Showing papers by "Columbia University published in 2019"

Transcatheter Aortic-Valve Replacement with a Balloon-Expandable Valve in Low-Risk Patients

Abstract: Background Among patients with aortic stenosis who are at intermediate or high risk for death with surgery, major outcomes are similar with transcatheter aortic-valve replacement (TAVR) an...

Guidelines on the Use of Therapeutic Apheresis in Clinical Practice—Evidence-Based Approach from the Writing Committee of the American Society for Apheresis: The Sixth Special Issue

Abstract: The American Society for Apheresis (ASFA) Journal of Clinical Apheresis (JCA) Special Issue Writing Committee is charged with reviewing, updating, and categorizing indications for the evidence-based use of therapeutic apheresis in human disease. Since the 2007 JCA Special Issue (Fourth Edition), the Committee has incorporated systematic review and evidence-based approaches in the grading and categorization of apheresis indications. This Seventh Edition of the JCA Special Issue continues to maintain this methodology and rigor to make recommendations on the use of apheresis in a wide variety of diseases/conditions. The JCA Seventh Edition, like its predecessor, has consistently applied the category and grading system definitions in the fact sheets. The general layout and concept of a fact sheet that was used since the fourth edition has largely been maintained in this edition. Each fact sheet succinctly summarizes the evidence for the use of therapeutic apheresis in a specific disease entity. The Seventh Edition discusses 87 fact sheets (14 new fact sheets since the Sixth Edition) for therapeutic apheresis diseases and medical conditions, with 179 indications, which are separately graded and categorized within the listed fact sheets. Several diseases that are Category IV which have been described in detail in previous editions and do not have significant new evidence since the last publication are summarized in a separate table. The Seventh Edition of the JCA Special Issue serves as a key resource that guides the utilization of therapeutic apheresis in the treatment of human disease. J. Clin. Apheresis 31:149-162, 2016. © 2016 Wiley Periodicals, Inc.

Natural Questions: A Benchmark for Question Answering Research

Abstract: We present the Natural Questions corpus, a question answering data set. Questions consist of real anonymized, aggregated queries issued to the Google search engine. An annotator is presented with a...

Tuning superconductivity in twisted bilayer graphene.

Abstract: Materials with flat electronic bands often exhibit exotic quantum phenomena owing to strong correlations. An isolated low-energy flat band can be induced in bilayer graphene by simply rotating the layers by 1.1°, resulting in the appearance of gate-tunable superconducting and correlated insulating phases. In this study, we demonstrate that in addition to the twist angle, the interlayer coupling can be varied to precisely tune these phases. We induce superconductivity at a twist angle larger than 1.1°—in which correlated phases are otherwise absent—by varying the interlayer spacing with hydrostatic pressure. Our low-disorder devices reveal details about the superconducting phase diagram and its relationship to the nearby insulator. Our results demonstrate twisted bilayer graphene to be a distinctively tunable platform for exploring correlated states.

Chronic pain as a symptom or a disease: the IASP Classification of Chronic Pain for the International Classification of Diseases (ICD-11).

Abstract: Chronic pain is a major source of suffering. It interferes with daily functioning and often is accompanied by distress. Yet, in the International Classification of Diseases, chronic pain diagnoses are not represented systematically. The lack of appropriate codes renders accurate epidemiological investigations difficult and impedes health policy decisions regarding chronic pain such as adequate financing of access to multimodal pain management. In cooperation with the WHO, an IASP Working Group has developed a classification system that is applicable in a wide range of contexts, including pain medicine, primary care, and low-resource environments. Chronic pain is defined as pain that persists or recurs for more than 3 months. In chronic pain syndromes, pain can be the sole or a leading complaint and requires special treatment and care. In conditions such as fibromyalgia or nonspecific low-back pain, chronic pain may be conceived as a disease in its own right; in our proposal, we call this subgroup "chronic primary pain." In 6 other subgroups, pain is secondary to an underlying disease: chronic cancer-related pain, chronic neuropathic pain, chronic secondary visceral pain, chronic posttraumatic and postsurgical pain, chronic secondary headache and orofacial pain, and chronic secondary musculoskeletal pain. These conditions are summarized as "chronic secondary pain" where pain may at least initially be conceived as a symptom. Implementation of these codes in the upcoming 11th edition of International Classification of Diseases will lead to improved classification and diagnostic coding, thereby advancing the recognition of chronic pain as a health condition in its own right.

The GTEx Consortium atlas of genetic regulatory effects across human tissues

Abstract: The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

CD8+ T cells regulate tumour ferroptosis during cancer immunotherapy

Abstract: Cancer immunotherapy restores or enhances the effector function of CD8+ T cells in the tumour microenvironment1,2. CD8+ T cells activated by cancer immunotherapy clear tumours mainly by inducing cell death through perforin-granzyme and Fas-Fas ligand pathways3,4. Ferroptosis is a form of cell death that differs from apoptosis and results from iron-dependent accumulation of lipid peroxide5,6. Although it has been investigated in vitro7,8, there is emerging evidence that ferroptosis might be implicated in a variety of pathological scenarios9,10. It is unclear whether, and how, ferroptosis is involved in T cell immunity and cancer immunotherapy. Here we show that immunotherapy-activated CD8+ T cells enhance ferroptosis-specific lipid peroxidation in tumour cells, and that increased ferroptosis contributes to the anti-tumour efficacy of immunotherapy. Mechanistically, interferon gamma (IFNγ) released from CD8+ T cells downregulates the expression of SLC3A2 and SLC7A11, two subunits of the glutamate-cystine antiporter system xc-, impairs the uptake of cystine by tumour cells, and as a consequence, promotes tumour cell lipid peroxidation and ferroptosis. In mouse models, depletion of cystine or cysteine by cyst(e)inase (an engineered enzyme that degrades both cystine and cysteine) in combination with checkpoint blockade synergistically enhanced T cell-mediated anti-tumour immunity and induced ferroptosis in tumour cells. Expression of system xc- was negatively associated, in cancer patients, with CD8+ T cell signature, IFNγ expression, and patient outcome. Analyses of human transcriptomes before and during nivolumab therapy revealed that clinical benefits correlate with reduced expression of SLC3A2 and increased IFNγ and CD8. Thus, T cell-promoted tumour ferroptosis is an anti-tumour mechanism, and targeting this pathway in combination with checkpoint blockade is a potential therapeutic approach.

Conserved cell types with divergent features in human versus mouse cortex.

Abstract: Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.

Ferroptosis as a target for protection against cardiomyopathy.

Abstract: Heart disease is the leading cause of death worldwide. A key pathogenic factor in the development of lethal heart failure is loss of terminally differentiated cardiomyocytes. However, mechanisms of cardiomyocyte death remain unclear. Here, we discovered and demonstrated that ferroptosis, a programmed iron-dependent cell death, as a mechanism in murine models of doxorubicin (DOX)- and ischemia/reperfusion (I/R)-induced cardiomyopathy. In canonical apoptosis and/or necroptosis-defective Ripk3−/−, Mlkl−/−, or Fadd−/−Mlkl−/− mice, DOX-treated cardiomyocytes showed features of typical ferroptotic cell death. Consistently, compared with dexrazoxane, the only FDA-approved drug for treating DOX-induced cardiotoxicity, inhibition of ferroptosis by ferrostatin-1 significantly reduced DOX cardiomyopathy. RNA-sequencing results revealed that heme oxygenase-1 (Hmox1) was significantly up-regulated in DOX-treated murine hearts. Administering DOX to mice induced cardiomyopathy with a rapid, systemic accumulation of nonheme iron via heme degradation by Nrf2-mediated up-regulation of Hmox1, which effect was abolished in Nrf2-deficent mice. Conversely, zinc protoporphyrin IX, an Hmox1 antagonist, protected the DOX-treated mice, suggesting free iron released on heme degradation is necessary and sufficient to induce cardiac injury. Given that ferroptosis is driven by damage to lipid membranes, we further investigated and found that excess free iron accumulated in mitochondria and caused lipid peroxidation on its membrane. Mitochondria-targeted antioxidant MitoTEMPO significantly rescued DOX cardiomyopathy, supporting oxidative damage of mitochondria as a major mechanism in ferroptosis-induced heart damage. Importantly, ferrostatin-1 and iron chelation also ameliorated heart failure induced by both acute and chronic I/R in mice. These findings highlight that targeting ferroptosis serves as a cardioprotective strategy for cardiomyopathy prevention.

