bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic Functional Characterization of Human 21st Chromosome Orthologs inCaenorhabditis elegans
Authors: Nordquist Sarah K. , Smith Sofia R. , Pierce Jonathan T. 
Published: May 2017

ABSTRACTIndividuals with Down syndrome have neurological and muscle impairments due to an additional copy of the human 21stchromosome (HSA21). Only a few of ~200 HSA21 genes encoding protein have been linked to specific Down syndrome phenotypes, while the remainder are understudied. To identify poorly characterized HSA21 genes required for nervous system function, we studied behavioral phenotypes caused by loss-of-function mutations in conserved HSA21 orthologs in the nematodeCaenorhabditis elegans. We identified ten HSA21 orthologs that are required for neuromuscular behaviors:cle-1(COL18A1),cysl-2(CBS),dnsn-1(DONSON),eva-1(EVA1C),mtq-2(N6ATM1),ncam-1(NCAM2),pad-2(POFUT2),pdxk-1(PDXK),rnt-1(RUNX1), andunc-26(SYNJ1). We also found that three of these genes are required for normal release of the neurotransmitter acetylcholine. This includes a known synaptic geneunc-26(SYNJ1), as well as uncharacterized genespdxk-1(PDXK) andmtq-2(N6ATM1). As the first systematic functional analysis of HSA21 orthologs, this study may serve as a platform to understand genes that underlie phenotypes associated with Down syndrome.ARTICLE SUMMARYDown syndrome causes neurological and muscle dysfunction due to an extra 21stchromosome. This chromosome has over 200 genes, most of which are understudied. To address this, we studied whether reducing function of these gene equivalents in the wormC. eleganscaused neuronal or muscle defects. We identified ten genes conserved between human and worm that mediate function of behaviors. Among these, we show the uncharacterized genesmtq-2andpdxk-1are important for synaptic transmission and are exclusively expressed in nervous system. Our analysis may reveal functions of poorly studied genes that affect nervous system function in Down syndrome.
Response-time behaviors of intercellular communication network motifs
Authors: Thurley Kevin , Wu Lani F , Altschuler Steven J 
Published: May 2017

AbstractCell-to-cell communication networks have critical roles in diverse organismal processes, such as coordinating tissue development or immune cell response. However, compared to intracellular signal transduction networks, the function and engineering principles of cell-to-cell communication networks are far less understood. Here, we study cell-to-cell communication networks using a framework that models the input-to-output relationship of intracellular signal transduction networks with a single function—the response-time distribution. We identify a prototypic response-time distribution—the gamma distribution—arising in both experimental data sets and mathematical models of signal-transduction pathways. We find that simple cell-to-cell communication circuits can generate bimodal response-time distributions, and can control synchronization and delay of cell-population responses independently. We apply our modeling approach to explain otherwise puzzling data on cytokine secretion onset times in T cells. Our approach can be used to predict communication network structure using experimentally accessible input-to-output measurements and without detailed knowledge of intermediate steps.
Ionic current correlations are ubiquitous across phyla
Authors: Tran Trinh , Unal Cagri T. , Zaborszky Laszlo , Rotstein Horacio , Kirkwood Alfredo , Golowasch Jorge 
Published: May 2017

AbstractIonic currents, whether measured as conductance amplitude or as ion channel transcript levels, can vary many-fold within a population of identified neurons. This variability has been observed in multiple invertebrate neuronal types, but they do so in a coordinated manner such that their magnitudes are correlated. These conductance correlations are thought to reflect a tight homeostasis of cellular excitability that enhances the robustness and stability of neuronal activity over long stretches of time. Notably, although such ionic current correlations are well documented in invertebrates, they have not been reported in vertebrates. Here we demonstrate with two examples, identified mouse hippocampal granule cells and cholinergic basal forebrain neurons, that ionic current correlations is a ubiquitous phenomenon expressed by a number of species across phyla.
Detecting molecular basis of phenotypic convergence
Authors: Chabrol Olivier , Royer-Carenzi Manuela , Pontarotti Pierre , Didier Gilles 
Published: May 2017

AbstractConvergence is the process by which several species independently evolve similar traits. This evolutionary process is not only strongly related to fundamental questions such as the predictability of evolution and the role of adaptation, its study also may provide new insights about genes involved in the convergent character. We focus on this latter question and aim to detect molecular basis of a given phenotypic convergence. After pointing out a number of concerns about detection methods based on ancestral reconstruction, we propose a novel approach combining an original measure of the extent to which a site supports a phenotypic convergence, with a statistical framework for selecting genes from the measure of their sites. First, our measure of “convergence level” outperforms two previous ones in distinguishing simulated convergent sites from non-convergent ones. Second, by applying our detection approach to the well-studied case of convergent echolocation between dolphins and bats, we identified a set of genes which is very significantly annotated with audition-related GO-terms. This result constitutes an indirect evidence that genes involved in a phenotypic convergence can be identified with a genome-wide approach, a point which was highly debated, notably in the echolocation case (the latest articles published on this topic were quite pessimistic). Our approach opens the way to systematic studies of numerous examples of convergent evolution in order to link (convergent) phenotype to genotype.
De novoannotation and characterization of the translatome with ribosome profiling data
Authors: Xiao Zhengtao , Huang Rongyao , Chen Yuling , Deng Haiteng , Yang Xuerui 
Published: May 2017

AbstractBy capturing and sequencing the RNA fragments protected by translating ribosomes, ribosome profiling sketches the landscape of translation at subcodon resolution. We developed a new method, RiboCode, which uses ribosome profiling data to assess the translation of each RNA transcript genome-wide. As shown by multiple tests with simulated data and cell type-specific QTI-seq and mass spectrometry data, RiboCode exhibits superior efficiency, sensitivity, and accuracy forde novoannotation of the translatome, which covers various types of novel ORFs in the previously annotated coding and non-coding regions and overlapping ORFs. Finally, to showcase its application, we applied RiboCode on a published ribosome profiling dataset and assembled the context-dependent translatomes of yeast under normal condition, heat shock, and oxidative stress. Comparisons among these translatomes revealed stress-activated novel upstream and downstream ORFs, some of which are associated with potential translational dysregulations of the main protein coding ORFs in response to the stress signals.
Easyml: Easily Build and Evaluate Machine Learning Models
Authors: Ahn Woo-Young , Hendricks Paul , Haines Nathaniel 
Published: May 2017

AbstractTheeasyml(easymachinelearning) package lowers the barrier to entry to machine learning and is ideal for undergraduate/graduate students, and practitioners who want to quickly apply machine learning algorithms to their research without having to worry about the best practices of implementing each algorithm. The package provides standardized recipes for regression and classification algorithms in R and Python and implements them in a functional, modular, and extensible framework. This package currently implements recipes for several common machine learning algorithms (e.g., penalized linear models, random forests, and support vector machines) and provides a unified interface to each one. Importantly, users can run and evaluate each machine learning algorithmwith a single line of coding.Each recipe is robust, implements best practices specific to each algorithm, and generates a report with details about the model, its performance, as well as journal-quality visualizations. The package’s functional, modular, and extensible framework also allows researchers and more advanced users to easily implement new recipes for other algorithms.
Protein features identification for machine learning-based prediction of protein-protein interactions
Authors: Raza Khalid 
Published: May 2017

AbstractThe long awaited challenge of post-genomic era and systems biology research is computational prediction of protein-protein interactions (PPIs) that ultimately lead to protein functions prediction. The important research questions is how protein complexes with known sequence and structure be used to identify and classify protein binding sites, and how to infer knowledge from these classification such as predicting PPIs of proteins with unknown sequence and structure. Several machine learning techniques have been applied for the prediction of PPIs, but the accuracy of their prediction wholly depends on the number of features being used for training. In this paper, we have performed a survey of protein features used for the prediction of PPIs. The open research challenges and opportunities in the area have also been discussed.
Inducible and reversible phenotypes in a novel mouse model of Friedreich’s Ataxia
Authors: Chandran Vijayendran , Gao Kun , Swarup Vivek , Versano Revital , Dong Hongmei , Jordan Maria C. , Geschwind Daniel H. 
Published: May 2017

ABSTRACTFriedreich’s ataxia (FRDA), the most common inherited ataxia, is caused by recessive mutations that reduce the levels of frataxin (FXN), a mitochondrial iron binding protein. We developed an inducible mouse model ofFxndeficiency that enabled us to control the onset and progression of disease phenotypes by the modulation ofFxnlevels. Systemic knockdown ofFxnin adult mice led to multiple phenotypes paralleling those observed in human patients across multiple organ systems. By reversing knockdown after clinical features appear, we were able to determine to what extent observed phenotypes represent reversible cellular dysfunction. Remarkably, upon restoration of near wild-type FXN levels, we observed significant recovery of function, associated pathology and transcriptomic dysregulation even after substantial motor dysfunction and pathology were observed. This model will be of broad utility in therapeutic development and in refining our understanding of the relative contribution of reversible cellular dysfunction at different stages in disease.
Cellular responses to proteostasis perturbations reveal non-optimal feedback in chaperone networks
Authors: Ghosh Asmita , Gangadharan Abhilash , Das Sarada , Verma Monika , Matai Latika , Dash Debasis , Mapa Koyeli , Chakraborty Kausik 
Published: May 2017

