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.

Sleep circuitry and the hypnotic mechanism of GABAA drugs.

Abstract: Early in the twentieth century, von Economo provided the first evidence linking the hypothalamus with sleep-wake behavior. His studies concluded that the anterior hypothalamus was associated with sleep, whereas the posterior hypothalamus was associated with waking. In the decades following these observations, a wealth of research has shown that an elaborate circuitry comprising a number of brain regions, cell types, and extracellular messengers underlies sleep-wake behavior. In this review, we discuss data generated in the past 10 years that highlight the role of the hypothalamus in sleep-wake behavior and control. In particular, we will focus on the identification of the ventrolateral preoptic nucleus (VLPO) as a sleep center and the hypocretin/orexin cells in the perifornical region of the hypothalamus as constituting a waking center; these two centers are critical for the maintenance of normal sleep-wake architecture, and provide a foundation for our understanding of sleep-wake behavior and its underlying physiology. The data from these and other regions traditionally associated with the sleep-wake cycle have led to a flip-flop switch model of sleep-wake control. The switch is composed of two sets of mutually inhibitory groups of neurons: a sleep group and an arousal group, with the latter modulated by orexin-containing neurons in the lateral hypothalamus. The sleep-promoting GABA (gamma-amino-butyric acid) receptor agonists are a diverse class of drugs, which include barbiturates, benzodiazepines, chloral hydrate, ethanol, and gaseous anesthetics, that have been used to study sleep physiology for many years. Recent studies suggest that these drugs may exert their hypnotic effects in a regionally specific manner. For example, some GABAA agonists appear to promote sleep by inhibiting the histaminergic cells in the tuberomammillary nucleus and weakly activating the VLPO via agonist binding to the alpha1 subunit of GABAA receptors; whereas, gaboxadol (THIP; 4,5,6,7-tetrahydroisoxazolo[5,4-c]pyridin-3-ol) binds to the alpha4delta-subunits, potentially promoting sleep by activation of the VLPO. The integration of these data into the flip-flop switch model can be used to better understand sleep-wake control and augment existing therapeutic treatments for sleep disorders.

microRNA Expression during Trophectoderm Specification

Abstract: Background Segregation of the trophectoderm from the inner cell mass of the embryo represents the first cell-fate decision of mammalian development. Transcription factors essential for specifying trophectoderm have been identified, but the role of microRNAs (miRNAs) in modulating this fate-choice has been largely unexplored. We have compared miRNA expression in embryonic stem cell (ESC)-derived trophectoderm and in staged murine embryos to identify a set of candidate miRNAs likely to be involved in trophectoderm specification.

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.