Simultaneous detection of sepsis host response biomarkers in whole blood using electrochemical biosensor.

Sepsis is a silent killer, caused by a syndromic reaction of the body's immune system to an infection that is typically the ultimate pathway to mortality due to numerous infectious diseases, including COVID-19 across the world. In the United States alone, sepsis claims 220,000 lives, with a dangerously high fatality rate between 25% and 50%. Early detection and treatment can avert 80% of sepsis mortality which is currently unavailable in most healthcare institutions. The novelty in this work is the ability to simultaneously detect eight (IL-6, IL-8, IL-10, IP-10, TRAIL, d-dimer, CRP, and G-CSF) heterogeneous immune response biomarkers directly in whole blood without the need for dilution or sample processing. The DETecT sepsis (Direct Electrochemical Technique Targeting Sepsis) 2.0 sensor device leverages electrochemical impedance spectroscopy as a technique to detect subtle binding interactions at the metal/semi-conductor sensor interface and reports results within 5 min using only two drops (~100 µl) of blood. The device positively (r >0.87) correlated with lab reference standard LUMINEX for clinical translation using 40 patient samples. The developed device showed diagnostic accuracy greater than 80% (AUC >0.8) establishing excellent specific and sensitive response. Portable handheld user-friendly feature coupled with precise quantification of immune biomarkers makes the device amenable in a versatile setting providing insights on patient's immune response. This work highlights an innovative solution of enhancing sepsis care and management in the absence of a decision support device in the continuum of sepsis care.

Multiplexed cytokine detection using electrochemical point-of-care sensing device towards rapid sepsis endotyping.

The implementation of endotype-driven effective intervention strategies is now considered as an essential component for sepsis management. Rapid screening and frequent monitoring of immune responses are critical for evidence-based informed decisions in the early hours of patient arrival. Current technologies focus on pathogen identification that lack rapid testing of the patient immune response, impeding clinicians from providing appropriate sepsis treatment. Herein, we demonstrate a first-of-its-kind novel point-of-care device that uses a unique approach by directly monitoring a panel of five cytokine biomarkers (IL-6, IL-8, IL-10, TRAIL & IP-10), that is attributed as a sign of the body's host immune response to sepsis. The developed point-of-care device encompasses a disposable sensor cartridge attached to an electrochemical reader. High sensitivity is achieved owing to the unique sensor design with an array of nanofilm semiconducting/metal electrode interface, functionalized with specific capture probes to measure target biomarkers simultaneously using non-faradaic electrochemical impedance spectroscopy. The sensor has a detection limit of ~1 pg/mL and provides results in less than five minutes from a single drop of undiluted plasma sample. Furthermore, the sensor demonstrates an excellent correlation (Pearson's r > 0.90) with the reference method for a total n = 40 clinical samples, and the sensor's performance is ~30 times faster compared to the standard reference technique. We have demonstrated the sensor's effectiveness to enhance diagnosis with a mechanistic biomarker-guided approach that can help disease endotypying for effective clinical management of sepsis at the patient bedside.

An approach to rapidly assess sepsis through multi-biomarker host response using machine learning algorithm.

Sepsis is a life-threatening condition and understanding the disease pathophysiology through the use of host immune response biomarkers is critical for patient stratification. Lack of accurate sepsis endotyping impedes clinicians from making timely decisions alongside insufficiencies in appropriate sepsis management. This work aims to demonstrate the potential feasibility of a data-driven validation model for supporting clinical decisions to predict sepsis host-immune response. Herein, we used a machine learning approach to determine the predictive potential of identifying sepsis host immune response for patient stratification by combining multiple biomarker measurements from a single plasma sample. Results were obtained using the following cytokines and chemokines IL-6, IL-8, IL-10, IP-10 and TRAIL where the test dataset was 70%. Supervised machine learning algorithm naïve Bayes and decision tree algorithm showed good accuracy of 96.64% and 94.64%. These promising findings indicate the proposed AI approach could be a valuable testing resource for promoting clinical decision making.

Establish pre-clinical diagnostic efficacy for parathyroid hormone as a point-of-surgery-testing-device (POST).

Measuring the Parathyroid hormone (PTH) levels assists in the investigation and management of patients with parathyroid disorders. Rapid PTH monitoring is a valid tool for accurate assessment intraoperatively. Rapid Electro-Analytical Device (READ) is a point-of-care device that uses impedance change between target and capture probe to assess the PTH concentration in undiluted patient plasma samples. The aim of this work focuses on evaluating the analytical performance of READ platform to Roche analyzer as a prospective clinical validation method. The coefficient of variation (CV) for intra-assay imprecision was < 5% and inter-assay imprecision CV was < 10% for high (942 pg/mL) and low (38.2 pg/mL) PTH concentration. Functional sensitivity defined at 15% CV was 1.9 pg/mL. Results obtained from READ platform correlated well (r = 0.99) with commercially available clinical laboratory method (Roche Diagnostics) to measure PTH concentrations with a turn-around time of less than 15 min. Furthermore, the mean bias of 7.6 pg/mL determined by Bland-Altman analysis, showed good agreement between the two methods. We envision such a sensing system would allow medical practitioners to facilitate targeted interventions, thereby, offering an immediate prognostic approach as the cornerstone to delivering successful treatment for patients suffering from primary hyperparathyroidism.

