Orbital Parameters and Spectroscopy of the Transient X-Ray Pulsar 4U 0115+63

We report on an outburst of the high mass X-ray binary 4U 0115+63 with a pulse period of 3.6s in spring 2008 as observed with INTEGRAL and RXTE. By analyzing the lightcurves we derive an updated orbital- and pulse period ephemeris of the neutron star. We also study the pulse profile variations as a function of time and energy as well as the variability of the spectral parameters. We find clear evidence for at least three cyclotron line features. In agreement with previous observations of 4U 0115+63, we detect an anti-correlation between the luminosity and the fundamental cyclotron line energy

Investigation of a nonsense mutation located in the complex KIV-2 copy number variation region of apolipoprotein(a) in 10,910 individuals

Background The concentrations of the highly atherogenic lipoprotein(a) [Lp(a)] are mainly genetically determined by the LPA gene locus. However, up to 70% of the coding sequence is located in the complex so-called kringle IV type 2 (KIV-2) copy number variation, a region hardly accessible by common genotyping and sequencing technologies. Despite its size, little is known about genetic variants in this complex region. The R21X variant is a functional variant located in this region, but it has never been analyzed in large cohorts. Methods We typed R21X in 10,910 individuals from three European populations using a newly developed high-throughput allele-specific qPCR assay. R21X allelic location was determined by separating the LPA alleles using pulsed-field gel electrophoresis (PFGE) and typing them separately. Using GWAS data, we identified a proxy SNP located outside of the KIV-2. Linkage disequilibrium was determined both statistically and by long-range haplotyping using PFGE. Worldwide frequencies were determined by reanalyzing the sequencing data of the 1000 Genomes Project with a dedicated pipeline. Results R21X carriers (frequency 0.016–0.021) showed significantly lower mean Lp(a) concentrations (− 11.7 mg/dL [− 15.5; − 7.82], p = 3.39e−32). The variant is located mostly on medium-sized LPA alleles. In the 1000 Genome data, R21X mostly occurs in Europeans and South Asians, is absent in Africans, and shows varying frequencies in South American populations (0 to 0.022). Of note, the best proxy SNP was another LPA null mutation (rs41272114, D′ = 0.958, R2 = 0.281). D′ was very high in all 1000G populations (0.986–0.996), although rs41272114 frequency varies considerably (0–0.182). Co-localization of both null mutations on the same allele was confirmed by PFGE-based long-range haplotyping. Conclusions We performed the largest epidemiological study on an LPA KIV-2 variant so far, showing that it is possible to assess LPA KIV-2 mutations on a large scale. Surprisingly, in all analyzed populations, R21X was located on the same haplotype as the splice mutation rs41272114, creating “double-null” LPA alleles. Despite being a nonsense variant, the R21X status does not provide additional information beyond the rs41272114 genotype. This has important implications for studies using LPA loss-of-function mutations as genetic instruments and emphasizes the complexity of LPA genetics

Local electric-field control of multiferroic spin-spiral domains in TbMnO3

Spin-spiral multiferroics exhibit a magnetoelectric coupling effects, leading to the formation of hybrid domains with inseparably entangled ferroelectric and antiferromagnetic order parameters. Due to this strong magnetoelectric coupling, conceptually advanced ways for controlling antiferromagnetism become possible and it has been reported that electric fields and laser pulses can reversibly switch the antiferromagnetic order. This switching of antiferromagnetic spin textures is of great interest for the emergent field of antiferromagnetic spintronics. Established approaches, however, require either high voltages or intense laser fields and are currently limited to the micrometer length scale, which forfeits the technological merit. Here, we image and control hybrid multiferroic domains in the spin-spiral system TbMnO3 using low-temperature electrostatic force microscopy (EFM). First, we show that image generation in EFM happens via surface screening charges, which allows for probing the previously hidden magnetically induced ferroelectric order in TbMnO3 (PS = 6 × 10−4 C/m2). We then set the antiferromagnetic domain configuration by acting on the surface screening charges with the EFM probe tip. Our study enables detection of entangled ferroelectric and antiferromagnetic domains with high sensitivity. The spatial resolution is limited only by the physical size of the probe tip, introducing a pathway towards controlling antiferromagnetic order at the nanoscale and with low energy.P.S., S.M., L.K., M.F. and D.M. acknowledge financial support by the SNSF projects 206021_150635, 200021_149192, 200021_178825. A.I. and T.K. were supported by JSPS KAKENHI under grant numbers JP17H01143 and JP19H05823. K.S. acknowledges the support of the European Research Council under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 724529) and Ministerio de Economia, Industria y Competitividad through Grant Nos. MAT2016-77100-C2-2-P and SEV-2015-0496. D.M. is supported by the Research Council of Norway (FRINATEK Project No. 263228/F20) and the Norwegian University of Science and Technology (NTNU) through the Onsager Fellowship Programme and the Outstanding Academic Fellows Programme.Peer reviewe

Local electric-field control of multiferroic spin-spiral domains in TbMnO3

Spin-spiral multiferroics exhibit a magnetoelectric coupling effects, leading to the formation of hybrid domains with inseparably entangled ferroelectric and antiferromagnetic order parameters. Due to this strong magnetoelectric coupling, conceptually advanced ways for controlling antiferromagnetism become possible and it has been reported that electric fields and laser pulses can reversibly switch the antiferromagnetic order. This switching of antiferromagnetic spin textures is of great interest for the emergent field of antiferromagnetic spintronics. Established approaches, however, require either high voltages or intense laser fields and are currently limited to the micrometer length scale, which forfeits the technological merit. Here, we image and control hybrid multiferroic domains in the spin-spiral system TbMnO3 using low-temperature electrostatic force microscopy (EFM). First, we show that image generation in EFM happens via surface screening charges, which allows for probing the previously hidden magnetically induced ferroelectric order in TbMnO3 (PS = 6 × 10−4 C/m2 ). We then set the antiferromagnetic domain configuration by acting on the surface screening charges with the EFM probe tip. Our study enables detection of entangled ferroelectric and antiferromagnetic domains with high sensitivity. The spatial resolution is limited only by the physical size of the probe tip, introducing a pathway towards controlling antiferromagnetic order at the nanoscale and with low energy

An Artificial Intelligence Generated Automated Algorithm to Measure Total Kidney Volume in ADPKD

Accurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, we report an artificial intelligence (AI)-generated method for routinely measuring total kidney volume (TKV). An ensemble U-net algorithm was created using the nnUNet approach. The training and internal cross-validation cohort consisted of all 1.5T magnetic resonance imaging (MRI) data acquired using 5 different MRI scanners (454 kidneys, 227 scans) in the CYSTic consortium, which was first manually segmented by a single human operator. As an independent validation cohort, we utilized 48 sequential clinical MRI scans with reference results of manual segmentation acquired by 6 individual analysts at a single center. The tool was then implemented for clinical use and its performance analyzed. The training or internal validation cohort was younger (mean age 44.0 vs. 51.5 years) and the female-to-male ratio higher (1.2 vs. 0.94) compared to the clinical validation cohort. The majority of CYSTic patients had PKD1 mutations (79%) and typical disease (Mayo Imaging class 1, 86%). The median DICE score on the clinical validation data set between the algorithm and human analysts was 0.96 for left and right kidneys with a median TKV error of −1.8%. The time taken to manually segment kidneys in the CYSTic data set was 56 (±28) minutes, whereas manual corrections of the algorithm output took 8.5 (±9.2) minutes per scan. Our AI-based algorithm demonstrates performance comparable to manual segmentation. Its rapidity and precision in real-world clinical cases demonstrate its suitability for clinical application

Reference-based phasing using the Haplotype Reference Consortium panel

Haplotype phasing is a fundamental problem in medical and population genetics. Phasing is generally performed via statistical phasing within a genotyped cohort, an approach that can attain high accuracy in very large cohorts but attains lower accuracy in smaller cohorts. Here, we instead explore the paradigm of reference-based phasing. We introduce a new phasing algorithm, Eagle2, that attains high accuracy across a broad range of cohort sizes by efficiently leveraging information from large external reference panels (such as the Haplotype Reference Consortium, HRC) using a new data structure based on the positional Burrows-Wheeler transform. We demonstrate that Eagle2 attains a ≈20x speedup and ≈10% increase in accuracy compared to reference-based phasing using SHAPEIT2. On European-ancestry samples, Eagle2 with the HRC panel achieves >2x the accuracy of 1000 Genomes-based phasing. Eagle2 is open source and freely available for HRC-based phasing via the Sanger Imputation Service and the Michigan Imputation Server

Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software (https://github.com/immunogenomics/HLA_analyses_tutorial). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.N