Showing papers by "University of Southern California published in 2013"
John N. Weinstein1, John N. Weinstein2, Eric A. Collisson3, Gordon B. Mills1 +376 more•Institutions (31)
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.
5,294 citations
TL;DR: A method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples and prediction accuracy is corroborated using 3,809 transcriptional profiles available elsewhere in the public domain.
Abstract: Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe 'Estimation of STromal and Immune cells in MAlignant Tumours using Expression data' (ESTIMATE)--a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on https://sourceforge.net/projects/estimateproject/.
4,651 citations
Washington University in St. Louis1, Brown University2, University of British Columbia3, University of North Carolina at Chapel Hill4, University of Southern California5, Massachusetts Institute of Technology6, Seattle Cancer Care Alliance7, Johns Hopkins University8, University of Texas MD Anderson Cancer Center9, Nationwide Children's Hospital10, National Institutes of Health11, SRA International12, Temple University13, University of Chicago14, University of Pennsylvania15
TL;DR: It is found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients and the databases from this study are widely available to serve as a foundation for further investigations of AMl pathogenesis, classification, and risk stratification.
Abstract: BACKGROUND—Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined The relationships between patterns of mutations and epigenetic phenotypes are not yet clear METHODS—We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis RESULTS—AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes Of these, an average of 5 are in genes that are recurrently mutated in AML A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcriptionfactor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumorsuppressor genes (16%), DNA-methylation–related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%) Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories CONCLUSIONS—We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification (Funded by the National Institutes of Health) The molecular pathogenesis of acute myeloid leukemia (AML) has been studied with the use of cytogenetic analysis for more than three decades Recurrent chromosomal structural variations are well established as diagnostic and prognostic markers, suggesting that acquired genetic abnormalities (ie, somatic mutations) have an essential role in pathogenesis 1,2 However, nearly 50% of AML samples have a normal karyotype, and many of these genomes lack structural abnormalities, even when assessed with high-density comparative genomic hybridization or single-nucleotide polymorphism (SNP) arrays 3-5 (see Glossary) Targeted sequencing has identified recurrent mutations in FLT3, NPM1, KIT, CEBPA, and TET2 6-8 Massively parallel sequencing enabled the discovery of recurrent mutations in DNMT3A 9,10 and IDH1 11 Recent studies have shown that many patients with
3,980 citations
TL;DR: In this paper, the authors performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array-and-sequencing-based technologies, and classified them into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy number high.
Abstract: We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.
3,719 citations
Memorial Sloan Kettering Cancer Center1, Broad Institute2, Heidelberg University3, University of São Paulo4, University of California, Santa Cruz5, Harvard University6, Institute for Systems Biology7, University of Texas MD Anderson Cancer Center8, Case Western Reserve University9, Henry Ford Health System10, Duke University11, Emory University12, University of California, San Francisco13, Cedars-Sinai Medical Center14, St. Joseph's Hospital and Medical Center15, University of Florida16, Thomas Jefferson University17, University of Toronto18, Christiana Care Health System19, Mayo Clinic20, Penrose Hospital21, University of Southern California22, University of North Carolina at Chapel Hill23, Baylor College of Medicine24, University of British Columbia25, Oregon Health & Science University26, Washington University in St. Louis27
TL;DR: Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM.
3,593 citations
TL;DR: The field of signal processing on graphs merges algebraic and spectral graph theoretic concepts with computational harmonic analysis to process high-dimensional data on graphs as discussed by the authors, which are the analogs to the classical frequency domain and highlight the importance of incorporating the irregular structures of graph data domains when processing signals on graphs.
Abstract: In applications such as social, energy, transportation, sensor, and neuronal networks, high-dimensional data naturally reside on the vertices of weighted graphs. The emerging field of signal processing on graphs merges algebraic and spectral graph theoretic concepts with computational harmonic analysis to process such signals on graphs. In this tutorial overview, we outline the main challenges of the area, discuss different ways to define graph spectral domains, which are the analogs to the classical frequency domain, and highlight the importance of incorporating the irregular structures of graph data domains when processing signals on graphs. We then review methods to generalize fundamental operations such as filtering, translation, modulation, dilation, and downsampling to the graph setting and survey the localized, multiscale transforms that have been proposed to efficiently extract information from high-dimensional data on graphs. We conclude with a brief discussion of open issues and possible extensions.
3,475 citations
Johns Hopkins University1, University of Utah2, University of Rochester3, The Royal Marsden NHS Foundation Trust4, National Institutes of Health5, Stanford University6, Washington University in St. Louis7, Ontario Institute for Cancer Research8, University of Sydney9, St. Jude Medical Center10, University of Toronto11, Mayo Clinic12, American Society of Clinical Oncology13, University of Southern California14, North Carolina State University15, Indiana University16, University of Milan17, University of Michigan18
TL;DR: The Update Committee recommends that HER2 status (HER2 negative or positive) be determined in all patients with invasive breast cancer on the basis of one or more HER2 test results (negative, equivocal, or positive).
Abstract: Purpose.—To update the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guideline recommendations for human epidermal growth factor receptor 2 (HER2) testing in b...
2,817 citations
Chad J. Creighton1, Margaret Morgan1, Preethi H. Gunaratne1, Preethi H. Gunaratne2 +288 more•Institutions (27)
TL;DR: Remodelling cellular metabolism constitutes a recurrent pattern in ccRCC that correlates with tumour stage and severity and offers new views on the opportunities for disease treatment.
Abstract: Genetic changes underlying clear cell renal cell carcinoma (ccRCC) include alterations in genes controlling cellular oxygen sensing (for example, VHL) and the maintenance of chromatin states (for example, PBRM1). We surveyed more than 400 tumours using different genomic platforms and identified 19 significantly mutated genes. The PI(3)K/AKT pathway was recurrently mutated, suggesting this pathway as a potential therapeutic target. Widespread DNA hypomethylation was associated with mutation of the H3K36 methyltransferase SETD2, and integrative analysis suggested that mutations involving the SWI/SNF chromatin remodelling complex (PBRM1, ARID1A, SMARCA4) could have far-reaching effects on other pathways. Aggressive cancers demonstrated evidence of a metabolic shift, involving downregulation of genes involved in the TCA cycle, decreased AMPK and PTEN protein levels, upregulation of the pentose phosphate pathway and the glutamine transporter genes, increased acetyl-CoA carboxylase protein, and altered promoter methylation of miR-21 (also known as MIR21) and GRB10. Remodelling cellular metabolism thus constitutes a recurrent pattern in ccRCC that correlates with tumour stage and severity and offers new views on the opportunities for disease treatment.
2,548 citations
TL;DR: In this paper, the authors discuss the properties of currently available glucose-lowering agents that may guide treatment choice in individual patients with type 2 diabetes mellitus, including vildagliptin.
Abstract: Erratum to: DiabetologiaDOI 10.1007/s00125-012-2534-0In the text box ‘Properties of currently available glucose-lowering agents that may guide treatment choice in individualpatients with type 2 diabetes mellitus ’ vildagliptin was incor-rectly assigned footnote ‘a’ (Limited use in the USA/Europe)instead of footnote ‘b’ (Not licensed in the USA).
2,509 citations
TL;DR: A quantitative model of aging is built using measurements at more than 450,000 CpG markers from the whole blood of 656 human individuals, aged 19 to 101, to measure the rate at which an individual's methylome ages, which is impacted by gender and genetic variants.
2,430 citations
TL;DR: The viability of using the orbital angular momentum (OAM) of light to create orthogonal, spatially distinct streams of data-transmitting channels that are multiplexed in a single fiber is demonstrated and suggest that OAM could provide an additional degree of freedom for data multiplexing in future fiber networks.
Abstract: Internet data traffic capacity is rapidly reaching limits imposed by optical fiber nonlinear effects Having almost exhausted available degrees of freedom to orthogonally multiplex data, the possibility is now being explored of using spatial modes of fibers to enhance data capacity We demonstrate the viability of using the orbital angular momentum (OAM) of light to create orthogonal, spatially distinct streams of data-transmitting channels that are multiplexed in a single fiber Over 11 kilometers of a specially designed optical fiber that minimizes mode coupling, we achieved 400-gigabits-per-second data transmission using four angular momentum modes at a single wavelength, and 16 terabits per second using two OAM modes over 10 wavelengths These demonstrations suggest that OAM could provide an additional degree of freedom for data multiplexing in future fiber networks
TL;DR: This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system, and redesigned the website interface to improve both user experience and the system's analytical capability.
