Headwater Influences on Downstream Water Quality

We investigated the influence of riparian and whole watershed land use as a function of stream size on surface water chemistry and assessed regional variation in these relationships. Sixty-eight watersheds in four level III U.S. EPA ecoregions in eastern Kansas were selected as study sites. Riparian land cover and watershed land use were quantified for the entire watershed, and by Strahler order. Multiple regression analyses using riparian land cover classifications as independent variables explained among-site variation in water chemistry parameters, particularly total nitrogen (41%), nitrate (61%), and total phosphorus (63%) concentrations. Whole watershed land use explained slightly less variance, but riparian and whole watershed land use were so tightly correlated that it was difficult to separate their effects. Water chemistry parameters sampled in downstream reaches were most closely correlated with riparian land cover adjacent to the smallest (first-order) streams of watersheds or land use in the entire watershed, with riparian zones immediately upstream of sampling sites offering less explanatory power as stream size increased. Interestingly, headwater effects were evident even at times when these small streams were unlikely to be flowing. Relationships were similar among ecoregions, indicating that land use characteristics were most responsible for water quality variation among watersheds. These findings suggest that nonpoint pollution control strategies should consider the influence of small upland streams and protection of downstream riparian zones alone is not sufficient to protect water quality

Quantifying loopy network architectures

Biology presents many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture containing closed loops at many different levels. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework, the hierarchical loop decomposition, that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated graphs, such as artificial models and optimal distribution networks, as well as natural graphs extracted from digitized images of dicotyledonous leaves and vasculature of rat cerebral neocortex. We calculate various metrics based on the Asymmetry, the cumulative size distribution and the Strahler bifurcation ratios of the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information (exact location of edges and nodes) from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.Comment: 17 pages, 8 figures. During preparation of this manuscript the authors became aware of the work of Mileyko at al., concurrently submitted for publicatio

A method to improve protein subcellular localization prediction by integrating various biological data sources

<p>Abstract</p> <p>Background</p> <p>Protein subcellular localization is crucial information to elucidate protein functions. Owing to the need for large-scale genome analysis, computational method for efficiently predicting protein subcellular localization is highly required. Although many previous works have been done for this task, the problem is still challenging due to several reasons: the number of subcellular locations in practice is large; distribution of protein in locations is imbalanced, that is the number of protein in each location remarkably different; and there are many proteins located in multiple locations. Thus it is necessary to explore new features and appropriate classification methods to improve the prediction performance.</p> <p>Results</p> <p>In this paper we propose a new predicting method which combines two key ideas: 1) Information of neighbour proteins in a probabilistic gene network is integrated to enrich the prediction features. 2) Fuzzy k-NN, a classification method based on fuzzy set theory is applied to predict protein locating in multiple sites. Experiment was conducted on a dataset consisting of 22 locations from Budding yeast proteins and significant improvement was observed.</p> <p>Conclusion</p> <p>Our results suggest that the neighbourhood information from functional gene networks is predictive to subcellular localization. The proposed method thus can be integrated and complementary to other available prediction methods.</p

Drug-induced activation of SREBP-controlled lipogenic gene expression in CNS-related cell lines: Marked differences between various antipsychotic drugs

BACKGROUND: The etiology of schizophrenia is unknown, but neurodevelopmental disturbances, myelin- and oligodendrocyte abnormalities and synaptic dysfunction have been suggested as pathophysiological factors in this severe psychiatric disorder. Cholesterol is an essential component of myelin and has proved important for synapse formation. Recently, we demonstrated that the antipsychotic drugs clozapine and haloperidol stimulate lipogenic gene expression in cultured glioma cells through activation of the sterol regulatory element-binding protein (SREBP) transcription factors. We here compare the action of chlorpromazine, haloperidol, clozapine, olanzapine, risperidone and ziprasidone on SREBP activation and SREBP-controlled gene expression (ACAT2, HMGCR, HMGCS1, FDPS, SC5DL, DHCR7, LDLR, FASN and SCD1) in four CNS-relevant human cell lines. RESULTS: There were marked differences in the ability of the antipsychotic drugs to activate the expression of SREBP target genes, with clozapine and chlorpromazine as the most potent stimulators in a context of therapeutically relevant concentrations. Glial-like cells (GaMg glioma and CCF-STTG1 astrocytoma cell lines) displayed more pronounced drug-induced SREBP activation compared to the response in HCN2 human cortical neurons and SH-SY5Y neuroblastoma cells, indicating that antipsychotic-induced activation of lipogenesis is most prominent in glial cells. CONCLUSION: Our present data show a marked variation in the ability of different antipsychotics to induce SREBP-controlled transcriptional activation of lipogenesis in cultured human CNS-relevant cells. We propose that this effect could be relevant for the therapeutic efficacy of some antipsychotic drugs

Determinants of Fatigue after First-Ever Ischemic Stroke during Acute Phase

© 2014 The Authors. Published by PLOS. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1371/journal.pone.0110037 A correction to the article was made on 19/12/2012: https://doi.org/10.1371/journal.pone.011646

Is Mate Choice in Humans MHC-Dependent?

In several species, including rodents and fish, it has been shown that the Major Histocompatibility Complex (MHC) influences mating preferences and, in some cases, that this may be mediated by preferences based on body odour. In humans, the picture has been less clear. Several studies have reported a tendency for humans to prefer MHC-dissimilar mates, a sexual selection that would favour the production of MHC-heterozygous offspring, who would be more resistant to pathogens, but these results are unsupported by other studies. Here, we report analyses of genome-wide genotype data (from the HapMap II dataset) and HLA types in African and European American couples to test whether humans tend to choose MHC-dissimilar mates. In order to distinguish MHC-specific effects from genome-wide effects, the pattern of similarity in the MHC region is compared to the pattern in the rest of the genome. African spouses show no significant pattern of similarity/dissimilarity across the MHC region (relatedness coefficient, R = 0.015, p = 0.23), whereas across the genome, they are more similar than random pairs of individuals (genome-wide R = 0.00185, p<10−3). We discuss several explanations for these observations, including demographic effects. On the other hand, the sampled European American couples are significantly more MHC-dissimilar than random pairs of individuals (R = −0.043, p = 0.015), and this pattern of dissimilarity is extreme when compared to the rest of the genome, both globally (genome-wide R = −0.00016, p = 0.739) and when broken into windows having the same length and recombination rate as the MHC (only nine genomic regions exhibit a higher level of genetic dissimilarity between spouses than does the MHC). This study thus supports the hypothesis that the MHC influences mate choice in some human populations

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

The highly attenuated oncolytic recombinant vaccinia virus GLV-1h68: comparative genomic features and the contribution of F14.5L inactivation

As a new anticancer treatment option, vaccinia virus (VACV) has shown remarkable antitumor activities (oncolysis) in preclinical studies, but potential infection of other organs remains a safety concern. We present here genome comparisons between the de novo sequence of GLV-1h68, a recombinant VACV, and other VACVs. The identified differences in open reading frames (ORFs) include genes encoding host-range selection, virulence and immune modulation proteins, e.g., ankyrin-like proteins, serine proteinase inhibitor SPI-2/CrmA, tumor necrosis factor (TNF) receptor homolog CrmC, semaphorin-like and interleukin-1 receptor homolog proteins. Phylogenetic analyses indicate that GLV-1h68 is closest to Lister strains but has lost several ORFs present in its parental LIVP strain, including genes encoding CrmE and a viral Golgi anti-apoptotic protein, v-GAAP. The reduced pathogenicity of GLV-1h68 is confirmed in male mice bearing C6 rat glioma and in immunocompetent mice bearing B16-F10 murine melanoma. The contribution of foreign gene expression cassettes in the F14.5L, J2R and A56R loci is analyzed, in particular the contribution of F14.5L inactivation to the reduced virulence is demonstrated by comparing the virulence of GLV-1h68 with its F14.5L-null and revertant viruses. GLV-1h68 is a promising engineered VACV variant for anticancer therapy with tumor-specific replication, reduced pathogenicity and benign tissue tropism

The Cool Little Kids randomised controlled trial: Population-level early prevention for anxiety disorders

Background: The World Health Organization predicts that by 2030 internalising problems (e.g. depression and anxiety) will be second only to HIV/AIDS in international burden of disease. Internalising problems affect 1 in 7 school aged children, impacting on peer relations, school engagement, and later mental health, relationships and employment. The development of early childhood prevention for internalising problems is in its infancy. The current study follows two successful &lsquo;efficacy&rsquo; trials of a parenting group intervention to reduce internalising disorders in temperamentally inhibited preschool children. Cool Little Kids is a population-level randomised trial to determine the impacts of systematically screening preschoolers for inhibition then offering a parenting group intervention, on child internalising problems and economic costs at school entry.Methods/Design: This randomised trial will be conducted within the preschool service system, attended by more than 95% of Australian children in the year before starting school. In early 2011, preschool services in four local government areas in Melbourne, Australia, will distribute the screening tool. The &asymp;16% (n&asymp;500) with temperamental inhibition will enter the trial. Intervention parents will be offered Cool Little Kids, a 6-session group program in the local community, focusing on ways to develop their child&rsquo;s bravery skills by reducing overprotective parenting interactions. Outcomes one and two years post-baseline will comprise child internalising diagnoses and symptoms, parenting interactions, and parent wellbeing. An economic evaluation (costconsequences framework) will compare incremental differences in costs of the intervention versus control children to incremental differences in outcomes, from a societal perspective. Analyses will use the intention-to-treat principle, using logistic and linear regression models (binary and continuous outcomes respectively) to compare outcomes between the trial arms.Discussion: This trial addresses gaps for internalising problems identified in the 2004 World Health Organization Prevention of Mental Disorders report. If effective and cost-effective, the intervention could readily be applied at a population level. Governments consider mental health to be a priority, enhancing the likelihood that an effective early prevention program would be adopted in Australia and internationally.<br /