Showing papers by "Jagiellonian University published in 2017"
Theo Vos1, Amanuel Alemu Abajobir, Kalkidan Hassen Abate2, Cristiana Abbafati3 +775 more•Institutions (305)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
10,401 citations
Valery L. Feigin1, Amanuel Alemu Abajobir2, Kalkidan Hassen Abate3, Foad Abd-Allah4 +267 more•Institutions (138)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors (GBD) study provides such information but does not routinely aggregate results that are of interest to clinicians specialising in neurological conditions as discussed by the authors.
Abstract: Summary Background Comparable data on the global and country-specific burden of neurological disorders and their trends are crucial for health-care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study provides such information but does not routinely aggregate results that are of interest to clinicians specialising in neurological conditions. In this systematic analysis, we quantified the global disease burden due to neurological disorders in 2015 and its relationship with country development level. Methods We estimated global and country-specific prevalence, mortality, disability-adjusted life-years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) for various neurological disorders that in the GBD classification have been previously spread across multiple disease groupings. The more inclusive grouping of neurological disorders included stroke, meningitis, encephalitis, tetanus, Alzheimer's disease and other dementias, Parkinson's disease, epilepsy, multiple sclerosis, motor neuron disease, migraine, tension-type headache, medication overuse headache, brain and nervous system cancers, and a residual category of other neurological disorders. We also analysed results based on the Socio-demographic Index (SDI), a compound measure of income per capita, education, and fertility, to identify patterns associated with development and how countries fare against expected outcomes relative to their level of development. Findings Neurological disorders ranked as the leading cause group of DALYs in 2015 (250·7 [95% uncertainty interval (UI) 229·1 to 274·7] million, comprising 10·2% of global DALYs) and the second-leading cause group of deaths (9·4 [9·1 to 9·7] million], comprising 16·8% of global deaths). The most prevalent neurological disorders were tension-type headache (1505·9 [UI 1337·3 to 1681·6 million cases]), migraine (958·8 [872·1 to 1055·6] million), medication overuse headache (58·5 [50·8 to 67·4 million]), and Alzheimer's disease and other dementias (46·0 [40·2 to 52·7 million]). Between 1990 and 2015, the number of deaths from neurological disorders increased by 36·7%, and the number of DALYs by 7·4%. These increases occurred despite decreases in age-standardised rates of death and DALYs of 26·1% and 29·7%, respectively; stroke and communicable neurological disorders were responsible for most of these decreases. Communicable neurological disorders were the largest cause of DALYs in countries with low SDI. Stroke rates were highest at middle levels of SDI and lowest at the highest SDI. Most of the changes in DALY rates of neurological disorders with development were driven by changes in YLLs. Interpretation Neurological disorders are an important cause of disability and death worldwide. Globally, the burden of neurological disorders has increased substantially over the past 25 years because of expanding population numbers and ageing, despite substantial decreases in mortality rates from stroke and communicable neurological disorders. The number of patients who will need care by clinicians with expertise in neurological conditions will continue to grow in coming decades. Policy makers and health-care providers should be aware of these trends to provide adequate services. Funding Bill & Melinda Gates Foundation.
2,995 citations
Population Health Research Institute1, Centra2, Charles University in Prague3, University of Washington Medical Center4, Brigham and Women's Hospital5, National University of Ireland, Galway6, University College London7, Jagiellonian University8, University of Würzburg9, Semmelweis University10, Karolinska Institutet11, University of the Philippines12, University of La Frontera13, University of Cape Town14, Aalborg University15, Katholieke Universiteit Leuven16, Catholic University of Korea17, Monash University18, Universiti Teknologi MARA19, Paris Diderot University20
TL;DR: Among patients with stable atherosclerotic vascular disease, those assigned to rivaroxaban (2.5 mg twice daily) plus aspirin had better cardiovascular outcomes and more major bleeding events than those assign to aspirin alone.
Abstract: BackgroundWe evaluated whether rivaroxaban alone or in combination with aspirin would be more effective than aspirin alone for secondary cardiovascular prevention. MethodsIn this double-blind trial, we randomly assigned 27,395 participants with stable atherosclerotic vascular disease to receive rivaroxaban (2.5 mg twice daily) plus aspirin (100 mg once daily), rivaroxaban (5 mg twice daily), or aspirin (100 mg once daily). The primary outcome was a composite of cardiovascular death, stroke, or myocardial infarction. The study was stopped for superiority of the rivaroxaban-plus-aspirin group after a mean follow-up of 23 months. ResultsThe primary outcome occurred in fewer patients in the rivaroxaban-plus-aspirin group than in the aspirin-alone group (379 patients [4.1%] vs. 496 patients [5.4%]; hazard ratio, 0.76; 95% confidence interval [CI], 0.66 to 0.86; P<0.001; z=−4.126), but major bleeding events occurred in more patients in the rivaroxaban-plus-aspirin group (288 patients [3.1%] vs. 170 patients [1....
1,587 citations
TL;DR: The number of adults with raised blood pressure increased from 594 million in 1975 to 1·13 billion in 2015, with the increase largely in low-income and middle-income countries, and the contributions of changes in prevalence versus population growth and ageing to the increase.
1,573 citations
TL;DR: Broad-spectrum antiviral GS-5734 inhibits both epidemic and zoonotic coronaviruses in vitro and in vivo and may prove effective against endemic MERS-CoV in the Middle East, circulating human CoV, and, possibly most importantly, emerging CoV of the future.
Abstract: Emerging viral infections are difficult to control because heterogeneous members periodically cycle in and out of humans and zoonotic hosts, complicating the development of specific antiviral therapies and vaccines. Coronaviruses (CoVs) have a proclivity to spread rapidly into new host species causing severe disease. Severe acute respiratory syndrome CoV (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV) successively emerged, causing severe epidemic respiratory disease in immunologically naive human populations throughout the globe. Broad-spectrum therapies capable of inhibiting CoV infections would address an immediate unmet medical need and could be invaluable in the treatment of emerging and endemic CoV infections. We show that a nucleotide prodrug, GS-5734, currently in clinical development for treatment of Ebola virus disease, can inhibit SARS-CoV and MERS-CoV replication in multiple in vitro systems, including primary human airway epithelial cell cultures with submicromolar IC50 values. GS-5734 was also effective against bat CoVs, prepandemic bat CoVs, and circulating contemporary human CoV in primary human lung cells, thus demonstrating broad-spectrum anti-CoV activity. In a mouse model of SARS-CoV pathogenesis, prophylactic and early therapeutic administration of GS-5734 significantly reduced lung viral load and improved clinical signs of disease as well as respiratory function. These data provide substantive evidence that GS-5734 may prove effective against endemic MERS-CoV in the Middle East, circulating human CoV, and, possibly most importantly, emerging CoV of the future.
1,274 citations
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TL;DR: This work introduces a Sparsely-Gated Mixture-of-Experts layer (MoE), consisting of up to thousands of feed-forward sub-networks, and applies the MoE to the tasks of language modeling and machine translation, where model capacity is critical for absorbing the vast quantities of knowledge available in the training corpora.
Abstract: The capacity of a neural network to absorb information is limited by its number of parameters. Conditional computation, where parts of the network are active on a per-example basis, has been proposed in theory as a way of dramatically increasing model capacity without a proportional increase in computation. In practice, however, there are significant algorithmic and performance challenges. In this work, we address these challenges and finally realize the promise of conditional computation, achieving greater than 1000x improvements in model capacity with only minor losses in computational efficiency on modern GPU clusters. We introduce a Sparsely-Gated Mixture-of-Experts layer (MoE), consisting of up to thousands of feed-forward sub-networks. A trainable gating network determines a sparse combination of these experts to use for each example. We apply the MoE to the tasks of language modeling and machine translation, where model capacity is critical for absorbing the vast quantities of knowledge available in the training corpora. We present model architectures in which a MoE with up to 137 billion parameters is applied convolutionally between stacked LSTM layers. On large language modeling and machine translation benchmarks, these models achieve significantly better results than state-of-the-art at lower computational cost.
1,187 citations
Proceedings Article•
06 Aug 2017
TL;DR: The analysis suggests that the notions of effective capacity which are dataset independent are unlikely to explain the generalization performance of deep networks when trained with gradient based methods because training data itself plays an important role in determining the degree of memorization.
Abstract: We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness. While deep networks are capable of memorizing noise data, our results suggest that they tend to prioritize learning simple patterns first. In our experiments, we expose qualitative differences in gradient-based optimization of deep neural networks (DNNs) on noise vs. real data. We also demonstrate that for appropriately tuned explicit regularization (e.g., dropout) we can degrade DNN training performance on noise datasets without compromising generalization on real data. Our analysis suggests that the notions of effective capacity which are dataset independent are unlikely to explain the generalization performance of deep networks when trained with gradient based methods because training data itself plays an important role in determining the degree of memorization.
1,080 citations
TL;DR: This paper serves as a comprehensive review, where for selected 14 carbohydrates in the solid state both FT-Raman and ATR FT-IR spectra were collected and assigned and marker bands of the studied molecules can be identified and correlated with their structure.
573 citations
TL;DR: This paper presents a short overview of the changes to the trigger and data acquisition systems during the first long shutdown of the LHC and shows the performance of the trigger system and its components based on the 2015 proton–proton collision data.
Abstract: During 2015 the ATLAS experiment recorded 3.8 fb(-1) of proton-proton collision data at a centre-of-mass energy of 13 TeV. The ATLAS trigger system is a crucial component of the experiment, respons ...
488 citations
University of British Columbia1, Jagiellonian University2, Memorial Sloan Kettering Cancer Center3, Mayo Clinic4, Sungkyunkwan University5, University of Debrecen6, University of Naples Federico II7, University of Texas MD Anderson Cancer Center8, Rutgers University9, Washington University in St. Louis10, Curie Institute11, City of Hope National Medical Center12, University of Bologna13, The Royal Marsden NHS Foundation Trust14, Seattle Genetics15, Takeda Pharmaceutical Company16, University of Manchester17
TL;DR: A+AVD had superior efficacy to ABVD in the treatment of patients with advanced‐stage Hodgkin's lymphoma, with a 4.9 percentage‐point lower combined risk of progression, death, or noncomplete response and use of subsequent anticancer therapy at 2 years.
Abstract: Background Brentuximab vedotin is an anti-CD30 antibody–drug conjugate that has been approved for relapsed and refractory Hodgkin’s lymphoma. Methods We conducted an open-label, multicenter, randomized phase 3 trial involving patients with previously untreated stage III or IV classic Hodgkin’s lymphoma, in which 664 were assigned to receive brentuximab vedotin, doxorubicin, vinblastine, and dacarbazine (A+AVD) and 670 were assigned to receive doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD). The primary end point was modified progression-free survival (the time to progression, death, or noncomplete response and use of subsequent anticancer therapy) as adjudicated by an independent review committee. The key secondary end point was overall survival. Results At a median follow-up of 24.6 months, 2-year modified progression-free survival rates in the A+AVD and ABVD groups were 82.1% (95% confidence interval [CI], 78.8 to 85.0) and 77.2% (95% CI, 73.7 to 80.4), respectively, a difference of...
479 citations
TL;DR: Considering the above issues, age‐related accumulation of neuromelanin in dopamine neurons shows an interesting link between aging and neurodegeneration.
Leiden University1, University of Edinburgh2, University of Hertfordshire3, ASTRON4, Commonwealth Scientific and Industrial Research Organisation5, Max Planck Society6, University of Sydney7, University of Hamburg8, Rhodes University9, Paris Diderot University10, Harvard University11, INAF12, Jagiellonian University13, Chalmers University of Technology14, Radboud University Nijmegen15, University of Manchester16, University of Oxford17, University of the Western Cape18, Kapteyn Astronomical Institute19, Open University20, Rutherford Appleton Laboratory21, University of Amsterdam22, Joint Institute for VLBI in Europe23, University of Orléans24, Centre national de la recherche scientifique25, Ruhr University Bochum26, University of Southampton27, Institute of Cosmology and Gravitation, University of Portsmouth28, University of Western Australia29, University of Oulu30, Tata Institute of Fundamental Research31, Bielefeld University32, Leibniz Institute for Astrophysics Potsdam33, European Southern Observatory34, University of Cape Town35
TL;DR: The LOFAR Two-metre Sky Survey (LoTSS) as mentioned in this paper is a deep 120-168 MHz imaging survey that will eventually cover the entire northern sky, where each of the 3170 pointings will be observed for 8 h, which, at most declinations, is sufficient to produce ~5? resolution images with a sensitivity of ~100?Jy/beam and accomplish the main scientific aims of the survey, which are to explore the formation and evolution of massive black holes, galaxies, clusters of galaxies and large-scale structure.
Abstract: The LOFAR Two-metre Sky Survey (LoTSS) is a deep 120-168 MHz imaging survey that will eventually cover the entire northern sky. Each of the 3170 pointings will be observed for 8 h, which, at most declinations, is sufficient to produce ~5? resolution images with a sensitivity of ~100 ?Jy/beam and accomplish the main scientific aims of the survey, which are to explore the formation and evolution of massive black holes, galaxies, clusters of galaxies and large-scale structure. Owing to the compact core and long baselines of LOFAR, the images provide excellent sensitivity to both highly extended and compact emission. For legacy value, the data are archived at high spectral and time resolution to facilitate subarcsecond imaging and spectral line studies. In this paper we provide an overview of the LoTSS. We outline the survey strategy, the observational status, the current calibration techniques, a preliminary data release, and the anticipated scientific impact. The preliminary images that we have released were created using a fully automated but direction-independent calibration strategy and are significantly more sensitive than those produced by any existing large-Area low-frequency survey. In excess of 44 000 sources are detected in the images that have a resolution of 25?, typical noise levels of less than 0.5 mJy/beam, and cover an area of over 350 square degrees in the region of the HETDEX Spring Field (right ascension 10h45m00s to 15h30m00s and declination 45°00?00? to 57°00?00?).
TL;DR: Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS and is exploited to apply a local energy calibration and corrections depending on the nature of the cluster.
Abstract: The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.
TL;DR: In this paper, the authors use the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015.
TL;DR: Together, these data demonstrate, for the first time in an in vivo model of infection, a dynamic NET-platelet-thrombin axis that promotes intravascular coagulation and microvascular dysfunction in sepsis.
TL;DR: This paper investigates how particular choices of loss functions affect deep models and their learning dynamics, as well as resulting classifiers robustness to various effects, and shows that L1 and L2 losses are justified classification objectives for deep nets, by providing probabilistic interpretation in terms of expected misclassification.
Abstract: Deep neural networks are currently among the most commonly used classifiers. Despite easily achieving very good performance, one of the best selling points of these models is their modular design – one can conveniently adapt their architecture to specific needs, change connectivity patterns, attach specialised layers, experiment with a large amount of activation functions, normalisation schemes and many others. While one can find impressively wide spread of various configurations of almost every aspect of the deep nets, one element is, in authors’ opinion, underrepresented – while solving classification problems, vast majority of papers and applications simply use log loss. In this paper we try to investigate how particular choices of loss functions affect deep models and their learning dynamics, as well as resulting classifiers robustness to various effects. We perform experiments on classical datasets, as well as provide some additional, theoretical insights into the problem. In particular we show that L1 and L2 losses are, quite surprisingly, justified classification objectives for deep nets, by providing probabilistic interpretation in terms of expected misclassification. We also introduce two losses which are not typically used as deep nets objectives and show that they are viable alternatives to the existing ones.
Keywords: loss function, deep learning, classification theory
Warsaw University of Life Sciences1, University of Florence2, University of Ferrara3, Sofia University4, Northwest A&F University5, Department of Biotechnology6, Central University of Jharkhand7, Polytechnic University of Valencia8, Indian Council of Agricultural Research9, National University of La Plata10, Slovak University of Agriculture11, University of Silesia in Katowice12, Jagiellonian University13
TL;DR: Questions about instruments, methods and applications based on chlorophyll a fluorescence, and the answers draw on knowledge from different Chl a Fluorescence analysis domains, yielding in several cases new insights.
