检索结果-内蒙古大学图书馆

42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020

作者： Bolleddula, Nithish Chun Hung, Geoffrey Yau Ma, Daren Noorian, Hoda Woodbridge, Diane Myung-Kyung Ms in Data Science Program University of San Francisco United States

ISBN: (纸本)9781728119908

As the world's older population grows dramatically, the needs of continuing care retirement communities increases. Studies show that privacy can be a major concern for adopting technologies, while the older population prefers smart homes [1]. In order to minimize the number of sensors to be installed in each house, we performed Principal Component Analysis (PCA) to filter out the relatively unimportant sensors. We applied a machine learning model to classify residents' activity types, using a different set of sensors chosen by PCA. Then, we validated the trade-off between the classification model accuracy and the number of sensors used in classification. Our experiment shows that feature engineering helps reduce accuracy degradation for activity type classification when using fewer sensors in smart homes. © 2020 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Sensor Selection for Activity Classification at Smart Home Environments

Sensor Selection for Activity Classification at Smart Home E...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Nithish Bolleddula Geoffrey Yau Chun Hung Daren Ma Hoda Noorian Diane Myung-kyung Woodbridge MS in Data Science Program University of San Francisco

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

关键词： Feature extraction Principal component analysis Microsoft Windows Machine learning Smart homes Distributed computing

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Approach to Detecting Low Medication State with Wearable Technologies

A Machine Learning Approach to Detecting Low Medication Stat...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Andy Cheon Stephanie Yeoju Jung Collin Prather Matthew Sarmiento Kevin Wong Diane Myung-kyung Woodbridge MS in Data Science Program University of San Francisco

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Medication adherence is a critical component and implicit assumption of the patient life cycle that is often violated, incurring financial and medical costs to both patients and the medical system at large. As obstacles to medication adherence are complex and varied, approaches to overcome them must themselves be *** paper demonstrates one such approach using sensor data recorded by an Apple Watch to detect low counts of pill medication in standard prescription bottles. We use distributed computing on a cloud-based platform to efficiently process large volumes of high-frequency data and train a Gradient Boosted Tree machine learning model. Our final model yielded average cross-validated accuracy and F1 scores of 80.27% and 80.22%, *** conclude this paper with two use cases in which wearable devices such as the Apple Watch can contribute to efforts to improve patient medication adherence.

关键词： Microsoft Windows Machine learning Computational modeling Standards data models Containers Gyroscopes

来源：评论

学校读者我要写书评

暂无评论

SARS-CoV-2 surveillance of wastewater in small rural communities identifies lack of vaccine coverage as influence of omicron outbreak

引用

Water Research 2025年 283卷 123818页

作者： Solana Narum Thibault Stalder Benjamin Ridenhour Erik R. Coats Bioinformatics and Computational Biology Graduate Program (BCB) University of Idaho 875 Perimeter Drive MS 1103 Moscow ID 83844 United States Institute for Modeling Collaboration and Innovation (IMCI) University of Idaho 875 Perimeter Drive MS 1122 Moscow ID 83844 United States Department of Biological Sciences University of Idaho 875 Perimeter Drive MS 3051 Moscow ID 83844 United States Institute for Interdisciplinary Data Sciences (IIDS) University of Idaho 875 Perimeter Drive MS 3051 Moscow ID 83844 United States Department of Mathematics and Statistical Science University of Idaho 875 Perimeter Drive MS 1103 Moscow ID 83844 United States Department of Civil and Environmental Engineering University of Idaho 875 Perimeter Drive MS 1022 Moscow ID 83844 United States

