Bi-Objective Community Detection (BOCD) in Networks using Genetic Algorithm

A lot of research effort has been put into community detection from all corners of academic interest such as physics, mathematics and computer science. In this paper I have proposed a Bi-Objective Genetic Algorithm for community detection which maximizes modularity and community score. Then the results obtained for both benchmark and real life data sets are compared with other algorithms using the modularity and MNI performance metrics. The results show that the BOCD algorithm is capable of successfully detecting community structure in both real life and synthetic datasets, as well as improving upon the performance of previous techniques.Comment: 11 pages, 3 Figures, 3 Tables. arXiv admin note: substantial text overlap with arXiv:0906.061

Genetic algorithm with a local search strategy for discovering communities in complex networks

In order to further improve the performance of current genetic algorithms aiming at discovering communities, a local search based genetic algorithm GALS is here proposed. The core of GALS is a local search based mutation technique. In order to overcome the drawbacks of traditional mutation methods, the paper develops the concept of marginal gene and then the local monotonicity of modularity function Q is deduced from each nodes local view. Based on these two elements, a new mutation method combined with a local search strategy is presented. GALS has been evaluated on both synthetic benchmarks and several real networks, and compared with some presently competing algorithms. Experimental results show that GALS is highly effective and efficient for discovering community.Thanks are due to the referees for helpful comments. This work was supported by National Natural Science Foundation of China (60873149, 60973088, 61133011, 61202308), Scholarship Award for Excellent Doctoral Student granted by Ministry of Education (450060454018), Program for New Century Excellent Talents in University (NCET-11-0204), and Jilin University Innovation Project (450060481084)

Targeting the glucocorticoid receptor signature gene Mono Amine Oxidase-A enhances the efficacy of chemo- and anti-androgen therapy in advanced prostate cancer

Despite increasing options for treatment of castration-resistant prostate cancer, development of drug resistance is inevitable. The glucocorticoid receptor (GR) is a prime suspect for acquired therapy resistance, as prostate cancer (PCa) cells are able to increase GR signaling during anti-androgen therapy and thereby circumvent androgen receptor (AR)-blockade and cell death. As standard AR-directed therapies fail to block the GR and GR inhibitors might result in intolerable side effects, the identification of GR signature genes, which are better suited for a targeted approach, is of clinical importance. Therefore, the specific epithelial and stromal GR signature was determined in cancer-associated fibroblasts as well as in abiraterone and enzalutamide-resistant cells after glucocorticoid (GC) treatment. Microarray and ChIP analysis identified MAO-A as a directly up-regulated mutual epithelial and stromal GR target, which is induced after GC treatment and during PCa progression. Elevated MAO-A levels were confirmed in in vitro cell models, in primary tissue cultures after GC treatment, and in patients after neoadjuvant chemotherapy with GCs. MAO-A expression correlates with GR/AR activity as well as with a reduced progression-free survival. Pharmacological MAO-A inhibition combined with 2(nd) generation AR signaling inhibitors or chemotherapeutics results in impaired growth of androgen-dependent, androgen-independent, and long-term anti-androgen-treated cells. In summary, these findings demonstrate that targeting MAO-A represents an innovative therapeutic strategy to synergistically block GR and AR dependent PCa cell growth and thereby overcome therapy resistance.Prostatic carcinom

Moxifloxacin enhances antiproliferative and apoptotic effects of etoposide but inhibits its proinflammatory effects in THP-1 and Jurkat cells

