Different bio-recognition, their applications and features.
\r\n\tIC offer services both at the macro-scale (country) and at the micro-scale (cities). The stability and the protection of these networks on both scales are a significant task, entrusted to the Operators who operate CI in a concession mandate. Due to the high level of interdependency of CI, which exchange services to each other for their functioning, their management and protection cannot be carried out by a "linearized" strategy (each infrastructure managed and protected independently on the others) due to the presence of tight links which connect each other. CI protection through provision of "smart" properties such as resilience, has become a complex task which must be tackled not only by deploying advanced technological means but also by triggering new management strategies, enabling holistic and global management policies.
\r\n\r\n\tThe book aims at providing an overview of the understanding of complex phenomena taking place on interdependent networks and of the advanced technical solutions related to management, risk analysis and resilience enhancement of networks, either from a theoretical and operational (i.e. with solution related to real or realistic cases) points of view. A large emphasis is provided to the capability opened by the use of field and remote sensing tools for monitoring and assessing risks on CI. The use of comprehensive data set, the access to big data is going to open the way to the realization of new tools for supporting the decision making process needed for both daily and emergency management.
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Brunoro",slug:"giselle-v.-brunoro"}]},{id:"34279",title:"The Genetics of CFTR: Genotype - Phenotype Relationship, Diagnostic Challenge and Therapeutic Implications",slug:"the-genetics-of-cftr-genotype-phenotype-relationship-diagnostic-challenge-and-therapeutic-implicatio",signatures:"Marco Lucarelli, Silvia Pierandrei, Sabina Maria Bruno and Roberto Strom",authors:[{id:"81744",title:"Prof.",name:"Marco",middleName:null,surname:"Lucarelli",fullName:"Marco Lucarelli",slug:"marco-lucarelli"},{id:"88095",title:"Dr.",name:"Silvia",middleName:null,surname:"Pierandrei",fullName:"Silvia Pierandrei",slug:"silvia-pierandrei"},{id:"88097",title:"Prof.",name:"Roberto",middleName:null,surname:"Strom",fullName:"Roberto Strom",slug:"roberto-strom"},{id:"124716",title:"Dr.",name:"Sabina Maria",middleName:null,surname:"Bruno",fullName:"Sabina Maria Bruno",slug:"sabina-maria-bruno"}]},{id:"34280",title:"Biochemical and Molecular Genetic Testing Used in the Diagnosis and Assessment of Cystic Fibrosis",slug:"biochemical-and-molecular-genetic-testing-used-in-the-diagnosis-and-assessment-of-cystic-fibrosis",signatures:"Donovan McGrowder",authors:[{id:"79123",title:"Dr.",name:"Donovan",middleName:null,surname:"McGrowder",fullName:"Donovan McGrowder",slug:"donovan-mcgrowder"}]},{id:"34281",title:"Pseudomonas aeruginosa Biofilm Formation in the CF Lung and Its Implications for Therapy",slug:"pseudomonas-aeruginosa-biofilm-formation-in-the-cf-lung-and-its-implications-for-therapy",signatures:"Gregory G. Anderson",authors:[{id:"82957",title:"Dr.",name:"Gregory",middleName:null,surname:"Anderson",fullName:"Gregory Anderson",slug:"gregory-anderson"}]},{id:"34282",title:"Outcome and Prevention of Pseudomonas aeruginosa-Staphylococcus aureus Interactions During Pulmonary Infections in Cystic Fibrosis",slug:"outcome-and-prevention-of-pseudomonas-aeruginosa-staphylococcus-aureus-interactions-during-pulmonary",signatures:"Gabriel Mitchell and François Malouin",authors:[{id:"87619",title:"Dr.",name:"Francois",middleName:null,surname:"Malouin",fullName:"Francois Malouin",slug:"francois-malouin"},{id:"89089",title:"Mr.",name:"Gabriel",middleName:null,surname:"Mitchell",fullName:"Gabriel