MEASURE: Multiplex Exhaled Breath Condensate - Scanning Using Rapid Electro-Analytics.

Exhaled breath condensate is an emerging source of inflammatory biomarkers suitable for the noninvasive detection of respiratory disorders. Current gold standard methods are highly invasive and pose challenges in sample collection during airway inflammation monitoring. Cytokine biomarkers are detectable in EBC at increased or decreased concentrations. IL-6, IL-1ß, IL-8, and hs-CRP are characteristic biomarkers identified in respiratory disorders. We have demonstrated the promising outcomes of a 16-plexed electrochemical platform - READ 2.0 for the multiplexed detection of characteristic biomarkers in EBC. The sensor demonstrates dynamic ranges of 1-243 pg/mL with a lower detection limit of 1 pg/mL for IL-6 and IL-1ß, while the detection range and limit of detection for IL-8 and hs-CRP is 1-150 pg/mL and 3 pg/mL, respectively. The detection accuracies for the biomarkers are in the range of ∼85 ± 15% to ∼100 ± 10%. The sensor shows a nonspecific response to similar cross-reacting biomarkers. Analytical validation of the sensor with ELISA as the standard reference generated a correlation of R2 > 0.96 and mean biases of 10.9, 3.5, 17.4, and 3.9 pg/mL between the two methods for IL-6, IL-1ß, IL-8, and hs-CRP, respectively. The precision of the sensor in detecting low biomarker concentrations yields a %CV of <7%. The variation in the sensor's response on repeat EBC sample measurements and within a 6 h duration is less than 10%. The READ 2.0 platform shows a promise that EBC-based biomarker detection can prove to be vital in predicting the severity and survival rates of respiratory disorders and serve as a reference point for monitoring EBC-based biomarkers.

Electrochemical Aptasensing for Lifestyle and Chronic Disease Management.

Over the past decade, researchers have investigated electrochemical sensing for the purpose of fabricating wearable point-of-use platforms. These wearable platforms have the ability to non-invasively track biomarkers that are clinically relevant and provide a comprehensive evaluation of the user's health. Due to many significant operational advantages, aptamer-based sensing is gaining traction.Aptamer-based sensors have properties like long-term stability, resistance to denaturation, and high sensitivity. Using electrochemical sensing with aptamer-based biorecognition is advantageous because it provides significant benefits like lower detection limits, a wider range of operations, and, most importantly, the ability to detect using a label-free approach. This paper provides an outlook into the current state of electrochemical aptasensing. This review looks into the significance of the detection of biomarkers like glucose, cortisol etc., for the purpose of lifestyle and chronic disease monitoring. Moreover, this review will also provide a comprehensive evaluation of the current challenges and prospects in this field.

EBC-SURE (exhaled breath condensate- scanning using rapid electro analytics): A non-faradaic and non-invasive electrochemical assay to screen for pro-inflammatory biomarkers in human breath condensate.

The innovation of this work lies in the trace detection of inflammatory biomarkers (IL-6, hs-CRP) in human exhaled breath condensate on the developed EBC-SURE platform as a point-of-care aid for respiratory disorder diagnosis. The unique design of the EBC-SURE leverages non-faradaic electrochemical impedance spectroscopy to capture target-specific biomolecular interactions for highly sensitive biomarker detection. For sensor calibration, EBC-SURE's performance is assessed to measure the response of the sensor to a known concentration by spike and recovery analysis with a recovery error of <20% and an extended dynamic range over 3-log orders. The lowest detection limits for IL-6 and hs-CRP detection in EBC were found to be 3.2 pg/mL and 4 pg/mL respectively. The intra-assay and inter-assay efficacy of EBC-SURE for its usage as a diagnostic device was established through repeatability and reproducibility (over 48 h s) performance testing. The percentage variations (<20%) met the Clinical and Laboratory Standards Institute standards (CLSI) indicating a highly stable performance for robust biomarker detection. EBC-SURE generated highly selective IL-6 and hs-CRP responses in the presence of other non-specific cytokines. Statistical validation methods- Correlation and Bland Altman analysis established the one-to-one agreement between EBC-SURE and the reference method. Correlation analysis generated a Pearson's R value of 0.99 for IL-6 and hs-CRP. Bland-Altman analysis indicated a good agreement between both the methods with all data points confined within the ±2SD limits. We have demonstrated EBC-SURE's ability in detecting inflammatory biomarkers in human breath condensate towards developing a non-invasive technology that can quantify biomarker levels associated with healthy and acute inflammatory conditions.

