Yi Chen

Bio: Yi Chen is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Large Hadron Collider & Medicine. The author has an hindex of 217, co-authored 4342 publications receiving 293080 citations. Previous affiliations of Yi Chen include Rochester Institute of Technology & National Institutes of Health.

R16, a novel amonafide analogue, induces apoptosis and G2-M arrest via poisoning topoisomerase II.

Abstract: Amonafide, a naphthalimide derivative, although selected for exploratory clinical trials for its potent anticancer activity, has long been challenged by its unpredictable side effects. In the present study, a novel amonafide analogue, 2-(2-dimethylamino)-6-thia-2-aza-benzo-[def]-chrysene-1,3-diones (R16) was synthesized by substituting 5'-NH(2) of the naphthyl with a heterocyclic group to amonafide, with additional introduction of a thiol group. In a panel of various human tumor cell lines, R16 was more cytotoxic than its parent compound amonafide. It was also effective against multidrug-resistant cells. Importantly, the i.p. administration of R16 inhibited tumor growth in mice implanted with S-180 sarcoma and H(22) hepatoma. The molecular and cellular machinery studies showed that the R16 functions as a topoisomerase II (topo II) poison via binding to the ATPase domain of human topo IIalpha. The superior cytotoxicity of R16 to amonafide was ascribed to its potent effects on trapping topo II-DNA cleavage complexes. Moreover, using a topo II catalytic inhibitor aclarubicin, ataxia-telangiectasia-mutated (ATM)/ATM- and Rad3-related (ATR) kinase inhibitor caffeine and topo II-deficient HL-60/MX2 cells, we further showed that R16-triggered DNA double-strand breaks, tumor cell cycle arrest, and apoptosis were in a topo II-dependent manner. Taken together, R16 stood out by its improved anticancer activity, appreciable anti-multidrug resistance activities, and well-defined topo II poisoning mechanisms, as comparable with the parent compound amonafide. All these collectively promise the potential value of R16 as an anticancer drug candidate, which deserves further development.

Access scheme of Multi-Level Cell Spin-Transfer Torque Random Access Memory and its optimization

Abstract: In this work, we study the access (read and write) scheme of the newly proposed Multi-Level Cell Spin-Transfer Torque Random Access Memory (MLC STT-RAM) from both the circuit design and architectural perspectives. Based on the physical principles of the resistance state transition of MLC STT-RAM, we proposed a read circuitry based on Dichotomic search algorithm and three write schemes with various design complexities - simple, complex, and hybrid schemes. The circuit and architectural level evaluations were conducted to analyze the power and performance tradeoffs in each proposed write mechanisms of MLC STT-RAM.

A novel glycidyl methacrylate-based monolith with sub-micron skeletons and well-defined macropores

Abstract: A series of glycidyl methacrylate-based polymer monoliths, including spherical walled structures, sub-micron skeletons, and lamellar morphologies, are reproducibly prepared by high internal phase emulsions in combination with block copolymer chemistry. The morphologies could be manipulated over a wide range by only altering the typical tri-block copolymer (Pluronic F127) concentration. The ability of the Pluronic F127 to direct supramolecular self-assembly is the main reason for the rich phase behavior exhibited such as the micellar phase (i.e., spherical micelles, wormlike micelles), the bicontinuous phase, and the lamellar phase. Equally important, the glycidyl methacrylate-based monoliths differ significantly from conventional polymer monoliths; they have sub-micron skeletons (100–1000 nm), micrometer-sized throughpores, relatively large specific surface area (161 m2 g−1), and excellent permeability (6.1 × 10−13 m2). Further, the monoliths display superiority in fast and high-throughput separation of proteins. This, together with easy fabrication makes the novel monoliths a promising alternative to commercially available monolithic supports.

Memristor-Based Design of Sparse Compact Convolutional Neural Network

Abstract: Memristor has been widely studied for hardware implementation of neural networks due to the advantages of nanometer size, low power consumption, fast switching speed and functional similarity to biological synapse. However, it is difficult to realize memristor-based deep neural networks for there exist a large number of network parameters in general structures such as LeNet, FCN, etc. To mitigate this problem, this paper aims to design a memristor-based sparse compact convolutional neural network (MSCCNN) to reduce the number of memristors. We firstly use an average pooling and $1\times 1$ convolutional layer to replace fully connected layers. Meanwhile, depthwise separation convolution is utilized to replace traditional convolution to further reduce the number of parameters. Furthermore, a network pruning method is adopted to remove the redundant memristor crossbars for depthwise separation convolutional layers. Therefore, a more compact network structure is obtained while the recognition accuracy remaining unchanged. Simulation results show that the designed model achieves superior accuracy rates while greatly reducing the scale of the hardware circuit. Compared with traditional designs of memristor-based CNN, our proposed model has smaller area and lower power consumption.

Identification of boosted, hadronically decaying W bosons and comparisons with ATLAS data taken at √s = 8 TeV

Abstract: This paper reports a detailed study of techniques for identifying boosted, hadronically decaying W bosons using 20.3 fb −¹ of proton–proton collision data collected by the ATLAS detector at the LHC at a centre-of-mass energy √s = 8 TeV. A range of techniques for optimising the signal jet mass resolution are combined with various jet substructure variables. The results of these studies in Monte Carlo simulations show that a simple pairwise combination of groomed jet mass and one substructure variable can provide a 50 % efficiency for identifying W bosons with transverse momenta larger than 200 GeV while maintaining multijet background efficiencies of 2–4 % for jets with the same transverse momentum. These signal and background efficiencies are confirmed in data for a selection of tagging techniques.

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 …

KEGG: Kyoto Encyclopedia of Genes and Genomes

Abstract: Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

Atherosclerosis — An Inflammatory Disease

Abstract: Atherosclerosis is an inflammatory disease. Because high plasma concentrations of cholesterol, in particular those of low-density lipoprotein (LDL) cholesterol, are one of the principal risk factors for atherosclerosis,1 the process of atherogenesis has been considered by many to consist largely of the accumulation of lipids within the artery wall; however, it is much more than that. Despite changes in lifestyle and the use of new pharmacologic approaches to lower plasma cholesterol concentrations,2,3 cardiovascular disease continues to be the principal cause of death in the United States, Europe, and much of Asia.4,5 In fact, the lesions of atherosclerosis represent . . .