Chronic lower extremity wounds (diabetic foot ulcers) are a serious and prevalent complication of diabetes. These wounds exhibit low healing rates and present a high risk of amputation. Current diagnostic options for foot ulcers are limited to macroscopic wound analysis such as wound depth, implicated tissues, and infection. Molecular diagnostics promises to improve foot ulcer diagnosis, staging, and assessment of the treatment response. In this perspective, we report recent progress in understanding the pathophysiology of diabetic wound healing and point to recently emerged novel molecular targets for wound diagnostics. We discuss selected diagnostic wound dressings under preclinical development that detect one or several inflammatory markers, bacterial secretions, hyperglycemia, and mechanical stress. We also highlight key translational challenges of investigational diagnostic bandages for diabetic foot ulcers.

Calcite dissolution kinetics at the single particle scale are determined. It is demonstrated that at high undersaturation and in the absence of inhibitors the particulate mineral dissolution rate is controlled by a saturated calcite surface in local equilibrium with dissolved Ca2+ and CO32– coupled with rate determining diffusive transport of the ions away from the surface. Previous work is revisited and inconsistencies arising from the assumption of a surface-controlled reaction are highlighted. The data have implications for ocean modeling of climate change.

Online techniques for the quantitative analysis of reaction products have many advantages over offline methods. However, owing to the low product formation rates in electrochemical reactions, few of these techniques can be coupled to electrochemistry. An exception is differential electrochemical mass spectrometry (DEMS), which gains increasing popularity not least because of its high time resolution in the sub-second regime. DEMS is often combined with a dual thin-layer cell (a two-compartment flow cell), which helps to mitigate a number of problems that arise due to the existence of a vacuum|electrolyte interface. However, the efficiency with which this cell transfers volatile reaction products into the vacuum of the mass spectrometer is far below 100%. Therefore, a calibration constant that considers not only the sensitivity of the DEMS setup but also the transfer efficiency of the dual thin-layer cell is needed to translate the signals observed in the mass spectrometer into electrochemical product formation rates. However, it can be challenging or impossible to design an experiment that yields such a calibration constant. Here, we show that the transfer efficiency of the dual thin-layer cell depends on the diffusion coefficient of the analyte. Based on this observation, we suggest a two-point calibration method. That is, a plot of the logarithm of the transfer efficiencies determined for H2 and O2 versus the logarithm of their diffusion coefficients defines a straight line. Extrapolation of this line to the diffusion coefficient of another analyte yields a good estimate of its transfer efficiency. This is a versatile and easy calibration method, because the transfer efficiencies of H2 and O2 are readily accessible for a large range of electrode–electrolyte combinations.

L-DOPA (levodopa) is a therapeutic agent which is the most effective medication for treating Parkinson’s disease, but it needs dose optimization, and therefore its analytical determination is required. Laboratory analytical instruments can be routinely used to measure L-DOPA but are not always available in clinical settings and traditional research laboratories, and they also have slow result delivery times and high costs. The use of electroanalytical sensing overcomes these problems providing a highly sensitivity, low-cost, and readily portable solution. Consequently, we overview the electroanalytical determination of L-DOPA reported throughout the literature summarizing the endeavors toward sensing L-DOPA, and we offer insights into future research opportunities.

Square wave voltammetry (SWV) is a voltammetric technique for measuring Faradaic current while minimizing contributions from non-Faradaic processes. In square wave voltammetry, the potential waveform applied to a working electrode and the current sampling protocols followed are designed to minimize contributions from non-Faradaic processes (i.e., double layer charging) to improve voltammetric sensitivity. To achieve this, the current is measured at the end of each forward and reverse potential pulse after allowing time for non-Faradaic currents to decay exponentially. A consequence of sampling current at the end of a potential pulse is that the current data from the preceding time of the potential pulse are discarded. These discarded data can provide information about the non-Faradaic contributions as well as information about the redox system including charge transfer rates. In this paper, we introduce continuous square wave voltammetry (cSWV), which utilizes the continuous collection of current to maximize the information content obtainable from a single voltammetry sweep eliminating the need for multiple scans. cSWV enables acquiring a multitude of voltammograms corresponding to various frequencies and, thus, different scan rates from a single sweep. An application that benefits significantly from cSWV is conformation switching, functional nucleic acid sensors. We demonstrate the utility of cSWV on two representative small molecules targeting electrochemical, aptamer-based sensors. Moreover, we show that cSWV provides comparable results to those obtained from traditional square wave voltammetry, but with cSWV, we are able to acquire dynamic information about the sensor surfaces enabling rapid calibration and optimization of sensing performance. We also demonstrate cSWV on soluble redox markers. cSWV can potentially become a mainstay technique in the field of conformation switching sensors.