Abstract: The PANTHER (protein annotation through evolutionary relationship) classification system (http://wwwpantherdborg/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs) Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists In the 2013 release of PANTHER (v80), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system
TL;DR: Evidence is provided for a continuing role of targeted treatment after disease progression, with regorafenib offering a potential new line of therapy in this treatment-refractory population of patients with metastatic colorectal cancer.
University of Wisconsin-Madison1, University of Hawaii2, University of Kiel3, Cornell University4, Max Planck Society5, Pasteur Institute6, Stanford University7, University of Helsinki8, University of Würzburg9, University of California, Berkeley10, University of New South Wales11, Harvard University12, California Institute of Technology13, University of Colorado Boulder14, University of Southern California15, University of North Carolina at Chapel Hill16, University of Connecticut17, Duke University18
TL;DR: Recent technological and intellectual advances that have changed thinking about five questions about how have bacteria facilitated the origin and evolution of animals; how do animals and bacteria affect each other’s genomes; how does normal animal development depend on bacterial partners; and how is homeostasis maintained between animals and their symbionts are highlighted.
Abstract: In the last two decades, the widespread application of genetic and genomic approaches has revealed a bacterial world astonishing in its ubiquity and diversity. This review examines how a growing knowledge of the vast range of animal–bacterial interactions, whether in shared ecosystems or intimate symbioses, is fundamentally altering our understanding of animal biology. Specifically, we highlight recent technological and intellectual advances that have changed our thinking about five questions: how have bacteria facilitated the origin and evolution of animals; how do animals and bacteria affect each other’s genomes; how does normal animal development depend on bacterial partners; how is homeostasis maintained between animals and their symbionts; and how can ecological approaches deepen our understanding of the multiple levels of animal–bacterial interaction. As answers to these fundamental questions emerge, all biologists will be challenged to broaden their appreciation of these interactions and to include investigations of the relationships between and among bacteria and their animal partners as we seek a better understanding of the natural world.
TL;DR: Empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.
Abstract: Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.
TL;DR: The time is right to rethink the role of IT strategy, from that of a functional-level strategy--aligned but essentially always subordinate to business strategy--to one that reflects a fusion between IT strategy and business strategy, herein termed digital business strategy.
Abstract: Over the last three decades, the prevailing view of information technology strategy has been that it is a functional-level strategy that must be aligned with the firm's chosen business strategy. Even within this so-called alignment view, business strategy directed IT strategy. During the last decade, the business infrastructure has become digital with increased interconnections among products, processes, and services. Across many firms spanning different industries and sectors, digital technologies (viewed as combinations of information, computing, communication, and connectivity technologies) are fundamentally transforming business strategies, business processes, firm capabilities, products and services, and key interfirm relationships in extended business networks. Accordingly, we argue that the time is right to rethink the role of IT strategy, from that of a functional-level strategy--aligned but essentially always subordinate to business strategy--to one that reflects a fusion between IT strategy and business strategy. This fusion is herein termed digital business strategy.
We identify four key themes to guide our thinking on digital business strategy and help provide a framework to define the next generation of insights. The four themes are (1) the scope of digital business strategy, (2) the scale of digital business strategy, (3) the speed of digital business strategy, and (4) the sources of business value creation and capture in digital business strategy. After elaborating on each of these four themes, we discuss the success metrics and potential performance implications from pursuing a digital business strategy. We also show how the papers in the special issue shed light on digital strategies and offer directions to advance insights and shape future research.
TL;DR: A taxonomy of nearly 65 models of attention provides a critical comparison of approaches, their capabilities, and shortcomings, and addresses several challenging issues with models, including biological plausibility of the computations, correlation with eye movement datasets, bottom-up and top-down dissociation, and constructing meaningful performance measures.
