Cell-Based Biosensors Principles and Applications Artech House Series Bioinformatics & Biomedical Imaging

Total Page:16

File Type:pdf, Size:1020Kb

Cell-Based Biosensors Principles and Applications Artech House Series Bioinformatics & Biomedical Imaging Cell-Based Biosensors Principles and Applications Artech House Series Bioinformatics & Biomedical Imaging Series Editors Stephen T. C. Wong, The Methodist Hospital and Weill Cornell Medical College Guang-Zhong Yang, Imperial College Advances in Diagnostic and Therapeutic Ultrasound Imaging, Jasjit S. Suri, Chirinjeev Kathuria, Ruey-Feng Chang, Filippo Molinari, and Aaron Fenster, editors Biological Database Modeling, Jake Chen and Amandeep S. Sidhu, editors Biomedical Informatics in Translational Research, Hai Hu, Michael Liebman, and Richard Mural Cell-Based Biosensors: Principles and Applications, Ping Wang and Qinjun Liu, editors Data Mining in Biomedicine Using Ontologies, Mihail Popescu and Dong Xu, editors Genome Sequencing Technology and Algorithms, Sun Kim, Haixu Tang, and Elaine R. Mardis, editors High-Throughput Image Reconstruction and Analysis, A. Ravishankar Rao and Guillermo A. Cecchi, editors Life Science Automation Fundamentals and Applications, Mingjun Zhang, Bradley Nelson, and Robin Felder, editors Microscopic Image Analysis for Life Science Applications, Jens Rittscher, Stephen T. C. Wong, and Raghu Machiraju, editors Next Generation Artifi cial Vision Systems: Reverse Engineering the Human Visual System, Maria Petrou and Anil Bharath, editors Systems Bioinformatics: An Engineering Case-Based Approach, Gil Alterovitz and Marco F. Ramoni, editors Text Mining for Biology and Biomedicine, Sophia Ananiadou and John McNaught, editors Translational Multimodality Optical Imaging, Fred S. Azar and Xavier Intes, editors Cell-Based Biosensors Principles and Applications Ping Wang Qingjun Liu Editors Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the U.S. Library of Congress. British Library Cataloguing in Publication Data A catalog record for this book is available from the British Library. ISBN-13: 978-1-59693-439-9 Cover design by Pilar Colleran © 2010 Artech House 685 Canton Street Norwood, MA 02062 All rights reserved. Printed and bound in the United States of America. No part of this book may be reproduced or utilized in any form or by any means, elec- tronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. All terms mentioned in this book that are known to be trademarks or service marks have been appropriately capitalized. Artech House cannot attest to the accuracy of this information. Use of a term in this book should not be regarded as affecting the validity of any trademark or service mark. 10 9 8 7 6 5 4 3 2 1 Contents Foreword xi Preface xiii Acknowledgments xvii CHAPTER 1 Introduction 1 1.1 Defi nition of Cell-Based Biosensors 1 1.2 Characteristics of Cell-Based Biosensors 3 1.3 Types of Cell-Based Biosensors 4 1.4 Summary 10 References 11 CHAPTER 2 Cell Culture on Chips 13 2.1 Introduction 13 2.2 Cell Immobilization Factors 14 2.2.1 Physical Factors 14 2.2.2 Chemical Factors 15 2.2.3 Biological Factors 