ALBERT

Beschreibung: We present a study of timing properties of the accreting pulsar 2S 1417-624 observed during its 2018 outburst, based on Swift/BAT, Fermi/GBM, Insight-HXMT and NICER observations. We report a dramatic change of the pulse profiles with luminosity. The morphology of the profile in the range 0.2-10.0 keV switches from double to triple peaks at ∼2.5 $ m imes 10^{37}{it D}_{10}^2 erg s^{-1}$ and from triple to quadruple peaks at ∼7 $ m imes 10^{37}{it D}_{10}^2 erg s^{-1}$. The profile at high energies (25-100 keV) shows significant evolutions as well. We explain this phenomenon according to existing theoretical models. We argue that the first change is related to the transition from the sub to the super-critical accretion regime, while the second to the transition of the accretion disc from the gas-dominated to the radiation pressure-dominated state. Considering the spin-up as well due to the accretion torque, this interpretation allows to estimate the magnetic field self-consistently at ∼7 × 1012 G.

Beschreibung: We report on analysis of observations of the bright transient X-ray pulsar Swift J0243.6+6124 obtained during its 2017-2018 giant outburst with Insight-HXMT, NuSTAR, and Swift observatories. We focus on the discovery of a sharp state transition of the timing and spectral properties of the source at super-Eddington accretion rates, which we associate with the transition of the accretion disk to a radiation pressure dominated (RPD) state, the first ever directly observed for magnetized neutron star. This transition occurs at slightly higher luminosity compared to already reported transition of the source from sub- to super-critical accretion regime associate with onset of an accretion column. We argue that this scenario can only be realized for comparatively weakly magnetized neutron star, not dissimilar to other ultra-luminous X-ray pulsars (ULPs), which accrete at similar rates. Further evidence for this conclusion is provided by the non-detection of the transition to the propeller state in quiescence which strongly implies compact magnetosphere and thus rules out magnetar-like fields.

Beschreibung: 〈p〉The edges of layered materials have unique properties that substantially differ from the body regions. In this work, we perform a systematic Raman study of the edges of various layered materials (MoS〈sub〉2〈/sub〉, WS〈sub〉2〈/sub〉, WSe〈sub〉2〈/sub〉, PtS〈sub〉2〈/sub〉, and black phosphorus). The Raman spectra of the edges feature newly observed forbidden Raman modes, which are originally undetectable from the body region. By selecting the edge type and the polarization directions of the incident and scattered light, all forbidden Raman modes are distinctly detected. Optical simulations show that the edges of layered materials drastically distort the electromagnetic fields of both the incident and scattered light, so that the light interacts with the edges in a distinct way, which differs from its interactions with the body regions.〈/p〉

Beschreibung: The edges of layered materials have unique properties that substantially differ from the body regions. In this work, we perform a systematic Raman study of the edges of various layered materials (MoS 2 , WS 2 , WSe 2 , PtS 2 , and black phosphorus). The Raman spectra of the edges feature newly observed forbidden Raman modes, which are originally undetectable from the body region. By selecting the edge type and the polarization directions of the incident and scattered light, all forbidden Raman modes are distinctly detected. Optical simulations show that the edges of layered materials drastically distort the electromagnetic fields of both the incident and scattered light, so that the light interacts with the edges in a distinct way, which differs from its interactions with the body regions.

Beschreibung: We present CCD UBVRI photometry of the field of the open cluster NGC 6866. Structural parameters of the cluster are determined utilizing the stellar density profile of the stars in the field. We calculate the probabilities of the stars being physical members of the cluster, using their astrometric data, and perform further analyses using only the most probable members. The reddening and metallicity of the cluster were determined by independent methods. The LAMOST spectra and the ultraviolet excess of the F- and G-type main-sequence stars in the cluster indicate that the metallicity of the cluster is about the solar value. We estimated the reddening E ( B – V ) = 0.074 ± 0.050 mag using the U – B versus B – V two-colour diagram. The distance modula, the distance and the age of NGC 6866 were derived as μ = 10.60 ± 0.10 mag, d  = 1189 ± 75 pc and t  = 813 ± 50 Myr, respectively, by fitting colour–magnitude diagrams of the cluster with the PARSEC isochrones. The Galactic orbit of NGC 6866 indicates that the cluster is orbiting in a slightly eccentric orbit with e  = 0.12. The mass function slope x  = 1.35 ± 0.08 was derived by using the most probable members of the cluster.

