A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud

Software as a Service (SaaS) in Cloud is getting more and more significant among software users and providers recently. A SaaS that is delivered as composite application has many benefits including reduced delivery costs, flexible offers of the SaaS functions and decreased subscription cost for users. However, this approach has introduced a new problem in managing the resources allocated to the composite SaaS. The resource allocation that has been done at the initial stage may be overloaded or wasted due to the dynamic environment of a Cloud. A typical data center resource management usually triggers a placement reconfiguration for the SaaS in order to maintain its performance as well as to minimize the resource used. Existing approaches for this problem often ignore the underlying dependencies between SaaS components. In addition, the reconfiguration also has to comply with SaaS constraints in terms of its resource requirements, placement requirement as well as its SLA. To tackle the problem, this paper proposes a penalty-based Grouping Genetic Algorithm for multiple composite SaaS components clustering in Cloud. The main objective is to minimize the resource used by the SaaS by clustering its component without violating any constraint. Experimental results demonstrate the feasibility and the scalability of the proposed algorithm.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

The effect of silicate ions on proliferation, osteogenic differentiation and cell signalling pathways (WNT and SHH) of bone marrow stromal cells

Silicon (Si) is a trace element, which plays an important role in human bone growth. Si has been incorporated into biomaterials for bone regeneration in order to improve their osteogenic potential, both in vitro and in vivo. Little is known, however, as to how Si ions elicit their biological response on bone-forming cells. The aim of this study was to investigate the effect of Si ions on the proliferation, differentiation, bone-related gene expression and cell signalling pathways of bone marrow stromal cells (BMSCs) by comparing the BMSC responses to different concentrations of NaCl and Na2SiO3, while taking into account and excluding the effect of Na ions. Our study showed that Si ions at a concentration of 0.625 mM significantly enhanced the proliferation, mineralization nodule formation, bone-related gene expression (OCN, OPN and ALP) and bone matrix proteins (ALP and OPN) of BMSCs. Furthermore, Si ions at 0.625 mM could counteract the effect of the WNT inhibitor (W.I.) cardamonin on the osteogenic genes expression, (OPN, OCN and ALP), WNT and SHH signalling pathway-related genes in BMSCs. These results suggest that Si ions by themselves play an important role in regulating the proliferation and osteogenic differentiation of BMSCs, with the involvement of WNT and SHH signalling pathways. Our study provides evidence to explain possible molecular mechanisms whereby Si ions released from Si-containing biomaterials can acquire enhanced bioactivity at desired concentration.

Kallikrein 14 is down-regulated by androgen receptor signalling and harbours genetic variation that is associated with prostate tumour aggressiveness

Kallikrein 14 (KLK14) has been proposed as a useful prognostic marker in prostate cancer, with expression reported to be associated with tumour characteristics such as higher stage and Gleason score. KLK14 tumour expression has also shown the potential to predict prostate cancer patients at risk of disease recurrence after radical prostatectomy. The KLKs are a remarkably hormone-responsive family of genes, although detailed studies of androgen regulation of KLK14 in prostate cancer have not been undertaken to date. Using in vitro studies, we have demonstrated that unlike many other prostatic KLK genes that are strictly androgen responsive, KLK14 is more broadly expressed and inversely androgen regulated in prostate cancer cells. Given these results and evidence that KLK14 may play a role in prostate cancer prognosis, we also investigated whether common genetic variants in the KLK14 locus are associated with risk and/or aggressiveness of prostate cancer in approximately 1200 prostate cancer cases and 1300 male controls. Of 41 single nucleotide polymorphisms assessed, three were associated with higher Gleason score (≥7): rs17728459 and rs4802765, both located upstream of KLK14, and rs35287116, which encodes a p.Gln33Arg substitution in the KLK14 signal peptide region. Our findings provide further support for KLK14 as a marker of prognosis in prostate cancer.

Genetic analysis of maize streak virus isolates from Uganda reveals widespread distribution of a recombinant variant

Maize streak virus (MSV) contributes significantly to the problem of extremely low African maize yields. Whilst a diverse range of MSV and MSV-like viruses are endemic in sub-Saharan Africa and neighbouring islands, only a single group of maize-adapted variants - MSV subtypes A1 -A6 - causes severe enough disease in maize to influence yields substantially. In order to assist in designing effective strategies to control MSV in maize, a large survey covering 155 locations was conducted to assess the diversity, distribution and genetic characteristics of the Ugandan MSV-A population. PCR-restriction fragment-length polymorphism analyses of 391 virus isolates identified 49 genetic variants. Sixty-two full-genome sequences were determined, 52 of which were detectably recombinant. All but two recombinants contained predominantly MSV-A1-like sequences. Of the ten distinct recombination events observed, seven involved inter-MSV-A subtype recombination and three involved intra-MSV-A1 recombination. One of the intra-MSV-A1 recombinants, designated MSV-A1 UgIII, accounted for >60% of all MSV infections sampled throughout Uganda. Although recombination may be an important factor in the emergence of novel geminivirus variants, it is demonstrated that its characteristics in MSV are quite different from those observed in related African cassava-infecting geminivirus species. © 2007 SGM.