15 2.3 Basic Surface Modifi cation Rules 16 2.3.1 Hydrophilicity Improving 17 2.3.2 Roughness Changing 18 2.3.3 Chemical Coating 18 2.4 Typical Methods 20 2.4.1 Special Physical Structure 22 2.4.2 Microcontact Printing 24 2.4.3 Fast Ink-Jet Printing 26 2.4.4 Perforated Microelectrode 27 2.4.5 Self-Assembled Monolayer 29 2.4.6 Microfl uidic Technology 30 2.5 Summary 33 References 33 v vi Contents CHAPTER 3 Mechanisms of Cell-Based Biosensors 37 3.1 Introduction 37 3.2 Metabolic Measurements 38 3.2.1 Cell Metabolism 38 3.2.2 Extracellular pH Monitoring 40 3.2.3 Other Extracellular Metabolite Sensing 43 3.2.4 Secondary Transducers 44 3.3 Action Potential Measurements 44 3.3.1 Action Potential 45 3.3.2 The Solid-Electrolyte Interface 47 3.3.3 Cell-Electrode Interface Model 52 3.3.4 Cell-Silicon Interface Model 54 3.3.5 Secondary Transducers 55 3.4 Impedance Measurements 56 3.4.1 Membrane Impedance 56 3.4.2 Impedance Model of Single Cells 57 3.4.3 Impedance Model of Populations of Cells 59 3.4.4 Secondary Transducers 61 3.5 Noise Sources 62 3.5.1 Electrode Noise 62 3.5.2 Electromagnetic Interference 63 3.5.3 Biological Noise 63 3.6 Summary 64 References 64 CHAPTER 4 Microelectrode Arrays (MEA) as Cell-Based Biosensors 65 4.1 Introduction 65 4.2 Principle 68 4.3 Fabrication and Design of MEA System 69 4.3.1 Fabrication 69 4.3.2 Different MEA Chips 74 4.3.3 Measurement Setup 77 4.4 Theoretical Analysis of Signal Process in MEA Systems 79 4.4.1 Equivalent Circuit Model of Signal Process 79 4.4.2 Impedance Properties Analysis of MEA 80 4.4.3 Analysis of Extracellular Signal 82 4.5 Application of MEA 84 4.5.1 Dissociated Neural Network on MEA 84 4.5.2 Slice on MEA 86 4.5.3 Retina on MEA 88 4.5.4 Pharmacological Application 89 4.6 Development Trends 92 4.6.1 Lab on a Chip 92 4.6.2 Portable MEA System 92 Contents vii 4.6.3 Other Developmental Trends 92 4.7 Summary 93 References 93 CHAPTER 5 Field Effect Transistor (FET) as Cell-Based Biosensors 97 5.1 Introduction 97 5.2 Principle 98 5.3 Device and System 100 5.3.1 Fabrication of FET-Based Biosensor 100 5.3.2 FET Sensor System 102 5.4 Theoretical Analysis 103 5.4.1 Area-Contact Model 104 5.4.2 Point-Contact Model 105 5.5 Application 106 5.5.1 Electrophysiological Recording of Neuronal Activity 106 5.5.2 Two-Way Communication Between Silicon Chip and Neuron 108 5.5.3 Neuronal Network Study 109 5.5.4 Cell Microenvironment Monitoring 112 5.6 Development Trends 114 5.7 Summary 115 References 116 CHAPTER 6 Light Addressable Potentiometric Sensor (LAPS) as Cell-Based Biosensors 119 6.1 Introduction 119 6.2 Principle 121 6.2.1 Fundamental 121 6.2.2 Numerical Analysis 122 6.3 Device and System 124 6.3.1 Device 124 6.3.2 Microphysiometer System 126 6.3.3 Detecting System of Cell-Semiconductor Hybrid LAPS 129 6.4 Application 132 6.4.1 Signaling Mechanism Study 133 6.4.2 Functional Characterization of Ligand/Receptor Binding 134 6.4.3 Identifi cation of Ligand/Receptor 136 6.4.4 Drug Analysis 137 6.5 Developing Trend 143 6.5.1 LAPS Array System for Parallel Detecting 144 6.5.2 Multifunctional LAPS System 145 6.6 Summary 146 References 146 viii Contents