Recent advances in cortisol sensing technologies for point-of-care application.

Biosensors and Bioelectronics 53 (2014) 499–512

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Recent advances in cortisol sensing technologies for point-of-care application Ajeet Kaushik a,n, Abhay Vasudev a, Sunil K. Arya b, Syed Khalid Pasha a, Shekhar Bhansali a,n a b

Bio-MEMS and Microsystems Laboratory, Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, United States Bioelectronics Program, Institute of Microelectronics, AnStar, 11 Science Park Road, Singapore Science Park II, Singapore

art ic l e i nf o

a b s t r a c t

Article history: Received 19 July 2013 Received in revised form 14 September 2013 Accepted 17 September 2013 Available online 17 October 2013

Everyday lifestyle related issues are the main cause of psychological stress, which contributes to health disparities experienced by individuals. Prolonged exposure to stress leads to the activation of signaling pathways from the brain that leads to release of cortisol from the adrenal cortex. Various biomarkers have been affected by psychological stress, but cortisol “a steroid hormone” is known as a potential biomarker for its estimation. Cortisol can also be used as a target analyte marker to determine the effect of exposure such as organophosphates on central nervous system, which alters the endocrine system, leading to imbalance in cortisol secretion. Cortisol secretion of individuals depends on day–night cycle and field environment hence its detection at point-of-care (POC) is deemed essential to provide personalized healthcare. Chromatographic techniques have been traditionally used to detect cortisol. The issues relating to assay formation, system complexity, and multistep extraction/purification limits its application in the field. In order to overcome these issues and to make portable and effective miniaturized platform, various immunoassays sensing strategies are being explored. However, electrochemical immunosensing of cortisol is considered as a recent advancement towards POC application. Highly sensitive, label-free and selective cortisol immunosensor based on microelectrodes are being integrated with the microfluidic system for automated diurnal cortisol monitoring useful for personalized healthcare. Although the reported sensing devices for cortisol detection may have a great scope to improve portability, electronic designing, performance of the integrated sensor, data safety and lifetime for point-of-care applications, This review is an attempt to describe the various cortisol sensing platforms and their potential to be integrated into a wearable system for online and continuous monitoring of cortisol rhythm at POC as a function of one’s environment. & 2013 Elsevier B.V. All rights reserved.

Keywords: Psychological stress Cortisol Immunoassays Electrochemical immunosensing Point-of-care (POC)

Contents 1. 2. 3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Secretion of cortisol. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Urine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Interstitial fluid (ISF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Hair . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Sweat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Blood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6. Saliva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Detection of cortisol: state-of-the-art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Chromatographic techniques for cortisol detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Immunoassays for cortisol detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Electrochemical immunosensing of cortisol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4. Cortisol detection at point-of-care (POC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Corresponding authors. Tel.: þ 1 305 348 3710. E-mail address: [email protected] (A. Kaushik).

0956-5663/$ - see front matter & 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.bios.2013.09.060

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A. Kaushik et al. / Biosensors and Bioelectronics 53 (2014) 499–512

1. Introduction Cortisol, a steroid hormone, is a biomarker for numerous diseases and plays an important role in the regulation of various physiological processes such as blood pressure, glucose levels, and carbohydrate metabolism. It also plays an important role in homeostasis of the cardiovascular, immune, renal, skeletal and endocrine system (Ron de Kloet and Holsboer, 2005; Gatti et al., 2009; Levine et al., 2007). It is known that cortisol secretion follows a circadian rhythm through a 24 h cycle with cortisol levels highest during daybreak (30 min after awakening) and progressively lower by night sleep (Corbalan-Tutau et al., 2012; Nicolson, 2008) (Fig. 1). Apart from the day–night cycle, several controllable factors can affect cortisol levels such as eating patterns and physical activity. Abnormal increase in cortisol levels inhibits inflammation, depresses immune system, increases fatty and amino acid levels in blood. While excess cortisol levels have been shown to contribute to the development of Cushing’s disease with the symptoms of obesity, fatigue and bone fragility (McEwen, 2002), decreased cortisol levels lead to Addison’s disease which is manifested by weight loss, fatigue, and darkening of skin folds and scars (Edwards et al., 1974). The most dominating effect on cortisol variation comes from psychological/emotional stress, which is why cortisol is popularly called the “stress-hormone” (Holsboer and Ising, 2010). Increasing level of psychological stress due to the globalization, altered living style, and competition is becoming a serious concern in everyday schedule and life threatening diseases such as heart attack, depression, and brain pain are the health challenges faced by the most developed countries (Djuric et al., 2008). The potential causes of health disparities in everyday lifestyle are multiple and shown in Fig. 2, Source: NIH Public Access (Djuric et al., 2008). The accurate and precise detection of psychological stress is thus gaining attention for personalized health monitoring and diagnostics. The physiological effects of psychological stress on human health are shown in Fig. 2 (Djuric et al., 2008). The stress cycles (Fig. 3) in human find its ways into nervous system and upsets the chemistry of entire body (Fulford and Stone, 1997). The schematic diagram of the procedures in the body during stress full time is shown in Fig. 4. Efforts are being made to develop wearable detection analytical devices to quantify stress and related abnormalities in environmental condition to gain useful information for timely diagnostics and treatment. Studies have linked cortisol levels with human stress and hence cortisol has emerged as a most potent biomarker for physiological stress detection (Gatti et al., 2009; Levine et al., 2007). There has been growing interest in measurement of cortisol

Fig. 1. Chemical structure of cortisol and typical diurnal variation of cortisol levels over a 24 h cycle.

to establish whether cortisol variation can be used as a precursor to medically and psychologically relevant events such as stress, the most recent affliction being post-traumatic stress disorder (PTSD) (Delahanty et al., 2000; Yehuda et al., 2002, 2001). Since cortisol secretion is dependent on environmental and behavioral triggers, its measurement at point-of-care has become imperative to understand behavioral patterns. Currently, in clinical practice, total cortisol, which is the sum of free and protein bound fractions, is measured. However, free cortisol is the only biologically active fraction (Le Roux et al., 2003) and is responsible for all cortisol-related activities in the body. Hence, in order to accurately diagnose and treat cortisolrelated conditions, regular estimation of free cortisol is required. Most current strategies for the estimation of free cortisol are limited to laboratory techniques that are laborious, time-consuming, require large sample volume, expensive, and cannot be implemented at point of care (Frasconi et al., 2009; Lewis and Elder, 1985; Ruder et al., 1972; Tilden 1977; Turpeinen et al., 1997; Yaneva et al., 2009; Yang et al., 1994). Another significant shortcoming of the current set-up is that they only provide a snapshot of the cortisol levels of samples submitted in a diagnostic lab and do not provide a true representation of the cortisol variations that a specimen undergoes in an environment that triggers cortisol generation or suppression. Hence, real-time and continuous monitoring of cortisol levels is required to obtain valuable information that could assist doctors in better diagnosis and treatment of cortisol-related conditions. Detection of 24-h cortisol levels is currently a cumbersome process, which either involves admitting the patient for the time of study (Czeisler et al., 1976) or where the patient samples blood/saliva into vials at specified time intervals during the 24-h time period, and ships it to a diagnostic laboratory (Brezina et al., 2011). The typical turnaround time is 8–10 days and is still not a true representation of cortisol levels in stressful environments. Hence, there is a need to develop sensing platforms for the detection of cortisol at point-of-care. Application at pointof-care requires that the sensor be portable, have a miniaturized form factor, disposable, sterile, low power consumption, have low turnaround time and is cost effective (Ahn et al., 2004; Soper et al., 2006; Wang, 2006). This review highlights the current efforts to develop strategies and technologies that enable detection of cortisol at POC.