CLIP: Carbon Dioxide testing suitable for Low power microelectronics and IOT interfaces using Room temperature Ionic Liquid Platform.

Health and safety considerations of room occupants in enclosed spaces is crucial for building management which entails control and stringent monitoring of CO2 levels to maintain acceptable air quality standards and improve energy efficiency. Smart building management systems equipped with portable, low-power, non-invasive CO2 sensing techniques can predict room occupancy detection based on CO2 levels exhaled by humans. In this work, we have demonstrated the development and proof-of-feasibility working of an electrochemical RTIL- based sensor prototype for CO2 detection in exhaled human breath. The portability, small form factor, embedded RTIL sensing element, integrability with low-power microelectronic and IOT interfaces makes this CO2 sensor prototype a potential application for passive room occupancy monitoring. This prototype exhibits a wide dynamic range of 400-8000 ppm, a short response time of ~10 secs, and a reset time of ~6 secs in comparison to commercial standards. The calibration response of the prototype exhibits an R2 of 0.956. With RTIL as the sensing element, we have achieved a sensitivity of 29 pF/ppm towards CO2 at ambient environmental conditions and a three times greater selectivity towards CO2 in the presence of N2 and O2. CO2 detection is accomplished by quantifying the capacitance modulations arising within the electrical double layer from the RTIL- CO2 interactions through AC- based electrochemical impedance spectroscopy and DC- based chronoamperometry.

Non-faradaic electrochemical impedimetric profiling of procalcitonin and C-reactive protein as a dual marker biosensor for early sepsis detection.

In this work, we demonstrate a robust, dual marker, biosensing strategy for specific and sensitive electrochemical response of Procalcitonin and C-reactive protein in complex body fluids such as human serum and whole blood for the detection of sepsis. Enhanced sensitivity is achieved by leveraging the physicochemical properties of zinc oxide at the electrode-solution interface. Characterization techniques such as SEM, EDAX, AFM, FTIR and fluorescence microscopy were performed to ensure a suitable biosensing surface. The characteristic biomolecular interactions between the target analyte and specific capture probe is quantified through unique frequency signatures using non-faradaic electrochemical impedance spectroscopy (EIS). The developed biosensor demonstrated a detection limit of 0.10 ng mL-1 for PCT in human serum and whole blood with an R2 of 0.99 and 0.98 respectively. CRP demonstrated a detection limit of 0.10 µg mL-1 in human serum and whole blood with an R2 of 0.90 and 0.98 respectively. Cross-reactivity analysis demonstrated robust selectivity to PCT and CRP with negligible interaction to non-specific biomolecules. The novel aspect of this technology is the ability to fine-tune individual biomarkers response owing to the optimal frequency tuning capability. The developed biosensor requires an ultra-low sample volume of 10 µL without the need for sample dilution for rapid analysis. We envision the developed dual marker biosensor to be useful as a sepsis-screening device for prognostic monitoring.

Development of ultra-low volume, multi-bio fluid, cortisol sensing platform.

The development of a non-faradaic electrochemical sensor for screening across multiple bio-fluids that demonstrate the expression of cortisol using a gold microelectrode-based sensor is reported in this paper. Room temperature ionic liquid (RTIL), BMIM[BF4] was used as the buffer to modulate the electrical double layer (EDL) to enhance the electrochemical signal response of the sensor. The sensor design and the surface chemistry was optimized using COMSOL Multiphysics software simulations and FTIR respectively. The sensor was designed so that it uses ultra-low volumes between 3-5 µL of bio-fluid for detection. Cortisol detection was achieved in the physiologically relevant ranges when tested in serum, blood, sweat, and, saliva using non-faradaic Electrochemical Impedance Spectroscopy (EIS) and performance parameters of the sensor were determined. Sensor's response was tested against the only commercially available salivary cortisol point-of-care kit using regression analysis. Cross-reactive studies using prednisone indicated that the sensor is specific for cortisol. The sensor displayed a correlation value i.e. R2 > 0.95 between the signal response and the concentration of cortisol present in the system. Dynamic range of the sensor was across the physiologically relevant range of cortisol i.e. 50-200 ng/ml for serum/blood, 1-40 ng/ml for saliva, and 10-150 ng/ml for sweat. Limit of detection for serum and sweat was 10 ng/ml and 1 ng/ml for saliva.

Multiplexed electrochemical detection of three cardiac biomarkers cTnI, cTnT and BNP using nanostructured ZnO-sensing platform.

AIM: Development of a label-free multiplexed point-of-care diagnostic device for a panel of cardiac biomarkers - cardiac troponin-T (cTnT), troponin-I (cTnI) and B-type natriuretic peptide (BNP). METHODS: A nonfaradaic electrochemical immunoassay designed with anisotropic high surface area ZnO nanostructures grown using low-temperature hydrothermal methods was selectively immobilized with capture antibodies. Multiplexed detection in human serum using ZnO nanostructures based on complementary electrochemical measurement techniques - electrochemical impedance spectroscopy and Mott-Schottky. RESULTS: Linear signal response for detection of three biomarkers in human serum with dynamic range of 1 pg/ml-100 ng/ml and limit of detection at 1 pg/ml and low signal response to background interferences was achieved. CONCLUSION: First demonstration of simultaneous detection of three cardiac biomarkers in clinically relevant range with sensor's analytical performance and linear response of detection showed potential utility in screening clinical samples for early diagnosis of acute myocardial infarction and chronic heart failure.