Showing papers by "Stony Brook University published in 2016"
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes.
For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy.
Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.
5,187 citations
University of Nebraska Medical Center1, University of Connecticut2, Harvard University3, Queen's University4, University of California, San Diego5, Stony Brook University6, University of Michigan7, National Institutes of Health8, Johns Hopkins University9, University of Barcelona10, University at Buffalo11, Summa Health System12, University of Texas Health Science Center at San Antonio13, University of Queensland14, Royal Brisbane and Women's Hospital15, University of Western Australia16, University of Colorado Denver17, McMaster University18
TL;DR: These guidelines are intended for use by healthcare professionals who care for patients at risk for hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), including specialists in infectious diseases, pulmonary diseases, critical care, and surgeons, anesthesiologists, hospitalists, and any clinicians and healthcare providers caring for hospitalized patients with nosocomial pneumonia.
Abstract: It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.These guidelines are intended for use by healthcare professionals who care for patients at risk for hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), including specialists in infectious diseases, pulmonary diseases, critical care, and surgeons, anesthesiologists, hospitalists, and any clinicians and healthcare providers caring for hospitalized patients with nosocomial pneumonia. The panel's recommendations for the diagnosis and treatment of HAP and VAP are based upon evidence derived from topic-specific systematic literature reviews.
2,359 citations
Broad Institute1, Harvard University2, Howard Hughes Medical Institute3, University of California, Berkeley4, University of California, Los Angeles5, Chinese Academy of Sciences6, Max Planck Society7, Columbia University8, Massachusetts Institute of Technology9, Cayetano Heredia University10, University of Pennsylvania11, University College London12, University of Bern13, Leiden University14, Nanyang Technological University15, University of Chicago16, Estonian Biocentre17, National University of La Plata18, University of Oxford19, University of Bergen20, Novosibirsk State University21, Moscow Institute of Physics and Technology22, Sofia Medical University23, Armenian National Academy of Sciences24, Wellcome Trust Sanger Institute25, Raja Isteri Pengiran Anak Saleha Hospital26, Case Western Reserve University27, University of Tartu28, Estonian Academy of Sciences29, Stony Brook University30, Illumina31, Gladstone Institutes32, University of Helsinki33, University of Washington34, Bashkir State University35, Jaramogi Oginga Odinga University of Science and Technology36, Pompeu Fabra University37, University of Arizona38, University of Cambridge39, Leidos40, Université de Montréal41, University of Utah42, Altai State University43, Council of Scientific and Industrial Research44
TL;DR: It is demonstrated that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.
Abstract: Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.
1,133 citations
Hampton University1, Thomas Jefferson National Accelerator Facility2, University of Paris-Sud3, University of Santiago, Chile4, Brookhaven National Laboratory5, University of Pavia6, University of Groningen7, Federico Santa María Technical University8, Shandong University9, Goethe University Frankfurt10, Stony Brook University11, Baruch College12, Duke University13, Argonne National Laboratory14, The Catholic University of America15, Old Dominion University16, Lawrence Berkeley National Laboratory17, Ohio State University18, University of Zagreb19, University of Jyväskylä20, Tel Aviv University21, CERN22, Temple University23, Massachusetts Institute of Technology24, Columbia University25, Ruhr University Bochum26, California Institute of Technology27, University of Massachusetts Amherst28, University of Buenos Aires29, University of the Basque Country30, University of Connecticut31, University of Tübingen32, Pennsylvania State University33, Stanford University34, Dalhousie University35, Central China Normal University36
TL;DR: In this article, the science case of an Electron-Ion Collider (EIC), focused on the structure and interactions of gluon-dominated matter, with the intent to articulate it to the broader nuclear science community, is presented.
Abstract: This White Paper presents the science case of an Electron-Ion Collider (EIC), focused on the structure and interactions of gluon-dominated matter, with the intent to articulate it to the broader nuclear science community. It was commissioned by the managements of Brookhaven National Laboratory (BNL) and Thomas Jefferson National Accelerator Facility (JLab) with the objective of presenting a summary of scientific opportunities and goals of the EIC as a follow-up to the 2007 NSAC Long Range plan. This document is a culmination of a community-wide effort in nuclear science following a series of workshops on EIC physics over the past decades and, in particular, the focused ten-week program on “Gluons and quark sea at high energies” at the Institute for Nuclear Theory in Fall 2010. It contains a brief description of a few golden physics measurements along with accelerator and detector concepts required to achieve them. It has been benefited profoundly from inputs by the users’ communities of BNL and JLab. This White Paper offers the promise to propel the QCD science program in the US, established with the CEBAF accelerator at JLab and the RHIC collider at BNL, to the next QCD frontier.
