2,649 research outputs found

    Bacterial genospecies that are not ecologically coherent : population genomics of Rhizobium leguminosarum

    Get PDF
    Biological species may remain distinct because of genetic isolation or ecological adaptation, but these two aspects do not always coincide. To establish the nature of the species boundary within a local bacterial population, we characterized a sympatric population of the bacterium Rhizobium leguminosarum by genomic sequencing of 72 isolates. Although all strains have 16S rRNA typical of R. leguminosarum, they fall into five genospecies by the criterion of average nucleotide identity (ANI). Many genes, on plasmids as well as the chromosome, support this division: recombination of core genes has been largely within genospecies. Nevertheless, variation in ecological properties, including symbiotic host range and carbon-source utilization, cuts across these genospecies, so that none of these phenotypes is diagnostic of genospecies. This phenotypic variation is conferred by mobile genes. The genospecies meet the Mayr criteria for biological species in respect of their core genes, but do not correspond to coherent ecological groups, so periodic selection may not be effective in purging variation within them. The population structure is incompatible with traditional 'polyphasic taxonomy' that requires bacterial species to have both phylogenetic coherence and distinctive phenotypes. More generally, genomics has revealed that many bacterial species share adaptive modules by horizontal gene transfer, and we envisage a more consistent taxonomic framework that explicitly recognizes this. Significant phenotypes should be recognized as 'biovars' within species that are defined by core gene phylogeny

    Implicit Iteration Process for Common Fixed Points of Strictly Asymptotically Pseudocontractive Mappings in Banach Spaces

    Full text link
    In this paper, a new implicit iteration process with errors for finite families of strictly asymptotically pseudocontractive mappings and nonexpansive mappings is introduced. By using the iterative process, some strong convergence theorems to approximating a common fixed point of strictly asymptotically pseudocontractive mappings and nonexpansive mappings are proved. The results presented in the paper are new which extend and improve some recent results of Osilike et al. (2007), Liu (1996), Osilike (2004), Su and Li (2006), Gu (2007), Xu and Ori (2001)

    Probabilistic inference of binary Markov random fields in spiking neural networks through mean-field approximation

    Get PDF
    Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like Markov random fields. Nevertheless, it remains unclear how probabilistic inference can be implemented by a network of spiking neurons in the brain. Previous studies have tried to relate the inference equation of binary Markov random fields to the dynamic equation of spiking neural networks through belief propagation algorithm and reparameterization, but they are valid only for Markov random fields with limited network structure. In this paper, we propose a spiking neural network model that can implement inference of arbitrary binary Markov random fields. Specifically, we design a spiking recurrent neural network and prove that its neuronal dynamics are mathematically equivalent to the inference process of Markov random fields by adopting mean-field theory. Furthermore, our mean-field approach unifies previous works. Theoretical analysis and experimental results, together with the application to image denoising, demonstrate that our proposed spiking neural network can get comparable results to that of mean-field inference

    Antitumor activity and mechanisms of action of total glycosides from aerial part of Cimicifuga dahurica targeted against hepatoma

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Medicinal plant is a main source of cancer drug development. Some of the cycloartane triterpenoids isolated from the aerial part of <it>Cimicifuga dahurica </it>showed cytotoxicity in several cancer cell lines. It is of great interest to examine the antiproliferative activity and mechanisms of total triterpenoid glycosides of <it>C. dahurica </it>and therefore might eventually be useful in the prevention or treatment of Hepatoma.</p> <p>Methods</p> <p>The total glycosides from the aerial part (TGA) was extracted and its cytotoxicity was evaluated in HepG2 cells and primary cultured normal mouse hepatocytes by an MTT assay. Morphology observation, Annexin V-FITC/PI staining, cell cycle analysis and western blot were used to further elucidate the cytotoxic mechanism of TGA. Implanted mouse H<sub>22 </sub>hepatoma model was used to demonstrate the tumor growth inhibitory activity of TGA <it>in vivo</it>.</p> <p>Results</p> <p>The IC<sub>50 </sub>values of TGA in HepG2 and primary cultured normal mouse hepatocytes were 21 and 105 ÎŒg/ml, respectively. TGA induced G<sub>0</sub>/G<sub>1 </sub>cell cycle arrest at lower concentration (25 ÎŒg/ml), and triggered G<sub>2</sub>/M arrest and apoptosis at higher concentrations (50 and 100 ÎŒg/ml respectively). An increase in the ratio of Bax/Bcl-2 was implicated in TGA-induced apoptosis. In addition, TGA inhibited the growth of the implanted mouse H<sub>22 </sub>tumor in a dose-dependent manner.</p> <p>Conclusion</p> <p>TGA may potentially find use as a new therapy for the treatment of hepatoma.</p

    Association screening for genes with multiple potentially rare variants: an inverse-probability weighted clustering approach

    Get PDF
    Both common variants and rare variants are involved in the etiology of most complex diseases in humans. Developments in sequencing technology have led to the identification of a high density of rare variant single-nucleotide polymorphisms (SNPs) on the genome, each of which affects only at most 1% of the population. Genotypes derived from these SNPs allow one to study the involvement of rare variants in common human disorders. Here, we propose an association screening approach that treats genes as units of analysis. SNPs within a gene are used to create partitions of individuals, and inverse-probability weighting is used to overweight genotypic differences observed on rare variants. Association between a phenotype trait and the constructed partition is then evaluated. We consider three association tests (one-way ANOVA, chi-square test, and the partition retention method) and compare these strategies using the simulated data from the Genetic Analysis Workshop 17. Several genes that contain causal SNPs were identified by the proposed method as top genes
    • 

    corecore