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临床传统医学和药理学（英文） 2024年第2期5卷 13-22页

作者： Temitayo Olabisi Ajibade Esther Oluwaseyi Oliyide Oluwaseun Olanrewaju Esan Moses Olusola Adetona Omolola Victoria Awoyomi Taiwo Olaide Oyagbemi Adewumi Victoria Adeogun Ademola Adetokunbo Oyagbemi Temidayo Olutayo Omobowale Kehinde Olugboyega Soetan Sanah Malomile Nkadimeng Lyndy Joy McGaw Prudence Ngalula Kayoka-Kabongo Momoh Audu Yakubu Evaristus Nwulia Oluwafemi Omoniyi Oguntibeju Department of Veterinary Physiology and Biochemistry Faculty of Veterinary MedicineUniversity of IbadanIbadanOyo State 200001Nigeria Department of Veterinary Medicine Faculty of Veterinary MedicineUniversity of Ibadan IbadanOyo State 200001Nigeria Department of Anatomy Faculty of Basic Medical SciencesCollege of MedicineUniversity of IbadanIbadanOyo State 200001Nigeria Federal College of Animal Health and Production Technology Moor PlantationIbadanOyo State 200001Nigeria Department of Life and Consumer Sciences Collage of Agriculture and Environmental SciencesUniversity of South Africa Florida CampusUniversity of South AfricaUnisa 0003South Africa Department of Paraclinical Science Faculty of Veterinary ScienceUniversity of PretoriaOnderstepoort0110 0028South Africa Department of Environmental & Interdisciplinary Sciences College of ScienceEngineering & TechnologyCOPHSTexas Southern UniversityHoustonTX 77587USA Howard University College of MedicineDepartment of Psychiatry and Behavioral SciencesHoward University Hospital2041 Georgia AvenueWashingtonDC 20060USA Department of Biomedical Sciences Faculty of Health and Wellness SciencesCape Peninsula University of TechnologyBellvill 7535South Africa

背景:槲皮素是一种生物类黄酮苷,在柑橘类水果中含量丰富,自古就作为天然草药治疗剂,应用于传统医学中.槲皮素有很强的抗氧化活性,可缓解哺乳动物系统中,由氧化应激介导的心血管和肾功能损伤.目的:该文探讨了槲皮素对氟虫腈诱导的心脏-... 详细信息

背景:槲皮素是一种生物类黄酮苷,在柑橘类水果中含量丰富,自古就作为天然草药治疗剂,应用于传统医学中.槲皮素有很强的抗氧化活性,可缓解哺乳动物系统中,由氧化应激介导的心血管和肾功能损伤.目的:该文探讨了槲皮素对氟虫腈诱导的心脏-肾脏功能障碍的可能调节机制.方法:将24只体重为140±3.0 g的Wistar大鼠分为四组,包括正常对照组(生理盐水)、10 mg/kg氟虫腈(FIP)、FIP+100 mg/kg槲皮素和100 mg/kg槲皮素.槲皮素和氟虫腈的给药通过口服灌胃连续进行28天.随后进行尿液分析、血压监测、生化检测、组织学和免疫组织化学评估.结果:槲皮素显著降低血压参数和氧化应激标志物(P＜0.001),但系统抗氧化物水平(P＜0.001)显著提高.同样,槲皮素能够预防氟虫腈诱导的心脏和肾脏组织中的充血和细胞浸润等组织病理学病变.此外,槲皮素减轻了心脏组织中肌钙蛋白1和基质金属蛋白酶-2的免疫组织化学表达,但与氟虫腈组相比提高了血管紧张素转换酶2的表达.结论:研究结果表明,槲皮素通过抑制与氧化和炎症相关的过程,有效降低氟虫腈诱导的毒性.

关键词：心肾功能障碍生物标志物氟虫腈毒性槲皮素免疫组化

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Sucrose-based cryoprotective storage of extracellular vesicles

Extracellular vesicle

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Extracellular vesicle 2022年 1卷 100016页

作者： Sierra A Walker Irina Davidovich Yubo Yang Andrew Lai Jenifer Pendiuk Goncalves Vatsal Deliwala Sara Busatto Shane Shapiro Na'ama Koifman Carlos Salomon Yeshayahu Talmon Joy Wolfram Department of Biochemistry and Molecular Biology Department of Physiology and Biomedical Engineering Department of Transplantation Mayo Clinic Jacksonville FL 32224 USA. Department of Chemical Engineering and the Russell Berrie Nanotechnology Institute (RBNI) Technion-Israel Institute of Technology Haifa 3200003 Israel. Exosome Biology Laboratory Centre for Clinical Diagnostics University of Queensland Centre for Clinical Research Royal Brisbane and Women's Hospital Faculty of Medicine The University of Queensland Brisbane QLD 4006 Australia. Australian Institute for Bioengineering and Nanotechnology The University of Queensland Brisbane QLD 4072 Australia. School of Chemical Engineering The University of Queensland Brisbane QLD Australia. Vascular Biology Program Boston Children's Hospital Boston MA 02115 United States. Department of Surgery Harvard Medical School Boston MA 02115 United States. Department of Orthopedic Surgery Mayo Clinic Jacksonville FL 32224 USA. Center of Microscopy and Microanalysis The University of Queensland Brisbane QLD 4072 Australia. Departamento de Investigación Postgrado y Educación Continua (DIPEC) Facultad de Ciencias de la Salud Universidad del Alba Santiago 8320000 Chile.

Advancements in extracellular vesicle (EV) studies necessitate the development of optimized storage conditions to ensure preservation of physical and biochemical characteristics. In this study, the most common buffer for EV storage (phosphate-buffered saline/PBS) was compared to a cryoprotective 5% sucrose solution. The size distribution and concentration of EVs from two different sources changed to a greater extent after -80 °C storage in PBS compared to the sucrose solution. Additionally, molecular surface protrusions and transmembrane proteins were more prevalent in EVs stored in the sucrose solution compared to those stored in PBS. This study demonstrates, for the first time, that distinct ring-like molecular complexes and cristae-like folded membranous structures are visible upon EV degradation. Taken together, the size, concentration, molecular surface extensions, and transmembrane proteins of EVs varied substantially based on the buffer used for -80 °C storage, suggesting that biocompatible cryoprotectants, such as sucrose, should be considered for EV studies.

关键词： Cryoprotection exosome extracellular vesicle storage sucrose

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Molecular identification and phylogenetic reconstruction of two fiddler crabs (Uca forcipata and Uca triangularis)

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IOP Conference Series. Earth and Environmental Science 2019年第1期236卷 012036-012036页

作者： Andriyono, S Pramono, H Kim, H W Interdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan 48513 Republic of Korea Department of Marine Fisheries and Marine Faculty C Campus Jl. Mulyorejo Surabaya 60115. Universitas Airlangga Surabaya East Java Indonesia Department of Marine Fisheries and Marine Faculty C Campus Jl. Mulyorejo Surabaya 60115. Universitas Airlangga Surabaya East Java Indonesia Interdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan 48513 Republic of Korea Department of Marine Biology Pukyong National University Busan 48513 Republic of Korea

Fiddler crabs are one of the types of fauna that inhabit the mangrove ecosystem. They have an essential role in nutrient improvements in the mangrove substrate, besides increasing oxygenation, decomposition and percolation rate, and decreasing salinity and the sulfide substrate condition. This study performed the identification of two species based on their molecular qualities through COI gene markers. The samples were collected from Surabaya, Indonesia and their genomic DNA was extracted through DNA kit extraction at the Molecular Physiology Laboratory PKNU, Busan Korea. Based on the molecular identification in BLASTN, the two species confirmed were Uca forcipata and Uca triangularis with 99% certainty. The species were classified as an Asian fiddler crab species based on the phylogenetic tree featuring 59 species of fiddler crab from around the world.

