bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contrasting responses of protistan plant parasites and phagotrophs to ecosystems, land management and soil properties
Authors: Fiore-Donno Anna Maria , Richter-Heitmann Tim , Bonkowski Michael 
Published: March 2020

AbstractFunctional traits are increasingly used in ecology to link the structure of microbial communities to ecosystem processes. We investigated two important protistan lineages, Cercozoa and Endomyxa (Rhizaria) in soil using Illumina sequencing and analysed their diversity and functional traits along with their responses to environmental factors in grassland and forest across Germany. From 600 soil samples, we obtained 2,101 Operational Taxonomy Units representing ~18 million Illumina reads (region V4, 18S rRNA gene). All major taxonomic and functional groups were present, dominated by small bacterivorous flagellates (Glissomonadida). Endomyxan plant parasites were absent from forest. In grassland, they were promoted by more intensive land use management. Grassland and forest strikingly differed in community composition. Relative abundances of bacterivores and eukaryvores were contrastingly influenced by environmental factors, indicating bottom-up regulation by food resources. These patterns provide new insights into the functional organization of soil biota and indications for a more sustainable land-use management.HighlightsProtistan plant parasites of worldwide importance (Phytomyxea) are absent from forestProtistan plant parasites are enhanced by land use intensification in grasslandOpposite responses of protistan trophic guilds to environmental conditions in forestDrastic differences in protistan community composition between grassland and forest
F5N: Nanopore Sequence Analysis Toolkit for Android Smartphones
Authors: Samarakoon Hiruna , Punchihewa Sanoj , Senanayake Anjana , Ragel Roshan , Gamaarachchi Hasindu 
Published: March 2020

AbstractF5Nis the first ever Android application for nanopore sequence analysis on a mobile phone, comprised of popular tools for read alignment (Minimap2), sequence data manipulation (Samtools) and methylation calling (F5C/Nanopolish). On NA12878 nanopore data,F5Ncan perform a complete methylation calling pipeline on a mobile phone in ∼15 minutes for a batch of 4000 nanopore reads (∼34 megabases).F5Nis not only a toolkit but also a framework for integrating existing C/C++ based command line tools to run on Android.F5Nwill enable performing nanopore sequence analysis on-site when used with an ultra-portable nanopore sequencer (eg: MinION or the anticipated smidgION), consequently reducing the cost for special computers and high-speed Internet.Availability and implementationF5NAndroid application is available on Google Play store athttps://play.google.com/store/apps/details?id=com.mobilegenomics.genopo&hl=enand the source code is available on Github athttps://github.com/SanojPunchihewa/f5n.Contacthirunas@eng.pdn.ac.lk
Governance networks around grasslands with contrasting management history
Authors: Manolache Steluta , Nita Andreea , Hartel Tibor , Miu Iulia Viorica , Ciocanea Cristiana Maria , Rozylowicz Laurentiu 
Published: March 2020

AbstractRomanian grasslands have high nature value, being among the most important biodiversity hotspots at the European level. The European Union Common Agricultural Policy (CAP) contradicts the Biodiversity Strategy to 2020 objective by hindering coordinated grassland governance and collaboration among the involved actors. At the European level, few attempts have been made in creating conceptual strategies for implementing conservation measures in a multi-actor and multi-scale governance setting. Our paper focuses on a comparative network analysis of grassland landscape governance of three Romanian regions (Iron Gates Natural Park – SW; Sighisoara - Tarnava Mare – center; and Dobrogea - SE), representatives for grassland management in mountain and lowland settings. We investigated the structural characteristics of one-mode directed grassland governance networks in the three protected areas (standard cohesion and reciprocity metrics and exponential random graph models), the position of institutions participating in networks (node-level centrality metrics), and the perception of CAP influence on grassland governance by farmers benefiting of CAP agri-environmental payments. In Sighisoara, grasslands governance has been centralized but biodiversity-friendly, while in Iron Gates, grasslands were traditionally managed through a decentralized, community-level system, and this type of governance continues to date. Whereas for Dobrogea’s grasslands, the governance was performed in an intensive, centralized state-run management regime during the communist time and by large landowners after the transition period ended. Our findings illustrate the structure of the three governance networks and dissimilar patterns of collaboration, indicating distinct particularities to be considered when exploring barriers to and options for successful governance in traditionally managed grasslands in the context of CAP measures-driven management.
Dynamic Normalization
Authors: Heeger David J. , Zemlianova Klavdia O. 
Published: March 2020

AbstractThe normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model’s defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. In spite of the success of the normalization model, there are 3 unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how nor-malization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another’s normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a new family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can reca-pitulate key experimental observations of the dynamics of neural activity in V1.Significance StatementA family of recurrent circuit models is proposed to explain the dynamics of neural activity in primary visual cortex (V1). Each of the models in this family exhibits steady state output responses that are already known to fit a wide range of experimental data from diverse neural systems. These models can recapitulate the complex dynamics of V1 activity, including oscillations (so-called gamma oscillations, ∼30-80 Hz). This theoretical framework may also be used to explain key aspects of working memory and motor control. Consequently, the same circuit architecture is applicable to a variety of neural systems, and V1 can be used as a model system for understanding the neural computations in many brain areas.
Organized cannabinoid receptor distribution in neurons revealed by super-resolution fluorescence imaging
Authors: Li Hui , Yang Jie , Cuiping Tian , Diao Min , Wang Quan , Zhao Simeng , Li Shanshan , Tan Fangzhi , Hua Tian , Lin Chao-Po , Deska-Gauthier Dylan , Thompson Garth , Zhang Ying , Wang Tong , Shui Wenqing , Liu Zhi-Jie , Zhong Guisheng 
Published: March 2020

AbstractG-protein-coupled receptors (GPCRs) play important roles in cellular functions. However, their intracellular organization is largely unknown. Through investigation of the cannabinoid receptor 1 (CB1), we discovered periodically repeating clusters of CB1 hotspots within the axons of neurons. We observed these CB1hotspots interact with the membrane-associated periodic skeleton (MPS) forming a complex crucial in the regulation of CB1signaling. Furthermore, we found that CB1hotspot periodicity increased upon CB1agonist application, and these activated CB1 displayed less dynamic movement compared to non-activated CB1. Our results suggest that CB1forms periodic hotspots organized by the MPS as a mechanism to increase signaling efficacy when being activated.
Single-cell RNA-Seq reveals the link betweenCD45isoforms and tumor-infiltrating T cells heterogeneity in liver cancer
Authors: Zhou Biaofeng , Liu Shang , Wu Liang , Sun Yan , Chen Jie , Liu Shiping 
Published: March 2020

AbstractCD45isoforms play a major role in characterizing T cell function, phenotype, and development. However, there is lacking comprehensive interrogation about the relationship betweenCD45isoforms and T lymphocytes from cancer patients at the single-cell level yet. Here, we investigated the CD45 isoforms component of published 5,063 T cells of hepatocellular carcinoma (HCC), which has been assigned functional states. We found that the distribution ofCD45isoforms in T lymphocytes cells depended on tissue resource, cell type, and functional state. Further, we demonstrated that CD45RO and CD45RA dominate in characterizing the phenotype and function of T cell though multipleCD45isoforms coexist in T cells, through a novel alternative splicing pattern analysis. We identified a novel development trajectory of tumor-infiltrating T cells from Tcm to Temra (effector memory T cells re-expresses CD45RA) after detecting two subpopulations in state of transition, Tcm (central memory T) and Tem (effector memory T). Temra, capable of high cytotoxic characteristics, was discovered to be associated with the stage of HCC and may be a target of immunotherapy. Our study presents a comprehension of the connection betweenCD45isoforms and the function, states, sources of T lymphocytes cells in HCC patients at the single-cell level, providing novel insight for the effect ofCD45isoforms on T cell heterogeneity.
Sex determination through X-Y heterogamety inSalix nigra
Authors: Sanderson Brian J. , Feng Guanqiao , Hu Nan , Carlson Craig H. , Smart Lawrence B. , Keefover-Ring Ken , Yin Tongming , Ma Tao , Liu Jianquan , DiFazio Stephen P. , Olson Matthew S. 
Published: March 2020

AbstractThe development of non-recombining sex chromosomes has radical effects on the evolution of discrete sexes and sexual dimorphism. Although dioecy is rare in plants, sex chromosomes have evolved repeatedly throughout the diversification of angiosperms, and many of these sex chromosomes are relatively young compared to those found in vertebrates. In this study, we designed and used a sequence capture array to identify a novel sex-linked region (SLR) inSalix nigra, a basal species in the willow clade, and demonstrated that this species has XY heterogamety. We did not detect any genetic overlap with the previously characterized ZW SLRs in willows, which map to a different chromosome. TheS. nigraSLR is characterized by strong recombination suppression across a 2 MB region and an excess of low frequency alleles, resulting in a low Tajima’s D compared to the remainder of the genome. We speculate that either a recent bottleneck in population size or factors related to positive or background selection generated this differential pattern of Tajima’s D on the X and autosomes. This discovery provides insights into factors that may influence the evolution of sex chromosomes in plants and contributes to a large number of recent observations that underscore their dynamic nature.
Mechanism of action of HBV capsid assembly modulators predicted from binding to early assembly intermediates
Authors: Pavlova Anna , Bassit Leda , Cox Bryan D. , Korablyov Maksym , Chipot Chris , Verma Kiran , Russell Olivia O. , Schinazi Raymond F. , Gumbart James C. 
Published: March 2020

ABSTRACTInterfering with the self-assembly of virus nucleocapsids is a promising approach for the development of novel antiviral agents. Applied to hepatitis B virus (HBV), this approach has led to several classes of capsid assembly modulators (CAMs) that target the virus by either accelerating nucleocapsid assembly or misdirecting it into non-capsid-like particles. Here, we have assessed the structures of early nucleocapsid assembly intermediates, with and without bound CAMs, using molecular dynamics simulations. We find that distinct conformations of the intermediates are induced depending on whether the bound CAM accelerates or misdirects assembly; these structures are predictive of the final assembly. We also selected non-capsid-like structures from our simulations for virtual screening, resulting in the discovery of several compounds with moderate anti-viral activity and low toxicity. Cryo-electron microscopy and capsid melting experiments suggest that our compounds possess a novel mechanism for assembly modulation, potentially opening new avenues for HBV inhibition.
Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data with ImmClassifier
Authors: Liu Xuan , Gosline Sara J.C. , Pflieger Lance T. , Wallet Pierre , Iyer Archana , Guinney Justin , Bild Andrea H. , Chang Jeffrey T. 
Published: March 2020

AbstractSingle-cell RNA sequencing is an emerging strategy for characterizing the immune cell population in diverse environments including blood, tumor or healthy tissues. While this has traditionally been done with flow or mass cytometry targeting protein expression, scRNA-Seq has several established and potential advantages in that it can profile immune cells and non-immune cells (e.g. cancer cells) in the same sample, identify cell types that lack precise markers for flow cytometry, or identify a potentially larger number of immune cell types and activation states than is achievable in a single flow assay. However, scRNA-Seq is currently limited due to the need to identify the types of each immune cell from its transcriptional profile, which is not only time-consuming but also requires a significant knowledge of immunology. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells vs macrophages), making fine distinctions has turned out to be a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that ImmClassifier outperforms other tools (+20% recall, +14% precision) in distinguishing fine-grained cell types (e.g. CD8+ effector memory T cells) with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.
Modality-independent effect of gravity in shaping the internal representation of 3D space
Authors: Theo Morfoisse , Gabriela Herrera Altamira , Leonardo Angelini , Gilles Clément , Mathieu Beraneck , Joseph McIntyre , Michele Tagliabue 
Published: March 2020

AbstractHuman 3D perception of visual objects is flawed by distortions, which are influenced by non-visual factors, such as gravitational vestibular signals. Whether gravity acts specifically on the visual system or at a higher, modality-independent, level of information processing remains unknown. To test these modality-specific vs modality-independent hypotheses, we performed experiments comparing visual versus haptic 3D shape perception in normo-gravity and microgravity. The results obtained for upright and supine posture in 1g show that visual and haptic perceptual anisotropies are systematically in opposing ego-centered, but not gravity-centered, directions suggesting they share a common origin. On the other hand, microgravity significantly modulates both visual and haptic perceptual distortion in the same direction. Overall, our results show a clear link between the visual and haptic perceptual distortions and demonstrate a role of gravity-related signals on a modality-independent internal representation of 3D space used to interpret incoming sensory inputs.
The Presence of Periodontal Pathogens in Gastric Cancer
Authors: de Leeuw Marcel A. , Duval Manuel X. 
Published: March 2020

BackgroundThe microbiome is thought to play a role in the development of gastric cancer (GC). Several studies have put forward putatively carcinogenic species in addition toHelicobacter pylori, but are not in perfect alignment, possibly due to variable parameters in the experiments, including downstream processing. Meta-analyses have not been published so far, so there is lack in clinical guidance beyondH. pylorieradication therapy.MethodsHere, we analysed gastric mucosa samples from nine public data sets, including GC samples. Using both unsupervised and supervised learning, we defined fine grain bacterial networks of gastric mucosa and identified species associated with tumor status of samples.ResultsWe found anatomic locations and cohort regions among the possible factors leading to the observation of study specific gastric microbiomes. Despite this variability, the periodontal speciesFusobacterium nucleatum, Parvimonas micraandPeptostreptococcus stomatiswere found in association with tumor status in several datasets. The three species were predicted to be in interaction by ecological network analysis and also formed the intersection of tumor associated species between four GC data sets and five colorectal cancer (CRC) data sets we reanalyzed. We formulated a probiotic composition putatively competing with the GC pathogen spectrum, from correlation analysis in a large superset of gut samples (n=17,800) from clinical- and crowd-sourced studies.ImplicationsThe overlapping bacterial pathogen spectrum between two gastrointestinal tumor types, GC and CRC, has implications for etiology, treatment and prevention. In vitro testing results reported in literature suggestH. pylorieradication treatment should be efficient against the GC pathogen spectrum, yet the existence of an upstream periodontal reservoir is of concern. To address this, we propose longer term use of the formulated probiotics composition.
The mechanism of coupled folding-upon-binding of an intrinsically disordered protein
Authors: Robustelli Paul , Piana Stefano , Shaw David E. 
Published: March 2020

AbstractIntrinsically disordered proteins (IDPs), which in isolation do not adopt a well-defined tertiary structure but instead populate a structurally heterogeneous ensemble of interconverting states, play important roles in many biological pathways. IDPs often fold into ordered states upon binding to their physiological interaction partners (a so-called “folding-upon-binding” process), but it has proven difficult to obtain an atomic-level description of the structural mechanisms by which they do so. Here, we describe in atomic detail the folding-upon-binding mechanism of an IDP segment to its binding partner, as observed in unbiased molecular dynamics simulations. In our simulations, we observed over 70 binding and unbinding events between the α-helical molecular recognition element (α-MoRE) of the intrinsically disordered C-terminal domain of the measles virus nucleoprotein (NTAIL) and the X domain (XD) of the measles virus phosphoprotein complex. We found that folding-upon-binding primarily occurred through induced-folding pathways (in which intermolecular contacts form before or concurrently with the secondary structure of the disordered protein)—an observation supported by previous experiments—and that the transition state ensemble was characterized by the formation of just a few key intermolecular contacts, and was otherwise highly structurally heterogeneous. We found that when a large amount of helical content was present early in a transition path, NTAILtypically unfolded, then refolded after additional intermolecular contacts formed. We also found that, among conformations with similar numbers of intermolecular contacts, those with less helical content had a higher probability of ultimately forming the native complex than conformations with more helical content, which were more likely to unbind. These observations suggest that even after intermolecular contacts have formed, disordered regions can have a kinetic advantage over folded regions in the folding-upon-binding process.
A long noncoding RNA, LOC157273, is the effector transcript at the chromosome 8p23.1-PPP1R3B metabolic traits and type 2 diabetes risk locus
Authors: Manning Alisa K. , Goustin Anton Scott , Kleinbrink Erica L. , Thepsuwan Pattaraporn , Cai Juan , Ju Donghong , Leong Aaron , Udler Miriam S. , Brown James Bentley , Goodarzi Mark O. , Rotter Jerome I. , Sladek Robert , Meigs James B. , Lipovich Leonard 
Published: March 2020

AbstractAimsCausal transcripts at genomic loci associated with type 2 diabetes are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, LOC157273, located 175 kilobases from PPP1R3B, which encodes a key protein regulating insulin-mediated hepatic glycogen storage in humans. We hypothesized that LOC157273 regulates expression of PPP1R3B in human hepatocytes.MethodsWe tested our hypothesis using Stellaris fluorescent in-situ hybridization to assess subcellular localization of LOC157273; siRNA knockdown of LOC157273, followed by RT-PCR to quantify LOC157273 and PPP1R3B expression; RNA-seq to quantify the whole-transcriptome gene expression response to LOC157273 knockdown and an insulin-stimulated assay to measure hepatocyte glycogen deposition before and after knockdown.ResultsWe found that siRNA knockdown decreased LOC157273 transcript levels by approximately 80%, increased PPP1R3B mRNA levels by 1.7-fold and increased glycogen deposition by >50% in primary human hepatocytes. An A/G heterozygous carrier (vs. three G/G carriers) had reduced LOC157273 abundance due to reduced transcription of the A allele and increased PPP1R3B expression and glycogen deposition.ConclusionWe show that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and the causal transcript at an insulin resistant type 2 diabetes risk locus.
Machine learning pattern recognition and differential network analysis of gastric microbiome in the presence of proton pump inhibitor treatment orHelicobacter pyloriinfection
Authors: Ciucci Sara , Durán Claudio , Palladini Alessandra , Ijaz Umer Z. , Sterbini Francesco Paroni , Masucci Luca , Cammarota Giovanni , Ianiro Gianluca , Spuul Pirjo , Schroeder Michael , Grill Stephan W. , Parsons Bryony N. , Pritchard D. Mark , Posteraro Brunella , Sanguinetti Maurizio , Gasbarrini Giovanni , Gasbarrini Antonio , Cannistraci Carlo Vittorio 
Published: March 2020

AbstractAlthough long thought to be a sterile and inhospitable environment, the stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of orally administered drugs such as Proton Pump Inhibitors (PPIs), or bacterial infection such asHelicobacter pylori, cause significant microbial alterations. Yet, studies revealing how the commensal bacteria re-organize, due to these perturbations of the gastric environment, are in the early phase. They mainly focus on the most prevalent taxa and rely on linear techniques for multivariate analysis.Here we disclose the importance of complementing linear dimensionality reduction techniques such as Principal Component Analysis and Multidimensional Scaling with nonlinear approaches derived from the physics of complex systems. Then, we show the importance to complete multivariate pattern analysis with differential network analysis, to reveal mechanisms of re-organizations which emerge from combinatorial microbial variations induced by a medical treatment (PPIs) or an infectious state (H. pylori).