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Author Correction: Filling the gap between topological insulator nanomaterials and triboelectric nanogenerators

Nature communications 2022年第1期13卷 1570页

作者： Mengjiao Li Hong-Wei Lu Shu-Wei Wang Rei-Ping Li Jiann-Yeu Chen Wen-Shuo Chuang Feng-Shou Yang Yen-Fu Lin Chih-Yen Chen Ying-Chih Lai Department of Materials Science and Engineering National Chung Hsing University Taichung 40227 Taiwan. Department of Physics National Chung Hsing University Taichung 40227 Taiwan. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA 90089 USA. Francis Bitter Magnet Lab Massachusetts Institute of Technology Cambridge MA 02139 USA. Department of Materials and Optoelectronic Science National Sun Yat-Sen University Kaohsiung 80424 Taiwan. i-Center for Advanced Science and Technology National Chung Hsing University Taichung 40227 Taiwan. Innovation and Development Center of Sustainable Agriculture National Chung Hsing University Taichung 40227 Taiwan. Department of Physics National Chung Hsing University Taichung 40227 Taiwan. yenfulin@nchu.edu.tw. i-Center for Advanced Science and Technology National Chung Hsing University Taichung 40227 Taiwan. yenfulin@nchu.edu.tw. Department of Materials and Optoelectronic Science National Sun Yat-Sen University Kaohsiung 80424 Taiwan. cychen@mail.nsysu.edu.tw. Department of Materials Science and Engineering National Chung Hsing University Taichung 40227 Taiwan. yclai@nchu.edu.tw. i-Center for Advanced Science and Technology National Chung Hsing University Taichung 40227 Taiwan. yclai@nchu.edu.tw. Innovation and Development Center of Sustainable Agriculture National Chung Hsing University Taichung 40227 Taiwan. yclai@nchu.edu.tw.

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Targeted Cancer Therapy: Sequential Magneto-Actuated and Optics-Triggered Biomicrorobots for Targeted Cancer Therapy (Adv. Funct. Mater. 11/2021)

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advanced Functional Materials 2021年第11期31卷

作者： Jiehua Xing Ting Yin Shuiming Li Tiantian Xu Aiqing Ma Ze Chen Yingmei Luo Zhengyu Lai Yingnian Lv Hong Pan Ruijing Liang Xinyu Wu Mingbin Zheng Lintao Cai Guangdong Key Laboratory of Nanomedicine CAS-HK Joint Lab for Biomaterials Shenzhen Institutes of Advanced Technology (SIAT) Chinese Academy of Sciences Shenzhen 518055 P. R. China Guangdong Key Laboratory for Research and Development of Natural Drugs Key Laboratory for Nanomedicine Guangdong Medical University Dongguan 523808 P. R. China Shenzhen Key Laboratory Microbiology and Gene Engineering Shenzhen University Shenzhen 518060 P. R. China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 P. R. China Zhuhai Institute of Advanced Technology Chinese Academy of Sciences Zhuhai 519000 P. R. China The Third People's Hospital of Shenzhen Shenzhen 518114 P. R. China

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Residual Networks for Light Field Image Super-Resolution

Residual Networks for Light Field Image Super-Resolution

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Shuo Zhang Youfang Lin Hao Sheng Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University Key Laboratory of Intelligent Passenger Service of Civil Aviation CAAC State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Light field cameras are considered to have many potential applications since angular and spatial information is captured simultaneously. However, the limited spatial resolution has brought lots of difficulties in developing related applications and becomes the main bottleneck of light field cameras. In this paper, a learning-based method using residual convolutional networks is proposed to reconstruct light fields with higher spatial resolution. The view images in one light field are first grouped into different image stacks with consistent sub-pixel offsets and fed into different network branches to implicitly learn inherent corresponding relations. The residual information in different spatial directions is then calculated from each branch and further integrated to supplement high-frequency details for the view image. Finally, a flexible solution is proposed to super-resolve entire light field images with various angular resolutions. Experimental results on synthetic and real-world datasets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in both visual and numerical evaluations. Furthermore, the proposed method shows good performances in preserving the inherent epipolar property in light field images.

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Cell stiffness measurement by two-fingered micro-hand system with plate shaped end effector 29

Cell stiffness measurement by two-fingered micro-hand system...

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29th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2018

作者： Kojima, Masaru Tanaka, Taisei Mae, Yasushi Ogura, Toshihiko Arai, Tatsuo School of Engineering Science Osaka University 1-3 Machikaneyama-cho Toyonaka Osaka560-8531 Japan Developmental Neurobiology Aging and Cancer Institute of Development Tohoku University Japan Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Global Alliance Lab University of Electro-Communications Japan

ISBN: (纸本)9781538667927

Micro robotics are developed and applied to life-science for advancing this research field. In particular, force measurement methodology of the tissues or single cell have much attention, because the mechanical stimulus is important factor of the histogenesis and cellular differentiation. Furthermore, evaluation of stiffness of organelle is also important for understanding several phenomena in cell. Therefore, we focus on cell and cell nucleus in this study, and reported these stiffness measurement methods and evaluated result. © 2018 IEEE.

关键词： Cell proliferation

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Cell culture-derived extracellular vesicles: Considerations for reporting cell culturing parameters

Journal of Extracellular Biology

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Journal of Extracellular Biology 2023年第10期2卷 e115页

作者： Shekari, Faezeh Alibhai, Faisal J. Baharvand, Hossein Börger, Verena Bruno, Stefania Davies, Owen Giebel, Bernd Gimona, Mario Salekdeh, Ghasem Hosseini Martin-Jaular, Lorena Mathivanan, Suresh Nelissen, Inge Nolte-’t Hoen, Esther Perut, Francesca Pluchino, Stefano Pocsfalvi, Gabriella Salomon, Carlos Soekmadji, Carolina Staubach, Simon Torrecilhas, Ana Claudia Shelke, Ganesh Vilas Tertel, Tobias Zhu, Dandan Théry, Clotilde Witwer, Kenneth Nieuwland, Rienk Department of Stem Cells and Developmental Biology Cell Science Research Center Royan Institute for Stem Cell Biology and Technology ACECR Tehran Iran Advanced Therapy Medicinal Product Technology Development Center (ATMP-TDC) Cell Science Research Center Royan Institute for Stem Cell Biology and Technology ACECR Tehran Iran University Health Network Toronto Canada Department of Developmental Biology School of Basic Sciences and Advanced Technologies in Biology University of Science and Culture Tehran Iran Institute for Transfusion Medicine University Hospital Essen University of Duisburg-Essen Essen Germany Department of Medical Sciences and Molecular Biotechnology Center University of Torino Turin Italy School of Sport Exercise and Health Sciences Loughborough University Loughborough United Kingdom GMP Unit Spinal Cord Injury & Tissue Regeneration Centre Salzburg (SCI-TReCS) and Research Program “Nanovesicular Therapies” Paracelsus Medical University Salzburg Austria Faculty of Natural Sciences Macquarie University North Ryde NSW Australia Institut Curie INSERM U932 and Curie CoreTech Extracellular Vesicles PSL Research University Paris France Department of Biochemistry and Genetics La Trobe Institute for Molecular Science La Trobe University Melbourne VIC Australia VITO (Flemish Institute for Technological Research) Health department Boeretang Belgium Department of Biomolecular Health Sciences Faculty of Veterinary Medicine Utrecht University Utrecht Netherlands School of Pharmacy and Pharmaceutical Sciences & Trinity Biomedical Sciences Institute Trinity College Dublin Dublin Ireland Biomedical Science and Technologies and Nanobiotechnology Lab IRCCS Istituto Ortopedico Rizzoli Bologna Italy Department of Clinical Neurosciences University of Cambridge Cambridge United Kingdom Institute of Biosciences and BioResources National Research Council Naples Italy Translational Extracellular Vesicles in Obstetrics and Gynae-Oncology Group UQ Centre for Cli

Cell culture-conditioned medium (CCM) is a valuable source of extracellular vesicles (EVs) for basic scientific, therapeutic and diagnostic applications. Cell culturing parameters affect the biochemical composition, release and possibly the function of CCM-derived EVs (CCM-EV). The CCM-EV task force of the Rigor and Standardization Subcommittee of the International Society for Extracellular Vesicles aims to identify relevant cell culturing parameters, describe their effects based on current knowledge, recommend reporting parameters and identify outstanding questions. While some recommendations are valid for all cell types, cell-specific recommendations may need to be established for non-mammalian sources, such as bacteria, yeast and plant cells. Current progress towards these goals is summarized in this perspective paper, along with a checklist to facilitate transparent reporting of cell culturing parameters to improve the reproducibility of CCM-EV research. © 2023 The Authors. Journal of Extracellular Biology published by Wiley Periodicals LLC on behalf of International Society for Extracellular Vesicles.

关键词： cell culture-conditioned medium cellular therapy ectosomes exosomes extracellular vesicles in vitro reproducibility rigor standardization

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The pigment transporter Redboy confers programmed body colour transition in orchid mantises

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Nature ecology & evolution 2025年 2025 May 30页

作者： Xiao-Jin Pei Dong Zhao Jie Luo Pei-Yao Jia Yuan Luo Dong-Wei Yuan Wen-Xin Hou Zhan-Feng Zhang Dan-Yan Huang Jia-Xin Ni Hui-Ze Gao Zhanqi Chen Yun-Xia Luan Xue-Xin Chen Wei Zhang Sheng Li Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology Guangzhou Key Laboratory of Insect Development Regulation and Application Research Institute of Insect Science and Technology School of Life Sciences South China Normal University Guangzhou China. Guangmeiyuan R&D Center Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology South China Normal University Meizhou China. Guangdong Laboratory for Lingnan Modern Agriculture Guangzhou China. State Key Laboratory of Gene Function and Modulation Research School of Life Sciences Peking University Beijing China. Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Peking University Beijing China. State Key Laboratory of Crop Stress Biology for Arid Areas and Key Laboratory of Integrated Pest Management on Crops in Northwestern Loess Plateau Ministry of Agriculture and Rural Affairs Northwest A&F University Yangling People's Republic of China. Key Laboratory of Tropical Forest Ecology Xishuangbanna Tropical Botanical Garden Chinese Academy of Sciences Yunnan China. Guangdong Laboratory for Lingnan Modern Agriculture Guangzhou China. xxchen@***. Ministry of Agriculture and Rural Affairs Key Lab of Molecular Biology of Crop Pathogens and Insect Pests Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province Institute of insect Sciences Zhejiang University Hangzhou China. xxchen@***. State Key Laboratory of Gene Function and Modulation Research School of Life Sciences Peking University Beijing China. weizhangvv@***. Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Peking University Beijing China. weizhangvv@***. Institute of Ecology Peking University Beijing China. weizhangvv@***. Institute for Tibetan Plateau Research Peking University Beijing China. weizhangvv@***. Medog Biodiversity Observation and Research Station of Xizang Autonomous Region Nyingchi China

Programmed phenotypic transition is prevalent throughout the tree of life, yet the concrete mechanisms that underpin this phenomenon are poorly understood. The orchid mantis (Hymenopus coronatus, Mantodea) is a model study system for programmed body colour transitions that displays a prominent black-red body colour in first-instar nymphs, then switches to a flowery white body colour in later-instar nymphs. Here we reveal that this body colour transition is achieved by the simultaneous excretion of decarboxylated-xanthommatin (red pigment) and the accumulation of uric acid (white pigment) in the epidermis during the first moult. This change in pigmentation is associated with a novel subtype of ABCG pigment transporter that we call 'Redboy' in Polyneoptera, which is upregulated by insect steroid hormone (ecdysone) during the first moult of orchid mantises. RNAi assay and pigment analyses show that Redboy functions together with the co-transporter White, exporting red pigments from and concurrently importing white pigments into the epidermal cells. Spectral reflectance analyses and predation experiments reveal that Redboy-conferred programmed body colour transition enhances predator avoidance during the first instar, and both prey attraction and predator avoidance in later instars. Our findings clarify how gene family evolution and hormone regulation coordinate programmed phenotypic transition and promote ecological adaptation in orchid mantises.

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CuFe 2 O 4 embedded on polyaniline nanosheet a promising electrocatalyst for OER

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Journal of the Indian Chemical Society 2025年第7期102卷

作者： Nighat Kareem Iffat Karim Sarah A. Alsalhi Jayanti Makasana M.M. Rekha G. Senthil Kumar Mohammed A. Al-Anber Sankar Narayan Das Rahul Raj Chaudhary Abhinav Kumar Ankit D. Oza Advanced Materials and Electrochemical Research Lab Taunsa Sharif 32100 Pakistan Department of Chemistry University of Education DG Khan Campus Lahore Pakistan Department of Physics College of Science Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Marwadi University Research Center Department of Mechanical Engineering Faculty of Engineering & Technology Marwadi University Rajkot 360003 Gujarat India Department of Chemistry and Biochemistry School of Sciences JAIN (Deemed to be University) Bangalore Karnataka India Department of Mechanical Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Department of Chemistry Faculty of Sciences Applied Science Private University P.O. Box 166 Amman 11931 Jordan Department of Mechanical Engineering Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar Odisha 751030 India Department of Mechanical Engineering Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Mohali 140307 Punjab India Department of Nuclear and Renewable Energy Ural Federal University Named after the First President of Russia Boris Yeltsin Ekaterinburg 620002 Russia Department of Mechanical Engineering and Renewable Energy Technical Engineering College The Islamic University Najaf Iraq Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura 140401 Punjab India University Centre for Research and Development Chandigarh University Mohali Punjab 140413 India

