56 research outputs found

    Discovering Application-Level Insider Attacks Using Symbolic Execution

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    Coordinated Science Laboratory was formerly known as Control Systems LaboratoryNational Science Foundation / 727 NSF CNS 05-5166

    Anti-counterfeiting: Mixing the Physical and the Digital World

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    In this paper, we overview a set of desiderata for building digital anti-counterfeiting technologies that rely upon the difficulty of manufacturing randomized complex 3D objects. Then, we observe how this set is addressed by RF-DNA, an anti-counterfeiting technology recently proposed by DeJean and Kirovski. RF-DNA constructs certificates of authenticity as random objects that exhibit substantial uniqueness in the electromagnetic domain

    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

    Projected WIMP sensitivity of the LUX-ZEPLIN dark matter experiment

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    LUX-ZEPLIN (LZ) is a next-generation dark matter direct detection experiment that will operate 4850 feet underground at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. Using a two-phase xenon detector with an active mass of 7 tonnes, LZ will search primarily for low-energy interactions with weakly interacting massive particles (WIMPs), which are hypothesized to make up the dark matter in our galactic halo. In this paper, the projected WIMP sensitivity of LZ is presented based on the latest background estimates and simulations of the detector. For a 1000 live day run using a 5.6-tonne fiducial mass, LZ is projected to exclude at 90% confidence level spin-independent WIMP-nucleon cross sections above 1.4 × 10-48cm2 for a 40 GeV/c2 mass WIMP. Additionally, a 5σ discovery potential is projected, reaching cross sections below the exclusion limits of recent experiments. For spin-dependent WIMP-neutron(-proton) scattering, a sensitivity of 2.3 × 10−43 cm2 (7.1 × 10−42 cm2) for a 40 GeV/c2 mass WIMP is expected. With underground installation well underway, LZ is on track for commissioning at SURF in 2020

    Design und Qualitätskontrolle der zahnmedizinischen Untersuchung in der NAKO Gesundheitsstudie [Design and quality control of the oral health status examination in the German National Cohort (GNC)]

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    BACKGROUND: Caries and periodontitis are highly prevalent worldwide. Because detailed data on these oral diseases were collected within the framework of the German National Cohort (GNC), associations between oral and systemic diseases and conditions can be investigated. OBJECTIVES: The study protocol for the oral examination was designed to ensure a comprehensive collection of dental findings by trained non-dental staff within a limited examination time. At the mid-term of the GNC baseline examination, a first quality evaluation was performed to check the plausibility of results and to propose measures to improve the data quality. MATERIALS AND METHODS: A dental interview, saliva sampling and oral diagnostics were conducted. As part of the level‑1 examination, the number of teeth and prostheses were recorded. As part of the level‑2 examination, detailed periodontal, cariological and functional aspects were examined. All examinations were conducted by trained non-dental personnel. Parameters were checked for plausibility and variable distributions were descriptively analysed. RESULTS: Analyses included data of 57,967 interview participants, 56,913 level‑1 participants and 6295 level‑2 participants. Percentages of missing values for individual clinical parameters assessed in level 1 and level 2 ranged between 0.02 and 3.9%. Results showed a plausible distribution of the data; rarely, implausible values were observed, e.g. for measurements of horizontal and vertical overbite (overjet and overbite). Intra-class correlation coefficients indicated differences in individual parameters between regional clusters, study centres and across different examiners. CONCLUSIONS: he results confirm the feasibility of the study protocol by non-dental personnel and its successful integration into the GNC's overall assessment program. However, rigorous dental support of the study centres is required for quality management

    Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

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    Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

    Measurement of the gamma ray background in the Davis Cavern at the Sanford Underground Research Facility

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    Deep underground environments are ideal for low background searches due to the attenuation of cosmic rays by passage through the earth. However, they are affected by backgrounds from γ-rays emitted by 40K and the 238U and 232Th decay chains in the surrounding rock. The LUX-ZEPLIN (LZ) experiment will search for dark matter particle interactions with a liquid xenon TPC located within the Davis campus at the Sanford Underground Research Facility, Lead, South Dakota, at the 4,850-foot level. In order to characterise the cavern background, in-situ γ-ray measurements were taken with a sodium iodide detector in various locations and with lead shielding. The integral count rates (0--3300~keV) varied from 596~Hz to 1355~Hz for unshielded measurements, corresponding to a total flux in the cavern of 1.9±0.4~γ cm−2s−1. The resulting activity in the walls of the cavern can be characterised as 220±60~Bq/kg of 40K, 29±15~Bq/kg of 238U, and 13±3~Bq/kg of 232Th

    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

    Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

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    The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing

    lncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in Cancer

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    We characterized the epigenetic landscape of genes encoding long noncoding RNAs (lncRNAs) across 6,475 tumors and 455 cancer cell lines. In stark contrast to the CpG island hypermethylation phenotype in cancer, we observed a recurrent hypomethylation of 1,006 lncRNA genes in cancer, including EPIC1 (epigenetically-induced lncRNA1). Overexpression of EPIC1 is associated with poor prognosis in luminal B breast cancer patients and enhances tumor growth in vitro and in vivo. Mechanistically, EPIC1 promotes cell-cycle progression by interacting with MYC through EPIC1's 129\u2013283 nt region. EPIC1 knockdown reduces the occupancy of MYC to its target genes (e.g., CDKN1A, CCNA2, CDC20, and CDC45). MYC depletion abolishes EPIC1's regulation of MYC target and luminal breast cancer tumorigenesis in vitro and in vivo. Wang et al. characterize the epigenetic landscape of lncRNAs genes across a large number of human tumors and cancer cell lines and observe recurrent hypomethylation of lncRNA genes, including EPIC1. EPIC1 RNA promotes cell-cycle progression by interacting with MYC and enhancing its binding to target genes
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