Showing papers by "University of Cambridge published in 2020"
University of California, Berkeley1, Stellenbosch University2, University of Jyväskylä3, University of Cambridge4, Google5, University of Toronto6, University of Birmingham7, Temple University8, University of British Columbia9, Amazon.com10, University of Georgia11, University of Oxford12, Los Alamos National Laboratory13, University of California, Irvine14
TL;DR: In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
Abstract: Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
7,624 citations
TL;DR: Detailed virological analysis of nine cases of coronavirus disease 2019 (COVID-19) provides proof of active replication of the SARS-CoV-2 virus in tissues of the upper respiratory tract.
Abstract: Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in late 20191,2. Initial outbreaks in China involved 13.8% of cases with severe courses, and 6.1% of cases with critical courses3. This severe presentation may result from the virus using a virus receptor that is expressed predominantly in the lung2,4; the same receptor tropism is thought to have determined the pathogenicity—but also aided in the control—of severe acute respiratory syndrome (SARS) in 20035. However, there are reports of cases of COVID-19 in which the patient shows mild upper respiratory tract symptoms, which suggests the potential for pre- or oligosymptomatic transmission6–8. There is an urgent need for information on virus replication, immunity and infectivity in specific sites of the body. Here we report a detailed virological analysis of nine cases of COVID-19 that provides proof of active virus replication in tissues of the upper respiratory tract. Pharyngeal virus shedding was very high during the first week of symptoms, with a peak at 7.11 × 108 RNA copies per throat swab on day 4. Infectious virus was readily isolated from samples derived from the throat or lung, but not from stool samples—in spite of high concentrations of virus RNA. Blood and urine samples never yielded virus. Active replication in the throat was confirmed by the presence of viral replicative RNA intermediates in the throat samples. We consistently detected sequence-distinct virus populations in throat and lung samples from one patient, proving independent replication. The shedding of viral RNA from sputum outlasted the end of symptoms. Seroconversion occurred after 7 days in 50% of patients (and by day 14 in all patients), but was not followed by a rapid decline in viral load. COVID-19 can present as a mild illness of the upper respiratory tract. The confirmation of active virus replication in the upper respiratory tract has implications for the containment of COVID-19. Detailed virological analysis of nine cases of coronavirus disease 2019 (COVID-19) provides proof of active replication of the SARS-CoV-2 virus in tissues of the upper respiratory tract.
5,840 citations
TL;DR: In this article, the authors present cosmological parameter results from the full-mission Planck measurements of the cosmic microwave background (CMB) anisotropies, combining information from the temperature and polarization maps and the lensing reconstruction.
Abstract: We present cosmological parameter results from the final full-mission Planck measurements of the cosmic microwave background (CMB) anisotropies, combining information from the temperature and polarization maps and the lensing reconstruction Compared to the 2015 results, improved measurements of large-scale polarization allow the reionization optical depth to be measured with higher precision, leading to significant gains in the precision of other correlated parameters Improved modelling of the small-scale polarization leads to more robust constraints on manyparameters,withresidualmodellinguncertaintiesestimatedtoaffectthemonlyatthe05σlevelWefindgoodconsistencywiththestandard spatially-flat6-parameter ΛCDMcosmologyhavingapower-lawspectrumofadiabaticscalarperturbations(denoted“base ΛCDM”inthispaper), from polarization, temperature, and lensing, separately and in combination A combined analysis gives dark matter density Ωch2 = 0120±0001, baryon density Ωbh2 = 00224±00001, scalar spectral index ns = 0965±0004, and optical depth τ = 0054±0007 (in this abstract we quote 68% confidence regions on measured parameters and 95% on upper limits) The angular acoustic scale is measured to 003% precision, with 100θ∗ = 10411±00003Theseresultsareonlyweaklydependentonthecosmologicalmodelandremainstable,withsomewhatincreasederrors, in many commonly considered extensions Assuming the base-ΛCDM cosmology, the inferred (model-dependent) late-Universe parameters are: HubbleconstantH0 = (674±05)kms−1Mpc−1;matterdensityparameterΩm = 0315±0007;andmatterfluctuationamplitudeσ8 = 0811±0006 We find no compelling evidence for extensions to the base-ΛCDM model Combining with baryon acoustic oscillation (BAO) measurements (and consideringsingle-parameterextensions)weconstraintheeffectiveextrarelativisticdegreesoffreedomtobe Neff = 299±017,inagreementwith the Standard Model prediction Neff = 3046, and find that the neutrino mass is