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.

Predicting the formation of NADES using a transformer-based model.

The application of natural deep eutectic solvents (NADES) in the pharmaceutical, agricultural, and food industries represents one of the fastest growing fields of green chemistry, as these mixtures can potentially replace traditional organic solvents. These advances are, however, limited by the development of new NADES which is today, almost exclusively empirically driven and often derivative from known mixtures. To overcome this limitation, we propose the use of a transformer-based machine learning approach. Here, the transformer-based neural network model was first pre-trained to recognize chemical patterns from SMILES representations (unlabeled general chemical data) and then fine-tuned to recognize the patterns in strings that lead to the formation of either stable NADES or simple mixtures of compounds not leading to the formation of stable NADES (binary classification). Because this strategy was adapted from language learning, it allows the use of relatively small datasets and relatively low computational resources. The resulting algorithm is capable of predicting the formation of multiple new stable eutectic mixtures (n = 337) from a general database of natural compounds. More importantly, the system is also able to predict the components and molar ratios needed to render NADES with new molecules (not present in the training database), an aspect that was validated using previously reported NADES as well as by developing multiple novel solvents containing ibuprofen. We believe this strategy has the potential to transform the screening process for NADES as well as the pharmaceutical industry, streamlining the use of bioactive compounds as functional components of liquid formulations, rather than simple solutes.

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.

Removal of metals and inorganics from rendered fat using polyamine-modified cellulose nanocrystals.

Meatpacking and poultry operations produce an enormous amount of co-products including offal, fat, blood, feathers etc. that are collected and processed by the rendering industry into value-added materials such as various protein meals and rendered fat products. Rendered fats (mainly composed of triglycerides from the adipose tissue of animals or used cooking oil from the restaurant industry) are sold for a variety of applications including animal feed formulations. Nonetheless, in the current context of energy scarcity, their use as feedstocks for the generation of renewable fuels including biodiesel and renewable diesel represents a growing market. The diverse composition of the source material can impose significant challenges in terms of compliance, requiring the control (and reduction) of the concentration of elements such as phosphorus, sulfur, calcium, magnesium, sodium, potassium, and other undesirable metals that can otherwise interfere with critical aspects of the refining process or contaminate the renewable fuel products. To address this critical need, we describe the application of poly(ethylenimine)-modified cellulose nanocrystals as a low-cost material for the removal of unwanted metal/inorganic cations from rendered fat. A total of 28 real samples including poultry, white pork grease, and beef tallow were analyzed. Test results showed that the approach can effectively decrease the concentration of the target elements by 95 ± 2%, suggesting that this treatment protocol could dramatically improve the application of rendered fat products for renewable fuel refining.

Correction: Removal of metals and inorganics from rendered fat using polyamine-modified cellulose nanocrystals.

[This corrects the article DOI: 10.1039/D3SU00116D.].

Predicting Antioxidant Synergism via Artificial Intelligence and Benchtop Data.

Lipid oxidation is a major issue affecting products containing unsaturated fatty acids as ingredients or components, leading to the formation of low molecular weight species with diverse functional groups that impart off-odors and off-flavors. Aiming to control this process, antioxidants are commonly added to these products, often deployed as combinations of two or more compounds, a strategy that allows for lowering the amount used while boosting the total antioxidant capacity of the formulation. While this approach allows for minimizing the potential organoleptic and toxic effects of these compounds, predicting how these mixtures of antioxidants will behave has traditionally been one of the most challenging tasks, often leading to simple additive, antagonistic, or synergistic effects. Approaches to understanding these interactions have been predominantly empirically driven but thus far, inefficient and unable to account for the complexity and multifaceted nature of antioxidant responses. To address this current gap in knowledge, we describe the use of an artificial intelligence model based on deep learning architecture to predict the type of interaction (synergistic, additive, and antagonistic) of antioxidant combinations. Here, each mixture was associated with a combination index value (CI) and used as input for our model, which was challenged against a test (n = 140) data set. Despite the encouraging preliminary results, this algorithm failed to provide accurate predictions of oxidation experiments performed in-house using binary mixtures of phenolic antioxidants and a lard sample. To overcome this problem, the AI algorithm was then enhanced with various amounts of experimental data (antioxidant power data assessed by the TBARS assay), demonstrating the importance of having chemically relevant experimental data to enhance the model's performance and provide suitable predictions with statistical relevance. We believe the proposed method could be used as an auxiliary tool in benchmark analysis routines, offering a novel strategy to enable broader and more rational predictions related to the behavior of antioxidant mixtures.

