Browsing by Author "Bhide, Ashlesha"
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Item CLASP (Continuous Lifestyle Awareness Through Sweat Platform): A Novel Sensor for Simultaneous Detection of Alcohol and Glucose from Passive Perspired Sweat(Elsevier Ltd) Bhide, Ashlesha; Muthukumar, S.; Prasad, Shalini; Bhide, Ashlesha; Prasad, ShaliniWearable- IOT based low- cost platforms can enable dynamic lifestyle monitoring through enabling promising and exciting opportunities for wellness and chronic- disease management in personalized environments. Diabetic and pre- diabetic populations can modulate their alcohol intake by tracking their glycemic content continuously to prevent health risks through these platforms. We demonstrate the first technological proof of a combinatorial biosensor for continuous, dynamic monitoring of alcohol and glucose in ultra- low volumes (1–5 µL) of passive perspired sweat towards developing a wearable- IOT based platform. Non-invasive biosensing in sweat is achieved by a unique gold- zinc oxide (ZnO) thin film electrode stack fabricated on a flexible substrate suitable for wearable applications. The active ZnO sensing region is immobilized with enzyme complexes specific for the detection of alcohol and glucose through non- faradaic electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA). Biomolecular interactions occurring at the electrode- sweat interface are represented by the impedance and capacitive current changes in response to charge modulations arising in the double layer. We also report the detection of alcohol concentrations of 0.01–100 mg/dl and glucose concentrations of 0.01–50 mg/dl present in synthetic sweat and perspired human sweat. The limit of detection obtained for alcohol and glucose was found to be 0.1 mg/dl in perspired human sweat. Cross- reactivity studies revealed that glucose and alcohol did not show any signal response to cross- reactive molecules. Furthermore, the stable temporal response of the combinatorial biosensor on continuous exposure to passive perspired human sweat spiked with alcohol and glucose over a 120-min duration was demonstrated. © 2018 Elsevier B.V.Item Enzymatic Low Volume Passive Sweat Based Assays for Multi-Biomarker Detection(MDPI, 2019-01-16) Bhide, Ashlesha; Cheeran, Sarah; Muthukumar, Sriram; Prasad, Shalini; Bhide, Ashlesha; Cheeran, Sarah; Prasad, ShaliniSimultaneous detection of correlated multi-biomarkers on a single low-cost platform in ultra-low fluid volumes with robustness is in growing demand for the development of wearable diagnostics. A non-faradaic biosensor for the simultaneous detection of alcohol, glucose, and lactate utilizing low volumes (1-5 μL) of sweat is demonstrated. Biosensing is implemented using nanotextured ZnO films integrated on a flexible porous membrane to achieve enhanced sensor performance. The ZnO sensing region is functionalized with enzymes specific for the detection of alcohol, glucose, and lactate in the ranges encompassing their physiologically relevant levels. A non-faradaic chronoamperometry technique is used to measure the current changes associated with interactions of the target biomarkers with their specific enzyme. The specificity performance of the biosensing platform was established in the presence of cortisol as the non-specific molecule. Biosensing performance of the platform in a continuous mode performed over a 1.5-h duration showed a stable current response to cumulative lifestyle biomarker concentrations with capability to distinguish reliably between low, mid, and high concentration ranges of alcohol (0.1, 25, 100 mg/dL), glucose (0.1, 10, 50 mg/dL), and lactate (1, 50, 100 mM). The low detection limits and a broader dynamic range for the lifestyle biomarker detection are quantified in this research demonstrating its suitability for translation into a wearable device.Item Multiplexed Comprehensive Design and Characterization of an Electrochemical Interface Accessing Non-invasive Bodily Fluids Towards Quality-of-life Monitoring(December 2021) Bhide, Ashlesha; Prasad, Shalini; Balsara, Poras; Muthukumar, Sriram; Cogan, Stuart; Ardestani Khoubrouy, SoudehThe research presented in this thesis outlines the design and development of novel biosensing platforms for monitoring biomarkers by the non-invasive sampling of body fluids with emphasis on self-health and disease management. The purpose of this work is to demonstrate the efficacy of two combinatorial biosensors – Continuous awareness through sweat platform (CLASP) and Exhaled breath condensate scanning using rapid electro analytics (EBC-SURE) for the detection of metabolic and inflammatory biomarkers towards integration onto low-power internet of things (IoT) platforms for wearable and point-of-care diagnostic applications. First, this work demonstrated the technical utility of a lancet-free, label-free platform for the combinatorial, and continuous monitoring of alcohol and glucose in perspired human sweat produced without external sweat induction strategies. The motivation of this study was to develop a sweat-based wearable platform for alcohol and glucose management to monitor glucose