tightly constrained toPmν < 012 eV The CMB spectra continue to prefer higher lensing amplitudesthan predicted in base ΛCDM at over 2σ, which pulls some parameters that affect thelensing amplitude away from the ΛCDM model; however, this is not supported by the lensing reconstruction or (in models that also change the background geometry) BAOdataThejointconstraintwithBAOmeasurementsonspatialcurvatureisconsistentwithaflatuniverse, ΩK = 0001±0002Alsocombining with Type Ia supernovae (SNe), the dark-energy equation of state parameter is measured to be w0 = −103±003, consistent with a cosmological constant We find no evidence for deviations from a purely power-law primordial spectrum, and combining with data from BAO, BICEP2, and Keck Array data, we place a limit on the tensor-to-scalar ratio r0002 < 006 Standard big-bang nucleosynthesis predictions for the helium and deuterium abundances for the base-ΛCDM cosmology are in excellent agreement with observations The Planck base-ΛCDM results are in good agreement with BAO, SNe, and some galaxy lensing observations, but in slight tension with the Dark Energy Survey’s combined-probe results including galaxy clustering (which prefers lower fluctuation amplitudes or matter density parameters), and in significant, 36σ, tension with local measurements of the Hubble constant (which prefer a higher value) Simple model extensions that can partially resolve these tensions are not favoured by the Planck data
4,688 citations
University of California, Berkeley1, Stellenbosch University2, University of Jyväskylä3, University of Cambridge4, Google5, University of Toronto6, University of Birmingham7, Temple University8, University of British Columbia9, Amazon.com10, University of Georgia11, University of Oxford12, Los Alamos National Laboratory13, University of California, Irvine14
TL;DR: How a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data is reviewed.
Abstract: Array programming provides a powerful, compact, expressive syntax for accessing, manipulating, and operating on data in vectors, matrices, and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It plays an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, material science, engineering, finance, and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves and the first imaging of a black hole. Here we show how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring, and analyzing scientific data. NumPy is the foundation upon which the entire scientific Python universe is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Because of its central position in the ecosystem, NumPy increasingly plays the role of an interoperability layer between these new array computation libraries.
4,342 citations
Karolinska Institutet1, Uppsala University2, University of Glasgow3, University College London4, University of Oxford5, King's College London6, University of Exeter7, Black Dog Institute8, University of California, Irvine9, University of Cambridge10, Swansea University11, Guy's and St Thomas' NHS Foundation Trust12, UCL Institute of Child Health13, St George's, University of London14, Emory University15, University of Bristol16, Academy of Medical Sciences, United Kingdom17
TL;DR: There is an urgent need for research to address how mental health consequences for vulnerable groups can be mitigated under pandemic conditions, and on the impact of repeated media consumption and health messaging around COVID-19.
3,909 citations
Camden and Islington NHS Foundation Trust1, University College London2, Royal Melbourne Hospital3, University of Exeter4, University of Plymouth5, University of Cambridge6, University of Manchester7, Tel Aviv University8, Goa Medical College9, Johns Hopkins University10, University of California, Davis11, Kaiser Permanente12, University College Hospital, Ibadan13, University of Montpellier14, Dalhousie University15, University of Southern California16, Oslo University Hospital17, University of Washington18
TL;DR: Author(s): Livingston, Gill; Huntley, Jonathan; Sommerlad, Andrew ; Sommer Glad, Andrew; Ames, David; Ballard, Clive; Banerjee, Sube; Brayne, Carol; Burns, Alistair; Cohen-Mansfield, Jiska; Cooper, Claudia; Costafreda, Sergi G; Dias, Amit; Fox, Nick; Gitlin, Laura N; Howard, Robert; Kales, Helen C;
3,559 citations
Turku University Hospital1, National University of Ireland, Galway2, University of Catania3, University of Naples Federico II4, University of Paris5, Bispebjerg Hospital6, University of Sheffield7, University of Cambridge8, Stavanger University Hospital9, Oslo University Hospital10, Hospital Clínico San Carlos11, Mayo Clinic12, University of Western Brittany13, Rabin Medical Center14, Slovak Medical University15, Saarland University16, University of Barcelona17, University of Brescia18, University of Bern19, University of Erlangen-Nuremberg20, Leiden University Medical Center21
TL;DR: In this article, the authors present guidelines for the management of patients with coronary artery disease (CAD), which is a pathological process characterized by atherosclerotic plaque accumulation in the epicardial arteries.
Abstract: Coronary artery disease (CAD) is a pathological process characterized by atherosclerotic plaque accumulation in the epicardial arteries, whether obstructive or non-obstructive. This process can be modified by lifestyle adjustments, pharmacological therapies, and invasive interventions designed to achieve disease stabilization or regression. The disease can have long, stable periods but can also become unstable at any time, typically due to an acute atherothrombotic event caused by plaque rupture or erosion. However, the disease is chronic, most often progressive, and hence serious, even in clinically apparently silent periods. The dynamic nature of the CAD process results in various clinical presentations, which can be conveniently categorized as either acute coronary syndromes (ACS) or chronic coronary syndromes (CCS). The Guidelines presented here refer to the management of patients with CCS. The natural history of CCS is illustrated in Figure 1.
3,448 citations
TL;DR: This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19, the novel severe acute respiratory syndrome coronavirus 2 pandemic that has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease.
Abstract: Importance The coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19. Observations SARS-CoV-2 is spread primarily via respiratory droplets during close face-to-face contact. Infection can be spread by asymptomatic, presymptomatic, and symptomatic carriers. The average time from exposure to symptom onset is 5 days, and 97.5% of people who develop symptoms do so within 11.5 days. The most common symptoms are fever, dry cough, and shortness of breath. Radiographic and laboratory abnormalities, such as lymphopenia and elevated lactate dehydrogenase, are common, but nonspecific. Diagnosis is made by detection of SARS-CoV-2 via reverse transcription polymerase chain reaction testing, although false-negative test results may occur in up to 20% to 67% of patients; however, this is dependent on the quality and timing of testing. Manifestations of COVID-19 include asymptomatic carriers and fulminant disease characterized by sepsis and acute respiratory failure. Approximately 5% of patients with COVID-19, and 20% of those hospitalized, experience severe symptoms necessitating intensive care. More than 75% of patients hospitalized with COVID-19 require supplemental oxygen. Treatment for individuals with COVID-19 includes best practices for supportive management of acute hypoxic respiratory failure. Emerging data indicate that dexamethasone therapy reduces 28-day mortality in patients requiring supplemental oxygen compared with usual care (21.6% vs 24.6%; age-adjusted rate ratio, 0.83 [95% CI, 0.74-0.92]) and that remdesivir improves time to recovery (hospital discharge or no supplemental oxygen requirement) from 15 to 11 days. In a randomized trial of 103 patients with COVID-19, convalescent plasma did not shorten time to recovery. Ongoing trials are testing antiviral therapies, immune modulators, and anticoagulants. The case-fatality rate for COVID-19 varies markedly by age, ranging from 0.3 deaths per 1000 cases among patients aged 5 to 17 years to 304.9 deaths per 1000 cases among patients aged 85 years or older in the US. Among patients hospitalized in the intensive care unit, the case fatality is up to 40%. At least 120 SARS-CoV-2 vaccines are under development. Until an effective vaccine is available, the primary methods to reduce spread are face masks, social distancing, and contact tracing. Monoclonal antibodies and hyperimmune globulin may provide additional preventive strategies. Conclusions and Relevance As of July 1, 2020, more than 10 million people worldwide had been infected with SARS-CoV-2. Many aspects of transmission, infection, and treatment remain unclear. Advances in prevention and effective management of COVID-19 will require basic and clinical investigation and public health and clinical interventions.
3,371 citations
New York University1, University of Chicago2, Mackenzie Presbyterian University3, Middlesex University4, Nicolaus Copernicus University in Toruń5, University of Kent6, Harvard University7, Yale University8, Stanford University9, Northwestern University10, University of Sussex11, Utrecht University12, University of California, San Diego13, University of Maryland, College Park14, McGovern Institute for Brain Research15, University of Queensland16, University of Michigan17, California Institute of Technology18, Lehigh University19, University of Regina20, University of Oregon21, Ohio State University22, Massachusetts Institute of Technology23, University of St Andrews24, University of Cambridge25, University of British Columbia26, University of Illinois at Chicago27, University of California, Berkeley28, Carleton University29, VU University Amsterdam30, Cornell University31
TL;DR: Evidence from a selection of research topics relevant to pandemics is discussed, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping.
Abstract: The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.
3,223 citations
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23 Feb 2020
TL;DR: The ATLAS detector as installed in its experimental cavern at point 1 at CERN is described in this paper, where a brief overview of the expected performance of the detector when the Large Hadron Collider begins operation is also presented.
Abstract: The ATLAS detector as installed in its experimental cavern at point 1 at CERN is described in this paper. A brief overview of the expected performance of the detector when the Large Hadron Collider begins operation is also presented.
3,111 citations
Capital Medical University1, China-Japan Friendship Hospital2, Peking Union Medical College3, Huazhong University of Science and Technology4, Wuhan University5, Tsinghua University6, Beijing University of Chinese Medicine7, University of Cambridge8, Lancaster University9, University of Virginia10, University of Oxford11
TL;DR: In this study of adult patients admitted to hospital for severe COVID-19, remdesivir was not associated with statistically significant clinical benefits, however, the numerical reduction in time to clinical improvement in those treated earlier requires confirmation in larger studies.
TL;DR: A rational and dynamic virus nomenclature that uses a phylogenetic framework to identify those lineages that contribute most to active spread and is designed to provide a real-time bird’s-eye view of the diversity of the hundreds of thousands of genome sequences collected worldwide.
Abstract: The ongoing pandemic spread of a new human coronavirus, SARS-CoV-2, which is associated with severe pneumonia/disease (COVID-19), has resulted in the generation of tens of thousands of virus genome sequences. The rate of genome generation is unprecedented, yet there is currently no coherent nor accepted scheme for naming the expanding phylogenetic diversity of SARS-CoV-2. Here, we present a rational and dynamic virus nomenclature that uses a phylogenetic framework to identify those lineages that contribute most to active spread. Our system is made tractable by constraining the number and depth of hierarchical lineage labels and by flagging and delabelling virus lineages that become unobserved and hence are probably inactive. By focusing on active virus lineages and those spreading to new locations, this nomenclature will assist in tracking and understanding the patterns and determinants of the global spread of SARS-CoV-2.
TL;DR: An overview of Mercury 4.0, an analysis, design and prediction platform that acts as a hub for the entire Cambridge Structural Database software suite, is presented.
Abstract: The program Mercury, developed at the Cambridge Crystallographic Data Centre, was originally designed primarily as a crystal structure visualization tool. Over the years the fields and scientific communities of chemical crystallography and crystal engineering have developed to require more advanced structural analysis software. Mercury has evolved alongside these scientific communities and is now a powerful analysis, design and prediction platform which goes a lot further than simple structure visualization.
TL;DR: In this paper, the expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors was investigated, and co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission.
Abstract: We investigated SARS-CoV-2 potential tropism by surveying expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors. We co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission. These genes are co-expressed in nasal epithelial cells with genes involved in innate immunity, highlighting the cells' potential role in initial viral infection, spread and clearance. The study offers a useful resource for further lines of inquiry with valuable clinical samples from COVID-19 patients and we provide our data in a comprehensive, open and user-friendly fashion at www.covid19cellatlas.org.
Donostia International Physics Center1, Rovira i Virgili University2, MacDiarmid Institute for Advanced Materials and Nanotechnology3, Victoria University of Wellington4, University of Cambridge5, University of California, Santa Barbara6, Queen's University Belfast7, Technical University of Denmark8, University of Victoria9, Chung-Ang University10, Leibniz Institute of Photonic Technology11, University of Jena12, Rutgers University13, University of Strathclyde14, University of Liverpool15, University of Iowa16, University of Minnesota17, Heidelberg University18, National Institute of Advanced Industrial Science and Technology19, Chalmers University of Technology20, Humboldt University of Berlin21, University of Michigan22, Jiangnan University23, Stanford University24, Xiamen University25, Ludwig Maximilian University of Munich26, Hokkaido University27, Seoul National University28, University of Illinois at Urbana–Champaign29, Kwansei Gakuin University30, University of Vigo31, Free University of Berlin32, Northwestern University33, University of Duisburg-Essen34, National Research Council35, Indian Institute of Science Education and Research, Thiruvananthapuram36, Duke University37, Northeastern University (China)38, Temple University39, Wuhan University40, Japan Advanced Institute of Science and Technology41, Jilin University42, Ikerbasque43
TL;DR: Prominent authors from all over the world joined efforts to summarize the current state-of-the-art in understanding and using SERS, as well as to propose what can be expected in the near future, in terms of research, applications, and technological development.
