1,167 research outputs found
Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations.
We present a novel method for the identification of sets of mutually exclusive gene alterations in a given set of genomic profiles. We scan the groups of genes with a common downstream effect on the signaling network, using a mutual exclusivity criterion that ensures that each gene in the group significantly contributes to the mutual exclusivity pattern. We test the method on all available TCGA cancer genomics datasets, and detect multiple previously unreported alterations that show significant mutual exclusivity and are likely to be driver events
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Epidemic Exposure, Financial Technology, and the Digital Divide
We ask whether epidemic exposure leads to a shift in financial technology usage and who participates in this shift. We exploit a dataset combining Gallup World Polls and Global Findex surveys for some 250,000 individuals in 140 countries, merging them with information on the incidence of epidemics and local 3G internet infrastructure. Epidemic exposure is associated with an increase in remote-access (online/mobile) banking and substitution from bank branch-based to ATM activity. Heterogeneity in response centers on the age, income and employment of respondents. Young, high-income earners in full-time employment have the greatest tendency to shift to online/mobile trans-actions in response to epidemics. These effects are larger for individuals with better exante 3G signal coverage, highlighting the role of the digital divide in adaption to new technologies necessitated by adverse external shocks
The effect of anesthesia type on stress hormone response: Comparison of general versus epidural anesthesia
Aim: The aim of this study was to investigate the effect of different types of anesthesia on stress hormones.Materials and Methods: The study was included 60 ASAI-II cases scheduled for major lower extremity surgery. The cases were randomized into 2 groups: The EA group was administered epidural anesthesia and the GA group was administered standard general anesthesia. In order to evaluate the surgical trauma - related stress response, CRP, TSH, cortisol, and fasting blood sugar(FBS) levels were measured preoperatively, 30 min after surgical incision, and 24 h post surgery.Results: Between-group comparisons; Preoperative values were not significantly different between the groups.(P > 0,05) Pulse rate and cortisol values significantly higher in general group at 30 min. (P < 0,05), and the FBS values were significantly higher in the epidural group at 24 h.(P < 0,05) There were not found differences for other parameters at evaluation times.Conclusion: No differences were observed between the two anesthesia methods, in terms of minimizing the stress response due to surgical trauma during major low extremity surgery.Key words: Epidural anesthesia, general anesthesia, stress hormone
Land cover classification with multi-sensor fusion of partly missing data
We describe a system that uses decision tree-based tools for seamless acquisition of knowledge for classification of remotely sensed imagery. We concentrate on three important problems in this process: information fusion, model understandability, and handling of missing data. Importance of multi-sensor information fusion and the use of decision tree classifiers for such problems have been well-studied in the literature. However, these studies have been limited to the cases where all data sources have a full coverage for the scene under consideration. Our contribution in this paper is to show how decision tree classifiers can be learned with alternative (surrogate) decision nodes and result in models that are capable of dealing with missing data during both training and classification to handle cases where one or more measurements do not exist for some locations. We present detailed performance evaluation regarding the effectiveness of these classifiers for information fusion and feature selection, and study three different methods for handling missing data in comparative experiments. The results show that surrogate decisions incorporated into decision tree classifiers provide powerful models for fusing information from different data layers while being robust to missing data. © 2009 American Society for Photogrammetry and Remote Sensing
Interactive training of advanced classifiers for mining remote sensing image archives
Advances in satellite technology and availability of down-loaded images constantly increase the sizes of remote sensing image archives. Automatic content extraction, classification and content-based retrieval have become highly desired goals for the development of intelligent remote sensing databases. The common approach for mining these databases uses rules created by analysts. However, incorporating GIS information and human expert knowledge with digital image processing improves remote sensing image analysis. We developed a system that uses decision tree classifiers for interactive learning of land cover models and mining of image archives. Decision trees provide a promising solution for this problem because they can operate on both numerical (continuous) and categorical (discrete) data sources, and they do not require any assumptions about neither the distributions nor the independence of attribute values. This is especially important for the fusion of measurements from different sources like spectral data, DEM data and other ancillary GIS data. Furthermore, using surrogate splits provides the capability of dealing with missing data during both training and classification, and enables handling instrument malfunctions or the cases where one or more measurements do not exist for some locations. Quantitative and qualitative performance evaluation showed that decision trees provide powerful tools for modeling both pixel and region contents of images and mining of remote sensing image archives
Bilkent University at TRECVID 2007
We describe our fourth participation, that includes two high-level feature extraction runs, and one manual search run, to the TRECVID video retrieval evaluation. All of these runs have used a system trained on the common development collection. Only visual information, consisting of color, texture and edge-based low-level features, was used
Transient Inhibition of PI3Kδ Enhances the Therapeutic Effect of Intravenous Delivery of Oncolytic Vaccinia Virus
Tumor-targeting oncolytic viruses such as vaccinia virus (VV) are attractive cancer therapeutic agents that act through multiple mechanisms to provoke both tumor lysis and anti-tumor immune responses. However, delivery of these agents remains restricted to intra-tumoral administration, which prevents effective targeting of inaccessible and disseminated tumor cells. In the present study we have identified transient pharmacological inhibition of the leukocyte-enriched phosphoinositide 3-kinase δ (PI3Kδ) as a novel mechanism to potentiate intravenous delivery of oncolytic VV to tumors. Pre-treatment of immunocompetent mice with the PI3Kδ-selective inhibitor IC87114 or the clinically approved idelalisib (CAL-101), prior to intravenous delivery of a tumor-tropic VV, dramatically improved viral delivery to tumors. This occurred via an inhibition of viral attachment to, but not internalization by, systemic macrophages through perturbation of signaling pathways involving RhoA/ROCK, AKT, and Rac. Pre-treatment using PI3Kδ-selective inhibitors prior to intravenous delivery of VV resulted in enhanced anti-tumor efficacy and significantly prolonged survival compared to delivery without PI3Kδ inhibition. These results indicate that effective intravenous delivery of oncolytic VV may be clinically achievable and could be useful in improving anti-tumor efficacy of oncolytic virotherapy
Properties of 42 Solar-type Kepler Targets from the Asteroseismic Modeling Portal
Recently the number of main-sequence and subgiant stars exhibiting solar-like
oscillations that are resolved into individual mode frequencies has increased
dramatically. While only a few such data sets were available for detailed
modeling just a decade ago, the Kepler mission has produced suitable
observations for hundreds of new targets. This rapid expansion in observational
capacity has been accompanied by a shift in analysis and modeling strategies to
yield uniform sets of derived stellar properties more quickly and easily. We
use previously published asteroseismic and spectroscopic data sets to provide a
uniform analysis of 42 solar-type Kepler targets from the Asteroseismic
Modeling Portal (AMP). We find that fitting the individual frequencies
typically doubles the precision of the asteroseismic radius, mass and age
compared to grid-based modeling of the global oscillation properties, and
improves the precision of the radius and mass by about a factor of three over
empirical scaling relations. We demonstrate the utility of the derived
properties with several applications.Comment: 12 emulateapj pages, 9 figures, 1 online-only extended figure, 1
table, ApJS accepted (typo corrected in Eq.8
Tsetse Immune System Maturation Requires the Presence of Obligate Symbionts in Larvae
Tsetse harbors an obligate symbiont, Wigglesworthia glossinidia,
that must be present during larval maturation for the fly's immune system to
develop and function properly during adulthood
Incorporating scale dependence in disease burden estimates:the case of human African trypanosomiasis in Uganda
The WHO has established the disability-adjusted life year (DALY) as a metric for measuring the burden of human disease and injury globally. However, most DALY estimates have been calculated as national totals. We mapped spatial variation in the burden of human African trypanosomiasis (HAT) in Uganda for the years 2000-2009. This represents the first geographically delimited estimation of HAT disease burden at the sub-country scale.Disability-adjusted life-year (DALY) totals for HAT were estimated based on modelled age and mortality distributions, mapped using Geographic Information Systems (GIS) software, and summarised by parish and district. While the national total burden of HAT is low relative to other conditions, high-impact districts in Uganda had DALY rates comparable to the national burden rates for major infectious diseases. The calculated average national DALY rate for 2000-2009 was 486.3 DALYs/100 000 persons/year, whereas three districts afflicted by rhodesiense HAT in southeastern Uganda had burden rates above 5000 DALYs/100 000 persons/year, comparable to national GBD 2004 average burden rates for malaria and HIV/AIDS.These results provide updated and improved estimates of HAT burden across Uganda, taking into account sensitivity to under-reporting. Our results highlight the critical importance of spatial scale in disease burden analyses. National aggregations of disease burden have resulted in an implied bias against highly focal diseases for which geographically targeted interventions may be feasible and cost-effective. This has significant implications for the use of DALY estimates to prioritize disease interventions and inform cost-benefit analyses
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