bluuebunny/crossref_metadata_2025_split huggingface dataset:
Profiling DNA Methylation Differences Between Inbred Mouse Strains on the Illumina Human Infinium MethylationEPIC Microarray
Authors: Gujar Hemant , Liang Jane W. , Wong Nicholas C. , Mozhui Khyobeni 
Published: September 2017

AbstractThe Illumina Infinium MethylationEPIC provides an efficient platform for profiling DNA methylation in humans at over 850,000 CpGs. Model organisms such as mice do not currently benefit from an equivalent array. Here we used this array to measure DNA methylation in mice. We defined probes targeting conserved regions and performed a comparison between the array-based assay and affinity-based DNA sequencing of methyl-CpGs (MBD-seq). Mouse samples consisted of 11 liver DNA from two strains, C57BL/6J (B6) and DBA/2J (D2), that varied widely in age. Linear regression was applied to detect differential methylation. In total, 13,665 probes (1.6% of total probes) aligned to conserved CpGs. Beta-values (β-value) for these probes showed a distribution similar to that in humans. Overall, there was high concordance in methylation signal between the EPIC array and MBD-seq (Pearson correlation r = 0.70, p-value < 0.0001). However, the EPIC probes had higher quantitative sensitivity at CpGs that are hypo-(β-value < 0.3) or hypermethylated (β-value > 0.7). In terms of differential methylation, no EPIC probe detected significant difference between age groups at a Benjamini-Hochberg threshold of 10%, and the MBD-seq performed better at detecting age-dependent change in methylation. However, the top most significant probe for age (cg13269407; uncorrected p-value = 1.8 × 10−5) is part of the clock CpGs used to estimate the human epigenetic age. For strain, 219 Infinium probes detected significant differential methylation (FDR cutoff 10%) with ∼80% CpGs associated with higher methylation in D2. This higher methylation profile in D2 compared to B6 was also replicated by the MBD-seq data. To summarize, we found only a small subset of EPIC probes that target conserved sites. However, for this small subset the array provides areliable assay of DNA methylation and can be effectively used to measure differential methylation in mice.
Transcriptional development of phospholipid and lipoprotein metabolism in different intestinal regions of Atlantic salmon (Salmo salar) fry
Authors: Jin Yang , Olsen Rolf Erik , Østensen Mari-Ann , Gillard Gareth Benjamin , Korsvoll Sven Arild , Santi Nina , Gjuvsland Arne Bjørke , Vik Jon Olav , Torgersen Jacob Seilø , Sandve Simen Rød , Olsen Yngvar 
Published: September 2017

AbstractBackgroundIt has been suggested that the high phospholipid (PL) requirement in Atlantic salmon (Salmo salar) fry is due to insufficient intestinalde-novosynthesis causing low lipoprotein (LP) production and reduced transport capacity of dietary lipids. However, there has not been performed any in-depth ontological analysis of intestinal PL and LP synthesis with development of salmon. Therefore in this paper we used RNA-seq technology to test the hypothesis that the high PL requirement in salmon fry was associated with undeveloped PL synthesis and LP formation pathways in intestine. There was a special focus on the understanding homologous genes, especially from salmonid-specific fourth vertebrate whole-genome duplication (Ss4R), contribution to salmonid specific features of regulation of PL metabolic pathways. The study was performed in stomach, pyloric caeca and hindgut at 0.16g (1 day before first-feeding), 2.5g and 10g of salmon.ResultsIn general, we found an up-regulation ofde-novophosphatidylcholine (PtdCho) synthesis, phosphatidylethanolamine (PtdEtn) and LP formation pathways in pyloric caeca of salmon between 0.16g and 10g. Thirteen genes in these pathways were highly (q<0.05) up-regulated in 2.5g salmon compared to 0.16g, while only five more significant (q<0.05) genes were found when the fish grew up to 10g. Different homologous genes were found dominating in stomach, pyloric caeca and hindgut. However, the expression of dominating genes in PL and LP synthesis pathways was much higher in pyloric caeca than stomach and hindgut. Salmon-specific homologous (Ss4R) genes had similar expression during development, while other homologs had more diverged expression.ConclusionsAn increasing capacity for PL synthesis and LP formation was confirmed in pyloric caeca. The up-regulation of thede-novoPtdCho pathway confirms that the salmon fry have increasing requirement for dietary PtdCho compared to adult. The similar expressions between Ss4R homologous genes suggest that the functional divergence of these genes was incomplete compared to homologs derived from other whole genome duplication. The results of the present study have provided new information on the molecular mechanisms of phospholipid synthesis and lipoprotein formation in fish.
Quantification of cellular distribution as Poisson process in 3D matrix using a multiview light-sheet microscope
Authors: Colomb Warren , Osmond Matthew , Durfee Charles , Krebs Melissa D. , Sarkar Susanta K. 
Published: September 2017

