Simultaneous Counting of Molecules in the Halo and Dense-Core of Nanovesicles by Regulating Dynamics of Vesicle Opening

Hydrodynamics-Controlled Single-Particle Electrocatalysis

Electrocatalysis is considered promising in renewable energy conversion and storage, yet numerous efforts rely on catalyst design to advance catalytic activity. Herein, a hydrodynamic single-particle electrocatalysis methodology is developed by integrating collision electrochemistry and microfluidics to improve the activity of an electrocatalysis system. As a proof-of-concept, hydrogen evolution reaction (HER) is electrocatalyzed by individual palladium nanoparticles (Pd NPs), with the development of microchannel-based ultramicroelectrodes. The controlled laminar flow enables the precise delivery of Pd NPs to the electrode-electrolyte interface one by one. Compared to the diffusion condition, hydrodynamic collision improves the number of active sites on a given electrode by 2 orders of magnitude. Furthermore, forced convection enables the enhancement of proton mass transport, thereby increasing the electrocatalytic activity of each single Pd NP. It turns out that the improvement in mass transport increases the reaction rate of HER at individual Pd NPs, thus a phase transition without requiring a high overpotential. This study provides new avenues for enhancing electrocatalytic activity by altering operating conditions, beyond material design limitations.

Emerging Data Processing Methods for Single-Entity Electrochemistry

Single-entity electrochemistry is a powerful tool that enables the study of electrochemical processes at interfaces and provides insights into the intrinsic chemical and structural heterogeneities of individual entities. Signal processing is a critical aspect of single-entity electrochemical measurements and can be used for data recognition, classification, and interpretation. In this review, we summarize the recent five-year advances in signal processing techniques for single-entity electrochemistry and highlight their importance in obtaining high-quality data and extracting effective features from electrochemical signals, which are generally applicable in single-entity electrochemistry. Moreover, we shed light on electrochemical noise analysis to obtain single-molecule frequency fingerprint spectra that can provide rich information about the ion networks at the interface. By incorporating advanced data analysis tools and artificial intelligence algorithms, single-entity electrochemical measurements would revolutionize the field of single-entity analysis, leading to new fundamental discoveries.

Amperometry and Electron Microscopy show Stress Granules Induce Homotypic Fusion of Catecholamine Vesicles

An overreactive stress granule (SG) pathway and long-lived, stable SGs formation are thought to participate in the progress of neurodegenerative diseases (NDs). To understand if and how SGs contribute to disorders of neurotransmitter release in NDs, we examined the interaction between extracellular isolated SGs and vesicles. Amperometry shows that the vesicular content increases and dynamics of vesicle opening slow down after vesicles are treated with SGs, suggesting larger vesicles are formed. Data from transmission electron microscopy (TEM) clearly shows that a portion of large dense-core vesicles (LDCVs) with double/multiple cores appear, thus confirming that SGs induce homotypic fusion between LDCVs. This might be a protective step to help cells to survive following high oxidative stress. A hypothetical mechanism is proposed whereby enriched mRNA or protein in the shell of SGs is likely to bind intrinsically disordered protein (IDP) regions of vesicle associated membrane protein (VAMP) driving a disrupted membrane between two closely buddled vesicles to fuse with each other to form double-core vesicles. Our results show that SGs induce homotypic fusion of LDCVs, providing better understanding of how SGs intervene in pathological processes and opening a new direction to investigations of SGs involved neurodegenerative disease.

Multi-Spatiotemporal Probing of Neurochemical Events by Advanced Electrochemical Sensing Methods

Neurochemical events involving biosignals of different time and space dimensionalities constitute the complex basis of neurological functions and diseases. In view of this fact, electrochemical measurements enabling real-time quantification of neurochemicals at multiple levels of spatiotemporal resolution can provide informative clues to decode the molecular networks bridging vesicles and brains. This Minireview focuses on how scientific questions regarding the properties of single vesicles, neurotransmitter release kinetics, interstitial neurochemical dynamics, and multisignal interconnections in vivo have driven the design of electrochemical nano/microsensors, sensing interface engineering, and signal/data processing. An outlook for the future frontline in this realm will also be provided.

Chemical Imaging and Analysis of Single Nerve Cells by Secondary Ion Mass Spectrometry Imaging and Cellular Electrochemistry

A nerve cell is a unit of neuronal communication in the nervous system and is a heterogeneous molecular structure, which is highly mediated to accommodate cellular functions. Understanding the complex regulatory mechanisms of neural communication at the single cell level requires analytical techniques with high sensitivity, specificity, and spatial resolution. Challenging technologies for chemical imaging and analysis of nerve cells will be described in this review. Secondary ion mass spectrometry (SIMS) allows for non-targeted and targeted molecular imaging of nerve cells and synapses at subcellular resolution. Cellular electrochemistry is well-suited for quantifying the amount of reactive chemicals released from living nerve cells. These techniques will also be discussed regarding multimodal imaging approaches that have recently been shown to be advantageous for the understanding of structural and functional relationships in the nervous system. This review aims to provide an insight into the strengths, limitations, and potentials of these technologies for synaptic and neuronal analyses.