Wastewater-based epidemiology (WBE) can provide critical early warnings to aid public health, which can be particularly beneficial in rural communities with limited access to health care. Spikes of SARS-CoV-2 RNA concentration in wastewater have been used to represent infections in a community, but wastewater holds a wealth of information that has not been explored yet. The objectives of this research were to expand the use of WBE to 1) determine the dynamic of SARS-CoV-2 variants in rural communities, and 2) evaluate the relationship between community vaccination status and the outbreak of a variant. We quantified the concentration of SARS-CoV-2 RNA, as well as specific mutations that are consistent with Delta and Omicron in influent raw wastewater samples collected from wastewater treatment facilities (WWTFs) for five populations with <1000 residents and one larger population in Latah County, ID. A binomial generalized linear model using the percent of the population with protection against Omicron from the initial vaccines and the booster shot was able to predict the probability of an uptick in Omicron concentration in wastewater with an accuracy of 0.96. Evaluation of vaccination data indicate that the spike in Omicron infections in December 2021 in the studied towns was linked to low levels of population protection from the initial shots of the COVID-19 vaccine against Omicron infection and limited uptake of booster shots in these communities. Despite difficulties with applying WBE in rural regions, this study shows that beyond evaluating spikes of viral infections, WBE can be used to evaluate the effect of a population’s vaccine coverage on SARS-CoV-2 variant dynamics.

关键词： COVID-19 Delta Modeling Omicron Population coverage Prediction

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Analyzing Atomic Force Microscopy (AFM) Images Generated from Polymer Blends

arXiv

引用

arXiv 2024年

作者： Paruchuri, Aanish Wang, Yunfei Gu, Xiaodan Jayaraman, Arthi Master of Science in Data Science Program University of Delaware NewarkDE19713 United States School of Polymer Science and Engineering University of Southern Mississippi 118 College Drive #5050 HattiesburgMS39406 United States Department of Chemical and Biomolecular Engineering University of Delaware 150 Academy St NewarkDE19713 United States Department of Materials Science and Engineering University of Delaware NewarkDE19713 United States Data Science Institute University of Delaware NewarkDE19713 United States

In this paper we present a new machine learning (ML) workflow with unsupervised learning techniques to identify domains within atomic force microscopy (AFM) images obtained from polymer films. The goal of the workflow is to identify the spatial location of the two types of polymer domains with little to no manual intervention (Task 1) and calculate the domain size distributions which in turn can help qualify the phase separated state of the material as macrophase or microphase ordered/disordered domains (Task 2). We briefly review existing approaches used in other fields - computer vision and signal processing - that can be applicable for the above tasks that happen frequently in the field of polymer science and engineering. We then test these approaches from computer vision and signal processing on the AFM image dataset to identify the strengths and limitations of each of these approaches for our first task. For our first domain segmentation task, we found that the workflow using discrete Fourier transform (DFT) or discrete cosine transform (DCT) with variance statistics as the feature works the best. The popular ResNet50 deep learning approach from computer vision field exhibited relatively poorer performance in the domain segmentation task for our AFM images as compared to the DFT and DCT based workflows. For the second task, for each of 144 input AFM images, we then used an existing porespy python package to calculate the domain size distribution from the output of that image from DFT-based workflow. The information and open-source codes we share in this paper can serve as a guide for researchers in the polymer and soft materials fields who need ML modeling and workflows for automated analyses of AFM images from polymer samples that may have crystalline/amorphous domains, sharp/rough interfaces between domains, or micro or macro- phase separated domains. © 2024, CC BY.

关键词： Unsupervised learning

来源：评论

学校读者我要写书评

暂无评论

Kernel-based parameter estimation of dynamical systems with unknown observation functions

arXiv

引用

arXiv 2020年

作者： Lindenbaum, Ofir Sagiv, Amir Mishne, Gal Talmon, Ronen Program in Applied Mathematics Yale University 51 Prospect Street New HavenCT06511 United States Department of Applied Physics and Applied Mathematics Columbia University 500 West 120th Street New YorkNY10027 United States Halicioglu Data Science Institute UC San Diego 9500 Gilman Drive MS0555 United States SDSC 215E San DiegoCA92093-0555 United States Faculty of Electrical Engineering Technion - Israel Institute of Technology Haifa32000 Israel

A low-dimensional dynamical system is observed in an experiment as a high-dimensional signal;for example, a video of a chaotic pendulums system. Assuming that we know the dynamical model up to some unknown parameters, can we estimate the underlying system's parameters by measuring its time-evolution only once? The key information for performing this estimation lies in the temporal inter-dependencies between the signal and the model. We propose a kernel-based score to compare these dependencies. Our score generalizes a maximum likelihood estimator for a linear model to a general nonlinear setting in an unknown feature space. We estimate the system's underlying parameters by maximizing the proposed score. We demonstrate the accuracy and efficiency of the method using two chaotic dynamical systems - the double pendulum and the Lorenz'63 model. © 2020, CC BY.

关键词： Maximum likelihood estimation

来源：评论

学校读者我要写书评

暂无评论

ARCTIC TRAFFICABILITY program - A REVIEW

引用

NAVAL ENGINEERS JOURNAL 1984年第3期96卷 169-175页

作者： VOELKER, R GLEN, IF SEIBOLD, F BAYLY, I Richard Voelker:is Vice President of ARCTEC Incorporated a firm specializing in cold regions technology. He has been responsible for the management of thePolarClass Traffic-ability Program since its inception and annually participates in the field data collection in the Arctic. His prior experience includes positions with the U.S. Coast Guard in the icebreaker design project the Military Sealift Command and at Newport News Shipbuilding. He is a graduate of N. Y.S. Maritime College and has a MS degree from the University of Michigan. I.F. Glen:received his professional degrees in naval architecture from the Royal Naval Engineering College Manadon Plymouth and RN College Greenwich London entering the Royal Corps of Naval Constructors in 1967. After serving as a Constructor Lieutenant in the Royal Navy's Far East Fleet for a short period he joined the Polaris submarine project team in Bath England in 1968. In 1971 he was seconded to the Canadian Department of National Defense in Ottawa as a Constructor Lieutenant Commander under NATO exchange arrangements where he had responsibilities initially for conventional submarines and latterly for computer aided conceptual design. He ventured to Bath England in 1974 and joined Forward Design Group. In 1975 he took a position as a civilian engineer in the Canadian Defense Department and was Head of Hull Systems Engineering from 1977 to 1979. He joined ARCTEC CANADA LIMITED in 1980 and in addition to managing ice model testing projects and full scale trials has specialized in structural response of ships to ice impact. He headed ARCTEC's Kanata Laboratory from 1981 to 1983 when he was promoted to president. Frederick Seibold:is a research program manager with the Maritime Administration's Office of Advanced Ship Development and Technology. He is responsible for the marine science program which includes research in the areas of ship powering structures and propeller performance and Arctic technology. Mr. Seibold has been employed by Mar Ad since 1961 having hel

This paper describes a multiyear program to make an operational assessment on the feasibility of a year-round Arctic marine transportation system to serve Alaska. Specifically, the three objectives were to: collect meteorological and ice data along potential marine routes; instrument the hull and propulsion machinery to improve design critera for ice-worthy ships; and demonstrate that ships can operate in midwinter Alaskan Arctic ice conditions. The U.S. Coast Guard's Polar class icebreakers were used to make the operational assessment by annually extending the route northward and by operating throughout the winter season. This paper reviews some of the operational and technical achievements to date, as well as plans for future Arctic deployments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A multi-frequency study of sub-parsec jets with the Event Horizon Telescope

