Showing papers by "New York University published in 2017"
St George's Hospital1, New York University2, McMaster University3, Brown University4, Catholic University of the Sacred Heart5, Hebron University6, University of Manitoba7, Emory University Hospital8, Hebrew University of Jerusalem9, Sunnybrook Health Sciences Centre10, University of Pittsburgh11, Saint Thomas - West Hospital12, University College London13, Vanderbilt University Medical Center14, Keio University15, Memorial Hospital of South Bend16, Cooper University Hospital17, University of Mississippi Medical Center18, Rush University Medical Center19, University of Ulsan20, Federal University of São Paulo21, Regions Hospital22, St. Michael's Hospital23, Washington University in St. Louis24, Ottawa Hospital25, University of Sydney26, Mount Sinai Hospital27, University of New South Wales28, Fujita Health University29, Christiana Care Health System30, Stanford University31, King Abdullah University of Science and Technology32, University of Kansas33, Harvard University34, California Pacific Medical Center35, University of Amsterdam36, Houston Methodist Hospital37
TL;DR: Although a significant number of aspects of care have relatively weak support, evidence-based recommendations regarding the acute management of sepsis and septic shock are the foundation of improved outcomes for these critically ill patients with high mortality.
Abstract: To provide an update to “Surviving Sepsis Campaign Guidelines for Management of Sepsis and Septic Shock: 2012”. A consensus committee of 55 international experts representing 25 international organizations was convened. Nominal groups were assembled at key international meetings (for those committee members attending the conference). A formal conflict-of-interest (COI) policy was developed at the onset of the process and enforced throughout. A stand-alone meeting was held for all panel members in December 2015. Teleconferences and electronic-based discussion among subgroups and among the entire committee served as an integral part of the development. The panel consisted of five sections: hemodynamics, infection, adjunctive therapies, metabolic, and ventilation. Population, intervention, comparison, and outcomes (PICO) questions were reviewed and updated as needed, and evidence profiles were generated. Each subgroup generated a list of questions, searched for best available evidence, and then followed the principles of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to assess the quality of evidence from high to very low, and to formulate recommendations as strong or weak, or best practice statement when applicable. The Surviving Sepsis Guideline panel provided 93 statements on early management and resuscitation of patients with sepsis or septic shock. Overall, 32 were strong recommendations, 39 were weak recommendations, and 18 were best-practice statements. No recommendation was provided for four questions. Substantial agreement exists among a large cohort of international experts regarding many strong recommendations for the best care of patients with sepsis. Although a significant number of aspects of care have relatively weak support, evidence-based recommendations regarding the acute management of sepsis and septic shock are the foundation of improved outcomes for these critically ill patients with high mortality.
4,303 citations
TL;DR: The authors found that people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks, and that the average American adult saw on the order of one or perhaps several fake news stories in the months around the 2016 U.S. presidential election, with just over half of those who recalled seeing them believing them.
Abstract: Following the 2016 U.S. presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: (i) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; (ii) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; (iii) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and (iv) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.
3,959 citations
University College London1, Children's Hospital of Philadelphia2, VU University Medical Center3, Sir Charles Gairdner Hospital4, National Multiple Sclerosis Society5, Vita-Salute San Raffaele University6, Medical University of Graz7, Ottawa Hospital Research Institute8, Fukushima Medical University9, New York University10, University of Düsseldorf11, University of Basel12, Corinne Goldsmith Dickinson Center for Multiple Sclerosis13, University of Manitoba14, St. Michael's Hospital15, Hebron University16, Johns Hopkins University17, University of Copenhagen18, University of British Columbia19, University of Bari20, French Institute of Health and Medical Research21, Claude Bernard University Lyon 122, University of California, San Francisco23, Mayo Clinic24, Salisbury University25, Cleveland Clinic26
TL;DR: The 2017 McDonald criteria continue to apply primarily to patients experiencing a typical clinically isolated syndrome, define what is needed to fulfil dissemination in time and space of lesions in the CNS, and stress the need for no better explanation for the presentation.
Abstract: The 2010 McDonald criteria for the diagnosis of multiple sclerosis are widely used in research and clinical practice. Scientific advances in the past 7 years suggest that they might no longer provide the most up-to-date guidance for clinicians and researchers. The International Panel on Diagnosis of Multiple Sclerosis reviewed the 2010 McDonald criteria and recommended revisions. The 2017 McDonald criteria continue to apply primarily to patients experiencing a typical clinically isolated syndrome, define what is needed to fulfil dissemination in time and space of lesions in the CNS, and stress the need for no better explanation for the presentation. The following changes were made: in patients with a typical clinically isolated syndrome and clinical or MRI demonstration of dissemination in space, the presence of CSF-specific oligoclonal bands allows a diagnosis of multiple sclerosis; symptomatic lesions can be used to demonstrate dissemination in space or time in patients with supratentorial, infratentorial, or spinal cord syndrome; and cortical lesions can be used to demonstrate dissemination in space. Research to further refine the criteria should focus on optic nerve involvement, validation in diverse populations, and incorporation of advanced imaging, neurophysiological, and body fluid markers.
3,945 citations
Columbia University1, University of Pittsburgh2, Florey Institute of Neuroscience and Mental Health3, Stanford University4, German Cancer Research Center5, Ludwig Maximilian University of Munich6, Yale University7, Memorial Sloan Kettering Cancer Center8, Dresden University of Technology9, Wistar Institute10, National University of Mar del Plata11, University of Texas Health Science Center at San Antonio12, Guangzhou Medical University13, University of Connecticut Health Center14, Nagoya University15, New York University16, University of Arizona17
TL;DR: The mechanisms underlying ferroptosis are reviewed, connections to other areas of biology and medicine are highlighted, and tools and guidelines for studying this emerging form of regulated cell death are recommended.
3,356 citations
University of Melbourne1, University of British Columbia2, New York University3, Federal University of São Paulo4, French Institute of Health and Medical Research5, University of California, Los Angeles6, Albert Einstein College of Medicine7, Children's Hospital Los Angeles8, University of Pavia9, Karolinska Institutet10, University of Calgary11, Peking University12, University of Glasgow13, Royal Hospital for Sick Children14
TL;DR: The International League Against Epilepsy (ILAE) Classification of the Epilepsies has been updated to reflect our gain in understanding of the epilepsies and their underlying mechanisms following the major scientific advances that have taken place since the last ratified classification in 1989 as mentioned in this paper.
Abstract: The International League Against Epilepsy (ILAE) Classification of the Epilepsies has been updated to reflect our gain in understanding of the epilepsies and their underlying mechanisms following the major scientific advances that have taken place since the last ratified classification in 1989. As a critical tool for the practicing clinician, epilepsy classification must be relevant and dynamic to changes in thinking, yet robust and translatable to all areas of the globe. Its primary purpose is for diagnosis of patients, but it is also critical for epilepsy research, development of antiepileptic therapies, and communication around the world. The new classification originates from a draft document submitted for public comments in 2013, which was revised to incorporate extensive feedback from the international epilepsy community over several rounds of consultation. It presents three levels, starting with seizure type, where it assumes that the patient is having epileptic seizures as defined by the new 2017 ILAE Seizure Classification. After diagnosis of the seizure type, the next step is diagnosis of epilepsy type, including focal epilepsy, generalized epilepsy, combined generalized, and focal epilepsy, and also an unknown epilepsy group. The third level is that of epilepsy syndrome, where a specific syndromic diagnosis can be made. The new classification incorporates etiology along each stage, emphasizing the need to consider etiology at each step of diagnosis, as it often carries significant treatment implications. Etiology is broken into six subgroups, selected because of their potential therapeutic consequences. New terminology is introduced such as developmental and epileptic encephalopathy. The term benign is replaced by the terms self-limited and pharmacoresponsive, to be used where appropriate. It is hoped that this new framework will assist in improving epilepsy care and research in the 21st century.
2,842 citations
Icahn School of Medicine at Mount Sinai1, Pure Earth2, World Bank3, University of Arizona4, McGill University5, Indian Ministry of Environment and Forests6, Qatar Airways7, Ludwig Maximilian University of Munich8, University of Health Sciences Antigua9, Johns Hopkins University10, Boston College11, Chulabhorn Research Institute12, University of Maryland, College Park13, University of Ghana14, Centro Nacional de Investigaciones Cardiovasculares15, University of Chicago16, University of London17, University of Oxford18, Indian Institute of Technology Delhi19, Simon Fraser University20, Consortium of Universities for Global Health21, University of Ottawa22, Columbia University23, Stockholm Resilience Centre24, Massachusetts Institute of Technology25, University of Queensland26, University of California, Berkeley27, New York University28, National Institutes of Health29, Public Health Research Institute30, United Nations Industrial Development Organization31, Renmin University of China32
TL;DR: This book is dedicated to the memory of those who have served in the armed forces and their families during the conflicts of the twentieth century.
2,628 citations
TL;DR: In many applications, such geometric data are large and complex (in the case of social networks, on the scale of billions) and are natural targets for machine-learning techniques as mentioned in this paper.
Abstract: Many scientific fields study data with an underlying structure that is non-Euclidean. Some examples include social networks in computational social sciences, sensor networks in communications, functional networks in brain imaging, regulatory networks in genetics, and meshed surfaces in computer graphics. In many applications, such geometric data are large and complex (in the case of social networks, on the scale of billions) and are natural targets for machine-learning techniques. In particular, we would like to use deep neural networks, which have recently proven to be powerful tools for a broad range of problems from computer vision, natural-language processing, and audio analysis. However, these tools have been most successful on data with an underlying Euclidean or grid-like structure and in cases where the invariances of these structures are built into networks used to model them.
2,565 citations
St George’s University Hospitals NHS Foundation Trust1, New York University2, McMaster University3, Brown University4, Catholic University of the Sacred Heart5, Autonomous University of Barcelona6, University of Manitoba7, Emory University8, Hebrew University of Jerusalem9, University of Toronto10, University of Pittsburgh11, St Thomas' Hospital12, University College London13, Vanderbilt University14, Keio University15, Memorial Hospital of South Bend16, Rowan University17, University of Mississippi18, Rush University Medical Center19, University of Ulsan20, Universidade Federal do Rio Grande do Sul21, Federal University of São Paulo22, Regions Hospital23, Washington University in St. Louis24, University of Ottawa25, University of Sydney26, University of New South Wales27, Fujita Health University28, University of Copenhagen29, Sapienza University of Rome30, Christiana Care Health System31, Stanford University32, King Abdullah University of Science and Technology33, University of Kansas34, Harvard University35, California Pacific Medical Center36, University of Amsterdam37, Université libre de Bruxelles38, Houston Methodist Hospital39
TL;DR: A consensus committee of 55 international experts representing 25 international organizations was assembled at key international meetings (forSurviving Sepsis Campaign Guidelines for Management of Sepsis and Septic Shock: 2012 as discussed by the authors ).
Abstract: Objective:To provide an update to “Surviving Sepsis Campaign Guidelines for Management of Sepsis and Septic Shock: 2012.”Design:A consensus committee of 55 international experts representing 25 international organizations was convened. Nominal groups were assembled at key international meetings (for
2,414 citations
Carnegie Mellon University1, Leibniz Institute for Astrophysics Potsdam2, Lawrence Berkeley National Laboratory3, New Mexico State University4, Sternberg Astronomical Institute5, Ohio State University6, University of Utah7, Yale University8, Autonomous University of Madrid9, University of Barcelona10, Harvard University11, Aix-Marseille University12, University of Paris13, Pierre-and-Marie-Curie University14, Max Planck Society15, University of California, Berkeley16, University of California, Irvine17, University of Portsmouth18, University of Cambridge19, Spanish National Research Council20, University of La Laguna21, Institut d'Astrophysique de Paris22, Princeton University23, University of Edinburgh24, Sejong University25, Kansas State University26, Pennsylvania State University27, National University of La Plata28, National Scientific and Technical Research Council29, Ohio University30, Brookhaven National Laboratory31, New York University32, University of St Andrews33, National Autonomous University of Mexico34, University of Wisconsin-Madison35, Open University36, Chinese Academy of Sciences37, University of Pittsburgh38, Case Western Reserve University39
TL;DR: In this article, the authors present cosmological results from the final galaxy clustering data set of the Baryon Oscillation Spectroscopic Survey, part of the Sloan Digital Sky Survey III.
Abstract: We present cosmological results from the final galaxy clustering data set of the Baryon Oscillation Spectroscopic Survey, part of the Sloan Digital Sky Survey III. Our combined galaxy sample comprises 1.2 million massive galaxies over an effective area of 9329 deg^2 and volume of 18.7 Gpc^3, divided into three partially overlapping redshift slices centred at effective redshifts 0.38, 0.51 and 0.61. We measure the angular diameter distance and Hubble parameter H from the baryon acoustic oscillation (BAO) method, in combination with a cosmic microwave background prior on the sound horizon scale, after applying reconstruction to reduce non-linear effects on the BAO feature. Using the anisotropic clustering of the pre-reconstruction density field, we measure the product D_MH from the Alcock–Paczynski (AP) effect and the growth of structure, quantified by fσ_8(z), from redshift-space distortions (RSD). We combine individual measurements presented in seven companion papers into a set of consensus values and likelihoods, obtaining constraints that are tighter and more robust than those from any one method; in particular, the AP measurement from sub-BAO scales sharpens constraints from post-reconstruction BAOs by breaking degeneracy between D_M and H. Combined with Planck 2016 cosmic microwave background measurements, our distance scale measurements simultaneously imply curvature Ω_K = 0.0003 ± 0.0026 and a dark energy equation-of-state parameter w = −1.01 ± 0.06, in strong affirmation of the spatially flat cold dark matter (CDM) model with a cosmological constant (ΛCDM). Our RSD measurements of fσ_8, at 6 per cent precision, are similarly consistent with this model. When combined with supernova Ia data, we find H_0 = 67.3 ± 1.0 km s^−1 Mpc^−1 even for our most general dark energy model, in tension with some direct measurements. Adding extra relativistic species as a degree of freedom loosens the constraint only slightly, to H_0 = 67.8 ± 1.2 km s^−1 Mpc^−1. Assuming flat ΛCDM, we find Ω_m = 0.310 ± 0.005 and H_0 = 67.6 ± 0.5 km s^−1 Mpc^−1, and we find a 95 per cent upper limit of 0.16 eV c^−2 on the neutrino mass sum.
2,413 citations
Houston Methodist Hospital1, Erasmus University Rotterdam2, Beth Israel Deaconess Medical Center3, University of Copenhagen4, Pinnacle Financial Partners5, Mount Sinai Hospital6, New York University7, University of Michigan8, University of Pittsburgh9, Spectrum Health10, Mayo Clinic11, McGill University12, University of Bern13, Riverside Methodist Hospital14, Cedars-Sinai Medical Center15, Johns Hopkins University16, Medtronic plc17, Paradigm18
TL;DR: TAVR was a noninferior alternative to surgery in patients with severe aortic stenosis at intermediate surgical risk, with a different pattern of adverse events associated with each procedure.
Abstract: BackgroundAlthough transcatheter aortic-valve replacement (TAVR) is an accepted alternative to surgery in patients with severe aortic stenosis who are at high surgical risk, less is known about comparative outcomes among patients with aortic stenosis who are at intermediate surgical risk. MethodsWe evaluated the clinical outcomes in intermediate-risk patients with severe, symptomatic aortic stenosis in a randomized trial comparing TAVR (performed with the use of a self-expanding prosthesis) with surgical aortic-valve replacement. The primary end point was a composite of death from any cause or disabling stroke at 24 months in patients undergoing attempted aortic-valve replacement. We used Bayesian analytical methods (with a margin of 0.07) to evaluate the noninferiority of TAVR as compared with surgical valve replacement. ResultsA total of 1746 patients underwent randomization at 87 centers. Of these patients, 1660 underwent an attempted TAVR or surgical procedure. The mean (±SD) age of the patients was 7...
2,095 citations
TL;DR: In this article, a review of recent progress in cognitive science suggests that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it.
Abstract: Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.
TL;DR: In this article, a method called cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is proposed, in which oligonucleotide-labeled antibodies are used to integrate cellular protein and transcriptome measurements into an efficient, single-cell readout.
Abstract: High-throughput single-cell RNA sequencing has transformed our understanding of complex cell populations, but it does not provide phenotypic information such as cell-surface protein levels. Here, we describe cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), a method in which oligonucleotide-labeled antibodies are used to integrate cellular protein and transcriptome measurements into an efficient, single-cell readout. CITE-seq is compatible with existing single-cell sequencing approaches and scales readily with throughput increases.
New York University1, Icahn School of Medicine at Mount Sinai2, Memorial Sloan Kettering Cancer Center3, Queen Mary University of London4, Yale University5, Harvard University6, Université Paris-Saclay7, University of Milan8, University of Navarra9, MedStar Georgetown University Hospital10, Netherlands Cancer Institute11, University of Virginia12, Stanford University13, Technische Universität München14, Mayo Clinic15, University of California, Los Angeles16, Wayne State University17, Princess Margaret Cancer Centre18, University of Southern California19, Cleveland Clinic20, Fred Hutchinson Cancer Research Center21, Genentech22
TL;DR: Atezolizumab showed encouraging durable response rates, survival, and tolerability, supporting its therapeutic use in untreated metastatic urothelial cancer.
