Tuning the Chemical and Electrochemical Properties of Paper-Based Carbon Electrodes by Pyrolysis of Polydopamine.

Electrochemical paper-based analytical devices represent an important platform for portable, low-cost, affordable, and decentralized diagnostics. For this kind of application, chemical functionalization plays a pivotal role to ensure high clinical performance by tuning surface properties and the area of electrodes. However, controlling different surface properties of electrodes by using a single functionalization route is still challenging. In this work, we attempted to tune the wettability, chemical composition, and electroactive area of carbon-paper-based devices by thermally treating polydopamine (PDA) at different temperatures. PDA films were deposited onto pyrolyzed paper (PP) electrodes and thermally treated in the range of 300-1000 °C. After deposition of PDA, the surface is rich in nitrogen and oxygen, it is superhydrophilic, and it has a high electroactive area. As the temperature increases, the surface becomes hydrophobic, and the electroactive area decreases. The surface modifications were followed by Raman, X-ray photoelectron microscopy (XPS), laser scanning confocal microscopy (LSCM), contact angle, scanning electron microscopy (SEM-EDS), electrical measurements, transmission electron microscopy (TEM), and electrochemical experiments. In addition, the chemical composition of nitrogen species can be tuned on the surface. As a proof of concept, we employed PDA-treated surfaces to anchor [AuCl4]- ions. After electrochemical reduction, we observed that it is possible to control the size of the nanoparticles on the surface. Our route opens a new avenue to add versatility to electrochemical interfaces in the field of paper-based electrochemical biosensors.

Ultradense Electrochemical Chips with Arrays of Nanostructured Microelectrodes to Enable Sensitive Diffusion-Limited Bioassays.

Nanostructured microelectrodes (NMEs) are an attractive alternative to yield sensitive bioassays in unprocessed samples. However, although valuable for different applications, nanoporous NMEs usually cannot boost the sensitivity of diffusion-limited analyses because of the enlarged Debye length within the nanopores, which reduces their accessibility. To circumvent this limitation, nanopore-free gold NMEs were electrodeposited from 45 µm SU-8 apertures, featuring nanoridged microspikes on a recessed surface of gold thin film while carrying interconnected crown-like and spiky structures along the edge of a SU-8 passivation layer. These structures were grown onto ultradense, vertical array chips that offer a promising strategy for translating reproducible, high-resolution, and cost-effective sensors into real-world applications. The NMEs yielded reproducible analyses, while machine learning allowed us to predict the analytical responses from NME electrodeposition data. By taking advantage of the high surface area and accessible structure of the NMEs, these structures provided a sensitivity for [Fe(CN)6]3-/4- that was 5.5× higher than that of bare WEs while also delivering a moderate antibiofouling property in undiluted human plasma. As a proof of concept, these electrodes were applied toward the fast (22 min) and simple determination of Staphylococcus aureus by monitoring the oxidation of [Fe(CN)6]4-, which acted as a cellular respiration rate redox reporter. The sensors also showed a wide dynamic range, spanning 5 orders of magnitude, and a calculated limit of detection of 0.2 CFU mL-1.

Single-Response Duplexing of Electrochemical Label-Free Biosensor from the Same Tag.

Multiplexing is a valuable strategy to boost throughput and improve clinical accuracy. Exploiting the vertical, meshed design of reproducible and low-cost ultra-dense electrochemical chips, the unprecedented single-response multiplexing of typical label-free biosensors is reported. Using a cheap, handheld one-channel workstation and a single redox probe, that is, ferro/ferricyanide, the recognition events taking place on two spatially resolved locations of the same working electrode can be tracked along a single voltammetry scan by collecting the electrochemical signatures of the probe in relation to different quasi-reference electrodes, Au (0 V) and Ag/AgCl ink (+0.2 V). This spatial isolation prevents crosstalk between the redox tags and interferences over functionalization and binding steps, representing an advantage over the existing non-spatially resolved single-response multiplex strategies. As proof of concept, peptide-tethered immunosensors are demonstrated to provide the duplex detection of COVID-19 antibodies, thereby doubling the throughput while achieving 100% accuracy in serum samples. The approach is envisioned to enable broad applications in high-throughput and multi-analyte platforms, as it can be tailored to other biosensing devices and formats.

