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Highlights
• Sampling the large conformational space of disordered proteins requires extensive molecular dynamics (MD) simulations.
• Fragment assembly complements MD simulations to produce extensive ensembles of disordered proteins with atomic detail.
• Hierarchical chain growth (HCG) ensembles capture key experimental descriptors “out of the box”.
• HCG has revealed local structural characteristics associated with protein dysfunction in neurodegeneration.
Abstract
Disordered proteins and nucleic acids play key roles in cellular function and disease. Here, we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. While atomistic molecular dynamics (MD) simulation has seen a lot of improvement in recent years, large-scale computing resources and careful validation are required to simulate full-length disordered biopolymers in solution. As a computationally efficient alternative, hierarchical chain growth (HCG) combines pre-sampled chain fragments in a statistically reproducible manner into ensembles of full-length atomically detailed biomolecular structures. Experimental data can be integrated during and after chain assembly. Applications to the neurodegeneration-linked proteins α-synuclein, tau, and TDP-43, including as condensate, illustrate the use of HCG. We conclude by highlighting the emerging connections to AI-based structural modeling including AlphaFold2.
Electronic and magnetic properties of the RuX3 (X=Cl, Br, I) family: two siblings - and a cousin?
(2022)
Motivated by reports of metallic behavior in the recently synthesized RuI3, in contrast to the Mott-insulating nature of the actively discussed α-RuCl3, as well as RuBr3, we present a detailed comparative analysis of the electronic and magnetic properties of this family of trihalides. Using a combination of first-principles calculations and effective-model considerations, we conclude that RuI3, similarly to the other two members, is most probably on the verge of a Mott insulator, but with much smaller magnetic moments and strong magnetic frustration. We predict the ideal pristine crystal of RuI3 to have a nearly vanishing conventional nearest-neighbor Heisenberg interaction and to be a quantum spin liquid candidate of a possibly different kind than the Kitaev spin liquid. In order to understand the apparent contradiction to the reported resistivity ρ, we analyze the experimental evidence for all three compounds and propose a scenario for the observed metallicity in existing samples of RuI3. Furthermore, for the Mott insulator RuBr3, we obtain a magnetic Hamiltonian of a similar form to that in the much-discussed α-RuCl3 and show that this Hamiltonian is in agreement with experimental evidence in RuBr3.
Due to the small photon momentum, optical spectroscopy commonly probes magnetic excitations only at the center of the Brillouin zone; however, there are ways to override this restriction. In case of the distorted kagome quantum magnet Y-kapellasite, Y3Cu9(OH)19Cl8, under scrutiny here, the spin (magnon) density of states (SDOS) can be accessed over the entire Brillouin zone through three-center magnon excitations. This mechanism is aided by the three different magnetic sublattices and strong short-range correlations in the distorted kagome lattice. The results of THz time-domain experiments agree remarkably well with linear spin-wave theory (LSWT). Relaxing the conventional zone-center constraint of photons gives a new aspect to probe magnetism in matter.
The new heavy ion superconducting continuous wave HElmholtz LInear ACcelerator (HELIAC) is under construction at GSI. A normal conducting injector, comprising an ECR ion source, an RFQ and a DTL, is recently in development. The new Interdigital H-mode DTL, presented in this paper, accelerates the heavy ion beam from 300 to 1400 keV/u, applying an Alternating Phase Focusing (APF) beam dynamics scheme. This APF section, consisting of two separately controlled tanks, has to provide for stable routine operation with assistance of dedicated beam diagnostics devices in the Intertank section. The installed quadrupole lenses and beam steerers installed there ensure full transmission in a wide range of input beam parameters.
Bounded rationality is one crucial component in human behaviours. It plays a key role in the typical collective behaviour of evacuation, in which heterogeneous information can lead to deviations from optimal choices. In this study, we propose a framework of deep learning to extract a key dynamical parameter that drives crowd evacuation behaviour in a cellular automaton (CA) model. On simulation data sets of a replica dynamic CA model, trained deep convolution neural networks (CNNs) can accurately predict dynamics from multiple frames of images. The dynamical parameter could be regarded as a factor describing the optimality of path-choosing decisions in evacuation behaviour. In addition, it should be noted that the performance of this method is robust to incomplete images, in which the information loss caused by cutting images does not hinder the feasibility of the method. Moreover, this framework provides us with a platform to quantitatively measure the optimal strategy in evacuation, and this approach can be extended to other well-designed crowd behaviour experiments.
To determine the neutron flux in activation experiments, a commonly used monitor is zirconium and in particular the stable isotopes 94,96Zr. 96Zr is very sensitive to epithermal neutrons. Despite its widespread application, most gamma intensities of the radioactive neutron capture product, 97Zr, yield large uncertainties. With the help of a new γ spectroscopy setup and GEANT simulations, we succeeded in determining a new set of γ-ray intensities with significantly reduced uncertainties.
Vanadium and Manganese Carbonyls as Precursors in Electron-Induced and Thermal Deposition Processes
(2022)
The material composition and electrical properties of nanostructures obtained from focused electron beam-induced deposition (FEBID) using manganese and vanadium carbonyl precursors have been investigated. The composition of the FEBID deposits has been compared with thin films derived by the thermal decomposition of the same precursors in chemical vapor deposition (CVD). FEBID of V(CO)6 gives access to a material with a V/C ratio of 0.63–0.86, while in CVD a lower carbon content with V/C ratios of 1.1–1.3 is obtained. Microstructural characterization reveals for V-based materials derived from both deposition techniques crystallites of a cubic phase that can be associated with VC1−xOx. In addition, the electrical transport measurements of direct-write VC1−xOx show moderate resistivity values of 0.8–1.2 × 103 µΩ·cm, a negligible influence of contact resistances and signatures of a granular metal in the temperature-dependent conductivity. Mn-based deposits obtained from Mn2(CO)10 contain ~40 at% Mn for FEBID and a slightly higher metal percentage for CVD. Exclusively insulating material has been observed in FEBID deposits as deduced from electrical conductivity measurements. In addition, strong tendencies for postgrowth oxidation have to be considered.
The development of epilepsy (epileptogenesis) involves a complex interplay of neuronal and immune processes. Here, we present a first-of-its-kind mathematical model to better understand the relationships among these processes. Our model describes the interaction between neuroinflammation, blood-brain barrier disruption, neuronal loss, circuit remodeling, and seizures. Formulated as a system of nonlinear differential equations, the model reproduces the available data from three animal models. The model successfully describes characteristic features of epileptogenesis such as its paradoxically long timescales (up to decades) despite short and transient injuries or the existence of qualitatively different outcomes for varying injury intensity. In line with the concept of degeneracy, our simulations reveal multiple routes toward epilepsy with neuronal loss as a sufficient but non-necessary component. Finally, we show that our model allows for in silico predictions of therapeutic strategies, revealing injury-specific therapeutic targets and optimal time windows for intervention.
Dual formulations of Abelian U(1) and Z(N) LGT with a static fermion determinant are constructed at finite temperatures and non-zero chemical potential. The dual form is valid for a broad class of lattice gauge actions, for arbitrary number of fermion flavors and in any dimension. The distinguished feature of the dual formulation is that the dual Boltzmann weight is strictly positive. This allows to gain reliable results at finite density via the Monte-Carlo simulations. As a byproduct of the dual representation we outline an exact solution for the partition function of the (1+1)-dimensional theory and reveal an existence of a phase with oscillating correlations.