Low-Cost and Rapid-Production Microfluidic Electrochemical Double-Layer Capacitors for Fast and Sensitive Breast Cancer Diagnosis.

This technical note describes a new microfluidic sensor that combines low-cost (USD $0.97) with rapid fabrication and user-friendly, fast, sensitive, and accurate quantification of a breast cancer biomarker. The electrodes consisted of cost-effective bare stainless-steel capillaries, whose mass production is already well-established. These capillaries were used as received, without any surface modification. Microfluidic chips containing electrical double-layer capillary capacitors (µEDLC) were obtained by a cleanroom-free prototyping that allows the fabrication of dozens to hundreds of chips in 1 h. This sensor provided the successful quantification of CA 15-3, a biomarker protein for breast cancer, in serum samples from cancer patients. Antibody-anchored magnetic beads were utilized for immunocapture of the marker, and then, water was added to dilute the protein. Next, the CA 15-3 detection (<2 min) was made without using redox probes, antibody on electrode (sandwich immunoassay), or signal amplification strategies. In addition, the capacitance tests eliminated external pumping systems and precise volumetric sampling steps, as well as presented low sample volume (5 µL) and high sensitivity using bare capillaries in a new design for double-layer capacitors. The achieved limit-of-detection (92.0 µU mL-1) is lower than that of most methods reported in the literature for CA 15-3, which are based on nanostructured electrodes. The data shown in this technical note support the potential of the µEDLC toward breast cancer diagnosis even at early stages. We believe that accurate analyses using a simple sample pretreatment such as magnetic field-assisted immunocapture and cost-effective bare electrodes can be extended to quantify other cancer biomarkers and even biomolecules by changing the biorecognition element.

Single-Response Electronic Tongue and Machine Learning Enable the Multidetermination of Extracellular Vesicle Biomarkers for Cancer Diagnostics Without Recognition Elements.

Platforms based on impedimetric electronic tongue (nonselective sensor) and machine learning are promising to bring disease screening biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point-of-care, thus contributing to rationalize and decentralize laboratory tests with social and economic impacts being achieved. By combining a low-cost and scalable electronic tongue with machine learning, in this chapter, we describe the simultaneous determination of two extracellular vesicle (EV) biomarkers, i.e., the concentrations of EV and carried proteins, in mice blood with Ehrlich tumor from a single impedance spectrum without using biorecognizing elements. This tumor shows primary features of mammary tumor cells. Pencil HB core electrodes are integrated into polydimethylsiloxane (PDMS) microfluidic chip. The platform shows the highest throughput in comparison with the methods addressed in the literature to determine EV biomarkers.

Scalable and green formation of graphitic nanolayers produces highly conductive pyrolyzed paper toward sensitive electrochemical sensors.

While pyrolyzed paper (PP) is a green and abundant material that can provide functionalized electrodes with wide detection windows for a plethora of targets, it poses long-standing challenges against sensing assays such as poor electrical conductivity, with resistivities generally higher than 200.0 mΩ cm (e.g., gold and silver show resistivities 1000-fold lower, ∼0.2 mΩ cm). In this regard, the fundamental hypothesis that drives this work is whether a scalable, cost-effective, and eco-friendly strategy is capable of significantly reducing the resistivity of PP electrodes toward the development of sensitive electrochemical sensors, whether faradaic or capacitive. We address this hypothesis by simply annealing PP under an isopropanol atmosphere for 1 h, reaching resistivities as low as 7 mΩ cm. Specifically, the annealing of PP at 800 or 1000 °C under isopropanol vapor leads to the formation of a highly graphitic nanolayer (∼15 nm) on the PP surface, boosting conductivity as the delocalization of π electrons stemming from carbon sp2 is favored. The reduction of carbonyl groups and the deposition of dehydrated isopropanol during the annealing process are hypothesized herein as the dominant PP graphitization mechanisms. Electrochemical analyses demonstrated the capability of the annealed PP to increase the charge-transfer kinetics, with the optimum heterogeneous standard rate constant being roughly 3.6 × 10-3 cm s-1. This value is larger than the constants reported for other carbon electrodes and indium tin oxide. Furthermore, freestanding fingers of the annealed PP were prototyped using a knife plotter to fabricate impedimetric on-leaf electrodes. These wearable sensors ensured the real-time and in situ monitoring of the loss of water content from soy leaves, outperforming non-annealed electrodes in terms of reproducibility and sensitivity. Such an application is of pivotal importance for precision agriculture and development of agricultural inputs. This work addresses the foundations for the achievement of conductive PP in a scalable, low-cost, simple, and eco-friendly way, i.e. without producing any liquid chemical waste, providing new opportunities to translate PP-based sensitive electrochemical devices into practical use.

In Situ Nanocoating on Porous Pyrolyzed Paper Enables Antibiofouling and Sensitive Electrochemical Analyses in Biological Fluids.

Electrochemical detection in complex biofluids is a long-standing challenge as electrode biofouling hampers its sensing performance and commercial translation. To overcome this drawback, pyrolyzed paper as porous electrode coupled with the drop casting of an off-the-shelf polysorbate, that is, Tween 20 (T20), is described here by taking advantage of the in situ formation of a hydrophilic nanocoating (2 nm layer of T20). The latter prevents biofouling while providing the capillarity of samples through paper pores, leveraging redox reactions across both only partially fouled and fresh electrodic surfaces with increasing detection areas. The nanometric thickness of this blocking layer is also essential by not significantly impairing the electron-transfer kinetics. These phenomena behave synergistically to enhance the sensibility that further increases over long-term exposures (4 h) in biological fluids. While the state-of-the-art antibiofouling strategies compromise the sensibility, this approach leads to peak currents that are up to 12.5-fold higher than the original currents after 1 h exposure to unprocessed human plasma. Label-free impedimetric immunoassays through modular bioconjugation by directly anchoring spike protein on gold nanoparticles are also allowed, as demonstrated for the COVID-19 screening of patient sera. The scalability and simplicity of the platform combined with its unique ability to operate in biofluids with enhanced sensibility provide the generation of promising biosensing technologies toward real-world applications in point-of-care diagnostics, mass testing, and in-home monitoring of chronic diseases.

Alcohol-Triggered Capillarity through Porous Pyrolyzed Paper-Based Electrodes Enables Ultrasensitive Electrochemical Detection of Phosphate.

The sensing field has shed light on an urgent necessity for field-deployable, user-friendly, sensitive, and scalable platforms that are able to translate solutions into the real world. Here, we attempt to meet these requests by addressing a simple, low-cost, and fast electrochemical approach to provide sensitive assays that consist of dropping a small volume (0.5 µL) of off-the-shelf alcohols on pyrolyzed paper-based electrodes before adding the sample (150 µL). This method was applied in the detection of phosphate after the formation of the phosphomolybdate complex (250-860 nm in size). Prior drops of isopropanol allow for the fast penetration of the sample through pores of this hydrophobic paper, delivering hindrance-free redox reactions across increasing active areas and ultimately improving the detection performance. The sensitivity (-1.9 10-6 mA cm-2 ppb-1) and limit of detection (1.1 ppb) were improved, respectively, by factors of 33 and 99 over the data achieved without the addition of isopropanol, listing among the lowest values when compared with those results reported in the literature for phosphate (expressed in terms of the concentration of phosphorus). The approach enabled the quantification of this analyte in real samples with accuracies ranging from 87 to 103%. Furthermore, preliminary measurements demonstrated the successful performance of the electrodes with prior addition of other widely used alcohols, that is, methanol and ethanol. These results may extend the applicability of the method. In special, the scalability and eco-friendly character of the electrode fabrication combined with the sensitivity and simplicity of the analyses make the developed platform a promising alternative that may help to pave the way for a new generation of disposable sensors toward the daily monitoring of phosphate in water samples, thus contributing to prevent ecological side effects.

Converging Multidimensional Sensor and Machine Learning Toward High-Throughput and Biorecognition Element-Free Multidetermination of Extracellular Vesicle Biomarkers.

Extracellular vesicles (EVs) are a frontier class of circulating biomarkers for the diagnosis and prognosis of different diseases. These lipid structures afford various biomarkers such as the concentrations of the EVs (CV) themselves and carried proteins (CP). However, simple, high-throughput, and accurate determination of these targets remains a key challenge. Herein, we address the simultaneous monitoring of CV and CP from a single impedance spectrum without using recognizing elements by combining a multidimensional sensor and machine learning models. This multidetermination is essential for diagnostic accuracy because of the heterogeneous composition of EVs and their molecular cargoes both within the tumor itself and among patients. Pencil HB cores acting as electric double-layer capacitors were integrated into a scalable microfluidic device, whereas supervised models provided accurate predictions, even from a small number of training samples. User-friendly measurements were performed with sample-to-answer data processing on a smartphone. This new platform further showed the highest throughput when compared with the techniques described in the literature to quantify EVs biomarkers. Our results shed light on a method with the ability to determine multiple EVs biomarkers in a simple and fast way, providing a promising platform to translate biofluid-based diagnostics into clinical workflows.