bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recruitment of mRNAs to P granules by gelation with intrinsically-disordered proteins
Authors: Lee Chih-Yung S. , Putnam Andrea , Lu Tu , He Shuaixin , Ouyang John Paul T. , Seydoux Geraldine 
Published: August 2019

AbstractAnimals with germ plasm assemble cytoplasmic RNA granules (germ granules) that segregate with the embryonic germ lineage. How germ granules assemble and recruit RNA is not well understood. Here we characterize the assembly and RNA composition of the germ (P) granules ofC. elegans. ∼500 maternal mRNAs are recruited into P granules by a sequence independent mechanism that favors mRNAs with low ribosome coverage. Translational activation correlates temporally with P granule exit for two mRNAs that code for germ cell fate regulators. mRNAs are recruited into the granules by MEG-3, an intrinsically disordered protein that condenses with RNA to form nanoscale gels. Our observations reveal parallels between germ granules and stress granules and suggest that cytoplasmic RNA granules are reversible super-assemblies of nanoscale RNA-protein gel condensates.
Improvising at Rest: Differentiating Jazz and Classical Music Training with Resting State Functional Connectivity
Authors: Belden Alexander , Zeng Tima , Przysinda Emily , Anteraper Sheeba Arnold , Whitfield-Gabrieli Susan , Loui Psyche 
Published: August 2019

AbstractJazz improvisation offers a model for creative cognition, as it involves the real-time creation of a novel, information-rich product. Previous research has shown that when musicians improvise, they recruit regions in the Default Mode Network (DMN) and Executive Control Network (ECN). Here, we ask whether these findings from task-fMRI studies might extend to intrinsic differences in resting state functional connectivity. We compared Improvising musicians, Classical musicians, and Minimally Musically Trained (MMT) controls in seed-based functional connectivity and network analyses in resting state functional MRI. We also examined the functional correlates of behavioral performance in musical improvisation and divergent thinking. Seed-based analysis consistently showed higher connectivity in ventral DMN (vDMN) and bilateral ECN in both groups of musically trained individuals as compared to MMT controls, with additional group differences in primary visual network, precuneus network, and posterior salience network. In particular, primary visual network connectivity to DMN and ECN was highest in Improvisational musicians, whereas within-network connectivity of vDMN and precuneus network was higher in both Improvisational and Classical musicians than in MMT controls; in contrast, connectivity between posterior salience network and superior parietal lobule was highest in Classical musicians. Furthermore, graph-theoretical analysis indicated heightened betweenness centrality, clustering, and local efficiency in Classical musicians. Taken together, results suggest that heightened functional connectivity among musicians can be explained by higher within-network connectivity (more tight-knit cortical networks) in Classical musicians, as opposed to more disperse, globally-connected cortical networks in Improvisational musicians.HighlightsMusic training is associated with higher resting state connectivityHigher connectivity in Improvisational musicians from visual network to ECN and DMNClassical musicians show higher vDMN and Precuneus within-network connectivityImprovisation and divergent thinking performance correlate with similar connectivity patterns
Unexpected sound omissions are signaled in human posterior superior temporal gyrus: an intracranial study
Authors: Fonken Yvonne M. , Mukerji Arjun , Jimenez Richard , Lin Jack , Brunner Peter , Schalk Gerwin , Knight Robert T. 
Published: August 2019

AbstractContext modulates sensory neural activations enhancing perceptual and behavioral performance and reducing prediction errors. However, the mechanism of when and where these high-level expectations act on sensory processing is unclear. Here, we isolate the effect of expectation absent any auditory evoked activity by assessing the response to omitted expected sounds. Electrophysiological signals were recorded directly from the superior temporal gyrus (STG) and superior temporal sulcus (STS) in patients with medically refractory epilepsy. Subjects listened to a predictable sequence of syllables, with some infrequently omitted. We found a high frequency band (HFB, 70-150Hz) response to omissions, which overlap with a posterior subset of auditory active electrodes. This response is distinct from omission activations observed in non-auditory selective sites in STG. Heard syllables could be classified reliably from STG, but not the identity of the omitted stimulus. Both omission- and target detection activations were also observed in prefrontal cortex.We propose that the posterior STG and STS are central for implementing predictions in the auditory environment. HFB omission activations in this region appear to index mismatch-signaling or salience detection processes.
Shrinkage Classification for Overlapping Time Series: An interpretable method for mapping stimulus-differentiated evoked response
Authors: Elliott Peter W. , Boring Matthew J. , Li Yuanning , Richardson R. Mark , Ghuman Avniel Singh , G’Sell Max 
Published: August 2019

AbstractMultivariate time series from neural electrophysiological recordings are a rich source of information about neural processing systems and require appropriate methods for proper analysis. Current methods for mapping brain function in these data using neural decoding aggregate information across space and time in limited ways, rarely incorporating spatial dependence across recording locations. We propose Shrinkage Classification for Overlapping Time Series (SCOTS), a neural decoding method that maps brain function, while accounting for spatio-temporal dependence, through interpretable dimensionality reduction and classification of multivariate neural time series. SCOTS has two components: first, overlapping clustering from sparse semi-nonnegative matrix factorization gives a data-driven aggregation of neural information across space; second, wavelet-transformed nearest shrunken centroids with sparse group lasso performs multi-class classification with selection of informative clusters and time intervals. We demonstrate use of SCOTS by applying it to human intracranial electrophysiological and MEG data collected while participants viewed visual stimuli from a range of categories. The method reveals the dynamic activation of brain regions with sensitivity to different object categories, giving insight into spatio-temporal contributions of these neural processing systems.
Girdin is a component of the lateral polarity protein network restricting cell dissemination
Authors: Biehler Cornélia , Wang Li-Ting , Sévigny Myriam , Jetté Alexandra , Gamblin Clémence , Catterall Rachel , Houssin Élise , McCaffrey Luke , Laprise Patrick 
Published: August 2019

AbstractEpithelial cell polarity defects support cancer progression. It is thus crucial to decipher the functional interactions within the polarity protein network. Here we show thatDrosophilaGirdin and its human ortholog (GIRDIN) sustain the function of crucial lateral polarity proteins by inhibiting the apical kinase aPKC. Loss of GIRDIN expression is also associated with overgrowth of disorganized cell cysts. Moreover, we observed cell dissemination fromGIRDINknockdown cysts and tumorspheres, thereby showing that GIRDIN supports the cohesion of multicellular epithelial structures. Consistent with these observations, alteration ofGIRDINexpression is associated with a poor overall survival in subtypes of breast and lung cancers. Overall, we discovered a core mechanism contributing to epithelial cell polarization from flies to humans. Our data also indicate that GIRDIN has the potential to impair the progression of epithelial cancers by preserving cell polarity and restricting cell dissemination.
Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0
Authors: Deutsch Eric W. , Lane Lydie , Overall Christopher M. , Bandeira Nuno , Baker Mark S. , Pineau Charles , Moritz Robert L. , Corrales Fernando , Orchard Sandra , Van Eyk Jennifer E. , Paik Young-Ki , Weintraub Susan T. , Vandenbrouck Yves , Omenn Gilbert S. 
Published: August 2019

AbstractThe Human Proteome Organization’s (HUPO) Human Proteome Project (HPP) developed Mass Spectrometry (MS) Data Interpretation Guidelines that have been applied since 2016. These guidelines have helped ensure that the emerging draft of the complete human proteome is highly accurate and with low numbers of false-positive protein identifications. Here, we describe an update to these guidelines based on consensus-reaching discussions with the wider HPP community over the past year. The revised 3.0 guidelines address several major and minor identified gaps. We have added guidelines for emerging data independent acquisition (DIA) MS workflows and for use of the new Universal Spectrum Identifier (USI) system being developed by the HUPO Proteomics Standards Initiative (PSI). In addition, we discuss updates to the standard HPP pipeline for collecting MS evidence for all proteins in the HPP, including refinements to minimum evidence. We present a new plan for incorporating MassIVE-KB into the HPP pipeline for the next (HPP 2020) cycle in order to obtain more comprehensive coverage of public MS data sets. The main checklist has been reorganized under headings and subitems and related guidelines have been grouped. In sum, Version 2.1 of the HPP MS Data Interpretation Guidelines has served well and this timely update to version 3.0 will aid the HPP as it approaches its goal of collecting and curating MS evidence of translation and expression for all predicted ∼20,000 human proteins encoded by the human genome.Abstract Figure
Benchmarking machine learning models for the analysis of genetic data using FRESA.CAD Binary Classification Benchmarking
Authors: de Velasco Oriol Javier , Martinez-Torteya Antonio , Trevino Victor , Alanis Israel , Vallejo Edgar E. , Tamez-Pena Jose Gerardo 
Published: August 2019

AbstractBackgroundMachine learning models have proven to be useful tools for the analysis of genetic data. However, with the availability of a wide variety of such methods, model selection has become increasingly difficult, both from the human and computational perspective.ResultsWe present the R package FRESA.CAD Binary Classification Benchmarking that performs systematic comparisons between a collection of representative machine learning methods for solving binary classification problems on genetic datasets.ConclusionsFRESA.CAD Binary Benchmarking demonstrates to be a useful tool over a variety of binary classification problems comprising the analysis of genetic data showing both quantitative and qualitative advantages over similar packages.
Statistics of spatial rotations in 3D electron cryo-microscopy by unit quaternion description
Authors: Hu Mingxu , Zhang Qi , Yang Jing , Li Xueming 
Published: August 2019

AbstractElectron cryo-microscopy (cryoEM) involves the estimation of orientations of projection images or three-dimensional (3D) volumes. However, the lack of statistical tools of rotations in cryoEM fails to answer the growing demands for adopting advanced statistical methods. In this study, we develop a comprehensive statistical tool specialized for cryoEM based on an unit quaternion description of spatial rotations. Some basic properties and definitions of the quaternion, as well as a way to use the unit quaternion to describe and perform rotations, are first recalled. Then, based on the unit quaternion, the distance and geodesic between rotations are designed for cryoEM to enable comparisons and interpolations between rotations, which are prerequisites of statistics of rotations in 3D cryoEM. Further, methods of directional statistics specialized for cryoEM are developed, including calculations of the average rotation, sampling, and inference with uniform and angular central Gaussian (ACG) distribution, as well as an estimation of the rotation precision. Finally, the method of handling molecular symmetry is introduced. Using the unit quaternion system for cryoEM, we provide comprehensive mathematical tools for the analysis of spatial rotations in cryoEM.
Selection for altruistic defense in structured populations
Authors: Jordan Felix , Hutzenthaler Martin , Metzler Dirk 
Published: August 2019

AbstractWe model natural selection for or against an anti-parasite (or anti-predator) defense allele in a host (or prey) population that is structured into many demes. The defense behavior has a fitness cost for the actor compared to non defenders (“cheaters”) in the same deme and locally reduces parasite growth rates. Hutzenthaler et al. (2022) have analytically derived a criterion for fixation or extinction of defenders in the limit of large populations, many demes, weak selection and slow migration. Here, we use both individual-based and diffusion-based simulation approaches to analyze related models. We find that the criterion still leads to accurate predictions for settings with finitely many demes and with various migration patterns.A key mechanism of providing a benefit of the defense trait is genetic drift due to randomness of reproduction and death events leading to between-deme differences in defense allele frequencies and host population sizes. We discuss an inclusive-fitness interpretation of this mechanism and presentin-silicoevidence that under these conditions a defense trait can be altruistic and still spread in a structured population.
Dissecting genetic and sex-specific host heterogeneity in pathogen transmission potential
Authors: Siva-Jothy Jonathon A. , Vale Pedro F. 
Published: August 2019

AbstractHeterogeneity in disease transmission is widespread and, when not accounted for, can produce unpredictable outbreaks of infectious disease. Despite this, precisely how different sources of variation in host traits drive heterogeneity in disease transmission is poorly understood. Here we dissected the sources of variation in pathogen transmission usingDrosophila melanogasterandDrosophilaC Virus as a host-pathogen model system. We found that infected lifespan, viral growth, virus shedding, and viral load at death were all significantly influenced by fly genetic background, sex and female mating status. To understand how variation in each of these traits may generate heterogeneity in disease transmission, we estimated individual transmission potential by integrating data on virus shedding and lifespan alongside previously collected data on social aggregation. We found that ∼15% of between-individual heterogeneity in disease transmission was explained by a significant interaction between genetic and sex-specific variation. We also characterised the amount of variation in viral load, virus shedding, and lifespan following infection that could be explained by genetic background and sex. Amongst the determinants of individual variation in disease transmission these sources of host variation play roles of varying importance, with genetic background generally playing the largest role. Our results highlight the importance of characterising sources of variation in multiple host traits when studying disease transmission at the individual-level.
Lecithin:Retinol Acyl Transferase (LRAT) induces the formation of lipid droplets
Authors: Molenaar Martijn R. , Wassenaar Tsjerk A. , Yadav Kamlesh K. , Toulmay Alexandre , Mari Muriel C. , Caillon Lucie , Chorlay Aymeric , Haaker Maya W. , Wubbolts Richard W. , Houweling Martin , Vaandrager A. Bas , Reggiori Fulvio , Thiam Abdou Rachid , Prinz William A. , Helms J. Bernd 
Published: August 2019

AbstractLipid droplets are unique and nearly ubiquitous organelles that store neutral lipids in a hydrophobic core, surrounded by a monolayer of phospholipids. The primary neutral lipids are triacylglycerols and steryl esters. It is not known whether other classes of neutral lipids can form lipid droplets by themselves. Here we show that production of retinyl esters by lecithin:retinol acyl transferase (LRAT) in yeast cells, incapable of producing triacylglycerols and steryl esters, causes the formation of lipid droplets. By electron microscopy, these lipid droplets are morphologically indistinguishable from those in wild-type cells.In silicoandin vitroexperiments confirmed the propensity of retinyl esters to segregate from membranes and to form lipid droplets. The hydrophobic N-terminus of LRAT displays preferential interactions with retinyl esters in membranes and promotes the formation of large retinyl ester-containing lipid droplets in mammalian cells. Our combined data indicate that the molecular design of LRAT is optimally suited to allow the formation of characteristic large lipid droplets in retinyl ester-storing cells.
Single nucleus andin situRNA sequencing reveals cell topographies in the human pancreas
Authors: Tosti Luca , Hang Yan , Debnath Olivia , Tiesmeyer Sebastian , Trefzer Timo , Steiger Katja , Ten Foo Wei , Lukassen Sören , Ballke Simone , Kühl Anja A. , Spieckermann Simone , Bottino Rita , Ishaque Naveed , Weichert Wilko , Kim Seung K. , Eils Roland , Conrad Christian 
Published: August 2019

AbstractMolecular evidence of cellular heterogeneity in the human exocrine pancreas has not been established, due to the local concentration of hydrolytic enzymes that can rapidly degrade cells and RNA upon resection. Here we innovated single-nucleus RNA sequencing protocols, and profiled more than 120,000 cells from adult and neonatal human donors to create the first comprehensive atlas of human pancreas cells, including epithelial and non-epithelial constituents. Adult and neonatal pancreata shared common features, including the presence of previously undetected acinar subtypes, but also showed marked differences in the composition of the endocrine, endothelial, and immune compartments. Spatial cartography, including cell proximity mapping throughin situsequencing, revealed dynamic developmental cell topographies in the endocrine and exocrine pancreas. Our human pancreas cell atlas can be interrogated to understand pancreatic cell biology, and provides a crucial reference set for future comparisons with diseased tissue samples to map the cellular foundations of pancreatic diseases.
Dynamic synergetic configurations of resting-state networks in ADHD
Authors: Kaboodvand Neda , Iravani Behzad , Fransson Peter 
Published: August 2019

AbstractAttention deficit hyperactivity disorder (ADHD) is characterized by high distractibility and impaired executive functions. Notably, there is mounting evidence suggesting that ADHD could be regarded as a default mode network (DMN) disorder. In particular, failure in regulating the dynamics of activity and interactions of the DMN and cognitive control networks have been hypothesized as the main source of task interference causing attentional problems. On the other hand, previous studies indicated pronounced fluctuations in the strength of functional connections over time, particularly for the inter-network connections between the DMN and fronto-parietal control networks. Hence, characterization of connectivity disturbances in ADHD disorder requires a thorough assessment of time-varying FCs. In this study, we propose a dynamical systems perspective to assess how the DMN over time recruits different configurations of network segregation and integration. Specifically, we were interested in configurations for which both intra- and inter-network connections are retained, as opposed to commonly used methods which assess network segregation as a single measure. From resting-state fMRI data, we extracted three different stable configurations of FC patterns for the DMN, namely synergies. We provide evidence supporting our hypothesis that the ADHD brain differs in both recruitment rate and the topology of specific synergies between resting-state networks.
What difference do retractions make? An estimate of the epistemic impact of retractions on recent meta-analyses
Authors: Fanelli Daniele , Moher David 
Published: August 2019

ABSTRACTEvery year, several hundred publications are retracted due to fabrication and falsification of data or plagiarism and other breeches of research integrity and ethics. Despite considerable research on this phenomenon, the extent to which a retraction requires revising previous scientific estimates and beliefs – which we define as the epistemic impact - is unknown. We collected a representative sample of recently retracted studies that had been included in recent meta-analyses, and compared the summary effect size of these meta analyses with and without the refracted studies. On average, the retractions had occurred about six years prior to the publication of the corresponding meta-analyses.Our results suggest that retractions have varying impacts depending on their causes. In particular, removing from an analysis a study retracted because of issues with data, methods or results, led to a statistically significant reduction of the estimated effect size. Assuming that the results of these retracted studies are completely false, then the meta-analyses that had included them had overestimated the summary effect sizes by, averaging across effect size metrics, 30% (median, 13%). However, retractions due to plagiarism or other issues not related to data, methods or results had no impact on the conclusions of meta-analyses.Since retractions due to plagiarism or other non-data related issues typically constitute over 75% of total retractions, our results suggest that the epistemic impact of most retractions is likely to be null. However, our results also suggest that retractions due to issues with data, methods or results should be accompanied by a revision of relevant meta-analyses, and by extension a downwards revision of prior scientific beliefs.
Analysis of the lineage ofPhytophthora infestansisolates using mating type assay, traditional markers, and next generation sequencing technologies
Authors: Arafa Ramadan A. , Kamel Said M. , Rakha Mohamed T. , Soliman Nour Elden K. , Moussa Olfat M. , Shirasawa Kenta 
Published: August 2019

AbstractPhytophthora infestans(Mont.) de Bary, a hemibiotrophic oomycete, has caused severe epidemics of late blight in tomato and potato crops around the world since the Irish Potato Famine in the 1840s. Breeding of late blight resistant cultivars is one of the most effective strategies to overcome this disruptive disease. However,P. infestansis able to break down host resistance and acquire resistance to various fungicides, possibly because of the existence of high genetic variability amongP. infestansisolates via sexual and asexual reproduction. Therefore, to manage this disease, it is important to understand the genetic divergence ofP. infestansisolates. In this study, we analyzed the genomes ofP. infestansisolates collected from Egypt and Japan using various molecular approaches including the mating type assay and genotyping simple sequence repeats, mitochondria DNA, and effector genes. We also analyzed genome-wide single nucleotide polymorphisms using double-digest restriction-site associated DNA sequencing and whole genome resequencing (WGRS). The isolates were classified adequately using high-resolution genome-wide approaches. Moreover, these analyses revealed new clusters ofP. infestansisolates in the Egyptian population. Monitoring the genetic divergence ofP. infestansisolates as well as breeding of resistant cultivars would facilitate the elimination of the late blight disease.