bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multitrait genetic-phenotype associations to connect disease variants and biological mechanisms
Authors: Julienne Hanna , Laville Vincent , McCaw Zachary R. , He Zihuai , Guillemot Vincent , Lasry Carla , Ziyatdinov Andrey , Vaysse Amaury , Lechat Pierre , Ménager Hervé , Goff Wilfried Le , Dube Marie-Pierre , Kraft Peter , Ionita-Laza Iuliana , Vilhjálmsson Bjarni J. , Aschard Hugues 
Published: June 2020

AbstractBackgroundGenome-wide association studies (GWAS) uncovered a wealth of associations between common variants and human phenotypes. These results, widely shared across the scientific community as summary statistics, fostered a flurry of secondary analysis: heritability and genetic correlation assessment, pleiotropy characterization and multitrait association test. Amongst these secondary analyses, a rising new field is the decomposition of multitrait genetic effects into distinct profiles of pleiotropy.ResultsWe conducted an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link to biological mechanisms. We started by benchmarking multitrait association tests on a large panel of phenotype sets and established theOmnibustest as the most powerful in practice. We detected 322 new associations that were not previously reported by univariate screening. Using independent significant associations, we investigated the breakdown of genetic association into clusters of variants harboring similar multitrait association profile. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how SNPs within clusters can be mapped to biological pathways and disease mechanisms, providing a putative insight for numerous SNPs with unknown biological function. Finally, for the metabolism set, we investigate the link between gene cluster assignment and success of drug targets in random control trials. We report additional uninvestigated drug targets classified by clusters.ConclusionsMultitrait genetic signals can be decomposed into distinct pleiotropy profiles that reveal consistent with pathways databases and random control trials. We propose this method for the mapping of unannotated SNPs to putative pathways.
Coupling between fast and slow oscillator circuits inCancer borealisis temperature compensated
Authors: Powell D.J. , Haddad S.A. , Gorur-Shandilya S. , Marder E. 
Published: June 2020

AbstractCoupled oscillatory circuits are ubiquitous in nervous systems. Given that most biological processes are temperature sensitive, it is remarkable that the neuronal circuits of poikilothermic animals can maintain coupling across a wide range of temperatures. Within the stomatogastric ganglion (STG) of the crab,Cancer borealis, the fast pyloric rhythm (~1Hz) and the slow gastric mill rhythm (~0.1Hz) are precisely coordinated at ~11°C such that there is an integer number of pyloric cycles per gastric mill cycle (integer coupling). Upon increasing temperature from 7-23°C, both oscillators showed similar temperature-dependent increases in cycle frequency, and integer coupling between the circuits was conserved. Thus, although both rhythms show temperature dependent changes in rhythm frequency, the processes that couple these circuits maintain their coordination over a wide range of temperature. Such robustness to temperature changes could be part of a toolbox of processes that enables neural circuits to maintain function despite global perturbations.
Inhibition of Mitochondrial Fission and iNOS in the Dorsal Vagal Complex Protects from Overeating and Weight Gain
Authors: Patel Bianca , New Lauryn , Griffiths Joanne C. , Deuchars Jim , Filippi Beatrice M. 
Published: June 2020

AbstractThe dorsal vagal complex (DVC) senses changes in insulin levels and controls glucose homeostasis, feeding behaviour and body weight. Three days of high-fat diet (HFD) in rats is sufficient to induce insulin resistance in the DVC and impair its ability to regulate feeding behaviour. HFD-feeding is associated with increased mitochondrial fission in the DVC and fission is regulated by dynamin-related protein 1 (Drp1). Higher Drp1 activity can inhibit insulin signalling, although the exact mechanisms controlling body weight remain elusive. Here we show that Drp1 activation in DVC leads to higher body weight in rats and Drp1 inhibition in HFD-fed rats reduced body weight gain, cumulative food intake and adipose tissue, and prevented insulin resistance. Rats expressing active Drp1 in the DVC had higher levels of inducible nitric oxide synthase (iNOS) and knockdown of iNOS in the DVC of HFD-fed rats led to a reduction in body weight gain, cumulative food intake and adipose tissue, and prevented insulin resistance. In obese insulin-resistant animals, inhibition of mitochondrial fission or DVC iNOS knockdown restored insulin sensitivity and decreased food intake, body weight and fat deposition. Finally, we show that inhibiting mitochondrial fission in DVC astrocytes is sufficient to protect rats from developing HFD-dependent insulin resistance, hyperphagia, body weight gain and fat deposition. Our study uncovers new molecular and cellular targets for brain regulation of whole-body metabolism, which could inform new strategies to combat obesity and diabetes.
MAGIC: Mosaic Analysis by gRNA-Induced Crossing-over
Authors: Allen Sarah E. , Koreman Gabriel T. , Sarkar Ankita , Wang Bei , Wolfner Mariana F. , Han Chun 
Published: June 2020

AbstractMosaic animals have provided the platform for many fundamental discoveries in developmental biology, cell biology, and other fields. Techniques to produce mosaic animals by mitotic recombination have been extensively developed inDrosophila melanogasterbut are less common for other laboratory organisms. Here, we reportmosaicanalysis bygRNA-inducedcrossing-over (MAGIC), a new technique for generating mosaic animals based on DNA double-strand breaks produced by CRISPR/Cas9. MAGIC efficiently produces mosaic clones in both somatic tissues and the germline ofDrosophila. Further, by developing a MAGIC toolkit for one chromosome arm, we demonstrate the method’s application in characterizing gene function in neural development and in generating fluorescently marked clones in wild-derivedDrosophilastrains. Eliminating the need to introduce recombinase-recognition sites in the genome, this simple and versatile system simplifies mosaic analysis inDrosophilaand can be applied in any organism that is compatible with CRISPR/Cas9.
LINE-1 expression in cancer correlates with DNA damage response, copy number variation, and cell cycle progression
Authors: McKerrow Wilson , Wang Xuya , Mita Paolo , Cao Song , Grivainis Mark , Ding Li , LaCava John , Boeke Jef , Fenyö David 
Published: June 2020

ABSTRACTRetrotransposons are genomic DNA sequences that are capable of copying themselves to new genomic locations via RNA intermediates; LINE-1 is the only retrotransposon that remains autonomous and active in the human genome. The mobility of LINE-1 is largely repressed in somatic tissues, but LINE-1 is active in many cancers. Recent studies using LINE-1 constructs indicate that host cells activate a DNA damage response (DDR) to repair retrotransposition intermediates and resolve conflicts between LINE-1 and DNA replication. Using multi-omic data from the CPTAC project, we found correlations between LINE-1 expression and ATM-MRN-SMC DDR signalling in endometrial cancer and between LINE-1 and the ATR-CHEK1 pathway in p53 wild type breast cancer. This provides evidence that conflicts between LINE-1 and DNA replication occur in at least some human cancers. Furthermore, LINE-1 expression in these cancers is correlated with the total amount of copy number variation genome wide, indicating that, when active in cancer, pointing to a direct impact of LINE-1 associated DNA damage on genome structure. We also find that, in endometrial and ovarian cancer, LINE-1 expression is correlated with the expression of genes that drive cycle progression including E2F3, PLK1 and Aurora kinase B. This study provides evidence, supporting recent work in model cell lines, of a LINE-1/DDR connection in human tumors and raises the possibility of additional interactions between LINE-1 and the cell cycle.
Ceramic Packaging in Neural Implants
Authors: Shen Konlin , Maharbiz Michel M. 
Published: June 2020

AbstractThe lifetime of neural implants is strongly dependent on packaging due to the aqueous and biochemically aggressive nature of the body. Over the last decade, there has been a drive towards neuromodulatory implants which are wireless and approaching millimeter-scales with increasing electrode count. A so-far unrealized goal for these new types of devices is an in-vivo lifetime comparable to a sizable fraction of a healthy patient’s lifetime (>10-20 years). Existing, approved medical implants commonly encapsulate components in metal enclosures (e.g. titanium) with brazed ceramic inserts for electrode feedthrough. It is unclear how amenable the traditional approach is to the simultaneous goals of miniaturization, increased channel count, and wireless communication. Ceramic materials have also played a significant role in traditional medical implants due to their dielectric properties, corrosion resistance, biocompatibility, and high strength, but are not as commonly used for housing materials due to their brittleness and the difficulty they present in creating complex housing geometries. However, thin film technology has opened new opportunities for ceramics processing. Thin films derived largely from the semiconductor industry can be deposited and patterned in new ways, have conductivities which can be altered during manufacturing to provide conductors as well as insulators, and can be used to fabricate flexible substrates. In this review, we give an overview of packaging for neural implants, with an emphasis on how ceramic materials have been utilized in medical device packaging, as well as how ceramic thin film micromachining and processing may be further developed to create truly reliable, miniaturized, neural implants
Multispecies integrated population model reveals bottom-up dynamics in a seabird predator-prey system
Authors: Quéroué Maud , Barbraud Christophe , Barraquand Frédéric , Turek Daniel , Delord Karine , Pacoureau Nathan , Gimenez Olivier 
Published: June 2020

AbstractAssessing the effects of climate and interspecific relationships on communities is challenging because of the complex interplay between species population dynamics, their interactions, and the need to integrate information across several biological levels (individuals – populations – communities). Usually used to quantify species interactions, integrated population models (IPMs) have recently been extended to communities. These models allow fitting multispecies matrix models to data from multiple sources while simultaneously accounting for various sources of uncertainty in each data source. We used multispecies IPMs accommodating climate conditions to quantify the relative contribution of climate vs. interspecific interactions on demographic parameters, such as survival and breeding success, in the dynamics of a predator-prey system. We considered a stage-structured predator–prey system combining 22 years of capture–recapture data and population counts of two seabirds, the Brown Skua (Catharacta lönnbergi) and its main prey the Blue Petrel (Halobaena caerulea) both breeding on the Kerguelen Islands in the Southern Ocean. Our results showed that climate and predator-prey interactions drive the demography of skuas and petrels in different ways. The breeding success of skuas appeared to be largely driven by the number of petrels and to a lesser extent by intraspecific density-dependence. In contrast, there was no evidence of predation effects on the demographic parameters of petrels, which were affected by oceanographic factors (chlorophyll a and sea surface temperature anomalies). We conclude that bottom-up mechanisms are the main drivers of this skua-petrel system. We discuss the mechanisms by which climate variability and predator-prey relationships may affect the demographic parameters of these seabirds. Taking into account both species interactions and environmental covariates in the same analysis improved our understanding of species dynamics.
Estimating intracranial pressure via low-dimensional models: toward a practical tool for clinical decision support at multi-hour timescales
Authors: Stroh J.N. , Bennett T. , Kheyfets V. , Albers D. 
Published: June 2020

AbstractBroad clinical application of non-invasive intracranial pressure (ICP) monitoring using computational models requires a method of modeling ICP on the basis of easily measured patient data such as radial or brachial arterial blood pressure (ABP). These models may be highly complex, rendering them too slow for clinical and operational use, or may rely on data that is not consistently available. Coupling these models to an upstream vasculature component model decreases data requirements. For the purposes of clinical decision support at multi-hour timescales, two natural choices for model development are to increase intracranial model complexity or to include feedback mechanisms between ICP and vascular model components. We compare the performance of these two approaches by evaluating model estimates against observed ICP in the case of a slow hypertensive event from a publically available dataset. The simpler model with bi-directional feedback requires minimal identifiability and is sufficiently accurate over these timescales, while a more complex is difficult and expensive to identify well enough to be accurate. Furthermore, the bi-directional simple model operates orders of magnitude faster than the more anatomically accurate model when driven by high-resolution ABP. It may also be configured to use lower resolution ABP summary data that is consistently clinically available. The simpler models are fast enough to support future developments such as patient-specific parametrization and assimilation of other clinical data streams which are illustrated during the case of a complex ICP regime for a different patient. We present model comparisons to highlight the advantages of the incorporated simple model and its possible predictive power with further optimization.
Impact of the accuracy of case-based surveillance data on the estimation of time-varying reproduction numbers
Authors: Starnini Michele , Aleta Alberto , Tizzoni Michele , Moreno Yamir 
Published: June 2020

AbstractStudies aimed at characterizing the evolution of COVID-19 disease often rely on case-based surveillance data publicly released by health authorities, that can be incomplete and prone to errors. Here, we quantify the biases caused by the use of inaccurate data in the estimation of the Time-Varying Reproduction Number R(t). By focusing on Italy and Spain, two of the hardest-hit countries in Europe and worldwide, we show that if the symptoms’ onset time-series is inferred from the notification date series, the R(t) curve cannot capture nor describe accurately the early dynamics of the epidemic. Furthermore, the effectiveness of the containment measures that were implemented, such as national lockdowns, can be properly evaluated only when R(t) is estimated using the real time-series of dates of symptoms’ onset. Our findings show that extreme care should be taken when a pivotal quantity like R(t) is used to make decisions and to evaluate different alternatives.
Short Communication: Vitamin D and COVID-19 infection and mortality in UK Biobank
Authors: Hastie Claire E , Pell Jill P , Sattar Naveed 
Published: June 2020

AbstractPurposeVitamin D has been proposed as a potential causal factor in COVID-19 risk. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 mortality, and inpatient confirmed COVID-19 infection, in UK Biobank participants.MethodsUK Biobank recruited 502,624 participants aged 37-73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration, were linked to COVID-19 mortality. Univariable and multivariable Cox proportional hazards regression analyses were performed for the association between 25(OH)D and COVID-19 death, and poisson regression analyses for the association between 25(OH)D and severe COVID-19 infection.ResultsComplete data were available for 341,484 UK Biobank participants, of which 656 had inpatient confirmed COVID-19 infection and 203 died of COVID-19 infection. Vitamin D was associated with severe COVID-19 infection and mortality univariably (mortality HR=0.99; 95% CI 0.98-0.998; p=0.016), but not after adjustment for confounders (mortality HR=0.998; 95% CI=0.99-1.01; p=0.696).ConclusionsOur findings do not support a potential link between vitamin D concentrations and risk of severe COVID-19 infection and mortality. Recommendations for vitamin D supplementation to lessen COVID-19 risks may provide false reassurance.
Identification of SARS-CoV-2 RNA in Healthcare Heating, Ventilation, and Air Conditioning Units
Authors: Horve Patrick F. , Dietz Leslie , Fretz Mark , Constant David A. , Wilkes Andrew , Townes John M. , Martindale Robert G. , Messer William B. , Van Den Wymelenberg Kevin G. 
Published: June 2020

AbstractAvailable information on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission by small particle aerosols continues to evolve rapidly. To assess the potential role of heating, ventilation, and air conditioning (HVAC) systems in airborne viral transmission, this study sought to determine the viral presence, if any, on air handling units in a healthcare setting where Coronavirus Disease 2019 (COVID-19) patients were being treated. The presence of SARS-CoV-2 RNA was detected in approximately 25% of samples taken from nine different locations in multiple air handlers. While samples were not evaluated for viral infectivity, the presence of viral RNA in air handlers raises the possibility that viral particles can enter and travel within the air handling system of a hospital, from room return air through high efficiency MERV-15 filters and into supply air ducts. Although no known transmission events were determined to be associated with these specimens, the findings suggest the potential for HVAC systems to facilitate transmission by environmental contamination via shared air volumes with locations remote from areas where infected persons reside. More work is needed to further evaluate the risk of SARS-CoV-2 transmission via HVAC systems and to verify effectiveness of building operations mitigation strategies for the protection of building occupants. These results are important within and outside of healthcare settings and may present a matter of some urgency for building operators of facilities that are not equipped with high-efficiency filtration.
Fast Variational Alignment of non-flat 1D Displacements for Applications in Neuroimaging
Authors: Flotho Philipp , Thinnes David , Kuhn Bernd , Roome Christopher J. , Vibell Jonas F. , Strauss Daniel J. 
Published: June 2020

AbstractBackgroundIn the context of signal analysis and pattern matching, alignment of 1D signals for the comparison of signal morphologies is an important problem. For image processing and computer vision, 2Doptical flow(OF) methods find wide application for motion analysis and image registration and variational OF methods have been continuously improved over the past decades.New MethodWe propose a variational method for the alignment and displacement estimation of 1D signals. We pose the estimation of non-flat displacements as an optimization problem with a similarity and smoothness term similar to variational OF estimation. To this end, we can make use of efficient optimization strategies that allow real-time applications on consumer grade hardware.ResultsWe apply our method to two applications from functional neuroimaging: The alignment of 2-photon imaging line scan recordings and the denoising of evoked and event-related potentials in single trial matrices. We can report state of the art results in terms of alignment quality and computing speeds.Existing MethodsExisting methods for 1D alignment target mostly constant displacements, do not allow native subsample precision or precise control over regularization or are slower than the proposed method.ConclusionsOur method is implemented as a MATLAB toolbox and is online available. It is suitable for 1D alignment problems, where high accuracy and high speed is needed and non-constant displacements occur.
Dynamic population stage-structure stabilizes complex ecological communities
Authors: de Roos André M. 
Published: June 2020

SummaryNatural ecological communities are diverse, complex and often surprisingly stable, but the mechanisms underlying their stability remain a theoretical enigma1-5. Interactions such as competition and predation presumably structure communities6, yet theory predicts that complex communities are only stable when species growth rates are mostly limited by intraspecific self-regulation rather than by interactions with resources, competitors and predators3,5,7. Current theory, however, only considers the network topology of population-level interactions between species and neglects within-population differences among juvenile and adult individuals. Here, using model simulations, I show that including commonly observed differences in vulnerability to predation and foraging efficiency between juvenile and adult individuals results in up to ten times larger, more complex communities than in simulations without population stage-structure. These diverse communities are stable or fluctuate with limited amplitude, even though in the model only a single basal species is self-regulated and the population-level interaction network is highly connected. Analysis of the species interaction matrix predicts the simulated communities to be unstable but extending the matrix with a population structure subsystem reveals that dynamic changes in population stage-structure completely cancel out this instability. Common differences between juveniles and adults and fluctuations in their relative abundance hence have a decisive influence on the stability of complex natural communities and their vulnerability when environmental conditions change. Thus, community persistence can not be explained by the network of interactions between the constituting species alone.