bluuebunny/crossref_metadata_2025_split huggingface dataset:
Beyond two-point statistics: using the minimum spanning tree as a tool for cosmology
Authors: Naidoo Krishna , Whiteway Lorne , Massara Elena , Gualdi Davide , Lahav Ofer , Viel Matteo , Gil-Marín Héctor , Font-Ribera Andreu 
Published: October 2019

ABSTRACT
Cosmological studies of large-scale structure have relied on two-point statistics, not fully exploiting the rich structure of the cosmic web. In this paper we show how to capture some of this cosmic web information by using the minimum spanning tree (MST), for the first time using it to estimate cosmological parameters in simulations. Discrete tracers of dark matter such as galaxies, N-body particles or haloes are used as nodes to construct a unique graph, the MST, that traces skeletal structure. We study the dependence of the MST on cosmological parameters using haloes from a suite of COmoving Lagrangian Acceleration (COLA) simulations with a box size of $250\ h^{-1}\, {\rm Mpc}$, varying the amplitude of scalar fluctuations (As), matter density (Ωm), and neutrino mass (∑mν). The power spectrum P and bispectrum B are measured for wavenumbers between 0.125 and 0.5 $h\, {\rm Mpc}^{-1}$, while a corresponding lower cut of ∼12.6 $h^{-1}\, {\rm Mpc}$ is applied to the MST. The constraints from the individual methods are fairly similar but when combined we see improved 1σ constraints of $\sim 17{{\ \rm per\ cent}}$ ($\sim 12{{\ \rm per\ cent}}$) on Ωm and $\sim 12{{\ \rm per\ cent}}$ ($\sim 10{{\ \rm per\ cent}}$) on As with respect to P (P + B) thus showing the MST is providing additional information. The MST can be applied to current and future spectroscopic surveys (BOSS, DESI, Euclid, PSF, WFIRST, and 4MOST) in 3D and photometric surveys (DES and LSST) in tomographic shells to constrain parameters and/or test systematics.
Light curve variation caused by accretion column switching stellar hemispheres
Authors: Čemeljić Miljenko , Siwak Michał 
Published: October 2019

Abstract
We investigate switching of the accretion column between the stellar hemispheres in the magnetosphere of a star with the dipole magnetic field aligned with the stellar rotation axis. We show that such switching can produce “hiccups” in the observed lightcurves. The intensity of emitted radiation from the stellar surface as seen by distant observers is computed from our two dimensional axisymmetric viscous and resistive magnetohydrodynamic numerical simulations. This result is used to construct a three-dimensional model of a star with the ring-shaped hot spots from the accretion columns at the stellar surface. We compute the intensity from such hot spots. To obtain a non-axisymmetric model with arc-shaped hot spots, we remove a ring section in the azimuthal direction from the hot-spots and compute the intensity of the radiated emission. Such models can be used to relate physical parameters in the simulations to the observations. We show an example with the intensity computed from our model compared to observational light curve.
Genotyping and De Novo Discovery of Allelic Variants at the Brassicaceae Self-Incompatibility Locus from Short-Read Sequencing Data
Authors: Genete Mathieu , Castric Vincent , Vekemans Xavier 
Published: October 2019

AbstractPlant self-incompatibility (SI) is a genetic system that prevents selfing and enforces outcrossing. Because of strong balancing selection, the genes encoding SI are predicted to maintain extraordinarily high levels of polymorphism, both in terms of the number of functionally distinct S-alleles that segregate in SI species and in terms of their nucleotide sequence divergence. However, because of these two combined features, documenting polymorphism of these genes also presents important methodological challenges that have so far largely prevented the comprehensive analysis of complete allelic series in natural populations, and also precluded the obtention of complete genic sequences for many S-alleles. Here, we develop a powerful methodological approach based on a computationally optimized comparison of short Illumina sequencing reads from genomic DNA to a database of known nucleotide sequences of the extracellular domain of SRK (eSRK). By examining mapping patterns along the reference sequences, we obtain highly reliable predictions of S-genotypes from individuals collected from natural populations of Arabidopsis halleri. Furthermore, using a de novo assembly approach of the filtered short reads, we obtain full-length sequences of eSRK even when the initial sequence in the database was only partial, and we discover putative new SRK alleles that were not initially present in the database. When including those new alleles in the reference database, we were able to resolve the complete diploid SI genotypes of all individuals. Beyond the specific case of Brassicaceae S-alleles, our approach can be readily applied to other polymorphic loci, given reference allelic sequences are available.
Structural transitions in the RNA 7SK 5′ hairpin and their effect on HEXIM binding
Authors: Röder Konstantin , Stirnemann Guillaume , Dock-Bregeon Anne-Catherine , Wales David J , Pasquali Samuela 
Published: October 2019

Abstract7SK RNA, as part of the 7SK ribonucleoprotein complex, is crucial to the regulation of transcription by RNA-polymerase II, via its interaction with the positive transcription elongation factor P-TEFb. The interaction is induced by binding of the protein HEXIM to the 5′ hairpin (HP1) of 7SK RNA. Four distinct structural models have been obtained experimentally for HP1. Here, we employ computational methods to investigate the relative stability of these structures, transitions between them, and the effects of mutations on the observed structural ensembles. We further analyse the results with respect to mutational binding assays, and hypothesize a mechanism for HEXIM binding. Our results indicate that the dominant structure in the wild type exhibits a triplet involving the unpaired nucleotide U40 and the base pair A43-U66 in the GAUC/GAUC repeat. This conformation leads to an open major groove with enough potential binding sites for peptide recognition. Sequence mutations of the RNA change the relative stability of the different structural ensembles. Binding affinity is consequently lost if these changes alter the dominant structure.
A unique internal ribosome entry site representing a dynamic equilibrium state of RNA tertiary structure in the 5′-UTR of Wheat yellow mosaic virus RNA1
Authors: Geng Guowei , Yu Chengming , Li Xiangdong , Yuan Xuefeng 
Published: October 2019

AbstractInternal ribosome entry sites (IRESes) were first reported in RNA viruses and subsequently identified in cellular mRNAs. In this study, IRES activity of the 5′-UTR in Wheat yellow mosaic virus (WYMV) RNA1 was identified, and the 3′-UTR synergistically enhanced this IRES activity via long-distance RNA–RNA interaction between C80U81and A7574G7575. Within the 5′-UTR, the hairpin 1(H1), flexible hairpin 2 (H2) and linker region (LR1) between H1 and H2 played an essential role in cap-independent translation, which is associated with the structural stability of H1, length of discontinuous stems and nucleotide specificity of the H2 upper loop and the long-distance RNA–RNA interaction sites in LR1. The H2 upper loop is a target region of the eIF4E. Cytosines (C55, C66, C105 and C108) in H1 and H2 and guanines (G73, G79 and G85) in LR1 form discontinuous and alternative base pairing to maintain the dynamic equilibrium state, which is used to elaborately regulate translation at a suitable level. The WYMV RNA1 5′-UTR contains a novel IRES, which is different from reported IRESes because of the dynamic equilibrium state. It is also suggested that robustness not at the maximum level of translation is the selection target during evolution of WYMV RNA1.
Nanopore sequencing and Hi-C scaffolding provide insight into the evolutionary dynamics of transposable elements and piRNA production in wild strains of Drosophila melanogaster
Authors: Ellison Christopher E , Cao Weihuan 
Published: November 2019

Abstract
Illumina sequencing has allowed for population-level surveys of transposable element (TE) polymorphism via split alignment approaches, which has provided important insight into the population dynamics of TEs. However, such approaches are not able to identify insertions of uncharacterized TEs, nor can they assemble the full sequence of inserted elements. Here, we use nanopore sequencing and Hi-C scaffolding to produce de novo genome assemblies for two wild strains of Drosophila melanogaster from the Drosophila Genetic Reference Panel (DGRP). Ovarian piRNA populations and Illumina split-read TE insertion profiles have been previously produced for both strains. We find that nanopore sequencing with Hi-C scaffolding produces highly contiguous, chromosome-length scaffolds, and we identify hundreds of TE insertions that were missed by Illumina-based methods, including a novel micropia-like element that has recently invaded the DGRP population. We also find hundreds of piRNA-producing loci that are specific to each strain. Some of these loci are created by strain-specific TE insertions, while others appear to be epigenetically controlled. Our results suggest that Illumina approaches reveal only a portion of the repetitive sequence landscape of eukaryotic genomes and that population-level resequencing using long reads is likely to provide novel insight into the evolutionary dynamics of repetitive elements.
A DNA aptamer for binding and inhibition of DNA methyltransferase 1
Authors: Wang Linlin , Lee Ju Yong , Gao Linfeng , Yin Jiekai , Duan Yaokai , Jimenez Luis A , Adkins Gary Brent , Ren Wendan , Li Linhui , Fang Jian , Wang Yinsheng , Song Jikui , Zhong Wenwan 
Published: November 2019

Abstract
DNA methyltransferases (DNMTs) are enzymes responsible for establishing and maintaining DNA methylation in cells. DNMT inhibition is actively pursued in cancer treatment, dominantly through the formation of irreversible covalent complexes between small molecular compounds and DNMTs that suffers from low efficacy and high cytotoxicity, as well as no selectivity towards different DNMTs. Herein, we discover aptamers against the maintenance DNA methyltransferase, DNMT1, by coupling Asymmetrical Flow Field-Flow Fractionation (AF4) with Systematic Evolution of Ligands by EXponential enrichment (SELEX). One of the identified aptamers, Apt. #9, contains a stem-loop structure, and can displace the hemi-methylated DNA duplex, the native substrate of DNMT1, off the protein on sub-micromolar scale, leading for effective enzymatic inhibition. Apt. #9 shows no inhibition nor binding activity towards two de novo DNMTs, DNMT3A and DNMT3B. Intriguingly, it can enter cancer cells with over-expression of DNMT1, colocalize with DNMT1 inside the nuclei, and inhibit the activity of DNMT1 in cells. This study opens the possibility of exploring the aptameric DNMT inhibitors being a new cancer therapeutic approach, by modulating DNMT activity selectively through reversible interaction. The aptamers could also be valuable tools for study of the functions of DNMTs and the related epigenetic mechanisms.
DSR-GUP, maximally localized state, and black hole thermodynamics
Authors: Chung Won Sang , Hassanabadi Hassan 
Published: October 2019

Abstract
We consider a new type of doubly special relativity transformation which gives a new types of generalized uncertainty principle. This model is known to have invariant Planck energy (or Planck momentum) and minimal length. For this model we discuss the generalized uncertainty relation and compute the minimal length and momentum upper bound. We also compute the corresponding maximally localized state explicitly. Finally, we use the generalized uncertainty relation compatible with doubly special relativity to discuss black hole thermodynamics.
Factors associated with long-term wearable physical activity monitor user engagement
Authors: Friel Ciarán P , Cornelius Talea , Diaz Keith M 
Published: October 2019

Abstract
Wearable physical activity monitors (PAMs) have potential to positively influence physical activity. However, high rates of disengagement have been reported, which dampens enthusiasm, as these devices are unlikely to impact habitual physical activity if they are not worn for a sustained period of time. The purpose of this study was to identify demographic and device-use characteristics (e.g., data sharing) associated with sustained device engagement. Current PAM users (n = 418; mean age: 35.0 ± 12.5; 78% female) from across the USA were recruited online and completed a baseline web-based survey in 2015–2016 comprising questions about demographics and device use. Participants were followed-up again in 2017, at which time they reported whether or not they still used a PAM. Sustained PAM engagement was defined as those who continued use at follow-up. The median follow-up time was 15.5 (±3.7) months. In fully adjusted models, the following were significantly associated with long-term engagement: age (odds ratio [OR]: 1.03; 95% confidence interval [CI]: 1.01–1.05, p = .014), Hispanic ethnicity (OR: 3.67; 95% CI: 1.20–11.26, p = .023), running as a preferred exercise (OR: 1.82; 95% CI: 1.02–3.24, p = .043), wanting to monitor health variables as a reason for choosing to use a PAM (OR: 1.73; 95% CI: 1.02–2.92, p = .042), and sharing data from the PAM publicly on social media (e.g., Facebook and Twitter; OR: 5.11; 95% CI: 1.64–15.93, p = .005). A number of sociodemographic and use characteristics were associated with sustained device use over a median follow-up of 1.3 years. One modifiable factor that may lead to longer device engagement is encouraging users to share data publicly.
Detecting Local Genetic Correlations with Scan Statistics
Authors: Guo Hanmin , Li James J. , Lu Qiongshi , Hou Lin 
Published: October 2019