Mitchell",slug:"gabriel-mitchell"}]},{id:"34283",title:"Infection by Non Tuberculous Mycobacteria in Cystic Fibrosis",slug:"infection-by-nontuberculous-mycobacteria-in-cystic-fibrosis",signatures:"María Santos, Ana Gil-Brusola and Pilar Morales",authors:[{id:"87481",title:"Dr.",name:"Pilar",middleName:null,surname:"Morales",fullName:"Pilar Morales",slug:"pilar-morales"}]},{id:"34284",title:"Atypical Bacteria in the CF Airways: Diversity, Clinical Consequences, Emergence and Adaptation",slug:"atypical-bacteria-in-the-cf-airways-diversity-clinical-consequences-emergence-and-adaptation",signatures:"Marchandin Hélène, Michon Anne-Laure and Jumas-Bilak Estelle",authors:[{id:"81613",title:"Prof.",name:"Hélène",middleName:null,surname:"Marchandin",fullName:"Hélène Marchandin",slug:"helene-marchandin"},{id:"88985",title:"Prof.",name:"Anne-Laure",middleName:null,surname:"Michon",fullName:"Anne-Laure Michon",slug:"anne-laure-michon"},{id:"88986",title:"Prof.",name:"Estelle",middleName:null,surname:"Jumas-Bilak",fullName:"Estelle Jumas-Bilak",slug:"estelle-jumas-bilak"}]},{id:"34285",title:"Viral Respiratory Tract Infections in Cystic Fibrosis",slug:"viral-respiratory-tract-infections-in-cystic-fibrosis",signatures:"Dennis Wat",authors:[{id:"92549",title:"Dr.",name:"Dennis",middleName:null,surname:"Wat",fullName:"Dennis Wat",slug:"dennis-wat"}]},{id:"34286",title:"Immune Dysfunction in Cystic Fibrosis",slug:"immune-response-in-cystic-fibrosis",signatures:"Yaqin Xu and Stefan Worgall",authors:[{id:"81718",title:"Prof.",name:"Stefan",middleName:null,surname:"Worgall",fullName:"Stefan Worgall",slug:"stefan-worgall"}]},{id:"34287",title:"Channel Replacement Therapy for Cystic Fibrosis",slug:"channel-replacement-therapy-for-cf",signatures:"John M. Tomich, Urška Bukovnik, Jammie Layman and Bruce D. Schultz",authors:[{id:"79549",title:"Prof.",name:"John M.",middleName:null,surname:"Tomich",fullName:"John M. Tomich",slug:"john-m.-tomich"}]},{id:"34288",title:"Improving Cell Surface Functional Expression of Delta F508 CFTR: A Quest for Therapeutic Targets",slug:"improving-cell-surface-functional-expression-of-deltaf508-cftr-a-quest-for-therapeutic-targets",signatures:"Yifei Fan, Yeshavanth K. Banasavadi-Siddegowda and Xiaodong Wang",authors:[{id:"88330",title:"Dr.",name:"Xiaodong",middleName:"Robert",surname:"Wang",fullName:"Xiaodong Wang",slug:"xiaodong-wang"},{id:"124468",title:"Dr.",name:"Yifei",middleName:null,surname:"Fan",fullName:"Yifei Fan",slug:"yifei-fan"},{id:"124470",title:"Dr.",name:"Yeshavanth",middleName:null,surname:"Banasavadi-Siddegowda",fullName:"Yeshavanth Banasavadi-Siddegowda",slug:"yeshavanth-banasavadi-siddegowda"}]},{id:"34289",title:"Fine Tuning of CFTR Traffic and Function by PDZ Scaffolding Proteins",slug:"fine-tuning-of-cftr-traffic-and-function-by-pdz-scaffolding-proteins",signatures:"Florian Bossard, Emilie Silantieff and Chantal Gauthier",authors:[{id:"87647",title:"Prof.",name:"Chantal",middleName:null,surname:"Gauthier",fullName:"Chantal Gauthier",slug:"chantal-gauthier"}]},{id:"34290",title:"CFTR Gene Transfer and Tracking the CFTR Protein in the Airway Epithelium",slug:"cftr-gene-transfer-and-tracking-the-cftr-protein-in-the-airway-epithelium",signatures:"Gaëlle Gonzalez, Pierre Boulanger and Saw-See Hong",authors:[{id:"84406",title:"Dr.",name:"Saw-See",middleName:null,surname:"Hong",fullName:"Saw-See Hong",slug:"saw-see-hong"},{id:"86153",title:"Prof.",name:"Pierre",middleName:null,surname:"Boulanger",fullName:"Pierre Boulanger",slug:"pierre-boulanger"},{id:"86155",title:"Dr.",name:"Gaëlle",middleName:null,surname:"Gonzalez",fullName:"Gaëlle Gonzalez",slug:"gaelle-gonzalez"}]},{id:"34291",title:"VIP as a Corrector of CFTR Trafficking and Membrane Stability",slug:"vasoative-intestinal-peptide-vip-as-a-corrector-of-cftr-trafficking-and-membrane-stability",signatures:"Valerie Chappe and Sami I. Said",authors:[{id:"84459",title:"Prof.",name:"Valerie",middleName:null,surname:"Chappe",fullName:"Valerie Chappe",slug:"valerie-chappe"},{id:"91057",title:"Prof.",name:"Sami",middleName:null,surname:"Said",fullName:"Sami Said",slug:"sami-said"}]},{id:"34292",title:"Pharmacological Potential of PDE5 Inhibitors for the Treatment of Cystic Fibrosis",slug:"pharmacological-potential-of-pde5-inhibitors-for-the-treatment-of-cystic-fibrosis",signatures:"Bob Lubamba, Barbara Dhooghe, Sabrina Noël and Teresinha Leal",authors:[{id:"88540",title:"Prof.",name:"Teresinha",middleName:null,surname:"Leal",fullName:"Teresinha Leal",slug:"teresinha-leal"},{id:"129673",title:"Dr.",name:"Bob",middleName:"Arthur",surname:"Lubamba",fullName:"Bob Lubamba",slug:"bob-lubamba"}]},{id:"34293",title:"Pharmacological Modulators of Sphingolipid Metabolism for the Treatment of Cystic Fibrosis Lung Inflammation",slug:"pharmacological-modulators-of-sphingolipid-metabolism-for-the-treatment-of-cystic-fibrosis-lung-infl",signatures:"M.C. Dechecchi, E. Nicolis, P. Mazzi, M. Paroni, F. Cioffi, A. Tamanini,V. Bezzerri, M. Tebon, I. Lampronti, S. Huang, L. Wiszniewski, M.T. Scupoli, A. Bragonzi, R. Gambari, G. Berton and G. Cabrini",authors:[{id:"53357",title:"Prof.",name:"Roberto",middleName:null,surname:"Gambari",fullName:"Roberto Gambari",slug:"roberto-gambari"},{id:"82889",title:"Dr.",name:"Song",middleName:null,surname:"Huang",fullName:"Song Huang",slug:"song-huang"},{id:"85366",title:"Dr.",name:"Maria Cristina",middleName:null,surname:"Dechecchi",fullName:"Maria Cristina Dechecchi",slug:"maria-cristina-dechecchi"},{id:"86524",title:"Dr.",name:"Elena",middleName:null,surname:"Nicolis",fullName:"Elena Nicolis",slug:"elena-nicolis"},{id:"86525",title:"Dr.",name:"Paola",middleName:null,surname:"Mazzi",fullName:"Paola Mazzi",slug:"paola-mazzi"},{id:"86527",title:"Dr.",name:"Moira",middleName:null,surname:"Paroni",fullName:"Moira Paroni",slug:"moira-paroni"},{id:"86528",title:"Dr.",name:"Federica",middleName:null,surname:"Cioffi",fullName:"Federica Cioffi",slug:"federica-cioffi"},{id:"86529",title:"Dr.",name:"Valentino",middleName:null,surname:"Bezzerri",fullName:"Valentino Bezzerri",slug:"valentino-bezzerri"},{id:"86531",title:"Dr.",name:"Maela",middleName:null,surname:"Tebon",fullName:"Maela Tebon",slug:"maela-tebon"},{id:"86536",title:"Dr.",name:"Ilaria",middleName:null,surname:"Lampronti",fullName:"Ilaria Lampronti",slug:"ilaria-lampronti"},{id:"86540",title:"Dr.",name:"Ludovic",middleName:null,surname:"Wiszniewski",fullName:"Ludovic Wiszniewski",slug:"ludovic-wiszniewski"},{id:"86541",title:"Dr.",name:"Maria Teresa",middleName:null,surname:"Scupoli",fullName:"Maria Teresa Scupoli",slug:"maria-teresa-scupoli"},{id:"86543",title:"Prof.",name:"Alessandra",middleName:null,surname:"Bragonzi",fullName:"Alessandra Bragonzi",slug:"alessandra-bragonzi"},{id:"86544",title:"Prof.",name:"Giorgio",middleName:null,surname:"Berton",fullName:"Giorgio Berton",slug:"giorgio-berton"},{id:"86546",title:"Dr.",name:"Giulio",middleName:null,surname:"Cabrini",fullName:"Giulio Cabrini",slug:"giulio-cabrini"}]},{id:"34294",title:"The Importance of Adherence and Compliance with Treatment in Cystic Fibrosis",slug:"the-importance-of-adherence-and-compliance-with-treatment-in-cystic-fibrosis",signatures:"Rosa Patricia Arias-Llorente, Carlos Bousoño García and Juan J. Díaz Martín",authors:[{id:"81752",title:"Dr.",name:"Rosa Patricia",middleName:null,surname:"Arias Llorente",fullName:"Rosa Patricia Arias Llorente",slug:"rosa-patricia-arias-llorente"},{id:"88980",title:"Prof.",name:"Carlos",middleName:"GarcÃa",surname:"Bousoño",fullName:"Carlos Bousoño",slug:"carlos-bousono"}]},{id:"34295",title:"Improving the Likelihood of