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Early disease diagnosis and management are crucial aspects of healthcare and research. Biomarker recognition is one of the vital techniques that efficiently provides real-time and precise biological information for early diagnosis. Biomarkers are used as crucial biological indicators in medical exploration and treatment. The examination of biomarkers has evolved into a promising non-invasive means for safe, informal and pain-free monitoring, with the potential to amend the current methods of medical analysis and management. Rapid progress in sensor technology, has led to the development of high-performance sensors for human health monitoring. Since as early as 1867, molecular sensors have been renowned as intelligent devices capable of addressing various issues associated with our environment and health. In the human healthcare system, sensors are garnering interest owing to their high potential to provide incessant and immediate physiological and chemical information, as well as non-invasive measurements of biomarkers in human bio-fluids such as saliva, tears, sweat, interstitial fluid, and human volatiles. In this chapter, we have concisely described numerous types of biosensing units and their operation as well as the role of biosensors in detecting various types of biomarkers in humans.

Human health has always been one of the more intricate issues in contemporary science.1  Diseases are an inherent aspect of human life. However, the diseases that may seem relatively manageable in well-established countries can indeed have devastating consequences in less developed regions across the globe. Some diseases can impose significant physical, emotional and socioeconomic burdens by claiming thousands of lives. The cost, both in material resources and ethical considerations, can be profound throughout the treatment procedure. Cardiac diseases, cerebral diseases, and hypertensive heart diseases collectively contribute significantly to global mortality rates, as highlighted by World Health Organization (WHO) statistics.2  Cancer disease is one of the most dangerous diseases and a noteworthy obstacle for global development. Cardiovascular disease has 100 diverse variants that can affect different major organs in the human body. It is one of the main causes of mortality and disease worldwide.3–5  Human beings are exposed to an escalating number of biological toxicants, some of which have steadily been revealed to be imperative hazard factors for metabolic diseases, such as obesity and diabetes.6  Diabetes mellitus includes both acute and chronic problems, making it a complex and multifaceted condition.7  Kidney diseases are complex and heterogeneous with acute kidney injury (AKI) being common in kids and coupled with increased inpatient death and duration of hospital stay.8  According to WHO, psychological diseases present overwhelming rates of incidence, morbidity, death, and disability. Affliction with a grave psychological illness decreases regular life expectancy by 13 to 32 years.9,10  In most Western countries, despite mortality, mental health disorders are indeed the foremost cause of disability, contributing significantly to chronic sick leave and about 4% of the gross domestic product.11  In total, the analysis and treatment of such severe ailments has been a considerable focus for both academicians and state officials, who have devotedly worked to discover efficient techniques and supplies for earlier and cheaper diagnosis and competent treatment. Human health and performance monitoring (HHPM) is essential for providing inferences crucial for shielding, estimating, supporting and humanizing people in various professional areas, for example, academia, industry, recreation, sports, and military.12  The detection of disease at an early stage plays a pivotal role in disease control and prevention efforts. Early detection allows for prompt medical intervention, which can prevent the progression of disease to more advanced stages. Diseases that are detected early are often more treatable, leading to lower rates of morbidity and mortality.13,14  The traditional screening techniques such as biopsy, blood analysis and clinical imaging have been valuable in diagnosing diseases, but they have limitations, especially when it comes to detecting diseases at very early stages.15  The blood analysis process entails the invasive gathering of blood samples from the human body, generally few micro- or milliliters, which is associated with pain and discomfort and needs trained staff to collect the blood.16  One way to diagnose diseases at an earlier stage is the application of precise molecules entitled biomarkers. Indeed, biomarkers play a crucial role in medical diagnosis and therapy.

Biosensors have the capability to identify a single biomarker or an array of biomarkers with remarkable sensitivity and specificity, even when they are present in low or minute concentrations. These are measurable indicators of normal biological processes, pathogenic processes or responses to therapeutic interventions.17  These biomarkers can be genes, proteins, cells, enzymes, or other measurable substances found in blood, urine, tissue or saliva. These bio-molecules are responsible for various roles in an organism, for example the transmission and storage of hereditary information, regulation of biological activities, catalytic actions or transport of various molecules and they are possibly present in body fluids like blood, urine, or oral fluid and tissues such as tumor tissue.18,19  In individuals who are sick, the level of convinced biomarkers may be found above or below the standard.20  An ideal biomarker should be capable of identifying and monitoring the disease, identifying the particular endotype/phenotype, and detecting the prognosis, effortlessly with minimum distress or threat to the patient. The primary objective of biomarker identification and utilization is to enhance both the diagnosis as well as the treatment of diseases, ideally at the earliest stages possible, to maximize the benefits to patients. Understanding the pathophysiological connection between a biomarker and an investigative and therapeutic endpoint is essential to understand the significance of a biomarker.21,22  There are few important points to consider for a particular molecule to be recognized as a biomarker: (a) there must be substantial confirmation linking the molecule to the disease or condition of interest, (b) the biomarker must be assessable using reliable and validated methods that adhere to appropriate guidelines and standards, and (c) that the results obtained from measurements must be consistent and reproducible across studies conducted in different laboratories.21  Generally, biomarkers are widely used for the early identification of several diseases, including the majority of lethal ones, for example heart disease, cancer and diabetes. Biomarker measurements can help elucidate the empirical outcomes of clinical trials by linking the effects of interventions on cellular and molecular pathways to clinical responses. In recent years, there have been significant efforts to discover biomarkers as promising tools for enhancing prevention, diagnosis, and drug response and development in psychiatric disorders. Currently, no devices or examinations are able to predict critical events, for instance, heart attacks, heat strokes, or epilepsy episodes. Additionally, various health situations, such as lengthy COVID-19 and Alzheimer disease, do not yet have characteristic alarming bio-molecules or biomarkers. For the detection of a biomarker, one should use an explicit appliance termed sensor. A sensor is an apparatus or a device that responds to various stimuli such as changes in temperature, sound, pressure, etc. and responds with an electrical signal. These electrical signals can be measured, analyzed or processed to obtain information about the environment or the target being sensed. The sensors are composed of a recognition element or a bioreceptor that is responsible for recognizing the target analyte and a transducer (e.g., electronic or electrochemical, optical, surface-enhanced Raman scattering (SERS) and heat or mass-based) that translates the detection event into a measurable signal.23  Sensors employ various transduction methods to convert a stimulus into an electrical signal, facilitating the measurement and analysis of the analyte. There are numerous optical and electrochemical transduction methods used for the read out. Potentiometry, voltammetry, colorimetry, and fluorimetry are the most widely established and adopted transduction methods due to their simplicity, cost effectiveness, fast response time, detection of low analyte concentration etc. The electrochemical technique is commonly used for analyzing test samples in aqueous matrices due to its versatility, sensitivity and suitability for real time measurements.22  Optical sensor systems utilize chemical or biological reactions that modify optical detection elements, leading to changes in light emission, absorption or scattering. When sensors are developed using nanotechnological methods and nanomaterials, they are referred to as nanosensors.24  Electrochemical transducers commonly utilize conducting carbon materials like gold and silver surfaces due to their excellent electrochemical stability and high electrical conductivity.25  The availability of metallic nanoparticles in different shapes and sizes, their solubility and long-term stability, as well as their cost effective properties make them generally preferred for various applications.26  Nanomaterials such as carbon nanotubes (CNTs), graphene, MXenes, metal–organic framework (MOFs) are also promising candidates for developing highly sensitive transducer surfaces.27 

The main focus of this chapter is to examine how nanosensors contribute to the detection of biomarkers. The initial segment of the chapter is dedicated to exploring the biomarkers and their role in disease diagnosis. However, the latter part of the chapter gives a brief description of the nanomaterials and their classification describing its use as sensing elements, as well as its advantages in sensor design. Finally the detection of biomarkers has been discussed in detail. We have also discussed electrochemical, optical, magneto resistance and surface plasmon resonance (SPR) based sensors and their applications in detail. The chapter concludes with a detail discussion on the future scope of sensors in biomarker detection.

In the identification of disease, biomarkers are crucial for predicting the onset of certain diseases, thus allowing for early detection, prognosis and personalized treatment strategies. The use of biomarkers for prognostic and diagnostic purposes dates back to the 19th century.28,29  The search for protein cancer biomarkers in urine marked the beginning of research in biomarkers (Bence Jones protein).30  The 1950s marked a significant period in the history when Dr Abraham White and his colleague identified few molecules in the blood which can serve as potential indicators for myocardial infarction and other cardiovascular disease. From then on, the term “biomarker” became evident in the literature.31,32  The United Nations’ World Health Organization (WHO) defines a biomarker as any substance, structure or process measurable within the body or its products, which can influence or predict disease incidence.33  Since 1970s, the detection of cancer biomarkers has marked a significant advancement, paving the way for extensive research in this area. With the advent of human genome sequencing in 2000s, the discovery of gene biomarkers gained momentum. Today, research in biopharmaceutical and biotechnology sectors has expanded significantly to focus on novel biomarkers and their applications. Biomarkers are indispensable tools in modern medicine, serving as biological indicators that reflect various aspects of health and disease. They encompass a wide range of biophysical and biochemical parameters, offering insights into biological processes, physiological functions, and even responses to therapeutic interventions.34,35  In diagnostics, biomarkers can be used to detect the presence of a disease, assess its severity, or monitor its progression. For example, elevated levels of certain proteins in the blood can indicate the presence of specific diseases, such as cardiac troponins for myocardial infarction or prostate-specific antigen (PSA) for prostate cancer. Similarly, biomarkers like blood glucose levels are vital for diagnosing and monitoring diabetes. Biomarkers serve as a comprehensive term encompassing the utilization and advancement of tools and technologies for monitoring drug discovery and development.36  Biomarkers represent crucial cellular or molecular occurrences that significantly contribute to comprehending the interplay between exposure to biological chemicals, the onset of chronic human diseases, and the identification of high risk subgroups.37  Additionally, they serve as notable diagnostic indicators for assessing the presence or risk of disease. Therefore the biomarkers are also referred to as the ‘molecular signature’ of a disease’s physiological state at a specific moment.38  Biomarkers are objectively measured and assessed characteristics that indicate normal pathogenic processes, biological activities, or responses to therapeutic intervention. Biomarkers encompass a variety of molecules found throughout various organs of human bodies such as genes, nucleic acid sequences (RNA, DNA and m-RNA), enzymes/proteins, lipids, circulating lump cells or extracellular vesicles. As personalized medicine gains traction in current therapeutics, the significance of biomarkers is steadily increasing. They enable detailed and objective patient characterization which is a fundamental aspect of personalized medicine.30  Biomarkers serve as invaluable indicators, offering insights not just into present ailments but also provide us information regarding individualized medical condition. In individuals who are unwell, certain biomarkers deviate from standard levels, either dropping below or rising above the normal level.

A perfect biomarker demonstrates high specificity, sensitivity, and predictive value.2  Furthermore, it should prioritize patient safety and ease of detection, ideally through non-invasive means, to enhance accessibility and comfort.39  Choosing the right biomarkers to indicate both healthy and diseased states is crucial for early disease detection and effective treatment, enabling identification before the symptoms become apparent. Analyzing the outcomes obtained from both patient and normal samples offers rapid insights into morbidity, sub-clinical conditions, and other biological information. The detection of biomarkers is imperative and should be carefully evaluated as indicators of normal biological and pathogenic criteria. Biomarkers are developed and confirmed through the process of analytical validation, clinical validation, and the manifestation of clinical utility.40 

The US Food and Drug Administration (FDA) and the National Institute of Health (NIH) have categorized biomarkers into various types according to their primary clinical applications including diagnostic, response/pharmacodynamic, monitoring, predictive, safety, prognostic and risk/susceptibility biomarkers.41,42  Clinical biomarkers43  are primary aimed at diagnosing specific disease states, as outlined and exemplified in Table 1.1.

Table 1.1

Classification of clinical biomarkers with examples.

