112,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: IEEE Press Series on Sensors
- Sprache: Englisch
Comprehensive resource covering new technologies, materials, strategies, and recent advancements in the field of biosensing
Biosensors summarizes cutting-edge technologies in biosensing, including gene editing (known as Clustered Regularly Interspaced Short Palindromic Repeat or CRISPR), quorum sensing utilizing inter and intra cell signals, two-dimensional (2D) materials and aptamer-mediated sensor designs, and more, with additional coverage of the latest materials, strategies, and advancements made in the field.
Chapters are categorized on the basis of various bio-recognition elements that include aptamer, nucleic acid, enzymes, antibodies, bacteriophages, peptides, and molecular imprinted polymers. Plasmonic, surface-enhanced Raman scattering, colorimetric, fluorescence, electrochemical, magneto and piezo-electric biosensor sensing techniques are also considered. The roles of various nanomaterials, advancement in synthesis, signal enhancement strategies, and new trends for biomedical applications are also described. Current challenges, limitations, and future prospects to developing biosensors for point-of-care and clinical applications are also discussed.
Written by three highly qualified authors, Biosensors includes information on:
- Diverse bio-receptors include nucleic acids, aptamers, enzymes, antibodies, bacteriophages, molecularly imprinted polymers, whole-cell, and techniques of immobilization
- Different transduction principles using bio-receptors (e.g., optical, electrochemical, piezo-electrical, and SERS) to detect microorganism, toxins, and diseases
- Nanomaterials synthesis, their role in biosensing, pros and cons of carbon, polymer, metals, metal oxides, and quantum dots-based nanomaterials in medical biosensing applications
Biosensors is a comprehensive and complete resource on the subject for researchers and professionals in physics, chemistry, and biomedical science, research communities working in the fields of plasmonics, optics, biosensors, and nano-photonics, and students in related programs of study.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 487
Veröffentlichungsjahr: 2024
Ähnliche
Table of Contents
Cover
Table of Contents
Series Page
Title Page
Copyright Page
About the Authors
Preface
Acknowledgments
List of Abbreviations
About the Companion Website
1 Fundamentals of Biomedical Sensors
1.1 Introduction
1.2 Classification of Biosensors
1.3 Elements of Biosensors
1.4 Bio‐recognition Elements
1.5 Sensing Techniques
References
2 Immobilization Techniques for Bioreceptors
2.1 Introduction
2.2 Requirements of Immobilization
2.3 Immobilization Methods
2.4 Materials Used in Different Immobilization Techniques and Supports
2.5 Future Prospects and Possibilities in Immobilization Technology
2.6 Summary
References
3 Nucleic Acid–Based Biosensors
3.1 Introduction
3.2 ECL Biosensor Designs
3.3 Nucleic Acid–Based Colorimetric Biosensors
3.4 Nucleic Acid–Based Fluorescent Biosensor
3.5 Nucleic Acid–Based Plasmonic Biosensor
3.6 SERS‐Based Nucleic Acid Biosensors
3.7 Interferometric NA Biosensors
3.8 Conclusions and Future Prospects
References
4 Antibody‐Based Biosensors
4.1 Polyclonal Antibody and Monoclonal Antibody
4.2 Cardiovascular Biomarker, Autoimmune Disorder, and Cholesterol Biomarker
4.3 Conclusions and Future Directions
References
5 Aptamer‐Based Biosensors
5.1 Introduction
5.2 Selection of Aptamers and Design Strategies
5.3 Sepsis, Pathogens, and Biomarkers to Detect Disease and Pollutants
5.4 Small Biomolecules
5.5 Summary
References
6 Bacteriophage‐Based Biosensors
6.1 Introduction
6.2 Design of Bacteriophage‐Based Biosensor
6.3 Future Prospects
6.4 Summary
References
7 Peptide‐Based Biosensors
7.1 Introduction
7.2 Synthesis Methods
7.3 Summary
References
8 Synthetic BREs and Smart Nanomaterial‐Based Biosensors
8.1 MIPs as Bioreceptors and Their Applications
8.2 Nanomaterials‐Based Sensors
8.3 Summary
References
9 Advancement in Optical Biosensors to Detect Malignant Tumors
9.1 Introduction
9.2 Cancer Biomarkers
9.3 Types of Optical Biosensors
9.4 Challenges and Future Prospects
9.5 Summary
References
Index
IEEE Press Series on Sensors
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Advantages and drawbacks associated with immobilization technique...
Table 2.2 Classification of support materials used in immobilization method...
Table 2.3 Various reported biosensors based on different support materials ...
Table 2.4 Reported ECL, optical, and mass‐based biosensors, analytes, immob...
Chapter 3
Table 3.1 Recently reported nucleic acid–based ECL biosensors.
Table 3.2 Recently reported nucleic‐acid based colorimetric biosensors.
Table 3.3 Recently reported nucleic acid–based fluorescence biosensors.
Table 3.4 Recently reported nucleic‐acid‐based plasmonic biosensors.
Chapter 4
Table 4.1 Cardiovascular, autoimmune disorder, and cholesterol biomarkers....
Table 4.2 Recent optical, ECL and mass‐based biosensors to detect the cance...
Table 4.3 Biosensor for tuberculosis detection.
Table 4.4 Recently reported biosensor designs to detect the cardiovascular ...
Table 4.5 Biosensor designs to detect the autoimmune diseases.
Table 4.6 Recently reported immunosensors for stress related diseases.
Table 4.7 Antibody‐based biosensor designs for cholesterol detection.
Table 4.8 Performance study of biosensors for glucose detection.
Table 4.9 Detection of different bacteria with various sensing schemes.
Table 4.10 Nanomaterials integrated with ECL and optical biosensors for AFB
Chapter 5
Table 5.1 Various nanomaterial‐based platforms for aptamer selection throug...
Table 5.2 Recently reported aptamer‐based ECL biosensors on different sensi...
Table 5.3 Toxins and their examples reported using different sensing platfo...
Table 5.4 Aptamer‐based biosensors on different sensing platforms to detect...
Chapter 6
Table 6.1 Common orders and families of bacteriophages, their morphology, e...
Table 6.2 Comparison of immobilization techniques for bacteriophages [27–33...
Table 6.3 Recently reported bacteriophage‐based ECL, optical, and piezoelec...
Chapter 7
Table 7.1 Recently reported peptide‐based ECL biosensors.
Table 7.2 Recently reported peptide‐based plasmonic biosensors.
Table 7.3 Recently reported peptide‐based plasmonic and ECL biosensors.
Table 7.4 Recently reported peptide‐based plasmonic biosensors.
Table 7.5 Recently reported peptide‐based colorimetric biosensors.
Table 7.6 Summary of recently reported peptide‐based interferometric biosen...
Table 7.7 Recently reported peptide‐based SERS biosensors.
Chapter 8
Table 8.1 Summary of recently reported biosensors using different MIP metho...
Table 8.2 Summary of various metal and metal‐oxide nanomaterial‐based senso...
Table 8.3 Summary of various carbon‐nanomaterial‐based sensors.
Table 8.4 Magnetic, 2D nanomaterials, quantum dots, and polymer nanomateria...
Table 8.5 Sensor design with target for magnetic, 2D nanomaterials, quantum...
Table 8.6 Summary of commercially available nanomaterials‐based wearable se...
Chapter 9
Table 9.1 Commonly used biomarkers associated with cancer.
Table 9.2 Nanomaterials‐based sensors.
List of Illustrations
Chapter 1
Figure 1.1 An illustration of components of a sensor structure.
Figure 1.2 A schematic illustration of year‐wise progress made in the field ...
Figure 1.3 Commercialization and market pull of different types of biosensor...
Figure 1.4 Schematic design of the (a) biosensor components (b) different an...
Figure 1.5 Stepwise diagram of the SELEX technique to choose the specific ap...
Figure 1.6 Structure of a Y‐shaped antibody.
Figure 1.7 Graphic illustration of the F5‐4 bacteriophage‐based colorimetric...
Figure 1.8 Graphic illustration of (a) various steps involved in covalent an...
Figure 1.9 Biosensor design based on whole cell.
Figure 1.10 A fluorescent polymer dot‐manganese oxide complex–based ECL sens...
Figure 1.11 Schematic illustration of (a) surface plasmons existence at the ...
Figure 1.12 Schematic of light coupling in a plasmonic‐based sensor using (a...
Figure 1.13 Schematic of fiberoptic configuration.
Figure 1.14 Schematic of (a) MZI‐based biosensor design.(b) FPI sensor....
Figure 1.15 Schematic of AuNPs and aptamer‐based colorimetric biosensor desi...
Figure 1.16 Schematic illustration of (a) label‐free and (b) labeled SERS bi...
Figure 1.17 Schematic picture of a fluorescence‐based sensing mechanism that...
Figure 1.18 Schematic demonstration of different types of PCFs for numerous ...
Figure 1.19 Schematic of frequency vs. time plot and structure of Au and qua...
Chapter 2
Figure 2.1 The schematic of year‐wise progress of immobilization techniques....
Figure 2.2 Classification of different techniques for bioreceptor immobiliza...
Figure 2.3 The schematic illustration of adsorption immobilization includes ...
Figure 2.4 Schematic illustration of (a) entrapment and (b) covalent immobil...
Figure 2.5 Schematic illustration of (a) HRP enzyme through covalent immobil...
Figure 2.6 Lactate dehydrogenase /pyruvate oxidase using cross‐linking immob...
Figure 2.7 Schematic depiction of the hydrogel‐based ECL sensor for HER2 det...
Figure 2.8 Numbers of articles published on different platforms based on bio...
Chapter 3
Figure 3.1 Schematic of structure of human genome DNA and RNA molecules with...
Figure 3.2 Schematic of (a) a dual‐target responsive ECL sensor for COVID‐19...
Figure 3.3 Schematic of (a) hairpin DNA‐AuNPs conjugates colorimetric sensor...
Figure 3.4 Schematic of (a) fluorescent biosensor assisted with polymerase c...
Figure 3.5 Schematic of (a) Ag‐MoS
2
‐graphene hybrid SPR biosensor.(b) Tr...
Figure 3.6 Schematic of (a) Au@Ag@4MBA@5’‐NH
2
‐ssDNA probe‐based SERS sensor....
Figure 3.7 (a) Schematic diagram of the MZI fiber surface modification proce...
Chapter 4
Figure 4.1 Schematic of immunoglobulin with heavy and light chains, variable...
Figure 4.2 Schematic of (a) antibody‐based multicore fiber LSPR sensor.(...
Figure 4.3 Schematic illustration of an Au screen‐printed electrode and an a...
Figure 4.4 Illustration of a graphene quantum dots (GQD)‐polyamidoamine nano...
Chapter 5
Figure 5.1 Schematic diagram of (a) SELEX and non‐SELEX methods to select th...
Figure 5.2 Schematic diagram of (1) click particle display that enriches apt...
Figure 5.3 Schematic illustration of single‐pot SELEX to detect estradiol, p...
Figure 5.4 Depiction of switching aptamers via SELEX and non‐SELEX method th...
Figure 5.5 Representation of aptamers structures (a) hairpin or stem loop (b...
Figure 5.6 Schematic illustration of split aptamers.
Figure 5.7 Schematic diagram of approaches to isolate the specific and nonsp...
Figure 5.8 Schematic diagram of (a) polymer‐QD and nanocomposite‐based ECL s...
Figure 5.9 Schematic drawing of the (a) coccolith‐based aptamer‐based ECL bi...
Chapter 6
Figure 6.1 Schematic illustration of (a) different stages of the lytic and l...
Figure 6.2 Structure of phage receptor‐binding proteins.
Figure 6.3 Schematic illustration of (a) SiO
2
‐ and AuNP‐based core‐shell‐str...
Figure 6.4 Schematic illustration of the (a) fluoro‐peptide‐graphene oxide n...
Figure 6.5 Design of (a) engineered bacteriophage Genome to detect
E. coli
a...
Figure 6.6 Schematic depiction of (a) R3#10 phage bacteriophage‐based ECL bi...
Figure 6.7 A schematic illustration of the (a) M13 phage‐based ECL sensor to...
Chapter 7
Figure 7.1 Schematic illustration of various steps involved in commonly used...
Figure 7.2 Schematic of HER2 detection using PEDOT and AuNPs ECL biosensor....
Figure 7.3 Schematic of ECL biosensor (a) (b) synthesis of peptide‐Lum‐AuNPs...
Figure 7.4 Schematic illustration of (A) platelet‐derived growth factor ‐BB ...
Figure 7.5 Schematic of (a) pre‐immobilized and post‐immobilized method used...
Figure 7.6 Schematic of aptamer‐AuNPs‐peptide‐based colorimetric biosensors ...
Figure 7.7 Schematic illustration of the (a) fluorescent biosensor for HER2 ...
Figure 7.8 Schematic diagram of (a) pyridine‐AgNRs‐based M‐SERS sensor.(...
Chapter 8
Figure 8.1 Schematic of fabrication and stepwise details of MIP.
Figure 8.2 Classification of nanomaterials used in optical platforms to dete...
Figure 8.3 Schematic illustration of Au and platinum with metal‐organic fram...
Figure 8.4 Schematic of (a) AuNPs modified SERS sensor to detect the S. typh...
Chapter 9
Figure 9.1 An illustration of various types of nanoparticles that include or...
Figure 9.2 Schematic representation of (a) a MIM nano‐disk‐based LSPR cancer...
Figure 9.3 Schematic representation of (a) amplification process using dual ...
Figure 9.4 Graphic illustration of (a) pH colorimetric‐based aptasensor....
Figure 9.5 Illustration of a (a) fluorescent biosensor that consist of graph...
Figure 9.6 Illustration of (a) an optical fiber surface and functionalized A...
Figure 9.7 Biosensor structure of (a) a polymer imprinted SERS sensor.(b...
Figure 9.8 Schematic illustration of the photonic crystal and two MIM plasmo...