AbstractThe proteostasis network (PN) comprises a plethora of proteins that are dedicated to aid in protein folding; some with over-lapping functions. Despite this, there are multiple pathophysiological states associated with depletion of chaperones. This is counter-intuitive assuming cells have the ability to re-program transcriptional outputs in accordance with its proteostasic limitations. To this effect, we have usedS. cerevisiaeto understand the route a cell takes as a response when challenged with different proteostasis impairments. Using 14 single deletion strains of genes of Protein Quality Control (PQC) system, we quantify their proteostasis impairment and the transcriptional response. In most cases cellular response was incapable of restoring proteostasis. The response did not activate proteostasis components or pathways that could complement the function of the missing PQC gene. Over-expression of alternate machineries, could restore part of the proteostasis defect in deletion strains. We posit that epistasis guided synthetic biology approaches may be helpful in realizing the true potential of the cellular chaperone machinery.
Inferring Genetic Interactions From Comparative Fitness Data
Authors: Crona Kristina , Gavryushkin Alex , Greene Devin , Beerenwinkel Niko 
Published: May 2017

AbstractDarwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasitePlasmodium vivax, the fungusAspergillus niger, and the TEM-family ofβ-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.
Behavioural outcomes of adult female offspring following maternal stress and perinatal fluoxetine exposure
Authors: Kiryanova Veronika , Meunier Sara J. , Dyck Richard H. 
Published: May 2017

AbstractDepression, anxiety, and stress are common in pregnant women. One of the primary pharmacological treatments for anxiety and depression is the antidepressant fluoxetine (Flx). Maternal stress, depression, and Flx exposure are known to effect neurodevelopment of the offspring, however, their combined effects have been scarcely studied, especially in female offspring. The present study investigated the combined effects of maternal stress during pregnancy and perinatal exposure to Flx on the behaviour of female mice as adults. METHODS: Mouse dams were exposed to either chronic unpredictable stress (embryonic (E) day 7 to E18), or FLX (E15-postnatal day 12), or a combination of stress and FLX or left untreated. At two months of age, the female offspring went through a comprehensive behavioural test battery. RESULTS: Maternal stress led to increased activity and alterations of prepulse inhibition in the adult female offspring. Maternal treatment with Flx had a potentially beneficial effect on spatial memory. The combination of prenatal stress and perinatal Flx exposure did not interact in their effects. These results suggest that gestational Flx exposure may have a limited negative impact on female offspring.
Genome-wide association study reveals genetic link between diarrhea-associatedEntamoeba histolyticainfection and inflammatory bowel disease
Authors: Wojcik Genevieve L , Marie Chelsea , Abhyankar Mayuresh M , Yoshida Nobuya , Watanabe Koji , Mychaleckyj Josyf , Kirkpatrick Beth D , Rich Stephen S , Concannon Patrick , Haque Rashidul , Tsokos George C. , Petri William A , Duggal Priya 
Published: May 2017

AbstractDiarrhea is the second leading cause of death for children globally, causing 760,000 deaths each year in children under the age of 5. Amoebic dysentery contributes significantly to this burden, especially in developing countries. We hypothesize that genetic variation contributes to susceptibility to diarrhea-associatedEntamoeba histolyticainfection in Bangladeshi infants; thus, we conducted a genome-wide association study (GWAS) in two independent birth cohorts of diarrhea-associatedE. histolyticainfection. Cases were defined as children with at least one diarrheal episode positive forE. histolyticathrough either PCR or ELISA within the first year of life. Controls were children without any episodes positive forE. histolyticain the same time frame. Meta-analyses under a fixed-effects inverse variance weighting model identified variants in two neighboring genes on chromosome 10:CUL2(cullin 2) andCREM(cAMP responsive element modulator) associated withE. histolyticainfection, with SNP rs58000832 achieving genome-wide significance (Pmeta=4.2x10−10). Each additional risk allele (an intergenic insertion betweenCREMandCCNY) of rs58000832 conferred 2.5 increased odds of a diarrhea-associatedE. histolyticainfection. The most associated SNP within a gene was in an intron ofCREM(rs58468685, Pmeta=2.3x10−9), which withCUL2, has been implicated as a susceptibility locus for Inflammatory Bowel Disease (IBD) and Crohn’s Disease. Gene expression resources suggest these loci are related to the higher expression ofCREM, but notCUL2. IncreasedCREMexpression is also observed in earlyE. histolyticainfection. Further,CREM-/-mice were more susceptible toE. histolyticaamebic colitis. These genetic associations reinforce the pathological similarities observed in gut inflammation betweenE. histolyticainfection and IBD.
Maximum Entropy Framework For Inference Of Cell Population Heterogeneity In Signaling Networks
Authors: Dixit Purushottam D. , Lyashenko Eugenia , Niepel Mario , Vitkup Dennis 
Published: May 2017

