bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultraviolet A Radiation and COVID-19 Deaths in the USA with replication studies in England and Italy
Authors: Cherrie Mark , Clemens Tom , Colandrea Claudio , Feng Zhiqiang , Webb David J , Dibben Chris , Weller Richard B 
Published: July 2020

AbstractObjectivesTo determine whether UVA exposure might be associated with COVID-19 deathsDesignEcological regression, with replication in two other countries and pooled estimationSetting2,474 counties of the contiguous USA, 6,755 municipalities in Italy, 6,274 small areas in England. Only small areas in their ‘Vitamin D winter’ (monthly mean UVvitd of under 165 KJ/m2) from Jan to April 2020.ParticipantsThe ‘at-risk’ population is the total small area population, with measures to incorporate spatial infection into the model. The model is adjusted for potential confounders including long-term winter temperature and humidity.Main outcome measuresWe derive UVA measures for each area from remote sensed data and estimate their relationship with COVID-19 mortality with a random effect for States, in a multilevel zero-inflated negative binomial model. In the USA and England death certificates had to record COVID-19. In Italy excess deaths in 2020 over expected from 2015-19.Data sourcesSatellite derived mean daily UVA dataset from Japan Aerospace Exploration Agency. Data on deaths compiled by Center for Disease Control (USA), Office for National Statistics (England) and Italian Institute of Statistics.ResultsDaily mean UVA (January-April 2020) varied between 450 to 1,000 KJ/m2 across the three countries. Our fully adjusted model showed an inverse correlation between UVA and COVID-19 mortality with a Mortality Risk Ratio (MRR) of 0.71 (0.60 to 0.85) per 100KJ/m2 increase UVA in the USA, 0.81 (0.71 to 0.93) in Italy and 0.49 (0.38 to 0.64) in England. Pooled MRR was 0.68 (0.52 to 0.88).ConclusionsOur analysis, replicated in 3 independent national datasets, suggests ambient UVA exposure is associated with lower COVID-19 specific mortality. This effect is independent of vitamin D, as it occurred at irradiances below that likely to induce significant cutaneous vitamin D3 synthesis. Causal interpretations must be made cautiously in observational studies. Nonetheless this study suggests strategies for reduction of COVID-19 mortality.
Advanced imaging to improve remission rates in patients undergoing transsphenoidal surgery for Cushing’s disease
Authors: Koh Chan Hee , Khan Danyal Z. , Horsfall Hugo Layard , Ali Ahmad , Digpal Ronneil , Evanson Jane , Marcus Hani J. , Korbonits Márta 
Published: July 2020

ABSTRACTINTRODUCTIONCushing’s disease is a condition of hypercortisolaemia caused by a functional adrenocorti-cotropic hormone secreting pituitary adenoma. Surgical management is the first line of treatment for Cushing’s disease, but remains challenging in some cases. Various imaging modalities have been tried in an attempt to improve surgical remission rates. However, the sizes and certainties of any effect, in comparison to standard preoperative MRI imaging, remain unclear.METHODSThis protocol has been developed according to the PRISMA-P 2015 standards. Searches of PubMed and Embase were conducted on 21 May 2020, and abstract screening commenced. The eligibility criteria, items for data extraction, and the analysis plan are laid out in this protocol, and uploaded prior to commencement of formal data extraction.DISCUSSIONThe results of this review will inform decision-making and priority-setting at the clinical, organisational and research levels. The results will be disseminated throughout the international neurosurgical community through presentations and publications.
Near Term Predictions of Covid-19 Cases in West Bengal, Maharashtra, Delhi and Tamil Nadu in India Based on Basu Model
Authors: Basu Santanu 
Published: July 2020

