Second-order mean-field approximation for calculating dynamics in Au-nanoparticle networks.

Exploiting physical processes for fast and energy-efficient computation bears great potential in the advancement of modern hardware components. This paper explores nonlinear charge tunneling in nanoparticle networks, controlled by external voltages. The dynamics are described by a master equation, which expresses the time-evolution of a distribution function over the set of charge occupation numbers. The driving force behind this evolution is charge tunneling events among nanoparticles and their associated rates. We introduce two mean-field approximations to this master equation. By parametrization of the distribution function using its first- and second-order statistical moments, and a subsequent projection of the dynamics onto the resulting moment manifold, one can deterministically calculate expected charges and currents. Unlike a kinetic Monte Carlo approach, which extracts samples from the distribution function, this mean-field approach avoids any random elements. A comparison of results between the mean-field approximation and an already available kinetic Monte Carlo simulation demonstrates great accuracy. Our analysis also reveals that transitioning from a first-order to a second-order approximation significantly enhances the accuracy. Furthermore, we demonstrate the applicability of our approach to time-dependent simulations, using Eulerian time-integration schemes.

Microscopic derivation of the thin film equation using the Mori-Zwanzig formalism.

The hydrodynamics of thin films is typically described using macroscopic models whose connection to the microscopic particle dynamics is a subject of ongoing research. Existing methods based on density functional theory provide a good description of static thin films but are not sufficient for understanding nonequilibrium dynamics. In this work, we present a microscopic derivation of the thin film equation using the Mori-Zwanzig projection operator formalism. This method allows to directly obtain the correct gradient dynamics structure along with microscopic expressions for mobility and free energy. Our results are verified against molecular dynamics simulations for both simple fluids and polymers.

Synergistic Enhancement of Mechanical and Electrochemical Properties in Grafted Polymer/Oxide Hybrid Electrolytes.

Lithium metal batteries operated with high voltage cathodes are predestined for the realization of high energy storage systems, where solid polymer electrolytes offer a possibility to improve battery safety. Al2O3_PCL is introduced as promising hybrid electrolyte made from polycaprolactone (PCL) and Al2O3 nanoparticles that can be prepared in a one-pot synthesis as a random mixture of linear PCL and PCL-grafted Al2O3. Upon grafting, synergistic effects of mechanical stability and ionic conductivity are achieved. Due to the mechanical stability, manufacture of PCL-based membranes with a thickness of 50 µm is feasible, yielding an ionic conductivity of 5·10-5 S cm-1 at 60 °C. The membrane exhibits an impressive performance of Li deposition in symmetric Li||Li cells, operating for 1200 h at a constant and low overvoltage of 54 mV and a current density of 0.2 mA cm-2. NMC622 | Al2O3_PCL | Li cells are cycled at rates of up to 1 C, achieving 140 cycles at >80% state of health. The straightforward synthesis and opportunity of upscaling as well as solvent-free polymerization render the Al2O3_PCL hybrid material as rather safe, potentially sustainable and affordable alternative to conventional polymer-based electrolytes.

Forced LMX1A expression induces dorsal neural fates and disrupts patterning of human embryonic stem cells into ventral midbrain dopaminergic neurons.

The differentiation of human pluripotent stem cells into ventral mesencephalic dopaminergic (DA) fate is relevant for the treatment of Parkinson's disease. Shortcuts to obtaining DA cells through direct reprogramming often include forced expression of the transcription factor LMX1A. Although reprogramming with LMX1A can generate tyrosine hydroxylase (TH)-positive cells, their regional identity remains elusive. Using an in vitro model of early human neural tube patterning, we report that forced LMX1A expression induced a ventral-to-dorsal fate shift along the entire neuroaxis with the emergence of roof plate fates despite the presence of ventralizing molecules. The LMX1A-expressing progenitors gave rise to grafts containing roof plate-derived choroid plexus cysts as well as ectopically induced TH-positive neurons of a forebrain identity. Early activation of LMX1A prior to floor plate specification was necessary for the dorsalizing effect. Our work suggests using caution in employing LMX1A for the induction of DA fate, as this factor may generate roof plate rather than midbrain fates.