2. Secretion of cortisol Cortisol is a hormone that is secreted from the adrenal glands located above the kidneys. Cortisol is the end product of the hypothalamic–pituitary–adrenal (HPA) axis, which is the main component of the human body’s adaptive system to maintain regulated physiological processes under changing environmental factors. As the name suggests, the HPA axis is a complex signaling system among the hypothalamus in the brain, the pituitary glands and the adrenal glands (Dobson and Smith, 2000; Ron de Kloet and Holsboer, 2005). Fig. 5a presents a schematic of the HPA axis in which a typical response to an environmental trigger is initiated at the hypothalamus that releases a hormone called the CRH (corticotrophin releasing hormone) that travels to the pituitary glands. Specialized cells that work synergistically with the pituitary glands release ACTH (adrenocorticotrophic hormone) into the blood stream that travels to the adrenal cortex. The adrenal cortex responds by increasing the production of cortisol. The produced cortisol then goes to participate in all the governing physiological processes. Since the adrenal glands have no visible innervation, it can be inferred that ACTH is the sole stimulant for initiating cortisol production. The adrenal glands do not store cortisol, but they are


Psychosocial Stress

Race, Ethnicity, Gender, Physical Environment, Income, Education

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Poor Nutrition

Stress Hormone Immune Function Metabolic Deregulation

Inherited Traits, Lifestyle and Diet, Healthcare

Allostatic Load Oxidative Damage Chronic Inflammation

Biological Stress

Disease

Psychological Stress

Infections Cardio-vascular Disease Complication of Obesity & Diabetes Cancer Cognitive Decline in Aging

Fig. 2. Factors act independently and interactively to cause health disparities and physiological mediators of psychological stress (Djuric et al., 2008).

Constricted Blood Vessels & Hypertonic Muscle Fibers Anaerobic Muscle Constriction & Lactic Acid Byproduct

Decreased Co-ordination

Joint Stiffness & Muscles Weakness

Muscle Hypertonicity &

Stress Cycle

Trigger Points

Subluxation /Vertebral Fixation

Decreased Static & Dynamic Muscles Performance

Immobilization and Disuse Recurrent Pain

Pain Avoidance

Depression

Illness Behavior

Fig. 3. Stress cycle and its effect on human nervous system.

prevalent in the form of precursors. Cholesterol undergoes multiple catalyzed oxidation reactions to result in the formation of cortisol. This entire process takes place in a time space of few minutes. The HPA axis is a negative feedback system, where cortisol plays a critical role in the homeostasis of the HPA axis. Moderate homeostatic alterations in the HPA axis are beneficial for the physiological and the psychological development of the human body, sustained and prolonged exposure to environmental triggers such as stress leads to abnormal levels of cortisol in the circulatory system (Dobson and Smith, 2000; Ron de Kloet and Holsboer, 2005).

3. Sources of sample Secreted cortisol finds its way into the circulatory system and can be found in detectable quantities in several bio-fluids. In this section, an assessment of the advantages and disadvantages of using various bio-fluids such as urine, blood, sweat, interstitial

Fig. 4. Stress effect on the adrenaline gland and cortisol production. Source: http://www.headshaker.eu/en/stradrcor.html

fluid (ISF) and saliva for the detection of cortisol is presented (Fig. 5b). 3.1. Urine Cortisol level in urine is measured over a 24-h period and is referred to as the 24-h urinary free cortisol (UFC) test. Only free cortisol, which is the active form of cortisol in the human body, is found in urine and is hence a relevant bio-fluids for the detection of cortisol. The excretion of hormones, salts and other waste chemicals through urine is a well-characterized process with good knowledge about the concentration of these waste substances under normal function. Observation of drastic variation in concentrations of hormones such as cortisol can be used to diagnose abnormalities in the adrenal function. Measurement of cortisol in urine typically requires the collection of all the urine generated over a 24-h time period. Normal range for cortisol in urine is 10–100 μg/24 h. A review of the reported literature for urinary cortisol assays has been presented by Brossaud et al. (2012). While the 24-h urinary free cortisol test provides a means for a non-invasive, painless method of obtaining body fluid for cortisol measurement, it also poses several drawbacks with respect to convenience and reliability. Since the collection of the urine is spanned over a 24-h time period, sample collection becomes an inconvenient process where the patient needs to carry the special

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Fig. 5. (a) Cortisol secretion regulated by the HPA axis and (b) various bio-fluids used for cortisol estimation.

Fig. 6. (a) Cross-section of micropore generated through laser ablation; (b) four pores relative to the size of a penny; and (c) handheld laser source used to create micropores (Venugopal et al., 2011).

