bluuebunny/crossref_metadata_2025_split huggingface dataset:
22kHz and 55kHz ultrasonic vocalizations differentially influence neural and behavioral outcomes: Implications for modeling anxiety via auditory stimuli in the rat
Authors: Demaestri Camila , Brenhouse Heather C. , Honeycutt Jennifer A. 
Published: August 2018

AbstractThe communicative role of ultrasonic vocalizations (USVs) in rodents is well established, with distinct USVs indicative of different affective states. USVs in the 22kHz range are typically emitted by adult rats when in anxiety-or fear-provoking situations (e.g. predator odor, social defeat), while 55kHz range USVs are emitted in appetitive situations (e.g., play, anticipation of reward). Previous work indicates that USVs (real-time and playback) can effectively communicate these affective states and influence changes in behavior and neural activity of the receiver. Changes in cFos activation following 22kHz USVs have been seen in cortical and limbic regions involved in anxiety, including the basolateral amygdala (BLA). However, it is unknown how USV playback influences cFos activity within the basal nucleus of the stria terminalis (BNST), a region also thought to be critical in processing anxiety-related information. The present work sought to characterize distinct behavioral, physiological, and neural responses in rats presented with aversive (22kHz) compared to appetitive (55kHz) USVs or silence. Our findings show that rats exposed to 22kHz USVs: 1) engage in anxiety-like behaviors in the open field and elevated zero maze, and 2) show distinct patterns of cFos activation within the BLA and BNST that contrast those seen in 55kHz playback. Specifically, 22kHz USVs increased cFos density in the anterodorsal nuclei, while 55kHz playback increased cFos in the oval nucleus of the BNST. These results provide important groundwork for leveraging ethologically-relevant stimuli in the rat to improve our understanding of anxiety-related responses in both typical and pathological populations.
Automated Electrodes Detection during simultaneous EEG/fMRI
Authors: Fleury Mathis , Barillot Christian , Mano Marsel , Bannier Elise , Maurel Pierre 
Published: August 2018

1AbstractThe coupling of Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) enables the measure of brain activity at high spatial and temporal resolution. The localisation of EEG sources depends on several parameters including the knowledge of the position of the electrodes on the scalp. An accurate knowledge about this information is important for source reconstruction. Currently, when acquiring EEG and fMRI together, the position of the electrodes is generally estimated according to fiducial points by using a template. In the context of simultaneous EEG/fMRI acquisition, a natural idea is to use magnetic resonance (MR) images to localise EEG electrodes. However, most MR compatible electrodes are built to be almost invisible on MR Images. Taking advantage of a recently proposed Ultra short Echo Time (UTE) sequence, we introduce a fully automatic method to detect and label those electrodes in MR images. Our method was tested on 8 subjects wearing a 64-channel EEG cap. This automated method showed an average detection accuracy of 94% and the average position error was 3.1 mm. These results suggest that the proposed method has potential for determining the position of the electrodes during simultaneous EEG/fMRI acquisition with a very light cost procedure.
Human-specificARHGAP11Binduces hallmarks of neocortical expansion in developing ferret neocortex
Authors: Kalebic Nereo , Gilardi Carlotta , Albert Mareike , Namba Takashi , Long Katherine R. , Kostic Milos , Langen Barbara , Huttner Wieland B. 
Published: August 2018

AbstractThe evolutionary increase in size and complexity of the primate neocortex is thought to underlie the higher cognitive abilities of humans.ARHGAP11Bis a human-specific gene that, based on its expression pattern in fetal human neocortex and progenitor effects in embryonic mouse neocortex, has been proposed to have a key function in the evolutionary expansion of the neocortex. Here, we study the effects ofARHGAP11Bexpression in the developing neocortex of the gyrencephalic ferret. In contrast to its effects in mouse, ARHGAP11B markedly increases proliferative basal radial glia, a progenitor cell type thought to be instrumental for neocortical expansion, and results in extension of the neurogenic period and an increase in upper-layer neurons. As a consequence, the postnatal ferret neocortex exhibits an increased neuron density in the upper cortical layers and expands in the radial dimension. Thus, human-specific ARHGAP11B can elicit hallmarks of neocortical expansion in developing ferret neocortex.
The RNA helicase UPF1 associates with mRNAs co-transcriptionally and is required for the release of mRNAs from transcription sites
Authors: Singh Anand K. , Choudhury Subhendu Roy , De Sandip , Zhang Jie , Kissane Stephen , Dwivedi Vibha , Ramanathan Preethi , Orsini Luisa , Hebenstreit Daniel , Brogna Saverio 
Published: August 2018

