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arXiv 2024年

作者： Schulte, Jack Rodriguez, Joseph E. Bieryla, Allyson Quinn, Samuel N. Collins, Karen A. Yee, Samuel W. Nine, Andrew C. Soares-Furtado, Melinda Latham, David W. Eastman, Jason D. Barkaoui, Khalid Ciardi, David R. Dragomir, Diana Everett, Mark E. Giacalone, Steven Mireles, Ismael Murgas, Felipe Narita, Norio Shporer, Avi Strakhov, Ivan A. Striegel, Stephanie Vaňko, Martin Vowell, Noah Wang, Gavin Ziegler, Carl Bellaver, Michael Benni, Paul Bergeron, Serge Boffin, Henri M.J. Briceño, César Clark, Catherine A. Collins, Kevin I. de Leon, Jerome P. Dressing, Courtney D. Evans, Phil Esparza-Borges, Emma Fedewa, Jeremy Fukui, Akihiko Gan, Tianjun Gerasimov, Ivan S. Hartman, Joel D. Gill, Holden Gillon, Michaël Horne, Keith Horta, Ferran Grau Howell, Steve B. Isogai, Keisuke Jehin, Emmanuël Jenkins, Jon M. Karjalainen, Raine Kielkopf, John F. Lester, Kathryn V. Littlefield, Colin Lund, Michael B. Mann, Andrew W. McCormack, Mason Michaels, Edward J. Painter, Shane Palle, Enric Parviainen, Hannu Peterson, David-Michael Pozuelos, Francisco J. Raup, Zachary Reed, Phillip Relles, Howard M. Ricker, George R. Savel, Arjun B. Schwarz, Richard P. Seager, S. Sefako, Ramotholo Srdoc, Gregor Stockdale, Chris Sullivan, Hannah Timmermans, Mathilde Winn, Joshua N. Center for Data Intensive and Time Domain Astronomy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Center for Astrophysics | Harvard & Smithsonian 60 Garden St CambridgeMA02138 United States Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08544 United States Department of Astronomy University of Wisconsin-Madison 475 N Charter St. MadisonWI53706 United States Department of Physics and Astronomy Carleton College 215 Goodsell Circle NorthfieldMN55057 United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States Astrobiology Research Unit Université de Liège 19C Allée du 6 Août Liège4000 Belgium Department of Earth Atmospheric and Planetary Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Tenerife La Laguna38200 Spain NASA Exoplanet Science Institute-Caltech IPAC PasadenaCA91125 United States Department of Physics and Astronomy University of New Mexico 210 Yale Blvd NE AlbuquerqueNM87106 United States NSF's National Optical-Infrared Astronomy Research Laboratory 950 N. Cherry Ave. TucsonAZ85719 United States Department of Astronomy California Institute of Technology PasadenaCA91125 United States Tenerife La Laguna38206 Spain Komaba Institute for Science The University of Tokyo 3-8-1 Komaba Meguro Tokyo153-8902 Japan Astrobiology Center 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Sternberg Astronomical Institute Lomonosov Moscow State University Universitetsky pr. 13 Moscow119234 Russia SETI Institute Mountain ViewCA94043 United States NASA Ames Research Center Moffett FieldCA94035 United States Astronomical Institute Slovak Academy of Sciences Tatranská Lomnica059 60 Slovakia Tsinghua International School Beijing100084 China Department of Physics Engineering and Astronomy Stephen F. Aust

Hot Jupiters were many of the first exoplanets discovered in the 1990s, but in the decades since their discovery, the mysteries surrounding their origins remain. Here, we present nine new hot Jupiters (TOI-1855 b, TOI-2107 b, TOI-2368 b, TOI-3321 b, TOI-3894 b, TOI-3919 b, TOI-4153 b, TOI-5232 b, and TOI-5301 b) discovered by NASA's TESS mission and confirmed using ground-based imaging and spectroscopy. These discoveries are the first in a series of papers named the Migration and Evolution of giant ExoPlanets (MEEP) survey and are part of an ongoing effort to build a complete sample of hot Jupiters orbiting FGK stars, with a limiting Gaia G-band magnitude of 12.5. This effort aims to use homogeneous detection and analysis techniques to generate a set of precisely measured stellar and planetary properties that is ripe for statistical analysis. The nine planets presented in this work occupy a range of masses (0.55 Jupiter masses (MJ) P J) and sizes (0.967 Jupiter radii (RJ) P J) and orbit stars that range in temperature from 5360 K eff Copyright © 2024, The Authors. All rights reserved.