urine collection container all day long or has to remain confined to a location for the 24-h period. The container also needs to be stored under refrigeration from the time of collection till it is delivered to a diagnostic lab for testing. Also, several factors such as pregnancy and medication such as diuretics can alter the concentration of cortisol in urine making it a lesser reliable biofluids for cortisol detection. These several additional factors have severely limited the use of urine in cases where patients are admitted to the hospital for long-term treatments. The requirement of 24 h sample collection has rendered urine unfit for realtime detection at point of care. 3.2. Interstitial fluid (ISF) ISF is an extra cellular fluid that surrounds the cells in the human body. In composition, it is similar to blood plasma. Metabolites and proteins move into ISF as they move from capillaries to cells. In general, small to moderate sized molecules, including glucose, ethanol, and cortisol, are found in ISF in similar proportion as in blood. Thus, periodic calibration using blood sampling is not required to obtain the concentration of these metabolites from ISF. ISF is present just below the skin, but the low permeability of the epidermal keratinized layer (the stratum corneum) blocks the permeation of the fluid through the skin. However, obtaining ISF for the detection of a target biomarker could require an invasive approach as it is not readily accessible. Several approaches have been reported in the literature to obtain ISF in a minimally invasive, painless process. Venugopal et al. (2008) have reported the construction of an ISF harvesting system that utilizes a low-energy laser to create micropores in the stratum corneum (the uppermost layer of dead cells) (Fig. 6). The diameter of the micropores is approximately equal to that of a human hair. The micropores only penetrate the stratum corneum and, hence, this procedure is essentially painless. ISF is drawn through these

micropores continuously by the application of a small amount of vacuum pressure. Harvesting of ISF using this set-up is reported at a rate of 10 mL/h Fig. 6. Coupled with an electrochemical detection system, Venugopal et al. (2011) have reported the detection of cortisol using the same microporation set-up. Cortisol levels in ISF were found to be 3–4 times larger than that in saliva, which makes ISF an attractive biofluid for the detection of cortisol. While this set-up may provide a means to access ISF for cortisol detection, the low harvesting rate (10 mL/h) would limit its applicability for obtaining instantaneous cortisol values in a point-of-care setting. Micromachined microneedles for transdermal application are another option to harvest ISF (El-Laboudi et al., 2013; Prausnitz, 2004). Microneedles have been used extensively for transdermal drug delivery (Khanna et al., 2008; Prausnitz, 2004). Mukerjee et al. have reported the design, fabrication and testing of a hollow microneedle array containing fluidic microchannels for the transdermal extraction of ISF from human skin (Mukerjee et al., 2004). Wang et al. (2005) have also reported the fabrication of glass microneedles for ISF extraction for glucose monitoring. These approaches show promise for creating painless, minimally invasive methods for extraction of ISF. Microneedles based transdermal ISF extraction may find good application in wearable biosensing system, where there is a critical need to continuously sample body fluids such as ISF at a low sampling rate. However, concerns regarding biocompatibility and biodegradation of the microneedles, protection from infection due to usage of needles and other sterility issues will need to be carefully addressed for successful implementation. 3.3. Hair The use of hair as the biological sample for analysis and testing in forensic sciences, toxological science, doping control and clinical diagnostics has gained considerable attention over the last two


decades (Bennett and Hayssen, 2006). Human hair grows at a predictable rate of approximately 1 cm/month. Cortisol is known to deposit in the shaft of the hair and the most proximal 1 cm segment of hair closest to the scalp approximates the last month’s cortisol production and so on. The mechanism for the incorporation of cortisol into the hair shaft has been proposed by Bennett et al. (Bennett and Hayssen, 2006; Russell et al., 2012b). Fig. 7 presents an illustration of cortisol storage mechanism in the hair follicle and its usage for analysis of long-term exposure of cortisol. Cortisol is thought to enter hair primarily at the level of the medulla of the hair shaft via passive diffusion from blood. In this scenario hair cortisol would be hypothesized to reflect the integrated free cortisol fraction rather than the total cortisol concentration in serum. One of the first studies to establish feasibility of using hair for cortisol detection was reported by Koren et al. (2002) using hair from wild hyraxes. Detection was performed using a modified salivary ELISA protocol. Sauve et al. (2007) reported the first study on human hair samples for cortisol detection and reported a reference range from 1.7 to 153.2 pg/mL. The obtained values were compared to those obtained from saliva, serum and 24-h urine. A positive correlation was identified only to that of 24-h urine, with no correlation to that of saliva or serum. Hair cortisol measurement surely provides a non-invasive method of obtaining a biological sample. Since the cortisol concentration in hair is hypothesized to represent long-term system exposure, it could be used as an indexing method to maintain a cortisol secretion calendar. From the various other reported studies (Gao et al., 2010; Gow et al., 2010; Kalra et al., 2007; Krischbaum et al., 2009; Manenschijn et al., 2011; Raul et al., 2004; Stalder et al., 2012) for cortisol detection from human hair, it is evident that cortisol values only for long-term exposure to factors such as stress can be obtained. The resolution of the data obtained is in the order of months, with very little clinical data available to support the correlation of hair cortisol levels to stress levels. 3.4. Sweat Sweat analysis is a well-established method for diagnosing certain conditions such as cystic fibrosis and drug abuse. Sweat patches could be used as an effective non-invasive tool to collect sweat (Prunty et al., 2004). Cortisol in sweat has been measured by

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Russell et al. (2012a) with cortisol concentrations ranging from 141.7 ng/mL (daytime) to 8.16 ng/mL. It is hypothesized that there exists a strong correlation between cortisol levels in sweat and hair due the path that cortisol traverses from serum, sebum and sweat to the hair. However, very little is known about cortisol in sweat and several inherent drawbacks exist in obtaining reliable and repeatable sweat samples to accurately measure cortisol in sweat. Perspiration is dependent on several factors such as weather conditions (humidity, temperature), geographic conditions, physical activity levels, ambient temperature or conditioned temperature and genetic make of the patient. Development of microfluidic sweat collection cloth has been proposed as further advancement in sweat based cortisol detection where sweat will be collected using the cloth patches and analyzed using an integrated device (Xing et al., 2013). 3.5. Blood More than 90% of cortisol in blood is in an inactive state being bound to corticosteroid binding globulin (CBG) and serum albumin. Only 10% of the total cortisol is in a biologically active state to participate in cortisol initiated processes. Typically assays for measuring cortisol in blood involve measuring the total cortisol (bound þfree) and then the active fraction, called the Cortisol Free Index (CFI) is deduced using Coolen’s equation (Le Roux et al., 2003). Blood sampling for cortisol detection has been the oldest form of bio-fluid sampling. The nominal value for cortisol in blood varies from 25 mg/dL (9 AM) to 2 mg/dL (midnight). Blood, however, is afflicted by many drawbacks, which has made it a last choice sampling fluid. Sampling blood requires attention from medical staff and specialized, sterile equipment with an ever-existing concern for infections. While cortisol is an unstable molecule at room temperature, its presence in plasma requires special handling and storage condition as it is considered a biohazard. Since sampling blood requires puncture of veins, a painful procedure, the stress experienced by patients prior to and during sampling may elevate cortisol levels (Levine et al., 2007). Although the typical response time for cortisol spiking is 10–15 min in humans, prior knowledge of venipuncture can initiate the stress response induced cortisol spiking. Also, the costs associated with staff, equipment, handling and storage make the blood based assay a shunned option.

Fig. 7. Illustration of the accumulation of cortisol in the medulla of a hair follicle (Russell et al., 2012b).

