Passive sweat wearable: A new paradigm in the wearable landscape toward enabling "detect to treat" opportunities.

Growing interest over recent years in personalized health monitoring coupled with the skyrocketing popularity of wearable smart devices has led to the increased relevance of wearable sweat-based sensors for biomarker detection. From optimizing workouts to risk management of cardiovascular diseases and monitoring prediabetes, the ability of sweat sensors to continuously and noninvasively measure biomarkers in real-time has a wide range of applications. Conventional sweat sensors utilize external stimulation of sweat glands to obtain samples, however; this stimulation influences the expression profile of the biomarkers and reduces the accuracy of the detection method. To address this limitation, our laboratory pioneered the development of the passive sweat sensor subfield, which allowed for our progress in developing a sweat chemistry panel. Passive sweat sensors utilize nanoporous structures to confine and detect biomarkers in ultra-low sweat volumes. The ability of passive sweat sensors to use smaller samples than conventional sensors enable users with sedentary lifestyles who perspire less to benefit from sweat sensor technology not previously afforded to them. Herein, the mechanisms and strategies of current sweat sensors are summarized with an emphasis on the emerging subfield of passive sweat-based diagnostics. Prospects for this technology include discovering new biomarkers expressed in sweat and expanding the list of relevant detectable biomarkers. Moreover, the accuracy of biomarker detection can be enhanced with machine learning using prediction algorithms trained on clinical data. Applying this machine learning in conjunction with multiplex biomarker detection will allow for a more holistic approach to trend predictions. This article is categorized under: Diagnostic Tools > Diagnostic Nanodevices Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Diagnostic Tools > Biosensing.

H.O.S.T.: Hemoglobin microbubble-based Oxidative stress Sensing Technology.

In this work, we discuss the development of H.O.S.T., a novel hemoglobin microbubble-based electrochemical biosensor for label-free detection of Hydrogen peroxide (H2O2) towards oxidative stress and cancer diagnostic applications. The novelty of the constructed sensor lies in the use of a sonochemically prepared hemoglobin microbubble capture probe, which allowed for an extended dynamic range, lower detection limit, and enhanced resolution compared to the native hemoglobin based H2O2 biosensors. The size of the prepared particles Hemoglobin microbubbles was characterized using Coulter Counter analysis and was found to be 4.4 microns, and the morphology of these spherical microbubbles was shown using Brightfield microscopy. The binding chemistry of the sensor stack elements of HbMbs' and P.A.N.H.S. crosslinker was characterized using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy and UV-Vis Spectroscopy. The electrochemical biosensor calibration (R2 > 0.95) was done using Electrochemical Impedance Spectroscopy, Cyclic Voltammetry, and Square Wave Voltammetry. The electrochemical biosensor calibration (R2 > 0.95) was done using Electrochemical Impedance Spectroscopy, Cyclic Voltammetry, and Square Wave Voltammetry. The specificity of the sensor for H2O2 was analyzed using cross-reactivity studies using ascorbic acid and glucose as interferents (p < 0.0001 for the highest non-specific dose versus the lowest specific dose). The developed sensor showed good agreement in performance with a commercially available kit for H2O2 detection using Bland Altman Analysis (mean bias = 0.37 for E.I.S. and - 24.26 for CV). The diagnostic potential of the biosensor was further tested in cancerous (N.G.P.) and non-cancerous (H.E.K.) cell lysate for H2O2 detection (p = 0.0064 for E.I.S. and p = 0.0062 for CV). The Michaelis Menten constant calculated from the linear portion of the sensor was found to be [Formula: see text] of 19.44 µM indicating that our biosensor has a higher affinity to Hydrogen peroxide than other available enzymatic sensors, it is attributed to the unique design of the hemoglobin polymers in microbubble.

Inflammatory Stimuli Responsive Non-Faradaic, Ultrasensitive Combinatorial Electrochemical Urine Biosensor.

In this work, we propose a novel diagnostic biosensor that can enable stratification of disease states based on severity and hence allow for clear and actionable diagnoses. The scheme can potentially boost current Point-Of-Care (POC) biosensors for diseases that require time-critical stratification. Here, two key inflammatory biomarkers­Interleukin-8 and Interleukin-6­have been explored as proof of concept, and a four-class stratification of inflammatory disease severity is discussed. Our method is superior to traditional lab techniques as it is faster (<4 minutes turn-around time) and can work with any combination of disease biomarkers to categorize diseases by subtypes and severity. At its core, the biosensor relies on electrochemical impedance spectroscopy to transduce subtle inflammatory stimuli at the input for IL-8 and IL-6 for a limit of detection (LOD) of 1 pg/mL each. The biosensing scheme utilizes a two-stage random forest machine learning model for 4-state output disease classification with a 98.437% accuracy. This scheme can potentially boost the diagnostic power of current electrochemical biosensors for better precision therapy and improved patient outcomes.