Category of biomarkers Definition Example
Diagnostic biomarker  A biomarker used to detect any specific disease at an early stage or identify subtypes.  Carcinoma antigen 125 biomarker may be used as diagnostic biomarker for ovarian cancer.44   
Response//pharmacodynamic  A biomarker used to access the biological reaction to a medical product or an environmental factor.  Blood pressure and antibodies can serve as response biomarkers in the assessment of patients with hypertension and vaccination effectiveness, respectively.17   
Monitoring biomarker  A biomarker used to monitor the status of a disease or to quantify exposure to a medical product and the response to the interventions.  During the medical examination for risk of kidney and diabetes malfunction creatinine and glucose are used as monitoring biomarkers, respectively.17   
Prognostic biomarker  A biomarker utilized to assess the likelihood of a clinical event, disease recurrence or progression in patients who have been diagnosed with the disease.  Elevated levels of PSA can serve as a prognostic biomarker during follow-up assessments with prostate cancer patients, aiding to gauge the probability of cancer progression.45   
Susceptibility/risk biomarker  A biomarker utilized to assess an individual’s risk of developing a disease or clinically noticeable medical condition.  Breast cancer genes 1 and 2 (BRCA1/2) mutations can serve as a biomarker for assessing the risk of individuals’ predisposition to developing breast cancer.46   
Predictive biomarker  Predictive biomarkers are employed to evaluate the probability of disease onset, predicting its occurrence before symptoms manifest.  Cytokines, antibodies targeting amyloid-beta protein and homocysteine levels is taken as predictive biomarkers for Alzheimer’s disease.47   
Safety biomarkers  A biomarker quantified to signal the likelihood, onset or extent of toxicity as an adverse outcome.  Bilirubin and creatinine are safety biomarkers for drugs which affect liver and kidney, respectively.48   
Category of biomarkers Definition Example
Diagnostic biomarker  A biomarker used to detect any specific disease at an early stage or identify subtypes.  Carcinoma antigen 125 biomarker may be used as diagnostic biomarker for ovarian cancer.44   
Response//pharmacodynamic  A biomarker used to access the biological reaction to a medical product or an environmental factor.  Blood pressure and antibodies can serve as response biomarkers in the assessment of patients with hypertension and vaccination effectiveness, respectively.17   
Monitoring biomarker  A biomarker used to monitor the status of a disease or to quantify exposure to a medical product and the response to the interventions.  During the medical examination for risk of kidney and diabetes malfunction creatinine and glucose are used as monitoring biomarkers, respectively.17   
Prognostic biomarker  A biomarker utilized to assess the likelihood of a clinical event, disease recurrence or progression in patients who have been diagnosed with the disease.  Elevated levels of PSA can serve as a prognostic biomarker during follow-up assessments with prostate cancer patients, aiding to gauge the probability of cancer progression.45   
Susceptibility/risk biomarker  A biomarker utilized to assess an individual’s risk of developing a disease or clinically noticeable medical condition.  Breast cancer genes 1 and 2 (BRCA1/2) mutations can serve as a biomarker for assessing the risk of individuals’ predisposition to developing breast cancer.46   
Predictive biomarker  Predictive biomarkers are employed to evaluate the probability of disease onset, predicting its occurrence before symptoms manifest.  Cytokines, antibodies targeting amyloid-beta protein and homocysteine levels is taken as predictive biomarkers for Alzheimer’s disease.47   
Safety biomarkers  A biomarker quantified to signal the likelihood, onset or extent of toxicity as an adverse outcome.  Bilirubin and creatinine are safety biomarkers for drugs which affect liver and kidney, respectively.48   

On the basis of secretion location, appearance, molecular weights and physicochemical properties biomarkers vary widely. On the basis of origin, biomarkers can be classified into two categories namely invasive and non-invasive sources. Saliva, breath and urine are the important non-invasive sources. Invasive testing is a medical procedure that is executed by puncturing or cutting of the skin or by inserting a tool into the body. The essential non-invasive sources are blood, intestinal fluid, cerebrospinal fluid and exosomes. Table 1.2 presents few representative examples of biomarkers from exhaled breath samples, physical signatures, and human body fluids as the biomarker types.12 

Table 1.2

Few examples of biomarkers representing the human health status.12  Reproduced from ref. 12, https://doi.org/10.1002/advs.202104426, under the terms of the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/.

Category of biomarker Biomarkers Reflecting human status
Vapor-phase biomarkers 
  • Acetone

  • Malondialdehyde

  • Ethane

  • Isoprene

 
  • Metabolic rate

  • Cellular oxidation status

  • Psychological stress

  • Hypoxia/respiratory status

 
Noninvasive physical biomarkers 
  • Blood pressure/pulse wave

  • Sweat rate

  • Breathing rate

  • Skin temperature/hardness

  • Skin conductance

  • pH value

 
  • Psychological stress

  • Thermal stress

  • Psychological stress

  • Thermal stress

  • Hydration state

  • Tooth decay and gum diseases

 
Biomarkers in body fluids 
  • Na+/K+

  • Lactate

  • Dopamine

  • Cortisol and Cholesterol

  • Creatinine

 
  • Hydration state

  • Fatigue level

  • Psychological stress

  • Psychological stress

  • Chronic kidney disease

 
Category of biomarker Biomarkers Reflecting human status
Vapor-phase biomarkers 
  • Acetone

  • Malondialdehyde

  • Ethane

  • Isoprene

 
  • Metabolic rate

  • Cellular oxidation status

  • Psychological stress

  • Hypoxia/respiratory status

 
Noninvasive physical biomarkers 
  • Blood pressure/pulse wave

  • Sweat rate

  • Breathing rate

  • Skin temperature/hardness

  • Skin conductance

  • pH value

 
  • Psychological stress

  • Thermal stress

  • Psychological stress

  • Thermal stress

  • Hydration state

  • Tooth decay and gum diseases

 
Biomarkers in body fluids 
  • Na+/K+

  • Lactate

  • Dopamine

  • Cortisol and Cholesterol

  • Creatinine

 
  • Hydration state

  • Fatigue level

  • Psychological stress

  • Psychological stress

  • Chronic kidney disease

 

Various biomarkers have been explored in dietary studies to understand the connections between diet/nutrition and health. These biomarkers are utilized to assess the nutritional intake. For instance, urine nitrogen serves as a reliable biomarker for protein intake. Urine/plasma genistein and daidzein are promising biomarkers of soy intake. Elevated levels of homocysteine can indicate deficiencies in certain B vitamins like folate, vitamin B6, and B12, which are crucial for this metabolic pathway. However, it can also be influenced by genetic factors and other health conditions, making it a multifaceted biomarker. Some biomarkers relate directly to the disease risk such as plasma concentration of cholesterol or triglycerides, which suggest a risk of cardiovascular diseases.49,50 

Omic platforms are particularly adept at uncovering and characterizing novel nutritional markers, defining an individual’s nutritional status and identifying nutritional bioactive compounds responsible for beneficial health effects, as illustrated in Table 1.3.49,50 

Table 1.3

Nutrigenomic biomarkers with characteristics.

Category of biomarker Characteristics
Genetic biomarkers  Biomarkers based on changes in DNA, predominantly focusing on single nucleotide polymorphisms (SNP). 
Transcriptomic biomarkers  Biomarkers based on RNA expression. 
Proteomic biomarkers  Biomarkers stemming from the examination of proteome. 
Epigenetic biomarkers  Epigenetic regulators: non-coding RNAs and DNA methylation, histone modification. 
Metabolomic biomarkers  Biomarkers derived from the Metabolomics or metabolite profiling. 
Lipidomic biomarkers  Biomarkers based metabolomic analysis of lipids. 
Category of biomarker Characteristics
Genetic biomarkers  Biomarkers based on changes in DNA, predominantly focusing on single nucleotide polymorphisms (SNP). 
Transcriptomic biomarkers  Biomarkers based on RNA expression. 
Proteomic biomarkers  Biomarkers stemming from the examination of proteome. 
Epigenetic biomarkers  Epigenetic regulators: non-coding RNAs and DNA methylation, histone modification. 
Metabolomic biomarkers  Biomarkers derived from the Metabolomics or metabolite profiling. 
Lipidomic biomarkers  Biomarkers based metabolomic analysis of lipids. 

Overall, biomarkers significantly aid in diagnosing and detecting particular diseases or associated risks of a disease at an early stage. In addition, they can also be applied to understand the outcome and prognosis of the disease. Various studies such as genomics, proteomics, metabolomics and lipidomics have been widely used to understand the dynamics of these biomarkers.49,50 

Biomarker detection is a decisive step for both early diagnosis and prognosis of diseases, which assists in improving the quality of patients’ life.5  Two important considerations for biosensors are the sensitivity of detection techniques and selectivity toward biomarkers/bio-molecules. Bio-sensing technologies have shown potential in medical diagnostics and point of care hospitals, multi-specialty clinics and laboratories. Biosensors are compact analytical electronic devices containing biologically derived sensing elements integrated with physio-chemical transducers. “Sensing and biological recognition” are the two elemental functional principles of a biosensor.

A sensor is a device that measures chemical or biochemical information and convert it into an analytically useful signal.51  Conversely, biosensors are accomplished candidates for the simultaneous and specific detection of biomarkers and the study of their associated reactions, because their components can be easily improved and modified. According to IUPAC nomenclature, a biosensor is a device that employs precise biochemical reactions interceded by isolated immune systems, enzymes, organelles, tissues or whole cells to detect chemical compounds (analyte) usually through optical, electrical and thermal signals. The biosensor comprises four standard components: a bioreceptor, a transducer, a micro-electronics/electronic system/an electronic assembly and a display/readout unit which are connected in a series as shown in Figure 1.1.52  Interactions between the bioreceptor (e.g., enzymes, antigens or antibodies, cells, and nucleic acids) and target analyte generate a change which is detected by the transducer (e.g., optical, electrochemical, heat or mass-based), which significantly transforms the collected information into a measurable output. Sensors are employed to recognize and determine the target analyte present in the matrix under observation. The mutual collaborative development and integration between disciplines have become a trend in present scenario. Therefore, the combination of sensing technology and material science holds extensive promise and very important research significance.

Figure 1.1

(a) Elements/components of a biosensor and (b) schematic of biosensor components.

Figure 1.1

(a) Elements/components of a biosensor and (b) schematic of biosensor components.

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Nanoscale sensors are based on conjugating the nanoparticles with the targeting ligand where the ligands are tailored to detect the specific marker of interest, providing them high specificity and sensitivity. Nanoparticles impart unmatched fascinating characteristics for detection such as increased reactivity, augmented electrical conductivity and strength, distinctive magnetic properties and a significant surface area to volume ratio.14  For label free recognition, a number of nanomaterials are being implemented such as electro-polymers, quantum dots, etc. The use of nanomaterials offers a more accurate and precise approach for biosensing. Nanomaterials can be classified according to their composition and origin. As per the composition they can be categorized into metal-based (silver or gold nanoparticles and metal oxides), carbon-based (fullerenes, grapheme and its oxide, carbon nanotubes (CNTs), carbon nanoribbons, etc.); semiconductor-based (quantum dots); polymer-based (dendrimers); composite-based (nanoclays); and MOFs-based nanomaterials. Based on their origin, nanomaterials have been classified as natural nanomaterials (milk, blood capsid, protein, claws, skin, feathers, hair, the human bone matrix, etc.); incidental nanomaterials (which are generated from industrial waste stream, for example, vehicle exhaust gases; combustion; etc.); and engineered nanomaterials. The natural and incidental nanomaterials can possess irregular or regular shapes; however, engineered nanomaterials exhibits regular shapes such as nanotubes, nanospheres, and nanorings.53 

A biosensor is an analytical device consisting of four standard components: a biorecognition element/bioreceptor, a transducer, micro-electronics and a display unit which is used to detect the presence and analyte concentration. In addition to this, they are used to examine cell mechanics, cell physiology, drug analysis, etc.54  The basic design of a biosensor with its components is shown in Figure 1.2. The chemical information associated to the analyte (present in various biological fluids such as sweat, blood, saliva, interstitial fluid, tears, breath and human volatiles) is transformed to a readable output via sensing/recognition and transduction. Specificity and selectivity are crucial aspects of biorecognition elements (BERs), also known as bio-receptors, that identify the target analyte.55,56 

Figure 1.2

Basic design of biosensors.56  Reproduced from ref. 56, https://doi.org/10.3390/s21041109, under the terms of the CC BY 4.0 license, https://creativecommons.org/licenses/by/4.0/.

Figure 1.2

Basic design of biosensors.56  Reproduced from ref. 56, https://doi.org/10.3390/s21041109, under the terms of the CC BY 4.0 license, https://creativecommons.org/licenses/by/4.0/.

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Examples of various biorecognition elements are (i) enzymes; (ii) antibodies; (iii) nucleic acids (iv) molecularly imprinted polymers (MIPs); (v) cells; (vi) aptamers; (vii) DNA, etc. The examples (i–iii) belong to the most widely used bioreceptors. The biorecognition elements immobilize on the biosensor surface, allowing the interaction of the target analyte with the immobilize bioreceptors, which will be conveyed to the transducer that transforms the recognition event into a readable output which can be further analyzed and amplified.57,58  The transducing systems can be optical, electrochemical, piezoelectric, ion-sensitive, thermometric, magnetic or acoustic one.59  Biosensors may comprise various types of display units such as a computer, liquid crystal display (LCD) or a printer, which provide a pictographic demonstration of the measured signal. According to the needs of the users, the format for the output signals can be different, for instance, the final outcome can be either in a tabular form, numeric, an image or graphics.

In order to be applicable in the diagnostic field, a biosensor must possess the following characteristics (a) repeatability; (b) selectivity and specificity; (c) simplicity; (d) low early detection readings; (e) minimal procedure; (f) observer-independent; (g) target specific); (h) sensitivity and linearity, and (i) stability (Figure 1.3).14,64 

Figure 1.3

Characteristics of an ideal biosensor.

Figure 1.3

Characteristics of an ideal biosensor.

Close modal

Biosensors can be categorized based on their biological selectivity mechanism (enzyme, nucleic acid, aptamer, and antibody based) or by their transduction mechanism.60–62 

Figure 1.4 suggests the classification of biosensors based on the transduction mechanism.60 

Figure 1.4

Transduction mechanism-based classification of biosensors.

Figure 1.4

Transduction mechanism-based classification of biosensors.

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ECBs are primarily a subset of chemical sensors that combine the high specificity of biological recognition procedures and the sensitivity of electrochemical transducers.63,64  According to IUPAC, an ECB is defined as a self-contained integrated device capable of analyzing specific quantitative or semi-quantitative information. These biosensors typically employ a biological recognition element, which is in direct spatial contact with an electrochemical transduction element, usually a working electrode where the biochemical reaction occurs generating an electrical signal proportional to the target analyte concentration.65,66  ECBs operate by detecting alterations in potential, conductance, current or field effect resulting from the interaction between the target molecule and the bioreceptor elements on the sensing surface. The fundamental principle of these biosensors lies in the chemical reactions occurring between the target analyte and immobilized biomolecules, which either consume or produce electrons or ions. This in turn, affects the electrical properties of the analyte. ECBs quantify the current generated by oxidation and reduction reactions within the electrochemical system initiated by specific electroactive species.63 

This type of biosensors embraces a set of electrodes, namely, a sensing electrode (SE)/working electrode (WE; glassy carbon electrode or GCE, serves as the transducing element), a reference electrode (RE; Ag/AgCl electrode impart stable potential) and an auxiliary/counter electrode (CE; Pt electrode functions to complete the circuit).64  Mainly, the redox reaction occurs on the WE surface and the potential is synchronized by the RE and sometimes the circuit is completed by the CE. To ensure both chemical stability and conductivity, electrodes commonly utilize materials such as gold, platinum, graphite and silicon compounds, chosen based on the nature of the analyte. Mehrvar et al. have offered a comprehensive review of electrochemical biosensors, detailing characteristics such as detection limits.67  Direct or label-free sensing relies on changes in the electrical signal resulting from the targeted recognition event. In contrast, indirect or labeled sensing involves the use of a secondary compound (such as enzyme tagged secondary antibodies) as a label to facilitate electrochemical events.68  Most biosensors use EC detection for the transducer owing to their remarkable delectability, accessibility, portability, cost effectiveness, selectivity, robustness, sensitivity, analytical performances and simplicity of construction than other biosensors.63  Based on the transducer utilized, ECBs are classified into conductometry, potentiometry, amperometry, voltammetry and electrochemical impedance spectroscopy (EIS).58  All of these measurement techniques will be discussed further, and sample curves for these electrochemical measurements are depicted in Figure 1.5.

Figure 1.5

Sample curves for various sensors (a) amperometric, (b) potentiometric, (c) voltammetric, (d) colorimetric, and (e) fluorescence. Adapted from ref. 17 with permission from Springer Nature, Copyright 2022.

Figure 1.5

Sample curves for various sensors (a) amperometric, (b) potentiometric, (c) voltammetric, (d) colorimetric, and (e) fluorescence. Adapted from ref. 17 with permission from Springer Nature, Copyright 2022.

Close modal

In amperometric biosensors, a constant potential (V) is applied between the working electrode and the reference electrode, and the resulting current (I) from to the redox reactions of electrochemical species is measured. This applied potential triggers redox reactions of the electrolytes within the solution at the surface of the working electrode, generating electrons at a precise potential determined by the nature of the electrolyte. The maximum current value measured within a linear potential range is directly proportional to the bulk concentration of the analyte.69  This method is less influenced by the electrode’s characteristics, as well as the nature and type of the supporting electrolyte. Additionally, it does not necessitate maintaining a fixed temperature during titration, and the substance being analyzed doesn’t need to be reactive at the electrode. This method allows for continuous measurements with rapid response time and has found application in commercial glucose monitors.70  A practical application of amperometry involves its combination with immunosensing techniques to measure levels of the human chorionic gonadotropin β-subunit (βHCG) in advanced pregnancy testing.71  A summary of recently developed amperometry biosensors for various biomarker detections is shown in Table 1.4.

Table 1.4

Biosensors for biomarker detection employing amperometry techniques.

Biosensor material Biomarker Disease LOD/LOQ Ref.
Fe3O4@GO  Prostate specific antigen (PSA)  Prostate cancer  15 fg mL−1   72   
Fe3O4@GO  Prostate specific membrane antigen (PSMA)  Prostate cancer  4.8 fg m−1   72   
Redox polymer P(SS-GMA-BA)-Os  para-Hydroxyphenylacetate (p-HPA)  Urinary disease  —  73   
V2O5 nanoplates/AuE  Methylglyoxal  Diabetes mellitus  0.24 µM  74   
Ti3C2TX/Pt–Pd  Sarcosine  Cancer  0.16 µM  75   
Ferrocene monocarboxylic acid linked anti-VEGF (Fc-anti-VEGF)  Vascular endothelial growth factor  Cancer  38 pg m−1   76   
LDH/RGO-AuNPs/SPCE  l-Lactate  Cancer  0.13 µM  77   
Biosensor material Biomarker Disease LOD/LOQ Ref.
Fe3O4@GO  Prostate specific antigen (PSA)  Prostate cancer  15 fg mL−1   72   
Fe3O4@GO  Prostate specific membrane antigen (PSMA)  Prostate cancer  4.8 fg m−1   72   
Redox polymer P(SS-GMA-BA)-Os  para-Hydroxyphenylacetate (p-HPA)  Urinary disease  —  73   
V2O5 nanoplates/AuE  Methylglyoxal  Diabetes mellitus  0.24 µM  74   
Ti3C2TX/Pt–Pd  Sarcosine  Cancer  0.16 µM  75   
Ferrocene monocarboxylic acid linked anti-VEGF (Fc-anti-VEGF)  Vascular endothelial growth factor  Cancer  38 pg m−1   76   
LDH/RGO-AuNPs/SPCE  l-Lactate  Cancer  0.13 µM  77   

Another adaptable and promising electrochemical detection method is voltammetric detection, which involves varying the applied potential with controlled steps and speed. Voltammetry refers to techniques where the potential is swept across a predetermined range, and the current is measured as the potential varies under controlled conditions.69  Voltammetric detection is commonly employed to monitor electroactive molecules such as uric acid and vitamin C by directly detecting their direct redox reactions near a specific redox potential on the electrode surface under an applied potential waveform.78  The current response typically manifests as a plateau or a peak, which is directly proportional to the analyte concentration. Voltammetric methods encompass various techniques such as cyclic voltammetry, linear sweep voltammetry, hydrodynamic voltammetry, square-wave voltammetry, differential pulse voltammetry, AC voltammetry, stripping voltammetry and polarography. These techniques offer a broad dynamic range and are also beneficial for low level quantitation. Stripping voltammetry, which involves an analyte preconcentration step followed by a voltammetric scan, enables the detection of trace levels of heavy metals in body fluids.78  Herein, a summary of recently developed voltammetry biosensors for various biomarker detections is shown in Table 1.5.

Table 1.5

Biosensors for biomarker detection employing voltammetry techniques.

Biosensor material Biomarker Disease LOD/LOQ Ref.
Silica nanowires  Interleukin-10 (IL10)  Lung cancer  1 pg Ml−1   
Osteopontin (OPN)  Lung cancer  —  79   
Au/AbCD14-FITC-Fc  Creatine kinase (CK)  Heart disease  0.5 pg mL−1   80   
Au/Ab-IL10-FITC-Fc  Cytokine interleukin 10 (IL10)  Heart disease  —  80   
Anti-IL-8/AuNPs-rGO/ITO  Interleukin (IL)-8  Oral Cancer  72.73 pg mL−1   81   
Biosensor material Biomarker Disease LOD/LOQ Ref.
Silica nanowires  Interleukin-10 (IL10)  Lung cancer  1 pg Ml−1   
Osteopontin (OPN)  Lung cancer  —  79   
Au/AbCD14-FITC-Fc  Creatine kinase (CK)  Heart disease  0.5 pg mL−1   80   
Au/Ab-IL10-FITC-Fc  Cytokine interleukin 10 (IL10)  Heart disease  —  80   
Anti-IL-8/AuNPs-rGO/ITO  Interleukin (IL)-8  Oral Cancer  72.73 pg mL−1   81   
Potentiometric biosensors known for their cost effectiveness, simplicity and widespread familiarity have been employed extensively since the early 1930s.82  These biosensors compute the potential of an EC cell at the WE which arises across an ion-selective membrane that separates the two solutions when there is no current flowing in the EC cell. Biological recognition elements (BREs), specifically enzymes, are typically integrated into potentiometric sensors, where the ions produced catalytically are detected by the electrodes. The Nernst equation (eqn (1.1)) governs the relationship between the concentration of the analyte and the potential of the EC cell.
(1.1)
where, Ecell is the potential of the EC cell in zero current, E cell 0 is the constant potential of the EC cell, T is the absolute temperature, R is the real gas constant, F is the Faraday constant, n is the number of electrons transferred and Q is the ratio of ion concentrations at the oxidized state and reduced state. Potentiometric biosensors are broadly categorized into three types, namely, coated wire electrodes (CWEs), ion-selective electrodes (ISEs) and field-effect transistors (FETs).83  Freiser in 1970s first introduced coated wire electrodes. In the conventional CWE design, a conductor is directly covered with a suitable ion-selective polymer membrane, creating an electrode system that is responsive to changes in electrolyte concentration. The ISE is an indicating electrode capable of selectively assessing the activity of a meticulous ionic species. In the typical design, such electrodes are generally membrane based devices where a permselective membrane separates the sample from the inside of the electrode. This type of potentiometric method is a low cost and old technique which has the ability to alter portable kits. Enzyme electrodes are constructed by immobilizing an enzyme onto gas-selective electrode or onto an ion or ISFET.84  The selection of potentiometric procedures for the determination of ions (cations and anions) or biomaterials depends on the capability of a membrane substance employed in the development of potentiometric sensors. The enzyme-catalyzed reaction consumes or generates a species, which is detected by an ion-selective electrode. The significant advantage of potentiometric biosensor lies in its ability to easily manufacture smaller devices, making it significantly useful for in vivo testing of numerous ions. Light-addressable potentiometric biosensors (LAPS) are a novel approach to ISFET and operate based on the field-effect in a semiconductor. LAPS potentiometric nanosensors comprise a semiconductor plate covered with an insulating layer and also an ohmic contact on the bottom surface. Moreover, such potentiometric nanosensors are developed with the help of apt electronics and light emitting diodes. Silicon tetra nitrate (Si3N4), tantalum pentoxide (Ta2O5) and aluminum oxide (Al2O3) having a thickness of 50–100 nm were employed as an insulating layer in previously reported studies.85–87  Lately, the molecularly imprinted polymer (MIP) has been introduced as a new approach for enhancing the performance of potentiometric nanosensors which work based on the lock and key method.88  Active sites in the polymeric structures of these biosensors create specific interactions with target molecules, enhancing sensitivity. Wearable potentiometric sensors (WPISs) represent a changed outlook on the physiological and clinical applications of potentiometric sensors. WPISs can be demarcated as electrochemical sensors based on ion-selective electrodes, incorporating materials and electronics to permit on-body measurements. WPISs are biomarker recognition devices designed to measure the concentration and activity of important analytes in body fluids and they provide a comprehensive information on physiological activities of body in diverse conformations like sweatbands, textiles, and epidermal patches.89  In summary, potentiometric biosensors have achieved significant success in industries, clinics and other major sectors where precision, accuracy, speed, and ease of use are paramount.

Conductometry, a subset of impedimetric devices, monitors alterations in the electrical conductivity of the sample solution as the composition of the solution or medium changes during a chemical reaction process.69  Conductometric biosensors can detect biorecognition events that alter the ionic concentration. Typically, these reactions result in changes in the concentration of the ionic species, which in turn cause variations in current flow or electrical conductivity.90  There is currently heightened interest in conductometric immunosensors, particularly in conjunction with nanostructures, especially nanowires, for biosensing applications.69  Conductometric methods have garnered interest among various research groups due to their ease of use and simplicity, eliminating the need for a specialized reference electrode. A conductometric biosensor has been reported for the detection of apolipoprotein A1, a biomarker crucial for diagnosing bladder cancer. Conductometric sensors have found applications in environmental monitoring, chemical analysis and detection of food borne pathogens such as Salmonella spp. and Escherichia coli.91  A summary of recently developed conductometric biosensors for biomarker detection is listed in Table 1.6.

Table 1.6

Biosensors for biomarker detection employing conductometry techniques.

Biosensor material Biomarker Disease LOD/LOQ Ref.
Si/SiO2/oxygen-deficient ZnO/Au/Cr  Interleukin-6 (IL 6) and C-reactive protein (CRP) antigens  Cardiac inflammation  0.5 nm  92   
Single site-specific polyaniline (PANI) nanowire  Myoglobin (Myo), cardiac troponin I (cTnI), creatine kinase-MB (CK-MB), and b-type natriuretic peptide (BNP)  Cardiovascular diseases  Myo-100 pg mL−1, cTnI-250 fg mL−1, CK-MB-150 fg mL−1, BNP-50 fg mL−1   93   
Nickel/Si-nanowire/nickel sandwich  Apolipoprotein A1  Bladder cancer  1 ng mL−1   94   
Biosensor material Biomarker Disease LOD/LOQ Ref.
Si/SiO2/oxygen-deficient ZnO/Au/Cr  Interleukin-6 (IL 6) and C-reactive protein (CRP) antigens  Cardiac inflammation  0.5 nm  92   
Single site-specific polyaniline (PANI) nanowire  Myoglobin (Myo), cardiac troponin I (cTnI), creatine kinase-MB (CK-MB), and b-type natriuretic peptide (BNP)  Cardiovascular diseases  Myo-100 pg mL−1, cTnI-250 fg mL−1, CK-MB-150 fg mL−1, BNP-50 fg mL−1   93   
Nickel/Si-nanowire/nickel sandwich  Apolipoprotein A1  Bladder cancer  1 ng mL−1   94   

It was introduced by Lorenz and Schulze in 1975, involving the application of a sinusoidal potential ranging from 2–10 mV to measure the resulting current response (I). This response encompasses both resistive and capacitive properties of materials. The frequency is systematically adjusted across a wide range to achieve the impedance spectrum.63  The capacitive and resistive components of impedance are determined by analyzing the out-of-phase and in-phase current responses, respectively. Impedance techniques are highly effective as they can detect mass transfer at low frequency and electron transfer at high frequency. These methods are primarily employed for affinity biosensors. Impedance sensors were developed for the detection of water in an oil-in-water emulsion as well as for detecting NO2 and tobacco smoke, aiding in odor detection.64  An instance of impedimetric detection involves monitoring immunological binding events of antigens (Ag) and antibodies (Ab) on an electrode surface. This process entails measuring slight changes in impedance, which are directly proportional to the concentration of Ag in measured species.95  EIS serves as a valuable tool in both the development and investigation of materials for biosensor transduction. For example, it is utilized in studying processes such as polymer degradation. An inventory of selected studies in the literature on biomarker detection via nanomaterials by using EIS techniques is presented in Table 1.7.

Table 1.7

Biosensors for biomarker detection employing EIS techniques.

Biosensor material Biomarker Disease LOD/LOQ Ref.
Gold screen-printed electrodes modified with a specific thiolated antibody  Triggering Receptor-1 Expressed on Myeloid cells (TREM-1), Matrix MetalloPeptidase 9 (MMP-9), N-3-oxo-dodecanoyl-l-Homo Serine Lactone (HSL)  Infection  3.3 pM for TREM-1, 1.1 nM for MMP-9, 1.4 nM for HSL  96   
Glassy carbon electrode (GCE)/single-walled carbon nanohorns (SCN)  a-fetoprotein (AFP)  Cancer  0.3 pg mL−1   97   
Ab/core–shell Au–Ag NPs/SPE  Cancer antigen 125 (CA125)  Ovarian cancer  1.03 IU mL−1   98   
Integrated graphene electrode  Carcinoembryonic antigen (CEA)  Lung cancer  0.085 ng ml−1   99   
Anti-Mb-IgG/MWCNTs/SPE  Mb  Acute myocardial infarction  0.08 ng mL−1   100   
Biosensor material Biomarker Disease LOD/LOQ Ref.
Gold screen-printed electrodes modified with a specific thiolated antibody  Triggering Receptor-1 Expressed on Myeloid cells (TREM-1), Matrix MetalloPeptidase 9 (MMP-9), N-3-oxo-dodecanoyl-l-Homo Serine Lactone (HSL)  Infection  3.3 pM for TREM-1, 1.1 nM for MMP-9, 1.4 nM for HSL  96   
Glassy carbon electrode (GCE)/single-walled carbon nanohorns (SCN)  a-fetoprotein (AFP)  Cancer  0.3 pg mL−1   97   
Ab/core–shell Au–Ag NPs/SPE  Cancer antigen 125 (CA125)  Ovarian cancer  1.03 IU mL−1   98   
Integrated graphene electrode  Carcinoembryonic antigen (CEA)  Lung cancer  0.085 ng ml−1   99   
Anti-Mb-IgG/MWCNTs/SPE  Mb  Acute myocardial infarction  0.08 ng mL−1   100   

Following the electrochemical approach, the second most common biosensors are optical biosensors. They have extensive applications in health care, pharmaceuticals, homeland security, monitoring of environmental contaminants, etc.101  The optical recognition of biomarkers occurs when the optical field interacts with the bio-recognition element, leading to changes in optical properties, which can be analyzed and correlated with the analyte concentration. The optical properties include changes in the phase, polarization, or frequency. The optical biosensor integrates the optical transducer intimately with the biosensing element. The working principle of optical biosensors primarily depends on the type of optical transducer employed.101  Depending on the transducer, an optical biosensor is classified into colorimetric/spectrophotometric (based on absorption of light), fluorometric, chemiluminescence and surface plasmon resonance (SPR)-based biosensors.66  Another commonly used approach to categorize optical biosensors is by classifying them as label-free or label-based. In label-free optical sensing, the output signal is generated owing to the on-site interaction between the transducer and analyte, such as in surface plasmon resonance (SPR) sensing. Conversely, in label-based optical sensing, a label is utilized to access the recognition, and the optical signal is generated via mechanisms including colorimetric, fluorescence or luminescence. Labels can be enzymes, nanoparticles, fluorescent materials/luminescent molecules, etc. Optical biosensing methods have gained significant popularity due to their numerous advantages over conventional analytical techniques. These advantages include real-time sensing, remote sensing capabilities, minimally invasive characteristics suitable for in vivo measurements, high specificity and sensitivity, compact size, cost effectiveness and the provision of detailed chemical information on analytes. The fundamental components of optical biosensors include a source of light, an optical-transmission medium such as fiber or a waveguide, immobilized biological recognition elements such as enzymes, antibodies and microbes and the optical sensing platform.101 

Colorimetry is one of the most common optical detection approaches for the recognition of analytes by quantitatively estimating the color change. It works on the principle of the Beer–Lambert law (1.2). The target analyte typically undergoes a chemical reaction that leads to a detectable color change which occurs when molecules/analytes absorb light in the UV-visible range. The main advantage of this technique is its simplicity, easy operational procedures and cost effectiveness. However, their sensitivity is little less compared to other optical methods. Colorimetric methods are so straightforward that the outcome can be seen by the naked eye or through simple software and, even applications on mobile phones.102  These types of sensors can be alienated into two formats: flat substrate based and solution based. The flat substrate based sensors generally uses glass and paper and are mostly interesting for analyzing small sample volume and easy use. The solution-based sensors use nanomaterials and are mostly interesting for analyzing large sample volume allowing simple and rapid detection.66 
(1.2)
where, I represents the electromagnetic wave intensity; I0 is the incident electromagnetic intensity, ε is the molar extinction coefficient of the medium, c is the analyte concentration, and l is the path length. Numerous studies have been reported for the colorimetric detection of cancer biomarkers including examples like LFA and uPADs.5,103  Few examples of biomarker detection via colorimetric technique are shown in Table 1.8.
Table 1.8

Few reported examples of biomarker detection using colorimetric, fluorescence and luminescence techniques.

Biosensing method Biosensor material Biomarker Disease LOD/LOQ Ref.
Colorimetric  MIP/CdTe-MPA-QDs  Myoglobin (Mb)  Acute myocardial infarction  7.6 fM  113   
Colorimetric  AuNPs and Ag enhancement  CA 125  Ovarian cancer  30 U mL−1   102   
Colorimetric  Chromogenic substrate  Prostate cancer antigen 3  Prostate cancer  0.34 fg µL−1   114   
Fluorescence  Biotin-labeled CNWMINKEC peptide  Kidney injury molecule-1 (KIM-1)  Chronic kidney disease (CKD), acute kidney injury (AKI) and nephrotoxicity  —  115   
Fluorescence  CuS NPs as signal tag  CEA  Colorectal, pancreatic, gastric, and cervical cancers  0.05 pg mL−1   116   
Fluorescence  Qdot-based lateral flow test strip (LFTS)  Nitrated ceruloplasmin  Cardiovascular disease, lung cancer, and stress response  1 ng mL−1   117   
Fluorescence  DNA capture probe-magnetic silicon microsphere-rGO  miRNA 21  Different type cancer  0.098 nM  118   
Luminescence  α-NaYF4:Yb3+,Er3+ upconversion NPs  Vascular endothelial growth factor (VEGF)  Cancer  6 pM  119   
Luminescence  Anti-AFP/PPI/AuNPs/GCE  Alpha fetoprotein (AFP)  Teratoblastoma  0.0022 ng mL−1   120   
Luminescence  Nickel(ii) metal–organic framework (NiMOF)  3-Nitrotyrosine (3-NT)  Inflammatory disorders, nitrosative stress  0.165 µM  121   
Luminescence  Polyvinylidene fluoride imbibed with poly(3-alkoxy-4-methylthiophene)  8-Hydroxy-2′-deoxyguanosine (8-OHdG)  Oxidative stress  300 pM (fluorometric), 350 pM (colorimetric)  122   
Electrochemiluminescence  GSH-MXene QD  miRNA221  Breast cancer  10 fM  123   
Biosensing method Biosensor material Biomarker Disease LOD/LOQ Ref.
Colorimetric  MIP/CdTe-MPA-QDs  Myoglobin (Mb)  Acute myocardial infarction  7.6 fM  113   
Colorimetric  AuNPs and Ag enhancement  CA 125  Ovarian cancer  30 U mL−1   102   
Colorimetric  Chromogenic substrate  Prostate cancer antigen 3  Prostate cancer  0.34 fg µL−1   114   
Fluorescence  Biotin-labeled CNWMINKEC peptide  Kidney injury molecule-1 (KIM-1)  Chronic kidney disease (CKD), acute kidney injury (AKI) and nephrotoxicity  —  115   
Fluorescence  CuS NPs as signal tag  CEA  Colorectal, pancreatic, gastric, and cervical cancers  0.05 pg mL−1   116   
Fluorescence  Qdot-based lateral flow test strip (LFTS)  Nitrated ceruloplasmin  Cardiovascular disease, lung cancer, and stress response  1 ng mL−1   117   
Fluorescence  DNA capture probe-magnetic silicon microsphere-rGO  miRNA 21  Different type cancer  0.098 nM  118   
Luminescence  α-NaYF4:Yb3+,Er3+ upconversion NPs  Vascular endothelial growth factor (VEGF)  Cancer  6 pM  119   
Luminescence  Anti-AFP/PPI/AuNPs/GCE  Alpha fetoprotein (AFP)  Teratoblastoma  0.0022 ng mL−1   120   
Luminescence  Nickel(ii) metal–organic framework (NiMOF)  3-Nitrotyrosine (3-NT)  Inflammatory disorders, nitrosative stress  0.165 µM  121   
Luminescence  Polyvinylidene fluoride imbibed with poly(3-alkoxy-4-methylthiophene)  8-Hydroxy-2′-deoxyguanosine (8-OHdG)  Oxidative stress  300 pM (fluorometric), 350 pM (colorimetric)  122   
Electrochemiluminescence  GSH-MXene QD  miRNA221  Breast cancer  10 fM  123   

Fluorescence is indeed a keystone in biosensing owing to its sensitivity and versatility. Its basic principle involves the emission of light by a substance called fluorophore, after it absorbs photons from an external light source known as excitation light. The light emitted is typically of a longer wavelength than the excitation light which enables its separation through filters. In biosensing applications, the intensity of fluorescence emitted by a labeled target molecule can be correlated with its concentration or presence, providing valuable analytical information.104,105  Fluorescent materials/fluorophores can be used as sensing probes owing to their ability to change their intrinsic fluorescence properties when interacting with other elements. The widespread adoption of highly sensitive and selective fluorescent labeling renders fluorescence one of the most commonly utilized optical procedures for biomarker sensing in various microfluidic systems. In contrast to colorimetric detection, one of the disadvantages of this detection is that it is bulky and fairly complex. Furthermore, the fluorescent materials are costly, often influenced by pH and have a limited shelf life. The labeling process involves intricate fluid handling, which poses a challenge to automating rapid assays.106,107  Fluorescence was primarily used for cell imaging to present the growth and viability of cells on a chip, and afterward it was used for the study of cellular components and cell membranes. Fluorescence detection has found diverse applications in areas such as the detection of protein biomarkers for cancer and infectious diseases. Few examples belonging to this class are given in Table 1.8.

Luminescence is a phenomenon of light emission wherein a compound or sample returns to its original ground-state after being electronically excited. This emission is utilized to measure chemical or biological reactions, either directly or with the enzyme label, whereas, chemiluminescence occurs during a chemical reaction generating an electronically activated state.108  Biosensor based on chemiluminescence was developed to detect lysozyme in human urine matrix, utilizing an aptamer/DNAzyme-GQDs immobilized on carbon fiber composites.109 

The benefit of this technique for lab-on-a chip (LOCs) is that emission filters and excitation light sources are not essential, thus minimizing probable background interferences.110  However, the need of the hour is the fabrication of cost effective photodetectors for application in point-of-care (POC) devices. In the present scenario, electrochemiluminescence (ECL) is gaining popularity in sensing and biosensing applications.111  ECL combines the benefits of chemiluminescence while controlling the spatial and temporal aspects of the light emitting reaction. This allows for improved detection limits by rapidly releasing chemiluminescence generated through the electrochemical recycling of reagents. Zhang et al. reported an ECL aptasensor for miRNA-16 recognition in leukemia patients.112  Few examples of luminescence techniques are provided in Table 1.8.

The label-free optical phenomenon employed for sensing applications is the surface plasmon resonance (SPR) technique. Its first biosensing application was demonstrated by Liedberg et al. in 1983. SPR occurs when the free electrons of a metal are excited by photons, generating an evanescent wave. The SPR method is not just noninvasive, but also a label-free method for studying the binding affinities between two different molecules, i.e., an injected analyte and an immobilized biomolecule in real time. It measures refractive index changes corresponding to the analyte binding at a metal surface (gold, silver or aluminum). They help in studying specificity, binding affinity, and binding kinetics, as well as measuring the concentration of target analytes in complex biological samples (Figure 1.6). The identified objects are generally biomolecules that have receptors and ligands with properties similar to proteins, nuclear acids, antibodies and enzymes. It is mainly suitable for quantification analysis and process monitoring of immunity reactions. SPR takes place only at the nanometer scale in metals (silver and gold are preferred) and is classified into two categories: SPR when it occurs in a metallic film and localized surface plasmon resonance (LSPR) when it takes place in metallic nanoparticles. The plasmon created depends directly on the size of the metal film, nanoparticle and the material used.107  Unlike other traditional methods, SPR directly provides information on biomolecular interactions without the need for prior labeling. However, limitations stemming from restricted mass transfer, nonspecific binding and avidity can sometimes obscure SPR analysis. A list of selected studies in the literature on biomarker discovery via nanoparticles employing the SPR technique is shown in Table 1.9.

Figure 1.6

Surface plasmon resonance principle.69  Reproduced from ref. 69 with permission from Elsevier, Copyright 2015.

Figure 1.6

Surface plasmon resonance principle.69  Reproduced from ref. 69 with permission from Elsevier, Copyright 2015.

Close modal
Table 1.9

Few examples of SPR and SERS biosensors to detect biomarkers.

Biosensing method Biosensor material Biomarker Disease LOD/LOQ Ref.
SPR  Ag nanosphere  Tumor necrosis factor-α  Cancer  200 ng mL−1   131   
SPR  Gold nanoprisms  MicroRNA  Pancreatic cancer  —  22 and 132   
SPR  Ab–Au sensor chip  α-Casein  Food allergy  57.8 ng mL−1   133   
SERS  Apt-AuNP-WS2 nanohybrid based SERS active platform  Myoglobin  Acute myocardial infarction  0.5 aM  134   
SERS  Ab1-magnetic NPs  CEA  Breast tumors  10−12 135   
SERS  LFAS using citratecapped Au@Ag-AuNPs  Cardiac troponin I  Acutemyocardial infarction  0.09 ng mL−1   136   
Biosensing method Biosensor material Biomarker Disease LOD/LOQ Ref.
SPR  Ag nanosphere  Tumor necrosis factor-α  Cancer  200 ng mL−1   131   
SPR  Gold nanoprisms  MicroRNA  Pancreatic cancer  —  22 and 132   
SPR  Ab–Au sensor chip  α-Casein  Food allergy  57.8 ng mL−1   133   
SERS  Apt-AuNP-WS2 nanohybrid based SERS active platform  Myoglobin  Acute myocardial infarction  0.5 aM  134   
SERS  Ab1-magnetic NPs  CEA  Breast tumors  10−12 135   
SERS  LFAS using citratecapped Au@Ag-AuNPs  Cardiac troponin I  Acutemyocardial infarction  0.09 ng mL−1   136   

Raman spectroscopy (RS) quantifies the elastically scattered photons generated by vibrational frequencies of a molecular structure when excited by monochromatic light, typically from a laser. This method furnishes fingerprint information regarding the bond structure of a molecule. The Raman microscopy is a novel platform for cell pharmacology, cell sorting and pathology studies.124  The surface-enhanced technique boosts the sensitivity of the Raman spectrum, leading to surface-enhanced Raman scattering (SERS) microscopy. This method addresses a major limitation of classical Raman spectroscopy by utilizing surface-enhancement with metals like gold, silver, and copper to enhance sensitivity.125  The SERS sensors emerged in the 1990s and have undergone rapid development in the last two decades, offering an attractive approach for next-generation sensing. They possess unique features compared to other portable devices. SERS has drawn attention as a powerful technology for detecting biomarkers with high selectivity and sensitivity. SERS significantly enhances the Raman signal by over 10 to 14 orders of magnitude through localized surface plasmon resonance at specific sites. This amplification occurs by intensifying the local electric field substantially when the target analytes are positioned within or adjacent to these hot spots. SERS stands out as an exemplary optical detection method and an ultra-sensitive vibrational spectroscopy technique for characterizing and determining analytes/biomarkers. Its distinguished features include fingerprint recognition, robust anti-interference capability, high resolution, non-destructive sampling, high sensitivity, swift operation, and the ability for multiplexed chemical sensing of complex analytes. Importantly, SERS achieves this label-free and noninvasively without requiring prior knowledge of the analytes.126–128  However, despite its promising capabilities, SERS encounters two significant challenges at its current stage, i.e., designing interfaces for capturing targets and overcoming interference from the surrounding matrix. SERS relies on targets being in close proximity to the substrate surface to function effectively. Nonetheless, researchers have made strides in addressing these challenges, with the development of a SERS biosensor for the sensitive and rapid detection of a protein biomarker associated with endocrine-disrupting compounds in an aquatic environment.129  Ju et al. unveiled a groundbreaking SERS biosensor, aimed at detecting glucose levels within the skin. Their creation relies on a micro-needle array crafted from cost-effective poly(methyl methacrylate).130  This development offers a user friendly and affordable approach for monitoring glucose levels directly at the source. Few selected investigations from the literature on biomarker detection via nanoparticles using the SERS technique are shown in Table 1.9.

Magnetoresistance (MR) is the change in the electrical resistance of a material under applied magnetic fields. It was discovered by William Thomson in 1856. In the presence an external magnetic field and a consistent sensing current, the resistance of a material experiences fluctuations, manifesting as changes in voltage. The resistance variations stem from the magnetic fringe field generated by functionalized magnetic labels upon binding surface-bound biomolecules. Lord Kelvin not only pioneered the initial measurement of MR in 1857 but also provided a mathematical framework for it, as depicted in eqn (1.3):
(1.3)
Here, ρ is the resistivity of the material and Rmin and Rmax are the resistance of the material in the absence of a magnetic field and in the presence of a saturated magnetic field, respectively. Quantitative analysis involves adjusting the resistance of the MR material in response to alterations in the applied magnetic field. Different MR materials have been studied to improve the performance of MR sensors. Giant magnetoresistance (GMR) and tunneling magnetoresistance (TMR) multilayer systems along with granular and graphene-based MR systems have been widely applied in commercial MR sensors. The MR sensing technology offers a user-friendly, cost-effective, high sensitivity and compact solution with remarkable features such as high sensitivity, low power consumption and enhanced detection ability. It possesses wide applications in the fields of versatile biomedical diagnosis, environmental monitoring, food safety, etc.137  Until now, MR sensing techniques have been explored for the detection of various biomarkers including PAPP-A, CA125 II, HE4, IL6, IgG, IgM, cTnI, HCG, PSA, etc.137 
A thermal sensor serves as an invaluable tool for measuring the temperature or heat in an environment. It converts this information into electronic data, enabling the monitoring and recording of temperature fluctuations. This technology enables us to better understand and respond to changes in our surroundings, ensuring safety and comfort in various settings. Thermal biosensors measure the heat energy absorbed or released during the biochemical reaction (exothermic or endothermic reaction). The temperature change (ΔT) or heat energy evolved/absorbed measured by a thermal biosensor is proportional to the number of product molecules (np) generated in the biochemical process and to the enthalpy (ΔH) and is also influenced by the heat capacity (Cp), which can be shown by relations (1.4) and (1.5) as:
(1.4)
(1.5)
Mostly, the flow injection method has been utilized for real-time monitoring of biochemical reactions by incorporating an immobilized enzyme reactor, which provides a solid support within reactor for processing of biological reactions. When analytes pass through the reactor and react specifically with the enzyme, they generate heat which causes a change in temperature. The measurement of differential temperature across the enzyme reaction will provide information about the reaction kinetics from which various parameters such as the rate of the reaction, enzyme activity and substrate concentration can be analyzed.

Thermopiles and thermistors are the two forms of temperature biosensors. Thermopiles gauge temperature fluctuations between two regions, offering a nuanced perspective on thermal changes. Conversely, thermistors rely on alterations in electrical resistance due to temperature shifts, enabling the determination of absolute temperature. However, their sensitivity is somewhat constrained, impacting their efficacy in certain applications. For enzymatic catalysis, ΔH between ∼−10 to −200 kJ mol−1 is adequate for the determination of substrate concentrations in clinically relevant metabolites such as glucose, oxalate, lactate, cholesterol, triglycerides, etc. In recent times, thermal biosensors have garnered notable attention due to their user friendly nature and easy maintenance. Ongoing advancements have propelled the creation of compact thermal biosensor devices, which are instrumental in bioprocessing applications. Thermoelectric biosensors have been reported to detect l-glutamate (a neurotransmitter),138  C-reactive protein (a reactive protein that increases during inflammation, CVS diseases and depression),139  and cortisol.140  Recently, microelectromechanical system (MEMS) thermal biosensors have emerged as valuable tools for examining metabolic processes through temperature detection. These MEMS thermal sensors possess attributes such as low thermal mass and improved thermal isolation. Moreover, the sample volume within MEMS thermal biosensors enhances sensitivity, extends the linear range, minimizes power consumption and reduces measurement time.

