A new family of synthetic diterpenes that regulates cytokine synthesis by inhibiting IkappaBalpha phosphorylation

The synthesis and the biological evaluation of a new family diterpenes are presented. The synthetic studies were inspired by the structural framework of acanthoic acid (1) and yielded a family of compounds that were evaluated as anti-inflammatory agents. Among them, compounds 2, 10, 12, and 16 exhibited a very low nonspecific cytotoxicity and inhibited the synthesis of TNF-alpha with greater than 65 % efficacy at low micromolar concentrations. Cytokine-specificity studies revealed that these compounds also inhibited the synthesis of the proinflammatory cytokines IL-1beta and IL-6, while inhibition of IL-1ra and IL-8 synthesis was marginal and only occurred at high concentrations. Further studies, through EMSA and Western blot analyses, indicated that these compounds decreased the extent of phosphorylation of IkappaBalpha; this suggests that they exert their anti-inflammatory profile by inhibiting NF-kappaB-mediated cytokine synthesis. These findings imply that these diterpenes represent promising leads for the development of novel anti-inflammatory agents.     

The validation of the E-Victimisation Scale (E-VS) and the E-Bullying Scale (E-BS) for adolescents

This study investigates the psychometric properties of the E-Victimisation Scale (E-VS) and E-Bullying Scale (E-BS) designed to assess Cyber Bullying among Chinese adolescents. Participants were 484 adolescents aged between 11–16 years randomly recruited from high schools within a region. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were applied to investigate the factorial structure of these scales. Reliability was examined by Cronbach’s alpha coefficients by sex. The convergent validity was investigated by correlations among these scales and the Centre for Epidemiological Studies-Depression for Children as well as the Zung’s Anxiety Scales. A single-factor model for the E-VS and a 2-factor model for the E-BS were resulted from the EFA with large factor loadings and about 47% and 56% of variance explained respectively. Cronhach’s alpha values provided evidence for good internal reliability with values ranging from 0.55 to 0.96. Correlations between the E-VS and Depression as well as Anxiety scales showed positive and significant relationships, however, the E-BS was only related to Depression. Psychometric evidence has shown that both E-VS and E-BS are valid instruments for measuring Cyber bullying behaviour and victimisation. Further studies are required on the test–retest reliability, discriminate validity, responsiveness, as well as normative information for standardisation.     

Quantum transport simulations of graphene nanoribbon devices using Dirac equation calibrated with tight-binding π-bond model

We present an efficient approach to study the carrier transport in graphene nanoribbon (GNR) devices using the non-equilibrium Green''s function approach (NEGF) based on the Dirac equation calibrated to the tight-binding π-bond model for graphene. The approach has the advantage of the computational efficiency of the Dirac equation and still captures sufficient quantitative details of the bandstructure from the tight-binding π-bond model for graphene. We demonstrate how the exact self-energies due to the leads can be calculated in the NEGF-Dirac model. We apply our approach to GNR systems of different widths subjecting to different potential profiles to characterize their device physics. Specifically, the validity and accuracy of our approach will be demonstrated by benchmarking the density of states and transmissions characteristics with that of the more expensive transport calculations for the tight-binding π-bond model.     

Low‐level PGAS computing on many‐core processors with TSHMEM

Diminishing returns from increased clock frequencies and instruction‐level parallelism have forced computer architects to adopt architectures that exploit wider parallelism through multiple processor cores. While emerging many‐core architectures have progressed at a remarkable rate, concerns arise regarding the performance and productivity of numerous parallel‐programming tools for application development. Development of parallel applications on many‐core processors often requires developers to familiarize themselves with unique characteristics of a target platform while attempting to maximize performance and maintain correctness of their applications. The family of partitioned global address space (PGAS) programming models comprises the current state of the art in balancing performance and programmability. One such PGAS approach is SHMEM, a lightweight, shared‐memory programming library that has demonstrated high performance and productivity potential for parallel‐computing systems with distributed‐memory architectures. In the paper, we present research, design, and analysis of a new SHMEM infrastructure specifically crafted for low‐level PGAS on modern and emerging many‐core processors featuring dozens of cores and more. Our approach (with a new library known as TSHMEM) is investigated and evaluated atop two generations of Tilera architectures, which are among the most sophisticated and scalable many‐core processors to date, and is intended to enable similar libraries atop other architectures now emerging. In developing TSHMEM, we explore design decisions and their impact on parallel performance for the Tilera TILE‐Gx and TILEPro many‐core architectures, and then evaluate the designs and algorithms within TSHMEM through microbenchmarking and applications studies with other communication libraries. Our results with barrier primitives provided by the Tilera libraries show dissimilar performance between the TILE‐Gx and TILEPro; therefore, TSHMEM's barrier design takes an alternative approach and leverages the on‐chip mesh network to provide consistent low‐latency performance. In addition, our experiments with TSHMEM show that naive collective algorithms consistently outperformed linear distributed collective algorithms when executed in an SMP‐centric environment. In leveraging these insights for the design of TSHMEM, our approach outperforms the OpenSHMEM reference implementation, achieves similar to positive performance over OpenMP and OSHMPI atop MPICH, and supports similar libraries in delivering high‐performance parallel computing to emerging many‐core systems. Copyright © 2015 John Wiley & Sons, Ltd.