A Consistent Picture Emerges: A Compact X-ray Continuum Emission Region in the Gravitationally Lensed Quasar SDSS J0924+0219

We analyze the optical, UV, and X-ray microlensing variability of the lensed quasar SDSS J0924+0219 using six epochs of Chandra data in two energy bands (spanning 0.4-8.0 keV, or 1-20 keV in the quasar rest frame), 10 epochs of F275W (rest-frame 1089A) Hubble Space Telescope data, and high-cadence R-band (rest-frame 2770A) monitoring spanning eleven years. Our joint analysis provides robust constraints on the extent of the X-ray continuum emission region and the projected area of the accretion disk. The best-fit half-light radius of the soft X-ray continuum emission region is between 5x10^13 and 10^15 cm, and we find an upper limit of 10^15 cm for the hard X-rays. The best-fit soft-band size is about 13 times smaller than the optical size, and roughly 7 GM_BH/c^2 for a 2.8x10^8 M_sol black hole, similar to the results for other systems. We find that the UV emitting region falls in between the optical and X-ray emitting regions at 10^14 cm < r_1/2,UV < 3x10^15 cm. Finally, the optical size is significantly larger, by 1.5*sigma, than the theoretical thin-disk estimate based on the observed, magnification-corrected I-band flux, suggesting a shallower temperature profile than expected for a standard disk.Comment: Replaced with accepted version to Ap

The Utilization of Data Analysis Techniques in Predicting Student Performance in Massive Open Online Courses (MOOCs)

The growth of the Internet has enabled the popularity of open online learning platforms to increase over the years. This has led to the inception of Massive Open Online Courses (MOOCs) that enrol, millions of people, from all over the world. Such courses operate under the concept of open learning, where content does not have to be delivered via standard mechanisms that institutions employ, such as physically attending lectures. Instead learning occurs online via recorded lecture material and online tasks. This shift has allowed more people to gain access to education, regardless of their learning background. However, despite these advancements in delivering education, completion rates for MOOCs are low. In order to investigate this issue, the paper explores the impact that technology has on open learning and identifies how data about student performance can be captured to predict trend so that at risk students can be identified before they drop-out. In achieving this, subjects surrounding student engagement and performance in MOOCs and data analysis techniques are explored to investigate how technology can be used to address this issue. The paper is then concluded with our approach of predicting behaviour and a case study of the eRegister system, which has been developed to capture and analyse data. Keywords: Open Learning; Prediction; Data Mining; Educational Systems; Massive Open Online Course; Data Analysi

Regulation of ABCC6 trafficking and stability by a conserved C-terminal PDZ-like sequence

Mutations in the ABCC6 ABC-transporter are causative of pseudoxanthoma elasticum (PXE). The loss of functional ABCC6 protein in the basolateral membrane of the kidney and liver is putatively associated with altered secretion of a circulatory factor. As a result, systemic changes in elastic tissues are caused by progressive mineralization and degradation of elastic fibers. Premature arteriosclerosis, loss of skin and vascular tone, and a progressive loss of vision result from this ectopic mineralization. However, the identity of the circulatory factor and the specific role of ABCC6 in disease pathophysiology are not known. Though recessive loss-of-function alleles are associated with alterations in ABCC6 expression and function, the molecular pathologies associated with the majority of PXE-causing mutations are also not known. Sequence analysis of orthologous ABCC6 proteins indicates the C-terminal sequences are highly conserved and share high similarity to the PDZ sequences found in other ABCC subfamily members. Genetic testing of PXE patients suggests that at least one disease-causing mutation is located in a PDZ-like sequence at the extreme C-terminus of the ABCC6 protein. To evaluate the role of this C-terminal sequence in the biosynthesis and trafficking of ABCC6, a series of mutations were utilized to probe changes in ABCC6 biosynthesis, membrane stability and turnover. Removal of this PDZ-like sequence resulted in decreased steady-state ABCC6 levels, decreased cell surface expression and stability, and mislocalization of the ABCC6 protein in polarized cells. These data suggest that the conserved, PDZ-like sequence promotes the proper biosynthesis and trafficking of the ABCC6 protein. © 2014 Xue et al

Use of an Electrochemical Split Cell Technique to Evaluate the Influence of Shewanella oneidensis Activities on Corrosion of Carbon Steel

Microbially induced corrosion (MIC) is a complex problem that affects various industries. Several techniques have been developed to monitor corrosion and elucidate corrosion mechanisms, including microbiological processes that induce metal deterioration. We used zero resistance ammetry (ZRA) in a split chamber configuration to evaluate the effects of the facultatively anaerobic Fe(III) reducing bacterium Shewanella oneidensis MR-1 on the corrosion of UNS G10180 carbon steel. We show that activities of S. oneidensis inhibit corrosion of steel with which that organism has direct contact. However, when a carbon steel coupon in contact with S. oneidensis was electrically connected to a second coupon that was free of biofilm (in separate chambers of the split chamber assembly), ZRA-based measurements indicated that current moved from the S. oneidensis-containing chamber to the cell-free chamber. This electron transfer enhanced the O2 reduction reaction on the coupon deployed in the cell free chamber, and consequently, enhanced oxidation and corrosion of that electrode. Our results illustrate a novel mechanism for MIC in cases where metal surfaces are heterogeneously covered by biofilms

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014–2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic