Showing papers by "University of British Columbia published in 2019"
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Northern Arizona University1, National Institutes of Health2, University of Minnesota3, University of California, Davis4, Woods Hole Oceanographic Institution5, Massachusetts Institute of Technology6, University of Copenhagen7, University of Trento8, Chinese Academy of Sciences9, University of California, San Francisco10, University of Pennsylvania11, Pacific Northwest National Laboratory12, North Carolina State University13, University of California, San Diego14, Institute for Systems Biology15, Dalhousie University16, University of British Columbia17, Statens Serum Institut18, Anschutz Medical Campus19, University of Washington20, Michigan State University21, Stanford University22, Broad Institute23, Harvard University24, Australian National University25, University of Düsseldorf26, University of New South Wales27, Sookmyung Women's University28, San Diego State University29, Howard Hughes Medical Institute30, Cornell University31, Max Planck Society32, Colorado State University33, Google34, Syracuse University35, Webster University36, United States Department of Agriculture37, University of Arkansas for Medical Sciences38, Colorado School of Mines39, University of Southern Mississippi40, National Oceanic and Atmospheric Administration41, University of California, Merced42, Wageningen University and Research Centre43, University of Arizona44, Environment Agency45, University of Florida46, Merck & Co.47
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Abstract: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.
8,821 citations
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The George Institute for Global Health1, Royal North Shore Hospital2, Concord Repatriation General Hospital3, University of Sydney4, Imperial College London5, Harvard University6, New York University7, Janssen Pharmaceutica8, Indiana University – Purdue University Indianapolis9, Veterans Health Administration10, University of Chicago11, Kolling Institute of Medical Research12, Utah System of Higher Education13, University of British Columbia14, University College London15, Peking University16, Lunenfeld-Tanenbaum Research Institute17, Stanford University18
TL;DR: In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years.
Abstract: Background Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium...
3,233 citations
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Scott & White Hospital1, Columbia University2, Georgetown University3, Rutgers University4, Cleveland Clinic5, Laval University6, University of British Columbia7, New York University8, University of Washington9, Emory University10, Lankenau Institute for Medical Research11, University of Pennsylvania12, Morristown Medical Center13, University of London14
TL;DR: Among patients with severe aortic stenosis who were at low surgical risk, the rate of the composite of death, stroke, or rehospitalization at 1 year was significantly lower with TAVR than with surgery.
Abstract: Background Among patients with aortic stenosis who are at intermediate or high risk for death with surgery, major outcomes are similar with transcatheter aortic-valve replacement (TAVR) an...
2,917 citations
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University of California, Santa Barbara1, University of Texas at Austin2, University of Wrocław3, Dresden University of Technology4, University of Tartu5, Gulu University6, Middle East University7, Stockholm University8, University of the Punjab9, University of Nigeria, Nsukka10, Istanbul University11, Franklin & Marshall College12, Norwegian University of Science and Technology13, University of Algiers14, Australian National University15, Russian Academy of Sciences16, Russian State University for the Humanities17, İzmir University of Economics18, University of Social Sciences and Humanities19, Université catholique de Louvain20, Ankara University21, Pontifical Catholic University of Peru22, Cumhuriyet University23, University of the Republic24, ISCTE – University Institute of Lisbon25, The Chinese University of Hong Kong26, National Autonomous University of Mexico27, University of Pécs28, University of Constantine the Philosopher29, University of Maribor30, University of Zagreb31, University of Malaya32, Central University of Finance and Economics33, University of Crete34, University of Primorska35, Institute of Molecular and Cell Biology36, University of Amsterdam37, Catholic University of the Sacred Heart38, VU University Amsterdam39, University of Granada40, University of Delhi41, University of Havana42, Pontifical Catholic University of Rio de Janeiro43, University of Vienna44, Universiti Utara Malaysia45, Vilnius University46, University of British Columbia47, University of Sussex48, Romanian Academy49, Slovak Academy of Sciences50, Comenius University in Bratislava51, University of Monterrey52, SAS Institute53, DHA Suffa University54, Pontifical Catholic University of Chile55, South-West University "Neofit Rilski"56, University of São Paulo57, Kyung Hee University58, University of Ljubljana59
TL;DR: This work combines this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets and finds that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.
Abstract: Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.
1,827 citations
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Memorial Sloan Kettering Cancer Center1, Netherlands Cancer Institute2, Cleveland Clinic3, Institut Gustave Roussy4, University of Texas MD Anderson Cancer Center5, University of Glasgow6, University of British Columbia7, University of Lyon8, Osaka University9, University of Ulsan10, Russian Railways11, McGill University12, Medical University of Vienna13, The Royal Marsden NHS Foundation Trust14, Georgetown University15, University of Tübingen16, Pfizer17, Harvard University18
TL;DR: Progression‐free survival was significantly longer with avelumab plus axitinib than with sunit inib among patients who received these agents as first‐line treatment for advanced renal‐cell carcinoma.
Abstract: Background In a single-group, phase 1b trial, avelumab plus axitinib resulted in objective responses in patients with advanced renal-cell carcinoma. This phase 3 trial involving previously...
1,597 citations
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TL;DR: A new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes, able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants.
Abstract: The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.
1,526 citations
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University of British Columbia1, University of Western Australia2, University Hospital of Lausanne3, University of Hong Kong4, National Institutes of Health5, University of Pittsburgh6, Charité7, University of Grenoble8, University of Wisconsin-Madison9, All India Institute of Medical Sciences10, Federal University of São Paulo11, University of California, San Diego12
TL;DR: This is the first study to report global prevalence of obstructive sleep apnoea; with almost 1 billion people affected, and with prevalence exceeding 50% in some countries, effective diagnostic and treatment strategies are needed to minimise the negative health impacts and to maximise cost-effectiveness.
1,487 citations
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TL;DR: In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs, and 156 PFMs were updated, and the genomic tracks, inference tool, and TF-binding profile similarity clusters were updated.
Abstract: JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups. In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs (169 for vertebrates, 42 for plants, 17 for nematodes, 10 for insects, and 7 for fungi), and 156 PFMs were updated (125 for vertebrates, 28 for plants and 3 for insects). These new profiles represent an 18% expansion compared to the previous release. JASPAR 2020 comes with a novel collection of unvalidated TF-binding profiles for which our curators did not find orthogonal supporting evidence in the literature. This collection has a dedicated web form to engage the community in the curation of unvalidated TF-binding profiles. Moreover, we created a Q&A forum to ease the communication between the user community and JASPAR curators. Finally, we updated the genomic tracks, inference tool, and TF-binding profile similarity clusters. All the data is available through the JASPAR website, its associated RESTful API, and through the JASPAR2020 R/Bioconductor package.
1,219 citations
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University of British Columbia1, Oregon Health & Science University2, Heidelberg University3, Utrecht University4, Northern Arizona University5, University of Alberta6, George Mason University7, Wingate University8, American Cancer Society9, University of California, San Francisco10, Penn State Cancer Institute11
TL;DR: Enough evidence was available to conclude that specific doses of aerobic, combined aerobic plus resistance training, and/or resistance training could improve common cancer-related health outcomes, including anxiety, depressive symptoms, fatigue, physical functioning, and health-related quality of life.
Abstract: PurposeThe number of cancer survivors worldwide is growing, with over 15.5 million cancer survivors in the United States alone—a figure expected to double in the coming decades. Cancer survivors face unique health challenges as a result of their cancer diagnosis and the impact of treatments
1,174 citations
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University of Manchester1, University of Barcelona2, University of Texas Health Science Center at San Antonio3, National Institutes of Health4, McGill University Health Centre5, Brigham and Women's Hospital6, Temple University7, Flinders University8, Royal Devon and Exeter Hospital9, University of Michigan10, University of the Republic11, NewYork–Presbyterian Hospital12, Central University of Venezuela13, University of Ferrara14, Paris Descartes University15, University of British Columbia16, University of Birmingham17, University of Marburg18
TL;DR: Blood eosinophils are recommended as a biomarker to support clinical decisions regarding the use of inhaled corticosteroids in chronic obstructive pulmonary disease patients, based on recent evidence from clinical trials.