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.

Machine learning toward high-performance electrochemical sensors.

The so-coined fourth paradigm in science has reached the sensing area, with the use of machine learning (ML) toward data-driven improvements in sensitivity, reproducibility, and accuracy, along with the determination of multiple targets from a single measurement using multi-output regression models. Particularly, the use of supervised ML models trained on large data sets produced by electrical and electrochemical bio/sensors has emerged as an impacting trend in the literature by allowing accurate analyses even in the presence of usual issues such as electrode fouling, poor signal-to-noise ratio, chemical interferences, and matrix effects. In this trend article, apart from an outlook for the coming years, we present examples from the literature that demonstrate how helpful ML algorithms can be for dispensing the adoption of experimental methods to address the aforesaid interfering issues, ultimately contributing to translate testing technologies into on-site, practical, and daily applications.

Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests.

Limitations of the recognition elements in terms of synthesis, cost, availability, and stability have impaired the translation of biosensors into practical use. Inspired by nature to mimic the molecular recognition of the anti-SARS-CoV-2 S protein antibody (AbS) by the S protein binding site, we synthesized the peptide sequence of Asn-Asn-Ala-Thr-Asn-COOH (abbreviated as PEP2003) to create COVID-19 screening label-free (LF) biosensors based on a carbon electrode, gold nanoparticles (AuNPs), and electrochemical impedance spectroscopy. The PEP2003 is easily obtained by chemical synthesis, and it can be adsorbed on electrodes while maintaining its ability for AbS recognition, further leading to a sensitivity 3.4-fold higher than the full-length S protein, which is in agreement with the increase in the target-to-receptor size ratio. Peptide-loaded LF devices based on noncovalent immobilization were developed by affording fast and simple analyses, along with a modular functionalization. From studies by molecular docking, the peptide-AbS binding was found to be driven by hydrogen bonds and hydrophobic interactions. Moreover, the peptide is not amenable to denaturation, thus addressing the trade-off between scalability, cost, and robustness. The biosensor preserves 95.1% of the initial signal for 20 days when stored dry at 4 °C. With the aid of two simple equations fitted by machine learning (ML), the method was able to make the COVID-19 screening of 39 biological samples into healthy and infected groups with 100.0% accuracy. By taking advantage of peptide-related merits combined with advances in surface chemistry and ML-aided accuracy, this platform is promising to bring COVID-19 biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point of care, with social and economic impacts being achieved.

Real-Time and In Situ Monitoring of the Synthesis of Silica Nanoparticles.

The real-time and in situ monitoring of the synthesis of nanomaterials (NMs) remains a challenging task, which is of pivotal importance by assisting fundamental studies (e.g., synthesis kinetics and colloidal phenomena) and providing optimized quality control. In fact, the lack of reproducibility in the synthesis of NMs is a bottleneck against the translation of nanotechnologies into the market toward daily practice. Here, we address an impedimetric millifluidic sensor with data processing by machine learning (ML) as a sensing platform to monitor silica nanoparticles (SiO2NPs) over a 24 h synthesis from a single measurement. The SiO2NPs were selected as a model NM because of their extensive applications. Impressively, simple ML-fitted descriptors were capable of overcoming interferences derived from SiO2NP adsorption over the signals of polarizable Au interdigitate electrodes to assure the determination of the size and concentration of nanoparticles over synthesis while meeting the trade-off between accuracy and speed/simplicity of computation. The root-mean-square errors were calculated as ∼2.0 nm (size) and 2.6 × 1010 nanoparticles mL-1 (concentration). Further, the robustness of the ML size descriptor was successfully challenged in data obtained along independent syntheses using different devices, with the global average accuracy being 103.7 ± 1.9%. Our work advances the developments required to transform a closed flow system basically encompassing the reactional flask and an impedimetric sensor into a scalable and user-friendly platform to assess the in situ synthesis of SiO2NPs. Since the sensor presents a universal response principle, the method is expected to enable the monitoring of other NMs. Such a platform may help to pave the way for translating "sense-act" systems into practice use in nanotechnology.

Fast and efficient electrochemical thinning of ultra-large supported and free-standing MoS2 layers on gold surfaces.

Molybdenum disulfide (MoS2) is a very promising layered material for electrical, optical, and electrochemical applications because of its unique and outstanding properties. To unlock its full potential, among different preparation routes, electrochemistry has gain interest due to its simple, fast, scalable and simple instrumentation. However, obtaining large-area monolayer MoS2 that will enable the fabrication of novel electronic and electrochemical devices is still challenging. In this work, we reported a simple and fast electrochemical thinning process that results in ultra-large MoS2 down to monolayer on Au surfaces. The high affinity of MoS2 by Au surfaces enables the removal of bulk layers while preserving the first layer attached to the electrode. With a proper choice of the applied potential, more than 90% of the bulk regions can be removed from large-area MoS2 crystals, as confirmed by atomic force microscopy, photoluminescence, and Raman spectroscopy. We further address a set of contributions that are helpful to elucidate the features of MoS2, namely, the hyphenation of electrochemistry and optical microscopy for real-time observation of the thinning process that was revealed to occur from the edges to the center of the flake, an image treatment to estimate the thinning area and thinning rate, and the preparation of free-standing MoS2 layers by electrochemically thinning bulk flakes on microhole-structured Ni/Au meshes.

Biocompatible Wearable Electrodes on Leaves toward the On-Site Monitoring of Water Loss from Plants.

Impedimetric wearable sensors are a promising strategy for determining the loss of water content (LWC) from leaves because they can afford on-site and nondestructive quantification of cellular water from a single measurement. Because the water content is a key marker of leaf health, monitoring of the LWC can lend key insights into daily practice in precision agriculture, toxicity studies, and the development of agricultural inputs. Ongoing challenges with this monitoring are the on-leaf adhesion, compatibility, scalability, and reproducibility of the electrodes, especially when subjected to long-term measurements. This paper introduces a set of sensing material, technological, and data processing solutions that overwhelm such obstacles. Mass-production-suitable electrodes consisting of stand-alone Ni films obtained by well-established microfabrication methods or ecofriendly pyrolyzed paper enabled reproducible determination of the LWC from soy leaves with optimized sensibilities of 27.0 (Ni) and 17.5 kΩ %-1 (paper). The freestanding design of the Ni electrodes was further key to delivering high on-leaf adhesion and long-term compatibility. Their impedances remained unchanged under the action of wind at velocities of up to 2.00 m s-1, whereas X-ray nanoprobe fluorescence assays allowed us to confirm the Ni sensor compatibility by the monitoring of the soy leaf health in an electrode-exposed area. Both electrodes operated through direct transfer of the conductive materials on hairy soy leaves using an ordinary adhesive tape. We used a hand-held and low-power potentiostat with wireless connection to a smartphone to determine the LWC over 24 h. Impressively, a machine-learning model was able to convert the sensing responses into a simple mathematical equation that gauged the impairments on the water content at two temperatures (30 and 20 °C) with reduced root-mean-square errors (0.1% up to 0.3%). These data suggest broad applicability of the platform by enabling direct determination of the LWC from leaves even at variable temperatures. Overall, our findings may help to pave the way for translating "sense-act" technologies into practice toward the on-site and remote investigation of plant drought stress. These platforms can provide key information for aiding efficient data-driven management and guiding decision-making steps.

Using machine learning and an electronic tongue for discriminating saliva samples from oral cavity cancer patients and healthy individuals.

The diagnosis of cancer and other diseases using data from non-specific sensors - such as the electronic tongues (e-tongues) - is challenging owing to the lack of selectivity, in addition to the variability of biological samples. In this study, we demonstrate that impedance data obtained with an e-tongue in saliva samples can be used to diagnose cancer in the mouth. Data taken with a single-response microfluidic e-tongue applied to the saliva of 27 individuals were treated with multidimensional projection techniques and non-supervised and supervised machine learning algorithms. The distinction between healthy individuals and patients with cancer on the floor of mouth or oral cavity could only be made with supervised learning. Accuracy above 80% was obtained for the binary classification (YES or NO for cancer) using a Support Vector Machine (SVM) with radial basis function kernel and Random Forest. In the classification considering the type of cancer, the accuracy dropped to ca. 70%. The accuracy tended to increase when clinical information such as alcohol consumption was used in conjunction with the e-tongue data. With the random forest algorithm, the rules to explain the diagnosis could be identified using the concept of Multidimensional Calibration Space. Since the training of the machine learning algorithms is believed to be more efficient when the data of a larger number of patients are employed, the approach presented here is promising for computer-assisted diagnosis.

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.

Development of a sticker sealed microfluidic device for in situ analytical measurements using synchrotron radiation.

Shedding synchrotron light on microfluidic systems, exploring several contrasts in situ/operando at the nanoscale, like X-ray fluorescence, diffraction, luminescence, and absorption, has the potential to reveal new properties and functionalities of materials across diverse areas, such as green energy, photonics, and nanomedicine. In this work, we present the micro-fabrication and characterization of a multifunctional polyester/glass sealed microfluidic device well-suited to combine with analytical X-ray techniques. The device consists of smooth microchannels patterned on glass, where three gold electrodes are deposited into the channels to serve in situ electrochemistry analysis or standard electrical measurements. It has been efficiently sealed through an ultraviolet-sensitive sticker-like layer based on a polyester film, and The burst pressure determined by pumping water through the microchannel(up to 0.22 MPa). Overall, the device has demonstrated exquisite chemical resistance to organic solvents, and its efficiency in the presence of biological samples (proteins) is remarkable. The device potentialities, and its high transparency to X-rays, have been demonstrated by taking advantage of the X-ray nanoprobe Carnaúba/Sirius/LNLS, by obtaining 2D X-ray nanofluorescence maps on the microchannel filled with water and after an electrochemical nucleation reaction. To wrap up, the microfluidic device characterized here has the potential to be employed in standard laboratory experiments as well as in in situ and in vivo analytical experiments using a wide electromagnetic window, from infrared to X-rays, which could serve experiments in many branches of science.

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.

Bifunctional Metal Meshes Acting as a Semipermeable Membrane and Electrode for Sensitive Electrochemical Determination of Volatile Compounds.

The monitoring of toxic inorganic gases and volatile organic compounds has brought the development of field-deployable, sensitive, and scalable sensors into focus. Here, we attempted to meet these requirements by using concurrently microhole-structured meshes as (i) a membrane for the gas diffusion extraction of an analyte from a donor sample and (ii) an electrode for the sensitive electrochemical determination of this target with the receptor electrolyte at rest. We used two types of meshes with complementary benefits, i.e., Ni mesh fabricated by robust, scalable, and well-established methods for manufacturing specific designs and stainless steel wire mesh (SSWM), which is commercially available at a low cost. The diffusion of gas (from a donor) was conducted in headspace mode, thus minimizing issues related to mesh fouling. When compared with the conventional polytetrafluoroethylene (PTFE) membrane, both the meshes (40 µm hole diameter) led to a higher amount of vapor collected into the electrolyte for subsequent detection. This inedited fashion produced a kind of reverse diffusion of the analyte dissolved into the electrolyte (receptor), i.e., from the electrode to bulk, which further enabled highly sensitive analyses. Using Ni mesh coated with Ni(OH)2 nanoparticles, the limit of detection reached for ethanol was 24-fold lower than the data attained by a platform with a PTFE membrane and placement of the electrode into electrolyte bulk. This system was applied in the determination of ethanol in complex samples related to the production of ethanol biofuel. It is noteworthy that a simple equation fitted by machine learning was able to provide accurate assays (accuracies from 97 to 102%) by overcoming matrix effect-related interferences on detection performance. Furthermore, preliminary measurements demonstrated the successful coating of the meshes with gold films as an alternative raw electrode material and the monitoring of HCl utilizing Au-coated SSWMs. These strategies extend the applicability of the platform that may help to develop valuable volatile sensing solutions.

3D micromixer for nanoliposome synthesis: a promising advance in high mass productivity.

This paper addresses an important breakthrough in the high mass production of liposomes by microfluidics technology. We investigated the synthesis of liposomes using a high flow rate microfluidic device (HFR-MD) with a 3D-twisted cross-sectional microchannel to favor chaotic advection. A simple construction scaffold technique was used to manufacture the HFR-MD. The synthesis of liposomes combined the effects of high flow and high concentration of lipids, resulting in high mass productivity (2.27 g of lipid per h) which, to our knowledge, has never been registered by only one microdevice. We assessed the effects of the flow rate ratio (FRR), total flow rate (TFR), and lipid concentration on the liposome physicochemical properties. HFR-MD liposomes were monodisperse (0.074) with a size around 100 nm under the condition of an FRR of 1 (50% v/v ethanol) and TFR of 5 ml min-1 (expandable to 10 ml min-1). We demonstrated that the mixing conditions are not the only parameter controlling liposome synthesis using experimental and computational fluid dynamics analysis. A vacuum concentrator was used for ethanol removal, and there is no further modification after processing in accordance with the structural (SAXS) and morphological (cryo-TEM) analysis. Hence, the HFR-MD can be used to prepare nanoliposomes. It emerges as an innovative tool with high mass production.

Inexpensive and nonconventional fabrication of microfluidic devices in PMMA based on a soft-embossing protocol.

This study describes an inexpensive and nonconventional soft-embossing protocol to produce microfluidic devices in poly(methyl methacrylate) (PMMA). The desirable microfluidic structure was photo-patterned in a poly(vinyl acetate) (PVAc) film deposited on glass substrate to produce a low-relief master. Then, this template was used to generate a high-relief pattern in stiffened PDMS by increasing of curing agent /monomer ratio (1:5) followed by thermal aging in a laboratory oven (200°C for 24 h). The stiffened PDMS masters were used to replicate microfluidic devices in PMMA based on soft embossing at 220-230°C and thermal sealing at 140°C. Both embossing and sealing stages were performed by using binder clips. The proposed protocol has ensured the replication of microfluidic devices in PMMA with great fidelity (>94%). Examples of MCE devices, droplet generator devices and spot test array were successfully demonstrated. For testing MCE devices, a mixture containing inorganic cations was selected as model and the achieved analytical performance did not reveal significant difference from commercial PMMA devices. Water droplets were successfully generated in an oil phase at rate of ca. 60 droplets/min (fixing the continuous phase flow rate at 100 µL/h) with size of ca. 322 ± 6 µm. Glucose colorimetric assay was performed on spot test devices and good detectability level (5 µmol/L) was achieved. The obtained results for two artificial serum samples revealed good agreement with the certified concentrations. Based on the fabrication simplicity and great analytical performance, the proposed soft-embossing protocol may emerge as promising approach for manufacturing PMMA devices.

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.

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.

Monitoring the Surface Chemistry of Functionalized Nanomaterials with a Microfluidic Electronic Tongue.

Advances in nanomaterials have led to tremendous progress in different areas with the development of high performance and multifunctional platforms. However, a relevant gap remains in providing the mass-production of these nanomaterials with reproducible surfaces. Accordingly, the monitoring of such materials across their entire life cycle becomes mandatory to both industry and academy. In this paper, we use a microfluidic electronic tongue (e-tongue) as a user-friendly and cost-effective method to classify nanomaterials according to their surface chemistry. The chip relies on a new single response e-tongue with association of capacitors in parallel, which consisted of stainless steel microwires coated with SiO2, NiO2, Al2O3, and Fe2O3 thin films. Utilizing impedance spectroscopy and a multidimensional projection technique, the chip was sufficiently sensitive to distinguish silica nanoparticles and multiwalled carbon nanotubes dispersed in water in spite of the very small surface modifications induced by distinct functionalization and oxidation extents, respectively. Flow analyses were made acquiring the analytical readouts in a label-free mode. The device also allowed for multiplex monitoring in an unprecedented way to speed up the tests. Our goal is not to replace the traditional techniques of surface analysis, but rather propose the use of libraries from e-tongue data as benchmark for routine screening of modified nanomaterials in industry and academy.