Ternary Solid Polymer Electrolytes at the Electrochemical Interface: A Computational Study.

Polymer-based solid-like gel electrolytes have emerged as a promising alternative to improve battery performance. However, there is a scarcity of studies on the behavior of these media at the electrochemical interface. In this work, we report classical MD simulations of ternary polymer electrolytes composed of poly(ethylene oxide), a lithium salt [lithium bis(trifluoromethanesulfonyl)imide], and different ionic liquids [1-butyl-1-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide and 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide] confined between two charged and uncharged graphene-like surfaces. The molecular solvation of Li+ ions and their diffusion as well as the polymer conformational picture were characterized in terms of the radial distribution functions, coordination numbers, number density profiles, orientations, displacement variance, polymer radius of gyration, and polymer end-to-end distance. Our results show that the layering behavior of the ternary electrolyte in the interfacial region leads to a decrease of Li+ mobility in the direction perpendicular to the electrodes and high energy barriers that hinder lithium cations from coming into direct contact with the graphene-like surface. The nature of the ionic liquid and its concentration were found to influence the structural and dynamic properties at the electrode/electrolyte interface, the electrolyte with low amounts of the pyrrolidinium-based ionic liquid being that with the best performance since it favors the migration of Li+ cations toward the negative electrode when compared to the imidazolium-based one.

Elucidating the Membrane Binding Process of a Disordered Protein: Dynamic Interplay of Anionic Lipids and the Polybasic Region.

Intrinsically disordered regions of proteins are responsible for many biological processes such as in the case of liver kinase B1 (LKB1)-a serine/threonine kinase relevant for cell proliferation and cell polarity. LKB1 becomes fully activated upon recruitment to the plasma membrane by binding of its disordered C-terminal polybasic motif consisting of eight lysines/arginines to phospholipids. Here, we present extensive molecular dynamics (MD) simulations of the polybasic motif interacting with a model membrane composed of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-palmitoyl-2-oleyl phosphatidic acid (PA) and cell culture experiments. Protein-membrane binding effects are due to the electrostatic interactions between the polybasic amino acids and PAs. For significant binding, the first three lysines turn out to be dispensable, which was also recapitulated in cell culture using transfected GFP-LKB1 variants. LKB1-membrane binding results in nonmonotonous changes in the structure of the protein as well as the membrane, in particular, accumulation of PAs and reduced thickness at the protein-membrane contact area. The protein-lipid binding turns out to be highly dynamic due to an interplay of PA-PA repulsion and protein-PA attraction. The thermodynamics of this interplay is captured by a statistical fluctuation model, which allows the estimation of both energies. Quantification of the significance of each polar amino acid in the polybasic provides detailed insights into the molecular mechanism of protein-membrane binding of LKB1. These results can likely be transferred to other proteins, which interact by intrinsically disordered polybasic regions with anionic membranes.

Electron transfer reaction of TEMPO-based organic radical batteries in different solvent environments: comparing quantum and classical approaches.

In this study, we delve into the complex electron transfer reactions associated with the redox-active (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO), a common component in organic radical batteries (ORBs). Our approach estimates quantum electron-transfer (ET) energies using Density Functional Theory (DFT) calculations by sampling from structures simulated classically. This work presents a comparative study of reorganization energies in ET reactions across different solvents. Furthermore, we investigate how changes in the electrolyte environment can modify the reorganization energy and, consequently, impact ET dynamics. We also explore the relationship between classical and quantum vertical energies using linear regression models. Importantly, this comparison between quantum and classical vertical energies underscores the role of quantum effects, like charge delocalization, in offering added stabilization post-redox reactions. These effects are not adequately represented by the classical vertical energy distribution. Our study shows that, although we find a significant correlation between the vertical energies computed by DFT and the classical force field, the regression parameters depend on the solvent, highlighting that classical methods should be benchmarked by DFT before applying them to novel electrolyte materials.