The coupling of enzymes and/or intact bacteria with electrodes has been vastly investigated due to the wide range of existing applications. These span from biomedical and biosensing to energy production purposes and bioelectrosynthesis, whether for theoretical research or pure applied industrial processes. Both enzymes and bacteria offer a potential biotechnological alternative to noble/rare metal-dependent catalytic processes. However, when developing these biohybrid electrochemical systems, it is of the utmost importance to investigate how the approaches utilized to couple biocatalysts and electrodes influence the resulting bioelectrocatalytic response. Accordingly, this tutorial review starts by recalling some basic principles and applications of bioelectrochemistry, presenting the electrode and/or biocatalyst modifications that facilitate the interaction between the biotic and abiotic components of bioelectrochemical systems. Focus is then directed toward the methods used to evaluate the effectiveness of enzyme/bacteria–electrode interaction and the insights that they provide. The basic concepts of electrochemical methods widely employed in enzymatic and microbial electrochemistry, such as amperometry and voltammetry, are initially presented to later focus on various complementary methods such as spectroelectrochemistry, fluorescence spectroscopy and microscopy, and surface analytical/characterization techniques such as quartz crystal microbalance and atomic force microscopy. The tutorial review is thus aimed at students and graduate students approaching the field of enzymatic and microbial electrochemistry, while also providing a critical and up-to-date reference for senior researchers working in the field.

The majority of carbon based transmission electron microscopy (TEM) platforms (grids) have a significant sp2 carbon component. Here, we report a top down fabrication technique for producing freestanding, robust, electron beam transparent and conductive sp3 carbon substrates from boron doped diamond (BDD) using an ion milling/polishing process. X-ray photoelectron spectroscopy and electrochemical measurements reveal the sp3 carbon character and advantageous electrochemical properties of a BDD electrode are retained during the milling process. TEM diffraction studies show a dominant (110) crystallographic orientation. Compared with conventional carbon TEM films on metal supports, the BDD-TEM electrodes offer superior thermal, mechanical and electrochemical stability properties. For the latter, no carbon loss is observed over a wide electrochemical potential range (up to 1.80 V vs RHE) under prolonged testing times (5 h) in acid (comparable with accelerated stress testing protocols). This result also highlights the use of BDD as a corrosion free electrocatalyst TEM support for fundamental studies, and in practical energy conversion applications. High magnification TEM imaging demonstrates resolution of isolated, single atoms on the BDD-TEM electrode during electrodeposition, due to the low background electron scattering of the BDD surface. Given the high thermal conductivity and stability of the BDD-TEM electrodes, in situ monitoring of thermally induced morphological changes is also possible, shown here for the thermally induced crystallization of amorphous electrodeposited manganese oxide to the electrochemically active γ-phase.

High-resolution X-ray computed tomography (CT) has become an invaluable tool in battery research for its ability to probe phase distributions in sealed samples. The Cartesian coordinates used in describing the CT image stack are not appropriate for understanding radial dependencies, like that seen in bobbin-type batteries. The most prominent of these bobbin-type batteries is alkaline Zn–MnO2, which dominates the primary battery market. To understand material radial dependencies within these batteries, a method is presented to approximate the Cartesian coordinates of CT data into pseudo-cylindrical coordinates. This is important because radial volume fractions are the output of computational battery models, and this will allow the correlation of a battery model to CT data. A selection of 10 anodes inside Zn–MnO2 AA batteries are used to demonstrate the method. For these, the pseudo-radius is defined as the relative distance in the anode between the central current collecting pin and the separator. Using these anodes, we validate that this method results in averaged one-dimensional material profiles that, when compared to other methods, show a better quantitative match to individual local slices of the anodes in the polar θ-direction. The other methods tested are methods that average to an absolute center point based on either the pin or the separator. The pseudo-cylindrical method also corrects for slight asymmetries observed in bobbin-type batteries because the pin is often slightly off-center and the separator often has a noncircular shape.

With the demands of the high-throughput assay of biomarkers of ultralow concentrations in clinics, a 36-channel instrument utilizing immunomagnetic reduction (IMR) has been developed. The instrument involves the use of a high-Tc superconducting-quantum-interference-device (SQUID) magnetometer to detect the signals due to the associations between target biomarker molecules and the antibody-functionalized magnetic nanoparticles in the reagent of IMR. In addition to illustrating the design and the measurements of the instrument, the assay characterizations for eight kinds of biomarkers related to neurodegenerative disease are investigated. Furthermore, the assay results among three independent instruments were compared. For an instrument, the channel-to-channel variations in measured concentrations of biomarkers are within a range of 2.09 to 5.62%. The assay accuracy was found to be from 99 to 103.7%. The p values in measured concentrations for any of the tested biomarkers were higher than 0.05 among the three instruments. The results demonstrate high throughput, high stability, and high consistency for the SQUID-IMR instruments.

Lyme disease, caused by infection with pathogenic Borrelia bacteria, has emerged as a pervasive illness throughout North America and many other regions of the world in recent years, owing in part to climate-mediated habitat expansion of the tick vectors. Standard diagnostic testing has remained largely unchanged over the past several decades and is indirect, relying on detection of antibodies against the Borrelia pathogen, rather than detection of the pathogen itself. The development of new rapid, point-of-care tests for Lyme disease that directly detects the pathogen could drastically improve patient health by enabling faster and more frequent testing that could better inform patient treatment. Here, we describe a proof-of-concept electrochemical sensing approach to the detection of the Lyme disease-causing bacteria, which utilizes a biomimetic electrode to interact with the Borrelia bacteria that induce impedance alterations. In addition, the catch-bond mechanism between bacterial BBK32 protein and human fibronectin protein, which exhibits improved bond strength with increased tensile force, is tested within an electrochemical injection flow-cell to achieve Borrelia detection under shear stress.

A spectroelectrochemical cell is described that enables confocal Raman microscopy studies of electrode-supported films. The confocal probe volume (∼1 μm3) was treated as a fixed-volume reservoir for the observation of potential-induced changes in chemical composition at microscopic locations within an ∼20 μm thickness layer of a redox polymer cast onto a 3 mm diameter carbon disk electrode. Using a Raman system with high collection efficiency and wavelength reproducibility, spectral subtraction achieved excellent rejection of background interferences, opening opportunities for measuring within micrometer-scale thickness redox films on widely available, low-cost, and conventional carbon disk electrodes. The cell performance and spectral difference technique are demonstrated in experiments that detect transformations of redox-active molecules exchanged into electrode-supported ionomer membranes. The in situ measurements were sensitive to changes in the film oxidation state and swelling/deswelling of the polymer framework in response to the uptake and discharge of charge-compensating electrolyte ions. The studies lay a foundation for confocal Raman microscopy as a quantitative in situ probe of processes within electrode-immobilized redox polymers under development for a range of applications, including electrosynthesis, energy conversion, and chemical sensing.

If someone asks you to list the names of famous scientific women, could you easily name at least 5 of them? Hard, right? Scientists like Ada Lovelace, Rosalind Franklin, Margarita Salas, Jane Goodall, and Donna Strickland, among other women, have made fundamental contributions to science and technology. Yet, many people are unfamiliar with these names and those of the many other women who have changed the face of science. The fact that few individuals realize this shows how gender inequality affects our society, including in STEM fields. Throughout history, social prejudices have not allowed women to be valued or recognized for their efforts, preventing them from gaining the respect and attention they deserve. Latin America enjoys biodiversity, cultural richness, and talented people. However, some members of the Latin American community cannot fully develop their talents due to political and economic issues. Naturally, it is hard for everybody to work in STEM areas. But, for Latin-American women, it is a heroic act! As Latin Americans and scientists, we recognize the enormous challenge faced by Latin American people interested in pursuing STEM education and careers, especially for minority groups. Our cover art is inspired by a feminist and sorority perspective (Figure 1). The women at the bottom of the cover image represent all the women in STEM who aim to have a place in these fields and every day struggle against sexism, gender-based violence, and discouraging comments that can harm and shatter hearts and minds. They all fight not only for their own aspirations but also for the dreams of future generations of women. Figure 1. Mariana D. Avila-Huerta and Diana L. Mancera-Zapata, authors of this Editorial and cover artwork encouraging Latin American women in STEM to “reach for the stars”. We include the DNA strands in the image because your DNA contains all the information that makes you yourself, defining you from a biological perspective. In addition, the structure of the DNA strand resembles stairs, which may help you ascend the STEM path to reach your dreams. Every effort you put into your career as a woman is a brick to build a more equitable world. Every success that you achieve has an impact on the girls that want to follow in your footsteps. The star represents every little girl’s dream, which she hopes to achieve thanks to the support of all the women who have walked on that path before. We also want to illustrate the importance of having female role models that inspire little girls to pursue STEM education and careers. In addition, we highlight the importance of women in a diverse and inclusive environment, showcasing the career opportunities available to the younger generations of women. We hope this message can reach Latin American women in STEM, not only to recognize their efforts and achievements but to cheer them on and inspire them to continue changing the world. We acknowledge our mentor, Dr. Eden Morales-Narváez, who encouraged and supported us to participate in the DEIR Cover Art program; he helped us to believe in our artistic skills, invited us to participate in this initiative, and guided us on this path. This article has not yet been cited by other publications. Figure 1. Mariana D. Avila-Huerta and Diana L. Mancera-Zapata, authors of this Editorial and cover artwork encouraging Latin American women in STEM to “reach for the stars”.

Extracting information from experimental measurements in the chemical sciences typically requires curve fitting, deconvolution, and/or solving the governing partial differential equations via numerical (e.g., finite element analysis) or analytical methods. However, using numerical or analytical methods for high-throughput data analysis typically requires significant postprocessing efforts. Here, we show that deep learning artificial neural networks can be a very effective tool for extracting information from experimental data. As an example, reactivity and topography information from scanning electrochemical microscopy (SECM) approach curves are highly convoluted. This study utilized multilayer perceptrons and convolutional neural networks trained on simulated SECM data to extract kinetic rate constants of catalytic substrates. Our key findings were that multilayer perceptron models performed very well when the experimental data were close to the ideal conditions with which the model was trained. However, convolutional neural networks, which analyze images as opposed to direct data, were able to accurately predict the kinetic rate constant of Fe-doped nickel (oxy)hydroxide catalyst at different applied potentials even though the experimental approach curves were not ideal. Due to the speed at which machine learning models can analyze data, we believe this study shows that artificial neural networks could become powerful tools in high-throughput data analysis.

Ultramicroelectrode (UME), or, equivalently, microelectrode, probes are increasingly used for single-cell measurements of cellular properties and processes, including physiological activity, such as metabolic fluxes and respiration rates. Major challenges for the sensitivity of such measurements include: (i) the relative magnitude of cellular and UME fluxes (manifested in the current); and (ii) issues around the stability of the UME response over time. To explore the extent to which these factors impact the precision of electrochemical cellular measurements, we undertake a systematic analysis of measurement conditions and experimental parameters for determining single cell respiration rates via the oxygen consumption rate (OCR) in single HeLa cells. Using scanning electrochemical microscopy (SECM), with a platinum UME as the probe, we employ a self-referencing measurement protocol, rarely employed in SECM, whereby the UME is repeatedly approached from bulk solution to a cell, and a short pulse to oxygen reduction reaction (ORR) potential is performed near the cell and in bulk solution. This approach enables the periodic tracking of the bulk UME response to which the near-cell response is repeatedly compared (referenced) and also ensures that the ORR near the cell is performed only briefly, minimizing the effect of the electrochemical process on the cell. SECM experiments are combined with a finite element method (FEM) modeling framework to simulate oxygen diffusion and the UME response. Taking a realistic range of single cell OCR to be 1 × 10–18 to 1 × 10–16 mol s–1, results from the combination of FEM simulations and self-referencing SECM measurements show that these OCR values are at, or below, the present detection sensitivity of the technique. We provide a set of model-based suggestions for improving these measurements in the future but highlight that extraordinary improvements in the stability and precision of SECM measurements will be required if single cell OCR measurements are to be realized.

Measuring structural features of proteins dispersed in buffer solution, in contrast to crystal form, is indispensable in understanding morphological characteristics of the biomolecule in a native environment. We report on the structure and apparent viscosity of unfolded α and β variants of SARS-CoV-2 spike proteins dispersed in buffer solutions. The radius of gyration of the β variant is found to be larger than that of the α variant, while the ab initio computation of one of the possible particle-like bodies is consistent with the small-angle X-ray scattering (SAXS) profiles resembling a conformation similar to the three-dimensional structure of the folded state of the corresponding α and β spike variant. However, a smaller radius of gyration with respect to the predicted folded state of 2.4 and 2.7 is observed for both α and β variants, respectively. Our work complements the structural characterization of spike proteins using cryo-electron microscopy techniques. The measurement/analysis discussed here might be useful for quick and cost-effective evaluation of several protein structures, let alone mutated viral proteins, which is useful for drug discovery/development applications.

Sea spray aerosol (SSA) is one of the largest global sources of atmospheric aerosol, but little is known about SSA generated in coastal regions with salinity gradients near estuaries and river outflows. SSA particles are chemically complex with substantial particle-to-particle variability due to changes in water temperature, salinity, and biological activity. In previous studies, the ability to resolve the aerosol composition to the level of individual particles has proven necessary for the accurate parameterization of the direct and indirect aerosol effects; therefore, measurements of individual SSA particles are needed for the characterization of this large source of atmospheric aerosol. An integrated analytical measurement approach is required to probe the chemical composition of individual SSA particles. By combining complementary vibrational microspectroscopic (Raman and optical photothermal infrared, O-PTIR) measurements with elemental information from computer-controlled scanning electron microscopy with energy-dispersive X-ray analysis (CCSEM–EDX), we gained unique insights into the individual particle chemical composition and morphology. Herein, we analyzed particles from four experiments on laboratory-based SSA production using coastal seawater collected in January 2018 from the Gulf of Maine. Individual salt particles were enriched in organics compared to that in natural seawater, both with and without added microalgal filtrate, with greater enrichment observed for smaller particle sizes, as evidenced by higher carbon/sodium ratios. Functional group analysis was carried out using the Raman and infrared spectra collected from individual SSA particles. Additionally, the Raman spectra were compared with a library of Raman spectra consisting of marine-derived organic compounds. Saccharides, followed by fatty acids, were the dominant components of the organic coatings surrounding the salt cores of these particles. This combined Raman, infrared, and X-ray spectroscopic approach will enable further understanding of the factors determining the individual particle composition, which is important for understanding the impacts of SSA produced within estuaries and river outflows, as well as areas of snow and ice melt.

