bluuebunny/crossref_metadata_2025_split huggingface dataset:
An analysis and comparison of the statistical sensitivity of semantic similarity metrics
Authors: Manda Prashanti , Vision Todd 
Published: May 2018

1AbstractSemantic similarity has been used for comparing genes, proteins, phenotypes, diseases, etc. for various biological applications. The rise of ontology-based data representation in biology has also led to the development of several semantic similarity metrics that use different statistics to estimate similarity.Although semantic similarity has become a crucial computational tool in several applications, there has not been a formal evaluation of the statistical sensitivity of these metrics and their ability to recognize similarity between distantly related biological objects.Here, we present a statistical sensitivity comparison of five semantic similarity metrics (Jaccard, Resnik, Lin, Jiang& Conrath, and Hybrid Relative Specificity Similarity) representing three different kinds of metrics (Edge based, Node based, and Hybrid) and explore key parameter choices that can impact sensitivity. Furthermore, we compare four methods of aggregating individual annotation similarities to estimate similarity between two biological objects - All Pairs, Best Pairs, Best Pairs Symmetric, and Groupwise.To evaluate sensitivity in a controlled fashion, we explore two different models for simulating data with varying levels of similarity and compare to the noise distribution using resampling. Source data are derived from the Phenoscape Knowledgebase of evolutionary phenotypes.Our results indicate that the choice of similarity metric along with different parameter choices can substantially affect sensitivity. Among the five metrics evaluated, we find that Resnik similarity shows the greatest sensitivity to weak semantic similarity. Among the ways to combine pairwise statistics, the Groupwise approach provides the greatest discrimination among values above the sensitivity threshold, while the Best Pairs statistic can be parametrically tuned to provide the highest sensitivity.Our findings serve as a guideline for an appropriate choice and parameterization of semantic similarity metrics, and point to the need for improved reporting of the statistical significance of semantic similarity matches in cases where weak similarity is of interest
Gene editing and mutagenesis reveal inter-cultivar differences and additivity in the contribution of TaGW2 homoeologues to grain size and weight in wheat
Authors: wang wei , Simmonds James , Pan Qianli , Davidson Dwight , He Fei , Battal Abdulhamit , Akhunova Alina , Trick Harold N. , Uauy Cristobal , Akhunov Eduard 
Published: May 2018

AbstractThe TaGW2 gene homoeologues have been reported to be negative regulators of grain size (GS) and thousand grain weight (TGW) in wheat. However, the contribution of each homoeologue to trait variation among different wheat cultivars is not well documented. We used the CRISPR-Cas9 system and TILLING to mutagenize each homoeologous gene copy in cultivars Bobwhite and Paragon, respectively. Plants carrying single-copy nonsense mutations in different genomes showed different levels of GS/TGW increase, with TGW increasing by an average of 5.5% (edited lines) and 5.3% (TILLING mutants). In any combination, the double homoeologue mutants showed higher phenotypic effects than the respective single-genome mutants. The double mutants had on average 12.1% (edited) and 10.5% (TILLING) higher TGW with respect to wild-type lines. The highest increase in GS and TGW was shown for triple mutants of both cultivars, with increases of 16.3% (edited) and 20.7% (TILLING) in TGW. The additive effects of the TaGW2 homoeologues were also demonstrated by the negative correlation between the functional gene copy number and GS/TGW in Bobwhite mutants and an F2 population. The highest single-genome increases in GS and TGW in Paragon and Bobwhite were obtained by mutations in the B and D genomes, respectively. These inter-cultivar differences in the phenotypic effects between the TaGW2 gene homoeologues coincide with inter-cultivar differences in the homoeologue expression levels. These results indicate that GS/TGW variation in wheat can be modulated by the dosage of homoeologous genes with inter-cultivar differences in the magnitude of the individual homoeologue effects.
Enforced Symmetry: The Necessity of Symmetric Waxing and Waning
Authors: Hohmann Niklas 
Published: May 2018

AbstractThis paper demonstrates that the symmetric waxing and waning pat-terns that can be observed in ecological measures such as occupancy and geographic range are created by averaging, rescaling, conditioning and combining different sources of information. Therefore symmetric waxing and waning from the origination of a taxon to the extinction of a taxon in any measure should be treated as the null hypothesis and non-informative.
Dynamic interactions of type I cohesin modules fine-tune the structure of the cellulosome of Clostridium thermocellum
Authors: Barth Anders , Hendrix Jelle , Fried Daniel , Barak Yoav , Bayer Edward , Lamb Don C. 
Published: May 2018

