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International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)

作者： Chen Feng Narumon Jadram Yuri Nakagawa Midori Sugaya Department of Information Science and Engineering Shibaura Institute of Technology Tokyo Japan Functional Control System Graduate School Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798331516451

ISBN: (纸本)9798331516468

The industrial world is shifting from mass production to meeting individual needs, requiring guidelines to incorporate emotions and preferences. Traditional questionnaires fall short in capturing detailed real-time emotion changes. Therefore, we propose a novel approach using Electroencephalography(EEG), which reflects central nervous system activity, and heart rate variability(HRV), which reflects autonomic nervous system activity, to estimate emotions in real-time by analyzing arousal and valence. Based on the 2D Arousal-Valence model, we plot EEG and HRV data onto this model to visualize emotion changes caused by external stimuli. Using this proposed method, we conducted joint research with the home and personal care sector to evaluate emotional responses to aroma products, and with the automotive sector to assess drivers' emotional states. These studies demonstrate the value of academic research in guiding the industrial sector, particularly through emotion estimation based on EEG and HRV. Our findings suggest that these technologies offer valuable insights into consumer emotions, which can help improve product design and user experience. Ongoing collaboration between academia and the industrial sector is crucial for overcoming challenges in interpreting physiological signals and effectively integrating these methods into practice.

关键词： Estimation Collaboration Companies Brain modeling Electroencephalography User experience Real-time systems Product design Data models Heart rate variability

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Elucidation of the formation process and shape determining factors of GP zones and nanoclusters in Al-Cu and Al-Mg-Si alloys

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第12期74卷 535-545页

作者： Shoji, Mizuki Kurihara, Kensuke Lobzenko, Ivan Tsuru, Tomohito Serizawa, Ai Materials Science and Engineering Graduate School of Engineering and Science Shibaura Institute of Technology 3-7-5 Toyosu Tokyo Koto-ku135-8548 Japan Functional Control System Graduate School of Engineering and Science Shibaura Institute of Technology Tokyo Koto-ku Japan Nuclear Science and Engineering Center Japan Atomic Energy Agency Ibaraki Naka-gun Japan Department of Materials Science and Engineering Shibaura Institute of technology Tokyo Koto-ku Japan

While plate-like Guinier-Preston (GP) zones are formed during aging process in Al-Cu alloys, spherical nanocluster formation occurs in the early stage of aging in Al-Mg-Si alloys. Unlike well-known GP (I) zone in Al-Cu, there is no specific configurations within the nanocluster. However, the solute concentration and local configuration should play decisive role in subsequent formation of precipitates. In the present study, the first-principles calculations were performed to investigate the factors determining the stable shape during the formation process of GP zones and clusters in Al-Cu and Al-Mg-Si alloys. As a result of formation energy calculation of three-body bonds, the Cu-Cu-Cu triplet with the bond angle of 90° was the most stable. Monte Carlo simulations with newly developed machine-learning potential were then performed, and consequently the segregation of Cu atoms with the bond angle of 90° was observed more frequently. In contrast, three-body triplet with the bond angle of 60°was most stable without any specific directional anisotropy in Al-Mg-Si alloy, resulting in the formation of spherical nanoclusters. These results suggest that the intrinsic feature of the stability of local bonding dominates the shape of GP zones and nanoclusters, in which planar- or spherical-like cluster is formed. © 2024 The Japan Institute of Light Metals.

关键词： Silicon alloys

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New Sensing Technologies for Monitoring Machinery,Structures,and Manufacturing Processes

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Journal of Dynamics, Monitoring and Diagnostics 2023年第2期2卷 69-88页

作者： JDMD Editorial Office Zhaoyan Fan Robert X.Gao Qingbo He Yi Huang Tianxi Jiang Zhike Peng Luc Thévenaz Yuyong Xiong Shuncong Zhong Editorial Office of JDMD Chongqing University of TechnologyChongqingPeople’s Republic of China Department of Mechanical Industrialand Manufacturing EngineeringOregon State UniversityCorvallisORUSA Department of Mechanical and Aerospace Engineering Case Western Reserve UniversityClevelandOHUSA State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghaiPeople’s Republic of China Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and AutomationFuzhou UniversityFuzhouPeople’s Republic of China Institute of Precision Instrument and Intelligent Measurement&Control Fuzhou UniversityFuzhouPeople’s Republic of China School of Mechanical Engineering Ningxia UniversityYinchuanPeople’s Republic of China EPFL Ecole Polytechnique Fédérale de Lausanne Group for Fibre OpticsSCI-STI-LT Station 111015 LausanneSwitzerland

Sensing is the fundamental technique for sensor data acquisition in monitoring the operation condition of the machinery,structures,and manufacturing *** this paper,we briefly discuss the general idea and advances of various new sensing technologies,including multiphysics sensing,smart materials and metamaterials sensing,microwave sensing,fiber optic sensors,and terahertz sensing,for measuring vibration,deformation,strain,acoustics,temperature,spectroscopic,*** on the observations from the state of the art,we provide comprehensive discussions on the possible opportunities and challenges of these new sensing technologies so as to steer future development.

关键词： fiber optic sensor metamaterials sensing microwave sensing multiphysics sensing terahertz sensing

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Recent development of chemically complex metallic glasses: from accelerated compositional design, additive manufacturing to novel applications

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Materials Futures 2022年第1期1卷 9-31页

作者： J Y Zhang Z Q Zhou Z B Zhang M H Park Q Yu Z Li J Ma A D Wang H G Huang M Song B S Guo Q Wang Y Yang Department of Mechanical Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople’s Republic of China Shenzhen Key Laboratory of High Performance Nontraditional Manufacturing College of Mechatronics and Control EngineeringShenzhen UniversityShenzhenGuangdong 518060People’s Republic of China School of Materials Science and Engineering Dongguan University of TechnologyDongguanGuangdong 523808People’s Republic of China Institute of Materials China Academy of Engineering PhysicsJiangyouSichuan 621907People’s Republic of China State Key Laboratory of Powder Metallurgy Central South UniversityChangshaHunan 410083People’s Republic of China Institute of Advanced Wear&Corrosion Resistant and Functional Materials Jinan UniversityGuangzhouGuangdong 510632People’s Republic of China Institute of Materials Laboratory for MicrostructuresShanghai UniversityShanghai 200444People’s Republic of China Department of Materials Science and Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople’s Republic of China Department of Advanced Design and System Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople’s Republic of China

Metallic glasses(MGs)or amorphous alloys are an important engineering material that has a history of research of about 80–90 *** different fast cooling methods were developed for multi-component MGs between 1960s and 1980s,1990s witnessed a surge of research interest in the development of bulk metallic glasses(BGMs).Since then,one central theme of research in the metallic-glass community has been compositional design that aims to search for MGs with a better glass forming ability,a larger size and/or more interesting properties,which can hence meet the demands from more important *** this review article,we focus on the recent development of chemically complex MGs,such as high entropy MGs,with new tools that were not available or mature yet until recently,such as the state-of-the-art additive manufacturing technologies,high throughput materials design techniques and the methods for big data analyses(*** learning and artificial intelligence).We also discuss the recent use of MGs in a variety of novel and important applications,from personal healthcare,electric energy transfer to nuclear energy that plays a pivotal role in the battle against global warming.

关键词： metallic glasses amorphous alloys alloy design additive manufacturing machine learning high throughput materials design

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Recent development of chemically complex metallic glasses:from accelerated compositional design,additive manufacturing to novel applications

