IgG anti-apolipoprotein A-1 antibodies in patients with systemic lupus erythematosus are associated with disease activity and corticosteroid therapy: an observational study.

IgG anti-apolipoprotein A-1 (IgG anti-apoA-1) antibodies are present in patients with systemic lupus erythematosus (SLE) and may link inflammatory disease activity and the increased risk of developing atherosclerosis and cardiovascular disease (CVD) in these patients. We carried out a rigorous analysis of the associations between IgG anti-apoA-1 levels and disease activity, drug therapy, serology, damage, mortality and CVD events in a large British SLE cohort

Integrated life cycle assessment and thermodynamic simulation of a public building's envelope renovation : Conventional vs. Passivhaus proposal

Unidad de excelencia María de Maeztu MdM-2015-0552The need to improve the energy efficiency of buildings has introduced the concept of nearly zero-energy buildings into European energy policies. Moreover, a percentage of the building stock will have to be renovated annually to attain high energy performance. Conventional passive interventions in buildings are focused on increasing the insulation of the building envelope to increase its energy efficiency during the operating phase. Often, however, intervention practices imply the incorporation of embodied energy into the building materials and increase the associated environmental impacts.This paper presents and evaluates a comparison of two different proposals for a real-world building renovation. The first proposal was a conventional project for energy renovation, while the second was a low-energy building proposal (following the Passivhaus standard). This study analysed the proposals using an integrated life cycle and thermal dynamic simulation assessment to identify the adequacy of each renovation alternative regarding the post-renovation energy performance of the building, including an evaluation of the introduction of a renewable insulation material into the low-energy building proposal, specifically a specific cork solution. The most significant conclusion was the convenience of the renovation, achieving energy savings of 60% and 80% for the conventional and Passivhaus renovations (ENERPHIT), respectively. The former supposed less embodied energy and environmental impacts but also generated less energy savings. The latter increased the embodied impacts in the building, mainly for the large amount of insulation material. The environmental implications of both proposals can be compensated for within a reasonable period of time, over 2 years in the majority of alternatives and impact categories. However, the ENERPHIT project was 30% better than the conventional proposal when the total lifespan of the building was considered. The introduction of cork did not fit the requirements for competing with the common non-renewable insulation materials because it did not imply better environmental performance in buildings, but cork insulation solutions currently present ample room for improvement

The Relationship between the UniProt Knowledgebase (UniProtKB) and the IntAct Molecular Interaction Databases

IntAct provides a freely available, open source database system and analysis tools for protein interaction data. All interactions are derived from literature curation or direct user submission and all experimental information relating to binary protein-protein
interactions is entered into the IntAct database by curators, via a web-based editor. Interaction information is added to the SUBUNIT comment and the RP line of the relevant publication within the UniProtKB entry. There may be a single INTERACTION comment present within a UniProtKB entry, which conveys information relevant to binary protein-protein interactions. This is automatically derived from the IntAct database and is updated on a triweekly basis. Interactions can be derived by any appropriate experimental method but must be confirmed by a second interaction if resulting from a single yeast2hybrid experiment. For large-scale experiments, interactions are considered if a high confidence score is assigned by the authors. The INTERACTION line contains a direct link to IntAct that provides detailed information for the experimental support. These lines are not changed manually and any discrepancy is reported to IntAct for updates. There is also a database crossreference line within the UniProtKB entry i.e.: DR IntAct _UniProtKB AC, which directs the user to additional interaction data for that molecule. 
UniProt is supported by grants from the National Institutes of Health, European Commission, Swiss Federal Government and PATRIC BRC.
IntAct is funded by the European Commission under FELICS, contract number 021902 (RII3) within the Research Infrastructure Action of the FP6 "Structuring the European Research Area" Programme

