United States Department of Energy

About: United States Department of Energy is a government organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Coal & Catalysis. The organization has 13656 authors who have published 14177 publications receiving 556962 citations. The organization is also known as: DOE & Department of Energy.

Spatial Mapping of Lipids at Cellular Resolution in Embryos of Cotton

Abstract: Advances in mass spectrometry (MS) have made comprehensive lipidomics analysis of complex tissues relatively commonplace. These compositional analyses, although able to resolve hundreds of molecular species of lipids in single extracts, lose the original cellular context from which these lipids are derived. Recently, high-resolution MS of individual lipid droplets from seed tissues indicated organelle-to-organelle variation in lipid composition, suggesting that heterogeneity of lipid distributions at the cellular level may be prevalent. Here, we employed matrix-assisted laser desorption/ ionization–MS imaging (MALDI-MSI) approaches to visualize lipid species directly in seed tissues of upland cotton (Gossypium hirsutum). MS imaging of cryosections of mature cotton embryos revealed a distinct, heterogeneous distribution of molecular species of triacylglycerols and phosphatidylcholines, the major storage and membrane lipid classes in cotton embryos. Other lipids were imaged, including phosphatidylethanolamines, phosphatidic acids, sterols, and gossypol, indicating the broad range of metabolites and applications for this chemical visualization approach. We conclude that comprehensive lipidomics images generated by MALDI-MSI report accurate, relative amounts of lipid species in plant tissues and reveal previously unseen differences in spatial distributions providing for a new level of understanding in cellular biochemistry.

Structure of neutral aluminum clusters Al n ( 2 ⩽ n ⩽ 23 ) : Genetic algorithm tight-binding calculations

Abstract: We performed global structural optimizations for neutral aluminum clusters ${\mathrm{Al}}_{n}$ ($n$ up to 23) using a genetic algorithm (GA) coupled with a tight-binding interatomic potential. Structural candidates obtained from our GA search were further optimized by using first-principles total energy calculations. We report the lowest energy structures of neutral ${\mathrm{Al}}_{n}$ $(n=2\ensuremath{-}23)$. We found that the icosahedral structure of ${\mathrm{Al}}_{13}$ serves as the core for the growth of aluminum clusters from ${\mathrm{Al}}_{14}$ to ${\mathrm{Al}}_{18}$.