1,022 citations
Perimeter Institute for Theoretical Physics1, Niigata University2, CERN3, University of Connecticut4, Leiden University5, Korea Astronomy and Space Science Institute6, Federico Santa María Technical University7, University of California, Santa Barbara8, University of Maryland, College Park9, University of Lyon10, Claude Bernard University Lyon 111, Northwestern University12, University of Victoria13, University of Manchester14, University of Bonn15, Technische Universität München16, École Polytechnique Fédérale de Lausanne17, Stony Brook University18, Autonomous University of Madrid19, University of Paris20, Centre national de la recherche scientifique21, Moscow Institute of Physics and Technology22, Autonomous University of Barcelona23, University of Copenhagen24, Université libre de Bruxelles25, University of La Serena26, University of Valencia27, Taras Shevchenko National University of Kyiv28, Heidelberg University29, Yonsei University30, Princeton University31, Harvard University32, University of Geneva33, Tomsk Polytechnic University34, University of Tübingen35, Tomsk State University36, University of Washington37, University of Florida38, University of Hamburg39, TRIUMF40, University of Iowa41, University of Grenoble42, International Centre for Theoretical Physics43, Hokkai Gakuen University44, University of Illinois at Urbana–Champaign45, Durham University46, University of Melbourne47, University of Naples Federico II48, York University49, University of California, Berkeley50, Lawrence Berkeley National Laboratory51
TL;DR: It is demonstrated that the SHiP experiment has a unique potential to discover new physics and can directly probe a number of solutions of beyond the standard model puzzles, such as neutrino masses, baryon asymmetry of the Universe, dark matter, and inflation.
Abstract: This paper describes the physics case for a new fixed target facility at CERN SPS. The SHiP (search for hidden particles) experiment is intended to hunt for new physics in the largely unexplored domain of very weakly interacting particles with masses below the Fermi scale, inaccessible to the LHC experiments, and to study tau neutrino physics. The same proton beam setup can be used later to look for decays of tau-leptons with lepton flavour number non-conservation, $\tau \to 3\mu $ and to search for weakly-interacting sub-GeV dark matter candidates. We discuss the evidence for physics beyond the standard model and describe interactions between new particles and four different portals—scalars, vectors, fermions or axion-like particles. We discuss motivations for different models, manifesting themselves via these interactions, and how they can be probed with the SHiP experiment and present several case studies. The prospects to search for relatively light SUSY and composite particles at SHiP are also discussed. We demonstrate that the SHiP experiment has a unique potential to discover new physics and can directly probe a number of solutions of beyond the standard model puzzles, such as neutrino masses, baryon asymmetry of the Universe, dark matter, and inflation.
842 citations
TL;DR: A magnetotransport study of zirconium pentatelluride, ZrTe5, has been carried out in this paper, which reveals evidence for a chiral magnetic effect, a striking macroscopic manifestation of the quantum and relativistic nature of Weyl semimetals.
Abstract: A magnetotransport study of zirconium pentatelluride now reveals evidence for a chiral magnetic effect, a striking macroscopic manifestation of the quantum and relativistic nature of Weyl semimetals The chiral magnetic effect is the generation of an electric current induced by chirality imbalance in the presence of a magnetic field It is a macroscopic manifestation of the quantum anomaly1,2 in relativistic field theory of chiral fermions (massless spin 1/2 particles with a definite projection of spin on momentum)—a remarkable phenomenon arising from a collective motion of particles and antiparticles in the Dirac sea The recent discovery3,4,5,6 of Dirac semimetals with chiral quasiparticles opens a fascinating possibility to study this phenomenon in condensed matter experiments Here we report on the measurement of magnetotransport in zirconium pentatelluride, ZrTe5, that provides strong evidence for the chiral magnetic effect Our angle-resolved photoemission spectroscopy experiments show that this material’s electronic structure is consistent with a three-dimensional Dirac semimetal We observe a large negative magnetoresistance when the magnetic field is parallel with the current The measured quadratic field dependence of the magnetoconductance is a clear indication of the chiral magnetic effect The observed phenomenon stems from the effective transmutation of a Dirac semimetal into a Weyl semimetal induced by parallel electric and magnetic fields that represent a topologically non-trivial gauge field background We expect that the chiral magnetic effect may emerge in a wide class of materials that are near the transition between the trivial and topological insulators
806 citations
Stony Brook University1, University of Balamand2, Harvard University3, University of Washington4, University of Pennsylvania5, University of Cape Town6, Pompeu Fabra University7, Moi University8, Ulster University9, Katholieke Universiteit Leuven10, Universidade Nova de Lisboa11, University College Hospital, Ibadan12, Peking University13, Paris Diderot University14, University of Tokyo15, Paris Descartes University16, University of Otago17, New York University18, University of New South Wales19, Utrecht University20, Center for Excellence in Education21, Universidade Federal do Espírito Santo22
TL;DR: Exposure to interpersonal violence had the strongest associations with subsequent traumatic events, and limited resources may best be dedicated to those that are more likely to be further exposed such as victims of interpersonal violence.
Abstract: BACKGROUND: Considerable research has documented that exposure to traumatic events has negative effects on physical and mental health. Much less research has examined the predictors of traumatic event exposure. Increased understanding of risk factors for exposure to traumatic events could be of considerable value in targeting preventive interventions and anticipating service needs. METHOD: General population surveys in 24 countries with a combined sample of 68 894 adult respondents across six continents assessed exposure to 29 traumatic event types. Differences in prevalence were examined with cross-tabulations. Exploratory factor analysis was conducted to determine whether traumatic event types clustered into interpretable factors. Survival analysis was carried out to examine associations of sociodemographic characteristics and prior traumatic events with subsequent exposure. RESULTS: Over 70% of respondents reported a traumatic event; 30.5% were exposed to four or more. Five types - witnessing death or serious injury, the unexpected death of a loved one, being mugged, being in a life-threatening automobile accident, and experiencing a life-threatening illness or injury - accounted for over half of all exposures. Exposure varied by country, sociodemographics and history of prior traumatic events. Being married was the most consistent protective factor. Exposure to interpersonal violence had the strongest associations with subsequent traumatic events. CONCLUSIONS: Given the near ubiquity of exposure, limited resources may best be dedicated to those that are more likely to be further exposed such as victims of interpersonal violence. Identifying mechanisms that account for the associations of prior interpersonal violence with subsequent trauma is critical to develop interventions to prevent revictimization. Language: en
721 citations
TL;DR: The ability of Microcystis assemblages to minimize their mortality losses by resisting grazing by zooplankton and bivalves, as well as viral lysis, and discuss factors facilitating assemblage resilience are highlighted.
704 citations
TL;DR: Parmbsc1, a force field for DNA atomistic simulation, which has been parameterized from high-level quantum mechanical data and tested for nearly 100 systems and provides high-quality results in diverse systems is presented.
Abstract: We present parmbsc1, a force field for DNA atomistic simulation, which has been parameterized from high-level quantum mechanical data and tested for nearly 100 systems (representing a total simulation time of ~140 μs) covering most of DNA structural space. Parmbsc1 provides high-quality results in diverse systems. Parameters and trajectories are available at http://mmb.irbbarcelona.org/ParmBSC1/.
699 citations
01 Jun 2016
TL;DR: A novel Expectation-Maximization (EM) based method is formulated that automatically locates discriminative patches robustly by utilizing the spatial relationships of patches and applies it to the classification of glioma and non-small-cell lung carcinoma cases into subtypes.
Abstract: Convolutional Neural Networks (CNN) are state-of-theart models for many image classification tasks. However, to recognize cancer subtypes automatically, training a CNN on gigapixel resolution Whole Slide Tissue Images (WSI) is currently computationally impossible. The differentiation of cancer subtypes is based on cellular-level visual features observed on image patch scale. Therefore, we argue that in this situation, training a patch-level classifier on image patches will perform better than or similar to an image-level classifier. The challenge becomes how to intelligently combine patch-level classification results and model the fact that not all patches will be discriminative. We propose to train a decision fusion model to aggregate patch-level predictions given by patch-level CNNs, which to the best of our knowledge has not been shown before. Furthermore, we formulate a novel Expectation-Maximization (EM) based method that automatically locates discriminative patches robustly by utilizing the spatial relationships of patches. We apply our method to the classification of glioma and non-small-cell lung carcinoma cases into subtypes. The classification accuracy of our method is similar to the inter-observer agreement between pathologists. Although it is impossible to train CNNs on WSIs, we experimentally demonstrate using a comparable non-cancer dataset of smaller images that a patch-based CNN can outperform an image-based CNN.
611 citations
TL;DR: This study reports on the development of self-standing ternary FexCo1-xP nanowire array on carbon cloth as a Pt-free HER catalyst with activities being strongly related to Fe substitution ratio, and reveals that Fe substitution of Co in CoP leads to more optimal free energy of hydrogen adsorption to the catalyst surface.