Abstract: Modeling visual attention-particularly stimulus-driven, saliency-based attention-has been a very active research area over the past 25 years. Many different models of attention are now available which, aside from lending theoretical contributions to other fields, have demonstrated successful applications in computer vision, mobile robotics, and cognitive systems. Here we review, from a computational perspective, the basic concepts of attention implemented in these models. We present a taxonomy of nearly 65 models, which provides a critical comparison of approaches, their capabilities, and shortcomings. In particular, 13 criteria derived from behavioral and computational studies are formulated for qualitative comparison of attention models. Furthermore, we address several challenging issues with models, including biological plausibility of the computations, correlation with eye movement datasets, bottom-up and top-down dissociation, and constructing meaningful performance measures. Finally, we highlight current research trends in attention modeling and provide insights for future.
TL;DR: The Cancer Genome Atlas Pan-Cancer data set was used in this article to investigate the role of SCNAs in cancer-related SCNA patterns, including whole-genome doubling, TP53 mutations, CCNE1 amplifications and alterations of PPP2R complex.
Abstract: Determining how somatic copy number alterations (SCNAs) promote cancer is an important goal. We characterized SCNA patterns in 4,934 cancers from The Cancer Genome Atlas Pan-Cancer data set. Whole-genome doubling, observed in 37% of cancers, was associated with higher rates of every other type of SCNA, TP53 mutations, CCNE1 amplifications and alterations of the PPP2R complex. SCNAs that were internal to chromosomes tended to be shorter than telomere-bounded SCNAs, suggesting different mechanisms underlying their generation. Significantly recurrent focal SCNAs were observed in 140 regions, including 102 without known oncogene or tumor suppressor gene targets and 50 with significantly mutated genes. Amplified regions without known oncogenes were enriched for genes involved in epigenetic regulation. When levels of genomic disruption were accounted for, 7% of region pairs were anticorrelated, and these regions tended to encompass genes whose proteins physically interact, suggesting related functions. These results provide insights into mechanisms of generation and functional consequences of cancer-related SCNAs.
Alternatives1, John Innes Centre2, University of Bonn3, University of North Carolina at Chapel Hill4, University of Wisconsin-Madison5, University of Utah6, University of Southern California7, University of Edinburgh8, University of Warwick9, Harvard University10, University College Cork11, University of Queensland12, University of Hertfordshire13, University of Potsdam14, University of California, San Diego15, Goethe University Frankfurt16, University of California, San Francisco17, University of Delaware18, Uppsala University19, Medical University of Vienna20, J. Craig Venter Institute21, University of Hawaii at Manoa22, Leibniz Association23, University of Iowa24, University of Aberdeen25, Georgia Institute of Technology26, University of California, Berkeley27, University of Groningen28, Princeton University29, University of Marburg30, University of Illinois at Urbana–Champaign31, Saarland University32, Norwegian University of Life Sciences33, Massey University34, Toyama Prefectural University35, ETH Zurich36, University of Saskatchewan37, Rutgers University38, Scripps Research Institute39, University of Helsinki40, Texas A&M University41, National Institutes of Health42, Technical University of Berlin43, University of Otago44, University of Cambridge45, University of Alberta46, Michigan State University47, Hofstra University48
TL;DR: This review presents recommended nomenclature for the biosynthesis of ribosomally synthesized and post-translationally modified peptides (RiPPs), a rapidly growing class of natural products.
TL;DR: Little or no rigor for justifying sample size was shown for virtually all of the IS studies in this dataset, implying the subjective nature of sample size in qualitative IS studies.
Abstract: This study examines 83 IS qualitative studies in leading IS journals for the following purposes: (a) identifying the extent to which IS qualitative studies employ best practices of justifying sample size; (b) identifying optimal ranges of interviews for various types of qualitative research; and (c) identifying the extent to which cultural factors (such as journal of publication, number of authors, world region) impact sample size of interviews. Little or no rigor for justifying sample size was shown for virtually all of the IS studies in this dataset. Furthermore, the number of interviews conducted for qualitative studies is correlated with cultural factors, implying the subjective nature of sample size in qualitative IS studies. Recommendations are provided for minimally acceptable practices of justifying sample size of interviews in qualitative IS studies.
TL;DR: The genome-wide architecture of intratumor variability in GB is revealed across multiple spatial scales and patient-specific patterns of cancer evolution, with consequences for treatment design.
