ACS Measurement Science Au最新文献

Peptide substrate reporters are short chains of amino acids designed to act as substrates for enzymes of interest. Combined with capillary electrophoresis and laser-induced fluorescence detection (CE-LIF), they are powerful molecular tools for quantitative measurements of enzyme activity even at the level of single cells. Although most peptide substrate reporters have been optimized for human or murine cells in health-related applications, their performance in nonmammalian organisms remains largely unexplored. In this study, we evaluated three peptide substrate reporters for protein kinase B (PKB) in two eukaryotic microbes, Dictyostelium discoideum and Tetrahymena thermophila, which are evolutionarily distant from mammals and from each other yet express PKB homologues. All three peptide substrate reporters were phosphorylated in lysates from both organisms but with varying phosphorylation kinetics and stability. To demonstrate reporter utility, we used one to screen for and identify the previously unknown stimulus needed to activate PHK5, the PKB homologue in T. thermophila. In D. discoideum, we employed the highly quantitative nature of these assays using CE-LIF to make precise measurements of PKB activity in response to transient stimulation, drug treatment, and genetic mutation. These results underscore the broad applicability of peptide substrate reporters across diverse species while highlighting the need for further research to determine effective peptide stabilization strategies across different biological contexts.

Caffeic acid is a polyphenol of critical importance in plants, involved in a variety of physiological processes including lignin formation, cellular growth, stress response, and external signaling. This small molecule also acts as a powerful antioxidant and thus has therapeutic potential for a variety of health conditions. Traditional methods of detecting caffeic acid lack appropriate temporal resolution to monitor real time concentration changes on a subsecond time scale with nM detection limits. Here we report on the first usage of fast-scan cyclic voltammetry with carbon fiber microelectrodes for the detection of caffeic acid. Through the use of flow injection analysis, the optimal waveform for its detection under acidic conditions at a scan rate of 400 V/s was determined to be sawtooth-shaped, from 0 to 1.4 to −0.4 to 0 V. Signal was linear with concentration up to 1 μM with a sensitivity of 44.8 ± 1.3 nA/μM and a detection limit of 2.3 ± 0.2 nM. The stability of its detection was exceptional, with an average of 0.96% relative standard deviation across 32 consecutive injections. This waveform was also successful in detecting other catechol-based plant antioxidants including 5-chlorogenic acid, oleuropein, rosmarinic acid, chicoric acid, and caffeic acid phenethyl ester. Finally, we show the successful use of fast-scan cyclic voltammetry in monitoring the degradation of caffeic acid by polyphenol oxidase on a subsecond time scale via a novel modification of a Ramsson cell. This work demonstrates that fast-scan cyclic voltammetry can be used to successfully monitor real-time dynamic changes in the concentrations of catechol-containing plant polyphenols.

Analysis of exhaled breath offers a noninvasive approach to understanding the metabolic state of the body. This study focuses on the efficacy of an innovative Electrochemical Hand-held Breathalyzer COVID-19 Sensing Technology (E.Co.Tech) for predicting COVID-19 infection, specifically in populations of never or former light smokers. The electrochemical nose technology used in this device aims to discriminate changes in exhaled nitric oxide levels, which are associated with COVID-19-linked respiratory inflammation. The methodology combines the device with a machine learning-based algorithm trained on a diverse data set of breath profiles from both infected and noninfected individuals. A cohort of 46 participants, consisting of never or former light smokers, was recruited. Each participant was tested using the E.Co.Tech prototype device and an iHealth COVID-19 antigen rapid test. The performance of the device was assessed by calculating sensitivity, specificity, positive predictive value, and negative predictive value (NPV). The results demonstrated high specificity (91.11%) and NPV (97.62%) for the device in this demographic group. This case study underscores the potential of E.Co.Tech as a valuable tool for point-of-care COVID-19 diagnosis, particularly in populations with unique smoking histories. The technology’s high sensitivity and specificity, along with its rapid results, make it a promising candidate for deployment in resource-limited settings and situations where timely detection is crucial for effective public health management. Further large-scale clinical trials and real-world validations are necessary to establish the device’s utility across diverse population groups.

The scanning gas diffusion electrode (S-GDE) half-cell is introduced as a new tool to improve the evaluation of electrodes used in electrochemical energy conversion technologies. It allows both fast screening and fundamental studies of real catalyst layers by applying coupled mass spectrometry techniques such as inductively coupled plasma mass spectrometry and online gas mass spectrometry. Hence, the proposed setup overcomes the limitations of aqueous model systems and full cell-level studies, bridging the gap between the two approaches. In this proof-of-concept work, standard fuel cell electrodes are investigated at elevated oxygen reduction reaction current densities, while dissolved Pt^x+ ions in the electrolyte and gaseous CO₂ in the outlet gas stream are detected to track platinum dissolution and carbon corrosion, respectively. Relevant current densities of up to 0.75 A cm^–2 are demonstrated. The electrochemically active surface area, oxygen reduction reaction activity, and Pt dissolution rates are quantified and benchmarked to the values obtained in the conventional stationary GDE half-cell. Moreover, it is found that Pt dissolution is suppressed when O₂ is purged into the catalyst layer. Overall, this work demonstrates the feasibility of fast fuel cell electrode screening obtaining, complementary to electrochemical, mass spectrometry data necessary in fundamental studies on structure/performance relationships under actual reaction conditions. While Pt/C, in relevance to its fuel cell application, is used in this study, the proposed setup can be applied in water electrolysis, CO₂ conversion, metal-air batteries, and other neighbor technologies.

Among electroanalytical techniques, electrochemical impedance spectroscopy (EIS) offers the unique advantage of a high degree of frequency resolution. This enables EIS to readily deconvolute between the capacitive, resistive, and diffusional processes that underlie electrochemical devices. Here, we report the measurement of impedance spectra of individual, pseudocapacitive nanoparticles. We chose Prussian blue as our model system, as it couples an electron-transfer reaction with sodium ion intercalation─processes which, while intrinsically convoluted, can be readily resolved using EIS. We used a scanning electrochemical cell microscope (SECCM) to isolate single Prussian blue particles in a microdroplet and measured their impedance spectra using the multi-sine, fast Fourier transform technique. In doing so, we were able to extract the exchange current density and sodium ion diffusivity for each particle, which respectively inform on their electronic and ionic conductivities. Surprisingly, these parameters vary by over an order of magnitude between particles and are not correlated to particle size nor to each other. The implication of this apparent heterogeneity is that in a hypothetical battery cathode, one active particle may transfer electrons 10 times faster than its neighbor; another may suffer from sluggish sodium ion transport and have restricted charging rate capabilities compared to a better-performing particle elsewhere in the same electrode. Our results inform on this intrinsic heterogeneity while demonstrating the utility of EIS in future single-particle studies.