bluuebunny/crossref_metadata_2025_split huggingface dataset:
Migraine aura, a predictor of near-death experiences in a crowdsourced study
Authors: Kondziella Daniel , Olsen Markus Harboe , Lemale Coline L. , Dreier Jens P. 
Published: October 2019

AbstractBackgroundNear-death experiences (NDE) occur with imminent death and in situations of stress and danger but are poorly understood. Evidence suggests that NDE are associated with rapid eye movement (REM) sleep intrusion, a feature of narcolepsy. Previous studies further found REM abnormalities and an increased frequency of dream-enacting behavior in migraine patients, as well as an association between migraine with aura and narcolepsy. We therefore investigated if NDE are more common in people with migraine aura.MethodsWe recruited 1037 laypeople from 35 countries via a crowdsourcing platform. Reports were validated using the Greyson NDE Scale.ResultsEighty-one of 1037 participants had NDE (7.8%; CI 6.3-9.7%). There were no significant associations between NDE and age (p>0.6, t-test independent samples) or gender (p>0.9, chi-square test). The only significant association was between NDE and migraine aura: Forty-eight (6.1%) of 783 subjects without migraine aura and 33 (13.0%) of 254 subjects with migraine aura had NDE (p<0.001, chi-square test, odds ratio (OR) = 2.29). In multiple logistic regression analysis, migraine aura remained significant after adjustment for age (p≤0.001, OR 2.31), gender (p<0.001, OR 2.33), or both (p<0.001, OR 2.33).ConclusionsIn our sample, migraine aura was a predictor of NDE. This indirectly supports the association between NDE and REM intrusion and might have implications for the understanding of NDE, because a variant of spreading depolarization (SD), terminal SD, occurs in humans at the end of life, while a short-lasting variant of SD is considered the pathophysiological correlate of migraine aura.
Towards an information theory of quantitative genetics
Authors: Galas David J. , Kunert-Graf James , Uechi Lisa , Sakhanenko Nikita A. 
Published: October 2019

AbstractQuantitative genetics has evolved dramatically in the past century, and the proliferation of genetic data, in quantity as well as type, enables the characterization of complex interactions and mechanisms beyond the scope of its theoretical foundations. In this paper, we argue that revisiting the framework for analysis is important and we begin to lay the foundations of an alternative formulation of quantitative genetics based on information theory. Information theory can provide sensitive and unbiased measures of statistical dependencies among variables, and it provides a natural mathematical language for an alternative view of quantitative genetics. In previous work we examined the information content of discrete functions and applied this approach and methods to the analysis of genetic data. In this paper we present a framework built around a set of relationships that both unifies the information measures for the discrete functions and uses them to express key quantitative genetic relationships. Information theory measures of variable interdependency are used to identify significant interactions, and a general approach is described for inferring functional relationships within genotype and phenotype data. We present information-based measures of the genetic quantities: penetrance, heritability and degrees of statistical epistasis. Our scope here includes the consideration of both two- and three-variable dependencies and independently segregating variants, which captures additive effects, genetic interactions, and two phenotype pleiotropy. This formalism and the theoretical approach naturally applies to higher multi-variable interactions and complex dependencies, and can be adapted to account for population structure, linkage and non-randomly segregating markers. This paper thus focuses on presenting the initial groundwork for a full formulation of quantitative genetics based on information theory.
Linking influenza virus evolution within and between human hosts
Authors: Xue Katherine S. , Bloom Jesse D. 
Published: October 2019

