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.

Thalidomide pharmacokinetics and metabolite formation in mice, rabbits, and multiple myeloma patients.

Abstract: Purpose: Thalidomide has a variety of biological effects that vary considerably according to the species tested. We sought to establish whether differences in pharmacokinetics could form a basis for the species-specific effects of thalidomide. Experimental Design: Mice and rabbits were administered thalidomide (2 mg/kg) p.o. or i.v., and plasma concentrations of thalidomide were measured after drug administration using high performance liquid chromotography. Plasma samples from five multiple myeloma patients over 24 hours after their first dose of thalidomide (200 mg) were similarly analyzed and all data were fitted to a one-compartment model. Metabolites of thalidomide in plasma were identified simultaneously using liquid chromatography-mass spectrometry. Results: Plasma concentration-time profiles for the individual patients were very similar to each other, but widely different pharmacokinetic properties were found between patients compared with those in mice or rabbits. Area under the concentration curve values for mice, rabbits, and multiple myeloma patients were 4, 8, and 81 μmol/L · hour, respectively, and corresponding elimination half-lives were 0.5, 2.2, and 7.3 hours, respectively. Large differences were also observed between the metabolite profiles from the three species. Hydrolysis products were detected for all species, and the proportion of hydroxylated metabolites was higher in mice than in rabbits and undetectable in patients. Conclusions: Our results show major interspecies differences in the pharmacokinetics of thalidomide that are related to the altered degree of metabolism. We suggest that the interspecies differences in biological effects of thalidomide may be attributable, at least in part, to the differences in its metabolism and hence pharmacokinetics.

An adenosine analogue, IB-MECA, down-regulates estrogen receptor alpha and suppresses human breast cancer cell proliferation.

Abstract: Adenosine, a natural metabolite, plays important roles in several physiological and pathological processes, including modulation of cellular proliferation. Here, we report that among different adenosine analogues tested, micromolar concentrations of the A(3) adenosine receptor (A(3)AR)-selective agonist N(6)-(3-iodobenzyl)adenosine-5'-N-methyluronamide (IB-MECA) completely inhibited the growth of the human breast cancer cell lines MCF-7 and ZR-75 while inducing apoptosis in T47D and Hs578T cells, which do not express A(3)AR mRNA. In MCF-7 cells, A(3)AR overexpression did not increase the sensitivity to drug treatment and an A(3)AR antagonist did not abolish IB-MECA effect. In search for mechanisms of the effect of this ligand, we found that in estrogen receptor alpha (ERalpha)-positive cells, IB-MECA rapidly down-regulated ERalpha at mRNA and protein levels and consequently at the transcriptional activity level. Moreover, overexpression of ERalpha in MCF-7 cells alleviated the proliferation inhibition induced by IB-MECA. The inhibitory effects on cell growth and to some extent on ERalpha were mimicked by 2-chloro-adenosine >3'-deoxyadenosine> adenosine but not by a variety of other ligands. Our studies indicate that IB-MECA can down-regulate ERalpha and inhibit proliferation or induce apoptosis in different breast cancer cell types and raise the possibility of using this and related compounds in breast cancer treatment.

Role of hydrogen for the elastic properties of alumina thin films

Abstract: We describe the role of the presence of hydrogen on the elastic properties of AlxOyHz (0.32less than or equal toxless than or equal to0.4, 0.54less than or equal toyless than or equal to0.6, 3x10(- ...

An Extremely Fast Charging Li3V2(PO4)3 Cathode at a 4.8 V Cutoff Voltage for Li-Ion Batteries

Abstract: Energy storage materials with extreme fast charging (XFC) is currently a crucial technology for lithium-ion batteries (LIBs). However, it is generally believed that attaining both high power densit...

Mechanisms of laser drilling of metal plates underwater

Abstract: Several metal plates with different thickness including copper, iron, aluminum, and stainless steel have been drilled in the surroundings of air and water, respectively, by a Q-switched pulsed Nd:yttrium–aluminum–garnet laser. It is observed that for the same metal plate less energy is needed to drill a hole in water than that in air, and the surface morphology of hole drilled in water is improved greatly than that in air by comparison of the scanning electron micrographs. The underlying mechanisms behind the efficiency and quality enhancement in water are further investigated by means of optical beam deflection technique. The experimental results show that due to the water confinement the peak amplitude and duration of the laser-ablation-generated impact underwater is much larger than that in air. During the underwater laser drilling, besides laser ablation effect, both the first and second liquid-jet-induced impulses by cavitation bubble collapse in the vicinity of a solid boundary are also observed and...

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.