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  1. Biological supramolecular assemblies, such as phospholipid bilayer membranes, have been used to demonstrate signal processing via short-term synaptic plasticity (STP) in the form of paired pulse facilitation and depression, emulating the brain’s efficiency and flexible cognitive capabilities. However, STP memory in lipid bilayers is volatile and cannot be stored or accessed over relevant periods of time, a key requirement for learning. Using droplet interface bilayers (DIBs) composed of lipids, water and hexadecane, and an electrical stimulation training protocol featuring repetitive sinusoidal voltage cycling, we show that DIBs displaying memcapacitive properties can also exhibit persistent synaptic plasticity in the form of long-term potentiation (LTP) associated with capacitive energy storage in the phospholipid bilayer. The time scales for the physical changes associated with the LTP range between minutes and hours, and are substantially longer than previous STP studies, where stored energy dissipated after only a few seconds. STP behavior is the result of reversible changes in bilayer area and thickness. On the other hand, LTP is the result of additional molecular and structural changes to the zwitterionic lipid headgroups and the dielectric properties of the lipid bilayer that result from the buildup of an increasingly asymmetric charge distribution at the bilayer interfaces.
    Free, publicly-accessible full text available December 13, 2023
  2. Correction for ‘Interfacial acidity on the strontium titanate surface: a scaling paradigm and the role of the hydrogen bond’ by Robert C. Chapleski, Jr. et al. , Phys. Chem. Chem. Phys. , 2021, 23 , 23478–23485, DOI: 10.1039/D1CP03587H.
  3. A fundamental understanding of acidity at an interface, as mediated by structure and molecule–surface interactions, is essential to elucidate the mechanisms of a range of chemical transformations. While the strength of an acid in homogeneous gas and solution phases is conceptually well understood, acid–base chemistry at heterogeneous interfaces is notoriously more complicated. Using density functional theory and nonlinear vibrational spectroscopy, we present a method to determine the interfacial Brønsted–Lowry acidity of aliphatic alcohols adsorbed on the (100) surface of the model perovskite, strontium titanate. While shorter and less branched alkanols are known to be less acidic in the gas phase and more acidic in solution, here we show that shorter alcohols are less acidic whereas less substituted alkanols are more acidic at the gas–oxide interface. Hydrogen bonding plays a critical role in defining acidity, whereas structure–acidity relationships are dominated by van der Waals interactions between the alcohol and the surface.
  4. Single-cell quantification of RNAs is important for understanding cellular heterogeneity and gene regulation, yet current approaches suffer from low sensitivity for individual transcripts, limiting their utility for many applications. Here we present Hybridization of Probes to RNA for sequencing (HyPR-seq), a method to sensitively quantify the expression of hundreds of chosen genes in single cells. HyPR-seq involves hybridizing DNA probes to RNA, distributing cells into nanoliter droplets, amplifying the probes with PCR, and sequencing the amplicons to quantify the expression of chosen genes. HyPR-seq achieves high sensitivity for individual transcripts, detects nonpolyadenylated and low-abundance transcripts, and can profile more than 100,000 single cells. We demonstrate how HyPR-seq can profile the effects of CRISPR perturbations in pooled screens, detect time-resolved changes in gene expression via measurements of gene introns, and detect rare transcripts and quantify cell-type frequencies in tissue using low-abundance marker genes. By directing sequencing power to genes of interest and sensitively quantifying individual transcripts, HyPR-seq reduces costs by up to 100-fold compared to whole-transcriptome single-cell RNA-sequencing, making HyPR-seq a powerful method for targeted RNA profiling in single cells.