Jun Lu

Bio: Jun Lu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Materials science. The author has an hindex of 135, co-authored 1526 publications receiving 99767 citations. Previous affiliations of Jun Lu include Drexel University & Argonne National Laboratory.

Structural basis for the cooperative allosteric activation of the free fatty acid receptor GPR40

Abstract: Clinical studies indicate that partial agonists of the G-protein-coupled, free fatty acid receptor 1 GPR40 enhance glucose-dependent insulin secretion and represent a potential mechanism for the treatment of type 2 diabetes mellitus. Full allosteric agonists (AgoPAMs) of GPR40 bind to a site distinct from partial agonists and can provide additional efficacy. We report the 3.2-A crystal structure of human GPR40 (hGPR40) in complex with both the partial agonist MK-8666 and an AgoPAM, which exposes a novel lipid-facing AgoPAM-binding pocket outside the transmembrane helical bundle. Comparison with an additional 2.2-A structure of the hGPR40-MK-8666 binary complex reveals an induced-fit conformational coupling between the partial agonist and AgoPAM binding sites, involving rearrangements of the transmembrane helices 4 and 5 (TM4 and TM5) and transition of the intracellular loop 2 (ICL2) into a short helix. These conformational changes likely prime GPR40 to a more active-like state and explain the binding cooperativity between these ligands.

Mudskipper genomes provide insights into the terrestrial adaptation of amphibious fishes

Abstract: Mudskippers are amphibious fishes that have adapted to live on mudflats. Here, the authors sequence the genomes of four different mudskipper species and highlight genetic changes that may have had an evolutionary role in the water-to-land transition of vertebrates.

Anion-redox nanolithia cathodes for Li-ion batteries

Abstract: The significant phase change between gaseous and crystalline oxygen deteriorates the performance of lithium–air batteries. Here the authors report a battery with a cathode consisting of Li2O and Co3O4 nanocomposites, which displays stable cyclability and high energy density, without involving any gas evolution.

Effect of Ti Intermetallic Catalysts on Hydrogen Storage Properties of Magnesium Hydride

Abstract: Magnesium hydride is a promising candidate for solid-state hydrogen storage and thermal energy storage applications. A series of Ti-based intermetallic alloy (TiAl, Ti3Al, TiNi, TiFe, TiNb, TiMn2, and TiVMn)-doped MgH2 materials were systematically investigated in this study to improve its hydrogen storage properties. The dehydrogenation and hydrogenation properties were studied by using both thermogravimetric analysis and pressure–composition–temperature (PCT) isothermal to characterize the temperature of dehydrogenation and the kinetics of both desorption and absorption of hydrogen by these doped MgH2. Results show significant improvements of both dehydrogenation and hydrogenation kinetics as a result of adding the Ti intermetallic alloys as catalysts. In particular, the TiMn2-doped Mg demonstrated extraordinary hydrogen absorption capability at room temperature and 1 bar hydrogen pressure. The PCT experiments also show that the hydrogen equilibrium pressures of MgH2 were not affected by these additives.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.