A novel multiple-walk parallel algorithm for the Barnes–Hut treecode on GPUs – towards cost effective, high performance N-body simulation

Tree-Code Based Improvement of Computational Performance of the X-ray-Matter-Interaction Simulation Tool XMDYN

In this work, we report on incorporating for the first time tree-algorithm based solvers into the molecular dynamics code, XMDYN. XMDYN was developed to describe the interaction of ultrafast X-ray pulses with atomic assemblies. It is also a part of the simulation platform, SIMEX, developed for computational single-particle imaging studies at the SPB/SFX instrument of the European XFEL facility. In order to improve the XMDYN performance, we incorporated the existing tree-algorithm based Coulomb solver, PEPC, into the code, and developed a dedicated tree-algorithm based secondary ionization solver, now also included in the XMDYN code. These extensions enable computationally efficient simulations of X-ray irradiated large atomic assemblies, e.g., large protein systems or viruses that are of strong interest for ultrafast X-ray science. The XMDYN-based preparatory simulations can now guide future single-particle-imaging experiments at the free-electron-laser facility, EuXFEL.

Electrospray molecular dynamics simulations using an octree-based Coulomb interaction method

A new octree-based Coulomb interaction model is developed to model the electrospray of ionic liquids (ILs) in molecular dynamics. Using an octree-based method, Coulomb interactions are categorized as intra- and interleaf Coulomb interactions based on a criterion related to the Bjerrum length of the IL. The octree-based method is found capable of reproducing Coulomb energy in agreement with established and computationally more expensive models, such as the direct Coulomb and the damped shifted force (DSF) method in the absence of an external electric field. In the presence of an external electric field, the octree-based method produces distinctly different results compared to that obtained by the direct Coulomb method. The time required to form Taylor's cone was shorter for the octree method compared to the direct Coulomb approach. While no emission larger than monomers was observed from the direct Coulomb simulation, emission of larger species such as dimers and trimers was observed when the octree-based Coulomb interaction model was used. Furthermore, the octree-based model forms a smaller ion emission cone compared to that from the direct Coulomb method.

Long-Term Continuous Double Station Observation of Faint Meteor Showers

Meteor detection and analysis is an essential topic in the field of astronomy. In this paper, a high-sensitivity and high-time-resolution imaging device for the detection of faint meteoric events is presented. The instrument is based on a fast CCD camera and an image intensifier. Two such instruments form a double-station observation network. The MAIA (Meteor Automatic Imager and Analyzer) system has been in continuous operation since 2013 and has successfully captured hundreds of meteors belonging to different meteor showers, as well as sporadic meteors. A data processing pipeline for the efficient processing and evaluation of the massive amount of video sequences is also introduced in this paper.

Identification of microRNA-regulated autophagic pathways in plant lectin-induced cancer cell death

OBJECTIVES

Plant lectins, carbohydrate-binding proteins of non-immune origin, have recently been reported to induce programmed cell death (including apoptosis and autophagy) in many types of cancer cells. MicroRNAs (miRNAs), small, non-coding endogenous RNAs, ~22 nucleotides (nt) in length, have been well characterized to play essential roles in regulation of the autophagy process in cancer; however, how these miRNAs regulate autophagic pathways in plant lectin-induced cancer cells, still remains an enigma.

MATERIALS AND METHODS

Identification of microRNA-regulated autophagic pathways was carried out using a series of elegant systems - biology and bioinformatics approaches, such as network construction, hub protein identification, targeted microRNA prediction, microarray analyses and molecular docking.

RESULTS

We computationally constructed the human autophagic protein-protein interaction (PPI) network, and further modified this network into a plant lectin-induced network. Subsequently, we identified 9 autophagic hub proteins and 13 relevant oncogenic and tumour suppressive miRNAs, that could regulate these aforementioned targeted autophagic hub proteins, in human breast carcinoma MCF-7 cells. In addition, we confirmed that plant lectins could block the sugar-containing receptor EGFR-mediated survival pathways, involved in autophagic hub proteins and relevant miRNAs, thereby ultimately culminating in autophagic cell death.

CONCLUSIONS

These results demonstrate that network-based identification of microRNAs modulate autophagic pathways in plant lectin-treated cancer cells, which may shed new light on the discovery of plant lectins as potent autophagic inducers, for cancer drug discovery.