bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carbapenemases on the move: it’s good to be on ICE
Authors: Botelho João , Roberts Adam P. , León-Sampedro Ricardo , Grosso Filipa , Peixe Luísa 
Published: August 2018

AbstractThe evolution and spread of antibiotic resistance is often mediated by mobile geneticelements. Integrative and conjugative elements (ICEs) are the most abundant conjugativeelements among prokaryotes. However, the contribution of ICEs to horizontal gene transferof antibiotic resistance has been largely unexplored. Here we report that ICEs belonging tomating-pair formation (MPF) classes G and T are highly prevalent among the opportunisticpathogen Pseudomonas aeruginosa, contributing to the spread of carbapenemase-encodinggenes (CEGs). Most CEGs of the MPFG class were encoded within class I integrons, which co-harbour genes conferring resistance to other antibiotics. The majority of the integrons werelocated within Tn3-like and composite transposons. A conserved attachment site could bepredicted for the MPFGclass ICEs. MPFTclass ICEs carried the CEGs within compositetransposons which were not associated with integrons. The data presented here provides aglobal snapshot of the different CEG-harbouring ICEs and sheds light on the underappreciatedcontribution of these elements for the evolution and dissemination of antibiotic resistanceon P. aeruginosa.
Intact mast cell content during mild head injury is required for the development of latent pain sensitization - implications for mechanisms underlying post-traumatic headache
Authors: Bree Dara , Levy Dan 
Published: August 2018

AbstractPosttraumatic headache (PTH) is one of the most common, debilitating and difficult symptoms to manage after a traumatic head injury. While the mechanisms underlying PTH remain elusive, recent studies in rodent models suggest the potential involvement of calcitonin gene-related peptide (CGRP), a mediator of neurogenic inflammation, and the ensuing activation of meningeal mast cells (MCs), pro-algesic resident immune cells that can lead to the activation of the headache pain pathway. Here, we investigated the relative contribution of MCs to the development of PTH-like pain behaviors in a model of mild closed head injury (mCHI) in male rats. We initially tested the relative contribution of peripheral CGRP signaling to the activation of meningeal MCs following mCHI using an anti-CGRP monoclonal antibody. We then employed a prophylactic MC granule depletion approach to address the hypotheses that intact meningeal MC granule content is necessary for the development of PTH-related pain-like behaviors. The data suggest that following mCHI, ongoing activation of meningeal MCs is not mediated by peripheral CGRP signaling, and does not contribute to development of the mCHI-evoked cephalic mechanical pain hypersensitivity. Our data, however, also reveals that the development of latent sensitization, manifested as persistent hypersensitivity upon the recovery from mCHI-evoked acute cranial hyperalgesia to the headache trigger glyceryl trinitrate requires intact MC content during and immediately after mCHI. Collectively, our data implicate the acute activation of meningeal MCs as mediator of chronic pain hypersensitivity following a concussion or mCHI. Targeting MCs may be explored for early prophylactic treatment of PTH.
Stochasticity in multi-phosphorylation and quasi steady state approximation in stochastic simulation
Authors: Das S. , Barik D. 
Published: August 2018

AbstractQuantitative and qualitative nature of chemical noise propagation in a network of chemical reactions depend crucially on the topology of reaction networks. Multisite reversible phosphorylation-dephosphorylation of target proteins is one such recurrently found topology in various cellular networks regulating key functions in living cells. Here we analytically calculated the stochasticity in multistep reversible chemical reactions by determining variance of phosphorylated species at the steady state using linear noise approximation. We investigated the dependence of variance on the rate parameters in the reaction chain and the number of phosphorylation sites on the species. Assuming a quasi steady state approximation on the multistep reactions, originating from the disparity in time scales in the network, we propose a simulation scheme for coupled chemical reactions to improve the computational efficiency of stochastic simulation of the network. We performed case studies on signal transduction cascade and positive feedback loop with bistability to show the accuracy and efficiency of the method.
An algorithm for automated, noninvasive detection of cortical spreading depolarizations based on EEG simulations
Authors: Chamanzar Alireza , George Shilpa , Venkatesh Praveen , Chamanzar Maysamreza , Shutter Lori , Elmer Jonathan , Grover Pulkit 
Published: August 2018

