Suppressive effects of resveratrol treatment on the intrinsic evoked excitability of CA1 pyramidal neurons

Objective: Resveratrol, a phytoalexin, has a wide range of desirable biological actions. Despite a growing body of evidence indicating that resveratrol induces changes in neuronal function, little effort, if any, has been made to investigate the cellular effect of resveratrol treatment on intrinsic neuronal properties. Materials and Methods: This experimental study was performed to examine the acute effects of resveratrol (100 μ M) on the intrinsic evoked responses of rat Cornu Ammonis (CA1) pyramidal neurons in brain slices, using whole cell patch clamp recording under current clamp conditions. Results: Findings showed that resveratrol treatment caused dramatic changes in evoked responses of pyramidal neurons. Its treatment induced a significant (P<0.05) increase in the after hyperpolarization amplitude of the first evoked action potential. Resveratrol-treated cells displayed a significantly broader action potential (AP) when compared with either control or vehicle-treated groups. In addition, the mean instantaneous firing frequency between the first two action potentials was significantly lower in resveratrol-treated neurons. It also caused a significant reduction in the time to maximum decay of AP. The rheobase current and the utilization time were both significantly greater following resveratrol treatment. Neurons exhibited a significantly depolarized voltage threshold when exposed to resveratrol. Conclusion: Results provide direct electrophysiological evidence for the inhibitory effects of resveratrol on pyramidal neurons, at least in part, by reducing the evoked neural activity

The Impact of Water on the Lateral Nanostructure of a Deep Eutectic Solvent-Solid Interface

Deep eutectic solvents (DESs) are tuneable solvents with attractive properties for numerous applications. Their structure–property relationships are still under investigation, especially at the solid–liquid interface. Moreover, the influence of water on interfacial nanostructure must be understood for process optimization. Here, we employ a combination of atomic force microscopy and molecular dynamics simulations to determine the lateral and surface-normal nanostructure of the DES choline chloride:glycerol at the mica interface with different concentrations of water. For the neat DES system, the lateral nanostructure is driven by polar interactions. The surface adsorbed layer forms a distinct rhomboidal symmetry, with a repeat spacing of ~0.9 nm, comprising all DES species. The adsorbed nanostructure remains largely unchanged in 75 mol-% DES compared with pure DES, but at 50 mol-%, the structure is broken and there is a compromise between the native DES and pure water structure. By 25 mol-% DES, the water species dominates the adsorbed liquid layer, leaving very few DES species aggregates at the interface. In contrast, the near-surface surface-normal nanostructure, over a depth of ~3 nm from the surface, remains relatively unchanged down to 25 mol-% DES where the liquid arrangement changed. These results demonstrate not only the significant influence that water has on liquid nanostructure, but also show that there is an asymmetric effect whereby water disrupts the nanostructure to a greater degree closer to the surface. This work provides insight into the complex interactions between DES and water and may enhance their optimization for surface-based applications.</jats:p

A systematic comparison of the structural and dynamic properties of commonly used water models for molecular dynamics simulations

Water is a unique solvent that is ubiquitous in biology and present in a variety of solutions, mixtures, and materials settings. It therefore forms the basis for all molecular dynamics simulations of biological phenomena, as well as for many chemical, industrial, and materials investigations. Over the years, many water models have been developed, and it remains a challenge to find a single water model that accurately reproduces all experimental properties of water simultaneously. Here, we report a comprehensive comparison of structural and dynamic properties of 30 commonly used 3-point, 4-point, 5-point, and polarizable water models simulated using consistent settings and analysis methods. For the properties of density, coordination number, surface tension, dielectric constant, self-diffusion coefficient, and solvation free energy of methane, models published within the past two decades consistently show better agreement with experimental values compared to models published earlier, albeit with some notable exceptions. However, no single model reproduced all experimental values exactly, highlighting the need to carefully choose a water model for a particular study, depending on the phenomena of interest. Finally, machine learning algorithms quantified the relationship between the water model force field parameters and the resulting bulk properties, providing insight into the parameter-property relationship and illustrating the challenges of developing a water model that can accurately reproduce all properties of water simultaneously