AbstractPredictive models of signaling networks are essential tools for understanding cell population heterogeneity and designing rational interventions in disease. However, using network models to predict signaling dynamics heterogeneity is often challenging due to the extensive variability of signaling parameters across cell populations. Here, we describe aMaximumEntropy-based fRamework for Inference of heterogeneity inDynamics of sIgAlingNetworks (MERIDIAN). MERIDIAN allows us to estimate the joint probability distribution over signaling parameters that is consistent with experimentally observed cell-to-cell variability in abundances of network species. We apply the developed approach to investigate the heterogeneity in the signaling network activated by the epidermal growth factor (EGF) and leading to phosphorylation of protein kinase B (Akt). Using the inferred parameter distribution, we also predict heterogeneity of phosphorylated Akt levels and the distribution of EGF receptor abundance hours after EGF stimulation. We discuss how MERIDIAN can be generalized and applied to problems beyond modeling of heterogeneous signaling dynamics.
The effect of social spending on reducing poverty
Authors: Celikay Ferdi , Gumus Erdal 
Published: May 2017

Purpose
The purpose of this paper is to provide new empirical evidence on the relationship between social expenditure and poverty in Turkey.

Design/methodology/approach
There are voluminous studies in the literature and many of which contain condradictory results. The authors use panel error correction models and employ Turkish statistical territorial units data (26 regions) covering the period 2004-2011 in the analysis.

Findings
The authors have found that in the short run, there is a negative relationship between social expenditure and poverty, as expected. In the long run, however, there exists a positive relation between them. The authors utilize expenditure on education as one component of social expenditure, and the authors obtain a negative relationship between education expenditure and poverty, both in the short run and in the long run.

Social implications
Poverty is an important social problem that more studies on this subject should examine various aspects and find policies to alleviate it.

Originality/value
Literature on poverty and social spending are growing and their results are contradictory. However, this paper clearly and significantly provides new empirical evidence on the effect of social spending on reducing poverty using Turkish data. This kind of study is hardly found for developing countries like Turkey. It contributes to the literature.
Twelve methods of money laundering
Authors: Teichmann Fabian Maximilian Johannes 
Published: May 2017

Purpose
This paper aims to discuss how feasible it is for intelligent criminals to circumvent existing anti-money laundering mechanisms.

Design/methodology/approach
Based upon ten informal interviews with money launderers and their advisers; 18 formal, semi-standardized expert interviews with selected anti-money laundering specialists; and a quantitative survey of 181 compliance officers, 12 effective methods to launder money have been developed.

Findings
It has been found that gold, jewellery, raw diamonds, antiquities, art, real estate projects, consulting firms, mergers and acquisitions, banks in Dubai, deposit boxes, private cash deals and currency exchange offices continue to be extraordinarily suitable tools for money laundering.

Originality/value
The identification of gaps in anti-money laundering mechanisms is meant to provide both compliance officers and legislators with valuable insights. While the existing literature focuses on estimating the volume of money laundered in certain geographical areas and on the improvement of anti-money laundering mechanisms, this paper describes how money launderers proceed to avoid getting caught.
Engagement platforms in the sharing economy
Authors: Breidbach Christoph F. , Brodie Roderick J. 
Published: May 2017

PurposeThe purpose of this paper is to identify and delineate research directions that guide future empirical studies exploring how engagement platforms facilitate value co-creation and actor engagement in the context of the sharing economy.Design/methodology/approachThe authors adopt a midrange theorizing approach with service-dominant logic as the integrating meta-theoretical perspective to develop a theoretical framework about service platforms, engagement platforms, and actor engagement in information communication technology (ICT) mediated environments. The authors then contextualize the framework for the sharing economy.FindingsThe authors introduce 20 unique research questions to guide future studies related to service ecosystems, engagement platforms, and actor engagement practices in the context of the sharing economy.Research limitations/implicationsThe sharing economy is an emerging phenomenon that is driven by the development and proliferation of engagement platforms. The engagement platform concept therefore provides a novel perspective for exploration of how ICT can be utilized to facilitate value co-creation and engagement amongst interdependent economic actors in a service ecosystem.Practical implicationsThe purpose of this paper is to guide future academic research, rather than managerial practice. Future research based on the framework can help guide decision-makers to implement and use engagement platforms more effectively.Originality/valueThis paper offers new insight into the important intersection of ICT and service research, and guides future studies exploring the role of engagement platforms in the context of the sharing economy.