Machine learning assisted and smartphone integrated homogeneous electrochemiluminescence biosensor platform for sample to answer detection of various human metabolites.

The sensitive and accurate detection of glucose and lactate is essential for early diagnosis and effective management of diabetes complications. Herein, a 3D Printed ECL imaging system integrated with a Smartphone has been demonstrated to advance the traditional ECL to make a portable, affordable, and turnkey point-of-care solution to detect various human metabolites. A universal cross-platform application was introduced for analyzing ECL emitted signals to automate the whole detection process for real-time monitoring and rapid diagnostics. The developed ECL system was successfully applied and validated for detecting glucose and lactate using a single-electrode ECL biosensing platform. For glucose and lactate detection, the device showed a linear range from 0.1 mM to 1 mM and 0.1 mM-4 mM with a detection limit (LoD) of 0.04 mM and 0.1 mM, and a quantification limit (LoQ) of 0.142 mM and 0.342 mM, respectively. The developed method was evaluated for device stability, accuracy, interference, and real sample analysis. Furthermore, to assist in selecting the accurate and economic ECL sensing platform, SE-ECL devices fabricated via different fabrication approaches such as Laser-Induced Graphene, Screen Printing, and 3D Printing are studied for the conductivity of electrode and its significance on ECL signal. It was observed that emitted ECL signal is independent of the electrical conductivity for the same concentration of analytes. The findings suggested that the developed miniaturized point-of-care ECL platform would be a comprehensive and integrated solution for detecting other human metabolites and have the potential to be used in clinical applications.

Multiplexed and simultaneous biosensing in a 3D-printed portable six-well smartphone operated electrochemiluminescence standalone point-of-care platform.

3D-printed portable devices have immense and proven potential to transform the field of electrochemiluminescence (ECL) for diverse biochemical applications. 3D printing (3DP) offers unparalleled ability to build tiny devices in a single step with high accuracy and compatibility, and integrability as per the requirement. In this study, for the first time, a six-well 3D-printed closed bipolar electrochemiluminescence (3DP-CBPE-ECL) device has been successfully fabricated and validated by performing single-step detection of various biochemicals such as glucose and choline. Luminol/H2O2-based enzymatic reactions were performed with optimized parameters for selective sensing of glucose and choline. The single-step detection of glucose and choline was accomplished for the linear ranges of 0.1 to 10 mM and 0.1 to 5 mM, with a limit of detections (LODs) of 24 µM and 10 µM, respectively. A smartphone was leveraged to execute multiple activities such as powering the ECL device, capturing ECL images, and calculating the ECL intensity of the obtained ECL signal. The feasibility of a six-well 3DP-CBPE-ECL device was tested by sensing glucose and choline simultaneously in a single device at three different concentrations. Furthermore, the concentration of glucose and choline was calculated in real blood serum using the conventional additive (spiking) method, demonstrating the high practicability of the fabricated ECL device and yielding promising findings. Finally, based on the obtained results and other advantages such as low-cost, fast prototyping and requirement of a minimum sample volume, the fabricated six-well 3DP-CBPE-ECL device has shown potential to be used in the field of biochemical applications.

Internet of things-enabled photomultiplier tube- and smartphone-based electrochemiluminescence platform to detect choline and dopamine using 3D-printed closed bipolar electrodes.

There is a growing demand to realize low-cost miniaturized point-of-care testing diagnostic devices capable of performing many analytical assays. To fabricate such devices, three-dimensional printing (3DP)-based fabrication techniques provide a turnkey approach with marked precision and accuracy. Here, a 3DP fabrication technique was successfully utilized to fabricate closed bipolar electrode-based electrochemiluminescence (ECL) devices using conductive graphene filament. Furthermore, using these ECL devices, Ru(bpy)3 2+ /TPrA- and luminol/H2 O2 -based electrochemistry was leveraged to sense dopamine and choline respectively. For ECL signal capture, two distinct approaches were used, first a smartphone-based miniaturized platform and the second with a photomultiplier tube embedded with the internet of things technology. Choline sensing led to a linear range 5-700 µM and 30-700 µM with a limit of detection (LOD) of 1.25 µM (R2 = 0.98, N = 3) and 3.27 µM (R2 = 0.97, N = 3). Furthermore, dopamine sensing was achieved in a linear range 0.5-100 µM with an LOD = 2 µM (R2 = 0.99, N = 3) and LOD = 0.33 µM (R2 = 0.98, N = 3). Overall, the fabricated devices have the potential to be utilized effectively in real-time applications such as point-of-care testing.

Miniaturized Electrochemiluminescence Platform With Laser-Induced Graphene Electrodes for Multiple Biosensing.

The present work demonstrates a miniaturized 3D printed Electrochemiluminescence (ECL) sensing platform with Laser-Induced Graphene (LIG) based Open Bipolar Electrodes (OBEs). To fabricate OBEs, polyimide (PI) substrate has been used as it provides properties like low-cost fabrication, high selectivity, great stability, easy reproducibility, cost-effectiveness and rapid prototyping. Moreover, graphene can be created on PI in a single step during the ablation of the CO2 laser. Android smartphone was efficiently used to sense ECL signals as well as to drive the required voltage to the OBEs. With the optimized parameters, the imaging system was successfully used to detect Hydrogen Peroxide (H2 O2) with a linear range of 1 [Formula: see text] to [Formula: see text] and detection of limit (LOD) [Formula: see text] (R2 = 0.9449, n = 3). In addition, the detection of glucose has been carried out with a linear range of [Formula: see text] to [Formula: see text] and detection of limit (LOD) [Formula: see text] (R2 = 0.9875, n = 3). Further, real samples were tested to manifest the workability of the platform for random samples. Overall, the developed low-cost, rapidly realized and the miniaturized system can be used in many biomedical applications, environmental monitoring and point-of-care testings.