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Unequivocally, Pb2+ as a harmful substance damaging children’s brain and nerve systems, thereby causing behavior and learning disabilities, should be detected much lower than the elevated blood lead for children, 240 nM, endorsed by US CDC considering the unknown neurotoxic effects, yet the ultralow detection limit up to sub-ppb level remains a challenge due to the intrinsically insufficient sensitivity in the current analytical techniques. Here, we present nanoemulsion (NE)-integrated single-entity electrochemistry (NI-SEE) toward ultrasensitive sensing of blood lead using Pb-ion-selective ionophores inside a NE, i.e., Pb2+-selective NE. Through the high thermodynamic selectivity between Pb2+ and Pb–ionophore IV, and the extremely large partition coefficient for the Pb2+–Pb–ionophore complex inside NEs, we modulate the selectivity and sensitivity of NI-SEE for Pb2+ sensing up to an unprecedentedly low detection limit, 20 ppt in aqueous solutions, and lower limit of quantitation, 40 ppb in blood serums. This observation is supported by molecular dynamics simulations, which clearly corroborate intermolecular interactions, e.g., H-bonding and π*–n, between the aromatic rings of Pb–ionophore and lone pair electrons of oxygen in dioctyl sebacate (DOS), plasticizers of NEs, subsequently enhancing the current intensity in NI-SEE. Moreover, the highly sensitive sensing of Pb2+ is enabled by the appropriate suppression of hydroxyl radical formation during NI-SEE under a cathodic potential applied to a Pt electrode. Overall, the experimentally demonstrated NI-SEE approach and the results position our new sensing technology as potential sensors for practical environmental and biomedical applications as well as a platform to interrogate the stoichiometry of target ion–ionophore recognition inside a NE as nanoreactors. 

ABSTRACT Polymicrobial biofilms are present in many environments particularly in the human oral cavity where they can prevent or facilitate the onset of disease. While recent advances have provided a clear picture of both the constituents and their biogeographic arrangement, it is still unclear what mechanisms of interaction occur between individual species in close proximity within these communities. In this study, we investigated two mechanisms of interaction between the highly abundant supragingival plaque (SUPP) commensalCorynebacterium matruchotiiandStreptococcus mitiswhich are directly adjacent/attachedin vivo. We discovered thatC. matruchotiienhanced the fitness of streptococci dependent on its ability to detoxify streptococcal-produced hydrogen peroxide and its ability to oxidize lactate also produced by streptococci. We demonstrate that the fitness of adjacent streptococci was linked to that ofC. matruchotiiand that these mechanisms support the previously described “corncob” arrangement between these species but that this is favorable only in aerobic conditions. Furthermore, we utilized scanning electrochemical microscopy to quantify lactate production and consumption between individual bacterial cells for the first time, revealing that lactate oxidation provides a fitness benefit toS. mitisnot due to pH mitigation. This study describes mechanistic interactions between two highly abundant human commensals that can explain their observedin vivospatial arrangements and suggest a way by which they may help preserve a healthy oral bacterial community. IMPORTANCEAs the microbiome era matures, the need for mechanistic interaction data between species is crucial to understand how stable microbiomes are preserved, especially in healthy conditions where the microbiota could help resist opportunistic or exogenous pathogens. Here we reveal multiple mechanisms of interaction between two commensals that dictate their biogeographic relationship to each other in previously described structures in human supragingival plaque. Using a novel variation for chemical detection, we observed metabolite exchange between individual bacterial cells in real time validating the ability of these organisms to carry out metabolic crossfeeding at distal and temporal scales observedin vivo. These findings reveal one way by which these interactions are both favorable to the interacting commensals and potentially the host. 

Herein, we feature our recent efforts toward the development and application of nanoelectrochemistry at liquid/liquid interfaces, which are also known as interfaces between two immiscible electrolyte solutions (ITIES). 

ABSTRACT Geographical random forest (GRF) is a recently developed and spatially explicit machine learning model. With the ability to provide more accurate predictions and local interpretations, GRF has already been used in many studies. The current GRF model, however, has limitations in its determination of the local model weight and bandwidth hyperparameters, potentially insufficient numbers of local training samples, and sometimes high local prediction errors. Also, implemented as an R package, GRF currently does not have a Python version which limits its adoption among machine learning practitioners who prefer Python. This work addresses these limitations by introducing theory‐informed hyperparameter determination, local training sample expansion, and spatially weighted local prediction. We also develop a Python‐based GRF model and package, PyGRF, to facilitate the use of the model. We evaluate the performance of PyGRF on an example dataset and further demonstrate its use in two case studies in public health and natural disasters. 

The challenge of site-selectivity must be overcome in many chemical research contexts, including selective functionalization in complex natural products and labeling of one biomolecule in a living system. Synthetic catalysts incorporating molecular recognition domains can mimic naturally-occurring enzymes to direct a chemical reaction to a particular instance of a functional group. We propose that DNA-conjugated small molecule catalysts (DCats), prepared by tethering a small molecule catalyst to a DNA aptamer, are a promising class of reagents for site-selective transformations. Specifically, a DNA-imidazole conjugate able to increase the rate of ester hydrolysis in a target ester by >100-fold compared with equimolar untethered imidazole was developed. Other esters are unaffected. Furthermore, DCat-catalyzed hydrolysis follows enzyme-like kinetics and a stimuli-responsive variant of the DCat enables programmable “turn on” of the desired reaction.