SummaryUPF1 is an RNA helicase that is required for efficient nonsense-mediated mRNA decay (NMD) in eukaryotes, and the predominant view is that UPF1 mainly operates on the 3’UTRs of mRNAs that are directed for NMD in the cytoplasm. Here we offer evidence, obtained fromDrosophila, that UPF1 constantly moves between the nucleus and cytoplasm and that it has multiple functions in the nucleus. It is associated, genome-wide, with nascent RNAs at most of the active Pol II transcription sites and at some Pol III-transcribed genes, as demonstrated microscopically on the polytene chromosomes of salivary gland and by ChIP-seq analysis in S2 cells. Intron recognition seems to interfere with association and translocation of UPF1 on nascent pre-mRNA transcripts, and cells depleted of UPF1 show defects in several nuclear processes essential to correct gene expression – most strikingly, the release of mRNAs from transcription sites and mRNA export from the nucleus.
NHBA is processed by kallikrein from human saliva
Authors: Pantano Elisa , Marchi Sara , Biagini Massimiliano , Fede Martina Di , Nardi-Dei Vincenzo , Paccani Silvia Rossi , Pizza Mariagrazia , Cartocci Elena 
Published: August 2018

AbstractNeisserial Heparin Binding Antigen (NHBA) is a surface-exposed lipoprotein and a component of the Bexsero vaccine. NHBA is characterized by the presence of a highly conserved Arg-rich region involved in binding to heparin and heparin sulphate proteoglycans present on the surface of host epithelial cells, suggesting a possible role of NHBA duringN. meningitidiscolonization. NHBA has been shown to be cleaved by the bacterial NalP protein, a meningococcal protease and by human lactoferrin (hLF), a host protease present in different body fluids (saliva, breast milk and serum). Cleavage occurs upstream or downstream the Arg-rich region. Since the human nasopharynx is the only known reservoir of infection, we further investigated the susceptibility of NHBA to human proteases present in the saliva to assess whether proteolytic cleavage could happen during the initial steps of colonization. Here we show that human saliva proteolytically cleaves NHBA; and identified human kallikrein 1 (KLK1) as the main protease responsible for this cleavage. Kallikrein is an important enzyme present in blood plasma, lymph, urine, saliva, pancreatic juices, and other body fluids that catalyze the proteolysis of several human proteins. We report thein vitrocharacterization of NHBA cleavage by kallikrein; the identification of the cleavage in the recombinant NHBA protein and, on the native protein, when expressed on live bacteria. Overall, this findings provide new insights on NHBA as target of host proteases, highlights a potential role of NHBA in theNeisseria meningitidisnasopharyngeal colonization, and of kallikrein as a defensive agent against meningococcal infection.
An interaction network of the human SEPT9 established by quantitative mass spectrometry reveals an interplay with myosin motors
Authors: Hecht Matthias , Rösler Reinhild , Wiese Sebastian , Johnsson Nils , Gronemeyer Thomas 
Published: August 2018

SummaryPhenotypic variations of an organism or a single cell often arise from alterations of protein interaction networks. We provide here an interaction network of the human SEPT9, an important component of the human septin cytoskeleton.AbstractExperimentally deciphering and understanding the interaction network of a particular protein provides often evidence for so far unknown functions. For the septins, a class of cytoskeletal proteins, targeted high-throughput approaches that aim at systematically deciphering interaction partners have not yet been performed. Septins regulate the organization of the acin cytoskeleton, vesicle transport and fusion, chromosome alignment-and segregation, and cytokinesis. SEPT9 is part of the core septin hetero-octamer in human cells which is composed of SEPT2, SEPT6, SEPT7, and SEPT9. SEPT9 has been linked to a variety of intracellular functions as well as to diseases and diverse types of cancer. We applied a quantitative proteomics approach to establish an interactome of SEPT9 in human fibroblast cells. We identified among others so far unknown interaction partners from the myosin family and could provide evidence that SEPT9 participates in vesicle transport from and to the plasma membrane as well as in the attachment of actin stress fibers to cellular adhesions.
The fungal root endophyte Serendipita indica modifies extracellular nucleotides to subvert plant immunity
Authors: Nizam Shadab , Qiang Xiaoyu , Wawra Stephan , Nostadt Robin , Getzke Felix , Schwanke Florian , Dreyer Ingo , Langen Gregor , Zuccaro Alga 
Published: August 2018