材料展望（英文）

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材料展望（英文） 2022年第1期 9-31页

作者： J Y Zhang Z Q Zhou Z B Zhang M H Park Q Yu Z Li J Ma A D Wang H G Huang M Song B S Guo Q Wang Y Yang Department of Mechanical Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople's Republic of China Shenzhen Key Laboratory of High Performance Nontraditional Manufacturing College of Mechatronics and Control EngineeringShenzhen UniversityShenzhenGuangdong 518060People's Republic of China School of Materials Science and Engineering Dongguan University of TechnologyDongguanGuangdong 523808People's Republic of China Institute of Materials China Academy of Engineering PhysicsJiangyouSichuan 621907People's Republic of China State Key Laboratory of Powder Metallurgy Central South UniversityChangshaHunan 410083People's Republic of China Department of Mechanical Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople's Republic of China Institute of Advanced Wear & Corrosion Resistant and Functional Materials Jinan UniversityGuangzhouGuangdong 510632People's Republic of China Institute of Materials Laboratory for MicrostructuresShanghai UniversityShanghai 200444People's Republic of China Department of Mechanical Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople's Republic of China Department of Materials Science and Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople's Republic of China Department of Advanced Design and System Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongPeople's Republic of China

Metallic glasses(MGs)or amorphous alloys are an important engineering material that has a history of research of about 80-90 *** different fast cooling methods were developed for multi-component MGs between 1960s and 1980s,1990s witnessed a surge of research interest in the development of bulk metallic glasses(BGMs).Since then,one central theme of research in the metallic-glass community has been compositional design that aims to search for MGs with a better glass forming ability,a larger size and/or more interesting properties,which can hence meet the demands from more important *** this review article,we focus on the recent development of chemically complex MGs,such as high entropy MGs,with new tools that were not available or mature yet until recently,such as the state-of-the-art additive manufacturing technologies,high throughput materials design techniques and the methods for big data analyses(*** learning and artificial intelligence).We also discuss the recent use of MGs in a variety of novel and important applications,from personal healthcare,electric energy transfer to nuclear energy that plays a pivotal role in the battle against global warming.

关键词： metallic glasses amorphous alloys alloy design additive manufacturing machine learning high throughput materials design

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Polygenic risk modeling for prediction of epithelial ovarian cancer risk (vol 30, pg 349, 2021)

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EUROPEAN JOURNAL OF HUMAN GENETICS 2022年第5期30卷 630-631页

