117 resultados para Boneh-Boyen Signatures


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BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.

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Sunspots on the surface of the Sun are the observational signatures of intense manifestations of tightly packed magnetic field lines, with near-vertical field strengths exceeding 6,000 G in extreme cases1. It is well accepted that both the plasma density and the magnitude of the magnetic field strength decrease rapidly away from the solar surface, making high-cadence coronal measurements through traditional Zeeman and Hanle effects difficult as the observational signatures are fraught with low-amplitude signals that can become swamped with instrumental noise2, 3. Magneto-hydrodynamic (MHD) techniques have previously been applied to coronal structures, with single and spatially isolated magnetic field strengths estimated as 9–55 G (refs 4,5,6,7). A drawback with previous MHD approaches is that they rely on particular wave modes alongside the detectability of harmonic overtones. Here we show, for the first time, how omnipresent magneto-acoustic waves, originating from within the underlying sunspot and propagating radially outwards, allow the spatial variation of the local coronal magnetic field to be mapped with high precision. We find coronal magnetic field strengths of 32 ± 5 G above the sunspot, which decrease rapidly to values of approximately 1 G over a lateral distance of 7,000 km, consistent with previous isolated and unresolved estimations. Our results demonstrate a new, powerful technique that harnesses the omnipresent nature of sunspot oscillations to provide magnetic field mapping capabilities close to a magnetic source in the solar corona.

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As cryptographic implementations are increasingly subsumed as functional blocks within larger systems on chip, it becomes more difficult to identify the power consumption signatures of cryptographic operations amongst other unrelated processing activities. In addition, at higher clock frequencies, the current decay between successive processing rounds is only partial, making it more difficult to apply existing pattern matching techniques in side-channel analysis. We show however, through the use of a phase-sensitive detector, that power traces can be pre-processed to generate a filtered output which exhibits an enhanced round pattern, enabling the identification of locations on a device where encryption operations are occurring and also assisting with the re-alignment of power traces for side-channel attacks.

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Increasing evidence suggests that asthma is a heterogeneous disorder regulated by distinct molecular mechanisms. In a cross-sectional study of asthmatics of varying severity (n = 51), endobronchial tissue gene expression analysis revealed three major patient clusters: TH2-high, TH17-high, and TH2/17-low. TH2-high and TH17-high patterns were mutually exclusive in individual patient samples, and their gene signatures were inversely correlated and differentially regulated by interleukin-13 (IL-13) and IL-17A. To understand this dichotomous pattern of T helper 2 (TH2) and TH17 signatures, we investigated the potential of type 2 cytokine suppression in promoting TH17 responses in a preclinical model of allergen-induced asthma. Neutralization of IL-4 and/or IL-13 resulted in increased TH17 cells and neutrophilic inflammation in the lung. However, neutralization of IL-13 and IL-17 protected mice from eosinophilia, mucus hyperplasia, and airway hyperreactivity and abolished the neutrophilic inflammation, suggesting that combination therapies targeting both pathways may maximize therapeutic efficacy across a patient population comprising both TH2 and TH17 endotypes.

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We calculate and analyze Feshbach resonance spectra for ultracold Yb(1S0)+Yb(3P2) collisions as a function of an interatomic potential scaling factor λ and external magnetic field. We show that, at zero field, the resonances are distributed randomly in λ, but that signatures of quantum chaos emerge as a field is applied. The random zero-field distribution arises from superposition of structured spectra associated with individual total angular momenta. In addition, we show that the resonances with respect to magnetic field in the experimentally accessible range of 400 to 2000 G are chaotically distributed, with strong level repulsion that is characteristic of quantum chaos.

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Breast cancer is a heterogeneous disease, at both an inter- and intra-tumoural level. Appreciating heterogeneity through the application of biomarkers and molecular signatures adds complexity to tumour taxonomy but is key to personalising diagnosis, treatment and prognosis. The extent to which heterogeneity exists, and its interpretation remains a challenge to pathologists. Using HER2 as an exemplar, we have developed a simple reproducible heterogeneity index. Cell-to-cell HER2 heterogeneity was extensive in a proportion of both reported 'amplified' and 'non-amplified' cases. The highest levels of heterogeneity objectively identified occurred in borderline categories and higher ratio non-amplified cases. A case with particularly striking heterogeneity was analysed further with an array of biomarkers in order to assign a molecular diagnosis. Broad biological complexity was evident. In essence, interpretation, depending on the area of tumour sampled, could have been one of three distinct phenotypes, each of which would infer different therapeutic interventions. Therefore, we recommend that heterogeneity is assessed and taken into account when determining treatment options.

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This chapter reviews the recent observations of waves and oscillations manifesting in fine-scale magnetic structures in the solar photosphere, which are often interpreted as the "building blocks' of the magnetic Sun. The authors found, through phase relationships between the various waveforms, that small-scale magnetic bright points (MBPs) in the photosphere demonstrated signatures of specific magnetoacoustic waves, in particular the sausage and kink modes. Modern magnetohydrodynamic (MHD) simulations of the lower solar atmosphere clearly show how torsional motions can easily be induced in magnetic elements in the photosphere through the processes of vortical motions and/or buffeting by neighboring granules. The authors detected significant power associated with high-frequency horizontal motions, and suggested that these cases may be especially important in the creation of a turbulent environment that efficiently promotes Alfvén wave dissipation.

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Passive intermodulation (PIM) often limits the performance of communication systems with analog and digitally-modulated signals and especially of systems supporting multiple carriers. Since the origins of the apparently multiple physical sources of nonlinearity causing PIM are not fully understood, the behavioral models are frequently used to describe the process of PIM generation. In this paper a polynomial model of memoryless nonlinearity is deduced from PIM measurements of a microstrip line with distributed nonlinearity with two-tone CW signals. The analytical model of nonlinearity is incorporated in Keysight Technology’s ADS simulator to evaluate the metrics of signal fidelity in the receive band for analog and digitally-modulated signals. PIM-induced distortion and cross-band interference with modulated signals are compared to those with two-tone CW signals. It is shown that conventional metrics can be applied to quantify the effect of distributed nonlinearities on signal fidelity. It is found that the two-tone CW test provides a worst-case estimate of cross-band interference for two-carrier modulated signals whereas with a three-carrier signal PIM interference in the receive band is noticeably overestimated. The simulated constellation diagrams for QPSK signals demonstrate that PIM interference exhibits the distinctive signatures of correlated distortion and this indicates that there are opportunities for mitigating PIM interference and that PIM interference cannot be treated as noise. One of the interesting results is that PIM distortion on a transmission line results in asymmetrical regrowth of output PIM interference for modulated signals.

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Prostate cancer is a unique and heterogeneous disease. Currently, a major unmet clinical need exists to develop biomarkers that enable indolent disease to be distinguished from aggressive disease. The prostate is an abundant secretor of glycoproteins of all types, and alterations in glycans are, therefore, attractive as potential biomarkers and therapeutic targets. Despite progress over the past decade in profiling the genome and proteome, the prostate cancer glycoproteome remains relatively understudied. A wide range of alterations in the glycoproteins on prostate cancer cells can occur, including increased sialylation and fucosylation, increased O-β-N-acetylglucosamine (GlcNAc) conjugation, the emergence of cryptic and high-mannose N-glycans and alterations to proteoglycans. Glycosylation can alter protein function and has a key role in many important biological processes in cancer including cell adhesion, migration, interactions with the cell matrix, immune surveillance, cell signalling and cellular metabolism; altered glycosylation in prostate cancer might modify some, or all of these processes. In the past three years, powerful tools such as glycosylation-specific antibodies and glycosylation gene signatures have been developed, which enable detailed analyses of changes in glycosylation. Thus, emerging data on these often overlooked modifications have the potential to improve risk stratification and therapeutic strategies in patients with prostate cancer.

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Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

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Rapid blue- and redshifted excursions (RBEs and RREs) are likely to be the on-disk counterparts of Type II spicules. Recently, heating signatures from RBEs/RREs have been detected in IRIS slit-jaw images dominated by transition region (TR) lines around network patches. Additionally, signatures of Type II spicules have been observed in Atmospheric Imaging Assembly (AIA) diagnostics. The full-disk, ever-present nature of the AIA diagnostics should provide us with sufficient statistics to directly determine how important RBEs and RREs are to the heating of the TR and corona. We find, with high statistical significance, that at least 11% of the low coronal brightenings detected in a quiet-Sun region in He ii 304 Å can be attributed to either RBEs or RREs as observed in Hα, and a 6% match of Fe IX 171 Å detected events to RBEs or RREs with very similar statistics for both types of Hα features. We took a statistical approach that allows for noisy detections in the coronal channels and provides us with a lower, but statistical significant, bound. Further, we consider matches based on overlapping features in both time and space, and find strong visual indications of further correspondence between coronal events and co-evolving but non-overlapping, RBEs and RREs.

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Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user’s perspective.