CHAPTER 7 Electric Cell-Substrate Impedance Sensor (ECIS) as Cell-Based Biosensors 151 7.1 Introduction 151 7.2 Principle 152 7.2.1 Electrochemical Impedance 152 7.2.2 Cell-Substrate Impedance 154 7.2.3 AC Frequency and Sensitivity Characteristics of Interdigitated Electrodes 156 7.3 Device and System 160 7.3.1 Device Fabrication 160 7.3.2 Bioimpedance Measurement System 161 7.4 Theoretical Analysis 164 7.4.1 Lumped Model 164 7.4.2 Analytical Model 165 7.4.3 Data Calculation and Presentation 165 7.5 Applications 167 7.5.1 Monitoring of Cell Adhesion, Spreading, Morphology, and Proliferation 167 7.5.2 Monitoring of Cell Migration and Invasion 169 7.5.3 Monitoring of Cellular Ligand-Receptor Interactions 170 7.5.4 Cytotoxicity Assays 172 7.6 Development Trends 173 7.6.1 High-Throughput Screening 173 7.6.2 Integrated Chip 175 7.7 Summary 175 References 176 CHAPTER 8 Patch Clamp Chip as Cell-Based Biosensors 179 8.1 Introduction 179 8.2 Theory 179 8.2.1 Conventional Patch Clamp 179 8.2.2 Patch Clamp Chip 181 8.3 Sensor Device and System 182 8.3.1 Patch Clamp Chip Device 182 8.3.2 Patch Clamp Chip System 188 8.3.3 Cells Preparation 193 8.4 Biomedical Application 194 8.4.1 Ionic Channels Research 194 8.4.2 Drug Discovery 199 8.4.3 Drug Safety 200 8.5 Development Trends 202 8.6 Summary 203 References 203 Contents ix CHAPTER 9 Other Cell-Based Biosensors 207 9.1 Quartz Crystal Microbalance (QCM) as Cell-Based Biosensors 207 9.1.1 Introduction 207 9.1.2 Principle of QCM 208 9.1.3 QCM Sensors and Measurement System 210 9.1.4 Biomedical Application 211 9.2 Surface Plasmon Resonance (SPR) as Cell-Based Biosensors 217 9.2.1 Introduction 217 9.2.2 The Principle of SPR 219 9.2.3 SPR Sensors and Measurement System 220 9.2.4 Biomedical Application 221 9.3 Immune Cell-Based Biosensors 225 9.3.1 Introduction 225 9.3.2 Mast Cell–Based Biosensors 226 9.3.3 Dendritic Cell–Based Biosensors 227 9.3.4 B Cell–Based Biosensors 229 9.4 Summary 229 References 230 CHAPTER 10 Developments of Cell-Based Biosensors 233 10.1 Introduction 233 10.2 Cell-Based Biosensors with Integrated Chips 233 10.2.1 Integration Chip of the Same or Similar Functional Sensors 234 10.2.2 Multisensors Involve Sensing Elements with Different Functions 235 10.2.3 Multifunctional Chip Monitoring Different Parameters 236 10.3 Cell-Based Biosensors Using Nanotechnology 237 10.3.1 Nano-Micropatterned Cell Cultures 238 10.3.2 Nanoporous-Based Biosensor 239 10.3.3 Nanoprobes to Intracellular Nanosensors 240 10.4 Cell-Based Biosensors with Microfl uidic Chips 241 10.4.1 Microfl uidic Flow 242 10.4.2 Soft Lithography 243 10.4.3 Dielectrophoresis 245 10.5 Biomimetic Olfactory and Gustatory Cell-Based Biosensors 246 10.5.1 Bioelectronic Nose and Bioelectronic Tongue 247 10.5.2 Olfactory and Gustatory Biosensors with Special Receptors 247 10.5.3 Olfactory and Gustatory Cell-Based Biosensors 248 References 250 Glossary 255 About the Editors 261 List of Contributors 262 Index 263 Foreword The fi eld of biosensors and bioelectronics has enveloped many new areas such as molecularly sensitive receptors, biomimetic sensors, nanotechnology, and more.