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Federated Learning Enables Big Data for Rare Cancer Boundary Detection

arXiv

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arXiv 2022年

作者： Pati, Sarthak Baid, Ujjwal Edwards, Brandon Sheller, Micah Wang, Shih-Han Reina, G. Anthony Foley, Patrick Gruzdev, Alexey Karkada, Deepthi Davatzikos, Christos Sako, Chiharu Ghodasara, Satyam Bilello, Michel Mohan, Suyash Vollmuth, Philipp Brugnara, Gianluca Preetha, Chandrakanth J. Sahm, Felix Maier-Hein, Klaus Zenk, Maximilian Bendszus, Martin Wick, Wolfgang Calabrese, Evan Rudie, Jeffrey Villanueva-Meyer, Javier Cha, Soonmee Ingalhalikar, Madhura Jadhav, Manali Pandey, Umang Saini, Jitender Garrett, John Larson, Matthew Jeraj, Robert Currie, Stuart Frood, Russell Fatania, Kavi Huang, Raymond Y. Chang, Ken Balana, Carmen Capellades, Jaume Puig, Josep Trenkler, Johannes Pichler, Josef Necker, Georg Haunschmidt, Andreas Meckel, Stephan Shukla, Gaurav Liem, Spencer Alexander, Gregory S. Lombardo, Joseph Palmer, Joshua D. Flanders, Adam E. Dicker, Adam P. Sair, Haris I. Jones, Craig K. Venkataraman, Archana Jiang, Meirui So, Tiffany Y. Chen, Cheng Heng, Pheng Ann Dou, Qi Kozubek, Michal Lux, Filip Michálek, Jan Matula, Petr Keřkovský, Miloš Kopřivová, Tereza Dostál, Marek Vybíhal, Václav Vogelbaum, Michael A. Mitchell, J. Ross Farinhas, Joaquim Maldjian, Joseph A. Yogananda, Chandan Ganesh Bangalore Pinho, Marco C. Reddy, Divya Holcomb, James Wagner, Benjamin C. Ellingson, Benjamin M. Cloughesy, Timothy F. Raymond, Catalina Oughourlian, Talia Hagiwara, Akifumi Wang, Chencai To, Minh-Son Bhardwaj, Sargam Chong, Chee Agzarian, Marc Falcão, Alexandre Xavier Martins, Samuel B. Teixeira, Bernardo C.A. Sprenger, Flávia Menotti, David Lucio, Diego R. LaMontagne, Pamela Marcus, Daniel Wiestler, Benedikt Kofler, Florian Ezhov, Ivan Metz, Marie Jain, Rajan Lee, Matthew Lui, Yvonne W. McKinley, Richard Slotboom, Johannes Radojewski, Piotr Meier, Raphael Wiest, Roland Derrick, Murcia Fu, Eric Haas, Rourke Thompson, John Ormond, David Ryan Badve, Chaitra Sloan, Andrew E. Vadmal, Vachan Waite, Kristin Colen, Rivka R. Pei, Linmin Ak, Murat Srinivasan, Ashok Bapuraj, J. Rajiv Rao, Arvind Wang, Nicholas Yoshiaki, Ota Moritani, Tos University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Informatics Technical University of Munich Bavaria Munich Germany Intel Corporation Santa ClaraCA United States Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Heidelberg Germany Department of Neuropathology Heidelberg University Hospital Heidelberg Germany Division of Medical Image Computing German Cancer Research Center Heidelberg Germany Neurology Clinic Heidelberg University Hospital Heidelberg Germany Department of Radiology & Biomedical Imaging University of California San Francisco San FranciscoCA United States Symbiosis Center for Medical Image Analysis Symbiosis International University Maharashtra Pune India Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Karnataka Bangalore India Department of Radiology School of Medicine and Public Health University of Wisconsin MadisonWI United States Department of Medical Physics School of Medicine and Public Health University of Wisconsin MadisonWI United States Department of Neuroradiology Clinical Neuroscience Center University Hospital Zurich University of Zurich Zurich Switzerland Leeds Teaching Hospitals Trust Department of Radiology Leeds United Kingdom Department of Radiology Brigham and Women's Hospital Harvard Medical School BostonMA United States Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA United States Catalan Institute of Oncology Badalona Spain Consorci MAR Parc de Salut de Barcelona Catalonia Spain Josep Trueta University Hospital Girona Spain

Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally sharing ample, and importantly diverse, data from multiple sites. However, such centralization is challenging to scale (or even not feasible) due to various limitations. Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here we present findings from the largest FL study to-date, involving data from 71 healthcare institutions across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, utilizing the largest dataset of such patients ever used in the literature (25,256 MRI scans from 6,314 patients). We demonstrate a 33% improvement over a publicly trained model to delineate the surgically targetable tumor, and 23% improvement over the tumor's entire extent. We anticipate our study to: 1) enable more studies in healthcare informed by large and diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further quantitative analyses for glioblastoma via performance optimization of our consensus model for eventual public release, and 3) demonstrate the effectiveness of FL at such scale and task complexity as a paradigm shift for multi-site collaborations, alleviating the need for data sharing. © 2022, CC BY.

关键词： Tumors

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Ten quick tips for deep learning in biology

arXiv

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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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Cover Feature: Synthesis and Photophysical Properties of Hexabenzocoronene-Tetrabenzoporphyrin Architectures (Eur. J. Org. Chem. 40/2020)

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European Journal of Organic Chemistry 2020年第40期2020卷

作者： Michael Ruppel Lampros-Pascal Gazetas Dr. Dominik Lungerich Dr. Norbert Jux Department of Chemistry and Pharmacy & Interdisciplinary Center for Molecular Materials (ICMM) Friedrich-Alexander University Erlangen-Nuremberg Nikolaus-Fiebiger-Str. 10 91058 Erlangen Germany Institute for Basic Science (IBS) 50 Yonsei-ro Seodaemun-gu Center for Nanomedicine 03722 Seoul Republic of Korea Graduate Program of Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University 03722 Seoul Republic of Korea

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Adaptive in vivo Device for Theranostics of Inflammation by Monitoring of Cytokine Interferon-γ and Its Triggered Aspirin Release

SSRN

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SSRN 2019年

作者： Cao, Chaomin Jin, Ronghua Wei, Hui Liu, Zhongning Ni, Shengnan Chen, Xin Young, Howard A. Liu, Guojun Liu, Guozhen International Joint Research Center for Intelligent Biosensor Technology and Health Central China Normal University Wuhan430079 China School of Chemical Engineering and Technology Shanxi Key Laboratory of Energy Chemical Process Intensification Institute of Polymer Science in Chemical Engineering Xi’an Jiao Tong University Xi’an710049 China Department of Prosthodontics Peking University School and Hospital of Stomatology National Clinical Research Center for Oral Diseases National Engineering Laboratory for Digital and Material Technology of Stomatology Beijing Key Laboratory of Digital Stomatology Beijing100081 China Australian Nuclear Science and Technology Organization New Illuwarra Road Lucas HeightsNSW2234 Australia Graduate School of Biomedical Engineering ARC Centre of Excellent for Nanoscale Bipphotonics Faculty of Engineering University of New South Wales SydneyNSW2052 Australia Cancer and Inflammation Program Center for Cancer Research National Cancer Institute at Frederick FrederickMD21702 United States

