bluuebunny/crossref_metadata_2025_split huggingface dataset:
Finding the difference between periosteal and endocortical bone adaptation by using Artificial Neural Networks
Authors: Tiwari Abhishek Kumar , Prasad Jitendra 
Published: July 2018

AbstractIn silico models of bone adaptation successfully simulated in vivo periosteal bone apposition, however, there are instances where these models may have limited success in predicting the new bone formation at endocortical surface. In vivo studies have highlighted that cortical bone surfaces may have differences in their modeling or remodeling responses to mechanical loading. However, the principle which the two cortical surfaces follow in bone adaptation is not very clear. This work accordingly attempts to understand how periosteal and endocortical surfaces accommodate loading-induced new bone formation. A neural network model is used to serve the purpose. A relationship is established to compute new bone thickness as a function of mechanical parameters (normal and shear strains) and non-mechanical parameters (distances from the neutral axis and the centroid) at the two surfaces. Analytical results indicate that two cortical surfaces behave opposite to each other in order to achieve optimal distribution of newly formed bone. The outcomes may be useful in establishing a unifying principle to predict site-specific new bone formation.
Modelling the brain response to arbitrary visual stimulation patterns for a flexible high-speed BCI
Authors: Nagel Sebastian , Spüler Martin 
Published: July 2018

AbstractVisual evoked potentials (VEPs) can be measured in the EEG as response to a visual stimulus. Commonly, VEPs are displayed by averaging multiple responses to a certain stimulus or a classifier is trained to identify the response to a certain stimulus. While the traditional approach is limited to a set of predefined stimulation patterns, we present a method that models the general process of VEP generation and thereby can be used to predict arbitrary visual stimulation patterns from EEG and predict how the brain responds to arbitrary stimulation patterns. We demonstrate how this method can be used to model single-flash VEPs, steady state VEPs (SSVEPs) or VEPs to complex stimulation patterns. It is further shown that this method can also be used in a BCI to allow information transfer rates of more than 470 bit/min and lead to more flexible BCIs with a virtually unlimited amount of targets and any desired trial duration.
Chromatin Condensation Fluctuations Rather than Steady-State Predict Chromatin Accessibility
Authors: Audugé Nicolas , Padilla-Parra Sergi , Tramier Marc , Borghi Nicolas , Coppey-Moisan Maïté 
Published: July 2018

AbstractChromatin accessibility to protein factors is critical for genome activities. Dynamic changes in nucleosomal DNA compaction and higher order chromatin structures are expected to allow specific sites to be accessible to regulatory factors and the transcriptional machinery. However, the dynamic properties of chromatin that regulate its accessibility are poorly understood. Here, we took advantage of the microenvironment sensitivity of the fluorescence lifetime of EGFP-H4 histone incorporated in chromatin to map in the nucleus of live cells the dynamics of chromatin condensation and its direct interaction with a tail acetylation recognition domain (the double bromodomain module of human TAFII250, dBD). We reveal chromatin condensation fluctuations supported by mechanisms fundamentally distinct from that of condensation. Fluctuations are spontaneous, yet their amplitudes are affected by their sub-nuclear localization and by distinct and competing mechanisms dependent on histone acetylation, ATP, and both. Moreover, we show that accessibility of acetylated histone H4 to dBD is not restricted by chromatin condensation nor predicted by acetylation, rather, it is predicted by chromatin condensation fluctuations.SignificanceIn higher eukaryotes, the structure and compaction of chromatin are considered as barriers to genome activities. Epigenetic marks such as post-translational modifications of histones can modify the structure and compaction of chromatin. The accessibility of protein factors to these epigenetic marks is therefore of paramount importance for genome activities. We reveal chromatin condensation fluctuations supported by mechanisms fundamentally distinct from that of condensation itself. We show that accessibility of acetylated histone H4 to double bromodomains is not restricted by chromatin condensation nor predicted by acetylation, rather, it is predicted by chromatin condensation fluctuations.ClassificationBiological Sciences, Cell Biology
Diallel Analysis for Morphological and Biochemical Traits in Tomato Cultivated Under the Influence of Tomato Leaf Curl Virus
Authors: Kaushik Prashant , Dhaliwal Major Singh 
Published: July 2018

AbstractEloquent information about the genetic basis of inheritance is important for any breeding program. Therefore, a diallel study was conducted under the influence of tomato leaf curl virus (TLCV) disease, using the eleven advanced lines of tomato. Firstly, the information regarding percent disease index (PDI) was determined via artificial screening with viruliferous whiteflies. Later, these lines were crossed in half diallel mating design to produce fifty-five one-way hybrids. These hybrids and parental genotypes were evaluated for seven morphological and three biochemical traits under open field conditions. Using the Griffing approach (Method II and Model I) basis of inheritance of traits were determined. Also, a Bayesian model was applied to the total yield descriptor. Correlations data indicated that total yield was not correlated with any other trait. The significant general combining ability (GCA) and specific combining ability (SCA) values indicates exploitable genetic variation. The broad-sense heritability values were larger than narrow-sense heritability, showing that selection will be efficient for the improvement of these traits. Hybrid combinations H23, H42 and H49 can be considered efficient for the selection of multiple traits, including yield. Overall, this study provides a useful information regarding the genetics of important traits of tomato under TLCV infestation.
Antiviral Response by Plasmacytoid Dendritic Cells via Interferogenic Synapse with Infected Cells
Authors: Assil Sonia , Coléon Séverin , Décembre Elodie , Sherry Lee , Allatif Omran , Webster Brian , Dreux Marlene 
Published: July 2018

SummaryType I interferon (IFN-I) is critical for protection against viral infections. Plasmacytoid dendritic cells (pDCs) massively produce IFN-I against viruses. Physical contacts are required for pDC-mediated sensing of cells infected by genetically distant viruses. How and why these contacts are established remains enigmatic. Using dengue, hepatitis C, zika viruses, we demonstrate that the pDC/infected cell interface is a specialized platform for viral immunostimulatory-RNA transfer, which we named interferogenic synapse and required for pDC-mediated antiviral response. This synapse is an exquisitely differentiated territory with polarized adhesion complexes and regulators of actin network and endocytosis. Toll-like receptor 7-induced signaling in pDCs promotes the interferogenic synapse establishment, thus providing a feed-forward regulation that sustains contacts with infected cells. We propose that the interferogenic synapse is crucial to pDC function as it allows scanning of infected cells to locally secrete IFN-I at the infection site, thereby confining a response potentially deleterious to the host.HighlightspDCs adhere to infected cells via αLβ2integrin/ICAM-1Regulators of actin network and endocytosis polarize at contactTLR7-induced signaling potentiates pDC polarityInfected cells activate pDCs by interferogenic synapse
LRScaf: Improving Draft Genomes Using Long Noisy Reads
Authors: Qin Mao , Wu Shigang , Li Alun , Zhao Fengli , Feng Hu , Ding Lulu , Chang Yuxiao , Ruan Jue 
Published: July 2018

AbstractBackgroundThe advent of Third Generation Sequencing (TGS) technologies opens the door to improve genome assembly. Long reads are promised to enhance the quality of fragmental draft assemblies constructed from Next Generation Sequencing (NGS) technologies. To date, a few of algorithms, i.e., SSPACE-LongRead, OPERA-LG, SMIS, npScarf, DBG2OLC, Unicycler, and LINKS, have been released that are capable of improving draft assemblies. However, hybrid assembly on large genomes is still challenging.ResultsWe develop a scalable and computationally efficient scaffolder, Long Reads Scaffolder (LRScaf), that is capable of boosting assembly contiguity to a large extent using long reads. In our experiment, our method significantly improves the contiguity of human draft assemblies, increasing the NG50 value of CHM1 from 127.5 Kb to 10.4 Mb using 20-fold coverage PacBio dataset and the NG50 value of NA12878 from 115.7 Kb to 17.4 Mb using 35-fold coverage Nanopore dataset. The run time for the scaffolding procedure using LRScaf is the shortest in all cases of our experiment. Compared with the run time of SSPACE-LongRead, LRScaf is faster 300 times for S. cerevisiae and 2,300 times for D. melanogaster. The peak RAM of LRScaf, by contrast, is more efficient than LINKS in our test. For the rice case, the peak RAM of LINKS (877.72 Gb) is about 196 times higher than LRScaf. For the experiment of human assembly, the peak RAM of LINKS is beyond the capacity of system memory (1 Tb) whereas LRScaf takes 20.28 and 41.20 Gb on CHM1 and NA12878 datasets.ConclusionsThe new method, LRScaf, yields the best or at least moderate contiguity and accuracy of scaffolds in the shortest run time compared with the state-of-the-art methods. Furthermore, it offers a new opportunity for the hybrid assembly of large genomes.
Integrated sequence and gene expression analysis of mouse models of breast cancer reveals critical events with human parallels
Authors: Rennhack Jonathan P , Swiatnicki Matthew , Zhang Yueqi , Li Caralynn , Bylett Evan , Ross Christina , Szczepanek Karol , Hanrahan William , Jayatissa Muthu , Hunter Kent , Andrechek Eran R. 
Published: July 2018

AbstractMouse models have an essential role in cancer research, yet little is known about how various models resemble human cancer at a genomic level. However, the shared genomic alterations in each model and corresponding human cancer are critical for translating findings in mice to the clinic. We have completed whole genome sequencing and transcriptome profiling of two widely used mouse models of breast cancer, MMTV-Neu and MMTV-PyMT. This genomic information was integrated with phenotypic data and CRISPR/Cas9 studies to understand the impact of key events on tumor biology. Despite the engineered initiating transgenic event in these mouse models, they contain similar copy number alterations, single nucleotide variants, and translocation events as human breast cancer. Through integrative in vitro and in vivo studies, we identified copy number alterations in key extracellular matrix proteins including Collagen 1 Type 1 alpha 1 (Col1a1) and Chondroadherin (CHAD) that drive metastasis in these mouse models. Importantly this amplification is also found in 25% of HER2+ human breast cancer and is associated with increased metastasis. In addition to copy number alterations, we observed a propensity of the tumors to modulate tyrosine kinase mediated signaling through mutation of phosphatases. Specifically, we found that 81% of MMTV-PyMT tumors have a mutation in the EGFR regulatory phosphatase, PTPRH. Mutation in PTPRH led to increased phospho-EGFR levels and decreased latency. Moreover, PTPRH mutations increased response to EGFR kinase inhibitors. Analogous PTPRH mutations are present in lung cancer patients and together this data suggests that a previously unidentified population of human lung cancer patients may respond to EGFR targeted therapy. These findings underscore the importance of understanding the complete genomic landscape of a mouse model and illustrate the utility this has in understanding human cancers.
Scedar: a scalable Python package for single-cell RNA-seq exploratory data analysis
Authors: Zhang Yuanchao , Kim Man S. , Reichenberger Erin R. , Stear Ben , Taylor Deanne M. 
Published: July 2018

AbstractIn single-cell RNA-seq (scRNA-seq) experiments, the number of individual cells has increased exponentially, and the sequencing depth of each cell has decreased significantly. As a result, analyzing scRNA-seq data requires extensive considerations of program efficiency and method selection. In order to reduce the complexity of scRNA-seq data analysis, we present scedar, a scalable Python package for scRNA-seq exploratory data analysis. The package provides a convenient and reliable interface for performing visualization, imputation of gene dropouts, detection of rare transcriptomic profiles, and clustering on large-scale scRNA-seq datasets. The analytical methods are efficient, and they also do not assume that the data follow certain statistical distributions. The package is extensible and modular, which would facilitate the further development of functionalities for future requirements with the open-source development community. The scedar package is distributed under the terms of the MIT license at https://pypi.org/project/scedar.
Development of a vanillate biosensor for the vanillin biosynthesis pathway in E. coli
Authors: Kunjapur Aditya M. , Prather Kristala L. J. 
Published: July 2018

AbstractGenetically encoded small molecule sensors can facilitate metabolic engineering by enabling high-throughput detection of metabolite concentrations, directed evolution of host and pathway enzymes, and dynamic regulation. The engineered de novo vanillin biosynthesis pathway assembled in Escherichia coli is industrially relevant and ideal for biosensor deployment given that the pathway requires only three heterologous enzyme-catalyzed reactions, generates naturally occurring metabolites, and may benefit from dynamic regulation. However, pathway flux is stalled and diverted by the activity of the Homo sapiens catechol O-methyltransferase, which is intended to catalyze the conversion of protocatechuate to vanillate. To confront this challenge, we constructed and applied a vanillate sensor based on the Caulobacter crescentus VanR-VanO system. Using components from a previously characterized E. coli promoter library, we achieved greater than 14-fold dynamic range in our best rationally constructed sensor. We characterized sensor substrate specificity and found that this construct and an evolved variant are remarkably selective, exhibiting no detectable response to the regioisomer byproduct isovanillate. We then harnessed the evolved biosensor to conduct rapid bioprospecting of natural catechol O-methyltransferases. We identified eight that appear to have greater desired activity than the originally used variant, including three previously uncharacterized O-methyltransferases. Collectively, these efforts enrich our knowledge of how biosensing can aid metabolic engineering and constitute the foundation for future improvements in vanillin pathway productivity.
Kipoi: accelerating the community exchange and reuse of predictive models for genomics
Authors: Avsec Žiga , Kreuzhuber Roman , Israeli Johnny , Xu Nancy , Cheng Jun , Shrikumar Avanti , Banerjee Abhimanyu , Kim Daniel S. , Urban Lara , Kundaje Anshul , Stegle Oliver , Gagneur Julien 
Published: July 2018

AbstractAdvanced machine learning models applied to large-scale genomics datasets hold the promise to be major drivers for genome science. Once trained, such models can serve as a tool to probe the relationships between data modalities, including the effect of genetic variants on phenotype. However, lack of standardization and limited accessibility of trained models have hampered their impact in practice. To address this, we present Kipoi, a collaborative initiative to define standards and to foster reuse of trained models in genomics. Already, the Kipoi repository contains over 2,000 trained models that cover canonical prediction tasks in transcriptional and post-transcriptional gene regulation. The Kipoi model standard grants automated software installation and provides unified interfaces to apply and interpret models. We illustrate Kipoi through canonical use cases, including model benchmarking, transfer learning, variant effect prediction, and building new models from existing ones. By providing a unified framework to archive, share, access, use, and build on models developed by the community, Kipoi will foster the dissemination and use of machine learning models in genomics.
DNA Methylation by Restriction Modification Systems Affects the Global Transcriptome Profile inBorrelia burgdorferi
Authors: Casselli Timothy , Tourand Yvonne , Scheidegger Adam , Arnold William K. , Proulx Anna , Stevenson Brian , Brissette Catherine A. 
Published: July 2018

ABSTRACTProkaryote restriction modification (RM) systems serve to protect bacteria from potentially detrimental foreign DNA. Recent evidence suggests that DNA methylation by the methyltransferase (MTase) components of RM systems can also have effects on transcriptome profiles. The causative agent of Lyme disease,Borrelia burgdorferi, encodes two RM systems with N6-Methyladenosine (m6A) MTase activity. The specific recognition and/or methylation sequences have not been identified for eitherB. burgdorferiMTase, and it is not currently known whether these RM systems influence transcriptome profiles. In the current study, Single Molecule Real Time sequencing was utilized to map genome-wide m6A sites, and to identify consensus modified motifs in wild-typeB. burgdorferias well as isogenic MTase mutants. Four conserved m6A motifs were identified, and were fully attributable to the presence of specific MTases. Whole-genome transcriptome changes were observed in conjunction with the loss of MTase enzymes, indicating that DNA methylation by RM systems has effects on gene expression inB. burgdorferi. The results of this study provide a comprehensive view of the DNA methylation pattern inB. burgdorferi, and the accompanying gene expression profiles add to the emerging body of research on RM systems and gene regulation in bacteria.IMPORTANCELyme disease is the most prevalent vector-borne disease in North America, and is classified by the Centers for Disease Control and Prevention (CDC) as an emerging infectious disease with an expanding geographical area of occurrence. Previous studies have shown that the causative bacterium,Borrelia burgdorferi, methylates its genome using restriction modification systems that allow for the distinction of self from foreign DNA. Although much research has focused on the regulation of gene expression inB. burgdorferi, the effects of DNA methylation on gene regulation has not been evaluated. The current study characterizes the patterns of DNA methylation by restriction modification systems inB. burgdorferi, and evaluates the resulting effects on gene regulation in this important pathogen.
Rootstocks shape the rhizobiome: Rhizosphere and endosphere bacterial communities in the grafted tomato system
Authors: Poudel Ravin , Jumpponen Ari , Kennelly Megan M. , Rivard Cary L. , Gomez-Montano Lorena , Garrett Karen A. 
Published: July 2018

AbstractRoot-associated microbes are critical to plant health and performance, although understanding of the factors that structure these microbial communities and theory to predict microbial assemblages are still limited. Here we use a grafted tomato system to study the effects of rootstock genotypes and grafting in endosphere and rhizosphere microbiomes that were evaluated by sequencing 16S rRNA. We compared the microbiomes of nongrafted tomato cultivar BHN589, selfgrafted BHN589, and BHN589 grafted to Maxifort or RST-04-106 hybrid rootstocks. OTU-based bacterial diversity was greater in Maxifort compared to nongraft controls, whereas bacterial diversity in the controls (selfgraft and nongraft) and the other rootstock (RST-04-106) was similar. Grafting itself did not affect bacterial diversity; diversity in the selfgraft was similar to the nongraft. Bacterial diversity was higher in the rhizosphere than in the endosphere for all treatments. However, despite the lower overall diversity, there was a greater number of differentially abundant OTUs (DAOTUs) in the endosphere, with the greatest number of DAOTUs associated with Maxifort. In a PERMANOVA analysis, there was evidence for an effect of rootstock genotype on bacterial communities. The endosphere-rhizosphere compartment and study site explained a high percentage of the differences among bacterial communities. Further analyses identified OTUs responsive to rootstock genotypes in both the endosphere and the rhizosphere. Our findings highlight the effects of rootstocks on bacterial diversity and composition. The influence of rootstock and plant compartment on microbial communities indicates opportunities for the development of designer communities and microbiome-based breeding to improve future crop production.ImportanceUnderstanding factors that control microbial communities is essential for designing and supporting microbiome-based agriculture. In this study, we used a grafted tomato system to study the effect of rootstock genotypes and grafting on bacterial communities colonizing the endosphere and the rhizosphere. Comparing the bacterial communities in control treatments (nongraft and selfgraft plants) with the hybrid rootstocks used by farmers, we evaluated the effect of rootstocks on overall bacterial diversity and composition. These findings indicate the potential for using plant genotype to indirectly select bacterial taxa. In addition, we identify taxa responsive to each rootstock treatments, which may represent candidate taxa useful for biocontrol and in biofertilizers.