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Worldwide Soundscapes: A Synthesis of Passive Acoustic Monitoring Across Realms

Global Ecology and Biogeography 2025年第5期34卷

作者： Kevin F. A. Darras Rodney A. Rountree Steven L. Van Wilgenburg Anna F. Cord Frederik Pitz Youfang Chen Lijun Dong Agnès Rocquencourt Camille Desjonquères Patrick Mauritz Diaz Tzu-Hao Lin Théophile Turco Louise Emmerson Tom Bradfer-Lawrence Amandine Gasc Sarah Marley Marcus Salton Laura Schillé Paul J. Wensveen Shih-Hung Wu Adriana C. Acero-Murcia Orlando Acevedo-Charry Matyáš Adam Jacopo Aguzzi Irmak Akoglu M. Clara P. Amorim Mina Anders Michel André Alexandre Antonelli Leandro Aparecido Do Nascimento Giulliana Appel Stephanie Archer Christos Astaras Andrey Atemasov Jamieson Atkinson Joël Attia Emanuel Baltag Luc Barbaro Fritjof Basan Carly Batist Julio Ernesto Baumgarten Just T. Bayle Sempere Kristen Bellisario Asaf Ben David Oded Berger-Tal Frédéric Bertucci Matthew G. Betts Iqbal S. Bhalla Thiago Bicudo Marta Bolgan Sara Bombaci Gerard Bota Martin Boullhesen Robert A. Briers Susannah Buchan Michal Budka Katie Burchard Giuseppa Buscaino Alice Calvente Marconi Campos-Cerqueira Maria Isabel Carvalho Gonçalves Maria Ceraulo Maite Cerezo-Araujo Gunnar Cerwén Adams A. Chaskda Maria Chistopolova Christopher W. Clark Kieran D. Cox Benjamin Cretois Chapin Czarnecki Luis P. da Silva Wigna da Silva Laurence H. De Clippele David de la Haye Ana Silvia de Oliveira Tissiani Devin de Zwaan M. Eugenia Degano Jessica Deichmann Joaquin del Rio Christian Devenish Ricardo Díaz-Delgado Pedro Diniz Dorgival Diógenes Oliveira-Júnior Thiago Dorigo Saskia Dröge Marina Duarte Adam Duarte Kerry Dunleavy Robert Dziak Simon Elise Hiroto Enari Haruka S. Enari Florence Erbs Britas Klemens Eriksson Pınar Ertör-Akyazi Nina C. Ferrari Luane Ferreira Abram B. Fleishman Paulo J. Fonseca Bárbara Freitas Nicholas R. Friedman Jérémy S. P. Froidevaux Svetlana Gogoleva Carolina Gonzaga José Miguel González Correa Eben Goodale Benjamin Gottesman Ingo Grass Jack Greenhalgh Jocelyn Gregoire Samuel Haché Jonas Hagge William Halliday Antonia Hammer Tara Hanf-Dressler Sylvain Haupert Samara Haver Becky Heath Daniel Hending Jose Hernandez-Blanco Dennis Higgs EFNO ECODIV INRAE Domaine des Barres Nogent-sur-Vernisson France Sustainable Agricultural Systems & Engineering Lab School of Engineering Westlake University Hangzhou Zhejiang China Chair of Computational Landscape Ecology Faculty of Environmental Sciences Dresden University of Technology Dresden Germany Biology Department University of Victoria Victoria British Columbia Canada The Fish Listener Waguoit Massachusetts USA Terrestrial Unit Prairie Region Canadian Wildlife Service Environment & Climate Change Canada Prairie & Northern Wildlife Research Centre Saskatoon Saskatchewan Canada Agro-ecological Modeling Group Faculty of Agriculture University of Bonn Bonn Germany Marine Mammal and Marine Bioacoustics Laboratory Department of Deep Sea Science Institute of Deep-sea Science and Engineering Chinese Academy of Sciences Sanya Hainan China Institut de Systématique Évolution Biodiversité Muséum National d’Histoire Naturelle Paris France Université Grenoble Alpes Université Savoie Mont Blanc CNRS LECA Grenoble France Climate Change and Biodiversity Hanns R. Neumann Stiftung Indonesia Muaradua Indonesia Biodiversity Research Center Academia Sinica Nankang Taipei Taiwan ENES Bioacoustics Research Laboratory University of Saint-Etienne CRNL CNRS UMR 5292 Inserm UMR_S 1028 Saint-Etienne France Australian Antarctic Division Science Branch Department of Climate Change Energy Environment and Water Channel Highway Kingston Tasmania Australia Biological and Environmental Sciences University of Stirling Stirling Scotland Centre for Conservation Science RSPB Edinburgh UK IMBE Aix Marseille Univ Avignon Univ CNRS IRD Aix-en-Provence France Scotland's Rural College Craibstone Estate Aberdeen UK BIOGECO INRAE University of Bordeaux Cestas France Westman Islands Research Centre University of Iceland Vestmannaeyjar Iceland Qigu Research Center Taiwan Biodiversity Research Institute Nantou County Taiwan Programa de Pós-graduação em Ecologia

Aim The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). Location Worldwide, 12,343 sites, all ecosystem types. Time Period 1991 to present. Major Taxa Studied All soniferous taxa. Methods We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms. Results Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm 2 ) than aquatic sampling (0.3 and 1.8 sites/Mkm 2 in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds. Main Conclusions PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio-temporal replication in freshwater habitats. Overall, this

关键词： ARU automated sound recorder biodiversity conservation biology ecoacoustics IUCN GET realm Passive Acoustic Monitoring phenology soundscape ecology

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Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Muhammad Iqbal Dahlan Abdullah H Hartono Cut Ita Erliana S Sriadhi Nurmawati M Adhi Prasnowo Abdurrozzaq Hasibuan Akbar Iskandar Kundharu Saddhono Abdussakir Hastuti Musa Muhammad Ikhsan Setiawan Youmeni Sagala Rumiris Siahaan Eka Mayastika Sinaga Anggraini Syahputri Feby Milanie Henry Aspan Muammar Khaddafi Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan-Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making System of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods.

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Retraction: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method (J. Phys.: Conf. Ser. 1114 012082)

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Journal of Physics: Conference Series 2018年第1期1114卷

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs

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Cell systems 2023年第4期14卷 302-311.e4页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Yu-Te Lin Cristhian Roman-Vicharra Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Department of Nutrition and the Program in Integrative Nutrition & Complex Diseases Texas A&M University College Station TX 77843 USA. Electronic address: r-chapkin@tamu.edu. Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA. Electronic address: jcai@tamu.edu.

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

关键词： cell-cell interaction cellular communication gene regression network machine learning manifold alignment neural networks scRNA-seq single-cell RNA sequencing

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Correction to: Comparison of Virological Efficacy of DTG/ABC/3TG and B/F/TAF Regimens and Discontinuation Patterns in Persons Living with Advanced HIV in the Era of Rapid ART: A Retrospective Multicenter Cohort Study

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Infectious diseases and therapy 2023年第3期12卷 863-869页

作者： Chun-Yuan Lee Chen-Hsiang Lee Hung-Jen Tang Hung-Chin Tsai Chen-Hsun Yang Yi-Pei Lin Sheng-Fan Wang Po-Liang Lu Division of Infectious Diseases Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University No. 100 Ziyou 1st Rd. Sanmin District Kaohsiung City 807 Taiwan. Graduate Institute of Medicine College of Medicine Kaohsiung Medical University No. 100 Ziyou 1st Rd. Sanmin District Kaohsiung City Taiwan. School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan. M.Sc. Program in Tropical Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan. Division of Infectious Diseases Department of Internal Medicine Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine No.123 DAPI Rd. Niaosong District Kaohsiung City Taiwan. Department of Medicine Chi Mei Medical Center No.901 Zhonghua Rd. Yongkang District Tainan City Taiwan. School of Medicine National Yang-Ming University Taipei Taiwan. Department of Internal Medicine Kaohsiung Veterans General Hospital No.386 Dazhong 1st Rd. Zuoying District Kaohsiung City Taiwan. Center for Tropical Medicine and Infectious Disease Kaohsiung Medical University Kaohsiung Taiwan. Department of Medical Laboratory Science and Biotechnology Kaohsiung Medical University Kaohsiung Taiwan. Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung Medical University No. 100 Ziyou 1st Rd. Sanmin District Kaohsiung City Taiwan. Division of Infectious Diseases Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University No. 100 Ziyou 1st Rd. Sanmin District Kaohsiung City 807 Taiwan. d830166@***. School of Post-Baccalaureate Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan. d830166@***. Center for Liquid Biopsy and Cohort Research Kaohsiung Medical University Kaohsiung Taiwan. d830166@***.

