584 research outputs found

    Gene Tree Labeling Using Nonnegative Matrix Factorization on Biomedical Literature

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    Identifying functional groups of genes is a challenging problem for biological applications. Text mining approaches can be used to build hierarchical clusters or trees from the information in the biological literature. In particular, the nonnegative matrix factorization (NMF) is examined as one approach to label hierarchical trees. A generic labeling algorithm as well as an evaluation technique is proposed, and the effects of different NMF parameters with regard to convergence and labeling accuracy are discussed. The primary goals of this study are to provide a qualitative assessment of the NMF and its various parameters and initialization, to provide an automated way to classify biomedical data, and to provide a method for evaluating labeled data assuming a static input tree. As a byproduct, a method for generating gold standard trees is proposed

    Divergent effects of listening demands and evaluative threat on listening effort in online and laboratory settings

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    ObjectiveListening effort (LE) varies as a function of listening demands, motivation and resource availability, among other things. Motivation is posited to have a greater influence on listening effort under high, compared to low, listening demands.MethodsTo test this prediction, we manipulated the listening demands of a speech recognition task using tone vocoders to create moderate and high listening demand conditions. We manipulated motivation using evaluative threat, i.e., informing participants that they must reach a particular “score” for their results to be usable. Resource availability was assessed by means of working memory span and included as a fixed effects predictor. Outcome measures were indices of LE, including reaction times (RTs), self-rated work and self-rated tiredness, in addition to task performance (correct response rates). Given the recent popularity of online studies, we also wanted to examine the effect of experimental context (online vs. laboratory) on the efficacy of manipulations of listening demands and motivation. We carried out two highly similar experiments with two groups of 37 young adults, a laboratory experiment and an online experiment. To make listening demands comparable between the two studies, vocoder settings had to differ. All results were analysed using linear mixed models.ResultsResults showed that under laboratory conditions, listening demands affected all outcomes, with significantly lower correct response rates, slower RTs and greater self-rated work with higher listening demands. In the online study, listening demands only affected RTs. In addition, motivation affected self-rated work. Resource availability was only a significant predictor for RTs in the online study.DiscussionThese results show that the influence of motivation and listening demands on LE depends on the type of outcome measures used and the experimental context. It may also depend on the exact vocoder settings. A controlled laboratory settings and/or particular vocoder settings may be necessary to observe all expected effects of listening demands and motivation

    First Results on Survival from a Large Phase 3 Clinical Trial of an Autologous Dendritic Cell Vaccine in Newly Diagnosed Glioblastoma

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    Background: Standard therapy for glioblastoma includes surgery, radiotherapy, and temozolomide. This Phase 3 trial evaluates the addition of an autologous tumor lysate-pulsed dendritic cell vaccine (DCVax®-L) to standard therapy for newly diagnosed glioblastoma. Methods: After surgery and chemoradiotherapy, patients were randomized (2:1) to receive temozolomide plus DCVax-L (n = 232) or temozolomide and placebo (n = 99). Following recurrence, all patients were allowed to receive DCVax-L, without unblinding. The primary endpoint was progression free survival (PFS); the secondary endpoint was overall survival (OS). Results: For the intent-to-treat (ITT) population (n = 331), median OS (mOS) was 23.1 months from surgery. Because of the cross-over trial design, nearly 90% of the ITT population received DCVax-L. For patients with methylated MGMT (n = 131), mOS was 34.7 months from surgery, with a 3-year survival of 46.4%. As of this analysis, 223 patients are ≥ 30 months past their surgery date; 67 of these (30.0%) have lived ≥ 30 months and have a Kaplan-Meier (KM)-derived mOS of 46.5 months. 182 patients are ≥ 36 months past surgery; 44 of these (24.2%) have lived ≥ 36 months and have a KM-derived mOS of 88.2 months. A population of extended survivors (n = 100) with mOS of 40.5 months, not explained by known prognostic factors, will be analyzed further. Only 2.1% of ITT patients (n = 7) had a grade 3 or 4 adverse event that was deemed at least possibly related to the vaccine. Overall adverse events with DCVax were comparable to standard therapy alone. Conclusions: Addition of DCVax-L to standard therapy is feasible and safe in glioblastoma patients, and may extend survival

    Correction to: First results on survival from a large Phase 3 clinical trial of an autologous dendritic cell vaccine in newly diagnosed glioblastoma

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    Following publication of the original article [1], the authors reported an error in the spelling of one of the author names. In this Correction the incorrect and correct author names are indicated and the author name has been updated in the original publication. The authors also reported an error in the Methods section of the original article. In this Correction the incorrect and correct versions of the affected sentence are indicated. The original article has not been updated with regards to the error in the Methods section.https://deepblue.lib.umich.edu/bitstream/2027.42/144529/1/12967_2018_Article_1552.pd

    Hydrothermal origin of halogens at Home Plate, Gusev Crater

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    In the Inner Basin of the Columbia Hills, Gusev Crater is Home Plate, an 80 m platform of layered clastic rocks of the Barnhill class with microscopic and macroscopic textures, including a bomb sag, suggestive of a phreatomagmatic origin. We present data acquired by the Spirit Mars Exploration Rover by Alpha Particle X-Ray Spectrometer (APXS), Mössbauer Spectrometer, Miniature Thermal Emission Spectrometer (Mini- TES), and Panoramic Camera (Pancam) for the Barnhill class rocks and nearby vesicular Irvine class basalts. In major element concentrations (e.g., SiO2, Al2O3, MgO, and FeO*), the two rock classes are similar, suggesting that they are derived from a similar magmatic source. The Barnhill class, however, has higher abundances of Cl, Br, Zn, and Ge with comparable SO3 to the Irvine basalts. Nanophase ferric oxide (np ox) and volcanic glass were detected in the Barnhill class rocks by Mössbauer and Mini-TES, respectively, and imply greater alteration and cooling rates in the Barnhill than in the Irvine class rocks. The high volatile elements in the Barnhill class agree with volcanic textures that imply interaction with a briny groundwater during eruption and (or) by later alteration. Differences in composition between the Barnhill and Irvine classes allow the fingerprinting of a Na-Mg-Zn-Ge-Cl-Br (±Fe ± Ca ± CO2) brine with low S. Nearby sulfate salt soils of fumarolic origin may reflect fractionation of an acidic S-rich vapor during boiling of a hydrothermal brine at depth. Persistent groundwater was likely present during and after the formation of Home Plate

    Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies

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    Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low–BMI cases are larger than those estimated from high–BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1×10−9). The improvement varied across diseases with a 16% median increase in χ2 test statistics and a commensurate increase in power. This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci

    The Transcription Factor Ultraspiracle Influences Honey Bee Social Behavior and Behavior-Related Gene Expression

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    Behavior is among the most dynamic animal phenotypes, modulated by a variety of internal and external stimuli. Behavioral differences are associated with large-scale changes in gene expression, but little is known about how these changes are regulated. Here we show how a transcription factor (TF), ultraspiracle (usp; the insect homolog of the Retinoid X Receptor), working in complex transcriptional networks, can regulate behavioral plasticity and associated changes in gene expression. We first show that RNAi knockdown of USP in honey bee abdominal fat bodies delayed the transition from working in the hive (primarily “nursing” brood) to foraging outside. We then demonstrate through transcriptomics experiments that USP induced many maturation-related transcriptional changes in the fat bodies by mediating transcriptional responses to juvenile hormone. These maturation-related transcriptional responses to USP occurred without changes in USP's genomic binding sites, as revealed by ChIP–chip. Instead, behaviorally related gene expression is likely determined by combinatorial interactions between USP and other TFs whose cis-regulatory motifs were enriched at USP's binding sites. Many modules of JH– and maturation-related genes were co-regulated in both the fat body and brain, predicting that usp and cofactors influence shared transcriptional networks in both of these maturation-related tissues. Our findings demonstrate how “single gene effects” on behavioral plasticity can involve complex transcriptional networks, in both brain and peripheral tissues
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