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Perspectives of Earth and Space Scientists 2024年第1期5卷

作者： Sophie Goliber Jason Coenen Heather Fair Angela R. Szesciorka Kirstin Schulz David J. Harning Benjamin Fernando Stanislav Saas Ksenofontov Astrid Pacini Marisol Juarez Rivera Radiance Calmer John A. Conroy Eva Lisa Doting Marie Bergelin Devon Dunmire Maria Luisa Sánchez Montes Alexandra M. Ravelo Anne Sledd Taylor R. Stinchcomb Emily J. Tibbett Mariama C. Dryák-Vallies The State University of New York at Buffalo Buffalo NY USA Department of Earth and Atmospheric Sciences University of Nebraska-Lincoln Lincoln NE USA Department of Plant and Microbial Biology University of Minnesota Saint Paul MN USA Marine Mammal Institute Hatfield Marine Science Center Oregon State University Newport OR USA Oden Institute for Computational Engineering and Sciences The University of Texas at Austin Austin TX USA Institute of Arctic and Alpine Research University of Colorado Boulder Boulder CO USA Johns Hopkins University Baltimore MD USA ARCTICenter University of Northern Iowa Cedar Falls IA USA Applied Physics Laboratory Polar Science Center University of Washington Seattle WA USA University of New Mexico Albuquerque NM USA Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder CO USA Ocean Sciences Department University of California Santa Cruz Santa Cruz CA USA Department of Earth and Environmental Science University of Pennsylvania Philadelphia PA USA Berkeley Geochronology Center Berkeley CA USA Department of Earth and Environmental Sciences KU Leuven Heverlee Belgium International Arctic Research Center University of Alaska Fairbanks Fairbanks AK USA National Oceanic and Atmospheric Administration Physical Sciences Laboratory Boulder CO USA Wildlife Conservation Society Arctic-Beringia Program Fairbanks AK USA University of Massachusetts Amherst Amherst MA USA Polar Science Early Career Community Office University of Colorado Boulder Boulder CO USA

In 2023, the first Polar Postdoc Leadership Workshop convened to discuss present and future polar science issues and to develop leadership skills. The workshop discussions fostered a collective commitment to inclusive leadership within the polar science community among all participants. Here, we outline challenges encountered by underrepresented groups in polar sciences, while also noting that progress has been made to improve inclusivity in the field. Further, we highlight the inclusive leadership principles identified by workshop participants to bring to the polar community as we transition into leadership roles. Finally, insights and practical knowledge we gained from the workshop are shared, aiming to inform the community of our commitment to inclusive leadership and encourage the polar community to join us in pursuing action toward our shared vision for a more welcoming polar science future. As a small community of postdoctoral researchers, we outline the leadership skills envisioned for an inclusive future in polar sciences Our vision is to increase the success of underrepresented individuals as leaders by creating a welcoming and supportive career environment Group norms and leadership skills focused on emotional intelligence are critical to equity and inclusion in polar sciences

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Remembering the work of Phillip L. Geissler: A coda to his scientific trajectory

arXiv

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arXiv 2023年

作者： Bowman, Gregory R. Cox, Stephen J. Dellago, Christoph DuBay, Kateri H. Eaves, Joel D. Fletcher, Daniel A. Frechette, Layne B. Grünwald, Michael Klymko, Katherine Ku, JiYeon Omar, Ahmad K. Rabani, Eran Reichman, David R. Rogers, Julia R. Rosnik, Andreana M. Rotskoff, Grant M. Schneider, Anna R. Schwierz, Nadine Sivak, David A. Vaikuntanathan, Suriyanarayanan Whitelam, Stephen Widmer-Cooper, Asaph Bioengineering Biochemistry and Biophysics University of Pennsylvania PA19104 United States Yusuf Hamied Department of Chemistry University of Cambridge Lensfield Road CambridgeCB2 1EW United Kingdom Faculty of Physics University of Vienna Vienna1090 Austria Department of Chemistry University of Virginia CharlottesvilleVA22903 United States Department of Chemistry University of Colorado Boulder BoulderCO80309 United States Department of Bioengineering & Biophysics Program University of California Berkeley Berkeley United States Division of Biological Systems & Engineering Lawrence Berkeley National Laboratory Berkeley United States Chan Zuckerberg Biohub San Francisco United States Martin A. Fisher School of Physics Brandeis University WalthamMA02454 United States Department of Chemistry University of Utah Salt Lake City84112 United States Lawrence Berkeley National Lab BerkeleyCA94720 United States Co. Ltd Suwon16229 Korea Republic of Department of Materials Science and Engineering University of California BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Chemistry University of California BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States The Raymond and Beverly Sackler Center Computational Molecular and Materials Science Tel Aviv University Tel Aviv69978 Israel Department of Chemistry Columbia University New YorkNY United States Department of Systems Biology Columbia University New YorkNY10032 United States Atomwise San FranciscoCA94103 United States Department of Chemistry Stanford University StanfordCA94305 United States Form Energy BerkeleyCA94710 United States Institute of Physics University of Augsburg Germany Department of Physics Simon Fraser University BurnabyBCV5A1S6 Canada Department of Chemistry University of Chicago ChicagoIL6063

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective, we celebrate his work at these frontiers. Copyright © 2023, The Authors. All rights reserved.

关键词： Statistical mechanics

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems 15

A Neuro-Inspired Approach to Solve a Simultaneous Location a...

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15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018

作者： Menezes, Matheus Chaves De Freitas, Edison Pignaton Cheng, Sen De Oliveira, Alexandre Cesar Muniz De Almeida Ribeiro, Paulo Rogerio Graduate Program on Computer Science Federal University of Maranhão Sao Luis Brazil Computational Neuroscience Ruhr University Bochum Institute for Neural Computation Bochum Germany Department of Informatics Federal University of Maranhão Sao Luis Maranhao Brazil Department of Computer Engineering Federal University of Maranhão Sao Luis Maranhao Brazil

ISBN: (纸本)9781538695821

This paper presents a neuro-inspired mapping approach that uses partial information shared by multiple robots to reduce the time to create a map of an entire environment. Robots using a neurobiologically inspired algorithm, namely RatSLAM, map an environment sharing video information among themselves. RatSLAM, which is based on the navigation system present in the hippocampus of rodents' brain, has been widely used on simultaneous localization and mapping (SLAM) problem. This proposal has been able to generate suitable maps mainly when there is redundant information, e.g. a scene is seen more than once, since this fact activates local view cells that inject activity inside the pose cells via an excitatory link. The work here reported extends this approach by merging partial information acquired by multiple robots. The results from the performed experiments show that the final map built by two robots with shared information is similar to one built by two robots performing the same mapping task individually, i.e. without sharing information. However, the time spent to generate the whole map with the proposed shared approach was smaller than the one without the shared information. Thus, the current approach allows creating a complete map of an environment within a reduced time using multiple robots. © 2018 IEEE.

关键词： Mapping

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Author Correction: T cell egress via lymphatic vessels is tuned by antigen encounter and limits tumor control

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Nature immunology 2023年第4期24卷 729页

作者： Maria M Steele Abhinav Jaiswal Ines Delclaux Ian D Dryg Dhaarini Murugan Julia Femel Sunny Son Haley du Bois Cameron Hill Sancy A Leachman Young H Chang Lisa M Coussens Niroshana Anandasabapathy Amanda W Lund Ronald O. Perelman Department of Dermatology NYU Grossman School of Medicine New York University Langone Health New York NY USA. Department of Cell Developmental and Cancer Biology and Knight Cancer Institute Oregon Health and Science University Portland OR USA. Department of Dermatology Microbiology and Immunology Meyer Cancer Center Englander Institute of Precision Medicine Weill Cornell Medicine New York NY USA. Applied Bioinformatics Laboratories NYU Langone Health New York NY USA. Department of Dermatology Oregon Health and Science University Portland OR USA. Department of Biomedical Engineering and Computational Biology Program Oregon Health and Science University Portland OR USA. OHSU Center for Spatial Systems Biomedicine Oregon Health and Science University Portland OR USA. Ronald O. Perelman Department of Dermatology NYU Grossman School of Medicine New York University Langone Health New York NY USA. amanda.lund@***. Department of Cell Developmental and Cancer Biology and Knight Cancer Institute Oregon Health and Science University Portland OR USA. amanda.lund@***. Department of Pathology NYU Grossman School of Medicine New York University Langone Health New York NY USA. amanda.lund@***. Laura and Isaac Perlmutter Cancer Center NYU Grossman School of Medicine New York University Langone Health New York NY USA. amanda.lund@***.

