Detection of Coronal Mass Ejections in V471 Tauri with the Hubble Space Telescope

V471 Tauri, an eclipsing system consisting of a hot DA white dwarf (WD) and a dK2 companion in a 12.5-hour orbit, is the prototype of the pre-cataclysmic binaries. The late-type component is magnetically active, due to its being constrained to rotate synchronously with the short orbital period. During a program of UV spectroscopy of V471 Tau, carried out with the Goddard High Resolution Spectrograph (GHRS) onboard the Hubble Space Telescope, we serendipitously detected two episodes in which transient absorptions in the Si III 1206 A resonance line appeared suddenly, on a timescale of <2 min. The observations were taken in a narrow spectral region around Ly-alpha, and were all obtained near the two quadratures of the binary orbit, i.e., at maximum projected separation (~3.3 Rsun) of the WD and K star. We suggest that these transient features arise when coronal mass ejections (CME's) from the K2 dwarf pass across the line of sight to the WD. Estimates of the velocities, densities, and masses of the events in V471 Tau are generally consistent with the properties of solar CME's. Given our detection of 2 events during 6.8 hr of GHRS observing, along with a consideration of the restricted range of latitudes and longitudes on the K star's surface that can give rise to trajectories passing in front of the WD as seen from Earth, we estimate that the active V471 Tau dK star emits some 100-500 CME's per day, as compared to 1-3 per day for the Sun. The K dwarf's mass-loss rate associated with CME's is at least (5-25) x 10^{-14} Msun/yr, but it may well be orders of magnitude higher if most of the silicon is in ionization states other than Si III.Comment: 24 pages AASTeX, 4 figures. Accepted by Astrophysical Journa

Compatibility of Zr2AlCZr_{2}AlC MAX phase-based ceramics with oxygen-poor, static liquid lead-bismuth eutectic

This work investigates the compatibility of $Zr_{2}AlC$ MAX phase-based ceramics with liquid LBE, and proposes a mechanism to explain the observed local $Zr_{2}AlC$/LBE interaction. The ceramics were exposed to oxygen-poor ($C_{O}\le2.2 \cdot10^{-10}$ mass%), static liquid LBE at 500{\deg}C for 1000 h. A new $Zr_{2}(Al,Bi,Pb)C$ MAX phase solid solution formed in-situ in the LBE-affected $Zr_{2}AlC$ grains. Out-of-plane ordering was favorable in the new solid solution, whereby $\textit{A}$-layers with high and low-Bi/Pb contents alternated in the crystal structure, in agreement with first-principles calculations. Bulk $Zr_{2}(Al,Bi,Pb)C$ was synthesized by reactive hot pressing to study the crystal structure of the solid solution by neutron diffraction

Renal amyloidosis in children

Renal amyloidosis is a detrimental disease caused by the deposition of amyloid fibrils. A child with renal amyloidosis may present with proteinuria or nephrotic syndrome. Chronic renal failure may follow. Amyloid fibrils may deposit in other organs as well. The diagnosis is through the typical appearance on histopathology. Although chronic infections and chronic inflammatory diseases used to be the causes of secondary amyloidosis in children, the most frequent cause is now autoinflammatory diseases. Among this group of diseases, the most frequent one throughout the world is familial Mediterranean fever (FMF). FMF is typically characterized by attacks of clinical inflammation in the form of fever and serositis and high acute-phase reactants. Persisting inflammation in inadequately treated disease is associated with the development of secondary amyloidosis. The main treatment is colchicine. A number of other monogenic autoinflammatory diseases have also been identified. Among them cryopyrin-associated periodic syndrome (CAPS) is outstanding with its clinical features and the predilection to develop secondary amyloidosis in untreated cases. The treatment of secondary amyloidosis mainly depends on the treatment of the disease. However, a number of new treatments for amyloid per se are in the pipeline

Data Descriptor : A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins

Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment.Peer reviewe

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent