bluuebunny/crossref_metadata_2025_split huggingface dataset:
mirtronDB: a mirtron knowledge base
Authors: Ribeiro Da Fonseca Bruno Henrique , Silva Domingues Douglas , Rossi Paschoal Alexandre 
Published: October 2018

AbstractMotivationMirtrons are originated from short introns with atypical cleavage from the miRNA canonical pathway by using the splicing mechanism. Several studies describe mirtrons in chordates, invertebrates and plants but in the current literature there is no repository that centralizes and organizes these public and available data. To fill this gap, we created the first knowledge database dedicated to mirtron, called mirtronDB, available at http://mirtrondb.cp.utfpr.edu.br/. MirtronDB has a total of 1,407 mirtron precursors and 2,426 mirtron mature sequences in 18 species.ResultsThrough a user-friendly interface, users can browse and search mirtrons by organism, organism group, type and name. MirtronDB is a specialized resource to explore mirtrons and their regulations, providing free, user-friendly access to knowledge on mirtron data.AvailabilityMirtronDB is available at http://mirtrondb.cp.utfpr.edu.br/.Contactpaschoal@utfpr.edu.brSupplementary informationSupplementary data are available.
Managing Marek’s disease in the egg industry
Authors: Rozins Carly , Day Troy , Greenhalgh Scott 
Published: October 2018

AbstractThe industrialization of farming has had an enormous impact. To most, this impact is viewed solely in the context of productivity, but the denser living conditions and shorter rearing periods of industrial livestock farms provide pathogens with an ideal opportunity to spread and evolve. For example, the industrialization of poultry farms drove the Marek’s disease virus (MDV) to evolve from causing a mild paralytic syndrome to causing a highly contagious, globally prevalent, disease that can have up to a 100% mortality rate. Fortunately, the economic catastrophe that would occur from MDV evolution has been prevented through widespread use of live imperfect vaccines that limit disease symptoms, but fail to prevent transmission. Unfortunately, the continued rollout of such imperfect vaccines is steering the evolution of MDV towards an even greater virulence and an ability to evade vaccine protection. Thus, there is a need to investigate alternative economically viable control measures for their ability to inhibit MDV spread and evolution. In what follows we examine the economic viability of standard husbandry practices for their ability to inhibit the spread of both virulent MDV and very virulent MDV throughout an industrialized egg farm. To do this, we parameterized a dynamic MDV transmission model and calculate the loss in egg production due to disease. We find that the MDV strain as well as the cohort duration had the greatest influence on disease burden and hence egg production. Additionally, we find that the standard husbandry practice involving conventional cages, often referred to as “battery cages”, results in the least per capita loss in egg production due to MDV infection when compared to alternative enriched or aviary (free-run) systems for virulent MDV, but not very virulent MDV, in which case the Aviary system performs the best. These results highlight an important cost that managers will face when implementing new hen husbandry practices.
Creating basis for introducing NIPT in the Estonian public health setting
Authors: Žilina Olga , Rekker Kadri , Kaplinski Lauris , Sauk Martin , Paluoja Priit , Teder Hindrek , Ustav Eva-Liina , Tõnisson Neeme , Ridnõi Konstantin , Palta Priit , Krjutškov Kaarel , Kurg Ants , Salumets Andres 
Published: October 2018

AbstractObjectiveThe study aimed to validate a whole-genome sequencing-based NIPT method and our newly developed NIPTmer analysis software with the potential to integrate the pipeline into prenatal clinical care in Estonia.MethodIn total, 447 maternal blood samples were included to the study. Analysis pipeline involved whole-genome library preparation and massively parallel sequencing on Illumina NextSeq 500. Aneuploidy status was determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data. To estimate fetal fraction (FF) from total cell-free DNA SeqFF was implemented.ResultsNIPTmer software allowed to identify correctly all samples of non-mosaic T21 (15/15), T18 (9/9) and T13 (4/4) cases. However, one mosaic T18 remained undetected. Six false positive results were observed, including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). FF < 4% (2.8-3.99%) was estimated in eight samples, including two samples with T13 and T18. Despite low FF, these two samples were determined as aneuploid with NIPTmer software.ConclusionOur NIPT analysis pipeline proved to perform efficiently in detecting common fetal aneuploidies T21, T18 and T13 and is feasible for implementation into clinical service in Estonia.
Protein model quality assessment using 3D oriented convolutional neural networks
Authors: Pagès Guillaume , Charmettant Benoit , Grudinin Sergei 
Published: October 2018

Protein model quality assessment (QA) is a crucial and yet open problem in structural bioinformatics. The current best methods for single-model QA typically combine results from different approaches, each based on different input features constructed by experts in the field. Then, the prediction model is trained using a machine-learning algorithm. Recently, with the development of convolutional neural networks (CNN), the training paradigm has changed. In computer vision, the expert-developed features have been significantly overpassed by automatically trained convolutional filters. This motivated us to apply a three-dimensional (3D) CNN to the problem of protein model QA.We developed a novel method for single-model QA called Ornate. Ornate (Oriented Routed Neural network with Automatic Typing) is a residue-wise scoring function that takes as input 3D density maps. It predicts the local (residue-wise) and the global model quality through a deep 3D CNN. Specifically, Ornate aligns the input density map, corresponding to each residue and its neighborhood, with the backbone topology of this residue. This circumvents the problem of ambiguous orientations of the initial models. Also, Ornate includes automatic identification of atom types and dynamic routing of the data in the network. Established benchmarks (CASP 11 and CASP 12) demonstrate the state-of-the-art performance of our approach among singlemodel QA methods.The method is available athttps://team.inria.fr/nanod/software/Ornate/. It consists of a C++ executable that transforms molecular structures into volumetric density maps, and a Python code based on the TensorFlow framework for applying the Ornate model to these maps.
Genomic prediction of autotetraploids; influence of relationship matrices, allele dosage, and continuous genotyping calls in the phenotype prediction
Authors: Oliveira Ivone de Bem , Resende Marcio F. R. , Ferrão Luis Felipe V. , Amadeu Rodrigo R. , Endelman Jeffrey B. , Kirst Matias , Coelho Alexandre S. G. , Munoz Patricio R. 
Published: October 2018

ABSTRACTEstimation of allele dosage in autopolyploids is challenging and current methods often result in the misclassification of genotypes. Here we propose and compare the use of next generation sequencing read depth as continuous parameterization for autotetraploid genomic prediction of breeding values, using blueberry (Vaccinium corybosumspp.) as a model. Additionally, we investigated the influence of different sources of information to build relationship matrices in phenotype prediction; no relationship, pedigree, and genomic information, considering either diploid or tetraploid parameterizations. A real breeding population composed of 1,847 individuals was phenotyped for eight yield and fruit quality traits over two years. Analyses were based on extensive pedigree (since 1908) and high-density marker data (86K markers). Our results show that marker-based matrices can yield significantly better prediction than pedigree for most of the traits, based on model fitting and expected genetic gain. Continuous genotypic based models performed as well as the current best models and presented a significantly better goodness-of-fit for all traits analyzed. This approach also reduces the computational time required for marker calling and avoids problems associated with misclassification of genotypic classes when assigning dosage in polyploid species. Accuracies are encouraging for application of genomic selection (GS) for blueberry breeding. Conservatively, GS could reduce the time for cultivar release by three years. GS could increase the genetic gain per cycle by 86% on average when compared to phenotypic selection, and 32% when compared with pedigree-based selection.
Finding structure in multi-armed bandits
Authors: Schulz Eric , Franklin Nicholas T. , Gershman Samuel J. 
Published: October 2018

