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arXiv 2020年

作者： Herbold, Steffen Trautsch, Alexander Ledel, Benjamin Aghamohammadi, Alireza Ghaleb, Taher Ahmed Chahal, Kuljit Kaur Bossenmaier, Tim Nagaria, Bhaveet Makedonski, Philip Ahmadabadi, Matin Nili Szabados, Kristof Spieker, Helge Madeja, Matej Hoy, Nathaniel G. Lenarduzzi, Valentina Wang, Shangwen Rodríguez-Pérez, Gema Colomo-Palacios, Ricardo Verdecchia, Roberto Singh, Paramvir Qin, Yihao Chakroborti, Debasish Davis, Willard Walunj, Vijay Wu, Hongjun Marcilio, Diego Alam, Omar Aldaeej, Abdullah Amit, Idan Turhan, Burak Eismann, Simon Wickert, Anna-Katharina Malavolta, Ivano Sulír, Matúš Fard, Fatemeh Henley, Austin Z. Kourtzanidis, Stratos Tuzun, Eray Treude, Christoph Shamasbi, Simin Maleki Pashchenko, Ivan Wyrich, Marvin Davis, James C. Serebrenik, Alexander Albrecht, Ella Aktas, Ethem Utku Strüber, Daniel Erbel, Johannes Institute for Software and Systems Engineering TU Clausthal Clausthal-Zellefeld Germany Institute of Computer Science University of Goettingen Goettingen Germany Department of Computer Engineering Sharif University of Technology Tehran Iran School of Computing Queen's University Kingston Canada Department of Computer Science Guru Nanak Dev University Amritsar India Karlsruhe Germany Brunel University London Uxbridge United Kingdom Institute of Computer Science University of Goettingen Germany University of Tehran Tehran Iran Ericsson Hungary Ltd. Budapest Hungary Simula Research Laboratory Fornebu Norway Technical University of Košice Košice Slovakia LUT University Finland National University of Defense Technology Changsha China University of British Columbia Kelowna Canada Østfold University College Halden Norway Vrije Universiteit Amsterdam Amsterdam Netherlands University of Auckland Auckland New Zealand University of Saskatchewan Saskatoon Canada IBM Boulder United States University of Missouri-Kansas City Kansas City United States Università della Svizzera italiana Lugano Switzerland Trent University Peterborough Canada University of Maryland Baltimore County United States Imam Abdulrahman Bin Faisal University Saudi Arabia The Hebrew University Acumen Jerusalem Israel University of Oulu Oulu Finland Monash University Melbourne Australia University of Würzburg Würzburg Germany Technische Universität Darmstadt Darmstadt Germany University of Tennessee Knoxville United States University of Macedonia Thessaloniki Greece Department of Computer Engineering Bilkent University Ankara Turkey University of Melbourne Melbourne Australia Independent Researcher Tehran Iran University of Trento Trento Italy University of Stuttgart Stuttgart Germany Purdue University West LafayetteIN United States Eindhoven University of Technology Eindhoven Netherlands Softtech Inc. Research and Development Center Istanbul34947 Turkey Radboud Universi

Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs. Objective: We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits. Methods: We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits. Each line is labeled by four participants. If at least three participants agree on the same label, we have consensus. Results: We estimate that between 17% and 32% of all changes in bug fixing commits modify the source code to fix the underlying problem. However, when we only consider changes to the production code files this ratio increases to 66% to 87%. We find that about 11% of lines are hard to label leading to active disagreements between participants. Due to confirmed tangling and the uncertainty in our data, we estimate that 3% to 47% of data is noisy without manual untangling, depending on the use case. Conclusion: Tangled commits have a high prevalence in bug fixes and can lead to a large amount of noise in the data. Prior research indicates that this noise may alter results. As researchers, we should be skeptics and assume that unvalidated data is likely very noisy, until proven otherwise. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

arXiv

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arXiv 2023年

作者： Eastman, Peter Galvelis, Raimondas Peláez, Raúl P. Abreu, Charlles R.A. Farr, Stephen E. Gallicchio, Emilio Gorenko, Anton Henry, Michael M. Hu, Frank Huang, Jing Krämer, Andreas Michel, Julien Mitchell, Joshua A. Pande, Vijay S. Rodrigues, João P.G.L.M. Rodriguez-Guerra, Jaime Simmonett, Andrew C. Singh, Sukrit Swails, Jason Turner, Philip Wang, Yuanqing Zhang, Ivy Chodera, John D. De Fabritiis, Gianni Markland, Thomas E. Department of Chemistry Stanford University StanfordCA94305 United States Acellera Labs C Dr Trueta 183 Barcelona08005 Spain C Dr. Aiguader 88 Barcelona08003 Spain Chemical Engineering Department School of Chemistry Federal University of Rio de Janeiro Rio de Janeiro68542 Brazil Redesign Science Inc. 180 Varick St. New YorkNY10014 United States EaStCHEM School of Chemistry University of Edinburgh EH9 3FJ United Kingdom Department of Chemistry and Biochemistry Brooklyn College The City University of New York NY United States Ph.D. Program in Chemistry Ph.D. Program in Biochemistry The Graduate Center of the City University of New York New YorkNY United States Stream HPC Koningin Wilhelminaplein 1 - 40601 Amsterdam1062 HG Netherlands Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New YorkNY10065 United States Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University 18 Shilongshan Road Zhejiang Hangzhou310024 China Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 12 Berlin14195 Germany The Open Force Field Initiative Open Molecular Software Foundation DavisCA95616 United States Andreessen Horowitz 2865 Sand Hill Rd Menlo ParkCA94025 United States Department of Structural Biology Stanford University StanfordCA94305 United States Charité Universitätsmedizin Berlin In silico Toxicology and Structural Bioinformatics Virchowweg 6 Berlin10117 Germany Laboratory of Computational Biology National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Entos Inc. 9310 Athena Circle La Jolla CA92037 United States College of Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States Simons Center for Computational Physical Chemistry Center for Data Science New York University 24 Waverly Place New YorkNY10004 United States T

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Calculation of the temperature distribution in an asynchronous machine

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European Transactions on Electrical Power 1995年第3期5卷 181-186页

作者： Xypteras, J. Maras, K. Spyrelis, D. Associate Professor Dr.-Ing. Jannis Xypteras (1937) Director of the Electrical Machines Laboratory Dept. of Electrical Engineering Aristotle University of Thessaloniki (AUT)/Greece graduated from the Fakultatfur Elektrotechnik of the RWTH AachedGermany. During the years 1965 to 1980 he had been employed in German and Greek factories for electrical machines several years as chief of development departments. In 1978 he obtained his Dr. Electr. Eng. degree in the AUT. His subject was in the area of eddy currents. Since 1984 he is Ass. hofessor in the same University. His special interests: Design and development of electrical machines vibration and noise problems electromagnetic fields eddy currents. (Dept. of Electrical Engineering Aristotle University GR-54006 Thessaloniki/Greece T +30 3 1 I99 62 93 Fax +303 11 99 63 02) Kostas Maras (1966) received his degree in Electrical Engineering from the Electrotechnical Faculty of Aristotle University of Thessaloniki/Greece in 1989. In 1990 he graduated as M.Sc. in Digital Electronics in the King's College London at the University of LondordGB with the project “Design of a Transversal Filter on VLSI CMOS”. Since then he has been working at M. Papasavas S.A. at KallithedGreece as an analyst in developing industrial software. Projects: Design and implementation of a dynamic relational model used to tackle production problems in industry. From 1991 to 93 he was responsible for the development of production planning used in industries. (M. Papasavas S.A. Sofocleus 261 GR-17874 KallithedGreece T +30 119423246 Fax +30 1/9429561) Dimitrios S. Spyrelis (1965) received his Diploma in Electrical Engineering from the University of Thessalonikil Greece in 1989. In 1990 he joined the Coding Center of Greek Army as research Assistant. He is currently working as technical director in a pigpoultry breeding company which includes feed processing industry slaughter houses by product process industry wastes treatment systems from farm livestock. His last fields of interest

In this paper the temperature distribution on the section vertical to the axis of an asynchronous machine is calculated. For the calculation the numerical method of “Control Volumes” has been used. The technique used can be easily modified to fit any kind of machine. It can also analyse transients. Copyright © 1995 John Wiley & Sons, Ltd.

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How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

arXiv

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arXiv 2023年

作者： Bosoni, Emanuele Beal, Louis Bercx, Marnik Blaha, Peter Blügel, Stefan Bröder, Jens Callsen, Martin Cottenier, Stefaan Degomme, Augustin Dikan, Vladimir Eimre, Kristjan Flage-Larsen, Espen Fornari, Marco Garcia, Alberto Genovese, Luigi Giantomassi, Matteo Huber, Sebastiaan P. Janssen, Henning Kastlunger, Georg Krack, Matthias Kresse, Georg Kühne, Thomas D. Lejaeghere, Kurt Madsen, Georg K.H. Marsman, Martijn Marzari, Nicola Michalicek, Gregor Mirhosseini, Hossein Müller, Tiziano M.A. Petretto, Guido Pickard, Chris J. Poncé, Samuel Rignanese, Gian-Marco Rubel, Oleg Ruh, Thomas Sluydts, Michael Vanpoucke, Danny E.P. Vijay, Sudarshan Wolloch, Michael Wortmann, Daniel Yakutovich, Aliaksandr V. Yu, Jusong Zadoks, Austin Zhu, Bonan Pizzi, Giovanni Institut de Ciència de Materials de Barcelona ICMAB-CSIC Campus UAB Bellaterra08193 Spain Univ. Grenoble-Alpes CEA IRIG-MEM-L Sim Grenoble38000 France LausanneCH-1015 Switzerland Institute for Materials Chemistry Technical University of Vienna Getreidemarkt 9/165-TC ViennaA-1060 Austria Peter Grünberg Institut Institute for Advanced Simulation Forschungszentrum Jülich JARA JülichD-52425 Germany Forschungszentrum Jülich JülichD-52425 Germany Department of Electromechanical Systems and Metal Engineering Ghent University Belgium Ghent University Belgium Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Norwegian EuroHPC Competence Center Sigma2 AS Norway SINTEF Industry Materials Physics Oslo Norway Department of Physics Science of Advanced Materials Program Central Michigan University Mount PleasantMI48859 United States Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium LausanneCH-1015 Switzerland Kongens Lyngby2800 Denmark VilligenCH-5232 Switzerland University of Vienna Faculty of Physics Center for Computational Materials Science Kolingasse 14-16 ViennaA-1090 Austria VASP Software GmbH Sensengasse 8 ViennaA-1090 Austria Helmholtz-Zentrum Dresden-Rossendorf GörlitzD-02826 Germany Center for Sustainable Systems Design University of Paderborn PaderbornD-33098 Germany OCAS NV ArcelorMittal Global R&D Gent Pres. J. F. Kennedylaan 3 ZelzateB-9060 Belgium Dynamics of Condensed Matter Theoretical Chemistry University of Paderborn PaderbornD-33098 Germany HPE HPC EMEA Research Lab BaselCH-4051 Switzerland Department of Materials Science & Metallurgy University of Cambridge 27 Charles Babbage Road CambridgeCB3 0FS United Kingdom Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba Sendai980-8577 Japan Department of Materials Science and Engineering McMaster University 1280 Main Street West HamiltonONL8S 4L8 Canada ePot

In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). © 2023, CC BY.

关键词： Density functional theory

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DATICS-2010: Welcome message from workshop organizers: FutureTech 2010

2010 5th International Conference on Future Information Tech...

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2010 5th International Conference on Future Information Technology, FutureTech 2010 - Proceedings 2010年

作者： Man, Ka Lok Mercaldi, Michele Hahanov, Vladimir Prinetto, Paolo Poncino, Massimo MacIi, Alberto Choi, Joongho Li, Wei Schellekens, Michel Popovici, Emanuel Seon, Jong-Kug Rossi, Umberto Fummi, Franco Pravadelli, Graziano Lam, Yui Fai PavLov, Vladimir Patel, Ajay Huang, Jinfeng Vallee, Thierry Boubekeur, Menouer Sokolova, Ana Almerares, Sergio Donno, Monica Cho, Jun-Dong Alam, Ahm Zahirul Provan, Gregory Velev, Miroslav N. Nasir Uddin, M. Botchkarev, Alexei Bosnacki, Dragan Hickey, Dave O'Keeffe, Maria Krilavičius, Tomas Pastrnak, Milan Herbert, John Lu, Zhe-Ming Pan, Jeng-Shyang Chang, Chin-Chen Horng, Mong-Fong Chen, Liang Lim, Chee-Peng Tao, Ngo Quoc Deb, Suash Merniz, Salah Valero, Oscar Yi, Yang Woods, Damien Vedrine, Franck Monsuez, Bruno Yen, Kang Matsuura, Takenobu Timothy Edwards, R. Tveretina, Olga Fino, Maria Helena O'Riordan, Adrian Patrick Labiak, Grzegorz Gaur, M.S. Chang, Jian Chung, Yeh-Ching Derezinska, Anna Cho, Kyoung-Rok Zhang, Yong Liutkevičius, R. Zeng, Yuanyuan Vasudevan, D.P. Bukowiec, Arkadiusz Kitsos, Paris Goudarzi, Maziar Dong, Jin Song Bhalla, Ateet Al-Khalili, Dhamin Navabi, Zainalabedin Zinchenko, Lyudmila Anjum, Muhammad Almas Narasimha, Deepak Laxmi Hughes, Danny Tadjouddine, Emmanuel M Wang, Jun Kumar, A.P. Sathish Jaisankar, N. Mansoor, Atif Hollands, Steven Mohammadi, Siamak Klein, Felipe Westermann, Peter English, Tom Planas, Miquel Moreto Chung, Chelho Chakrabarti, Amlan Lei, Chi-Un Bamakhrama, Mohamed Naik, B. Rajendra Harte, Sean Yin, Alexander Giancardi, Luigi Mady, Alie El-Din Joseph, Arun Khandekar, Prasad D. Pandey, Hari Mohan Xi'an Jiaotong-Liverpool University China Kharkov National University of Radio Electronics Italy Politecnico di Torino Italy University of Seoul China Fudan University Ireland University College Cork Ireland System LSI Lab. LS Industrial Systems R and D Center Korea Republic of STMicroelectronics Italy University of Verona Hong Kong Hong Kong University of Science and Technology Hong Kong Hong Kong International Software and Productivity Engineering Institute United States Intelligent Support Ltd. United Kingdom Philips and LiteOn Digital Solutions Netherlands Netherlands Georgia Southern University Statesboro GA Austria University of Salzburg Korea Republic of Sung Kyun Kwan University Malaysia International Islamic University Malaysia Malaysia Aries Design Automation United States Lakehead University Canada IEEE Canada Board of Directors Canada Eindhoven University of Technology Lithuania Vytautas Magnus University Greece Siemens IT Solutions and Services Slovakia Sun Yat-Sen University China National Kaohsiung University of Applied Sciences Taiwan Feng Chia University Taiwan Shu-Te University Canada University of Northern British Columbia Australia University of South Australia Viet Nam Vietnamese Academy of Science and Technology Viet Nam C. V. Raman College of Engineering India Mentouri University Constantine Spain University of Balearic Islands Spain University of Seville France CEA France ENSTA France Florida International University Japan Tokai University Japan MultiGiG Inc. United States Karlsruhe University Portugal Universidade Nova de Lisboa Poland University of Zielona Gora India Malaviya National Institute of Technology Jaipur India Texas Instruments Inc United States National Tsing-Hua University Poland Warsaw University of Technology Korea Republic of Chungbuk National University China Shenzhen University Lithuania Vytautas Magnus University Kaunas Greece Hellenic Open University Patras Singapore National University of Singapore Sing

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Glucose-Responsive Charge-Switchable Lipid Nanoparticles for Insulin Delivery

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Angewandte Chemie 2023年第20期135卷

作者： Yun Liu Yanfang Wang Yuejun Yao Juan Zhang Wei Liu Kangfan Ji Xinwei Wei Yuanwu Wang Prof. Xiangsheng Liu Prof. Shiming Zhang Prof. Jinqiang Wang Prof. Zhen Gu Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province College of Pharmaceutical Sciences Zhejiang University 310058 Hangzhou China Jinhua Institute of Zhejiang University 321299 Jinhua China Contribution: Data curation (lead) Formal analysis (lead) Investigation (lead) Methodology (lead) Software (lead) Validation (lead) Visualization (lead) Writing - original draft (lead) Writing - review & editing (lead) Contribution: Data curation (supporting) Investigation (supporting) Visualization (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Contribution: Formal analysis (supporting) Investigation (supporting) Methodology (supporting) Contribution: Formal analysis (supporting) Investigation (supporting) Contribution: Writing - review & editing (supporting) Contribution: Investigation (supporting) Zhejiang Cancer Hospital Hangzhou Institute of Medicine (HIM) Chinese Academy of Sciences 310022 Hangzhou China Department of Electrical and Electronic Engineering The University of Hong Kong 999077 Hong Kong SAR China Second Affiliated Hospital Zhejiang University School of Medicine 310009 Hangzhou China Contribution: Conceptualization (lead) Data curation (equal) Formal analysis (equal) Funding acquisition (lead) Investigation (lead) Methodology (equal) Project administration (lead) Resources (lead) Software (lead) Supervision (lead) Validation (supporting) Visualization (supporting) Writing - review & editing (lead) Department of General Surgery Sir Run Run Shaw Hospital School of Medicine Zhejiang University 310009 Hangzhou China Zhejiang Laboratory of Systems & Precision Medicine Zhejiang University Medical Center 310009 Hangzhou China MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and Engineering Zhejiang University 310009 Hangzhou China Contribution: Funding acquisition (lead) Project administration (lead) Resources (lead) Softwar

Lipid nanoparticle-based drug delivery systems have a profound clinical impact on nucleic acid-based therapy and vaccination. Recombinant human insulin, a negatively-charged biomolecule like mRNA, may also be delivered by rationally-designed positively-charged lipid nanoparticles with glucose-sensing elements and be released in a glucose-responsive manner. Herein, we have designed phenylboronic acid-based quaternary amine-type cationic lipids that can self-assemble into spherical lipid nanoparticles in an aqueous solution. Upon mixing insulin and the lipid nanoparticles, a heterostructured insulin complex is formed immediately arising from the electrostatic attraction. In a hyperglycemia-relevant glucose solution, lipid nanoparticles become less positively charged over time, leading to reduced attraction and subsequent insulin release. Compared with native insulin, this lipid nanoparticle-based glucose-responsive insulin shows prolonged blood glucose regulation ability and blood glucose-triggered insulin release in a type 1 diabetic mouse model.

关键词： Diabetes Drug Delivery Glucose-Responsive Insulin Delivery Lipid Nanoparticles

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Meeting Report: BioSharing at ISMB 2010

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Standards in genomic sciences 2010年第3期3卷 254-8页

作者： Dawn Field Susanna Sansone Edward F Delong Peter Sterk Iddo Friedberg Pascale Gaudet Susanna Lewis Renzo Kottmann Lynette Hirschman George Garrity Guy Cochrane John Wooley Folker Meyer Sarah Hunter Owen White Brian Bramlett Susan Gregurick Hilmar Lapp Sandra Orchard Philippe Rocca-Serra Alan Ruttenberg Nigam Shah Chris Taylor Anne Thessen Centre for Ecology & Hydrology Wallingford UK Oxford e-Research Centre University of Oxford Oxford UK Department of Biological Engineering Massachusetts Institue of Technology Cambridge USA Department of Microbiology Miami University Oxford USA Department of Computer Science and Software Engineering Miami University Oxford USA Swiss Institute of Bioinformatics Geneva 4 Switzerland Lawrence Berkeley National Laboratory Berkeley USA Microbial Genomics Group Max Planck Institute for Marine Microbiology & Jacobs University Bremen Bremen Germany Information Technology Center The MITRE Corporation Bedford USA Department of Microbiology and Molecular Genetics Michigan State University East Lansing USA European Molecular Biology Laboratory (EMBL) Outstation European Bioinformatics Institute (EBI) Cambridge UK University of California San Diego La Jolla USA Argonne National Laboratory Argonne USA Institute for Genome Sciences University of Maryland School of Medicine Baltimore USA Lux Bio Group Portland USA Biological Systems Science Division Department of Energy Washington DC USA National Evolutionary Synthesis Center (NESCent) Durham USA Science Commons c/o Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory Cambridge USA Stanford Center for Biomedical Informatics Research Stanford USA Marine Biological Laboratory USA

This report summarizes the proceedings of the one day BioSharing meeting held at the Intelligent systems for Molecular Biology (ISMB) 2010 conference in Boston, MA, USA This inaugural BioSharing event was hosted by the Genomic Standards Consortium as part of its M3 & BioSharing special interest group (SIG) workshop. The BioSharing event included invited talks from a range of community leaders and a panel discussion at the end of the day. The panel session led to the formal agreement among community leaders to join together to promote cross-community knowledge exchange and collaborations. A key focus of the newly formed Biosharing community will be linking up resources to promote real-world data sharing (virtuous cycle of data) and supporting compliance with data policies through the creation of a one-stop-portal of information. Further information about the newly established BioSharing effort can be found at http://***.

关键词： Community Leader Funding Agency Special Interest Group Panel Discussion Standardization Effort

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MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

arXiv

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arXiv 2023年

作者： Li, Jianning Zhou, Zongwei Yang, Jiancheng Pepe, Antonio Gsaxner, Christina Luijten, Gijs Qu, Chongyu Zhang, Tiezheng Chen, Xiaoxi Li, Wenxuan Wodzinski, Marek Friedrich, Paul Xie, Kangxian Jin, Yuan Ambigapathy, Narmada Nasca, Enrico Solak, Naida Melito, Gian Marco Vu, Viet Duc Memon, Afaque R. Schlachta, Christopher De Ribaupierre, Sandrine Patel, Rajnikant Eagleson, Roy Chen, Xiaojun Mächler, Heinrich Kirschke, Jan Stefan de la Rosa, Ezequiel Christ, Patrick Ferdinand Li, Hongwei Bran Ellis, David G. Aizenberg, Michele R. Gatidis, Sergios Küstner, Thomas Shusharina, Nadya Heller, Nicholas Andrearczyk, Vincent Depeursinge, Adrien Hatt, Mathieu Sekuboyina, Anjany Löffler, Maximilian Liebl, Hans Dorent, Reuben Vercauteren, Tom Shapey, Jonathan Kujawa, Aaron Cornelissen, Stefan Langenhuizen, Patrick Ben-Hamadou, Achraf Rekik, Ahmed Pujades, Sergi Boyer, Edmond Bolelli, Federico Grana, Costantino Lumetti, Luca Salehi, Hamidreza Ma, Jun Zhang, Yao Gharleghi, Ramtin Beier, Susann Sowmya, Arcot Garza-Villarreal, Eduardo A. Balducci, Thania Angeles-Valdez, Diego Souza, Roberto Rittner, Leticia Frayne, Richard Ji, Yuanfeng Ferrari, Vincenzo Chatterjee, Soumick Dubost, Florian Schreiber, Stefanie Mattern, Hendrik Speck, Oliver Haehn, Daniel John, Christoph Nürnberger, Andreas Pedrosa, João Ferreira, Carlos Aresta, Guilherme Cunha, António Campilho, Aurélio Suter, Yannick Garcia, Jose Lalande, Alain Vandenbossche, Vicky Van Oevelen, Aline Duquesne, Kate Mekhzoum, Hamza Vandemeulebroucke, Jef Audenaert, Emmanuel Krebs, Claudia van Leeuwen, Timo Vereecke, Evie Heidemeyer, Hauke Röhrig, Rainer Hölzle, Frank Badeli, Vahid Krieger, Kathrin Gunzer, Matthias Chen, Jianxu van Meegdenburg, Timo Dada, Amin Balzer, Miriam Fragemann, Jana Jonske, Frederic Rempe, Moritz Malorodov, Stanislav Bahnsen, Fin H. Seibold, Constantin Jaus, Alexander Marinov, Zdravko Jaeger, Paul F. Stiefelhagen, Rainer Santos, Ana Sofia Lindo, Mariana Ferreira, André Alves, Victor Kamp, Michael Abourayya, Amr Nensa, Felix Hörst, Fabian Brehmer, Alexander Hein Girardetstraße 2 Essen45131 Germany Graz University of Technology Inffeldgasse 16c Graz8010 Austria Graz Austria The Department of Computer Science Johns Hopkins University Malone Hall 3400 N Charles St BaltimoreMD21218 United States Rte Cantonale Lausanne1015 Switzerland The Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Sierre Switzerland Department of Biomedical Engineering University of Basel Hegenheimermattweg Allschwil167C CH-4123 Switzerland The Boston College 140 Commonwealth Ave Chestnut HillMA02467 United States University Hospital B7-200 339 Windermere Road LondonN6A 5A5 Canada The Department of Radiology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai200240 China The Research Center for Connected Healthcare Big Data ZhejiangLab Zhejiang Hangzhou311121 China The Faculty of Statistics Technical University Dortmund August-Schmidt-Straße 1 Dortmund44227 Germany The Institute of Mechanics Graz University of Technology Kopernikusgasse 24/IV Graz8010 Austria The Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China The Department of Cardiac Surgery Medical University Graz Auenbruggerplatz 29 Graz8036 Austria The Department of Diagnostic and Interventional Radiology University Hospital Giessen Justus-Liebig-University Giessen Klinikstraße 33 Giessen35392 Germany The Department of Mechanical Engineering Mehran University of Engineering and Technology Jamshoro Sindh76062 Pakistan The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Geschäftsführender Oberarzt Abteilung für Interventionelle und Diagnostische Neuroradiologie Universitätsklinikum der Technischen Universität München Ismaningerstr. 22 München81675 Germany icometrix Kolonel Be

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://***/ and https://***/Jianningli/*** Codes 68T01 © 2023, CC BY.

关键词： Large dataset

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Multimodal bioimaging across disciplines and scales: challenges, opportunities and breaking down barriers

npj Imaging

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npj Imaging 2024年第1期2卷 1-6页

作者： Johanna Bischof Antje Keppler Georgina Fletcher Maddy Parsons Paul Verkade Claudia Kuntner Julia Fernandez-Rodriguez Linda Chaabane Leor Ariel Rose Assaf Zaritsky Andreas Walter Michiel Vandenbosch Marc A. M. J. van Zandvoort Euro-BioImaging ERIC Bio-Hub European Molecular Biology Laboratory (EMBL) Heidelberg Meyerhofstraße 1 69117 Heidelberg Germany BioImagingUK and Royal Microscopical Society 37/38 St Clements Oxford Oxford OX4 1AJ UK Randall Centre for Cell and Molecular Biophysics King’s College London Guy’s Campus London SE1 1UL UK School of Biochemistry University of Bristol Bristol BS8 1TD UK Department of Biomedical Imaging and Image-guided Therapy Medical University of Vienna Vienna Austria Centre for Cellular Imaging Sahlgrenska Academy University of Gothenburg SE-405 30 Gothenburg Sweden Euro-BioImaging ERIC Med-Hub Institute of Biostructures and Bioimaging (IBB) Italian National Research Council (CNR) Via Nizza 52 Torino 10126 Italy Department of Software and Information Systems Engineering Ben-Gurion University of the Negev Beer-Sheva 84105 Israel Center of Optical Technologies Aalen University Aalen Germany Department FHML Maastricht University Maastricht Multimodal Molecular imaging institute Maastricht The Netherlands Department of Genetics and Cell Biology Maastricht University Institutes CARIM GROW and MHeNS Maastricht the Netherlands Institute for Molecular Cardiovascular Research (IMCAR) RWTH Aachen University Clinic Aachen Germany

Multimodal bioimaging is a broad term used to describe experimental workflows that employ two or more different imaging modalities. Such approaches have been in use across life science domains for several years but these remain relatively limited in scope, in part due to the complexity of undertaking these types of analysis. Expanding these workflows to encompass diverse, emerging technology holds potential to revolutionize our understanding of spatial biology. In this perspective we reflect on the instrument and workflows in current use, emerging areas to consider and our experience of the barriers to broader adoption and progress. We propose several enabling solutions across the different challenge areas, emerging opportunities for consideration and highlight some of the key community activities to help move the field forward.

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Varying the Stiffness and Diffusivity of Rod-Shaped Microgels Independently through Their Molecular Building Blocks

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Angewandte Chemie 2023年第44期135卷

作者： Yonca Kittel Luis P. B. Guerzoni Carolina Itzin Dirk Rommel Matthias Mork Céline Bastard Bernhard Häßel Abdolrahman Omidinia-Anarkoli Silvia P. Centeno Tamás Haraszti Kyoohyun Kim Jochen Guck Alexander J. C. Kuehne Laura De Laporte DWI-Leibniz Institute for Interactive Materials e. V. Forckenbeckstraße 50 52074 Aachen Germany Institute of Technical and Macromolecular Chemistry RWTH Aachen University Worringerweg 1–2 52074 Aachen Germany Institute of Organic and Macromolecular Chemistry Ulm University Albert-Einstein Allee 11 89081 Ulm Germany Contribution: Conceptualization (equal) Data curation (lead) Formal analysis (lead) Investigation (lead) Project administration (lead) Visualization (lead) Writing - original draft (lead) Contribution: Conceptualization (equal) Investigation (supporting) Supervision (supporting) Writing - review & editing (supporting) Contribution: Investigation (supporting) Validation (supporting) Visualization (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Investigation (supporting) Validation (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Formal analysis (supporting) Investigation (supporting) Visualization (supporting) Writing - review & editing (equal) Center for Biohybrid Medical Systems (CBMS) Advanced Materials for Biomedicine (AMB) Institute of Applied Medical Engineering (AME) Forckenbeckstraße 55 52074 Aachen Germany Contribution: Conceptualization (supporting) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Contribution: Formal analysis (equal) Software (lead) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Max Planck Institute for the Science of Light and Max-Planck-Zentrum für Physik und Medizin Staudtstraße 2 91058 Erlangen Germany Contribution: Conceptualization (supporting) Investigation (supporting) Software (supporting) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Writing - review

Microgels are water-swollen, crosslinked polymers that are widely used as colloidal building blocks in scaffold materials for tissue engineering and regenerative medicine. Microgels can be controlled in their stiffness, degree of swelling, and mesh size depending on their polymer architecture, crosslink density, and fabrication method—all of which influence their function and interaction with the environment. Currently, there is a lack of understanding of how the polymer composition influences the internal structure of soft microgels and how this morphology affects specific biomedical applications. In this report, we systematically vary the architecture and molar mass of polyethylene glycol-acrylate (PEG-Ac) precursors, as well as their concentration and combination, to gain insight in the different parameters that affect the internal structure of rod-shaped microgels. We characterize the mechanical properties and diffusivity, as well as the conversion of acrylate groups during photopolymerization, in both bulk hydrogels and microgels produced from the PEG-Ac precursors. Furthermore, we investigate cell-microgel interaction, and we observe improved cell spreading on microgels with more accessible RGD peptide and with a stiffness in a range of 20 kPa to 50 kPa lead to better cell growth.

关键词： Diffusion Internal Structure Mechanical Properties Microfluidics PEG Microgels

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