ABSTRACTFour states in India account for nearly two thirds of the Covid-19 cases and the numbers are growing fast. A mathematical model which has been recently developed and which has been applied to other countries and regions in the world has been used in this paper to anchor the available data to date and to make near term projections. The projections can be compared to actual data to take steps in the near term in controlling the spread of this disease.
Cis-regulatory architecture of human ESC-derived hypothalamic neuron differentiation aids in variant-to-gene mapping of relevant complex traits
Authors: Pahl Matthew C. , Doege Claudia A. , Hodge Kenyaita M. , Littleton Sheridan H. , Leonard Michelle E. , Lu Sumei , Rausch Rick , Pippin James A. , Bradfield Jonathan P. , Hammond Reza K. , Boehm Keith , Berkowitz Robert I. , Lasconi Chiara , Su Chun , Chesi Alessandra , Johnson Matthew E. , Wells Andrew D. , Voight Benjamin F. , Leibel Rudolph L. , Cousminer Diana L. , Grant Struan F.A. 
Published: July 2020

SummaryThe hypothalamus regulates metabolic homeostasis by influencing behavior, energy utilization and endocrine systems. Given its role governing health-relevant traits, such as body weight and reproductive timing, understanding the genetic regulation of hypothalamic development and function should yield insights into these traits and diseases. However, given its inaccessibility, studying human hypothalamic gene regulation has proven challenging. To address this gap, we generated a chromatin architecture atlas of an established embryonic stem cell (ESC)-derived hypothalamic-like neuron (HN) model across three stages ofin vitrodifferentiation. We profiled accessible chromatin and identified physically interacting contacts between gene promoters and their putative cis-regulatory elements (cREs) to characterize changes in the gene regulatory landscape during hypothalamic differentiation. Next, we integrated these data with GWAS loci for multiple traits and diseases enriched for heritability in these cells, identifying candidate effector genes and cREs impacting transcription factor binding. Our results reveal common target genes for these traits, potentially identifying core hypothalamic developmental pathways. Our atlas will enable future efforts to determine precise mechanisms underlying hypothalamic development with respect to specific disease pathogenesis.
Identification of ligand-specific G-protein coupled receptor states and prediction of downstream efficacy via data-driven modeling
Authors: Fleetwood Oliver , Carlsson Jens , Delemotte Lucie 
Published: July 2020

AbstractG protein-coupled receptors (GPCRs) shift between inactive states and active signaling states, to which intracellular binding partners can bind. Extracellular binding of ligands stabilizes different receptor states and modulates the intracellular response via a complex allosteric process, which is not completely understood. Despite the recent advances in structure determination and spectroscopy techniques, a comprehensive view of the ligand-protein interplay remains a challenge. We derived free energy landscapes describing activation of the β2adrenergic receptor (β2AR) bound to ligands with different efficacy profiles using enhanced sampling molecular dynamics (MD) simulations. The resulting free energy landscapes reveal clear shifts towards active-like states at the G protein binding site for receptors bound to partial and full agonists compared to antagonists and inverse agonists. Not only do the ligands control the population of states, they also modulate the conformational ensemble of the receptor by tuning allosteric protein microswitches. We find an excellent correlation between the conformation of the microswitches close to the ligand binding site and in the transmembrane region and experimentally reported cAMP signaling responses, highlighting the predictive power of our approach. Using dimensionality reduction techniques, we could further assess the similarity between the unique conformational states induced by different ligands. Two distant hotspots governing agonism on transmembrane helices 5 and 7, including the conserved NPxxY motif, formed the endpoints of an allosteric pathway between the binding sites. Our results demonstrate how molecular dynamics simulations can further provide insights into the mechanism of GPCR regulation by ligands, which may contribute to the design of drugs with specific efficacy profiles.
NMR structure of a vestigial nuclease provides insight into the evolution of functional transitions in viral dsDNA packaging motors
Authors: Mahler Bryon P. , Bujalowski Pawel J. , Mao Huzhang , Dill Erik A. , Jardine Paul J. , Choi Kay H. , Morais Marc C. 
Published: July 2020