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CENTML CONTROL SYSTEM TRAINING THROUGH STA TIC AND DYNAMIC SIMULATION

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Naval Engineers Journal 1980年第2期92卷 196-206页

作者： HALL, EDWIN E. MOSS, DONALD G. NORRIS, CLIFFORD S. PETERSON, HAROLD D. Mr. Edwin E. Hall received his Bachelor's degree in Electronics from Oklahoma City University. He also is a certified College-Level Instructor in the state of Florida and has done graduate work in Computer Science at the University of Florida. As the Technical Publications and Training Manager Simulation and Control Systems Department. General Electric Company Daytona Beach Fla. he currently is responsible for the costing. planning performance scheduling and timely completion of the Department's Technical Manuals and Technical Training Programs. These Training and Manual contracts cover Ship Systems Programs. Simulation Programs. and Communications Programs for the Armed Services and commercial customers. Mr. Hall has over twenty-years experience as a Technical Writer and Instructor and for the past seventeen years has been at the General Electric Company's Daytona Beach Facility. His experience ranges from teaching Basic Electronics and Radar Circuitry as a civilian instructor for the U.S. Army to writing Manuals Proposals Reports Specifications and Brochures for General Electric's product lines. Mr. Donald G. MOSS is a graduate of Kansas State University from which he received both his B.S. degree in Business Administration and his M.S. degree in Electrical Engineering. He is presently a Senior Systems Engineer for Control Systems in the Simulation and Control Systems Department at the General Electric Company's Daytona Beach Facility. He has been employed by General Electric for 23 years — the first seven as an Engineer and Program Manager on the Fire Control Systems for the Fleet Ballistics Missile Program the next six managing the design of control and checkout equipment on the APOLLO Program and the last ten years working on control equipment for the machinery plants of new Navy ships. Over the span of years at General Electric he has worked on propulsion control for the DD-963 propulsion electric plant and auxiliary control for the FFG-7: propulsion boiler burner electric auxiliary and car

Dynamic Simulation is defined as the hardware and software required to present to the student operator visual and audible cues and responses that are the same as those encountered when operating the Control Consoles aborad ship. This type of simulation is considered essential to the development of operator skills for critical tasks. Less critical tasks can be practiced using static simulation devices. This paper discusses the utilization of these types of training devices to train Navy crews. An overview of the Machinery Control Systems of the FFG 7 and AO 177 Class ships is discussed to provide an understanding of state‐of‐the‐art equipment development. The training programs for these two ship Classes are then reviewed to show how simulation devices are currently used by the Training Community, and this is followed by a brief discussion of the additional benefits that also are derived. © 1980 by the American Society of Naval Engineers, Inc.

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Genomic Surveillance of SARS-CoV-2 in Taiwan: A Perspective on Evolutionary Data Interpretation and Sequencing Issues

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Biomedical journal 2024年 100820页

作者： Yu-Nong Gong Nai-Yu Kuo Ting-Syuan Yeh Shin-Ru Shih Guang-Wu Chen Research Center for Emerging Viral Infections College of Medicine Chang Gung University Taoyuan Taiwan International Master Degree Program for Molecular Medicine in Emerging Viral Infections College of Medicine Chang Gung University Taoyuan Taiwan Department of Laboratory Medicine Linkou Chang Gung Memorial Hospital Taoyuan Taiwan. Medical Education Department Linkou Chang Gung Memorial Hospital Taoyuan Taiwan. National Institute of Infectious Diseases and Vaccinology National Health Research Institutes Taiwan. Department of Laboratory Medicine Linkou Chang Gung Memorial Hospital Taoyuan Taiwan Department of Medical Biotechnology and Laboratory Science College of Medicine Chang Gung University Taoyuan Taiwan Research Center for Chinese Herbal Medicine Research Center for Food and Cosmetic Safety and Graduate Institute of Health Industry Technology College of Human Ecology Chang Gung University of Science and Technology Taoyuan Taiwan. Department of Computer Science and Information Engineering College of Engineering Chang Gung University Taoyuan Taiwan. Electronic address: gwchen@mail.cgu.edu.tw.