One sentence abstractImmune modulation by metabolites in plant fungus interactionAbstractExtracellular adenosine 5′-triphosphate (eATP) is an essential signaling molecule that mediates different cellular processes through its interaction with membrane-associated receptor proteins in animals and plants. eATP regulates plant growth, development and responses to biotic and abiotic stresses. Its accumulation in the apoplast induces ROS production and cytoplasmic calcium increase mediating a defense response to invading microbes. We demonstrate that perception of eATP is important in plant-fungus interaction and that during colonization by the beneficial root endophyte Serendipita indica accumulation of eATP in the apoplast occurs at early symbiotic stages. We show by liquid chromatography-tandem mass spectrometry, cytological and functional analysis that S. indica subvert eATP host response by secreting SiE5’NT, an enzymatically active ecto-5′nucleotidase capable of hydrolyzing eATP to adenosine. A. thaliana lines producing extracellular SiE5’NT are signi?cantly better colonized and have reduced eATP levels and defense signaling, indicating that SiE5’NT functions as a compatibility factor. Our data show that extracellular bioactive nucleotides play an important role in fungus-root interactions and that fungi can modify plant derived metabolites in the apoplast to modulate host immunity.
Identifying incident dementia by applying machine learning to a very large administrative claims dataset
Authors: Nori Vijay S. , Hane Christopher A. , Martin David C. , Kravetz Alexander D. , Sanghavi Darshak M. 
Published: August 2018

ABSTRACTINTRODUCTIONAlzheimer’s disease and related dementias (ADRD) are highly prevalent conditions, and prior efforts to develop predictive models have relied on demographic and clinical risk factors using traditional logistical regression methods. We hypothesized that machine-learning algorithms using administrative claims data may represent a novel approach to predicting ADRD.METHODSUsing a national de-identified dataset of more than 125 million patients including over 10,000 clinical, pharmaceutical, and demographic variables, we developed a cohort to train a machine learning model to predict ADRD 4-5 years in advance.RESULTSThe Lasso algorithm selected a 50-variable model with an area under the curve (AUC) of 0.693. Top diagnosis codes in the model were memory loss (780.93), Parkinson’s disease (332.0), mild cognitive impairment (331.83) and bipolar disorder (296.80), and top pharmacy codes were psychoactive drugs.DISCUSSIONMachine learning algorithms can rapidly develop predictive models for ADRD with massive datasets, without requiring hypothesis-driven feature engineering.RESEARCH IN CONTEXTSystematic review: Previous attempts to predict incident dementia have relied on extensive clinical evaluations, cognitive testing, laboratory testing, neuro-imaging, genetic factors, demographics, and lifestyle variables. Applying machine learning to a large administrative claims dataset to identify individuals at increased likelihood for near-term diagnosis of dementia had not been tested.Interpretation: A 50-variable model to identify those at risk for near-term diagnosis of dementia was created and validated. Based on AUC analysis, the model compared favorably with other historical attempts at modeling more traditional forms of data.Future direction: Models, such as the one developed here, could be used to identify populations of higher prior probability for near-term diagnosis of dementia. These could then be subjected to more in-depth scrutiny for intervention or dementia-related research eligibility.
Excitable dynamics through toxin-induced mRNA cleavage in bacteria
Authors: Vet Stefan , Vandervelde Alexandra , Gelens Lendert 
Published: August 2018

