Transforming the development and dissemination of cutting-edge microscopy and computation

Long-range proton and hydroxide ion transfer dynamics at the water/CeO2 interface in the nanosecond regime: reactive molecular dynamics simulations and kinetic analysis

The structural properties, dynamical behaviors, and ion transport phenomena at the interface between water and cerium oxide are investigated by reactive molecular dynamics (MD) simulations employing neural network potentials (NNPs). The NNPs are trained to reproduce density functional theory (DFT) results, and DFT-based MD (DFT-MD) simulations with enhanced sampling techniques and refinement schemes are employed to efficiently and systematically acquire training data that include diverse hydrogen-bonding configurations caused by proton hopping events. The water interfaces with two low-index surfaces of (111) and (110) are explored with these NNPs, and the structure and long-range proton and hydroxide ion transfer dynamics are examined with unprecedented system sizes and long simulation times. Various types of proton hopping events at the interface are categorized and analyzed in detail. Furthermore, in order to decipher the proton and hydroxide ion transport phenomena along the surface, a counting analysis based on the semi-Markov process is formulated and applied to the MD trajectories to obtain reaction rates by considering the transport as stochastic jump processes. Through this model, the coupling between hopping events, vibrational motions, and hydrogen bond networks at the interface are quantitatively examined, and the high activity and ion transport phenomena at the water/CeO2 interface are unequivocally revealed in the nanosecond regime.

Live-cell imaging powered by computation

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.

The Role of Host Cell Glycans on Virus Infectivity: The SARS-CoV-2 Case

Glycans are ubiquitously expressed sugars, coating the cell and protein surfaces. They are found on many proteins as either short and branched chains or long chains sticking out from special membrane proteins, known as proteoglycans. This sugar cushion, the glycocalyx, modulates specific interactions and protects the cell. Here it is shown that both the expression of proteoglycans and the glycans expressed on the surface of both the host and virus proteins have a critical role in modulating viral attachment to the cell. A mathematical model using SARS-Cov-2 as an archetypical virus to study the glycan role during infection is proposed. It is shown that this occurs via a tug-of-war of forces. On one side, the multivalent molecular recognition that viral proteins have toward specific host glycans and receptors. On the other side, the glycan steric repulsion that a virus must overcome to approach such specific receptors. By balancing both interactions, viral tropism can be predicted. In other words, the authors can map out the cells susceptible to virus infection in terms of receptors and proteoglycans compositions.

Counteractive Effects of Choline Geranate (CAGE) ILs and Ethanol on Insulin's Stability-A Leap Forward towards Oral Insulin Formulation

Choline geranate (CAGE) ionic liquids (ILs) stabilize insulin, thereby aiding its oral delivery, whereas ethanol (EtOH) affects its stability by disrupting the hydrophobic interactions. In this study, cognizance of the stabilization mechanism of insulin dimer in the presence of both CAGE ILs and EtOH mixtures is achieved through biased and unbiased molecular dynamics (MD) simulations. Here, two order parameters are employed to study the insulin dimer dissociation using well-tempered metadynamics (WT-MetaD). The stability of insulin is found to be strongly maintained until a 0.20 mole fraction of EtOH. Besides, higher concentrations of EtOH marginally affect the insulin stability. Moreover, geranate anions form a higher number of H-bonding interactions with water molecules, which aids insulin stabilization. Conversely, the addition of EtOH minimizes the water-mediated H-bonding interactions of geranate. Additionally, geranate traps the EtOH molecules, thereby preventing the interactions between insulin and EtOH. Furthermore, the free energy landscape (FEL) reveals the absence of dimer dissociation along with noticeable deviations in the distances R and the number of contacts Q. The dimerization free energy of insulin was calculated to be −16.1 kcal/mol at a 0.20 mole fraction of EtOH. Moreover, increments in mole fractions of EtOH effectuate a decrease in the insulin stability. Thus, the present study represents CAGE ILs as efficient insulin dimer stabilizes at low concentrations of EtOH.

Multi-Scale Modelling of Aggregation of TiO2 Nanoparticle Suspensions in Water

Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO₂ nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large-scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetics described by the Smoluchowski theory. Ultimately, molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, enabling safe design strategies.

Synthesis of paracrystalline diamond

Solids in nature can be generally classified into crystalline and non-crystalline states^1-7, depending on whether long-range lattice periodicity is present in the material. The differentiation of the two states, however, could face fundamental challenges if the degree of long-range order in crystals is significantly reduced. Here we report a paracrystalline state of diamond that is distinct from either crystalline or amorphous diamond^8-10. The paracrystalline diamond reported in this work, consisting of sub-nanometre-sized paracrystallites that possess a well-defined crystalline medium-range order up to a few atomic shells^4,5,11-13, was synthesized in high-pressure high-temperature conditions (for example, 30 GPa and 1,600 K) employing face-centred cubic C₆₀ as a precursor. The structural characteristics of the paracrystalline diamond were identified through a combination of X-ray diffraction, high-resolution transmission microscopy and advanced molecular dynamics simulation. The formation of paracrystalline diamond is a result of densely distributed nucleation sites developed in compressed C₆₀ as well as pronounced second-nearest-neighbour short-range order in amorphous diamond due to strong sp³ bonding. The discovery of paracrystalline diamond adds an unusual diamond form to the enriched carbon family^14-16, which exhibits distinguishing physical properties and can be furthered exploited to develop new materials. Furthermore, this work reveals the missing link in the length scale between amorphous and crystalline states across the structural landscape, having profound implications for recognizing complex structures arising from amorphous materials.

Effect of interfacial dipole on heterogeneous ice nucleation

In this work, we performed molecular dynamics simulations of ice nucleation on a rigid surface model of cubic zinc blende structure with different surface dipole strength and orientation. Our results show that, although substrates are excellently lattice-matched to cubic ice, ice nucleation merely occurred as the interfacial water molecules (IWs) show identical or similar orientations to that of water molecules in cubic ice. Free energy landscapes revealed that, as substrates have non-suitable dipole strength/orientation, there exist large free energy barriers for rotating dipole IWs to the right orientation to trigger ice formation. This study stresses that, beyond the traditional view of lattice match and the similarity of lattice length between the substrate and new-formed crystal, the similarity between molecular orientations of interfacial component and component in the specific new-formed crystalline face is also critical for promoting ice nucleation.

A Novel Paradigm for Expert Core Facility Staff Training

Scientific research relies on a range of technologies, many of which are developing at a fast pace. Technical experts able to advise researchers on experimental design and validate the performance1 of shared instruments are increasingly recognized as critical members of the research community. Here I describe a novel postdoctoral fellowship program designed to train expert imaging scientists, which could easily be adapted for other technologies.