A machine learning-based on-demand sweat glucose reporting platform.

Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause of morbidity, resulting in a reduced quality of life even in developed societies, primarily affected by a sedentary lifestyle and often leading to mortality. Keeping track of blood glucose levels noninvasively has been made possible due to diverse breakthroughs in wearable sensor technology coupled with holistic digital healthcare. Efficient glucose management has been revolutionized by the development of continuous glucose monitoring sensors and wearable, non/minimally invasive devices that measure glucose concentration by exploiting different physical principles, e.g., glucose oxidase, fluorescence, or skin dielectric properties, and provide real-time measurements every 1-5 min. This paper presents a highly novel and completely non-invasive sweat sensor platform technology that can measure and report glucose concentrations from passively expressed human eccrine sweat using electrochemical impedance spectroscopy and affinity capture probe functionalized sensor surfaces. The sensor samples 1-5 µL of sweat from the wearer every 1-5 min and reports sweat glucose from a machine learning algorithm that samples the analytical reference values from the electrochemical sweat sensor. These values are then converted to continuous time-varying signals using the interpolation methodology. Supervised machine learning, the decision tree regression algorithm, shows the goodness of fit R2 of 0.94 was achieved with an RMSE value of 0.1 mg/dL. The output of the model was tested on three human subject datasets. The results were able to capture the glucose progression trend correctly. Sweet sensor platform technology demonstrates a dynamic response over the physiological sweat glucose range of 1-4 mg/dL measured from 3 human subjects. The technology described in the manuscript shows promise for real-time biomarkers such as glucose reporting from passively expressed human eccrine sweat.

Temporal profiling of cytokines in passively expressed sweat for detection of infection using wearable device.

This work presents the viability of passive eccrine sweat as a functional biofluid toward tracking the human body's inflammatory response. Cytokines are biomarkers that orchestrate the manifestation and progression of an infection/inflammatory event. Hence, noninvasive, real-time monitoring of cytokines can be pivotal in assessing the progression of infection/inflammatory event, which may be feasible through monitoring of host immune markers in eccrine sweat. This work is the first experimental proof demonstrating the ability to detect inflammation/infection such as fever, FLU directly from passively expressed sweat in human subjects using a wearable "SWEATSENSER" device. The developed SWEATSENSER device demonstrates stable, real-time monitoring of inflammatory cytokines in passive sweat. An accuracy of >90% and specificity >95% was achieved using SWEATSENSER for a panel of cytokines (interleukin-6, interleukin-8, interleukin-10, and tumor necrosis factor-α) over an analytical range of 0.2-200 pg mL-1. The SWEATSENSER demonstrated a correlation of Pearson's r > 0.98 for the study biomarkers in a cohort of 26 subjects when correlated with standard reference method. Comparable IL-8 levels (2-15 pg mL-1) between systemic circulation (serum) and eccrine sweat through clinical studies in a cohort of 15 subjects, and the ability to distinguish healthy and sick (infection) cohort using inflammatory cytokines in sweat provides pioneering evidence of the SWEATSENSER technology for noninvasive tracking of host immune response biomarkers. Such a wearable device can offer significant strides in improving prognosis and provide personalized therapeutic treatment for several inflammatory/infectious diseases.

Tracking metabolic responses based on macronutrient consumption: A comprehensive study to continuously monitor and quantify dual markers (cortisol and glucose) in human sweat using WATCH sensor.

Wearable Awareness Through Continuous Hidrosis (WATCH) sensor is a sweat based monitoring platform that tracks cortisol and glucose for the purpose of understanding metabolic responses related to macronutrient consumption. In this research article, we have demonstrated the ability of tracking these two biomarkers in passive human sweat over a workday period (8 h) for 10 human subjects in conjunction with their macronutrient consumption. The validation of the WATCH sensor performance was carried out via standard reference methods such as Luminex and ELISA This is a first demonstration of a passive sweat sensing technology that can detect interrelated dual metabolites, cortisol, and glucose, on a single sensing platform. The significance of detecting the two biomarkers simultaneously is that capturing the body's metabolic and endocrinal responses to dietary triggers can lead to improved lifestyle management. For sweat cortisol, we achieved a detection limit of 1 ng/ml (range ∼1-12.5 ng/ml) with Pearson's "r" of 0.897 in reference studies and 0.868 in WATCH studies. Similarly, for sweat glucose, we achieved a detection limit of 1 mg/dl (range ∼ 1-11 mg/dl) with Pearson's "r" of 0.968 in reference studies and 0.947 in WATCH studies, respectively. The statistical robustness of the WATCH sensor was established through the Bland-Altman analysis, whereby the sweat cortisol and sweat glucose levels are comparable to the standard reference method. The probability distribution (t-test), power analysis (power 0.82-0.87), α = 0.05. Mean absolute relative difference (MARD) outcome of Ë·5.10-5.15% further confirmed the statistical robustness of the sweat sensing WATCH device output.

