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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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A Reconfigurable DNA Accordion Rack

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Angewandte Chemie 2018年第11期130卷

作者： Yeongjae Choi Hansol Choi Amos C. Lee Hyunung Lee Sunghoon Kwon Department of Electrical and Computer Engineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea Interdisciplinary Program for Bioengineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea Institute of Entrepreneurial Bio Convergence Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea Seoul National University Hospital Biomedical Research Institute Seoul National University Hospital 101 Daehak-ro Jongno-gu Seoul 03080 Republic of Korea

DNA nanostructure‐based mechanical systems that control the distance between elements of interest have demonstrated great potential for various applications, including nanoplasmonic systems, molecular reactors, and other nanotechnology platforms. However, previously reported systems could not collectively manipulate a 2D or 3D nanoscale network of elements to various forms in multiple stages. A reconfigurable DNA accordion rack structure is introduced that is a DNA beam lattice that changes its conformation with a small amount of short‐length DNA locks as the controlling input. The lattice shape of the 2D DNA accordion rack and the diameter and the height of the 3D DNA nanotubular structure made of the DNA accordion rack could be controlled. Furthermore, by sequentially repeating the detachment and the attachment of the different DNA locks using strand displacement, the shape reconfiguration was repeatedly carried out.

关键词： DNA-Nanomaschinen DNA-Nanotechnologie DNA-Strukturen Nanoporen Selbstorganisation

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The impact of an introductory biomedical engineering course on students' perceptions of the engineering profession

The impact of an introductory biomedical engineering course ...

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作者： Cruz, Antonio Miguel Rincon, Adriana Rios Dueñas, William Ricardo Rodríguez Luna, Nestor Florez Torres, Daniel Alejandro Quiroga Occupational Therapy Program Biomedical Engineering Program School of Medicine and Health Sciences Universidad Del Rosario Calle 63D # 24-31 7 de Agosto Bogotá D.C Colombia Faculty of Rehabilitation Medicine University of Alberta 2-64 Corbett Hall EdmontonABT6G 2G4 Canada

After their first year roughly 50% of engineering students do not continue in that major. One cause could be that students have little idea as to what the profession of engineering is about. Freshman introductory courses provide a first approach to the engineering profession. Therefore, understanding the role of introductory engineering courses to increasing student knowledge of the profession is a relevant issue. The purpose of the study is to describe how student perceptions of the engineering profession overall change as a result of their educational experience in an introductory biomedical engineering course. This is a pre- post-test with no control group study design. One class (n = 41) on a first-year biomedical engineering course participated in a hybrid Project-based-learning (PBL)-lecture learning strategy. A survey composed of a demographic and 5-point Likert ("1" is strongly disagree and "5" is strongly agree) sections measured students' perceptions of the engineering profession and was administered (paper-based) to all the students enrolled on this course. The students' perceptions of the engineering profession were pooled into 3 main groups of skills, i.e. Technical skills, Professional skills, and Project management skills. Wilcoxon signed-rank test statistics were conducted to analyze the research question. Our analysis showed statistically significant results (pre-survey mean and SD: 4.01, 0.07;and postsurvey mean and SD: 4.21, 0.05, p © 2016 TEMPUS Publications.

关键词： Students

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INTRODUCTION

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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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Digital health technologies in the accelerating medicines Partnership® Schizophrenia program

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Schizophrenia (Heidelberg, Germany) 2025年第1期11卷 83页