Etoposide (VP-16) is a topoisomerase II (topo II) inhibitor chemotherapeutic agent. Studies indicate that VP-16 enhances proinflammatory cytokines secretion from tumour cells, including IL-8, a chemokine associated with proangiogenic effects. Fluoroquinolones inhibit topo II activity in eukaryotic cells by a mechanism different from that of VP-16. The fluoroquinolone moxifloxacin (MXF) has pronounced anti-inflammatory effects in vitro and in vivo. We studied the effects of MXF and VP-16 on purified human topo II activity and further analysed their combined activity on proliferation, apoptosis and caspase-3 activity in THP-1 and Jurkat cells. Moxifloxacin alone slightly inhibited the activity of human topo II; however, in combination with VP-16 it led to a 73% reduction in enzyme activity. VP-16 inhibited cell proliferation in a time and dose-dependent manner. The addition of moxifloxacin for 72 h to low-dose VP-16 doubled its cytotoxic effect in THP-1 and Jurkat cells (1.8- and 2.6-fold decrease in cell proliferation, respectively) (P<0.004). Moxifloxacin given alone did not induce apoptosis but enhanced VP-16-induced apoptosis in THP-1 and Jurkat cells (1.8- and two-fold increase in annexin V positive cells and caspase-3 activity, respectively) (P<0.04). VP-16 induced the release of IL-8 in a time and dose-dependent manner from THP-1 cells. Moxifloxacin completely blocked the enhanced release of IL-8 induced by 0.5 and 1 μg ml−1 VP-16, and decreased IL-8 release from cells incubated for 72 h with 3 μg ml−1 VP-16 (P<0.001). VP-16 enhanced the release of IL-1β and TNF-α from THP-1 cells, whereas the addition of MXF prevented the enhanced cytokine secretion (P<0.001). We conclude that MXF significantly enhances VP-16 cytotoxicity in tumour-derived cells while preventing VP-16-induced proinflammatory cytokine release. This unique combination may have clinical benefits and cytotoxic drug ‘sparing effect' and should be further studied in vivo

Evidence for link between modelled trends in Antarctic sea ice and underestimated westerly wind changes

Despite global warming, total Antarctic sea ice coverage increased over 1979-2013. However, the majority of Coupled Model Intercomparison Project phase 5 models simulate a decline. Mechanisms causing this discrepancy have so far remained elusive. Here we show that weaker trends in the intensification of the Southern Hemisphere westerly wind jet simulated by the models may contribute to this disparity. During austral summer, a strengthened jet leads to increased upwelling of cooler subsurface water and strengthened equatorward transport, conducive to increased sea ice. As the majority of models underestimate summer jet trends, this cooling process is underestimated compared with observations and is insufficient to offset warming in the models. Through the sea ice-albedo feedback, models produce a high-latitude surface ocean warming and sea ice decline, contrasting the observed net cooling and sea ice increase. A realistic simulation of observed wind changes may be crucial for reproducing the recent observed sea ice increase

Multicriteria building spatial design with mixed integer evolutionary algorithms

This paper proposes a first step towards multidisciplinary design of building spatial designs. Two criteria, total surface area (i.e. energy performance) and compliance (i.e. structural performance), are combined in a multicriteria optimisation framework. A new way of representing building spatial designs in a mixed integer parameter space is used within this framework. Two state-of-the-art algorithms, namely NSGA-II and SMS-EMOA, are used and compared to compute Pareto front approximations for problems of different size. Moreover, the paper discusses domain specific search operators, which are compared to generic operators, and techniques to handle constraints within the mutation. The results give first insights into the trade-off between energy and structural performance and the scalability of the approach

Multicriteria building spatial design with mixed integer evolutionary algorithms

This paper proposes a first step towards multidisciplinary design of building spatial designs. Two criteria, total surface area (i.e. energy performance) and compliance (i.e. structural performance), are combined in a multicriteria optimisation framework. A new way of representing building spatial designs in a mixed integer parameter space is used within this framework. Two state-of-the-art algorithms, namely NSGA-II and SMS-EMOA, are used and compared to compute Pareto front approximations for problems of different size. Moreover, the paper discusses domain specific search operators, which are compared to generic operators, and techniques to handle constraints within the mutation. The results give first insights into the trade-off between energy and structural performance and the scalability of the approach