No requirement of TRPV1 in long-term potentiation or long-term depression in the anterior cingulate cortex

One major interest in the study of transient receptor potential vanilloid type 1 (TRPV1) in sensory system is that it may serve as a drug target for treating chronic pain. While the roles of TRPV1 in peripheral nociception and sensitization have been well documented, less is known about its contribution to pain-related cortical plasticity. Here, we used 64 multi-electrode array recording to examine the potential role of TRPV1 in two major forms of synaptic plasticity, long-term potentiation (LTP) and long-term depression (LTD), in the anterior cingulate cortex (ACC). We found that pharmacological blockade of TRPV1 with either [(E)-3-(4-t-Butylphenyl)-N-(2,3-dihydrobenzo[b][1,4]dioxin-6-yl)acrylamide] (AMG9810, 10 μM) or N-(3-methoxyphenyl)-4-chlorocinnamide (SB366791, 20 μM) failed to affect LTP induced by strong theta burst stimulation in the ACC of adult mice. Similarly, neither AMG9810 nor SB366791 blocked the cingulate LTD induced by low-frequency stimulation. Analysis of the results from different layers of the ACC obtained the same conclusions. Spatial distribution of LTP or LTD-showing channels among the ACC network was also unaltered by the TRPV1 antagonists. Since cortical LTP and LTD in the ACC play critical roles in chronic pain triggered by inflammation or nerve injury, our findings suggest that TRPV1 may not be a viable target for treating chronic pain, especially at the cortical level

Identification of the Most Fragile Component for a Typical RC Bridge Using Seismic Fragility Curves

This paper identifies the most fragile component of a typical reinforced concrete (RC) continuous girder bridge through the seismic fragility analysis. The typical bridge, Liang-Zi River bridge located in Shandong Province of China, is taken as the case study. The Cloud analysis approach is adopted to construct the probabilistic seismic demand models (PSDMs). Both of the record-to-record uncertainty in ground motions and the structural model uncertainty are considered in the PSDMs by using several approaches such as the selection of real ground motion records from the NGA-West2 database and the Latin Hypercube Sampling (LHS) approach. The damage limit states defined refer to piers and bearings which are commonly regarded as the fragile components. Furthermore, the seismic fragility curves of components and the bridge system are developed. Results show that the middle piers are more fragile than the side piers; the bearings are more fragile than piers; it is different from experiences that the fixed bearings at the top of the middle pier are not always more fragile than sliding bearings at both of the transverse and longitudinal loading conditions

Effects of Geometrical Symmetry on the Vortex Nucleation and Penetration in Mesoscopic Superconductors

We investigate how the geometrical symmetry affects the penetration and arrangement of vortices in mesoscopic superconductors using self-consistent Bogoliubov-de Gennes equations. We find that the entrance of the vortex happens when the current density at the hot spots reaches the depairing current density. Through determining the spatial distribution of hot spots, the geometrical symmetry of the superconducting sample influences the nucleation and entrance of vortices. Our results propose one possible experimental approach to control and manipulate the quantum states of mesoscopic superconductors with their topological geometries, and they can be easily generalized to the confined superfluids and Bose-Einstein condensates

CSD: Discriminance with Conic Section for Improving Reverse k Nearest Neighbors Queries

The reverse $k$ nearest neighbor (R$k$NN) query finds all points that have the query point as one of their $k$ nearest neighbors ($k$NN), where the $k$NN query finds the $k$ closest points to its query point. Based on the characteristics of conic section, we propose a discriminance, named CSD (Conic Section Discriminance), to determine points whether belong to the R$k$NN set without issuing any queries with non-constant computational complexity. By using CSD, we also implement an efficient R$k$NN algorithm CSD-R$k$NN with a computational complexity at $O(k^{1.5}\cdot log\,k)$. The comparative experiments are conducted between CSD-R$k$NN and other two state-of-the-art RkNN algorithms, SLICE and VR-R$k$NN. The experimental results indicate that the efficiency of CSD-R$k$NN is significantly higher than its competitors

A new dawn for the use of traditional Chinese medicine in cancer therapy

Although traditional Chinese medicine has benefitted one fifth of the world's population in treating a plethora of diseases, its acceptance as a real therapeutic option by the West is only now emerging. In light of a new wave of recognition being given to traditional Chinese medicine by health professionals and regulatory bodies in the West, an understanding of their molecular basis and highlighting potential future applications of a proven group of traditional Chinese medicine in the treatment of a variety of cancers is crucial – this is where their calling holds much hope and promise in both animal and human trials. Furthermore, the rationale for combining conventional agents and modern biotechnological approaches to the delivery of traditional Chinese medicine is an avenue set to revolutionize the future practice of cancer medicine – and this may well bring on a new dawn of therapeutic strategies where East truly meets West