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.

Heteroatom-Doped Porous Carbon Materials with Unprecedented High Volumetric Capacitive Performance

Abstract: The design of carbon-based materials with a high mass density and large porosity has always been a challenging goal, since they fulfill the demands of next-generation supercapacitors and other electrochemical devices. We report a new class of high-density heteroatom-doped porous carbon that can be used as an aqueous-based supercapacitor material. The material was synthesized by an in situ dehalogenation reaction between a halogenated conjugated diene and nitrogen-containing nucleophiles. Under the given conditions, pyridinium salts can only continue to perform the dehalogenation if there is residue water remaining from the starting materials. The obtained carbon materials are highly doped by various heteroatoms, leading to high densities, abundant multimodal pores, and an excellent volumetric capacitive performance. Porous carbon tri-doped with nitrogen, phosphorous, and oxygen exhibits a high packing density (2.13 g cm-3 ) and an exceptional volumetric energy density (36.8 Wh L-1 ) in alkaline electrolytes, making it competitive to even some Ni-MH cells.

Effect of the size-selective silver clusters on lithium peroxide morphology in lithium-oxygen batteries.

Abstract: Lithium-oxygen batteries have the potential needed for long-range electric vehicles, but the charge and discharge chemistries are complex and not well understood. The active sites on cathode surfaces and their role in electrochemical reactions in aprotic lithium-oxygen cells are difficult to ascertain because the exact nature of the sites is unknown. Here we report the deposition of subnanometre silver clusters of exact size and number of atoms on passivated carbon to study the discharge process in lithium-oxygen cells. The results reveal dramatically different morphologies of the electrochemically grown lithium peroxide dependent on the size of the clusters. This dependence is found to be due to the influence of the cluster size on the formation mechanism, which also affects the charge process. The results of this study suggest that precise control of subnanometre surface structure on cathodes can be used as a means to improve the performance of lithium-oxygen cells.

Basal ganglia control of sleep-wake behavior and cortical activation

Abstract: The basal ganglia (BG) are involved in numerous neurobiological processes that operate on the basis of wakefulness, including motor function, learning, emotion and addictive behaviors. We hypothesized that the BG might play an important role in the regulation of wakefulness. To test this prediction, we made cell body-specific lesions in the striatum and globus pallidus (GP) using ibotenic acid. We found that rats with striatal (caudoputamen) lesions exhibited a 14.95% reduction in wakefulness and robust fragmentation of sleep-wake behavior, i.e. an increased number of state transitions and loss of ultra-long wake bouts (> 120 min). These lesions also resulted in a reduction in the diurnal variation of sleep-wakefulness. On the other hand, lesions of the accumbens core resulted in a 26.72% increase in wakefulness and a reduction in non-rapid eye movement (NREM) sleep bout duration. In addition, rats with accumbens core lesions exhibited excessive digging and scratching. GP lesions also produced a robust increase in wakefulness (45.52%), and frequent sleep-wake transitions and a concomitant decrease in NREM sleep bout duration. Lesions of the subthalamic nucleus or the substantia nigra reticular nucleus produced only minor changes in the amount of sleep-wakefulness and did not alter sleep architecture. Finally, power spectral analysis revealed that lesions of the striatum, accumbens and GP slowed down the cortical electroencephalogram. Collectively, our results suggest that the BG, via a cortico-striato-pallidal loop, are important neural circuitry regulating sleep-wake behaviors and cortical activation.

Human multipotent stromal cells from bone marrow and microRNA: regulation of differentiation and leukemia inhibitory factor expression.

Abstract: We observed that microRNAs (miRNAs) that regulate differentiation in a variety of simpler systems also regulate differentiation of human multipotent stromal cells (hMSCs) from bone marrow. Differentiation of hMSCs into osteoblasts and adipocytes was inhibited by using lentiviruses expressing shRNAs to decrease expression of Dicer and Drosha, two enzymes that process early transcripts to miRNA. Expression analysis of miRNAs during hMSC differentiation identified 19 miRNAs that were up-regulated during osteogenic differentiation and 20 during adipogenic differentiation, 11 of which were commonly up-regulated in both osteogenic and adipogenic differentiation. In silico models predicted that five of the up-regulated miRNAs targeted leukemia inhibitory factor (LIF) expression. The prediction was confirmed for two of the miRNAs, hsa-mir 199a and hsa-mir346, in that over-expression of the miRNAs decreased LIF secretion by hMSCs. The results demonstrate that differentiation of hMSCs is regulated by miRNAs and that several of these miRNAs target LIF.

The pontine REM switch: past and present.

Abstract: Rapid eye movement (REM) sleep is a behavioural state characterized by activation of the cortical and hippocampal EEG, rapid eye movements and muscle atonia. For the past 30 years, the most widely accepted neural circuitry model for the regulation of REM sleep has emphasized reciprocal inhibitory interactions between pontine brainstem monoaminergic and cholinergic neurons. In general support of the reciprocal interaction model, neuropharmacological studies have shown that cholinergic agonists promote REM sleep and muscarinic antagonists and monoamines inhibit REM sleep. It has nevertheless proven difficult to reconcile both the theoretical framework of this model and the pharmacological data with the fact that selective lesions of either cholinergic or monoaminergic (noradrenergic, serotoninergic or dopaminergic) nuclei in the brainstem have relatively limited effects on REM sleep. Recent work by our laboratory has revealed the presence of non-cholinergic and non-monoaminergic mutually inhibitory REM-off and REM-on areas in the mesopontine tegmentum that may form the neuroanatomical basis of the switching circuitry for REM sleep. These findings posit a REM switching circuitry model that is analogous to an electronic 'flip-flop' switch. In this flip-flop switch arrangement, GABAergic REM-on neurons (located in the sublaterodorsal tegmental nucleus (SLD)) inhibit GABAergic REM-off neurons (located in the ventrolateral periaqueductal grey matter (vlPAG) and lateral pontine tegmentum (LPT)) and vice versa. In the REM-on area are two populations of glutamatergic neurons, the first of which projects to the basal forebrain and regulates EEG components of REM sleep and the second of which projects to the ventromedial medulla and spinal cord and regulates atonia during REM sleep. Our findings demonstrating independent pathways mediating atonia and the EEG components of REM provide a basis for their occasional dissociation in pathological states, e.g. REM sleep behaviour disorder.

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.