In this chapter, we delved into the realm of biomarkers and how biosensors play a pivotal role in their detection. Our focus extends to the integration of nanomaterials in sensor fabrication, aiming to illuminate the techniques employed for biomarker determination and detection. Through this exploration, we highlight the strengths and limitations of the methodologies, fostering a deeper understanding of their comparative efficacy. Biosensors present an exciting alternative to traditional methods by combining a living part with a physicochemical identifier part, offering rapid “real-time” and multiple analyses for estimations and diagnosis. In this chapter, we embark on a comprehensive journey through the fundamentals of biosensors, unraveling their intricate design, operation mechanisms, and underlying principles. We explored the diverse types of biosensors and their wide ranging applications, shedding light on recent advancements in biosensor research. Ultimately, biosensors emerge as indispensible analytical instruments, offering swift and cost effective detection and analysis of numerous analytes and biomarkers. Nevertheless, despite the exponential outgrowth in biosensor publications in research and academics centers, the promising market trend is still far behind the corresponding technological developments. Therefore, future work in biosensors should focus on cost effectiveness and addressing the difficulties associated with the technological shift from academics to industries. Other work such as the design of simplified, robust and sensitive biosensing devices for real-world appliances, implementation of superior nano-material-based bio-analysis tools for the mitigation of “noisy” bio-environments and considerable improvements in the throughput rate, long-term stability, specificity and reliability might be an important step for the next generation of biosensors.

1
Liu
R.
,
Ye
X.
,
Cui
T.
,
Recent progress of biomarker detection sensors
,
Research
,
2020
pg.
7949037
2
Bozal-Palabiyik
B.
,
Uslu
B.
and
Marrazza
G.
, Nanosensors in biomarker detection, in
New Developments in Nanosensors for Pharmaceutical Analysis
,
Elsevier
,
2019
, pp.
327
380
.
3
Sung
H.
et al.,
Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
,
Ca-Cancer J. Clin.
,
2021
, vol.
71
3
(pg.
209
-
249
)
4
Song
Q.
,
Merajver
S. D.
,
Li
J. Z.
,
Cancer classification in the genomic era: five contemporary problems
,
Hum. Genomics
,
2015
, vol.
9
(pg.
1
-
8
)
5
Carneiro
M. C. C. G.
,
Rodrigues
L. R.
,
Moreira
F. T. C.
,
Sales
M. G. F.
,
Colorimetric paper-based sensors against cancer biomarkers
,
Sensors
,
2022
, vol.
22
9
pg.
3221
6
Sun
J.
et al.,
A review of environmental metabolism disrupting chemicals and effect biomarkers associating disease risks: Where exposomics meets metabolomics
,
Environ. Int.
,
2022
, vol.
158
pg.
106941
7
Kaur
H.
et al.,
Assessment of diabetes biomarker monitoring via novel biosensor activity
,
Results Chem.
,
2023
, vol.
5
pg.
100777
8
Sandokji
I.
,
Greenberg
J. H.
,
Novel biomarkers of acute kidney injury in children: an update on recent findings
,
Curr. Opin. Pediatr.
,
2020
, vol.
32
3
(pg.
354
-
359
)
9
Ilyas
A.
,
Chesney
E.
,
Patel
R.
,
Improving life expectancy in people with serious mental illness: should we place more emphasis on primary prevention?
,
Br. J. Psychiatry
,
2017
, vol.
211
4
(pg.
194
-
197
)
10
Chesney
E.
,
Goodwin
G. M.
,
Fazel
S.
,
Risks of all-cause and suicide mortality in mental disorders: a meta-review
,
World Psychiatry
,
2014
, vol.
13
2
(pg.
153
-
160
)
11
García-Gutiérrez
M. S.
,
Navarrete
F.
,
Sala
F.
,
Gasparyan
A.
,
Austrich-Olivares
A.
,
Manzanares
J.
,
Biomarkers in psychiatry: concept, definition, types and relevance to the clinical reality
,
Front. Psychiatry
,
2020
, vol.
11
pg.
527209
12
Sim
D.
et al.,
Biomarkers and detection platforms for human health and performance monitoring: a review
,
Adv. Sci.
,
2022
, vol.
9
7
pg.
2104426
13
Etzioni
R.
et al.,
The case for early detection
,
Nat. Rev. Cancer
,
2003
, vol.
3
4
(pg.
243
-
252
)
14
Swierczewska
M.
,
Liu
G.
,
Lee
S.
,
Chen
X.
,
High-sensitivity nanosensors for biomarker detection
,
Chem. Soc. Rev.
,
2012
, vol.
41
7
(pg.
2641
-
2655
)
15
Ludwig
J. A.
,
Weinstein
J. N.
,
Biomarkers in cancer staging, prognosis and treatment selection
,
Nat. Rev. Cancer
,
2005
, vol.
5
11
(pg.
845
-
856
)
16
Mani
V.
et al.,
Electrochemical sensors targeting salivary biomarkers: A comprehensive review
,
TrAC, Trends Anal. Chem.
,
2021
, vol.
135
pg.
116164
17
Sempionatto
J. R.
,
Lasalde-Ramírez
J. A.
,
Mahato
K.
,
Wang
J.
,
Gao
W.
,
Wearable chemical sensors for biomarker discovery in the omics era
,
Nat. Rev. Chem.
,
2022
, vol.
6
12
(pg.
899
-
915
)
18
Altintas
Z.
,
Tothill
I. E.
,
Molecular biosensors: promising new tools for early detection of cancer
,
Nanobiosens. Dis. Diagn.
,
2015
(pg.
1
-
10
)
19
Shankaran
D. R.
, Nano-Enabled Immunosensors for Point-of-Care Cancer Diagnosis, in
Applications of Nanomaterials
,
Elsevier
,
2018
, pp.
205
250
.
20
Mahmoudi
T.
,
de la Guardia
M.
,
Baradaran
B.
,
Lateral flow assays towards point-of-care cancer detection: A review of current progress and future trends
,
TrAC, Trends Anal. Chem.
,
2020
, vol.
125
pg.
115842
21
Aronson
J. K.
,
Ferner
R. E.
,
Biomarkers—a general review
,
Curr. Protoc. Pharmacol.
,
2017
, vol.
76
1
(pg.
9
-
23
)
22
Das
S.
,
Devireddy
R.
,
Gartia
M. R.
,
Surface plasmon resonance (SPR) sensor for cancer biomarker detection
,
Biosensors
,
2023
, vol.
13
3
pg.
396
23
Khattab
A. M.
, Basics of Biological Sensors, in
Handbook of Nanosensors: Materials and Technological Applications
,
Springer
,
2023
, pp.
1
43
.
24
Cass
T.
,
Nanosensors: Physical, Chemical, and Biological
,
Phys. Today
,
2012
, vol.
65
3
(pg.
55
-
56
)
25
Ambaye
A. D.
,
Kefeni
K. K.
,
Mishra
S. B.
,
Nxumalo
E. N.
,
Ntsendwana
B.
,
Recent developments in nanotechnology-based printing electrode systems for electrochemical sensors
,
Talanta
,
2021
, vol.
225
pg.
121951
26
Zazo
H.
,
Millán
C. G.
,
Colino
C. I.
and
Lanao
J. M.
, Applications of metallic nanoparticles in antimicrobial therapy, in
Antimicrobial nanoarchitectonics
,
Elsevier
,
2017
, pp.
411
444
.
27
Joshi
P.
,
Mishra
R.
,
Narayan
R. J.
,
Biosensing applications of carbon-based materials
,
Curr. Opin. Biomed. Eng.
,
2021
, vol.
18
pg.
100274
28
Navarrete
F.
,
Sala
F.
,
Garc
M. S.
,
Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality
,
Front. Psychiatry
,
2020
, vol.
11
(pg.
1
-
14
)
29
Porter
K. A.
,
Effect Of Homologous Bone Marrpw Injections In X-irradiated Rabbits
,
Br. J. Exp. Pathol.
,
1956
, vol.
4
38
pg.
401
30
Mishra
A.
,
Verma
M.
,
Cancer biomarkers: are we ready for the prime time?
,
Cancers
,
2010
, vol.
2
1
(pg.
190
-
208
)
31
Shah
A. S. V.
,
Ferry
A. V.
,
Mills
N. L.
,
Cardiac biomarkers and the diagnosis of myocardial infarction in women
,
Curr. Cardiol. Rep.
,
2017
, vol.
19
(pg.
1
-
10
)
32
Nursalim
A.
,
Suryaatmadja
M.
,
Panggabean
M.
,
Potential clinical application of novel cardiac biomarkers for acute myocardial infarction
,
Acta Med. Indones.
,
2013
, vol.
45
3
(pg.
240
-
250
)
33
W. H. Organization
,
Biomarkers in risk assessment: Validity and validation
,
World Health Organization
,
2001
.
34
Frank
R.
,
Hargreaves
R.
,
Clinical biomarkers in drug discovery and development
,
Nat. Rev. Drug Discovery
,
2003
, vol.
2
7
(pg.
566
-
580
)
35
Firestein
G. S.
,
A biomarker by any other name…
,
Nat. Clin. Pract. Rheumatol.
,
2006
, vol.
2
12
pg.
635
36
Naylor
S.
,
Biomarkers: current perspectives and future prospects
,
Expert Rev. Mol. Diagn.
,
2003
, vol.
3
5
(pg.
525
-
529
)
37
Yan
B.
,
Photofunctional MOF-based hybrid materials for the chemical sensing of biomarkers
,
J. Mater. Chem. C
,
2019
, vol.
7
27
(pg.
8155
-
8175
)
38
Smith
I.
,
Mycobacterium tuberculosis pathogenesis and molecular determinants of virulence
,
Clin. Microbiol. Rev.
,
2003
, vol.
16
3
(pg.
463
-
496
)
39
Ziemssen
T.
,
Akgün
K.
,
Brück
W.
,
Molecular biomarkers in multiple sclerosis
,
J. Neuroinflammation
,
2019
, vol.
16
1
pg.
272
40
Scher
H. I.
,
Morris
M. J.
,
Larson
S.
,
Heller
G.
,
Validation and clinical utility of prostate cancer biomarkers
,
Nat. Rev. Clin. Oncol.
,
2013
, vol.
10
4
(pg.
225
-
234
)
41
Bernhardt
A. M.
et al.,
A unified classification approach rating clinical utility of protein biomarkers across neurologic diseases
,
EBioMedicine
,
2023
, vol.
89
pg.
104456
42
Coravos
A.
,
Khozin
S.
,
Mandl
K. D.
,
Developing and adopting safe and effective digital biomarkers to improve patient outcomes
,
NPJ Digit. Med.
,
2019
, vol.
2
1
pg.
14
43
Ahmad
A.
,
Imran
M.
,
Ahsan
H.
,
Biomarkers as biomedical bioindicators: approaches and techniques for the detection, analysis, and validation of novel Biomarkers of diseases
,
Pharmaceutics
,
2023
, vol.
15
6
pg.
1630
44
Razmi
N.
,
Hasanzadeh
M.
,
Current advancement on diagnosis of ovarian cancer using biosensing of CA 125 biomarker: Analytical approaches
,
TrAC, Trends Anal. Chem.
,
2018
, vol.
108
(pg.
1
-
12
)
45
Duffy
M. J.
,
Biomarkers for prostate cancer: prostate-specific antigen and beyond
,
Clin. Chem. Lab. Med.
,
2020
, vol.
58
3
(pg.
326
-
339
)
46
Fackenthal
J. D.
,
Olopade
O. I.
,
Breast cancer risk associated with BRCA1 and BRCA2 in diverse populations
,
Nat. Rev. Cancer
,
2007
, vol.
7
12
(pg.
937
-
948
)
47
Guzman-Martinez
L.
,
Maccioni
R. B.
,
Farías
G. A.
,
Fuentes
P.
,
Navarrete
L. P.
,
Biomarkers for Alzheimer’s disease
,
Curr. Res.
,
2019
, vol.
16
6
(pg.
518
-
528
)
48
Schomaker
S.
,
Ramaiah
S.
,
Khan
N.
,
Burkhardt
J.
,
Safety biomarker applications in drug development
,
J. Toxicol. Sci.
,
2019
, vol.
44
4
(pg.
225
-
235
)
49
Corella
D.
,
Ordovás
J. M.
,
Biomarkers: background, classification and guidelines for applications in nutritional epidemiology
,
Nutr. Hosp.
,
2015
, vol.
31
3
(pg.
177
-
188
)
50
Picó
C.
,
Serra
F.
,
Rodríguez
A. M.
,
Keijer
J.
,
Palou
A.
,
Biomarkers of nutrition and health: new tools for new approaches
,
Nutrients
,
2019
, vol.
11
5
pg.
1092
51
Stetter
J. R.
,
Penrose
W. R.
,
Yao
S.
,
Sensors, chemical sensors, electrochemical sensors, and ECS
,
J. Electrochem. Soc.
,
2003
, vol.
150
2
pg.
S11
52
Jha
M.
,
Gupta
R.
and
Saxena
R.
, A review on non-invasive biosensors for early detection of lung cancer, in 2020 6th International Conference on Signal Processing and Communication (ICSC), 2020, pp. 162–166.
53
Holzinger
M.
,
Le Goff
A.
,
Cosnier
S.
,
Nanomaterials for biosensing applications: a review
,
Front. Chem.
,
2014
, vol.
2
pg.
63
54
Thomas
A.
and
Kumar
K. G.
, Voltammetric and optical sensors for individual, dual and simultaneous determination of some antioxidants and biomarkers, Cochin University of Science and Technology, 2019.
55
Ramesh
M.
,
Janani
R.
,
Deepa
C.
,
Rajeshkumar
L.
,
Nanotechnology-enabled biosensors: A review of fundamentals, design principles, materials, and applications
,
Biosensors
,
2022
, vol.
13
1
pg.
40
56
Naresh
V.
,
Lee
N.
,
A review on biosensors and recent development of nanostructured materials-enabled biosensors
,
Sensors
,
2021
, vol.
21
4
pg.
1109
57
Soleymani
L.
,
Li
F.
,
Mechanistic challenges and advantages of biosensor miniaturization into the nanoscale
,
ACS Sens.
,
2017
, vol.
2
4
(pg.
458
-
467
)
58
Bhattarai
P.
and
Hameed
S.
, Basics of biosensors and nanobiosensors, in
Nanobiosensors: From Design to Applications
,
2020
, pp.
1
22
.
59
Monošík
R.
,
Streďanský
M.
,
Šturdík
E.
,
Biosensors-classification, characterization and new trends
,
Acta Chim. Slovaca
,
2012
, vol.
5
1
(pg.
109
-
120
)
60
Yang
F.
,
Ma
Y.
,
Stanciu
S. G.
, and
Wu
A.
, Transduction process-based classification of biosensors,
Nanobiosensors: From Design to Applications
,
2020
, pp.
23
44
.
61
Yoo
S. M.
,
Lee
S. Y.
,
Optical biosensors for the detection of pathogenic microorganisms
,
Trends Biotechnol.
,
2016
, vol.
34
1
(pg.
7
-
25
)
62
Kaur
H.
,
Bhosale
A.
,
Shrivastav
S.
,
Biosensors: classification, fundamental characterization and new trends: a review
,
Int. J. Health Sci. Res.
,
2018
, vol.
8
6
(pg.
315
-
333
)
63
Ronkainen
N. J.
,
Halsall
H. B.
,
Heineman
W. R.
,
Electrochemical biosensors
,
Chem. Soc. Rev.
,
2010
, vol.
39
5
(pg.
1747
-
1763
)
64
Stradiotto
N. R.
,
Yamanaka
H.
,
Zanoni
M. V. B.
,
Electrochemical sensors: A powerful tool in analytical chemistry
,
J. Braz. Chem. Soc.
,
2003
, vol.
14
(pg.
159
-
173
)
65
Karunakaran
C.
,
Rajkumar
R.
and
Bhargava
K.
, Introduction to biosensors, in
Biosensors and bioelectronics
,
Elsevier
,
2015
, pp.
1
68
.
66
Purohit
B.
,
Vernekar
P. R.
,
Shetti
N. P.
,
Chandra
P.
,
Biosensor nanoengineering: Design, operation, and implementation for biomolecular analysis
,
Sens. Int.
,
2020
, vol.
1
pg.
100040
67
Mehrvar
M.
,
Abdi
M.
,
Recent developments, characteristics, and potential applications of electrochemical biosensors
,
Anal. Sci.
,
2004
, vol.
20
8
(pg.
1113
-
1126
)
68
Durkin
T. J.
,
Barua
B.
,
Savagatrup
S.
,
Rapid detection of sepsis: Recent advances in biomarker sensing platforms
,
ACS Omega
,
2021
, vol.
6
47
(pg.
31390
-
31395
)
69
Grieshaber
D.
,
MacKenzie
R.
,
Vörös
J.
,
Reimhult
E.
,
Electrochemical biosensors-sensor principles and architectures
,
Sensors
,
2008
, vol.
8
3
(pg.
1400
-
1458
)
70
Kim
J.
,
Campbell
A. S.
,
Wang
J.
,
Wearable non-invasive epidermal glucose sensors: A review
,
Talanta
,
2018
, vol.
177
(pg.
163
-
170
)
71
Santandreu
M.
,
Alegret
S.
,
Fabregas
E.
,
Determination of β-HCG using amperometric immunosensors based on a conducting immunocomposite
,
Anal. Chim. Acta
,
1999
, vol.
396
2–3
(pg.
181
-
188
)
72
Sharafeldin
M.
,
Bishop
G. W.
,
Bhakta
S.
,
El-Sawy
A.
,
Suib
S. L.
,
Rusling
J. F.
,
Fe3O4 nanoparticles on graphene oxide sheets for isolation and ultrasensitive amperometric detection of cancer biomarker proteins
,
Biosens. Bioelectron.
,
2017
, vol.
91
(pg.
359
-
366
)
73
Teanphonkrang
S.
et al.,
Amperometric detection of the urinary disease biomarker p-HPA by allosteric modulation of a redox polymer-embedded bacterial reductase
,
ACS Sens.
,
2019
, vol.
4
5
(pg.
1270
-
1278
)
74
Bhat
L. R.
,
Vedantham
S.
,
Krishnan
U. M.
,
Rayappan
J. B. B.
,
A non-enzymatic two step catalytic reduction of methylglyoxal by nanostructured V2O5 modified electrode
,
Biosens. Bioelectron.
,
2018
, vol.
103
(pg.
143
-
150
)
75
Ran
B.
,
Chen
C.
,
Liu
B.
,
Lan
M.
,
Chen
H.
,
Zhu
Y.
,
A Ti3C2TX/Pt–Pd based amperometric biosensor for sensitive cancer biomarker detection
,
Electrophoresis
,
2022
, vol.
43
20
(pg.
2033
-
2043
)
76
Prabhulkar
S.
,
Alwarappan
S.
,
Liu
G.
,
Li
C.-Z.
,
Amperometric micro-immunosensor for the detection of tumor biomarker
,
Biosens. Bioelectron.
,
2009
, vol.
24
12
(pg.
3524
-
3530
)
77
Azzouzi
S.
,
Rotariu
L.
,
Benito
A. M.
,
Maser
W. K.
,
Ben Ali
M.
,
Bala
C.
,
A novel amperometric biosensor based on gold nanoparticles anchored on reduced graphene oxide for sensitive detection of l-lactate tumor biomarker
,
Biosens. Bioelectron.
,
2015
, vol.
69
(pg.
280
-
286
)
78
Yang
Y.
et al.,
A laser-engraved wearable sensor for sensitive detection of uric acid and tyrosine in sweat
,
Nat. Biotechnol.
,
2020
, vol.
38
2
(pg.
217
-
224
)
79
Ramgir
N. S.
,
Zajac
A.
,
Sekhar
P. K.
,
Lee
L.
,
Zhukov
T. A.
,
Bhansali
S.
,
Voltammetric detection of cancer biomarkers exemplified by interleukin-10 and osteopontin with silica nanowires
,
J. Phys. Chem. C
,
2007
, vol.
111
37
(pg.
13981
-
13987
)
80
Dou
Y.
,
Haswell
S. J.
,
Greenman
J.
,
Wadhawan
J.
,
Voltammetric immunoassay for the detection of protein biomarkers
,
Electroanalysis
,
2012
, vol.
24
2
(pg.
264
-
272
)
81
Verma
S.
et al.,
Anti-IL8/AuNPs-rGO/ITO as an immunosensing platform for noninvasive electrochemical detection of oral cancer
,
ACS Appl. Mater. Interfaces
,
2017
, vol.
9
33
(pg.
27462
-
27474
)
82
Koncki
R.
,
Recent developments in potentiometric biosensors for biomedical analysis
,
Anal. Chim. Acta
,
2007
, vol.
599
1
(pg.
7
-
15
)
83
Chumbimuni-Torres
K. Y.
et al.,
Potentiometric biosensing of proteins with ultrasensitive ion-selective microelectrodes and nanoparticle labels
,
J. Am. Chem. Soc.
,
2006
, vol.
128
42
(pg.
13676
-
13677
)
84
Nguyen
H. H.
,
Lee
S. H.
,
Lee
U. J.
,
Fermin
C. D.
,
Kim
M.
,
Immobilized enzymes in biosensor applications
,
Materials
,
2019
, vol.
12
1
pg.
121
85
Adami
M.
et al.,
Characterization of silicon transducers with Si3N4 sensing surfaces by an AFM and a PAB system
,
Sens. Actuators, B
,
1995
, vol.
25
1–3
(pg.
889
-
893
)
86
Ismail
A. B. M.
,
Harada
T.
,
Yoshinobu
T.
,
Iwasaki
H.
,
Schöning
M. J.
,
Lüth
H.
,
Investigation of pulsed laser-deposited Al2O3 as a high pH-sensitive layer for LAPS-based biosensing applications
,
Sens. Actuators, B
,
2000
, vol.
71
3
(pg.
169
-
172
)
87
Yoshinobu
T.
,
Ecken
H.
,
Poghossian
A.
,
Lüth
H.
,
Iwasaki
H.
,
Schöning
M. J.
,
Alternative sensor materials for light-addressable potentiometric sensors
,
Sens. Actuators, B
,
2001
, vol.
76
1–3
(pg.
388
-
392
)
88
Ibarra
I. S.
,
Miranda
J. M.
,
Pérez-Silva
I.
,
Jardinez
C.
,
Islas
G.
,
Sample treatment based on molecularly imprinted polymers for the analysis of veterinary drugs in food samples: a review
,
Anal. Methods
,
2020
, vol.
12
23
(pg.
2958
-
2977
)
89
Parrilla
M.
et al.,
Wearable all-solid-state potentiometric microneedle patch for intradermal potassium detection
,
Anal. Chem.
,
2018
, vol.
91
2
(pg.
1578
-
1586
)
90
Mikkelsen
S. R.
,
Rechnitz
G. A.
,
Conductometric tranducers for enzyme-based biosensors
,
Anal. Chem.
,
1989
, vol.
61
15
(pg.
1737
-
1742
)
91
Uda
M. N. A.
et al.,
Conductometric immunosensor for specific Escherichia coli O157: H7 detection on chemically funcationalizaed interdigitated aptasensor
,
Heliyon
,
2024
, vol.
10
5
pg.
e26988
92
Perera
G. S.
,
Ahmed
T.
,
Heiss
L.
,
Walia
S.
,
Bhaskaran
M.
,
Sriram
S.
,
Rapid and selective biomarker detection with conductometric sensors
,
Small
,
2021
, vol.
17
7
pg.
2005582
93
Lee
I.
,
Luo
X.
,
Huang
J.
,
Cui
X. T.
,
Yun
M.
,
Detection of cardiac biomarkers using single polyaniline nanowire-based conductometric biosensors
,
Biosensors
,
2012
, vol.
2
2
(pg.
205
-
220
)
94
Lin
Y.-H.
,
Lin
W.-S.
,
Wong
J.-C.
,
Hsu
W.-C.
,
Peng
Y.-S.
,
Chen
C.-L.
,
Bottom-up assembly of silicon nanowire conductometric sensors for the detection of apolipoprotein A1, a biomarker for bladder cancer
,
Microchim. Acta
,
2017
, vol.
184
(pg.
2419
-
2428
)
95
Pei
R.
,
Cheng
Z.
,
Wang
E.
,
Yang
X.
,
Amplification of antigen–antibody interactions based on biotin labeled protein–streptavidin network complex using impedance spectroscopy
,
Biosens. Bioelectron.
,
2001
, vol.
16
6
(pg.
355
-
361
)
96
Ciani
I.
et al.,
Development of immunosensors for direct detection of three wound infection biomarkers at point of care using electrochemical impedance spectroscopy
,
Biosens. Bioelectron.
,
2012
, vol.
31
1
(pg.
413
-
418
)
97
Shen
X.
,
Ma
Y.
,
Zeng
Q.
,
Tao
J.
,
Huang
J.
,
Wang
L.
,
Molecularly imprinted electrochemical sensor for advanced diagnosis of alpha-fetoprotein
,
Anal. Methods
,
2016
, vol.
40
8
(pg.
7361
-
7368
)
98
Raghav
R.
,
Srivastava
S.
,
Core–shell gold–silver nanoparticles based impedimetric immunosensor for cancer antigen CA125
,
Sens. Actuators, B
,
2015
, vol.
220
(pg.
557
-
564
)
99
Wang
Y.
,
Chen
L.
,
Xuan
T.
,
Wang
J.
,
Wang
X.
,
Label-free electrochemical impedance spectroscopy aptasensor for ultrasensitive detection of lung cancer biomarker carcinoembryonic antigen
,
Front. Chem.
,
2021
, vol.
9
pg.
721008
100
Khan
R.
,
Pal
M.
,
Kuzikov
A. V.
,
Bulko
T.
,
Suprun
E. V.
,
Shumyantseva
V. V.
,
Impedimetric immunosensor for detection of cardiovascular disorder risk biomarker
,
Mater. Sci. Eng. C
,
2016
, vol.
68
(pg.
52
-
58
)
101
Singh
A. K.
,
Mittal
S.
,
Das
M.
,
Saharia
A.
,
Tiwari
M.
,
Optical biosensors: A decade in review
,
Alexandria Eng. J.
,
2023
, vol.
67
(pg.
673
-
691
)
102
Hosu
O.
,
Ravalli
A.
,
Lo Piccolo
G. M.
,
Cristea
C.
,
Sandulescu
R.
,
Marrazza
G.
,
Smartphone-based immunosensor for CA125 detection
,
Talanta
,
2017
, vol.
166
(pg.
234
-
240
)
103
Yin
B.
et al.,
An enzyme-mediated competitive colorimetric sensor based on Au@Ag bimetallic nanoparticles for highly sensitive detection of disease biomarkers
,
Analyst
,
2017
, vol.
142
16
(pg.
2954
-
2960
)
104
Pires
N. M. M.
,
Dong
T.
,
Hanke
U.
,
Hoivik
N.
,
Recent developments in optical detection technologies in lab-on-a-chip devices for biosensing applications
,
Sensors
,
2014
, vol.
14
8
(pg.
15458
-
15479
)
105
Herrera-Domínguez
M.
,
Morales-Luna
G.
,
Mahlknecht
J.
,
Cheng
Q.
,
Aguilar-Hernández
I.
,
Ornelas-Soto
N.
,
Optical biosensors and their applications for the detection of water pollutants
,
Biosensors
,
2023
, vol.
13
3
pg.
370
106
Sanjay
S. T.
et al.,
Biomarker detection for disease diagnosis using cost-effective microfluidic platforms
,
Analyst
,
2015
, vol.
140
21
(pg.
7062
-
7081
)
107
Dan-Qun
H. U. O.
et al.,
Recent advances on optical detection methods and techniques for cell-based microfluidic systems
,
Chin. J. Anal. Chem.
,
2010
, vol.
38
9
(pg.
1357
-
1365
)
108
Murthy
K. V. R.
and
Virk
H. S.
, Luminescence phenomena: an introduction, in
Defect and diffusion forum
,
2014
, vol.
347
, pp.
1
34
.
109
Sun
Y.
,
Lin
Y.
,
Han
R.
,
Wang
X.
,
Luo
C.
,
A chemiluminescence biosensor for lysozyme detection based on aptamers and hemin/G-quadruplex DNAzyme modified sandwich-rod carbon fiber composite
,
Talanta
,
2019
, vol.
200
(pg.
57
-
66
)
110
Zhou
P.
,
He
H.
,
Ma
H.
,
Wang
S.
,
Hu
S.
,
A review of optical imaging technologies for microfluidics
,
Micromachines
,
2022
, vol.
13
2
pg.
274
111
Yoo
S.-M.
,
Jeon
Y.-M.
,
Heo
S.-Y.
,
Electrochemiluminescence Systems for the Detection of Biomarkers: Strategical and Technological Advances
,
Biosensors
,
2022
, vol.
12
9
pg.
738
112
Zhang
M.
,
Zhou
F.
,
Zhou
D.
,
Chen
D.
,
Hai
H.
,
Li
J.
,
An aptamer biosensor for leukemia marker mRNA detection based on polymerase-assisted signal amplification and aggregation of illuminator
,
Anal. Bioanal. Chem.
,
2019
, vol.
411
(pg.
139
-
146
)
113
Piloto
A. M.
,
Ribeiro
D. S. M.
,
Rodrigues
S. S. M.
,
Santos
C.
,
Santos
J. L. M.
,
Sales
M. G. F.
,
Plastic antibodies tailored on quantum dots for an optical detection of myoglobin down to the femtomolar range
,
Sci. Rep.
,
2018
, vol.
8
1
(pg.
1
-
11
)
114
Hu
J.
et al.,
Advances in paper-based point-of-care diagnostics
,
Biosens. Bioelectron.
,
2014
, vol.
54
(pg.
585
-
597
)
115
Yao
B.
,
Giel
M.-C.
,
Hong
Y.
,
Detection of kidney disease biomarkers based on fluorescence technology
,
Mater. Chem. Front.
,
2021
, vol.
5
5
(pg.
2124
-
2142
)
116
Wang
H.
,
Sun
Y.
,
Yue
W.
,
Kang
Q.
,
Li
H.
,
Shen
D.
,
A smartphone-based double-channel fluorescence setup for immunoassay of a carcinoembryonic antigen using CuS nanoparticles for signal amplification
,
Analyst
,
2018
, vol.
143
7
(pg.
1670
-
1678
)
117
Li
Z.
,
Wang
Y.
,
Wang
J.
,
Tang
Z.
,
Pounds
J. G.
,
Lin
Y.
,
Rapid and sensitive detection of protein biomarker using a portable fluorescence biosensor based on quantum dots and a lateral flow test strip
,
Anal. Chem.
,
2010
, vol.
82
16
(pg.
7008
-
7014
)
118
Li
S.
,
He
K.
,
Liao
R.
,
Chen
C.
,
Chen
X.
,
Cai
C.
,
An interference-free and label-free sandwich-type magnetic silicon microsphere-rGO-based probe for fluorescence detection of microRNA
,
Talanta
,
2017
, vol.
174
(pg.
679
-
683
)
119
Lan
J.
et al.,
Upconversion luminescence assay for the detection of the vascular endothelial growth factor, a biomarker for breast cancer
,
Microchim. Acta
,
2016
, vol.
183
(pg.
3201
-
3208
)
120
Idris
A. O.
,
Mabuba
N.
,
Arotiba
O. A.
,
A Dendrimer Supported Electrochemical Immunosensor for the Detection of Alpha-feto protein—a Cancer Biomarker
,
Electroanalysis
,
2018
, vol.
30
1
(pg.
31
-
37
)
121
Lei
N.
et al.,
A bifunctional luminescence sensor for biomarkers detection in serum and urine based on chemorobust Nickel(ii) metal–organic framework
,
Spectrochim. Acta, Part A
,
2024
, vol.
306
pg.
123585
122
Ammanath
G.
,
Yildiz
U. H.
,
Palaniappan
A.
,
Liedberg
B.
,
Luminescent device for the detection of oxidative stress biomarkers in artificial urine
,
ACS Appl. Mater. Interfaces
,
2018
, vol.
10
9
(pg.
7730
-
7736
)
123
Li
Z.
,
Wang
Z.
,
Nie
Y.
,
Wang
P.
,
Ma
Q.
,
A novel GSH-capping MXene QD-based ECL biosensor for the detection of miRNA221 in triple-negative breast cancer tumor
,
Chem. Eng. J.
,
2022
, vol.
448
pg.
137636
124
Elumalai
S.
,
Managó
S.
,
De Luca
A. C.
,
Raman microscopy: progress in research on cancer cell sensing
,
Sensors
,
2020
, vol.
20
19
pg.
5525
125
Uskoković-Marković
S.
,
Kuntić
V.
,
Bajuk-Bogdanović
D.
and
Holclajtner Antunović
I.
, Surface-enhanced raman scattering (SERS) biochemical applications, in
Encyclopedia of spectroscopy and spectrometry
,
2017
.
126
Tang
H.
,
Zhu
C.
,
Meng
G.
,
Wu
N.
,
Surface-enhanced Raman scattering sensors for food safety and environmental monitoring
,
J. Electrochem. Soc.
,
2018
, vol.
165
8
pg.
B3098
127
Liu
L.
et al.,
Highly scalable, wearable surface-enhanced Raman spectroscopy
,
Adv. Opt. Mater.
,
2022
, vol.
10
17
pg.
2200054
128
Yang
S. J.
,
Lee
J. U.
,
Jeon
M. J.
,
Sim
S. J.
,
Highly sensitive surface-enhanced Raman scattering-based immunosensor incorporating half antibody-fragment for quantitative detection of Alzheimer’s disease biomarker in blood
,
Anal. Chim. Acta
,
2022
, vol.
1195
pg.
339445
129
Srivastava
S. K.
,
Shalabney
A.
,
Khalaila
I.
,
Grüner
C.
,
Rauschenbach
B.
,
Abdulhalim
I.
,
SERS Biosensor Using Metallic Nano-Sculptured Thin Films for the Detection of Endocrine Disrupting Compound Biomarker Vitellogenin
,
Small
,
2014
, vol.
10
17
(pg.
3579
-
3587
)
130
Ju
J.
et al.,
Surface enhanced Raman spectroscopy based biosensor with a microneedle array for minimally invasive in vivo glucose measurements
,
ACS Sens.
,
2020
, vol.
5
6
(pg.
1777
-
1785
)
131
Hong
Y.
,
Huh
Y.-M.
,
Yoon
D. S.
,
Yang
J.
,
Nanobiosensors based on localized surface plasmon resonance for biomarker detection
,
J. Nanomater.
,
2012
, vol.
2012
pg.
111
132
Qian
L.
,
Li
Q.
,
Baryeh
K.
,
Qiu
W.
,
Li
K.
,
Zhang
J.
,
Yu
Q.
,
Xu
D.
,
Liu
W.
,
Brand
R. E.
,
Zhang
X.
,
Chen
W.
,
Biosensors for early diagnosis of pancreatic cancer: a review
,
Transl. Res.
,
2019
, vol.
213
(pg.
67
-
89
)
133
Ashley
J.
et al.,
An SPR based sensor for allergens detection
,
Biosens. Bioelectron.
,
2017
, vol.
88
(pg.
109
-
113
)
134
Shorie
M.
,
Kumar
V.
,
Kaur
H.
,
Singh
K.
,
Tomer
V. K.
,
Sabherwal
P.
,
Plasmonic DNA hotspots made from tungsten disulfide nanosheets and gold nanoparticles for ultrasensitive aptamer-based SERS detection of myoglobin
,
Microchim. Acta
,
2018
, vol.
185
(pg.
1
-
8
)
135
Zou
K.
et al.,
Picomolar detection of carcinoembryonic antigen in whole blood using microfluidics and surface-enhanced Raman spectroscopy
,
Electrophoresis
,
2016
, vol.
37
5–6
(pg.
786
-
789
)
136
Bai
T.
et al.,
Functionalized Au@ Ag-Au nanoparticles as an optical and SERS dual probe for lateral flow sensing
,
Anal. Bioanal. Chem.
,
2018
, vol.
410
(pg.
2291
-
2303
)
137
Ren
C.
,
Bayin
Q.
,
Feng
S.
,
Fu
Y.
,
Ma
X.
,
Guo
J.
,
Biomarkers detection with magnetoresistance-based sensors
,
Biosens. Bioelectron.
,
2020
, vol.
165
pg.
112340
138
Kopparthy
V. L.
,
Tangutooru
S. M.
,
Guilbeau
E. J.
,
Label free detection of L-glutamate using microfluidic based thermal biosensor
,
Bioengineering
,
2015
, vol.
2
1
(pg.
2
-
14
)
139
Lee
S. H.
et al.,
A photothermal biosensor for detection of C-reactive protein in human saliva
,
Sens. Actuators, B
,
2017
, vol.
246
(pg.
471
-
476
)
140
Lee
S.
et al.,
Bi nanowire-based thermal biosensor for the detection of salivary cortisol using the Thomson effect
,
Appl. Phys. Lett.
,
2013
, vol.
103
14
pg.
219902
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