Lysine specific demethylase 1 (LSD1), the first identified histone demethylase, plays an important role in epigenetic regulation of gene activation and repression. The up-regulated LSD1's expression has been reported in several malignant tumors. In the current study, we designed and synthesized five series of 1, 2, 3-triazole-dithiocarbamate hybrids and screened their inhibitory activity toward LSD1. We found that some of these compounds, especially compound 26, exhibited the most specific and robust inhibition of LSD1. Interestingly, compound 26 also showed potent and selective cytotoxicity against LSD1 overexpressing gastric cancer cell lines MGC-803 and HGC-27, as well as marked inhibition of cell migration and invasion, compared to 2-PCPA. Furthermore, compound 26 effectively reduced the tumor growth bared by human gastric cancer cells in vivo with no signs of adverse side effects. These findings suggested that compound 26 deserves further investigation as a lead compound in the treatment of LSD1 overexpressing gastric cancer.

Inductors are essential components of radio frequency integrated circuits (RFICs). While the active devices in RF systems downscale steadily, inductors have not been able to keep up with the pace of continual miniaturization because of the trade-off between size and performance as well as fabrication complexity. Strain-induced self-rolled-up nanotechnology allows the formation of three-dimensional (3D) architectures, such as multiple-turn spiral tubes, through planar processing. Here, we report on using 3D SiN(x) tubular structures with accompanying prepatterned metal layers, as a novel on-chip tube inductor design platform. We found, by an equivalent lumped circuit and electromagnetic modeling, that the 3D metal spiral structure has the ability to significantly better confine magnetic field compared to conventional planar spiral on-chip inductors. More than 100× reduction in footprint can be realized using this platform while achieving excellent electrical performance, including large inductance, high quality (Q) factor, and high self-resonance frequency (f(0)).

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In this letter, the support vector machine (SVM) regression approach is introduced to model the three-dimensional (3-D) high density microwave packaging structure. The SVM is based on the structural risk minimization principle, which leads to a good generalization ability. With a 3-D vertical interconnect used as an example, the SVM regression model is electromagnetically developed with a set of training data and testing data, which is produced by the electromagnetic simulation. Experimental results suggest that the developed model performs with a good predictive ability in analyzing the electrical performance. Index Terms-Fuzz button, low temperature co-fired ceramic (LTCC), support vector machine (SVM), support vector regression (SVR), three-dimensional (3-D) vertical interconnect.

This paper proposes an efficient parameter extraction algorithm for GaN high electron mobility transistors smallsignal equivalent circuit model. The algorithm combines parameter scanning and iteration methods to solve the problem of error accumulation in conventional methods and is implemented in MATLAB programming. By using the iteration method, the algorithm each time uses more accurate element values thus makes the results converge to the optimal value faster. A 20-element small-signal equivalent circuit model of GaN high electron mobility transistors is used to validate the proposed algorithm, and the results show that the calculated S-parameters agree well with the measured S-parameters within the frequency range of 0.1 to 40 GHz.