作者： Dareng, Eileen O. Tyrer, Jonathan P. Barnes, Daniel R. Jones, Michelle R. Yang, Xin Aben, Katja K. H. Adank, Muriel A. Agata, Simona Andrulis, Irene L. Anton-Culver, Hoda Antonenkova, Natalia N. Aravantinos, Gerasimos Arun, Banu K. Augustinsson, Annelie Balmana, Judith Bandera, Elisa V. Barkardottir, Rosa B. Barrowdale, Daniel Beckmann, Matthias W. Beeghly-Fadiel, Alicia Benitez, Javier Bermisheva, Marina Bernardini, Marcus Q. Bjorge, Line Black, Amanda Bogdanova, Natalia V. Bonanni, Bernardo Borg, Ake Brenton, James D. Budzilowska, Agnieszka Butzow, Ralf Buys, Saundra S. Cai, Hui Caligo, Maria A. Campbell, Ian Cannioto, Rikki Cassingham, Hayley Chang-Claude, Jenny Chanock, Stephen J. Chen, Kexin Chiew, Yoke-Eng Chung, Wendy K. Claes, Kathleen B. M. Colonna, Sarah Cook, Linda S. Couch, Fergus J. Daly, Mary B. Dao, Fanny Davies, Eleanor de la Hoya, Miguel de Putter, Robin Dennis, Joe DePersia, Allison Devilee, Peter Diez, Orland Ding, Yuan Chun Doherty, Jennifer A. Domchek, Susan M. Dork, Thilo du Bois, Andreas Durst, Matthias Eccles, Diana M. Eliassen, Heather A. Engel, Christoph Evans, Gareth D. Fasching, Peter A. Flanagan, James M. Fortner, Renee T. Machackova, Eva Friedman, Eitan Ganz, Patricia A. Garber, Judy Gensini, Francesca Giles, Graham G. Glendon, Gord Godwin, Andrew K. Goodman, Marc T. Greene, Mark H. Gronwald, Jacek Hahnen, Eric Haiman, Christopher A. Hakansson, Niclas Hamann, Ute Hansen, Thomas V. O. Harris, Holly R. Hartman, Mikael Heitz, Florian Hildebrandt, Michelle A. T. Hogdall, Estrid Hogdall, Claus K. Hopper, John L. Huang, Ruea-Yea Huff, Chad Hulick, Peter J. Huntsman, David G. Imyanitov, Evgeny N. Isaacs, Claudine Jakubowska, Anna James, Paul A. Janavicius, Ramunas Jensen, Allan Johannsson, Oskar Th. John, Esther M. Jones, Michael E. Kang, Daehee Karlan, Beth Y. Karnezis, Anthony Kelemen, Linda E. Khusnutdinova, Elza Kiemeney, Lambertus A. Kim, Byoung-Gie Kjaer, Susanne K. Komenaka, Ian Kupryjanczyk, Jolanta Kurian, Allison W. Kwong, Ava Lambrechts, Diether Larson, Melissa C. Lazaro, Conxi L University of Cambridge Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care Cambridge UK University of Cambridge Centre for Cancer Genetic Epidemiology Department of Oncology Cambridge UK Center for Bioinformatics and Functional Genomics Cedars-Sinai Medical Center Los Angeles CA USA Women’s Cancer Program at the Samuel Oschin Comprehensive Cancer Institute Cedars-Sinai Medical Centre Department of Obstetrics and Gynecology Los Angeles CA USA Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen The Netherlands Netherlands Comprehensive Cancer Organisation Utrecht The Netherlands The Netherlands Cancer Institute—Antoni van Leeuwenhoek hospital Family Cancer Clinic Amsterdam The Netherlands Veneto Institute of Oncology IOV—IRCCS Immunology and Molecular Oncology Unit Padua Italy Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Fred A. Litwin Center for Cancer Genetics Toronto ON Canada University of Toronto Department of Molecular Genetics Toronto ON Canada University of California Irvine Department of Epidemiology Genetic Epidemiology Research Institute Irvine CA USA N.N. Alexandrov Research Institute of Oncology and Medical Radiology Minsk Belarus Hannover Medical School Department of Radiation Oncology Hannover Germany Hannover Medical School Gynaecology Research Unit Hannover Germany ‘Agii Anargiri’ Cancer Hospital Athens Greece University of Texas MD Anderson Cancer Center Department of Breast Medical Oncology Houston TX USA Lund University Department of Cancer Epidemiology Clinical Sciences Lund Sweden Vall d’Hebron Institute of Oncology Hereditary cancer Genetics Group Barcelona Spain University Hospital of Vall d’Hebron Department of Medical Oncology Barcelona Spain Rutgers Cancer Institute of New Jersey Cancer Prevention and Control Program New Brunswick NJ USA Landspitali University Hospital Department of Pathology Reykjavik Iceland University of Iceland BMC (B

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915BRCA1and 12,337BRCA2pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) inBRCA1pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) inBRCA2pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

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Global ray-casting range image registration

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IPSJ Transactions on Computer Vision and Applications 2017年第1期9卷 1-15页

作者： Tao, Linh Bui, Tam Hasegawa, Hiroshi Department of Functional Control System Shibaura Institute of Technology 307 Fukasaku Minuma-ku Saitama City Saitama337-8570 Japan School of Mechanical Engineering Hanoi University of Science and Technology 1 Dai Co Viet Road Ha Noi Viet Nam Department of Machinery and Control System Shibaura Institute of Technology 307 Fukasaku Minuma-ku Saitama City Saitama337-8570 Japan

This paper presents a novel method for pair-wise range image registration, a backbone task in world modeling, parts inspection and manufacture, object recognition, pose estimation, robotic navigation, and reverse engineering. The method finds the most suitable homogeneous transformation matrix between two constructed range images to create a more complete 3D view of a scene. The proposed solution integrates a ray casting-based fitness estimation with a global optimization method called improved self-adaptive differential evolution. This method eliminates the fine registration steps of the well-known iterative closest point (ICP) algorithm used in previously proposed methods, and thus, is the first direct global registration algorithm. With its parallel implementation potential, the ray casting-based algorithm speeds up the fitness calculation for the global optimization method, which effectively exploits the search space to find the best transformation solution. The integration was successfully implemented in a parallel paradigm on a multi-core computer processor to solve a simultaneous 3D localization problem. The fast, accurate, and robust results show that the proposed algorithm significantly improves on the registration problem over state-of-the-art algorithms. © The Author(s).

关键词： Global optimization

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Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk

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European journal of human genetics : EJHG 2022年第5期30卷 630-631页

作者： Eileen O Dareng Jonathan P Tyrer Daniel R Barnes Michelle R Jones Xin Yang Katja K H Aben Muriel A Adank Simona Agata Irene L Andrulis Hoda Anton-Culver Natalia N Antonenkova Gerasimos Aravantinos Banu K Arun Annelie Augustinsson Judith Balmaña Elisa V Bandera Rosa B Barkardottir Daniel Barrowdale Matthias W Beckmann Alicia Beeghly-Fadiel Javier Benitez Marina Bermisheva Marcus Q Bernardini Line Bjorge Amanda Black Natalia V Bogdanova Bernardo Bonanni Ake Borg James D Brenton Agnieszka Budzilowska Ralf Butzow Saundra S Buys Hui Cai Maria A Caligo Ian Campbell Rikki Cannioto Hayley Cassingham Jenny Chang-Claude Stephen J Chanock Kexin Chen Yoke-Eng Chiew Wendy K Chung Kathleen B M Claes Sarah Colonna Linda S Cook Fergus J Couch Mary B Daly Fanny Dao Eleanor Davies Miguel de la Hoya Robin de Putter Joe Dennis Allison DePersia Peter Devilee Orland Diez Yuan Chun Ding Jennifer A Doherty Susan M Domchek Thilo Dörk Andreas du Bois Matthias Dürst Diana M Eccles Heather A Eliassen Christoph Engel Gareth D Evans Peter A Fasching James M Flanagan Renée T Fortner Eva Machackova Eitan Friedman Patricia A Ganz Judy Garber Francesca Gensini Graham G Giles Gord Glendon Andrew K Godwin Marc T Goodman Mark H Greene Jacek Gronwald Eric Hahnen Christopher A Haiman Niclas Håkansson Ute Hamann Thomas V O Hansen Holly R Harris Mikael Hartman Florian Heitz Michelle A T Hildebrandt Estrid Høgdall Claus K Høgdall John L Hopper Ruea-Yea Huang Chad Huff Peter J Hulick David G Huntsman Evgeny N Imyanitov Claudine Isaacs Anna Jakubowska Paul A James Ramunas Janavicius Allan Jensen Oskar Th Johannsson Esther M John Michael E Jones Daehee Kang Beth Y Karlan Anthony Karnezis Linda E Kelemen Elza Khusnutdinova Lambertus A Kiemeney Byoung-Gie Kim Susanne K Kjaer Ian Komenaka Jolanta Kupryjanczyk Allison W Kurian Ava Kwong Diether Lambrechts Melissa C Larson Conxi Lazaro Nhu D Le Goska Leslie Jenny Lester Fabienne Lesueur Douglas A Levine Lian Li Jingmei Li Jennifer T Loud Karen H Lu Jan Lubiński Phuong L Mai Siranoush Manoukian Jeffrey R Marks Ra University of Cambridge Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care Cambridge UK. University of Cambridge Centre for Cancer Genetic Epidemiology Department of Oncology Cambridge UK. Center for Bioinformatics and Functional Genomics Cedars-Sinai Medical Center Los Angeles CA USA. Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen The Netherlands. Netherlands Comprehensive Cancer Organisation Utrecht The Netherlands. The Netherlands Cancer Institute-Antoni van Leeuwenhoek hospital Family Cancer Clinic Amsterdam The Netherlands. Veneto Institute of Oncology IOV-IRCCS Immunology and Molecular Oncology Unit Padua Italy. Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Fred A. Litwin Center for Cancer Genetics Toronto ON Canada. University of Toronto Department of Molecular Genetics Toronto ON Canada. University of California Irvine Department of Epidemiology Genetic Epidemiology Research Institute Irvine CA USA. N.N. Alexandrov Research Institute of Oncology and Medical Radiology Minsk Belarus. 'Agii Anargiri' Cancer Hospital Athens Greece. University of Texas MD Anderson Cancer Center Department of Breast Medical Oncology Houston TX USA. Lund University Department of Cancer Epidemiology Clinical Sciences Lund Sweden. Vall d'Hebron Institute of Oncology Hereditary cancer Genetics Group Barcelona Spain. University Hospital of Vall d'Hebron Department of Medical Oncology Barcelona Spain. Rutgers Cancer Institute of New Jersey Cancer Prevention and Control Program New Brunswick NJ USA. Landspitali University Hospital Department of Pathology Reykjavik Iceland. University of Iceland BMC (Biomedical Centre) Faculty of Medicine Reykjavik Iceland. University Hospital Erlangen Friedrich-Alexander-University Erlangen-Nuremberg Department of Gynecology and Obstetrics Comprehensive Cancer Center ER-EMN Erlangen Germany. Vanderbilt University School of Medicine Division of Epide

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

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Gynecologic oncology 2019年第2期153卷 343-355页

作者： Kate Lawrenson Fengju Song Dennis J Hazelett Siddhartha P Kar Jonathan Tyrer Catherine M Phelan Rosario I Corona Norma I Rodríguez-Malavé Ji-Hei Seo Emily Adler Simon G Coetzee Felipe Segato Marcos A S Fonseca Christopher I Amos Michael E Carney Georgia Chenevix-Trench Jiyeob Choi Jennifer A Doherty Weihua Jia Gang J Jin Byoung-Gie Kim Nhu D Le Juyeon Lee Lian Li Boon K Lim Noor A Adenan Mika Mizuno Boyoung Park Celeste L Pearce Kang Shan Yongyong Shi Xiao-Ou Shu Weiva Sieh Pamela J Thompson Lynne R Wilkens Qingyi Wei Yin L Woo Li Yan Beth Y Karlan Matthew L Freedman Houtan Noushmehr Ellen L Goode Andrew Berchuck Thomas A Sellers Soo-Hwang Teo Wei Zheng Keitaro Matsuo Sue Park Kexin Chen Paul D P Pharoah Simon A Gayther Marc T Goodman Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute Cedars-Sinai Medical Center 8700 Beverly Boulevard Suite 290W Los Angeles CA USA Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Electronic address: kate.lawrenson@***. National Clinical Research Center for Cancer Tianjin Medical University Cancer Institute and Hospital Tianjin China Department of Epidemiology and Biostatistics Key Laboratory of Cancer Prevention and Therapy Tianjin China. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Oncology Centre for Cancer Genetic Epidemiology University of Cambridge Strangeways Research Laboratory Cambridge UK. Department of Gynecologic Oncology Moffitt Cancer Center Tampa FL USA Department of Cancer Epidemiology Moffitt Cancer Center Tampa FL USA. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA. Department of Preventive Medicine University of Southern California Keck School of Medicine 1450 Biggy Street Los Angeles CA USA. Department of Genetics Ribeirão Preto Medical School University of São Paulo 14049-900 Brazil. Institute for Clinical and Translational Research Department of Medicine Baylor School of Medicine HoustonTX USA. Department of Obstetrics and Gynecology John A. Burns School of Medicine University of Hawaii Honolulu HI USA. Genetics and Computational Biology Department QIMR Berghofer Medical Research Institute 300 Herston Road Herston QLD 4006 Australia. Department of Preventive Medicine Seoul National University College of Medicine Seoul Republic of Korea Cancer Research Institute Seoul National University Seoul Republic of Korea Department of Biomedical Science Graduate School Seoul National Un

OBJECTIVE:Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS:Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS:At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10). SNP rs6902488 at 6p25.2 (r = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10). CONCLUSION:While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

关键词： Asian ancestry Enhancer Epithelial ovarian cancer Gene regulation Genome-wide association study eQTL

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