Tetraspanner-based nanodomains modulate BAR domain-induced membrane curvature.

The topography of biological membranes is critical for formation of protein and lipid microdomains. One prominent example in the yeast plasma membrane (PM) are BAR domain-induced PM furrows. Here we report a novel function for the Sur7 family of tetraspanner proteins in the regulation of local PM topography. Combining TIRF imaging, STED nanoscopy, freeze-fracture EM and membrane simulations we find that Sur7 tetraspanners form multimeric strands at the edges of PM furrows, where they modulate forces exerted by BAR domain proteins at the furrow base. Loss of Sur7 tetraspanners or Sur7 displacement due to altered PIP2 homeostasis leads to increased PM invagination and a distinct form of membrane tubulation. Physiological defects associated with PM tubulation are rescued by synthetic anchoring of Sur7 to furrows. Our findings suggest a key role for tetraspanner proteins in sculpting local membrane domains. The maintenance of stable PM furrows depends on a balance between negative curvature at the base which is generated by BAR domains and positive curvature at the furrows' edges which is stabilized by strands of Sur7 tetraspanners.

Multimodal investigation of electronic transport in PTMA and its impact on organic radical battery performance.

Organic radical batteries (ORBs) represent a viable pathway to a more sustainable energy storage technology compared to conventional Li-ion batteries. For further materials and cell development towards competitive energy and power densities, a deeper understanding of electron transport and conductivity in organic radical polymer cathodes is required. Such electron transport is characterised by electron hopping processes, which depend on the presence of closely spaced hopping sites. Using a combination of electrochemical, electron paramagnetic resonance (EPR) spectroscopic, and theoretical molecular dynamics as well as density functional theory modelling techniques, we explored how compositional characteristics of cross-linked poly(2,2,6,6-tetramethyl-1-piperidinyloxy-4-yl methacrylate) (PTMA) polymers govern electron hopping and rationalise their impact on ORB performance. Electrochemistry and EPR spectroscopy not only show a correlation between capacity and the total number of radicals in an ORB using a PTMA cathode, but also indicates that the state-of-health degrades about twice as fast if the amount of radical is reduced by 15%. The presence of up to 3% free monomer radicals did not improve fast charging capabilities. Pulsed EPR indicated that these radicals readily dissolve into the electrolyte but a direct effect on battery degradation could not be shown. However, a qualitative impact cannot be excluded either. The work further illustrates that nitroxide units have a high affinity to the carbon black conductive additive, indicating the possibility of its participation in electron hopping. At the same time, the polymers attempt to adopt a compact conformation to increase radical-radical contact. Hence, a kinetic competition exists, which might gradually be altered towards a thermodynamically more stable configuration by repeated cycling, yet further investigations are required for its characterisation.

Mechanistic understanding of the correlation between structure and dynamics of liquid carbonate electrolytes: impact of polarization.

Liquid electrolyte design and modelling is an essential part of the development of improved lithium ion batteries. For mixed organic carbonates (ethylene carbonate (EC) and ethyl-methyl carbonate (EMC) mixtures)-based electrolytes with LiPF6 as salt, we have compared a polarizable force field with the standard non-polarizable force field with and without charge rescaling to model the structural and dynamic properties. The result of our molecular dynamics simulations shows that both polarizable and non-polarizable force fields have similar structural factors, which are also in agreement with X-ray diffraction experimental results. In contrast, structural differences are observed for the lithium neighborhood, while the lithium-anion neighbourhood is much more pronounced for the polarizable force field. Comparison of EC/EMC coordination statistics with Fourier transformed infrared spectroscopy (FTIR) shows the best agreement for the polarizable force field. Also for transport quantities such as ionic conductivities, transference numbers, and viscosities, the agreement with the polarizable force field is by far better for a large range of salt concentrations and EC : EMC ratios. In contrast, for the non-polarizable variants, the dynamics are largely underestimated. The excellent performance of the polarizable force field is explored in different ways to pave the way to a realistic description of the structure-dynamics relationships for a wide range of salt and solvent compositions for this standard electrolyte. In particular, we can characterize the distinct correlation terms between like and unlike ions, relate them to structural properties, and explore to which degree the transport in this electrolyte is mass or charge limited.