Strategies for capillary electrophoresis: Method development and validation for pharmaceutical and biological applications-Updated and completely revised edition.

This review is in support of the development of selective, precise, fast, and validated capillary electrophoresis (CE) methods. It follows up a similar article from 1998, Wätzig H, Degenhardt M, Kunkel A. "Strategies for capillary electrophoresis: method development and validation for pharmaceutical and biological applications," pointing out which fundamentals are still valid and at the same time showing the enormous achievements in the last 25 years. The structures of both reviews are widely similar, in order to facilitate their simultaneous use. Focusing on pharmaceutical and biological applications, the successful use of CE is now demonstrated by more than 600 carefully selected references. Many of those are recent reviews; therefore, a significant overview about the field is provided. There are extra sections about sample pretreatment related to CE and microchip CE, and a completely revised section about method development for protein analytes and biomolecules in general. The general strategies for method development are summed up with regard to selectivity, efficiency, precision, analysis time, limit of detection, sample pretreatment requirements, and validation.

Lab-on-a-Drone: remote voltammetric analysis of lead in water with real-time data transmission.

The present work describes a laboratory-on-a-drone (Lab-on-a-Drone) developed to perform in situ detection of contaminants in environmental water samples. Toward this goal, the system was mounted on an unmanned aerial vehicle (UAV) (drone) and remotely controlled via Wi-Fi to acquire a water sample, perform the electrochemical detection step, and then send the voltammetry data to a smartphone. This Lab-on-a-Drone system was also able to recharge its battery using a solar cell, greatly increasing the autonomy of the system, even in the absence of a power line. As a proof of concept, the Lab-on-a-Drone was employed for the detection of Pb2+ in environmental waters, using a simple electrochemical cell containing a miniaturized screen-printed boron-doped diamond electrode (SP-BDDE) as a working electrode, an Ag/AgCl as a reference electrode, and a graphite ink as a counter electrode. For quantification purposes, analytical curves were constructed covering a concentration range from 1.0 µg L-1 (4.83 nmol L-1) to 80.0 µg L-1 (386.10 nmol L-1), featuring a detection limit of 0.062 µg L-1 (0.30 nmol L-1). The Lab-on-a-Drone was applied to monitor a water reservoir in the Metropolitan Region of Recife, Brazil. To evaluate its performance regarding accuracy and precision, a reference method based on inductively coupled plasma optical emission spectrometry (ICP-OES) was applied, and the results obtained by both methods showed no statistical differences (t-test at 95% confidence level, n = 3). These results represent the first demonstration of the capabilities of an adapted UAV for the quantification of electroactive environmental contaminant using voltammetry, with real-time data transmission. Thus, the Lab-on-a-Drone makes it possible to reach difficult-to-access environmental reserves and to monitor potentially polluting activity in distant water bodies. Thus, this tool can be used by governments and non-profit organizations to monitor environmental waters using fast, low-cost, process autonomy with accurate and precise data useful to decision making.

Advancements and future directions in cardiac biomarker detection using lateral flow assays.

Lateral flow assays (LFAs) have emerged as one of the most prominent paper-based biosensor platforms for rapidly detecting and quantifying analytes. Their selectivity, cost-effectiveness, efficiency, and simplicity make them ideal candidates for point-of-care (POC) applications, particularly when time-sensitive decisions are needed, such as cardiovascular events. The profound impact of cardiovascular diseases (CVDs), characterized by their high morbidity, mortality, and rehospitalization rates, necessitates an optimized approach for the early detection of cardiac muscle damage. This comprehensive review aims to consolidate the existing scientific literature on LFAs that specifically target cardiovascular biomarkers, including myoglobin and cardiac troponin I, over the past decade. By examining the advancements and findings in this field, valuable insights can be gained regarding the potential and future directions of LFAs in cardiovascular diagnostics.

Rapid Detection of Staphylococcus aureus Using Paper-Derived Electrochemical Biosensors.

Several groups have recently explored the idea of developing electrochemical paper-based wearable devices, specifically targeting metabolites in sweat. While these sensors have the potential to provide a breadth of analytical information, there are several key challenges to address before these sensors can be widely adopted for clinical interventions. Toward this goal, we describe the development of a paper-based electrochemical sensor for the detection of Staphylococcus aureus. Enabling the application, this report describes the use of paper-derived carbon electrodes, which were modified with a thin layer of sputtered gold (that minimizes lateral resistivity and significantly improves the electron transfer process) and with chitosan (used as a binder, to offer flexibility). The resulting material was laser-patterned and applied for the development of an electrochemical biosensor controlled (via a wireless connection) by a custom-built, portable potentiostat. As no interference was observed when exposed to other bacteria or common metabolites, this wearable system (paper-derived electrodes + potentiostat) has the potential to detect the presence of S. aureus in the skin, a commonly misdiagnosed and mistreated infection.

Predicting the Orientation of Adsorbed Proteins Steered with Electric Fields Using a Simple Electrostatic Model.

Under the most common experimental conditions, the adsorption of proteins to solid surfaces is a spontaneous process that leads to a rather compact layer of randomly oriented molecules. However, controlling such orientation is critically important for the development of catalytic surfaces. In this regard, the use of electric fields is one of the most promising alternatives. Our work is motivated by experimental observations that show important differences in catalytic activity of a trypsin-covered surface, which depended on the applied potential during the adsorption. Even though adsorption results from the combination of several processes, we were able to determine that (under the selected conditions) mean-field electrostatics play a dominant role, determining the orientation and yielding a difference in catalytic activity. We simulated the electrostatic potential numerically, using an implicit-solvent model based on the linearized Poisson-Boltzmann equation. This was implemented in an extension of the code PyGBe that included an external electric field, and rendered the electrostatic component of the solvation free energy. Our model (extensions available at the Github repository) allowed estimating the overall affinity of the protein with the surface, and their most likely orientation as a function of the potential applied. Our results show that the active sites of trypsin are, on average, more exposed when the electric field is negative, which agrees with the experimental results of catalytic activity, and confirm the premise that electrostatic interactions can be used to control the orientation of adsorbed proteins.

Dielectric Spectroscopy Can Predict the Effect of External AC Fields on the Dynamic Adsorption of Lysozyme.

This report describes the application of dielectric spectroscopy as a simple and fast way to guide protein adsorption experiments. Specifically, the polarization behavior of a layer of adsorbed lysozyme was investigated using a triangular-wave signal with frequencies varying from 0.5 to 2 Hz. The basic experiment, which can be performed in less than 5 min and with a single sample, not only allowed confirming the susceptibility of the selected protein towards the electric signal but also identified that this protein would respond more efficiently to signals with lower frequencies. To verify the validity of these observations, the adsorption behavior of lysozyme onto optically transparent carbon electrodes was also investigated under the influence of an applied alternating potential. In these experiments, the applied signal was defined by a sinusoidal wave with an amplitude of 100 mV and superimposed to +800 mV (applied as a working potential) and varying the frequency in the 0.1-10000 Hz range. The experimental data showed that the greatest adsorbed amounts of lysozyme were obtained at the lowest tested frequencies (0.1-1.0 Hz), results that are in line with the corresponding dielectric features of the protein.

Taking the leap between analytical chemistry and artificial intelligence: A tutorial review.

The last 10 years have witnessed the growth of artificial intelligence into different research areas, emerging as a vibrant discipline with the capacity to process large amounts of information and even intuitively interact with humans. In the chemical world, these innovations in both hardware and algorithms have allowed the development of revolutionary approaches in organic synthesis, drug discovery, and materials' design. Despite these advances, the use of AI to support analytical purposes has been mostly limited to data-intensive methodologies linked to image recognition, vibrational spectroscopy, and mass spectrometry but not to other technologies that, albeit simpler, offer promise of greatly enhanced analytics now that AI is becoming mature enough to take advantage of them. To address the imminent opportunity of analytical chemists to use AI, this tutorial review aims to serve as a first step for junior researchers considering integrating AI into their programs. Thus, basic concepts related to AI are first discussed followed by a critical assessment of representative reports integrating AI with various sensors, spectroscopies, and separation techniques. For those with the courage (and the time) needed to get started, the review also provides a general sequence of steps to begin integrating AI into their programs.