Abstract: Replacement of precious Pt with earth-abundant electrocatalysts for the hydrogen evolution reaction (HER) holds great promise for clean energy devices, but the development of low-cost and durable HER catalysts with Pt-like activity is still a huge challenge. In this communication, we report on the development of self-standing ternary FexCo1–xP nanowire array on carbon cloth (FexCo1–xP/CC) as a Pt-free HER catalyst with activities being strongly related to Fe substitution ratio. Electrochemical tests show that Fe0.5Co0.5P/CC not only possesses Pt-like activity with the need of overpotential of only 37 mV to drive 10 mA cm–2, outperforming all non-noble-metal HER catalysts reported to date, but demonstrates superior long-term durability in 0.5 M H2SO4. Density functional theory calculations further reveal that Fe substitution of Co in CoP leads to more optimal free energy of hydrogen adsorption to the catalyst surface. This study offers us a promising flexible monolithic catalyst for practical applications.
TL;DR: TransRate is a tool for reference-free quality assessment of de novo transcriptome assemblies using only the sequenced reads and the assembly as input and it is revealed that variance in the quality of the input data explains 43% of the variance inThe quality of published de noVO transcriptome assembly assemblies.
Abstract: TransRate is a tool for reference-free quality assessment of de novo transcriptome assemblies Using only the sequenced reads and the assembly as input, we show that multiple common artifacts of de novo transcriptome assembly can be readily detected These include chimeras, structural errors, incomplete assembly, and base errors TransRate evaluates these errors to produce a diagnostic quality score for each contig, and these contig scores are integrated to evaluate whole assemblies Thus, TransRate can be used for de novo assembly filtering and optimization as well as comparison of assemblies generated using different methods from the same input reads Applying the method to a data set of 155 published de novo transcriptome assemblies, we deconstruct the contribution that assembly method, read length, read quantity, and read quality make to the accuracy of de novo transcriptome assemblies and reveal that variance in the quality of the input data explains 43% of the variance in the quality of published de novo transcriptome assemblies Because TransRate is reference-free, it is suitable for assessment of assemblies of all types of RNA, including assemblies of long noncoding RNA, rRNA, mRNA, and mixed RNA samples
TL;DR: In this article, the authors explored the drivers of residential, institutional, and commercial food waste generation in developed countries, particularly in the U.S., and examined the impacts of food system modernization on food waste, including impacts related to food system industrialization, urbanization, globalization, and economic growth.
Abstract: There has been growing interest in establishing food waste prevention and recovery programs throughout the world. The drive to target food waste stems from increasing concerns about resource conservation, food security, food waste's environmental and economic costs, and a general trend in the waste management industry to transition to more sustainable practices. Here the drivers of residential, institutional, and commercial food waste generation in developed countries, particularly in the U.S., are explored. The impacts of food system modernization on food waste generation are examined, including impacts related to food system industrialization, urbanization, globalization, and economic growth. Socio-demographic, cultural, political, and economic drivers of food waste are described with emphasis on how food waste perspectives may vary globally. Specific behaviors and attitudes which result from many of these waste drivers are then discussed. The examination of the range of food wastage drivers are used to provide insight into the best policy approaches to sustainably manage food waste. Food waste prevention policies are placed in context of the waste generating behaviors and attitudes that they address. A review of important background information on food waste is also provided, including definitions of key terms, food waste history, quantities of food waste generated, and the importance of food waste prevention for sustainability, as this information is all critical for effective policy development.
TL;DR: The data suggest that induction of NETs by cancer cells is a previously unidentified metastasis-promoting tumor-host interaction and a potential therapeutic target, and treatment with NET-digesting, DNase I–coated nanoparticles markedly reduced lung metastases in mice.
Abstract: Neutrophils, the most abundant type of leukocytes in blood, can form neutrophil extracellular traps (NETs). These are pathogen-trapping structures generated by expulsion of the neutrophil's DNA with associated proteolytic enzymes. NETs produced by infection can promote cancer metastasis. We show that metastatic breast cancer cells can induce neutrophils to form metastasis-supporting NETs in the absence of infection. Using intravital imaging, we observed NET-like structures around metastatic 4T1 cancer cells that had reached the lungs of mice. We also found NETs in clinical samples of triple-negative human breast cancer. The formation of NETs stimulated the invasion and migration of breast cancer cells in vitro. Inhibiting NET formation or digesting NETs with deoxyribonuclease I (DNase I) blocked these processes. Treatment with NET-digesting, DNase I-coated nanoparticles markedly reduced lung metastases in mice. Our data suggest that induction of NETs by cancer cells is a previously unidentified metastasis-promoting tumor-host interaction and a potential therapeutic target.
TL;DR: It is shown that cancer risk is heavily influenced by extrinsic factors, and the rates of endogenous mutation accumulation by intrinsic processes are not sufficient to account for the observed cancer risks.
Abstract: Recent research has highlighted a strong correlation between tissue-specific cancer risk and the lifetime number of tissue-specific stem-cell divisions. Whether such correlation implies a high unavoidable intrinsic cancer risk has become a key public health debate with the dissemination of the 'bad luck' hypothesis. Here we provide evidence that intrinsic risk factors contribute only modestly (less than ~10-30% of lifetime risk) to cancer development. First, we demonstrate that the correlation between stem-cell division and cancer risk does not distinguish between the effects of intrinsic and extrinsic factors. We then show that intrinsic risk is better estimated by the lower bound risk controlling for total stem-cell divisions. Finally, we show that the rates of endogenous mutation accumulation by intrinsic processes are not sufficient to account for the observed cancer risks. Collectively, we conclude that cancer risk is heavily influenced by extrinsic factors. These results are important for strategizing cancer prevention, research and public health.
TL;DR: In this paper, an isotropic, unbroken power-law flux with a normalization at 100 TeV neutrino energy of (0.90 -0.27 +0.30) × 10-18 Gev-1 cm-2 s-1 sr-1 and a hard spectral index of γ = 2.13 ± 0.13.
Abstract: The IceCube Collaboration has previously discovered a high-energy astrophysical neutrino flux using neutrino events with interaction vertices contained within the instrumented volume of the IceCube detector. We present a complementary measurement using charged current muon neutrino events where the interaction vertex can be outside this volume. As a consequence of the large muon range the effective area is significantly larger but the field of view is restricted to the Northern Hemisphere. IceCube data from 2009 through 2015 have been analyzed using a likelihood approach based on the reconstructed muon energy and zenith angle. At the highest neutrino energies between 194 TeV and 7.8 PeV a significant astrophysical contribution is observed, excluding a purely atmospheric origin of these events at 5.6s significance. The data are well described by an isotropic, unbroken power-law flux with a normalization at 100 TeV neutrino energy of (0.90 -0.27 +0.30) × 10-18 Gev-1 cm-2 s-1 sr-1and a hard spectral index of γ = 2.13 ± 0.13. The observed spectrum is harder in comparison to previous IceCube analyses with lower energy thresholds which may indicate a break in the astrophysical neutrino spectrum of unknown origin. The highest-energy event observed has a reconstructed muon energy of (4.5 ± 1.2) PeV which implies a probability of less than 0.005% for this event to be of atmospheric origin. Analyzing the arrival directions of all events with reconstructed muon energies above 200 TeV no correlation with known γ-ray sources was found. Using the high statistics of atmospheric neutrinos we report the current best constraints on a prompt atmospheric muon neutrino flux originating from charmed meson decays which is below 1.06 in units of the flux normalization of the model in Enberg et al.
California Institute of Technology1, National Radio Astronomy Observatory2, University of Paris3, INAF4, University of Texas at Austin5, Stony Brook University6, Centre national de la recherche scientifique7, University of Hawaii8, Institut d'Astrophysique de Paris9, University of Massachusetts Amherst10, University of Copenhagen11, University of Edinburgh12
TL;DR: In this paper, the authors used ALMA Cycle 2 observations of longwavelength dust emission in 145 star-forming galaxies to probe the evolution of the starforming interstellar medium (ISM) and developed a physical basis and empirical calibration for using the dust continuum as a quantitative probe of ISM masses.
Abstract: ALMA Cycle 2 observations of long-wavelength dust emission in 145 star-forming galaxies are used to probe the evolution of the star-forming interstellar medium (ISM). We also develop a physical basis and empirical calibration (with 72 low-z and z ~ 2 galaxies) for using the dust continuum as a quantitative probe of ISM masses. The galaxies with the highest star formation rates (SFRs) at = 2.2 and 4.4 have gas masses up to 100 times that of the Milky Way and gas mass fractions reaching 50%–80%, i.e., gas masses 1-4× their stellar masses. We find a single high-z star formation law: SFR = 35 M^(0.89)_(mol) x (1 + z)^(0.95)_(z=2) x (sSFR)^(0.23)_(MS)
M⊙yr^(−1)—an approximately linear dependence on the ISM mass and an increased star formation efficiency per unit gas mass at higher redshift. Galaxies above the main sequence (MS) have larger gas masses but are converting their ISM into stars on a timescale only slightly shorter than those on the MS; thus, these "starbursts" are largely the result of having greatly increased gas masses rather than an increased efficiency of converting gas to stars. At z > 1, the entire population of star-forming galaxies has ~2–5 times shorter gas depletion times than low-z galaxies. These shorter depletion times indicate a different mode of star formation in the early universe—most likely dynamically driven by compressive, high-dispersion gas motions—a natural consequence of the high gas accretion rates.
