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Informed Molecular Design of Conjugated Oligoelectrolytes To Increase Cell Affinity and Antimicrobial Activity

Angewandte Chemie 2018年第27期130卷

作者： Cheng Zhou Geraldine W. N. Chia James C. S. Ho Thomas Seviour Talgat Sailov Bo Liedberg Staffan Kjelleberg Jamie Hinks Guillermo C. Bazan School of Chemical and Biomedical Engineering Singapore Interdisciplinary Graduate School Singapore Singapore Centre on Environmental Life Sciences Engineering (SCELSE) Singapore Centre for Biomimetic Sensor Science School of Materials Science & Engineering Nanyang Technological University (NTU) Singapore 639798 Singapore Center for Polymers and Organic Solids Departments of Chemistry & Biochemistry and Materials University of California Santa Barbara Santa Barbara CA 93106 USA

Membrane‐intercalating conjugated oligoelectrolytes (COEs) are emerging as potential alternatives to conventional, yet increasingly ineffective, antibiotics. Three readily accessible COEs, belonging to an unreported series containing a stilbene core, namely D4 , D6 , and D8 , were designed and synthesized so that the hydrophobicity increases with increasing side‐chain length. Decreased aqueous solubility correlates with increased uptake by E. coli . The minimum inhibitory concentration (MIC) of D8 is 4 μg mL −1 against both E. coli and E. faecalis , with an effective uptake of 72 %. In contrast, the MIC value of the shortest COE, D4 , is 128 μg mL −1 owing to the low cellular uptake of 3 %. These findings demonstrate the application of rational design to generate efficacious antimicrobial COEs that have potential as low‐cost antimicrobial agents.

关键词： Antimikrobielle Aktivität Konjugierte Oligoelektrolyte Membranruptur Zellaffinität

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The integrated applications of WIFI and APP used in the shopping mall environment for menber card E-marketing

The integrated applications of WIFI and APP used in the shop...

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Chung, Cheng-Kung Chung, Iau-Quen Wang, Yung-Hau Chang, Ching-Ter Chang Gung University Graduate Institute of Business and Management Taiwan Chung Yuan Christian University Department of Biomedical Engineering Taiwan TaiMall Shopping Center Department of Engineering Taiwan Chang Gung University Department of Information Management Taiwan

ISBN: (纸本)9781509003891

In the Information Age, the problem of information overload as a form of explicitly good news or pollution has become more popular, the consumer's attention also becomes the scarce resource to be allocated. Member card can provide personal identification, authentication, data storage, and relevant application. It may provide strong marketing media for customer relationship within business organizations. However, many customers have received annoyed messages in the inappropriate time and place on their mobile devices when they were not expecting it. In this paper, the integrated applications of mall's Wi-Fi and App are proposed. The mobile devices of member card holder's media access control address (MAC address) collected by way of the mall's App via local Wi-Fi APs(access point) which connected the central administration server and received or interchanged information and configuration settings with the card account. By the integrated system, the mall and card members always keep in communication upon the system infrastructure;meanwhile, they are in visiting mall domain area. This is an important opportunity moment for the mall managers to grasp the categorized customers in real time. As the above mentioned moment, the mall manager could create extensive value and precisely aim to their products or services to their targeted customers by delivering marketing information. The typical deployment zone for the proposed approach is multiple computing applications. Our expected goal is to build a smart mall applications and location-based services (LBS). © 2016 IEEE.

关键词： Location based services

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Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health

arXiv

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arXiv 2021年

作者： Scott, Ryan T. Antonsen, Erik L. Sanders, Lauren M. Hastings, Jaden J.A. Park, Seung-Min Mackintosh, Graham Reynolds, Robert J. Hoarfrost, Adrienne L. Sawyer, Aenor Greene, Casey S. Glicksberg, Benjamin S. Theriot, Corey A. Berrios, Daniel C. Miller, Jack Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Chalk, Stuart Delgado-Aparicio, Guillermo M. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Kalantari, John Khezeli, Kia Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Martin, Hector Garcia Mason, Christopher E. Matar, Mona Mias, George I. Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Parsons-Wingerter, Patricia Prabhu, R.K. Qutub, Amina Ann Rask, Jon Saravia-Butler, Amanda Saria, Suchi Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Yang, Jason H. Zitnik, Marinka Costes, Sylvain V. KBR Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Department of Urology Department of Radiology Stanford University School of Medicine StanfordCA94305 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett FieldCA94035 United States Mortality Research & Consulting Inc. HoustonTX77058 United States Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States UC Space Health Department of Orthopaedic Surgery University of California San Francisco San FranciscoCA94143 United States Center for Health AI Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine Anschutz Medical Campus AuroraCO80045 United States Hasso Plattner Institute for Digital Health at Mount Sinai Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New YorkNY10065 United States Department of Preventive Medicine and Community Health UTMB GalvestonTX77551 United States Human Health and Performance Directorate NASA Johnson Space Center HoustonTX77058 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Data Scienc

Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth-independence, rather than Earth-reliance. Promising developments in the fields of artificial intelligence and machine learning for biology and health can address these needs. We propose an appropriately autonomous and intelligent Precision Space Health system that will monitor, aggregate, and assess biomedical statuses;analyze and predict personalized adverse health outcomes;adapt and respond to newly accumulated data;and provide preventive, actionable, and timely insights to individual deep space crew members and iterative decision support to their crew medical officer. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration, on future applications of artificial intelligence in space biology and health. In the next decade, biomonitoring technology, biomarker science, spacecraft hardware, intelligent software, and streamlined data management must mature and be woven together into a Precision Space Health system to enable humanity to thrive in deep space. © 2021, CC BY.

关键词： Earth (planet)

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Fast Saliency Detection Using Sparse Random Color Samples and Joint Upsampling

Fast Saliency Detection Using Sparse Random Color Samples an...

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Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI)

作者： Maiko Min Ian Lie Gustavo Benvenutti Borba Hugo Vieira Neto Humberto Remigio Gamba Grad. Program in Electr. & Comput. Eng. Fed. Univ. of Technol.-Parana Curitiba Brazil Graduate Program in Biomedical Engineering Graduate Program in Electrical and Computer Engineering

ISBN: (纸本)9781509035694;9781509035687

The human visual system employs a mechanism of visual attention, which selects only part of the incoming information for further processing. Through this mechanism, the brain avoids overloading its limited cognitive capacities. In computer vision, this task is usually accomplished through saliency detection, which outputs the regions of an image that are distinctive with respect to its surroundings. This ability is desirable in many technological applications, such as image compression, video quality assessment and content-based image retrieval. In this paper, a saliency detection method based on color distance with sparse random samples and joint upsampling is presented. This approach computes full-resolution saliency maps with short runtime by leveraging both edge-preserving smoothing and joint upsampling capabilities of the Fast Global Smoother. The proposed method is assessed through precision-recall curves, F-measure and average runtime on the MSRA1K dataset. Results show that the method is competitive with state-of-the-art algorithms in both saliency detection accuracy and runtime.

关键词： Image color analysis Runtime Visualization Image edge detection Smoothing methods Computational modeling Noise measurement

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Correction to: Editorial: Special Issue on Heart Valve Mechanobiology : New Insights into Mechanical Regulation of Valve Disease and Regeneration

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Cardiovascular engineering and technology 2018年第2期9卷 268页

作者： Craig A Simmons Hanjoong Jo Translational Biology and Engineering Program Ted Rogers Centre for Heart Research Toronto ON Canada. c.simmons@utoronto.ca. Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON Canada. c.simmons@utoronto.ca. Department of Mechanical and Industrial Engineering University of Toronto Toronto ON Canada. c.simmons@utoronto.ca. Coulter Department of Biomedical Engineering Emory University and Georgia Institute of Technology Atlanta GA USA. hjo@bme.gatech.edu. Department of Cardiology Emory University Atlanta GA USA. hjo@bme.gatech.edu.

Original article has been updated to include names and affiliations of authors.

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Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

arXiv

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arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

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A new dynamic surface reconstruction method for cardiac 3D mapping procedure

A new dynamic surface reconstruction method for cardiac 3D m...

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2016 6th International Conference on Machinery,Materials,Environment,Biotechnology and Computer(MMEBC 2016)

作者： Yingsong Huang Jian Wu Riqing Chen Research Center of Biomedical Engineering Graduate School of Shenzhen Tsinghua University

ISBN: (纸本)9781510828087

During cardiac 3D mapping procedure, the dynamic surface reconstruction of heart chambers helps to diagnose cardiac disease and improve the operation precision by keeping the catheter in placeThe paper introduces a new fast dynamic surface reconstruction method considering the distribution characteristics of the sample points collected during ablationThe algorithm defines the possible optimum reconstructed surface embedding in the Delaunay diagram of the sample points, and uses an iteration method to construct the defined optimum surfaceThe optimum reconstructed surface constraints can guarantee that the reconstructed surface is geometrically approximate to the original surfaceThe algorithm successively inserts points into the reconstructed surface by replacing the surface structure in a small neighbor of the inserted pointsIn order to keeping the integrity of the surface, the algorithm completes the replacement on basis of inside/outside of the Delaunay diagramIn order to assure a topological equivalence between the reconstructed surface and the original surface, the paper introduces an inflating method to keep reconstructed surface manifoldThe reconstructed surface is smoothed by the Loop subdivision algorithmThe paper experiments on six left atrium(LA) CT models, and the reconstruction results demonstrate that the proposed method can progressively reconstruct a surface which is geometrically and topologically approximate to the original heart chamber with a fast speed.

关键词： Cardiac Mapping Dynamic Surface Reconstruction Delaunay Based Iterative Replacement

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Assessing a scaffolded, interactive, and reflective analysis framework for developing ethical reasoning in engineering students 123

Assessing a scaffolded, interactive, and reflective analysis...

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123rd ASEE Annual Conference and Exposition

作者： Kisselburgh, Lorraine G. Hess, Justin L. Zoltowski, Carla B. Beever, Jonathan Brightman, Andrew O. Purdue University School of Engineering Education West Lafayette United States Purdue University EPICS Program West Lafayette United States University of Central Florida Department of Philosophy and Faculty Texts and Technology Program United States Purdue University Department of Engineering Practice Weldon School of Biomedical Engineering West Lafayette United States

Educating future engineers to effectively reason through complex ethical decisions encountered in the design and development of new technologies is a critical and relevant challenge. However, a coherent framework to analyze ethical issues with emerging technologies has not been widely adopted. Over three years, we developed and tested an innovative approach to teaching ethical reasoning that integrates a reflexive process of evaluation in a cyber-enabled learning environment. We posited that ethics should: be taught as a reasoning process;allow significant interaction between students;and include reflective application of ethical principles as part of a coherent, reflexive framework. To respond to this need, we developed: a) a pedagogical framework for ethics education of Scaffolded, Interactive, and Reflective Analysis (SIRA) that extends beyond case-based analyses;b) a coherent ethical reasoning approach, Reflexive Principlism (RP), applicable within engineering;and c) four case-based modules, integrating the SIRA/RP approach, with a novel, multimedia learning platform, each deliverable in a hybrid format for stand-alone course or embedded curricular applications. Previously, we have demonstrated that ethical reasoning scores of engineering students increase significantly as a result of participating in our SIRA/RP courses. In this paper, we explore the research question: "Which characteristics of the SIRA approach contribute to changes in ethical reasoning." To assess our framework we designed a SIRA assessment scale that uses student reported ratings of effectiveness of the scaffolding, interactivity, and reflective analysis characteristics of the course. After pilot-testing and refinement, the 12-item scale and sub-scales were found to be highly consistent (α =.847). To determine which SIRA characteristics contributed to increased ethical reasoning scores we ran a hierarchical multiple regression analysis with satisfaction and SIRA efficacy scores as predictors

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Analysis system for urine strip test using image processing technique

Analysis system for urine strip test using image processing ...

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biomedical engineering International Conference (BMEiCON)

作者： Chaowarit Ongkum Kriwut Keawmitr Ekkarat Boonchieng Faculty of Science Chiang Mai University BT Medical Laboratory Chiang Mai Biomedical Engineering Program Biomedical Engineering Center Faculty of Engineering Chiang Mai University

ISBN: (纸本)9781509039418

Urine is waste that must be discharged from living bodies. In the medical field, urine is very useful for analyzing and curing diseases. The kidneys extract waste from the blood. Urinalysis is used to determine and inspect urinary function and system. This research developed an analytical System for a Urine Strip Test Using Image Processing to compare among human eyes and Urine automated with 100 samples. The result shows there is no differences with significant alpha below 0.05. In conclusion, any medical technician can use this system instead of a conventional method. It is cheaper and faster.

关键词： Strips Image color analysis Testing Blood Chemicals Standards Colored noise

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Correction to: Requirement or exclusion of inverted repeat sequences with cruciform-forming potential in Escherichia coli revealed by genome-wide analyses

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Current genetics 2018年第5期64卷 1171页

作者： Osamu Miura Toshihiro Ogake Takashi Ohyama Department of Biology Faculty of Education and Integrated Arts and Sciences Waseda University 2-2 Wakamatsu-cho Shinjuku-ku Tokyo 162-8480 Japan. Major in Integrative Bioscience and Biomedical Engineering Graduate School of Science and Engineering Waseda University 2-2 Wakamatsu-cho Shinjuku-ku Tokyo 162-8480 Japan. Department of Biology Faculty of Education and Integrated Arts and Sciences Waseda University 2-2 Wakamatsu-cho Shinjuku-ku Tokyo 162-8480 Japan. ohyama@waseda.jp. Major in Integrative Bioscience and Biomedical Engineering Graduate School of Science and Engineering Waseda University 2-2 Wakamatsu-cho Shinjuku-ku Tokyo 162-8480 Japan. ohyama@waseda.jp.

The article 'Requirement or exclusion of inverted repeat sequences with cruciform-forming potential in Escherichia coli revealed by genome-wide analyses' written by Osamu Miura, Toshihiro Ogake, Takashi Ohyama...

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