Use of universal 3D-Printed smartphone spectrophotometer to develop a time-based analysis for hypochlorite.

A fully-functional smartphone-based spectrophotometer was designed and built using 3D printing. The major advantage of this approach is its capacity to be interfaced with a variety of smartphones, allowing the use of the smartphone's camera and display, and regardless of the relative position of the camera. The analytical performance of the device was analyzed using a model dye (crystal violet), leading to a proportional response for concentrations in the 0.06-15.0 mg L-1 range, with a variability of 1.0% (intra-day) and 2.6% (inter-day). To demonstrate the functionality of the device, the degradation process of the dye by sodium hypochlorite was studied. The results obtained were applied to develop a paper-based test for NaClO in sanitation solutions, in which the time required to bleach the dye was used to estimate the concentration of the solution. This device represents a simple and inexpensive tool for everyday laboratory use and could address important analytical challenges in low-income communities and features a versatile arrangement, that is compatible with a wide variety of smartphones and software platforms.

Fast Degradation of Hydrogen Peroxide by Immobilized Catalase to Enable the Use of Biosensors in Extraterrestrial Bodies.

Hydrogen peroxide has been postulated to be present on the surface of Europa and Enceladus. While it could represent a potential source of energy for possible life-forms, H2O2 may also interfere with a number of current detection technologies, including biosensors. To take advantage of the selectivity and portability of these devices, simple and reliable routes to degrade the potential H2O2 present should be developed and implemented to prepare for this possibility. Unfortunately, most of the current approaches for removing H2O2 are slow, may affect the sample, or could interfere with the performance of biosensors. To address these limitations, catalase was immobilized onto silica particles and used as a means to selectively decompose H2O2 prior to the analysis of common biomarkers with a biosensor. For these experiments, glucose, l-leucine, and lactic acid were used as representative examples of biomolecules such as carbohydrates, amino acids, and organic acids, respectively, which could be used as biomarkers on extraterrestrial bodies. While the decomposition reaction between catalase and H2O2 is well known, to our knowledge this is the first instance where catalase has been used in combination with a microfluidic paper-based analytical device (µPAD) to implement selective sample pretreatment.

A Multi-Pump Magnetohydrodynamics Lab-On-A-Chip Device for Automated Flow Control and Analyte Delivery.

This article shows the development of a computer-controlled lab-on-a-chip device with three magnetohydrodynamic (MHD) pumps and a pneumatic valve. The chip was made of a stack of layers of polymethylmethacrylate (PMMA), cut using a laser engraver and thermally bonded. The MHD pumps were built using permanent magnets (neodymium) and platinum electrodes, all of them controlled by an Arduino board and a set of relays. The implemented pumps were able to drive solutions in the open channels with a flow rate that increased proportionally with the channel width and applied voltage. To address the characteristic low pressures generated by this kind of pump, all channels were interconnected. Because the electrodes were immersed in the electrolyte, causing electrolysis and pH variations, the composition and ionic strength of the electrolyte solution were controlled. Additionally, side structures for releasing bubbles were integrated. With this multi-pump and valve solution, the device was used to demonstrate the possibility of performing an injection sequence in a system that resembles a traditional flow injection analysis system. Ultimately, the results demonstrate the possibility of performing injection sequences using an array of MHD pumps that can perform fluid handling in the 0-5 µL s-1 range.

Integrated instrumental analysis teaching platform with smartphone-operated fluorometer.

The present work describes an Integrated Teaching Tool (ITT) to facilitate the learning process in analytical chemistry. The first instrument integrated in the platform to demonstrate the concept is a wireless, portable fluorometer, produced by 3D printing. The low-cost instrument features a Teensy 3.1 board as the microcontroller, a high-power UV-LED, a secondary filter, a photodiode, and simple auxiliary electronic circuits. Modules of the ITT app were designed to manage the instrument and perform data acquisition remotely from any Android smartphone via Bluetooth, plot and transmit the results. Supporting the educational purpose of the platform, examples of basic concepts about fluorescence as well as technical information about the instrument are also provided to be considered for the app, which also allows instructors to assist and evaluate students through push notifications.

