The formation and early evolution of embedded star clusters in spiral galaxies

The equipment was funded by BEIS capital funding via STFC capital grants ST/K000373/1 and ST/R002363/1 and STFC DiRAC Operations grant ST/K001014/1. DiRAC is part of the National E-Infrastructure. SR acknowledges funding from STFC Consolidated Grant ST/R000395/1. CLD acknowledges funding from the European Research Council for the Horizon 2020 ERC consolidator grant project ICYBOB, grant number 818940.We present Ekster, a new method for simulating star clusters from birth in a live galaxy simulation that combines the smoothed-particle hydrodynamics (SPH) method Phantom with the N-body method PeTar. With Ekster, it becomes possible to simulate individual stars in a simulation with only moderately high resolution for the gas, allowing us to study whole sections of a galaxy rather than be restricted to individual clouds. We use this method to simulate star and star cluster formation in spiral arms, investigating massive GMCs and spiral arm regions with lower mass clouds, from two galaxy models with different spiral potentials. After selecting these regions from pre-run galaxy simulations, we re-sample the particles to obtain a higher resolution. We then re-simulate these regions for 3 Myr to study where and how star clusters form. We analyse the early evolution of the embedded star clusters in these regions. We find that the massive GMC regions, which are more common with stronger spiral arms, form more massive clusters than the sections of spiral arms containing lower mass clouds. Clusters form both by accreting gas and by merging with other proto-clusters, the latter happening more frequently in the denser GMC regions.Publisher PDFPeer reviewe

Deep Hierarchical Super-Resolution for Scientific Data Reduction and Visualization

We present an approach for hierarchical super resolution (SR) using neural networks on an octree data representation. We train a hierarchy of neural networks, each capable of 2x upscaling in each spatial dimension between two levels of detail, and use these networks in tandem to facilitate large scale factor super resolution, scaling with the number of trained networks. We utilize these networks in a hierarchical super resolution algorithm that upscales multiresolution data to a uniform high resolution without introducing seam artifacts on octree node boundaries. We evaluate application of this algorithm in a data reduction framework by dynamically downscaling input data to an octree-based data structure to represent the multiresolution data before compressing for additional storage reduction. We demonstrate that our approach avoids seam artifacts common to multiresolution data formats, and show how neural network super resolution assisted data reduction can preserve global features better than compressors alone at the same compression ratios

An Innovative Protocol for Metaproteomic Analyses of Microbial Pathogens in Cystic Fibrosis Sputum

Hallmarks of cystic fibrosis (CF) are increased viscosity of mucus and impaired mucociliary clearance within the airways due to mutations of the cystic fibrosis conductance regulator gene. This facilitates the colonization of the lung by microbial pathogens and the concomitant establishment of chronic infections leading to tissue damage, reduced lung function, and decreased life expectancy. Although the interplay between key CF pathogens plays a major role during disease progression, the pathophysiology of the microbial community in CF lungs remains poorly understood. Particular challenges in the analysis of the microbial population present in CF sputum is (I) the inhomogeneous, viscous, and slimy consistence of CF sputum, and (II) the high number of human proteins masking comparably low abundant microbial proteins. To address these challenges, we used 21 CF sputum samples to develop a reliable, reproducible and widely applicable protocol for sputum processing, microbial enrichment, cell disruption, protein extraction and subsequent metaproteomic analyses. As a proof of concept, we selected three sputum samples for detailed metaproteome analyses and complemented and validated metaproteome data by 16S sequencing, metabolomic as well as microscopic analyses. Applying our protocol, the number of bacterial proteins/protein groups increased from 199-425 to 392-868 in enriched samples compared to nonenriched controls. These early microbial metaproteome data suggest that the arginine deiminase pathway and multiple proteases and peptidases identified from various bacterial genera could so far be underappreciated in their contribution to the CF pathophysiology. By providing a standardized and effective protocol for sputum processing and microbial enrichment, our study represents an important basis for future studies investigating the physiology of microbial pathogens in CF in vivo – an important prerequisite for the development of novel antimicrobial therapies to combat chronic recurrent airway infection in CF

Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis

The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future

Comprehensive multimodality characterization of hemodynamically significant and non-significant coronary lesions using invasive and noninvasive measures

Background There is limited knowledge about morphological molecular-imaging-derived parameters to further characterize hemodynamically relevant coronary lesions. Objective The aim of this study was to describe and differentiate specific parameters between hemodynamically significant and non-significant coronary lesions using various invasive and non-invasive measures. Methods This clinical study analyzed patients with symptoms suggestive of coronary artery disease (CAD) who underwent native T1-weighted CMR and gadofosveset-enhanced CMR as well as invasive coronary angiography. OCT of the culprit vessel to determine the plaque type was performed in a subset of patients. Functional relevance of all lesions was examined using quantitative flow reserve (QFR-angiography). Hemodynamically significant lesions were defined as lesions with a QFR <0.8. Signal intensity (contrast-to-noise ratios; CNRs) on native T1-weighted CMR and gadofosveset-enhanced CMR was defined as a measure for intraplaque hemorrhage and endothelial permeability, respectively. Results Overall 29 coronary segments from 14 patients were examined. Segments containing lesions with a QFR 0.8; n = 19) (5.32 (4.47–7.02) vs. 2.42 (1.04–5.11); p = 0.042). No differences in signal enhancement were seen on native T1-weighted CMR (2.2 (0.68–6.75) vs. 2.09 (0.91–6.57), p = 0.412). 66.7% (4 out of 6) of all vulnerable plaque and 33.3% (2 out of 6) of all non-vulnerable plaque (fibroatheroma) as assessed by OCT were hemodynamically significant lesions. Conclusion The findings of this pilot study suggest that signal enhancement on albumin-binding probe-enhanced CMR but not on T1-weighted CMR is associated with hemodynamically relevant coronary lesion

Impact of the McDonald Criteria 2017 on Early Diagnosis of Relapsing-Remitting Multiple Sclerosis

Multiple sclerosis is a chronic immune mediated demyelinating disease leading to neurological disabilities that need to be diagnosed and treated early. Guidelines on multiple sclerosis diagnosis and monitoring experienced comprehensive changes over the last decades. The first McDonald criteria published in 2001 emphasized the importance of MR imaging but also recognized the role of cerebrospinal fluid diagnostics. The demonstration of an intrathecal immunoglobulin G synthesis is a well-established additional component and has a long tradition in the diagnosis of relapsing-remitting multiple sclerosis. However, the role of cerebrospinal fluid for diagnostic purposes was rather diminished in each revision of the McDonald criteria. In the latest revision of the McDonald criteria of 2017, the detection of an intrathecal immunoglobulin G synthesis as oligoclonal bands experienced a revival. Patients with the first clinical event suggesting multiple sclerosis who fulfill the criteria for dissemination in space can be diagnosed with relapsing-remitting multiple sclerosis when oligoclonal bands in cerebrospinal fluid are detected. The diagnostic sensitivity of these novel criteria with a focus on dissemination in time and oligoclonal bands as a substitute for dissemination in time was published in different cohorts in the last year and is of special interest in this review. Recently published data show that by applying the 2017 McDonald criteria, multiple sclerosis can be diagnosed more frequently at the time of first clinical event as compared to the 2010 McDonald criteria. The main effect was due to the implementation of oligoclonal bands as a substitute for dissemination in time. However, careful differential diagnosis is essential in patients with atypical clinical manifestations to avoid misdiagnoses

Investigation of Oligoclonal IgG Bands in Tear Fluid of Multiple Sclerosis Patients

Background: Oligoclonal IgG bands (OCB) in the cerebrospinal fluid (CSF) represent a typical marker for inflammation in multiple sclerosis (MS) patients and have a predictive and diagnostic value in patients with a first suspected demyelinating event. The detection in tears remains controversial but some reports suggested a replacement of CSF analysis by OCB detection in tears. We aimed to investigate the value of OCB detection in tears systematically in patients with MS.Methods: Tears of 59 patients with suspected or diagnosed MS were collected with Schirmer filter paper strips. Tear IgG was purified by affinity chromatography with protein G. After isoelectric focusing in polyacrylamide gels OCB detection was performed with direct silver staining. Paired triplets of CSF, serum, and tears were analyzed. For comparison purposes we additionally used other tear collection methods (flush procedure and plastic capillary tubes) or detection techniques (Immunoblotting). Clinical and paraclinical parameters are provided.Results: IgG collection in tears was most reliable by using Schirmer strips. Thirteen patients had to be excluded due to insufficient sample material. Tear specific proteins that interfered with OCB detection were successfully eliminated by IgG purification. The concordance of OCB in tears and CSF of all investigated MS patients was 39% with a high rate of only marginal pattern in tears. Five patients demonstrated restricted bands in tears, neither detectable in CSF nor serum. Occurrence of OCB in tears was significantly associated with pathological visual evoked potentials (P = 0.0094) and a history of optic neuritis (P = 0.0258).Conclusion: Due to the limited concordance, high rate of samples with insufficient material, and the unknown origin of tear IgG we cannot recommend that tear OCB detection may replace CSF OCB detection in MS patients. The detection of unique OCB in tears might offer new insights in ophthalmological diseases

Forecasts, scenarios, visions, backcasts and roadmaps to the hydrogen economy: a review of the hydrogen futures literature

Scenarios, roadmaps and similar foresight methods are used to cope with uncertainty in areas with long planning horizons, such as energy policy, and research into the future of hydrogen energy has been no exception. Such studies can play an important role in the development of shared visions of the future: creating powerful expectations of the potential of emerging technologies and mobilising resources necessary for their realisation. This paper reviews the hydrogen futures literature, using a six-fold typology to map the state of the art of scenario construction. The paper then explores the expectations embodied in the literature, through the 'answers' it provides to questions about the future of hydrogen. What are the drivers, barriers and challenges facing the development of a hydrogen economy? What are the key technological building blocks required? In what kinds of futures does hydrogen become important? What does a hydrogen economy look like, how and when does it evolve, and what does it achieve? The literature describes a diverse range of possible futures, from decentralised systems based upon the small-scale renewables, through to centralised systems reliant on nuclear energy or carbon-sequestration. There is a broad consensus that the hydrogen economy emerges only slowly, if all under 'Business as Usual' scenarios. Rapid transitions to hydrogen occur only under conditions of strong governmental support combined with, or as a result of, major 'discontinuities' such as shifts in society's environmental values, 'game changing' technological breakthroughs, or rapid increases in the oil price or speed and intensity of climate change

Key insights for the future of urban ecosystem services research

Understanding the dynamics of urban ecosystem services is a necessary requirement for adequate planning, management, and governance of urban green infrastructure. Through the three-year Urban Biodiversity and Ecosystem Services (URBES) research project, we conducted case study and comparative research on urban biodiversity and ecosystem services across seven cities in Europe and the United States. Reviewing > 50 peer-reviewed publications from the project, we present and discuss seven key insights that reflect cumulative findings from the project as well as the state-of-the-art knowledge in urban ecosystem services research. The insights from our review indicate that cross-sectoral, multiscale, interdisciplinary research is beginning to provide a solid scientific foundation for applying the ecosystem services framework in urban areas and land management. Our review offers a foundation for seeking novel, nature-based solutions to emerging urban challenges such as wicked environmental change issues