AbstractToxin-antitoxin (TA) systems in bacteria and archaea are small genetic elements consisting of the genes coding for an intracellular toxin and an antitoxin that can neutralize this toxin. In various cases, the toxins cleave the mRNA. In this theoretical work we use deterministic and stochastic modeling to explain how toxin-induced cleavage of mRNA in TA systems can lead to excitability, allowing large transient spikes in toxin levels to be triggered. By using a simplified network where secondary complex formation and transcriptional regulation are not included, we show that a two-dimensional, deterministic model captures the origin of such toxin excitations. Moreover, it allows to increase our understanding by examining the dynamics in the phase plane. By systematically comparing the deterministic results with Gillespie simulations we demonstrate that even though the real TA system is intrinsically stochastic, toxin excitations can be accurately described deterministically. A bifurcation analysis of the system shows that the excitable behavior is due to a nearby Hopf bifurcation in the parameter space, where the system becomes oscillatory. The influence of stress is modeled by varying the degradation rate of the antitoxin and the translation rate of the toxin. We find that stress increases the frequency of toxin excitations and decreases the excitation time. The inclusion of secondary complex formation and transcriptional regulation does not fundamentally change the mechanism of toxin excitations. Therefore, the deterministic model used in this work provides a simple and intuitive explanation of toxin excitations in TA systems.Author summaryThe genomes of most bacteria and archaea encode several toxin-antitoxin (TA) systems, small genetic elements consisting of the genes coding for an intracellular toxin and an antitoxin that can neutralize this toxin. For several toxins, the target is the mRNA. In this theoretical work we use deterministic and stochastic modeling to explain how toxin-induced cleavage of mRNA in TA systems can trigger large transient spikes in toxin levels. By using a simplified network where secondary complex formation and transcriptional regulation are not included, we show that a two-dimensional, deterministic model captures the origin of such toxin excitations. By systematically comparing our findings with more complex models, we find that the intrinsically stochastic TA system shows similar toxin excitations that are accurately predicted by the underlying simplified theory. This has allowed us to understand how the TA system responds in the presence of stress conditions, finding that toxin excitations become shorter and more frequent.
Epigallocatechin-3-gallate yield in different temperature gradients in green tea (Camellia sinensis) brewing
Authors: Hsieh Meng Hsuen , Hsieh Meng Ju , Wu Chi-Rei , Peng Wen-Huang , Hsieh Ming-Tsuen , Hsieh Chia-Chang 
Published: August 2018

ABSTRACTIntroductionEpigallocatechin-3-gallate (EGCG) is a chemical catechin, a natural organic compound found in green teas with strong antioxidative effects. EGCG degrades or epimerizes according to temperature, fluctuating its concentration in green tea (Camellia sinensis). This study is conducted to determine the specified correlation between EGCG and tea temperature, and to conclude with the optimal temperature for EGCG yield.MethodsEGCG concentrations in different solutions of green tea are analyzed using a high-performance liquid chromatography (HPLC), with a diode array detector (DAD). The solutions are created from green tea brewed in water from 20°C to 100°C at increments of 20°C and undergo an ultrasonic bath of 30 minutes before being analyzed.ResultsThere is a discernible difference between EGCG concentrations in all temperatures. At 20, 40, 60, 80 and 100°C, the concentrations are 6.18 μg/mL, 32.37 μg/mL, 57.36 μg/mL, 36.13 μg/mL, and 44.85 μg/mL, respectively. EGCG concentration maximizes at 60°C. The lowest EGCG concentration yield is at 20°C.ConclusionThe results of our experiments lead us to recommend hot brewing over cold brewing for green tea if one wishes to maximize the potential of the effects of EGCG due to its higher concentration.
Allele-specific binding of RNA-binding proteins reveals functional genetic variants in the RNA
Authors: Yang Ei-Wen , Bahn Jae Hoon , Yun-Hua Hsiao Esther , Tan Boon Xin , Sun Yiwei , Fu Ting , Zhou Bo , Van Nostrand Erc L. , Pratt Gabriel A. , Freese Peter , Wei Xintao , Quinones-Valdez Giovanni , Urban Alexander E. , Graveley Brenton R. , Burge Christopher B. , Yeo Gene W. , Xiao Xinshu 
Published: August 2018

AbstractAllele-specific protein-RNA binding is an essential aspect that may reveal functional genetic variants influencing RNA processing and gene expression phenotypes. Recently, genome-wide detection of in vivo binding sites of RNA binding proteins (RBPs) is greatly facilitated by the enhanced UV crosslinking and immunoprecipitation (eCLIP) protocol. Hundreds of eCLIP-Seq data sets were generated from HepG2 and K562 cells during the ENCODE3 phase. These data afford a valuable opportunity to examine allele-specific binding (ASB) of RBPs. To this end, we developed a new computational algorithm, called BEAPR (Binding Estimation of Allele-specific Protein-RNA interaction). In identifying statistically significant ASB sites, BEAPR takes into account UV cross-linking induced sequence propensity and technical variations between replicated experiments. Using simulated data and actual eCLIP-Seq data, we show that BEAPR largely outperforms often-used methods Chi-Squared test and Fisher’s Exact test. Importantly, BEAPR overcomes the inherent over-dispersion problem of the other methods. Complemented by experimental validations, we demonstrate that ASB events are significantly associated with genetic regulation of splicing and mRNA abundance, supporting the usage of this method to pinpoint functional genetic variants in post-transcriptional gene regulation. Many variants with ASB patterns of RBPs were found as genetic variants with cancer or other disease relevance. About 38% of ASB variants were in linkage disequilibrium with single nucleotide polymorphisms from genome-wide association studies. Overall, our results suggest that BEAPR is an effective method to reveal ASB patterns in eCLIP and can inform functional interpretation of disease-related genetic variants.
CRUMBLER: A Tool for the Prediction of Ancestry in Cattle
Authors: Crum Tamar E. , Schnabel Robert D. , Decker Jared E. , Regitano Luciana CA , Taylor Jeremy F. 
Published: August 2018

AbstractBackgroundIn many beef and some dairy production systems, crossbreeding is used to take advantage of breed complementarity and heterosis. Admixed animals are frequently identified by their coat color and body conformation phenotypes, however, without pedigree information it is not possible to identify the expected breed composition of an admixed animal and in the presence of selection, the actual composition may differ from expectation. As the roles of DNA and genotype data become more pervasive in animal agriculture, a systematic method for estimating the breed composition (the proportions of an animal’s genome originating from ancestral pure breeds) has utility for a variety of downstream analyses including the estimation of genomic breeding values for crossbred animals, the estimation of quantitative trait locus effects, and heterosis and heterosis retention in advanced generation composite animals. Currently, there is no automated or semi-automated ancestry estimation platform for cattle and the objective of this study was to evaluate the utility of extant public software for ancestry estimation and determine the effects of reference population size and composition and number of utilized single nucleotide polymorphism loci on ancestry estimation. We also sought to develop an analysis pipeline that would simplify this process for members of the livestock genomics research community.ResultsWe developed and tested a tool, “CRUMBLER”, to estimate the global ancestry of cattle using ADMIXTURE and SNPweights based on a defined reference panel.CRUMBLER, was developed and evaluated in cattle, but is a species agnostic pipeline that facilitates the streamlined estimation of breed composition for individuals with potentially complex ancestries using publicly available global ancestry software and a specified reference population SNP dataset. We developed the reference panel from a large cattle genotype data set and breed association pedigree information using iterative analyses to identify purebred individuals that were representative of each breed. We also evaluated the numbers of markers necessary for breed composition estimation and simulated genotypes for advanced generation composite animals to evaluate the precision of the developed tool.ConclusionThe developed CRUMBLER pipeline extracts a specified subset of genotypes that is common to all current commercially available genotyping platforms, processes these into the file formats required for the analysis software, and predicts admixture proportions using the specified reference population allele frequencies.
Mortality causes universal changes in microbial community composition
Authors: Abreu Clare I. , Friedman Jonathan , Andersen Woltz Vilhelm L. , Gore Jeff 
Published: August 2018

AbstractAll organisms are sensitive to the abiotic environment, and a deteriorating environment can lead to extinction. However, survival in a multispecies community also depends upon inter-species interactions, and some species may even be favored by a harsh environment that impairs competitors. A deteriorating environment can thus cause surprising transitions in community composition. Here, we combine theory and laboratory microcosms to develop a predictive understanding of how simple multispecies communities change under added mortality, a parameter that represents environmental harshness. In order to explain changes in a multispecies microbial system across a mortality gradient, we examine its members’ pairwise interactions. We find that increasing mortality favors the faster grower, confirming a prediction of simple models. Furthermore, if the slower grower outcompetes the faster grower in environments with low or no added mortality, the competitive outcome can reverse as mortality increases. We find that this tradeoff between growth rate and competitive ability is indeed prevalent in our system, allowing for striking pairwise outcome changes that propagate up to multispecies communities. These results argue that a bottom-up approach can provide insight into how communities will change under stress.