Guide
Series Page
Cover Page
Table of Contents
Series Page
Title Page
Copyright Page
About the Authors
Preface
Acknowledgments
List of Abbreviations
About the Companion Website
Begin Reading
Index
WILEY END USER LICENSE AGREEMENT
Pages
ii
iii
iv
ix
x
xi
xiii
xiv
xv
xvi
xvii
xviii
xix
xx
xxi
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
IEEE Press445 Hoes LanePiscataway, NJ 08854
IEEE Press Editorial BoardSarah Spurgeon, Editor‐in‐Chief
Moeness AminJón Atli BenediktssonAdam DrobotJames Duncan
Ekram HossainBrian JohnsonHai LiJames LykeJoydeep Mitra
Desineni Subbaram NaiduTony Q. S. QuekBehzad RazaviThomas RobertazziDiomidis Spinellis
Biosensors
Nanomaterials, Approaches, and Performance‐Enhancement Strategies
Baljinder Kaur
Department of Physics, Madhav Institute of Technology & ScienceGwalior, Madhya Pradesh, India
Santosh Kumar
Department of Electronics and Communication Engineering, KoneruLakshmaiah Education Foundation Deemed to be University,Vaddeswaram, Guntur, India
Brajesh Kumar Kaushik
Department of Electronics and Communication EngineeringIndian Institute of Technology Roorkee, Roorkee, India
Copyright © 2025 by The Institute of Electrical and Electronics Engineers, Inc.All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per‐copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750‐8400, fax (978) 750‐4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748‐6011, fax (201) 748‐6008, or online at http://www.wiley.com/go/permission.
Trademarks: Wiley and the Wiley logo are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates in the United States and other countries and may not be used without written permission. All other trademarks are the property of their respective owners. John Wiley & Sons, Inc. is not associated with any product or vendor mentioned in this book.
Limit of Liability/Disclaimer of WarrantyWhile the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762‐2974, outside the United States at (317) 572‐3993 or fax (317) 572‐4002.
Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our website at www.wiley.com.
Library of Congress Cataloging‐in‐Publication Data Applied for:
Hardback ISBN: 9781394268207
Cover Design: WileyCover Image: © zf L/Getty Images
About the Authors
Baljinder Kaur received her Doctorate of Philosophy (PhD) in 2020 from the National Institute of Technology, Delhi, India. She completed her Post‐Doctoral Fellowship in 2023 at the Indian Institute of Technology, Roorkee, India. She is currently an assistant professor in the Department of Physics at Madhav Institute of Technology & Science, Gwalior, Madhya Pradesh, India. She has published more than 30 research articles in national and international SCI journals. Her research interests include plasmonic sensors, optical device modelling, fiber optics, and 2D materials.
Santosh Kumar (Fellow of SPIE) received his PhD degree from IIT (ISM) Dhanbad, Dhanbad, India, in 2014. He was with Liaocheng University, Liaocheng, China, from 2018 to 2023. He is currently a professor in the Department of Electronics and Communication Engineering at Koneru Lakshmaiah Education Foundation, Vaddeswaram, India. He has been recognized as one of the worlds’s top 2% scientists by Stanford University during the last three consecutive years. With extensive research experience, he has supervised 20 MTech dissertations and 7 PhD candidates. His contributions to the field include the publication of over 400 research articles in prestigious SCI journals and conferences, with more than 8000 citations and an H‐index of 55. His work has been featured in renowned journals such as Biosensors and Bioelectronics, Journal of Lightwave Technology, Optics Express, Optics Letters, Applied Physics Letters, ACS Applied Nano Materials, and Biosensors, and various IEEE Transactions. He has presented his research at conferences across in India, China, Belgium, and the USA, demonstrating his global reach. He is the author of four scholarly books published under CRC Press (Taylor & Francis) and Springer Nature. He was recently granted a patent application for his groundbreaking optical fiber‐sensing technology. As a highly regarded expert, he has reviewed over 2200 manuscripts for esteemed SCI journals published by IEEE, Elsevier, Springer, OPTICA, SPIE, and Nature. With expertise in electronics, communications engineering, and physics, his research focuses on WaveFlex biosensors, fiberoptic sensors, photonics and plasmonic devices, nano‐ and biophotonics, waveguides, interferometers, and the Internet of Things. Through fruitful collaborations with renowned universities in India, China, Portugal, Brazil, and Italy, he conducts cutting‐edge scientific research.
Dr. Kumar is a Fellow of SPIE, a Life Fellow member of the Optical Society of India (OSI), and a senior member of IEEE, OPTICA, and SPIE. He also serves as an OPTICA traveling lecturer. Recognizing his contributions, he has been appointed as the Chair of the Optica Optical Biosensor Technical Group and as an associate editor for IEEE Sensors Journal,IEEE Internet of Things Journal, and Biomedical Optics Express.
Brajesh Kumar Kaushik received his Doctorate of Philosophy (PhD) in 2007 from the Indian Institute of Technology, Roorkee, India. He joined the Department of Electronics and Communication Engineering, Indian Institute of Technology, Roorkee, as an assistant professor in December 2009; promoted to associate professor in April 2014; and since August 2020, he has been serving as a full professor. He had been a visiting professor at TU‐Dortmund, Germany, in 2017; McGill University, Canada, in 2018; and Liaocheng University, China, in 2018. He served as a visiting lecturer of SPIE Society to deliver lectures in the area of spintronics and optics to SPIE chapters located across the world. He regularly serves as general chair, technical chair, and keynote speaker at reputed international and national conferences. He also served as the chairman and vice chairman of IEEE Roorkee Sub‐section. Dr. Kaushik is a senior member of IEEE and a member of many expert committees constituted by government and nongovernment organizations. He is currently serving as a distinguished lecturer (DL) for the IEEE Electron Devices Society (EDS) to offer EDS chapters with quality lectures in his research domain. He is editor‐in‐chief of the Elsevier Journal, Memories – Materials, Devices, Circuits and Systems; an editor for IEEE Transactions on Electron Devices; an associate editor for the IEEE Sensors Journal and IET Circuits, Devices & Systems; an editor for Microelectronics Journal, Elsevier; and an editorial board member for Circuit World, Emerald. He is among the top 2% scientists in world as per Stanford University reports in 2019 and 2021. He is currently serving as a member of two technical committees – namely, Spintronics (TC‐5) and Quantum Computing, Neuromorphic Computing and Unconventional Computing (TC‐16) of IEEE Nanotechnology Council. He is also the regional coordinator (R10) for IEEE Nanotechnology Council chapters. He has 12 books to his credit, published by reputed publishers such as CRC Press, Springer, Artech, and Elsevier. One his books, titled Nanoscale Devices: Physics, Modeling, and Their Application, CRC Press, won the 2018 Outstanding Book and Digital Product Award in the Reference/Monograph Category from the Taylor and Francis Group. He has attained fellowships and awards from DAAD, Shastri Indo‐Canadian Institute (SICI), ASEM Duo, and the United States–India Educational Foundation (Fulbright‐Nehru Academic and Professional Excellence). His research interests are in the areas of high‐speed interconnects, optics‐ and photonics‐based devices, image processing, spintronics‐based devices, circuits, and computing.
Preface
Due to advancement of new technologies in synthesis methods, the biosensing field has emerged as a promising tool in diverse fields that include healthcare, environmental monitoring, food, and agriculture industry. The need of early diagnosis of globally spread deadly diseases, such as cancer, tuberculosis, and cardiovascular disease, has increased the demand for rapid, cost‐effective, highly sensitive, and accurate methods and devices.
This book embarks on a journey through the captivating progress made in biosensors to detect various diseases on the basis of bio‐recognition elements. Nucleic acid, enzyme, aptamer, antibodies, bacteriophages, peptides, and synthetic molecular imprinted polymer‐based sensor design in optical, electrochemical, and mass‐based biosensors are discussed for different biomedical applications. More precisely, sensing techniques include plasmonic surface plasmon resonance (SPR)/localized (L) SPR sensors, surface‐enhanced Raman scattering (SERS), colorimetric, fluorescence, electrochemical, magneto, and piezoelectric biosensors to detect the different biosamples will be discussed in detail.
The chapters are divided on the basis of bioreceptors and new nanomaterials that cover recent advances in diseased detection using various biosensor design that are not summarized in a single book in the previously published reviews. This book also focuses on advancements in nanostructured materials synthesis, signal enhancement strategies, and biomarker detection the diseases such as cancer, pathogenic bacterial infection, and tuberculosis. It also includes the main challenges, limitations, and future prospects to develop the biosensor for point‐of‐care and clinical applications. The cons and pros of each technique and bio‐receptors are discussed in a summary section.
This book will be of interest to researchers in the fields of physics, chemistry, and biomedical science and a broad audience of researchers and experts in the diagnostic and analytical industry. We envisage that people working in medical diagnostics, biosensors, environmental and food safety monitoring, electronics and material engineers, defense/homeland security, and professors/postgraduate students in these sectors will benefit greatly by reading this book. Therefore, this book will attract the attention of various industries and researchers that will help to improve the performance of sensors. The new technologies include gene editing known as clustered regularly interspaced short palindromic repeat (CRISPR), quorum sensing that utilizes inter‐ and intra‐cell signal, two‐dimensional (2D) materials, and aptamer‐mediated sensor designs with high performance and low detection limits required in case of bio‐samples; these are discussed in detail.
Outline of This Book
This book provides a comprehensive overview of recent advancements in biomedical sensors. It includes advanced materials and various enhancement strategies to improve the performance of different biosensing platforms. It presents an exploration of ECL, mass‐based biosensors, and optical biosensor technologies grounded in resonance, absorption, interference, fluorescence, and scattering. This book provides an overview of the innovations and their applications, as well as future perspectives and insights to ensure reader’s confidence and enhance knowledge in the biosensing field. It also covers the immobilization methods used in industry and the lab to fabricate different bioreceptor‐based biosensor structures.
The book provides readers with deep knowledge regarding nanomaterial‐based biosensors to detect biomarkers and pathogens associated with diseases that spread throughout the world. This book will be of interest to researchers in the fields of physics, chemistry, and biomedical science, and to people working in medical diagnostics, biosensors, environmental and food safety monitoring, electronics and material engineers, defense, and homeland security. Professors and postgraduate students in these sectors will greatly benefit from reading it. Examples are usually pulled from everyday life and recent advancements in plasmonic biosensing devices to pique the readers' interest and make them eager to learn more. Following are descriptions of the book's outline.
Chapter 1 introduces biosensors, constituents, and operating principles. This chapter will give insight on bioreceptor types and their role in the detection process of various sensing schemes. Various biosamples, including cancer cells, tuberculosis, and infectious pathogens, are discussed, as well as various signal enhancement strategies and nanomaterials.
Thereafter, Chapter 2 introduces the currently and previously used immobilization techniques used to immobilize antibodies, aptamers, cells, nucleic acids, bacteriophages, enzymes, and imprinted polymers. It focuses on adsorption or electrostatic interaction, covalent binding, entrapment, cross‐linking‐based immobilization techniques, and the battle among them toward the selection of a method to immobilize a specific bioreceptor. It also demonstrates the details and properties of different materials used as supports, such as glass, polymers, hydrogels, self‐assembled monolayers (SAM), metals, nanoparticles, and membranes. It also summarizes the recently reported ECL, optical, and mass‐based biosensors that use different immobilized methods for each receptor in the different biosensing applications.
Chapter 3 discusses recent developments in biosensors for detecting various diseases in food, beverages, and clinical samples using nucleic acid‐based sensor technology. It provides a summary of the different types of aptamer‐based biosensors (e.g. optical, ECL, piezoelectrical, and SERS) for the detection of microorganisms, toxins, and diseases.
Chapter 4 discusses the development of antibody‐based optical sensor designs for detecting cancerous cell lines, highlighting the various sensor types. The possibilities of integration of these biosensors, point‐of‐care testing, and the emergence of new materials that include black phosphorus, phosphorene, silicene, Mxenes, immobilization methods, synthesis methods, and gene editing technologies are addressed. Additionally, the disadvantages of antibodies and the benefits of aptamers over antibodies are discussed.
Chapter 5 discusses the development of biosensor technologies based on small and 3D‐shaped aptamers as compared to bulky antibodies that can surpass conventional in vitro diagnostics for disease detection and health monitoring. It explores the criteria to choose the target‐specific aptamer and design strategies from the pool of aptamers through the SELEX method. It also discusses section‐wise details of various types of SELEX and non‐SELEX methods and steps involved in aptamer synthesis.
Chapter 6 discusses the bacteriophage‐based biosensor designs, structure, family of phages used to specifically detect viruses, bacteria, and microorganisms related to various diseases. The chapter presents a comparative study of bacteriophage‐based and traditional bacterial detection methods. It includes the details of reporter, stained, lytic, capturing, and receptor‐binding protein‐based probes. As this technology is still limited to the detection of microorganisms, its possibilities to explore other analytes have been discussed.
Chapter 7 discusses a peptide‐based biosensor to detect analytes. It also provides an overview of the operating principle, the synthesis of peptides, and their use in the fabrication of sensors. This chapter examines the function of peptides as specific sequence cleavers, hydroxyl group phosphorylation catalysts, and antifouling agents in biosensors.
Chapter 8 discusses synthetic BRE, such as molecule imprinted polymers, and several nanomaterials‐based biosensor designs for detecting various diseases, biomolecules, and other infected biosamples. It is concerned with the advantages and disadvantages of carbon, polymers, metals, metal oxides, and quantum dot‐based nanomaterials in medical biosensing applications. A section also discusses the challenges and developments in the field of wearable biosensors to detect diseases.
Chapter 9 discusses the role of novel nanomaterials and advancements in optical biosensors for cancer detection due to the increased incidence of cancer‐related diseases. It also illustrates various types of nanoparticles, including organic and inorganic, with different optical platforms to detect cancer‐related diseases. Table 9.1 summarizes various biosensors designed to detect cancer. In addition, the chapter presents future development directions and characteristics of the next generation of paper‐based devices.
Baljinder Kaur
Santosh Kumar
Brajesh Kumar Kaushik
Acknowledgments
The authors wish to extend their heartfelt appreciation to IEEE‐Wiley Press, especially the editor, who diligently polished the book for its publication. Apart from the contributions of a solitary individual, the accomplishment of research work is dependent on the motivation, support, effective input, discussion, and guidance provided by the experts, and colleagues. It has been a great pleasure working with them, and we trust they feel the same, too.
Baljinder Kaur extends her wholehearted and deep gratitude to Prof. B. K. Kaushik and Prof. Santosh Kumar for their priceless mentorship, motivation, guidance, and unwavering backing during the write‐up of this book. Dr. Kaur would also like to express her deep sense of appreciation to her family and friends for their constant support, encouragement, and cooperation.