作者： Johanna T W Wigman Ann Ee Ching Yoonho Chung Habiballah Rahimi Eichi Erlend Lane Carsten Langholm Aditya Vaidyam Andrew Jin Soo Byun Anastasia Haidar Jessica Hartmann Angela Nunez Dominic Dwyer Adibah Amani Nasarudin Owen Borders Isabelle Scott Zailyn Tamayo Priya Matneja Kang-Ik Cho Jean Addington Luis K Alameda Celso Arango Nicholas J K Breitborde Matthew R Broome Kristin S Cadenhead Monica E Calkins Eric Yu Hai Chen Jimmy Choi Philippe Conus Cheryl M Corcoran Barbara A Cornblatt Covadonga M Diaz-Caneja Lauren M Ellman Paolo Fusar-Poli Pablo A Gaspar Carla Gerber Louise Birkedal Glenthøj Leslie E Horton Christy Lai Ming Hui Joseph Kambeitz Lana Kambeitz-Ilankovic Matcheri S Keshavan Sung-Wan Kim Nikolaos Koutsouleris Kerstin Langbein Daniel Mamah Daniel H Mathalon Vijay A Mittal Merete Nordentoft Godfrey D Pearlson Jesus Perez Diana O Perkins Albert R Powers Jack Rogers Fred W Sabb Jason Schiffman Jai L Shah Steven M Silverstein Stefan Smesny Walid Yassin William S Stone Gregory P Strauss Judy L Thompson Rachel Upthegrove Swapna Verma Jijun Wang Daniel H Wolf Phillip Wolff Laura M Rowland Simon D'Alfonso Ofer Pasternak Sylvain Bouix Patrick D McGorry Rene S Kahn John M Kane Carrie E Bearden Scott W Woods Martha E Shenton Barnaby Nelson Justin T Baker John Torous University of Groningen University Medical Center Groningen Department of Psychiatry Interdisciplinary Centre of Psychopathology and Emotion regulation Groningen The Netherlands. Centre for Youth Mental Health The University of Melbourne Parkville VIC Australia. Orygen Parkville VIC Australia. McLean Hospital Belmont MA USA. Harvard Medical School Boston MA USA. Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA. Brigham and Women's Hospital Harvard Medical School Boston MA USA. Yale University New Haven CT USA. Northwell Health Glen Oaks NY USA. Department of Psychiatry Hotchkiss Brain Institute University of Calgary Calgary AB Canada. Service de Psychiatrie Générale Dép. de Psychiatrie CHUV Lausanne Lausanne Switzerland. Department of Child and Adolescent Psychiatry Institute of Psychiatry and Mental Health Hospital General Universitario Gregorio Marañón Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM) CIBERSAM ISCIII School of Medicine Universidad Complutense Madrid Spain. Department of Psychiatry and Behavioral Health Ohio State University Columbus OH USA. Department of Psychology Ohio State University Columbus OH USA. Institute for Mental Health School of Psychology University of Birmingham Birmingham UK. Birmingham Women's and Children's NHS Foundation Trust Birmingham UK. University of California San Diego CA USA. Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Psychiatry School of Clinical Medicine Li Ka Shing Faculty of Medicine University of Hong Kong Hong Kong Hong Kong. Olin Neuropsychiatry Research Center Hartford HealthCare Behavioral Health Network Hartford CT USA. Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA. Department of Psychiatry Donald and Barbara Zucker School of Medicine Hempstead NY USA. Feinstein Institute for Medical Research Manhasset NY USA. Department of Psych

Although meta-analytic studies have shown that 25-33% of those at Clinical High Risk (CHR) for psychosis transition to a first episode of psychosis within three years, less is known about estimating the risk of transition at an individual level. Digital phenotyping offers a novel approach to explore the nature of CHR and may help to improve personalized risk prediction. Specifically, digital data enable detailed mapping of experiences, moods and behaviors during longer periods of time (e.g., weeks, months) and offer more insight into patterns over time at the individual level across their routine daily life. However, while novel digital health technologies open up many new avenues of research, they also come with specific challenges, including replicability of results and the adherence of participants. This paper outlines the design of the digital component of the Accelerating Medicines Partnership® Schizophrenia program (AMP SCZ) project, a large international collaborative project that follows individuals at CHR for psychosis over a period of two years. The digital component comprises one-year smartphone-based digital phenotyping and actigraphy. Smartphone-based digital phenotyping includes 30-item short daily self-report surveys and voice diaries as well as passive data capture (geolocation, on/off screen state, and accelerometer). Actigraphy data are collected via an Axivity wristwatch. The aim of this paper is to describe the design and the three goals of the digital measures used in AMP SCZ to: (i) better understand the symptoms, real-life experiences, and behaviors of those at CHR for psychosis, (ii) improve the prediction of transition to psychosis and other health outcomes in this population based on digital phenotyping and, (iii) serve as an example for replicable and ethical research across geographically diverse regions and cultures. Accordingly, we describe the rationale, protocol and implementation of these digital components of the AMP SCZ project. **