Success in Trials and the Efficiency of Delivery of Mucolytics and Antibiotics",slug:"improving-the-likelihood-of-success-in-trials-and-efficiency-of-delivery-of-mucolytics-and-antibioti",signatures:"Carlos F. Lange",authors:[{id:"87618",title:"Prof.",name:"Carlos",middleName:"Frederico",surname:"Lange",fullName:"Carlos Lange",slug:"carlos-lange"}]},{id:"34296",title:"Airways Clearance Techniques in Cystic Fibrosis: Physiology, Devices and the Future",slug:"airway-clearance-techniques-in-cystic-fibrosis-physiology-devices-and-the-future",signatures:"Adrian H. Kendrick",authors:[{id:"81571",title:"Dr.",name:"Adrian",middleName:"H.",surname:"Kendrick",fullName:"Adrian Kendrick",slug:"adrian-kendrick"}]},{id:"34297",title:"The Physiotherapist's Use of Exercise in the Management of Young People with Cystic Fibrosis",slug:"the-physiotherapist-s-use-of-exercise-in-the-management-of-young-people-with-cystic-fibrosis",signatures:"Allison Mandrusiak and Pauline Watter",authors:[{id:"84089",title:"Dr.",name:"Allison",middleName:null,surname:"Mandrusiak",fullName:"Allison Mandrusiak",slug:"allison-mandrusiak"},{id:"87978",title:"Dr.",name:"Pauline",middleName:null,surname:"Watter",fullName:"Pauline Watter",slug:"pauline-watter"}]},{id:"34298",title:"Exercise Performance and Breathing Patterns in Cystic Fibrosis",slug:"exercise-performance-and-breathing-patterns-in-cystic-fibrosis",signatures:"Georgia Perpati",authors:[{id:"79721",title:"Dr.",name:"Georgia",middleName:null,surname:"Perpati",fullName:"Georgia Perpati",slug:"georgia-perpati"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"75180",title:"Optoelectronics and Optical Bio-Sensors",doi:"10.5772/intechopen.96183",slug:"optoelectronics-and-optical-bio-sensors",body:'OB are classified as one of the most reliable recognizing and detecting devices. Ideally, they are composed of integrated system of photonic sources and biomolecule recognition component, which in spatial contact with the transductor, that can recognize and interact with specific molecule analytes present in sample [1, 2]. The interaction induces a variation in an electrical, optical or mechanical property of the transduces, the degree of variation reflects to the quantity of the analytes [2]. The fundamental structure of OB features the 1- bio-recognition element, such as; enzymes, nucleic acids, antibodies, microbes, polysaccharides. 2- Single transductor including electrical current, potential, impedance, EM radiations, mass, optical, piezoelectric or thermal, and 3- amplifier [3, 4, 5, 6]. The interaction occur between bio-recognition element and analyte produces a signal due to a number of factors, either alteration in proton concentration, release or capture of gases or electron, or light mission, absorption or reflectance, heat emission, change in mass [4]. The produced signal can be converted into measurable value (e.g. current, temperature alteration) by the transducer as shown in Figure 1.
Schematic diagram illustrate biosensor structure [7].
OB provide an accurate and sensitive, timely detection technology [8]. In the current era, having such an analytical and informative features become an essence, especially in healthcare diagnostics, environment quality monitoring, food safety and security, biological warfare and biodefense [9]. Therefore, it become an attractive tool that subjected to a modification and development and emerging with nanotechnologies, microelectromechanical systems (MEMS), biotechnologies [10, 11, 12]. This reflected in the rapid advancement in biosensors, which is associated with the market growth application and is estimated by 21.18 billion USD in North America in the 2020 [13]. There is no universal or standard OB for detection; however, there are groups of OBs developed for specific applications and targets.