DNA methylation GrimAge strongly predicts lifespan and healthspan.

Abstract: It was unknown whether plasma protein levels can be estimated based on DNA methylation (DNAm) levels, and if so, how the resulting surrogates can be consolidated into a powerful predictor of lifespan. We present here, seven DNAm-based estimators of plasma proteins including those of plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. The resulting predictor of lifespan, DNAm GrimAge (in units of years), is a composite biomarker based on the seven DNAm surrogates and a DNAm-based estimator of smoking pack-years. Adjusting DNAm GrimAge for chronological age generated novel measure of epigenetic age acceleration, AgeAccelGrim.Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E-17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment.Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies.

Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts

Abstract: Cancer-associated fibroblasts (CAF) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we use single-cell RNA sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human and mouse PDAC tumors. We corroborate the presence of myofibroblastic CAFs and inflammatory CAFs and define their unique gene signatures in vivo. Moreover, we describe a new population of CAFs that express MHC class II and CD74, but do not express classic costimulatory molecules. We term this cell population "antigen-presenting CAFs" and find that they activate CD4+ T cells in an antigen-specific fashion in a model system, confirming their putative immune-modulatory capacity. Our cross-species analysis paves the way for investigating distinct functions of CAF subtypes in PDAC immunity and progression. SIGNIFICANCE: Appreciating the full spectrum of fibroblast heterogeneity in pancreatic ductal adenocarcinoma is crucial to developing therapies that specifically target tumor-promoting CAFs. This work identifies MHC class II-expressing CAFs with a capacity to present antigens to CD4+ T cells, and potentially to modulate the immune response in pancreatic tumors.See related commentary by Belle and DeNardo, p. 1001.This article is highlighted in the In This Issue feature, p. 983.

CHOPCHOP v3: expanding the CRISPR web toolbox beyond genome editing

Abstract: The CRISPR-Cas system is a powerful genome editing tool that functions in a diverse array of organisms and cell types. The technology was initially developed to induce targeted mutations in DNA, but CRISPR-Cas has now been adapted to target nucleic acids for a range of purposes. CHOPCHOP is a web tool for identifying CRISPR-Cas single guide RNA (sgRNA) targets. In this major update of CHOPCHOP, we expand our toolbox beyond knockouts. We introduce functionality for targeting RNA with Cas13, which includes support for alternative transcript isoforms and RNA accessibility predictions. We incorporate new DNA targeting modes, including CRISPR activation/repression, targeted enrichment of loci for long-read sequencing, and prediction of Cas9 repair outcomes. Finally, we expand our results page visualization to reveal alternative isoforms and downstream ATG sites, which will aid users in avoiding the expression of truncated proteins. The CHOPCHOP web tool now supports over 200 genomes and we have released a command-line script for running larger jobs and handling unsupported genomes. CHOPCHOP v3 can be found at https://chopchop.cbu.uib.no.

Effect of Catheter Ablation vs Antiarrhythmic Drug Therapy on Mortality, Stroke, Bleeding, and Cardiac Arrest Among Patients With Atrial Fibrillation: The CABANA Randomized Clinical Trial

Abstract: Importance Catheter ablation is effective in restoring sinus rhythm in atrial fibrillation (AF), but its effects on long-term mortality and stroke risk are uncertain. Objective To determine whether catheter ablation is more effective than conventional medical therapy for improving outcomes in AF. Design, Setting, and Participants The Catheter Ablation vs Antiarrhythmic Drug Therapy for Atrial Fibrillation trial is an investigator-initiated, open-label, multicenter, randomized trial involving 126 centers in 10 countries. A total of 2204 symptomatic patients with AF aged 65 years and older or younger than 65 years with 1 or more risk factors for stroke were enrolled from November 2009 to April 2016, with follow-up through December 31, 2017. Interventions The catheter ablation group (n = 1108) underwent pulmonary vein isolation, with additional ablative procedures at the discretion of site investigators. The drug therapy group (n = 1096) received standard rhythm and/or rate control drugs guided by contemporaneous guidelines. Main Outcomes and Measures The primary end point was a composite of death, disabling stroke, serious bleeding, or cardiac arrest. Among 13 prespecified secondary end points, 3 are included in this report: all-cause mortality; total mortality or cardiovascular hospitalization; and AF recurrence. Results Of the 2204 patients randomized (median age, 68 years; 37.2% female; 42.9% had paroxysmal AF and 57.1% had persistent AF), 89.3% completed the trial. Of the patients assigned to catheter ablation, 1006 (90.8%) underwent the procedure. Of the patients assigned to drug therapy, 301 (27.5%) ultimately received catheter ablation. In the intention-to-treat analysis, over a median follow-up of 48.5 months, the primary end point occurred in 8.0% (n = 89) of patients in the ablation group vs 9.2% (n = 101) of patients in the drug therapy group (hazard ratio [HR], 0.86 [95% CI, 0.65-1.15];P = .30). Among the secondary end points, outcomes in the ablation group vs the drug therapy group, respectively, were 5.2% vs 6.1% for all-cause mortality (HR, 0.85 [95% CI, 0.60-1.21];P = .38), 51.7% vs 58.1% for death or cardiovascular hospitalization (HR, 0.83 [95% CI, 0.74-0.93];P = .001), and 49.9% vs 69.5% for AF recurrence (HR, 0.52 [95% CI, 0.45-0.60];P Conclusions and Relevance Among patients with AF, the strategy of catheter ablation, compared with medical therapy, did not significantly reduce the primary composite end point of death, disabling stroke, serious bleeding, or cardiac arrest. However, the estimated treatment effect of catheter ablation was affected by lower-than-expected event rates and treatment crossovers, which should be considered in interpreting the results of the trial. Trial Registration ClinicalTrials.gov Identifier:NCT00911508

Reconciling modern machine-learning practice and the classical bias-variance trade-off.

Abstract: Breakthroughs in machine learning are rapidly changing science and society, yet our fundamental understanding of this technology has lagged far behind. Indeed, one of the central tenets of the field, the bias-variance trade-off, appears to be at odds with the observed behavior of methods used in modern machine-learning practice. The bias-variance trade-off implies that a model should balance underfitting and overfitting: Rich enough to express underlying structure in data and simple enough to avoid fitting spurious patterns. However, in modern practice, very rich models such as neural networks are trained to exactly fit (i.e., interpolate) the data. Classically, such models would be considered overfitted, and yet they often obtain high accuracy on test data. This apparent contradiction has raised questions about the mathematical foundations of machine learning and their relevance to practitioners. In this paper, we reconcile the classical understanding and the modern practice within a unified performance curve. This "double-descent" curve subsumes the textbook U-shaped bias-variance trade-off curve by showing how increasing model capacity beyond the point of interpolation results in improved performance. We provide evidence for the existence and ubiquity of double descent for a wide spectrum of models and datasets, and we posit a mechanism for its emergence. This connection between the performance and the structure of machine-learning models delineates the limits of classical analyses and has implications for both the theory and the practice of machine learning.