Global genetic diversity and geographical and host-species distribution of beak and feather disease virus isolates

Psittacine beak and feather disease (PBFD) has a broad host range and is widespread in wild and captive psittacine populations in Asia, Africa, the Americas, Europe and Australasia. Beak and feather disease circovirus (BFDV) is the causative agent. BFDV has an ~2 kb single stranded circular DNA genome encoding just two proteins (Rep and CP). In this study we provide support for demarcation of BFDV strains by phylogenetic analysis of 65 complete genomes from databases and 22 new BFDV sequences isolated from infected psittacines in South Africa. We propose 94% genome-wide sequence identity as a strain demarcation threshold, with isolates sharing > 94% identity belonging to the same strain, and strain subtypes sharing> 98% identity. Currently, BFDV diversity falls within 14 strains, with five highly divergent isolates from budgerigars probably representing a new species of circovirus with three strains (budgerigar circovirus; BCV-A, -B and -C). The geographical distribution of BFDV and BCV strains is strongly linked to the international trade in exotic birds; strains with more than one host are generally located in the same geographical area. Lastly, we examined BFDV and BCV sequences for evidence of recombination, and determined that recombination had occurred in most BFDV and BCV strains. We established that there were two globally significant recombination hotspots in the viral genome: the first is along the entire intergenic region and the second is in the C-terminal portion of the CP ORF. The implications of our results for the taxonomy and classification of circoviruses are discussed. © 2011 SGM.

Non-invasive identification of proteoglycans and chondrocyte differentiation state by Raman microspectroscopy

Proteoglycans (PGs) are crucial extracellular matrix (ECM) components that are present in all tissues and organs. Pathological remodeling of these macromolecules can lead to severe diseases such as osteoarthritis or rheumatoid arthritis. To date, PG-associated ECM alterations are routinely diagnosed by invasive analytical methods. Here, we employed Raman microspectroscopy, a laser-based, marker-free and non-destructive technique that allows the generation of spectra with peaks originating from molecular vibrations within a sample, to identify specific Raman bands that can be assigned to PGs within human and porcine cartilage samples and chondrocytes. Based on the non-invasively acquired Raman spectra, we further revealed that a prolonged in vitro culture leads to phenotypic alterations of chondrocytes, resulting in a decreased PG synthesis rate and loss of lipid contents. Our results are the first to demonstrate the applicability of Raman microspectroscopy as an analytical and potential diagnostic tool for non-invasive cell and tissue state monitoring of cartilage in biomedical research. ((c) 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Neural differentiation of mouse embryonic stem cells on conductive nanofiber scaffolds

Nerve tissue engineering requires suitable precursor cells as well as the necessary biochemical and physical cues to guide neurite extension and tissue development. An ideal scaffold for neural regeneration would be both fibrous and electrically conductive. We have contrasted the growth and neural differentiation of mouse embryonic stem cells on three different aligned nanofiber scaffolds composed of poly L: -lactic acid supplemented with either single- or multi-walled carbon-nanotubes. The addition of the nanotubes conferred conductivity to the nanofibers and promoted mESC neural differentiation as evidenced by an increased mature neuronal markers expression. We propose that the conductive scaffold could be a useful tool for the generation of neural tissue mimics in vitro and potentially as a scaffold for the repair of neural defects in vivo.

Adaptive sizing of populations and number of islands in distributed genetic algorithms

Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.

Dynamic optimization of migration topology in internet-based distributed genetic algorithms

Distributed Genetic Algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

BSTA Promotes mTORC2-Mediated Phosphorylation of Akt1 to Suppress Expression of FoxC2 and Stimulate Adipocyte Differentiation

Phosphorylation and activation of Akt1 is a crucial signaling event that promotes adipogenesis. However, neither the complex multistep process that leads to activation of Akt1 through phosphorylation at Thr308 and Ser473 nor the mechanism by which Akt1 stimulates adipogenesis is fully understood. We found that the BSD domain–containing signal transducer and Akt interactor (BSTA) promoted phosphorylation of Akt1 at Ser473 in various human and murine cells, and we uncovered a function for the BSD domain in BSTA-Akt1 complex formation. The mammalian target of rapamycin complex 2 (mTORC2) facilitated the phosphorylation of BSTA and its association with Akt1, and the BSTA-Akt1 interaction promoted the association of mTORC2 with Akt1 and phosphorylation of Akt1 at Ser473 in response to growth factor stimulation. Furthermore, analyses of bsta gene-trap murine embryonic stem cells revealed an essential function for BSTA and phosphorylation of Akt1 at Ser473 in promoting adipocyte differentiation, which required suppression of the expression of the gene encoding the transcription factor FoxC2. These findings indicate that BSTA is a molecular switch that promotes phosphorylation of Akt1 at Ser473 and reveal an mTORC2-BSTA-Akt1-FoxC2–mediated signaling mechanism that is critical for adipocyte differentiation.

Genetic polymorphisms in the human tissue kallikrein (KLK) locus and their implication in various malignant and non-malignant diseases

The Kallikrein (KLK) gene locus encodes a family of serine proteases and is the largest contiguous cluster of protease-encoding genes attributed an evolutionary age of 330 million years. The KLK locus has been implicated as a high susceptibility risk loci in numerous cancer studies through the last decade. The KLK3 gene already has established clinical relevance as a biomarker in prostate cancer prognosis through its encoded protein, prostate-specific antigen. Data mined through genome-wide association studies (GWAS) and next-generation sequencing point to many important candidate single nucleotide polymorphisms (SNPs) in KLK3 and other KLK genes. SNPs in the KLK locus have been found to be associated with several diseases including cancer, hypertension, cardiovascular disease and atopic dermatitis. Moreover, introducing a model incorporating SNPs to improve the efficiency of prostate-specific antigen in detecting malignant states of prostate cancer has been recently suggested. Establishing the functional relevance of these newly-discovered SNPs, and their interactions with each other, through in silico investigations followed by experimental validation, can accelerate the discovery of diagnostic and prognostic biomarkers. In this review, we discuss the various genetic association studies on the KLK loci identified either through candidate gene association studies or at the GWAS and post-GWAS front to aid researchers in streamlining their search for the most significant, relevant and therapeutically promising candidate KLK gene and/or SNP for future investigations.

Genetic association of the KLK4 locus with risk of prostate cancer

The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (±10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the Ptrend<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r2≥0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.