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The impact of the change of trade pattern on China’s energy industry——Based on the measurement of the upstreamness of production of the value chains

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Procedia Computer Science 2018年 139卷 248-255页

作者： Xinran Wang Xiaoxian Guo Yan Song Shasha Cao Tian Wu Xin Tian Zhenping Li Shanghai Pudong Development Bank Shnaghai 200000 China China Petroleum Technology and Development Corporation Beijing 100028 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China NCMIS Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Information Beijing Wuzi University Beijing 101149 China

The natural monopoly of China’s upstream industry and the vertical structure of industrial chain’s upstream and downstream competition is an important feature of China’s industrial economic structure, and the impact of the change of trade pattern on the energy industry, which located at the upstream of the China’s value chain, has become an important issue in the industrial economy. Since China has entered into the WTO in 2001, we use it for event analysis based on 1987-2007 China input-output data. The study calculates the upstreamness of production of the value chain in various industrial sectors of China’s energy industry every five years, and make correlation analysis of upstreamness of production and other economic indicators to check the characteristics of periodic inspection of China’s industrial structure with the development of industrial economy and the change of trade pattern.

关键词： Energy industry industrial economic structure upstreamness of production trade pattern

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What Does Equitable Co-Production Entail? Three Perspectives

Community Science

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Community Science 2023年第2期2卷

作者： K. L. Akerlof K. M. F. Timm A. Chase E. T. Cloyd E. Heath B. A. McGhghy A. Bamzai-Dodson G. Bogard S. Carter J. Garron M. Gavazzi N. Kettle M. Labriole J. S. Littell M. Madajewicz J. Reyes L. Rivers III J. L. Sheats C. F. Simpson R. C. Toohey Department of Environmental Science & Policy George Mason University Fairfax VA USA Contribution: Conceptualization Funding acquisition Investigation Methodology Project administration Data curation Formal analysis Writing - original draft Writing - review & editing International Arctic Research Center University of Alaska Fairbanks Fairbanks AK USA Contribution: Conceptualization Funding acquisition Investigation Methodology Writing - original draft Writing - review & editing Contribution: Investigation Writing - original draft Writing - review & editing Department of Energy and Environment Government of the District of Columbia Washington DC USA Contribution: Conceptualization Funding acquisition Investigation Writing - original draft Writing - review & editing American Association for the Advancement of Science Washington DC USA American Geophysical Union Washington DC USA Contribution: Writing - original draft Writing - review & editing U.S. Geological Survey North Central Climate Adaptation Science Center Boulder CO USA U.S. Geological Survey National Climate Adaptation Science Center Reston VA USA U.S. Department of Agriculture Research Triangle Park NC USA New York Hall of Science Queens NY USA U.S. Geological Survey Alaska Climate Adaptation Science Center Anchorage AK USA Center for Climate Systems Research The Climate School Columbia University New York NY USA NOAA Climate Adaptation Partnerships (CAP) Consortium for Climate Risk in the Urban Northeast (CCRUN) New York NY USA U.S. Department of Agriculture Washington DC USA Environmental Protection Agency Office of Research and Development Research Triangle Park NC USA Department of Social Behavioral and Population Sciences Tulane University School of Public Health &Tropical Medicine New Orleans LA USA Aspen Institute Science & Society Program Washington DC USA National Oceanic and Atmospheric Administration Climate Adaptation Partnerships Silver Spring MD USA

Co-production practices are increasingly being adopted in research conducted for the purpose of societal impact. However, the ways in which co-production is conducted can perpetuate long-standing inequity and inequality. This study investigates which principles of co-production design are perceived to advance more equitable processes and outcomes based on the experiences of participants in three projects funded by U.S. federal programs that support decision-relevant climate science, along with others engaged in co-production efforts. We found three distinct perspectives: (a) Ways of Knowing and Power; (b) Participants and Interactions; and (c) Science as Capacity Building. Each viewpoint differentially weights the salience of statements associated with five dimensions of co-production practices: (a) outcomes; (b) power; (c) place-based, community rights and respect; (d) audiences and participation; and (e) interactions. In the final stage of the study, we hosted a workshop of participants representing various roles in co-production efforts to vet and discuss each perspective. We found that the perspectives remained distinct after each of the groups selected core statements that reflect their views. The degree of variation across the three perspectives suggests that co-production processes would benefit from an initial discussion of, and decisions about, rules of engagement to ensure that participants view the process as equitable.

关键词： co-production equity climate change federal research programs

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

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NATURE 2023年第7948期614卷 E38-E38页

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

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Publisher Correction: Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance

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Nature genetics 2024年第10期56卷 2281页

作者： Qingbo S Wang Takanori Hasegawa Ho Namkoong Ryunosuke Saiki Ryuya Edahiro Kyuto Sonehara Hiromu Tanaka Shuhei Azekawa Shotaro Chubachi Yugo Takahashi Saori Sakaue Shinichi Namba Kenichi Yamamoto Yuichi Shiraishi Kenichi Chiba Hiroko Tanaka Hideki Makishima Yasuhito Nannya Zicong Zhang Rika Tsujikawa Ryuji Koike Tomomi Takano Makoto Ishii Akinori Kimura Fumitaka Inoue Takanori Kanai Koichi Fukunaga Seishi Ogawa Seiya Imoto Satoru Miyano Yukinori Okada Department of Genome Informatics Graduate School of Medicine University of Tokyo Tokyo Japan. qingbow@m.u-tokyo.ac.jp. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. qingbow@m.u-tokyo.ac.jp. M&D Data Science Center Tokyo Medical and Dental University Tokyo Japan. Department of Infectious Diseases Keio University School of Medicine Tokyo Japan. hounamugun@keio.jp. Department of Pathology and Tumor Biology Kyoto University Kyoto Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Department of Respiratory Medicine and Clinical Immunology Osaka University Graduate School of Medicine Suita Japan. Department of Genome Informatics Graduate School of Medicine University of Tokyo Tokyo Japan. Division of Pulmonary Medicine Department of Medicine Keio University School of Medicine Tokyo Japan. Faculty of Medicine Osaka University Suita Japan. Center for Data Sciences Brigham and Women's Hospital Harvard Medical School Boston MA USA. Divisions of Genetics and Rheumatology Department of Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA. Laboratory of Children's Health and Genetics Division of Health Science Osaka University Graduate School of Medicine Suita Japan. Department of Pediatrics Osaka University Graduate School of Medicine Suita Japan. Division of Genome Analysis Platform Development National Cancer Center Research Institute Tokyo Japan. Institute for the Advanced Study of Human Biology (WPI-ASHBi) Kyoto University Kyoto Japan. Health Science Research and Development Center (HeRD) Tokyo Medical and Dental University Tokyo Japan. Laboratory of Veterinary Infectious Disease Department of Veterinary Medicine Kitasato University Tokyo Japan. Department of Respiratory Medicine Nagoya University Graduate School of Medicine Nagoya Japan. In

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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A universal language for finding mass spectrometry data patterns