Beschreibung: Motivation: Identifying protein subchloroplast localization in chloroplast organelle is very helpful for understanding the function of chloroplast proteins. There have existed a few computational prediction methods for protein subchloroplast localization. However, these existing works have ignored proteins with multiple subchloroplast locations when constructing prediction models, so that they can predict only one of all subchloroplast locations of this kind of multilabel proteins. Results: To address this problem, through utilizing label-specific features and label correlations simultaneously, a novel multilabel classifier was developed for predicting protein subchloroplast location(s) with both single and multiple location sites. As an initial study, the overall accuracy of our proposed algorithm reaches 55.52%, which is quite high to be able to become a promising tool for further studies. Availability and implementation: An online web server for our proposed algorithm named MultiP-SChlo was developed, which are freely accessible at http://biomed.zzuli.edu.cn/bioinfo/multip-schlo/ . Contact: pandaxiaoxi@gmail.com or gzli@tongji.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Defective lysosomal acid β-glucosidase (GCase) in Gaucher disease causes accumulation of glucosylceramide (GC) and glucosylsphingosine (GS) that distress cellular functions. To study novel pathological mechanisms in neuronopathic Gaucher disease (nGD), a mouse model (4L;C*), an analogue to subacute human nGD, was investigated for global profiles of differentially expressed brain mRNAs (DEGs) and miRNAs (DEmiRs). 4L;C* mice displayed accumulation of GC and GS, activated microglial cells, reduced number of neurons and aberrant mitochondrial function in the brain followed by deterioration in motor function. DEGs and DEmiRs were characterized from sequencing of mRNA and miRNA from cerebral cortex, brain stem, midbrain and cerebellum of 4L;C* mice. Gene ontology enrichment and pathway analysis showed preferential mitochondrial dysfunction in midbrain and uniform inflammatory response and identified novel pathways, axonal guidance signaling, synaptic transmission, eIF2 and mammalian target of rapamycin (mTOR) signaling potentially involved in nGD. Similar analyses were performed with mice treated with isofagomine (IFG), a pharmacologic chaperone for GCase. IFG treatment did not alter the GS and GC accumulation significantly but attenuated the progression of the disease and altered numerous DEmiRs and target DEGs to their respective normal levels in inflammation, mitochondrial function and axonal guidance pathways, suggesting its regulation on miRNA and the associated mRNA that underlie the neurodegeneration in nGD. These analyses demonstrate that the neurodegenerative phenotype in 4L;C* mice was associated with dysregulation of brain mRNAs and miRNAs in axonal guidance, synaptic plasticity, mitochondria function, eIF2 and mTOR signaling and inflammation and provides new insights for the nGD pathological mechanism.

Beschreibung: Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically ‘small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as ‘large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression data from a malaria vaccine trial by big-data-based edge biomarkers from module network rewiring-analysis. The illustrative results show that the identified module biomarkers can accurately distinguish vaccines with or without protection and outperformed previous reported gene signatures in terms of effectiveness and efficiency.

Beschreibung: Recombinant adenoviruses containing a double-stranded DNA genome of 26–45 kb were broadly explored in basic virology, for vaccination purposes, for treatment of tumors based on oncolytic virotherapy, or simply as a tool for efficient gene transfer. However, the majority of recombinant adenoviral vectors (AdVs) is based on a small fraction of adenovirus types and their genetic modification. Recombineering techniques provide powerful tools for arbitrary engineering of recombinant DNA. Here, we adopted a seamless recombineering technology for high-throughput and arbitrary genetic engineering of recombinant adenoviral DNA molecules. Our cloning platform which also includes a novel recombination pipeline is based on bacterial artificial chromosomes (BACs). It enables generation of novel recombinant adenoviruses from different sources and switching between commonly used early generation AdVs and the last generation high-capacity AdVs lacking all viral coding sequences making them attractive candidates for clinical use. In combination with a novel recombination pipeline allowing cloning of AdVs containing large and complex transgenes and the possibility to generate arbitrary chimeric capsid-modified adenoviruses, these techniques allow generation of tailored AdVs with distinct features. Our technologies will pave the way toward broader applications of AdVs in molecular medicine including gene therapy and vaccination studies.