Recommended publications
  • APPROPRIATE HEALTH TECHNOLOGY Emlrc44itech.Disc./1
    WORLD HEALTH ORGANIZATION ~egional Office for the Eastern Mediterranean ORGANISATION MONDIALE DE LA SANTE Bureau regional de la Mediterranee orientale REGIONAL COMMITTEE FOR THE EMlRC44/Tech.Disc'/l EASTERN MEDITERRANEAN August 1997 Forty-fourth Session Original: Arabic Agenda item 7 TECHNICAL DISCUSSIONS APPROPRIATE HEALTH TECHNOLOGY EMlRC44ITech.Disc./1 CONTENTS page Executive Summary 1. Introduction....................................................................................................... 1 2. Definitions......................................................................................................... 1 2.1 Health technology..................................................................................... I 2.2 Appropriate technology............................................................................. I 3. Appropriate technology and future trends........................................................... 3 3. I General..................................................................................................... 3 3.2 Health care.................................................................... ............................ 3 3.3 Gene technology..... ....... ....... ............ ........................................................ 4 3.4 Laboratory medicine technologies............................................................. 4 3.5 Transfusion medicine................................................................................. 5 3.6 Diagnostic imaging...................................................................................
    [Show full text]
  • A Caspase-1 Biosensor to Monitor the Progression of Inflammation in Vivo
    Published October 2, 2019, doi:10.4049/jimmunol.1900619 The Journal of Immunology A Caspase-1 Biosensor to Monitor the Progression of Inflammation In Vivo Sarah Talley,* Olga Kalinina,† Michael Winek,‡ Wonbeom Paik,† Abigail R. Cannon,* Francis Alonzo, III,† Mashkoor A. Choudhry,* Katherine L. Knight,† and Edward M. Campbell*,†,‡ Inflammasomes are multiprotein complexes that coordinate cellular inflammatory responses and mediate host defense. Following recognition of pathogens and danger signals, inflammasomes assemble and recruit and activate caspase-1, the cysteine protease that cleaves numerous downstream targets, including pro–IL-1b and pro–IL-18 into their biologically active form. In this study, we sought to develop a biosensor that would allow us to monitor the initiation, progression, and resolution of inflammation in living animals. To this end, we inserted a known caspase-1 target sequence into a circularly permuted luciferase construct that becomes bioluminescent upon protease cleavage. This biosensor was activated in response to various inflammatory stimuli in human monocytic cell lines and murine bone marrow–derived macrophages. Next, we generated C57BL/6 transgenic mice constitutively expressing the caspase-1 biosensor. We were able to monitor the spatiotemporal dynamics of caspase-1 activation and onset of inflammation in individual animals in the context of a systemic bacterial infection, colitis, and acute graft-versus-host disease. These data established a model whereby the development and progression of inflammatory responses can be monitored in the context of these and other mouse models of disease. The Journal of Immunology, 2019, 203: 000–000. umerous cell types, canonically cells of the innate im- filamentous complexes, providing a platform for the recruitment mune system, express cytosolic, nuclear, and membrane- and subsequent activation of caspase-1 (1–4, 8, 10–15).
    [Show full text]
  • The Future for Biosensors in Biopharmaceutical Production
    Pharmaceutical Commentary BRACEWELL & POLIZZI The future for biosensors in biopharmaceutical production 2 Commentary The future for biosensors in biopharmaceutical production Pharm. Bioprocess. Keywords: bioprocess monitoring • bioprocess control • in-vivo biosensor • PAT Daniel G Bracewell*,1 • synthetic biology & Karen M Polizzi2 1The Advanced Centre for Biochemical Engineering, Department of Biochemical A defining feature of bioprocesses is the need straightforward. This is not to say there have Engineering, University College London, for measurement, monitoring and control; in not been significant successes: Torrington Place, London, WC1E 7JE, UK the context of biopharmaceuticals this need 2Department of Life Sciences & Centre • The world’s diabetic population depends is further heightened by the absolute require- for Synthetic Biology & Innovation, on blood glucose measurements to admin- Imperial College London, London, UK ment to ensure the quality of the product [1] . ister insulin based on an amperometric *Author for correspondence: This is evidenced by the size of bioanalytical based biosensor technology (enzyme elec- [email protected] endeavor found within the R&D programs trodes). This represents the largest single of the major biopharmaceutical companies biosensor application in terms of numbers and the supplier industry that caters for this of devices and market size; instrumentation need. It is a need that grows at a pace reflected in the initiatives involv- • Optical biosensors, largely surface plas- ing the regulatory authorities such as PAT mon resonance (BIAcore) has become central to the larger vision of QbD. At the the default method to directly mea- core of these attempts to improve biophar- sure protein–protein interactions in the maceutical production is the need for rapid, laboratory.
    [Show full text]
  • Biosensors and Bioelectronics 141 (2019) 111467
    Biosensors and Bioelectronics 141 (2019) 111467 Contents lists available at ScienceDirect Biosensors and Bioelectronics journal homepage: www.elsevier.com/locate/bios Designing and fabrication of new VIP biosensor for the rapid and selective detection of foot-and-mouth disease virus (FMDV) T ∗∗ Heba A. Husseina,c,1, Rabeay Y.A. Hassana,b,1, Rasha Mohamed El Nashard, , Samy A. Khalile, ∗ Sayed A. Salemc, Ibrahim M. El-Sherbinya, a Nanomaterials Laboratory, Center for Materials Science, Zewail City of Science and Technology, 6th October City, 12578, Giza, Egypt b Applied Organic Chemistry Department, National Research Centre (NRC), Dokki, 12622, Giza, Egypt c Virology Department, Animal Health Research Institute (AHRI), Agricultural Research Center (ARC), Egypt d Chemistry Department, Faculty of Science, Cairo University, Giza, 12613, Egypt e Microbiology Department, Faculty of Veterinary Medicine, Alexandria University, Egypt ARTICLE INFO ABSTRACT Keywords: Foot and mouth disease virus (FMDV), is a highly contagious virus due to its ease of transmission. FMDV has Foot and mouth disease virus (FMDV) seven genetically distinguished serotypes with many subtypes within each serotype. The traditional diagnostic Virus imprinted polymers (VIPs) methods of FMDV have demonstrated many drawbacks related to sensitivity, specificity, and cross-reactivity. In Screen printed electrode (SPE) the current study, a new viral imprinted polymer (VIP)-based biosensor was designed and fabricated for the Biomimetic virus biosensors rapid and selective detection of the FMDV. The bio-recognition components were formed via electrochemical polymerization of the oxidized O-aminophenol (O-AP) film imprinted with FMDV serotype O on a gold screen- printed electrode (SPE). The overall changes in the design template have been investigated using cyclic vol- tammetry (CV), atomic force microscopy (AFM), Field emission-scanning electron microscopy (FE-SEM), and Fourier-transform infrared spectroscopy (FT-IR).
    [Show full text]
  • Novel Microwire-Based Biosensor Probe for Simultaneous Real-Time Measurement of Glutamate and GABA Dynamics in Vitro and in Vivo
    www.nature.com/scientificreports OPEN Novel microwire‑based biosensor probe for simultaneous real‑time measurement of glutamate and GABA dynamics in vitro and in vivo P. Timothy Doughty1,4, Imran Hossain2,4, Chenggong Gong2, Kayla A. Ponder1, Sandipan Pati3, Prabhu U. Arumugam1,2* & Teresa A. Murray1* Glutamate (GLU) and γ-aminobutyric acid (GABA) are the major excitatory (E) and inhibitory (I) neurotransmitters in the brain, respectively. Dysregulation of the E/I ratio is associated with numerous neurological disorders. Enzyme‑based microelectrode array biosensors present the potential for improved biocompatibility, localized sample volumes, and much faster sampling rates over existing measurement methods. However, enzymes degrade over time. To overcome the time limitation of permanently implanted microbiosensors, we created a microwire-based biosensor that can be periodically inserted into a permanently implanted cannula. Biosensor coatings were based on our previously developed GLU and reagent-free GABA shank-type biosensor. In addition, the microwire biosensors were in the same geometric plane for the improved acquisition of signals in planar tissue including rodent brain slices, cultured cells, and brain regions with laminar structure. We measured real-time dynamics of GLU and GABA in rat hippocampal slices and observed a signifcant, nonlinear shift in the E/I ratio from excitatory to inhibitory dominance as electrical stimulation frequency increased from 10 to 140 Hz, suggesting that GABA release is a component of a homeostatic mechanism in the hippocampus to prevent excitotoxic damage. Additionally, we recorded from a freely moving rat over fourteen weeks, inserting fresh biosensors each time, thus demonstrating that the microwire biosensor overcomes the time limitation of permanently implanted biosensors and that the biosensors detect relevant changes in GLU and GABA levels that are consistent with various behaviors.