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Nature Methods 2025年 1-8页

作者： Damiani, Tito Jarmusch, Alan K. Aron, Allegra T. Petras, Daniel Phelan, Vanessa V. Zhao, Haoqi Nina Bittremieux, Wout Acharya, Deepa D. Ahmed, Mohammed M. A. Bauermeister, Anelize Bertin, Matthew J. Boudreau, Paul D. Borges, Ricardo M. Bowen, Benjamin P. Brown, Christopher J. Chagas, Fernanda O. Clevenger, Kenneth D. Correia, Mario S. P. Crandall, William J. Crüsemann, Max Fahy, Eoin Fiehn, Oliver Garg, Neha Gerwick, William H. Gilbert, Jeffrey R. Globisch, Daniel Gomes, Paulo Wender P. Heuckeroth, Steffen James, C. Andrew Jarmusch, Scott A. Kakhkhorov, Sarvar A. Kang, Kyo Bin Kessler, Nikolas Kersten, Roland D. Kim, Hyunwoo Kirk, Riley D. Kohlbacher, Oliver Kontou, Eftychia E. Liu, Ken Lizama-Chamu, Itzel Luu, Gordon T. Luzzatto Knaan, Tal Mannochio-Russo, Helena Marty, Michael T. Matsuzawa, Yuki McAvoy, Andrew C. McCall, Laura-Isobel Mohamed, Osama G. Nahor, Omri Neuweger, Heiko Niedermeyer, Timo H. J. Nishida, Kozo Northen, Trent R. Overdahl, Kirsten E. Rainer, Johannes Reher, Raphael Rodriguez, Elys Sachsenberg, Timo T. Sanchez, Laura M. Schmid, Robin Stevens, Cole Subramaniam, Shankar Tian, Zhenyu Tripathi, Ashootosh Tsugawa, Hiroshi van der Hooft, Justin J. J. Vicini, Andrea Walter, Axel Weber, Tilmann Xiong, Quanbo Xu, Tao Pluskal, Tomáš Dorrestein, Pieter C. Wang, Mingxun Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences Prague Czech Republic Metabolomics Core Facility Immunity Inflammation and Disease Laboratory Division of Intramural Research National Institute of Environmental Health Sciences National Institutes of Health Research Triangle Park NC United States Department of Chemistry and Biochemistry University of Denver Denver CO United States Functional Metabolomics Lab CMFI Cluster of Excellence University of Tuebingen Tuebingen Germany Department of Biochemistry University of California Riverside Riverside CA United States Department of Pharmaceutical Sciences Skaggs School of Pharmacy and Pharmaceutical Sciences University of Colorado Anschutz Medical Campus Aurora CO United States Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA United States Biologicals and Natural Products Discovery Crop Protection R & D Corteva Agrisciences Indianapolis IN United States BioMolecular Sciences School of Pharmacy University of Mississippi Oxford MS United States Pharmacognosy Faculty of Pharmacy Al-Azhar University Nasr City Egypt Department of Fundamental Chemistry Institute of Chemistry University of São Paulo São Paulo Brazil Department of Chemistry Case Western Reserve University Cleveland OH United States Walter Mors Institute of Research on Natural Products Federal University of Rio de Janeiro Rio de Janeiro Brazil Environmental Genomics and Systems Biology Division Lawrence Berkeley National Lab Berkeley CA United States The Joint Genome Institute Lawrence Berkeley National Lab Berkeley CA United States Mass Spectrometry Center of Expertise Regulatory and Stewardship Corteva Agrisciences Indianapolis IN United States Biologicals and Natural Products Crop Protection R & D Corteva Agrisciences Indianapolis IN United States Department of Chemistry – BMC Science for Life Laborat

Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized;most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabling the community to directly query mass spectrometry data with an expressive set of user-defined mass spectrometry patterns. Illustrated by real-world examples, MassQL provides a data-driven definition of chemical diversity by enabling the reanalysis of all public untargeted metabolomics data, empowering scientists across many disciplines to make new discoveries. MassQL has been widely implemented in multiple open-source and commercial mass spectrometry analysis tools, which enhances the ability, interoperability and reproducibility of mining of mass spectrometry data for the research community. © The Author(s), under exclusive licence to Springer Nature America, Inc. 2025.

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Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

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Stroke genetics informs drug discovery and risk prediction across ancestries (vol 611, pg 115, 2022)

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NATURE 2022年第7938期612卷 E7-E7页

作者： Mishra, Aniket Malik, Rainer Hachiya, Tsuyoshi Jurgenson, Tuuli Namba, Shinichi Posner, Daniel C. Kamanu, Frederick K. Koido, Masaru Le Grand, Quentin Shi, Mingyang He, Yunye Georgakis, Marios K. Caro, Ilana Krebs, Kristi Liaw, Yi-Ching Vaura, Felix C. Lin, Kuang Winsvold, Bendik Slagsvold Srinivasasainagendra, Vinodh Parodi, Livia Bae, Hee-Joon Chauhan, Ganesh Chong, Michael R. Tomppo, Liisa Akinyemi, Rufus Roshchupkin, Gennady V. Habib, Naomi Jee, Yon Ho Thomassen, Jesper Qvist Abedi, Vida Carcel-Marquez, Jara Nygaard, Marianne Leonard, Hampton L. Yang, Chaojie Yonova-Doing, Ekaterina Knol, Maria J. Lewis, Adam J. Judy, Renae L. Ago, Tetsuro Amouyel, Philippe Armstrong, Nicole D. Bakker, Mark K. Bartz, Traci M. Bennett, David A. Bis, Joshua C. Bordes, Constance Borte, Sigrid Cain, Anael Ridker, Paul M. Cho, Kelly Chen, Zhengming Cruchaga, Carlos Cole, John W. de Jager, Phil L. de Cid, Rafael Endres, Matthias Ferreira, Leslie E. Geerlings, Mirjam I. Gasca, Natalie C. Gudnason, Vilmundur Hata, Jun He, Jing Heath, Alicia K. Ho, Yuk-Lam Havulinna, Aki S. Hopewell, Jemma C. Hyacinth, I. Hyacinth Inouye, Michael Jacob, Mina A. Jeon, Christina E. Jern, Christina Kamouchi, Masahiro Keene, Keith L. Kitazono, Takanari Kittner, Steven J. Konuma, Takahiro Kumar, Amit Lacaze, Paul Launer, Lenore J. Lee, Keon-Joo Lepik, Kaido Li, Jiang Li, Liming Manichaikul, Ani Markus, Hugh S. Marston, Nicholas A. Meitinger, Thomas Mitchell, Braxton D. Montellano, Felipe A. Morisaki, Takayuki Mosley, Thomas H. Nalls, Mike A. Nordestgaard, Borge G. O'Donnell, Martin J. Okada, Yukinori Onland-Moret, N. Charlotte Ovbiagele, Bruce Peters, Annette Psaty, Bruce M. Rich, Stephen S. Rosand, Jonathan Sabatine, Marc S. Sacco, Ralph L. Saleheen, Danish Sandset, Else Charlotte Salomaa, Veikko Sargurupremraj, Muralidharan Sasaki, Makoto Satizabal, Claudia L. Schmidt, Carsten O. Shimizu, Atsushi Smith, Nicholas L. Sloane, Kelly L. Sutoh, Yoichi Sun, Yan V. Tanno, Kozo Tiedt, Steffen Tatlisumak, Turgut Torres-Aguila, Nuria P. Tiwari, Hemant K. Tregouet, Bordeaux Population Health Research Center University of Bordeaux Inserm UMR 1219 Bordeaux France Department of Public Health Bordeaux University Hospital Bordeaux France Department of Neurology Memory Clinic Bordeaux University Hospital Bordeaux France Department of Neurology Institute for Neurodegenerative Diseases CHU de Bordeaux Bordeaux France Institute for Stroke and Dementia Research (ISD) University Hospital LMU Munich Munich Germany Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of Harvard and the Massachusetts Institute of Technology Cambridge MA USA Munich Cluster for Systems Neurology Munich Germany German Center for Neurodegenerative Diseases (DZNE) Munich Germany Iwate Tohoku Medical Megabank Organization Iwate Medical University Iwate Japan Estonian Genome Centre Institute of Genomics University of Tartu Tartu Estonia Institute of Mathematics and Statistics University of Tartu Tartu Estonia Department of Computational Biology University of Lausanne Lausanne Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland University Center for Primary Care and Public Health Lausanne Switzerland Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan Department of Genome Informatics Graduate School of Medicine The University of Tokyo Tokyo Japan Laboratory for Systems Genetics RIKEN Center for Integrative Medical Sciences Yokohama Japan Laboratory of Statistical Immunology Immunology Frontier Research Center (WPI-IFReC) Osaka University Suita Japan Integrated Frontier Research for Medical Science Division Institute for Open and Transdisciplinary Research Initiatives Osaka University Suita Japan Center for Infectious Disease Education and Research (CiDER) Osaka University Suita Japan Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) VA Boston Healthcare System Boston MA USA TIMI S

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Body fluid biomarkers and psychosis risk in The Accelerating Medicines Partnership® Schizophrenia Program: design considerations

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Schizophrenia (Heidelberg, Germany) 2025年第1期11卷 78页

