Neuronal ApoE Regulates the Cell-to-Cell Transmission of α-Synuclein

The presence of protein inclusions, called Lewy bodies (LBs) and Lewy neurites (LNs), in the brain is the main feature of Parkinson’s disease (PD). Recent evidence that the prion-like propagation of α-synuclein (α-syn), as a major component of LBs and LNs, plays an important role in the progression of PD has gained much attention, although the molecular mechanism remains unclear. In this study, we evaluated whether neuronal ApoE regulates the cell-to-cell transmission of α-syn and explored its molecular mechanism using in vitro and in vivo model systems. We demonstrate that neuronal ApoE deficiency attenuates both α-syn uptake and release by downregulating LRP-1 and LDLR expression and enhancing chaperone-mediated autophagy activity, respectively, thereby contributing to α-syn propagation. In addition, we observed that α-syn propagation was attenuated in ApoE knockout mice injected with pre-formed mouse α-syn fibrils. This study will help our understanding of the molecular mechanisms underlying α-syn propagation.     

HDAC8-Selective Inhibition by PCI-34051 Enhances the Anticancer Effects of ACY-241 in Ovarian Cancer Cells

HDAC6 is overexpressed in ovarian cancer and is known to be correlated with tumorigenesis. Accordingly, ACY-241, a selective HDAC6 inhibitor, is currently under clinical trial and has been tested in combination with various drugs. HDAC8, another member of the HDAC family, has recently gained attention as a novel target for cancer therapy. Here, we evaluated the synergistic anticancer effects of PCI-34051 and ACY-241 in ovarian cancer. Among various ovarian cancer cells, PCI-34051 effectively suppresses cell proliferation in wild-type p53 ovarian cancer cells compared with mutant p53 ovarian cancer cells. In ovarian cancer cells harboring wild-type p53, PCI-34051 in combination with ACY-241 synergistically represses cell proliferation, enhances apoptosis, and suppresses cell migration. The expression of pro-apoptotic proteins is synergistically upregulated, whereas the expressions of anti-apoptotic proteins and metastasis-associated proteins are significantly downregulated in combination treatment. Furthermore, the level of acetyl-p53 at K381 is synergistically upregulated upon combination treatment. Overall, co-inhibition of HDAC6 and HDAC8 through selective inhibitors synergistically suppresses cancer cell proliferation and metastasis in p53 wild-type ovarian cancer cells. These results suggest a novel approach to treating ovarian cancer patients and the therapeutic potential in developing HDAC6/8 dual inhibitors.     

Electrospun PEDOT:PSS/PVP nanofibers as the chemiresistor in chemical vapour sensing

Herein, PEDOT:PSS/PVP nanofibers were produced by electrospinning. The presence of PEDOT:PSS in the nanofibers was confirmed by FT-Raman spectroscopy. The applied voltage-dependent diameter of PEDOT:PSS/PVP nanofibers was observed. Also, sensing behaviors of electrospun PEDOT:PSS/PVP nanofibers were explored by measuring its response upon cyclic exposure to organic vapours such as ethanol, methanol, THF, and acetone at room temperature. When PEDOT:PSS/PVP nanofibers were exposed to each solvent, the protic and aprotic solvents resulted in opposite electrical responses. These findings exhibit that electrospun PEDOT:PSS/PVP nanofibers are the promising candidate for the organic vapour sensing material.     

基于注入法的小电流接地系统故障定位新方法

介绍了基于“S注入法”的小电流接地系统单相接地故障选线定位保护。当故障停电后,该保护就存在绝缘恢复和定位困难的问题。为此提出了一种定位新方法。该方法通过向停电后的接地线路故障相外加恒定直流高压,再注入交流信号,并根据所注交流信号的消失点准确地判定故障位置。基于新方法的故障定位装置运行很成功。     

Fast Super‐Resolution Algorithm Based on Dictionary Size Reduction Using k‐Means Clustering

This paper proposes a computationally efficient learning‐based super‐resolution algorithm using k‐means clustering. Conventional learning‐based super‐resolution requires a huge dictionary for reliable performance, which brings about a tremendous memory cost as well as a burdensome matching computation. In order to overcome this problem, the proposed algorithm significantly reduces the size of the trained dictionary by properly clustering similar patches at the learning phase. Experimental results show that the proposed algorithm provides superior visual quality to the conventional algorithms, while needing much less computational complexity.     

Improved Scalar Multiplication on Elliptic Curves Defined over F2mn

We propose two improved scalar multiplication methods on elliptic curves over F_qn where q = 2^m using Frobenius expansion. The scalar multiplication of elliptic curves defined over subfield F_q can be sped up by Frobenius expansion. Previous methods are restricted to the case of a small m. However, when m is small, it is hard to find curves having good cryptographic properties. Our methods are suitable for curves defined over medium‐sized fields, that is, 10 ≤ m ≤ 20. These methods are variants of the conventional multiple‐base binary (MBB) method combined with the window method. One of our methods is for a polynomial basis representation with software implementation, and the other is for a normal basis representation with hardware implementation. Our software experiment shows that it is about 10% faster than the MBB method, which also uses Frobenius expansion, and about 20% faster than the Montgomery method, which is the fastest general method in polynomial basis implementation.