Abstract: Using chlorophyll (Chl) a fluorescence many aspects of the photosynthetic apparatus can be studied, both in vitro and, noninvasively, in vivo. Complementary techniques can help to interpret changes in the Chl a fluorescence kinetics. Kalaji et al. (Photosynth Res 122:121–158, 2014a) addressed several questions about instruments, methods and applications based on Chl a fluorescence. Here, additional Chl a fluorescence-related topics are discussed again in a question and answer format. Examples are the effect of connectivity on photochemical quenching, the correction of F
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/F
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values for PSI fluorescence, the energy partitioning concept, the interpretation of the complementary area, probing the donor side of PSII, the assignment of bands of 77 K fluorescence emission spectra to fluorescence emitters, the relationship between prompt and delayed fluorescence, potential problems when sampling tree canopies, the use of fluorescence parameters in QTL studies, the use of Chl a fluorescence in biosensor applications and the application of neural network approaches for the analysis of fluorescence measurements. The answers draw on knowledge from different Chl a fluorescence analysis domains, yielding in several cases new insights.
TL;DR: In this article, a search for new resonant and non-resonant high-mass phenomena in dielectron and dimuon fi nal states was conducted using 36 : 1 fb(-1) of proton-proton collision data.
Abstract: A search is conducted for new resonant and non-resonant high-mass phenomena in dielectron and dimuon fi nal states. The search uses 36 : 1 fb(-1) of proton-proton collision data, collected at root ...
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TL;DR: The authors examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness, showing that deep networks tend to prioritize learning simple patterns first.
Abstract: We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness. While deep networks are capable of memorizing noise data, our results suggest that they tend to prioritize learning simple patterns first. In our experiments, we expose qualitative differences in gradient-based optimization of deep neural networks (DNNs) on noise vs. real data. We also demonstrate that for appropriately tuned explicit regularization (e.g., dropout) we can degrade DNN training performance on noise datasets without compromising generalization on real data. Our analysis suggests that the notions of effective capacity which are dataset independent are unlikely to explain the generalization performance of deep networks when trained with gradient based methods because training data itself plays an important role in determining the degree of memorization.
TL;DR: The Third catalog of Hard Fermi-LAT Sources (3FHL) as mentioned in this paper contains 1556 objects characterized in the 10 GeV-2 TeV energy range.
Abstract: We present a catalog of sources detected above 10 GeV by the Fermi Large Area Telescope (LAT) in the first 7 years of data using the Pass 8 event-level analysis. This is the Third Catalog of Hard Fermi-LAT Sources (3FHL), containing 1556 objects characterized in the 10 GeV–2 TeV energy range. The sensitivity and angular resolution are improved by factors of 3 and 2 relative to the previous LAT catalog at the same energies (1FHL). The vast majority of detected sources (79%) are associated with extragalactic counterparts at other wavelengths, including 16 sources located at very high redshift (z > 2). Eight percent of the sources have Galactic counterparts and 13% are unassociated (or associated with a source of unknown nature). The high-latitude sky and the Galactic plane are observed with a flux sensitivity of 4.4 to 9.5 ×10 −11 ph cm −2 s −1 , respectively (this is approximately 0.5 % and 1 % of the Crab Nebula flux above 10 GeV). The catalog includes 214 new γ-ray sources. The substantial increase in the number of photons (more than 4 times relative to 1FHL and 10 times to 2FHL) also allows us to measure significant spectral curvature for 32 sources and find flux variability for 163 of them. Furthermore, we estimate that for the same flux limit of 10 −12 erg cm −2 s −1 , the energy range above 10 GeV has twice as many sources as above 50 GeV, highlighting the importance, for future Cherenkov telescopes, of lowering the energy threshold as much as possible.
University College London1, Imperial College London2, University of Oxford3, Clinical Trial Service Unit4, St Bartholomew's Hospital5, Wellcome Trust Centre for Human Genetics6, University of Glasgow7, Universidade Federal de Pelotas8, UCL Institute of Child Health9, University of South Australia10, European Bioinformatics Institute11, Charité12, University of Lübeck13, Max Planck Society14, Innsbruck Medical University15, Bradford Royal Infirmary16, University of Bristol17, St George's, University of London18, University of Edinburgh19, University of Lausanne20, University of Nicosia21, Cyprus University of Technology22, Utrecht University23, University of Turin24, Cancer Epidemiology Unit25, University of Cambridge26, Russian Academy27, Jagiellonian University28, Lithuanian University of Health Sciences29, University of Copenhagen30, Marshfield Clinic31, Children's Hospital of Philadelphia32, Group Health Research Institute33, Mayo Clinic34, Vanderbilt University35, George Washington University36, University of Newcastle37, Population Health Research Institute38, University Medical Center Groningen39, Leiden University Medical Center40, Uppsala University41, Science for Life Laboratory42, Stanford University43, Erasmus University Medical Center44, Greifswald University Hospital45, University of Regensburg46, University of London47, Robertson Centre for Biostatistics48, university of lille49, French Institute of Health and Medical Research50, University of Nantes51, University of Essex52, Brigham and Women's Hospital53, Fred Hutchinson Cancer Research Center54, University of Colorado Denver55, Pennsylvania State University56, Geisinger Health System57, University of Pennsylvania58
TL;DR: PCSK9 variants associated with lower LDL cholesterol were also associated with circulating higher fasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes.
University of Texas MD Anderson Cancer Center1, University of Plymouth2, University of Bologna3, Hackensack University Medical Center4, French Institute of Health and Medical Research5, Fred Hutchinson Cancer Research Center6, Erasmus University Rotterdam7, University of Navarra8, Southampton General Hospital9, University of Southampton10, Harvard University11, University of Amsterdam12, Medical University of Łódź13, Jagiellonian University14
TL;DR: Oral acalabrutinib treatment provided a high rate of durable responses and a favourable safety profile in patients with relapsed or refractory mantle cell lymphoma, and suggest an important role for acAlabrUTinib in the treatment of this disease population.
TL;DR: The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates.
Abstract: Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. The transition from the QGP back to the hadron gas is found to be a smooth cross over. For larger net-baryon densities and lower temperatures, it is expected that the QCD phase diagram exhibits a rich structure, such as a first-order phase transition between hadronic and partonic matter which terminates in a critical point, or exotic phases like quarkyonic matter. The discovery of these landmarks would be a breakthrough in our understanding of the strong interaction and is therefore in the focus of various high-energy heavy-ion research programs. The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates. High-rate operation is the key prerequisite for high-precision measurements of multi-differential observables and of rare diagnostic probes which are sensitive to the dense phase of the nuclear fireball. The goal of the CBM experiment at SIS100 ( $\sqrt{s_{NN}}=$ 2.7--4.9 GeV) is to discover fundamental properties of QCD matter: the phase structure at large baryon-chemical potentials ( $\mu_B > 500$ MeV), effects of chiral symmetry, and the equation of state at high density as it is expected to occur in the core of neutron stars. In this article, we review the motivation for and the physics programme of CBM, including activities before the start of data taking in 2024, in the context of the worldwide efforts to explore high-density QCD matter.
TL;DR: The clinical and experimental evidence supporting the new paradigm of citrullinated epitopes recognized by anti-citrullination protein antibodies is discussed and the potential mechanisms involved in linking periodontitis to RA are presented.
Abstract: Rheumatoid arthritis (RA), an autoimmune disease that affects ∼1% of the human population, is driven by autoantibodies that target modified self-epitopes, whereas ∼11% of the global adult population are affected by severe chronic periodontitis, a disease in which the commensal microflora on the tooth surface is replaced by a dysbiotic consortium of bacteria that promote the chronic inflammatory destruction of periodontal tissue. Despite differences in aetiology, RA and periodontitis are similar in terms of pathogenesis; both diseases involve chronic inflammation fuelled by pro-inflammatory cytokines, connective tissue breakdown and bone erosion. The two diseases also share risk factors such as smoking and ageing, and have strong epidemiological, serological and clinical associations. In light of the ground-breaking discovery that Porphyromonas gingivalis, a pivotal periodontal pathogen, is the only human pathogen known to express peptidylarginine deiminase, an enzyme that generates citrullinated epitopes that are recognized by anti-citrullinated protein antibodies, a new paradigm is emerging. In this Review, the clinical and experimental evidence supporting this paradigm is discussed and the potential mechanisms involved in linking periodontitis to RA are presented.
TL;DR: Dysfunctional AT may also serve as an important reservoir and possible site of activation in autoimmune-mediated and inflammatory diseases, and reciprocal regulation between immune cell infiltration and AT dysfunction is a promising future therapeutic target.
Abstract: Adipose tissue (AT) dysfunction, characterized by loss of its homeostatic functions, is a hallmark of non-communicable diseases. It is characterized by chronic low-grade inflammation and is observed in obesity, metabolic disorders such as insulin resistance and diabetes. While classically it has been identified by increased cytokine or chemokine expression, such as increased MCP-1, RANTES, IL-6, interferon (IFN) gamma or TNFα, mechanistically, immune cell infiltration is a prominent feature of the dysfunctional AT. These immune cells include M1 and M2 macrophages, effector and memory T cells, IL-10 producing FoxP3+ T regulatory cells, natural killer and NKT cells and granulocytes. Immune composition varies, depending on the stage and the type of pathology. Infiltrating immune cells not only produce cytokines but also metalloproteinases, reactive oxygen species, and chemokines that participate in tissue remodelling, cell signalling, and regulation of immunity. The presence of inflammatory cells in AT affects adjacent tissues and organs. In blood vessels, perivascular AT inflammation leads to vascular remodelling, superoxide production, endothelial dysfunction with loss of nitric oxide (NO) bioavailability, contributing to vascular disease, atherosclerosis, and plaque instability. Dysfunctional AT also releases adipokines such as leptin, resistin, and visfatin that promote metabolic dysfunction, alter systemic homeostasis, sympathetic outflow, glucose handling, and insulin sensitivity. Anti-inflammatory and protective adiponectin is reduced. AT may also serve as an important reservoir and possible site of activation in autoimmune-mediated and inflammatory diseases. Thus, reciprocal regulation between immune cell infiltration and AT dysfunction is a promising future therapeutic target.
TL;DR: In this paper, Dijet events are studied in the proton-proton collision dataset recorded at root s = 13 TeV with the ATLAS detector at the Large Hadron Collider in 2015 and 2016.
Abstract: Dijet events are studied in the proton-proton collision dataset recorded at root s = 13 TeV with the ATLAS detector at the Large Hadron Collider in 2015 and 2016, corresponding to integrated lumino ...
TL;DR: It is essential to develop techniques for monitoring the characteristics of PVAT and assessing its inflammation to lead to a better understanding of the early stages of vascular pathologies and the development of new therapeutic strategies focusing on perivascular adipose tissue.
Abstract: Perivascular adipose tissue (PVAT) plays a critical role in the pathogenesis of cardiovascular disease. In vascular pathologies perivascular adipose tissue increases in volume and becomes dysfunctional, with altered cellular composition and molecular characteristics. PVAT dysfunction is characterized by its inflammatory character, oxidative stress, diminished production of vaso-protective adipocyte derived relaxing factors (ADRFs) and increased production of paracrine factors such as resistin, leptin, cytokines (IL-6, TNF-α) and chemokines (RANTES, MCP-1). These adipocyte-derived factors initiate and orchestrate inflammatory cell infiltration including primarily T cells, macrophages, dendritic cells (DCs), B cells as well as NK cells. Protective factors such as adiponectin can reduce NADPH oxidase superoxide production and increase nitric oxide bioavailability in the vessel wall, while inflammation (e.g. IFN-γ or IL-17) induces vascular oxidases and eNOS dysfunction in the endothelium, vascular smooth muscle cells and adventitial fibroblasts. All of these events link dysfunctional perivascular fat to vascular dysfunction. These mechanisms are important in the context of a number of cardiovascular disorders including atherosclerosis, hypertension, diabetes and obesity. Inflammatory changes in PVAT molecular and cellular responses are uniquely different from classical visceral or subcutaneous adipose tissue or from adventitia, emphasizing unique structural and functional features of this adipose tissue compartment. Therefore, it is essential to develop techniques for monitoring PVAT characteristics and assessing its inflammation. This will lead to better understanding of the early stages of vascular pathologies and development of new therapeutic strategies focusing on perivascular adipose tissue.