New York University1, National and Kapodistrian University of Athens2, University of Barcelona3, Texas Oncology4, Complutense University of Madrid5, Aix-Marseille University6, University of Toronto7, University of Oxford8, University of Queensland9, University of Colorado Denver10, Emory University11, Cross Cancer Institute12, Centre Hospitalier Universitaire de Toulouse13, Georgetown University14, University of Sydney15, University of Washington16, University of Paris17, Nagoya University18, Seoul National University19, Bristol-Myers Squibb20, The Royal Marsden NHS Foundation Trust21
TL;DR: Among patients undergoing resection of stage IIIB, IIIC, or IV melanoma, adjuvant therapy with nivolumab resulted in significantly longer recurrence‐free survival and a lower rate of grade 3 or 4 adverse events than adjuant therapy with ipilimumab.
Abstract: BackgroundNivolumab and ipilimumab are immune checkpoint inhibitors that have been approved for the treatment of advanced melanoma. In the United States, ipilimumab has also been approved as adjuvant therapy for melanoma on the basis of recurrence-free and overall survival rates that were higher than those with placebo in a phase 3 trial. We wanted to determine the efficacy of nivolumab versus ipilimumab for adjuvant therapy in patients with resected advanced melanoma. MethodsIn this randomized, double-blind, phase 3 trial, we randomly assigned 906 patients (≥15 years of age) who were undergoing complete resection of stage IIIB, IIIC, or IV melanoma to receive an intravenous infusion of either nivolumab at a dose of 3 mg per kilogram of body weight every 2 weeks (453 patients) or ipilimumab at a dose of 10 mg per kilogram every 3 weeks for four doses and then every 12 weeks (453 patients). The patients were treated for a period of up to 1 year or until disease recurrence, a report of unacceptable toxic ef...
TL;DR: This refined analysis has identified, among others, a previously unknown dendritic cell population that potently activates T cells and reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.
University of Chicago1, New York University2, Sungkyunkwan University3, Stanford University4, University of British Columbia5, Cleveland Clinic6, Kobe University7, Icahn School of Medicine at Mount Sinai8, Radboud University Nijmegen9, Duke University10, Memorial Sloan Kettering Cancer Center11, University of Antwerp12, Harvard University13
TL;DR: These guidelines represent the consensus of the Fleischner Society, and as such, they incorporate the opinions of a multidisciplinary international group of thoracic radiologists, pulmonologists, surgeons, pathologists, and other specialists.
Abstract: The Fleischner Society Guidelines for management of solid nodules were published in 2005, and separate guidelines for subsolid nodules were issued in 2013. Since then, new information has become available; therefore, the guidelines have been revised to reflect current thinking on nodule management. The revised guidelines incorporate several substantive changes that reflect current thinking on the management of small nodules. The minimum threshold size for routine follow-up has been increased, and recommended follow-up intervals are now given as a range rather than as a precise time period to give radiologists, clinicians, and patients greater discretion to accommodate individual risk factors and preferences. The guidelines for solid and subsolid nodules have been combined in one simplified table, and specific recommendations have been included for multiple nodules. These guidelines represent the consensus of the Fleischner Society, and as such, they incorporate the opinions of a multidisciplinary international group of thoracic radiologists, pulmonologists, surgeons, pathologists, and other specialists. Changes from the previous guidelines issued by the Fleischner Society are based on new data and accumulated experience. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on March 13, 2017.
[...]
Howard Hughes Medical Institute1, Broad Institute2, Massachusetts Institute of Technology3, European Bioinformatics Institute4, University of Cambridge5, Wellcome Trust Sanger Institute6, Harvard University7, Weizmann Institute of Science8, University of Zurich9, Laboratory of Molecular Biology10, Utrecht University11, École Polytechnique Fédérale de Lausanne12, University of Pennsylvania13, Heidelberg University14, German Cancer Research Center15, Ludwig Maximilian University of Munich16, John Radcliffe Hospital17, Newcastle University18, Stanford University19, University of Oxford20, University of California, San Francisco21, Allen Institute for Brain Science22, Karolinska Institutet23, Royal Institute of Technology24, Icahn School of Medicine at Mount Sinai25, University of Cape Town26, University Medical Center Groningen27, Radboud University Nijmegen28, Kettering University29, University of Edinburgh30, Babraham Institute31, New York University32, Netherlands Cancer Institute33, Ragon Institute of MGH, MIT and Harvard34, University of Texas Health Science Center at Houston35, Technische Universität München36, Technical University of Denmark37, University of California, Berkeley38, King's College London39, California Institute of Technology40
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.