SummaryDouble-stranded DNA viruses use ATP-powered molecular motors to package their genomes. To do so, these motors must efficiently transition between initiation, translocation, and termination modes. Here, we report structural and biophysical analyses of the C-terminal domain of the bacteriophage phi29 ATPase (CTD) that suggest a structural basis for these functional transitions. Sedimentation experiments show that the inter-domain linker in the full-length protein promotes dimerization and thus may play a role in assembly of the functional motor. The NMR solution structure of the CTD indicates it is a vestigial nuclease domain that likely evolved from conserved nuclease domains in phage terminases. Despite the loss of nuclease activity, fluorescence binding assays confirm the CTD retains its DNA binding capabilities and fitting the CTD into cryoEM density of the phi29 motor shows that the CTD directly binds DNA. However, the interacting residues differ from those identified by NMR titration in solution, suggesting that packaging motors undergo conformational changes to transition between initiation, translocation, and termination.
Revisiting the carbon isotope discrimination and water use efficiency relation: the influence of mesophyll conductance
Authors: Ma Wei Ting , Tcherkez Guillaume , Wang Xu Ming , Schäufele Rudi , Schnyder Hans , Yang Yusheng , Gong Xiao Ying 
Published: July 2020

SummaryThe carbon isotope discrimination (Δ) has been used widely to infer intrinsic water-use efficiency (iWUE) of C3plants, a key parameter linking carbon and water fluxes. Despite the essential role of mesophyll conductance (gm) in photosynthesis and Δ, its effect on Δ-based predictions of iWUE has generally been neglected.Here, we derive a mathematical expression of iWUE as a function of Δ that includesgm(iWUEmes) and exploits thegm-stomatal conductance (gsc) relationship across drought-stress levels and plant functional groups (deciduous or semi-deciduous woody, evergreen woody and herbaceous species) in a global database. iWUEmeswas further validated with an independent dataset of online-Δ and CO2and H2O gas exchange measurements with seven species.Drought stress reducedgscby 52% andgmby 45% averaged over all plant functional groups, but had no significant effect on thegsc/gmratio, suggesting a well-constrainedgsc/gmratio of 0.79±0.07 (95%CI,n=198) across plant functional groups and drought-stress treatments. Due in part to the synchronous behavior ofgscandgm,gmwas negatively correlated to iWUE. Incorporating thegsc/gmratio in the iWUEmesmodel significantly improved the estimation of iWUE compared to the simple model.The inclusion ofgmeffects, even using a fixedgsc/gmratio of 0.79 whengmis unknown, proved desirable to eliminate significant bias in estimating iWUE from Δ across various C3vegetation types.
Nutations in plant shoots: endogenous and exogenous factors in the presence of mechanical deformations
Authors: Agostinelli Daniele , DeSimone Antonio , Noselli Giovanni 
Published: July 2020

AbstractWe present a three-dimensional morphoelastic rod model capable to describe the morphogenesis of growing plant shoots, as driven by differential growth at the tip. We discuss the evolution laws for endogenous oscillators, straightening mechanisms and reorientations to directional cues, such as phototropic responses to a far light source and gravitropic reactions governed by the statoliths avalanche dynamics. We use this model to investigate the role of elastic deflections due to gravity loading in circumnutating plant shoots. We show that, in the absence of endogenous cues, pendular and circular oscillations arise as a critical length is attained, thus suggesting the occurrence of a Hopf bifurcation reminiscent of flutter instabilities exhibited by structural systems under nonconservative loads. When also oscillations due to endogenous cues are present, their weight relative to those associated with the Hopf instability varies in time as the shoot length and other biomechanical properties change. Thanks to the simultaneous occurrence of these two oscillatory mechanisms, we are able to reproduce a variety of complex behaviors, including trochoid-like patterns, which evolve into circular orbits as the shoot length increases, and the amplitude of the flutter induced oscillations becomes dominant. Our findings suggest that the relative importance of the two mechanisms is an emergent property of the system that is affected by the amplitude of elastic deformations, and highlight the crucial role of elasticity in the analysis of circumnutations.
A Node-based Informed Modularity Strategy to Identify Organizational Modules in Anatomical Networks
Authors: Esteve-Altava Borja 
Published: July 2020

