764 research outputs found

    EGIA–evolutionary optimisation of gene regulatory networks, an integrative approach

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    Quantitative modelling of gene regulatory networks (GRNs) is still limited by data issues such as noise and the restricted length of available time series, creating an under-determination problem. However, large amounts of other types of biological data and knowledge are available, such as knockout experiments, annotations and so on, and it has been postulated that integration of these can improve model quality. However, integration has not been fully explored, to date. Here, we present a novel integrative framework for different types of data that aims to enhance model inference. This is based on evolutionary computation and uses different types of knowledge to introduce a novel customised initialisation and mutation operator and complex evaluation criteria, used to distinguish between candidate models. Specifically, the algorithm uses information from (i) knockout experiments, (ii) annotations of transcription factors, (iii) binding site motifs (expressed as position weight matrices) and (iv) DNA sequence of gene promoters, to drive the algorithm towards more plausible network structures. Further, the evaluation basis is also extended to include structure information included in these additional data. This framework is applied to both synthetic and real gene expression data. Models obtained by data integration display both quantitative and qualitative improvement

    Trialling technologies to reduce hospital in‐patient falls: an agential realist analysis

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    This paper analyses the 'failure' of a patient safety intervention. Our study was part of an RCT of bed and bedside chair pressure sensors linked to radio pagers to prevent bedside falls in older people admitted to hospital. We use agential realism within science and technology studies to examine the fall and its prevention as a situated phenomenon of knowledge that is made and unmade through intra-actions between environment, culture, humans and technologies. We show that neither the intervention (the pressure sensor system), nor the outcome (fall prevention) could be disentangled from the broader sociomaterial context of the ward, the patients, the nurses and (especially) their work through the RCT. We argue that the RCT design, by virtue of its unacknowledged assumptions, played a part in creating the negative findings. The study also raises wider questions about the kind of subjectivities, agencies and power relations these entanglements might effect and (re)produce in the hospital ward

    Real-time measurement of metabolic rate during freezing and thawing of the wood frog, Rana sylvatica: Implications for overwinter energy use

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    Ectotherms overwintering in temperate ecosystems must survive low temperatures while conserving energy to fuel post-winter reproduction. Freeze-tolerant wood frogs, Rana sylvatica, have an active response to the initiation of ice formation that includes mobilising glucose from glycogen and circulating it around the body to act as a cryoprotectant. We used flow-through respirometry to measure CO2 production (VCO2) in real time during cooling, freezing and thawing. CO2 production increases sharply at three points during freeze-thaw: at +1°C during cooling prior to ice formation (total of 104±17 Όl CO2 frog-1 event-1), at the initiation of freezing (565±85 Όl CO 2 frog-1 freezing event-1) and after the frog has thawed (564±75 Όl CO2 frog-1 freezing event-1). We interpret these increases in metabolic rate to represent the energetic costs of preparation for freezing, the response to freezing and the re-establishment of homeostasis and repair of damage after thawing, respectively. We assumed that frogs metabolise lipid when unfrozen and that carbohydrate fuels metabolism during cooling, freezing and thawing, and when frozen. We then used microclimate temperature data to predict overwinter energetics of wood frogs. Based on the freezing and melting points we measured, frogs in the field were predicted to experience as many as 23 freeze-thaw cycles in the winter of our microclimate recordings. Overwinter carbohydrate consumption appears to be driven by the frequency of freeze-thaw events, and changes in overwinter climate that affect the frequency of freeze-thaw will influence carbohydrate consumption, but changes that affect mean temperatures and the frequency of winter warm spells will modify lipid consumption

    Quantifying Between-Cohort and Between-Sex Genetic Heterogeneity in Major Depressive Disorder

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    Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between-cohort and between-sex heterogeneity. First, we used genome-wide association study (GWAS) summary statistics to investigate between-cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases = 16,823, N controls = 25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs community sources). Second, we evaluated between-sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD

    Influence of Anodic Conditions on Self-ordered Growth of Highly Aligned Titanium Oxide Nanopores

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    Self-aligned nanoporous TiO2templates synthesized via dc current electrochemical anodization have been carefully analyzed. The influence of environmental temperature during the anodization, ranging from 2 °C to ambient, on the structure and morphology of the nanoporous oxide formation has been investigated, as well as that of the HF electrolyte chemical composition, its concentration and their mixtures with other acids employed for the anodization. Arrays of self-assembled titania nanopores with inner pores diameter ranging between 50 and 100 nm, wall thickness around 20–60 nm and 300 nm in length, are grown in amorphous phase, vertical to the Ti substrate, parallel aligned to each other and uniformly disordering distributed over all the sample surface. Additional remarks about the photoluminiscence properties of the titania nanoporous templates and the magnetic behavior of the Ni filled nanoporous semiconductor Ti oxide template are also included

    D* Production in Deep Inelastic Scattering at HERA

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    This paper presents measurements of D^{*\pm} production in deep inelastic scattering from collisions between 27.5 GeV positrons and 820 GeV protons. The data have been taken with the ZEUS detector at HERA. The decay channel D∗+→(D0→K−π+)π+D^{*+}\to (D^0 \to K^- \pi^+) \pi^+ (+ c.c.) has been used in the study. The e+pe^+p cross section for inclusive D^{*\pm} production with 5<Q2<100GeV25<Q^2<100 GeV^2 and y<0.7y<0.7 is 5.3 \pms 1.0 \pms 0.8 nb in the kinematic region {1.3<pT(D∗±)<9.01.3<p_T(D^{*\pm})<9.0 GeV and ∣η(D∗±)∣<1.5| \eta(D^{*\pm}) |<1.5}. Differential cross sections as functions of p_T(D^{*\pm}), η(D∗±),W\eta(D^{*\pm}), W and Q2Q^2 are compared with next-to-leading order QCD calculations based on the photon-gluon fusion production mechanism. After an extrapolation of the cross section to the full kinematic region in p_T(D^{*\pm}) and η\eta(D^{*\pm}), the charm contribution F2ccˉ(x,Q2)F_2^{c\bar{c}}(x,Q^2) to the proton structure function is determined for Bjorken xx between 2 ⋅\cdot 10−4^{-4} and 5 ⋅\cdot 10−3^{-3}.Comment: 17 pages including 4 figure

    Observation of Scaling Violations in Scaled Momentum Distributions at HERA

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    Charged particle production has been measured in deep inelastic scattering (DIS) events over a large range of xx and Q2Q^2 using the ZEUS detector. The evolution of the scaled momentum, xpx_p, with Q2,Q^2, in the range 10 to 1280 GeV2GeV^2, has been investigated in the current fragmentation region of the Breit frame. The results show clear evidence, in a single experiment, for scaling violations in scaled momenta as a function of Q2Q^2.Comment: 21 pages including 4 figures, to be published in Physics Letters B. Two references adde

    Intercalibration of the barrel electromagnetic calorimeter of the CMS experiment at start-up

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    Calibration of the relative response of the individual channels of the barrel electromagnetic calorimeter of the CMS detector was accomplished, before installation, with cosmic ray muons and test beams. One fourth of the calorimeter was exposed to a beam of high energy electrons and the relative calibration of the channels, the intercalibration, was found to be reproducible to a precision of about 0.3%. Additionally, data were collected with cosmic rays for the entire ECAL barrel during the commissioning phase. By comparing the intercalibration constants obtained with the electron beam data with those from the cosmic ray data, it is demonstrated that the latter provide an intercalibration precision of 1.5% over most of the barrel ECAL. The best intercalibration precision is expected to come from the analysis of events collected in situ during the LHC operation. Using data collected with both electrons and pion beams, several aspects of the intercalibration procedures based on electrons or neutral pions were investigated

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types
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