This review presents a comprehensive perspective on the genomic surveillance of SARS-CoV-2 in Taiwan, with a focus on next-generation sequencing and phylogenetic interpretation. This article aimed to explore how Taiwan has utilized genomic sequencing technologies and surveillance to monitor and mitigate the spread of COVID-19. We examined databases and sources of genomic sequences and highlighted the role of data science methodologies in the explanation and analyses of evolutionary data. This review addressed the challenges and limitations inherent in genomic surveillance, such as concerns regarding data quality and the necessity for interdisciplinary expertise for accurate data interpretation. Special attention was given to the unique challenges faced by Taiwan, including its high population density and major transit destination for international travelers. We underscored the far-reaching implications of genomic surveillance data for public health policy, particularly in influencing decisions regarding travel restrictions, vaccine administration, and public health decision-making. Studies were examined to demonstrate the effectiveness of using genomic data to implement public health measures. Future research should prioritize the integration of methodologies and technologies in evolutionary data science, particularly focusing on phylodynamic analytics. This integration is crucial to enhance the precision and applicability of genomic data. Overall, we have provided an overview of the significance of genomic surveillance in tracking SARS-CoV-2 variants globally and the pivotal role of data science methodologies in interpreting these data for effective public health interventions.

关键词： SARS-CoV-2 data science genomic surveillance next-generation sequencing phylodynamics

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Diallyl trisulfide (DATS) protects cardiac cells against advanced glycation end-product-induced apoptosis by enhancing FoxO3A-dependent upregulation of miRNA-210

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The Journal of nutritional biochemistry 2024年 125卷 109567页

作者： Kuan-Ho Lin Shang-Chuan Ng Shang-Yeh Lu Yueh-Min Lin Shu-Hui Lin Tzu-Cheng Su Chih-Yang Huang Wei-Wen Kuo College of Medicine China Medical University Taichung Taiwan ROC Department of Emergency Medicine China Medical University Hospital Taichung Taiwan ROC. Department of Biological Science and Technology College of Life Sciences China Medical University Taichung Taiwan ROC. Division of Cardiovascular Medicine Department of Internal Medicine China Medical University Hospital Taichung Taiwan ROC. Department of Surgical Pathology Changhua Christian Hospital Changhua Taiwan ROC School of Medicine Chung Shan Medical University Taichung Taiwan ROC Department of Medical Laboratory Science and Biotechnology Central Taiwan University of Science and Technology Taichung Taiwan ROC. Department of Medical Laboratory Science and Biotechnology Central Taiwan University of Science and Technology Taichung Taiwan ROC Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan ROC. School of Medicine Chung Shan Medical University Taichung Taiwan ROC. Cardiovascular and Mitochondrial Related Disease Research Center Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan ROC Center of General Education Buddhist Tzu Chi Medical Foundation Tzu Chi University of Science and Technology Hualien Taiwan ROC Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan ROC Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan ROC Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan ROC. Department of Biological Science and Technology College of Life Sciences China Medical University Taichung Taiwan ROC Program for Biotechnology Industry China Medical University Taichung Taiwan ROC. Electronic address: wwkuo@mail.cmu.edu.tw.

Diabetic cardiomyopathy is a common complication of diabetes, resulting in cardiac hypertrophy and heart failure associated with excessive reactive oxygen species and mitochondria-mediated apoptosis generation. Mitogen-activated protein kinase-c-Jun N-terminal kinase (MAPK-JNK), regulated by microRNA (miR)-210, affects mitochondrial function and is activated by advanced glycation end-products (AGE) in cardiac cells. Diallyl trisulfide (DATS), an antioxidant in garlic oil, inhibits stress-induced cardiac apoptosis. This study examined whether DATS enhances miR-210 expression to attenuate cardiac apoptosis. We investigated the DATS-mediated attenuation mechanism of AGE-enhanced cardiac apoptosis by modulating miR-210 and its upstream transcriptional regulator, FoxO3a. We found FoxO3a binding sites in the miR-210 promoter region. Our results indicated that DATS treatment inhibited AGE-induced JNK activation, phosphoprotein c-Jun nuclear transactivation, and cardiac apoptosis and reversed the AGE-induced reduction in cardiac miR-210 levels. The luciferase activity after DATS treatment was significantly lower than that of the control and was reversed following AGE treatment. We also showed that FoxO3a, upregulated by DATS treatment, may bind to the miR-210 promoter to enhance its expression and downregulates JNK expression to attenuate AGE-induced cardiac apoptosis. Oral administration of DATS enhanced FoxO3a expression in the heart and reduced diabetes-induced heart apoptosis. Our findings indicate that DATS mediates AGE-induced cardiac cell apoptosis attenuation by promoting FoxO3a nuclear transactivation to enhance miR-210 expression and regulate JNK activation. Our results suggest that DATS can be used as a cardioprotective agent, and miR-210 is a critical regulator in inhibiting diabetic cardiomyopathy.

关键词： Advanced glycation end products (AGEs) Diallyl trisulfide (DATS) Forkhead box O3a (FoxO3a) c-Jun N-terminal kinase (JNK) microRNA-210

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A Machine Learning-Based Approach for Classification of Alzheimer’s Disease and its Risk Prediction

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Alzheimer's & Dementia 2022年第S11期18卷

作者： Payam Hosseinzadeh Kasani Jung-Kyeom Kim Peyman Hosseinzadeh Kassani Yeshin Kim Jeong-Ah Kim Chihyun Park Cheol-Heui Yun Seong Hye Choi Sang-Ah Lee Seo-Young Lee Jae-Won Jang Department of Neurology Kangwon National University Hospital Chuncheon Korea Republic of (South) Interdisciplinary Graduate Program in Medical Bigdata Convergence Kangwon National University Chuncheon Korea Republic of (South) Department of Neurology and Neurological Sciences Stanford University Stanford CA USA College of Medicine Kangwon National University Chuncheon Korea Republic of (South) Department of Ophthalmology Kangwon National University Hospital Chuncheon Korea Republic of (South) Department of Computer Science and Engineering Kangwon National University Chuncheon Korea Republic of (South) Department of Agricultural Biotechnology Seoul National University Seoul Korea Republic of (South) Research Institute of Agriculture and Life Sciences Seoul National University Seoul Korea Republic of (South) Department of Neurology Inha University School of Medicine Incheon Korea Republic of (South) Department of Preventive Medicine Kangwon National University School of Medicine Chuncheon Korea Republic of (South)

Background Dementia, a clinical syndrome with progressive neurodegenerative disease, is one of the inevitable aging consequences. Alzheimer’s disease (AD) is the most common cause of dementia. Accurate detection and classification of Alzheimer’s disease alongside its conversion from Mild Cognitive Impairment (MCI) to AD at an early stage is of significant clinical importance. However, a reliable diagnosis with a multi-label classification approach remains a challenging task. This study aimed to measure the effectiveness of machine learning algorithm integrated with feature importance techniques to constitutes a multi-label classification of AD prediction for clinical practice. Method The machine learning algorithms are validated using a nationwide cohort dataset, the Korean Brain Aging Study for the early diagnosis and prediction of AD (KBASE) to identify the most important risk factors, where a database is classified into three classes namely, normal cognition (NC, n = 91), mild cognitive impairment (MCI, n = 61), and Alzheimer’s disease (AD, n = 49). Applying eight state-of-the-art supervised machine learning algorithms namely Support Vector Machine, Naive Bayes, XGBoost, Decision Tree, Logistic Regression, Random Forest, Bagging, and AdaBoost. A stratified 10-fold cross-validation was used for every train/test split and several performance measures, including accuracy, precision, recall and f1-score were used to compare the classifier performances. Result Based on the performance evaluation, the XGBoost classifier significantly outperformed all other models and achieved 82.55% accuracy followed by the Bagging classifier (81%). According to the XGBoost model, calculating risk factors to predict performance, the Consortium to Establish a Registry for AD (CERAD) subsets is among the highest ranked feature. It was intriguing that the parameters including job, job levels and retirement achieved a minimal, if any, impact in the final performance. Conclusion Collectivel

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Author Correction: Cortical astrocytes modulate dominance behavior in male mice by regulating synaptic excitatory and inhibitory balance

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Nature neuroscience 2023年第12期26卷 2250页

作者： Kyungchul Noh Woo-Hyun Cho Byung Hun Lee Dong Wook Kim Yoo Sung Kim Keebum Park Minkyu Hwang Ellane Barcelon Yoon Kyung Cho C Justin Lee Bo-Eun Yoon Se-Young Choi Hye Yoon Park Sang Beom Jun Sung Joong Lee Department of Physiology and Neuroscience Dental Research Institute Seoul National University School of Dentistry Seoul Republic of Korea. Department of Physics and Astronomy Seoul National University Seoul Republic of Korea. Department of Molecular Biology Dankook University Cheonan Republic of Korea. Department of Electronic and Electrical Engineering Ewha Womans University Seoul Republic of Korea. Center for Cognition and Sociality Institute for Basic Science (IBS) Daejeon Republic of Korea. Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN USA. Graduate Program in Smart Factory Ewha Womans University Seoul Republic of Korea. Department of Brain & Cognitive Sciences Ewha Womans University Seoul Republic of Korea. Department of Physiology and Neuroscience Dental Research Institute Seoul National University School of Dentistry Seoul Republic of Korea. sjlee87@snu.ac.kr.

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