Abstract: Glioblastoma (GB) is the most common and aggressive primary brain malignancy, with poor prognosis and a lack of effective therapeutic options. Accumulating evidence suggests that intratumor heterogeneity likely is the key to understanding treatment failure. However, the extent of intratumor heterogeneity as a result of tumor evolution is still poorly understood. To address this, we developed a unique surgical multisampling scheme to collect spatially distinct tumor fragments from 11 GB patients. We present an integrated genomic analysis that uncovers extensive intratumor heterogeneity, with most patients displaying different GB subtypes within the same tumor. Moreover, we reconstructed the phylogeny of the fragments for each patient, identifying copy number alterations in EGFR and CDKN2A/B/p14ARF as early events, and aberrations in PDGFRA and PTEN as later events during cancer progression. We also characterized the clonal organization of each tumor fragment at the single-molecule level, detecting multiple coexisting cell lineages. Our results reveal the genome-wide architecture of intratumor variability in GB across multiple spatial scales and patient-specific patterns of cancer evolution, with consequences for treatment design.
TL;DR: This review covers the current knowledge of fusion protein linkers and summarizes examples for their design and application and considers the general properties of linkers derived from naturally-occurring multi-domain proteins as the foundation in linker design.
TL;DR: Dynamical movement primitives is presented, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques, and its properties are evaluated in motor control and robotics.
Abstract: Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear systems is the focus of investigations, it is of equal importance to create goal-directed behavior e.g., stable locomotion from a system of coupled oscillators under perceptual guidance. Modeling goal-directed behavior with nonlinear systems is, however, rather difficult due to the parameter sensitivity of these systems, their complex phase transitions in response to subtle parameter changes, and the difficulty of analyzing and predicting their long-term behavior; intuition and time-consuming parameter tuning play a major role. This letter presents and reviews dynamical movement primitives, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques. The essence of our approach is to start with a simple dynamical system, such as a set of linear differential equations, and transform those into a weakly nonlinear system with prescribed attractor dynamics by means of a learnable autonomous forcing term. Both point attractors and limit cycle attractors of almost arbitrary complexity can be generated. We explain the design principle of our approach and evaluate its properties in several example applications in motor control and robotics.
TL;DR: JSDM achieves significant savings both in the downlink training and in the CSIT uplink feedback, thus making the use of large antenna arrays at the base station potentially suitable also for frequency division duplexing systems, for which uplink/downlink channel reciprocity cannot be exploited.
Abstract: We propose joint spatial division and multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base station while requiring reduced-dimensional channel state information at the transmitter (CSIT). JSDM achieves significant savings both in the downlink training and in the CSIT uplink feedback, thus making the use of large antenna arrays at the base station potentially suitable also for frequency division duplexing (FDD) systems, for which uplink/downlink channel reciprocity cannot be exploited. In the proposed scheme, the multiuser MIMO downlink precoder is obtained by concatenating a prebeamforming matrix, which depends only on the channel second-order statistics, with a classical multiuser precoder, based on the instantaneous knowledge of the resulting reduced dimensional “effective” channel matrix. We prove a simple condition under which JSDM incurs no loss of optimality with respect to the full CSIT case. For linear uniformly spaced arrays, we show that such condition is approached in the large number of antennas limit. For this case, we use Szego's asymptotic theory of Toeplitz matrices to show that a DFT-based prebeamforming matrix is near-optimal, requiring only coarse information about the users angles of arrival and angular spread. Finally, we extend these ideas to the case of a 2-D base station antenna array, with 3-D beamforming, including multiple beams in the elevation angle direction. We provide guidelines for the prebeamforming optimization and calculate the system spectral efficiency under proportional fairness and max-min fairness criteria, showing extremely attractive performance. Our numerical results are obtained via asymptotic random matrix theory, avoiding lengthy Monte Carlo simulations and providing accurate results for realistic (finite) number of antennas and users.
TL;DR: This work shows that the uncoded optimum file assignment is NP-hard, and develops a greedy strategy that is provably within a factor 2 of the optimum, and provides an efficient algorithm achieving a provably better approximation ratio of 1-1/d d, where d is the maximum number of helpers a user can be connected to.
Abstract: Video on-demand streaming from Internet-based servers is becoming one of the most important services offered by wireless networks today. In order to improve the area spectral efficiency of video transmission in cellular systems, small cells heterogeneous architectures (e.g., femtocells, WiFi off-loading) are being proposed, such that video traffic to nomadic users can be handled by short-range links to the nearest small cell access points (referred to as “helpers”). As the helper deployment density increases, the backhaul capacity becomes the system bottleneck. In order to alleviate such bottleneck we propose a system where helpers with low-rate backhaul but high storage capacity cache popular video files. Files not available from helpers are transmitted by the cellular base station. We analyze the optimum way of assigning files to the helpers, in order to minimize the expected downloading time for files. We distinguish between the uncoded case (where only complete files are stored) and the coded case, where segments of Fountain-encoded versions of the video files are stored at helpers. We show that the uncoded optimum file assignment is NP-hard, and develop a greedy strategy that is provably within a factor 2 of the optimum. Further, for a special case we provide an efficient algorithm achieving a provably better approximation ratio of 1-(1-1/d )d, where d is the maximum number of helpers a user can be connected to. We also show that the coded optimum cache assignment problem is convex that can be further reduced to a linear program. We present numerical results comparing the proposed schemes.
TL;DR: In the past decade, surface plasmon resonance of Ag and Au nanoparticles has been investigated to improve the efficiency of photocatalytic processes as discussed by the authors, which is particularly interesting for its ability to store the sun's energy in chemical bonds that can be released later without producing harmful byproducts.
Abstract: In the past decade, the surface plasmon resonance of Ag and Au nanoparticles has been investigated to improve the efficiency of photocatalytic processes. The photocatalytic production of fuels is particularly interesting for its ability to store the sun's energy in chemical bonds that can be released later without producing harmful byproducts. This Feature Article reviews recent work demonstrating plasmon-enhanced photocatalytic water splitting, reduction of CO2 with H2O to form hydrocarbon fuels, and degradation of organic molecules. Focus is placed on several possible mechanisms that have been previously discussed in the literature. A particular emphasis is given to several aspects of these mechanisms that are not fully understood and will require further investigation.
TL;DR: Graphene CVD on various metal substrates with an emphasis on Ni and Cu is reviewed, showing how few-layer graphene grown on Ni can function as flexible transparent conductive electrodes for organic photovoltaic cells and in field effect transistors.
Abstract: Since its debut in 2004, graphene has attracted enormous interest because of its unique properties. Chemical vapor deposition (CVD) has emerged as an important method for the preparation and production of graphene for various applications since the method was first reported in 2008/2009. In this Account, we review graphene CVD on various metal substrates with an emphasis on Ni and Cu. In addition, we discuss important and representative applications of graphene formed by CVD, including as flexible transparent conductors for organic photovoltaic cells and in field effect transistors.Growth on polycrystalline Ni films leads to both monolayer and few-layer graphene with multiple layers because of the grain boundaries on Ni films. We can greatly increase the percentage of monolayer graphene by using single-crystalline Ni(111) substrates, which have smooth surface and no grain boundaries. Due to the extremely low solubility of carbon in Cu, Cu has emerged as an even better catalyst for the growth of monolayer ...
TL;DR: The roles of miRNAs and lncRNAs in cancer are summarized, with a focus on the recently identified novel mechanisms of action, and the current strategies in designing ncRNA-targeting therapeutics are discussed.
Abstract: The first cancer-targeted microRNA (miRNA) drug - MRX34, a liposome-based miR-34 mimic - entered Phase I clinical trials in patients with advanced hepatocellular carcinoma in April 2013, and miRNA therapeutics are attracting special attention from both academia and biotechnology companies. Although miRNAs are the most studied non-coding RNAs (ncRNAs) to date, the importance of long non-coding RNAs (lncRNAs) is increasingly being recognized. Here, we summarize the roles of miRNAs and lncRNAs in cancer, with a focus on the recently identified novel mechanisms of action, and discuss the current strategies in designing ncRNA-targeting therapeutics, as well as the associated challenges.
TL;DR: Surgical resection remains the primary and preferred approach to the treatment of stage I and II NSCLC, and mediastinal lymph node sampling at the time of curative intent surgical resection can be performed without increased morbidity.
TL;DR: A meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, and identified 29,807 SNPs for further genotyping suggests that more than 1,000 additional loci are involved in breast cancer susceptibility.
Abstract: Breast cancer is the most common cancer among women Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC) The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10(-8)) Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility