Two new 8-isopentenyl isoflavane derivatives from Astragalus dolichochaete diels.

Astragali Radix (Huangqi) is one of the well-known traditional Chinese medicines and has been used in China for more than two thousand years. As a close species, Astragalus dolichochaete Diels was found to possess cytotoxicity during our preliminary study of Astragalus plants from Yunnan Province, China. To better understand the chemical foundation of the cytotoxicity, the major constituents of A. dolichochaete were studied. As a result, two new 8-isopentenyl isoflavane derivatives, dolichochaeteins A and B (1 and 2), together with ten known constituents were isolated, and their structures were elucidated by means of spectroscopy, mainly 1D and 2D NMR techniques. The cytotoxic activities were evaluated for the raw extract, ethyl acetate fraction, compound 2 and glyasperin H (3) against human gastric carcinoma cell line SGC-7901, human hepatoma cell line SMMC-7721 and human leukemic cell line K562. All the samples exhibited significant cytotoxicity.

Particle swarm optimization with composite particles in dynamic environments.

In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address dynamic optimization problems. PSO-CP partitions the swarm into a set of composite particles based on their similarity using a "worst first" principle. Inspired by the composite particle phenomenon in physics, the elementary members in each composite particle interact via a velocity-anisotropic reflection scheme to integrate valuable information for effectively and rapidly finding the promising optima in the search space. Each composite particle maintains the diversity by a scattering operator. In addition, an integral movement strategy is introduced to promote the swarm diversity. Experiments on a typical dynamic test benchmark problem provide a guideline for setting the involved parameters and show that PSO-CP is efficient in comparison with several state-of-the-art PSO algorithms for dynamic optimization problems.

Adaptive primal-dual genetic algorithms in dynamic environments.

Recently, there has been an increasing interest in applying genetic algorithms (GAs) in dynamic environments. Inspired by the complementary and dominance mechanisms in nature, a primal-dual GA (PDGA) has been proposed for dynamic optimization problems (DOPs). In this paper, an important operator in PDGA, i.e., the primal-dual mapping (PDM) scheme, is further investigated to improve the robustness and adaptability of PDGA in dynamic environments. In the improved scheme, two different probability-based PDM operators, where the mapping probability of each allele in the chromosome string is calculated through the statistical information of the distribution of alleles in the corresponding gene locus over the population, are effectively combined according to an adaptive Lamarckian learning mechanism. In addition, an adaptive dominant replacement scheme, which can probabilistically accept inferior chromosomes, is also introduced into the proposed algorithm to enhance the diversity level of the population. Experimental results on a series of dynamic problems generated from several stationary benchmark problems show that the proposed algorithm is a good optimizer for DOPs.

Immune intervention with monoclonal antibodies targeting CD152 (CTLA-4) for autoimmune and malignant diseases.

CD152 or cytotoxic T lymphocyte antigen-4 (CTLA-4) is an essential receptor involved in the negative regulation of T cell activation. Because of its profound inhibitory role, CD152 has been considered a sound susceptible candidate in autoimmunity and a persuasive target for cancer immunotherapy for over a decade. However, the precise roles played by this molecule continue to emerge. In particular, recent evidence suggests that CD152 is also important in the homeostasis and function of a population of suppressive cells, termed regulatory T cells (Treg). In this review, we discuss the recent progress and main features of monoclonal antibodies (mAbs) targeting CD152 and examine how each mAb prepared to a distinct epitope may impact differently upon CD152 modulation depending on its demonstrated regulatory role acting as an agonist, antagonist, or inverse agonist.

Predatory search algorithm with restriction of solution distance.

A variety of methods and algorithms have been developed to solve NP-Hard problems in recent decades. In this paper, we are concerned with a relatively new algorithm based on animal behavioral adaptability and evolutionary computation, namely predatory search. When first introduced, the algorithm was implemented with restrictions based on solution cost as a simplification of distance adopted by search-intensive predators. Our research concentrates on exploring the possibility of using distance to restrict search area. Based on the research of Boese et al. (1994), we propose a type of predatory search algorithm restricted by solution distance (particularly bond distance), and compare it with the original algorithm based on three benchmark traveling salesman problems. The results indicate that both algorithms are suitable for solving the traveling salesman problems, while our proposed algorithm either outperforms or at least matches its predecessor with respect to both the running time and the quality of solutions. In addition, further experiments suggest that there exists a certain relationship between the two algorithms.