Decomposition of Chemical Warfare Agent Simulants Utilizing Pyrolyzed Cotton Balls as Wicks.

A simple method to improve the thermal decomposition of chemical warfare agent simulants is reported. Utilizing pyrolyzed cotton balls as a substrate for the delivery of an incendiary agent into a bulk volume of chemical warfare agent simulants, significant enhancements in the burning rates were achieved with respect to either other wicks or the incendiary agent by itself. To perform the decomposition experiments and follow the reaction in real time, while still addressing the important safety considerations related to experiments involving chemical warfare agent simulants and incendiary agents, a simple instrument was assembled in a laboratory hood, where all experiments were performed. Under ambient conditions, this method was able to enhance the decomposition of simulants for both sulfur mustard (HD) and sarin (GB) chemical warfare agents. Overall, the proposed approach represents one of the simplest and more cost-effective ways to improve the decomposition of these dangerous substances, presenting options for field expedient and low-cost processes that could be applied in the near future to the safe destruction of an actual CWA.

Fluorescent patterning of paper through laser engraving.

While thermal treatment of paper can lead to the formation of aromatic structures via hydrothermal treatment (low temperature) or pyrolysis (high temperature), neither of these approaches allow patterning the substrates. Somewhere in between these two extremes, a handful of research groups have used CO2 lasers to pattern paper and induce carbonization. However, none of the previously reported papers have focused on the possibility to form fluorescent derivatives via laser-thermal engraving. Exploring this possibility, this article describes the possibility of using a CO2 laser engraver to selectively treat paper, resulting in the formation of fluorescent compounds, similar to those present on the surface of carbon dots. To determine the most relevant variables controlling this process, 3 MM chromatography paper was treated using a standard 30 W CO2 laser engraver. Under selected experimental conditions, a blue fluorescent pattern was observed when the substrate was irradiated with UV light (365 nm). The effect of various experimental conditions (engraving speed, engraving power, and number of engraving steps) was investigated to maximize the fluorescence intensity. Through a comprehensive characterization effort, it was determined that 5-(hydroxymethyl)furfural and a handful of related compounds were formed (varying in amount) under all selected experimental conditions. To illustrate the potential advantages of this strategy, that could complement those applications traditionally developed from carbon dots (sensors, currency marking, etc.), a redox-based optical sensor for sodium hypochlorite was developed.

Fabrication of microwell plates and microfluidic devices in polyester films using a cutting printer.

This study reports, for the first time, the possibility to manufacture analytical devices on polyester substrates using a cutting printer. The protocol involves the design of a layout in a graphical software, the cut into polyester films and the lamination against one or multiple polyester films coated with a thermosensitive layer. The feasibility of the proposed approach was demonstrated through the fabrication of 96-microwell plates, 3D microfluidic mixing and distance-based microfluidic devices. The printer has enabled cutting microchannels wider than 300 µm on polyester films and a thickness of 250 µm. Urea and glucose assays were performed on microwell plates aiming for their quantification in artificial urine and serum samples. The presented results revealed good agreement with the expected values. The complexation reaction between Fe2+ and o-phenanthroline was selected as model to investigate the feasibility of the 3D mixing device. Absorbance measurements were recorded for the reaction product performed in both on and off-chip modes. Considering the achieved data, the on-chip mixing exhibited similar behavior when compared to off-chip reaction, thus demonstrating to be efficient to perform mixtures due to the turbulence generated inside three-dimensional channels. Lastly, a distance-based device was designed to detect H2O2 based on the displacement of a dye plug promoted by the oxygen generation using a copper-modified paper sheet. The distance-based peroxymeter revealed a linear behavior in the concentration range between 1 and 5% (v/v) and a LOD equal to 0.5% (65.2 mM). Based on the results herein reported, the proposed method represents a simple and alternative protocol to produce microdevices, using affordable and inexpensive raw materials, within 10 min, and at a cost lower than US$ 0.10 per unit.