Non-invasive Monitoring of α-Synuclein in Saliva for Parkinson's Disease Using Organic Electrolyte-Gated FET Aptasensor.

Parkinson's disease (PD) currently affects more than 1 million people in the US alone, with nearly 8.5 million suffering from the disease worldwide, as per the World Health Organization. However, there remains no fast, pain-free, and effective method of screening for the disease in the ageing population, which also happens to be the most susceptible to this neurodegenerative disease. αSynuclein (αSyn) is a promising PD biomarker, demonstrating clear delineations between levels of the αSyn monomer and the extent of αSyn aggregation in the saliva of PD patients and healthy controls. In this work, we have demonstrated a laboratory prototype of a soft fluidics integrated organic electrolyte-gated field-effect transistor (OEGFET) aptasensor platform capable of quantifying levels of αSyn aggregation in saliva. The aptasensor relies on a recently reported synthetic aptamer which selectively binds to αSyn monomer as the bio-recognition molecule within the integrated fluidic channel of the biosensor. The produced saliva sensor is label-free, fast, and reusable, demonstrating good selectivity only to the target molecule in its monomer form. The novelty of these devices is the fully isolated organic semiconductor, which extends the shelf life, and the novel fully integrated soft microfluidic channels, which simplify saliva loading and testing. The OEGFET aptasensor has a limit of detection of 10 fg/L for the αSyn monomer in spiked saliva supernatant solutions, with a linear range of 100 fg/L to 10 µg/L. The linear range covers the physiological range of the αSyn monomer in the saliva of PD patients. Our biosensors demonstrate a desirably low limit of detection, an extended linear range, and fully integrated microchannels for saliva sample handling, making them a promising platform for non-invasive point-of-care testing of PD.

A System-on-Board Integrated Multi-analyte PoC Biosensor for Combined Analysis of Saliva and Exhaled Breath.

The need for oral health monitoring Point of Care (PoC) systems is ever growing. This is effectively highlighted by the ongoing COVID-19 pandemic where the lack of rapid PoC testing has placed an unsustainable burden on centralized laboratory testing. Urgent development has furthered pathogenic nucleic acid and antibody detection in oral samples throat swabs, but without corresponding advancements in biochemical monitoring through oral biosensing. We have recently reported two novel biosensor technologies for detection of high impact hormones: cortisol in saliva by organic electrolyte gated FETs (OEGFETs), and 8-isoprostane in exhaled breath condensate (EBC) using molecularly imprinted electroimpedance spectroscopy biosensors (MIP EIS). In this work, we report a first stage integration of the two biosensors - previously bench-top proven - with a miniaturized semi-hermetically sealed soft-fluidic enclosure, onto a low-power (<300 mW) customized printed circuit board. Our findings established comparable detection thresholds for the miniaturized board-based configuration and a lab-based test setup, and their ability to characterize, calibrate, and operate these small footprint biosensors. Testing with the 8-isoprostane EBC MIP EIS biosensors showed the system-on-board had an effective frequency range of 100-100kHz, comparable to lab bench impedance analyzers. Despite internal impedance increases of 210%, the expected data features are present in the impedance graphs collected with the PCB. The system-on-board experiments using OEGFET aptasensor showed a predictable behavior and comparable sensor detection range and resolution using unadulterated supernatant and serial dilutions of cortisol over a range of 273 µM to 2.73pM. The portable, multi-analyte oral biosensor is a promising prototype for future packaging and clinical validation.

Modeling the Double Layer Capacitance Effect in Electrolyte Gated FETs with Gel and Aqueous Electrolytes.

Potential implementation of bio-gel Electrolyte Double Layer capacitors (bio-gel EDLCs) and electrolyte-gated FET biosensors, two commonly reported configurations of bio-electrolytic electronic devices, requires a robust analysis of their complex internal capacitive behavior. Presently there is neither enough of the parameter extraction literature, nor an effective simulation model to represent the transient behavior of these systems. Our work aims to supplement present transient thin film transistor modelling techniques with the reported parameter extraction method, to accurately model both bio-gel EDLC and the aqueous electrolyte gated FET devices. Our parameter extraction method was tested with capacitors analogous to polymer-electrolyte gated FETs, electrolyte gated Field effect transistor (EGOFET) and Organic Electrolyte Gated Field Effect Transistor (OEGFET) capacitance stacks. Our method predicts the input/output electrical behavior of bio-gel EDLC and EGOFET devices far more accurately than conventional DLC techniques, with less than 5% error. It is also more effective in capturing the characteristic aqueous electrolyte charging behavior and maximum charging capability which are unique to these systems, than the conventional DLC Zubieta and the Two branch models. We believe this significant improvement in device simulation is a pivotal step towards further integration and commercial implementation of organic bio-electrolyte devices. The effective reproduction of the transient response of the OEGFET equivalent system also predicts the transient capacitive effects observed in our previously reported label-free OEGFET biosensor devices. This is the first parameter extraction method specifically designed for electrical parameter-based modelling of organic bio-electrolytic capacitor devices.