Label-Free, Novel Electrofluidic Capacitor Biosensor for Prostaglandin E2 Detection toward Early and Rapid Urinary Tract Infection Diagnosis.

Urine Prostaglandin E2 (PGE2) has been identified as an attractive diagnostic and prognostic biomarker for urinary tract infection (UTI). This work demonstrates the use of PGE2 as a biomarker for rapid and label-free testing for UTI. In this work, we have developed a novel electrofluidic capacitor-based biosensor that can used for home-based UTI management with high accuracy in less than 5 min for small volume urine samples (<60 µL). The PGE2 biosensor works on the principle of affinity capture using highly specific monoclonal PGE2 antibody and relies on non-faradaic electrical impedance spectroscopy (EIS) and Mott-Schottky (MS) for quantifying subtle variations in PGE2 levels expressed in human urine (pH 5-8). Dynamic light scattering experiments were performed to characterize surface charge properties and the impact of bulk interferents on the interfacial modulation of electrical properties due to binding and urine pH variations. Binding chemistry between the key elements of the immunosensor stack was validated using attenuated total reflectance-Fourier transform infrared spectroscopy and surface plasmon resonance studies. Linear calibration dose responses were obtained for PGE2 for both EIS and MS. The sensor reliably distinguished between UTI negative and UTI positive cases for both artificial (pH 5-8) and pooled human urine samples. The sensor was not found to cross-react with Prostaglandin D2, a structurally similar interferent, and other abundant urine interferents (urea and creatinine). Human subject studies confirmed the validity of the sensor for robust and accurate UTI diagnosis. This work can be extended to achieve easy, reliable, and rapid home-based UTI management, which can consequently help physicians with timely and appropriate administration of therapy to improve patient outcomes and treatment success.

Label-Free Protein Glycosylation Analysis Using NanoMonitor-An Ultrasensitive Electrochemical Biosensor.

Glycans (oligosaccharide chains attached to glycoproteins) are a promising class of biomarkers, found in body fluids such as serum, saliva, urine, etc., that can be used for the diagnosis of disease conditions. Subtle changes in glycans resulting from altered glycosylation machinery have been reported during various diseases, including carcinogenesis. In this article, we detail protocols for the rapid, label-free analysis of glycans using a previously developed highly sensitive and selective electrochemical impedance spectroscopy-based biosensing diagnostic platform called "NanoMonitor." The glycosensor operation is based on the specific affinity capture of the target glycans on the sensor surface by glycan-binding proteins known as lectins. This glycan-lectin binding activity modulates the impedance of the electrical double layer at the buffer-electrode interface. Protocols for the preparation of glycoprotein samples and glycosylation analysis using NanoMonitor and lectin-based ELISA are described here. The data obtained using these protocols show that NanoMonitor is capable of distinguishing between glycoform variants of the glycoprotein fetuin and glycoproteins derived from cultured human pancreatic cancer cells with high sensitivity (orders of magnitude higher than lectin-based ELISA) and selectivity. The results obtained indicate that NanoMonitor protocols can be further developed to enable use of NanoMonitor as a handheld electronic biosensor device for routine multiplexed detection of glycan biomarkers from clinical samples. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Preparing the NanoMonitor surface for glycan biosensing Support Protocol: Synthesis of glycoform variants of fetuin Basic Protocol 2: Performing Electrochemical Impedance Spectroscopy (EIS) for analyzing glycoprotein structures.

Next-Generation Continuous Metabolite Sensing toward Emerging Sensor Needs.

This article discusses the emergent biosensor technology focused on continuous biosensing of metabolites by non-invasive sampling of body fluids emphasized on physiological monitoring in mobility-constrained populations, resource-challenged settings, and harsh environments. The boom of innovative ideas and endless opportunities in healthcare technologies has transformed traditional medicine into a sustainable link between medical practitioners and patients to provide solutions for faster disease diagnosis. The future of healthcare is focused on empowering users to manage their own health. The confluence of big data and predictive analysis and the internet of things (IoT) technology have shown the potential of converting the abundant health profile data amassed from medical diagnosis of patients into useable information, whilst allowing caregivers to provide suitable treatment plans. The implementation of the IoT technology has opened up advanced approaches in real-time, continuous, remote monitoring of patients. Wearable, point-of-care biosensors are the future roadmap to providing direct, real-time information of health status to the user and medical professionals in this digitized era.