arXiv

引用

arXiv 2025年

作者： Röder, Jan Wielgus, Maciek Lobanov, Andrei P. Krichbaum, Thomas P. Nair, Dhanya G. Lee, Sang-Sung Ros, Eduardo Fish, Vincent L. Blackburn, Lindy Chan, Chi-Kwan Issaoun, Sara Janssen, Michael Johnson, Michael D. Doeleman, Sheperd S. Bower, Geoffrey C. Crew, Geoffrey B. Tilanus, Remo P.J. Savolainen, Tuomas Impellizzeri, C.M. Violette Alberdi, Antxon Baczko, Anne-Kathrin Gómez, José L. Lu, Ru-Sen Paraschos, Georgios F. Traianou, Efthalia Goddi, Ciriaco Kim, Daewon Lisakov, Mikhail Kovalev, Yuri Y. Voitsik, Petr A. Sokolovsky, Kirill V. Akiyama, Kazunori Albentosa-Ruíz, Ezequiel Alef, Walter Algaba, Juan Carlos Anantua, Richard Asada, Keiichi Azulay, Rebecca Bach, Uwe Ball, David Baloković, Mislav Bandyopadhyay, Bidisha Barrett, John Bauböck, Michi Benson, Bradford A. Bintley, Dan Blundell, Raymond Bouman, Katherine L. Bremer, Michael Brinkerink, Christiaan D. Brissenden, Roger Britzen, Silke Broderick, Avery E. Broguiere, Dominique Bronzwaer, Thomas Bustamante, Sandra Byun, Do-Young Carlstrom, John E. Ceccobello, Chiara Chael, Andrew Chang, Dominic O. Chatterjee, Koushik Chatterjee, Shami Chen, Ming-Tang Chen, Yongjun Cheng, Xiaopeng Cho, Ilje Christian, Pierre Conroy, Nicholas S. Conway, John E. Cordes, James M. Crawford, Thomas M. Cruz-Osorio, Alejandro Cui, Yuzhu Curd, Brandon Dahale, Rohan Davelaar, Jordy De Laurentis, Mariafelicia Deane, Roger Dempsey, Jessica Desvignes, Gregory Dexter, Jason Dhruv, Vedant Dihingia, Indu K. Dougall, Sean Taylor Dzib, Sergio A. Eatough, Ralph P. Emami, Razieh Falcke, Heino Farah, Joseph Fomalont, Edward H. Ford, Alyson Foschi, Marianna Fraga-Encinas, Raquel Freeman, William T. Friberg, Per Fromm, Christian M. Fuentes, Antonio Galison, Peter Gammie, Charles F. García, Roberto Gentaz, Olivier Georgiev, Boris Gold, Roman Gómez-Ruiz, Arturo I. Gu, Minfeng Gurwell, Mark Hada, Kazuhiro Haggard, Daryl Haworth, Kari Hecht, Michael H. Hesper, Ronald Heumann, Dirk Ho, Luis C. Ho, Paul Honma, Mareki Huang, Chih-Wei L. Huang, Lei Hughes, David H. Ikeda, Shiro Inoue, Makoto James, David J. Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n GranadaE-18008 Spain Astronomy Department Universidad de Concepción Casilla 160-C Concepción Chile Korea Astronomy and Space Science Institute Daedeok-daero 776 Yuseong-gu Daejeon34055 Korea Republic of Massachusetts Institute of Technology Haystack Observatory 99 Millstone Road WestfordMA01886 United States Black Hole Initiative Harvard University 20 Garden Street CambridgeMA02138 United States Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States NASA Hubble Fellowship Program United States Radboud University P.O. Box 9010 Nijmegen6500 GL Netherlands Institute of Astronomy and Astrophysics Academia Sinica 645 N. A’ohoku Place HiloHI96720 United States Department of Physics and Astronomy University of Hawaii at Manoa 2505 Correa Road HonoluluHI96822 United States Leiden Observatory Leiden University Postbus 2300 Leiden9513 RA Netherlands Postbus 93138 Den Haag2509 AC Netherlands Aalto University Department of Electronics and Nanoengineering PL 15500 AaltoFI-00076 Finland Aalto University Metsähovi Radio Observatory Metsähovintie 114 KylmäläFI-02540 Finland National Radio Astronomy Observatory 520 Edgemont Road CharlottesvilleVA22903 United States Department of Space Earth and Environment Chalmers University of Technology Onsala Space Observatory OnsalaSE-43992 Sweden Shanghai Astronomical Observatory Chinese Academy of Sciences 80 Nandan Road Shanghai200030 China Key Laboratory of Radio Astronomy Chinese Academy of Scien

Context. The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed, including the main science targets, Sgr A* and M 87 and various calibrators. Sixteen sources were AGN. Aims. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-Königl (BK) jet model. In particular, we aimed to study the signatures of jet acceleration and magnetic energy conversion. Methods. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components (1749+096, 1055+018, BL Lac, J0132–1654, J0006–0623, CTA 102, 3C 454.3) and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Combining these data into a multi-frequency EHT+ data set, we studied the dependences of the VLBI core component flux density, size, and brightness temperature on the frequency measured in the AGN host frame (and hence on the distance from the central black hole), characterizing them with power law fits. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Results. Our observations spanning event horizon- to parsec scales indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Only some of the discrepancies may be alleviated by tweaking the model parameters or the jet collimation profile. Either bulk acceleration of the jet material, energ

关键词： Luminance

来源：评论

学校读者我要写书评

暂无评论

COMPUTER-SYSTEM ARCHITECTURE CONCEPTS FOR FUTURE COMBAT SYSTEms

引用

NAVAL ENGINEERS JOURNAL 1990年第3期102卷 43-62页

作者： ZITZMAN, LH FALATKO, SM PAPACH, JL Dr. Lewis H. Zitzman:is the group supervisor of the Advanced Systems Design Group Fleet Systems Department The Johns Hopkins University Applied Physics Laboratory (JHU/APL). He has been employed at JHU/APL since 1972 performing applied research in computer science and in investigating and applying advanced computer technologies to Navy shipboard systems. He is currently chairman of Aegis Computer Architecture Data Bus and Fiber Optics Working Group from which many concepts for this paper were generated. Dr. Zitzman received his B.S. degree in physics from Brigham Young University in 1963 and his M.S. and Ph.D. degrees in physics from the University of Illinois in 1967 and 1972 respectively. Stephen M. Falatko:was a senior engineering analyst in the Combat Systems Engineering Department Comptek Research Incorporated for the majority of this effort. He is currently employed at ManTech Services Corporation. During his eight-year career first at The Johns Hopkins University Applied Physics Laboratory and currently with ManTech Mr. Falatko's work has centered around the development of requirements and specifications for future Navy systems and the application of advanced technology to Navy command and control systems. He is a member of both the Computer Architecture Fiber Optics and Data Bus Working Group and the Aegis Fiber Optics Working Group. Mr. Falatko received his B.S. degree in aerospace engineering with high distinction from the University of Virginia in 1982 and his M.S. degree in applied physics from The Johns Hopkins University in 1985. Mr. Falatko is a member of Tau Beta Pi Sigma Gamma Tau the American Society of Naval Engineers and the U.S. Naval Institute. Janet L. Papach:is a section leader and senior engineering analyst in the Combat Systems Engineering Department Comptek Research Incorporated. She has ten years' experience as an analyst supporting NavSea Spa War and the U.S. Department of State. She currently participates in working group efforts under Aegis Combat System Doctrin

This paper sets forth computer systems architecture concepts for the combat system of the 2010-2030 timeframe that satisfy the needs of the next generation of surface combatants. It builds upon the current Aegis computer systems architecture, expanding that architecture while preserving, and adhering to, the Aegis fundamental principle of thorough systems engineering, dedicated to maintaining a well integrated, highly reliable, and easily operable combat system. The implementation of these proposed computer systems concepts in a coherent architecture would support the future battle force capable combat system and allow the expansion necessary to accommodate evolutionary changes in both the threat environment and the technology then available to effectively counter that threat. Changes to the current Aegis computer architecture must be carefully and effectively managed such that the fleet will retain its combat readiness capability at all times. This paper describes a possible transition approach for evolving the current Aegis computer architecture to a general architecture for the future. The proposed computer systems architecture concepts encompass the use of combinations of physically distributed, microprocessorbased computers, collocated with the equipment they support or embedded within the equipment itself. They draw heavily on widely used and available industry standards, including instruction set architectures (ISAs), backplane busses, microprocessors, computer programming languages and development environments, and local area networks (LANs). In this proposal, LANs, based on fiber optics, will provide the interconnection to support system expandability, redundancy, and higher data throughput rates. A system of cross connected LANs will support a high level of combat system integration, spanning the major warfare areas, and will facilitate the coordination and development of a coherent multiwarfare tactical picture supporting the future combatant command staf

关键词： Computer Architecture

来源：评论

学校读者我要写书评

暂无评论

Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele

引用

Nature communications 2025年第1期16卷 3470-3470页

作者： Zhang, Xinruo Brody, Jennifer A. Graff, Mariaelisa Highland, Heather M. Chami, Nathalie Xu, Hanfei Wang, Zhe Ferrier, Kendra R. Chittoor, Geetha Josyula, Navya Shilpa Meyer, Mariah Gupta, Shreyash Li, Xihao Li, Zilin Allison, Matthew A. Becker, Diane M. Bielak, Lawrence F. Bis, Joshua C. Boorgula, Meher Preethi Bowden, Donald W. Broome, Jai G. Buth, Erin J. Carlson, Christopher S. Chang, Kyong-Mi Chavan, Sameer Chiu, Yen-Feng Chuang, Lee-Ming Conomos, Matthew P. DeMeo, Dawn L. Du, Mengmeng Duggirala, Ravindranath Eng, Celeste Fohner, Alison E. Freedman, Barry I. Garrett, Melanie E. Guo, Xiuqing Haiman, Chris Heavner, Benjamin D. Hidalgo, Bertha Hixson, James E. Ho, Yuk-Lam Hobbs, Brian D. Hu, Donglei Hui, Qin Hwu, Chii-Min Jackson, Rebecca D. Jain, Deepti Kalyani, Rita R. Kardia, Sharon L R Kelly, Tanika N. Lange, Ethan M. LeNoir, Michael Li, Changwei Le Marchand, Loic McDonald, Merry-Lynn N McHugh, Caitlin P. Morrison, Alanna C. Naseri, Take Palmer, Nicholette D. Pankow, James S. Perry, James A. Peters, Ulrike Preuss, Michael H. Rao, D.C. Regan, Elizabeth A. Reupena, Sefuiva M. Roden, Dan M. Rodriguez-Santana, Jose Sitlani, Colleen M. Smith, Jennifer A. Tiwari, Hemant K. Vasan, Ramachandran S. Wang, Zeyuan Weeks, Daniel E. Wessel, Jennifer Wiggins, Kerri L. Wilkens, Lynne R. Wilson, Peter W F Yanek, Lisa R. Yoneda, Zachary T. Zhao, Wei Zöllner, Sebastian Arnett, Donna K. Ashley-Koch, Allison E. Barnes, Kathleen C. Blangero, John Boerwinkle, Eric Burchard, Esteban G. Carson, April P. Chasman, Daniel I. Ida Chen, Yii-Der Curran, Joanne E. Fornage, Myriam Gordeuk, Victor R. He, Jiang Heckbert, Susan R. Hou, Lifang Irvin, Marguerite R. Kooperberg, Charles Minster, Ryan L. Mitchell, Braxton D. Nouraie, Mehdi Psaty, Bruce M. Raffield, Laura M. Reiner, Alexander P. Rich, Stephen S. Rotter, Jerome I. Benjamin Shoemaker, M. Smith, Nicholas L. Taylor, Kent D. Telen, Marilyn J. Weiss, Scott T. Zhang, Yingze Heard-Costa, Nancy Sun, Yan V. Lin, Xihong Cupples, L Adrienne Lange, Leslie A. Liu, Ching-Ti Loos, Ruth J F North, K Department of Epidemiology Gillings School of Global Public Health University of North Carolina at Chapel Hill Chapel Hill NC United States Cardiovascular Health Research Unit Department of Medicine University of Washington Seattle WA United States The Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA The Mindich Child Health and Development Institute Icahn School of Medicine at Mount Sinai New York NY USA Department of Biostatistics School of Public Health Boston University Boston MA United States Division of Biomedical Informatics and Personalized Medicine University of Colorado School of Medicine Anschutz Medical Campus Aurora CO United States Population Health Sciences Geisinger Danville PA United States Department of Biostatistics Harvard T.H. Chan School of Public Health Boston MA United States Department of Biostatistics Gillings School of Global Public Health University of North Carolina at Chapel Hill Chapel Hill NC United States Department of Genetics School of Medicine University of North Carolina at Chapel Hill Chapel Hill NC United States Biostatistics and Health Data Science Indiana University School of Medicine Indianapolis IN United States School of Mathematics and Statistics and KLAS Northeast Normal University Changchun Jilin China Department of Family Medicine Division of Preventive Medicine University of California San Diego La Jolla CA United States Department of Medicine General Internal Medicine Johns Hopkins University School of Medicine Baltimore MD United States Department of Epidemiology School of Public Health University of Michigan Ann Arbor MI United States Department of Medicine University of Colorado School of Medicine Aurora CO United States Department of Biochemistry Wake Forest School of Medicine Winston-Salem NC United States Department of Biostatistics School of Public Health University of Washington Seattle WA United States Department of

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10-9), including two secondary signals. Notably, we identified and replicated a novel low-frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine. © 2025. The Author(s).

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：