In water-splitting oxygen evolution is a crucial and best method to provide clean hydrogen fuel for this purpose many electrocatalysts have been employed. However, creating electrocatalysts for water splitting with a low overpotential is a big challenge. The present work reported the formation of a polyaniline-based CuFe 2 O 4 composite for water-splitting via a hydrothermal route. The structure, shape and texture properties of manufactured electrocatalysts have been determined using different strategies like X-ray diffraction, Scanning electron microscope and Brunauer-Emmett-Teller. Additionally, Electrochemical impedance spectroscopy, linear sweep voltammetry and Chronoamperometry were used to estimate the kinetics of reaction and durability of the electrocatalyst. The electrochemical results demonstrated that the produced material has over-potential 218 mV at current density 10 mA/cm 2 with a Tafel slope of 37 mV dec −1 . While 30 h durability test confirmed that fabricated composite has greater potential with slight variation in current. The exceptional electrochemical properties of the CuFe 2 O 4 /PANI composite make it a promising catalyst for OER and other energy conversion applications.

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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A consensus protocol for functional connectivity analysis in the rat brain (vol 26, pg 673, 2023)

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NATURE NEUROSCIENCE 2023年第6期26卷 1127-1128页

作者： Grandjean, Joanes Desrosiers-Gregoire, Gabriel Anckaerts, Cynthia Angeles-Valdez, Diego Ayad, Fadi Barriere, David A. Blockx, Ines Bortel, Aleksandra Broadwater, Margaret Cardoso, Beatriz M. Celestine, Marina Chavez-Negrete, Jorge E. Choi, Sangcheon Christiaen, Emma Clavijo, Perrin Colon-Perez, Luis Cramer, Samuel Daniele, Tolomeo Dempsey, Elaine Diao, Yujian Doelemeyer, Arno Dopfel, David Dvorakova, Lenka Falfan-Melgoza, Claudia Fernandes, Francisca F. Fowler, Caitlin F. Fuentes-Ibanez, Antonio Garin, Clement M. Gelderman, Eveline Golden, Carla E. M. Guo, Chao C. G. Henckens, Marloes J. A. G. Hennessy, Lauren A. Herman, Peter Hofwijks, Nita Horien, Corey Ionescu, Tudor M. Jones, Jolyon Kaesser, Johannes Kim, Eugene Lambers, Henriette Lazari, Alberto Lee, Sung-Ho Lillywhite, Amanda Liu, Yikang Liu, Yanyan Y. Lopez-Castro, Alejandra Lopez-Gil, Xavier Ma, Zilu MacNicol, Eilidh Madularu, Dan Mandino, Francesca Marciano, Sabina McAuslan, Matthew J. McCunn, Patrick McIntosh, Alison Meng, Xianzong Meyer-Baese, Lisa Missault, Stephan Moro, Federico Naessens, Daphne M. P. Nava-Gomez, Laura J. Nonaka, Hiroi Ortiz, Juan J. Paasonen, Jaakko Peeters, Lore M. Pereira, Mickael Perez, Pablo D. Pompilus, Marjory Prior, Malcolm Rakhmatullin, Rustam Reimann, Henning M. Reinwald, Jonathan Del Rio, Rodrigo Triana Rivera-Olvera, Alejandro Ruiz-Perez, Daniel Russo, Gabriele Rutten, Tobias J. Ryoke, Rie Sack, Markus Salvan, Piergiorgio Sanganahalli, Basavaraju G. Schroeter, Aileen Seewoo, Bhedita J. Selingue, Erwan Seuwen, Aline Shi, Bowen Sirmpilatze, Nikoloz Smith, Joanna A. B. Smith, Corrie Sobczak, Filip Stenroos, Petteri J. Straathof, Milou Strobelt, Sandra Sumiyoshi, Akira Takahashi, Kengo Torres-Garcia, Maria E. Tudela, Raul van den Berg, Monica van der Marel, Kajo van Hout, Aran T. B. Vertullo, Roberta Vidal, Benjamin Vrooman, Roel M. Wang, Victora X. Wank, Isabel Watson, David J. G. Yin, Ting Zhang, Yongzhi Zurbruegg, Stefan Achard, Sophie Alcauter, Sarael Auer, Dorothee P. Barbier, Emmanuel L. Baudewig, Juergen Beckmann, Chri Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada Integrated Program in Neuroscience McGill University Montreal QC Canada Bio-imaging Lab University of Antwerp Antwerp Belgium µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico Biological and Biomedical Engineering McGill University Montreal QC Canada McConnell Brain Imaging Centre McGill University Montreal QC Canada Montreal Neurological Institute McGill University Montreal QC Canada UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France Department of Neurology and Neurosurgery McGill University Montreal QC Canada Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cybernetics Tuebingen Germany Graduate Training Centre of Neuroscience International Max

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.

关键词： Databases Neural circuits

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The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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