作者： Diana O Perkins Clark D Jeffries Scott R Clark Rachel Upthegrove Cassandra M J Wannan Naomi R Wray Qingqin S Li Kim Q Do Elaine Walker G Paul Amminger Alan Anticevic David Cotter Lauren M Ellman David Mongan Christina Phassouliotis Jenna Barbee Sharin Roth Tashrif Billah Cheryl Corcoran Monica E Calkins Felecia Cerrato Ines Khadimallah Paul Klauser Inge Winter-van Rossum Angela R Nunez Rachel S Bleggi Alicia R Martin Sylvain Bouix Ofer Pasternak Jai L Shah Catherine Toben Daniel H Wolf Rene S Kahn John M Kane Patrick D McGorry Carrie E Bearden Barnaby Nelson Martha E Shenton Scott W Woods Department of Psychiatry University of North Carolina at Chapel Hill Chapel Hill NC USA. diana_perkins@med.unc.edu. Rennaisance Computing Institute University of North Carolina at Chapel Hill Chapel Hill NC USA. Discipline of Psychiatry University of Adelaide Adelaide SA Australia. Basil Hetzel Institute Woodville SA Australia. Institute for Mental Health University of Birmingham Birmingham UK. Birmingham Womens and Childrens NHS Foundation Trust Birmingham UK. Centre for Youth Mental Health The University of Melbourne Parkville VIC Australia. Orygen Parkville VIC Australia. Department of Psychiatry University of Oxford Oxford UK. Institute for Molecular Biosciences University of Queensland Queensland Australia. JRD Data Science Janssen Research & Development LLC Titusville NJ USA. Department of Psychiatry Center for Psychiatric Neuroscience Lausanne University Hospital and University of Lausanne Lausanne Switzerland. Department of Psychological Medicine Institute of Psychiatry Psychology and Neuroscience King's College London London UK. Departments of Psychology and Psychiatry Emory University Atlanta GA United States of America. Department of Psychiatry Yale University School of Medicine New Haven CT USA. Department of Psychiatry Royal College of Surgeons in Ireland Dublin Ireland. School of Computing and Information Systems The University of Melbourne Parkville VIC Australia. Department of Psychology and Neuroscience Temple University Philadelphia PA USA. Centre for Public Health Queen's University Belfast Belfast United Kingdom. Department of Psychiatry University of North Carolina at Chapel Hill Chapel Hill NC USA. Genomics and Biomarker Research Otsuka Pharmaceutical Development & Commercialization Inc Rockville MD USA. Department of Psychiatry Brigham and Women's Hospital and Harvard Medical School Boston MA USA. Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA. Department of Psychiatry Pe

Advances in proteomic assay methodologies and genomics have significantly improved our understanding of the blood proteome. Schizophrenia and psychosis risk are linked to polygenic scores for schizophrenia and other mental disorders, as well as to altered blood and saliva levels of biomarkers involved in hormonal signaling, redox balance, and chronic systemic inflammation. The Accelerating Medicines Partnership® Schizophrenia (AMP®SCZ) aims to ascertain biomarkers that both predict clinical outcomes and provide insights into the biological processes driving clinical outcomes in persons meeting CHR criteria. AMP®SCZ will follow almost 2000 CHR and 640 community study participants for two years, assessing biomarkers at baseline and two-month follow-up including the collection of blood and saliva samples. The following provides the rationale and methods for plans to utilize polygenic risk scores for schizophrenia and other disorders, salivary cortisol levels, and a discovery-based proteomic platform for plasma analyses. We also provide details about the standardized methods used to collect and store these biological samples, as well as the study participant metadata and quality control measures related to preanalytical factors that could influence the values of the biomarkers. Finally, we discuss our plans for analyzing the results of blood- and saliva-based biomarkers. Watch Dr. Perkins discuss their work and this article: https://***/1062879582?share=copy#t=0 .

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Distributed software development of a cloud solution for collaborative manufacturing networks 23

Distributed software development of a cloud solution for col...

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23rd International Conference on Engineering, Technology and Innovation, ICE/ITMC 2017

作者： Bendas, Dan Saari, Leila Coutinho, Carlos De Juan Marin, Ruben Gisbert, Josep Bernabe Lopes, Luis Data-Driven Solutions VTT Technical Research Centre of Finland Ltd. Oulu Finland ISTAR-IUL Caixa Mágica Software CMS Lisbon Portugal Distributed Systems Instituto Tecnológico de Informática ITI Valencia Spain Research and Development Caixa Mágica Software CMS Lisbon Portugal

ISBN: (纸本)9781538607749

Distributed software development poses extra difficulties in terms of communication, coordination and awareness. Those difficulties usually imply more time consumption that causes productiveness reduction deriving finally in delays. So, projects where such kind of development is needed have to deal with them in order to ensure the success of the project. The case project has adopted this development approach due to its nature. The main goal of the project is to develop a cloud solution for enhancing collaboration and transparency between manufacturing companies forming a collaborative network. In order to implement it, the overall solution has been divided into several pieces, having many interdependencies among them. Thus, different working teams geographically spread from different organizations have participated in the implementation, integration, verification and validation tasks. This paper explains how the case project has organized the working teams, infrastructure, procedures and practices to guarantee the success of the project. © 2017 IEEE.

关键词： Software design

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