01 Apr 2017
TL;DR: In this paper, the authors performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells, which led them to identify and validate six Dendritic cells (DCs) and four monocyte subtypes.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.
Baylor College of Medicine1, Stanford University2, Rice University3, Broad Institute4, Harvard University5, New York University6, University of California, San Diego7, New York University Shanghai8, Courant Institute of Mathematical Sciences9, National Institutes of Health10, Massachusetts Institute of Technology11
TL;DR: In this paper, the effects of degrading cohesin were explored, showing that loop domains can be eliminated and re-formed in under an hour, consistent with a model where loop extrusion is rapid.
Michael R. Blanton1, Matthew A. Bershady2, Bela Abolfathi3, Franco D. Albareti4 +412 more•Institutions (91)
TL;DR: SDSS-IV as mentioned in this paper is a project encompassing three major spectroscopic programs: the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA), the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and the Time Domain Spectroscopy Survey (TDSS).
Abstract: We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median $z\sim 0.03$). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between $z\sim 0.6$ and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.
University of Virginia1, Liverpool John Moores University2, Texas Christian University3, Spanish National Research Council4, University of La Laguna5, Johns Hopkins University6, Sternberg Astronomical Institute7, New Mexico State University8, University of Arizona9, Ohio State University10, Pennsylvania State University11, University of Wisconsin-Madison12, Eötvös Loránd University13, University of Toronto14, University of Michigan15, University of Texas at Austin16, Leibniz Institute for Astrophysics Potsdam17, Yale University18, University of Colorado Boulder19, New York University20, Princeton University21, University of Utah22, Goddard Space Flight Center23, Aarhus University24, University of Birmingham25, Harvard University26, Space Telescope Science Institute27, Computer Sciences Corporation28, Paris Diderot University29, INAF30, Max Planck Society31, Space Science Institute32, Pierre-and-Marie-Curie University33, University of Franche-Comté34, Federal University of Rio de Janeiro35, University of Nice Sophia Antipolis36
TL;DR: In this article, the Hungarian National Research, Development and Innovation Office (K-119517) and Hungarian National Science Foundation (KNFI) have proposed a method to detect the presence of asteroids in Earth's magnetic field.
Abstract: National Science Foundation [AST-1109178, AST-1616636]; Gemini Observatory; Spanish Ministry of Economy and Competitiveness [AYA-2011-27754]; NASA [NNX12AE17G]; Hungarian Academy of Sciences; Hungarian NKFI of the Hungarian National Research, Development and Innovation Office [K-119517]; Alfred P. Sloan Foundation; National Science Foundation; U.S. Department of Energy Office of Science
Paris Descartes University1, Cornell University2, University of Massachusetts Medical School3, Spanish National Research Council4, University of Rome Tor Vergata5, Boston Children's Hospital6, University of Pittsburgh7, National University of Cuyo8, National Scientific and Technical Research Council9, Albert Einstein College of Medicine10, University of California, San Francisco11, University of New Mexico12, University of Split13, Goethe University Frankfurt14, University of Helsinki15, University of Salento16, German Cancer Research Center17, Virginia Commonwealth University18, St. Jude Children's Research Hospital19, Discovery Institute20, Harvard University21, University of Tromsø22, Eötvös Loránd University23, Hungarian Academy of Sciences24, New York University25, University of Vienna26, Babraham Institute27, University of South Australia28, University of Texas Southwestern Medical Center29, Howard Hughes Medical Institute30, University of Oviedo31, University of Graz32, National Institutes of Health33, City University of New York34, Queens College35, University of Tokyo36, University of Zurich37, Novartis38, Austrian Academy of Sciences39, University of Groningen40, University of Cambridge41, University of Padua42, University of Oxford43, University of Bern44, University of Oslo45, Foundation for Research & Technology – Hellas46, University of Crete47, Francis Crick Institute48, Osaka University49, Icahn School of Medicine at Mount Sinai50
TL;DR: A panel of leading experts in the field attempts here to define several autophagy‐related terms based on specific biochemical features to formulate recommendations that facilitate the dissemination of knowledge within and outside the field of autophagic research.
Abstract: Over the past two decades, the molecular machinery that underlies autophagic responses has been characterized with ever increasing precision in multiple model organisms. Moreover, it has become clear that autophagy and autophagy-related processes have profound implications for human pathophysiology. However, considerable confusion persists about the use of appropriate terms to indicate specific types of autophagy and some components of the autophagy machinery, which may have detrimental effects on the expansion of the field. Driven by the overt recognition of such a potential obstacle, a panel of leading experts in the field attempts here to define several autophagy-related terms based on specific biochemical features. The ultimate objective of this collaborative exchange is to formulate recommendations that facilitate the dissemination of knowledge within and outside the field of autophagy research.
TL;DR: It is shown that the DNA exonuclease Trex1 is induced by radiation doses above 12–18 Gy in different cancer cells, and attenuates their immunogenicity by degrading DNA that accumulates in the cytosol upon radiation.
Abstract: Trex1 is an exonuclease that degrades cytosolic DNA and has been associated with modulation of interferon responses in autoimmunity and viral infections. Here, the authors show that Trex1 attenuates the immunogenicity of cancer cells treated with high radiation doses by d…
TL;DR: Among patients with the Dravet syndrome, cannabidiol resulted in a greater reduction in convulsive‐seizure frequency than placebo and was associated with higher rates of adverse events.
Abstract: BackgroundThe Dravet syndrome is a complex childhood epilepsy disorder that is associated with drug-resistant seizures and a high mortality rate We studied cannabidiol for the treatment of drug-resistant seizures in the Dravet syndrome MethodsIn this double-blind, placebo-controlled trial, we randomly assigned 120 children and young adults with the Dravet syndrome and drug-resistant seizures to receive either cannabidiol oral solution at a dose of 20 mg per kilogram of body weight per day or placebo, in addition to standard antiepileptic treatment The primary end point was the change in convulsive-seizure frequency over a 14-week treatment period, as compared with a 4-week baseline period ResultsThe median frequency of convulsive seizures per month decreased from 124 to 59 with cannabidiol, as compared with a decrease from 149 to 141 with placebo (adjusted median difference between the cannabidiol group and the placebo group in change in seizure frequency, −228 percentage points; 95% confidence i
TL;DR: It is shown that the improved performance stems from the combination of a deep, high-capacity model and an augmented training set: this combination outperforms both the proposed CNN without augmentation and a “shallow” dictionary learning model with augmentation.
Abstract: The ability of deep convolutional neural networks (CNNs) to learn discriminative spectro-temporal patterns makes them well suited to environmental sound classification. However, the relative scarcity of labeled data has impeded the exploitation of this family of high-capacity models. This study has two primary contributions: first, we propose a deep CNN architecture for environmental sound classification. Second, we propose the use of audio data augmentation for overcoming the problem of data scarcity and explore the influence of different augmentations on the performance of the proposed CNN architecture. Combined with data augmentation, the proposed model produces state-of-the-art results for environmental sound classification. We show that the improved performance stems from the combination of a deep, high-capacity model and an augmented training set: this combination outperforms both the proposed CNN without augmentation and a “shallow” dictionary learning model with augmentation. Finally, we examine the influence of each augmentation on the model's classification accuracy for each class, and observe that the accuracy for each class is influenced differently by each augmentation, suggesting that the performance of the model could be improved further by applying class-conditional data augmentation.
Proceedings Article•
04 Dec 2017TL;DR: This paper develops a framework for modeling fairness using tools from causal inference and demonstrates the framework on a real-world problem of fair prediction of success in law school.
Abstract: Machine learning can impact people with legal or ethical consequences when it is used to automate decisions in areas such as insurance, lending, hiring, and predictive policing. In many of these scenarios, previous decisions have been made that are unfairly biased against certain subpopulations, for example those of a particular race, gender, or sexual orientation. Since this past data may be biased, machine learning predictors must account for this to avoid perpetuating or creating discriminatory practices. In this paper, we develop a framework for modeling fairness using tools from causal inference. Our definition of counterfactual fairness captures the intuition that a decision is fair towards an individual if it the same in (a) the actual world and (b) a counterfactual world where the individual belonged to a different demographic group. We demonstrate our framework on a real-world problem of fair prediction of success in law school.
TL;DR: First-line pembrolizumab has antitumour activity and acceptable tolerability in cisplatin-ineligible patients with urothelial cancer, most of whom were elderly, had poor prognostic factors, or had serious comorbidities.
Abstract: Summary Background More than half of all patients with advanced urothelial cancer cannot receive standard, first-line cisplatin-based chemotherapy because of renal dysfunction, poor performance status, or other comorbidities. We assessed the activity and safety of first-line pembrolizumab in cisplatin-ineligible patients with locally advanced and unresectable or metastatic urothelial cancer. Methods In this multicentre, single-arm, phase 2 study (KEYNOTE-052), cisplatin-ineligible patients with advanced urothelial cancer who had not been previously treated with systemic chemotherapy were recruited from 91 academic medical centres in 20 countries. Enrolled patients received intravenous pembrolizumab 200 mg every 3 weeks. The primary endpoint was objective response (the proportion of patients who achieved complete or partial response) in all patients and by PD-L1 expression status according to the Response Evaluation Criteria in Solid Tumors, version 1.1, as assessed by independent central review. PD-L1 expression was assessed in tumour and inflammatory cells from tumour biopsies provided at study entry. Activity and safety were analysed in all patients who received at least one dose of pembrolizumab (all-patients-treated population). This study is registered with ClinicalTrials.gov, number NCT02335424, and follow-up is ongoing. Findings Between Feb 24, 2015, and Aug 8, 2016, 374 patients were enrolled and 370 patients received at least one dose of pembrolizumab. 89 (24%, 95% CI 20–29) of 370 patients had a centrally assessed objective response, and as of Sept 1, 2016 (data cutoff), 74 (83%) of 89 responses were ongoing. Median follow-up was 5 months (IQR 3·0–8·6). A PD-L1-expression cutoff of 10% was associated with a higher frequency of response to pembrolizumab; 42 (38%, 95% CI 29–48) of 110 patients with a combined positive score of 10% or more had a centrally assessed objective response. The most common grade 3 or 4 treatment-related adverse events were fatigue (eight [2%] of 370 patients), alkaline phosphatase increase (five [1%]), colitis, and muscle weakness (both four [1%]). 36 (10%) of 370 patients had a serious treatment-related adverse event. 17 (5%) of 370 patients died from non-treatment-related adverse events associated with death, and one patient died from treatment-related adverse events (myositis in addition to grade 3 thyroiditis, grade 3 hepatitis, grade 3 pneumonia, and grade 4 myocarditis). Interpretation First-line pembrolizumab has antitumour activity and acceptable tolerability in cisplatin-ineligible patients with urothelial cancer, most of whom were elderly, had poor prognostic factors, or had serious comorbidities. In view of this result, pembrolizumab has become a new treatment option for patients who are cisplatin-ineligible or not suitable candidates for chemotherapy. Pembrolizumab in the first-line setting is being further assessed in the phase 3 KEYNOTE-361 trial (ClinicalTrials.gov, NCT02335424). Funding Merck & Co.
University of California, San Diego1, Johns Hopkins University2, University of Washington3, University of California, San Francisco4, University of Pennsylvania5, Duke University6, University of Toronto7, University of Chicago8, New York University9, University of Maryland, Baltimore10, University of Paris11, University of Jena12, Victoria University of Wellington13, Primary Children's Hospital14, Brigham Young University15, McGill University16, Kaiser Permanente17, University of Pittsburgh18, Brown University19
TL;DR: An international multidisciplinary team of 29 members with expertise in guideline development, evidence analysis, and family-centered care is assembled to revise the 2007 Clinical Practice Guidelines for support of the family in the patient-centered ICU.
Abstract: Objective:To provide clinicians with evidence-based strategies to optimize the support of the family of critically ill patients in the ICU.Methods:We used the Council of Medical Specialty Societies principles for the development of clinical guidelines as the framework for guideline development. We a
TL;DR: A more pluralistic notion of neuroscience is advocated when it comes to the brain-behavior relationship: behavioral work provides understanding, whereas neural interventions test causality.
TL;DR: This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, called the Rosetta Energy Function 2015 (REF15), and explains how to use Rosetta energies to identify and analyze the features of biomolecular models.
Abstract: Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta’s success is the energy function: a model parametrized from small-molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, called the Rosetta Energy Function 2015 (REF15). Applying these concepts, we explain how to use Rosetta energies to identify and analyze the features of biomolecular models. Finally, we discuss the latest advances in the energy function that extend its capabilities from soluble proteins to also include membrane proteins, peptides containing noncanonical amino acids, small molecules, carbohydrates, nucleic acids, and other macromolecules.