AbstractWe present a novel signal processing algorithm for automated, noninvasive detection of Cortical Spreading Depolarizations (CSDs) using electroencephalography (EEG) signals and validate the algorithm on simulated EEG signals. CSDs are waves of neurochemical changes that suppress neuronal activity as they propagate across the brain’s cortical surface. CSDs are believed to mediate secondary brain damage after brain trauma and cerebrovascular diseases like stroke. We address key challenges in detecting CSDs from EEG signals: (i) decay of high spatial frequencies as they travel from the cortical surface to the scalp surface; and (ii) presence of sulci and gyri, which makes it difficult to track the CSD waves as they travel across the cortex. Our algorithm detects and tracks “wavefronts” of the CSD wave, and stitches together data across space and time to decide on the presence of a CSD wave. To test our algorithm, we provide different models and complex patterns of CSD waves, including different widths of CSD suppressions, and use these models to simulate scalp EEG signals using head models of 4 subjects from the OASIS dataset. Our results suggest that the average width of suppression that a low-density EEG grid of 40 electrodes can detect is 1.1 cm, which includes a vast majority of CSD suppressions, but not all. A higher density EEG grid having 340 electrodes can detect complex CSD patterns as thin as 0.43 cm (less than minimum widths reported in prior works), among which single-gyrus propagation is the hardest to detect because of its small suppression area.
Structures of the substrate-engaged 26S proteasome reveal the mechanisms for ATP hydrolysis-driven translocation
Authors: de la Peña Andres H. , Goodall Ellen A. , Gates Stephanie N. , Lander Gabriel C. , Martin Andreas 
Published: August 2018

AbstractThe 26S proteasome is the primary eukaryotic degradation machine and thus critically involved in numerous cellular processes. The hetero-hexameric ATPase motor of the proteasome unfolds and translocates targeted protein substrates into the open gate of a proteolytic core, while a proteasomal deubiquitinase concomitantly removes substrate-attached ubiquitin chains. However, the mechanisms by which ATP hydrolysis drives the conformational changes responsible for these processes have remained elusive. Here we present the cryo-EM structures of four distinct conformational states of the actively ATP-hydrolyzing, substrate-engaged 26S proteasome. These structures reveal how mechanical substrate translocation accelerates deubiquitination, and how ATP-binding, hydrolysis, and phosphate-release events are coordinated within the AAA+ motor to induce conformational changes and propel the substrate through the central pore.
scMerge: Integration of multiple single-cell transcriptomics datasets leveraging stable expression and pseudo-replication
Authors: Lin Yingxin , Ghazanfar Shila , Wang Kevin , Gagnon-Bartsch Johann A. , Lo Kitty K. , Su Xianbin , Han Ze-Guang , Ormerod John T. , Speed Terence P. , Yang Pengyi , Hwa Yang Jean Yee 
Published: August 2018

AbstractConcerted examination of multiple collections of single cell RNA-Seq (scRNA-Seq) data promises further biological insights that cannot be uncovered with individual datasets. However, such integrative analyses are challenging and require sophisticated methodologies. To enable effective interrogation of multiple scRNA-Seq datasets, we have developed a novel algorithm, named scMerge, that removes unwanted variation by combining stably expressed genes and utilizing pseudo-replicates across datasets. Analysis of large collections of publicly available datasets demonstrates that scMerge performs well in multiple scenarios and enhances biological discovery, including inferring cell developmental trajectories.
Dual role of Bnl/Fgf signaling in proliferation and endoreplication of Drosophila tracheal adult progenitor cells
Authors: Miguel Cristina de , Cruz Josefa , Martín David , Franch-Marro Xavier 
Published: August 2018

AbstractAdult progenitor cells activation is a key event in the formation of adult organs during development. The initiation of proliferation of these progenitor cells requires specific temporal signals, mostly of them still unknown. InDrosophila, formation of adult tracheal system depends on the activation of tracheal adult progenitors (tracheoblasts) of Tr4 and Tr5 tracheal metamers specific spiracular branches (SB) during the last larval stage. The mitotic activity of these tracheoblasts generate a pool of tracheal differentiated cells that migrate during pupal development along the larval trachea by the activation of the Branchless (Bnl)/Fibroblast growth factor (FGF) signaling to form the abdominal adult tracheal system. In here, we found that, in addition to migration, Bnl/FGF signaling, mediated by the transcription factor Pointed, is also required for adult progenitor cell proliferation in the SBs. Moreover, we found that tracheoblast proliferation in Tr4 and Tr5 SBs relies on the specific expression of the FGF ligandBnlin their nearby transverse connective branches. Finally, we also show that, in absence of the transcription factor Cut (Ct), Bnl/FGF signaling induces endoreplication of differentiated tracheoblast daughter cells by in part promotingFizzy-related(Fzr) expression. Altogether, our results suggest a dual role of Bnl/FGF signaling in tracheal adult progenitors, inducing both proliferation and endoreplication of tracheoblasts in late larval development, depending on the presence or absence of the transcription factorct, respectively.Author summaryThe generation of adult organs and tissue renewal are complex processes that depend on the proliferation and posterior differentiation of undifferentiated progenitor cells in a temporal coordinated manner. Although many signals that regulate the activity of progenitor cells have been identified, the characterization of the mechanisms underlying the temporal and spatial control of such events remain unknown. The tracheal system ofDrosophila, the respiratory organ, forms during embryogenesis and it is remodeled during metamorphosis from quiescent adult progenitor cells that proliferate. We have discovered that this proliferation depends on the activation of the FGF signaling as mutations that either inactivate or over-activate the pathway blocks cell division or induced over-proliferation of progenitor cells, respectively. Interestingly, we have found that the same signaling pathway also controls tracheal progenitor cells differentiation by promoting endoreplication. We found that this dual role of FGF signaling in adult progenitor cells, depends on the presence or absence of the transcription factor Cut. Altogether, our results, reveal the mechanism that control the division and differentiation of progenitor cells and open the possibility that analogous signaling pathway may play a similar role in vertebrate stem cell regulation and tumor growth.
Optimized Cas9 expression systems for highly efficient Arabidopsis genome editing facilitate isolation of complex alleles in a single generation
Authors: Ordon Jana , Bressan Mauro , Kretschmer Carola , Dall’Osto Luca , Marillonnet Sylvestre , Bassi Roberto , Stuttmann Johannes 
Published: August 2018

AbstractGenetic resources for the model plant Arabidopsis comprise mutant lines defective in almost any single gene in reference accession Columbia. However, gene redundancy and/or close linkage often render it extremely laborious or even impossible to isolate a desired line lacking a specific function or set of genes from segregating populations. Therefore, we here evaluated strategies and efficiencies for the inactivation of multiple genes by Cas9-based nucleases and multiplexing. In first attempts, we succeeded in isolating a mutant line carrying a 70 kb deletion, which occurred at a frequency of ~1.6% in the T2 generation, through PCR-based screening of numerous individuals. However, we failed to isolate a line lacking Lhcb1 genes, which are present in five copies organized at two loci in the Arabidopsis genome. To improve efficiency of our Cas9-based nuclease system, regulatory sequences controlling Cas9 expression levels and timing were systematically compared. Indeed, use of DD45 and RPS5a promoters improved efficiency of our genome editing system by approximately 25-30-fold in comparison to the previous ubiquitin promoter. Using an optimized genome editing system with RPS5a promoter-driven Cas9, putatively quintuple mutant lines lacking detectable amounts of Lhcb1 protein represented approximately 30% of T1 transformants. These results show how improved genome editing systems facilitate the isolation of complex mutant alleles, previously considered impossible to generate, at high frequency even in a single (T1) generation.
The Relative Contribution of Color and Material in Object Selection
Authors: Radonjić Ana , Cottaris Nicolas P. , Brainard David H. 
Published: August 2018

AbstractInformation about color, material, texture and shape guide how we interact with objects. We developed a paradigm that quantifies how two object properties (color and material) combine in object selection. On each experimental trial, observers viewed three blob-shaped objects — the target and two tests — and selected the test that was more similar to the target. Across trials the target was fixed while the tests varied in color and material. We present a novel observer model that allows us to describe observers’ selection data in terms of (1) the underlying perceptual stimulus representation and (2) a color-material weight, which quantifies the relative importance of color vs. material in selection. We document large individual differences in the color-material weight. Furthermore, our analyses reveal limits on how precisely selection data simultaneously constrain perceptual representations and the color-material weight. These limits should guide future efforts towards understanding the multidimensional nature of object perception.
NucBreak: Location of structural errors in a genome assembly by using paired-end Illumina reads
Authors: Khelik Ksenia , Sandve Geir Kjetil , Nederbragt Alexander Johan , Rognes Torbjørn 
Published: August 2018

AbstractBackgroundAdvances in whole genome sequencing strategies have provided the opportunity for genomic and comparative genomic analysis of a vast variety of organisms. The analysis results are highly dependent on the quality of the genome assemblies used. Assessment of the assembly accuracy may significantly increase the reliability of the analysis results and is therefore of great importance.ResultsHere, we present a new tool called NucBreak aimed at detecting structural errors in assemblies, including insertions, deletions, duplications, inversions, and different inter-and intra-chromosomal rearrangements. NucBreak analyses the alignments of reads properly mapped to an assembly and exploits information about the alternative read alignments. We have compared NucBreak with other existing assembly accuracy assessment tools, namely Pilon, REAPR, and FRCbam as well as with several structural variant detection tools, including BreakDancer, Lumpy, and Wham, by using both simulated and real datasets.ConclusionsThe benchmarking results have shown that NucBreak in general predicts assembly errors of different types and sizes with relatively high sensitivity and with higher precision than the other tools. Such a balance between sensitivity and precision makes NucBreak a good alternative to the existing assembly accuracy assessment tools and SV detection tools. NucBreak is freely available at https://github.com/uio-bmi/NucBreak under the MPL license.
Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies
Authors: Piray Payam , Dezfouli Amir , Heskes Tom , Frank Michael J. , Daw Nathaniel D. 
Published: August 2018

AbstractComputational modeling plays an important role in modern neuroscience research. Much previous research has relied on statistical methods, separately, to address two problems that are actually interdependent. First, given a particular computational model, Bayesian hierarchical techniques have been used to estimate individual variation in parameters over a population of subjects, leveraging their population-level distributions. Second, candidate models are themselves compared, and individual variation in the expressed model estimated, according to the fits of the models to each subject. The interdependence between these two problems arises because the relevant population for estimating parameters of a model depends on which other subjects express the model. Here, we propose a hierarchical Bayesian inference (HBI) framework for concurrent model comparison, parameter estimation and inference at the population level, combining previous approaches. We show that this framework has important advantages for both parameter estimation and model comparison theoretically and experimentally. The parameters estimated by the HBI show smaller errors compared to other methods. Model comparison by HBI is robust against outliers and is not biased towards overly simplistic models. Furthermore, the fully Bayesian approach of HBI enables researchers to quantify uncertainty in group parameter estimates, for each candidate model separately, and to perform statistical tests on parameters of a population.
The neural dynamics of familiar face recognition
Authors: Ambrus Géza Gergely , Kaiser Daniel , Cichy Radoslaw Martin , Kovács Gyula 
Published: August 2018

AbstractIn real-life situations, the appearance of a person’s face can vary substantially across different encounters, making face recognition a challenging task for the visual system. Recent fMRI decoding studies have suggested that face recognition is supported by identity representations located in regions of the occipito-temporal cortex. Here, we used EEG to elucidate the temporal emergence of these representations. Human participants (both sexes) viewed a set of highly variable face images of four highly familiar celebrities (two male, two female), while performing an orthogonal task. Univariate analyses of event-related EEG responses revealed a pronounced differentiation between male and female faces, but not between identities of the same sex. Using multivariate representational similarity analysis, we observed a gradual emergence of face identity representations, with an increasing degree of invariance. Face identity information emerged rapidly, starting shortly after 100ms from stimulus onset. From 400ms after onset and predominantly in the right hemisphere, identity representations showed two invariance properties: (1) they equally discriminated identities of opposite sexes and of the same sex, and (2) they were tolerant to image-based variations. These invariant representations may be a crucial prerequisite for successful face recognition in everyday situations, where the appearance of a familiar person can vary drastically.Significance StatementRecognizing the face of a friend on the street is a task we effortlessly perform in our everyday lives. However, the necessary visual processing underlying familiar face recognition is highly complex. As the appearance of a given person varies drastically between encounters, for example across viewpoints or emotional expressions, the brain needs to extract identity information that is invariant to such changes. Using multivariate analyses of EEG data, we characterize how invariant representations of face identity emerge gradually over time. After 400ms of processing, cortical representations reliably differentiated two similar identities (e.g., two famous male actors), even across a set of highly variable images. These representations may support face recognition under challenging real-life conditions.
Spatial Structure Can Decrease Symbiotic Cooperation
Authors: Vostinar Anya E. , Ofria Charles 
Published: August 2018

AbstractMutualisms occur when at least two species provide a net fitness benefit to each other. These types of interactions are ubiquitous in nature, with more being discovered regularly. Mutualisms are vital to humankind: pollinators and soil microbes are critical in agriculture, bacterial microbiomes regulate our health, and domesticated animals provide us with food and companionship. Many hypotheses exist on how mutualisms evolve, however they are difficult to evaluate without bias due to the fragile and idiosyncratic systems most often investigated. Instead, we have created an artificial life simulation, Symbulation, that we use to examine mutualism evolution based on: 1) the probability of vertical transmission (symbiont being passed to offspring) and 2) the spatial structure of the environment. We found that spatial structure can lead to less mutualism at intermediate vertical transmission rates. We provide evidence that this effect is due to the ability of quasi-species to purge parasites, reducing the diversity of available symbionts. Our simulation is easily extended to test many additional hypotheses about the evolution of mutualism and serves as a general model to quantitatively compare how different environments affect the evolution of mutualism.
Ultrafast clustering of single-cell ow cytometry data using FlowGrid
Authors: Ye Xiaoxin , Ho Joshua W. K. 
Published: August 2018

AbstractFlow cytometry is a popular technology for quantitative single-cell profiling of cell surface markers. It enables expression measurement of tens of cell surface protein markers in millions of single cells. It is a powerful tool for discovering cell sub-populations and quantifying cell population heterogeneity. Traditionally, scientists use manual gating to identify cell types, but the process is subjective and is not effective for large multidimensional data. Many clustering algorithms have been developed to analyse these data but most of them are not scalable to very large data sets with more than ten million cells.Here, we present a new clustering algorithm that combines the advantages of density-based clustering algorithm DBSCAN with the scalability of grid-based clustering. This new clustering algorithm is implemented in python as an open source package, FlowGrid. FlowGrid is memory efficient and scales linearly with respect to the number of cells. We have evaluated the performance of FlowGrid against other state-of-the-art clustering programs and found that FlowGrid produces similar clustering results but with substantially less time. For example, FlowGrid is able to complete a clustering task on a data set of 23.6 million cells in less than 12 seconds, while other algorithms take more than 500 seconds or get into error.FlowGrid is an ultrafast clustering algorithm for large single-cell flow cy-tometry data. The source code is available at https://github.com/VCCRI/FlowGrid.