Cytokines mediate and control immune and inflammatory responses. Complex interactions exist between cytokines, inflammation and the adaptive responses in maintaining homeostasis, health, and well being. On-demand, local delivery of anti-inflammatory drug molecules to target tissues provides a means for effective drug dosing while reducing the adverse effects of systemic drug delivery. This work demonstrates a proof-of-concept theranostic approach for inflammation based on analyte-kissing induced signaling, whereby a drug (in this report, aspirin) can be released upon detection of a target level of a proinfammatory cytokine(i.e. Interferon-γ (IFN-γ)) in real time. The structure-switching aptamer based biosensor described here is capable of quantitatively and dynamically detecting IFN-γ both in vitro and in vivo with a sensitivity of 10 pg mL-1. Moreover, the released aspirin triggered by the inflammatory cytokine IFN-γ is able to inhibit inflammation in the inflammatory rat model, and the releasing of aspirin can be quantitatively controlled. Herein research provides a novel and promising strategy for in vivo detection of proinflammatory cytokines and the subsequent therapeutic delivery of anti-inflammatory molecules. This universal theranostic platform is expected to achieve great potentials on personalized medicine towards treatment of various of diseases and health conditions. © 2019, The Authors. All rights reserved.

关键词： Pathology

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Commentaries on Viewpoint: Using V̇o2max as a marker of training status in athletes - can we do better?

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Journal of applied physiology (Bethesda, Md. : 1985) 2022年第1期133卷 148-164页

作者： Pedro L Valenzuela Manuel Mateo-March Xabier Muriel Mikel Zabala Alejandro Lucia David Barranco-Gil Grégoire P Millet Franck Brocherie Johannes Burtscher Martin Burtscher Benjamin J Ryan Rachel A Gioscia-Ryan Stephane Perrey Víctor Rodrigo-Carranza Fernando González-Mohíno José María González-Ravé Jordan Santos-Concejero Benedito S Denadai Camila C Greco Arturo Casado Carl Foster Raffaele Mazzolari Giulia Nicole Baldrighi Elisa Pastorio Davide Malatesta Aurélien Patoz Fabio Borrani Stephen J Ives Justin A DeBlauw Ricardo Dantas de Lucas Fernando Klitzke Borszcz Eduardo Marcel Fernandes Nascimento Luiz Guilherme Antonacci Guglielmo Tiago Turnes Richard T Jaspers Stephan van der Zwaard Romuald Lepers Julien Louis Anderson Meireles Hiago L. R. de Souza Géssyca T de Oliveira Marcelo P dos Santos Rhaí A Arriel Moacir Marocolo B Hunter S Meyler D Muniz-Pumares Renato M Ferreira Abigail S Sogard Stephen J Carter Timothy D Mickleborough Guilherme Pereira Saborosa Raphael Dinalli de Oliveira Freitas Paula Souza Alves dos Santos João Pedro de Souza Ferreira Francisco de Assis Manoel Sandro Fernandes da Silva Christoph Triska Bettina Karsten Dajo Sanders Elliot S Lipksi David J Spindler Matthijs K. C. Hesselink Rodrigo Zacca Márcio Fagundes Goethel David Bruce Pyne Brayden M Wood Peyton E Allen Jaden L Gabelhausen Alexandra M Keller Mast T Lige Alicia S Oumsang Greg L Smart Hunter L Paris Arthur H Dewolf Guillaume Toffoli Borja Martinez-Gonzalez Samuele M Marcora Daniela Terson de Paleville Ricardo J Fernandes Susana M Soares J. Arturo Abraldes Guilherme Matta Arthur Henrique Bossi D G McCarthy W Bostad J Gibala Mary Vagula Grupo de Investigación en Actividad física y Salud (PaHerg) Instituto de Investigación Hospital 12 de Octubre (imas12) Madrid Spain Faculty of Sport Sciences Universidad Europea de Madrid Madrid Spain Sport Science Department. Universidad Miguel Hernández Elche Spain Human Performance and Sports Science Laboratory Faculty of Sport Sciences University of Murcia Murcia Spain Department of Physical Education & Sport Faculty of Sport Sciences University of Granada Granada Spain Institute of Sport Sciences University of Lausanne Lausanne Switzerland Laboratory Sport Expertise and Performance (EA 7370) French Institute of Sport (INSEP) Paris France Department of Sport Science University of Innsbruck Innsbruck Austria Thermal and Mountain Medicine Division US Army Research Institute of Environmental Medicine Natick Massachusetts Department of Anesthesiology University of Michigan Ann Arbor Michigan EuroMov Digital Health in Motion University of Montpellier Montpellier France Sport Training Lab University of Castilla-La Mancha Toledo Spain Facultad de Ciencias de la Vida y de la Naturaleza Universidad Nebrija Madrid Spain Department of Physical Education and Sport University of the Basque Country UPV/EHU Vitoria-Gasteiz Spain Human Performance Laboratory São Paulo State University Rio Claro Brazil Center for Sport Studies Rey Juan Carlos University Madrid Spain University of Wisconsin-La Crosse La Crosse Wisconsin Department of Physical Education and Sport University of the Basque Country (UPV/EHU) Vitoria-Gasteiz Spain Department of Molecular Medicine University of Pavia Pavia Italy Department of Brain and Behavioural Sciences − Medical and Genomic Statistics Unit University of Pavia Pavia Italy Department of Biomedical Sciences for Health University of Milan Milan Italy Institute of Sport Sciences of University of Lausanne (ISSUL) University of Lausanne Lausanne Switzerland Health and Human Physiological Sciences Skidmore College Saratoga Springs New