关键词： Stars

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Author Correction: Opportunities and challenges of single-cell and spatially resolved genomics methods for neuroscience discovery

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Nature neuroscience 2025年第1期28卷 216页

作者： Boyan Bonev Gonçalo Castelo-Branco Fei Chen Simone Codeluppi M Ryan Corces Jean Fan Myriam Heiman Kenneth Harris Fumitaka Inoue Manolis Kellis Ariel Levine Mo Lotfollahi Chongyuan Luo Kristen R Maynard Mor Nitzan Vijay Ramani Rahul Satijia Lucas Schirmer Yin Shen Na Sun Gilad S Green Fabian Theis Xiao Wang Joshua D Welch Ozgun Gokce Genevieve Konopka Shane Liddelow Evan Macosko Omer Ali Bayraktar Naomi Habib Tomasz J Nowakowski Helmholtz Pioneer Campus Helmholtz Zentrum München Neuherberg Germany. Physiological Genomics Biomedical Center Ludwig-Maximilians-Universität München Munich Germany. Laboratory of Molecular Neurobiology Department of Medical Biochemistry and Biophysics Karolinska Institutet Stockholm Sweden. The Broad Institute of MIT and Harvard Cambridge MA USA. Moleculent Stockholm Sweden. Gladstone Institute of Neurological Disease San Francisco CA USA. Gladstone Institute of Data Science and Biotechnology San Francisco CA USA. Department of Neurology University of California San Francisco San Francisco CA USA. Department of Biomedical Engineering Johns Hopkins University Baltimore MD USA. Department of Brain and Cognitive Sciences MIT Cambridge MA USA. The Picower Institute for Learning and Memory MIT Cambridge MA USA. UCL Queen Square Institute of Neurology University College London London UK. Institute for the Advanced Study of Human Biology (WPI-ASHBi) Kyoto University Kyoto Japan. Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology Cambridge MA USA. Spinal Circuits and Plasticity Unit National Institute of Neurological Disorders and Stroke Bethesda MD USA. Institute of Computational Biology Helmholtz Center Munich - German Research Center for Environmental Health Neuherberg Germany. Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK. Department of Human Genetics University of California Los Angeles Los Angeles CA USA. Lieber Institute for Brain Development Baltimore MD USA. Department of Psychiatry Johns Hopkins School of Medicine Baltimore MD USA. Department of Neuroscience Johns Hopkins School of Medicine Baltimore MD USA. School of Computer Science and Engineering The Hebrew University of Jerusalem Jerusalem Israel. Racah Institute of Physics The Hebrew University of Jerusalem Jerusalem Israel. Faculty of Medicine The Hebrew University of Jerusalem Jerusalem Israel. Department of Biochemis

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Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Research Square

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Research Square 2021年

作者： Zhang, Martin Jinye Hou, Kangcheng Pasaniuc, Bogdan Price, Alkes L. Dey, Kushal K. Jagadeesh, Karthik A. Weinand, Kathryn Sakaue, Saori Taychameekiatchai, Aris Rao, Poorvi Pisco, Angela Oliveira Zou, James Wang, Bruce Gandal, Michael Raychaudhuri, Soumya Harvard University United States Osaka University Japan Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA United States Bioinformatics Interdepartmental Program University of California Los Angeles Los AngelesCA United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Center for Data Sciences Brigham and Women’s Hospital BostonMA United States Division of Genetics Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Division of Rheumatology Inflammation and Immunity Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Medicine and Liver Center University of California San Francisco San FranciscoCA United States Developmental and Stem Cell Biology Graduate Program University of California San Francisco San FranciscoCA United States Chan Zuckerberg Biohub San FranciscoCA United States Department of Electrical Engineering Stanford University Palo AltoCA United States Department of Biomedical Data Science Stanford University Palo AltoCA United States Department of Psychiatry David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Program in Neurobehavioral Genetics Semel Institute David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Versus Arthritis Centre for Genetics and Genomic

Gene expression at the individual cell-level resolution, as quantified by single-cell RNA-sequencing (scRNA-seq), can provide unique insights into the pathology and cellular origin of diseases and complex traits. Here, we introduce single-cell Disease Relevance Score (scDRS), an approach that links scRNA-seq with polygenic risk of disease at individual cell resolution;scDRS identifies individual cells that show excess expression levels for genes in a disease-specific gene set constructed from GWAS data. We determined via simulations that scDRS is well-calibrated and powerful in identifying individual cells associated to disease. We applied scDRS to GWAS data from 74 diseases and complex traits (average N =341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs. At the cell type level, scDRS broadly recapitulated known links between classical cell types and disease, and also produced novel biologically plausible findings. At the individual cell level, scDRS identified subpopulations of disease-associated cells that are not captured by existing cell type labels, including subpopulations of CD4+ T cells associated with inflammatory bowel disease, partially characterized by their effector-like states;subpopulations of hippocampal CA1 pyramidal neurons associated with schizophrenia, partially characterized by their spatial location at the proximal part of the hippocampal CA1 region;and subpopulations of hepatocytes associated with triglyceride levels, partially characterized by their higher ploidy levels. At the gene level, we determined that genes whose expression across individual cells was correlated with the scDRS score (thus reflecting co-expression with GWAS disease genes) were strongly enriched for gold-standard drug target and Mendelian disease genes. © 2021, CC BY.

关键词： RNA

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Dense matter with eXTP

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science China(Physics,Mechanics & Astronomy) 2019年第2期62卷 28-44页

作者： Anna L.Watts WenFei Yu Juri Poutanen Shu Zhang Sudip Bhattacharyya Slavko Bogdanov Long Ji Alessandro Patruno Thomas E.Riley Pavel Bakala Altan Baykal Federico Bernardini Ignazio Bombaci Edward Brown Yuri Cavecchi Deepto Chakrabarty Jér?me Chenevez Nathalie Degenaar Melania Del Santo Tiziana Di Salvo Victor Doroshenko Maurizio Falanga Robert D.Ferdman Marco Feroci Angelo F.Gambino MingYu Ge Svenja K.Greif Sebastien Guillot Can Gungor Dieter H.Hartmann Kai Hebeler Alexander Heger Jeroen Homan Rosario Iaria Jean in 't Zand Oleg Kargaltsev Aleksi KurkelaTheoretical Physics Department CERN XiaoYu Lai Ang Li XiangDong Li ZhaoSheng Li Manuel Linares FangJun Lu Simin Mahmoodifar Mariano Méndez M.Coleman Miller Sharon Morsink Joonas N?ttil? Andrea Possenti Chanda Prescod-Weinstein JinLu Qu Alessandro Riggio Tuomo Salmi Andrea Sanna Andrea Santangelo Hendrik Schatz Achim Schwenk LiMing Song Eva?rámková Benjamin Stappers Holger Stiele Tod Strohmayer Ingo Tews Laura Tolos Gabriel T?r?k David Tsang Martin Urbanec Andrea Vacchi RenXin Xu YuPeng Xu Silvia Zane GuoBao Zhang ShuangNan Zhang WenDa Zhang ShiJie Zheng Xia Zhou Anton Pannekoek Institute for Astronomy University of Amsterdam Shanghai Astronomical Observatory Tuorla Observatory Department of Physics and Astronomy University of Turku Nordita KTH Royal Institute of Technology and Stockholm University Institute of High Energy Physics Chinese Academy Sciences Tata Institute of Fundamental Research Columbia Astrophysics Laboratory Columbia University Institut für Astronomie und Astrophysik Tübingen Universit?t Tübingen Leiden Observatory Leiden University Research Center for Computational Physics and Data Processing Silesian University in Opava Physics Department Middle East Technical University INAF Osservatorio Astronomico di Roma New York University Abu Dhabi Dipartimento di Fisica Enrico Fermi University of Pisa INFN Italian National Institute for Nuclear Physics Department of Physics and Astronomy Michigan State University Department of Astrophysical Sciences Princeton University Mathematical Sciences and STAG Research Centre University of Southampton MIT Kavli Institute for Astrophysics and Space Research DTU Space Technical University of Denmark INAF/IASF Palermo via Ugo La Malfa 153 Universita degli Studi di Palermo Dipartimento di Fisica e Chimica International Space Science Institute (ISSI) Faculty of Science University of East Anglia INAF Istituto di Astrofisica e Planetologie Spaziali Institut für Kernphysik Technische Universit?t Darmstadt ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Instituto de Astrof'?sica Pontificia Universidad Católica de Chile Department of Physics & Astronomy Kinard Lab of Physics Clemson University School of Physics and Astronomy Monash University SRON Netherlands Institute for Space Research Department of Physics The George Washington University Faculty of Science and Technology University of Stavanger School of Physics and Mechanical & Electrical Engineering Hubei University of Education Department of Astronomy Xiamen University (Haiyun Campus) School of Astronomy and Space

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry(eXTP) mission for determining the nature of dense matter; neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of sciences, the eXTP mission is expected to be launched in the mid 2020 s.

关键词： neutron X-rays dense matter equation of state

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Analysis and computation of some tumor growth models with nutrient: From cell density models to free boundary dynamics

arXiv

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arXiv 2018年

作者： Liu, Jian-Guo Tang, Min Wang, Li Zhou, Zhennan Department of Mathematics Department of Physics Duke University School of Mathematics and Institute of Natural Sciences MOE-LSC Shanghai JiaoTong University Department of Mathematics Computational and Data-Enabled Science and Engineering Program State University of New York Buffalo United States Beijing International Center for Mathematical Research Peking University

In this paper, we study the tumor growth equation along with various models for the nutrient component, including the in vitro model and the in vivo model. At the cell density level, the spatial availability of the tumor density n is governed by the Darcy law via the pressure p\(n\) = nγ. For finite γ, we prove some a priori estimates of the tumor growth model, such as boundedness of the nutrient density, and non-negativity and growth estimate of the tumor density. As γ → ∞, the cell density models formally converge to Hele-Shaw flow models, which determine the free boundary dynamics of the tumor tissue in the incompressible limit. We derive several analytical solutions to the Hele-Shaw flow models, which serve as benchmark solutions to the geometric motion of tumor front propagation. Finally, we apply a conservative and positivity preserving numerical scheme to the cell density models, with numerical results verifying the link between cell density models and the free boundary dynamical *** Codes 35K55, 35B25, 76D27, 92C50 Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Blood pressure trajectories from early life and their association with cognitive function changes in midlife

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Alzheimer's & Dementia 2021年第S10期17卷

作者： Ileana De Anda-Duran Camilo Fernandez-Alonso Owen T Carmichael Rhoda Au Lydia Bazzano Vijaya B Kolachalama Tulane School of Public Health and Tropical Medicine New Orleans LA USA Tulane University New Orleans LA USA Pennington Biomedical Research Center Baton Rouge LA USA Boston University Alzheimer’s Disease Center Boston University Boston MA USA The Framingham Heart Study Boston University School of Medicine Boston University School of Public Health Boston MA USA Boston University Schools of Medicine & Public Health Boston MA USA Hariri Institute for Computing and Computational Science & Engineering Boston University Boston MA USA College of Arts & Sciences Boston University Boston MA USA Boston University School of Medicine Boston MA USA Faculty of Computing & Data Sciences Boston University Boston MA USA Whitaker Cardiovascular Institute Boston University School of Medicine Boston MA USA

Background Hypertension (HTN) is a well-established risk factor for cognitive impairment and dementia. HTN-induced vascular endothelium and smooth muscle damage have been described as pivotal components of the pathophysiological cascade over the life-course. While the impact on cognitive function (CF) changes has been studied from midlife- to old age, the impact from childhood to middle age exposure remains poorly understood. We aimed to explore this relationship in a community-based cohort of middle-age adults. Methods The analysis included a total of 342 adult participants (67.3% Woman, 38.9% African American) from the Bogalusa Heart Study, with CF assessments at two time points, baseline (age 48.8 ± 4.9 years) and follow-up (age 51.7 ± 5.2 years), and at least 3 observations of BP since childhood. CF change was assessed by computing the difference of the two timepoints standardized global cognitive score (GCS) obtained from a battery of tests covering major neuropsychological domains. Systolic BP (SBP) trajectories were created using latent class trajectory modeling. Mixed linear models with unstructured covariance were used to determine the association between SBP trajectories and CF changes in midlife. Results Mean CF assessment follow-up was 2.9 ± 0.6 years, and mean follow-up for BP and other traditional cardiovascular (CV) risk factors was 41.8 ± 3.4 years. Three distinct trajectory classes of SBP were identified: increasing to plateau (n=226 [66.1%]), moderate- (n=54 [15.8%]) and high- (n=62 [18.1%]) increasing (see Figure 1). With the increasing to plateau SBP trajectory as reference, and after adjustment for modifiable dementia risk factors and traditional CV risk factors, the high-increasing SBP trajectory was associated with greater decrease in GCS (β= -1.22 [95%CI -2.39, -0.07]; p =0.038). The moderate-increasing SBP trajectory showed no statistically significant association with GCS change (β= -1.00 [95%CI -2.23, - 0.22]; p =0.109). (see Table 1) Conc

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The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients

arXiv

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arXiv 2021年

作者： Baheti, Bhakti Chakrabarty, Satrajit Akbari, Hamed Bilello, Michel Wiestler, Benedikt Schwarting, Julian Calabrese, Evan Rudie, Jeffrey Abidi, Syed Mousa, Mina Villanueva-Meyer, Javier Fields, Brandon K.K. Kofler, Florian Shinohara, Russell Takeshi Iglesias, Juan Eugenio Mok, Tony C.W. Chung, Albert C.S. Wodzinski, Marek Jurgas, Artur Marini, Niccolò Atzori, Manfredo Müller, Henning Grosbröhmer, Christoph Siebert, Hanna Hansen, Lasse Heinrich, Mattias P. Canalini, Luca Klein, Jan Gerken, Annika Heldmann, Stefan Hering, Alessa Hahn, Horst K. Meng, Mingyuan Bi, Lei Feng, Dagan Kim, Jinman Zeineldinal, Ramy A. Karar, Mohamed E. Mathis-Ullrich, Franziska Burgert, Oliver Abderezaei, Javid Pionteck, Aymeric Chopra, Agamdeep Kurt, Mehmet Yan, Kewei Yan, Yonghong Tang, Zhe Ma, Jianqiang Nasser, Sahar Almahfouz Kurian, Nikhil Cherian Meena, Mohit Shamsi, Saqib Sethi, Amit Tustison, Nicholas J. Avants, Brian B. Cook, Philip Gee, James C. Tian, Lin Greer, Hastings Niethammer, Marc Hoopesar, Andrew Hoffmannas, Malte Dalcaar, Adrian V. Christodoulidis, Stergios Estiene, Théo Vakalopoulou, Maria Paragios, Nikos Marcus, Daniel S. Davatzikos, Christos Sotiras, Aristeidis Menze, Bjoern Bakas, Spyridon Waldmannstetter, Diana Division of Computational Pathology Department of Pathology and Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Department of Electrical and Systems Engineering Washington University in St. Louis St. LouisMO United States GE HealthCare San RamonCA United States University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Mallinckrodt Institute of Radiology Washington University School of Medicine St. LouisMO United States Institute for Informatics Data Science & Biostatistics Washington University School of Medicine St. LouisMO United States Department of Bioengineering Santa Clara University Santa ClaraCA United States Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Computer Science TUM School of Computation Information and Technology Technical University of Munich Munich Germany Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Munich Germany Department of Nuclear Medicine University Hospital Regensburg Regensburg Germany University Hospital Regensburg Regensburg Germany Department of Radiology & Biomedical Imaging University of California San FranciscoCA United States Department of Radiology Duke University Medical Center DurhamNC United States Department of Radiology University of California San DiegoCA United States Helmholtz AI Helmholtz Munich Neuherberg Germany Penn Statistics in Imaging and Visualization Center Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Philadelphia United States Massachusetts General Hospital Harvard Medical School United States Centre for Medical Imaging Computing University College London United Kingdom The Hong Kong University of Science and Technology Hong Kong University of Applied Sciences West

Registration of longitudinal brain Magnetic Resonance Imaging (MRI) scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been considerable progress in developing general-purpose medical image registration techniques, they have not yet attained the requisite precision and reliability for this task, highlighting its inherent complexity. Here we describe the Brain Tumor Sequence Registration (BraTS-Reg) challenge, as the first public benchmark environment for deformable registration algorithms focusing on estimating correspondences between pre-operative and follow-up scans of the same patient diagnosed with a diffuse brain glioma. The challenge was conducted in conjunction with both the IEEE International Symposium on Biomedical Imaging (ISBI) 2022 and the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. The BraTS-Reg data comprise de-identified multi-institutional multi-parametric MRI (mpMRI) scans, curated for size and resolution according to a canonical anatomical template, and divided into training, validation, and testing sets. Clinical experts annotated ground truth (GT) landmark points of anatomical locations distinct across the temporal domain. The training data with their GT annotations, were publicly released to enable the development of registration algorithms. The validation data, without their GT annotations, were also released to allow for algorithmic evaluation prior to the testing phase, which only allowed submission of containerized algorithms for evaluation on hidden hold-out testing data. Quantitative evaluation and ranking was based on the Median Euclidean Error (MEE), Robustness, and the determinant of the Jacobian of the displacement field. The top-ranked methodologies yielded similar performance across all evaluation metrics and shared several methodological commonalities, including pre-alignment, deep neural networks, inverse consistency

关键词： Magnetic resonance imaging

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SN 2022acko: the First Early Far-Ultraviolet Spectra of a Type IIP Supernova

arXiv

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arXiv 2023年

作者： Bostroem, K. Azalee Dessart, Luc Hillier, D. John Lundquist, Michael Andrews, Jennifer E. Sand, David J. Dong, Yize Valenti, Stefano Haislip, Joshua Hoang, Emily T. Hosseinzadeh, Griffin Janzen, Daryl Jencson, Jacob E. Jha, Saurabh W. Kouprianov, Vladimir Pearson, Jeniveve Meza Retamal, Nicolas E. Reichart, Daniel E. Shrestha, Manisha Ashall, Christopher Baron, E. Brown, Peter J. DerKacy, James M. Farah, Joseph Galbany, Lluís Hernández, J.I. González Green, Elizabeth Hoeflich, Peter Howell, D. Andrew Kwok, Lindsey A. McCully, Curtis Müller-Bravo, Tomás E. Newsome, Megan Gonzalez, Estefania Padilla Pellegrino, Craig Rho, Jeonghee Rowe, Micalyn Schwab, Michaela Shahbandeh, Melissa Smith, Nathan Strader, Jay Terreran, Giacomo Van Dyk, Schuyler D. Wyatt, Samuel Steward Observatory University of Arizona 933 North Cherry Avenue TucsonAZ85721-0065 United States Institut d’Astrophysique de Paris CNRS-Sorbonne Université 98 bis boulevard Arago Paris75014 France University of Pittsburgh 3941 O’Hara Street PittsburghPA15260 United States W. M. Keck Observatory 65-1120 Māmalahoa Highway KamuelaHI96743-8431 United States Gemini Observatory 670 North A‘ohoku Place HiloHI96720-2700 United States Department of Physics and Astronomy University of California Davis 1 Shields Avenue DavisCA95616-5270 United States Department of Physics and Astronomy University of North Carolina 120 East Cameron Avenue Chapel HillNC27599 United States Department of Physics and Engineering Physics University of Saskatchewan 116 Science Place SaskatoonSKS7N 5E2 Canada Department of Physics and Astronomy The Johns Hopkins University 3400 North Charles Street BaltimoreMD21218 United States Department of Physics and Astronomy Rutgers the State University of New Jersey 136 Frelinghuysen Road PiscatawayNJ08854-8019 United States Department of Physics Virginia Tech BlacksburgVA24061 United States Planetary Science Institute 1700 East Fort Lowell Suite 106 TucsonAZ85719-2395 United States Hamburger Sternwarte Gojenbergsweg 112 HamburgD-21029 Germany Homer L. Dodge Department of Physics and Astronomy University of Oklahoma 440 W. Brooks Rm 100 NormanOK73019-2061 United States Department of Physics and Astronomy Texas A&M University 4242 TAMU College StationTX77843 United States Las Cumbres Observatory 6740 Cortona Drive Suite 102 GoletaCA93117-5575 United States Department of Physics University of California Santa BarbaraCA93106-9530 United States Campus UAB Carrer de Can Magrans s/n BarcelonaE-08193 Spain Institut d’Estudis Espacials de Catalunya Gran Capità 2-4 Edifici Nexus Desp. 201 BarcelonaE-08034 Spain Instituto de Astrofísica de Canarias La Laguna TenerifeE-38205 Spain Universidad de La Lag

We present five far- and near-ultraviolet spectra of the Type II plateau supernova, SN 2022acko, obtained 5, 6, 7, 19, and 21 days after explosion, all observed with the Hubble Space Telescope/Space Telescope Imaging Spectrograph. The first three epochs are earlier than any Type II plateau supernova has been observed in the far-ultraviolet revealing unprecedented characteristics. These three spectra are dominated by strong lines, primarily from metals, which contrasts with the featureless early optical spectra. The flux decreases over the initial time series as the ejecta cool and line-blanketing takes effect. We model this unique dataset with the non-local thermodynamic equilibrium radiation transport code CMFGEN, finding a good match to the explosion of a low-mass red supergiant with energy Ekin = 6 × 1050 erg. With these models we identify, for the first time, the ions that dominate the early ultraviolet spectra. We present optical photometry and spectroscopy, showing that SN 2022acko has a peak absolute magnitude of V = −15.4 mag and plateau length of ∼ 115d. The spectra closely resemble those of SN 2005cs and SN 2012A. Using the combined optical and ultraviolet spectra, we report the fraction of flux as a function of bluest wavelength on days 5, 7, and 19. We create a spectral time-series of Type II supernovae in the ultraviolet, demonstrating the rapid decline of flux over the first few weeks of evolution. Future observations of Type II supernovae are required to map out the landscape of exploding red supergiants, with and without circumstellar material, which is best revealed in high-quality ultraviolet spectra. © 2023, CC BY.

关键词： Supernovae

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The first nova eruption in a novalike variable: YZ Ret as seen in X-rays and γ-rays

arXiv

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arXiv 2021年

作者： Sokolovsky, Kirill V. Li, Kwan-Lok de Oliveira, Raimundo Lopes Ness, Jan-Uwe Mukai, Koji Chomiuk, Laura Aydi, Elias Steinberg, Elad Vurm, Indrek Metzger, Brian D. Babul, Aliya-Nur Kawash, Adam Linford, Justin D. Nelson, Thomas Page, Kim L. Rupen, Michael P. Sokoloski, Jennifer L. Strader, Jay Kilkenny, David Center for Data Intensive and Time Domain Astronomy Department of Physics and Astronomy Michigan State University 567 Wilson Rd East LansingMI48824 United States Sternberg Astronomical Institute Moscow State University Universitetskii pr. 13 Moscow119992 Russia Department of Physics National Cheng Kung University Tainan70101 Taiwan Departamento de Astronomia Instituto de Astronomia Geofísica e Ciências Atmosféricas Universidade de São Paulo Cidade Universitária R. do Matão 1226 SP São Paulo05508-090 Brazil Departamento de Física Universidade Federal de Sergipe Av. Marechal Rondon S/N SE São Cristóvão49100-000 Brazil Observatório Nacional Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil European Space Astronomy Centre Camino Bajo del Castillo s/n Urb. Villafranca del Castillo Villanueva de la Cañada MadridE-28692 Spain CRESST and X-ray Astrophysics Laboratory NASA/GSFC GreenbeltMD20771 United States Racah Institute of Physics The Hebrew University Jerusalem9190401 Israel Tartu Observatory University of Tartu Tõravere Tartumaa 61602 Estonia Department of Physics Columbia Astrophysics Laboratory Columbia University New YorkNY10027 United States National Radio Astronomy Observatory Domenici Science Operations Center 1003 Lopezville Road SocorroNM87801 United States Department of Physics and Astronomy University of Pittsburgh PittsburghPA15260 United States School of Physics and Astronomy University of Leicester University Road LeicesterLE1 7RH United Kingdom National Research Council Herzberg Astronomy and Astrophysics 717 White Lake Rd PO Box 248 PentictonBCV2A 6J9 Canada Department of Physics & Astronomy University of the Western Cape Private Bag X17 Bellville7535 South Africa Center for Computational Astrophysics Flatiron Institute 162 5th Ave New YorkNY10010 United States

Peaking at 3.7 mag on 2020 July 11, YZ Ret was the second-brightest nova of the decade. The nova’s moderate proximity (2.7 kpc, from Gaia) provided an opportunity to explore its multi-wavelength properties in great detail. Here we report on YZ Ret as part of a long-term project to identify the physical mechanisms responsible for high-energy emission in classical novae. We use simultaneous Fermi/LAT and NuSTAR observations complemented by XMM-Newton X-ray grating spectroscopy to probe the physical parameters of the shocked ejecta and the nova-hosting white dwarf. The XMM-Newton observations revealed a super-soft X-ray emission which is dominated by emission lines of C v, C vi, N vi, N vii, and O viii rather than a blackbody-like continuum, suggesting CO-composition of the white dwarf in a high-inclination binary system. Fermi/LAT detected YZ Ret for 15 days with the γ-ray spectrum best described by a power law with an exponential cut-off at 1.9 ± 0.6 GeV. In stark contrast with theoretical predictions and in keeping with previous NuSTAR observations of Fermi-detected classical novae (V5855 Sgr and V906 Car), the 3.5-78 keV X-ray emission is found to be two orders of magnitude fainter than the GeV emission. The X-ray emission observed by NuSTAR is consistent with a single-temperature thermal plasma model. We do not detect a non-thermal tail of the GeV emission expected to extend down to the NuSTAR band. NuSTAR observations continue to challenge theories of high-energy emission from shocks in novae. Copyright © 2021, The Authors. All rights reserved.

关键词： X ray scattering

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Erratum for Wang et al., "Clinically Applicable System for Rapidly Predicting Enterococcus faecium Susceptibility to Vancomycin"

引用

Microbiology spectrum 2022年第1期10卷 e0261021页

作者： Hsin-Yao Wang Chia-Ru Chung Chao-Jung Chen Ko-Pei Lu Yi-Ju Tseng Tzu-Hao Chang Min-Hsien Wu Wan-Ting Huang Ting-Wei Lin Tsui-Ping Liu Tzong-Yi Lee Jorng-Tzong Horng Jang-Jih Lu Department of Laboratory Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Ph.D. Program in Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Computer Science and Information Engineering National Central Universitygrid.37589.30 Taoyuan City Taiwan. Graduate Institute of Integrated Medicine China Medical Universitygrid.254145.3 Taichung Taiwan. Proteomics Core Laboratory China Medical Universitygrid.254145.3 Hospital Taichung Taiwan. Graduate Program in Biomedical Information Yuan-Ze University Taoyuan City Taiwan. Department of Information Management Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City Taiwan. Clinical Big Data Research Center Taipei Medical University Hospital Taipei City Taiwan. Graduate Institute of Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Division of Haematology/Oncology Department of Internal Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Biosensor Group Biomedical Engineering Research Center Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Pathology Kaohsiung Chang Gung Memorial Hospitalgrid.413801.f and Chang Gung University College of Medicine Kaohsiung Taiwan. School of Life and Health Sciences The Chinese University of Hong Kong Shenzhen China. Warshel Institute for Computational Biology The Chinese University of Hong Kong Shenzhen China. Department of Bioinformatics and Medical Engineering Asia University Taichung City Taiwan. School of Medicine Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Medical Biotechnology and Laboratory Science Chang Gung Universitygrid.145695.a Taoyuan City Taiwan.

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