bluuebunny/crossref_metadata_2025_split huggingface dataset:
eSPRESSO: a spatial self-organizing-map clustering method for single-cell transcriptomes of various tissue structures using graph-based networks
Authors: Mori Tomoya , Takase Toshiro , Lan Kuan-Chun , Yamane Junko , Alev Cantas , Osafune Kenji , Yamashisa Jun , Fujibuchi Wataru 
Published: January 2021

ABSTRACTAnimal cells are spatially organized as tissues and cellular gene expression data contain such information that governs body structure and morphogenesis during developmental process. Although several computational tissue reconstruction methods using transcriptomic data have been proposed, those methods are insufficient with regard to arranging cells in their correct positions in tissues or organs unless spatial information is explicitly provided. Here, we propose eSPRESSO, a powerfulin silicothree-dimensional (3D) tissue reconstruction method using stochastic self-organizing map (stochastic-SOM) clustering, together with optimization of gene set by Markov chain Monte Carlo (MCMC) framework, to estimate the spatial domain structure of cells in any topology of tissues or organs from only their transcriptome profiles. We confirmed the performance of eSPRESSO by mouse embryo, embryonic heart, adult cortical layers, and human pancreas organoid with high reproducibility (success rate = 72.5–100%), while discovering morphologically important spatial discriminator genes (SDGs). Furthermore, we applied eSPRESSO to analysis of human adult heart diseases by virtual gene knockouts, and revealed candidate mechanisms of deformation of heart structure. The eSPRESSO may provide novel methods to analyze the mechanisms of 3D structure formation and morphology-based disease mechanisms.
Putative mobilized colistin resistance genes in the human gut microbiome
Authors: Andrade Bruno G. N. , Goris Tobias , Afli Haithem , Coutinho Felipe H. , Davila Alberto M.R. , Cuadrat Rafael R. C. 
Published: January 2021

AbstractBackgroundThe high incidence of bacterial genes that confer resistance to last-resort antibiotics, such as colistin caused by MCR genes, poses an unprecedented threat to our civilization’s health. To understand the spread, evolution, and distribution of such genes among human populations, with the final goal of diminishing their occurrence in human environments should be a priority. To tackle this problem, we investigated the distribution and prevalence of potential mcr genes in the human gut microbiome we used a set of bioinformatics tools to screen the Unified Human Gastrointestinal Genome (UHGG) collection for the presence, synteny and phylogeny of putative mcr genes, and co-located antibiotic resistance genes.ResultsA total of 2,079 ARGs were classified as different MCR in 2,046 Metagenome assembled genomes (MAGs), present in 1,596 individuals from 41 countries, of which 215 MCRs were identified in plasmidial contigs. The genera that presented the largest number of MCR-like genes wereSuterellaandParasuterella, prevalent human gut bacteria of whichSuterella wadsworthensisis associated with autism. Other potential pathogens carrying MCR genes belonged to the genusVibrio,EscherichiaandCampylobacter. Finally, we identified a total of 22,746 ARGs belonging to 21 different classes in the same 2,046 MAGs, suggesting multi-resistance potential in the corresponding bacterial strains, increasing the concern of ARGs impact in the clinical settings.ConclusionThis study uncovers the diversity of MCR-like genes in the human gut microbiome. We showed the cosmopolitan distribution of these genes in individuals worldwide and the co-presence of other antibiotic resistance genes, including Extended-spectrum beta-lactamases (ESBL). Also, we described mcr-like genes fused to a PAP2-like domain inS. wadsworthensis. Although these novel sequences increase our knowledge about the diversity and evolution of mcr-like genes, their activity and a potential colistin resistance in the corresponding strains has to be experimentally validated.
Fast and Robust 2D Inverse Laplace Transformation of Single-Molecule Fluorescence Lifetime Data
Authors: Talele Saurabh , King John T. 
Published: January 2021

AbstractFluorescence spectroscopy at the single-molecule scale has been indispensable for studying conformational dynamics and rare states of biological macromolecules. Single-molecule 2D-fluorescence lifetime correlation spectroscopy (sm-2D-FLCS) is an emerging technique that holds great promise for the study of protein and nucleic acid dynamics as it 1) resolves conformational dynamics using a single chromophore, 2) measures forward and reverse transitions independently, and 3) has a dynamic window ranging from microseconds to seconds. However, the calculation of a 2D fluorescence relaxation spectrum requires an inverse Laplace transition (ILT), which is an ill-conditioned inversion that must be estimated numerically through a regularized minimization. The current methods for performing ILTs of fluorescence relaxation can be computationally inefficient, sensitive to noise corruption, and difficult to implement. Here, we adopt an approach developed for NMR spectroscopy (T1-T2 relaxometry) to perform 1D and 2D-ILTs on single-molecule fluorescence spectroscopy data using singular-valued decomposition and Tikhonov regularization. This approach provides fast, robust, and easy to implement Laplace inversions of single-molecule fluorescence data.Significance StatementInverse Laplace transformations are a powerful approach for analyzing relaxation data. The inversion computes a relaxation rate spectrum from experimentally measured temporal relaxation, circumventing the need to choose appropriate fitting functions. They are routinely performed in NMR spectroscopy and are becoming increasing used in single-molecule fluorescence experiments. However, as Laplace inversions are ill-conditioned transformations, they must be estimated from regularization algorithms that are often computationally costly and difficult to implement. In this work, we adopt an algorithm first developed for NMR relaxometry to provide fast, robust, and easy to implement 1D and 2D inverse Laplace transformations on single-molecule fluorescence data.
Effect of public health interventions during the first epidemic wave of COVID-19 in Cyprus: a modelling study
Authors: Gountas Ilias , Quattrocchi Annalisa , Mamais Ioannis , Tsioutis Constantinos , Christaki Eirini , Fokianos Konstantinos , Nikolopoulos Georgios 
Published: January 2021

AbstractBackgroundCyprus addressed the first wave of SARS CoV-2 (COVID-19) by implementing non-pharmaceutical interventions. The aims of this study were: a) to estimate epidemiological parameters of this wave including infection attack ratio, infection fatality ratio, and case ascertainment ratio, b) to assess the impact of public health interventions, and c) to examine what would have happened if those interventions had not been implemented.MethodsA dynamic, stochastic, individual-based Susceptible-Exposed-Infected-Recovered (SEIR) model was developed to simulate COVID-19 transmission and progression in the population of the Republic of Cyprus. The model was fitted to the observed trends in COVID-19 deaths and intensive care unit (ICU) bed use.ResultsBy May 8 2020th, the infection attack ratio was 0.31% (95% Credible Interval (CrI): 0.15%, 0.54%), the infection fatality ratio was 0.71% (95% CrI: 0.44%, 1.61%), and the case ascertainment ratio was 33.2% (95% CrI: 19.7%, 68.7%). If Cyprus had not implemented any public health measure, the healthcare system would have been overwhelmed by April 14th. The interventions averted 715 (95% CrI: 339, 1235) deaths. If Cyprus had only increased ICU beds, without any social distancing measure, the healthcare system would have been overwhelmed by April 19th.ConclusionsThe decision of the Cypriot authorities to launch early non-pharmaceutical interventions limited the burden of the first wave of COVID-19. The findings of these analyses could help address the next waves of COVID-19 in Cyprus and other similar settings.
Urban-adapted mammal species have more known pathogens
Authors: Albery Gregory F. , Carlson Colin J. , Cohen Lily E. , Eskew Evan A. , Gibb Rory , Ryan Sadie J. , Sweeny Amy R. , Becker Daniel J. 
Published: January 2021