Six transformations to achieve the Sustainable Development Goals

Abstract: The Sustainable Development Goals (SDGs) and the Paris Agreement on Climate Change call for deep transformations in every country that will require complementary actions by governments, civil society, science and business. Yet stakeholders lack a shared understanding of how the 17 SDGs can be operationalized. Drawing on earlier work by The World in 2050 initiative, we introduce six SDG Transformations as modular building-blocks of SDG achievement: (1) education, gender and inequality; (2) health, well-being and demography; (3) energy decarbonization and sustainable industry; (4) sustainable food, land, water and oceans; (5) sustainable cities and communities; and (6) digital revolution for sustainable development. Each Transformation identifies priority investments and regulatory challenges, calling for actions by well-defined parts of government working with business and civil society. Transformations may therefore be operationalized within the structures of government while respecting the strong interdependencies across the 17 SDGs. We also outline an action agenda for science to provide the knowledge required for designing, implementing and monitoring the SDG Transformations. The Sustainable Development Goals require profound national and societal changes. This Perspective introduces six Transformations as building blocks for achieving the SDGs and an agenda for science to provide the requisite knowledge.

PSR J0030+0451 Mass and Radius from NICER Data and Implications for the Properties of Neutron Star Matter

Abstract: Neutron stars are not only of astrophysical interest, but are also of great interest to nuclear physicists because their attributes can be used to determine the properties of the dense matter in their cores. One of the most informative approaches for determining the equation of state (EoS) of this dense matter is to measure both a star’s equatorial circumferential radius R e and its gravitational mass M. Here we report estimates of the mass and radius of the isolated 205.53 Hz millisecond pulsar PSR J0030+0451 obtained using a Bayesian inference approach to analyze its energy-dependent thermal X-ray waveform, which was observed using the Neutron Star Interior Composition Explorer (NICER). This approach is thought to be less subject to systematic errors than other approaches for estimating neutron star radii. We explored a variety of emission patterns on the stellar surface. Our best-fit model has three oval, uniform-temperature emitting spots and provides an excellent description of the pulse waveform observed using NICER. The radius and mass estimates given by this model are km and (68%). The independent analysis reported in the companion paper by Riley et al. explores different emitting spot models, but finds spot shapes and locations and estimates of R e and M that are consistent with those found in this work. We show that our measurements of R e and M for PSR J0030+0451 improve the astrophysical constraints on the EoS of cold, catalyzed matter above nuclear saturation density.

A fully magnetically levitated left ventricular assist device - Final report

Abstract: Background In two interim analyses of this trial, patients with advanced heart failure who were treated with a fully magnetically levitated centrifugal-flow left ventricular assist device ...

A NICER View of PSR J0030+0451: Millisecond Pulsar Parameter Estimation

Abstract: We report on Bayesian parameter estimation of the mass and equatorial radius of the millisecond pulsar PSR J0030+0451, conditional on pulse-profile modeling of Neutron Star Interior Composition Explorer X-ray spectral-timing event data. We perform relativistic ray-tracing of thermal emission from hot regions of the pulsar’s surface. We assume two distinct hot regions based on two clear pulsed components in the phase-folded pulse-profile data; we explore a number of forms (morphologies and topologies) for each hot region, inferring their parameters in addition to the stellar mass and radius. For the family of models considered, the evidence (prior predictive probability of the data) strongly favors a model that permits both hot regions to be located in the same rotational hemisphere. Models wherein both hot regions are assumed to be simply connected circular single-temperature spots, in particular those where the spots are assumed to be reflection-symmetric with respect to the stellar origin, are strongly disfavored. For the inferred configuration, one hot region subtends an angular extent of only a few degrees (in spherical coordinates with origin at the stellar center) and we are insensitive to other structural details; the second hot region is far more azimuthally extended in the form of a narrow arc, thus requiring a larger number of parameters to describe. The inferred mass M and equatorial radius R eq are, respectively, and , while the compactness is more tightly constrained; the credible interval bounds reported here are approximately the 16% and 84% quantiles in marginal posterior mass.

Artificial intelligence in cancer imaging: Clinical challenges and applications.

Abstract: Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

Properties of the Binary Neutron Star Merger GW170817

Abstract: On August 17, 2017, the Advanced LIGO and Advanced Virgo gravitational-wave detectors observed a low-mass compact binary inspiral. The initial sky localization of the source of the gravitational-wave signal, GW170817, allowed electromagnetic observatories to identify NGC 4993 as the host galaxy. In this work, we improve initial estimates of the binary's properties, including component masses, spins, and tidal parameters, using the known source location, improved modeling, and recalibrated Virgo data. We extend the range of gravitational-wave frequencies considered down to 23 Hz, compared to 30 Hz in the initial analysis. We also compare results inferred using several signal models, which are more accurate and incorporate additional physical effects as compared to the initial analysis. We improve the localization of the gravitational-wave source to a 90% credible region of 16 deg2. We find tighter constraints on the masses, spins, and tidal parameters, and continue to find no evidence for nonzero component spins. The component masses are inferred to lie between 1.00 and 1.89 M when allowing for large component spins, and to lie between 1.16 and 1.60 M (with a total mass 2.73-0.01+0.04 M) when the spins are restricted to be within the range observed in Galactic binary neutron stars. Using a precessing model and allowing for large component spins, we constrain the dimensionless spins of the components to be less than 0.50 for the primary and 0.61 for the secondary. Under minimal assumptions about the nature of the compact objects, our constraints for the tidal deformability parameter Λ are (0,630) when we allow for large component spins, and 300-230+420 (using a 90% highest posterior density interval) when restricting the magnitude of the component spins, ruling out several equation-of-state models at the 90% credible level. Finally, with LIGO and GEO600 data, we use a Bayesian analysis to place upper limits on the amplitude and spectral energy density of a possible postmerger signal.

Inflammation and its resolution in atherosclerosis: mediators and therapeutic opportunities

Abstract: Atherosclerosis is a lipid-driven inflammatory disease of the arterial intima in which the balance of pro-inflammatory and inflammation-resolving mechanisms dictates the final clinical outcome. Intimal infiltration and modification of plasma-derived lipoproteins and their uptake mainly by macrophages, with ensuing formation of lipid-filled foam cells, initiate atherosclerotic lesion formation, and deficient efferocytotic removal of apoptotic cells and foam cells sustains lesion progression. Defective efferocytosis, as a sign of inadequate inflammation resolution, leads to accumulation of secondarily necrotic macrophages and foam cells and the formation of an advanced lesion with a necrotic lipid core, indicative of plaque vulnerability. Resolution of inflammation is mediated by specialized pro-resolving lipid mediators derived from omega-3 fatty acids or arachidonic acid and by relevant proteins and signalling gaseous molecules. One of the major effects of inflammation resolution mediators is phenotypic conversion of pro-inflammatory macrophages into macrophages that suppress inflammation and promote healing. In advanced atherosclerotic lesions, the ratio between specialized pro-resolving mediators and pro-inflammatory lipids (in particular leukotrienes) is strikingly low, providing a molecular explanation for the defective inflammation resolution features of these lesions. In this Review, we discuss the mechanisms of the formation of clinically dangerous atherosclerotic lesions and the potential of pro-resolving mediator therapy to inhibit this process.

Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs

Abstract: It is common in regression discontinuity analysis to control for third, fourth, or higher-degree polynomials of the forcing variable. There appears to be a perception that such methods are theoreti...

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Abstract: Summary paragraph The Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency

The Community Land Model version 5 : description of new features, benchmarking, and impact of forcing uncertainty

Abstract: The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.

VideoBERT: A Joint Model for Video and Language Representation Learning.