Classification of Multiwavelength Transients with Machine Learning

With the advent of powerful telescopes such as the Square Kilometer Array and the Vera C. Rubin Observatory, we are entering an era of multiwavelength transient astronomy that will lead to a dramatic increase in data volume. Machine learning techniques are well suited to address this data challenge and rapidly classify newly detected transients. We present a multiwavelength classification algorithm consisting of three steps: (1) interpolation and augmentation of the data using Gaussian processes; (2) feature extraction using wavelets; and (3) classification with random forests. Augmentation provides improved performance at test time by balancing the classes and adding diversity into the training set. In the first application of machine learning to the classification of real radio transient data, we apply our technique to the Green Bank Interferometer and other radio light curves. We find we are able to accurately classify most of the 11 classes of radio variables and transients after just eight hours of observations, achieving an overall test accuracy of 78 percent. We fully investigate the impact of the small sample size of 82 publicly available light curves and use data augmentation techniques to mitigate the effect. We also show that on a significantly larger simulated representative training set that the algorithm achieves an overall accuracy of 97 percent, illustrating that the method is likely to provide excellent performance on future surveys. Finally, we demonstrate the effectiveness of simultaneous multiwavelength observations by showing how incorporating just one optical data point into the analysis improves the accuracy of the worst performing class by 19 percent.Comment: 16 pages, 12 figure

Mediated Remote Synchronization of Kuramoto-Sakaguchi Oscillators: the Number of Mediators Matters

Cortical regions without direct neuronal connections have been observed to exhibit synchronized dynamics. A recent empirical study has further revealed that such regions that share more common neighbors are more likely to behave coherently. To analytically investigate the underlying mechanisms, we consider that a set of n oscillators, which have no direct connections, are linked through m intermediate oscillators (called mediators), forming a complete bipartite network structure. Modeling the oscillators by the Kuramoto-Sakaguchi model, we rigorously prove that mediated remote synchronization, i.e., synchronization between those n oscillators that are not directly connected, becomes more robust as the number of mediators increases. Simulations are also carried out to show that our theoretical findings can be applied to other general and complex networks

Constraining a Model of the Radio Sky Below 6 MHz Using the Parker Solar Probe/FIELDS Instrument in Preparation for Upcoming Lunar-based Experiments

We present a Bayesian analysis of data from the FIELDS instrument on board the Parker Solar Probe (PSP) spacecraft with the aim of constraining low frequency ($\lesssim$ 6 MHz) sky in preparation for several upcoming lunar-based experiments. We utilize data recorded during PSP's ``coning roll'' maneuvers, in which the axis of the spacecraft is pointed 45$^{\circ}$ off of the Sun. The spacecraft then rotates about a line between the Sun and the spacecraft with a period of 24 minutes. We reduce the data into two formats: roll-averaged, in which the spectra are averaged over the roll, and phase-binned, in which the spectra are binned according to the phase of the roll. We construct a forward model of the FIELDS observations that includes numerical simulations of the antenna beam, an analytic emissivity function of the galaxy, and estimates of the absorption due to free electrons. Fitting 5 parameters, we find that the roll-averaged data can be fit well by this model and we obtain posterior parameter constraints that are in general agreement with previous estimates. The model is not, however, able to fit the phase-binned data well, likely due to limitations such as the lack of non-smooth emission structure at both small and large scales, enforced symmetry between the northern and southern galactic hemispheres, and large uncertainties in the free electron density. This suggests that significant improvement in the low frequency sky model is needed in order to fully and accurately represent the sky at frequencies below 6 MHz.Comment: 18 pages, 10 figures, 5 tables. Under review in the Astrophysical Journa

Structural subnetwork evolution across the life-span: rich-club, feeder, seeder

The impact of developmental and aging processes on brain connectivity and the connectome has been widely studied. Network theoretical measures and certain topological principles are computed from the entire brain, however there is a need to separate and understand the underlying subnetworks which contribute towards these observed holistic connectomic alterations. One organizational principle is the rich-club - a core subnetwork of brain regions that are strongly connected, forming a high-cost, high-capacity backbone that is critical for effective communication in the network. Investigations primarily focus on its alterations with disease and age. Here, we present a systematic analysis of not only the rich-club, but also other subnetworks derived from this backbone - namely feeder and seeder subnetworks. Our analysis is applied to structural connectomes in a normal cohort from a large, publicly available lifespan study. We demonstrate changes in rich-club membership with age alongside a shift in importance from 'peripheral' seeder to feeder subnetworks. Our results show a refinement within the rich-club structure (increase in transitivity and betweenness centrality), as well as increased efficiency in the feeder subnetwork and decreased measures of network integration and segregation in the seeder subnetwork. These results demonstrate the different developmental patterns when analyzing the connectome stratified according to its rich-club and the potential of utilizing this subnetwork analysis to reveal the evolution of brain architectural alterations across the life-span

Influence of wiring cost on the large-scale architecture of human cortical connectivity

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain