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Comparative immunologic profiling of mRNA and protein-conjugated vaccines: acute inflammatory responses and anti-PEG antibody production

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Integrative Biosciences 2025年第1期29卷 387-401页

作者： Gahyun Roh Jisun Lee Hyun-Mee Park Woori Kwak Hyo-Jung Park Ayoung Oh Yewon Na Dahyeon Ha Yu-Sun Lee Seo-Hyeon Bae Seonghyun Lee Subin Yoon Sowon Lee Jaehun Jung Jacob Lee Jae-Hwan Nam a Department of Medical and Biological Sciences The Catholic University of Korea Bucheon Gyeonggi-do Republic of Koreab BK Four Department of Biotechnology The Catholic University of Korea Bucheon Gyeonggi-do Republic of Korea a Department of Medical and Biological Sciences The Catholic University of Korea Bucheon Gyeonggi-do Republic of Korea c Advanced Analysis and Data Center Korea Institute of Science and Technology Seoul Republic of Korea d Department of Preventive Medicine Gachon University College of Medicine Incheon Republic of Korea e Division of Infectious Disease Department of Internal Medicine Kangnam Sacred Heart Hospital College of Medicine Hallym University Seoul Republic of Korea

ABSTRACTMessenger ribonucleic acid (mRNA) vaccines have become a prevalent immunization method, even as the coronavirus disease 2019 (COVID-19) pandemic recedes. However, the potential adverse effects using mRNA vaccines need to be explored in this evolving landscape. In this study, 60 participants were randomly assigned to receive either an mRNA vaccine, specifically for COVID-19, or a conventional vaccine for meningococcal disease. Symptom records and blood samples were collected on Days 0, 3, and 7 after vaccination. Results showed that recipients of mRNA vaccines exhibited elevated levels of serum acute-phase proteins, such as haptoglobin and C-reactive protein, alongside decreased white blood cell counts compared to those receiving conventional vaccines. Proteomic analysis identified significant changes in nine proteins, including interactions involving complement component C9, haptoglobin, and alpha-1-acid glycoprotein, suggesting implications for complement activation and inflammatory responses. Furthermore, variability in anti-polyethylene glycol antibody levels was noted among mRNA vaccine recipients compared to conventional vaccine recipients. This research aims to provide useful information to help develop future vaccination strategies and shape research directions to mitigate individual adverse *** ABSTRACTDisplay full size

关键词： mRNA COVID-19 vaccination meningococcal vaccines C-reactive protein haptoglobin

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A Wavelet-CNN-LSTM Model for Tailings Pond Risk Prediction

arXiv

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arXiv 2020年

作者： Yang, Jun Li, Qing Sun, Yixuan Wang, Wei Li, Linchao Wang, Xuwei Jia, Shengyao Tong, Renyuan National and Local Joint Engineering research center for Disaster Monitoring Technologies and Instruments China Jiliang University Hangzhou310051 China Zhejiang Provincial Key Laboratory of Intelligent Manufacturing Quality Big Data Traceability Analysis and Application China Jiliang University Hangzhou310051 China Zhejiang PeckerAI Technology. Ltd Hangzhou310018 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China

Tailings ponds are places for storing industrial waste. The saturation line is the key factor of quantifying the safety of tailings pond. Existing saturation line time-series prediction methods are mainly based on statistical models or shallow machine learning models. Although these models aim to capture the time dependence of the sequence data, the channel and temporal are even unavailable in principle. In this paper, we presents a two-stage forecasting method, which embeds the channel and temporal attention into a hybrid CNN-LSTM model to predict the saturation line. In the first stage, the discrete wavelet transform (DWT) is applied to capture the refined sequence information. In the second stage, the CNN-LSTM model is utilized to learn the basic spatial and temporal features in the time series. Furthermore, the channel and temporal attention model are embedded into CNN-LSTM model to enhance the feature extracting ability in channel and temporal dimension. Consequently, our proposed model is shown to outperform classic models on five real-world datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Forecasting