Rapid antigen tests have become a widely used COVID-19 diagnostic tool with demand accelerating in response to the highly contagious SARS-CoV-2 Omicron variant. Hundreds of such test kits are approved for use worldwide, predominantly reporting on the presence of the viral nucleocapsid (N) protein, yet the comparability among manufacturers remains unclear and the need for reference standards is recognized. To address this lack of standardization, the National Research Council Canada has developed a SARS-CoV-2 nucleocapsid protein reference material solution, NCAP-1. Reference value determination for N protein content was realized by amino acid analysis (AAA) via double isotope dilution liquid chromatography–tandem mass spectrometry (LC-ID-MS/MS) following acid hydrolysis of the protein, in conjunction with UV spectrophotometry based on tryptophan and tyrosine absorbance at 280 nm. The homogeneity of the material was established through spectrophotometric absorbance readings at 280 nm. The molar concentration of the N protein in NCAP-1 was 10.0 ± 1.9 μmol L–1 (k = 2, 95% confidence interval). Reference mass concentration and mass fraction values were subsequently calculated using the protein molecular weight and density of the NCAP-1 solution. Changes to protein higher-order structure, probed by size-exclusion liquid chromatography (LC-SEC) with UV detection, were used to evaluate transportation and storage stabilities. LC-SEC revealed nearly 90% of the N protein in the material is present as a mixture of hexamers and tetramers. The remaining low molecular weight species (<30 kDa) were interrogated by top-down mass spectrometry and determined to be autolysis products homologous to those previously documented for N protein of the original SARS-CoV [ Biochem. Biophys. Res. Commun. 2008t, 377, 429−433].

For decades, employing cyclic voltammetry for mechanistic investigation has demanded manual inspection of voltammograms. Here, we report a deep-learning-based algorithm that automatically analyzes cyclic voltammograms and designates a probable electrochemical mechanism among five of the most common ones in homogeneous molecular electrochemistry. The reported algorithm will aid researchers’ mechanistic analyses, utilize otherwise elusive features in voltammograms, and experimentally observe the gradual mechanism transitions encountered in electrochemistry. An automated voltammogram analysis will aid the analysis of complex electrochemical systems and promise autonomous high-throughput research in electrochemistry with minimal human interference.

A hybrid catalytic system composed of copper (I)-oxide-derived copper nanocenters immobilized within the network of tungsten oxide nanowires has exhibited electrocatalytic activity toward CO2 reduction in an acid medium (0.5 mol dm–3 H2SO4). The catalytic system facilitates conversion of CO2 to methanol and is fairly selective with respect to the competing hydrogen evolution. The preparative procedure has involved voltammetric electroreduction of Cu2O toward the formation and immobilization of catalytic Cu sites within the hexagonal structures of WO3 nanowires which are simultaneously partially reduced to mixed-valence hydrogen tungsten (VI, V) oxide bronzes, HxWO3, coexisting with sub-stoichiometric tungsten (VI, IV) oxides, WO3–y. After the initial loss of Cu through its dissolution to Cu2+ during positive potential scanning up to 1 V (vs RHE), the remaining copper is not electroactive and seems to be trapped within in the network of hexagonal WO3. Using the ultramicroelectrode-based probe, evidence has also been provided that partially reduced nonstoichiometric tungsten oxides induce reduction of CO2 to the CO-type reaction intermediates. The chronocoulometric data are consistent with the view that existence of copper sites dispersed in WO3 improves electron transfers and charge propagation within the hybrid catalytic layer. The enhanced tolerance of the catalyst to the competitive hydrogen evolution during CO2R should be explained in terms of the ability of HxWO3 to consume protons and absorb hydrogen as well as to shift the proton discharge at Cu toward more negative potentials. However, the capacity of WO3 to interact with catalytic copper and to adsorb CO-type reaction intermediates is expected to facilitate removal of the poisoning CO-type adsorbates from Cu sites.

This paper presents a simple and robust model to describe the wet adhesion of the AFM tip and substrate joined by a liquid bridge. The effects of contact angles, wetting circle radius, the volume of a liquid bridge, the gap between the AFM tip and substrate, environmental humidity, and tip geometry on the capillary force are studied. To model capillary forces, while a circular approximation for the meniscus of the bridge is assumed, the combination of the capillary adhesion due to the pressure difference across the free surface and the vertical component of the surface tension forces acting tangentially to the interface along the contact line is utilized. Finally, the validity of the proposed theoretical model is verified using numerical analysis and available experimental measurements. The results of this study can provide a basis to model the hydrophobic and hydrophilic tip/surfaces and study their effect on adhesion force between the AFM tip and the substrate.