Abstract: The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.
TL;DR: In this paper, a power-law fit to the angular power spectra of dust polarization at 353 GHz for six nested sky regions covering from 24 to 71 % of the sky is presented.
Abstract: The study of polarized dust emission has become entwined with the analysis of the cosmic microwave background (CMB) polarization. We use new Planck maps to characterize Galactic dust emission as a foreground to the CMB polarization. We present Planck EE, BB, and TE power spectra of dust polarization at 353 GHz for six nested sky regions covering from 24 to 71 % of the sky. We present power-law fits to the angular power spectra, yielding evidence for statistically significant variations of the exponents over sky regions and a difference between the values for the EE and BB spectra. The TE correlation and E/B power asymmetry extend to low multipoles that were not included in earlier Planck polarization papers. We also report evidence for a positive TB dust signal. Combining data from Planck and WMAP, we determine the amplitudes and spectral energy distributions (SEDs) of polarized foregrounds, including the correlation between dust and synchrotron polarized emission, for the six sky regions as a function of multipole. This quantifies the challenge of the component separation procedure required for detecting the reionization and recombination peaks of primordial CMB B modes. The SED of polarized dust emission is fit well by a single-temperature modified blackbody emission law from 353 GHz to below 70 GHz. For a dust temperature of 19.6 K, the mean spectral index for dust polarization is $\beta_{\rm d}^{P} = 1.53\pm0.02 $. By fitting multi-frequency cross-spectra, we examine the correlation of the dust polarization maps across frequency. We find no evidence for decorrelation. If the Planck limit for the largest sky region applies to the smaller sky regions observed by sub-orbital experiments, then decorrelation might not be a problem for CMB experiments aiming at a primordial B-mode detection limit on the tensor-to-scalar ratio $r\simeq0.01$ at the recombination peak.
TL;DR: Mental health in the UK had deteriorated compared with pre-COVID-19 trends by late April, 2020, and policies emphasising the needs of women, young people and those with preschool aged children are likely to play an important part in preventing future mental illness.
TL;DR: The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.
Abstract: Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1,2,3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10,11,12,13,14,15,16,17,18.
TL;DR: Policy makers need to be aware of the equivocal evidence when considering school closures for COVID-19, and that combinations of social distancing measures should be considered.
TL;DR: There was a wide spectrum of presenting signs and symptoms and disease severity, ranging from fever and inflammation to myocardial injury, shock, and development of coronary artery aneurysms, and comparison with the characteristics of other pediatric inflammatory disorders.
Abstract: Importance In communities with high rates of coronavirus disease 2019, reports have emerged of children with an unusual syndrome of fever and inflammation. Objectives To describe the clinical and laboratory characteristics of hospitalized children who met criteria for the pediatric inflammatory multisystem syndrome temporally associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (PIMS-TS) and compare these characteristics with other pediatric inflammatory disorders. Design, Setting, and Participants Case series of 58 children from 8 hospitals in England admitted between March 23 and May 16, 2020, with persistent fever and laboratory evidence of inflammation meeting published definitions for PIMS-TS. The final date of follow-up was May 22, 2020. Clinical and laboratory characteristics were abstracted by medical record review, and were compared with clinical characteristics of patients with Kawasaki disease (KD) (n = 1132), KD shock syndrome (n = 45), and toxic shock syndrome (n = 37) who had been admitted to hospitals in Europe and the US from 2002 to 2019. Exposures Signs and symptoms and laboratory and imaging findings of children who met definitional criteria for PIMS-TS from the UK, the US, and World Health Organization. Main Outcomes and Measures Clinical, laboratory, and imaging characteristics of children meeting definitional criteria for PIMS-TS, and comparison with the characteristics of other pediatric inflammatory disorders. Results Fifty-eight children (median age, 9 years [interquartile range {IQR}, 5.7-14]; 20 girls [34%]) were identified who met the criteria for PIMS-TS. Results from SARS-CoV-2 polymerase chain reaction tests were positive in 15 of 58 patients (26%) and SARS-CoV-2 IgG test results were positive in 40 of 46 (87%). In total, 45 of 58 patients (78%) had evidence of current or prior SARS-CoV-2 infection. All children presented with fever and nonspecific symptoms, including vomiting (26/58 [45%]), abdominal pain (31/58 [53%]), and diarrhea (30/58 [52%]). Rash was present in 30 of 58 (52%), and conjunctival injection in 26 of 58 (45%) cases. Laboratory evaluation was consistent with marked inflammation, for example, C-reactive protein (229 mg/L [IQR, 156-338], assessed in 58 of 58) and ferritin (610 μg/L [IQR, 