bluuebunny/crossref_metadata_2025_split huggingface dataset:
Charge-exchange soft X-ray emission of highly charged ions with inclusion of multiple-electron capture
Authors: Liang G Y , Zhu X L , Wei H G , Yuan D W , Zhong J Y , Wu Y , Hutton R , Cui W , Ma X W , Zhao G 
Published: September 2021

ABSTRACT
Charge exchange has been recognized as a primary source of soft X-ray emission in many astrophysical outflow environments, including cometary and planetary exospheres impacted by the solar wind. Some models have been set up by using different data collections of charge-exchange cross-sections. However, multiple-electron transfer has not been included in these models. In this paper, we set up a charge-exchange model with the inclusion of double-electron capture (DEC), and make a detailed investigation of this process on X-ray emissions of highly charged carbon, nitrogen, oxygen, and neon ions by using available experimental cross-sections. We also study the effect of different n-selective cross-sections on soft X-ray emission by using available experimental n-distributions. This work reveals that DEC enhancement on line intensity is linearly proportional to the ratio of ion abundance in the solar wind. It is more obvious for soft X-rays from carbon ions (C4+) in collision with CO2, and the enhancement on line intensity can be up to 53 per cent with typical ion abundances [Advanced Composition Explorer (ACE)] in the solar wind. The synthetic spectra with parameters from the Ulysses mission for the solar wind reveal velocity dependence, target dependence, as well as the non-negligible contribution from the DEC.
Gamma-ray burst detection prospects for next generation ground-based VHE facilities
Authors: La Mura G , Barres de Almeida U , Conceição R , De Angelis A , Longo F , Pimenta M , Prandini E , Ruiz-Velasco E , Tomé B 
Published: September 2021

ABSTRACT
Gamma-ray Bursts (GRB) were discovered by satellite-based detectors as powerful sources of transient γ-ray emission. The Fermi satellite detected an increasing number of these events with its dedicated Gamma-ray Burst Monitor (GBM), some of which were associated with high energy photons ($E \gt 10$ GeV), by the Large Area Telescope (LAT). More recently, follow-up observations by Cherenkov telescopes detected very high energy emission ($E \gt 100$ GeV) from GRBs, opening up a new observational window with implications on the interpretation of their central engines and on the propagation of very energetic photons across the Universe. Here, we use the data published in the 2nd Fermi-LAT Gamma Ray Burst Catalogue to characterize the duration, luminosity, redshift, and light curve of the high energy GRB emission. We extrapolate these properties to the very high energy domain, comparing the results with available observations and with the potential of future instruments. We use observed and simulated GRB populations to estimate the chances of detection with wide-field ground-based γ-ray instruments. Our analysis aims to evaluate the opportunities of the Southern Wide-field-of-view Gamma-ray Observatory (SWGO), to be installed in the Southern Hemisphere, to complement CTA. We show that a low-energy observing threshold ($E_{low} \lt 200$ GeV), with good point source sensitivity ($F_{lim} \approx 10^{-11} \,\mathrm{erg\, cm^{-2}\, s^{-1}}$ in $1$ yr), are optimal requirements to work as a GRB trigger facility and to probe the burst spectral properties down to time-scales as short as $10$ s, accessing a time domain that will not be available to Imaging Atmospheric Cherenkov Telescopes instruments.
Supplying angular momentum to the jittering jets explosion mechanism using inner convection layers
Authors: Shishkin Dmitry , Soker Noam 
Published: September 2021

ABSTRACT
We conduct one-dimensional stellar evolution simulations in the mass range 13–20 M⊙ to late core collapse times and find that an inner vigorous convective zone with large specific angular momentum fluctuations appears at the edge of the iron core during the collapse. The compression of this zone during the collapse increases the luminosity there and the convective velocities, such that the specific angular momentum fluctuations are of the order of $j_{\rm conv} \simeq 5 \times 10^{15} {~\rm cm}^2 {~\rm s}^{-1}$. If we consider that three-dimensional simulations show convective velocities that are three to four times larger than what the mixing length theory gives, and that the spiral standing accretion shock instability in the post-shock region of the stalled shock at a radius of ${\simeq}100 {~\rm km}$ amplifies perturbations, we conclude that the fluctuations that develop during core collapse are likely to lead to stochastic (intermittent) accretion discs around the newly born neutron star. In reaching this conclusion, we also make two basic assumptions with uncertainties that we discuss. Such intermittent discs can launch jets that explode the star in the frame of the jittering jets explosion mechanism.
Multiple Sources of Introduction of North AmericanArabidopsis thalianafrom across Eurasia
Authors: Shirsekar Gautam , Devos Jane , Latorre Sergio M , Blaha Andreas , Queiroz Dias Maique , González Hernando Alba , Lundberg Derek S , Burbano Hernán A , Fenster Charles B , Weigel Detlef 
Published: September 2021

AbstractLarge-scale movement of organisms across their habitable range, or migration, is an important evolutionary process that can shape genetic diversity and influence the adaptive spread of alleles. Although human migrations have been studied in great detail with modern and ancient genomes, recent anthropogenic influence on reducing the biogeographical constraints on the migration of nonnative species has presented opportunities in several study systems to ask the questions about how repeated introductions shape genetic diversity in the introduced range. We present an extensive overview of population structure of North American Arabidopsis thaliana by studying a set of 500 whole-genome sequenced and over 2,800 RAD-seq genotyped individuals in the context of global diversity represented by Afro-Eurasian genomes. We use methods based on haplotype and rare-allele sharing as well as phylogenetic modeling to identify likely sources of introductions of extant N. American A. thaliana from the native range in Africa and Eurasia. We find evidence of admixture among the introduced lineages having increased haplotype diversity and reduced mutational load. We also detect signals of selection in immune-system-related genes that may impart qualitative disease resistance to pathogens of bacterial and oomycete origin. We conclude that multiple introductions to a nonnative range can rapidly enhance the adaptive potential of a colonizing species by increasing haplotypic diversity through admixture. Our results lay the foundation for further investigations into the functional significance of admixture.
Selection on Accessible Chromatin Regions inCapsella grandiflora
Authors: Horvath Robert , Josephs Emily B , Pesquet Edouard , Stinchcombe John R , Wright Stephen I , Scofield Douglas , Slotte Tanja 
Published: September 2021

AbstractAccurate estimates of genome-wide rates and fitness effects of new mutations are essential for an improved understanding of molecular evolutionary processes. Although eukaryotic genomes generally contain a large noncoding fraction, functional noncoding regions and fitness effects of mutations in such regions are still incompletely characterized. A promising approach to characterize functional noncoding regions relies on identifying accessible chromatin regions (ACRs) tightly associated with regulatory DNA. Here, we applied this approach to identify and estimate selection on ACRs in Capsella grandiflora, a crucifer species ideal for population genomic quantification of selection due to its favorable population demography. We describe a population-wide ACR distribution based on ATAC-seq data for leaf samples of 16 individuals from a natural population. We use population genomic methods to estimate fitness effects and proportions of positively selected fixations (α) in ACRs and find that intergenic ACRs harbor a considerable fraction of weakly deleterious new mutations, as well as a significantly higher proportion of strongly deleterious mutations than comparable inaccessible intergenic regions. ACRs are enriched for expression quantitative trait loci (eQTL) and depleted of transposable element insertions, as expected if intergenic ACRs are under selection because they harbor regulatory regions. By integrating empirical identification of intergenic ACRs with analyses of eQTL and population genomic analyses of selection, we demonstrate that intergenic regulatory regions are an important source of nearly neutral mutations. These results improve our understanding of selection on noncoding regions and the role of nearly neutral mutations for evolutionary processes in outcrossing Brassicaceae species.
Small circular interfering RNAs (sciRNAs) as a potent therapeutic platform for gene-silencing
Authors: Jahns Hartmut , Degaonkar Rohan , Podbevsek Peter , Gupta Swati , Bisbe Anna , Aluri Krishna , Szeto John , Kumar Pawan , LeBlanc Sarah , Racie Tim , Brown Christopher R , Castoreno Adam , Guenther Dale C , Jadhav Vasant , Maier Martin A , Plavec Janez , Egli Martin , Manoharan Muthiah , Zlatev Ivan 
Published: September 2021

AbstractIn order to achieve efficient therapeutic post-transcriptional gene-silencing mediated by the RNA interference (RNAi) pathway, small interfering RNAs (siRNAs) must be chemically modified. Several supra-RNA structures, with the potential to stabilize siRNAs metabolically have been evaluated for their ability to induce gene silencing, but all have limitations or have not been explored in therapeutically relevant contexts. Covalently closed circular RNA transcripts are prevalent in eukaryotes and have potential as biomarkers and disease targets, and circular RNA mimics are being explored for use as therapies. Here we report the synthesis and evaluation of small circular interfering RNAs (sciRNAs). To synthesize sciRNAs, a sense strand functionalized with the trivalent N-acetylgalactosamine (GalNAc) ligand and cyclized using ‘click’ chemistry was annealed to an antisense strand. This strategy was used for synthesis of small circles, but could also be used for synthesis of larger circular RNA mimics. We evaluated various sciRNA designs in vitro and in vivo. We observed improved metabolic stability of the sense strand upon circularization and off-target effects were eliminated. The 5′-(E)-vinylphosphonate modification of the antisense strand resulted in GalNAc-sciRNAs that are potent in vivo at therapeutically relevant doses. Physicochemical studies and NMR-based structural analysis, together with molecular modeling studies, shed light on the interactions of this novel class of siRNAs, which have a partial duplex character, with the RNAi machinery.
SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators
Authors: Ma Xiaojun , Somasundaram Ashwin , Qi Zengbiao , Hartman Douglas J , Singh Harinder , Osmanbeyoglu Hatice Ulku 
Published: September 2021

AbstractThe identity and functions of specialized cell types are dependent on the complex interplay between signaling and transcriptional networks. Recently single-cell technologies have been developed that enable simultaneous quantitative analysis of cell-surface receptor expression with transcriptional states. To date, these datasets have not been used to systematically develop cell-context-specific maps of the interface between signaling and transcriptional regulators orchestrating cellular identity and function. We present SPaRTAN (Single-cell Proteomic and RNA based Transcription factor Activity Network), a computational method to link cell-surface receptors to transcription factors (TFs) by exploiting cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) datasets with cis-regulatory information. SPaRTAN is applied to immune cell types in the blood to predict the coupling of signaling receptors with cell context-specific TFs. Selected predictions are validated by prior knowledge and flow cytometry analyses. SPaRTAN is then used to predict the signaling coupled TF states of tumor infiltrating CD8+ T cells in malignant peritoneal and pleural mesotheliomas. SPaRTAN enhances the utility of CITE-seq datasets to uncover TF and cell-surface receptor relationships in diverse cellular states.
ΩqPCR measures telomere length from single-cells in base pair units
Authors: Xiong Fusheng , Frasch Wayne D 
Published: September 2021

AbstractΩqPCR determines absolute telomere length in kb units from single cells. Accuracy and precision of ΩqPCR were assessed using 800 bp and 1600 bp synthetic telomeres inserted into plasmids, which were measured to be 819 ± 19.6 and 1590 ± 42.3 bp, respectively. This is the first telomere length measuring method verified in this way. The approach uses Ω-probes, a DNA strand containing sequence information that enables: (i) hybridization with the telomere via the 3′ and 5′ ends that become opposed; (ii) ligation of the hybridized probes to circularize the Ω-probes and (iii) circularized-dependent qPCR due to sequence information for a forward primer, and for a reverse primer binding site, and qPCR hydrolysis probe binding. Read through of the polymerase during qPCR occurs only in circularized Ω-probes, which quantifies their number that is directly proportional to telomere length. When used in concert with information about the cell cycle stage from a single-copy gene, and ploidy, the MTL of single cells measured by ΩqPCR was consistent with that obtained from large sample sizes by TRF.
Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks
Authors: Dibaeinia Payam , Sinha Saurabh 
Published: September 2021

AbstractDeciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.
Fission yeast Stn1 maintains stability of repetitive DNA at subtelomere and ribosomal DNA regions
Authors: Yamamoto Io , Nakaoka Hidenori , Takikawa Masahiro , Tashiro Sanki , Kanoh Junko , Miyoshi Tomoichiro , Ishikawa Fuyuki 
Published: September 2021

Abstract
Telomere binding protein Stn1 forms the CST (Cdc13/CTC1-STN1-TEN1) complex in budding yeast and mammals. Likewise, fission yeast Stn1 and Ten1 form a complex indispensable for telomere protection. We have previously reported that stn1-1, a high-temperature sensitive mutant, rapidly loses telomere DNA at the restrictive temperature due to frequent failure of replication fork progression at telomeres and subtelomeres, both containing repetitive sequences. It is unclear, however, whether Stn1 is required for maintaining other repetitive DNAs such as ribosomal DNA. In this study, we have demonstrated that stn1-1 cells, even when grown at the permissive temperature, exhibited dynamic rearrangements in the telomere-proximal regions of subtelomere and ribosomal DNA repeats. Furthermore, Rad52 and γH2A accumulation was observed at ribosomal DNA repeats in the stn1-1 mutant. The phenotypes exhibited by the stn1-1 allele were largely suppressed in the absence of Reb1, a replication fork barrier-forming protein, suggesting that Stn1 is involved in the maintenance of the arrested replication forks. Collectively, we propose that Stn1 maintains the stability of repetitive DNAs at subtelomeres and rDNA regions.
scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network
Authors: Shao Xin , Yang Haihong , Zhuang Xiang , Liao Jie , Yang Penghui , Cheng Junyun , Lu Xiaoyan , Chen Huajun , Fan Xiaohui 
Published: September 2021

AbstractAdvances in single-cell RNA sequencing (scRNA-seq) have furthered the simultaneous classification of thousands of cells in a single assay based on transcriptome profiling. In most analysis protocols, single-cell type annotation relies on marker genes or RNA-seq profiles, resulting in poor extrapolation. Still, the accurate cell-type annotation for single-cell transcriptomic data remains a great challenge. Here, we introduce scDeepSort (https://github.com/ZJUFanLab/scDeepSort), a pre-trained cell-type annotation tool for single-cell transcriptomics that uses a deep learning model with a weighted graph neural network (GNN). Using human and mouse scRNA-seq data resources, we demonstrate the high performance and robustness of scDeepSort in labeling 764 741 cells involving 56 human and 32 mouse tissues. Significantly, scDeepSort outperformed other known methods in annotating 76 external test datasets, reaching an 83.79% accuracy across 265 489 cells in humans and mice. Moreover, we demonstrate the universality of scDeepSort using more challenging datasets and using references from different scRNA-seq technology. Above all, scDeepSort is the first attempt to annotate cell types of scRNA-seq data with a pre-trained GNN model, which can realize the accurate cell-type annotation without additional references, i.e. markers or RNA-seq profiles.
GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy
Authors: Parks Donovan H , Chuvochina Maria , Rinke Christian , Mussig Aaron J , Chaumeil Pierre-Alain , Hugenholtz Philip 
Published: September 2021

AbstractThe Genome Taxonomy Database (GTDB; https://gtdb.ecogenomic.org) provides a phylogenetically consistent and rank normalized genome-based taxonomy for prokaryotic genomes sourced from the NCBI Assembly database. GTDB R06-RS202 spans 254 090 bacterial and 4316 archaeal genomes, a 270% increase since the introduction of the GTDB in November, 2017. These genomes are organized into 45 555 bacterial and 2339 archaeal species clusters which is a 200% increase since the integration of species clusters into the GTDB in June, 2019. Here, we explore prokaryotic diversity from the perspective of the GTDB and highlight the importance of metagenome-assembled genomes in expanding available genomic representation. We also discuss improvements to the GTDB website which allow tracking of taxonomic changes, easy assessment of genome assembly quality, and identification of genomes assembled from type material or used as species representatives. Methodological updates and policy changes made since the inception of the GTDB are then described along with the procedure used to update species clusters in the GTDB. We conclude with a discussion on the use of average nucleotide identities as a pragmatic approach for delineating prokaryotic species.
A small regulatory RNA alters Staphylococcus aureus virulence by titrating RNAIII activity
Authors: Le Huyen Kim Boi , Gonzalez Cintia Daniela , Pascreau Gaëtan , Bordeau Valérie , Cattoir Vincent , Liu Wenfeng , Bouloc Philippe , Felden Brice , Chabelskaya Svetlana 
Published: September 2021

Abstract
Staphylococcus aureus is an opportunistic human and animal pathogen with an arsenal of virulence factors that are tightly regulated during bacterial infection. The latter is achieved through a sophisticated network of regulatory proteins and regulatory RNAs. Here, we describe the involvement of a novel prophage-carried small regulatory S. aureus RNA, SprY, in the control of virulence genes. An MS2-affinity purification assay reveals that SprY forms a complex in vivo with RNAIII, a major regulator of S. aureus virulence genes. SprY binds to the 13th stem-loop of RNAIII, a key functional region involved in the repression of multiple mRNA targets. mRNAs encoding the repressor of toxins Rot and the extracellular complement binding protein Ecb are among the targets whose expression is increased by SprY binding to RNAIII. Moreover, SprY decreases S. aureus hemolytic activity and virulence. Our results indicate that SprY titrates RNAIII activity by targeting a specific stem loop. Thus, we demonstrate that a prophage-encoded sRNA reduces the pathogenicity of S. aureus through RNA sponge activity.
gutMGene: a comprehensive database for target genes of gut microbes and microbial metabolites
Authors: Cheng Liang , Qi Changlu , Yang Haixiu , Lu Minke , Cai Yiting , Fu Tongze , Ren Jialiang , Jin Qu , Zhang Xue 
Published: September 2021

AbstractgutMGene (http://bio-annotation.cn/gutmgene), a manually curated database, aims at providing a comprehensive resource of target genes of gut microbes and microbial metabolites in humans and mice. Metagenomic sequencing of fecal samples has identified 3.3 × 106 non-redundant microbial genes from up to 1500 different species. One of the contributions of gut microbiota to host biology is the circulating pool of bacterially derived small-molecule metabolites. It has been estimated that 10% of metabolites found in mammalian blood are derived from the gut microbiota, where they can produce systemic effects on the host through activating or inhibiting gene expression. The current version of gutMGene documents 1331 curated relationships between 332 gut microbes, 207 microbial metabolites and 223 genes in humans, and 2349 curated relationships between 209 gut microbes, 149 microbial metabolites and 544 genes in mice. Each entry in the gutMGene contains detailed information on a relationship between gut microbe, microbial metabolite and target gene, a brief description of the relationship, experiment technology and platform, literature reference and so on. gutMGene provides a user-friendly interface to browse and retrieve each entry using gut microbes, disorders and intervention measures. It also offers the option to download all the entries and submit new experimentally validated associations.