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Effects of variation of chitosan concentration on the characteristics of membrane cellulose bacteria-chitosan biocomposites as candidates for artificial dura mater

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AIP Conference Proceedings 2017年第1期1817卷

作者： Prihartini Widiyanti Hajria Jabbar Djony Izak Rudyardjo 1Biomedical Engineering Study Program Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia 2Institute of Tropical Disease Universitas Airlangga Surabaya 60115 Indonesia 3Physics Study Program Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia

This study was conducted to determine the effect of variation in concentration of chitosan on the physical and biological characteristics of the membrane of bacterial cellulose-chitosan biocomposites through immersion precipitation method. Bacterial cellulose membrane was soaked in a solution of chitosan whose concentration variation are 0.1%; 0.3%; 0.5% and 0.7%. The characterization tests which were conducted included the analysis of functional groups (FTIR), tensile strength test, morphology test (SEM), and cytotoxicity assay using MTT Assay method. Based on the cluster analysis test, the results of FTIR spectra indicate changes in the physical bond which means that there is interaction between the bacterial cellulose membrane with chitosan on each sample. The bacteria produced cellulose membrane with tensile strength of 10.53 ± 0.19 MPa while the microbial cellulose membrane by adding 0.5% chitosan concentration had tensile strength value of 8:58 ± 0.19 MPa. It shows that with the addition of chitosan it would decrease the tensile strength in microbial cellulose membrane. This was shown by 496.2 nm - 2,032 µm pore size with a thickness (mm) of 0:35 ± 0.33 to 0.81 ± 0.26. Based on the test results of the analysis of functional groups, tensile strength test, and morphology test, membrane microbial cellulose-chitosan biocomposites have the potential to be used as artificial dura mater candidate.

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Driver drowsiness detection using the in-ear EEG

Driver drowsiness detection using the in-ear EEG

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

作者： Taeho Hwang Miyoung Kim Seunghyeok Hong Kwang Suk Park Samsung Electronics DMC Research Center Seoul South Korea Interdisciplinary Program in Bioengineering Seoul National University Seoul South Korea Department of Biomedical Engineering Seoul National University College of Medicine Seoul South Korea

ISBN: (纸本)9781457702198

Driver drowsiness monitoring is one of the most demanded technologies for active prevention of severe road accidents. Electroencephalogram (EEG) and several peripheral signals have been suggested for the drowsiness monitoring. However, each type of signal has partial limitations in terms of either convenience or accuracy. Recent emerged concept of in-ear EEG raises expectations due to reduced obtrusiveness. It is yet unclear whether the in-ear EEG is effective enough for drowsiness detection in comparison with on-scalp EEG or peripheral signals. In this work, we evaluated performance of the in-ear EEG in drivers' alertness-drowsiness classification for the first time. Simultaneously, we also tested three peripheral signals including electrocardiogram (ECG), photoplethysmogram (PPG), and galvanic skin response (GSR) which have advantage in convenience of measurement. The classification analysis using the in-ear EEG resulted in high classification accuracy comparable to that of the individual on-scalp EEG channels. The ECG, PPG and GSR showed competitive performance but only when used together in pairwise combinations. Our results suggest that the in-ear EEG would be viable alternative to the single channel EEG or the individual peripheral signals for the drowsiness monitoring.

关键词： Electroencephalography Electrocardiography Monitoring Vehicles Wheels Standards Ear

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A synthetic biological secondary metabolite,Lycogen^TM,produced and extracted from Rhodobacter sphaeroides WL-APD911 in an optimizatioal scale-up strategy

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Food Science and Human Wellness 2017年第4期6卷 195-201页

作者： Cheng-Chin Wang Shi-Ying Huang Shu-Hung Huang Zhi-Hong Wen Jyun-Ying Huang Wen-Sheng Liu Hui-Min David Wang Research and Development Department Chia-Yi SteelTainan 717TaiwanChina College of Oceanology and Food Science Quanzhou Normal UniversityQuanzhou 362000China Fujian Province Key Laboratory for the Development of Bioactive Material from Marine Algae Quanzhou 362000China Division of Plastic Surgery Department of SurgeryKaohsiung Medical University HospitalKaohsiung Medical UniversityKaohsiung 807TaiwanChina Graduate Institute of Medicine College of MedicineKaohsiung Medical UniversityKaohsiung 807TaiwanChina Center for Stem Cell Research Kaohsiung Medical UniversityKaohsiung 807TaiwanChina Department of Surgery Faculty of MedicineCollege of MedicineKaohsiung Medical UniversityKaohsiung 807TaiwanChina Orthopaedic Research Center Kaohsiung Medical UniversityKaohsiung 807TaiwanChina Doctoral Degree Program in Marine Biotechnology National Sun Yat-sen University and Academia SinicaKaohsiung 804TaiwanChina Marine Biomedical Laboratory and Center for Translational Biopharmaceuticals Department of Marine Biotechnology and ResourcesNational Sun Yat-sen UniversityKaohsiung 804TaiwanChina Graduate Institute of Biomedical Engineering National Chung Hsing UniversityTaichung 402TaiwanChina Department and Graduate Institute of Aquaculture National Kaohsiung Marine UniversityKaohsiung 811TaiwanChina Asia-Pacific Biotech Developing Inc.Kaohsiung 803TaiwanChina Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung 404TaiwanChina

The optimization of fermentation medium is important for synthetic biological secondary metabolite *** effect of rotation speed,inoculum amount,and medium supplements on the cell growth and Lycogen^TM secretion of photobacterium Rhodobacter sphaeroides WL-APD911 was *** results reveal that a higher rotational speed exhibit a higher cell density,and the increasing in the amount of inoculum amount show a slight augment on the growth of *** *** the case of nitrogen sources adding,Lycogen^TM production was achieved with a 0.5 mM l-lysine ***,the attention of Tween 80 presented a tremendous increase in the secondary *** surface methodology(RSM)exhibited the optimization of medium supplements for Lycogen^TM invention is accomplished at molasses concentration of 10 g/L,yeast extract concentration of 40 g/L,0.3%Tween 80 and NaCl concentration of 5 g/L,***,the batch fermentation is carried out in both 5 L and 20 L fermentors to study the scale-up process factors to be *** a 20 L fermentor,Lycogen^TM yields under the optimal culture condition are over 2 times than in the shake *** present results provide the Lycogen^TM optimal culture mediums,scale-up procedures and efficient extractions from *** WL-APD911.

关键词： Rhodobacter sphaeroides WL-APD911 Lycogen^TM Response surface methodology(RSM) Ferementation

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Development of high energy femtosecond fiber laser by all fiber coherent beam combining technology

Development of high energy femtosecond fiber laser by all fi...

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European Conference on Lasers and Electro-Optics, CLEO 2015

作者： Kambayashi, Y. Yoshida, M. Inoue, T. Yoshikawa, M. Program in Electronic Engineering Interdisciplinary Graduate Faculty of Science and Engineering Kinki University 3-4-1 Kowakae Higashi-osaka Osaka577-8502 Japan

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