Phage Particles in Ground Arctic Ice

Microbiology - This is the first report on investigation of bacteriophages in ancient Arctic ground ice of various genesis and geological age. Electron microscopy revealed phage particles in all...     

Diversity of the bphA1 Genes in a Microbial Community from Anthropogenically Contaminated Soil and Isolation of New Pseudomonads Degrading Biphenyl/Chlorinated Biphenyls

Microbiology - Molecular biological and cultivation-based approaches were used to investigate the microbial community of tehnogenic soil contaminated with poorly degradable toxic (chlorinated)...     

New Species of Malachite Beetles (Coleoptera,Dasytidae) in Baltic Amber

Paleontological Journal - Four new species of malachite beetles (Coleoptera, Dasytidae) are described from Late Eocene Baltic amber, namely two species of the genus Aplocnemus Stephens, 1830 and a...     

Prion Properties of Alpha-Synuclein

Molecular Biology - The prion properties of alpha-synuclein, a key aggregating protein involved in the pathogenesis of so-called synucleinopathies, including Parkinson’s disease (PD),...     

The Convergence of Alzheimer’s Disease Pathogenesis Concepts

Molecular Biology - Advances in the research of molecular factors involved in the onset and progression of Alzheimer’s disease, have led to the creation of several pathogenesis concepts of...     

A Group of Hypermethylated miRNA Genes in Breast Cancer and Their Diagnostic Potential

Molecular Biology - miRNA genes play an important role in cancer pathogenesis, while they may be suppressed by hypermethylation. Here, we assess the diagnostic potential of a group of...     

The Effects of Habitat on Dispersal Patterns of an Invasive Thistle, Cynara Cardunculus

Dispersal of offspring is a critical step in the spread of invasive species, yet dispersal patterns are seldom well studied, inhibiting effective management and ecological understanding of invasions. Dispersal patterns can be affected by characteristics of the parent plant and by climatic or site characteristics, including community vegetation structure, but these factors have not been studied in the context of plant invasion processes. Cynara cardunculus (L.) is a polycarpic perennial thistle invasive in coastal grasslands in California that produces large numbers of wind-dispersed seeds. This study quantified and compared C. cardunculus dispersal patterns in an exotic grassland (vegetated site) and an agricultural field (non-vegetated site). Seed size variation in C. cardunculus was also quantified within inflorescences, between inflorescences, and between years of production, and compared across dispersal distances. Results indicate that dispersal distance increased dramatically from less than 20 m in the vegetated site to more than 40 m in the non-vegetated site. Plants producing fewer seeds produced heavier seeds and dispersal distance decreased over time, but seed size was not related to dispersal distance, which may serve to spread the risk to seeds or seedlings across the environment. C. cardunculus has great potential for dispersal in open areas such as agricultural fields or disturbed sites, but may be limited in highly structured natural communities. Management of C. cardunculus and other wind-dispersed plant invasions may be improved by prioritizing populations with open or disturbed areas downwind and minimizing the removal of vegetation during dispersal.     

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression

Background  

The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model) method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication.     

Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks

Background  

The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the search space by means of clustering genes into putatively co-regulated groups, as opposed to those that are simply co-expressed. Be cause genes may be co-regulated only across a subset of all observed experimental conditions, biclustering (clustering of genes and conditions) is more appropriate than standard clustering. Co-regulated genes are also often functionally (physically, spatially, genetically, and/or evolutionarily) associated, and such a priori known or pre-computed associations can provide support for appropriately grouping genes. One important association is the presence of one or more common cis-regulatory motifs. In organisms where these motifs are not known, their de novo detection, integrated into the clustering algorithm, can help to guide the process towards more biologically parsimonious solutions.