AbstractThe world is rapidly urbanising, inviting mounting concern that urban environments will experience increased zoonotic disease risk. Urban animals could have more frequent contact with humans, and therefore may transmit more zoonotic parasites; however, these animals have a specific set of underlying traits that may determine their parasite burdens while predisposing them to urban living, and they may be subject to more intense research effort, both of which could complicate our ability to reliably identify the role of urbanisation in driving zoonotic risk. Here, we test whether urban mammal species host more known zoonotic parasites, investigating the potential underlying drivers while accounting for a correlated suite of phenotypic, taxonomic, and geographic predictors. We found that urban-adapted mammals have more documented parasites, and more zoonotic parasites specifically: despite comprising only 157 of the 2792 investigated species (6%), urban mammals provided 39% of known host-parasite combinations and showed consistently higher viral discovery rates throughout the last century. However, contrary to predictions, much of the observed effect was attributable to research effort rather than to urban adaptation status itself, and urban-adapted species in fact hosted fewer zoonoses than expected given their total observed parasite richness. We conclude that extended historical contact with humans has had a limited impact on the number of observed zoonotic parasites in urban-adapted mammals; instead, their greater observed zoonotic richness likely reflects sampling bias arising from proximity to humans, which supports a near-universal underlying pattern of conflation between zoonotic risk, research effort, and synanthropy. These findings underscore the need to resolve the ecological mechanisms underlying links between anthropogenic change, sampling bias, and observed wildlife disease dynamics.
Neuromolecular and behavioral effects of ethanol deprivation inDrosophila
Authors: D’Silva Natalie M. , McCullar Katie S. , Conard Ashley M. , Blackwater Tyler , Azanchi Reza , Heberlein Ulrike , Larschan Erica , Kaun Karla R. 
Published: January 2021

AbstractAlcohol use disorder (AUD) is characterized by loss of control in limiting alcohol intake. This may involve intermittent periods of abstinence followed by alcohol seeking and, consequently, relapse. However, little is understood of the molecular mechanisms underlying the impact of alcohol deprivation on behavior. Using a newDrosophila melanogasterrepeated intermittent alcohol exposure model, we sought to identify how ethanol deprivation alters spontaneous behavior, determine the associated neural structures, and reveal correlated changes in brain gene expression. We found that repeated intermittent ethanol-odor exposures followed by ethanol-deprivation dynamically induces behaviors associated with a negative affect state. Although behavioral states broadly mapped to many brain regions, persistent changes in social behaviors mapped to the mushroom body and surrounding neuropil. This occurred concurrently with changes in expression of genes associated with sensory responses, neural plasticity, and immunity. Like social behaviors, immune response genes were upregulated following three-day repeated intermittent ethanol-odor exposures and persisted with one or two days of ethanol-deprivation, suggesting an enduring change in molecular function. Our study provides a framework for identifying how ethanol deprivation alters behavior with correlated underlying circuit and molecular changes.
Analysis of the intensity of the COVID-19 epidemic in Berlin towards an universal prognostic relationship
Authors: Below D. , Mairanowski J. , Mairanowski F. 
Published: January 2021

AbstractThe present work is a continuation and development of research on prediction and analysis of the spread of the COVID-19 epidemic.The proposed model adequately describes the development of the coronavirus epidemic with insufficient adherence to quarantine and social distancing. The transition from the absolute number of infected persons to their relative number per inhabitant of a settlement makes it possible to obtain universal calculation ratios.In performing the calculations, the choice of the date of the beginning of the epidemic is of great importance. Recommendations are given on how to determine the date of the beginning of the epidemic based on the analysis of statistical data on the spread of the epidemic. The coefficient of virus transmission rate k included in the calculated prognostic relation depends on the population size and the type of virus strain in the settlement in question. A simple ratio for calculating this coefficient as a function of population size is proposed.Control calculations performed using only a single empirical coefficient showed high accuracy. The calculated curves for Germany, Berlin, and its districts agree well with the corresponding statistical data. The correlation coefficients between the corresponding curves reach values of 0.93 to 0.97. The further development of the model should thus go in the direction of identifying causal links between the intensity of the epidemic and the main factors affecting this process. Some of these factors are related to the characteristics of the population’s behaviour and the infrastructure of cities. The increase in the incidence in areas with a large percentage of the population rooted in Islamic countries is one of the main factors determining the development of the epidemic in Berlin. In order to explain and clarify this conclusion, it is necessary to make further assumptions about the possible emergence of a new strain of coronavirus in Berlin and in Germany and, accordingly, about the possibility of new epidemic waves. A preliminary ratio for predicting the spread of the epidemic under conditions of simultaneous existence of both strains of coronavirus is given.Simplicity of the proposed prognostic method and high accuracy of the results allow to recommend it as an effective tool for operative analysis of various measures aimed to control the spread of COVID-19 epidemic including mass vaccination of population.
Pan-genome Analysis in Sorghum Highlights the Extent of Genomic Variation and Sugarcane Aphid Resistance Genes
Authors: Wang Bo , Jiao Yinping , Chougule Kapeel , Olson Andrew , Huang Jian , Llaca Victor , Fengler Kevin , Wei Xuehong , Wang Liya , Wang Xiaofei , Regulski Michael , Drenkow Jorg , Gingeras Thomas , Hayes Chad , Armstrong J. Scott , Huang Yinghua , Xin Zhanguo , Ware Doreen 
Published: January 2021

ABSTRACTSorghum bicolor, one of the most important grass crops around the world, harbors a high degree of genetic diversity. We constructed chromosome-level genome assemblies for two important sorghum inbred lines, Tx2783 and RTx436. The final high-quality reference assemblies consist of 19 and 18 scaffolds, respectively, with contig N50 values of 25.6 and 20.3 Mb. Genes were annotated using evidence-based andde novogene predictors, and RAMPAGE data demonstrate that transcription start sites were effectively captured. Together with other public sorghum genomes, BTx623, RTx430, and Rio, extensive structural variations (SVs) of various sizes were characterized using Tx2783 as a reference. Genome-wide scanning for disease resistance (R) genes revealed high levels of diversity among these five sorghum accessions. To characterize sugarcane aphid (SCA) resistance in Tx2783, we mapped the resistance region on chromosome 6 using a recombinant inbred line (RIL) population and found a SV of 191 kb containing a cluster of R genes in Tx2783. Using Tx2783 as a backbone, along with the SVs, we constructed a pan-genome to support alignment of resequencing data from 62 sorghum accessions, and then identified core and dispensable genes using this population. This study provides the first overview of the extent of genomic structural variations and R genes in the sorghum population, and reveals potential targets for breeding of SCA resistance.
Imaging Multiple Sclerosis Pathology at 160μm Isotropic Resolution by Human Whole-BrainEx VivoMagnetic Resonance Imaging at 3T
Authors: Matthias Weigel , Peter Dechent , Riccardo Galbusera , Erik Bahn , Govind Nair , Ludwig Kappos , Wolfgang Brück , Christine Stadelmann , Cristina Granziera 
Published: January 2021

AbstractPostmortem magnetic resonance imaging (MRI) of the fixed healthy and diseased human brain facilitates spatial resolutions and image quality that is not achievable within vivoMRI scans. Though challenging - and almost exclusively performed at 7T field strength - depicting the tissue architecture of the entire brain in fine detail is invaluable since it enables the study of neuroanatomy and uncovers important pathological features in neurological disorders. The objectives of the present work were (i) to develop a 3D isotropic ultra-high-resolution imaging approach for human whole-brainex vivoacquisitions working on a standard clinical 3T MRI system, and (ii) to explore the sensitivity and specificity of this concept for specific pathoanatomical features of multiple sclerosis. The reconstructed images demonstrate unprecedented resolution and soft tissue contrast of the diseased human brain at 3T, thus allowing visualization of sub-millimetric lesions in the different cortical layers and in the cerebellar cortex, as well as unique cortical lesion characteristics such as the presence of incomplete / complete iron rims, and patterns of iron accumulation. Further details such as the subpial molecular layer, the line of Gennari, and some intrathalamic nuclei are also well distinguishable.
Controllability boosts neural and cognitive signatures of changes-of-mind in uncertain environments
Authors: Rouault Marion , Weiss Aurélien , Lee Junseok K. , Drugowitsch Jan , Chambon Valérian , Wyart Valentin 
Published: January 2021

SummaryIn uncertain environments, seeking information about alternative choice options is essential for adaptive learning and decision-making. However, information seeking is usually confounded with changes-of-mind about the reliability of the preferred option. Here, we exploited the fact that information seeking requires control over which option to sample to isolate its behavioral and neurophysiological signatures. We found that changes-of-mind occurring with control require more evidence against the current option, are associated with reduced confidence, but are nevertheless more likely to be confirmed on the next decision. Multimodal neurophysiological recordings showed that these changes-of-mind are preceded by stronger activation of the dorsal attention network in magnetoencephalography (MEG), and followed by increased pupil-linked arousal during the presentation of decision outcomes. Together, these findings indicate that information seeking increases the saliency of evidence perceived as the direct consequence of one’s own actions.HighlightsExploration-exploitation dilemmas confound information seeking with changes-of-mind.Unlike changes-of-mind, information seeking requires control over information sampling.Information seeking is associated with reduced confidence and active hypothesis testing.Stronger neurophysiological correlates of attention and arousal during information seeking.
A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes
Authors: Horton James S. , Flanagan Louise M. , Jackson Robert W. , Priest Nicholas K. , Taylor Tiffany B. 
Published: January 2021

AbstractMutational hotspots can determine evolutionary outcomes and make evolution repeatable. Hotspots are products of multiple evolutionary forces including mutation rate heterogeneity, but this variable is often hard to identify. In this work we reveal that a powerfully deterministic genetic hotspot can be built and broken by a handful of silent mutations. We observed this when studying homologous immotile variants of the bacteriaPseudomonas fluorescens, AR2 and Pf0-2x. AR2 resurrects motility through highly repeatablede novomutation of the same nucleotide in >95% lines in minimal media (ntrBA289C). Pf0-2x, however, evolves via a number of mutations meaning the two strains diverge significantly during adaptation. We determined that this evolutionary disparity was owed to just 6 synonymous variations within thentrBlocus, which we demonstrated by swapping the sites and observing that we were able to both break (>95% to 0% in AR2) and build (0% to 80% in Pf0-2x) a powerfully deterministic mutational hotspot. Our work reveals a fundamental role for silent genetic variation in determining adaptive outcomes.
Cryo-EM structure of the yeast TREX complex and coordination with the SR-like protein Gbp2
Authors: Xie Yihu , Clarke Bradley P. , Kim Yong Joon , Ivey Austin L. , Hill Pate S. , Shi Yi , Ren Yi 
Published: January 2021

AbstractThe evolutionarily conserved TREX complex plays central roles during mRNP (messenger ribonucleoprotein) maturation and export from the nucleus to the cytoplasm. In yeast, TREX is composed of the THO sub-complex (Tho2, Hpr1, Tex1, Mft1, and Thp2), the DEAD box ATPase Sub2, and Yra1. Here we present a 3.7 Å cryo-EM structure of the yeast THO•Sub2 complex. The structure reveals the intimate assembly of THO revolving around its largest subunit Tho2. THO stabilizes a semi-open conformation of the Sub2 ATPase via interactions with Tho2. We show that THO interacts with the SR-like protein Gbp2 through both the N-terminal domain and RRM domains of Gbp2. Crosslinking mass spectrometry analysis supports the extensive interactions between THO and Gbp2, further revealing that RRM domains of Gbp2 are in close proximity to the C-terminal domain of Tho2. We propose that THO serves as a landing pad to configure Gbp2 to facilitate its loading onto mRNP.
Stroke-related alterations in inter-areal communication
Authors: Allegra Michele , Favaretto Chiara , Metcalf Nicholas , Corbetta Maurizio , Brovelli Andrea 
Published: January 2021

ABSTRACTBeyond causing local ischemia and cell damage at the site of injury, stroke strongly affects long-range anatomical connections, perturbing the functional organization of brain networks. Several studies reported functional connectivity abnormalities parallelling both behavioral deficits and functional recovery across different cognitive domains. FC alterations suggest that long-range communication in the brain is altered after stroke. However, standard FC analyses cannot reveal the directionality and time scale of inter-areal information transfer. We used resting-state fMRI and covariance-based Granger causality analysis to quantify network-level information transfer and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was significantly decreased with respect to healthy controls. Second, stroke caused inter-hemispheric asymmetries, as information transfer within the affected hemisphere and from the affected to the intact hemisphere was significantly reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they correlated with impaired performance in several behavioral domains. Overall, our findings support the hypothesis that stroke provokes asymmetries between the affected and spared hemisphere, with different functional consequences depending on which hemisphere is lesioned.