Showing papers by "Tel Aviv University published in 2020"

The ATLAS Experiment at the CERN Large Hadron Collider

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.

Vaccine hesitancy: the next challenge in the fight against COVID-19.

Abstract: Vaccine hesitancy remains a barrier to full population inoculation against highly infectious diseases. Coincident with the rapid developments of COVID-19 vaccines globally, concerns about the safety of such a vaccine could contribute to vaccine hesitancy. We analyzed 1941 anonymous questionnaires completed by healthcare workers and members of the general Israeli population, regarding acceptance of a potential COVID-19 vaccine. Our results indicate that healthcare staff involved in the care of COVID-19 positive patients, and individuals considering themselves at risk of disease, were more likely to self-report acquiescence to COVID-19 vaccination if and when available. In contrast, parents, nurses, and medical workers not caring for SARS-CoV-2 positive patients expressed higher levels of vaccine hesitancy. Interventional educational campaigns targeted towards populations at risk of vaccine hesitancy are therefore urgently needed to combat misinformation and avoid low inoculation rates.

TRY plant trait database : Enhanced coverage and open access

Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

The human tumor microbiome is composed of tumor type–specific intracellular bacteria

Abstract: Bacteria were first detected in human tumors more than 100 years ago, but the characterization of the tumor microbiome has remained challenging because of its low biomass. We undertook a comprehensive analysis of the tumor microbiome, studying 1526 tumors and their adjacent normal tissues across seven cancer types, including breast, lung, ovary, pancreas, melanoma, bone, and brain tumors. We found that each tumor type has a distinct microbiome composition and that breast cancer has a particularly rich and diverse microbiome. The intratumor bacteria are mostly intracellular and are present in both cancer and immune cells. We also noted correlations between intratumor bacteria or their predicted functions with tumor types and subtypes, patients' smoking status, and the response to immunotherapy.

Angiotensin receptor blockers as tentative SARS-CoV-2 therapeutics.

Abstract: At the time of writing this commentary (February 2020), the coronavirus COVID-19 epidemic has already resulted in more fatalities compared with the SARS and MERS coronavirus epidemics combined. Therapeutics that may assist to contain its rapid spread and reduce its high mortality rates are urgently needed. Developing vaccines against the SARS-CoV-2 virus may take many months. Moreover, vaccines based on viral-encoded peptides may not be effective against future coronavirus epidemics, as virus mutations could make them futile. Indeed, new Influenza virus strains emerge every year, requiring new immunizations. A tentative suggestion based on existing therapeutics, which would likely be resistant to new coronavirus mutations, is to use available angiotensin receptor 1 (AT1R) blockers, such as losartan, as therapeutics for reducing the aggressiveness and mortality from SARS-CoV-2 virus infections. This idea is based on observations that the angiotensin-converting enzyme 2 (ACE2) very likely serves as the binding site for SARS-CoV-2, the strain implicated in the current COVID-19 epidemic, similarly to strain SARS-CoV implicated in the 2002-2003 SARS epidemic. This commentary elaborates on the idea of considering AT1R blockers as tentative treatment for SARS-CoV-2 infections, and proposes a research direction based on datamining of clinical patient records for assessing its feasibility.

Variability in the analysis of a single neuroimaging dataset by many teams

Abstract: Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

Abstract: We present a generic image-to-image translation framework, Pixel2Style2Pixel (pSp). Our pSp framework is based on a novel encoder network that directly generates a series of style vectors which are fed into a pretrained StyleGAN generator, forming the extended W+ latent space. We first show that our encoder can directly embed real images into W+, with no additional optimization. We further introduce a dedicated identity loss which is shown to achieve improved performance in the reconstruction of an input image. We demonstrate pSp to be a simple architecture that, by leveraging a well-trained, fixed generator network, can be easily applied on a wide-range of image-to-image translation tasks. Solving these tasks through the style representation results in a global approach that does not rely on a local pixel-to-pixel correspondence and further supports multi-modal synthesis via the resampling of styles. Notably, we demonstrate that pSp can be trained to align a face image to a frontal pose without any labeled data, generate multi-modal results for ambiguous tasks such as conditional face generation from segmentation maps, and construct high-resolution images from corresponding low-resolution images.

European Society Paediatric Gastroenterology, Hepatology and Nutrition Guidelines for Diagnosing Coeliac Disease 2020.

Abstract: OBJECTIVES The ESPGHAN 2012 coeliac disease (CD) diagnostic guidelines aimed to guide physicians in accurately diagnosing CD and permit omission of duodenal biopsies in selected cases. Here, an updated and expanded evidence-based guideline is presented. METHODS Literature databases and other sources of information were searched for studies that could inform on 10 formulated questions on symptoms, serology, HLA genetics, and histopathology. Eligible articles were assessed using QUADAS2. GRADE provided a basis for statements and recommendations. RESULTS Various symptoms are suggested for case finding, with limited contribution to diagnostic accuracy. If CD is suspected, measurement of total serum IgA and IgA-antibodies against transglutaminase 2 (TGA-IgA) is superior to other combinations. We recommend against deamidated gliadin peptide antibodies (DGP-IgG/IgA) for initial testing. Only if total IgA is low/undetectable, an IgG-based test is indicated. Patients with positive results should be referred to a paediatric gastroenterologist/specialist. If TGA-IgA is ≥10 times the upper limit of normal (10× ULN) and the family agrees, the no-biopsy diagnosis may be applied, provided endomysial antibodies (EMA-IgA) will test positive in a second blood sample. HLA DQ2-/DQ8 determination and symptoms are not obligatory criteria. In children with positive TGA-IgA <10× ULN at least 4 biopsies from the distal duodenum and at least 1 from the bulb should be taken. Discordant results between TGA-IgA and histopathology may require re-evaluation of biopsies. Patients with no/mild histological changes (Marsh 0/I) but confirmed autoimmunity (TGA-IgA/EMA-IgA+) should be followed closely. CONCLUSIONS CD diagnosis can be accurately established with or without duodenal biopsies if given recommendations are followed.

2019 update of EULAR recommendations for vaccination in adult patients with autoimmune inflammatory rheumatic diseases

Abstract: To update the European League Against Rheumatism (EULAR) recommendations for vaccination in adult patients with autoimmune inflammatory rheumatic diseases (AIIRD) published in 2011. Four systematic literature reviews were performed regarding the incidence/prevalence of vaccine-preventable infections among patients with AIIRD; efficacy, immunogenicity and safety of vaccines; effect of anti-rheumatic drugs on the response to vaccines; effect of vaccination of household of AIIRDs patients. Subsequently, recommendations were formulated based on the evidence and expert opinion. The updated recommendations comprise six overarching principles and nine recommendations. The former address the need for an annual vaccination status assessment, shared decision-making and timing of vaccination, favouring vaccination during quiescent disease, preferably prior to the initiation of immunosuppression. Non-live vaccines can be safely provided to AIIRD patients regardless of underlying therapy, whereas live-attenuated vaccines may be considered with caution. Influenza and pneumococcal vaccination should be strongly considered for the majority of patients with AIIRD. Tetanus toxoid and human papilloma virus vaccination should be provided to AIIRD patients as recommended for the general population. Hepatitis A, hepatitis B and herpes zoster vaccination should be administered to AIIRD patients at risk. Immunocompetent household members of patients with AIIRD should receive vaccines according to national guidelines, except for the oral poliomyelitis vaccine. Live-attenuated vaccines should be avoided during the first 6 months of life in newborns of mothers treated with biologics during the second half of pregnancy. These 2019 EULAR recommendations provide an up-to-date guidance on the management of vaccinations in patients with AIIRD.

Multiple wheat genomes reveal global variation in modern breeding.

Abstract: Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome1, and the lack of genome-assembly data for multiple wheat lines2,3. Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses4,5. We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm16, a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.

Fear of COVID-19 scale: Psychometric characteristics, reliability and validity in the Israeli population.

Abstract: Mental health clinicians worldwide have been expressing concerns regarding the broad psychological effects of the COVID-19 pandemic. Nonetheless, only a few studies have thus far evaluated the degree of fear of COVID-19, partially due to the lack of validated measures. In this study we evaluated the psychometric properties of the Hebrew version of the Fear of COVID-19 scale (FCV-19S), recently developed to assess different aspects of the fear of the pandemic, in a normative population of participants in Israel. Participants (n = 639) were asked to complete the FCV-19S scale, as well as to report anxiety, depression, and stress levels using validated scales. The results a unidimensional factor structure of the FCV-19S which explained 53.71% of the variance. When forcing a two-factor structure model, the analysis revealed two factors pertaining to emotional fear reactions and symptomatic expressions of fear. Gender, sociodemographic status, chronic illness, being in an at-risk group, and having a family member dying of COVID-19 were positively associated with fear of COVID-19. The measure was associated with anxiety, stress and depression. These results suggest that the FCV-19S has good psychometric properties, and can be utilized in studies assessing the effects of the pandemic on the population's mental health.

TaPas: Weakly Supervised Table Parsing via Pre-training

Abstract: Answering natural language questions over tables is usually seen as a semantic parsing task. To alleviate the collection cost of full logical forms, one popular approach focuses on weak supervision consisting of denotations instead of logical forms. However, training semantic parsers from weak supervision poses difficulties, and in addition, the generated logical forms are only used as an intermediate step prior to retrieving the denotation. In this paper, we present TaPas, an approach to question answering over tables without generating logical forms. TaPas trains from weak supervision, and predicts the denotation by selecting table cells and optionally applying a corresponding aggregation operator to such selection. TaPas extends BERT’s architecture to encode tables as input, initializes from an effective joint pre-training of text segments and tables crawled from Wikipedia, and is trained end-to-end. We experiment with three different semantic parsing datasets, and find that TaPas outperforms or rivals semantic parsing models by improving state-of-the-art accuracy on SQA from 55.1 to 67.2 and performing on par with the state-of-the-art on WikiSQL and WikiTQ, but with a simpler model architecture. We additionally find that transfer learning, which is trivial in our setting, from WikiSQL to WikiTQ, yields 48.7 accuracy, 4.2 points above the state-of-the-art.

Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling.

Abstract: Anti-cancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM, a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features. Our findings include compounds that killed by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, which killed via the multi-drug resistance protein ABCB1. The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.

Context is everything: aneuploidy in cancer

Abstract: Cancer is driven by multiple types of genetic alterations, which range in size from point mutations to whole-chromosome gains and losses, known as aneuploidy. Chromosome instability, the process that gives rise to aneuploidy, can promote tumorigenesis by increasing genetic heterogeneity and promoting tumour evolution. However, much less is known about how aneuploidy itself contributes to tumour formation and progression. Unlike some pan-cancer oncogenes and tumour suppressor genes that drive transformation in virtually all cell types and cellular contexts, aneuploidy is not a universal promoter of tumorigenesis. Instead, recent studies suggest that aneuploidy is a context-dependent, cancer-type-specific oncogenic event that may have clinical relevance as a prognostic marker and as a potential therapeutic target. Aneuploidy contributes to tumorigenesis, but the underlying processes are not well understood. This Review explains the context dependency of aneuploidy in cancer and discusses its clinical potential as a prognostic marker and a therapeutic target.

Artificial intelligence in COVID-19 drug repurposing.

Abstract: Drug repurposing or repositioning is a technique whereby existing drugs are used to treat emerging and challenging diseases, including COVID-19. Drug repurposing has become a promising approach because of the opportunity for reduced development timelines and overall costs. In the big data era, artificial intelligence (AI) and network medicine offer cutting-edge application of information science to defining disease, medicine, therapeutics, and identifying targets with the least error. In this Review, we introduce guidelines on how to use AI for accelerating drug repurposing or repositioning, for which AI approaches are not just formidable but are also necessary. We discuss how to use AI models in precision medicine, and as an example, how AI models can accelerate COVID-19 drug repurposing. Rapidly developing, powerful, and innovative AI and network medicine technologies can expedite therapeutic development. This Review provides a strong rationale for using AI-based assistive tools for drug repurposing medications for human disease, including during the COVID-19 pandemic.

Low plasma 25(OH) vitamin D level is associated with increased risk of COVID-19 infection: an Israeli population-based study.

Abstract: Vitamin D deficiency is a worldwide pandemic. The aim of this study was to evaluate associations of plasma 25(OH)D levels with the likelihood of coronavirus disease 2019 (COVID-19) infection and hospitalization. The study population included the 14 000 members of Leumit Health Services, who were tested for COVID-19 infection from February 1st to April 30th , 2020, and who had at least one previous blood test for the plasma 25(OH)D level. 'Suboptimal' or 'low' plasma 25(OH)D level was defined as plasma 25-hydroxyvitamin D, or 25(OH)D, concentration below the level of 30 ng/mL. Of 7807 individuals, 782 (10.02%) were COVID-19-positive, and 7025 (89.98%) COVID-19-negative. The mean plasma vitamin D level was significantly lower among those who tested positive than negative for COVID-19 [19.00 ng/mL1 (95% confidence interval (CI) 18.41-19.59) vs. 20.55 (95% CI: 20.32-20.78)]. Univariate analysis demonstrated an association between the low plasma 25(OH)D level and increased likelihood of COVID-19 infection [crude odds ratio (OR) of 1.58 (95% CI: 1.24-2.01, P < 0.001)], and of hospitalization due to the SARS-CoV-2 virus [crude OR of 2.09 (95% CI: 1.01-4.30, P < 0.05)]. In multivariate analyses that controlled for demographic variables, and psychiatric and somatic disorders, the adjusted OR of COVID-19 infection [1.45 (95% CI: 1.08-1.95, P < 0.001)] and of hospitalization due to the SARS-CoV-2 virus [1.95 (95% CI: 0.98-4.845, P = 0.061)] were preserved. In the multivariate analyses, age over 50 years, male gender and low-medium socioeconomic status were also positively associated with the risk of COVID-19 infection; age over 50 years was positively associated with the likelihood of hospitalization due to COVID-19. We concluded that low plasma 25(OH)D levels appear to be an independent risk factor for COVID-19 infection and hospitalization.

Drug resistance and tolerance in fungi.