Santosh Kumar would like to express his sincere gratitude to Shri Koneru Satyanarayana Garu, honorable president of the Koneru Lakshmaiah Education Foundation (deemed to be University), Vaddeswaram, Andhra Pradesh, India, for his immense encouragement and support throughout the writing of this book. Dr. Kumar would also like to express his heartfelt gratitude to his wife, Dr. Ragini Singh, and son, Ayaansh Singh, for their unwavering support, encouragement, and cooperation, as well as to his loving parents.
Brajesh Kumar Kaushik acknowledges the relentless efforts made by the co‐authors in bringing this book to the final stage. The support provided by the Indian Institute of Technology‐Roorkee is also highly acknowledged. This book is dedicated to all the friends and family members – especially to my mother, Mrs. Karuna Kaushik; wife, Dr. Supriya Kaushik; and son, Partha Kaushik for their unwavering support and understanding.
We hope that this book serves as a foundation for future advancements in the field and serves as a valuable reference for engineers, researchers, and students working in the fields of nano‐optics, nano‐photonics, plasmonics, and optical fiber biosensors in general.
List of Abbreviations
2D
Two‐dimensional
AEM
Absorption enhancement material
Al
2
O
3
Aluminum oxide
BRE
Bio‐recognition element
BSA
Bovine serum albumin
CaF
2
Calcium fluoride
CRISPR
Clustered regularly interspaced short palindromic repeats
D.A.
Detection accuracy
DNA
Deoxyribonucleic acid
E. Coli
Escherichia Coli
ECL
Electrochemical
ELISA
Enzyme‐linked immunosorbent assays
EW
Evanescent wave
FRET
Förster resonance energy transfer
FPI
Fabry–Perot
FOM
Figure of merit
FWHM
Full width at half maximum
HRP
Horseradish peroxidase
IR
Infrared
LSPR
Localized surface plasmon resonance
LOD
Limit of detection
MIP
Molecular imprinted polymer
MoS
2
Molybdenum disulfide
MoSe
2
Molybdenum diselenide
MZI
Mach–Zehnder interferometer
NIR
Near infrared
NA
Nucleic acids
NP
Nanoparticle
ORD
Optimum radiation damping
PathoBact
Pathogenic bacteria
PCF
Photonic crystal‐fiber
PF
Perfluorinated
PT
Polythiophene
RI
Refractive index
RIU
Refractive index unit
RNA
Ribonucleic acid
S
Sensitivity
SAM
Self‐assembled monolayers
SELEX
Systematic evolution of ligands by exponential enrichment
SERS
Surface‐enhanced Raman scattering
SP
Surface plasmon
SPP
Surface plasmon polariton
SPR
Surface plasmon resonance
TE
Transverse electric
TIR
Total internal reflection
TM
Transverse magnetic
TMDCs
Transition metal dichalcogenides
TMM
Transfer matrix method
UV
Ultraviolet light
WS
2
Tungsten disulfide
About the Companion Website
This book is accompanied by a companion website:
www.wiley.com/go/kaur
The website includes sample programs with MATLAB and Simulation data files.
1Fundamentals of Biomedical Sensors
1.1 Introduction
The use of sensors, education, communication, computers in daily routines, and development of technology over the years has played a significant part in simplifying the human lifestyle [1–3]. Figure 1.1 shows the schematic of a sensor that involve input signal, sensing unit, and output signal. A sensing unit transforms the input signal to an output signal that can be measured using diverse principles, structures, and geometry. Consequently, a sensor converts a physical parameter (temperature, humidity, index of refraction) into a signal that may be processed (e.g. optical, electrochemical (ECL), electrical, and mechanical) [4–7]. Fluorescence, absorbance, scattering, polarization, interference, color change, and luminescence are among the phenomena utilized in the development of sensors.
Sensors have been explored in the numerous sectors that include biomedicine, electronics, military applications, biochemical sensing, and environmental monitoring [8]. A wide variety of research articles on diverse sensing applications has been published in the recent few years due to advancement in various technologies. A biosensor structure is designed using a transducer, light source, and bioreceptor to detect an analyte. Clark reported a glucose oxidase solution encased in a semipermeable membrane as an electrode sensor for measuring the oxygen level in the blood in 1962 [9]. Updike and Hicks reported a sensor that entraps glucose oxidase solution within polyacrylamide gel in 1967 [10]. Guilbault and Montalvo reported a potentiometric sensor to detect the urease [11]. Then in 1972, 1975, 1976, and 1984, the ion‐selective field effect transistor, immunosensor utilizing a potentiometric transducer, ECL glucose sensor, and fiberoptic sensor utilizing polymerization techniques were reported [12–15].
Figure 1.1 An illustration of components of a sensor structure.
Optical biosensors have been explored to detect the neurotransmitters that convey intercellular chemical messages within the nervous system [16, 17]. These neurotransmitters are generated by nerve cells that move to another part of the body and convey information in the form of chemicals such as acetylcholine, dopamine, serotonin, norepinephrine, gamma‐aminobutyric acid, glutamate, endorphins, histamine, oxytocin, serotonin, and melatonin. Imbalances of these neurotransmitters are responsible for various neurological disorders such as Parkinson's disease, Alzheimer's, schizophrenia, depression, acetylcholine dysfunction, and altered levels of dopamine serotonin, and norepinephrine [18–25].
The emergence of the surface plasmon resonance (SPR) phenomenon advanced this research even more. Wood observed that reflected spectrum of light is associated with bright and dark bands as light passes through diffraction grating and become polarized [26]. Rayleigh and Fano explained this effect on the basis of the wave scattering from the diffraction grating [27]. Zenneck confirmed the existence of radio frequency waves at the metal‐dielectric interface and presented the corresponding Maxwell's equation solution [28]. Otto offered a comprehensive and exact comprehension of the SPR phenomenon using experimental methods in 1968 [29]. Liedberg et al. demonstrated the first SPR‐based sensor for measuring bimolecular interactions in 1983 [30]. In 1993, Jorgenson and Yee described a silver plasmonic metal‐based fiberoptic sensor, in which the prism is replaced with fiber core to detect the sucrose solution [31]. Later, numerous biosensor designs, including an ECL glucose sensor, the utilization of various enzymes, antibodies, and aptamers for glucose and other biochemical detection, were reported [32, 33]. Technological advances have led to a diversity of biosensor designs [34, 35]. Before they may be used, enzymes must undergo a number of processes, including isolation and purification [36].
Figure 1.2 is a timeline of the development of various biosensor design and milestones. Researchers have studied transducer systems to detect air, soil, and water pollution, as well as numerous infections, toxins, and diseases [37–40]. Identifying ultrasensitive biosensors with sensitivities in the nano, femto, and Pico range is vital to detect diseases at the initial stages – including cancer, tuberculosis infection, cardiovascular disease, and Alzheimer's disease, which are responsible for so many deaths worldwide.
Figure 1.2 A schematic illustration of year‐wise progress made in the field of biosensors.
In order to investigate plasmonic, ECL, surface‐enhanced Raman scattering (SERS), chemiluminescence, and mass‐based biosensors, researchers have investigated numerous methodologies [41–44]. The biosensors market, which includes thermal, ECL, piezoelectric, and optical sensors with applications in medical, food toxicity, bioreactors, agriculture, environment, home healthcare diagnostics, and point‐of‐care testing, was valued at US$24.9 billion in 2021 globally. It will reach up to US$49.6 billion through 2030 – an indication of an annual growth rate of 8.0% in the years 2022–2030 [45, 46].
Diabetes and cancer‐related diseases have increased due to several factors, including environment, food habits, and daily lifestyle. In recent years, the demand for biosensors has rapidly increased due to their wide medical applications, their potential for early diagnosis, and the number of patients affected by diabetes [47]. Of all types of optical sensor designs, ECL glucose biosensors and lateral flow assay‐based test for pregnancy have been commercialized most successfully in the global market. Fluorescence‐based polymerase chain reactions (PCR) are used in nucleic acid‐based tests due to its high specificity and sensitivity. Colorimetric biosensors are commonly used in serological tests that include lateral flow assays and enzyme‐linked immunosorbent assays (ELISA) to detect different type of antibodies. Colorimetric methods have the drawback of low sensitivity values. Most plasmonic and refractive‐index‐based biosensors are still limited to lab research use only [48]. Figure 1.3 illustrates the market demand of different types of biosensors; the sizes of slices indicate the estimated share for each type of biosensor.
Figure 1.3 Commercialization and market pull of different types of biosensor platforms.
1.2 Classification of Biosensors
Biosensors can be classified on the basis of bio‐recognition elements (BREs), different types of transducers, and physical phenomenon. The enzymes, molecular imprinted polymers (MIP), antibodies, nucleic acids, cells, and aptamers have been explored as a biological recognition element to detect numerous analytes [49]. Types of transducers include ECL, optical, piezoelectric, thermal, and magnetic transducers that changes the form of signal. Various optical sensing techniques, such as the evanescent wave (EW) technique [50], fiber grating, SPR‐based sensing, and SERS spectroscopy, are available for different applications [51]. ECL biosensors operate in potentiometric, amperometric, and conductometric mode while mass‐based sensors can be magnetoelectric and piezoelectric.
1.3 Elements of Biosensors
Figures 1.4a and b show the necessary components of a biosensor, including BRE and transducers to process the signal and output display [52].
1.4 Bio‐recognition Elements
BREs consist of nucleic acid (NA), lectins, enzymes, entire cells, antibodies, aptamers, bacteriophages, peptides, and molecularly imprinted polymers, as illustrated in Figure 1.4c [53]. Figure 1.4d depicts the many types of transducers. Bacteriophages are a type of pathogen that infects and replicates within bacteria by selectively attaching to tail‐spike proteins. Peptides consist of a short segment of 12–15 amino acid residues that are stable in harsh environments, inexpensive, and simple to produce on a large scale. NA utilize genetic materials such as deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) as bioreceptors and aptamers are single‐stranded DNA or RNA molecules [54]. Aptamers have a lower molecular weight, are readily produced at a low cost, and have excellent chemical stability [55]. Whole cells include microorganisms or cultivated tissues of multicellular organisms used in numerous biosensing applications due to its lower expenditures [56]. MIPs are artificial bioreceptors that are synthesized in the laboratory with binding sites designed corresponding to the target molecule [57].
1.4.1 Nucleic Acids
NAs are chains of linear polymers that consist of five nucleotides called bases: guanine, adenine, cytosine, uracil, and thymine. DNA is made up of a thymine base, while RNA uses uracil as a base. DNA is a unique genetic component of each individual organism. Due to its unique sequence and properties, NAs are used to design bioreceptors that match the complementary DNA of the concerned individual. The matching strand can be detected with different transducing mechanisms [54]. NA‐based biosensor designs are simple, easy, fast, and low‐cost, and they have high specificity to detect an analyte. Various NA biosensors have been reported to detect viruses, cancer cells, microorganisms, and biochemicals [58].
Figure 1.4 Schematic design of the (a) biosensor components (b) different analytes for sensing (c) bio‐recognition elements (d) biosensor classification based on types of transducers.
1.4.2 Aptamers
Aptamers are short sequences of oligonucleotides that form a three‐dimensional structure that is very specific to the target molecules [55]. To synthesize the aptamers, various chemical or enzymatic procedures or a combination of chemical and enzymatic methods are used [59, 60]. Aptamers are chosen from the systematic evolution of ligands by exponential enrichment (SELEX) techniques using several repeatable steps. The production steps for a single‐stranded DNA and its incubation are shown in Figure 1.5. Aptamers are selected using the repletion of various cycles, as these cycles increase the specificity toward the target [39].
1.4.3 Enzymes
Enzymes are target‐specific, another type of BRE combined with an appropriate substrate that generates electrons and transfers them to a transducer. Proteins are widely explored enzymes, except RNA enzymes [62]. Enzymes are preferred as labels compared to other BRE, as they can be conjugated with antibodies or aptamers for bioreceptor purposes. Horseradish peroxidase (HRP) and beta‐galactosidase are two examples of enzymes used in biosensor designing. Various enzymatic biosensors are also developed based on mass, plasmonic, ECL, thermistor, and piezoelectric techniques for different applications [63]. Enzyme immobilization in the biosensor design is advantageous as it can be used repetitively due to catalytic activity to detect the analyte as compared to the mobile enzyme [63]. Glucose and urease‐based biosensors are well‐known enzymatic biosensors, of which glucose biosensors are commercialized on different platforms due to their small detection limits and lifetimes.
1.4.4 Antibodies
Antibodies are another class of bioreceptors. They can be polyclonal and monoclonal depending on their production method [64]. Antibodies are proteins generated by plasma cells and classified into five groups that depend on their structure of heavy chain constant region sequences. Their structure is Y‐shaped, formed from heavy and light chains, as shown in Figure 1.6. Binding sites specific to antigens, known as epitopes, can be classified as monoclonal or polyclonal. Monoclonal antibodies can bind to a single epitope while polyclonal antibodies target different epitopes. The production cost and time for making monoclonal antibodies are both higher than for polyclonal antibodies. As compared to other bioreceptors, antibodies involve high costs and stability challenges requiring low‐temperature storage. Monoclonal antibodies act as the primary bio‐recognition element and polyclonal antibodies act as the secondary bio‐recognition element.
Figure 1.5 Stepwise diagram of the SELEX technique to choose the specific aptamers from the library that includes the separation of bound and unbound targets, target amplification, and generation of a specific aptamer.
Source:[61]/with permission of Elsevier.
Most antibodies are produced by living organisms. Antibodies contain different numbers of epitopes that can be single or multiple [65]. Recombinant antibodies can also be synthesized in the lab with the help of synthetic genes; they are monoclonal in nature. Polyclonal antibodies suffer from high cross‐reactivity as compared to monoclonal antibodies due to multiple epitopes. Instead of polyclonal antibodies, monoclonal antibodies are used to design highly specific biosensors because they bind only one epitope. The most important steps during the use of antibodies as a BRE are their immobilization and control of orientation on the surface without damaging their activity and specificity, as this affects the various performance factors, including the limit of detection (LOD), sensitivity, and figure of merit (FOM) [66].
Figure 1.6 Structure of a Y‐shaped antibody.
1.4.5 Bacteriophages
A bacteriophage belongs to a family of viruses that contaminate bacteria and are used as BREs to detect the pathogen, cancer biomarkers, tuberculosis, and other pathogenic diseases. Phages are very specific in nature and can affect a single bacterial species. T4, M2, Φ29, and MS2 are a few examples of commonly used phages. A polyhedral head, collar of short length, and a helical tail are the basic components of a phage. Bacteriophages are found in nature and can be used at high pressure, temperature, and pH values. Several biosensor designs have been reported that consider the bacteriophage as a BRE for various types of bacteria detection [67–70]. Pathogenic bacteria (PathoBact) cause infection that consists of single cells with diameter and length in the range of a few μm [71]. PathoBacts have different shapes and can survive in a harsh environment. Bacteria are prokaryotic microorganisms, without membrane‐bound organelles such as a nucleus or mitochondria [72]. The five PathoBacts Pseudomonas Aeruginosa, Klebsiella Pneumoniae, Staphylococcus Aureus, Escherichia Coli, and Streptococcus Pneumonia were responsible for 13.7 million global deaths in 2019 among 33 investigated PathoBacts [73]. The main structure components of bacteria are DNA, cell wall, ribosomes, capsule, cytoplasm, flagellum, and pili.
Gram‐positive and Gram‐negative bacteria are classified based on response of bacteria to Gram staining. Gram‐positive bacteria don't change from crystal violet color and thus remain purple while Gram‐negative bacteria turn red due to different thickness of outermost peptidoglycan cell wall that are made from glucose molecules and connected three short peptide chains [74]. In Gram‐positive bacteria, the peptidoglycan layer is 30–100 nm thick; this layer is 1–3 nm thick for Gram‐negative bacteria surrounded by extra lipopolysaccharides layer [75]. Microscopy, culture, cytological, biochemical test methods, Gram staining, hemagglutination assays, ELISA, and western blotting (serological tests) are conventional; and polymerase chain reaction, fluorescence in situ hybridization, next‐generation sequencing, spectroscopic, CRISPR technology, loop‐mediated isothermal amplification, microarray technology, and biosensors are advanced method to detect the PathoBacts [76, 77]. The advanced methods are highly sensitive, can select specific target stable, and have short detection time, low cost, simple structures, and less sample preparation. These advantages overcome the drawbacks of conventional methods [78]. Biosensors are advanced emerging and competitive techniques for detecting pathogens and other analytes [79–82]. They involve ECL, piezoelectric, and optical platforms to detect various microorganisms. However, it is important to mention that each technique suffers from several challenges to commercialize it for various applications as it is in the developing stage.
Bacteriophages have been explored in various biosensing applications focused to detect the microorganism due to their chemical and physical properties. They do not require labeling, which creates advantages of reduces cost, time, high sensitivity, widespread availability (food, soil, water, and environment) and specificity. Various biosensor designs using phages to detect the analytes have been reported so far. Figure 1.7 shows a SERS and colorimetric technique combined biosensor that detects Salmonella Enteritidis using F5–4 bacteriophage as a bioreceptor and [83].
1.4.6 MIPs
Diagnostic techniques ELISA, PCR, and cell culture require BRE, trained specialists, complex instruments, and sample preparation. They include mimicking various BRE that include NA, proteins, amino acids, cells, peptides, viruses, and bacteria that help to facilitate the easy isolation and investigation of complex samples. Molecular imprinting is a technique to develop the functionality of biomaterials into artificial materials, as naturally occurring materials are expensive and restricted in robustness with predefined specificity and selectivity [84]. MIP possesses better chemical stability, is temperature insensitive, requires less preparation time at a low cost, is easy to modify with chemicals, can be directly fabricated on the surface of the transducer, and has high physical and mechanical properties [85]. MIP synthesis involves reactive functional monomers that form specific complexes, cross‐linkers for functional group immobilization on imprinted molecules, and initiators to shorten the cycle reaction in the usual way.
Figure 1.7 Graphic illustration of the F5‐4 bacteriophage‐based colorimetric lateral flow assay and SERS biosensor structure.
Source:[83]/with permission of Elsevier.
Functional monomer and target‐based imprinting can be categorized in three ways that depend on their interaction: (i) covalent; (ii) semi‐covalent; (iii) noncovalent imprinting, as shown in Figure 1.8[86]. Figure 1.8a shows the stepwise synthesis of MIP, which includes self‐assembly, polymerization, and template removal. Similarly, Figure 1.8b shows the commonly used ingredients that include initiators, functional monomers, and cross‐linkers. Functional monomers are the polymers building block – for example, methacrylic acid (MAA), 4‐vinyl pyridine (4‐VP), acrylic acid (AA), 2‐vinyl pyridine (2‐VP) and cross‐linkers involve trimethylolpropane‐tri methacrylate (MBA), ethylene glycol dimethacrylate (EGDMA), divinylbenzene (DVB), and methylene acrylamide (TMPTM). An initiator is used to start the polymerization process, such as benzoyl peroxide (BPO), azobisisobutyronitrile (AIBN), and azodiisopentanyl (AIHN). Covalent imprinting uses a reverse bonding functional unit and template that distributes binding sites in a uniform mode [88]. Semi‐covalent imprinting involves covalent and noncovalent polymerization approaches that can be achieved via covalent bonding as well as noncovalent methods [89]. During noncovalent bonding, interaction between functional monomer and sensing analyte is weak in nature that occur via ionic hydrogen bonding, and dipole interaction [90]. Out of these three imprinting techniques, noncovalent imprinting technique is most often used to synthesize the MIP, as shown in Figure 1.8b [91]. Numerous biosensor designs using MIP technology that include optical, ECL, and quartz crystal microbalance biosensors have been reported with improved performance for diverse analytes that include molecules from small to large in size [92]. Until recently, MIP‐based biosensors have not been commercialized due to difficulties in large‐scale MIP production, complete removal of templates, low selectivity, and less efficient synthesis methods [93].
1.4.7 Biosensors Based on Whole Cells
Biosensors that include whole cells employ different microbes that include viruses, bacteria, protozoa, fungi, and algae as bioreceptors [53]. These bioreceptors can self‐replicate, are handled easily compared to plants and animal cells, are fast‐proliferating, and do not require any extraction or purification methods to produce other bioreceptors such as antibodies [94]. Various biosensor designs based on whole cells have been reported that exhibit good sensitivity and specificity values to detect the different analytes [56, 95, 96]. Figure 1.9 shows the mechanism of a whole‐cell‐based biosensor that includes molecular bioreceptor immobilizing bacteria or live cells on the substrate to detect the specific target. The target binds itself to the surface of immobilized receptor that modulates the output signal or gene expression and can be measured using different transduction mechanism [96].
Figure 1.8 Graphic illustration of (a) various steps involved in covalent and noncovalent molecularly imprinted polymer technique.
Source:[86]/MDPI/CC BY 4.0.
(b) Some commonly used initiators, functional monomers, and cross‐linkers during MIP fabrication.
Source:[87]/Frontiers Media S.A/CC BY 4.0.
Figure 1.9 Biosensor design based on whole cell.
Source:[96]/MDPI/CC BY 4.0.
1.5 Sensing Techniques
1.5.1 ECL Biosensors
An ECL (ECL) biosensor is made up of an interface for the analyte reaction, a receptor for binding the target molecule through BRE, and a device known as transducer that alters the interaction signal to a measurable electrical signal. This signal can be measured in the form of impedance, current, voltage, and conductance. ECL biosensors measure changes in electrical properties that result from a specific biochemical reaction. The principle of electrochemistry involves the connection between chemical reaction such as oxidation and reduction into electrical energy. The detection of biomarkers involves the use of an electrode modified with target that specifically binds to the disease biomarker. As the biomarker binds to the target molecule, this attachment changes in the measurable electrical signal. Electrochemical impedance spectroscopy (EIS) is an example that measures the output electrical signal as target cancer cells binds to bioreceptors, such as their size and surface charge. EIS can be used to monitor cancer cell growth and invasion and to detect cancer biomarkers in blood samples [97, 98].