AbstractEfficient degradation of plant cell walls by selected anaerobic bacteria is performed by large extracellular multienzyme complexes termed cellulosomes. The spatial arrangement within the cellulosome is organized by a protein called scaffoldin, which recruits the cellulolytic subunits through interactions between cohesin modules on the scaffoldin and dockerin modules on the enzymes. Although many structural studies of the individual components of cellulosomal scaffoldins have been performed, the role of interactions between individual cohesin modules and the flexible linker regions between them are still not entirely understood. Here, we report single-molecule measurements using Förster resonance energy transfer to study the conformational dynamics of a bimodular tandem cohesin segment of the scaffoldin protein CipA ofClostridium thermocellum. Our data reveal the existence of compacted structures in solution that persist on the timescale of milliseconds. The compacted conformation is found to be in dynamic equilibrium with an extended state that shows distance fluctuations on the microsecond timescale. Shortening of the inter-cohesin linker does not significantly alter the structural dynamics. Upon addition of dockerin-containing enzymes, an extension of the flexible state is observed but the cohesin-cohesin interactions persist. This suggests that the dockerin-binding interfaces are not involved in cohesin-cohesin interactions. The formation of cohesin-cohesin interactions is also observed in all-atom molecular dynamics simulations of the system. From the simulations, we identify possible inter-cohesin binding modes, none of which show obstruction of the cohesin-dockerin binding interfaces. Our results go beyond the view of scaffoldin as “beads on a string”. We propose that both the flexibility and cohesin-cohesin interactions are important factors for the precise spatial arrangement of the enzymatic subunits in the cellulosome that leads to the high catalytic synergy in these assemblies. Hence, the flexibility of the linker region and cohesin-cohesin interactions should be considered when designing cellulosomes for industrial applications.
Combined single-cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity
Authors: Linker Stephanie M. , Urban Lara , Clark Stephen , Chhatriwala Mariya , Amatya Shradha , McCarthy Davis J. , Ebersberger Ingo , Vallier Ludovic , Reik Wolf , Stegle Oliver , Bonder Marc Jan 
Published: May 2018

AbstractBackgroundAlternative splicing is a key regulatory mechanism in eukaryotic cells and increases the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied across human tissues and in genetically diverse populations. This has identified disease-relevant splicing events, as well as associations between splicing and genomic variations, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue or cell type and its determinants remain poorly understood.ResultsWe applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results shows that variation in single-cell splicing can be accurately predicted based on local sequence composition and genomic features. We observe moderate but consistent contributions from local DNA methylation profiles to splicing variation across cells. A combined model that is built based on sequence as well as DNA methylation information accurately predicts different splicing modes of individual cassette exons (AUC=0.85). These categories include the conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation.ConclusionsOur study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated link between DNA methylation variation and splicing.
Compulsivity and impulsivity are linked to distinct aberrant developmental trajectories of fronto-striatal myelination
Authors: Ziegler Gabriel , Hauser Tobias U. , Moutoussis Michael , Bullmore Edward T. , Goodyer Ian M. , Fonagy Peter , Jones Peter B. ,   NSPN Consortium, Lindenberger Ulman , Dolan Raymond J. 
Published: May 2018

AbstractThe transition from adolescence into adulthood is a period where rapid brain development coincides with an enhanced incidence of psychiatric disorder. The precise developmental brain changes that account for this emergent psychiatric symptomatology remain obscure. Capitalising on a unique longitudinal dataset, that includesin-vivomyelin-sensitive magnetization transfer (MT) MRI, we show this transition period is characterised by brain-wide growth in MT, within both gray matter and adjacent juxta-cortical white matter. We show that an expression of common developmental psychiatric risk symptomatology in this otherwise healthy population, specifically compulsivity and impulsivity, is tied to regionally specific aberrant unfolding of these MT trajectories. This is most marked in frontal midline structures for compulsivity, and in lateral frontal areas for impulsivity. The findings highlight a brain developmental linkage for emergent psychiatric risk features, evident in regionally specific perturbations in the expansion of MT-related myelination.
No effect of administration of unacylated ghrelin on subcutaneous PC3 xenograft growth in a Rag1−/− mouse model of metabolic dysfunction
Authors: Maugham Michelle L. , Seim Inge , Thomas Patrick B. , Crisp Gabrielle J. , Shah Esha T. , Herington Adrian C. , Brown Kristy A. , Gregory Laura S. , Nelson Colleen C. , Jeffery Penny L. , Chopin Lisa K. 
Published: May 2018

AbstractGhrelin is a peptide hormone which, when acylated, regulates appetite, energy balance and a range of other biological processes. Ghrelin predominately circulates in its unacylated form (unacylated ghrelin; UAG). UAG has a number of functions independent of acylated ghrelin, including modulation of metabolic parameters and cancer progression. UAG has also been postulated to antagonise some of the metabolic effects of acyl-ghrelin, including its effects on glucose and insulin regulation. In this study, Rag1−/− mice with high-fat diet-induced obesity and hyperinsulinaemia were subcutaneously implanted with PC3 prostate cancer xenografts to investigate the effect of UAG treatment on metabolic parameters and xenograft growth. Daily intraperitoneal injection of 100 μg/kg UAG had no effect on xenograft tumour growth in mice fed normal rodent chow or 23% high-fat diet. UAG significantly improved glucose tolerance in host Rag1−/− mice on a high-fat diet, but did not significantly improve other metabolic parameters. We hypothesise that UAG is not likely to be an effective treatment for prostate cancer, with or without associated metabolic syndrome.Conflict of interestThe authors declare no conflict of interest.
The relationship between subjective sleep quality and cognitive performance in healthy young adults: Evidence from three empirical studies
Authors: Zavecz Zsófia , Tamás Nagy , Galkó Adrienn , Nemeth Dezso , Janacsek Karolina 
Published: May 2018

AbstractThe role of sleep in cognitive performance has gained increasing attention in neuroscience and sleep research in the recent decades, however, the relationship between subjective (self-reported) sleep quality and cognitive performance has not yet been comprehensively characterized. In this paper, our aim was to test the relationship between subjective sleep quality and a wide range of cognitive functions in a healthy young adult sample combined across three studies. Sleep quality was assessed by Pittsburgh Sleep Quality Index, Athens Insomnia Scale, and a sleep diary to capture general subjective sleep quality, and Groningen Sleep Quality Scale to capture prior night’s sleep quality. Within cognitive functions, we tested working memory, executive functions, and several sub-processes of procedural learning. To provide more reliable results, we included robust frequentist and Bayesian statistical analyses as well. Unequivocally across all analyses, we showed that there is no association between subjective sleep quality and cognitive performance in the domain of working memory, executive functions and procedural learning in healthy young adults. Our paper can contribute to a deeper understanding of subjective sleep quality and its measures, and we discuss various factors that may affect whether associations can be observed between subjective sleep quality and cognitive performance.
Robust and fast Monte Carlo Markov Chain sampling of diffusion MRI microstructure models
Authors: Harms R.L. , Roebroeck A. 
Published: May 2018

AbstractIn diffusion MRI analysis, advances in biophysical multi-compartment modeling have gained popularity over the conventional Diffusion Tensor Imaging (DTI), because they possess greater specificity in relating the dMRI signal to underlying cellular microstructure. Biophysical multi-compartment models require parameter estimation, typically performed using either Maximum Likelihood Estimation (MLE) or using Monte Carlo Markov Chain (MCMC) sampling. Whereas MLE provides only a point estimate of the fitted model parameters, MCMC recovers the entire posterior distribution of the model parameters given the data, providing additional information such as parameter uncertainty and correlations. MCMC sampling is currently not routinely applied in dMRI microstructure modeling because it requires adjustments and tuning specific to each model, particularly in the choice of proposal distributions, burn-in length, thinning and the number of samples to store. In addition, sampling often takes at least an order of magnitude more time than non-linear optimization. Here we investigate the performance of MCMC algorithm variations over multiple popular diffusion microstructure models to see whether a single well performing variation could be applied efficiently and robustly to many models. Using an efficient GPU-based implementation, we show that run times can be removed as a prohibitive constraint for sampling of diffusion multi-compartment models. Using this implementation, we investigated the effectiveness of different adaptive MCMC algorithms, burn-in, initialization and thinning. Finally we apply the theory of Effective Sample Size to diffusion multi-compartment models as a way of determining a relatively general target for the number of samples needed to characterize parameter distributions for different models and datasets. We conclude that robust and fast sampling is achieved in most diffusion microstructure models with the Adaptive Metropolis-Within-Gibbs (AMWG) algorithm initialized with an MLE point estimate, in which case 100 to 200 samples are sufficient as a burn-in and thinning is mostly unnecessary. As a relatively general target for the number of samples, we recommend a multivariate Effective Sample Size of 2200.
Minimizing marine ingredients in diets of farmed Atlantic salmon (Salmo salar): Effects on growth performance and muscle lipid and fatty acid composition
Authors: Beheshti Foroutani Maryam , Parrish Christopher C. , Wells Jeanette , Taylor Richard , Rise Matthew , Shahidi Fereidoon 
Published: May 2018

AbstractDue to limited fish meal and fish oil resources and their high costs for the aquaculture industry, it is necessary to find alternative sustainable sources of protein and lipids. Therefore, seven different diets were formulated with different protein and lipid sources to feed farmed Atlantic salmon, and their effects on growth performance, muscle lipid class, and fatty acid composition were examined. Growth performance indicated that the diet with the lowest fish meal and fish oil content resulted in the lowest weight gain and final weight, followed by the diet containing the highest level of animal by-products. The lipid class analysis showed no statistical difference in the muscle total lipid content using different diets. However, significant statistical differences were observed among the main lipid classes; triacylglycerols, phospholipids, and sterols. The diet containing 1.4% omega-3 long-chain fatty acids resulted in the highest content of triacylglycerols and phospholipids. Diets containing medium and low levels of fish oil and fish meal, respectively, led to as high a level of ω3 fatty acids in muscle as when fish were fed diets with high levels of fish meal and fish oil. The results of this study suggest that feeding a diet containing low levels of fish meal and moderate levels of fish oil does not significantly affect ω3 fatty acid composition in muscle. Fish meal could be reduced to 5% without affecting growth as long as there was a minimum of 5% fish oil, and animal by-products did not exceed 26% of the diet.
Patterns and perceptions of cannabis use with physical activity
Authors: Lisano Jonathon K. , Phillips Kristina T. , Smith Jeremy D. , Barnes Matthew J. , Stewart Laura K. 
Published: May 2018

AbstractBackground and AimsPast research has shown that cannabis use is common among adults in the U.S. In addition, physical activity (PA), such as exercise, is often a component of many American’s daily routines. Anecdotal information suggests that a subset of individuals use cannabis in conjunction with PA, but the evidence base is lacking. The purpose of this study was to assess the frequency, methods of ingestion, strain types, and timing (before, during or after) of cannabis use in combination with PA. We also sought to better understand the types of PA that cannabis is being used with and reasons why individuals may use cannabis with PA.Methods and ResultsA brief survey was developed and was administered online to community residents (N = 105) who reported use of cannabis with PA. Analysis of survey responses revealed that participants were using cannabis in combination with a wide range of physical activities. While cannabis use was reported before, during, and after PA, the majority of participants (92%) reported use of cannabis before PA. Most participants (77%) believed that the use of cannabis products with their PA had a positive effect on their performance. The strain of cannabis used with PA was dependent on timing of cannabis use before, during, or after PA. Although participants reported a range of reasons for using cannabis before, during, or after PA, pain management was the only reason reported across all time periods.ConclusionsFindings from this study suggest that there is a sub-community of physically active individuals using cannabis with their PA, many who believe that cannabis use has a positive effect on their performance.
Hierarchical organization of the human cell from a cancer coessentiality network
Authors: Kim Eiru , Dede Merve , Lenoir Walter F. , Wang Gang , Srinivasan Sanjana , Colic Medina , Hart Traver 
Published: May 2018

AbstractGenetic interactions mediate the emergence of phenotype from genotype. Systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Systematic surveys of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains, and similarly implies shared biological function. We constructed a network of genes with correlated fitness profiles across 400 CRISPR knockout screens in cancer cell lines into a “coessentiality network,” with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of human gene function. Modules in the network are connected in a layered web that gives insight into the hierarchical organization of the cell.
Genome-centric metagenomics revealed the spatial distribution and the diverse metabolic functions of lignocellulose degrading uncultured bacteria
Authors: Kougias Panagiotis G. , Campanaro Stefano , Treu Laura , Tsapekos Panagiotis , Armani Andrea , Angelidaki Irini 
Published: May 2018

AbstractThe mechanisms by which specific anaerobic microorganisms remain firmly attached to lignocellulosic material allowing them to efficiently decompose the organic matter are far to be elucidated. To circumvent this issue, the microbiomes collected from anaerobic digesters treating pig manure and meadow grass were fractionated to separate the planktonic microbes from those adhered to lignocellulosic substrate. Assembly of shotgun reads followed by binning process recovered 151 population genomes, 80 out of which were completely new and were not previously deposited in any database. Genome coverage allowed the identification of microbial spatial distribution into the engineered ecosystem. Moreover, a composite bioinformatic analysis using multiple databases for functional annotation revealed that uncultured members of Bacteroidetes and Firmicutes follow diverse metabolic strategies for polysaccharide degradation. The structure of cellulosome in Firmicutes can vary depending on the number and functional roles of carbohydrate-binding modules. On contrary, members of Bacteroidetes are able to adhere and degrade lignocellulose due to the presence of multiple carbohydrate-binding family 6 modules in beta-xylosidase and endoglucanase proteins or S-layer homology modules in unknown proteins. This study combines the concept of variability in spatial distribution with genome-centric metagenomics allowing a functional and taxonomical exploration of the biogas microbiome.ImportanceThis work contributes new knowledge about lignocellulose degradation in engineered ecosystems. Specifically, the combination of the spatial distribution of uncultured microbes with genome-centric metagenomics provides novel insights into the metabolic properties of planktonic and firmly attached to plant biomass bacteria. Moreover, the knowledge obtained in this study enabled us to understand the diverse metabolic strategies for polysaccharide degradation in different species of Bacteroidetes and Clostridiales. Even though structural elements of cellulosome were restricted to Clostridiales, our study identified in Bacteroidetes a putative mechanism for biomass decomposition based on a gene cluster responsible for cellulose degradation, disaccharide cleavage to glucose and transport to cytoplasm.