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Author Correction: Mapping annual 10-m soybean cropland with spatiotemporal sample migration

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Scientific data 2024年第1期11卷 565页

作者： Hongchi Zhang Zihang Lou Dailiang Peng Bing Zhang Wang Luo Jianxi Huang Xiaoyang Zhang Le Yu Fumin Wang Linsheng Huang Guohua Liu Shuang Gao Jinkang Hu Songlin Yang Enhui Cheng Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. University of Chinese Academy of Sciences Beijing 100094 China. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. pengdl@***. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. pengdl@***. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. University of Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. Jiangxi Nuclearindustry Surveying and Mapping Institute Group Co. Ltd Nanchang 330038 China. College of Land Science and Technology China Agricultural University Beijing 100083 China. Geospatial Sciences Center of Excellence Department of Geography Geospatial Sciences South Dakota State University Brookings SD 57007 USA. Department of Earth System Science Tsinghua University Beijing 100084 China. Institute of Applied Remote Sensing & Information Technology Zhejiang University Hangzhou 310058 China. National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University Hefei 230601 China. Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai 200120 China.

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Evaluating the Accuracy and Reliability of Real-World Digital Mobility Outcomes in Older Adults After Hip Fracture: Cross-Sectional Observational Study

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JMIR Formative Research 2025年 9卷 e67792页

作者： Berge, Martin A. Paraschiv-Ionescu, Anisoara Kirk, Cameron Küderle, Arne Micó-Amigo, Encarna Becker, Clemens Cereatti, Andrea Del Din, Silvia Engdal, Monika Garcia-Aymerich, Judith Grønvik, Karoline B. Hansen, Clint Hausdorff, Jeffrey M. Helbostad, Jorunn L. Jansen, Carl-Philipp Johnsen, Lars Gunnar Klenk, Jochen Koch, Sarah Maetzler, Walter Megaritis, Dimitrios Müller, Arne Rochester, Lynn Schwickert, Lars Taraldsen, Kristin Vereijken, Beatrix Department of Neuromedicine and Movement Science Norwegian University of Science and Technology Trondheim Norway Laboratory of Movement Analysis and Measurement Ecole Polytechnique Federale de Lausanne Lausanne Switzerland Translational and Clinical Research Institute Faculty of Medical Sciences Newcastle University Newcastle Upon Tyne United Kingdom Machine Learning and Data Analytics Lab Department Artificial Intelligence in Biomedical Engineering Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Geriatric Center Medical Faculty Heidelberg Heidelberg University Heidelberg Germany Department of Geriatrics and Rehabilitation Robert Bosch Hospital Stuttgart Germany Department of Electronics and Telecommunications Politecnico di Torino Turin Italy National Institute for Health and Care Research Newcastle Biomedical Research Centre Newcastle University The Newcastle Upon Tyne Hospitals NHS Foundation Trust Newcastle Upon Tyne United Kingdom Barcelona Institute for Global Health Barcelona Spain Department of Medicine and Life Sciences Universitat Pompeu Fabra Catalonia Barcelona Spain CIBER Epidemiología y Salud Pública Madrid Spain Department of Neurology University Hospital Schleswig-Holstein Kiel University Kiel Germany Center for the Study of Movement Cognition and Mobility Neurological Institute Tel Aviv Medical Center Tel Aviv Israel Department of Physical Therapy Faculty of Medical & Health Sciences Tel Aviv University Tel Aviv Israel Sagol School of Neuroscience Tel Aviv University Tel Aviv Israel Rush Alzheimer’s Disease Center Rush University Medical Center Chicago IL United States Department of Orthopedic Surgery Rush Medical College Rush University Chicago IL United States Department of Orthopaedic Surgery St. Olav’s Hospital Trondheim Norway Institute of Epidemiology and Medical Biometry Ulm University Ulm Germany IB University of Health and Social Sciences Study Centre Stuttgart Stuttgart Germany Department of Sport

