Compatibility of neutrino DIS data and global analyses of parton distribution functions

Neutrino\antineutrino deep inelastic scattering (DIS) data provide useful constrains for the flavor decomposition in global fits of parton distribution functions (PDF). The smallness of the cross-sections requires the use of nuclear targets in the experimental setup. Understanding the nuclear corrections is, for this reason, of utmost importance for a precise determination of the PDFs. Here, we explore the nuclear effects in the neutrino\antineutrino-nucleon DIS by comparing the NuTeV, CDHSW, and CHORUS cross-sections to the predictions derived from the latest parton distribution functions and their nuclear modifications. We obtain a good description of these data and find no apparent disagreement between the nuclear effects in neutrino DIS and those in charged lepton DIS. These results also indicate that further improvements in the knowledge of the nuclear PDFs could be obtained by a more extensive use of these sets of neutrino data.Comment: 16 pages, 8 figure

Law Libraries and Laboratories: The Legacies of Langdell and His Metaphor

Law Librarians and others have often referred to Harvard Law School Dean C.C. Langdell’s statements that the law library is the lawyer’s laboratory. Professor Danner examines the context of what Langdell through his other writings, the educational environment at Harvard in the late nineteenth century, and the changing perceptions of university libraries generally. He then considers how the “laboratory metaphor” has been applied by librarians and legal scholars during the twentieth century and into the twenty-first. The article closes with thoughts on Langdell’s legacy for law librarians and the usefulness of the laboratory metaphor

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Clinical Manifestations and Case Management of Ebola Haemorrhagic Fever caused by a newly identified virus strain, Bundibugyo, Uganda, 2007-2008

A confirmed Ebola haemorrhagic fever (EHF) outbreak in Bundibugyo, Uganda, November 2007-February 2008, was caused by a putative new species (Bundibugyo ebolavirus). It included 93 putative cases, 56 laboratory-confirmed cases, and 37 deaths (CFR = 25%). Study objectives are to describe clinical manifestations and case management for 26 hospitalised laboratory-confirmed EHF patients. Clinical findings are congruous with previously reported EHF infections. The most frequently experienced symptoms were non-bloody diarrhoea (81%), severe headache (81%), and asthenia (77%). Seven patients reported or were observed with haemorrhagic symptoms, six of whom died. Ebola care remains difficult due to the resource-poor setting of outbreaks and the infection-control procedures required. However, quality data collection is essential to evaluate case definitions and therapeutic interventions, and needs improvement in future epidemics. Organizations usually involved in EHF case management have a particular responsibility in this respect

Kaposi's Sarcoma-Associated Herpesvirus ORF57 Protein Binds and Protects a Nuclear Noncoding RNA from Cellular RNA Decay Pathways

The control of RNA stability is a key determinant in cellular gene expression. The stability of any transcript is modulated through the activity of cis- or trans-acting regulatory factors as well as cellular quality control systems that ensure the integrity of a transcript. As a result, invading viral pathogens must be able to subvert cellular RNA decay pathways capable of destroying viral transcripts. Here we report that the Kaposi's sarcoma-associated herpesvirus (KSHV) ORF57 protein binds to a unique KSHV polyadenylated nuclear RNA, called PAN RNA, and protects it from degradation by cellular factors. ORF57 increases PAN RNA levels and its effects are greatest on unstable alleles of PAN RNA. Kinetic analysis of transcription pulse assays shows that ORF57 protects PAN RNA from a rapid cellular RNA decay process, but ORF57 has little effect on transcription or PAN RNA localization based on chromatin immunoprecipitation and in situ hybridization experiments, respectively. Using a UV cross-linking technique, we further demonstrate that ORF57 binds PAN RNA directly in living cells and we show that binding correlates with function. In addition, we define an ORF57-responsive element (ORE) that is necessary for ORF57 binding to PAN RNA and sufficient to confer ORF57-response to a heterologous intronless β-globin mRNA, but not its spliced counterparts. We conclude that ORF57 binds to viral transcripts in the nucleus and protects them from a cellular RNA decay pathway. We propose that KSHV ORF57 protein functions to enhance the nuclear stability of intronless viral transcripts by protecting them from a cellular RNA quality control pathway

Predicting enzyme targets for cancer drugs by profiling human Metabolic reactions in NCI-60 cell lines

<p>Abstract</p> <p>Background</p> <p>Drugs can influence the whole metabolic system by targeting enzymes which catalyze metabolic reactions. The existence of interactions between drugs and metabolic reactions suggests a potential way to discover drug targets.</p> <p>Results</p> <p>In this paper, we present a computational method to predict new targets for approved anti-cancer drugs by exploring drug-reaction interactions. We construct a Drug-Reaction Network to provide a global view of drug-reaction interactions and drug-pathway interactions. The recent reconstruction of the human metabolic network and development of flux analysis approaches make it possible to predict each metabolic reaction's cell line-specific flux state based on the cell line-specific gene expressions. We first profile each reaction by its flux states in NCI-60 cancer cell lines, and then propose a kernel k-nearest neighbor model to predict related metabolic reactions and enzyme targets for approved cancer drugs. We also integrate the target structure data with reaction flux profiles to predict drug targets and the area under curves can reach 0.92.</p> <p>Conclusions</p> <p>The cross validations using the methods with and without metabolic network indicate that the former method is significantly better than the latter. Further experiments show the synergism of reaction flux profiles and target structure for drug target prediction. It also implies the significant contribution of metabolic network to predict drug targets. Finally, we apply our method to predict new reactions and possible enzyme targets for cancer drugs.</p

Reconstructing CNV genotypes using segregation analysis: combining pedigree information with CNV assay

<p>Abstract</p> <p>Background</p> <p>Repeated blocks of genome sequence have been shown to be associated with genetic diversity and disease risk in humans, and with phenotypic diversity in model organisms and domestic animals. Reliable tests are desirable to determine whether individuals are carriers of copy number variants associated with disease risk in humans and livestock, or associated with economically important traits in livestock. In some cases, copy number variants affect the phenotype through a dosage effect but in other cases, allele combinations have non-additive effects. In the latter cases, it has been difficult to develop tests because assays typically return an estimate of the sum of the copy number counts on the maternally and paternally inherited chromosome segments, and this sum does not uniquely determine the allele configuration. In this study, we show that there is an old solution to this new problem: segregation analysis, which has been used for many years to infer alleles in pedigreed populations.</p> <p>Methods</p> <p>Segregation analysis was used to estimate copy number alleles from assay data on simulated half-sib sheep populations. Copy number variation at the Agouti locus, known to be responsible for the recessive self-colour black phenotype, was used as a model for the simulation and an appropriate penetrance function was derived. The precision with which carriers and non-carriers of the undesirable single copy allele could be identified, was used to evaluate the method for various family sizes, assay strategies and assay accuracies.</p> <p>Results</p> <p>Using relationship data and segregation analysis, the probabilities of carrying the copy number alleles responsible for black or white fleece were estimated with much greater precision than by analyzing assay results for animals individually. The proportion of lambs correctly identified as non-carriers of the undesirable allele increased from 7% when the lambs were analysed alone to 80% when the lambs were analysed in half-sib families.</p> <p>Conclusions</p> <p>When a quantitative assay is used to estimate copy number alleles, segregation analysis of related individuals can greatly improve the precision of the estimates. Existing software for segregation analysis would require little if any change to accommodate the penetrance function for copy number assay data.</p

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation