Showing papers by "Jagiellonian 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.

COVID-19 and the cardiovascular system: implications for risk assessment, diagnosis, and treatment options.

Abstract: The novel coronavirus disease (COVID-19) outbreak, caused by SARS-CoV-2, represents the greatest medical challenge in decades. We provide a comprehensive review of the clinical course of COVID-19, its comorbidities, and mechanistic considerations for future therapies. While COVID-19 primarily affects the lungs, causing interstitial pneumonitis and severe acute respiratory distress syndrome (ARDS), it also affects multiple organs, particularly the cardiovascular system. Risk of severe infection and mortality increase with advancing age and male sex. Mortality is increased by comorbidities: cardiovascular disease, hypertension, diabetes, chronic pulmonary disease, and cancer. The most common complications include arrhythmia (atrial fibrillation, ventricular tachyarrhythmia, and ventricular fibrillation), cardiac injury [elevated highly sensitive troponin I (hs-cTnI) and creatine kinase (CK) levels], fulminant myocarditis, heart failure, pulmonary embolism, and disseminated intravascular coagulation (DIC). Mechanistically, SARS-CoV-2, following proteolytic cleavage of its S protein by a serine protease, binds to the transmembrane angiotensin-converting enzyme 2 (ACE2) -a homologue of ACE-to enter type 2 pneumocytes, macrophages, perivascular pericytes, and cardiomyocytes. This may lead to myocardial dysfunction and damage, endothelial dysfunction, microvascular dysfunction, plaque instability, and myocardial infarction (MI). While ACE2 is essential for viral invasion, there is no evidence that ACE inhibitors or angiotensin receptor blockers (ARBs) worsen prognosis. Hence, patients should not discontinue their use. Moreover, renin-angiotensin-aldosterone system (RAAS) inhibitors might be beneficial in COVID-19. Initial immune and inflammatory responses induce a severe cytokine storm [interleukin (IL)-6, IL-7, IL-22, IL-17, etc.] during the rapid progression phase of COVID-19. Early evaluation and continued monitoring of cardiac damage (cTnI and NT-proBNP) and coagulation (D-dimer) after hospitalization may identify patients with cardiac injury and predict COVID-19 complications. Preventive measures (social distancing and social isolation) also increase cardiovascular risk. Cardiovascular considerations of therapies currently used, including remdesivir, chloroquine, hydroxychloroquine, tocilizumab, ribavirin, interferons, and lopinavir/ritonavir, as well as experimental therapies, such as human recombinant ACE2 (rhACE2), are discussed.

2D/2D/0D TiO2/C3N4/Ti3C2 MXene composite S-scheme photocatalyst with enhanced CO2 reduction activity

Abstract: Herein, two-dimensional (2D) TiO2 mesoporous nanosheets with three to four C3N4 layers grown in situ are employed to design a core–shell 2D/2D van der Waals heterojunction (TiO2/C3N4). Edge-terminated zero-dimensional (0D) Ti3C2 MXene quantum dots (TCQD) are subsequently integrated in the C3N4 surface via electrostatic interactions. The constructed 2D/2D/0D TiO2/C3N4/Ti3C2 composite heterojunction photocatalyst exhibits enhanced CO2 reduction activity compared to TiO2, C3N4, TiO2/C3N4, C3N4/Ti3C2 for CO and CH4 production. A step-scheme (S-scheme) charge transfer mechanism operates for the prepared samples during CO2 reduction, as authenticated by in situ X-ray photoelectron spectroscopy and electron paramagnetic resonance analysis. This study provides a paradigm of a rational structural design for regulating the number and type of heterointerfaces and further insights into the mechanism of multijunction photocatalysts.

Microbiome analyses of blood and tissues suggest cancer diagnostic approach

Abstract: Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1–10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia–IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration. Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach.

Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening

Abstract: We present a deep convolutional neural network for breast cancer screening exam classification, trained, and evaluated on over 200000 exams (over 1000000 images). Our network achieves an AUC of 0.895 in predicting the presence of cancer in the breast, when tested on the screening population. We attribute the high accuracy to a few technical advances. 1) Our network’s novel two-stage architecture and training procedure, which allows us to use a high-capacity patch-level network to learn from pixel-level labels alongside a network learning from macroscopic breast-level labels. 2) A custom ResNet-based network used as a building block of our model, whose balance of depth and width is optimized for high-resolution medical images. 3) Pretraining the network on screening BI-RADS classification, a related task with more noisy labels. 4) Combining multiple input views in an optimal way among a number of possible choices. To validate our model, we conducted a reader study with 14 readers, each reading 720 screening mammogram exams, and show that our model is as accurate as experienced radiologists when presented with the same data. We also show that a hybrid model, averaging the probability of malignancy predicted by a radiologist with a prediction of our neural network, is more accurate than either of the two separately. To further understand our results, we conduct a thorough analysis of our network’s performance on different subpopulations of the screening population, the model’s design, training procedure, errors, and properties of its internal representations. Our best models are publicly available at https://github.com/nyukat/breast_cancer_classifier .

A MHz-repetition-rate hard X-ray free-electron laser driven by a superconducting linear accelerator

Abstract: The European XFEL is a hard X-ray free-electron laser (FEL) based on a high-electron-energy superconducting linear accelerator. The superconducting technology allows for the acceleration of many electron bunches within one radio-frequency pulse of the accelerating voltage and, in turn, for the generation of a large number of hard X-ray pulses. We report on the performance of the European XFEL accelerator with up to 5,000 electron bunches per second and demonstrating a full energy of 17.5 GeV. Feedback mechanisms enable stabilization of the electron beam delivery at the FEL undulator in space and time. The measured FEL gain curve at 9.3 keV is in good agreement with predictions for saturated FEL radiation. Hard X-ray lasing was achieved between 7 keV and 14 keV with pulse energies of up to 2.0 mJ. Using the high repetition rate, an FEL beam with 6 W average power was created.

Hypertension, the renin-angiotensin system, and the risk of lower respiratory tract infections and lung injury: implications for COVID-19.

Abstract: Systemic arterial hypertension (referred to as hypertension herein) is a major risk factor of mortality worldwide, and its importance is further emphasized in the context of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection referred to as COVID-19. Patients with severe COVID-19 infections commonly are older and have a history of hypertension. Almost 75% of patients who have died in the pandemic in Italy had hypertension. This raised multiple questions regarding a more severe course of COVID-19 in relation to hypertension itself as well as its treatment with renin-angiotensin system (RAS) blockers, e.g. angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs). We provide a critical review on the relationship of hypertension, RAS, and risk of lung injury. We demonstrate lack of sound evidence that hypertension per se is an independent risk factor for COVID-19. Interestingly, ACEIs and ARBs may be associated with lower incidence and/or improved outcome in patients with lower respiratory tract infections. We also review in detail the molecular mechanisms linking the RAS to lung damage and the potential clinical impact of treatment with RAS blockers in patients with COVID-19 and a high cardiovascular and renal risk. This is related to the role of angiotensin-converting enzyme 2 (ACE2) for SARS-CoV-2 entry into cells, and expression of ACE2 in the lung, cardiovascular system, kidney, and other tissues. In summary, a critical review of available evidence does not support a deleterious effect of RAS blockers in COVID-19 infections. Therefore, there is currently no reason to discontinue RAS blockers in stable patients facing the COVID-19 pandemic.

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.

Measurement of the Permanent Electric Dipole Moment of the Neutron.

Abstract: We present the result of an experiment to measure the electric dipole moment EDM) of the neutron at the Paul Scherrer Institute using Ramsey's method of separated oscillating magnetic fields with ultracold neutrons (UCN). Our measurement stands in the long history of EDM experiments probing physics violating time reversal invariance. The salient features of this experiment were the use of a Hg-199 co-magnetometer and an array of optically pumped cesium vapor magnetometers to cancel and correct for magnetic field changes. The statistical analysis was performed on blinded datasets by two separate groups while the estimation of systematic effects profited from an unprecedented knowledge of the magnetic field. The measured value of the neutron EDM is $d_{\rm n} = (0.0\pm1.1_{\rm stat}\pm0.2_{\rmsys})\times10^{-26}e\,{\rm cm}$.

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.

Final Results of GERDA on the Search for Neutrinoless Double-β Decay.

Abstract: The GERmanium Detector Array (GERDA) experiment searched for the lepton-number-violating neutrinoless double-$\beta$ ($0 u\beta\beta$) decay of $^{76}$Ge, whose discovery would have far-reaching implications in cosmology and particle physics. By operating bare germanium diodes, enriched in $^{76}$Ge, in an active liquid argon shield, GERDA achieved an unprecedently low background index of $5.2\times10^{-4}$ counts/(keV$\cdot$kg$\cdot$yr) in the signal region and met the design goal to collect an exposure of 100 kg$\cdot$yr in a background-free regime. When combined with the result of Phase I, no signal is observed after 127.2 kg$\cdot$yr of total exposure. A limit on the half-life of $0 u\beta\beta$ decay in $^{76}$Ge is set at $T_{1/2}>1.8\times10^{26}$ yr at 90% C.L., which coincides with the sensitivity assuming no signal.

Citrus limon (Lemon) Phenomenon-A Review of the Chemistry, Pharmacological Properties, Applications in the Modern Pharmaceutical, Food, and Cosmetics Industries, and Biotechnological Studies.

Abstract: This review presents important botanical, chemical and pharmacological characteristics of Citrus limon (lemon)—a species with valuable pharmaceutical, cosmetic and culinary (healthy food) properties. A short description of the genus Citrus is followed by information on the chemical composition, metabolomic studies and biological activities of the main raw materials obtained from C. limon (fruit extract, juice, essential oil). The valuable biological activity of C. limon is determined by its high content of phenolic compounds, mainly flavonoids (e.g., diosmin, hesperidin, limocitrin) and phenolic acids (e.g., ferulic, synapic, p-hydroxybenzoic acids). The essential oil is rich in bioactive monoterpenoids such as D-limonene, β-pinene, γ-terpinene. Recently scientifically proven therapeutic activities of C. limon include anti-inflammatory, antimicrobial, anticancer and antiparasitic activities. The review pays particular attention, with references to published scientific research, to the use of C. limon in the food industry and cosmetology. It also addresses the safety of use and potential phototoxicity of the raw materials. Lastly, the review emphasizes the significance of biotechnological studies on C. limon.

Performance of electron and photon triggers in ATLAS during LHC Run 2

Abstract: Electron and photon triggers covering transverse energies from 5 GeV to several TeV are essential for the ATLAS experiment to record signals for a wide variety of physics: from Standard Model processes to searches for new phenomena in both proton–proton and heavy-ion collisions. To cope with a fourfold increase of peak LHC luminosity from 2015 to 2018 (Run 2), to 2.1×1034cm-2s-1, and a similar increase in the number of interactions per beam-crossing to about 60, trigger algorithms and selections were optimised to control the rates while retaining a high efficiency for physics analyses. For proton–proton collisions, the single-electron trigger efficiency relative to a single-electron offline selection is at least 75% for an offline electron of 31 GeV, and rises to 96% at 60 GeV; the trigger efficiency of a 25 GeV leg of the primary diphoton trigger relative to a tight offline photon selection is more than 96% for an offline photon of 30 GeV. For heavy-ion collisions, the primary electron and photon trigger efficiencies relative to the corresponding standard offline selections are at least 84% and 95%, respectively, at 5 GeV above the corresponding trigger threshold.

Search for Heavy Higgs Bosons Decaying into Two Tau Leptons with the ATLAS Detector Using pp Collisions at s =13 TeV

Abstract: A search for heavy neutral Higgs bosons is performed using the LHC Run 2 data, corresponding to an integrated luminosity of 139 fb^{-1} of proton-proton collisions at sqrt[s]=13 TeV recorded with the ATLAS detector. The search for heavy resonances is performed over the mass range 0.2-2.5 TeV for the τ^{+}τ^{-} decay with at least one τ-lepton decaying into final states with hadrons. The data are in good agreement with the background prediction of the standard model. In the M_{h}^{125} scenario of the minimal supersymmetric standard model, values of tanβ>8 and tanβ>21 are excluded at the 95% confidence level for neutral Higgs boson masses of 1.0 and 1.5 TeV, respectively, where tanβ is the ratio of the vacuum expectation values of the two Higgs doublets.

State of the art in total body PET

Abstract: The idea of a very sensitive positron emission tomography (PET) system covering a large portion of the body of a patient already dates back to the early 1990s. In the period 2000–2010, only some prototypes with long axial field of view (FOV) have been built, which never resulted in systems used for clinical research. One of the reasons was the limitations in the available detector technology, which did not yet have sufficient energy resolution, timing resolution or countrate capabilities for fully exploiting the benefits of a long axial FOV design. PET was also not yet as widespread as it is today: the growth in oncology, which has become the major application of PET, appeared only after the introduction of PET-CT (early 2000).The detector technology used in most clinical PET systems today has a combination of good energy and timing resolution with higher countrate capabilities and has now been used since more than a decade to build time-of-flight (TOF) PET systems with fully 3D acquisitions. Based on this technology, one can construct total body PET systems and the remaining challenges (data handling, fast image reconstruction, detector cooling) are mostly related to engineering. The direct benefits of long axial FOV systems are mostly related to the higher sensitivity. For single organ imaging, the gain is close to the point source sensitivity which increases linearly with the axial length until it is limited by solid angle and attenuation of the body. The gains for single organ (compared to a fully 3D PET 20-cm axial FOV) are limited to a factor 3–4. But for long objects (like body scans), it increases quadratically with scanner length and factors of 10–40 × higher sensitivity are predicted for the long axial FOV scanner. This application of PET has seen a major increase (mostly in oncology) during the last 2 decades and is now the main type of study in a PET centre. As the technology is available and the full body concept also seems to match with existing applications, the old concept of a total body PET scanner is seeing a clear revival. Several research groups are working on this concept and after showing the potential via extensive simulations; construction of these systems has started about 2 years ago. In the first phase, two PET systems with long axial FOV suitable for large animal imaging were constructed to explore the potential in more experimental settings. Recently, the first completed total body PET systems for human use, a 70-cm-long system, called PennPET Explorer, and a 2-m-long system, called uExplorer, have become reality and first clinical studies have been shown. These results illustrate the large potential of this concept with regard to low-dose imaging, faster scanning, whole-body dynamic imaging and follow-up of tracers over longer periods. This large range of possible technical improvements seems to have the potential to change the current clinical routine and to expand the number of clinical applications of molecular imaging. The J-PET prototype is a prototype system with a long axial FOV built from axially arranged plastic scintillator strips.This paper gives an overview of the recent technical developments with regard to PET scanners with a long axial FOV covering at least the majority of the body (so called total body PET systems). After explaining the benefits and challenges of total body PET systems, the different total body PET system designs proposed for large animal and clinical imaging are described in detail. The axial length is one of the major factors determining the total cost of the system, but there are also other options in detector technology, design and processing for reducing the cost these systems. The limitations and advantages of different designs for research and clinical use are discussed taking into account potential applications and the increased cost of these systems.

Thouless Time Analysis of Anderson and Many-Body Localization Transitions.

Abstract: Spectral statistics of disordered systems encode Thouless and Heisenberg timescales, whose ratio determines whether the system is chaotic or localized. We show that the scaling of the Thouless time with the system size and disorder strength is very similar in one-body Anderson models and in disordered quantum many-body systems. We argue that the two parameter scaling breaks down in the vicinity of the transition to the localized phase, signaling a slowing-down of dynamics.

SUCCOR study: an international European cohort observational study comparing minimally invasive surgery versus open abdominal radical hysterectomy in patients with stage IB1 cervical cancer

Abstract: Background Minimally invasive surgery in cervical cancer has demonstrated in recent publications worse outcomes than open surgery. The primary objective of the SUCCOR study, a European, multicenter, retrospective, observational cohort study was to evaluate disease-free survival in patients with stage IB1 (FIGO 2009) cervical cancer undergoing open vs minimally invasive radical hysterectomy. As a secondary objective, we aimed to investigate the association between protective surgical maneuvers and the risk of relapse. Methods We obtained data from 1272 patients that underwent a radical hysterectomy by open or minimally invasive surgery for stage IB1 cervical cancer (FIGO 2009) from January 2013 to December 2014. After applying all the inclusion-exclusion criteria, we used an inverse probability weighting to construct a weighted cohort of 693 patients to compare outcomes (minimally invasive surgery vs open). The first endpoint compared disease-free survival at 4.5 years in both groups. Secondary endpoints compared overall survival among groups and the impact of the use of a uterine manipulator and protective closure of the colpotomy over the tumor in the minimally invasive surgery group. Results Mean age was 48.3 years (range; 23–83) while the mean BMI was 25.7 kg/m2 (range; 15–49). The risk of recurrence for patients who underwent minimally invasive surgery was twice as high as that in the open surgery group (HR, 2.07; 95% CI, 1.35 to 3.15; P=0.001). Similarly, the risk of death was 2.42-times higher than in the open surgery group (HR, 2.45; 95% CI, 1.30 to 4.60, P=0.005). Patients that underwent minimally invasive surgery using a uterine manipulator had a 2.76-times higher hazard of relapse (HR, 2.76; 95% CI, 1.75 to 4.33; P Conclusions Minimally invasive surgery in cervical cancer increased the risk of relapse and death compared with open surgery. In this study, avoiding the uterine manipulator and using maneuvers to avoid tumor spread at the time of colpotomy in minimally invasive surgery was associated with similar outcomes to open surgery. Further prospective studies are warranted.

QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data.

Abstract: QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses-e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https://qiime2.org. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https://forum.qiime2.org. © 2020 The Authors. Basic Protocol: Using QIIME 2 with microbiome data Support Protocol: Further microbiome analyses.

Mol-CycleGAN: a generative model for molecular optimization

Abstract: Designing a molecule with desired properties is one of the biggest challenges in drug development, as it requires optimization of chemical compound structures with respect to many complex properties. To improve the compound design process, we introduce Mol-CycleGAN—a CycleGAN-based model that generates optimized compounds with high structural similarity to the original ones. Namely, given a molecule our model generates a structurally similar one with an optimized value of the considered property. We evaluate the performance of the model on selected optimization objectives related to structural properties (presence of halogen groups, number of aromatic rings) and to a physicochemical property (penalized logP). In the task of optimization of penalized logP of drug-like molecules our model significantly outperforms previous results.

Experimental evidence of neutrinos produced in the CNO fusion cycle in the Sun

Abstract: For most of their existence, stars are fuelled by the fusion of hydrogen into helium. Fusion proceeds via two processes that are well understood theoretically: the proton–proton (pp) chain and the carbon–nitrogen–oxygen (CNO) cycle. Neutrinos that are emitted along such fusion processes in the solar core are the only direct probe of the deep interior of the Sun. A complete spectroscopic study of neutrinos from the pp chain, which produces about 99 per cent of the solar energy, has been performed previously; however, there has been no reported experimental evidence of the CNO cycle. Here we report the direct observation, with a high statistical significance, of neutrinos produced in the CNO cycle in the Sun. This experimental evidence was obtained using the highly radiopure, large-volume, liquid-scintillator detector of Borexino, an experiment located at the underground Laboratori Nazionali del Gran Sasso in Italy. The main experimental challenge was to identify the excess signal—only a few counts per day above the background per 100 tonnes of target—that is attributed to interactions of the CNO neutrinos. Advances in the thermal stabilization of the detector over the last five years enabled us to develop a method to constrain the rate of bismuth-210 contaminating the scintillator. In the CNO cycle, the fusion of hydrogen is catalysed by carbon, nitrogen and oxygen, and so its rate—as well as the flux of emitted CNO neutrinos—depends directly on the abundance of these elements in the solar core. This result therefore paves the way towards a direct measurement of the solar metallicity using CNO neutrinos. Our findings quantify the relative contribution of CNO fusion in the Sun to be of the order of 1 per cent; however, in massive stars, this is the dominant process of energy production. This work provides experimental evidence of the primary mechanism for the stellar conversion of hydrogen into helium in the Universe.

Electronic Devices Using Open Framework Materials.

Abstract: Open framework materials (OFM) constitute a large and growing class of nanoporous crystalline structures that is attracting considerable attention for electronic device applications. This review summarizes the most recent reports concerning electronic devices enabled by either of the two primary categories of OFM, metal-organic frameworks (MOFs) and covalent-organic frameworks (COFs). Devices in which the OFM plays an active role (as opposed to acting only as a selective sorbent or filter) are the principal focus, with examples cited that include field-effect transistors, capacitors, memristors, and a wide variety of sensing architectures. As a brief tutorial, we also provide a concise summary of various methods of depositing or growing OFM on surfaces, as these are of crucial importance to the deployment of electronic OFM. Finally, we offer our perspective concerning future research directions, particularly regarding what in our view are the biggest challenges remaining to be addressed. On the basis of the literature discussed here, we conclude that OFM constitute a unique class of electronic materials with characteristics and advantages that are distinct from either conventional inorganic semiconductors or organic conductors. This suggests a bright future for these materials in applications such as edge computing, resistive switching, and mechanically flexible sensing and electronics.

A structured open dataset of government interventions in response to COVID-19.

Abstract: In response to the COVID-19 pandemic, governments have implemented a wide range of non-pharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020.

The association between stressors and telomeres in non-human vertebrates: a meta-analysis.

Abstract: Animal response to stressors such as harsh environmental conditions and demanding biological processes requires energy generated through increased mitochondrial activity. This results in the production of reactive oxygen species (ROS). In vitro and some in vivo studies suggest that oxidative damage of DNA caused by ROS is responsible for telomere shortening. Since telomere length is correlated with survival in many vertebrates, telomere loss is hypothesised to trigger cellular ageing and/ or to reflect the harshness of the environment an individual has experienced. To improve our understanding of stress-induced telomere dynamics in non-human vertebrates, we analysed 109 relevant studies in a meta-analytical framework. Overall, the exposure to possible stressors was associated with shorter telomeres or higher telomere shortening rate (average effect size = -0.16 ± 0.03). This relationship was consistent for all phylogenetic classes and for all a priori-selected stressor categories. It was stronger in the case of pathogen infection, competition, reproductive effort and high activity level, which emphasises their importance in explaining intraspecific telomere length variability and, potentially, lifespan variability. Interestingly, the association between stressor exposure and telomeres in one hand, and oxidative stress in the other hand, covaried, suggesting the implication of oxidative stress in telomere dynamics.

Endothelial GLP-1 (Glucagon-Like Peptide-1) Receptor Mediates Cardiovascular Protection by Liraglutide In Mice With Experimental Arterial Hypertension.

Abstract: Objective: Cardiovascular outcome trials demonstrated that GLP-1 (glucagon-like peptide-1) analogs including liraglutide reduce the risk of cardiovascular events in type 2 diabetes mellitus. Whethe...