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3.6. Saliva Over the last few years, saliva has gained considerable attention as a bio-fluid for analysis and detection of cortisol concentrations. This has come about mainly due to inherent advantages associated with saliva. First and foremost, a well-documented strong correlation exists between salivary and blood cortisol levels (Teruhisa et al., 1981; VanBruggen et al., 2011). Also, of high importance is the fact that cortisol in saliva exists entirely in the free state unlike in blood (90% bound), resulting in the detection of the relevant (biologically active) form of cortisol. This is mainly due to the filtering of the CBG and albumin bound cortisol during capillary exchange and other intracellular mechanisms at the salivary ducts. Harvesting samples for analysis is almost completely non-invasive with little or no discomfort to the specimen providing the sample (Van Caenegem et al., 2011). The last few years has seen the establishment of standard operation procedures for collection of saliva, which has led to lesser variability in analyzed results. The samples can be harvested with minimum efforts that have facilitated patients to collect their own samples at home. The advantages associated with salivary techniques have led to saliva being on the verge of becoming the preferred source of body fluid for the detection of cortisol. Also, the ease of sample collection, handling and storage have heightened its prospects for applying in point-of-care sensors for real-time and continuous detection of cortisol. However, there are certain aspects that may adversely affect the prospects of saliva based cortisol detection. Since only the active component of cortisol (free cortisol) is present in saliva, the concentration of cortisol is much lower than that of blood. Moreover, the room temperature instability of salivary cortisol possesses the problem of storage during on-site sample collection and processing. Also, the nominal values for cortisol in saliva during the diurnal cycle vary from 0.5 mg/dL to 0.05 mg/dL, which require high sensitivity assays with low detection limits for efficient detection of cortisol concentration in saliva. Deviation from the standard operating procedure for saliva collection can lead to erroneous results. Sometimes, the presence of blood due to oral lessons may lead to elevated levels of cortisol and cause erroneous results. Salivary cortisol assays have been reported in the literature extensively for characterizing the circadian rhythm (Price et al., 1983), Cushing’s syndrome (Raff et al., 1998), Addison’s disease

(Lovas et al., 2006), adrenal abnormalities (Granger et al., 2012) and stress related disorders (Carpenter et al., 2011). A comprehensive review-recent advancement of cortisol detection techniques in various bio-fluids lend themselves to detection at point of care is presented in next section.

4. Detection of cortisol: state-of-the-art Cortisol has been detected using various methods as shown in Fig. 8. Having studied the physiology of cortisol and evaluating the pros and cons of the different sources of bio-fluids for cortisol detection, this section provides a comprehensive overview of the various detection techniques for quantification of cortisol (Fig. 8). 4.1. Chromatographic techniques for cortisol detection Chromatographic techniques are the older and one of the first techniques to detect cortisol. These techniques are used to separate cortisol from saliva, hair, urine, serum, etc., using a process of mass transfer induced adsorption. In 1979, Kabra et al. (1979) described the use of liquid chromatographic (LC) technique to detect serum/plasma (1 mL) cortisol and achieved a detection limit of 2 ng/mL and a sensitivity of 5 ng/mL of serum cortisol. Raul et al. purposed that hair can document chronic abuse and can be therefore a complementary matrix for doping control. They developed an extraction, a purification and a separation technique using LC and mass spectrometry (MS) for the identification and quantification of cortisol and cortisone using 44 hair samples (Raul et al., 2004). This method exhibited a detection of 1 pg/mg and a limit of quantification as 5 pg/mL. The observed detection range for cortisol was from 5 to 91 pg/mg (mean 18 pg/mg) and for cortisone was ranged from 12 to 163 pg/mL (mean 70 pg/mL). The results were not influenced by hair color but found to be influenced by sex. Klopfenstein et al. (2011)have also utilized the LC-MS technology to develop and validate an improved method for measuring cortisol in blood plasma. Authors measured 24-h cortisol production rate (CPR) using steady-state infusion of deuterated cortisol and analysis of stable-isotope dilution by MS. This method showed improved selectivity over previous methods via elimination of interference from compounds such as

Fig. 8. State-of-the-art for cortisol detection.


20β-dihydrocortisol. This method exhibited a limit of quantification (LOQ) 1 ng/mL (2.73 nM), a limit of detection (LOD) of 0.6 ng/ mL (1.37 nM) and linearity ranging from 1.5 to 10% cortisol-d3 with correlation coefficients of 0.995%. High-performance thin-layer chromatography (HPTLC) has been used to estimate low concentration of fluorescence-labeled cortisol in human plasma (6–25 μg/100 mL) (Funk et al., 1981). This technique exhibited a detection limit of 2.5 pg/spot and a detection range of 10–1000 pg/spot for the samples pretreated by a column extraction. Results suggested that HPTLC may explore the separation of several serum samples on one plate simultaneously. A rapid highperformance liquid chromatographic (HPLC)/UV system has also been utilized to detect both cortisol and its dehydro metabolite cortisone (in saliva) (Wade and Haegele, 1991), where it was able to detect 0.5 ng/mL corticosteroid concentrations. Zhang et al. (2008) designed a fiber-packed solid-phase extraction (SPE) tip based on the electrospun nanofibers to investigate the extraction of hydrocortisone, cortisone acetate, ethinylestradiol, and estradiol. Author detected 0.74 ng/mL cortisol in water samples. This SPE tip was also utilized for the detection of cortisol with improved performance than the traditional SPE method. This group further utilized nanofiber-packed SPE to detect salivary-free cortisol using fluorescence pre-column derivatization and HPLC (Chen et al., 2010). An array pretreatment device based on nanofibers packed SPE was used to achieve high throughput sample extraction. This technique exhibited a detection limit of 0.01 mg/L for saliva cortisol and successfully had applied in the determination of free cortisol in human saliva ranged from 0.22 to 7.45 mg/L. The nanofiber-packed SPE overcame the low extraction recovery and bad cleanup effect of the conventional methods, and increased the sensitivity and selectivity. Gao et al. (2010) developed the HPLC-FLU method to detect cortisol in human hair (per cm segment along hair shaft). The extraction was derived with sulfuric acid using the SPE C18 column. This method exhibited a detection limit 1 pg/mL, and concentrations from 3.28 to 24.83 pg/mL based on 32 human samples. The presented method showed that the precision matched with mass spectroscopy and cortisol in per cm hair segment sensitively reflected a retrospective calendar over 1 month. These techniques have shown cortisol detection in physiological range. However, lacks of specificity that is required in measuring low concentrations, and effect of interference from co-eluting substances in the sample limits their application at POC. For example, HPLC requires many preprocessing procedures such as solid-phase extraction (Turpeinen et al., 1997). These problems may perhaps be overcome using immunoassays for the detection of cortisol. 4.2. Immunoassays for cortisol detection Immunoassays are based on the ability of an antibody to recognize and selectively bind to an antigen, referred to as the analyte (Fig. 9). The high degree of selectivity and specificity of an antigen–antibody binding makes immunoassays the gold standard

