bluuebunny/crossref_metadata_2025_split huggingface dataset:
Language Disorders in Huntington Disease: A Systematic Literature Review
Authors: Gagnon Maude , Barrette Jasmine , Macoir Joël 
Published: December 2018

Objective:
A systematic review examining the presence and nature of language disorders associated with Huntington disease (HD).

Background:
HD is characterized by gradual motor dysfunction, psychiatric problems, and cognitive decline. Communication abilities in HD may be affected not only by dysarthria but also by language impairment. However, the nature and type of this impairment is not well defined.

Methods:
We searched the PubMed and PsycINFO databases and selected studies on the basis of the original language of the article, peer-review status, and specificity of the results regarding language and communication disorders.

Results:
Thirty-one articles meeting the selection criteria were selected for this review. According to most of the studies, individuals with HD present with primary deficits of language. However, a few authors suggested that language deficits in HD result from nonlinguistic impairments, or that language abilities are largely preserved. More specifically, studies showed that HD is associated with difficulties in producing and understanding sentences and discourse, processing semantic representations of object and action concepts, retrieving lexical forms of nouns, and applying morphological and syntactic rules. There is some disagreement regarding whether HD affects reading abilities, sentence production, semantic processing, and application of morphological rules in verb conjugation.

Conclusions:
Although people with HD present with language impairment, further studies are needed to identify their functional origin. Clinical studies are also needed to determine the impact of such impairments on an individual’s functional communication in daily living and to chart the progression of the impairments over the course of the disease.
The heparin-binding proteome in normal pancreas and murine experimental acute pancreatitis
Authors: Nunes Quentin M. , Su Dunhao , Brownridge Philip J. , Simpson Deborah M. , Sun Changye , Li Yong , Bui Thao P. , Zhang Xiaoying , Huang Wei , Rigden Daniel J. , Beynon Robert J. , Sutton Robert , Fernig David G. 
Published: December 2018

AbstractAcute pancreatitis (AP) is acute inflammation of the pancreas, mainly caused by gallstones and alcohol, driven by changes in communication between cells. Heparin-binding proteins (HBPs) play a central role in health and diseases. Therefore, we used heparin affinity proteomics to identify extracellular HBPs in pancreas and plasma of normal mice and in a caerulein mouse model of AP. Many new extracellular HBPs (360) were discovered in the pancreas, taking the total number of HBPs known to 786. Extracellular pancreas HBPs form highly interconnected protein-protein interaction networks in both normal pancreas (NP) and AP. Thus, HBPs represent an important set of extracellular proteins with significant regulatory potential in the pancreas. HBPs in NP are associated with biological functions such as molecular transport and cellular movement that underlie pancreatic homeostasis. However, in AP HBPs are associated with additional inflammatory processes such as acute phase response signalling, complement activation and mitochondrial dysfunction, which has a central role in the development of AP. Plasma HBPs in AP included known AP biomarkers such as serum amyloid A, as well as emerging targets such as histone H2A. Other HBPs such as alpha 2-HS glycoprotein (AHSG) and histidine-rich glycoprotein (HRG) need further investigation for potential applications in the management of AP. Pancreas HBPs are extracellular and so easily accessible and are potential drug targets in AP, whereas plasma HBPs represent potential biomarkers for AP. Thus, their identification paves the way to determine which HBPs may have potential applications in the management of AP.
Strong and lasting impacts of past global warming on baleen whale and prey abundance
Authors: Cabrera Andrea A. , Schall Elena , Bérubé Martine , Bachmann Lutz , Berrow Simon , Best Peter B. , Clapham Phillip J. , Cunha Haydée A. , Rosa Luciano Dalla , Dias Carolina , Findlay Kenneth P. , Haug Tore , Heide-Jørgensen Mads Peter , Kovacs Kit M. , Landry Scott , Larsen Finn , Lopes Xênia Moreira , Lydersen Christian , Mattila David K. , Oosting Tom , Pace Richard M. , Papetti Chiara , Paspati Angeliki , Pastene Luis A. , Prieto Rui , Ramp Christian , Robbins Jooke , Ryan Conor , Sears Richard , Secchi Eduardo R. , Silva Monica A. , Víkingsson Gísli , Wiig Øystein , Øien Nils , Palsbøll Per J. 
Published: December 2018

AbstractThe demography of baleen whales and their prey during the past 30 thousand years was assessed to understand the effects of past rapid global warming on marine ecosystems. Mitochondrial and genome-wide DNA sequence variation in eight baleen whale and seven prey species revealed strong, ocean-wide demographic changes that were correlated with changes in global temperatures and regional oceanographic conditions. In the Southern Ocean baleen whale and prey abundance increased exponentially and in apparent synchrony, whereas changes in abundance varied among species in the more heterogeneous North Atlantic Ocean. The estimated changes in whale abundance correlated with increases in the abundance of prey likely driven by reductions in sea-ice cover and an overall increase in primary production. However, the specific regional oceanographic environment, trophic interactions and species ecology also appeared to play an important role. Somewhat surprisingly the abundance of baleen whales and prey continued to increase for several thousand years after global temperatures stabilized. These findings warn of the potential for dramatic, long-term effects of current climate changes on the marine ecosystem.One Sentence SummaryThe effects of past global warming on marine ecosystems were drastic, system-wide and long-lasting.
High Dimensional Mediation Analysis with Applications to Causal Gene Identification
Authors: Zhang Qi 
Published: December 2018

AbstractMediation analysis has been a popular framework for elucidating the mediating mechanism of the exposure effect on the outcome. Previous literature in causal mediation primarily focused on the classical settings with univariate exposure and univariate mediator, with recent growing interests in high dimensional mediator. In this paper, we study the mediation model with high dimensional exposure and high dimensional mediator, and introduce two procedures for mediator selection, MedFix and MedMix. MedFix is our new application of adaptive lasso with one additional tuning parameter. MedMix is a novel mediation model based on high dimensional linear mixed model, for which we also develop a new variable selection algorithm. Our study is motivated by the causal gene identification problem, where causal genes are defined as the genes that mediate the genetic effect. For this problem, the genetic variants are the high dimensional exposure, the gene expressions the high dimensional mediator, and the phenotype of interest the outcome. We evaluate the proposed methods using a mouse f2 dataset for diabetes study, and extensive real data driven simulations. We show that the mixed model based approach leads to higher accuracy in mediator selection and mediation effect size estimation, and is more reproducible across independent measurements of the response and more robust against model misspecification. The source R code will be made available on Githubhttps://github.com/QiZhangStat/highMedupon the publication of this paper.
A high-throughput fluorescence-based assay for rapid identification of petroleum degrading bacteria
Authors: French K. E. , Terry N. 
Published: December 2018

AbstractOver the past 100 years, oil spills and long-term waste deposition from oil refineries have significantly polluted the environment. These contaminants have widespread negative effects on human health and ecosystem functioning. Natural attenuation of long chain and polyaromatic hydrocarbons is slow and often incomplete. Bioaugmentation of polluted soils with indigenous bacteria that naturally consume petroleum hydrocarbons could speed up this process. However, the characterization of bacterial crude oil degradation efficiency—which often relies upon expensive, highly specialized gas-chromatography mass spectrometry analyses--can present a substantial bottleneck in developing and implementing these bioremediation strategies. Here, we develop a low-cost, rapid, high-throughput fluorescence-based assay for identifying wild-type bacteria that degrade crude oil using the dye Nile Red. We show that Nile Red fluoresces when in contact with crude oil and developed a robust linear model to calculate crude oil content in liquid cell cultures based on fluorescence intensity (FI). To test whether this assay could identify bacteria with enhanced metabolic capacities to break down crude oil, we screened bacteria isolated from a former Shell Oil refinery in Bay Point, CA and identified one strain (Cupriavidussp. OPK) with superior crude oil depletion efficiencies (up to 83%) in only three days. We further illustrate that this assay can be combined with fluorescence microscopy to study how bacteria interact with crude oil and the strategies they use to degrade this complex substance. We show for the first time that bacteria use three key strategies for degrading crude oil: biofilm formation, direct adherence to oil droplets, and vesicle encapsulation of oil. We propose that the quantitative and qualitative data from this assay can be used to develop new bioremediation strategies based on bioaugmentation and/or biomimetic materials that imitate the natural ability of bacteria to degrade crude oil.
Live imaging the Foreign Body Response reveals how dampening inflammation reduces fibrosis
Authors: Gurevich David B. , French Kathryn E. , Collin John D. , Cross Stephen J. , Martin Paul 
Published: December 2018

AbstractImplanting biomaterials such as surgical sutures leads to wound inflammation and a Foreign Body Response (FBR), which can result in scarring and ultimately biomaterial rejection. To investigate the cell and signalling events that underlie FBR, we use live imaging of zebrafish reporter lines to observe how inflammation and angiogenesis differ between a healthy acute wound versus suture implantation. We observe inflammation extending from the suture margins and correlates with subsequent avascular and fibrotic encapsulation zones: sutures that induce more inflammation result in increased zones of avascularity and fibrosis. Moreover, we capture macrophages as they fuse to become multinucleate foreign body giant cells (FBGCs) adjacent to the most pro-inflammatory sutures. Both genetic and pharmacological dampening of the inflammatory response minimises the FBR (including FBGC generation) and normalises the status of the tissue surrounding these sutures. This new model of FBR in adult zebrafish allows us, for the first time, to live image the process and to modulate it in ways that may lead us towards new strategies to ameliorate and circumvent FBR in humans.
Host evolutionary history predicts virus prevalence across bumblebee species
Authors: Pascall David J. , Tinsley Matthew C. , Obbard Darren J. , Wilfert Lena 
Published: December 2018

AbstractWhy a pathogen associates with one host but not another is one of the most important questions in disease ecology. Here we use transcriptome sequencing of wild-caught bumblebees from 13 species to describe their natural viruses, and to quantify the impact of evolutionary history on the realised associations between viruses and their pollinator hosts. We present 37 novel virus sequences representing at least 30 different viruses associated with bumblebees. We verified 17 of them by PCR and estimate their prevalence across species in the wild. Through small RNA sequencing, we demonstrate that at least 10 of these viruses form active infections in wild individuals. Using a phylogenetic mixed model approach, we show that the evolutionary history of the host shapes the current distribution of virus/bumblebee associations. Specifically, we find that related hosts share viral assemblages, viruses differ in their prevalence averaged across hosts and the prevalence of infection in individual virus-host pairings depends on precise characteristics of that pairing.Author’s SummaryDespite the importance of disease in the regulation of animal populations, our understanding of the distribution of pathogen burden across wild communities remains in its infancy. In this study, we investigated the distribution of viruses across natural populations of 13 different bumblebee species in Scotland. We first searched for viruses using a metatranscriptomic approach, finding at least 30 new viruses of bumblebees, and assayed a subset of them for their presence and absence in different host species. Then, in the first application of these methods to an animal-virus system, we used co-phylogenetic mixed models to investigate the factors that lead to species being having different prevalences for a subset of these viruses. While much of the variation in the prevalence of the viruses can be explained by the idiosyncrasies of individual bumblebee-virus pairings, there is a phylogenetic signal with related bumblebee species being infected at similar frequencies by the same sets of viruses. Consistent with previous work, our study indicates that, while in general the interaction between a host and a virus may be unpredictable, closely related species are more likely to exhibit similar patterns of infection.
Bayesian inference and comparison of stochastic transcription elongation models
Authors: Douglas Jordan , Kingston Richard , Drummond Alexei J. 
Published: December 2018

AbstractTranscription elongation can be modelled as a three step process, involving polymerase translocation, NTP binding, and nucleotide incorporation into the nascent mRNA. This cycle of events can be simulated at the single-molecule level as a continuous-time Markov process using parameters derived from single-molecule experiments. Previously developed models differ in the way they are parameterised, and in their incorporation of partial equilibrium approximations.We have formulated a hierarchical network comprised of 12 sequence-dependent transcription elongation models. The simplest model has two parameters and assumes that both translocation and NTP binding can be modelled as equilibrium processes. The most complex model has six parameters makes no partial equilibrium assumptions. We systematically compared the ability of these models to explain published force-velocity data, using approximate Bayesian computation. This analysis was performed using data for the RNA polymerase complexes ofE. coli, S. cerevisiaeand Bacteriophage T7.Our analysis indicates that the polymerases differ significantly in their translocation rates, with the rates in T7 pol being fast compared toE. coliRNAP andS. cerevisiaepol II. Different models are applicable in different cases. We also show that all three RNA polymerases have an energetic preference for the posttranslocated state over the pretranslocated state. A Bayesian inference and model selection framework, like the one presented in this publication, should be routinely applicable to the interrogation of single-molecule datasets.Author summaryTranscription is a critical biological process which occurs in all living organisms. It involves copying the organism’s genetic material into messenger RNA (mRNA) which directs protein synthesis on the ribosome. Transcription is performed by RNA polymerases which have been extensively studied using both ensemble and single-molecule techniques (see reviews: [1, 2]). Single-molecule data provides unique insights into the molecular behaviour of RNA polymerases. Transcription at the single-molecule level can be computationally simulated as a continuous-time Markov process and the model outputs compared with experimental data. In this study we use Bayesian techniques to perform a systematic comparison of 12 stochastic models of transcriptional elongation. We demonstrate how equilibrium approximations can strengthen or weaken the model, and show how Bayesian techniques can identify necessary or unnecessary model parameters. We describe a framework to a) simulate, b) perform inference on, and c) compare models of transcription elongation.
In vivomeasurements reveal a single 5’ intron is sufficient to increase protein expression level inC. elegans
Authors: Crane Matthew M. , Sands Bryan , Battaglia Christian , Johnson Brock , Yun Soo , Kaeberlein Matt , Brent Roger , Mendenhall Alex 
Published: December 2018

AbstractIntrons can increase gene expression levels using a variety of mechanisms collectively referred to as Intron Mediated Enhancement (IME). To date, the magnitude of IME has been quantified in human cell culture and plant models by comparing intronless reporter gene expression levels to those of intron-bearing reporter genesin vitro(mRNA, Western Blots, protein activity), using genome editing technologies that lacked full control of locus and copy number. Here, for the first time, we quantified IMEin vivo, in terms of protein expression levels, using fluorescent reporter proteins expressed from a single, defined locus inCaenorhabditis elegans. To quantify the magnitude of IME, we developed a microfluidic chip-based workflow to mount and image individual animals, including software for operation and image processing. We used this workflow to systematically test the effects of position, number and sequence of introns on two different proteins, mCherry and mEGFP, driven by two different promoters,vit-2andhsp-90. We found the three canonical synthetic introns commonly used inC. eleganstransgenes increased mCherry protein concentration by approximately 50%. The naturally-occurring introns found inhsp-90also increased mCherry expression level by about 50%. Furthermore, and consistent with prior results examining mRNA levels, protein activity or phenotypic rescue, we found that a single, natural or synthetic, 5’ intron was sufficient for the full IME effect while a 3’ intron was not. IME was also affected by protein coding sequence (50% for mCherry and 80% for mEGFP) but not strongly affected by promoter 46% forhsp-90and 54% for the strongervit-2. Our results show that IME of protein expression inC. elegansis affected by intron position and contextual coding sequence surrounding the introns, but not greatly by promoter strength. Our combined controlled transgenesis and microfluidic screening approach should facilitate screens for factors affecting IME and other intron-dependent processes.
Tensor Decomposition of Stimulated Monocyte and Macrophage Gene Expression Profiles Identifies Neurodegenerative Disease-specific Trans-eQTLs
Authors: Ramdhani Satesh , Navarro Elisa , Udine Evan , Schilder Brian M. , Parks Madison , Raj Towfique 
Published: December 2018

AbstractRecent human genetic studies suggest that cells of the innate immune system have a primary role in the pathogenesis of neurodegenerative diseases. However, the results from these studies often do not elucidate how the genetic variants affect the biology of these cells to modulate disease risk. Here, we applied a tensor decomposition method to uncover disease-associated gene networks linked to distal genetic variation in stimulated human monocytes and macrophages gene expression profiles. We report robust evidence that some disease-associated genetic variants affect the expression of multiple genes in trans. These include a Parkinson’s disease locus influencing the expression of genes mediated by a protease that controls lysosomal function, and Alzheimer’s disease loci influencing the expression of genes involved in type 1 interferon signaling, myeloid phagocytosis, and complement cascade pathways. Overall, we uncover gene networks in induced innate immune cells linked to disease-associated genetic variants, which may help elucidate the underlying biology of disease.
Respiration-phased switching between sensory inputs and top-down inputs in the olfactory cortex
Authors: Narikiyo Kimiya , Manabe Hiroyuki , Yoshihara Yoshihiro , Mori Kensaku 
Published: December 2018

Olfactory perception depends on respiration phases: olfactory cortex processes external odor signals during inhalation whereas it is isolated from the external odor world during exhalation. Olfactory cortex pyramidal cells receive the sensory signals via bottom-up pathways terminating on superficial layer (SL) dendrites while they receive top-down inputs on deep layer (DL) dendrites. Here we asked whether olfactory cortex pyramidal cells spontaneously change the action modes of receiving olfactory sensory inputs and receiving top-down inputs in relation to respiration phases. Current source density analysis of local field potentials recorded in three different olfactory cortex areas of waking immobile rats revealed	β- and γ-range fast oscillatory current sinks and a slow current sink in the SL during inhalation, whereas it showed β- and γ-range fast oscillatory current sinks and a slow current sink in the DL during exhalation. Sensory deprivation experiments showed that inhalation-phased olfactory sensory inputs drove the inhalation-phased fast oscillatory potentials in the SL but they drove neither the inhalation-phased slow current sink in the SL nor the exhalation-phased slow current sink in the DL. The results indicate that independent of inhalation-phased olfactory sensory inputs, olfactory cortex pyramidal cells spontaneously generate a slow depolarization in the SL dendrites during inhalation, which may selectively boost the concomitant olfactory sensory inputs to elicit spike outputs. In addition, the pyramidal cells spontaneously generate slow depolarization in the DL dendrites during exhalation, which may assist top-down inputs to elicit spike outputs. We thus hypothesize that the olfactory cortical areas coordinately perform inhalation/exhalation-phased switching of input biasing: inhalation phase is the time window for external odor signals that arrive in the SL dendrites, whereas exhalation phase is assigned to boost top-down signals to the DL dendrites that originate in higher brain centers.
Lean service system design: a simulation-based VSM case study
Authors: Cavdur Fatih , Yagmahan Betul , Oguzcan Ece , Arslan Nazli , Sahan Nurbanu 
Published: December 2018

PurposeThe purpose of this paper is to present a methodology for using simulation models together with value stream mapping (VSM) for designing lean service systems and illustrate it with a case study.Design/methodology/approachThe authors propose a methodology combining simulation and VSM. Simulation models for both current and future states are developed to validate the results of the corresponding maps of current and future states, respectively.FindingsThe results illustrate the advantages of the suggested design represented by the future state map. Additionally, using simulation models together with VSM for validating current and future states also allows decision makers to perform comprehensive analyses on the system and draw statistical conclusions.Originality/valueAlthough some lean applications in educational services exist in previous studies, according to the best of the authors’ knowledge, this study is the first one combining VSM and simulation for the implementation of the lean concepts in the construction and technical services of a public university.