AbstractThe use of anatomical networks to study the modular organization of morphological systems and their evolution is growing in recent years. A common strategy to find the best partition of anatomical networks into modules is to use a community detection algorithm that tries to optimize the modularity Q function. However, this strategy overlooks the fact that Q has a resolution limit for small modules, which is often the case in anatomical networks. This produces two problems. One is that some algorithms find inexplicable different modules when we input slightly different networks. The other is that algorithms find asymmetric modules in otherwise symmetric networks. These problems have discouraged researchers to use anatomical network analysis and boost criticisms to this methodology. Here, I propose aNode-based Informed Modularity Strategy(NIMS) to identify modules in anatomical networks that bypass resolution and sensitivity limitations by using a bottom-up approach. Starting with the local modularity around every individual node, NIMS returns the modular organization of the network by merging non-redundant modules and assessing their intersection statistically using combinatorial theory. Instead of acting as a black box, NIMS allows researcher to make informed decisions about whether to merge non-redundant modules. NIMS returns network modules that are robust to minor variation and does not require to optimize a global modularity function. NIMS may prove useful to identify modules also in small ecological and social networks.
Genome-wide analysis clarifies the population genetic structure of wild Gilthead Sea Bream (Sparus aurata)
Authors: Maroso Francesco , Gkagkavouzis Konstantinos , De Innocentiis Sabina , Hillen Jasmien , do Prado Fernanda , Karaiskou Nikoleta , Taggart John Bernard , Carr Adrian , Nielsen Einar ,   the Aquatrace consortium, Triantafyllidis Alexandros , Bargelloni Luca 
Published: July 2020

AbstractGilthead sea bream is an important target for both recreational and commercial fishing in Europe, where it is also one of the most important cultured fish. Its distribution range goes from the Mediterranean to the African and European coasts of the North-East Atlantic. So far, the genetic structure of this species in the wild has been studied with microsatellite DNA, but the pattern of differentiation could not be fully clarified. In this study, almost 1000 wild sea bream from 23 locations in the Mediterranean Sea and Atlantic ocean where genotyped at 1159 SNP markers, of which 18 potentially under selection. Neutral markers suggested the presence of a weak subdivision into three genetic clusters: Atlantic, West and East Mediterranean. This last group could be further subdivided into an Ionian/Adriatic and an Aegean group using outlier markers. Seascape analysis suggested that this differentiation was mainly due to difference in salinity, and this was also supported by preliminary genomic functional analysis. These results are of fundamental importance for the development of proper management of this species in the wild and are a first step toward the study of the potential genetic impact of the sea bream aquaculture industry.
Genetic diversity and population structure among goat genotypes in Kenya
Authors: Waineina Ruth W. , Ngeno Kiplangat , Otieno Tobias O. , Ilatsia Evans D. 
Published: July 2020

AbstractPopulation structure and relationship information among goats is critical for genetic improvement, utilization and conservation. This study explored population structure and level of gene intermixing among four goat genotypes in Kenya: Alpine (n = 30), Toggenburg (n = 28), Saanen (n = 24) and Galla (n = 12). The population structuring and relatedness were estimated using principal component analysis utilizing allele frequencies of the SNP markers. Genotype relationships were evaluated based on the calculated Reynolds genetic distances. A phylogenetic tree was constructed to represent genotype clustering using iTOL software. Population structure was investigated using model-based clustering (ADMIXTURE) Genotypes relationships revealed four distinctive clusters: Alpine, Galla, Saanen and Toggenburg. The ADMIXTURE results revealed some level of gene intermixing among Alpine, Toggenburg and Saanen with Galla. Saanen goats were the most admixed genotype with 84%, 7% and 4% of its genome derived from Galla, Alpine and Toggenburg respectively. Alpine and Toggenburg goats shared some associations with the Galla goat; 10% and 1% respectively. The association of Galla with other genotypes was anticipated since Galla goat was used as the founder population for crossbreeding with Saanen, Alpine and Toggenburg breed. The genetic variations among the goat genotypes observed, will provide a good opportunity for sustainable utilization, conservation and future genetic resource improvement programs in goat genotypes in Kenya.
Enlarged cortical cells and reduced cortical cell file number improve growth under suboptimal nitrogen, phosphorus and potassium availability
Authors: Yang Xiyu , Niemiec Miranda , Lynch Jonathan P. 
Published: July 2020