AbstractThe absence of quantitativein vitrocell-extracellular matrix models represents an important bottleneck for basic research and human health. Randomness of cellular distributions provides an opportunity for the development of a quantitativein vitromodel. However, quantification of the randomness of random cell distributions is still lacking. In this paper, we have imaged cellular distributions in an alginate matrix using a multiview light-sheet microscope and developed quantification metrics of randomness by modeling it as a Poisson process, a process that has constant probability of occurring in space or time. Our light-sheet microscope can image more than 5 mm thick optically clear samples with 2.9 ±0.4μmdepth-resolution. We applied our method to image fluorescently labeled human mesenchymal stem cells (hMSCs) embedded in an alginate matrix. Simulated randomness agrees well with the experiments. Quantification of distributions and validation by simulations will enable quantitative study of cell-matrix interactions in tissue models.
The Generalized Data Model for Clinical Research
Authors: Danese Mark D. , Halperin Marc , Duryea Jennifer , Duryea Ryan 
Published: September 2017

1.Abstract1.1 BackgroundMost healthcare data sources store information within their own unique schemas, making reliable and reproducible research challenging. Consequently, researchers have adopted various data models to improve the efficiency of research. Transforming and loading data into these models is a labor-intensive process that can alter the semantics of the original data. Therefore, we created a data model with a hierarchical structure that simplifies the transformation process and minimizes data alteration.1.2 MethodsThere were two design goals in constructing the tables and table relationships for the Generalized Data Model (GDM). The first was to focus on clinical codes in their original vocabularies to retain the original semantic representation of the data. The second was to retain hierarchical information present in the original data while retaining provenance. The model was tested by transforming synthetic Medicare data; Surveillance, Epidemiology, and End Results data linked to Medicare claims; and electronic health records from the Clinical Practice Research Datalink. We also tested a subsequent transformation from the GDM into the Sentinel data model.1.3 ResultsThe resulting data model contains 19 tables, with the Clinical Codes, Contexts, and Collections tables serving as the core of the model, and containing most of the clinical, provenance, and hierarchical information. In addition, a Mapping table allows users to apply an arbitrarily complex set of relationships among vocabulary elements to facilitate automated analyses.1.4 ConclusionsThe GDM offers researchers a simpler process for transforming data, clear data provenance, and a path for users to transform their data into other data models. The GDM is designed to retain hierarchical relationships among data elements as well as the original semantic representation of the data, ensuring consistency in protocol implementation as part of a complete data pipeline for researchers.
Resolving ESCRT-III spirals at the intercellular bridge of dividing cells using 3D STORM imaging
Authors: Goliand Inna , Dadosh Tali , Elia Natalie 
Published: September 2017

ABSTRACTThe ESCRT machinery mediates membrane fission in a verity of processes in cells. According to the proposed mechanism, ESCRT-III proteins drive membrane fission by assembling into helical filaments on membranes. Yet, ESCRT-III filaments have never been directly visualized in a cellular process that utilizes this machinery for its function. Here we used 3D STORM imaging of endogenous ESCRT-III component IST1, to describe the structural organization of ESCRT-III during mammalian cytokinetic abscission. Using this approach, ESCRT-III ring and spiral assemblies were resolved at the intercellular tube of cells undergoing abscission. Characterization of these structures indicates the ESCRT-III helical filament undergoes remodeling during abscission. This work provides the first evidence that ESCRT-III proteins assemble into helical filaments in physiological context, indicating that the ESCRT-III machine indeed derives its contractile activity through spiral assemblies. Moreover, it provides new structural information on ESCRT-III filaments, which raise new mechanistic scenarios for ESCRT driven membrane constriction.
Real Time Estimation of Population Receptive Fields Using Gradient Descent
Authors: Senden Mario 
Published: September 2017

AbstractA real-time population receptive field mapping procedure based on gradient descent is proposed. Model-free receptive fields produced by the algorithm are evaluated in context of simulated data exhibiting different levels of temporally autocorrelated noise and spatial point spread. As with any model-free approach, the exact shape of receptive fields produced by the real-time algorithm depends on the stimulus. Nevertheless, estimated receptive fields show good correspondence with ground-truth receptive fields in terms of both position and size. Furthermore, fitting a parametric model to the previously obtained estimates approximates the exact shape of the true underlying receptive fields well.
GLP-1 receptor agonist ameliorates obesity-induced chronic kidney injury via restoring renal lipid and energy metabolism homeostasis: revealed by metabolomics
Authors: Wang Chengshi , Li Ling , Liu Shuyun , Liao Guangneng , Chen Younan , Cheng Jingqiu , Lu Yanrong , Liu Jingping 
Published: September 2017