Abstract: Systemic fungal infections pose a serious clinical problem. Treatment options are limited, and antifungal drug resistance is increasing. In addition, a substantial proportion of patients do not respond to therapy despite being infected with fungi that are susceptible to the drug. The discordance between overall treatment outcome and low levels of clinical resistance may be attributable to antifungal drug tolerance. In this Review, we define and distinguish resistance and tolerance and discuss the current understanding of the molecular, genetic and physiological mechanisms that contribute to those phenomena. Distinguishing tolerance from resistance might provide important insights into the reasons for treatment failure in some settings. In this Review, Berman and Krysan define and distinguish resistance and tolerance, and discuss the current understanding of the molecular, genetic and physiological mechanisms that contribute to those phenomena. Distinguishing tolerance from resistance might provide important insights into the reasons for treatment failure in some settings.

Search for electroweak production of charginos and sleptons decaying into final states with two leptons and missing transverse momentum in √s = 13 TeV pp collisions using the ATLAS detector

Abstract: A search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented. The analysis is based on 139 fb$^{-1}$ of proton–proton collisions recorded by the ATLAS detector at the Large Hadron Collider at $\sqrt{s}=13$ $\text {TeV}$. Three R-parity-conserving scenarios where the lightest neutralino is the lightest supersymmetric particle are considered: the production of chargino pairs with decays via either W bosons or sleptons, and the direct production of slepton pairs. The analysis is optimised for the first of these scenarios, but the results are also interpreted in the others. No significant deviations from the Standard Model expectations are observed and limits at 95% confidence level are set on the masses of relevant supersymmetric particles in each of the scenarios. For a massless lightest neutralino, masses up to 420 $\text {Ge}\text {V}$ are excluded for the production of the lightest-chargino pairs assuming W-boson-mediated decays and up to 1 $\text {TeV}$ for slepton-mediated decays, whereas for slepton-pair production masses up to 700 $\text {Ge}\text {V}$ are excluded assuming three generations of mass-degenerate sleptons.

SENSEI: Direct-Detection Results on sub-GeV Dark Matter from a New Skipper CCD.

Abstract: We present the first direct-detection search for eV-to-GeV dark matter using a new ~2-gram high-resistivity Skipper-CCD from a dedicated fabrication batch that was optimized for dark-matter searches. Using 24 days of data acquired in the MINOS cavern at the Fermi National Accelerator Laboratory, we measure the lowest rates in silicon detectors of events containing one, two, three, or four electrons, and achieve world-leading sensitivity for a large range of sub-GeV dark matter masses. Data taken with different thicknesses of the detector shield suggest a correlation between the rate of high-energy tracks and the rate of single-electron events previously classified as "dark current." We detail key characteristics of the new Skipper-CCDs, which augur well for the planned construction of the ~100-gram SENSEI experiment at SNOLAB.

Immune-mediated approaches against COVID-19.

Abstract: The coronavirus disease-19 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The long incubation period of this new virus, which is mostly asymptomatic yet contagious, is a key reason for its rapid spread across the world. Currently, there is no worldwide-approved treatment for COVID-19. Therefore, the clinical and scientific communities have joint efforts to reduce the severe impact of the outbreak. Research on previous emerging infectious diseases have created valuable knowledge that is being exploited for drug repurposing and accelerated vaccine development. Nevertheless, it is important to generate knowledge on SARS-CoV-2 mechanisms of infection and its impact on host immunity, to guide the design of COVID-19 specific therapeutics and vaccines suitable for mass immunization. Nanoscale delivery systems are expected to play a paramount role in the success of these prophylactic and therapeutic approaches. This Review provides an overview of SARS-CoV-2 pathogenesis and examines immune-mediated approaches currently explored for COVID-19 treatments, with an emphasis on nanotechnological tools.

Simulating Lattice Gauge Theories within Quantum Technologies

Abstract: Lattice gauge theories, which originated from particle physics in the context of Quantum Chromodynamics (QCD), provide an important intellectual stimulus to further develop quantum information technologies. While one long-term goal is the reliable quantum simulation of currently intractable aspects of QCD itself, lattice gauge theories also play an important role in condensed matter physics and in quantum information science. In this way, lattice gauge theories provide both motivation and a framework for interdisciplinary research towards the development of special purpose digital and analog quantum simulators, and ultimately of scalable universal quantum computers. In this manuscript, recent results and new tools from a quantum science approach to study lattice gauge theories are reviewed. Two new complementary approaches are discussed: first, tensor network methods are presented – a classical simulation approach – applied to the study of lattice gauge theories together with some results on Abelian and non-Abelian lattice gauge theories. Then, recent proposals for the implementation of lattice gauge theory quantum simulators in different quantum hardware are reported, e.g., trapped ions, Rydberg atoms, and superconducting circuits. Finally, the first proof-of-principle trapped ions experimental quantum simulations of the Schwinger model are reviewed.