Autonomous, Real-Time Monitoring Electrochemical Aptasensor for Circadian Tracking of Cortisol Hormone in Sub-microliter Volumes of Passively Eluted Human Sweat.

The proposed work involves the development of an autonomous, label-free electrochemical sensor for real-time monitoring of cortisol levels expressed naturally in sub-microliter sweat volumes, for prolonged sensing periods of ∼8 h. Highly specific single-stranded DNA (ssDNA) aptamer is used for affinity capture of cortisol hormone eluted in sweat dynamically. The cortisol present in sweat binds to the aptamer capture probe that changes conformation and modulates electrochemical properties at the electrode-buffer interface, which was studied using dynamic light scattering studies for the entire physiological sweat pH. Attenuated total reflectance-Fourier transform infrared spectroscopy and UV-vis spectroscopy were used to optimize the binding chemistry of the elements of the sensor stack. Nonfaradaic electrochemical impedance spectroscopy was used to calibrate the sensor for a dynamic range of 1-256 ng/mL. An R2 of 0.97 with an output signal range of 20-50% was obtained. Dynamic cortisol level variation tracking was studied using continuous dosing experiments to calibrate the sensor for temporal variation. The sensor did not show significant susceptibility to noise due to cross-reactive interferents and nonspecific buffer constituents. The performance of the developed aptasensor was compared with the previously established cortisol immunosensor in terms of surface charge behavior and nonfaradaic biosensing. The aptamer sensor shows a higher signal-to-noise ratio, better resolution, and has a larger output range for the same input range as the cortisol immunosensor. The feasibility of deploying the developed aptasensing scheme as continuous lifestyle and performance monitors was validated through human subject studies.

A Combinatorial Electrochemical Biosensor for Sweat Biomarker Benchmarking.

Misclassification of an acute disease condition as chronic and vice versa by electrochemical sweat biomarker sensors can cause significant psychological, emotional, and financial stress among patients. To achieve higher accuracy in distinguishing between a chronic condition and an acute condition, there is a need to establish a reference biomarker to index the actual chronic disease biomarker of interest by combinatorial sensing. This work provides the first technological proof of leveraging the chloride ion content in sweat for a combinatorial sweat biomarker benchmarking scheme. In this scheme, the sweat chloride ion has been demonstrated as the reference/indexing biomarker, while sweat cortisol has been studied as the disease biomarker of interest. Label-free affinity biosensing is achieved by using a two-electrode electrochemical system on a flexible substrate suitable for wearable applications. The electrochemical stability of the fabricated electrodes for biosensing applications was studied by open-circuit potential measurements. Attenuated total reflectance-Fourier transform infrared spectroscopy spectra validate the crosslinker-antibody binding chemistry. Concentration-dependent analyte-capture probe binding induces a modulation in the electrical properties (charge transfer resistance and double-layer capacitance) at the electrode-sweat buffer interface, which are transduced by nonfaradaic electrochemical impedance spectroscopy (EIS). Calibration dose responses for the sensor for cortisol (5-200 ng/mL) and chloride (10-100 mM) detection were evaluated in synthetic (pH 6) and pooled human sweat (R2 > 0.95). The variation in the cortisol sensor response due to fluctuations in sweat chloride levels and the significance of reporting normalized biomarker levels were demonstrated to further emphasize the need for biomarker benchmarking in electrochemical sensors.

Passively Addressable Ultra-Low Volume Sweat Chloride Sensor.

This work demonstrates a novel electrochemical biosensor for the detection of chloride ion levels in ultra-low volumes (1-3 microliters) of passively expressed human sweat. We present here a hydration monitor that the pediatric, geriatric, and other immune-compromised or physically inactive/sedentary population cohort can utilize, for whom the current methods of chloride quantification of active stimulation of sweat glands through iontophoresis or treadmill runs are unsuitable. In this work, non-faradaic electroanalysis using gold microelectrodes deposited on a flexible nanoporous substrate, for high nanoscale surface area to volume enhancement, was leveraged to operate in ultra-low sweat volumes of <3 µL eluted at natural rates. The specific chloride ionophore-based affinity of chloride ions resulted in the modulation of charge transfer within the electrical double layer at the electrode-sweat buffer interface, which was transduced using electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA). Linear calibration dose responses with R-squared values of 0.9746 and 0.9403 for EIS and CA respectively were obtained for a dynamic range of 10-100 mM. The surface charge and the binding chemistry of the capture probe were studied using zeta potential studies and UV-Vis. The dynamic sweat chloride-tracking capability of the sensor was evaluated for a duration of 180 min. Studies were conducted to probe the efficacy of the developed sensor for passive ultra-low sweat chloride assessment on human subjects (n = 3).