AbstractInfluenza viruses rapidly diversify within individual human infections. Several recent studies have deep-sequenced clinical influenza infections to identify viral variation within hosts, but it remains unclear how within-host mutations fare in the global viral population. Here, we compare viral variation within and between hosts to link influenza’s evolutionary dynamics across scales. Synonymous sites evolve at similar rates at both scales, indicating that global evolution at these putatively neutral sites results from the accumulation of within-host variation. However, nonsynonymous mutations are depleted in global viral populations compared to within hosts, suggesting that selection purges many of the protein-altering changes that arise within hosts. The exception is at antigenic sites, where selection detectably favors nonsynonymous mutations at the global scale, but not within hosts. These results suggest that selection against deleterious mutations and selection for antigenic change are the main forces that transform influenza’s within-host genetic variation into global evolution.
Absolute quantification of transcription factors reveals principles of gene regulation in erythropoiesis
Authors: Gillespie Mark A. , Palii Carmen G. , Sanchez-Taltavull Daniel , Shannon Paul , Longabaugh William J.R. , Downes Damien J. , Sivaraman Karthi , Hughes Jim R. , Price Nathan D. , Perkins Theodore J. , Ranish Jeffrey A. , Brand Marjorie 
Published: October 2019

SummaryDynamic cellular processes such as differentiation are driven by changes in the abundances of transcription factors (TFs). Yet, despite years of studies we still do not know the protein copy number of TFs in the nucleus. Here, by determining the absolute abundances of 103 TFs and co-factors during the course of human erythropoiesis, we provide a dynamic and quantitative scale for TFs in the nucleus. Furthermore, we establish the first Gene Regulatory Network of cell fate commitment that integrates temporal protein stoichiometry data with mRNA measurements. The model revealed quantitative imbalances in TFs cross-antagonistic relationships that underlie lineage determination. Finally, we made the surprising discovery that in the nucleus, corepressors are dramatically more abundant than coactivators at the protein, but not at the RNA level, with profound implications for understanding transcriptional regulation. These analyses provide a unique quantitative framework to understand transcriptional regulation of cell differentiation in a dynamic context.
Cryopreservation impairs cytotoxicity and migration of NK cells in 3-D tissue: Implications for cancer immunotherapy
Authors: Mark Christoph , Czerwinski Tina , Roessner Susanne , Mainka Astrid , Hörsch Franziska , Heublein Lucas , Winterl Alexander , Sanokowski Sebastian , Richter Sebastian , Bauer Nina , Schuler Gerold , Fabry Ben , Voskens Caroline J. 
Published: October 2019

AbstractNatural killer (NK) cells are important effector cells in the immune response to cancer. Clinical trials on adoptively transferred NK cells in patients with solid tumors, however, have thus far been unsuccessful. As NK cells need to pass stringent safety evaluation for clinical use, the cells are cryopreserved to bridge the necessary evaluation time. While a degranulation assay confirms the ability of cryopreserved NK cells to kill target cells, we find a significant decrease of cytotoxicity after cryopreservation in a chromium release assay. We complement these standard assays with measurements of NK cell motility and cytotoxicity in 3-dimensional (3-D) collagen gels that serve as a substitute for connective tissue. We find a 5.6 fold decrease of cytotoxicity after cryopreservation and establish that this is mainly caused by a 6-fold decrease in the fraction of motile NK cells. These findings may explain the persistent failure of NK cell therapy in patients with solid tumors and highlight the crucial role of a 3-D environment for testing NK cell function.SynopsisCryopreservation of natural killer (NK) cells dramatically impairs their motility and cytotoxicity in tissue. This finding may explain the persistent failure of clinical trials in which NK cell therapy is used for treating solid tumors.
Model-based and model-free analyses of the neural correlates of tongue movements
Authors: Sörös Peter , Schäfer Sarah , Witt Karsten 
Published: October 2019

ABSTRACTThe tongue performs movements in all directions to subserve its diverse functions in chewing, swallowing, and speech production. The aims of the present study were twofold: using task-based functional MRI in a group of 17 healthy young participants, we studied (1) potential differences in the cerebral control of frontal, horizontal, and vertical tongue movements and (2) potential inter-individual differences in tongue motor control. To investigate differences between different tongue movements, we performed voxel-wise multiple linear regressions. To investigate inter-individual differences, we applied a novel approach, spatio-temporal filtering of independent components. For this approach, individual functional data sets were decomposed into spatially independent components and corresponding time courses using ICA. A temporal filter (correlation with the expected brain response) was used to identify independent components time-locked to the tongue motor task. A spatial filter (cross-correlation with established neurofunctional systems) was used to identify brain activity not time-locked to the task. Our results confirm the importance of an extended bilateral cortical and subcortical network for the control of tongue movements, including the lateral primary sensorimotor cortex, supplementary motor cortex, anterior cingulate gyrus, insula, basal ganglia, thalamus, and cerebellum. Frontal tongue movements, highly overlearned movements related to speech production, showed less activity in parts of the frontal and parietal lobes compared to horizontal and vertical movements and greater activity in parts of the left frontal and temporal lobes compared to vertical movements. The investigation of inter-individual differences revealed a component representing the tongue primary sensorimotor cortex time-locked to the task in all participants. Using the spatial filter, we found the default mode network in 16 of 17 participants, the left fronto-parietal network in 16, the right fronto-parietal network in 8, and the executive control network in 4 participants. Further detailed analyses of speech-related tongue movements are warranted to increase our understanding of tongue motor control as a crucial part of articulation. Spatio-temporal filtering of independent components appears to be a powerful approach to study inter-individual differences in task-based functional MRI. This approach may be particularly useful for the assessment of individual patients and may be related to individual clinical, behavioral, and genetic information.
Drivers of plant traits and forest functional composition in coastal plant communities of the Atlantic Forest
Authors: Lourenço Jehová , Newman Erica A. , Ventura Jose A. , Milanez Camilla Rozindo Dias , Thomaz Luciana Dias , Wandekoken Douglas Tinoco , Enquist Brian J. 
Published: October 2019

AbstractThe severe deforestation of Brazil’s Atlantic Forest and increasing effects of climate change underscore the need to understand how tree species respond to climate and soil drivers. We studied 42 plots of coastal restinga forest, which is highly diverse and spans strong environmental gradients. We determined the forest physiognomy and functional composition, which are physical properties of a community that respond to climate and soil properties, to elucidate which factors drive community-level traits. To identify the most important environmental drivers of coastal Atlantic forest functional composition, we performed a forest inventory of all plants of diameter 5 cm and above. We collected wood samples and leaves from ∼85% of the most abundant plant species and estimated height, aboveground biomass (AGB), and basal area of individual plants, and the community-weighted specific leaf area (SLA). In addition to plant traits, we measured water table depth and 25 physicochemical soil parameters. We then parameterized several models for different hypotheses relating the roles of nutrients and soil to tropical forest diversity and functioning, as represented by plant traits. Hypotheses were formalized via generalized additive models and piecewise structural equation models. Water table depth, soil coarseness, potential acidity, sodium saturation index (SSI) and aluminum concentration were all components of the best models for AGB, height, basal area, and trait composition. Among the 25 environmental parameters measured, those related to water availability (water table depth and coarse sand), followed by potential acidity, SSI, and aluminum consistently emerged as the most important drivers of forest physiognomy and functional composition. Increases in water table depth, coarse sand, and soil concentration of aluminum negatively impacted all the measured functional traits, whereas SSI had a positive effect on AGB and plant height. These results suggest that sodium is not merely tolerated by Atlantic Forest restinga plant communities, but is important to their structure and functioning. Presence of aluminum in the soil had a complex relationship to overall basal area, possibly mediated by soil organic matter.
Combined Atomic Force Microscope and Volumetric Light Sheet System for Mechanobiology
Authors: Nelsen E. , Hobson C.M. , Kern M.E. , Hsiao J.P. , O’Brien E.T. , Watanabe T. , Condon B.M. , Boyce M. , Grinstein S. , Hahn K.M. , Falvo M.R. , Superfine R. 
Published: October 2019