AbstractReduced cortical cell files (CCFN) and enlarged cortical cells (CCS) reduce root maintenance costs. We usedOpenSimRoot, a functional-structural model, to test the hypothesis that larger CCS, reduced CCFN, and their interactions with root cortical aerenchyma (RCA), are useful adaptations to suboptimal soil N, P, and K availability. Interactions of CCS and CCFN with lateral root branching density (LRBD) and increased carbon availability were evaluated under limited N, P and K availability. The combination of larger CCS and reduced CCFN increases the growth of maize up to 105%, 106%, and 144%, respectively, under limited N, P, or K availability. Interactions among larger CCS, reduced CCFN, and greater RCA results in combined growth benefits of up to 135%, 132%, and 161% under limited N, P, and K levels, respectively. Under low phosphorus and potassium availability, increased LRBD approximately doubles the utility of larger CCS and reduced CCFN. The utility of larger CCS and reduced CCFN is reduced by greater C availability as may occur in future climate scenarios. Our results support the hypothesis that larger CCS, reduced CCFN, and their interactions with RCA could increase nutrient acquisition by reducing root respiration and root nutrient demand. Phene synergisms may exist between CCS, CCFN, and LRBD. Natural genetic variation in CCS and CCFN merit consideration for breeding cereal crops with improved nutrient acquisition, which is critical for global food security.One sentence summaryFunctional-structural modeling indicates that enlarged root cortical cells and reduced cortical cell file number decrease root maintenance cost, permitting greater soil exploration, resource capture, and plant growth under suboptimal nitrogen, phosphorus and potassium availability.
i2dash: Creation of Flexible, Interactive and Web-based Dashboards for Visualization of Omics-pipeline Results
Authors: Ustjanzew Arsenij , Preussner Jens , Bentsen Mette , Kuenne Carsten , Looso Mario 
Published: July 2020

AbstractData visualization and interactive data exploration are important aspects of illustrating complex concepts and results from analyses of omics data. A suitable visualization has to be intuitive and accessible. Web-based dashboards have become popular tools for the arrangement, consolidation and display of such visualizations. However, the combination of automated data processing pipelines handling omics data and dynamically generated, interactive dashboards is poorly solved. Here, we present i2dash, an R package intended to encapsulate functionality for programmatic creation of customized dashboards. It supports interactive and responsive (linked) visualizations across a set of predefined graphical layouts. i2dash addresses the needs of data analysts for a tool that is compatible and attachable to any R-based analysis pipeline, thereby fostering the separation of data visualization on one hand and data analysis tasks on the other hand. In addition, the generic design of i2dash enables data analysts to generate modular extensions for specific needs. As a proof of principle, we provide an extension of i2dash optimized for single-cell RNA-sequencing analysis, supporting the creation of dashboards for the visualization needs of single-cell sequencing experiments. Equipped with these features, i2dash is suitable for extensive use in large scale sequencing/bioinformatics facilities. Along this line, we provide i2dash as a containerized solution, enabling a straightforward large-scale deployment and sharing of dashboards using cloud services.i2dash is freely available via the R package archive CRAN.
A DNA-based optical nanosensor forin vivoimaging of acetylcholine in the peripheral nervous system
Authors: Xia Junfei , Yang Hongrong , Mu Michelle , Micovic Nicholas , Poskanzer Kira E. , Monaghan James R. , Clark Heather A. 
Published: July 2020

AbstractThe ability to monitor the release of neurotransmitters during synaptic transmission would significantly impact the diagnosis and treatment of neurological disease. Here, we present a DNA-based enzymatic nanosensor for quantitative detection of acetylcholine (ACh) in the peripheral nervous system of living mice. ACh nanosensors consist of DNA as a scaffold, acetylcholinesterase as a recognition component, pH-sensitive fluorophores as signal generators, and α-bungarotoxin as a targeting moiety. We demonstrate the utility of the nanosensors in the submandibular ganglia of living mice to sensitively detect ACh ranging from 0.228 μM to 358 μM. In addition, the sensor response upon electrical stimulation of the efferent nerve is dose-dependent, reversible, and we observe a reduction of ~76% in sensor signal upon pharmacological inhibition of ACh release. Equipped with an advanced imaging processing tool, we further spatially resolve ACh signal propagation on the tissue level. Our platform enables sensitive measurement and mapping of ACh transmission in the peripheral nervous system.