حسگرهای زیستی پیشرفته برای تشخیص ویروس - تشخیص هوشمند برای مبارزه با SARS-CoV-2

Advanced Biosensors for Virus Detection: Smart Diagnostics to Combat Against the SARS-CoV2 Pandemic covers the development of biosensor-based approaches for the diagnosis and prognosis of viral infections, specifically coronaviruses. The book discusses wide-ranging topics of available biosensor-based technologies and their application for early viral detection. Sections cover the emergence of SARS-CoV, MERS-CoV and SARS-CoV2, the global health response, the impact on affected populations, state-of-the art biomarkers, and risk factors. Specific focus is given to COVID-19, with coverage of genomic profiling, strain variation and the pathogenesis of SARS-CoV2. In addition, current therapeutics, nano-abled advancements and challenges in the detection of SARS-CoV2 and COVID-19 management are discussed, along with the role of nanomaterials in the development of biosensors and how biosensors can be scaled up for clinical applications and commercialization. Deals with biosensors-based approaches that could be exploited to design and develop high throughput, rapid and cost-effective diagnostics technologies for the early detection of viral infections Illustrates the development of multiplexed, miniaturized analytical systems for point-of-care applications Provides information about fabrication protocols for various biosensor based diagnostic approaches that could be directly implemented to develop a novel biosensor Includes the past, present and future status of biosensors, along with information about biosensors currently under clinical trials Advanced Biosensors for Virus Detection Copyright Contents List of contributors Preface Acknowledgments 1 The emergence of severe acute respiratory syndrome-coronavirus 2 epidemic and pandemic 1.1 Introduction 1.2 Severe acute respiratory syndrome-coronavirus 2: the member of the coronavirus family 1.2.1 SARS-CoV-2 in connection with severe acute respiratory syndrome-coronavirus and Middle East respiratory syndrome-coro... 1.3 Virion structure of severe acute respiratory syndrome-coronavirus 2 1.4 Pathophysiology of severe acute respiratory syndrome-coronavirus 2 infection 1.5 Transmissibility of severe acute respiratory syndrome-coronavirus 2 1.6 Origin and etiology of severe acute respiratory syndrome-coronavirus 2 1.7 From epidemic to pandemic 1.8 Perspective References 2 Lesson learned from coronaviruses (SARS-CoV, MERS-CoV, and SARS-CoV-2) and socioeconomic impact of (SARS-CoV-2) pandemic 2.1 Introduction 2.2 Coronaviruses and family 2.2.1 Coronaviruses and human diseases 2.2.2 Coronavirus outbreaks in the past 2.2.3 Severe acute respiratory syndrome-coronavirus 2.2.4 Middle East respiratory syndrome-coronavirus 2.2.5 Severe acute respiratory syndrome-coronavirus 2 2.3 Diagnostics 2.4 Therapeutics 2.5 Vaccines 2.6 World health response to coronavirus disease 2.7 Public health response to coronavirus disease 2.8 Human–animal nexus 2.9 What we learned from pandemic and future 2.10 Conclusion Acknowledgment Conflicts of interest References 3 Structure, genomic analysis, and pathogenesis of SARS-CoV-2 3.1 Classification of coronaviruses 3.2 Morphology and structure of SARS-CoV-2 3.2.1 Spike (S) protein 3.2.2 Membrane (M) protein 3.2.3 Envelope (E) protein 3.2.4 Nucleocapsid (N) protein 3.3 Nonstructural proteins 3.3.1 RNA-dependent RNA polymerase 3.3.2 The main protease 3.4 Genomic analysis 3.4.1 Phylogenetic analysis 3.4.2 Emergence of newer variants of SARS-CoV-2 3.5 Pathogenesis of coronavirus 19 3.5.1 Infection and viremia 3.5.2 Inflammation and cytokine storm 3.5.2.1 Clinical manifestations of coronavirus 19 3.5.2.2 Coagulopathy 3.5.3 Postinflammatory pulmonary fibrosis 3.6 Extrapulmonary manifestations of coronavirus 19 3.6.1 Cardiac involvement 3.6.2 Hematological manifestations 3.6.3 Renal manifestation 3.6.4 Gastrointestinal and Hepatobiliary manifestations 3.6.5 Endocrine manifestations 3.6.6 Neurological manifestations 3.7 Conclusion Acknowledgment References 4 COVID-19 diagnosis: approaches and challenges 4.1 Introduction 4.2 Sample collection 4.3 qRT-PCR for detection of SARS-CoV-2 RNA 4.4 Cartridge-based