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The nucleocytoplasmic exchange is of fundamental importance to eukaryotic life and is mediated by karyo- pherins, a superfamily of nuclear transport receptors. However, the function and cargo spectrum of plant kar- yopherins are largely obscure. Here, we report proximity-labeling-based proteomic profiling of in vivo sub- strates of KA120, a karyopherin-b required for suppressing autoimmune induction in Arabidopsis. We identify multiple components of the MOS4-associated complex (MAC), a conserved splicing regulatory pro- tein complex. Surprisingly, we find that KA120 does not affect the nucleocytoplasmic distribution of MAC proteins but rather prevents their protein condensation in the nucleus. Furthermore, we demonstrate that MAC condensation is robustly induced by pathogen infection, which is sufficient to activate defense gene expression, possibly by sequestrating negative immune regulators via phase transition. Our study reveals a noncanonical chaperoning activity of a plant karyopherin, which modulates the nuclear condensation of an evolutionarily conserved splicing regulatory complex to coordinate plant immune activation. 

Low temperature plasmas are an emerging method to synthesize high quality nanoparticles (NPs). An established and successful technique to produce NPs is using a capacitively coupled plasma (CCP) in cylindrical geometry. Although a robust synthesis technique, optimizing or specifying NP properties using CCPs, is challenging. In this paper, results from a computational investigation for the growth of silicon NPs in flowing inductively coupled plasmas (ICPs) using Ar/SiH4 gas mixtures of up to a few Torr are discussed. ICPs produce more locally constrained and quiescent plasma potentials. These positive plasma potentials produce an electrostatic trap for negatively charged NPs, which can significantly extend the residence time of NPs in the plasma, which in turn provides a controllable period for particle growth. The computational platforms used in this study consist of a two-dimensional plasma hydrodynamics model, a three-dimensional nanoparticle growth and trajectory tracking model, and a molecular dynamics simulation for deriving reactive sticking coefficients of silane radicals on Si NPs. Trends for the nanoparticle growth as a function of SiH4 inlet fraction, gas residence time, energy deposition per particle, pressure, and reactor diameter are discussed. The general path for particle synthesis is the trapping of small NPs in the positive electrostatic potential, followed by entrainment in the gas flow upon reaching a critical particle size. Optimizing or controlling NP synthesis then depends on the spatial distribution of plasma potential, the density of growth species, and the relative time that particles spend in the electrostatic trap and flowing through higher densities of growth species upon leaving the trap. 

Graph generative models have recently emerged as an interesting approach to construct molecular structures atom‐by‐atom or fragment‐by‐fragment. In this study, we adopt the fragment‐based strategy and decompose each input molecule into a set of small chemical fragments. In drug discovery, a few drug molecules are designed by replacing certain chemical substituents with their bioisosteres or alternative chemical moieties. This inspires us to group decomposed fragments into different fragment clusters according to their local structural environment around bond‐breaking positions. In this way, an input structure can be transformed into an equivalent three‐layer graph, in which individual atoms, decomposed fragments, or obtained fragment clusters act as graph nodes at each corresponding layer. We further implement a prototype model, named multi‐resolution graph variational autoencoder (MRGVAE), to learn embeddings of constituted nodes at each layer in a fine‐to‐coarse order. Our decoder adopts a similar but conversely hierarchical structure. It first predicts the next possible fragment cluster, then samples an exact fragment structure out of the determined fragment cluster, and sequentially attaches it to the preceding chemical moiety. Our proposed approach demonstrates comparatively good performance in molecular evaluation metrics compared with several other graph‐based molecular generative models. The introduction of the additional fragment cluster graph layer will hopefully increase the odds of assembling new chemical moieties absent in the original training set and enhance their structural diversity. We hope that our prototyping work will inspire more creative research to explore the possibility of incorporating different kinds of chemical domain knowledge into a similar multi‐resolution neural network architecture.

 

For a single, intense 7 μm linearly polarized laser pulse, we found that the branching ratio for the fragmentation of ClCHO⁺→ Cl + HCO⁺, H + ClCO⁺, HCl⁺+CO depended strongly on the orientation of the molecule (J. Phys. Chem. Lett.2012,32541). The present study explores the possibility of controlling the branching ratio for fragmentation by using two independent pulses with different frequencies, alignment and delay. Born‐Oppenheimer molecular dynamics simulations in the laser field were carried out with the B3LYP/6‐311G(d,p) level of theory using combinations of 3.5, 7 and 10.5 μm sine squared pulses with field strengths of 0.03 au (peak intensity of 3.15×10¹³W/cm²) and lengths of 560 fs. A 3.5 μm pulse aligned with the C‐H bond and a 10.5 μm pulse perpendicular to the C‐H bond produced a larger branching ratio for HCl⁺+CO than a comparable single 7 μm pulse. When the 10.5 μm pulse was delayed by one quarter of the pulse envelope, the branching ratio for the high energy product, (HCl⁺+CO 73%) was a factor of three larger than the low energy product (Cl + HCO⁺, 25%). By contrast, when the 3.5 μm pulse was delayed by one quarter of the pulse envelope, the branching ratio was reversed (HCl⁺+CO 38%; Cl + HCO⁺, 60%). Continuous wavelet analysis was used to follow the interaction of the laser with the various vibrational modes as a function of time. © 2018 Wiley Periodicals, Inc.

 

Corneal transplantation is impeded by donor shortages, immune rejection, and ethical reservations. Pre‐made cornea prostheses (keratoprostheses) offer a proven option to alleviate these issues. Ideal keratoprostheses must possess optical clarity and mechanical robustness, but also high permeability, processability, and recyclability. Here, it is shown that rationally controlling the extent of arrested phase separation can lead to optimized multiscale structure that reconciles permeability and transparency, a previously conflicting goal by common pore‐forming strategies. The process is simply accomplished by hydrothermally treating a dense and transparent hydrophobic association hydrogel. The examination of multiscale structure evolution during hydrothermal treatment reveals that the phase separation with upper miscibility gap evolves to confer time‐dependent pore growth due to slow dynamics of polymer‐rich phase which is close to vitrification. Such a process can render a combination of multiple desired properties that equal or surpass those of the state‐of‐the‐art keratoprostheses. In vivo tests confirm that the keratoprosthesis can effectively repair corneal perforation and restore a transparent cornea with treatment outcomes akin to that of allo‐keratoplasty. The keratoprosthesis is easy to access and convenient to carry, and thus would be an effective temporary substitute for a corneal allograft in emergency conditions.