TL;DR: This Review attempts to identify areas of controversy, as well as consensus, on what is and is not yet known about how cholinergic signaling in the CNS contributes to normal cognitive processes, and delineates the findings from recent work on the extent to which Dysfunction of Cholinergic circuits contributes to cognitive decline associated with neurodegenerative disorders.
15 Oct 2016
TL;DR: This work finds that a previously unexplored dimension exists in the design space of CNN accelerators that focuses on the dataflow across convolutional layers, and is able to fuse the processing of multiple CNN layers by modifying the order in which the input data are brought on chip, enabling caching of intermediate data between the evaluation of adjacent CNN layers.
Abstract: Deep convolutional neural networks (CNNs) are rapidly becoming the dominant approach to computer vision and a major component of many other pervasive machine learning tasks, such as speech recognition, natural language processing, and fraud detection. As a result, accelerators for efficiently evaluating CNNs are rapidly growing in popularity. The conventional approaches to designing such CNN accelerators is to focus on creating accelerators to iteratively process the CNN layers. However, by processing each layer to completion, the accelerator designs must use off-chip memory to store intermediate data between layers, because the intermediate data are too large to fit on chip. In this work, we observe that a previously unexplored dimension exists in the design space of CNN accelerators that focuses on the dataflow across convolutional layers. We find that we are able to fuse the processing of multiple CNN layers by modifying the order in which the input data are brought on chip, enabling caching of intermediate data between the evaluation of adjacent CNN layers. We demonstrate the effectiveness of our approach by constructing a fused-layer CNN accelerator for the first five convolutional layers of the VGGNet-E network and comparing it to the state-of-the-art accelerator implemented on a Xilinx Virtex-7 FPGA. We find that, by using 362KB of on-chip storage, our fused-layer accelerator minimizes off-chip feature map data transfer, reducing the total transfer by 95%, from 77MB down to 3.6MB per image.
TL;DR: The importance of synergy between theory and experiments to elucidate the complex reaction mechanisms of CO2 hydrogenation for the realization of a better catalyst by design is demonstrated.
Abstract: Rational optimization of catalytic performance has been one of the major challenges in catalysis. Here we report a bottom-up study on the ability of TiO2 and ZrO2 to optimize the CO2 conversion to methanol on Cu, using combined density functional theory (DFT) calculations, kinetic Monte Carlo (KMC) simulations, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) measurements, and steady-state flow reactor tests. The theoretical results from DFT and KMC agree with in situ DRIFTS measurements, showing that both TiO2 and ZrO2 help to promote methanol synthesis on Cu via carboxyl intermediates and the reverse water–gas-shift (RWGS) pathway; the formate intermediates, on the other hand, likely act as a spectator eventually. The origin of the superior promoting effect of ZrO2 is associated with the fine-tuning capability of reduced Zr3+ at the interface, being able to bind the key reaction intermediates, e.g. *CO2, *CO, *HCO, and *H2CO, moderately to facilitate methanol formation. This ...
TL;DR: It is shown that viral infection of adult hippocampal neurons induces complement-mediated elimination of presynaptic terminals in a murine WNV neuroinvasive disease model, which provides a new murine model of WNV-induced spatial memory impairment, and identifies a potential mechanism underlying neurocognitive impairment in patients recovering from WNV Neuroinvasive Disease.
Abstract: Over 50% of patients who survive neuroinvasive infection with West Nile virus (WNV) exhibit chronic cognitive sequelae. Although thousands of cases of WNV-mediated memory dysfunction accrue annually, the mechanisms responsible for these impairments are unknown. The classical complement cascade, a key component of innate immune pathogen defence, mediates synaptic pruning by microglia during early postnatal development. Here we show that viral infection of adult hippocampal neurons induces complement-mediated elimination of presynaptic terminals in a murine WNV neuroinvasive disease model. Inoculation of WNV-NS5-E218A, a WNV with a mutant NS5(E218A) protein leads to survival rates and cognitive dysfunction that mirror human WNV neuroinvasive disease. WNV-NS5-E218A-recovered mice (recovery defined as survival after acute infection) display impaired spatial learning and persistence of phagocytic microglia without loss of hippocampal neurons or volume. Hippocampi from WNV-NS5-E218A-recovered mice with poor spatial learning show increased expression of genes that drive synaptic remodelling by microglia via complement. C1QA was upregulated and localized to microglia, infected neurons and presynaptic terminals during WNV neuroinvasive disease. Murine and human WNV neuroinvasive disease post-mortem samples exhibit loss of hippocampal CA3 presynaptic terminals, and murine studies revealed microglial engulfment of presynaptic terminals during acute infection and after recovery. Mice with fewer microglia (Il34(-/-) mice with a deficiency in IL-34 production) or deficiency in complement C3 or C3a receptor were protected from WNV-induced synaptic terminal loss. Our study provides a new murine model of WNV-induced spatial memory impairment, and identifies a potential mechanism underlying neurocognitive impairment in patients recovering from WNV neuroinvasive disease.
