bluuebunny/crossref_metadata_2025_split huggingface dataset:
HiNT: a computational method for detecting copy number variations and translocations from Hi-C data
Authors: Wang Su , Lee Soohyun , Chu Chong , Jain Dhawal , Nelson Geoff , Walsh Jennifer M. , Alver Burak H. , Park Peter J. 
Published: June 2019

AbstractThe three-dimensional conformation of a genome can be profiled using Hi-C, a technique that combines chromatin conformation capture with high-throughput sequencing. However, structural variations (SV) often yield features that can be mistaken for chromosomal interactions. Here, we describe a computational method HiNT (Hi-C for copy Number variation and Translocation detection), which detects copy number variations and inter-chromosomal translocations within Hi-C data with breakpoints at single base-pair resolution. We demonstrate that HiNT outperforms existing methods on both simulated and real data. We also show that Hi-C can supplement whole-genome sequencing in SV detection by locating breakpoints in repetitive regions.
Familial t(1;11) translocation is associated with disruption of white matter structural integrity and oligodendrocyte-myelin dysfunction
Authors: Vasistha Navneet A. , Johnstone Mandy , Barton Samantha K. , Mayerl Steffen , Selvaraj Bhuvaneish T. , Thomson Pippa A , Dando Owen , Grünewald Ellen , Alloza Clara , Bastin Mark E. , Livesey Matthew R. , Economides Kyriakos , Magnani Dario , Makedonopolou Paraskevi , Burr Karen , Story David J. , Blackwood Douglas J. , Wyllie David J.A , McIntosh Andrew M. , Kirsty Millar J. , ffrench-Constant Charles , Hardingham Giles E. , Lawrie Stephen M. , Chandran Siddharthan 
Published: June 2019

ABSTRACTAlthough the underlying neurobiology of major mental illness (MMI) remains unknown, emerging evidence implicates a role for oligodendrocyte-myelin abnormalities. Here, we took advantage of a large family carrying a balanced t(1;11) translocation, which substantially increases risk of MMI, to undertake both diffusion tensor imaging (DTI) and cellular studies to evaluate the consequences of the t(1;11) translocation on white matter structural integrity and oligodendrocyte-myelin biology. This translocation disrupts among others theDISC1gene which plays a crucial role in brain development. We show that translocation-carrying patients display significant disruption in white matter integrity compared to familial controls. At a cellular level, we observe dysregulation of key pathways controlling oligodendrocyte development and morphogenesis in induced pluripotent stem cell (iPSC) case derived oligodendrocytes. This is associated with reduced proliferation and a stunted morphologyin vitro. Further, myelin internodes in a humanized mouse model that recapitulates the human translocation as well as after transplantation of t(1;11) oligodendrocyte progenitors were significantly reduced compared to controls. Thus we provide evidence that the t(1;11) translocation has biological effects at both the systems and cellular level that together suggest oligodendrocyte-myelin dysfunction.
Diminished cortical excitation and elevated inhibition during perceptual impairments in a mouse model of autism
Authors: Rosario Joseph Del , Speed Anderson , Arrowood Hayley , Motz Cara , Pardue Machelle , Haider Bilal 
Published: June 2019

AbstractSensory impairments are a core feature of autism spectrum disorder (ASD). These impairments affect visual perception (Robertson and Baron-Cohen, 2017), and have been hypothesized to arise from imbalances in cortical excitatory and inhibitory activity (Rubenstein and Merzenich, 2003; Nelson and Valakh, 2015; Sohal and Rubenstein, 2019); however, there is little direct evidence testing this hypothesis in identified excitatory and inhibitory neurons during impairments of sensory perception. Several recent studies have examined cortical activity in transgenic mouse models of ASD (Goel et al., 2018; Antoine et al., 2019; Lazaro et al., 2019), but have provided conflicting evidence for excitatory versus inhibitory activity deficits. Here, we utilized a genetically relevant mouse model of ASD (CNTNAP2−/− knockout, KO; Arking et al., 2008; Penagarikano et al., 2011) and directly recorded putative excitatory and inhibitory population spiking in primary visual cortex (V1) while measuring visual perceptual behavior (Speed et al., 2019). We found quantitative impairments in the speed, accuracy, and contrast sensitivity of visual perception in KO mice. These impairments were simultaneously associated with elevated inhibitory and diminished excitatory neuron activity evoked by visual stimuli during behavior, along with aberrant 3 – 10 Hz oscillations in superficial cortical layers 2/3 (L2/3). These results establish that perceptual deficits relevant for ASD can arise from diminished sensory activity of excitatory neurons in feedforward layers of cortical circuits.
Spatially resolved dendritic integration: Towards a functional classification of neurons
Authors: Kirch Christoph , Gollo Leonardo L 
Published: June 2019

AbstractThe vast tree-like dendritic structure of neurons allows them to receive and integrate input from many neurons. A wide variety of neuronal morphologies exist, however, their role in dendritic integration, and how it shapes the response of the neuron, is not yet fully understood. Here, we study the evolution and interactions of dendritic spikes in excitable neurons with complex real branch structures. We focus on dozens of digitally reconstructed illustrative neurons from the online repository NeuroMorpho.org, which contains over 100,000 neurons. Yet, our methods can be promptly extended to any other neuron. This approach allows us to estimate and map specific and heterogeneous patterns of activity observed across extensive dendritic trees with thousands of compartments. We propose a classification of neurons based on the location of the soma (centrality) and the number of branches connected to the soma. These are key topological factors in determining the neuron’s energy consumption, firing rate, and the dynamic range, which quantifies the range in synaptic input rate that can be reliably encoded by the neuron’s firing rate. Moreover, we find that bifurcations, the structural building blocks of complex dendrites, play a major role in increasing the dynamic range of neurons. Our results provide a better understanding of the effects of neuronal morphology in the diversity of neuronal dynamics and function.
Inference of bacterial small RNA regulatory networks and integration with transcription factor driven regulatory networks
Authors: Arrieta-Ortiz Mario L. , Hafemeister Christoph , Shuster Bentley , Baliga Nitin S. , Bonneau Richard , Eichenberger Patrick 
Published: June 2019

ABSTRACTSmall non-coding RNAs (sRNAs) are key regulators of bacterial gene expression. Through complementary base pairing, sRNAs affect messenger RNA stability and translation efficiency. Here, we describe a network inference approach designed to identify sRNA-mediated regulation of transcript levels. We use existing transcriptional datasets and prior knowledge to infer sRNA regulons using our network inference tool, theInferelator. This approach produces genome-wide gene regulatory networks that include contributions by both transcription factors and sRNAs. We show the benefits of estimating and incorporating sRNA activities into network inference pipelines. We comprehensively assess the accuracy of inferred sRNA regulons using available experimental data. We uncover 30 novel experimentally supported sRNA-mRNA interactions inEscherichia coli, outperforming previous network-based efforts. Our findings expand the role of sRNAs in the regulation of chemotaxis, oxidation-reduction processes, galactose intake, and generation of pyruvate. Additionally, our pipeline complements sequence-based sRNA-mRNA interaction prediction methods by adding a data-driven filtering step. Finally, we show the general applicability of our approach by identifying novel, experimentally supported, sRNA-mRNA interactions inPseudomonas aeruginosaandBacillus subtilis. Overall, our strategy generates novel insights into the functional implications of sRNA regulation in multiple bacterial species.IMPORTANCEIndividual bacterial genomes can have dozens of small non-coding RNAs with largely unexplored regulatory functions. Although bacterial sRNAs influence a wide range of biological processes, including antibiotic resistance and pathogenicity, our current understanding of sRNA-mediated regulation is far from complete. Most of the available information is restricted to a few well-studied bacterial species; and even in those species, only partial sets of sRNA targets have been characterized in detail. To close this information gap, we developed a computational strategy that takes advantage of available transcriptional data and knowledge about validated and putative sRNA-mRNA interactions. Our approach facilitates the identification of experimentally supported novel interactions while filtering out false positives. Due to its data-driven nature, our method emerges as an ideal strategy to identify biologically relevant interactions among lists of candidate sRNA-target pairs predictedin silicofrom sequence analysis or derived from sRNA-mRNA binding experiments.
FAIRshake: toolkit to evaluate the findability, accessibility, interoperability, and reusability of research digital resources
Authors: Clarke Daniel J. B. , Wang Lily , Jones Alex , Wojciechowicz Megan L. , Torre Denis , Jagodnik Kathleen M. , Jenkins Sherry L. , McQuilton Peter , Flamholz Zachary , Silverstein Moshe C. , Schilder Brian M. , Robasky Kimberly , Castillo Claris , Idaszak Ray , Ahalt Stanley C. , Williams Jason , Schurer Stephan , Cooper Daniel J. , de Miranda Azevedo Ricardo , Klenk Juergen A. , Haendel Melissa A. , Nedzel Jared , Avillach Paul , Shimoyama Mary E. , Harris Rayna M. , Gamble Meredith , Poten Rudy , Charbonneau Amanda L. , Larkin Jennie , Brown C. Titus , Bonazzi Vivien R. , Dumontier Michel J. , Sansone Susanna-Assunta , Ma’ayan Avi 
Published: June 2019

AbstractAs more datasets, tools, workflows, APIs, and other digital resources are produced by the research community, it is becoming increasingly difficult to harmonize and organize these efforts for maximal synergistic integrated utilization. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have prompted many stakeholders to consider strategies for tackling this challenge by making these digital resources follow common standards and best practices so that they can become more integrated and organized. Faced with the question of how to make digital resources more FAIR, it has become imperative to measure what it means to be FAIR. The diversity of resources, communities, and stakeholders have different goals and use cases and this makes assessment of FAIRness particularly challenging. To begin resolving this challenge, the FAIRshake toolkit was developed to enable the establishment of community-driven FAIR metrics and rubrics paired with manual, semi- and fully-automated FAIR assessment capabilities. The FAIRshake toolkit contains a database that lists registered digital resources, with their associated metrics, rubrics, and assessments. The FAIRshake toolkit also has a browser extension and a bookmarklet that enables viewing and submitting assessments from any website. The FAIR assessment results are visualized as an insignia that can be viewed on the FAIRshake website, or embedded within hosting websites. Using FAIRshake, a variety of bioinformatics tools, datasets listed on dbGaP, APIs registered in SmartAPI, workflows in Dockstore, and other biomedical digital resources were manually and automatically assessed for FAIRness. In each case, the assessments revealed room for improvement, which prompted enhancements that significantly upgraded FAIRness scores of several digital resources.
Action information contributes to metacognitive decision-making
Authors: Wokke Martijn E. , Achoui Dalila , Cleeremans Axel 
Published: June 2019

AbstractMonitoring and control of our decision process are key ingredients of adept decision-making. Such metacognitive abilities allow us to adjust ongoing behavior and modify future decisions in the absence of external feedback. Although metacognition is critical in many daily life settings, it remains unclear what information is actually being monitored and what kind of information is being used for metacognitive decisions. In the present study, we investigated whether response information connected to perceptual events contribute to metacognitive decision-making. Therefore, we recorded EEG signals during a perceptual color discrimination task while participants were asked to provide an estimate about the quality of their decision on each trial. Critically, the moment participants provided second-order decisions varied across conditions, thereby changing the amount of action information (e.g., response competition or response fluency) available for metacognitive decisions.Results from three experiments demonstrate that metacognitive performance improved when first-order action information was available at the moment metacognitive decisions about the perceptual task had to be provided. This behavioral effect was accompanied by enhanced functional connectivity (beta phase synchrony) between motor areas and prefrontal regions, exclusively observed during metacognitive decision-making. Our findings demonstrate that action information contributes to metacognitive decision-making, thereby painting a picture of metacognition as a second-order process, integrating sensory evidence and the state of the decider during decision-making.SignificanceMonitoring and control of our decision process is a critical part of every day decision-making. When feedback is not available, metacognitive skills enable us to modify current behavior and adapt prospective decision-making. Here, we investigated what kind information is being used to compute an estimate about the quality of our decisions. Results demonstrate that during perceptual decision-making, information about one’s actions towards perceptual events is being used to evaluate the quality of one’s decisions. EEG results indicate that functional connectivity between motor regions and prefrontal cortex could serve as a mechanism to convey action information during metacognitive decision-making. Considered together, our results demonstrate that post-decisional information contributes to metacognition, thereby evaluating not only what one perceives (e.g., strength of perceptual evidence) but also how one responds towards perceptual events.
ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning
Authors: Rączkowski Łukasz , Możejko Marcin , Zambonelli Joanna , Szczurek Ewa 
Published: June 2019

ABSTRACTMachine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely accurate and, ideally, provide a measure of uncertainty for its predictions. Such accurate and reliable classifiers need enough labelled data for training, which requires time-consuming and costly manual annotation by pathologists. Thus, it is critical to minimise the amount of data needed to reach the desired accuracy by maximising the efficiency of training. We propose an accurate, reliable and active (ARA) image classification framework and introduce a new Bayesian Convolutional Neural Network (ARA-CNN) for classifying histopathological images of colorectal cancer. The model achieves exceptional classification accuracy, outperforming other models trained on the same dataset. The network outputs an uncertainty measurement for each tested image. We show that uncertainty measures can be used to detect mislabelled training samples and can be employed in an efficient active learning workflow. Using a variational dropout-based entropy measure of uncertainty in the workflow speeds up the learning process by roughly 45%. Finally, we utilise our model to segment whole-slide images of colorectal tissue and compute segmentation-based spatial statistics.
Linking genotypes with multiple phenotypes in single-cell CRISPR screens
Authors: Yang Lin , Zhu Yuqing , Yu Hua , Chen Sitong , Chu Yulan , Huang He , Zhang Jin , Li Wei 
Published: June 2019

AbstractCRISPR/Cas9 based functional screening coupled with single-cell RNA-seq (“single-cell CRISPR screening”) unravels gene regulatory networks and enhancer-gene regulations in a large scale. We propose scMAGeCK, a computational framework to systematically identify genes and non-coding elements associated with multiple expression-based phenotypes in single-cell CRISPR screening. scMAGeCK identified genes and enhancers that modulate the expression of a known proliferation marker, MKI67 (Ki-67), a result that resembles the outcome of proliferation-linked CRISPR screening. We further performed single-cell CRISPR screening on mouse embryonic stem cells (mESC), and identified key genes associated with different pluripotency states. scMAGeCK enabled an unbiased construction of genotype-phenotype network, where multiple phenotypes can be regulated by different gene perturbations. Finally, we studied key factors that improve the statistical power of single-cell CRISPR screens, including target gene expression and the number of guide RNAs (gRNAs) per cell. Collectively, scMAGeCK is a novel and effective computational tool to study genotype-phenotype relationships at a single-cell level.
Temporal dynamics of Bacteria, Archaea and protists in equatorial coastal waters
Authors: Chénard Caroline , Wijaya Winona , Vaulot Daniel , dos Santos Adriana Lopes , Martin Patrick , Kaur Avneet , Lauro Federico M 
Published: June 2019

ABSTRACTSingapore, an equatorial island in South East Asia, is influenced by a bi-annual reversal of wind directions which defines two monsoon seasons. We characterized the dynamics of the microbial communities of Singapore coastal waters by collecting monthly samples between February 2017 and July 2018 at four sites located across two straits with different trophic status, and sequencing the V6-V8 region of the small sub-unit ribosomal RNA gene (rRNA gene) of Bacteria, Archaea, and Eukaryota. Johor Strait, which is subjected to wider environmental fluctuations from anthropogenic activities, presented a higher abundance of copiotrophic microbes, including Cellvibrionales and Rhodobacterales. The mesotrophic Singapore Strait, where the seasonal variability is caused by changes in the oceanographic conditions, harboured a higher proportion of typically marine microbe groups such as Synechococcales, Nitrosupumilales, SAR11, SAR86, Marine Group II Archaea and Radiolaria. In addition, we observed seasonal variability of the microbial communities in the Singapore Strait, which was possibly influenced by the alternating monsoon regime, while no seasonal pattern was detected in the Johor Strait.
Axial variation of deoxyhemoglobin density as a source of the low-frequency time lag structure in blood oxygenation level-dependent signals
Authors: Aso Toshihiko , Urayama Shinnichi , Hidenao Fukuyama , Murai Toshiya 
Published: June 2019

AbstractPerfusion-related information is reportedly embedded in the low-frequency component of a blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. The blood-propagation pattern through the cerebral vascular tree is detected as an interregional lag variation of spontaneous low-frequency oscillations (sLFOs). Mapping of this lag, or phase, has been implicitly treated as a projection of the vascular tree structure onto real space. While accumulating evidence supports the biological significance of this signal component, the physiological basis of the “perfusion lag structure,” a requirement for an integrative resting-state fMRI-signal model, is lacking. In this study, we conducted analyses furthering the hypothesis that the sLFO is not only largely of systemic origin, but also essentially intrinsic to blood, and hence behaves as a virtual tracer. By summing the small fluctuations of instantaneous phase differences between adjacent vascular regions, a velocity response to respiratory challenges was detected. Regarding the relationship to neurovascular coupling, the removal of the whole lag structure, which can be considered as an optimized global-signal regression, resulted in a reduction of inter-individual variance while preserving the fMRI response. Examination of the T2* and S0, or non-BOLD, components of the fMRI signal revealed that the lag structure is deoxyhemoglobin dependent, while paradoxically presenting a signal-magnitude reduction in the venous side of the cerebral vasculature. These findings provide insight into the origin of BOLD sLFOs, suggesting that they are highly intrinsic to the circulating blood.
Tooth Fracture Frequency in Gray Wolves Reflects Prey Availability
Authors: Van Valkenburgh Blaire , Peterson Rolf O. , Smith Douglas W. , Stahler Daniel R. , Vucetich John A. 
Published: June 2019

AbstractExceptionally high rates of tooth fracture in large Pleistocene carnivorans imply intensified interspecific competition, given that tooth fracture rises with increased bone consumption, a behavior that likely occurs when prey are difficult to acquire. To assess the link between prey availability and dental attrition, we documented dental fracture rates over decades among three well-studied populations of extant gray wolves that differed in prey:predator ratio and levels of carcass utilization. When prey:predator ratios declined, kills were more fully consumed, and rates of tooth fracture more than doubled. This supports tooth fracture frequency as a relative measure of the difficulty of acquiring prey, and reveals a rapid response to diminished food levels in large carnivores despite risks of infection and reduced fitness due to dental injuries. More broadly, large carnivore tooth fracture frequency likely reflects energetic stress, an aspect of predator success that is challenging to quantify in wild populations.
Cytotoxicity of 1-deoxysphingolipid Unraveled by Genome-wide Genetic Screens and Lipidomics
Authors: Haribowo A. Galih , Hannich J. Thomas , Michel Agnès H. , Megyeri Márton , Schuldiner Maya , Kornmann Benoît , Riezman Howard 
Published: June 2019

AbstractHereditary Sensory and Autonomic Neuropathy (HSAN) type IA and IC are caused by elevated levels of an atypical class of lipid named 1-deoxysphingolipid (DoxSL). How elevated levels of DoxSL perturb the physiology of the cell and how the perturbations lead to HSAN IA/C are largely unknown. In this study, we show that C26-1-deoxydihydroceramide (C26-DoxDHCer) is highly toxic to the cell, while C16- and C18-DoxDHCer are less toxic. Genome-wide genetic screens and lipidomics revealed the dynamics of DoxSL accumulation and DoxSL species responsible for the toxicity over the course of DoxSL accumulation. Furthermore, we show that disruption of F-actin organization, alteration of mitochondrial shape, and accumulation of hydrophobic bodies by DoxSL are not sufficient to cause complete cellular failure. However, combined with collapsed ER membrane, these perturbations cause cell death. Thus, we have unraveled key principles of DoxSL cytotoxicity that help to explain the clinical features of HSAN IA/C.