Insights into the aggregation mechanism of RNA recognition motif domains in TDP-43: a theoretical exploration

The transactive response DNA-binding protein 43 (TDP-43) is associated with several diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) due to pathogenic aggregations. In this work, we examined the dimer, tetramer and hexamer models built from the RRM domains of TDP-43 using molecular dynamics simulations in combination with the protein–protein docking. Our results showed that the formations of the dimer models are mainly achieved by the interactions of the RRM1 domains. The parallel β-sheet layers between the RRM1 domains provide most of the binding sites in these oligomer models, and thus play an important role in the aggregation process. The approaching of the parallel β-sheet layers from small oligomer models gradually expand to large ones through the allosteric communication between the α1/α2 helices of the RRM1 domains, which maintains the binding affinities and interactions in the larger oligomer models. Using the repeatable-superimposing method based on the tetramer models, we proposed a new aggregation mechanism of RRM domains in TDP-43, which could well characterize the formation of the large aggregation models with the repeated, helical and rope-like structures. These new insights help to understand the amyloid-like aggregation phenomena of TDP-43 protein in ALS and FTLD diseases.

Reconstruction of low-rank aggregation kernels in univariate population balance equations

The dynamics of particle processes can be described by population balance equations which are governed by phenomena including growth, nucleation, breakage and aggregation. Estimating the kinetics of the aggregation phenomena from measured density data constitutes an ill-conditioned inverse problem. In this work, we focus on the aggregation problem and present an approach to estimate the aggregation kernel in discrete, low rank form from given (measured or simulated) data. The low-rank assumption for the kernel allows the application of fast techniques for the evaluation of the aggregation integral ($\mathcal {O}(n\log n)$ O ( n log n ) instead of $\mathcal {O}(n^{2})$ O ( n 2 ) where n denotes the number of unknowns in the discretization) and reduces the dimension of the optimization problem, allowing for efficient and accurate kernel reconstructions. We provide and compare two approaches which we will illustrate in numerical tests.

Molecular Dynamics Study of Nanoparticles/argon Atoms Size Effects on Atomic Aggregation Phenomena in Ideal Platinum Nanochannel Affected by the External Magnetic Field

In this paper, the computational method is used to describe the atomic behavior of Fe3O4 nanoparticles size effect on these nanoparticles aggregation phenomena in ideal platinum nanochannel and in the presence of outer magnetic major. In this work molecular dynamics (MD) method used and argon atoms described as base fluid. Technically, for the interaction between base fluid atoms, we used Lennard-jones (LJ) potential, while the nanochannel wall and nanoparticle structures are simulated. To calculate the atomic behavior of simulated systems, we report temperature, total energy, and distance of nanoparticles center of mass (COM) and time of aggregation phenomena. Our MD simulation results show the Fe3O4 nanoparticle size is an important factor in aggregation phenomenon occur. Numerically, by enlarging the Fe3O4 nanoparticle size, the aggregation time of Al2O3 nanoparticles changes from 1.41 ns to 1.29 ns. Further, the external magnetic field can be delayed this atomic phenomenon effectively.

Insights into the Aggregation Mechanism of RRM domains in TDP-43: A Molecular Dynamics Study

The transactive response DNA-binding protein 43 (TDP-43) is associated with several diseases such as Amyotrophic lateral sclerosis (ALS) and Frontotemporal lobar degeneration (FTLD) due to pathogenic aggregations. In this work, we examined the dimer, tetramer and hexamer models built from the RRM domains of TDP-43 using molecular dynamics simulations in combination with the protein-protein docking. Our results show that the parallel β-sheet layers in the RRM1 domains in these oligomer models were formed energetically favorable, which provide the potential binding sites in the aggregation process. The closeness of the parallel β-sheet layers from small oligomer models gradually expanded to large ones through the communication of the interaction between α1/α2 helices of RRM domains, which enhanced the binding affinities and interactions in these aggregation models to further promote the aggregation. Using the repeatable-superimposing method based on the tetramer models, we propose a new aggregation mechanism of RRM domains in TDP-43 which mediates the formation of large aggregation structure with the repeated, helical and rope-like characteristics. These new insights help to understand the amyloid-like aggregation phenomena of TDP-43 protein in ALS and FTLD diseases.

On a Class of Reaction-Diffusion Equations with Aggregation

In this paper, global-in-time existence and blow-up results are shown for a reaction-diffusion equation appearing in the theory of aggregation phenomena (including chemotaxis). Properties of the corresponding steady-state problem are also presented. Moreover, the stability around constant equilibria and the non-existence of nonconstant solutions are studied in certain cases.

Study on Adsorption and Aggregation in the Mixed System of Polyacrylamide, Cu(II) Ions and Innovative Carbon–Silica Composite

The paper presents an original study on adsorption and aggregation phenomena in a mixed system consisting of a macromolecular compound, heavy metal ions and an innovative adsorbent. The authors used ionic polyacrylamides (PAM), Cu(II) ions and carbon–silica composite (C-SiO2) in the experiments. Such a system has not yet been described in the literature and therefore, the article is of significant novelty and great importance. The composite was prepared by mixing phenol–formaldehyde resin with silica and pyrolysis at 800 °C. The adsorbed amounts of Cu(II) ions and PAM were determined spectrophotometrically. C-SiO2 was characterized using potentiometric titration, microelecrophoresis and Fourier Transform Infrared Spectroscopy (FTIR) analysis. In turn, the C-SiO2 aggregation was established turbidimetrically as well as using a particle size analyzer. The obtained results indicated that both Cu(II) ions and ionic polyacrylamide were adsorbed on the composite surface at pH 6. The highest noted adsorbed amounts were 9.8 mg/g for Cu(II) and 35.72 mg/g for CT PAM-25%. Cu(II) ions increased the anionic PAM adsorbed and reduced the cationic PAM one. The adsorption of anionic PAM (50 ppm) stimulated the solid aggregation significantly. What is more, Cu(II) ions enhanced this process. The size of particles/aggregates formed without additives equaled 0.44 μm, whereas in the mixed Cu(II)/AN PAM system, they were even at 1.04 μm.