TL;DR: In this paper, the authors provide an elementary introduction into the physics of anomalous chiral effects, to describe the current status of experimental studies in heavy ion physics, and outline the future work, both in experiment and theory, needed to eliminate the existing uncertainties in the interpretation of the data.
TL;DR: It is reported that genetic loss or systemic knockdown of Malat1 using antisense oligonucleotides (ASOs) in the MMTV-PyMT- and Her2/neu-amplified tumor organoids model results in slower tumor growth accompanied by significant differentiation into cystic tumors and a reduction in metastasis.
Abstract: Genome-wide analyses have identified thousands of long noncoding RNAs (lncRNAs). Malat1 (metastasis-associated lung adenocarcinoma transcript 1) is among the most abundant lncRNAs whose expression is altered in numerous cancers. Here we report that genetic loss or systemic knockdown of Malat1 using antisense oligonucleotides (ASOs) in the MMTV (mouse mammary tumor virus)-PyMT mouse mammary carcinoma model results in slower tumor growth accompanied by significant differentiation into cystic tumors and a reduction in metastasis. Furthermore, Malat1 loss results in a reduction of branching morphogenesis in MMTV-PyMT- and Her2/neu-amplified tumor organoids, increased cell adhesion, and loss of migration. At the molecular level, Malat1 knockdown results in alterations in gene expression and changes in splicing patterns of genes involved in differentiation and protumorigenic signaling pathways. Together, these data demonstrate for the first time a functional role of Malat1 in regulating critical processes in mammary cancer pathogenesis. Thus, Malat1 represents an exciting therapeutic target, and Malat1 ASOs represent a potential therapy for inhibiting breast cancer progression.
University of New South Wales1, University of Adelaide2, Centre national de la recherche scientifique3, Spanish National Research Council4, University of Alabama at Birmingham5, University of Auckland6, University of Alabama7, University of North Carolina at Wilmington8, Charles Darwin University9, UPRRP College of Natural Sciences10, University of Oldenburg11, University of Haifa12, Ludwig Maximilian University of Munich13, University of Chicago14, Argonne National Laboratory15, University of California, San Diego16, Stony Brook University17, Leibniz Institute of Marine Sciences18, Australian Institute of Marine Science19
TL;DR: It is shown that sponges are a reservoir of exceptional microbial diversity and major contributors to the total microbial diversity of the world's oceans, and a model of independent assembly and evolution in symbiont communities across the entire host phylum is supported.
Abstract: Sponges (phylum Porifera) are early-diverging metazoa renowned for establishing complex microbial symbioses. Here we present a global Porifera microbiome survey, set out to establish the ecological and evolutionary drivers of these host-microbe interactions. We show that sponges are a reservoir of exceptional microbial diversity and major contributors to the total microbial diversity of the world's oceans. Little commonality in species composition or structure is evident across the phylum, although symbiont communities are characterized by specialists and generalists rather than opportunists. Core sponge microbiomes are stable and characterized by generalist symbionts exhibiting amensal and/or commensal interactions. Symbionts that are phylogenetically unique to sponges do not disproportionally contribute to the core microbiome, and host phylogeny impacts complexity rather than composition of the symbiont community. Our findings support a model of independent assembly and evolution in symbiont communities across the entire host phylum, with convergent forces resulting in analogous community organization and interactions.
TL;DR: This paper reviewed the concept of innovation ecosystems as it is set forth in the academic and trade literature, and asked, "What is gained from adding 'eco-' to our treatment of national and regional innovation systems?" The answer is, "Very little, and the risks outweigh the benefits".
TL;DR: In this article, the performance of the ATLAS muon identification and reconstruction using the first LHC dataset recorded at s√ = 13 TeV in 2015 was evaluated using the Monte Carlo simulations.
Abstract: This article documents the performance of the ATLAS muon identification and reconstruction using the first LHC dataset recorded at s√ = 13 TeV in 2015. Using a large sample of J/ψ→μμ and Z→μμ decays from 3.2 fb−1 of pp collision data, measurements of the reconstruction efficiency, as well as of the momentum scale and resolution, are presented and compared to Monte Carlo simulations. The reconstruction efficiency is measured to be close to 99% over most of the covered phase space (|η| 2.2, the pT resolution for muons from Z→μμ decays is 2.9% while the precision of the momentum scale for low-pT muons from J/ψ→μμ decays is about 0.2%.
TL;DR: A high-throughput computational screening of large databases of metal–organic frameworks is carried out and it is affirm that SBMOF-1 exhibits by far the highest reported xenon adsorption capacity and a remarkable Xe/Kr selectivity under conditions pertinent to nuclear fuel reprocessing.
Abstract: Nuclear energy is among the most viable alternatives to our current fossil fuel-based energy economy. The mass deployment of nuclear energy as a low-emissions source requires the reprocessing of used nuclear fuel to recover fissile materials and mitigate radioactive waste. A major concern with reprocessing used nuclear fuel is the release of volatile radionuclides such as xenon and krypton that evolve into reprocessing facility off-gas in parts per million concentrations. The existing technology to remove these radioactive noble gases is a costly cryogenic distillation; alternatively, porous materials such as metal-organic frameworks have demonstrated the ability to selectively adsorb xenon and krypton at ambient conditions. Here we carry out a high-throughput computational screening of large databases of metal-organic frameworks and identify SBMOF-1 as the most selective for xenon. We affirm this prediction and report that SBMOF-1 exhibits by far the highest reported xenon adsorption capacity and a remarkable Xe/Kr selectivity under conditions pertinent to nuclear fuel reprocessing.
University of Florida1, University of Minnesota2, University of Oklahoma3, United States Department of Agriculture4, Donald Danforth Plant Science Center5, Stony Brook University6, Eckerd College7, Purdue University8, Cold Spring Harbor Laboratory9, University of Rhode Island10, University of California, Berkeley11, Colorado State University12, University of California, Riverside13, University of California, Davis14, Boyce Thompson Institute for Plant Research15, Stanford University16, Iowa State University17, University of Missouri18, University of Tennessee19
TL;DR: The state of plant transformation is reviewed and innovations needed to enable genome editing in crops are pointed to, including a potential game-changer in crop genetics when plant transformation systems are optimized.
Abstract: Plant transformation has enabled fundamental insights into plant biology and revolutionized commercial agriculture. Unfortunately, for most crops, transformation and regeneration remain arduous even after more than thirty years of technological advances. Genome editing provides new opportunities to enhance crop productivity, but relies on genetic transformation and plant regeneration, which are bottlenecks in the process. Herein we review the state of plant transformation and point to innovations needed to enable genome editing in crops. Plant tissue culture methods need optimization and simplification for efficiency and minimize time in culture. Currently, specialized facilities exist for crop transformation. Single cell and robotic techniques should be developed for high throughput genomic screens. Utilization of plant genes involved in developmental reprogramming, wound response, and/or homologous recombination could boost recovery of transformed plants. Engineering universal Agrobacterium strains and recruitment of other microbes, such as Ensifer or Rhizobium, could facilitate delivery of DNA and proteins into plant cells. Synthetic biology should be employed for de novo design of transformation systems. Genome editing is a potential game-changer in crop genetics when plant transformation systems are optimized.
TL;DR: In this article, the authors consider the role of the equation of state in medium-energy heavy-ion collisions and examine thermal properties of dense matter, which are important for supernovae and neutron star mergers, but which cannot be nearly as well constrained by experiment.
University of Mainz1, University College London2, Swiss Institute of Bioinformatics3, University of Fribourg4, Trinity College, Dublin5, Aristotle University of Thessaloniki6, University of Sheffield7, Hellenic Ministry of Culture and Sports8, Democritus University of Thrace9, Stony Brook University10, Ege University11, Austrian Academy of Sciences12, University of Geneva13
TL;DR: This study demonstrates a direct genetic link between Mediterranean and Central European early farmers and those of Greece and Anatolia, extending the European Neolithic migratory chain all the way back to southwestern Asia.
Abstract: Farming and sedentism first appeared in southwestern Asia during the early Holocene and later spread to neighboring regions, including Europe, along multiple dispersal routes. Conspicuous uncertainties remain about the relative roles of migration, cultural diffusion, and admixture with local foragers in the early Neolithization of Europe. Here we present paleogenomic data for five Neolithic individuals from northern Greece and northwestern Turkey spanning the time and region of the earliest spread of farming into Europe. We use a novel approach to recalibrate raw reads and call genotypes from ancient DNA and observe striking genetic similarity both among Aegean early farmers and with those from across Europe. Our study demonstrates a direct genetic link between Mediterranean and Central European early farmers and those of Greece and Anatolia, extending the European Neolithic migratory chain all the way back to southwestern Asia.