Abstract: Precision medicine is a patient-specific approach that integrates all relevant clinical, genetic and biological information in order to optimise the therapeutic benefit relative to the possibility of side-effects for each individual. Recent clinical trials have shown that higher blood eosinophil counts are associated with a greater efficacy of inhaled corticosteroids (ICSs) in chronic obstructive pulmonary disease (COPD) patients. Blood eosinophil counts are a biomarker with potential to be used in clinical practice, to help target ICS treatment with more precision in COPD patients with a history of exacerbations despite appropriate bronchodilator treatment. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2017 pharmacological treatment algorithms, based on the ABCD assessment, can be applied relatively easily to treatment-naive individuals at initial presentation. However, their use is more problematic during follow-up in patients who are already on maintenance treatment. There is a need for a different system to guide COPD pharmacological management during follow-up. Recent large randomised controlled trials have provided important new information concerning the therapeutic effects of ICSs and long-acting bronchodilators on exacerbations. The new evidence regarding blood eosinophils and inhaled treatments, and the need to distinguish between initial and follow-up pharmacological management, led to changes in the GOLD pharmacological treatment recommendations. This article explains the evidence and rationale for the GOLD 2019 pharmacological treatment recommendations.
1,122 citations
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TL;DR: The Simons Observatory (SO) is a new cosmic microwave background experiment being built on Cerro Toco in Chile, due to begin observations in the early 2020s as mentioned in this paper.
Abstract: The Simons Observatory (SO) is a new cosmic microwave background experiment being built on Cerro Toco in Chile, due to begin observations in the early 2020s. We describe the scientific goals of the experiment, motivate the design, and forecast its performance. SO will measure the temperature and polarization anisotropy of the cosmic microwave background in six frequency bands centered at: 27, 39, 93, 145, 225 and 280 GHz. The initial configuration of SO will have three small-aperture 0.5-m telescopes and one large-aperture 6-m telescope, with a total of 60,000 cryogenic bolometers. Our key science goals are to characterize the primordial perturbations, measure the number of relativistic species and the mass of neutrinos, test for deviations from a cosmological constant, improve our understanding of galaxy evolution, and constrain the duration of reionization. The small aperture telescopes will target the largest angular scales observable from Chile, mapping ≈ 10% of the sky to a white noise level of 2 μK-arcmin in combined 93 and 145 GHz bands, to measure the primordial tensor-to-scalar ratio, r, at a target level of σ(r)=0.003. The large aperture telescope will map ≈ 40% of the sky at arcminute angular resolution to an expected white noise level of 6 μK-arcmin in combined 93 and 145 GHz bands, overlapping with the majority of the Large Synoptic Survey Telescope sky region and partially with the Dark Energy Spectroscopic Instrument. With up to an order of magnitude lower polarization noise than maps from the Planck satellite, the high-resolution sky maps will constrain cosmological parameters derived from the damping tail, gravitational lensing of the microwave background, the primordial bispectrum, and the thermal and kinematic Sunyaev-Zel'dovich effects, and will aid in delensing the large-angle polarization signal to measure the tensor-to-scalar ratio. The survey will also provide a legacy catalog of 16,000 galaxy clusters and more than 20,000 extragalactic sources.
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TL;DR: The growing application of gene expression profiling demands powerful yet user-friendly bioinformatics tools to support systems-level data understanding and NetworkAnalyst was first released in 2014 to address the key need for interpreting gene expression data within the context of protein-protein interaction networks.
Abstract: The growing application of gene expression profiling demands powerful yet user-friendly bioinformatics tools to support systems-level data understanding. NetworkAnalyst was first released in 2014 to address the key need for interpreting gene expression data within the context of protein-protein interaction (PPI) networks. It was soon updated for gene expression meta-analysis with improved workflow and performance. Over the years, NetworkAnalyst has been continuously updated based on community feedback and technology progresses. Users can now perform gene expression profiling for 17 different species. In addition to generic PPI networks, users can now create cell-type or tissue specific PPI networks, gene regulatory networks, gene co-expression networks as well as networks for toxicogenomics and pharmacogenomics studies. The resulting networks can be customized and explored in 2D, 3D as well as Virtual Reality (VR) space. For meta-analysis, users can now visually compare multiple gene lists through interactive heatmaps, enrichment networks, Venn diagrams or chord diagrams. In addition, users have the option to create their own data analysis projects, which can be saved and resumed at a later time. These new features are released together as NetworkAnalyst 3.0, freely available at https://www.networkanalyst.ca.
