bluuebunny/crossref_metadata_2025_split huggingface dataset:
Money, Banking, and Financial Markets
Authors: Andolfatto David , Berentsen Aleksander , Martin Fernando M 
Published: September 2019

AbstractThe fact that money, banking, and financial markets interact in important ways seems self-evident. The theoretical nature of this interaction, however, has not been fully explored. To this end, we integrate the Diamond (1997, Journal of Political Economy105, 928–956) model of banking and financial markets with the Lagos and Wright (2005, Journal of Political Economy113, 463–484) dynamic model of monetary exchange—a union that bears a framework in which fractional reserve banks emerge in equilibrium, where bank assets are funded with liabilities made demandable in government money, where the terms of bank deposit contracts are affected by the liquidity insurance available in financial markets, where banks are subject to runs, and where a central bank has a meaningful role to play, both in terms of inflation policy and as a lender of last resort. Among other things, the model provides a rationale for nominal deposit contracts combined with a central bank lender-of-last-resort facility to promote efficient liquidity insurance and a panic-free banking system.
Neonatal platelet count trends during inhaled nitric oxide therapy
Authors: Thom Christopher S , Devine Matthew , Kleinman Stacey , Jensen Erik A , Lambert Michele P , Padula Michael A 
Published: September 2019

AbstractRecent debate has focused on the significance of platelets generated in lung tissue. Here, we retrospectively analyzed platelet count changes in neonates requiring inhaled nitric oxide (iNO) pulmonary vasodilation therapy for pulmonary hypertension. There were no clinically significant changes in platelet count upon iNO initiation or during iNO therapy. Unexpectedly, platelet counts increased after iNO cessation. These findings argue against a clinically meaningful untapped pulmonary repository of megakaryocytes and platelets in this context, although acute platelet count increases might be expected after discontinuing iNO in some patients. Further work is needed to clarify the underlying etiology for these observations, and to better delineate the mechanisms for platelet count increases after recovery from lung injury.
Toxicogenomic identification of repositioned therapy for a monogenic disease
Authors: Kort Eric J. , Sayed Nazish , Liu Chun , Wu Sean M. , Wu Joseph C. , Jovinge Stefan 
Published: September 2019

AbstractThe cost of drug development from initial concept to FDA approval has been estimated to be about 2.6 billion USD.1 This cost precludes development of targeted therapies for rare diseases such as monogenetic cardiomyopathies. As part of the Library of Integrated Network-based Cellular Signatures (LINCS) program funded by the NIH, the Broad Institute of MIT has publicly released transcriptional profiles quantifying the effects of more than 25,000 perturbagens on the expression of 978 genes in up to 77 cell lines.2 Transcriptomics has been shown to be a powerful tool in repurposing drugs3,4 and this dataset affords us the unique opportunity to systematically identify small molecule mimics or inhibitors of specific genes, thereby identifying novel treatments for genetic disorders. In this report, we take this approach to identify a novel drug therapy for a monogenic form of familial dilated cardiomyopathy with the transcriptional profile of FDA approved drugs. This approach could potentially be replicated for a wide range of monogenic diseases.
Food supplementation affects gut microbiota and immunological resistance to parasites in a wild bird species
Authors: Knutie Sarah A. 
Published: September 2019