There are a broad range of OB classification. Generally, the classification can be divided into two main classes: label-free and label-dependent classes. In label-free class the measured signal is produced directly by the interaction between transducer and the bio-analyte. Whereas in label-based sensors, a label is needed to produce signal, which can be measured later by a colorimetric, luminescent or fluorescent method as can be illustrated in Figure 2 [14].
Illustration graph showing label and label free recognition classes of OB.
Label-free mode is more economically efficient in comparison to label dependent mode. It requires less effort and expertise and eliminate the experimental errors such that resultant from label shelf life, signal noise background. These are commonly seen in antibody–antigen interaction using label, which has a wide application in detection technologies [15].
Different bio-recognisers are used in the OB detection and quantifying technologies. The diversity of the detected materials required a suitable recognizing element. Examples of analytes in the samples; genetic material, toxins, drugs, enzymes, heavy metals [16, 17, 18, 19]. Enzymes, nucleic acids, antibodies, cells and micro-organisms are commonly used as bio-recognisers [20, 21, 22, 23, 24]. Table 1 shows some of their applications and features in biosensing.
Biorecognition | (Bio)sensors | Selected application | Physical transducer/liner range | Detection limit |
---|---|---|---|---|
Enzyme | Multilayers of silver metal and tantalum oxide nanoflakes with acetylcholinesterase enzyme OB [25] | Alzahimer’s disease diagnosis | 50–400 uM | 8.709 nm/μM and a remarkable LOD value of 38 nM |
Tyrosinase on Fe3o4@Au core shell nanoparticles bio-probe [26] | Detection of dopamine, phenol and catechol | Linear response in the concentration range 5.0–75.0 μM, 10.0–100.0 μM for phenol and dopamine and 50.0–500.0 M for catechol | ND | |
Carbon nanofiber gold nanoparticles tyrosinase [27] | Detection of ferulic acid in cosmetics | ND | 2.89 × 10−9 mol/L | |
Nucleic acids | DNA - AuNTs-PC electrode | Human papilloma visus 16 & 18 [28] | 0.01pM to 1 μM. | 1 fM |
Disposable electrodes were fabricated by thermal evaporation on polyethylene terephthalatesubstrates covered with a nanometric gold layer manufactured in three-contact configurations | Zika virus [29] | 25 nM and 340 nM | 25 nM | |
Antibodies and Immuonsensor | Antibody against Aflatoxin immunosensor [30, 31] | Aflatoxin detection in food | ND | 100 pg./mL |
Graphene oxide (GO) composite and staphylococcal protein A [32] | Human IgG detection | 40–120 um/ml | 10 ng/mL | |
Cell/Microbial -based sensor | Bioelectric Recognition Assay [33] | L. monocytogenes detection | ND | 102 CFU/mL |
Different bio-recognition, their applications and features.
NM = not determined.
An optical measurement concept is used by optical biosensors devices. Fiber optics are used along with optoelectronic transducers in these devices. The opt rode term is composed of optical and electrode terms. Enzymes and antibodies such as transducing elements are examples of what types of elements involved in these sensors. A secure non-electrical is permitted in optical biosensors, in which a sensing of equipment is inaccessible [34]. An additional advantage is that devices do not require reference sensors [35]. The reason behind that is that a light source can generate a comparative signal, which is similar to that of the sampling sensor. In order to ecxite the sensing element, optical source such as LED or Laser should be focused into substrate and photodetector capture the output signal as shown in Figure 3 [36].
Schematic for optical biosensor working method [36].
Biosensors in general divided into categories which are Bioreceptor and Transducer. While, Optical biosensors are divided into two groups, which are: direct optical biosensor detection and labeled optical biosensor detection as follow:
Evanescent wave-based biosensors are used to investigate the exponential growth in life science applications. They include the dissociation and binding kinetics of receptor-ligand pairs and antibodies, epitope mapping, interactions between protein-DNA and DNA–DNA, phage, show libraries, and interactions between virus-protein and whole cell [37].
Waveguide interferometers have remarkable significance, because they merge both sensitive techniques that are: wave guiding and interferometry techniques. Hence, they provide great reliability and potential miniaturization and integration in optical chips. Through the utilization of evanescent wave technology, the interaction between biomolecules and receptors are measure by the waveguide interferometer in real time without using labels. On a sensor surface, receptors are frozen and the interaction with the close biomolecules leads to a variation in the refractive index. With being far from the surface, the evanescent wave decays exponentially, usually over the distance of 100 nm to approximately a wavelength. Due to the reason that the evanescent wave is a near-surface phenomena, therefore, by using the detection of evanescent wave stimulation to produce fluorescent signal is surface-sensitive. This means that solely fluorescent molecules close to the surface are stimulated as seen in Figure 4 [37, 38, 39, 40].
Evanescent wave fluorescence biosensors working method and the separation of molecules in the surface.
Fiber optic is an example of analytical devices that works as a transduction item, in which it generates a signal proportional to the density of chemical or biochemical elements with react of the biological element. In addition, they transfer light with silica glass or plastic fiber optic fiber based on the Total Internal Reflection (TIR) principle to the analysis site [41]. The fiber optics biosensors are categorized into two different types:
Intrinsic sensors: the environmental changes are transformed by the internal property of the optical fiber itself into light signal modulation. This light signal modulation may be in the form of phase, intensity, and frequency or it may be polarization [42].
Extrinsic sensors: on the other hand, the extrinsic sensors can use the fiber as carriers of information leading to a black box. In addition, these sensors produce a light signal based on the received information at black box. This black box can be made of gas, mirrors liquid cells or several other optical signal generation mechanisms (Figure 5) show the difference between Intrinsic and extrinsic optical biosensor) [44].
(a) Extrinsic types of fiber optic sensors, and (b) intrinsic types of fiber optic sensors [43].
The fiber-optical sensors essential benefits can vary from their: 1) capability of hard environment to robust EMI (electromagnetic interference immunity), chemical corrosion, high temperature, high voltage, and pressure. 2) Low power, very small size, and passive. 3) Exceptional performance such as wide bandwidth and high sensitivity. 4) Processing of long range. 5) They applied distributed or multiplexed measurements to cope with their main flaw of high cost and unfamiliarity of end-user [45].
Backscattering interferometry (BI) sensor is another category of optical biosensors. The detector can measure the uncalculated reflected intensity of a small sensing area by using a single wavelength laser light. Based on the sub wavelength formation on the top sensing area, the detector results in an interference pattern [46].
The improvement of Backscattering as a label-free detection technique appeared in field and applications as following: (a) applied to what is called lab-on-a-disc, (b) Silicon Sensor Surfaces SSS (bio reactions) application (c) Measuring minor refractive index transformations in capillaries of fused silica, and (d) Bio molecular interaction control in microfluidic channels [47].
Backscattering applications started with measuring bio molecular interactions on porous silicon based optical systems. In the pores, the surface is adjusted using elements of bio molecular recognition. Fabry-Perot fringes result in an interference pattern of impinging white light above and below the optical interference layer [48].
In order to investigate molecular interaction, a physical technique known as reflectometric interference spectroscopy is used. This technique depends on white light being interfered at thin films as shown in Figure 6. In Reflectometric Interference Spectroscopy (RIfS), biomolecular reactions happen on the sensing component. The sensing component is a glass slide adjusted with a thin layer of translucent dielectric material (e.g., SiO2, SiO2–Ta2O5). When the white light strikes the reverse side of the glass, an intervention occurs from the partial beams, reflected at each interface. This intervention alternates maximum and minimum reflectance range [50], which corresponds to the constructive and destructive reflected radiation interference. Biomolecular reactions cause build-up of an adlayer on top of the dielectric, which increases the optical path length. This results in a reflectance spectrum change [51]. This change can be associated with the intensity of the reacting biomolecules and is equivalent to the increase in thickness. Information about the viscosity and refractive index of the adsorbed protein layer is given by alterations in the polarized light phase and amplitude. For the identification and quantification of diclofenac in bovine milk, this approach was used, and the detection limit obtained was 0.112 μg.
Schematic illustration of (a) the RIfS principle and (b) the RIfS measurement system [49].
Surface Enhanced Raman scattering (SERS) spectroscopy method are used for the extremely sensitive biological analytes. With rapid growth during the last four decades, surface-enhanced Raman scattering has become one of the most reliable spectroscopic method. Applications for (SERS) detection are expanding quickly in various fields such as materials science, chemistry, biochemistry, and life sciences. Remarkable growth has resulted in biological and biomedical sensing applications from advances in the creation and production of SERS-based biosensors particularly. Electromagnetic improvement leads primarily to SERS improvement, and the configurations of the hotspot are essential to the success of responsive and reproducible detection [52]. Biosensors that are SERS-based can be generated according to the sensing requirements through direct and indirect methods. To define SERS, it is an extremely sensitive optical detection method using lasers in molecules adsorbed on the top of a metal nanoparticle in order to excite vibrational transitions. The Raman cross-section for a molecule on a surface is enhanced by factors of 10 caused by large optical fields. Because of molecular vibrational events, Raman scattering depends mainly on the loss (Stokes) or gain (anti-Stokes) of energy; from inflexible scattered photons and represents the information on the molecular structure, allowing in situ and real-time detection [53, 54]. SERS is a subclass of Raman dispersion and provides a million-fold improvement by plasmonic nanostructures, making the sensitivity of detection down to the level of a sole molecule as can be seen in Figure 7.
(A) SERS substrate modification by antitarget antibody, (B) target isolation, followed by binding of nanoparticles (NPs), (C) labeled by SeRS tag, and SeRS-tag detection [55].
The first observation of SPR physical phenomenon was in 1902. Through decades, this observation of an esoteric optical phenomenon developed into a complete comprehension of surface plasmon physics. Then, the first successful usage of SPR was in 1983 through the fabrication of an SPR-based sensor to detect the interactions of bimolecular. Pharmacia Biosensor AB was launched the first commercial SPR-based biosensor device, which was renamed as Biacore later. Currently, several manufacturing are fabricating SPR devices. Moreover, nowadays, the SPR-based biosensor is the dominant method of biosensing [56, 57].
The SPR appears on that surface of the device, when a polarized light such as Laser or LED is illuminated to the metal surface (usually gold or silver coated service) at a particular angle and at the interface of two media (commonly water and glass). This led to the surface plasmons generation and thus a reflected light intensity reduction is created at a particular angle known as the resonance angle. This impact is proportional to the mass on the surface. To obtain a sensogram, the shift of reflectivity, wavelengths or angle are measure against time. In all configuration, label-free, direct and real-time changes of refractive index is enabled by the phenomenon of SPR at the surface of sensor, in which it is proportional to the concentration of the biomolecule as shown in Figure 8 [58].
The schematic of the working principle of SPR and the steps of the SPR analytical cycle.
With the widespread and increased demand of biological sensing devices, there has been a considered attention on reliable and multipurpose biomolecule detection systems. The motivation to produce these detection systems become greater due the rising of health awareness and spread of aging in world population. The affinity-based biosensors, which consists of a biological element and a transducer, is one of the well-known biological agent sensing devices. In the biosensor, the biological element is typically used to identify the substance that necessarily must be detected. While the transducer is used to convert the energy from one form to another, which means converting the event of bio- recognition into an electrical signal that is measurable [59, 60].
Different types of transducers for biosensors are available currently; some of them are piezoelectric transducer, optical transducer and electrochemical transducer. Optical methods have become the most know method among these transducers, which are: surface plasmon resonance (SPR) spectroscopy, interferometry, fluorescence spectroscopy and evanescent wave-based detection. In the past years, the fluorescence-based detection methods, such as Enzyme-Linked Immunosorbent Assay (ELISA), have been implemented due to their capabilities of high throughput for samples and device sensitivity. But recently the new detection methods require processing of time-consuming labeling with several procedures of protocol detection. Detection systems based on the technology of SPR based bimolecular detection have been commercialized successfully regardless of their novelty. In addition, this method simplifies real-time controlling with high sensitivity without requiring any procedures of labeling. Nevertheless, the current implemented and commercial SPR sensors are comparatively massive size systems and have low throughput, in which they limit their applications range. Hence, higher throughputs are needed with additional disposable and compact SPR system, even though that some of their problems have solved partially [56, 61, 62, 63, 64].
This section and all the fabrication and results have been achieved previously by MQW Group at UCF [56, 57, 58, 59, 64]. In this work, a sensor head of optical surface plasmon resonance (SPR) has illustrated in this work. It depends on an inverted-rib dielectric waveguide. The changes happen at the gold metal-dielectric interface, in which the resonance wavelength of the surface plasmon is excited. These changes are in relationship with the environment changes that occur at the top metal surface. The sensor head of the SPR with the inverted-rib dielectric waveguide composed of SU-8 polymer layer with 1.5 refractive index, whereas the cladding lower layer contains silicon oxynitride (SiOxNy) with 1.526 refractive index. The top layer is painted with a 50 nm gold thick layer. The design of sensor head of the SPR permits controlling the media of analyte with 1.44 to 1.502 refractive index. By using reference liquids collection that represent the analyte medium, an analyzer of optical spectrum and a broadband light source were utilized to measure the SPR sensor sensitivity. It was realized that when a liquid contacts the gold metal with 1.442 refractive index, the transmission spectrum has a sharp resonance dip at 1525 nm and with using a liquid of 1.502, its position was shifted to 1537 nm. Therefore, based on these measurements, the sensor devices sensitivity was specified to be S = 232 nm.RIU-1. In this section, we demonstrate that the device can be integrated completely with a photodetection unit, a wavelength tunable light source and a liquid delivery system through microfluidic channels to make it an extremely compact unit [56, 57, 58, 59, 64].
Surface Plasmon is the Propagation of transverse magnetic (TM) surface electromagnetic waves at the dielectric interface of a gold metal. Below is the dispersion relation Eq. (1) which can be used to calculate the propagation constant.
The design of the reversed rib waveguide was to solely support the essential TM directed mode. The waveguide’s dimensions were chosen depending on waveguide dispersion relationship in Eq. (2).
Moreover, a particular surface plasmon resonance wavelength will appear from the refractive index of the analyte material that interacts with the gold-metal. To determine theoretical dependence, matching condition criterion for the surface plasmon propagation constant (Eq. (3)) can be used.
After all the equation have been calculated, The SPR sensor with the propagation of the waveguide has been design and simulation as shown in Figure 9.
Optical waveguide based surface plasmon excitation configuration and schematic of the SPR sensor head.
In order to define the wave vectors of the directed mode, the exact values of the refractive indices of the directing and cladding layers are important and therefore satisfy the matching condition for the SP mode to be launched. Hence, to design the top of the SPR sensor, the refractive indices for both films need to be classified carefully. To make the directing layer of the top of the SPR sensor; a SU-8 polymer with a fixed refractive index of 1.568 at 1550 nm, is used. Although the silicon oxynitride (SiOxNy) cladding layer film, generated using plasma enhanced chemical vapor deposition (PECVD), has a refractive index as shown in Figure 10, it can be changed by adjusting the relative nitrogen to oxygen composition of the SiOxNy film [56, 57, 58, 59, 64].
Refractive index (n) and K=kelvin of SU-8 film as function of wavelength measures using ellipsometer.
Eq. (3) calculated the theoretical dependence as appears in Table 2.
Analyte medium refractive index | Surface plasmon refractive index | Theoretical wavelength (nm) |
---|---|---|
1.44 | 1.463 | 1539.5 |
1.47 | 1.484 | 1533.8 |
1.49 | 1.504 | 1530 |
1.5 | 1.515 | 1528.1 |
1.518 | 1.533 | 1524.68 |
1.51 | 1.5255 | 1526.2 |
Calculated wavelength vs. the surface plasmon refractive index.
The beam propagation in the SPR sensor head is shown in Figure 11 as simulated using a RSoft beam package. It is noted here that the maximum size of the waveguide that can only support the basic TM mode are 4 μm and 500 nm respectively. The input light was given by the enhanced spontaneous emission of an erbium doped fiber transformer.
(a) Simulation of SPR sensor head performed by RSoft. (b) Fundamental mode for the simulation parameter from (a). (c) Real fundamental mode after fabrication and testing.
To guarantee that only the TM mode is launched to the SPR sensor waveguide by A 40× microscope objective lens, a polarizer was used. In Figure 12, the transmitted light at the output of the device was focused into an optical fiber. To monitor the transmission spectrum the optical fiber is connected to the Optical Spectrum Analyzer (OSA).
The emission spectrum from the SPR sensor head before placing the sample liquids.
It is probable that a resonant transfer of power from the waveguide can occur at the specific wavelength. The waveguide mode and the surface plasmon mode match the perfect pairing condition between them. In order for that to happen a wide spectrum of light needs to be launched into the system. For that reason, the spectrum of the transmitted light is almost the spectrum of the input light dip at the wavelength of SPR.
One after another, a set of analyte media with calibrated refractive indices (sample liquids) above the Top of the SPR sensor were implemented. To measure the transmission spectrum OSA was used to decide the wavelength of SPR. The transmission spectra for analyte media of refractive indices 1.462, 1.496, and 1.502 correspondingly. As shown in Figure 13, the sharp dip in the transmission spectrum moved to a shorter wavelength while lowering the sample liquid refractive index [54, 56, 57, 58, 59].
Emissions spectrum after placing the different sample liquids.
OB detection technology offers a timely, effective and inexpensive tool to measure analytes in samples. It facilitates the detection in different areas, such as; biomedical, environmental and foods. The development and demand of using such technology will continue to grow within the current and upcoming decades, which will result in introducing new generations of OBs to the analytical and diagnostic markets worldwide.
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