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Consistency of surface electromyography assessment at lower limb selected muscles during vertical countermovement 39

Consistency of surface electromyography assessment at lower ...

引用

39th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2017

作者： Rodrigues, Carlos Correia, Miguel Abrantes, Joao M. C. S. Nadal, Jurandir Rodrigues, Marco A. Benedetti Centre for Biomedical Engineering Research INESC TEC Porto4200 - 465 Portugal Department of Electrical and Computer Engineering Faculty of Engineering University of Porto 4200-465 Portugal MovLab Interactions and Interfaces Lab Lusófona University of Humanities and Technologies Lisboa1749-024 Portugal Biomedical Engineering Program Federal University of Rio de Janeiro 21941-972 Brazil Graduate Program in Electrical Engineering Federal University of Pernambuco Recife50740-550 Brazil

ISBN: (纸本)9781509028092

Given the difficulty of invasive methods to assess muscle action during natural human movement, surface electromyography (sEMG) has been increasingly used to capture muscle activity in relation to kinesiological analysis of specific tasks. Isolated isometric, concentric and eccentric forms of muscle action have been receiving the most attention for research purposes. Nevertheless natural muscle action frequently involves the use of a preceding eccentric muscle action as a form of potentiation of immediate muscle concentric action, in what is designated as muscle stretch-shortening cycle (SSC). The most frequently applied protocols for the evaluation of SSC on vertical jumps are by virtue of their reproducibility and control of experimental conditions, squat jump (SJ) without countermovement (CM), countermovement jump (CMJ) with long CM and drop jump (DJ) with short CM. The methods used to extract information and relationship of the captured signals also present a high diversity, with the question about the consistency of the methods and obtained results. The objective of this study is to evaluate the consistency of the analysis and results by applying different EMGs signal analysis techniques related to strategic muscle groups of the lower limbs at different countermovement evaluated in vertical jumps. Raw sEMG signals of 5 lower limb muscles of 6 subjects during SJ, CMJ and DJ were rectified, filtered and obtained their envelope, and then correlated (CR) for detection of synergistic, agonist and antagonist activity, applied principal component analysis (PCA) for the detection of uncorrelated components explaining maximum variability and normalized cross-correlation (CCRN) for detection of maximum correlations and time lag. CR of EMG envelopes presented higher coactivities (CoA) in DJ relative to SJ and these CoA superior to CMJ with greater synergy in DJ relative to SJ and CMJ that present several loop cycles corresponding to time lag of activity. CCRN of the EMG e

关键词： Muscles Correlation Electromyography Principal component analysis Eigenvalues and eigenfunctions Electronic mail Radio frequency

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