In ECL biosensors, electrodes are utilized as transducers and reaction sites that sense the analyte by reducing or oxidizing it [99]. Reference electrode and working electrode are two main components during ECL sensor design. Silver (Ag) and silver chloride (AgCl) are used to fabricate the reference electrode, which forms a connection with the electrolyte solution and is kept at a distance to maintain the potential at a stable value. Reference electrode using graphite, gold (Au), platinum (Pt), and compounds made from silicon (Si) have been reported so far.
ECL sensors are classified into amperometric, potentiometric, conductometric, field effect transistor, and impedimetric. Amperometric sensors measure the signal in the form of a current generated from ECL reaction, potentiometric sensors measure voltage generated at electrode surface, and impedimetric sensors measure impedance [100].
Clark reported using ECL biosensors to measure glucose solutions [63]. In the case of potentiometric ions in solution, BRE is measured after being converted to potential. Impedimetric biosensor measure the impedance to detect the presence of various analytes [101–105]. ECL biosensors have a short lifespan (i.e. 1–3 years), and components must be replacement. Some ECL sensor designs involve using electrolyte solutions to enhance performance and lifespan; however, refilling the solution regularly is another drawback. Figure 1.10 shows a manganese oxide‐fluorescent polymer dot–based ECL biosensor to detect Madin‐Darby canine kidney (MDCK) and MD Anderson‐metastatic breast (MDAMB) cancer cells cancer cells [106].
1.5.2 Optical Biosensors
Light is used in optical biosensors to detect the various analytes that possess advantages such as high sensitivity with low detection limits, fast speed, and shorter detection time. Optical biosensors detect changes in the optical properties of a sample resulting from a chemical reaction. Output is measured using optical transducers (i.e. colorimetric). Other examples of optical biosensors for cancer detection include fluorescence, Raman spectroscopy, and light scattering [39, 107, 108]. The classification of various optical sensor designs and their descriptions based on underlying operational principles and sensing applications are discussed in detail.
1.5.2.1 Plasmonic Biosensors
With the growing demand for portable, reliable, fast‐responding, and highly sensitive detection mechanisms, plasmonic biosensors that consist of surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR) have become a favorable alternative technology to detect the various biochemicals. In recent years, considerable progress has been witnessed in the field of plasmonic biosensors and their commercialization in the different application areas. More precisely, the unique properties of the SPR phenomenon are focused on a variety of applications such as the guiding of light, nanoscale manipulation, overcoming the difficulty to provide good resolution below the diffraction limit, and single molecule detection [109].
Prism‐based Kretschmann's configuration and fiberoptic structures are widely explored for various applications [110]. A surface plasmon (SP) phenomenon is excited using a transverse magnetic wave whose electric field exists along the interface of two materials with opposite permittivity values fulfilled by metal and dielectric material. Figures 1.11a and b show penetration depth in metals (δm), dielectric (δs), and their numeric values in the case of most widely explored plasmonic metals Au and Ag [111]. As the wave vector and momentum of an oscillating charge are always greater than those of a massless photon, it is difficult to excite the surface plasmons' incident light directly, but the light can be excited by different techniques that increase their momentum.
Figure 1.10 A fluorescent polymer dot‐manganese oxide complex–based ECL sensor to detect the cancer cells.
Source:[106]/with permission of Elsevier.
Excitation methods include prism, Bragg, and fiber configuration. In these methods, the incident electromagnetic light is coupled through prisms for biosensing applications. For practical purposes, the Otto configuration was not found suitable, as it was not possible to maintain the few nm gaps between the metal layer and the prism material. Otto configuration was modified and reported by Kretschmann and Raether by depositing the plasmonic active metal layer on the base of prism [112]. This configuration has been explored for various applications and lays the foundation for rapid growth of prism‐based SPR sensors. Figures 1.12a and b show the structure reported by Otto and Kretschmann for sensing purposes. SPR requires precise wave vector matching of incident light with surface plasmons at a specific angle known as resonance angle, denoted as θSPR[51]:
Figure 1.11 Schematic illustration of (a) surface plasmons existence at the interface of the metal and dielectric indication penetration depth in metals (δm), dielectric (δs) of the electromagnetic field and propagation length (Lsp) of surface plasmons; (b) numerical values of δm, δs, and Lsp for plasmonic active Ag and Au metals that are commonly used in biosensing applications.
Figure 1.12 Schematic of light coupling in a plasmonic‐based sensor using (a) Otto, (b) Kretschmann, and (c) Bragg grating configuration.
Eq. (1.1) represents the evanescent wave‐vector (kev), with dielectric permittivity (εs) and metal permittivity (εm). At resonance conditions, a decrease in intensity of reflected light is detected at resonance angle denoted as θSPR. This θSPR is responsive to any change in RI of sensing medium and shows angular shift (δθSPR) for other analytes, which is the principle behind SPR sensing [112, 113]. Phase‐matching condition with grating of holes or grooves having lattice constant a can be expressed as (Figure 1.12c).
β, ν and ns are the wave vector of surface plasmons (Eq. 1.2), diffraction order, and analyte RI. Fiberoptic‐based sensors possess the advantages of small size, low cost, remote sensing, electromagnetic radiation immunity, long‐term reliability, miniaturization, and online monitoring. Plasmonic sensors have been explored to detect the analytes such as gases, liquids, and various toxic materials. Furthermore, different strategies, transition metal dichalcogenides (TMDCs) [114], plasmonic nanocomposites [115], glass materials [116], and fiber geometries [117] have been used to improve the performance of SPR sensors in the visible to infrared region [118]. Discovery of other 2D materials and their unique properties has further triggered research in the field of SPR sensing [119]. Out of the four interrogation methods, wavelength and angular methods are most commonly used for the detection of various biochemical substances as they are simple to fabricate and provide superior resolution at a low cost [120]. Figure 1.13 shows the fiberoptic configuration used for various sensing applications.
Prism‐based configurations utilize the phenomenon of total internal reflection (TIR) to excite SPs; therefore, a prism (due to its bulky size) can be replaced with a core of optical fiber for sensing purposes, as shown in Figure 1.13.
1.5.2.2 Interferometric Sensors
Interferometric sensors explore the interference phenomenon to measure the various quantities that include disease‐related analytes, temperature, and humidity. Fabry‐Perot (FPI), Mach‐Zehnder (MZI), Sagnac, and Michelson interferometers are four types of interferometers used for many biochemical sensing applications. In interferometry, light is split into components that are further combined to produce maxima and minima series. The MZI interferometer is based on interference obtained by division of amplitude. Light can be split into its components using a beam splitter that covers the different path lengths and phases, which are further recombined with the help of another beam splitter [121]. Figure 1.14a shows the MZI interferometer structure that consist of laser light source, sensing arm with reference arm, input, output waveguide, and detector system.
Figure 1.13 Schematic of fiberoptic configuration.
