Trace element contents of selected antarctic meteorites, 1

Data are reported for volatile/mobile Ag, As, Au, Bi, Cd, Co, Cs, Cu, Ga, In, Rb, Sb, Se, Te, T1 and Zn in exterior and/or interior samples of four Antarctic meteorites: 77005 (unique achondrite); 77257 (unreilite); 77278 (L3); 77299 (H3). Exterior samples reflect contamination and/or leaching by weathering but trace element (ppm-ppt) contents in interior samples seem reasonable for representatives of these rare meteoritic types. The 77005 achondrite seems related to shergottites; other samples extend compositional ranges previously known for their types. With suitable precautions, Antarctic meteorite finds yield trace element data as reliable as those obtained from previously known falls

QuTIE: Quantum optimization for Target Identification by Enzymes

Target Identification by Enzymes (TIE) problem aims to identify the set of enzymes in a given metabolic network, such that their inhibition eliminates a given set of target compounds associated with a disease while incurring minimum damage to the rest of the compounds. This is an NP-complete problem, and thus optimal solutions using classical computers fail to scale to large metabolic networks. In this paper, we consider the TIE problem for identifying drug targets in metabolic networks. We develop the first quantum optimization solution, called QuTIE (Quantum optimization for Target Identification by Enzymes), to this NP-complete problem. We do that by developing an equivalent formulation of the TIE problem in Quadratic Unconstrained Binary Optimization (QUBO) form, then mapping it to a logical graph, which is then embedded on a hardware graph on a quantum computer. Our experimental results on 27 metabolic networks from Escherichia coli, Homo sapiens, and Mus musculus show that QuTIE yields solutions which are optimal or almost optimal. Our experiments also demonstrate that QuTIE can successfully identify enzyme targets already verified in wet-lab experiments for 14 major disease classes

Mutant methionyl-tRNA synthetase from bacteria enables site-selective N-terminal labeling of proteins expressed in mammalian cells

Newly synthesized cellular proteins can be tagged with a variety of metabolic labels that distinguish them from preexisting proteins and allow them to be identified and tracked. Many such labels are incorporated into proteins via the endogenous cellular machinery and can be used in numerous cell types and organisms. Though broad applicability has advantages, we aimed to develop a strategy to restrict protein labeling to specified mammalian cells that express a transgene. Here we report that heterologous expression of a mutant methionyl-tRNA synthetase from Escherichia coli permits incorporation of azidonorleucine (Anl) into proteins made in mammalian (HEK293) cells. Anl is incorporated site-selectively at N-terminal positions (in competition with initiator methionines) and is not found at internal sites. Site selectivity is enabled by the fact that the bacterial synthetase aminoacylates mammalian initiator tRNA, but not elongator tRNA. N-terminally labeled proteins can be selectively conjugated to a variety of useful probes; here we demonstrate use of this system in enrichment and visualization of proteins made during various stages of the cell cycle. N-terminal incorporation of Anl may also be used to engineer modified proteins for therapeutic and other applications

Spatial correlations in chaotic nanoscale systems with spin-orbit coupling

We investigate the statistical properties of wave functions in chaotic nanostructures with spin-orbit coupling (SOC), focussing in particular on spatial correlations of eigenfunctions. Numerical results from a microscopic model are compared with results from random matrix theory in the crossover from the gaussian orthogonal to the gaussian symplectic ensembles (with increasing SOC); one- and two-point distribution functions were computed to understand the properties of eigenfunctions in this crossover. It is found that correlations of wave function amplitudes are suppressed with SOC; nevertheless, eigenfunction correlations play a more important role in the two-point distribution function(s), compared to the case with vanishing SOC. Experimental consequences of our results are discussed.Comment: Submitted to PR

The software for oceanographic data management: VODC for PC 2.0

To manage and process a large amount of oceanographic data, users must have powerful tools that simplify these tasks. The VODC for PC is software designed to assist in managing oceanographic data. It based on 32 bits Windows operation system and used Microsoft Access database management system. With VODC for PC users can update data simply, convert to some international data formats, combine some VODC databases to one, calculate average, min, max fields for some types of data, check for valid data