nucleic acid amplification tests 4.5 Pooling of specimens for nucleic acid amplification test 4.6 Isothermal assays 4.7 Rapid antigen detection test 4.8 Quality control of COVID-19 testing 4.9 Conclusion References 5 Current therapeutic choices for coronavirus disease 2019: a state-of-the-art review 5.1 Introduction 5.2 Pathophysiology of coronavirus disease 5.2.1 Stage of infection and viremia 5.2.2 Stage of inflammation and cytokine storm 5.2.3 Postinflammatory pulmonary fibrosis and its complications 5.3 Therapeutics of proven utility, targeting stage of infection and viremia 5.3.1 Monoclonal antibodies 5.4 Therapeutics of limited or unproven utility, targeting stage of Infection and viremia 5.4.1 Remdesivir 5.4.2 Hydroxychloroquine 5.4.3 Ivermectin 5.4.4 Lopinavir 5.5 Therapeutics of proven utility, targeting cytokine storm 5.5.1 Glucocorticoids 5.5.2 Anticoagulants 5.6 Therapeutics of limited utility, targeting cytokine storm 5.6.1 Tocilizumab 5.6.2 Interferons 5.6.3 Baricitinib 5.6.4 Bevacizumab 5.6.5 Infliximab 5.6.6 Artesunate 5.7 Therapeutics of limited or uncertain utility, targeting post-coronavirus disease complications 5.7.1 Drugs targeting pulmonary fibrosis: nintedanib and pirfenidone 5.7.2 Colchicine 5.7.3 Drugs targeting pulmonary hypertension 5.7.4 Long term anticoagulation therapy 5.8 Conclusion References 6 Genomic, proteomic biomarkers and risk factors associated with COVID-19 6.1 Introduction 6.2 Biomarkers 6.3 Proteomic Biomarkers for COVID-19 6.3.1 Cytokines 6.3.2 Acute-phase proteins 6.3.3 Clinical biochemical parameters 6.3.4 Identification of novel proteomics biomarkers for COVID-19 6.4 Genetic biomarkers 6.4.1 Genetic predisposition biomarkers 6.4.1.1 Role of human leukocyte antigen in genetic predisposition to COVID-19 6.4.1.2 Single nucleotide polymorphism contribute to COVID-19 predisposition 6.4.2 Noncoding RNA 6.5 Conclusion and future perspective References 7 Biological/synthetic receptors (antibody, enzyme, and aptamer) used for biosensors development for virus detection 7.1 Introduction 7.2 Types of bioreceptors 7.2.1 Enzymes 7.2.2 Antibody and antigen 7.2.3 Nucleic acid 7.2.4 Whole cell 7.2.5 Aptamers 7.2.6 Peptides 7.2.7 Molecularly imprinted polymers 7.2.8 Other sensor paradigms 7.3 Properties of biosensors based on bioreceptors 7.4 Examples of biosensors for detection of coronavirus disease 2019 based on different bioreceptors 7.4.1 Antibody receptor based 7.4.2 Antigen receptor based 7.4.3 Nucleic acid receptor based 7.4.4 Peptide receptor based 7.5 Future prospects 7.6 Conclusion References 8 Potential electrochemical biosensors for early detection of viral infection 8.1 Introduction 8.2 Types of viral infections and their detection 8.2.1 Respiratory viral infection 8.2.1.1 Influenza virus (IV) 8.2.1.1.1 Electrochemical detection of IV 8.2.1.2 Corona virus 8.2.1.2.1 Electrochemical detection of coronavirus (SARS-CoV-2) 8.2.2 Sexually transmitted viral infection 8.2.2.1 Hepatitis B virus 8.2.2.2.1 Electrochemical detection of HBV 8.2.2.2 Human papilloma virus 8.2.2.2.1 Electrochemical detection of human papilloma virus 8.2.2.3 Human immunodeficiency virus 8.2.2.3.1 Electrochemical detection of human immunodeficiency virus 8.2.3 Food-borne viral infection 8.2.3.1 Norovirus 8.2.3.1.1 Electrochemical detection of Norovirus 8.2.3.2 Hepatitis A virus 8.2.3.2.1 Electrochemical detection of HAV 8.2.3.3 Hepatitis E virus 8.2.3.3.1 Electrochemical detection of hepatitis E virus 8.2.4 Mosquito-borne viral infection 8.2.4.1 Zika virus 8.2.4.1.1 Electrochemical detection Zika virus 8.2.4.2 Dengue virus 8.2.4.2.1 Electrochemical detection of Dengue virus 8.2.4.3 Chikungunya virus 8.2.4.3.1 Electrochemical detection of chikunguniya virus 8.3 Conclusion References 9 Optical biosensors for SARS-CoV-2 detection 9.1 Introduction 9.2 Biosensors: an introduction to optical biosensors 9.3 Surface-plasmon resonance-based biosensors 9.4 Localized surface plasmon resonance-based optical biosensors 9.5 Surface-enhanced Raman scattering-based optical biosensors 9.6 Optical lateral flow assay for SARS-CoV-2-detection 9.7 Challenges in developing optical biosensors 9.8 Conclusion and future perspectives Acknowledgments References 10 Recent developments of molecular/biosensor diagnostics for SARS-CoV-2 detection 10.1 Introduction 10.2 Nucleic acid-based detection 10.2.1 RT-q PCR-based detection 10.2.2 Alternate nucleic acid testing 10.2.2.1 Isothermal amplification 10.3 Serological testing 10.4 Biosensors for COVID-19 diagnostics 10.4.1 Electrochemical biosensors for SARS-CoV-2 detection 10.4.2 Optical biosensors 10.4.3 CRISPR-based biosensor for SARS-CoV-2 10.5 Electrical and piezoelectric biosensors 10.5.1 COVID test based on antibody detection 10.5.2 Detection of blocking antibodies 10.5.3 Harnessing wearable devices to detect SARS-CoV-2 infections 10.5.4 Smart toilet technology 10.6 Future directions 10.7 Conclusions Acknowledgments References 11 Role of magnetic nanoparticles in development of biosensors for viral infection diagnostics 11.1 Introduction 11.2 Capture, preconcentration, extraction 11.3 Multiple detections with immunomagnetic separation 11.4 Labeling 11.5 Magnetic label 11.6 Fluorometric label 11.7 Labeling based on the enzyme-like activity of magnetic nanoparticles 11.8 Dual role of magnetic nanoparticles and application in microfluidics 11.9 Conclusion and perspective References 12 Advances in nanomaterials-based biosensors for the development of virus detection 12.1 Introduction 12.2 Fundamental principles 12.3 Gold nanoparticles-based biosensor 12.3.1 Gold nanoparticles for the detection of Zika virus 12.3.2 Gold nanoparticles for the detection of SARS-CoV 12.4 Quantum dots-based nanomaterials 12.5 Upconversion nanoparticles 12.6 Conclusion and future perspective Abbreviations References 13 Multiplexed biosensors for virus detection 13.1 Introduction 13.2 Biosensors 13.3 Application of multiplex biosensors on detection of viruses 13.3.1 Coronaviruses 13.3.2 Zika virus 13.3.3 Ebola virus 13.3.4 Dengue 13.4 Conclusion 13.5 Future perspectives References 14 Electrical biosensors for virus detection 14.1 Introduction 14.2 Electrical biosensor 14.3 Electrode-based biosensor 14.3.1 Microelectrode-based biosensor 14.3.2 Interdigitated electrodes-based biosensor 14.4 Transistor-based biosensor 14.4.1 Ion sensitive field-effect transistor biosensor 14.4.2 Silicon nanowire biosensor 14.4.3 Organic field-effect transistor-based biosensor 14.5 Biorecognition elements 14.6 Electrical biosensor measurement techniques 14.6.1 Current versus voltage (I–V) measurement 14.6.2 Impedance measurement 14.6.3 LabVIEW-based measurement 14.7 Recent development in electrical biosensor 14.7.1 Wearable biosensors 14.7.2 Wireless biosensor 14.7.3 Internet-of-Things -based biosensing technology 14.7.4 Machine learning in biosensing 14.8 Conclusion and future scope Abbreviations References 15 Diagnostic biosensors for coronaviruses and recent developments 15.1 Introduction 15.2 Traditional detection methods 15.3 Biosensors in coronavirus detection 15.3.1 Electrochemical biosensors 15.3.1.1 Multiplexed electrochemical array 15.3.1.2 Cotton-tipped electrochemical biosensor 15.3.1.3 Magnetic nanoparticles-based electrochemical biosensors 15.3.1.4 Molecular imprinted polymer-based electrochemical biosensor 15.3.1.5 Graphene oxide/paper-based biosensor 15.3.1.6 DNA-based biosensor for the detection of the viral genes 15.3.2 Optical biosensors 15.3.2.1 Surface-enhanced Raman scattering and chemiluminescence 15.3.2.2 Plasmonic biosensors 15.3.2.3 Colourimetry-based biosensors 15.3.2.4 Microfluidic-based biosensors 15.3.3 Field-effect transistor 15.4 Conclusions and future perspectives References 16 Fluorescence-based biosensors for SARS-CoV-2 viral infection diagnostics 16.1 Introduction 16.2 Fluorescence-based strategies in biosensors 16.2.1 DNA staining and fluorescence labeling 16.2.2 Förster resonance energy transfer -based biosensors 16.2.3 Metal-enhanced fluorescence-based biosensors 16.3 Fluorescence-based biosensors in viral diagnostic applications 16.3.1 Hybridization-based probes 16.3.2 Light-up RNA aptamer probes 16.3.3 Antibody-based probes 16.4 Advances in fluorescence-based biosensors for SARS-CoV-2 viral infection diagnostics 16.4.1 Nucleic acid detection 16.4.2 Protein detection 16.4.3 Other approaches 16.5 Conclusion References 17 Miniaturized analytical system for point-of-care coronavirus infection diagnostics 17.1 Introduction 17.2 Current diagnostic techniques 17.2.1 Polymerase chain reaction/reverse transcription-polymerase chain reaction 17.2.2 Loop-mediated isothermal amplification/reverse transcription and loop-mediated isothermal amplification 17.2.3 Clustered regularly interspaced short palindromic repeats 17.2.4 Computerized tomography scan 17.2.5 Electrochemical-based biosensor 17.2.6 Optical-based biosensor 17.2.7 Lateral flow immunoassay 17.2.8 Microfluidic-based biosensor 17.2.9 Mass-spectroscopy-based biosensor 17.3 Potential point-of-car miniaturized biosensor 17.4 Conclusion Acknowledgments References 18 Microfluidic devices with integrated biosensors for coronavirus infection diagnostics 18.1 Introduction to coronavirus 18.2 Available detection methods for SARS-CoV-2 virus 18.3 Microfluidic-based biosensor system 18.3.1 Middle East respiratory syndrome 18.3.2 Severe acute respiratory syndrome 18.3.3 Severe acute respiratory syndrome-coronavirus 2 18.4 Commercially available biosensor systems 18.5 Conclusion Acknowledgment Conflicts of interest References 19 Approaches for fabrication of point-of-care biosensors for viral infection 19.1 Introduction 19.2 Methodology for fabrication of biosensor 19.3 Fabrication of electrochemical biosensor 19.4 Fabrication of optical biosensor 19.5 Fabrication of paper-based biosensor 19.6 Fabrication of microfluidic and lab-on-a-chip biosensor 19.7 Fabrication of molecularly imprinted polymer-based biosensor 19.8 Fabrication of magnetic biosensor 19.9 Fabrication of three-dimensional printing biosensor 19.10 Conclusion Acknowledgments References 20 Currently available biosensor-based approaches for severe acute respiratory syndrome-coronavirus 2 detection 20.1 Introduction 20.2 Diagnostic approaches for viral diseases 20.3 Biosensors in the detection of respiratory viruses 20.3.1 Electrochemical biosensor 20.3.2 Optical biosensor 20.3.3 Piezoelectric biosensor 20.3.4 Thermal biosensors 20.4 Present diagnostic methods for severe acute respiratory syndrome-coronavirus 2 detection 20.5 Advantages offered by biosensors 20.6 Concluding remark Abbreviations References 21 Biosensors-based approaches for other viral infection detection 21.1 Introduction 21.2 Appropriate target sites for the detection of viruses 21.2.1 Surface protein 21.2.2 Viral protein 21.2.3 Genetic material 21.3 Importance of biosensor in the diagnostics 21.4 Detection of mammalian viruses by a biosensor 21.4.1 Dengue 21.4.2 Human immunodeficiency virus 21.4.3 Zika 21.4.4 Hepatitis 21.4.5 Influenza virus 21.5 Importance and significance of biological analytes 21.6 Future scopes Abbreviations References Further reading 22 Scaling up of biosensors for clinical applications and commercialization 22.1 Introduction 22.2 Commercialization of biosensors 22.2.1 Commercial electrochemical biosensors 22.2.2 Commercial optical biosensors 22.2.3 Commercial piezoelectric biosensors 22.3 Future outlook References 23 Future aspects of biosensor-based devices in disease detection 23.1 Introduction 23.2 Need for advanced nanobiosensors 23.3 Detection of metabolites and metals by nanobiosensors 23.4 Applications of nanobiosensors in the detection of noncommunicable diseases 23.5 Applications of nanobiosensors in the detection of infectious diseases 23.6 Advanced biosensing applications toward disease detection 23.7 Conclusion Acknowledgment References Further reading Index This book constitutes refereed proceedings of the 14th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2022, held in Hammamet, Tunisia, in September 2022. The 43 full papers and 15 short papers were thoroughly reviewed and selected from 421 submissions. The papers are grouped in topical ​sections on ​collective intelligence and collective decision-making; natural language processing; deep learning; computational intelligence for multimedia understanding; computational intelligence in medical applications; applications for industry 4.0; experience enhanced intelligence to IoT and sensors; cooperative strategies for decision making and optimization; machine learning methods.