Initial clinical evaluation of stationary digital chest tomosynthesis in adult patients with cystic fibrosis

Objective: The imaging evaluation of cystic fibrosis currently relies on chest radiography or computed tomography. Recently, digital chest tomosynthesis has been proposed as an alternative. We have developed a stationary digital chest tomosynthesis (s-DCT) system based on a carbon nanotube (CNT) linear x-ray source array. This system enables tomographic imaging without movement of the x-ray tube and allows for physiological gating. The goal of this study was to evaluate the feasibility of clinical CF imaging with the s-DCT system. Materials and methods: CF patients undergoing clinically indicated chest radiography were recruited for the study and imaged on the s-DCT system. Three board-certified radiologists reviewed both the CXR and s-DCT images for image quality relevant to CF. CF disease severity was assessed by Brasfield score on CXR and chest tomosynthesis score on s-DCT. Disease severity measures were also evaluated against subject pulmonary function tests. Results: Fourteen patients underwent s-DCT imaging within 72 h of their chest radiograph imaging. Readers scored the visualization of proximal bronchi, small airways and vascular pattern higher on s-DCT than CXR. Correlation between the averaged Brasfield score and averaged tomosynthesis disease severity score for CF was -0.73, p = 0.0033. The CF disease severity score system for tomosynthesis had high correlation with FEV1 (r = -0.685) and FEF 25–75% (r = -0.719) as well as good correlation with FVC (r = -0.582). Conclusion: We demonstrate the potential of CNT x-ray-based s-DCT for use in the evaluation of cystic fibrosis disease status in the first clinical study of s-DCT. Key Points: • Carbon nanotube-based linear array x-ray tomosynthesis systems have the potential to provide diagnostically relevant information for patients with cystic fibrosis without the need for a moving gantry. • Despite the short angular span in this prototype system, lung features such as the proximal bronchi, small airways and pulmonary vasculature have improved visualization on s-DCT compared with CXR. Further improvements are anticipated with longer linear x-ray array tubes. • Evaluation of disease severity in CF patients is possible with s-DCT, yielding improved visualization of important lung features and high correlation with pulmonary function tests at a relatively low dose

Competing orders in a magnetic field: spin and charge order in the cuprate superconductors

We describe two-dimensional quantum spin fluctuations in a superconducting Abrikosov flux lattice induced by a magnetic field applied to a doped Mott insulator. Complete numerical solutions of a self-consistent large N theory provide detailed information on the phase diagram and on the spatial structure of the dynamic spin spectrum. Our results apply to phases with and without long-range spin density wave order and to the magnetic quantum critical point separating these phases. We discuss the relationship of our results to a number of recent neutron scattering measurements on the cuprate superconductors in the presence of an applied field. We compute the pinning of static charge order by the vortex cores in the `spin gap' phase where the spin order remains dynamically fluctuating, and argue that these results apply to recent scanning tunnelling microscopy (STM) measurements. We show that with a single typical set of values for the coupling constants, our model describes the field dependence of the elastic neutron scattering intensities, the absence of satellite Bragg peaks associated with the vortex lattice in existing neutron scattering observations, and the spatial extent of charge order in STM observations. We mention implications of our theory for NMR experiments. We also present a theoretical discussion of more exotic states that can be built out of the spin and charge order parameters, including spin nematics and phases with `exciton fractionalization'.Comment: 36 pages, 33 figures; for a popular introduction, see http://onsager.physics.yale.edu/superflow.html; (v2) Added reference to new work of Chen and Ting; (v3) reorganized presentation for improved clarity, and added new appendix on microscopic origin; (v4) final published version with minor change

Toward a Multifaceted Heuristic of Digital Reading to Inform Assessment, Research, Practice, and Policy

In this commentary, the author explores the tension between almost 30 years of work that has embraced increasingly complex conceptions of digital reading and recent studies that risk oversimplifying digital reading as a singular entity analogous with reading text on a screen. The author begins by tracing a line of theoretical and empirical work that both informs and complicates our understanding of digital literacy and, more specifically, digital reading. Then, a heuristic is proposed to systematically organize, label, and define a multifaceted set of increasingly complex terms, concepts, and practices that characterize the spectrum of digital reading experiences. Research that informs this heuristic is used to illustrate how more precision in defining digital reading can promote greater clarity across research methods and advance a more systematic study of promising digital reading practices. Finally, the author discusses implications for assessment, research, practice, and policy

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. Findings: Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. Interpretation: As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. Funding: Bill & Melinda Gates Foundation

Search for single vector-like B quark production and decay via B → bH(b¯b) in pp collisions at √s = 13 TeV with the ATLAS detector

A search is presented for single production of a vector-like B quark decaying into a Standard Model b-quark and a Standard Model Higgs boson, which decays into a b¯b pair. The search is carried out in 139 fb−1 of √s = 13 TeV proton-proton collision data collected by the ATLAS detector at the LHC between 2015 and 2018. No significant deviation from the Standard Model background prediction is observed, and mass-dependent exclusion limits at the 95% confidence level are set on the resonance production cross-section in several theoretical scenarios determined by the couplings cW, cZ and cH between the B quark and the Standard Model W, Z and Higgs bosons, respectively. For a vector-like B occurring as an isospin singlet, the search excludes values of cW greater than 0.45 for a B resonance mass (mB) between 1.0 and 1.2 TeV. For 1.2 TeV < mB < 2.0 TeV, cW values larger than 0.50–0.65 are excluded. If the B occurs as part of a (B, Y) doublet, the smallest excluded cZ coupling values range between 0.3 and 0.5 across the investigated resonance mass range 1.0 TeV < mB < 2.0 TeV

Search for light long-lived neutral particles that decay to collimated pairs of leptons or light hadrons in pp collisions at s√ = 13 TeV with the ATLAS detector

A search for light long-lived neutral particles with masses in the O(MeV–GeV) range is presented. The analysis targets the production of long-lived dark photons in the decay of a Higgs boson produced via gluon–gluon fusion or in association with a W boson. Events that contain displaced collimated Standard Model fermions reconstructed in the calorimeter or muon spectrometer are selected in 139 fb−1 of s√ = 13 TeV pp collision data collected by the ATLAS detector at the LHC. Background estimates for contributions from Standard Model processes and instrumental effects are extracted from data. The observed event yields are consistent with the expected background. Exclusion limits are reported on the production cross-section times branching fraction as a function of the mean proper decay length cτ of the dark photon, or as a function of the dark-photon mass and kinetic mixing parameter that quantifies the coupling between the Standard Model and potential hidden (dark) sectors. A Higgs boson branching fraction above 1% is excluded at 95% CL for a Higgs boson decaying into two dark photons for dark-photon mean proper decay lengths between 10 mm and 250 mm and dark photons with masses between 0.4 GeV and 2 GeV

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at s√ = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb−1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at s√ = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterising the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators OtG and O(8)tq, where the limits on the latter are the most stringent to date

Deep generative models for fast photon shower simulation in ATLAS

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques

Performance and calibration of quark/gluon-jet taggers using 140 fb−1 of pp collisions at √s = 13 TeV with the ATLAS detector

The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using √s = 13 TeV proton–proton collision data with an integrated luminosity of 140 fb-1 collected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points