ABSTRACTThe central goals of mechanobiology are to understand how cells generate force and how they respond to environmental mechanical stimuli. A full picture of these processes requires high-resolution, volumetric imaging with time-correlated force measurements. Here we present an instrument that combines an open-top, single-objective light sheet fluorescence microscope with an atomic force microscope (AFM), providing simultaneous volumetric imaging with high spatiotemporal resolution and high dynamic range force capability (10 pN – 100 nN). With this system we have captured lysosome trafficking, vimentin nuclear caging, and actin dynamics on the order of one second per volume. To showcase the unique advantages of combining Line Bessel light sheet imaging with AFM, we measured the forces exerted by a macrophage during FcɣR-mediated phagocytosis while performing both sequential two-color, fixed plane and volumetric imaging of F-actin. This unique instrument allows for a myriad of novel studies investigating the coupling of cellular dynamics and mechanical forces.
Feature-based Molecular Networking in the GNPS Analysis Environment
Authors: Nothias Louis Felix , Petras Daniel , Schmid Robin , Dührkop Kai , Rainer Johannes , Sarvepalli Abinesh , Protsyuk Ivan , Ernst Madeleine , Tsugawa Hiroshi , Fleischauer Markus , Aicheler Fabian , Aksenov Alexander , Alka Oliver , Allard Pierre-Marie , Barsch Aiko , Cachet Xavier , Caraballo Mauricio , Da Silva Ricardo R. , Dang Tam , Garg Neha , Gauglitz Julia M. , Gurevich Alexey , Isaac Giorgis , Jarmusch Alan K. , Kameník Zdeněk , Kang Kyo Bin , Kessler Nikolas , Koester Irina , Korf Ansgar , Gouellec Audrey Le , Ludwig Marcus , Christian Martin H. , McCall Laura-Isobel , McSayles Jonathan , Meyer Sven W. , Mohimani Hosein , Morsy Mustafa , Moyne Oriane , Neumann Steffen , Neuweger Heiko , Nguyen Ngoc Hung , Nothias-Esposito Melissa , Paolini Julien , Phelan Vanessa V. , Pluskal Tomáš , Quinn Robert A. , Rogers Simon , Shrestha Bindesh , Tripathi Anupriya , van der Hooft Justin J.J. , Vargas Fernando , Weldon Kelly C. , Witting Michael , Yang Heejung , Zhang Zheng , Zubeil Florian , Kohlbacher Oliver , Böcker Sebastian , Alexandrov Theodore , Bandeira Nuno , Wang Mingxun , Dorrestein Pieter C. 
Published: October 2019

AbstractMolecular networking has become a key method used to visualize and annotate the chemical space in non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and quantitative interpretation are currently limited. Therefore, we created Feature-based Molecular Networking (FBMN) as a new analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure. FBMN leverages feature detection and alignment tools to enhance quantitative analyses and isomer distinction, including from ion-mobility spectrometry experiments, in molecular networks.
Streptococcus equi subsp. zooepidemicus associated with sudden death of swine in North America
Authors: de Costa Matheus O. , Lage Brad 
Published: October 2019

AbstractHistorically described as a commensal of the swine upper-respiratory tract, Streptococcus equi subsp. zooepidemicus was only reported previously in Asia as an important swine pathogen. Here we report the isolation and whole genome characterization of Streptococcus equi subsp. zooepidemicus associated with a sudden death outbreak in pigs in North America.
Mapping Mesoscale Axonal Projections in the Mouse Brain Using A 3D Convolutional Network
Authors: Friedmann Drew , Pun Albert , Adams Eliza L , Lui Jan H , Kebschull Justus M , Grutzner Sophie M , Castagnola Caitlin , Tessier-Lavigne Marc , Luo Liqun 
Published: October 2019