AbstractHow do humans search for rewards? This question is commonly studied using multi-armed bandit tasks, which require participants to trade off exploration and exploitation. Standard multi-armed bandits assume that each option has an independent reward distribution. However, learning about options independently is unrealistic, since in the real world options often share an underlying structure. We study a class of structured bandit tasks, which we use to probe how generalization guides exploration. In a structured multi-armed bandit, options have a correlation structure dictated by a latent function. We focus on bandits in which rewards are linear functions of an option’s spatial position. Across 5 experiments, we find evidence that participants utilize functional structure to guide their exploration, and also exhibit a learning-to-learn effect across rounds, becoming progressively faster at identifying the latent function. Our experiments rule out several heuristic explanations and show that the same findings obtain with non-linear functions. Comparing several models of learning and decision making, we find that the best model of human behavior in our tasks combines three computational mechanisms: (1) function learning, (2) clustering of reward distributions across rounds, and (3) uncertainty-guided exploration. Our results suggest that human reinforcement learning can utilize latent structure in sophisticated ways to improve efficiency.
dream: Powerful differential expression analysis for repeated measures designs
Authors: Hoffman Gabriel E. , Roussos Panos 
Published: October 2018

ABSTRACTLarge-scale transcriptome studies with multiple samples per individual are widely used to study disease biology. Yet current methods for differential expression are inadequate for cross-individual testing for these repeated measures designs. Most problematic, we observe across multiple datasets that current methods can give reproducible false positive findings that are driven by genetic regulation of gene expression, yet are unrelated to the trait of interest. Here we introduce a statistical software package, dream, that increases power, controls the false positive rate, enables multiple types of hypothesis tests, and integrates with standard workflows. In 12 analyses in 6 independent datasets, dream yields biological insight not found with existing software while addressing the issue of reproducible false positive findings. Dream is available within the variancePartition Bioconductor package (http://bioconductor.org/packages/variancePartition).
Analysis of genomic loci harboring 59,732 human-specific regulatory sequences reveals unique to human regulatory patterns associated with brain development
Authors: Glinsky Gennadi V. 
Published: October 2018

AbstractExtensive searches for genomic regions harboring various types of candidate human-specific regulatory sequences (HSRS) identified thousands’ HSRS using high-resolution next-generation sequencing technologies and methodologically diverse comparative analyses of human and non-human primates’ reference genomes. Here, a comprehensive catalogue of 59,732 genomic loci harboring candidate HSRS has been assembled to facilitate the systematic analyses of genomic sequences that were either inherited from extinct common ancestors (ECAs) or created de novo in human genomes. Present analyses identified thousands of HSRS that appear inherited from ECAs yet absent in genomes of our closest evolutionary relatives, Chimpanzee and Bonobo, presumably due to the incomplete lineage sorting and/or species-specific loss or regulatory DNA. This pattern is particularly prominent for HSRS that have been putatively associated with human-specific (HS) gene expression changes in cerebral organoid models. Significant fractions of retrotransposon-derived loci transcriptionally-active in human dorsolateral prefrontal cortex (DLPFC) are highly conserved in genomes of Gorilla, Orangutan, Gibbon, and Rhesus (1,688; 1,371; 1,148; and 1,045 loci, respectively), yet they are absent in genomes of both Chimpanzee and Bonobo. A prominent majority of regions harboring HS mutations associated with HS expression changes during brain development is highly conserved in Chimpanzee, Bonobo, and Gorilla genomes. Among non-human primates (NHP), dominant fractions of HSRS associated with HS gene expression in both excitatory neurons (347 loci; 67%) and radial glia (683 loci; 72%) are highly conserved in the Gorilla genome. Analysis of 4,433 genes encoding virus-interacting proteins (VIPs) revealed that 95.9% of human VIPs are components of HS regulatory networks that appear to operate in distinct types of human cells from preimplantation embryos to adult DLPFC. Present analyses demonstrate that Modern Humans captured unique combinations of regulatory sequences, divergent subsets of which are highly conserved in distinct species of six NHP separated by 30 million years of evolution. Concurrently, this unique-to-human mosaic of genomic regulatory patterns inherited from ECAs was supplemented with 12,486 created de novo HSRS. Present analyses of HSRS support the model of complex continuous speciation process during evolution of the human lineage that is not likely to occur as an instantaneous event. Genes encoding VIPs may represent a principal genomic target of HS regulatory networks, thus affecting a functionally diverse spectrum of biological processes controlled by VIP-containing liquid-liquid phase separated condensates.
Unsupervised integration of multimodal dataset identifies novel signatures of health and disease
Authors: Shomorony Ilan , Cirulli Elizabeth T. , Huang Lei , Napier Lori A. , Heister Robyn R. , Hicks Michael , Cohen Isaac V. , Yu Hung-Chun , Swisher Christine Leon , Schenker-Ahmed Natalie M. , Li Weizhong , Kahn Andrew M. , Spector Timothy D. , Caskey C. Thomas , Venter J. Craig , Karow David S. , Kirkness Ewen F. , Shah Naisha 
Published: October 2018

AbstractModern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. We collected 1,385 data features from diverse modalities, including metabolome, microbiome, genetics and advanced imaging, from 1,253 individuals and from a longitudinal validation cohort of 1,083 individuals. We utilized an ensemble of unsupervised machine learning techniques to identify multimodal biomarker signatures of health and disease risk. In particular, our method identified a set of cardiometabolic biomarkers that goes beyond standard clinical biomarkers, which were used to cluster individuals into distinct health profiles. Cluster membership was a better predictor for diabetes than established clinical biomarkers such as glucose, insulin resistance, and BMI. The novel biomarkers in the diabetes signature included 1-stearoyl-2-dihomo-linolenoyl-GPC and 1-(1-enyl-palmitoyl)-2-oleoyl-GPC. Another metabolite, cinnamoylglycine, was identified as a potential biomarker for both gut microbiome health and lean mass percentage. We also identified an early disease signature for hypertension, and individuals at-risk for a poor metabolic health outcome. We found novel associations between an uremic toxin, p-cresol sulfate, and the abundance of the microbiome genera Intestinimonas and an unclassified genus in the Erysipelotrichaceae family. Our methodology and results demonstrate the potential of multimodal data integration, from the identification of novel biomarker signatures to a data-driven stratification of individuals into disease subtypes and stages -- an essential step towards personalized, preventative health risk assessment.
Right hemisphere superiority for executive control of attention
Authors: Spagna Alfredo , Kim Tae Hyeong , Wu Tingting , Fan Jin 
Published: October 2018

AbstractOver forty years have passed since the first evidence showing the unbalanced attentional allocation of humans across the two visual fields, and since then, a wealth of behavioral, neurophysiological, and clinical data increasingly showed a right hemisphere dominance for orienting of attention. However, inconsistent evidence exists regarding the right-hemisphere dominance for executive control of attention, possibly due to a lack of consideration of its dynamics with the alerting and orienting functions. In this study, we used a version of the Attentional Network Test with lateralized presentation of the stimuli to the left visual field (processed by the right hemisphere, RH) and right visual field (processed by the left hemisphere, LH) to examine visual field differences in executive control of attention under conditions of alerting or orienting. Analyses of behavioral performance (reaction time and error rate) showed a more efficient executive control (reduced conflict effect) in the RH compared to the LH for the reaction time, under conditions of increased alerting and of informative spatial orienting. These results demonstrate the right-hemisphere superiority for executive control, and that this effect depends on the activation of the alerting and orienting functions.
Expression of a recombinant high affinity IgG Fc receptor by engineered NK cells as a docking platform for therapeutic mAbs to target cancer cells
Authors: Snyder Kristin M. , Hullsiek Robert , Mishra Hemant K , Mendez Daniel C. , Li Yunfang , Rogich Allison , Kaufman Dan S. , Wu Jianming , Walcheck Bruce 
Published: October 2018

AbstractAnti-tumor mAbs are the most widely used and characterized cancer immunotherapy agents. Despite having a significant impact on some malignancies, most cancer patients respond poorly or develop resistance to this therapy. A known mechanism of action of these therapeutic mAbs is antibody-dependent cell-mediated cytotoxicity (ADCC), which is a primarily effector function of NK cells. CD16A on human NK cells has an exclusive role in binding to tumor-bound IgG antibodies. Though CD16A is a potent activating receptor, it is a low affinity FcγR and its cell surface levels can be rapidly downregulated by a proteolytic process involving ADAM17 upon NK cell activation, which are likely to limit the efficacy of tumor-targeting therapeutic mAbs in the tumor environment. We sought to enhance NK cell binding to anti-tumor mAbs by engineering these cells with a recombinant FcγR consisting of the extracellular region of CD64, the highest affinity IgG Fc receptor expressed by leukocytes, and the transmembrane and cytoplasmic regions of CD16A. This novel recombinant FcγR (CD64/16A) was expressed in the human NK cell line NK92 and in induced pluripotent stem cells from which primary NK cells were derived. CD64/16A also lacked the ADAM17 cleavage region in CD16A and it was not rapidly downregulated in expression following NK cell activation during ADCC. CD64/16A on NK cells facilitated conjugation to antibody-treated tumor cells, ADCC, and cytokine production, demonstrating functional activity by its two components. Unlike NK cells expressing CD16A, CD64/16A captured soluble therapeutic mAbs and the modified NK cells mediated tumor cell killing. Hence, CD64/16A could potentially be used as a docking platform on engineered NK cells for therapeutic mAbs and IgG Fc chimeric proteins, allowing for switchable targeting elements, and a novel cancer cellular therapy.
Light-based tuning of ligand half-life supports kinetic proofreading model of T cell activation
Authors: Tischer Doug , Weiner Orion D. 
Published: October 2018

AbstractT cells are thought to discriminate stimulatory versus non-stimulatory ligands by converting small changes in ligand binding half-life to large changes in cell activation. Such a kinetic proofreading model has been difficult to test directly, as existing methods of altering ligand binding half-life also change other potentially important biophysical parameters, most notably the stability of the receptor-ligand interaction under load. Here we develop an optogenetic approach to specifically tune the binding half-life of a light-responsive ligand to a chimeric antigen receptor without changing other binding parameters. By simultaneously manipulating binding half-life while controlling for receptor occupancy, we find that signaling is strongly gated by ligand binding half-life. Our results provide direct evidence of kinetic proofreading in ligand discrimination by T cells.One Sentence SummaryDirect control of ligand binding half-life with light shows that lifetime, not occupancy, dominates T cell activation.
Study of the action of lactic acid bacteria on acrylamide in food products
Authors: Surana Pallavi , Singh Shruti , Manokaran Sumathra , Reddy A.H. Manjunatha 
Published: October 2018

AbstractThe aim of this study is to extract Lactic acid bacteria (LAB) and test its effect on starchy food products. We extracted LAB as it is GRAS (Generally Recognised As Safe) and is abundantly present in probiotics like curd. After extraction of LAB colonies and were tested for its effect on foods rich in acrylamide content. Acrylamide formation is studied by the maillard reaction. Acrylamide is found in food products which have been subjected to very high temperatures. The application of LAB to remove many mutagens, by using the binding mechanism was assessed for acrylamide. When this acrylamide degrades it produces toxic gases like ammonia, hydrogen and carbon monoxide. Asparagine is an important precursor to acrylamide formation. So in foods containing free asparagine group with reducing sugars will form acrylamide. We used liquid chromatography to determine the presence of acrylamide in the food product. Acrylamide content in the body is responsible for various mutations at the genomic level thereby, leading to cancers like colon, breast. It also leads to neural damages and is directly linked to Alzhimers disease. This study concludes the beneficial effects of consuming probiotics and suggests a way to reduce the acrylamide formation in food products.
INSTRAL: Discordance-aware Phylogenetic Placement using Quartet Scores
Authors: Rabiee Maryam , Mirarab Siavash 
Published: October 2018

ABSTRACTPhylogenomic analyses have increasingly adopted species tree reconstruction using methods that account for gene tree discordance using pipelines that require both human effort and computational resources. As the number of available genomes continues to increase, a new problem is facing researchers. Once more species become available, they have to repeat the whole process from the beginning because updating species trees is currently not possible. However, thede novoinference can be prohibitively costly in human effort or machine time. In this paper, we introduce INSTRAL, a method that extends ASTRAL to enable phylogenetic placement. INSTRAL is designed to place a new species on an existing species tree after sequences from the new species have already been added to gene trees; thus, INSTRAL is complementary to existing placement methods that update gene trees.