Complutense University of Madrid1, John Radcliffe Hospital2, Belfast Health and Social Care Trust3, Imperial College London4, Hospital Universitario La Paz5, Papworth Hospital6, Newcastle University7, Manchester Royal Infirmary8, Erasmus University Rotterdam9, Brighton and Sussex University Hospitals NHS Trust10, Jagiellonian University11
TL;DR: At one year, clinical outcomes with the SYNTAX-II strategy were associated with improved clinical results compared to the PCI performed in comparable patients from the original SYN TAX-I trial, and a randomized clinical trial with contemporary CABG is warranted.
Abstract: Aims: To investigate if recent technical and procedural developments in percutaneous coronary intervention (PCI) significantly influence outcomes in appropriately selected patients with three-vessel (3VD) coronary artery disease. Methods and results: The SYNTAX II study is a multicenter, all-comers, open-label, single arm study that investigated the impact of a contemporary PCI strategy on clinical outcomes in patients with 3VD in 22 centres from four European countries. The SYNTAX-II strategy includes: heart team decision-making utilizing the SYNTAX Score II (a clinical tool combining anatomical and clinical factors), coronary physiology guided revascularisation, implantation of thin strut bio-resorbable-polymer drug-eluting stents, intravascular ultrasound (IVUS) guided stent implantation, contemporary chronic total occlusion revascularisation techniques and guideline-directed medical therapy. The rate of major adverse cardiac and cerebrovascular events (MACCE [composite of all-cause death, cerebrovascular event, any myocardial infarction and any revascularisation]) at one year was compared to a predefined PCI cohort from the original SYNTAX-I trial selected on the basis of equipoise 4-year mortality between CABG and PCI. As an exploratory endpoint, comparisons were made with the historical CABG cohort of the original SYNTAX-I trial. Overall 708 patients were screened and discussed within the heart team; 454 patients were deemed appropriate to undergo PCI. At one year, the SYNTAX-II strategy was superior to the equipoise-derived SYNTAX-I PCI cohort (MACCE SYNTAX-II 10.6% vs. SYNTAX-I 17.4%; HR 0.58, 95% CI 0.39-0.85, P= 0.006). This difference was driven by a significant reduction in the incidence of MI (HR 0.27, 95% CI 0.11-0.70, P= 0.007) and revascularisation (HR 0.57, 95% CI 0.37-0.9, P = 0.015). Rates of all-cause death (HR 0.69, 95% CI 0.27-1.73, P = 0.43) and stroke (HR 0.69, 95% CI 0.10-4.89, P = 0.71) were similar. The rate of definite stent thrombosis was significantly lower in SYNTAX-II (HR 0.26, 95% CI 0.07-0.97, P = 0.045). Conclusion: At one year, clinical outcomes with the SYNTAX-II strategy were associated with improved clinical results compared to the PCI performed in comparable patients from the original SYNTAX-I trial. Longer term follow-up is awaited and a randomized clinical trial with contemporary CABG is warranted.
TL;DR: The latest work on structural characterization of the checkpoint proteins, their interactions with cognate ligands and with therapeutic antibodies reveals that they all have a similar modular structure, composed of small domains similar in topology to the domains found in antibodies.
TL;DR: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters of asthmatic patients that associate with different pathobiological pathways.
Abstract: Background Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. Methods Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. Results Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. Conclusion Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.