Powerful Electron-Transfer Screen-Printed Platforms as Biosensing Tools: The Case of Uric Acid Biosensor

An ethyl cellulose novel biodegradable flexible substrate material for sustainable screen-printing

We introduce an innovative solution to reduce plastic dependence in flexible electronics: a biodegradable, water-resistant, and flexible cellulose-based substrate for crafting electrochemical printed platforms. This sustainable material based on ethyl cellulose (EC) serves as an eco-friendly alternative to PET in screen printing, boasting superior water resistance compared to other biodegradable options. Our study evaluates the performance of carbon-based screen-printed electrodes (SPEs) fabricated on conventional PET, recycled PET (r-PET), and (EC)-based materials. Electrochemical characterization reveals that EC-SPEs exhibit comparable analytical performance to both P-SPEs and rP-SPEs, as evidenced by similar limits of detection (LOD), limits of quantification (LOQ), and reproducibility values for all the analytes tested (ferro-ferricyanide, hexaammineruthenium chloride, uric acid, and hydroquinone). This finding underscores the potential of our cellulose-based substrate to match the performance of conventional PET-based electrodes. Moreover, the scalability and low-energy requirements of our fabrication process highlight the potential of this material to revolutionize eco-conscious manufacturing. By offering a sustainable alternative without compromising performance, our cellulose-based substrate paves the way for greener practices in flexible electronics production.

Uricase Crowding via Polyelectrolyte Layers Coacervation for Carbon Fiber-Based Electrochemical Detection of Uric Acid

Urate oxidase (UOx) surrounded by synthetic macromolecules, such as polyethyleneimine (PEI), poly(allylamine hydrochloride) (PAH), and poly(sodium 4-styrenesulfonate) (PSS) is a convenient model of redox-active biomacromolecules in a crowded environment and could display high enzymatic activity towards uric acid, an important marker of COVID-19 patients. In this work, the carbon fiber electrode was modified with Prussian blue (PB) redox mediator, UOx layer, and a layer-by-layer assembled polyelectrolyte film, which forms a complex coacervate consisting of a weakly charged polyelectrolyte (PEI or PAH) and a highly charged one (PSS). The film deposition process was controlled by cyclic voltammetry and scanning electron microscopy coupled with energy-dispersive X-ray analysis (at the stage of PB deposition) and through quartz crystal microbalance technique (at latter stages) revealed uniform distribution of the polyelectrolyte layers. Variation of the polyelectrolyte film composition derived the following statements. (1) There is a linear correlation between electrochemical signal and concentration of uric acid in the range of 10^-4-10^-6 M. (2) An increase in the number of polyelectrolyte layers provides more reproducible values for uric acid concentration in real urine samples of SARS-CoV-2 patients measured by electrochemical enzyme assay, which are comparable to those of spectrophotometric assay. (3) The PAH/UOx/PSS/(PAH/PSS)₂-coated carbon fiber electrode displays the highest sensitivity towards uric acid. (4) There is a high enzyme activity of UOx immobilized into the hydrogel nanolayer (values of the Michaelis-Menten constant are up to 2 μM) and, consequently, high affinity to uric acid.

A Deep Learning Approach to Organic Pollutants Classification Using Voltammetry

This paper proposes a deep leaning technique for accurate detection and reliable classification of organic pollutants in water. The pollutants are detected by means of cyclic voltammetry characterizations made by using low-cost disposable screen-printed electrodes. The paper demonstrates the possibility of strongly improving the detection of such platforms by modifying them with nanomaterials. The classification is addressed by using a deep learning approach with convolutional neural networks. To this end, the results of the voltammetry analysis are transformed into equivalent RGB images by means of Gramian angular field transformations. The proposed technique is applied to the detection and classification of hydroquinone and benzoquinone, which are particularly challenging since these two pollutants have a similar electroactivity and thus the voltammetry curves exhibit overlapping peaks. The modification of electrodes by carbon nanotubes improves the sensitivity of a factor of about ×25, whereas the convolution neural network after Gramian transformation correctly classifies 100% of the experiments.

Cost-effective and disposable label-free voltammetric immunosensor for sensitive detection of interleukin-6

IL-6 detection is highly desirable since can monitor many diseases in humans and assess the response to treatments. Herein, two novel label-free voltammetric immunosensors for rapid and accurate interleukin-6 (IL-6) detection in human serum are presented. The immunosensors are fabricated by immobilising two different IL-6 antibodies, identified as mAb-IL-6 clone-5 and clone-7, on in-house produced screen-printed electrodes modified with inexpensive recycling biochar (Bio-SPEs). To ensure high structural fidelity and performance, an in-depth electrochemical characterization of the layer-by-layer assembly of the immunosensor was conducted by cyclic voltammetry (CV) and sensing was performed using square wave voltammetry (SWV). The two immunosensors showed good analytical performances in human serum, exhibiting a wide linear range (LR) between 26-125 and 30-138 pg/mL, a good limit of detection (LOD) of 4.8 and 5.4 pg/mL and selectivity for IL-6 over other common cytokines, including IL-1β and TNF-α. Performance comparison of IL-6 immunosensors with those of a commercial spectrophotometric ELISA kit (LOD of 20 pg/mL, RSD% of 15%) denotes a better sensitivity and reproducibility of the proposed label-free devices, associated with a reduced detection time (30 min instead of more than 3 h for ELISA test). Furthermore, the proposed immunosensors were successfully applied in blood samples (with only a dilution of 1:100 v/v in PBS and without additional treatments) with good sensitivity (LOD of 14.3 pg/mL) and reproducibility (RSD% < 11%), thus paving the way for their application as viable diagnostic and therapeutic point-of-care tools alternative to the IL-6 detection techniques routinely used (ELISA and Western Blot).

Sensitive Detection of Industrial Pollutants Using Modified Electrochemical Platforms

Water pollution is nowadays a global problem and the effective detection of pollutants is of fundamental importance. Herein, a facile, efficient, robust, and rapid (response time < 2 min) method for the determination of important quinone-based industrial pollutants such as hydroquinone and benzoquinone is reported. The recognition method is based on the use of screen-printed electrodes as sensing platforms, enhanced with carbon-based nanomaterials. The enhancement is achieved by modifying the working electrode of such platforms through highly sensitive membranes made of Single- or Multi-Walled Carbon Nanotubes (SWNTs and MWNTs) or by graphene nanoplatelets. The modified sensing platforms are first carefully morphologically and electrochemically characterized, whereupon they are tested in the detection of different pollutants (i.e., hydroquinone and benzoquinone) in water solution, by using both cyclic and square-wave voltammetry. In particular, the sensors based on film-deposited nanomaterials show good sensitivity with a limit of detection in the nanomolar range (0.04 and 0.07 μM for SWNT- and MWNT-modified SPEs, respectively) and a linear working range of 10 to 1000 ppb under optimal conditions. The results highlight the improved performance of these novel sensing platforms and the large-scale applicability of this method for other analytes (i.e., toxins, pollutants).

A non-enzymatic electrochemical sensor composed of nano-berry shaped cobalt oxide nanostructures on a glassy carbon electrode for uric acid detection

Non-enzymatic electrochemical uric acid sensor fabrication with excellent performance using nano-berry shaped cobalt oxide nanostructures on a glassy carbon electrode.