359-1280], assessed in 53 of 58). Of the 58 children, 29 developed shock (with biochemical evidence of myocardial dysfunction) and required inotropic support and fluid resuscitation (including 23/29 [79%] who received mechanical ventilation); 13 met the American Heart Association definition of KD, and 23 had fever and inflammation without features of shock or KD. Eight patients (14%) developed coronary artery dilatation or aneurysm. Comparison of PIMS-TS with KD and with KD shock syndrome showed differences in clinical and laboratory features, including older age (median age, 9 years [IQR, 5.7-14] vs 2.7 years [IQR, 1.4-4.7] and 3.8 years [IQR, 0.2-18], respectively), and greater elevation of inflammatory markers such as C-reactive protein (median, 229 mg/L [IQR 156-338] vs 67 mg/L [IQR, 40-150 mg/L] and 193 mg/L [IQR, 83-237], respectively). Conclusions and Relevance In this case series of hospitalized children who met criteria for PIMS-TS, there was a wide spectrum of presenting signs and symptoms and disease severity, ranging from fever and inflammation to myocardial injury, shock, and development of coronary artery aneurysms. The comparison with patients with KD and KD shock syndrome provides insights into this syndrome, and suggests this disorder differs from other pediatric inflammatory entities.
TL;DR: A robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening and using a combination of AI and human inputs could help to improve screening efficiency.
Abstract: Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful1. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives2. Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening. An artificial intelligence (AI) system performs as well as or better than radiologists at detecting breast cancer from mammograms, and using a combination of AI and human inputs could help to improve screening efficiency.
TL;DR: The structure and content of CellPhoneDB is outlined, procedures for inferring cell–cell communication networks from single-cell RNA sequencing data are provided and a practical step-by-step guide to help implement the protocol is presented.
Abstract: Cell–cell communication mediated by ligand–receptor complexes is critical to coordinating diverse biological processes, such as development, differentiation and inflammation. To investigate how the context-dependent crosstalk of different cell types enables physiological processes to proceed, we developed CellPhoneDB, a novel repository of ligands, receptors and their interactions. In contrast to other repositories, our database takes into account the subunit architecture of both ligands and receptors, representing heteromeric complexes accurately. We integrated our resource with a statistical framework that predicts enriched cellular interactions between two cell types from single-cell transcriptomics data. Here, we outline the structure and content of our repository, provide procedures for inferring cell–cell communication networks from single-cell RNA sequencing data and present a practical step-by-step guide to help implement the protocol. CellPhoneDB v.2.0 is an updated version of our resource that incorporates additional functionalities to enable users to introduce new interacting molecules and reduces the time and resources needed to interrogate large datasets. CellPhoneDB v.2.0 is publicly available, both as code and as a user-friendly web interface; it can be used by both experts and researchers with little experience in computational genomics. In our protocol, we demonstrate how to evaluate meaningful biological interactions with CellPhoneDB v.2.0 using published datasets. This protocol typically takes ~2 h to complete, from installation to statistical analysis and visualization, for a dataset of ~10 GB, 10,000 cells and 19 cell types, and using five threads. CellPhoneDB combines an interactive database and a statistical framework for the exploration of ligand–receptor interactions inferred from single-cell transcriptomics measurements.
TL;DR: In 2019, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9 and the Virgo detector was also taking data that did not contribute to detection due to a low SINR but were used for subsequent parameter estimation as discussed by the authors.
Abstract: On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation. The 90% credible intervals for the component masses range from to if we restrict the dimensionless component spin magnitudes to be smaller than 0.05). These mass parameters are consistent with the individual binary components being neutron stars. However, both the source-frame chirp mass and the total mass of this system are significantly larger than those of any other known binary neutron star (BNS) system. The possibility that one or both binary components of the system are black holes cannot be ruled out from gravitational-wave data. We discuss possible origins of the system based on its inconsistency with the known Galactic BNS population. Under the assumption that the signal was produced by a BNS coalescence, the local rate of neutron star mergers is updated to 250-2810.
TL;DR: It is found that although levels of concern are relatively high, they are highest in the UK compared to all other sampled countries, and risk perception correlated significantly with reported adoption of preventative health behaviors in all ten countries.
Abstract: The World Health Organization has declared the rapid spread of COVID-19 around the world a global public health emergency. It is well-known that the spread of the disease is influenced by people’s ...
TL;DR: A low proportion of COVID-19 patients have a bacterial co-infection; less than in previous influenza pandemics; and these findings do not support the routine use of antibiotics in the management of confirmed CO VID-19 infection.
TL;DR: The potential consequences for health inequalities of the lockdown measures implemented internationally as a response to the COVID-19 pandemic are explored, focusing on the likely unequal impacts of the economic crisis.
Abstract: This essay examines the implications of the COVID-19 pandemic for health inequalities. It outlines historical and contemporary evidence of inequalities in pandemics-drawing on international research into the Spanish influenza pandemic of 1918, the H1N1 outbreak of 2009 and the emerging international estimates of socio-economic, ethnic and geographical inequalities in COVID-19 infection and mortality rates. It then examines how these inequalities in COVID-19 are related to existing inequalities in chronic diseases and the social determinants of health, arguing that we are experiencing a syndemic pandemic It then explores the potential consequences for health inequalities of the lockdown measures implemented internationally as a response to the COVID-19 pandemic, focusing on the likely unequal impacts of the economic crisis. The essay concludes by reflecting on the longer-term public health policy responses needed to ensure that the COVID-19 pandemic does not increase health inequalities for future generations.
University of Southampton1, University Hospital Southampton NHS Foundation Trust2, University of Newcastle3, National Institute for Health Research4, University of Liverpool5, Walton Centre6, King's College London7, University of Utah8, UCL Institute of Neurology9, University of Cambridge10, University of Edinburgh11, Manchester Academic Health Science Centre12, University of Oxford13, University College London14, Royal Victoria Infirmary15
TL;DR: This is the first nationwide, cross-specialty surveillance study of acute neurological and psychiatric complications of COVID-19 and provides valuable and timely data that are urgently needed by clinicians, researchers, and funders.
Queensland University of Technology1, University of Leicester2, Pennsylvania State University3, Delft University of Technology4, University of Cassino5, Chinese Academy of Sciences6, Edinburgh Napier University7, University of Cambridge8, ICM Partners9, Lund University10, Cooperative Institute for Research in Environmental Sciences11, Tallinn University of Technology12, University of Hong Kong13, Eindhoven University of Technology14, University of New South Wales15, Virginia Tech16, Polytechnic University of Milan17, Technical University of Denmark18, University of Colorado Boulder19, University of Maryland, College Park20, University of California, Berkeley21, Aalborg University22, University of Leeds23, Yale University24, Spanish National Research Council25, National University of Singapore26, Aalto University27, McGill University28, Peking University29
TL;DR: It is argued that existing evidence is sufficiently strong to warrant engineering controls targeting airborne transmission as part of an overall strategy to limit infection risk indoors, and that the use of engineering controls in public buildings would be an additional important measure globally to reduce the likelihood of transmission.
TL;DR: In this paper, the authors reported the observation of a compact binary coalescence involving a 222 −243 M ⊙ black hole and a compact object with a mass of 250 −267 M ⋆ (all measurements quoted at the 90% credible level) The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network.
Abstract: We report the observation of a compact binary coalescence involving a 222–243 M ⊙ black hole and a compact object with a mass of 250–267 M ⊙ (all measurements quoted at the 90% credible level) The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network The source was localized to 185 deg2 at a distance of ${241}_{-45}^{+41}$ Mpc; no electromagnetic counterpart has been confirmed to date The source has the most unequal mass ratio yet measured with gravitational waves, ${0112}_{-0009}^{+0008}$, and its secondary component is either the lightest black hole or the heaviest neutron star ever discovered in a double compact-object system The dimensionless spin of the primary black hole is tightly constrained to ≤007 Tests of general relativity reveal no measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at high confidence We estimate a merger rate density of 1–23 Gpc−3 yr−1 for the new class of binary coalescence sources that GW190814 represents Astrophysical models predict that binaries with mass ratios similar to this event can form through several channels, but are unlikely to have formed in globular clusters However, the combination of mass ratio, component masses, and the inferred merger rate for this event challenges all current models of the formation and mass distribution of compact-object binaries
TL;DR: In this paper, the authors present real-time survey evidence from the UK, US and Germany showing that the immediate labor market impacts of Covid-19 differ considerably across countries.