Abstract: Self-supervised learning has become increasingly important to leverage the abundance of unlabeled data available on platforms like YouTube. Whereas most existing approaches learn low-level representations, we propose a joint visual-linguistic model to learn high-level features without any explicit supervision. In particular, inspired by its recent success in language modeling, we build upon the BERT model to learn bidirectional joint distributions over sequences of visual and linguistic tokens, derived from vector quantization of video data and off-the-shelf speech recognition outputs, respectively. We use VideoBERT in numerous tasks, including action classification and video captioning. We show that it can be applied directly to open-vocabulary classification, and confirm that large amounts of training data and cross-modal information are critical to performance. Furthermore, we outperform the state-of-the-art on video captioning, and quantitative results verify that the model learns high-level semantic features.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Maximized electron interactions at the magic angle in twisted bilayer graphene

Abstract: The electronic properties of heterostructures of atomically thin van der Waals crystals can be modified substantially by moire superlattice potentials from an interlayer twist between crystals1,2. Moire tuning of the band structure has led to the recent discovery of superconductivity3,4 and correlated insulating phases5 in twisted bilayer graphene (TBG) near the ‘magic angle’ of twist of about 1.1 degrees, with a phase diagram reminiscent of high-transition-temperature superconductors. Here we directly map the atomic-scale structural and electronic properties of TBG near the magic angle using scanning tunnelling microscopy and spectroscopy. We observe two distinct van Hove singularities (VHSs) in the local density of states around the magic angle, with an energy separation of 57 millielectronvolts that drops to 40 millielectronvolts with high electron/hole doping. Unexpectedly, the VHS energy separation continues to decrease with decreasing twist angle, with a lowest value of 7 to 13 millielectronvolts at a magic angle of 0.79 degrees. More crucial to the correlated behaviour of this material, we find that at the magic angle, the ratio of the Coulomb interaction to the bandwidth of each individual VHS (U/t) is maximized, which is optimal for electronic Cooper pairing mechanisms. When doped near the half-moire-band filling, a correlation-induced gap splits the conduction VHS with a maximum size of 6.5 millielectronvolts at 1.15 degrees, dropping to 4 millielectronvolts at 0.79 degrees. We capture the doping-dependent and angle-dependent spectroscopy results using a Hartree–Fock model, which allows us to extract the on-site and nearest-neighbour Coulomb interactions. This analysis yields a U/t of order unity indicating that magic-angle TBG is moderately correlated. In addition, scanning tunnelling spectroscopy maps reveal an energy- and doping-dependent three-fold rotational-symmetry breaking of the local density of states in TBG, with the strongest symmetry breaking near the Fermi level and further enhanced when doped to the correlated gap regime. This indicates the presence of a strong electronic nematic susceptibility or even nematic order in TBG in regions of the phase diagram where superconductivity is observed. Scanning tunnelling spectroscopy is used to map the atomic-scale electronic structure of magic-angle twisted bilayer graphene, finding multiple signatures of electron correlations and thus providing insight into the sought-after mechanism behind superconductivity in graphene.

Photonic-chip-based frequency combs

Abstract: Recent developments in chip-based nonlinear photonics offer the tantalizing prospect of realizing many applications that can use optical frequency comb devices that have form factors smaller than 1 cm3 and that require less than 1 W of power. A key feature that enables such technology is the tight confinement of light due to the high refractive index contrast between the core and the cladding. This simultaneously produces high optical nonlinearities and allows for dispersion engineering to realize and phase match parametric nonlinear processes with laser-pointer powers across large spectral bandwidths. In this Review, we summarize the developments, applications and underlying physics of optical frequency comb generation in photonic-chip waveguides via supercontinuum generation and in microresonators via Kerr-comb generation that enable comb technology from the near-ultraviolet to the mid-infrared regime. This Review discusses the developments and applications of on-chip optical frequency comb generation based on two concepts—supercontinuum generation in photonic-chip waveguides and Kerr-comb generation in microresonators.