Yu Huang

Bio: Yu Huang 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 136, co-authored 1492 publications receiving 89209 citations. Previous affiliations of Yu Huang include The Chinese University of Hong Kong & Samsung.

Integrated optimization model of laser brazing by extreme learning machine and genetic algorithm

Abstract: Welding parameters play a significant role in determining the bead geometry and hence the quality of the weld joint. To further improve prediction accuracy and optimization quality of laser brazing, the published experiment results are utilized to build a prediction model of top and bottom width of weld bead and further establish an optimization model by a novel hybrid extreme learning machine and genetic algorithm method. Firstly, about two-third experiment results are used to train the extreme learning machine network for suitable weights, and then the rest one-third experiments are selected as a test set to illustrate the validity and reliability of the prediction network. Then, by regarding the prediction values from the extreme learning machine as the fitness values of genetic algorithm, optimal results of the inputs and outputs are obtained through the procedure of selection, crossover, and mutation. Eventually, the final optimization results are confirmed by verification experiments. Meanwhile, the hybrid model is more accurate and stable than that using back propagation neural network and genetic algorithm. In the whole, the proposed method in this paper is an effective and accurate way for optimizing laser brazing welding parameters and guiding the actual welding process.

Plasmonic/Nonlinear Optical Material Core/Shell Nanorods as Nanoscale Plasmon Modulators and Optical Voltage Sensors

Abstract: Herein, we report the design and synthesis of plasmonic/non-linear optical (NLO) material core/shell nanostructures that can allow dynamic manipulation of light signals using an external electrical field and enable a new generation of nanoscale optical voltage sensors. We show that gold nanorods (Au NRs) can be synthesized with tunable plasmonic properties and function as the nucleation seeds for continued growth of a shell of NLO materials (such as polyaniline, PANI) with variable thickness. The formation of a PANI nanoshell allows dynamic modulation of the dielectric environment of the plasmonic Au NRs, and therefore the plasmonic resonance characteristics, by an external electrical field. The finite element simulation confirms that such modulation is originated from the field-induced modulation of the dielectric constant of the NLO shell. This approach is general, and the coating of the Au NRs with other NLO materials (such as barium titanate, BTO) is found to produce a similar effect. These findings can not only open a new pathway to active modulation of plasmonic resonance at the sub-wavelength scale but also enable the creation of a new generation of nanoscale optical voltage sensors (NOVS).

Cyclic Nucleotide-Gated Channels Contribute to Thromboxane A2-Induced Contraction of Rat Small Mesenteric Arteries

Abstract: BACKGROUND Thromboxane A(2) (TxA(2))-induced smooth muscle contraction has been implicated in cardiovascular, renal and respiratory diseases. This contraction can be partly attributed to TxA(2)-induced Ca(2+) influx, which resulted in vascular contraction via Ca(2+)-calmodulin-MLCK pathway. This study aims to identify the channels that mediate TxA(2)-induced Ca(2+) influx in vascular smooth muscle cells. METHODOLOGY/PRINCIPAL FINDINGS Application of U-46619, a thromboxane A(2) mimic, resulted in a constriction in endothelium-denuded small mesenteric artery segments. The constriction relies on the presence of extracellular Ca(2+), because removal of extracellular Ca(2+) abolished the constriction. This constriction was partially inhibited by an L-type Ca(2+) channel inhibitor nifedipine (0.5-1 microM). The remaining component was inhibited by L-cis-diltiazem, a selective inhibitor for CNG channels, in a dose-dependent manner. Another CNG channel blocker LY83583 [6-(phenylamino)-5,8-quinolinedione] had similar effect. In the primary cultured smooth muscle cells derived from rat aorta, application of U46619 (100 nM) induced a rise in cytosolic Ca(2+) ([Ca(2+)](i)), which was inhibited by L-cis-diltiazem. Immunoblot experiments confirmed the presence of CNGA2 protein in vascular smooth muscle cells. CONCLUSIONS/SIGNIFICANCE These data suggest a functional role of CNG channels in U-46619-induced Ca(2+) influx and contraction of smooth muscle cells.

TM9SF4 is a novel factor promoting autophagic flux under amino acid starvation

Abstract: Autophagy is a highly complicated process with participation of large numbers of autophagy-related proteins. Under nutrient starvation, autophagy promotes cell survival by breaking down nonessential cellular components for recycling use. However, due to its high complexity, molecular mechanism of autophagy is still not fully understood. In the present study, we report a novel autophagy-related protein TM9SF4, which plays a functional role in the induction phase of autophagic process. TM9SF4 proteins were abundantly expressed in the kidney, especially in renal proximal tubular epithelial cells. At subcellular cells, TM9SF4 proteins were mostly localized in lysosome, Golgi, late endosome and autophagosome. Knockdown of TM9SF4 with TM9SF4-shRNAs markedly reduced the starvation-induced autophagy in HEK293 cells, the effect of which persisted in the presence of bafilomycin A1. TM9SF4-shRNAs also substantially attenuated the starvation-induced mTOR inactivation. In animal model, starvation was able to induce LC3-II accumulation and cause mTOR inactivation in renal cortical tissue in wild-type mice, the effect of which was minimal/absent in TM9SF4 knockout (TM9SF4−/−) mice. Co-immunoprecipitation and proximity ligation assay demonstrated physical interaction of TM9SF4 proteins with mTOR. In addition, knockdown or knockout of TM9SF4 reduced the starvation-induced cell death in HEK293 cells and animal model. Taken together, the present study identifies TM9SF4 as a novel autophagy-related protein. Under nutrient starvation, TM9SF4 functions to facilitate mTOR inactivation, resulting in an enhanced autophagic flux, which serves to protect cells from apoptotic cell death.

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.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。