Discovery HawthornVIC3122 Australia Australia Telescope National Facility CSIRO Space and Astronomy P.O. Box 76 EppingNSW1710 Australia Department of Physics and Astronomy MQ Research Centre in Astronomy Astrophysics and Astrophotonics Macquarie University NSW2109 Australia School of Physics and Astronomy Monash University VIC3800 Australia OzGrav: The Australian Research Council Centre of Excellence for Gravitational Wave Discovery ClaytonVIC3800 Australia Institute for Radio Astronomy & Space Research Auckland University of Technology Private Bag 92006 Auckland1142 New Zealand International Centre for Radio Astronomy Research Curtin University BentleyWA6102 Australia Astronomical Observatory University of Warsaw Aleje Ujazdowskie 4 Warsaw00-478 Poland Electrical and Computer Engineering University of California La Jolla San DiegoCA United States School of Science Western Sydney University Locked Bag 1797 Penrith South DCNSW2751 Australia L'AquilaI-67100 Italy INFN Laboratori Nazionali del Gran Sasso AssergiI-67100 Italy Space Science Division US Naval Research Laboratory 4555 Overlook Ave SW WashingtonDC20375 United States Physics Department Columbia Astrophysics Laboratory Columbia University 538 West 120th Street New YorkNY10027 United States Center for Computational Astrophysics Flatiron Institute 162 5th Ave NY10011 United States Manly Astrophysics 15/41-42 East Esplanade ManlyNSW2095 Australia CSIRO Scientific Computing Australian Technology Park Locked Bag 9013 AlexandriaNSW1435 Australia Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy University of Manchester ManchesterM13 9PL United Kingdom Purple Mountain Observatory Chinese Academy of Sciences Nanjing210008 China Advanced Instit

Pulsar timing arrays aim to detect nanohertz-frequency gravitational waves (GWs). A background of GWs modulates pulsar arrival times and manifests as a stochastic process, common to all pulsars, with a signature spatial correlation. Here we describe a search for an isotropic stochastic gravitational-wave background (GWB) using observations of 30 millisecond pulsars from the third data release of the Parkes Pulsar Timing Array (PPTA), which spans 18 years. Using current Bayesian inference techniques we recover and characterize a common-spectrum noise process. Represented as a strain spectrum hc = A(f/1yr−1)α, we measure (Equation presented) and α = −0.45 ± 0.20 respectively (median and 68% credible interval). For a spectral index of α = −2/3, corresponding to an isotropic background of GWs radiated by inspiraling supermassive black hole binaries, we recover an amplitude of (Equation presented). However, we demonstrate that the apparent signal strength is time-dependent, as the first half of our data set can be used to place an upper limit on A that is in tension with the inferred common-spectrum amplitude using the complete data set. We search for spatial correlations in the observations by hierarchically analyzing individual pulsar pairs, which also allows for significance validation through randomizing pulsar positions on the sky. For a process with α = −2/3, we measure spatial correlations consistent with a GWB, with an estimated false-alarm probability of p. 0.02 (approx. 2σ). The long timing baselines of the PPTA and the access to southern pulsars will continue to play an important role in the International Pulsar Timing Array. Copyright © 2023, The Authors. All rights reserved.

关键词： Pulsars

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RIS-assisted SATINs with RSMA and DRL: A Trade-off between Spectral, Secrecy, and Energy Efficiency

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IEEE Transactions on Communications 2025年

作者： Wu, Min Guo, Kefeng Li, Xingwang Lin, Zhi Yang, Liang Tsiftsis, Theodoros A. Yuen, Chau Beihang University Institute of Artificial Intelligence Beijing100191 China Beihang University Bejing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing100191 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing210016 China Space Engineering University School of Space Information Beijing101407 China Henan Polytechnic University School of Physics and Electronic Information Engineering Jiaozuo454003 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China National University of Defense Technology College of Electronic Engineering China Anhui Province Key Laboratory of Electronic Restriction Hefei230037 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece Nanyang Technological University School of Electrical and Electronics Engineering 50 Nanyang Ave 639798 Singapore

Given the rapid growth of diverse communication demands, future large-scale satellite-aerial-terrestrial integrated networks (SATINs) need to simultaneously provide services to users while guaranteeing spectral efficiency, secrecy and energy efficiency. This paper addresses the problem of maximising secrecy energy efficiency (SEE) in SATINs, which can accurately describe the effective trade-off between security, spectral efficiency and transmit power. Particularly, we investigate a secure beamforming (BF) scheme in cognitive SATINs that employs rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) in the presence of multiple eavesdroppers (Eves) in a UAV-aided secondary network (SN). To optimize the SEE for secondary vehicle users while satisfying the constraints of primary users (PUs), we utilize deep reinforcement learning (DRL) to address the coupling between different optimized parameters based on the improved long short-term memory proximal policy optimization (LSTM-PPO) algorithm. The main innovation of this paper is to design a sophisticated reward function, action space, and state space according to each constraint to speed up the convergence. In addition, simulation results show that the proposed DRL-based optimization scheme exhibits significant advantages in terms of SEE compared with benchmark schemes, validating the effectiveness of this work. © 1972-2012 IEEE.

关键词： Reinforcement learning

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Erratum to: Deep learning-based MR fingerprinting ASL ReconStruction (DeepMARS) (Magn Reson Med. 2020;84:1024-1034)

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Magnetic resonance in medicine 2022年第3期89卷 2022 Dec 9页

作者： Qiang Zhang Pan Su Zhensen Chen Ying Liao Shuo Chen Rui Guo Haikun Qi Xuesong Li Xue Zhang Zhangxuan Hu Hanzhang Lu Huijun Chen School of Medicine Center for Biomedical Imaging Research Tsinghua University Beijing China. The Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine Baltimore Maryland USA. Center for Biomedical Imaging Department of Radiology New York University School of Medicine New York USA. Center for Biomedical Imaging Research Department of Biomedical Engineering School of Medicine Tsinghua University Beijing China. Department of Medicine Cardiovascular Division Beth Israel Deaconess Medical Center Boston Massachusetts USA. School of Biomedical Engineering ShanghaiTech University Shanghai China. School of Computer Science and Technology Beijing Institute of Technology Beijing China. The Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore USA. Department of Biomedical Engineering School of Medicine Center for Biomedical Imaging Research Tsinghua University Beijing China.

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Metastatic State of Colorectal Cancer can be Accurately Predicted with Methylome 19

Metastatic State of Colorectal Cancer can be Accurately Pred...

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Proceedings of the 6th International Conference on Bioinformatics research and Applications

作者： Somayah Albaradei Maha Thafar Christophe Van Neste Magbubah Essack Vladimir B. Bajic King Abdullah University of Science and Technology Computational Bioscience Research Center (CBRC) Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division Thuwal Kingdom of Saudi Arabia King Abdulaziz University Jeddah Kingdom of Saudi Arabia Thuwal Kingdom of Saudi Arabia Taif University Taif Kingdom of Saudi Arabia Thuwal Kingdom of Saudi Arabia Ghent University Center for Medical Genetics Ghent (CMGG) Ghent Belgium Thuwal Kingdom of Saudi Arabia

ISBN: (纸本)9781450372183

Colorectal cancer (CRC) appears to be the third most common cancer as well as the fourth most common cause of cancer deaths in the world. Its most lethal states are when it becomes metastatic. It is of interest to find tests that can quickly and accurately determine if the patient has already developed metastasis. Changes in methylation profiles have been found to be characteristic of cancers at different stages and can therefore be used to develop diagnostic panels. We developed a deep learning (DL) model (Deep2Met) using methylation profiles of patients with CRC to predict if the cancer is in its metastatic state. Results suggest that our method achieves an AUPR and an average F-score of 96.99% and 94.71%, respectively, making Deep2Met potentially useful for diagnostic purposes. The DL model Deep2Met we developed, shows promise in the diagnosis of CRC based on methylation profiles of individual patients.

关键词： Computational biology Convolutional neural networks Deep learning Metastasis Bioinformatics DNA methylation Colorectal cancer

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Erratum: “Enhanced acoustic pressure sensors based on coherent perfect absorber-laser effect” [J. Appl. Phys. 129, 104902 (2021)]

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Journal of Applied Physics 2021年第22期129卷

作者： Mohamed Farhat Waqas W. Ahmad Abdelkrim Khelif Khaled N. Salama Ying Wu 1Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia 2Institut FEMTO-ST CNRS Universite de Bourgogne Franche-Comte 25000 Besancon France 3Sensors Lab Advanced Membranes & Porous Materials Center (AMPMC) King Abdullah University of Science and Technology (KAUST) Thuwal 23955 Saudi Arabia

There is a typo in Eq. (2) of the original paper.1 The corrected form of this equation is

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