bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the overlap between rheumatoid arthritis susceptibility loci and long non-coding RNA annotations
Authors: Ding James , Shi Chenfu , Bowes John , Eyre Stephen , Orozco Gisela 
Published: October 2019

ABSTRACTWhilst susceptibility variants for many complex diseases, such as rheumatoid arthritis (RA), have been well characterised, the mechanism by which risk is mediated is still unclear for many loci. This is especially true for the majority of variants that do not affect protein-coding regions. lncRNA represent a group of molecules that have been shown to be enriched amongst variants associated with RA and other complex diseases, compared to random variants. In order to establish to what degree direct disruption of lncRNA may represent a potential mechanism for mediating RA susceptibility, we chose to further explore this overlap. By testing the ability of annotated features to improve a model of disease susceptibility, we were able to demonstrate a local enrichment of enhancers from immune-relevant cell types amongst RA susceptibility variants (log2 enrichment 3.40). This was not possible for lncRNA annotations in general, however a small, but significant enrichment was observed for immune-enriched lncRNA (log2 enrichment 0.867002). This enrichment was no longer apparent when the model was conditioned on immune-relevant enhancers (log2 enrichment -0.372734), suggesting that direct disruption of lncRNA sequence, independent of enhancer disruption, does not represent a major mechanism by which susceptibility to complex diseases is mediated. Furthermore, we demonstrated that, in keeping with general lncRNA characteristics, immune-enriched lncRNA are expressed at low levels that may not be amenable to functional characterisation.
MINDFUL: A Method to Identify Novel and Diverse Signals with Fast, Unsupervised Learning
Authors: Parulekar Mallika , Narlikar Leelavati 
Published: October 2019

AbstractWith rapid advances in experimental methods that map transcription start sites (TSSs) at a high resolution, there is a need to characterize the sequence diversity of TSS neighborhoods. Most current techniques scan for previously discovered elements, such as the TATA box, the INR motif, CpG islands, etc. to categorize promoters into different classes. Reliance on such elements hinders the discovery of novel elements. On the other hand, methods that use standard motif discovery to discover de novo promoter elements are also limited by the fact that a motif is picked up only if it is over-represented in the dataset. An element that appears only in a small set of promoters can thus be missed. We previously developed a clustering-based approach that uses no prior knowledge of elements to solve this problem [1]. That method uses Gibbs sampling to learn the model parameters, but is untenable on large datasets. Here we propose a new, fast method called MINDFUL, that uses a greedy k-means-like approach to cluster promoters aligned by TSSs into diverse classes, while also learning the optimal value of k. It is general enough to be used for any data that has categorical variables, and is not restricted to DNA.
Prefrontal cortex exhibits multi-dimensional dynamic encoding during decision-making
Authors: Aoi Mikio C. , Mante Valerio , Pillow Jonathan W. 
Published: October 2019

AbstractRecent work has suggested that prefrontal cortex (PFC) plays a key role in context-dependent perceptual decision-making. Here we investigate population-level coding of decision variables in monkey PFC using a new method for identifying task-relevant dimensions of neural activity. Our analyses reveal that, in contrast to one-dimensional attractor models, PFC has a multi-dimensional code for decisions, context, and relevant as well as irrelevant sensory information. Moreover, these representations evolve in time, with an early linear accumulation phase followed by a phase with rotational dynamics. We identify the dimensions of neural activity associated with these phases, and show that they are not the product of distinct populations, but of a single population with broad tuning characteristics. Finally, we use model-based decoding to show that the transition from linear to rotational dynamics coincides with a sustained plateau in decoding accuracy, revealing that rotational dynamics in PFC preserve sensory as well as choice information for the duration of the stimulus integration period.
Centromere scission drives chromosome shuffling and reproductive isolation
Authors: Yadav Vikas , Sun Sheng , Coelho Marco A. , Heitman Joseph 
Published: October 2019

AbstractA fundamental characteristic of eukaryotic organisms is the generation of genetic variation via sexual reproduction. Conversely, significant large-scale genome structure variations could hamper sexual reproduction, causing reproductive isolation and promote speciation. The underlying processes behind large-scale genome rearrangements are not well understood and include chromosome translocations involving centromeres. Recent genomic studies in theCryptococcusspecies complex revealed that chromosome translocations generated via centromere recombination have reshaped the genomes of different species. In this study, multiple DNA double-strand breaks (DSBs) were generated via the CRISPR/Cas9 system at centromere-specific retrotransposons in the human fungal pathogenCryptococcus neoformans. The resulting DSBs were repaired in a complex manner, leading to the formation of multiple inter-chromosomal rearrangements and new telomeres, similar to chromothripsis-like events. The newly generated strains harboring chromosome translocations exhibited normal vegetative growth but failed to undergo successful sexual reproduction with the parental wild-type strain. One of these strains failed to produce any spores, while another produced ∼3% viable progeny. The germinated progeny exhibited aneuploidy for multiple chromosomes and showed improved fertility with both parents. All chromosome translocation events were accompanied without any detectable change in gene sequences and thus, suggest that chromosomal translocations alone may play an underappreciated role in the onset of reproductive isolation and speciation.
Decomposing Simon task BOLD activation using a drift-diffusion model framework
Authors: McIntosh James R , Sajda Paul 
Published: October 2019

ABSTRACTThe Simon effect is observed in spatial conflict tasks where the response time of subjects is increased if stimuli are presented in a lateralized manner so that they are incongruous with the response information that they represent symbolically. Previous studies have used fMRI to investigate this phenomenon, and while some have been driven by considerations of an underlying model, none have attempted to directly tie model and BOLD response together. It is likely that this is due to Simon models having been predominantly descriptive of the phenomenon rather than capturing the full spectrum of behavior at the level of individual subjects. Sequential sampling models (SSM) which capture full response distributions for correct and incorrect responses have recently been extended to capture conflict tasks.In this study we use our freely available framework for fitting and comparing non-standard SSM to fit the Simon effect SSM (SE-SSM) to behavioral data. This model extension includes specific estimates of automatic response bias and conflict monitoring based deployment of attention to individual subject behavioral data. We apply this approach in order to investigate whether our task specific model parameters have a correlate in BOLD response. Under the assumption that the SE-SSM reflects aspects of neural processing in this task, we go on to examine the BOLD correlates with the within trial expected decision-variable.We find that the SE-SSM captures the behavioral data and that our two conflict specific model parameters have clear across subject BOLD correlates, while other model parameters, as well as more standard behavioral measures do not. We also find that examining BOLD in terms of the expected decision-variable leads to a specific pattern of activation that would not be otherwise possible to extract.
Network dynamics underlying OFF responses in the auditory cortex
Authors: Bondanelli Giulio , Deneux Thomas , Bathellier Brice , Ostojic Srdjan 
Published: October 2019

AbstractAcross sensory systems, complex spatio-temporal patterns of neural activity arise following the onset (ON) and offset (OFF) of stimuli. While ON responses have been widely studied, the mechanisms generating OFF responses in cortical areas have so far not been fully elucidated. We examine here the hypothesis that OFF responses are single-cell signatures of recurrent interactions at the network level. To test this hypothesis, we performed population analyses of two-photon calcium recordings in the auditory cortex of awake mice listening to auditory stimuli, and compared linear single-cell and network models. While the single-cell model explained some prominent features of the data, it could not capture the structure across stimuli and trials. In contrast, the network model accounted for the low-dimensional organisation of population responses and their global structure across stimuli, where distinct stimuli activated mostly orthogonal dimensions in the neural state-space.
Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations
Authors: Duchene Sebastian , Lemey Philippe , Stadler Tanja , Ho Simon YW , Duchene David A , Dhanasekaran Vijaykrishna , Baele Guy 
Published: October 2019

AbstractPhylogenetic methods can use the sampling times of molecular sequence data to calibrate the molecular clock, enabling the estimation of evolutionary rates and timescales for rapidly evolving pathogens and data sets containing ancient DNA samples. A key aspect of such calibrations is whether a sufficient amount of molecular evolution has occurred over the sampling time window, that is, whether the data can be treated as having come from a measurably evolving population. Here we investigate the performance of a fully Bayesian evaluation of temporal signal (BETS) in sequence data. The method involves comparing the fit to the data of two models: a model in which the data are accompanied by the actual (heterochronous) sampling times, and a model in which the samples are constrained to be contemporaneous (isochronous). We conducted simulations under a wide range of conditions to demonstrate that BETS accurately classifies data sets according to whether they contain temporal signal or not, even when there is substantial among-lineage rate variation. We explore the behaviour of this classification in analyses of five empirical data sets: modern samples ofA/H1N1 influenza virus, the bacteriumBordetella pertussis, coronaviruses from mammalian hosts, ancient DNA fromHepatitis B virusand mitochondrial genomes of dog species. Our results indicate that BETS is an effective alternative to other tests of temporal signal. In particular, this method has the key advantage of allowing a coherent assessment of the entire model, including the molecular clock and tree prior which are essential aspects of Bayesian phylodynamic analyses.
DNA methylation in the APOE gene: its link with Alzheimer’s and cardiovascular health
Authors: Mur Jure , McCartney Daniel L. , Walker Rosie M. , Campbell Archie , Bermingham Mairead L. , Morris Stewart W. , Porteous David J. , McIntosh Andrew M. , Deary Ian J. , Evans Kathryn L. , Marioni Riccardo E. 
Published: October 2019

AbstractGenetic variation in the apolipoprotein E (APOE) gene is associated with Alzheimer’s disease (AD) and risk factors for cardiovascular disease (CVD). DNA methylation at APOE has been linked to altered cognition and AD. It is unclear if epigenetic marks could be used for predicting future disease. We assessed blood-based DNA methylation at 13 CpGs in the APOE gene in 5828 participants from the Generation Scotland (GS) cohort. Using linear regression, we examined the relationship between APOE methylation, cognition, cholesterol, and the risks for AD and CVD. DNA methylation at two CpGs was associated with the ratio of total-to-HDL cholesterol, but not with cognition, or the risks of AD or CVD. APOE methylation could be involved in the levels of blood cholesterol, but there is no evidence for the utility of APOE methylation as a biomarker for predicting AD or CVD.
Spontaneous Traveling Cortical Waves Gate Perception in Awake Behaving Primates
Authors: Davis Zachary W. , Muller Lyle , Trujillo Julio-Martinez , Sejnowski Terrence , Reynolds John H. 
Published: October 2019

AbstractPerceptual sensitivity varies from moment to moment. One potential source of variability is spontaneous fluctuations in cortical activity that can travel as a wave. Spontaneous traveling waves have been reported during anesthesia, but questioned as to whether they are relevant to waking cortical function. Using newly developed analytic techniques, we find spontaneous waves of activity in extrastriate visual cortex of awake marmosets (Callithrix jacchus). In monkeys trained to detect faint visual targets, the timing and position of spontaneous traveling waves, prior to target onset, predict the magnitude of evoked activity and the likelihood of detection. In contrast, spatially disorganized fluctuations of neural activity are much less predictive. These results reveal an important role for spontaneous traveling waves in sensory processing through modulating neural and perceptual sensitivity.One Sentence SummaryFluctuations in cortical activity often travel as waves, shape incoming sensory information, and affect conscious perception.
Identifying robust strategies for assisted migration in a competitive stochastic metacommunity
Authors: Backus Gregory A. , Baskett Marissa L. 
Published: October 2019

AbstractAssisted migration is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population might fail to establish within its donor community if there is high uncertainty in decision making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of assisted migration under different management scenarios, we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without assisted migration, the species in our model were vulnerable to climate change if they had low population sizes, short dispersal, and strong poleword competition. When relocating species that exemplified these traits, assisted migration increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat assisted migration in case they move the species at the wrong place and wrong time, especially when it is difficult to identify a species’ optimal climate. We found that assisted migration was most beneficial to species with low dispersal ability and least beneficial to species with narrow thermal tolerances, for which assisted migration increased extinction risk on average. Lastly, while relocation did not affect the persistence of non-target species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.
Physical activity improves sarcopenia in a murine model by enhancing the proliferative potential of muscle stem cells, oxidative capacity of mitochondrial enzymes and expression of Sestrins
Authors: Anwar Masroor , Mallick Saumya Ranjan , Paliwal Daizy , Sekhar Shashank , Panda S.K. , Dey Sharmistha , Dey A.B. 
Published: October 2019

AbstractSarcopenia is a major health issue in old age. Underlying molecular mechanisms in its genesis remain unclear and optimal animal models are yet to be established. A novel animal model was developed to identify structural and functional changes in skeletal muscles from sarcopenia. The influence of physical activity on animals of the sarcopenic model with respect to the expression of anti-oxidant proteins, mitochondrial oxidative capacity, and effect on muscle stem cells (MuSCs), were assessed. Male C57Bl/6 mice of different age groups were recruited: Y-Cntrl (young-control), A-Cntrl (aged-control), SAR-model and SAR-INT. SAR-model group was kept in a retrofitted confined cage and was fed with customized protein-restricted diet (14% protein), which is considered as a sarcopenic featured model. SAR-INT served as the intervention group. Three parameters, namely, muscle mass, grip strength, and physical endurance, were used to confirm the sarcopenic state. All physical parameters deteriorated most in SAR-model and it improved in the SAR-INT group. The impact of physical activity on the SAR-INT group was also evidenced by the improved proliferative potential of MuSCs determined by flow cytometric analysis. Compared with the SAR-model, the SAR-INT exhibited significant improvement in the oxidative capacity of mitochondrial enzymes and increased expression of anti-oxidant proteins, sestrins. In conclusion, physical activity improved physical parameters, MuSC proliferative potential, mitochondrial enzyme oxidative capacity and sestrin expression in sarcopenic animals. Hence, SAR-model in mice can serve as a novel sarcopenic model, physical activity provides scope for improvement in sarcopenic population and sestrin molecule can have a potential implication on sarcopenia.
Dual stochasticity in the cortex as a biologically plausible learning with the most efficient coding
Authors: Teramae Jun-nosuke 
Published: October 2019

AbstractNeurons and synapses in the cerebral cortex behave stochastically. The advantages of such stochastic properties have been proposed in several works, but the relationship and synergy between the stochasticities of neurons and synapses remain largely unexplored. Here, we show that these stochastic features can be inseparably integrated into a simple framework that provides a practical and biologically plausible learning algorithm that consistently accounts for various experimental results, including the most efficient power-law coding of the cortex. The derived algorithm overcomes many of the limitations of conventional learning algorithms of neural networks. As an experimentally testable prediction, we derived the slow retrograde modulation of the excitability of neurons from this algorithm. Because of the simplicity and flexibility of this algorithm, we anticipate that it will be useful in the development of neuromorphic devices and scalable AI chips, and that it will help bridge the gap between neuroscience and machine learning.
Deconstructing the individual steps of vertebrate translation initiation
Authors: Giess Adam , Torres Cleuren Yamila N. , Tjeldnes Håkon , Krause Maximilian , Bizuayehu Teshome Tilahun , Hiensch Senna , Okon Aniekan , Wagner Carston R. , Valen Eivind 
Published: October 2019

AbstractTranslation initiation is often attributed as the rate determining step of eukaryotic protein synthesis and key to gene expression control1. Despite this centrality the series of steps involved in this process are poorly understood2,3. Here we capture the transcriptome-wide occupancy of ribosomes across all stages of translation initiation, enabling us to characterize the transcriptome-wide dynamics of ribosome recruitment to mRNAs, scanning across 5’ UTRs and stop codon recognition, in a higher eukaryote. We provide mechanistic evidence for ribosomes attaching to the mRNA by threading the mRNA through the small subunit. Moreover, we identify features regulating the recruitment and processivity of scanning ribosomes, redefine optimal initiation contexts and demonstrate endoplasmic reticulum specific regulation of initiation. Our approach enables deconvoluting translation initiation into separate stages and identifying the regulators at each step.
Evolutionary relationships amongMassosporaspp. (Entomophthorales), obligate pathogens of cicadas
Authors: Macias Angie M. , Geiser David M. , Stajich Jason E. , Łukasik Piotr , Veloso Claudio , Bublitz DeAnna C. , Berger Matthew C. , Boyce Greg R. , Hodge Kathie , Kasson Matt T. 
Published: October 2019

AbstractThe fungal genusMassospora(Zoopagomycota: Entomophthorales) includes more than a dozen obligate, sexually transmissible pathogenic species that infect cicadas (Hemiptera) worldwide. At least two species are known to produce psychoactive compounds during infection, which has garnered considerable interest for this enigmatic genus. As with many Entomophthorales, the evolutionary relationships and host associations ofMassosporaspp. are not well understood. The acquisition ofM. diceroproctaefrom Arizona,M. tettigatisfrom Chile, andM. platypediaefrom California and Colorado provided an opportunity to conduct molecular phylogenetic analyses and morphological studies to investigate if these fungi represent a monophyletic group and delimit species boundaries. In a three-locus phylogenetic analysis including the D1–D2 domains of the nuclear 28S rRNA gene (28S),elongation factor 1 alpha-like(EFL), andbeta-tubulin(BTUB),Massosporawas resolved in a strongly supported monophyletic group containing four well-supported genealogically exclusive lineages, based on two of three methods of phylogenetic inference. There was incongruence among the single-gene trees: two methods of phylogenetic inference recovered trees with either the same topology as the 3-gene concatenated tree (EFL), or a basal polytomy (28S, BTUB).Massospora levisporaandM. platypediaeisolates formed a single lineage in all analyses and are synonymized here asM. levispora.Massospora diceroproctaewas sister toM. cicadinain all three single-gene trees and on an extremely long branch relative to the otherMassospora, and even the outgroup taxa, which may reflect an accelerated rate of molecular evolution and/or incomplete taxa sampling. The results of the morphological study presented here indicate that spore measurements may not be phylogenetically or diagnostically informative. Despite recent advances in understanding the ecology ofMassospora, much about its host range and diversity remains unexplored. The emerging phylogenetic framework can provide a foundation for exploring co-evolutionary relationships with cicada hosts and the evolution of behavior-altering compounds.