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National University of Cordoba1, Leipzig University2, Helmholtz Centre for Environmental Research - UFZ3, Indiana University4, United Nations5, University of the West Indies6, Karlsruhe Institute of Technology7, National Autonomous University of Mexico8, University of Minnesota9, University of Cambridge10, BirdLife International11, University of British Columbia12, National University of Río Negro13, Chiba University14, National Institute for Environmental Studies15, Michigan State University16, United Nations University17, International Institute of Minnesota18, Stellenbosch University19, Commonwealth Scientific and Industrial Research Organisation20, Simón Bolívar University21, Hungarian Academy of Sciences22, University of Queensland23, Duke University24, Natural History Museum25, Imperial College London26, University of the West of England27, Stockholm University28, Clark University29, University of Cape Town30, IFREMER31, George Mason University32, Radboud University Nijmegen33, University of Oxford34, Royal Botanic Gardens35, University of the Philippines Diliman36
TL;DR: The first integrated global-scale intergovernmental assessment of the status, trends, and future of the links between people and nature provides an unprecedented picture of the extent of the authors' mutual dependence, the breadth and depth of the ongoing and impending crisis, and the interconnectedness among sectors and regions.
Abstract: The human impact on life on Earth has increased sharply since the 1970s, driven by the demands of a growing population with rising average per capita income. Nature is currently supplying more materials than ever before, but this has come at the high cost of unprecedented global declines in the extent and integrity of ecosystems, distinctness of local ecological communities, abundance and number of wild species, and the number of local domesticated varieties. Such changes reduce vital benefits that people receive from nature and threaten the quality of life of future generations. Both the benefits of an expanding economy and the costs of reducing nature's benefits are unequally distributed. The fabric of life on which we all depend-nature and its contributions to people-is unravelling rapidly. Despite the severity of the threats and lack of enough progress in tackling them to date, opportunities exist to change future trajectories through transformative action. Such action must begin immediately, however, and address the root economic, social, and technological causes of nature's deterioration.
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University of Sydney1, Guy's and St Thomas' NHS Foundation Trust2, University of British Columbia3, Harvard University4, Monash University5, Royal Prince Alfred Hospital6, St. Vincent's Health System7, Garvan Institute of Medical Research8, Auckland City Hospital9, Sydney Adventist Hospital10, Mater Misericordiae University Hospital11, University College Dublin12, University of Alberta13, University of Adelaide14, Queen's University15, University of Ottawa16, Ottawa Hospital Research Institute17, University of Melbourne18, Royal Adelaide Hospital19, Royal Cornwall Hospital20
TL;DR: Enzalutamide was associated with significantly longer progression-free and overall survival than standard care in men with metastatic, hormone-sensitive prostate cancer receiving testosterone suppression.
Abstract: Background Enzalutamide, an androgen-receptor inhibitor, has been associated with improved overall survival in men with castration-resistant prostate cancer. It is not known whether adding enzalutamide to testosterone suppression, with or without early docetaxel, will improve survival in men with metastatic, hormone-sensitive prostate cancer. Methods In this open-label, randomized, phase 3 trial, we assigned patients to receive testosterone suppression plus either open-label enzalutamide or a standard nonsteroidal antiandrogen therapy (standard-care group). The primary end point was overall survival. Secondary end points included progression-free survival as determined by the prostate-specific antigen (PSA) level, clinical progression-free survival, and adverse events. Results A total of 1125 men underwent randomization; the median follow-up was 34 months. There were 102 deaths in the enzalutamide group and 143 deaths in the standard-care group (hazard ratio, 0.67; 95% confidence interval [CI], 0.52 to 0.86; P = 0.002). Kaplan-Meier estimates of overall survival at 3 years were 80% (based on 94 events) in the enzalutamide group and 72% (based on 130 events) in the standard-care group. Better results with enzalutamide were also seen in PSA progression-free survival (174 and 333 events, respectively; hazard ratio, 0.39; P Conclusions Enzalutamide was associated with significantly longer progression-free and overall survival than standard care in men with metastatic, hormone-sensitive prostate cancer receiving testosterone suppression. The enzalutamide group had a higher incidence of seizures and other toxic effects, especially among those treated with early docetaxel. (Funded by Astellas Scientific and Medical Affairs and others; ENZAMET (ANZUP 1304) ANZCTR number, ACTRN12614000110684; ClinicalTrials.gov number, NCT02446405; and EU Clinical Trials Register number, 2014-003190-42.).