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technique for the detection of presence, and measurement of the concentration of the analyte of interest. For the detection of cortisol, radioimmunoassay (RIA), which involves the use of radioisotopes as label was reported in the late 1970s (Abraham et al., 1972; Dash et al., 1975; Gomez-Sanchez et al., 1977; Kao et al., 1975; Ruder et al., 1972). Since 1980s, the use of RIA has diminished due to the potential harmful effects of handling radioisotopes. The focus has shifted towards the use of labels with a fluorescing property. The use of fluorescent tags such as fluorescein isothiocyanate (FITC) (Kobayashi et al., 1979), mixture of sulfuric acid and acetic acid (Appel et al., 2005) have been used as the label in cortisol immunoassays. A fluorescence detector is utilized to read the intensity of fluorescence, which is proportional to the concentration of the fluorescence-labeled analyte. Petkus et al. (2006) described magnetic field-induced structures of paramagnetic particles as a solid substrate to demonstrate improved detection limits for a separation free assay of cortisol. Authors utilized frequency and phase filtering for the signal generated from surface-bound labeled species to improved mass transport of the antigen to the surface of the rotating structures. Fluorescein isothiocyanate labeled cortisol (FITC-cortisol) has been detected at 300 pM using this method. Another popular optical based immunoassay is the electrochemiluminescence immunoassay (ECLIA). ECLIA is based on the electro-generated chemilumenescing property of intermediates undergoing a highly exergonic reaction to produce an electronically excited state that emits light. ECLIA has developed into highly reliable immunoassay technique due to the high sensitivity and precise control over the electrochemical reaction. ECLIA has found application in many clinical studies for cortisol detection in human samples for Cushing’s syndrome (Carrozza et al., 2010; Yaneva et al., 2009), obesity (Belaya et al., 2012), athletic disorders (Lippi et al., 2009) and stress related disorders such as PTSD (McRae et al., 2006; Pervanidou et al., 2007). van Aken et al. (2003) developed a fully automated sheep polyclonal antibody based competitive nonisotopic ECLIA assay for the measurement of cortisol in saliva. The obtained detection limit of 8 ng/mL (2 nM) within 18 min and reproducibility suggested its application for the assessment of the activity of hypothalamic–pituitary–adrenal axis. This method offers several advantages of automation, no pretreatment, short assay time over isotopic assays and commercially available enzyme immunoassays. Shi et al. (2009) described a chemiluminescence (CL, Fig. 10) strategy based on the reaction of a Ag(III) complex with luminol to detect cortisol. This assays incorporated with a flow injection analyses (FIA) for the estimation of free cortisol in human sera. This detection system was found to be highly sensitive and convenient and may find wide applications. This CL-FLA technique exhibited a detection linear range of 0.1–2.7 ng/mL (0.05–7.5 nM), LOD 0.07 ng/mL (200 nM) with a relative standard deviation (n ¼11) of 1.9% for 0.1 ng/mL (3.5 nM) cortisol. Recently, Kim et al. fabricated a sensitive bioluminescent probe for salivary cortisol. N-terminal-extended ligand binding domain

Fig. 9. Schematic illustrations of various immunoassay techniques.

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Fig. 10. Reaction mechanism suggested for the CL reaction.

of glucocorticoid receptor (GR HLBD) was situated downstream of a glucocorticoid response element (GRE) promoter in a reportergene system and was used to construct two on/off switches for cortisol (Kim et al., 2011). The reporter-gene system exerts an improved signal-to-background (S/B) ratio and exhibited 10 time enhanced detection limit to cortisol with longer from 0.36 to 36 ng/mL (1 pM–1 nM). The obtained sensing parameter was validated using ELISA and covered all the normal clinical ranges of serum, urine, and saliva. This was the first report to investigate the role of the HLBD of a nuclear receptor and multiple on/off switches for molecular probes and salivary cortisol. A competitive immunoassay based microchip integrated with electrophoretic system has been designed for the separation and quantification of free and bound labeled cortisol in blood serum (1–60 ng/dL) (Koutny et al., 1996). The separation was achieved in 30 s and high throughput was possible during parallel multiple channels operation. A capillary electrophoresis (CE) and a laserinduced fluorescence based competitive immunoassay for cortisol detection in serum were described by Schmalzing et al. (1995), where fluorescein-labeled cortisol, mouse monoclonal anticortisol antibody and serum were separated by CE with high reproducibility. This method exhibited a detection limit of 0.4 ng/mL (1.3 nM) and a linear detection range 1–60 mg/dL. Jia et al. (2002) reported a CE enzyme immunoassay for the electrochemical detection of cortisol. In competitive enzyme immunoreaction, the free enzyme (horseradish peroxidase, HRP)-labeled cortisol (HRP-cortisol) and the bound enzyme-labeled cortisol (HPR-cortisol–anti-cortisol) were separated using CE and then catalyzed the enzyme substrate [3,3,5,5-tetramethyl-benzidine dihydrochloride, TMB (red)]. Amperimetric detection of produced enzymatic catalysis reaction [TMB(Ox)] was done using a carbon fiber microdisk bundle electrode. A detection limit of 6 ng/mL (1.73 M/L) with the relative standard deviation of 3.3% has been exhibited using a carbon fiber microdisk based sensor. Among all the available labeled immunoassays, enzyme linked immunosorbent assay (ELISA) has been found to be the most sensitive and versatile and today, it is considered the gold standard in the protein concentration determination. ELISA is typically performed in a sandwich format, where an enzymatic substrate is added to the secondary antibody to amplify the colorimetric or fluorescent signal, thereby providing high sensitivity. Detection of cortisol using ELISA is used widely (Lewis and Elder, 1985; Shimada et al., 1995) and often has been the technique used to