Background: algorithms estimating real-world digital mobility outcomes (DMOs) are increasingly validated in healthy adults and various disease cohorts. However, their accuracy and reliability in older adults after hip fracture, who often walk slowly for short durations, is underexplored. Objective: This study examined DMO accuracy and reliability in a hip fracture cohort considering walking bout (WB) duration, physical function, days since surgery, and walking aid use. Methods: In total, 19 community-dwelling participants were real-world monitored for 2.5 hours using a lower back wearable device and a reference system combining inertial modules, distance sensors, and pressure insoles. A total of 6 DMO estimates from 164 WBs from 58% (11/19) of the participants (aged 71-90 years;assessed 32-390 days after surgery;Short Physical Performance Battery [SPPB] scores of 3-12;gait speed range 0.39-1.34 m/s) were assessed against the reference system at the WB and participant level. We stratified by WB duration (all WBs, WBs of >10 seconds, WBs of 10-30 seconds, and WBs of >30 seconds) and lower versus higher SPPB scores and observed whether days since surgery and walking aid use affected DMO accuracy and reliability. Results: Across WBs, walking speed and distance ranged from 0.25 to 1.29 m/s and from 1.7 to 436.5 m, respectively. Estimation of walking speed, cadence, stride duration, number of steps, and distance stratified by WB duration showed intraclass correlation coefficients (ICCs) ranging from 0.50 to 0.99 and mean relative errors (MREs) from –6.9% to 12.8%. Stride length estimation showed poor reliability, with ICCs ranging from 0.30 to 0.49 and MREs from 6.1% to 13.2%. Walking speed and distance ICCs in the higher–SPPB score group ranged from 0.85 to 0.99, and MREs ranged from –10.1% to –1.7%. In the lower–SPPB score group, walking speed and distance ICCs ranged from 0.17 to 0.99, and MREs ranged from 13.5% to 32.6%. There was no discernible effect of time since s

关键词： active aging cadence digital mobility assessment distance free living gait walking speed wearable device

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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Distinguishing Protein Chemical Topologies Using Supercharging Ion Mobility Spectrometry-Mass Spectrometry

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Angewandte Chemie 2023年第51期135卷

作者： Jiyeon Lee Dahye Im Yajie Liu Jing Fang Xibao Tian Minsu Kim Prof. Wen-Bin Zhang Prof. Jongcheol Seo Department of Chemistry Pohang University of Science and Technology (POSTECH) 77 Cheongam-ro Nam-gu Pohang 37673 Gyeonsangbuk-do (Republic of Korea Contribution: Data curation (lead) Formal analysis (equal) Visualization (lead) Writing - original draft (lead) Writing - review & editing (supporting) Contribution: Data curation (supporting) Formal analysis (equal) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (supporting) Beijing National Laboratory for Molecular Sciences Key Laboratory of Polymer Chemistry & Physics of Ministry of Education Center for Soft Matter Science and Engineering College of Chemistry and Molecular Engineering Peking University Beijing 100871 P. R. China Contribution: Resources (equal) Contribution: Data curation (supporting) Validation (supporting) Contribution: Conceptualization (equal) Funding acquisition (equal) Investigation (equal) Project administration (supporting) Writing - review & editing (equal) Contribution: Conceptualization (equal) Funding acquisition (equal) Investigation (lead) Project administration (lead) Validation (lead) Writing - review & editing (lead)

A technique combining ion mobility spectrometry-mass spectrometry (IMS-MS) and supercharging electrospray ionization (ESI) has been demonstrated to differentiate protein chemical topology effectively. Incorporating as many charges as possible into proteins via supercharging ESI allows the protein chains to be largely unfolded and stretched, revealing their hidden chemical topology. Different chemical topologies result in differing geometrical sizes of the unfolded proteins due to constraints in torsional rotations in cyclic domains. By introducing new topological indices, such as the chain-length-normalized collision cross-section (CCS) and the maximum charge state ( z M ) in the extensively unfolded state, we were able to successfully differentiate various protein chemical topologies, including linear chains, ring-containing topologies (lasso, tadpole, multicyclics, etc.), and mechanically interlocked rings, like catenanes.

关键词： Mass Spectrometry Protein Engineering Proteins

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INTRODUCTION

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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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Double-Cable Conjugated Polymers with Pendent Near-Infrared Electron Acceptors for Single-Component Organic Solar Cells

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Angewandte Chemie 2022年第35期134卷

作者： Shijie Liang Baiqiao Liu Dr. Safakath Karuthedath Jing Wang Dr. Yakun He Wen Liang Tan Hao Li Prof. Yunhua Xu Prof. Ning Li Prof. Jianhui Hou Prof. Zheng Tang Prof. Frédéric Laquai Prof. Christopher R. McNeill Prof. Christoph J. Brabec Prof. Weiwei Li Beijing Advanced Innovation Center for Soft Matter Science and Engineering & State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical Technology Beijing 100029 China Contribution: Data curation (lead) Formal analysis (lead) Investigation (equal) Writing - original draft (supporting) Writing - review & editing (supporting) Department of Chemistry School of Science Beijing Jiaotong University Beijing 100044 P. R. China KAUST Solar Center (KSC) Physical Sciences and Engineering Division (PSE) Material Science and Engineering Program (MSE) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Kingdom of Saudi Arabia Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Writing - original draft (supporting) Writing - review & editing (supporting) Center for Advanced Low-dimension Materials College of Materials Science and Engineering Donghua University Shanghai 201620 P. R. China Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Methodology (supporting) Writing - review & editing (supporting) Institute of Materials for Electronics and Energy Technology (i-MEET) Friedrich-Alexander-Universität Erlangen-Nürnberg Martensstrasse 7 91058 Erlangen Germany Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Methodology (supporting) Writing - original draft (supporting) Writing - review & editing (supporting) Department of Materials Science and Engineering Monash University Wellington Road Clayton Victoria 3800 Australia State Key Laboratory of Polymer Physics and Chemistry Beijing National Laboratory for Molecular Sciences Institute of Chemistry Chinese Academy of Sciences Beijing 100190 P. R. China Contribution: Data curation (supporting) Formal analysis (supporting) Writing - review & editing (supporting) Contribution: Funding acquisition (supporting) Writing - review & editing (supportin

Double-cable conjugated polymers with near-infrared (NIR) electron acceptors are synthesized for use in single-component organic solar cells (SCOSCs). Through the development of a judicious synthetic pathway, the highly sensitive nature of the 2-(3-oxo-2,3-dihydroinden-1-ylidene)malononitrile (IC)-based electron acceptors in basic and protonic solvents is overcome. In addition, an asymmetric design motif is adopted to optimize the packing of donor and acceptor segments, enhancing charge separation efficiency. As such, the new double-cable polymers are successfully applied in SCOSCs, providing an efficiency of over 10 % with a broad photo response from 300 to 850 nm and exhibiting excellent thermal/light stability. These results demonstrate the powerful design of NIR-acceptor-based double-cable polymers and will enable SCOSCs to enter a new stage.

关键词： Double-Cable Conjugated Polymers Electron Acceptors Near Infrared Single Component Solar Cells

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Prospect of 5G Application in Civil Airport

Prospect of 5G Application in Civil Airport

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IEEE International Conference on Civil Aviation Safety and Information technology (ICCASIT)

作者： Ningning Le Yinger Zheng Qian Huang Yanqiu Pei Big Data Analysis and Application Center China Academy of Civil Aviation Science and Technology Beijing China Service Lab Huawei Research Institute Huawei Technology Co. Ltd Beijing China College of Geoscience and Surveying Engineering China University of Mining and Technology Beijing China

ISBN: (纸本)9781728125992

With the rapid growth of China's civil aviation transportation volume, the airport has entered the era of big data in which data is massive, diversified, and converted at high speeds. Achievements for intelligent application of big data based on 5G technology have become an indispensable component of smart airports. Based on the characteristics of 5G technology, this paper combines various state-of-art technologies including Discrete Global Grid Systems, Complex Network, Artificial Intelligence, to prospect the application scenarios of 5G in airport, as efficient and secure wide-area wireless communication system, IoT-based smart monitoring, airport unmanned driving, high-speed entertainment experience, intelligent passenger service.

关键词： 5G New data technology Application prospect Civil airport Airports big data 5G mobile communication PASSENGER SERVICES Grid systems Prospecting Wireless communication systems High speed

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The 2021 report of the Lancet Countdown on health and climate change: code red for a healthy future

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The Lancet 2021年第10311期398卷 1619-1662页

作者： Romanello, Marina McGushin, Alice Di Napoli, Claudia Drummond, Paul Hughes, Nick Jamart, Louis Kennard, Harry Lampard, Pete Solano Rodriguez, Baltazar Arnell, Nigel Ayeb-Karlsson, Sonja Belesova, Kristine Cai, Wenjia Campbell-Lendrum, Diarmid Capstick, Stuart Chambers, Jonathan Chu, Lingzhi Ciampi, Luisa Dalin, Carole Dasandi, Niheer Dasgupta, Shouro Davies, Michael Dominguez-Salas, Paula Dubrow, Robert Ebi, Kristie L Eckelman, Matthew Ekins, Paul Escobar, Luis E Georgeson, Lucien Grace, Delia Graham, Hilary Gunther, Samuel H Hartinger, Stella He, Kehan Heaviside, Clare Hess, Jeremy Hsu, Shih-Che Jankin, Slava Jimenez, Marcia P Kelman, Ilan Kiesewetter, Gregor Kinney, Patrick L Kjellstrom, Tord Kniveton, Dominic Lee, Jason K W Lemke, Bruno Liu, Yang Liu, Zhao Lott, Melissa Lowe, Rachel Martinez-Urtaza, Jaime Maslin, Mark McAllister, Lucy McMichael, Celia Mi, Zhifu Milner, James Minor, Kelton Mohajeri, Nahid Moradi-Lakeh, Maziar Morrissey, Karyn Munzert, Simon Murray, Kris A Neville, Tara Nilsson, Maria Obradovich, Nick Sewe, Maquins Odhiambo Oreszczyn, Tadj Otto, Matthias Owfi, Fereidoon Pearman, Olivia Pencheon, David Rabbaniha, Mahnaz Robinson, Elizabeth Rocklöv, Joacim Salas, Renee N Semenza, Jan C Sherman, Jodi Shi, Liuhua Springmann, Marco Tabatabaei, Meisam Taylor, Jonathon Trinanes, Joaquin Shumake-Guillemot, Joy Vu, Bryan Wagner, Fabian Wilkinson, Paul Winning, Matthew Yglesias, Marisol Zhang, Shihui Gong, Peng Montgomery, Hugh Costello, Anthony Hamilton, Ian Institute for Global Health University College London London UK United Kingdom Institute for Sustainable Resources University College London London UK United Kingdom UCL Energy Institute University College London London UK United Kingdom Institute for Environmental Design and Engineering University College London London UK United Kingdom Department of Geography University College London London UK United Kingdom The Bartlett School of Sustainable Construction University College London London UK United Kingdom Centre for Human Health and Performance University College London London UK United Kingdom School of Agriculture Policy and Development University of Reading Reading United Kingdom Department of Meteorology University of Reading Reading United Kingdom The Walker Institute University of Reading Reading United Kingdom Department of Health Sciences University of York York United Kingdom Institute for Environment and Human Security United Nations University Bonn Germany Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK United Kingdom Centre for Mathematical Modelling of Infectious Diseases London School of Hygiene & Tropical Medicine London UK United Kingdom Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London UK United Kingdom Department of Earth System Science Tsinghua University Beijing China Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute for Environmental Sciences World Health Organization Geneva Switzerland Centre for Climate Change and Social Transformations School of Psychology Cardiff University Cardiff United Kingdom Yale Center on Climate Change and Health Yale University New Haven CT United States School of Government University of Birmingham Birmingham United Kingdom Economic analysis of Climate Impacts and Policy Centro Euro-Mediterraneo sui Cambiamenti Climatic

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