AbstractThe projection targets of a neuronal population are a key feature of its anatomical characterization. Historically, tissue sectioning, confocal microscopy, and manual scoring of specific regions of interest have been used to generate coarse summaries of mesoscale projectomes. We present here TrailMap, a 3D convolutional network for extracting axonal projections from intact cleared mouse brains imaged by light-sheet microscopy. TrailMap allows region-based quantification of total axon content in large and complex 3D structures after registration to a standard reference atlas. The identification of axonal structures as thin as one voxel benefits from data augmentation but also requires a loss function that tolerates errors in annotation. A network trained with volumes of serotonergic axons in all major brain regions can be generalized to map and quantify axons from thalamocortical, deep cerebellar, and cortical projection neurons, validating transfer learning as a tool to adapt the model to novel categories of axonal morphology. Speed of training, ease of use, and accuracy improve over existing tools without a need for specialized computing hardware. Given the recent emphasis on genetically and functionally defining cell types in neural circuit analysis, TrailMap will facilitate automated extraction and quantification of axons from these specific cell types at the scale of the entire mouse brain, an essential component of deciphering their connectivity.
Some Statistical Consideration in Transcriptome-Wide Association Studies
Authors: Xue Haoran , Pan Wei ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: October 2019

AbstractTranscriptome-wide association study (TWAS) has become popular in integrating a reference eQTL dataset with an independent main GWAS dataset to identify (putatively) causal genes, shedding mechanistic insights to biological pathways from genetic variants to a GWAS trait mediated by gene expression. Statistically TWAS is a (two-sample) 2-stage least squares (2SLS) method in the framework of instrumental variables analysis for causal inference: in Stage 1 it uses the reference eQTL data to impute a gene’s expression for the main GWAS data, then in Stage 2 it tests for association between the imputed gene expression and the GWAS trait; if an association is detected in Stage 2, a (putatively) causal relationship between the gene and the GWAS trait is claimed. If a non-linear model or a generalized linear model (GLM) is fitted in Stage 2 (e.g. for a binary GWAS trait), it is known that using only imputed gene expression, as in standard TWAS, in general does not lead to a consistent (i.e. asymptotically unbiased) estimate for the causal effect; accordingly, a variation of 2SLS, called two-stage residual inclusion (2SRI), has been proposed to yield better estimates (e.g. being consistent under suitable conditions). Our main goal is to investigate whether it is necessary or even better to apply 2SRI, instead of the standard 2SLS. In addition, due to the use of imputed gene expression (i.e. with measurement errors), it is known that in general some correction to the standard error estimate of the causal effect estimate has to be applied, while in the standard TWAS no correction is applied. Is this an issue? We also compare one-sample 2SLS with two-sample 2SLS (i.e. the standard TWAS). We used the ADNI data and simulated data mimicking the ADNI data to address the above questions. At the end, we conclude that, in practice with the large sample sizes and small effect sizes of genetic variants, the standard TWAS performs well and is recommended.
The kinase inhibitor AT9283 selectively kills colorectal cancer cells with hyperactive NRF2
Authors: Torrente Laura , Maan Gunjit , Casares Laura , Jackson Angus , Honda Tadashi , Wells Geoff , Kulesskiy Evgeny , Saarela Jani , Dinkova-Kostova Albena T. , de la Vega Laureano 
Published: October 2019

ABSTRACTAberrant hyperactivation of NRF2 is a common event in many tumour types and associates with resistance to therapy and poor patient prognosis. The identification of ways to overcome the protection provided by NRF2 and selectively kill cancer cells addicted to NRF2 is a desirable goal. Exploiting the CRISPR/Cas9 technology, we generated colorectal cancer cell lines with hyperactive NRF2, and used them to perform a drug screen. We identified AT9283, an Aurora kinase inhibitor, for its selectivity towards killing cancer cells with hyperactive NRF2 as a consequence to either genetic or pharmacological activation. Our results show that hyperactivation of NRF2 presents a potential vulnerability that could be therapeutically exploited, and further suggest that AT9283, a drug that is currently in clinical trials, holds promise for the treatment of tumours with hyperactive NRF2.HighlightsWe present a new model for NRF2 hyperactivation in colorectal cancer cells.AT9283 selectively kills cancer cells with hyperactive NRF2Both genetic and pharmacological activation of NRF2 sensitise cells to AT9283