validate results obtained from newer techniques being developed for cortisol detection (Small and Davis, 2007). Manenschijn et al. (2011) collected hair samples of 195 healthy individuals, nine hypercortisolemic and one hypocortisolemic patient to estimate cortisol using a salivary ELISA kit. A positive correlation between hair cortisol and both waist circumference (r¼ 0.392, p ¼0.007) and waist-to-hip ratio (WHR) (r ¼0.425, p ¼0.003) was found and no correlations were found between hair cortisol levels and blood pressure or age. While ELISA is the most widely used technique in research labs and industry, the method is limited by the need for a large sample and reagent volumes and complexity arising from multiple assay steps and large incubation times. To overcome the tedious processes, cost and shortcomings of the assay performance, focus has been shifted towards developing label-free immunosensing techniques with high sensitivity, lower detection limits and broader detection range (Cooper, 2003). One such technique that demonstrates label-free detection is based on surface plasma resonance (SPR) (Shankaran et al., 2007). SPR works on the principle of oscillation of valence electrons in a conducting substrate irradiated with light. SPR is highly sensitive to adsorption of molecules onto the substrate, where the resonance curves shift to higher wavelengths with the adsorption of molecules onto the surface. SPR has shown promise as a method to quantitatively measure the capture of analyte on substrates coated with antibodies. The associated detection optics and electronic for SPR measurement can be reduced to miniaturized form factors and have hence attracted efforts to create point-of-care immunosensors (Mitchell et al., 2008). More recently, detection of cortisol in saliva (Stevens et al., 2008) and other bio-fluids using SPR has been reported in the literature. On the same lines as SPR, another technique gaining ground for immunosensing is based on the resonance property of quartz crystal microbalance (QCM) (Atashbar et al., 2005). Cortisol antibody was layered onto the Au gold electrodes of a 10 MHz piezoelectric crystal to fabricate a piezoelectric crystal immunosensor for the detection of cortisol (Attili and Suleiman, 1995). Piezoelectric crystal was pre-cleaned, protein-A and immunosensors detected cortisol at a concentration of 3.628 μg/mL. The proposed sensor includes elements of simplicity, short analysis time, cost effectiveness and selectivity. However, there is a scope for improvement with respect to its detection limit. Stevens et al. (2008) described a portable cortisol-specific monoclonal antibodies based competition assay with a sixchannel portable SPR biosensor to detect cortisol in saliva. This assay exhibited a detection limit of 0.36 ng/mL (1.0 nM). Authors have used hollow fiber hydrophilic membrane in the filtering flow cell provided to separate small molecules from the complex macromolecular matrix of saliva. This immunoassay exhibited a detection limit of 1.0 ng/mL (3.6 nM) which is sufficiently sensitive for clinical use. A cortisol antibody immobilized polycarboxylatehydrogel-based SPR immunosensor for the real-time detection of cortisol and cortisone levels in urine and saliva samples were fabricated by Frasconi et al. (2009). The fabricated immunosensor was specific, exhibited stability during repeated regeneration and affinity reaction cycles. The obtained results were correlated with LC-MS for the analysis of cortisol and cortisone in urine and saliva samples. The sensor exhibited a detection limit of 10 μg/L with a negligible effect of interferents. The performance of SPR based immunosensing of cortisol detection in saliva was improved by Mitchell et al. (2009) via designing a cortisol-linker conjugate that allows high assay sensitivity. Assay employed a coating antigen in a microfluidic SPR immunoassay i.e., a competitive immunoassay using a secondary antibody for signal enhancement. This immunosensor was automated and showed high sensitivity and was capable of yielding results in 15 min. This cortisol assay showed a good


correlation to RIA (r ¼ 0.94) and exhibited a limit of detection of 49 pg/mL. Authors mentioned that covalently immobilized sensor surface provided stable responses for more than 140 binding and regeneration cycles, enabling reuse.

4.3. Electrochemical immunosensing of cortisol Recently, among the label-free technologies for detection in immunosensing, electrochemical immunosensing has emerged as the most promising alternative to optical detection. Electrochemical immunosensing is based on the principle of measuring the changes in electrical properties of a conductive material due to the adsorption of an analyte on the surface functionalized with antibodies. The electrical change is attributed to the change in the concentration of the electro active redox species at the electrode proximity. The mature processing capability of the microelectronics industry has allowed building microelectrodes that provide high sensitivity and very low detection limits. The simplicity of electronic circuitry for electrochemical detection and cheap volume manufacturing has driven efforts to bring electrochemical immunosensing up to speed with other immunosensing techniques (Ricci et al., 2012). Due to high sensitivity, easy fabrication using nanotechnology, and multi-parametric analysis, electrochemical immunosensor have shown a great potential to detect desired biomarkers at POC (Wan et al., 2013). Fig. 11 shows the strategies utilized for sensing the immunoreaction exist. Sun et al. (2008) reported cortisol antibodies immobilized on micro-fabricated Au electrodes for immune-electrochemical sensing using alkaline phosphatase (AP) enzyme for the determination of salivary cortisol. During the biochemical reaction, p-nitrophenol (pNP) generated via reaction between AP enzyme attached to the cortisol and antibodies in p-nitrophenyl phosphate (pNPP) solution pNP was detected using a cyclic voltammetry (CV) at room temperature. The fabricated immunosensor exhibited a detection limit of cortisol in saliva as 0.27 ng/mL with an incubation time of 10 min. Dithiobis (succinimidyl propionate) (DTSP) self-assembled monolayer (SAM) modified interdigitated m-electrodes (IDμEs) were used for the immobilization of Cortisol-specific monoclonal antibody (C-Mab) to detect cortisol using electrochemical impedance (EIS) technique (Arya et al., 2010a). EIS immunosensor exhibited the sensitivity of 2.855 kΩ/(pg/mL) and found to detect cortisol in the range of 0.36 pg/mL–0.36 ng/mL in saliva. This group has further used the same immunosensing strategy to detect cortisol in ISF in vitro (Arya et al., 2010b, 2010c). EA/CMab/DTSP/Au based biosensor can accurately detect cortisol in the range of 0.36 pg/mL–0.36 ng/mL with the detection limit of 0.36 pg/mL. The performance of this EIS based immunosensor was validated using ELISA. Authors purposed the feasibility of using impedance based biosensor as a disposable cortisol detector, capable of working with complex bodily fluids (e.g., saliva and ISF) at a point-of-care.

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Utilizing harvested ISF by means of vacuum pressure from micropores created on the stratum corneum layer of the skin, Venugopal et al. (2011) described the cortisol estimation via EA/CMab/DTSP/Au based immunosensor. The sensing parameters were validated using ELISA and showed a linear response to cortisol concentrations in the range 0.36 pg/mL–36 ng/mL. The results of the studies suggested that a circadian rhythm could be established between the subject’s ISF and the saliva samples collected over 24 h time-periods. Author proposed that continuous ISF harvests and cortisol monitoring over 24 h even when the subject is asleep can project commercial viability for an in vivo real-time cortisol sensor device. Current analytical approaches rely on immunoassays performed at distant, centralized laboratories and involve an elaborate specimen collection–processing–transportation storage–analysis–reporting cycle. To facilitate point-of-use measurement of salivary cortisol levels, Tlili et al. developed a sensitive, label-free immunosensor using single-walled carbon nanotubes (SWCNTs) based chemiresistive transducer. In this work, SWCNTs were functionalized with a cortisol analog [cortisol-3-CMO-NHS ester] and a monoclonal anti-cortisol antibody was legated to this receptor for immunosensing (Tlili et al., 2011). The immunosensor was selective and demonstrated an ultralow detection limit of 1 pg/ml, a linear range from 1 pg/mL to 10 ng/mL and had a sensitivity of 14.9 ng/mL (Fig. 12). Exploration of nanomaterials as a supporting matrix for antibody immobilization has shown promises to enhance the sensitivity and selectivity of cortisol detection (Moreno-Guzman et al., 2010). A competitive immunoassay fabricated using an anticortisol antibody immobilized onto protein A-modified magnetic particles and cortisol antigen labeled with alkaline phosphatase (AP), under optimized parameters, exhibited a linear range between 5.0 pg/mL and 150 ng/mL and a limit of detection was 3.5 pg/mL in DPV investigations. The fabricated sensor was highly sensitive and selective with respect to other corticosteroid compounds closely related to cortisol and demonstrated by analyzing certified human sera containing cortisol. In other study, Arya et al. utilized electrophoretically fabricated polyaniline (PANI)-Au nanocomposite to immobilized C-Mab covalently via EDC-NHS chemistry to fabricate a mediator and label-free electrochemical immunosensor for cortisol estimation using CV technique (Arya et al., 2011). This nanocomposite based immunosensor detected cortisol in the range of 0.36 pg/mL–36 ng/mL (1 pM–100 nM) and a detection limit of 1 pM with a sensitivity of 1.63 mA/M and found to be sensitive only for cortisol. Electrophoretically deposited PANI-core-shell Ag@AgO (NP 5 nm) nanocomposite films have also been explored for Anti-cortisol (Anti-Cab) antibody immobilization via EDC/NHS chemistry for mediator/labelfree electrochemical detection of cortisol. Authors proposed that nanocomposite exhibited a high magnitude of current response, which resulted in high electron transport at the electrode–electrolyte interface without a mediator (Fig. 13). This immunosensor exhibited a wide linear detection range of 0.36 pg/mL–3.6 mg/mL

Fig. 11. Schematic of strategies used for electrochemical immunosensing.

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(1 pM–1 mM), a detection limit of 0.64 pM/mL, and a high sensitivity of 66 mA/M with a regression coefficient of 0.998. There have been inherent limitations of the above-mentioned cortisol immunosensors that have been designed in field and on-site cortisol detection. Low shelf-life of immunosensor at room temperature and denaturation of an antibody due to the environmental factors (temperature fluctuations, humidity, change in pH, exposure to light, etc.) limits their application in the field for diurnal cortisol measurement. The encapsulation of antibody to retain its bio-integrity (Chantasirichot and Ishihara, 2012) and single domain antibodies (Goldman et al., 2008) which shows potential as inherently immune to changes in temperature can be the possible solution to overcome the issue to antibody stability. But these strategies are not yet in practice. Thus, there is a great scope to conduct research in the area of developing miniaturized electrochemical devices to monitor cortisol cycle for personalized healthcare at POC. 4.4. Cortisol detection at point-of-care (POC) Since the globalization and modern lifestyles affect genetic disorder and protein concentration, which are major causes of diseases, these systems are deemed as pioneer technology for the improvement of

Fig. 12. Calibration plot of cortisol immunosensor in artificial saliva (each data point is an average of six electrodes and error bars represent 71 SD) (Tlili et al., 2011).

both global healthcare and health disparities monitoring. The development of diagnostics tools that are capable of quantifying specific biomarkers and of providing health informatics for superior treatment strategy, such as POC sensors, are in high demand. The demand for real-time healthcare monitoring devices is rapidly increasing due to the numerous benefits that this technology offers from a social, scientific, and financial perspective (Chan et al., 2013; Price and Kricka, 2007; Yager et al., 2008). Recently, miniaturized sensing devices have been explored for biomarker detection in order to decrease the probability of human error and the sample volume required (Lillehoj et al., 2013; Loncaric et al., 2012). The obtained data can be used as health informatics that can be useful for the timely disease diagnostics. In this context, wearable sensor, devices either supported on human body or piece of clothing, has shown potentials in health diagnostics at POC. These devices are described as an autonomous and non-invasive system that performs a specific monitoring of target analyte in physiological conditions and provides physiological monitoring, data storage and processing (Glaros and Fotiadis, 2005). However, system integration, low power electronics, biocompatibility, timely calibration and short life time of integrated sensor are the major barriers to develop POC diagnostic systems. Portable miniaturized analytical devices for disease detection at early stages and for monitoring physiological variables at POC could be useful to personalize health diagnostics for appropriate effectual and exact treatment (Glaros and Fotiadis, 2005; Hung et al., 2004; Turner, 2013). Recently to improve on many of the current sensing systems that are used in diagnostic laboratories and cannot be applied at POC due to constraints of portability, cost, analysis time or requirement of highly skilled personnel to operate these systems, microfluidic systems have enabled the development of POC chemical and biological assays. The main advantages of microfluidic systems are small sample volumes, precise control of fluidic routines, repeatable sensing protocols, controlled environment for biomolecule reaction, reduced form factor and application at point of care. The high degree of automation that exists in microfluidic systems also eliminates error often associated with human handling and thereby reduces the percentage of false positive results. These features have drawn focus in integrating biosensors into a microfluidic environment with a goal to create point-of-care sensors. Kumar et al. (2007) have fabricated an electrochemical biosensor using Au nanowires coupled with cortisol antibodies using covalent

Fig. 13. (a and b) TEM image of Ag@AgO NP; (c) AFM image of Ag@AgO-PANI nanocomposite; (e) AFM image of Ag@AgO-PANI cortisol immunosensor; (d) calibration curve obtained from the electrochemical response studies of BSA/Anti-Cab/Ag@AgO-PANI/Au immunoelectrode as a function of cortisol concentration (1 pM–1 mM) (Kaushik et al., 2013).


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Fig. 14. (a) Schematic of immune-chromatographic test-strip, (b) competitive reaction of cortisol and GOD-cortisol conjugate, and (c) coloring by GOD enzyme reaction (Yamaguchi et al., 2009).

linkage chemistry and a fixed amount of 3 α-hydroxysteroid dehydrogenase was introduced into the reaction cell during each measurement to convert ketosteroid into hydroxyl steroid i.e., cortisone (inactive keto form) to cortisol (active form). Authors have fabricated microfluidic integrated immunosensor using MEMS technology to control on liquid flow over Au nanowires to minimize the signal to noise ratio. Authors concluded that the functionalized Au nanowires with MEMS device using enzyme fragment complementation technology exhibited a linear range from 3.7 to 12 mg/mL (10–80 mL) and can provide an easy and sensitive assay for cortisol detection in serum and other biological fluids. A portable, rapid and hand held biosensor based on disposable immune-chromatographic test strip has been proposed by Yamaguchi et al. (2009) to analyze salivary cortisol level at POC (Fig. 14). An immune-chromatographic test-strip (5 1.5 50 mm3) consists of a glucose oxidase (GOD)-cortisol which was synthesized for molecular recognition of cortisol. The fabricated cortisol biosensor (Fig. 13) based on calorimetric protocol detects cortisol concentrations between 1 and 10 ng/mL within 25 min. Yamaguchi et al. (2013) have also reported a SAM based cortisol immunosensor integrated with a fluid control mechanism which has both a vertical flow and a lateral flow. A competitive reaction between the sample cortisol and a glucose oxidase (GOD)-labeled cortisol conjugate was found to be inversely related to the concentration of cortisol and can be detected electrochemically. This sensor exhibited a salivary cortisol ranged from 0.1 to 10 ng/mL with a regression coefficient of 0.98 and a coefficient variance of 14%. This immunosensor was able to detect cortisol within 35 min and could be reuse. The results correlated with ELISA and immunosensor have capability of on-site and easy-to-use biosensing of salivary cortisol. A fully automated low temperature co-fired ceramic (LTCC) based microfluidic system integrated with an electrochemical immunosensor has been developed by Vasudev et al. (2013). Authors designed and optimized 3D microfluidic architecture (150 mm width) and successfully integrated with SAM modified IDmEs based electrochemical immunosensor for the detection of cortisol (Fig. 15). The integrated sensor exhibited a linear range of 36 pg/mL–36 ng/mL (10 pM–100 nM) at a sensitivity of 0.207 mA/M in an automated and controlled microfluidic environment. This LTCC based electrochemical cortisol detection device is a step toward realizing the development

Fig. 15. (a and b) Characterization of the valving function in the fluidic valve; (c) picture of the fully integrated microfluidic system with fluid valve, microfluidic manifold and the biosensor chip; (d) calibration curve obtained from the electrochemical response studies of EA/Anti-C-ab/DTSP/Au-Mac immunoelectrode as a function of cortisol concentration (10 pM–100 nM). (Vasudev et al., 2013).

for non-invasive, point-of-care measurement of human cortisol in desired bio-fluids. The sensing parameters of biosensor for cortisol detection at POC are summarized in Table 1. The above-mentioned electrochemical immunosensor integrated with MEMS technology could be interfaced to a wireless health monitoring system that could transfer sensor data over

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Table 1 Sensing parameters of various cortisol sensors for POC application. Sensing platform

Sensing parameters

Remarks

References

IM ¼ Au nanowires DT ¼ Electrical IB ¼ anti-cortisol antibodies labeled with hydroxysteroid dehydrogenase TA ¼ cortisol

DR ¼3.7–12 mg/mL DL¼ 3.7 mg/mL

Obtained parameters do not lie in the physiological range

Kumar et al. (2007)

IM ¼ immune-chromatographic strip DT ¼ calorimetric chromatography IB ¼ glucose oxidase (GOD)-cortisol conjugated labeled sensor. TA ¼ glucose/cortisol

DR ¼1–10 ng/mL. DL¼ 1 ng/mL RT¼ 25 min

Portable, rapid, and hand held. Proposed method is an indirect detection of cortisol

Yamaguchi et al. (2009)

IM ¼ SAM DT ¼ electrochemically IB ¼ glucose oxydase (GOD) labeled cortisol conjugate sensors TA ¼ glucose/cortisol

DR ¼0.1–10 ng/mL DL¼ 0.1 ng/mL RT¼ 35 min

Obtained parameters are in physiological range. Yamaguchi et al. But it is a multicomponent system (2013)

IM ¼ SAM modified IDE DT ¼ electrochemically IB ¼ monoclonal anti-cortisol antibody TA ¼ cortisol

DR ¼0.036–36 ng/mL DL¼ 0.036 ng/mL RT¼ 30 min

Obtained sensing parameters are in physiological range Automated, label free and suitable for POC application

Vasudev et al. (2013)

IM, immobilizing matrix; DT, detection techniques; DR, detection range; DL, detection limit; RT, response time; IB, immobilizing biomolecule; TA, target analyte.

existing wide-area networks such as the Internet and a cellular phone network to enable real-time remote monitoring of subjects. Since cortisol secretion is dependent on environmental and behavioral triggers, measurement of cortisol at POC has become imperative to understand behavioral patterns. Furthermore, normal levels of cortisol secretion follow a circadian rhythm with cortisol levels highest during daybreak and progressively lower as the day progresses. The development of miniaturized, automated and wearable cortisol sensor has good commercialization prospect. These devices can be used nearer to the patient (wearable/cloth mountable) and for online/on- field cortisol detection. Typical usage includes sensors integrated on Astronaut suits to understand their day–night cycle, for farmers to understand the effects of pesticides and toxins on cortisol secretion, to look into posttraumatic stress disorder (PTSD) among soldiers who returned from wars, fire fighters to understand the effect of heat and pollutants on their bodies, and other applications including to understand the correlation of cortisol with other biologically important physiological variables. The area of miniaturized electronics integrated with electrochemical biosensors has great significance for on-site diagnostics. The junction of laboratory biosensing protocols and miniaturized electronics can be explored for mass production with great prospects of commercialization.

5. Conclusion Cortisol secretion levels have been correlated to psychological stress in patients suffering from stress disorders such as PTSD, Cushing’s syndrome, and insomnia. Electrochemical cortisol immunosensing platforms reported in this review have the potential to be integrated into a wearable system for in-filed and online continuous monitoring of cortisol as a function of one’s environment. These cortisol sensors, coupled with a continuous bio-fluid harvesting system, could allow a continuous readout of cortisol levels in the ambulatory setting, providing real-time information on cortisol secretion values when a patient is subjected to psychological stress as a resultant of triggers from the surroundings and situations. The information arising from the data could be used to understand behavioral patterns and also could be used to create personalized and targeted medications for stress related disorders. The continuous cortisol monitoring system may also

provide information on the 24-h diurnal cortisol at the night time minimum value and can identify the precise point in the sleep cycle at which cortisol begins its morning cycle. It could provide easy access to the post-awakening daily peak of cortisol production as well.

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