AbstractIncreasing evidence indicate that obesity is highly associated with chronic kidney disease (CKD).GLP-1 receptor (GLP-1R) agonist has shown benefits on kidney diseases, but its direct role on kidney metabolism in obesity is still not clear. This study aims to investigate the protection and metabolic modulation role of liraglutide (Lira) on kidney of obesity. Rats were induced obese by high-fat diet (HFD), and renal function and metabolism changes were evaluated by metabolomic, biological and histological methods. HFD rats exhibited metabolic disorders including elevated body weight, hyperlipidemia and impaired glucose tolerance, and remarkable renal injuries including declined renal function and inflammatory/fibrotic changes, whereas Lira significantly ameliorated these adverse effects in HFD rats. Metabolomic data showed that Lira reduced renal lipids including fatty acid residues, cholesterol, phospholipids and triglycerides, and improved mitochondria metabolites such as succinate, citrate, taurine, fumarate and NAD+in the kidney of HDF rats. Furthermore, we revealed that Lira inhibited renal lipid accumulation by coordinating lipogenic and lipolytic signals, and rescued renal mitochondria function via Sirt1/AMPK/PGC1α pathways in HDF rats. This study suggested that Lira alleviated HFD-induced kidney injury via directly restoring renal lipid and energy metabolism, and GLP-1 receptor agonist is a promising therapy for obesity-associated CKD.
Integrative Statistical Inferences for Drug Sensitivity Biomarkers in Cancer
Authors: Ullah Ehsan , Shama Saila , Muftah Noora Al , Thompson Ian Richard , Rawi Reda , Mall Raghvendra , Bensmail Halima 
Published: September 2017

AbstractPersonal medicine has been associated with different patient responses to different anti-cancer therapies. Recently, scientists are looking not only for new biomarkers associated with a disease such as cancer but also identifying biomarkers that predict patients who are most likely to respond to a particular cancer treatment. Orderly endeavors to relate cancer mutational information with biological conditions may encourage the interpretation of somatic mutation indexes into significant biomarkers for patient stratification.We have screened and incorporated a board of cancer cell lines from Genomics of Drug Sensitivity in Cancer (GDSC) database to recognize genomic highlights related with drug sensitivity. We used mutation, DNA copy number variation, and gene expression information from Catalogue of Somatic Mutations in Cancer (COSMIC) and The Cancer Genome ATLAS (TCGA) for cell lines with their reactions to associate focused and cytotoxic treatments with approved drugs and drugs under clinical and preclinical examination.We discovered mutated cancer genes were related with cell reaction to, mostly accessible, cancer medications and some mutated genes were related with sensitivity to an expansive scope of therapeutic agents. By connecting drug activity to the useful many-sided quality of cancer genomes, efficient pharmacogenomic profiling in tumor cell lines gives an intense biomarker revelation stage to guide balanced malignancy remedial systems.Our study highlights that gene ANK2 amplification, and gene CELSER1 amplification and deletion are highly associated with anti-leukemic drug candidate LFM-A13. It also highlights that gene NUP214 and ROS1 copy number and gene NSD1 amplification are as a group highly associated with the parkinson drug Nilotinib. Finally, our study confirms that gene BRAF mutation is interacting with the BRAF-selective inhibitors drugs PLX4720 and SB590885. On the other hand, our study provides two open source analysis packages: bastah for the multitask-association analysis, and UNGeneAnno for automatic annotation of the variants.
History is written by the victors: the effect of the push of the past on the fossil record
Authors: Budd Graham E. , Mann Richard P. 
Published: September 2017

AbstractPhylogenies may be modelled using “birth-death” models for speciation and extinction, but even when a homogeneous rate of diversification is used, survivorship biases can generate remarkable rate heterogeneities through time. One such bias has been termed the “push of the past”, by which the length of time a clade has survived is conditioned on the rate of diversification that happened to pertain at its origin. This creates the illusion of a secular rate slow-down through time that is, rather, a reversion to the mean. Here we model the controls on the push of the past, and the effect it has on clade origination times, and show that it largely depends on underlying extinction rates. An extra effect increasing early rates of lineage generation is also seen in large clades. These biases are important but relatively neglected influences on many aspects of diversification patterns, such as diversification spikes after mass extinctions and at the origins of clades; they also influence rates of fossilisation, changes in rates of phenotypic evolution and even molecular clocks. These inevitable features of surviving and/or large clades should thus not be generalised to the diversification process as a whole without additional study of small and extinct clades.
Transcriptional control by Sall4 in blastocysts facilitates lineage commitment of inner cell mass cells
Authors: Miller Anzy , Gharbi Sarah , Etienne-Dumeau Charles , Nishinakamura Ryuichi , Hendrich Brian 
Published: September 2017

AbstractThe enhancer-binding zinc finger transcription factor Sall4 is essential for early mammalian postimplantation development and plays important roles in lineage commitment of embryonic stem cells. Enhancer binding by Sall4 results in transcriptional activation of some genes, but repression of others. Exactly how cells in preimplantation stage embryos use this transcriptional modulatory activity of Sall4 during early developmental transitions has not been determined. Using single cell gene expression analyses we show that Sall4 is required to maintain the gene regulatory network in inner cell mass (ICM) cells prior to lineage commitment. Although Sall4 is not required for ICM cells to adopt a correct epiblast or primitive endoderm gene expression profile, in the absence of Sall4 early ICM cells commit to either lineage at reduced frequency. We propose a model whereby Sall4 activity sets the stage for efficient progression from the uncommitted ICM progenitor state by modulating the gene regulatory network in early ICM cells.
Improved prediction of Bovine Leucocyte Antigens (BoLA) presented ligands by use of MS eluted ligands and in-vitro binding data; impact for the identification T cell epitopes
Authors: Nielsen Morten , Connelley Tim , Ternette Nicola 
Published: September 2017

AbstractPeptide binding to MHC class I molecules is the single most selective step in antigen presentation and the strongest single correlate to peptide cellular immunogenicity. The cost of experimentally characterizing the rules of peptide presentation for a given MHC-I molecule is extensive, and predictors of peptide-MHC interactions constitute an attractive alternative.Recently, an increasing amount of MHC presented peptides identified by mass spectrometry (MS ligands) has been published. Handling and interpretation of MS ligand data is in general challenging due to the poly-specificity nature of the data. We here outline a general pipeline for dealing with this challenge, and accurately annotate ligands to the relevant MHC-I molecule they were eluted from by use of GibbsClustering and binding motif information inferred fromin-silicomodels. We illustrate the approach here in the context of MHCI molecules (BoLA) of cattle. Next, we demonstrate how such annotated BoLA MS ligand data can readily be integrated within-vitrobinding affinity data in a prediction model with very high and unprecedented performance for identification of BoLA-I restricted T cell epitopes.The approach has here been applied to the BoLA-I system, but the pipeline is readily applicable to MHC systems in other species.
Enriched pathogen diversity under host-type heterogeneity and immune-mediated competition
Authors: Martinez Pamela P. , Woods Robert J. , Pascual Mercedes 
Published: September 2017

AbstractPathogen strains can stably coexist if they specialize on different hosts. Multiple strains can also coexist on a single host through negative frequency-dependent interactions mediated by partial cross-immunity. Understanding pathogen diversity remains a challenge however when both host specificity and cross-immunity are acting and may be functionally linked, as has been proposed for rotavirus, where a single protein is both antigenically important and determines host specificity by binding to the genetically encoded human blood group antigens. This situation is akin to the more general question in ecology of species coexistence when stabilizing and equalizing mechanisms interact. We examine this interaction with a theoretical model motivated by rotavirus and apply an adaptive dynamics framework to show how these two kinds of competition, typically considered separately, affect diversity. When cross-immunity depends on host-pathogen affinity, diversity is magnified as long-term evolution allows for the coexistence of multiple semi-specialized strains, similar to observations in rotavirus. In contrast, the simultaneous co-occurrence of several semi-specialized individuals is not observed when the degree of cross-immunity is independent from affinity distance among strains. The interplay of equalizing and stabilizing mechanisms fundamentally modifies diversity patterns and should be considered when addressing strain coexistence.
Global analysis of specificity determinants in eukaryotic protein kinases
Authors: Bradley David , Viéitez Cristina , Rajeeve Vinothini , Cutillas Pedro R. , Beltrao Pedro 
Published: September 2017

AbstractProtein kinases lie at the heart of cell signalling processes, constitute one of the largest human domain families and are often mutated in disease. Kinase target recognition at the active site is in part determined by a few amino acids around the phosphoacceptor residue. These preferences vary across kinases and despite the increased knowledge of target substrates little is known about how most preferences are encoded in the kinase sequence and how these preferences evolve. Here, we used alignment-based approaches to identify 30 putative specificity determinant residues (SDRs) for 16 preferences. These were studied using structural models and were validated by activity assays of mutant kinases. Mutation data from patient cancer samples revealed that kinase specificity is often targeted in cancer to a greater extent than catalytic residues. Throughout evolution we observed that kinase specificity is strongly conserved across orthologs but can diverge after gene duplication as illustrated by the evolution of the G-protein coupled receptor kinase family. The identified SDRs can be used to predict kinase specificity from sequence and aid in the interpretation of evolutionary or disease-related genomic variants.