A Sweat-based Wearable Enabling Technology for Real-time Monitoring of IL-1ß and CRP as Potential Markers for Inflammatory Bowel Disease.

BACKGROUND: More than 1.2 million people in the United States are affected by inflammatory bowel disease (IBD). Inflammatory bowel disease has a natural course characterized by alternating periods of remission and relapse. Currently, disease flares are unpredictable as they occur in a random way. Further, current testing methods and practices lack the ability for real-time tracking of flares. There exists no technology that can be utilized for continuous monitoring of biomarkers, as most of these rely on samples such as blood, feces, and testing methods by which continuous monitoring is not feasible. Cytokines play a key role in IBD; the development, recurrence, and exacerbation of the inflammatory process are orchestrated by their levels in time and space. Cytokines are also present in sweat. We hypothesize that demonstrating real-time continuous monitoring of interleukin-1ß (IL-1ß) and C-reactive protein (CRP) may help create an enabling technology to track inflammation in IBD patients and identify flare-ups and assess efficacy of therapy. METHODS: A multiplexed SWEATSENSER was used for noninvasive continuous monitoring of interleukin-1ß and C-reactive protein in human eccrine sweat. Impedance spectroscopy was used to measure the sensor response. Sweat was collected using an FDA-approved PharmChek patch from 26 healthy human subjects to determine the levels of the 2 study inflammatory markers. Correlation analysis was performed for preclinical validation of the SWEATSENSER with ELISA as the reference method. On-body continuous monitoring measurements were performed on 20 human subjects using EnLiSense's SWEATSENSER wearable device for real-time monitoring studies. RESULTS: The sensor device can detect interleukin-1ß and C-reactive protein in sweat over a dynamic range of 3 log orders. Pearson correlation of r = 0.99 and r = 0.95 was achieved for IL-1ß and CRP, respectively, for the SWEATSENSER with ELISA. Bland-Altman results further confirmed a good agreement (mean bias of -0.25 and -3.9 pg/mL for IL-1ß and CRP, respectively) of the device with the reference method, demonstrating applicability of the device for real-time monitoring. Continuous on-body measurements were performed in 20 healthy human subjects for the detection of IL-1ß to establish the preclinical utility of the sensor device. The continuous on-body measurements in healthy cohort reported a mean IL-1ß concentration of ~28 pg/mL. Stable measurements for over continuous 30 hours was reported by the device. CONCLUSION: This work demonstrates the first proof-of-feasibility of multiplexed cytokine and inflammatory marker detection in passively expressed eccrine sweat in a wearable form-factor that can be utilized toward better management of inflammatory bowel disease. This is a first step toward demonstrating a noninvasive enabling technology that can enable baseline tracking of an inflammatory response. Furthermore, this is the first study to report and quantify the presence of CRP in human eccrine sweat.

CortiWatch: watch-based cortisol tracker.

Sweat-based analytics have recently caught the attention of researchers and medical professionals alike because they do not require professionally trained personnel or invasive collection techniques to obtain a sample. The following presents a small form-factor biosensor for reporting physiological ranges of cortisol present in ambient sweat (8-151 ng/ml). This device obtains cortisol measurements through low volumes of unstimulated sweat from the user's wrist. We designed a potentiostatic circuit on a printed circuit board to perform electrochemical testing techniques. The detection modality developed for quantifying sensor response to varying cortisol concentrations is a current based electrochemical technique, chronoamperometry (CA). From the results, the sensor can detect cortisol in the physiologically relevant ranges of cortisol; thus, the sensor is a noninvasive, label free, cost-effective solution for tracking cortisol levels for circadian diagnostics.