levels on moderate consumption of alcohol of diabetic social drinkers. A nanotextured sensor stack was embedded into a flexible nanoporous substrate to achieve sensitive and specific affinity-based biomarker detection within physiologically relevant ranges in ultralow volumes of sweat. Non-faradaic EIS is employed as the signal transduction mechanism for biomarker detection to give an insight into the binding events occurring at the sensor interface. Additionally, the CLASP platform was benchmarked against commercially available hand-held devices to establish a one-to-one performance correlation. Furthermore, this platform was employed to demonstrate the epidermal functionality and sensor performance of CLASP for the on-body detection of sweat lactate to monitor restricted oxygen supply in sedentary populations. The successful implementation of CLASP in detecting metabolic biomarkers for health monitoring led to the transition of assessing the performance metrics of this platform for the detection of inflammatory biomarkers such as cortisol and TNF-α for chronic disease monitoring. The important highlight of this work was to establish the longterm temporal stability of the CLASP in detecting a simulated rise and fall in cortisol levels over a 6-hour sleep cycle. The last effort was focused on developing a point-of-care aid platform- EBCSURE for the trace detection of inflammatory biomarkers in exhaled breath condensate for monitoring respiratory disorders. Exhaled breath condensate is considered a promising source of inflammatory biomarkers that can determine the pathophysiological processes underlying lung inflammation in a simple and non-invasive manner. EBC-SURE displayed a stable performance after rigorous testing enabling its integration onto diagnostic platforms for rapid quantification of biomarkers related to a healthy and acute inflammatory disease condition.Item Simultaneous Lancet-Free Monitoring of Alcohol and Glucose from Low-Volumes of Perspired Human SweatBhide, Ashlesha; Muthukumar, Sriram; Saini, Amreek; Prasad, Shalini; 0000 0001 2765 4678 (Prasad, S); 0000-0002-2404-3801 (Prasad, S); Bhide, Ashlesha; Saini, Amreek; Prasad, ShaliniA lancet-free, label-free biosensor for simultaneous detection of sweat glucose and alcohol was demonstrated using zinc oxide thin films integrated into a nanoporous flexible electrode system. Sensing was achieved from perspired human sweat at low volumes (1-3μL), comparable to ambient conditions without external stimulation. Zinc oxide thin film electrodes were surface functionalized with alcohol oxidase enzyme and with glucose oxidase enzyme towards developing an affinity biosensor specific to the physiological relevant range of alcohol comprising of 0-2 drinks (0-50mg/dl) and physiologically relevant range of glucose ranging from hypo- to hyper-glycaemia (50- 130mg/dl) in perspired human sweat. Sensing was achieved by measuring impedance changes associated with alcohol and glucose binding onto the sensor interface using electrochemical impedance spectroscopy with a dynamic range from 0.01-200mg/dl and a limit of detection of 0.01mg/dl for alcohol in human sweat. Sensor calibration in synthetic sweat containing interferents (25-200mg/dl) and comparison using regression and Bland-Altman analysis of sweat sensor performance was done with BACtrack. Combinatorial detection of glucose and ethanol in perspired human sweat and comparison of sweat sensor performance with Accu-Chek blood glucose monitoring system that we expect would be relevant for pre-diabetics and diabetics for monitoring their glucose levels and alcohol consumption.Item Ultrasensitive and Rapid-Response Sensor for the Electrochemical Detection of Antibiotic Residues within Meat Samples(American Chemical Society) Stevenson, Hunter S.; Shetty, Shubrath S.; Thomas, Noel J.; Dhamu, Vidram N.; Bhide, Ashlesha; Prasad, Shalini; 0000-0002-2404-3801 (Prasad, S); Stevenson, Hunter S.; Shetty, Shubrath S.; Thomas, Noel J.; Dhamu, Vidram N.; Bhide, Ashlesha; Prasad, ShaliniAntimicrobial use in livestock has emerged as a pressing global issue because of the rise of antimicrobial-resistant bacteria. Regulatory authorities across the globe have taken steps to discourage the misuse of these antibiotics by banning or limiting the use of medically important antibiotics in food animals. However, to ensure that food animals are not being administered antibiotics inappropriately, there is a need for a reliable, raid-response biosensor that can detect the presence of these antibiotic residuals in meat products. We have developed an affinity-based electrochemical biosensor for the label-free detection of ceftiofur residues in meat samples. The sensor uses a self-assembled immunoassay to target the ceftiofur biomarker by employing electrochemical impedance spectroscopy to probe the interfacial capacitive changes as ceftiofur binds to the sensor surface. We have demonstrated a platform that can detect ceftiofur within 15 min of introducing the sample at concentrations down to 0.01 ng/mL in 1× phosphate-buffered saline and 10 ng/mL in 220 mg ground turkey meat samples. © 2019 American Chemical Society.