    [Show full text]
  • Strengthening Care Management with Health Information Technology a Learning Guide
    Strengthening Care Management with Health Information Technology A Learning Guide Presenting lessons learned by the 17 Beacon Community Awardees of the Office of the National Coordinator for Health Information Technology in the U.S. Department of Health and Human Services July 2013 i The Beacon Community Cooperative Agreement Program demonstrates how health IT investments and Meaningful Use of electronic health records (EHR) advance the vision of patient-centered care, while achieving the three-part aim of better health, better care at lower cost. The Department of Health and Human Services, Office of the National Coordinator for Health IT (ONC) is providing $250 million over three years to 17 selected communities throughout the United States that have already made inroads in the development of secure, private, and accurate systems of EHR adoption and health information exchange. Each of the 17 communities—with its unique population and regional context—is actively pursuing the following areas of focus: • Building and strengthening the health IT infrastructure and exchange capabilities within communities, positioning each community to pursue a new level of sustainable health care quality and efficiency over the coming years; • Translating investments in health IT to measureable improvements in cost, quality and population health; and • Developing innovative approaches to performance measurement, technology and care delivery to accelerate evidence generation for new approaches. For more information about the Beacon Community Program visit www.healthit.gov. This Learning Guide is part of the Beacon Nation project and is funded by the Hawai’i Island Beacon Community, an awardee of ONC Beacon Community Program. The Learning Guide was produced by Booz Allen Hamilton, under a contract with the Hawai’i Island Beacon Community.
    [Show full text]
  • How to Leverage Health Technology to Improve Patient Flow
    How to Leverage Health Technology to Improve Patient Flow 3/31/2017 A growing population has led to an increased demand for healthcare services. Concurrently, healthcare reforms and reimbursement requirements necessitate improvements in quality care and patient satisfaction. Healthcare facilities have begun searching for ways in which to handle the influx of patients without sacrificing either quality or the patient experience. How can your facility achieve increased volume and profits while maintaining quality and improving patient satisfaction? This whitepaper addresses how RTLS (Real Time Locating System) technology can be implemented to solve critical issues such as: · Increased capacity · Decreased waiting times · Patient and staff satisfaction · Increased healthcare staff productivity Increased Capacity The aging population in the United States is requiring more healthcare services. As the Baby Boomer population ages, almost twenty percent of the current population living in the United States will reach age 65 or older. This increase in the aging population leads to a significant growth in the number of individuals with chronic conditions. According to the American Hospital Association, the number of Boomers with multiple chronic conditions is continuing to grow and will reach about 37 million adults by 2030.i The prevalence of chronic conditions is also increasing in the United States population as a whole and calls for increased medical services and innovative approaches on how to properly deliver care to this population. Many healthcare delivery systems are utilizing RTLS technology to meet the increased population challenge. The Nor-Lea Medical Clinic in Lovington, New Mexico implemented an RTLS system to handle their growing influx of patients.
    [Show full text]
  • Space Biology Research and Biosensor Technologies: Past, Present, and Future †
    biosensors Perspective Space Biology Research and Biosensor Technologies: Past, Present, and Future † Ada Kanapskyte 1,2, Elizabeth M. Hawkins 1,3,4, Lauren C. Liddell 5,6, Shilpa R. Bhardwaj 5,7, Diana Gentry 5 and Sergio R. Santa Maria 5,8,* 1 Space Life Sciences Training Program, NASA Ames Research Center, Moffett Field, CA 94035, USA; [email protected] (A.K.); [email protected] (E.M.H.) 2 Biomedical Engineering Department, The Ohio State University, Columbus, OH 43210, USA 3 KBR Wyle, Moffett Field, CA 94035, USA 4 Mammoth Biosciences, Inc., South San Francisco, CA 94080, USA 5 NASA Ames Research Center, Moffett Field, CA 94035, USA; [email protected] (L.C.L.); [email protected] (S.R.B.); [email protected] (D.G.) 6 Logyx, LLC, Mountain View, CA 94043, USA 7 The Bionetics Corporation, Yorktown, VA 23693, USA 8 COSMIAC Research Institute, University of New Mexico, Albuquerque, NM 87131, USA * Correspondence: [email protected]; Tel.: +1-650-604-1411 † Presented at the 1st International Electronic Conference on Biosensors, 2–17 November 2020; Available online: https://iecb2020.sciforum.net/. Abstract: In light of future missions beyond low Earth orbit (LEO) and the potential establishment of bases on the Moon and Mars, the effects of the deep space environment on biology need to be examined in order to develop protective countermeasures. Although many biological experiments have been performed in space since the 1960s, most have occurred in LEO and for only short periods of time. These LEO missions have studied many biological phenomena in a variety of model organisms, and have utilized a broad range of technologies.
    [Show full text]
  • Current Biosensor Technologies in Drug Discovery
    Biosensor 5/7/06 12:37 Page 68 Assays Current biosensor technologies in drug discovery By Dr Matthew A. Over the past two decades the benefits of biosensor analysis have begun to Cooper make an impact in the market, and systems are beginning to be used as mainstream research tools in many laboratories1,2. Biosensors are devices that use biological or chemical receptors to detect analytes in a sample.They give detailed information on the binding affinity, and in many cases also the binding kinetics of an interaction.Typically, the receptor molecule must be connected in some way to a transducer that produces an electrical signal in real-time. Label- free biosensors do not require the use of reporter elements (fluorescent, luminescent, radiometric, or colorimetric) to facilitate measurements. Detailed information on an interaction can be obtained during analysis while minimising sample processing requirements and assay run times3. Unlike label- and reporter-based technologies that simply confirm the presence of the detector molecule, label-free techniques can provide direct information on analyte binding to target molecules typically in the form of mass addition or depletion from the surface of the sensor substrate, or measuring changes in the heat capacity of a sample4. However, these technologies have failed to gain widespread acceptance due to technical constraints, low throughput, high user expertise requirements, and cost.While they can be powerful tools in the hands of a skilled user evaluating purified samples, they are not readily adapted to every day lab use where simple to understand results on high numbers of samples are the norm.This article seeks to address some of the issues surrounding the un-met needs in the market place, and the difficulties faced by technology developers in meeting these needs with innovative products.
    [Show full text]
  • Biomedical Engineering (BMD ENG) 1
    Biomedical Engineering (BMD_ENG) 1 Through the course, students will learn how to apply these experimental BIOMEDICAL ENGINEERING and computational genomics technologies to study gene expression regulation underlying various biological processes, such as oncogenesis. (BMD_ENG) Students will also apply computational and statistical skills, using linux and R/Matlab/Python. BMD_ENG 101-0 Introduction to Biomedical Engineering (0 Unit) BMD_ENG 317-0 Biochemical Sensors (1 Unit) Information to 1) help students determine if BME is the right major Theory, design, and applications of chemical sensors used in medical for them and 2) learn how to make the most of their undergraduate diagnosis and patient monitoring. Electrochemical and optical sensors. experience. The field of biomedical engineering, career and research Prerequisites: BIOL_SCI 215-0; BIOL_SCI 219-0; CHEM 210-1; opportunities, ethics. PHYSICS 135-2; PHYSICS 135-3. BMD_ENG 207-0 BME Lab: Experimental Design (0.5 Unit) A laboratory BMD_ENG 323-0 Visual Engineering Science (1 Unit) course focusing on quantitative physiological measurements Mammalian visual system. Physiological optics. Visual image and analyses, instrument characterization, statistical design of representation and interpretation. Visual adaptation. Motion. Color vision. experiments, and training in preparation and organization of laboratory Prerequisite: PHYSICS 135-2. notes and reports. Prerequisite: BMD_ENG 220-0 or IEMS 303-0 or MECH_ENG 359-0. BMD_ENG 325-0 Introduction to Medical Imaging (1 Unit) Diagnostic X-rays; X-ray film and radiographic image; computed BMD_ENG 220-0 Introduction to Biomedical Statistics (1 Unit) Basic tomography; ultrasound. statistical concepts presented with emphasis on their relevance to Prerequisite: PHYSICS 135-3 or equivalent. biological and medical investigations.
    [Show full text]
  • The Application of Whole Cell-Based Biosensors for Use in Environmental Analysis and in Medical Diagnostics
    sensors Review The Application of Whole Cell-Based Biosensors for Use in Environmental Analysis and in Medical Diagnostics Qingyuan Gui 1, Tom Lawson 2, Suyan Shan 1, Lu Yan 1 and Yong Liu 1,* 1 Laboratory of Nanoscale Biosensing and Bioimaging, Instiute of Advanced Materials for Nano-Bio Applications, School of Ophthalmology and Optometry, Wenzhou Medical University, 270 Xueyuanxi Road, Wenzhou 325027, China; [email protected] (Q.G.); [email protected] (S.S.); [email protected] (L.Y.) 2 ARC Center of Excellence for Nanoscale BioPhotonics, Macquarie University, Sydney, NSW 2109, Australia; [email protected] * Correspondence: [email protected]; Tel.: +86-577-8806-7973 Received: 11 May 2017; Accepted: 8 July 2017; Published: 13 July 2017 Abstract: Various whole cell-based biosensors have been reported in the literature for the last 20 years and these reports have shown great potential for their use in the areas of pollution detection in environmental and in biomedical diagnostics. Unlike other reviews of this growing field, this mini-review argues that: (1) the selection of reporter genes and their regulatory proteins are directly linked to the performance of celllular biosensors; (2) broad enhancements in microelectronics and information technologies have also led to improvements in the performance of these sensors; (3) their future potential is most apparent in their use in the areas of medical diagnostics and in environmental monitoring; and (4) currently the most promising work is focused on the better integration of cellular sensors with nano and micro scaled integrated chips. With better integration it may become practical to see these cells used as (5) real-time portable devices for diagnostics at the bedside and for remote environmental toxin detection and this in situ application will make the technology commonplace and thus as unremarkable as other ubiquitous technologies.
    [Show full text]
  • Two-Dimensional Nanostructures for Electrochemical Biosensor
    sensors Review Two-Dimensional Nanostructures for Electrochemical Biosensor Reem Khan 1 , Antonio Radoi 2 , Sidra Rashid 3, Akhtar Hayat 3 , Alina Vasilescu 4 and Silvana Andreescu 1,* 1 Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY 13699, USA; [email protected] 2 National Institute for Research and Development in Microtechnology—IMT Bucharest, 126A Erou Iancu Nicolae Street, 077190 Voluntari, Romania; [email protected] 3 IRCBM, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan; [email protected] (S.R.); [email protected] (A.H.) 4 International Centre of Biodynamics, 1B Intrarea Portocalelor, 060101 Bucharest, Romania; [email protected] * Correspondence: [email protected] Abstract: Current advancements in the development of functional nanomaterials and precisely designed nanostructures have created new opportunities for the fabrication of practical biosensors for field analysis. Two-dimensional (2D) and three-dimensional (3D) nanomaterials provide unique hierarchical structures, high surface area, and layered configurations with multiple length scales and porosity, and the possibility to create functionalities for targeted recognition at their surface. Such hierarchical structures offer prospects to tune the characteristics of materials—e.g., the electronic properties, performance, and mechanical flexibility—and they provide additional functions such as structural color, organized morphological features, and the ability to recognize and respond to external stimuli. Combining these unique features of the different types of nanostructures and using them as support for bimolecular assemblies can provide biosensing platforms with targeted Citation: Khan, R.; Radoi, A.; Rashid, S.; Hayat, A.; Vasilescu, A.; recognition and transduction properties, and increased robustness, sensitivity, and selectivity for Andreescu, S. Two-Dimensional detection of a variety of analytes that can positively impact many fields.
    [Show full text]