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University of Saskatchewan1, Centre for Environment, Fisheries and Aquaculture Science2, Natural History Museum3, University of Rhode Island4, Sewanee: The University of the South5, Academy of Sciences of the Czech Republic6, National Institutes of Health7, Saint Petersburg State University8, University of Salzburg9, Centre national de la recherche scientifique10, Mississippi State University11, Science for Life Laboratory12, Uppsala University13, Charles University in Prague14, Spanish National Research Council15, University of Duisburg-Essen16, Kaiserslautern University of Technology17, University of Oslo18, Dalhousie University19, Pierre-and-Marie-Curie University20, American Museum of Natural History21, University of Michigan22, University of Warsaw23, University of São Paulo24, University of Paris25, University of British Columbia26, University of Guelph27, Royal Botanic Garden Edinburgh28, Kyungpook National University29, University of Geneva30, University of Alabama31, Pompeu Fabra University32, Edinburgh Napier University33, University of Arkansas34, Hosei University35, Oklahoma State University–Stillwater36, Chinese Academy of Sciences37
TL;DR: It is confirmed that eukaryotes form at least two domains, the loss of monophyly in the Excavata, robust support for the Haptista and Cryptista, and suggested primer sets for DNA sequences from environmental samples that are effective for each clade are provided.
Abstract: This revision of the classification of eukaryotes follows that of Adl et al., 2012 [J. Euk. Microbiol. 59(5)] and retains an emphasis on protists. Changes since have improved the resolution of many ...
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01 Jan 2019••
Stanford University1, University of Chicago2, Willamette University3, Wageningen University and Research Centre4, University of Bristol5, Bat Conservation International6, Stockholm Resilience Centre7, Royal Swedish Academy of Sciences8, University of Washington9, Wellcome Trust10, Uppsala University11, University of Illinois at Urbana–Champaign12, The Nature Conservancy13, Heidelberg University14, University of Glasgow15, Chinese Academy of Sciences16, University of Virginia17, University of British Columbia18, University of Exeter19
TL;DR: It is shown how ecosystem service assessments can be expanded to include mental health, and a heuristic, conceptual model for doing so is provided.
Abstract: A growing body of empirical evidence is revealing the value of nature experience for mental health. With rapid urbanization and declines in human contact with nature globally, crucial decisions must be made about how to preserve and enhance opportunities for nature experience. Here, we first provide points of consensus across the natural, social, and health sciences on the impacts of nature experience on cognitive functioning, emotional well-being, and other dimensions of mental health. We then show how ecosystem service assessments can be expanded to include mental health, and provide a heuristic, conceptual model for doing so.
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TL;DR: The authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types to illustrate how common clinical problems are being addressed.
Abstract: Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.
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TL;DR: A panorama of the latest advancements in the rational design and development of semiconductor polymeric graphitic carbon nitride (g-C3N4) photocatalysts for visible-light-induced hydrogen evolution reaction (HER) is presented in this paper.
Abstract: Semiconductor polymeric graphitic carbon nitride (g-C3N4) photocatalysts have attracted dramatically growing attention in the field of the visible-light-induced hydrogen evolution reaction (HER) because of their facile synthesis, easy functionalization, attractive electronic band structure, high physicochemical stability and photocatalytic activity. This review article presents a panorama of the latest advancements in the rational design and development of g-C3N4 and g-C3N4-based composite photocatalysts for HER application. Concretely, the review starts with the development history, synthetic strategy, electronic structure and physicochemical characteristics of g-C3N4 materials, followed by the rational design and engineering of various nanostructured g-C3N4 (e.g. thinner, highly crystalline, doped, and porous g-C3N4) photocatalysts for HER application. Then a series of highly efficient g-C3N4 (e.g., metal/g-C3N4, semiconductor/g-C3N4, metal organic framework/g-C3N4, carbon/g-C3N4, conducting polymer/g-C3N4, sensitizer/g-C3N4) composite photocatalysts are exemplified. Lastly, this review provides a comprehensive summary and outlook on the major challenges, opportunities, and inspiring perspectives for future research in this hot area on the basis of pioneering works. It is believed that the emerging g-C3N4-based photocatalysts will act as the “holy grail” for highly efficient photocatalytic HER under visible-light irradiation.
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TL;DR: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community providing the theory and key practical aspects offlow cytometry enabling immunologists to avoid the common errors that often undermine immunological data.
Abstract: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.
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Daniel Taliun1, Daniel N. Harris2, Michael D. Kessler2, Jedidiah Carlson3 +191 more•Institutions (61)
TL;DR: The nearly complete catalog of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and non-coding sequence variants to phenotypic variation as well as resources and early insights from the sequence data.
Abstract: Summary paragraph The Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency
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Nasim Mavaddat1, Kyriaki Michailidou2, Kyriaki Michailidou1, Joe Dennis1 +307 more•Institutions (105)
TL;DR: This PRS, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset is developed and empirically validated and is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
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TL;DR: Simulation results reveal that the proposed system is effective and feasible in collecting, calculating, and storing trust values in vehicular networks.
Abstract: Vehicular networks enable vehicles to generate and broadcast messages in order to improve traffic safety and efficiency. However, due to the nontrusted environments, it is difficult for vehicles to evaluate the credibilities of received messages. In this paper, we propose a decentralized trust management system in vehicular networks based on blockchain techniques. In this system, vehicles can validate the received messages from neighboring vehicles using Bayesian Inference Model. Based on the validation result, the vehicle will generate a rating for each message source vehicle. With the ratings uploaded from vehicles, roadside units (RSUs) calculate the trust value offsets of involved vehicles and pack these data into a “block.” Then, each RSU will try to add their “blocks” to the trust blockchain which is maintained by all the RSUs. By employing the joint proof-of-work (PoW) and proof-of-stake consensus mechanism, the more total value of offsets (stake) is in the block, the easier RSU can find the nonce for the hash function (PoW). In this way, all RSUs collaboratively maintain an updated, reliable, and consistent trust blockchain. Simulation results reveal that the proposed system is effective and feasible in collecting, calculating, and storing trust values in vehicular networks.
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United States Department of Veterans Affairs1, Georgetown University2, University of Maryland, College Park3, University of Colorado Boulder4, Stanford University5, University of Manitoba6, University of Alabama at Birmingham7, University of British Columbia8, Brown University9, National Multiple Sclerosis Society10
TL;DR: The estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists and has the potential to be used for other chronic neurologic conditions.
Abstract: Objective To generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets. Methods A validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017. Results The estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1–310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1–451.6) for women and 159.7 (95% CI 158.7–160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017. Conclusion The estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions.
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TL;DR: The regulatory approval of Onpattro, a lipid nanoparticle-based short interfering RNA drug for the treatment of polyneuropathies induced by hereditary transthyretin amyloidosis, paves the way for clinical development of many nucleic acid-based therapies enabled by nanoparticle delivery.
Abstract: The regulatory approval of Onpattro, a lipid nanoparticle-based short interfering RNA drug for the treatment of polyneuropathies induced by hereditary transthyretin amyloidosis, paves the way for clinical development of many nucleic acid-based therapies enabled by nanoparticle delivery.
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University of Southern California1, University of Washington2, University of Michigan3, Harvard University4, University of Groningen5, Max Planck Society6, University of Maryland, Baltimore7, Icahn School of Medicine at Mount Sinai8, Xi'an Jiaotong University9, University of Texas MD Anderson Cancer Center10, University of North Carolina at Charlotte11, Broad Institute12, European Bioinformatics Institute13, Yale University14, University of California, Davis15, University of Utah16, Pacific Biosciences17, University of California, San Diego18, Illumina19, Ludwig Institute for Cancer Research20, Ewha Womans University21, Drexel University22, University of Texas Health Science Center at Houston23, Washington University in St. Louis24, University of Malaya25, University of California, San Francisco26, BC Cancer Agency27, University of British Columbia28
TL;DR: A suite of long-read, short- read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms are applied to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner.
Abstract: The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.
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TL;DR: The steps and extensive considerations involved in performing SP3 in bottom-up proteomics are described, using a simplified protein cleanup scenario for illustration.
Abstract: A critical step in proteomics analysis is the optimal extraction and processing of protein material to ensure the highest sensitivity in downstream detection. Achieving this requires a sample-handling technology that exhibits unbiased protein manipulation, flexibility in reagent use, and virtually lossless processing. Addressing these needs, the single-pot, solid-phase-enhanced sample-preparation (SP3) technology is a paramagnetic bead–based approach for rapid, robust, and efficient processing of protein samples for proteomic analysis. SP3 uses a hydrophilic interaction mechanism for exchange or removal of components that are commonly used to facilitate cell or tissue lysis, protein solubilization, and enzymatic digestion (e.g., detergents, chaotropes, salts, buffers, acids, and solvents) before downstream proteomic analysis. The SP3 protocol consists of nonselective protein binding and rinsing steps that are enabled through the use of ethanol-driven solvation capture on the surface of hydrophilic beads, and elution of purified material in aqueous conditions. In contrast to alternative approaches, SP3 combines compatibility with a substantial collection of solution additives with virtually lossless and unbiased recovery of proteins independent of input quantity, all in a simplified single-tube protocol. The SP3 protocol is simple and efficient, and can be easily completed by a standard user in ~30 min, including reagent preparation. As a result of these properties, SP3 has successfully been used to facilitate examination of a broad range of sample types spanning simple and complex protein mixtures in large and very small amounts, across numerous organisms. This work describes the steps and extensive considerations involved in performing SP3 in bottom-up proteomics, using a simplified protein cleanup scenario for illustration. This protocol describes a single-pot, solid-phase-enhanced sample-preparation (SP3) method for rapid, robust, and efficient processing of protein samples for proteomic analysis.
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TL;DR: Evidence is provided that the proportional effect of SGLT2 inhibitors might attenuate with declining kidney function and there was clear, separate evidence of benefit for all eG FR subgroups, including for participants with a baseline eGFR 30-45 mL/min per 1·73 m2.
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Natural Resources Canada1, United States Geological Survey2, Michigan State University3, Goddard Space Flight Center4, Boston University5, University of Idaho6, Agricultural Research Service7, United States Forest Service8, University of Massachusetts Boston9, European Space Agency10, South Dakota State University11, University of British Columbia12, United States Department of Agriculture13, Humboldt University of Berlin14, Oregon State University15, Desert Research Institute16, University of Nebraska–Lincoln17, Geoscience Australia18, University of Colorado Boulder19, Rochester Institute of Technology20, University of California, Los Angeles21, Virginia Tech22, Texas Tech University23, University of Connecticut24
TL;DR: The programmatic developments and institutional context for the Landsat program and the unique ability of Landsat to meet the needs of national and international programs are described and the key trends in Landsat science are presented.
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TL;DR: The use of hydrogen as a fuel, when generated from water using semiconductor photocatalysts and driven by sunlight, is a sustainable alternative to fossil fuels as discussed by the authors, however, our understanding of the key properties underlying their photoinitiated redox processes has not kept pace, and this impedes further progress to generate cost-competitive technologies.
Abstract: The use of hydrogen as a fuel, when generated from water using semiconductor photocatalysts and driven by sunlight, is a sustainable alternative to fossil fuels. Polymeric photocatalysts are based on Earth-abundant elements and have the advantage over their inorganic counterparts in that their electronic properties are easily tuneable through molecular engineering. Polymeric photocatalysts have developed rapidly over the past decade, resulting in the discovery of many active materials. However, our understanding of the key properties underlying their photoinitiated redox processes has not kept pace, and this impedes further progress to generate cost-competitive technologies. Here, we discuss state-of-the-art polymeric photocatalysts and our microscopic understanding of their activities. We conclude with a discussion of five outstanding challenges in this field: non-standardized reporting of activities, limited photochemical stability, insufficient knowledge of reaction mechanisms, balancing charge carrier lifetimes with catalysis timescales and the use of unsustainable sacrificial reagents. Solar-driven photocatalytic water splitting provides a clean pathway for production of hydrogen fuel. This Review examines both amorphous and crystalline polymeric materials for water splitting, exploring polymer design strategies, theoretical understanding and challenges for the field.