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Primary and Metastatic Cellular Landscapes in Human Pancreatic Cancer

iscience 2025年

作者： Nina G. Steele Veerin R. Sirihorachai Ahmed M. Elhossiny Ian M. Loveless Padma Kadiyala Monica Bonilla Emily L. Lasse-Opsahl Carinna Solano Vargas Katelyn L. Donahue Samantha B. Kemp Valerie Gunchick Yatrik M. Shah Timothy L. Frankel Filip Bednar Arvind Rao Benjamin L. Allen Jiaqi Shi Vaibhav Sahai Howard C. Crawford Eileen S. Carpenter Marina Pasca di Magliano Department of Cell and Developmental Biology University of Michigan Ann Arbor MI 48109 USA Department of Surgery Henry Ford Health Systems Detroit MI 48202 USA Department of Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA 19104 USA Current institutional address: Division of Digestive Diseases Department of Internal Medicine College of Medicine University of Cincinnati Cincinnati OH 45267 Cancer Biology Program University of Michigan Ann Arbor MI 48109 USA Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI 48109 USA Center for Bioinformatics Department of Public Health Sciences Henry Ford Health Detroit MI 48202 USA Department of Computational Mathematics Science and Engineering； Medical Imaging and Data Integration Lab； Michigan State University East Lansing MI 48824 USA Department of Immunology University of Michigan Ann Arbor MI 48109 USA Department of Internal Medicine University of Michigan Ann Arbor MI 48109 USA Department of Surgery University of Michigan Ann Arbor MI 48109 USA Department of Molecular & Integrative Physiology University of Michigan Ann Arbor MI 48109 USA Rogel Cancer Center University of Michigan Ann Arbor MI 48109 USA Department of Biostatistics University of Michigan Ann Arbor MI 48109 USA Michigan Institute of Data Science (MIDAS) University of Michigan Ann Arbor MI 48109 USA Department of Radiation Oncology University of Michigan Ann Arbor MI 48109 USA Department of Pathology University of Michigan Ann Arbor MI 48109 USA Department of Internal Medicine Division of Gastroenterology University of Michigan Ann Arbor MI 48109 USA

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a complex tumor microenvironment (TME). We utilized single cell RNA sequencing to compare the TMEs of metastatic sites and primary tumors. We detected increased prevalence of exhausted CD8 + T cells in metastases, as well as enrichment of complement pathway encoding genes in immunosuppressive tumor-associated macrophages, consistent with profound immunosuppression in metastatic disease. In cancer-associated fibroblasts, we identified unique upregulation of metabolic genes including UPP1 in metastasis. In cancer cells, we uncovered a specific gene signature upregulated in liver metastases; this signature was present in a proportion of primary tumors in the TCGA dataset, where it correlated with worse survival. Overall, our analysis of primary and metastatic PDAC defines a “high-risk” gene signature, metabolic reprogramming and increased immune suppression in metastasis.

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Detecting anomalous citation groups in journal networks

arXiv

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arXiv 2020年

作者： Kojaku, Sadamori Livan, Giacomo Masuda, Naoki Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Computer Science University College London LondonWC1E 6EA United Kingdom Systemic Risk Centre London School of Economics and Political Science LondonWC2A 2AE United Kingdom Department of Mathematics University at Buffalo State University of New York BuffaloNY United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-2900 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more selective, and, ultimately, into higher publication standards. However, the fixation on higher impact factors leads some journals to artificially boost impact factors through the coordinated effort of a "citation cartel" of journals. "Citation cartel" behavior has become increasingly common in recent years, with several instances being reported. Here, we propose an algorithm—-named CIDRE—to detect anomalous groups of journals that exchange citations at excessively high rates when compared against a null model that accounts for scientific communities and journal size. CIDRE detects more than half of the journals suspended from Journal Citation Reports due to anomalous citation behavior in the year of suspension or in advance. Furthermore, CIDRE detects many new anomalous groups, where the impact factors of the member journals are lifted substantially higher by the citations from other member journals. We describe a number of such examples in detail and discuss the implications of our findings with regard to the current academic climate. Copyright © 2020, The Authors. All rights reserved.

关键词： Publishing

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The turtleback diagram for conditional probability

arXiv

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arXiv 2018年

作者： Yan, Donghui Davis, Gary E. Department of Mathematics and Program in Data Science University of Massachusetts Dartmouth MA United States

We elaborate on an alternative representation of conditional probabil- ity to the usual tree diagram. We term the representation "turtleback diagram" for its resemblance to the pattern on turtle shells. Adopting the set theoretic view of events and the sample space, the turtleback di- agram uses elements from Venn diagrams|set intersection, complement and partition|for conditioning, with the additional notion that the area of a set indicates probability whereas the ratio of areas for conditional probability. Once parts of the diagram are drawn and properly labeled, the calculation of conditional probability involves only simple arithmetic on the area of relevant sets. We discuss turtleback diagrams in relation to other visual representations of conditional probability, and detail several scenarios in which turtleback diagrams prove useful. By the equivalence of recursive space partition and the tree, the turtleback diagram is seen to be equally expressive as the tree diagram for representing abstract concepts. We also provide empirical data on the use of turtleback diagrams with undergraduate students in elementary statistics or probability courses. Copyright © 2018, The Authors. All rights reserved.

关键词： Students

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Skater’s dilemma

arXiv

引用

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

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Kernel-based parameter estimation of dynamical systems with unknown observation functions

arXiv

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arXiv 2020年

作者： Lindenbaum, Ofir Sagiv, Amir Mishne, Gal Talmon, Ronen Program in Applied Mathematics Yale University 51 Prospect Street New HavenCT06511 United States Department of Applied Physics and Applied Mathematics Columbia University 500 West 120th Street New YorkNY10027 United States Halicioglu Data Science Institute UC San Diego 9500 Gilman Drive MS0555 United States SDSC 215E San DiegoCA92093-0555 United States Faculty of Electrical Engineering Technion - Israel Institute of Technology Haifa32000 Israel

A low-dimensional dynamical system is observed in an experiment as a high-dimensional signal;for example, a video of a chaotic pendulums system. Assuming that we know the dynamical model up to some unknown parameters, can we estimate the underlying system's parameters by measuring its time-evolution only once? The key information for performing this estimation lies in the temporal inter-dependencies between the signal and the model. We propose a kernel-based score to compare these dependencies. Our score generalizes a maximum likelihood estimator for a linear model to a general nonlinear setting in an unknown feature space. We estimate the system's underlying parameters by maximizing the proposed score. We demonstrate the accuracy and efficiency of the method using two chaotic dynamical systems - the double pendulum and the Lorenz'63 model. © 2020, CC BY.

关键词： Maximum likelihood estimation

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Scale-specific dynamics of large-amplitude bursts in EEG capture behaviorally meaningful variability

arXiv

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arXiv 2020年

作者： Bansal, Kanika Garcia, Javier O. Lauharatanahirun, Nina Muldoon, Sarah F. Sajda, Paul Vettel, Jean M. U.S. Combat Capabilities Development Command Army Research Laboratory Aberdeen Proving GroundMD21005 United States Department of Biomedical Engineering Columbia University New YorkNY10027 United States Department of Biomedical Engineering University of Pennsylvania PhiladelphiaPA19104 United States Annenberg School of Communication University of Pennsylvania PhiladelphiaPA19104 United States Mathematics Department CDSE Program Neuroscience Program University at Buffalo SUNY BuffaloNY14260 United States Data Science Institute Columbia University New YorkNY10027 United States Department of Psychological and Brain Sciences University of California Santa BarbaraCA93106 United States

Cascading large-amplitude bursts in neural activity, termed avalanches, are thought to provide insight into the complex spatially distributed interactions in neural systems. In human neuroimaging, for example, avalanches occurring during resting-state show scale-invariant dynamics, supporting the hypothesis that the brain operates near a critical point that enables long range spatial communication. In fact, it has been suggested that such scale-invariant dynamics, characterized by a power-law distribution in these avalanches, are universal in neural systems and emerge through a common mechanism. While the analysis of avalanches and subsequent criticality is increasingly seen as a framework for using complex systems theory to understand brain function, it is unclear how the framework would account for the omnipresent cognitive variability, whether across individuals and/or tasks. To address this, we analyzed avalanches in the EEG activity of healthy humans during rest as well as two distinct task conditions that varied in cognitive demands and produced behavioral measures unique to each individual. In both rest and task conditions we observed that avalanche dynamics demonstrate scale-invariant characteristics, but differ in their specific features, demonstrating individual variability. Using a new metric we call normalized engagement, which estimates the likelihood for a brain region to produce high-amplitude bursts, we also investigated regional features of avalanche dynamics. Normalized engagement showed not only the expected individual and task dependent variability, but also scale-specificity that correlated with individual behavior. Our results suggest that the study of avalanches in human brain activity provides a tool to assess cognitive variability. Our findings expand our understanding of avalanche features and are supportive of the emerging theoretical idea that the dynamics of an active human brain operate close to a critical-like region and not a singular

关键词： Brain

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

引用

Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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Deep neural network for Wannier function centers

arXiv

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arXiv 2019年

作者： Zhang, Linfeng Chen, Mohan Wu, Xifan Wang, Han Weinan, E. Car, Roberto Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States CAPT HEDPS College of Engineering Peking University Beijing100871 China Department of Physics Temple University PhiladelphiaPA19122 United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China Department of Mathematics and Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Beijing Institute of Big Data Research Beijing100871 China Department of Chemistry Department of Physics Program in Applied and Computational Mathematics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States

We introduce a deep neural network (DNN) model that assigns the position of the centers of the electronic charge in the snapshots of a molecular dynamics trajectory. The electronic centers are uniquely specified by the unitary transformation that maps the occupied eigenstates onto maximally localized Wannier functions. In combination with deep potential molecular dynamics, a DNN approach to model the atomic potential energy surface at the ab initio density functional level of theory, the scheme makes possible to predict the dielectric properties of insulators for samples and trajectories inaccessible to direct ab initio simulation, without loss of accuracy. As an example, we report calculations of the infrared absorption spectra of light and heavy water at a dispersion inclusive hybrid functional level of theory, finding good agreement with experiment. Extensions to other spectroscopies, like Raman and sum frequency generation, are discussed. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum chemistry

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Critical mass effect in evolutionary games triggered by zealots

arXiv

引用

arXiv 2019年

作者： Cardillo, Alessio Masuda, Naoki Department of Engineering Mathematics University of Bristol BristolBS8 1UB United Kingdom Department of Computer Science and Mathematics University Rovira i Virgili TarragonaE-43007 Spain University of Zaragoza ZaragozaE-50018 Spain Department of Mathematics University at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Tiny perturbations may trigger large responses in systems near criticality, shifting them across equilibria. Committed minorities are suggested to be responsible for the emergence of collective behaviors in many physical, social, and biological systems. Using evolutionary game theory, we address the question whether a finite fraction of zealots can drive the system to large-scale coordination. We find that a tipping point exists in coordination games, whereas the same phenomenon depends on the selection pressure, update rule, and network structure in other types of games. Our study paves the way to understand social systems driven by the individuals’ benefit in presence of zealots, such as human vaccination behavior or cooperative transports in animal groups. Copyright © 2019, The Authors. All rights reserved.

关键词： Game theory

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Metadata for the Flux Density Calibration of the April 2018 Event Horizon Telescope data

arXiv

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arXiv 2023年

作者： Koay, J.Y. Romero-Cañizales, C. Matthews, L.D. Janssen, M. Blackburn, L. Tilanus, R.P.J. Park, J. Asada, K. Matsushita, S. Baczko, A.-K. Bella, N. La Chan, C.-K. Crew, G.B. Fish, V. Patel, N. Ramakrishnan, V. Rottmann, H. Wagner, J. Wiik, K. Friberg, P. Goddi, C. Issaoun, S. Keating, G. Kim, J. Krichbaum, T.P. Marrone, D. Narayanan, G. Roy, A. Ruíz, I. Sánchez, S. Torne, P. Weintroub, J. Academia Sinica Institute of Astronomy and Astrophysics No.1 Sec. 4 Roosevelt Rd Taipei10617 Taiwan Massachusetts Institute of Technology Haystack Observatory 99 Millstone Road WestfordMA01886 United States Auf dem Hügel 69 Bonn53121 Germany Center for Astrophysics Harvard & Smithsonian 60 Garden St. CambridgeMA02138 United States Black Hole Initiative Harvard University 20 Garden Street CambridgeMA02138 United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States Department of Astronomy and Space Science Kyung Hee University 1732 Deogyeong-daero Giheung-gu Gyeonggi-do Yongin-si17104 Korea Republic of Department of Astrophysics IMAPP Radboud University P.O. Box 9010 Nijmegen6500 GL Netherlands Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Finnish Centre for Astronomy with ESO University of Turku FI-20014 Finland Aalto University Metsähovi Radio Observatory Metsähovintie 114 KylmäläFI-02540 Finland Tuorla Observatory Department of Physics and Astronomy University of Turku Finland East Asian Observatory 660 N. A’ohoku Place HiloHI96720 United States INAF - Osservatorio Astronomico di Cagliari Via della Scienza 5 CA Selargius09047 Italy California Institute of Technology 1200 East California Boulevard PasadenaCA91125 United States Department of Astronomy University of Massachusetts AmherstMA01003 United States Institut de Radioastronomie Millimétrique Avenida Divina Pastora 7 Local 20 GranadaE-18012 Spain

The Event Horizon Telescope (EHT) observations carried out in 2018 April at 1.3 mm wavelengths included 9 stations in the array, comprising 7 single-dish telescopes and 2 phased arrays. The metadata package for the 2018 EHT observing campaign contains calibration tables required for the a-priori amplitude calibration of the 2018 April visibility data. This memo is the official documentation accompanying the release of the 2018 EHT metadata package, providing an overview of the contents of the package. We describe how telescope sensitivities, gain curves and other relevant parameters for each station in the EHT array were collected, processed, and validated to produce the calibration tables. Copyright © 2023, The Authors. All rights reserved.

关键词： Telescopes

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