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.

Facet-Dependent Thermal Instability in LiCoO2.

Abstract: Thermal runaways triggered by the oxygen release from oxide cathode materials pose a major safety concern for widespread application of lithium ion batteries. Utilizing in situ aberration-corrected scanning transmission electron microscopy (STEM) and electron energy loss spectroscopy (EELS) at high temperatures, we show that oxygen release from LixCoO2 cathode crystals is occurring at the surface of particles. We correlated this local oxygen evolution from the LixCoO2 structure with local phase transitions spanning from layered to spinel and then to rock salt structure upon exposure to elevated temperatures. Ab initio molecular dynamics simulations (AIMD) results show that oxygen release is highly dependent on LixCoO2 facet orientation. While the [001] facets are stable at 300 °C, oxygen release is observed from the [012] and [104] facets, where under-coordinated oxygen atoms from the delithiated structures can combine and eventually evolve as O2. The novel understanding that emerges from the present stud...

Pharmacological modulation of the AKT/microRNA-199a-5p/CAV1 pathway ameliorates cystic fibrosis lung hyper-inflammation

Abstract: In cystic fibrosis (CF) patients, hyper-inflammation is a key factor in lung destruction and disease morbidity. We have previously demonstrated that macrophages drive the lung hyper-inflammatory response to LPS in CF mice, because of reduced levels of the scaffold protein CAV1 with subsequent uncontrolled TLR4 signalling. Here we show that reduced CAV1 and, consequently, increased TLR4 signalling, in human and murine CF macrophages and murine CF lungs, is caused by high microRNA-199a-5p levels, which are PI3K/AKT-dependent. Downregulation of microRNA-199a-5p or increased AKT signalling restores CAV1 expression and reduces hyper-inflammation in CF macrophages. Importantly, the FDA-approved drug celecoxib re-establishes the AKT/miR-199a-5p/CAV1 axis in CF macrophages, and ameliorates lung hyper-inflammation in Cftr-deficient mice. Thus, we identify the AKT/miR-199a-5p/CAV1 pathway as a regulator of innate immunity, which is dysfunctional in CF macrophages contributing to lung hyper-inflammation. In addition, we found that this pathway can be targeted by celecoxib.

Multiepitope Trojan Antigen Peptide Vaccines for the Induction of Antitumor CTL and Th Immune Responses

Abstract: We describe in this study a strategy to produce synthetic vaccines based on a single polypeptide capable of eliciting strong immune responses to a combination CTL and Th epitopes with the purpose of treating malignancies or preventing infectious diseases. This strategy is based on the capacity of Trojan Ags to deliver exogenous Ags into the intracellular compartments, where processing into MHC-binding peptides takes place. Our previous work demonstrated that Trojan Ags containing a CTL epitope localized to intracellular compartments, where MHC class I-binding peptides were generated in a TAP-independent fashion by the action of various exopeptidases and the endopeptidase furin. In this study, we report that Trojan Ags containing several CTL epitopes joined via furin-sensitive linkers generated all of the corresponding MHC class I-binding peptides, which were recognized by CTL. However, Trojan Ags prepared with furin-resistant linkers failed to produce the MHC class I-binding peptides. We also present data indicating that Trojan Ags bearing both CTL and Th epitopes can generate the corresponding MHC class I- and II-binding peptides, which are capable of stimulating T cell responses. Most significantly, in vivo vaccination of mice with a single injection of multiepitope Trojan Ags resulted in strong CTL and Th responses that translated into significant antitumor responses in a model of malignant melanoma. The overall results indicate that Trojan Ags prepared with furin-sensitive linkers are ideal candidates for producing synthetic multiepitope vaccines for the induction of CTL and Th responses that could be used against a variety of diseases, including cancer.

An Aqueous Dual‑Ion Battery Cathode of Mn 3 O 4 via Reversible Insertion of Nitrate

Abstract: We report reversible electrochemical insertion of NO3 - into manganese(II, III) oxide (Mn3 O4 ) as a cathode for aqueous dual-ion batteries. Characterization by TGA, FTIR, EDX, XANES, EXAFS, and EQCM collectively provides unequivocal evidence that reversible oxidative NO3 - insertion takes place inside Mn3 O4 . Ex situ HRTEM and corresponding EDX mapping results suggest that NO3 - insertion de-crystallizes the structure of Mn3 O4 . Kinetic studies reveal fast migration of NO3 - in the Mn3 O4 structure. This finding may open a new direction for novel low-cost aqueous dual-ion batteries.

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.