AbstractGenetic correlation analysis has quickly gained popularity in the past few years and provided insights into the genetic etiology of numerous complex diseases. However, existing approaches oversimplify the shared genetic architecture between different phenotypes and cannot effectively identify precise genetic regions contributing to the genetic correlation. In this work, we introduce LOGODetect, a powerful and efficient statistical method to identify small genome segments harboring local genetic correlation signals. LOGODetect automatically identifies genetic regions showing consistent associations with multiple phenotypes through a scan statistic approach. It uses summary association statistics from genome-wide association studies (GWAS) as input and is robust to sample overlap between studies. Applied to five phenotypically distinct but genetically correlated psychiatric disorders, we identified 49 non-overlapping genome regions associated with multiple disorders, including multiple hub regions showing concordant effects on more than two disorders. Our method addresses critical limitations in existing analytic strategies and may have wide applications in post-GWAS analysis.
CRISPRCasIdentifier: Machine learning for accurate identification and classification of CRISPR-Cas systems
Authors: Padilha Victor A. , Alkhnbashi Omer S. , Shah Shiraz A. , de Carvalho André C. P. L. F. , Backofen Rolf 
Published: November 2019

ABSTRACTCRISPR-Cas genes are extraordinarily diverse and evolve rapidly when compared to other prokaryotic genes. With the rapid increase in newly sequenced archaeal and bacterial genomes, manual identification of CRISPR-Cas systems is no longer viable. Thus, an automated approach is required for advancing our understanding of the evolution and diversity of these systems, and for finding new candidates for genome engineering in eukaryotic models. In this paper, we introduce a holistic strategy that combines regression and classification models for improving the quality of protein cascades, predicting their subtypes, detecting signature genes and extracting potential rules that reveal functional modules for CRISPR.
RepCOOL: Computational Drug Repositioning Via Integrating Heterogeneous Biological Networks
Authors: Fahimian Ghazale , Zahiri Javad , Arab Seyed Sh. , Sajedi Reza H. 
Published: October 2019

AbstractBackgroundIt often takes more than 10 years and costs more than one billion dollars to develop a new drug for a disease and bring it to the market. Drug repositioning can significantly reduce costs and times in drug development. Recently, computational drug repositioning attracted a considerable amount of attention among researchers, and a plethora of computational drug repositioning methods have been proposed.MethodsIn this study, we propose a novel network-based method, named RepCOOL, for drug repositioning. RepCOOL integrates various heterogeneous biological networks to suggest new drug candidates for a given disease.ResultsThe proposed method showed a promising performance on benchmark datasets via rigorous cross-validation. Final drug repositioning model has been built based on random forest classifier, after examining various machine learning algorithms. Finally, in a case study, four FDA approved drugs were suggested for breast cancer stage II.ConclusionResults show the strength of the proposed method in detecting true drug-disease relationships. RepCOOL suggested four new drugs for breast cancer stage II namely Doxorubicin, Paclitaxel, Trastuzumab and Tamoxifen.
Discovery and Engineering of a Therapeutic Interfering Particle (TIP): a combination self-renewing antiviral
Authors: Tanner Elizabeth J , Jung Seung-Yong , Glazier Joshua , Thompson Cassandra , Zhou Yuqi , Martin Benjamin , Son Hye-In , Riley James L , Weinberger Leor S 
Published: October 2019

AbstractPopulation-level control of HIV-1 faces recognized challenges, including the evolution of viral resistance and adherence issues in resource-limited settings. It has long been proposed that viral deletion mutants that conditionally self-renew at the expense of the wild-type virus (i.e., Defective Interfering Particles, DIPs1) could constitute a long-term intervention that circumvents adherence challenges and has a high genetic barrier to resistance, echoing recent approaches2. Theories predict3, 4that DIPs could be engineered into a therapy for HIV-1 (i.e.,Therapeuticinterfering particles or ‘TIPs’) provided they stably persist in patients (R0>1) by spreading to new cells during active infection (hence, a self-replenishing antiviral). To date, DIPs amenable to such engineering have remained elusive for HIV-1. Here we report the discovery of an HIV-1 DIP and its subsequent engineering into a TIP. The TIP interferes with HIV-1 replication at multiple stages of the viral lifecycle, including genome packaging, virion maturation, and reverse transcription, essentially acting as a combination antiviral. In humanized mice, the TIP suppressed HIV-1 replication by ten-fold and significantly protected CD4+ T cells from HIV-1 mediated depletion. These data provide proof-of-concept for a class of biologic with the potential to circumvent significant barriers to HIV-1 control.
Reward Prediction Error Signaling during Reinforcement Learning in Social Anxiety Disorder is altered by Social Observation
Authors: Becker Michael P. I. , Voegler Rolf , Peterburs Jutta , Hofmann David , Bellebaum Christian , Straube Thomas 
Published: October 2019

ABSTRACTBACKGROUNDDysfunctional expectations of impending social or performance outcomes are core features of Social Anxiety Disorder (SAD) but often lack formal definition in clinical research. Reinforcement learning (RL) models offer a framework to define changes in outcome expectations in a formal way by computing the prediction error (PE). This study quantifies the updating of expectations by PEs in SAD and investigates alterations in RL regions associated with PE signaling.METHOD48 adult participants (24 diagnosed with SAD and 24 age-, gender-, and education- matched healthy controls (HC)) underwent event-related functional magnetic resonance imaging while learning from probabilistic feedback. Crucially, both groups completed two parallel versions of the task: one in which they learned under scrutiny (social observation) and one in which they learned without being overtly evaluated (non-social control condition).RESULTSCoupling to prediction errors in SAD was elevated in dorsomedial prefrontal cortex (DMPFC) when learning under observation. These findings provide the first evidence that PE signaling during social performance situations in SAD is associated with hypersensitive response signatures in DMPFC, a brain region associated with using others’ value standards as a proxy for one’s own value standards. Dynamic Causal Modelling further revealed that RPE-modulated connectivity from ventral pallidum to DMPFC during observation was reduced in SAD.CONCLUSIONSThe present results corroborate a crucial role of DMPFC in SAD, which corresponds to dysfunctional expectations about others’ alleged performance standards that play a prominent role in current models of the disorder.
Studying the precuneus reveals structure-function-affect correlation in long-term meditators
Authors: Berkovich-Ohana Aviva , Furman-Haran Edna , Malach Rafael , Arieli Amos , Harel Michal , Gilaie-Dotan Sharon 
Published: October 2019

AbstractUnderstanding the relationship between brain structure, function and self-reports has hardly been addressed until now in meditation research. Here we demonstrate such relationship, using Mindfulness meditation (MM). MM aims to reduce thought-related processes and enhance bodily awareness, thereby reducing identification with thought content and deconstructing maladaptive self-schema. We thus hypothesized that structure of the default mode network (DMN) regions, associated with spontaneous thoughts and self-representation, would negatively correlate with MM experience and self-reported positive affect, while positively correlating with DMN resting-state function.Cross-sectionally comparing a unique group of adept MM practitioners and meditation-naïve matched controls using voxel based morphometry revealed that gray matter (GM) density of the left precuneus (L-Prc) was negatively correlated with MM expertise. Furthermore, GM density of the L-Prc was positively correlated with resting state and task related functional (fMRI) measures within the L-Prc in the MM practitioners, but not in the controls. Finally, the L-Prc’s GM density negatively correlated with positive affect across all participants.Our findings may shed light on understanding structure-function-self reports relationship. While our approach enables studying suggestive correlations in expert MM practitioners, longitudinal studies are required for direct insights concerning the question of causality.Significance statementUnderstanding the relationship between brain structure and function, individual differences and self-reports, is an important goal of neuroscience. Yet, these factors were hardly investigated together in meditation research. The precuneus is part of the default mode network (DMN) involved in thought related processes. Mindfulness meditation (MM) is a mental practice aiming to reduce thought related processes. Here, by cross-sectionally comparing adept meditators and controls, we found that in the precuneus of MM practitioners, structure associated with function. Overall, structure negatively correlated with practice length, as well as with positive affect scores. The structure-function correlation was only significant in the meditators group, possibly implying that prolonged meditation improved structure and function attunement in the DMN. More generally, this study demonstrates that mental practice can be related to conjoint structural and functional effects, as well as to affective self-reports.