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Perspective on recent developments and challenges in regulatory and systems genomics

arXiv

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arXiv 2024年

作者： Zeiltinger, Julia Roy, Sushmita Ay, Ferhat Mathelier, Anthony Medina-Rivera, Alejandra Mahony, Shaun Sinha, Saurabh Ernst, Jason Stowers Institute for Medical Research Kansas CityMO64112 United States Department of Pathology & Laboratory Medicine The University of Kansas Medical Center Kansas CityKS66160 United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison Madison53715 United States Wisconsin Institute for Discovery University of Wisconsin-Madison Madison53715 United States Centers for Autoimmunity Inflammation and Cancer Immunotherapy La Jolla Institute for Immunology La Jolla CA United States Bioinformatics and Systems Biology Program University of California La Jolla San DiegoCA United States Department of Pediatrics University of California La Jolla San DiegoCA United States Nordic EMBL Partnership University of Oslo Oslo0318 Norway Department of Medical Genetics Institute of Clinical Medicine University of Oslo Oslo University Hospital Oslo Norway Department of Pharmacy University of Oslo Oslo Norway Laboratorio Internacional de Investigación sobre el Genoma Humano Universidad Nacional Autónoma de México Campus Juriquilla Blvd. Juriquilla 3001 Santiago de Querétaro76230 Mexico Center for Eukaryotic Gene Regulation Department of Biochemistry and Molecular Biology The Pennsylvania State University University ParkPA16802 United States Walter H. Coulter Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA United States H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology AtlantaGA United States Department of Biological Chemistry University of California Los Angeles Los AngelesCA90095 United States Computer Science Department University of California Los Angeles Los AngelesCA90095 United States Department of Computational Medicine University of California Los Angeles Los AngelesCA90095 United States Eli and Edythe Broad Center of Regenerative Medicine Stem Cell Research University of California Los Angeles Los AngelesCA90095 United States

Predicting how genetic variation affects phenotypic outcomes at the organismal, cellular, and molecular levels requires deciphering the cis-regulatory code, the sequence rules by which non-coding regions regulate genes. In this perspective, we discuss recent computational progress and challenges towards solving this fundamental problem. We describe how cis-regulatory elements are mapped and how their sequence rules can be learned and interpreted with sequence-to-function neural networks, with the goal of identifying genetic variants in human disease. We also discuss how studies of the 3D chromatin organization could help identifying long-range regulatory effects and how current methods for mapping gene regulatory networks could better describe biological processes. We point out current gaps in knowledge along with technical limitations and benchmarking challenges of computational methods. Finally, we discuss newly emerging technologies, such as spatial transcriptomics, and outline strategies for creating a more general model of the cis-regulatory code that is more broadly applicable across cell types and individuals. © 2024, CC BY-NC-SA.

关键词： Molecular docking

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Jammed packings of 3D superellipsoids with tunable packing fraction, contact number, and ordering

arXiv

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arXiv 2019年

作者： Yuan, Ye VanderWerf, Kyle Shattuck, Mark D. O’Hern, Corey S. Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department City College of New York New YorkNY10031 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

We carry out numerical studies of static packings of frictionless superellipsoidal particles in three spatial dimensions. We consider more than 200 different particle shapes by varying the three shape parameters that define superellipsoids. We characterize the structural and mechanical properties of both disordered and ordered packings using two packing-generation protocols. We perform athermal quasi-static compression simulations starting from either random, dilute configurations (Protocol 1) or thermalized, dense configurations (protocol 2), which allows us to tune the orientational order of the packings. In general, we find that the contact numbers at jamming onset for superellipsoid packings are hypostatic, with zJ f and df = 5 or 6 depending on whether the particles are axi-symmetric or not. Over the full range of orientational order, we find that the number of quartic modes of the dynamical matrix for the packings always matches the number of missing contacts relative to the isostatic value. This result suggests that there are no mechanically redundant contacts for ordered, yet hypostatic packings of superellipsoidal particles. Additionally, we find that the packing fraction at jamming onset for diordered packings of superellipsoidal particles can be collapsed using two particle shape parameters, e.g. the asphericity A and reduced aspect ratio β of the particles. Copyright © 2019, The Authors. All rights reserved.

关键词： Jamming

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Mathematical Modeling of Plasticity and Heterogeneity in EMT

arXiv

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arXiv 2019年

作者： Tripathi, Shubham Xing, Jianhua Levine, Herbert Jolly, Mohit Kumar Program in Systems Synthetic and Physical Biology Rice University HoustonTX77005 United States Department of Computational and Systems Biology University of Pittsburgh PittsburghPA15261 United States Department of Physics Department of Bioengineering Northeastern University BostonMA02115 United States Center for Theoretical Biological Physics Rice University HoustonTX77005 United States Centre for BioSystems Science and Engineering Indian Institute of Science Bangalore Karnataka560012 India

Epithelial-mesenchymal transition (EMT) and the corresponding reverse process, mesenchymal-epithelial transition (MET), are dynamic and reversible cellular programs orchestrated by many changes at biochemical and morphological levels. A recent surge in identifying the molecular mechanisms underlying EMT / MET has led to the development of various mathematical models that have contributed to our improved understanding of dynamics at single-cell and population levels: a) multistability (how many phenotypes can cells attain en route EMT / MET?), b) reversibility / irreversibility (what time and / or concentration of an EMT inducer marks the 'tipping point' when cells induced to undergo EMT cannot revert?), c) symmetry in EMT / MET (do cells take the same path when reverting as they took during the induction of EMT?), d) non-cell autonomous mechanisms (how does a cell undergoing EMT alter the tendency of its neighbors to undergo EMT)? These dynamical traits may facilitate a heterogenous response within a cell population undergoing EMT / MET. Here, we present a few examples of designing different mathematical models that can contribute to decoding EMT / MET dynamics. Copyright © 2019, The Authors. All rights reserved.

关键词： Cell proliferation

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An open-source realtime computational platform (short WIP paper)

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ACM SIGPLAN Notices 2018年第6期53卷 109-112页

作者： Mehrotra, Pavan Dasgupta, Sabar Robertson, Samantha Nuyujukian, Paul Stanford University Department of Electrical Engineering StanfordCA United States Stanford University Mathematical and Computational Science Program StanfordCA United States Stanford University Department of Bioengineering Department of Neurosurgery Department of Electrical Engineering Neurosciences Program Neurosciences Institute Bio-X Institute StanfordCA United States

ISBN: (纸本)9781450349116

Systems neuroscience studies involving in-vivo models often require realtime data processing. In these studies, many events must be monitored and processed quickly, including behavior of the subject (e.g., movement of a limb) or features of neural data (e.g., a neuron transmitting an action potential). Unfortunately, most realtime platforms are proprietary, require specific architectures, or are limited to low-level programming languages. Here we present a hardware-independent, open-source realtime computation platform that supports high-level programming. The resulting platform, LiCoRICE, can process on order 10e10 bits/sec of network data at 1 ms ticks with 18.2 μs jitter. It connects to various inputs and outputs (e.g., DIO, Ethernet, database logging, and analog line in/out) and minimizes reliance on custom device drivers by leveraging peripheral support via the Linux kernel. Its modular architecture supports model-based design for rapid prototyping with C and Python/Cython and can perform numerical operations via BLAS/LAPACK-optimized NumPy that is statically compiled via Numba's pycc. LiCoRICE is not only suitable for systems neuroscience research, but also for applications requiring closed-loop realtime data processing from robotics and control systems to interactive applications and quantitative financial trading. © 2018 ACM.

关键词： Python

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Integrating Genomic & Transcriptomic Features for Noninvasive Detection, Characterization, and Monitoring of T-Cell Lymphomas

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Blood 2024年 144卷 454-454页

作者： Takeshi Sugio Monica Nesselbush Navika Shukla Andrea Garofalo Jurik A. Mutter Mohammad Shahrokh Esfahani Stefan K. Alig Shuyu Shi Troy Noordenbos Mark P. Hamilton Cedric Rossi Feng Tian Chih Long Liu Mari Olsen Xiaoman Kang David A Russler-Germain Steven Horwitz Koji Kato Ayumu Ito Makoto Yamagishi Ash A. Alizadeh Department of Medicine Divisions of Oncology and Hematology Stanford University Stanford CA Program in Cancer Biology Stanford School of Medicine Stanford CA Divisions of Oncology and Hematology Stanford University Stanford CA Department of Radiation Oncology Stanford University Stanford CA Dept. of Bioengineering Schools of Engineering and Medicine Stanford CA Division of Blood and Marrow Transplantation and Cellular Therapy Stanford University School of Medicine Palo Alto CA CHU Dijon DIJON France Department of Medicine Division of Oncology Stanford University Stanford CA Siteman Cancer Center Division of Oncology Washington University School of Medicine Saint Louis MO Lymphoma Service Department of Medicine Memorial Sloan Kettering Cancer Center New York NY Department of Medicine and Biosystemic Science Kyushu University Graduate School of Medicine Fukuoka Japan Department of Hematopoietic Stem Cell Transplantation National Cancer Center Hospital Tokyo Japan Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo JPN

Background : Mature T-cell lymphoma (TCL) outcomes remain inferior to aggressive B-cell counterparts, and thus represent unmet need. Given high relapse rates after remissions induced by current regimens, more sensitive MRD methods are needed to personalize treatment. We tackled these questions by integrating distinct host and viral molecular features for noninvasive detection, risk profiling, and monitoring of diverse mature TCLs. Methods : We studied 132 patients diagnosed with diverse TCLs (PTCL-NOS n=21, ALCL n=13, TFH lymphoma n=21, ATLL n=54, ENKTL n=6, CTCL n=15, others n=2). 37% of pts had newly diagnosed TCL primarily treated with CHOP-based regimens, while 62% had relapsed/refractory disease treated with salvage chemotherapies (26%), nivolumab (5%), and/or allogeneic HSCT (31%). We molecularly profiled 530 specimens, including serial blood plasma samples drawn before, during, and at the end-of-therapy (EOT) (n=274), baseline tumor tissues (n=128), and matched normal cells (n=128). Plasma cfDNA for all cases were profiled to detect somatic mutations in 259 recurrently mutated TCL genes by CAPP-Seq, genome-wide CNVs by CANARy (Chabon 2020 Nature), clonotypic VDJ at all TCR/BCR loci by SABER, T/B-cell abundance by QUARTZ (Sugio ASH 2024 abstract #193441), and inferred expression of 381 TCL/immune-related genes by EPIC-Seq (Esfahani Nature biotechnology 2022). Viral load and genotyping for EBV and HTLV-1 were assessed by VirCAPP-Seq (Garofalo ASH2022). Plasma cfRNA expression was profiled using RARE-Seq, by targeting 6.8k coding genes (Nesselbush 2024 Cancer Research). Results : We found that mutation-based disease burden measurements in cfDNA by CAPP-Seq were significantly correlated with clonotypic cell-free TCR levels (cfTCR; R=0.95, p<0.001) across all patients and plasma HTLV-1 load in ATLL patients (R=0.84, p<0.001). When considering outcomes after CHOP-based regimens, detection of ctDNA-MRD at EOT predicted significantly higher relapse risk (p= 0.003), i

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