Astrocyte dysfunction and neuronal network hyperactivity in a CRISPR engineered pluripotent stem cell model of frontotemporal dementia.

Frontotemporal dementia (FTD) is the second most prevalent type of early-onset dementia and up to 40% of cases are familial forms. One of the genes mutated in patients is CHMP2B, which encodes a protein found in a complex important for maturation of late endosomes, an essential process for recycling membrane proteins through the endolysosomal system. Here, we have generated a CHMP2B-mutated human embryonic stem cell line using genome editing with the purpose to create a human in vitro FTD disease model. To date, most studies have focused on neuronal alterations; however, we present a new co-culture system in which neurons and astrocytes are independently generated from human embryonic stem cells and combined in co-cultures. With this approach, we have identified alterations in the endolysosomal system of FTD astrocytes, a higher capacity of astrocytes to uptake and respond to glutamate, and a neuronal network hyperactivity as well as excessive synchronization. Overall, our data indicates that astrocyte alterations precede neuronal impairments and could potentially trigger neuronal network changes, indicating the important and specific role of astrocytes in disease development.

Rapid and reversible optical switching of cell membrane area by an amphiphilic azobenzene.

Cellular membrane area is a key parameter for any living cell that is tightly regulated to avoid membrane damage. Changes in area-to-volume ratio are known to be critical for cell shape, but are mostly investigated by changing the cell volume via osmotic shocks. In turn, many important questions relating to cellular shape, membrane tension homeostasis and local membrane area cannot be easily addressed because experimental tools for controlled modulation of cell membrane area are lacking. Here we show that photoswitching an amphiphilic azobenzene can trigger its intercalation into the plasma membrane of various mammalian cells ranging from erythrocytes to myoblasts and cancer cells. The photoisomerization leads to a rapid (250-500 ms) and highly reversible membrane area change (ca 2 % for erythrocytes) that triggers a dramatic shape modulation of living cells.

Wettability gradient-driven droplets with an applied external force.

On homogeneous substrates, droplets can slide due to external driving forces, such as gravity, whereas in the presence of wettability gradients, sliding occurs without external forces since this gradient gives rise to an internal driving force. Here, we study via molecular dynamics simulations the more complex behavior when droplets are driven under the combined influence of an external and internal driving force. For comparison, the limiting cases of a single driving force are studied as well. During a large part of the sliding process over the borderline of both substrates, separating both wettabilities, the velocity is nearly constant. When expressing it as the product of the effective mobility and the effective force, the effective mobility mainly depends on the mobility of the initial substrate, experienced by the receding contact line. This observation can be reconciled with the properties of the flow pattern, indicating that the desorption of particles at the receding contact line is the time-limiting step. The effective force is the sum of the external force and a renormalized internal force. This renormalization can be interpreted as stronger dissipation effects when driving occurs via wettability gradients.

Deconvolution of spatial sequencing provides accurate characterization of hESC-derived DA transplants in vivo.

Cell therapy for Parkinson's disease has experienced substantial growth in the past decades with several ongoing clinical trials. Despite increasing refinement of differentiation protocols and standardization of the transplanted neural precursors, the transcriptomic analysis of cells in the transplant after its full maturation in vivo has not been thoroughly investigated. Here, we present spatial transcriptomics analysis of fully differentiated grafts in their host tissue. Unlike earlier transcriptomics analyses using single-cell technologies, we observe that cells derived from human embryonic stem cells (hESCs) in the grafts adopt mature dopaminergic signatures. We show that the presence of phenotypic dopaminergic genes, which were found to be differentially expressed in the transplants, is concentrated toward the edges of the grafts, in agreement with the immunohistochemical analyses. Deconvolution shows dopamine neurons being the dominating cell type in many features beneath the graft area. These findings further support the preferred environmental niche of TH-positive cells and confirm their dopaminergic phenotype through the presence of multiple dopaminergic markers.

A comparison of machine learning approaches for the quantification of microglial cells in the brain of mice, rats and non-human primates.

Microglial cells are brain-specific macrophages that swiftly react to disruptive events in the brain. Microglial activation leads to specific modifications, including proliferation, morphological changes, migration to the site of insult, and changes in gene expression profiles. A change in inflammatory status has been linked to many neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease. For this reason, the investigation and quantification of microglial cells is essential for better understanding their role in disease progression as well as for evaluating the cytocompatibility of novel therapeutic approaches for such conditions. In the following study we implemented a machine learning-based approach for the fast and automatized quantification of microglial cells; this tool was compared with manual quantification (ground truth), and with alternative free-ware such as the threshold-based ImageJ and the machine learning-based Ilastik. We first trained the algorithms on brain tissue obtained from rats and non-human primate immunohistochemically labelled for microglia. Subsequently we validated the accuracy of the trained algorithms in a preclinical rodent model of Parkinson's disease and demonstrated the robustness of the algorithms on tissue obtained from mice, as well as from images provided by three collaborating laboratories. Our results indicate that machine learning algorithms can detect and quantify microglial cells in all the three mammalian species in a precise manner, equipotent to the one observed following manual counting. Using this tool, we were able to detect and quantify small changes between the hemispheres, suggesting the power and reliability of the algorithm. Such a tool will be very useful for investigation of microglial response in disease development, as well as in the investigation of compatible novel therapeutics targeting the brain. As all network weights and labelled training data are made available, together with our step-by-step user guide, we anticipate that many laboratories will implement machine learning-based quantification of microglial cells in their research.

Hydrodynamic interactions in ion transport-Theory and simulation.

We present a hydrodynamic theory describing pair diffusion in systems with periodic boundary conditions, thereby generalizing earlier work on self-diffusion [B. Dünweg and K. Kremer, J. Chem. Phys. 99, 6983-6997 (1993) and I.-C. Yeh and G. Hummer, J. Phys. Chem. B 108, 15873-15879 (2004)]. Its predictions are compared with Molecular Dynamics simulations for a liquid carbonate electrolyte and two ionic liquids, for which we characterize the correlated motion between distinct ions. Overall, we observe good agreement between theory and simulation data, highlighting that hydrodynamic interactions universally dictate ion correlations. However, when summing over all ion pairs in the system to obtain the cross-contributions to the total cationic or anionic conductivity, the hydrodynamic interactions between ions with like and unlike charges largely cancel. Consequently, significant conductivity contributions only arise from deviations from a hydrodynamic flow field of an ideal fluid, which is from the local electrolyte structure as well as the relaxation processes in the subdiffusive regime. In the case of ionic liquids, the momentum-conservation constraint additionally is vital, which we study by employing different ionic masses in the simulations. Our formalism will likely also be helpful to estimate finite-size effects of the conductivity or of Maxwell-Stefan diffusivities in simulations.

Conformational and Interface Variability in Multivalent SIM-SUMO Interaction.

SUMO targeted ubiqutin ligases (STUbLs) like RNF4 or Arkadia/RNF111 recognize SUMO chains through multiple SUMO interacting motifs (SIMs). Typically, these are contained in disordered regions of these enzymes and also the individual SUMO domains of SUMO chains move relatively freely. It is assumed that binding the SIM region significantly restricts the conformational freedom of SUMO chains. Here, we present the results of extensive molecular dynamics simulations on the complex formed by the SIM2-SIM3 region of RNF4 and diSUMO3. Though our simulations highlight the importance of typical SIM-SUMO interfaces also in the multivalent situation, we observe that frequently other regions of the peptide than the canonical SIMs establish this interface. This variability regarding the individual interfaces leads to a conformationally highly flexible complex. Comparison with previous experimental measurements clearly supports our findings and indicates that our observations can be extended to other multivalent SIM-SUMO complexes.

Photo-Responsive Control of Adsorption and Structure Formation at the Air-Water Interface with Arylazopyrazoles.

Smart interfaces that are responsive to external triggers such as light are of great interest for the development of responsive or adaptive materials and interfaces. Using alkyl-arylazopyrazole butyl sulfonate surfactants (alkyl-AAP) that can undergo E/Z photoisomerization when irradiated with green (E) and UV (Z) lights, we demonstrate through a combination of experiments and computer simulations that there can be surprisingly large changes in surface tension and in the molecular structure and order at air-water interfaces. Surface tensiometry, vibrational sum-frequency generation (SFG) spectroscopy, and neutron reflectometry (NR) are applied to the study of custom-synthesized AAP surfactants with octyl- and H-terminal groups at air-water interfaces as a function of their bulk concentration and E/Z configuration. Upon photoswitching, a drastic influence of the alkyl chain on both the surface activity and the responsiveness of interfacial surfactants is revealed from changes in the surface tension, γ, where the largest changes in γ are observed for octyl-AAP (Δγ ∼ 23 mN/m) in contrast to H-AAP with Δγ < 10 mN/m. Results from vibrational SFG spectroscopy and NR show that the interfacial composition and the molecular order of the surfactants drastically change with E/Z photoisomerization and surface coverage. Indeed, from analysis of the S-O (head group) and C-H vibrational bands (hydrophobic tail), a qualitative analysis of orientational and structural changes of interfacial AAP surfactants is provided. The experiments are complemented by resolution of thermodynamic parameters such as equilibrium constants from ultra-coarse-grained simulations, which also capture details like island formation and interaction parameters of interfacial molecules. Here, the interparticle interaction ("stickiness") and the interaction with the surface are adjusted, closely reflecting experimental conditions.

Phosphorylation of LKB1 by PDK1 Inhibits Cell Proliferation and Organ Growth by Decreased Activation of AMPK.

The master kinase LKB1 is a key regulator of se veral cellular processes, including cell proliferation, cell polarity and cellular metabolism. It phosphorylates and activates several downstream kinases, including AMP-dependent kinase, AMPK. Activation of AMPK by low energy supply and phosphorylation of LKB1 results in an inhibition of mTOR, thus decreasing energy-consuming processes, in particular translation and, thus, cell growth. LKB1 itself is a constitutively active kinase, which is regulated by posttranslational modifications and direct binding to phospholipids of the plasma membrane. Here, we report that LKB1 binds to Phosphoinositide-dependent kinase (PDK1) by a conserved binding motif. Furthermore, a PDK1-consensus motif is located within the kinase domain of LKB1 and LKB1 gets phosphorylated by PDK1 in vitro. In Drosophila, knockin of phosphorylation-deficient LKB1 results in normal survival of the flies, but an increased activation of LKB1, whereas a phospho-mimetic LKB1 variant displays decreased AMPK activation. As a functional consequence, cell growth as well as organism size is decreased in phosphorylation-deficient LKB1. Molecular dynamics simulations of PDK1-mediated LKB1 phosphorylation revealed changes in the ATP binding pocket, suggesting a conformational change upon phosphorylation, which in turn can alter LKB1's kinase activity. Thus, phosphorylation of LKB1 by PDK1 results in an inhibition of LKB1, decreased activation of AMPK and enhanced cell growth.

Systematic analysis of curvature-dependent lipid dynamics in a stochastic 3D membrane model.

To minimize the free energy of the system, lipid membranes display curvature-dependent rearrangements at the local and global scale. The optimal membrane shape is generally approximated by averaging the curvature preference of individual lipids across the whole surface. Potential stress due to imperfections in lipid packing caused by local lipid inhomogeneities, however, is frequently neglected. Here, we developed a stochastic 3D membrane model to investigate the relevance of this parameter for shape-dependent lipid and membrane dynamics. A systematic analysis of the discretized Helfrich type Hamiltonian indicates that stress-energy arising from imperfections in packing is analogous to van der Waals interactions, jointly determining membrane shape and localization of curvature-sensitive lipids based on their relative strengths. Insights from this work can be used to characterize natural and design synthetic agents for membrane-shape changes.