AbstractSupplemental feeding can increase the overall health of animals but also can have varying consequences for animals dealing with parasites. Furthermore, the mechanism mediating the effect of food supplementation on host-parasite interactions remains poorly understood.The goal of the study was to determine the effect of food supplementation on host defenses against parasitic nest flies and whether host gut microbiota, which can affect immunity, potentially mediates these relationships. In a fully crossed design, I experimentally manipulated the abundance of parasitic nest flies (Protocalliphora sialia) and food availability then characterized the gut microbiota, immune responses, and nest parasite abundance of nestling eastern bluebirds (Sialia sialis).Food supplemented birds had 75% fewer parasites than unsupplemented birds. Parasite abundance decreased throughout the breeding season for unsupplemented birds, but abundance did not change throughout the season for supplemented birds. Food supplementation increased overall fledging success. Parasitism had a sublethal effects on blood loss, but food supplementation mitigated these effects by increasing parasite resistance via the nestling IgY antibody response.Food supplementation increased the gut bacterial diversity in nestlings, which was negatively related to parasite abundance. Food supplementation also increased the relative abundance ofClostridiumspp. in nestlings, which was positively related to their antibody response and negatively related to parasite abundance.Synthesis and applications. Overall, these results suggest that food supplementation, especially early in the breeding season, increases resistance to parasitism during the early life stage of the host, which could be mediated by the effect of supplementation on the gut microbiota. Wildlife food supplementation is a common pastime for humans worldwide and therefore it is important to determine the consequences of this activity on animal health. Furthermore, supplemental feeding could induce resistance to detrimental parasites (e.g. invasive parasites) in hosts when management of the parasite is not immediately possible.
High-resolution Expression Profiling of Selected Gene Sets during Plant Immune Activation
Authors: Ding Pingtao , Ngou Bruno Pok Man , Furzer Oliver J. , Sakai Toshiyuki , Shrestha Ram Krishna , MacLean Dan , Jones Jonathan D. G. 
Published: September 2019

SUMMARYSequence capture followed by next-generation sequencing has broad applications in cost-effective exploration of biological processes at high resolution [1, 2]. Genome-wide RNA sequencing (RNA-seq) over a time course can reveal the dynamics of differential gene expression. However, in many cases, only a limited set of genes are of interest, and are repeatedly used as markers for certain biological processes. Sequence capture can help generate high-resolution quantitative datasets to assess changes in abundance of selected genes. We previously used sequence capture to accelerate Resistance gene cloning [1, 3, 4], investigate immune receptor gene diversity [5] and investigate pathogen diversity and evolution [6, 7].The plant immune system involves detection of pathogens via both cell-surface and intracellular receptors. Both receptor classes can induce transcriptional reprogramming that elevates disease resistance [8]. To assess differential gene expression during plant immunity, we developed and deployed quantitative sequence capture (CAP-I). We designed and synthesized biotinylated single-strand RNA bait libraries targeted to a subset of defense genes, and generated sequence capture data from 99 RNA-seq libraries. We built a data processing pipeline to quantify the RNA-CAP-I-seq data, and visualize differential gene expression. Sequence capture in combination with quantitative RNA-seq enabled cost-effective assessment of the expression profile of a specified subset of genes. Quantitative sequence capture is not limited to RNA-seq or any specific organism and can potentially be incorporated into automated platforms for high-throughput sequencing.
scClassify: hierarchical classification of cells
Authors: Lin Yingxin , Cao Yue , Kim Hani J , Salim Agus , Speed Terence P. , Lin Dave , Yang Pengyi , Yang Jean Yee Hwa 
Published: September 2019

AbstractCell type identification is a key computational challenge in single-cell RNA-sequencing (scRNA-seq) data. To capitalize on the large collections of well-annotated scRNA-seq datasets, we present scClassify, a hierarchical classification framework based on ensemble learning. scClassify can identify cells from published scRNA-seq datasets more accurately and more finely than in the original publications. We also estimate the cell number needed for accurate classification anywhere in a cell type hierarchy.
Natural Epiallelic Variation is Associated with Quantitative Resistance to the PathogenPlasmodiophora Brassicae
Authors: Liégard Benjamin , Gravot Antoine , Quadrana Leandro , Aigu Yoann , Bénéjam Juliette , Lariagon Christine , Lemoine Jocelyne , Colot Vincent , Manzanares-Dauleux Maria J. , Jubault Mélanie 
Published: September 2019

AbstractClubroot caused by the protistPlasmodiophora brassicaeis a major disease affecting cultivatedBrassicaceae. Here, we uncover the existence of a natural epigenetic variation that is associated with partial resistance to clubroot inArabidopsis,by using QTL fine mapping followed by extensive DNA sequence and methylation analyses. We show that at QTLPb-At5.2, DNA methylation variation is extensive across accessions and strictly correlates with expression variation of the two neighboring genes At5g47260 and At5g47280, which encode NLR-immune receptors. Moreover, these natural variants are stably inherited and are not consistently associated with any nucleotide variation. These findings suggest a direct role for epigenetic variation in quantitative resistance of plants to pathogen attacks.
Monotherapy efficacy of BBB-permeable small molecule activators of PP2A in glioblastoma
Authors: Merisaari Joni , Denisova Oxana V. , Doroszko Milena , Le Joncour Vadim , Johansson Patrik , Leenders William P.J. , Kastrinsky David B. , Zaware Nilesh , Narla Goutham , Laakkonen Pirjo , Nelander Sven , Ohlmeyer Michael , Westermarck Jukka 
Published: September 2019

AbstractGlioblastoma (GB) is a fatal disease in which most targeted therapies have clinically failed. However, pharmacological reactivation of tumor suppressors has not been thoroughly studied as yet as a GB therapeutic strategy. Tumor suppressor Protein Phosphatase 2A (PP2A), is inhibited by non-genetic mechanisms in GB, and thus it would be potentially amendable for therapeutic reactivation. Here we demonstrate, that small molecule activators of PP2A (SMAPs), NZ-8-061 and DBK-1154, effectively cross the in vitro model of blood-brain barrier (BBB), and in vivo partition to mouse brain tissue after oral dosing. In vitro, SMAPs exhibit robust cell killing activity against five established GB cell lines, and nine patient-derived primary glioma cell lines. Collectively these cell lines have heterogenous genetic background, kinase inhibitor resistance profile, and stemness properties; and they represent different clinical GB subtypes. Oral dosing of either of the SMAPs significantly reduced growth of infiltrative intracranial GB tumors. DBK-1154, with both higher degree of brain/blood distribution, and more potent in vitro activity against all tested GB cell lines, also significantly increased survival of mice bearing orthotopic GB xenografts. In summary, this report presents a proof-of-principle data for BBB-permeable tumor suppressor reactivation therapy for glioblastoma cells of heterogenous molecular background.
FOCAL3D: A 3-dimensional clustering package for single-molecule localization microscopy
Authors: Nino D. , Djayakarsana D. , Milstein J. N. 
Published: September 2019

Single-molecule localization microscopy (SMLM) yields an image resolution 1-2 orders of magnitude below that of conventional light microscopy, resolving fine details on intracellular structure and macromolecular organization. The massive pointillistic data sets generated by SMLM require the development of new and highly efficient quantification tools. Density based clustering algorithms, such as DBSCAN, can provide spatial statistics on protein/nucleic acid aggregation or dispersion while explicitly identifying macromolecular clusters. The performance of DBSCAN, however, is typically dependent upon an arbitrary, or at least highly subjective, parametric tuning of the algorithm. Moreover, DBSCAN can be computationally expensive, which makes it arduous to evaluate on large image stacks. This is all the more important in 3-dimensions where there exist limited alternatives for quantifying clustering in SMLM data, and where a 2-dimensional analysis of true 3-dimensional data may give rise to image artefacts. We have developed an open-source software package in Python for both identifying and quantifying spatial clustering in 3-dimensional SMLM datasets. FOCAL3D is an extension of our previously developed, 2-dimensional, grid based clustering algorithm FOCAL. FOCAL3D provides a highly efficient way to spatially cluster SMLM datasets, scaling linearly with the number of localizations, and the algorithmic parameters may be systematically optimized so that the resulting analysis is insensitive to variation over a range of parameter choices. We initially validate the performance and parametric insensitivity of FOCAL3D on simulated datasets, then apply the algorithm to 3-dimensional, astigmatic dSTORM images of the nuclear pore complex in human osteosarcoma cells.The data and software package are available at: http://www.utm.utoronto.ca/milsteinlab/software/
Coordinated multiplexing of information about separate objects in visual cortex
Authors: Jun Na Young , Ruff Douglas A. , Kramer Lily E. , Bowes Brittany , Tokdar Surya T , Cohen Marlene R , Groh Jennifer M 
Published: September 2019

AbstractSensory receptive fields are large enough that they can contain more than one perceptible stimulus. How, then, can the brain encode information abouteachof the stimuli that may be present at a given moment? We recently showed that when more than one stimulus is present, single neurons can fluctuate between coding one vs. the other(s) across some time period, suggesting a form of neural multiplexing of different stimuli (Caruso et al., 2018). Here we investigate (a) whether such coding fluctuations occur in early visual cortical areas; (b) how coding fluctuations are coordinated across the neural population; and (c) how coordinated coding fluctuations depend on the parsing of stimuli into separate vs. fused objects. We found coding fluctuations do occur in macaque V1 but only when the two stimuli form separate objects. Such separate objects evoked a novel pattern of V1 spike count (“noise”) correlations involving distinct distributions of positive and negative values. This bimodal correlation pattern was most pronounced among pairs of neurons showing the strongest evidence for coding fluctuations or multiplexing. Whether a given pair of neurons exhibited positive or negative correlations depended on whether the two neurons both responded better to the same object or had different object preferences. Distinct distributions of spike count correlations based on stimulus preferences were also seen in V4 for separate objects but not when two stimuli fused to form one object. These findings suggest multiple objects evoke different response dynamics than those evoked by single stimuli, lending support to the multiplexing hypothesis and suggesting a means by which information about multiple objects can be preserved despite the apparent coarseness of sensory coding.Significance StatementHow the brain separates information about multiple objects despite overlap in the neurons responsive to each item is not well understood. Here we show that some neurons in V1 exhibit coding fluctuations in response to two objects, and that these coding fluctuations are coordinated at the population level in ways that are not observed for single objects. Broadly similar results were obtained in V4. These response dynamics lend support to the hypothesis that information about individual objects may be multiplexed across the neural population, preserving information about each item despite the coarseness of sensory coding.
A spatial genomic approach identifies time lags and historic barriers to gene flow in a rapidly fragmenting Appalachian landscape
Authors: Maigret Thomas A. , Cox John J. , Weisrock David W. 
Published: September 2019

AbstractThe resolution offered by genomic data sets coupled with recently developed spatially informed analyses are allowing researchers to quantify population structure at increasingly fine temporal and spatial scales. However, uncertainties regarding data set size and quality thresholds and the time scale at which barriers to gene flow become detectable have limited both empirical research and conservation measures. Here, we used restriction site associated DNA sequencing to generate a large SNP data set for the copperhead snake (Agkistrodon contortrix) and address the population genomic impacts of recent and widespread landscape modification across an approximately 1000 km2 region of eastern Kentucky. Nonspatial population-based assignment and clustering methods supported little to no population structure. However, using individual-based spatial autocorrelation approaches we found evidence for genetic structuring which closely follows the path of a historic highway which experienced high traffic volumes from ca. 1920 to 1970. We found no similar spatial genomic signatures associated with more recently constructed highways or surface mining activity, though a time lag effect may be responsible for the lack of any emergent spatial genetic patterns. Subsampling of our SNP data set suggested that similar results could be obtained with as few as 250 SNPs, and thresholds for missing data exhibited limited impacts on the spatial patterns we detected outside of very strict or permissive extremes. Our findings highlight the importance of temporal factors in landscape genetics approaches, and suggest the potential advantages of large genomic data sets and fine-scale, spatially-informed approaches for quantifying subtle genetic patterns in temporally complex landscapes.
The Panama Canal after a century of human impacts
Authors: Salgado Jorge , Vélez María I. , González-Arango Catalina , Rose Neil L. , Yang Handong , Huguet Carme , Camacho Juan , O’Dea Aaron 
Published: September 2019

AbstractLarge tropical river dam projects are set to accelerate over the forthcoming decades to satisfy growing demand for energy, irrigation and flood control. When tropical rivers are dammed, the immediate impacts are well studied, but the long-term (decades-centuries) consequences of impoundment remain poorly known. Here, we gather historical and paleoecological data from Gatun Lake, formed by the building of the Gatun Dam (Panama Canal, Panamá) over 100 years ago, to reconstruct the limnological evolution of the system in response to individual and linked stressors (river damming, forest flooding, deforestation, invasive species, pollution and hydro-climate). We found that after a century of dam construction parallels associated with the natural hydrological functioning of river floodplains persist. Hence, hydrology remains the most important temporal structural factor positively stimulating primary productivity, deposition of new minerals, and reduction of water transparency during wet periods. During dry periods, clear water and aerobic conditions prevail and nutrients transform into available forms in the detrital-rich reductive sediments. We highlight the importance of climate change as an ultimate rather than proximate anthropogenic factor for sustainable management options of tropical dams.
Studying Spatial Memory in Augmented and Virtual reality
Authors: Maidenbaum Shachar , Patel Ansh , Garlin Isaiah , Jacobs Josh 
Published: September 2019

AbstractSpatial memory is a crucial part of our lives. Spatial memory research and rehabilitation in humans is typically performed either in real environments, which is challenging practically, or in Virtual Reality (VR), which has limited realism. Here we explored the use of Augmented Reality (AR) for studying spatial cognition. AR combines the best features of real and VR paradigms by allowing subjects to learn spatial information in a flexible fashion while walking through a real-world environment. To compare these methods, we had subjects perform the same spatial memory task in VR and AR settings. Although subjects showed good performance in both, subjects reported that the AR task version was significantly easier, more immersive, and more fun than VR. Importantly, memory performance was significantly better in AR compared to VR. Our findings validate that integrating AR can lead to improved techniques for spatial memory research and suggest their potential for rehabilitation.HighlightsWe built matching spatial memory tasks in VR and ARSubjectively, subjects find the AR easier, more immersive and more funObjectively, subjects are significantly more accurate in AR compared to VRPointing based tasks did not fully show the same advantagesOnly AR walking significantly correlated with SBSoD, suggesting mobile AR better captures more natural spatial performance
Δ9-Tetrahydrocannabinol (THC) impairs visual working memory performance: A randomized crossover trial
Authors: Adam Kirsten C. S. , Doss Manoj K. , Pabon Elisa , Vogel Edward K. , de Wit Harriet 
Published: September 2019

AbstractWith the increasing prevalence of legal cannabis use and availability, there is an urgent need to identify cognitive impairments related to its use. It is widely believed that cannabis, or its main psychoactive component Δ9-tetrahydrocannabinol (THC), impairs working memory, i.e., the ability to temporarily hold information in mind. However, our review of the literature yielded surprisingly little empirical support for an effect of THC or cannabis on working memory. We thus conducted a study with 3 main goals: (1) quantify the effect of THC on visual working memory in a well-powered sample (2) test the potential role of cognitive effects (mind wandering and metacognition) in disrupting working memory, and (3) demonstrate how insufficient sample size and task duration reduce the likelihood of detecting a drug effect. We conducted two double-blind, randomized crossover experiments in which healthy adults (N=23, 23) performed a reliable and validated visual working memory task (the “Discrete Whole-Report task”, 90 trials) after administration of THC (7.5 and/or 15 mg oral) or placebo. We also assessed self-reported ‘mind wandering’ (Exp 1) and metacognitive accuracy about ongoing task performance (Exp 2). THC impaired working memory performance (d = .65), increased mind wandering (Exp 1), and decreased metacognitive accuracy about task performance (Exp 2). Thus, our findings indicate that THC does impair visual working memory, and that this impairment may be related to both increased mind-wandering and decreased monitoring of task performance. Finally, we used a down-sampling procedure to illustrate the effects of task length and sample size on power to detect the acute effect of THC on working memory.