bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vitamin D supplementation in primary allergy prevention: Systematic review of randomized and non‐randomized studies
Authors: Yepes‐Nuñez J. J. , Brożek J. L. , Fiocchi A. , Pawankar R. , Cuello‐García C. , Zhang Y. , Morgano G. P. , Agarwal Arnav , Gandhi S. , Terracciano L. , Schünemann H. J. 
Published: July 2017

AbstractBackgroundTo date, a systematic review of the evidence regarding the association between vitamin D and allergic diseases development has not yet been undertaken.ObjectiveTo review the efficacy and safety of vitamin D supplementation when compared to no supplementation in pregnant women, breastfeeding women, infants, and children for the prevention of allergies.MethodsThree databases were searched through January 30, 2016, including randomized (RCT) and nonrandomized studies (NRS). Two reviewers independently extracted data and assessed the certainty in the body of evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.ResultsAmong the 1932 articles identified, one RCT and four NRS were eligible. Very low certainty in the body of evidence across examined studies suggests that vitamin D supplementation for pregnant women, breastfeeding women, and infants may not decrease the risk of developing allergic diseases such as atopic dermatitis (in pregnant women), allergic rhinitis (in pregnant women and infants), asthma and/or wheezing (in pregnant women, breastfeeding women, and infants), or food allergies (in pregnant women). We found no studies of primary prevention of allergic diseases in children.ConclusionLimited information is available addressing primary prevention of allergic diseases after vitamin D supplementation, and its potential impact remains uncertain.
Estimating the causal effect of body mass index on hay fever, asthma and lung function using Mendelian randomization
Authors: Skaaby T. , Taylor A. E. , Thuesen B. H. , Jacobsen R. K. , Friedrich N. , Møllehave L. T. , Hansen S. , Larsen S. C. , Völker U. , Nauck M. , Völzke H. , Hansen T. , Pedersen O. , Jørgensen T. , Paternoster L. , Munafò M. , Grarup N. , Linneberg A. 
Published: July 2017

AbstractBackgroundObservational studies have shown that body mass index (BMI) is positively associated with asthma. However, observational data are prone to confounding and reverse causation. In Mendelian randomization, genetic variants are used as unconfounded markers of exposures to examine causal effects. We examined the causal effect of BMI on asthma, hay fever, allergic sensitization, serum total immunoglobulin E (IgE), forced expiratory volume in one‐second (FEV1) and forced vital capacity (FVC).MethodsWe included 490 497 participants in the observational and 162 124 participants in the genetic analyses. A genetic risk score (GRS) was created using 26 BMI‐associated single nucleotide polymorphisms (SNPs). Results were pooled in meta‐analyses and expressed as odds ratios (ORs) or β‐estimates with 95% confidence interval (CI).ResultsThe GRS was significantly associated with asthma (OR=1.009; 95% CI: 1.004, 1.013), but not with hay fever (OR= 0.998; 95% CI: 0.994, 1.002) or allergic sensitization (OR=0.999; 95% CI: 0.986, 1.012) per BMI‐increasing allele. The GRS was significantly associated with decrease in FEV1: β=−0.0012 (95% CI: −0.0019, −0.0006) and FVC: β=−0.0022 (95% CI: −0.0031, −0.0014) per BMI‐increasing allele. Effect sizes estimated by instrumental variable analyses were OR=1.07 (95% CI: 1.03, 1.10) for asthma, a 9 ml decrease in FEV1 (95% CI: 2.0‐15 mL decrease) and a 16 ml decrease in FVC (95% CI: 7.0‐24 mL decrease) per 1 kg/m2 higher BMI.ConclusionsThe results support the conclusion that increasing BMI is causally related to higher prevalence of asthma and decreased lung function, but not with hay fever or biomarkers of allergy.
Current and predicted distribution of the pathogenic fungus Batrachochytrium dendrobatidis in Colombia, a hotspot of amphibian biodiversity
Authors: Flechas Sandra V. , Paz Andrea , Crawford Andrew J. , Sarmiento Carolina , Acevedo Aldemar A. , Arboleda Alejandro , Bolívar‐García Wilmar , Echeverry‐Sandoval Claudia L. , Franco Rosmery , Mojica Cindy , Muñoz Amanda , Palacios‐Rodríguez Pablo , Posso‐Terranova Andrés M. , Quintero‐Marín Paulina , Rueda‐Solano Luis A. , Castro‐Herrera Fernando , Amézquita Adolfo 
Published: July 2017

AbstractGlobal amphibian declines have been attributed to several factors including the chytrid fungal pathogen, Batrachochytrium dendrobatidis (Bd), that infects hosts’ skin and causes death by inhibiting immune response and impairing osmoregulatory function. Here, we integrate extensive new field data with previously published locality records of Bd in Colombia, a megadiverse and environmentally heterogeneous country in northwestern South America, to determine the relative importance of environmental variables and reproductive mode for predicting the risk of Bd infection in amphibians. We surveyed 81 localities across Colombia and sampled 2876 individual amphibians belonging to 14 taxonomic families. Through a combination of end‐point PCR and real‐time PCR analyses, Bd was detected in 338 individuals (12%) representing 43 localities (53%) distributed from sea level to 3200 m. We found that annual mean temperature and variables related with seasonality in precipitation and temperature appeared to define the most suitable areas for the establishment of the pathogen. In addition, prevalence of infection appeared to be higher in species with a terrestrial reproductive mode. Our study provides the first large‐scale study of the current and potential distribution of Bd in the biodiversity hotspot centered on Colombia. We hope the newly provided information on the extent of the distribution of the pathogen and the potential areas where Bd may impact the amphibian fauna will inform decision making by environmental authorities and future conservation action.
Novel pyrrolocycloalkylpyrazole analogues as CB1 ligands
Authors: Asproni Battistina , Manca Ilaria , Pinna Giansalvo , Cichero Elena , Fossa Paola , Murineddu Gabriele , Lazzari Paolo , Loriga Giovanni , Pinna Gérard A. 
Published: July 2017

Novel 1,4‐dihydropyrazolo[3,4‐a]pyrrolizine‐, 4,5‐dihydro‐1H‐pyrazolo[4,3‐g]indolizine‐ and 1,4,5,6‐tetrahydropyrazolo[3,4‐c]pyrrolo[1,2‐a]azepine‐3‐carboxamide‐based compounds were designed and synthesized for cannabinoid CB1 and CB2 receptor interactions. Any of the new synthesized compounds showed high affinity for CB2 receptor with Ki values superior to 314 nm, whereas some of them showed moderate affinity for CB1 receptor with Ki values inferior to 400 nm. 7‐Chloro‐1‐(2,4‐dichlorophenyl)‐N‐(homopiperidin‐1‐yl)‐4,5‐dihydro‐1H‐pyrazolo[4,3‐g]indolizine‐3‐carboxamide (2j) exhibited good affinity for CB1 receptor (KiCB1 = 81 nm) and the highest CB2/CB1 selectively ratio (>12). Docking studies carried out on such compounds were performed using the hCB1 X‐ray in complex with the close pyrazole analogue AM6538 and disclosed specific pattern of interactions related to the tricyclic pyrrolopyrazole scaffolds as CB1 ligands.
Computing Contour Trees for 2D Piecewise Polynomial Functions
Authors: Nucha Girijanandan , Bonneau Georges‐Pierre , Hahmann Stefanie , Natarajan Vijay 
Published: July 2017

AbstractContour trees are extensively used in scalar field analysis. The contour tree is a data structure that tracks the evolution of level set topology in a scalar field. Scalar fields are typically available as samples at vertices of a mesh and are linearly interpolated within each cell of the mesh. A more suitable way of representing scalar fields, especially when a smoother function needs to be modeled, is via higher order interpolants. We propose an algorithm to compute the contour tree for such functions. The algorithm computes a local structure by connecting critical points using a numerically stable monotone path tracing procedure. Such structures are computed for each cell and are stitched together to obtain the contour tree of the function. The algorithm is scalable to higher degree interpolants whereas previous methods were restricted to quadratic or linear interpolants. The algorithm is intrinsically parallelizable and has potential applications to isosurface extraction.
Visual Analysis of Confocal Raman Spectroscopy Data using Cascaded Transfer Function Design
Authors: Schikora Christoph M. , Plack Markus , Bornemann Rainer , Bolívar Peter Haring , Kolb Andreas 
Published: July 2017

Abstract2D Confocal Raman Microscopy (CRM) data consist of high dimensional per‐pixel spectral data of 1000 bands and allows for complex spectral and spatial‐spectral analysis tasks, i.e., in material discrimination, material thickness, and spatial material distributions. Currently, simple integral methods are commonly applied as visual analysis solutions to CRM data which exhibit restricted discrimination power in various regards.In this paper we present a novel approach for the visual analysis of 2D multispectral CRM data using multi‐variate visualization techniques. Due to the large amount of data and the demand of an explorative approach without a‐priori restriction, our system allows for arbitrary interactive (de)selection of varaibles w/o limitation and an unrestricted online definition/construction of new, combined properties. Our approach integrates CRM specific quantitative measures and handles material‐related features for mixed materials in a quantitative manner. Technically, we realize the online definition/construction of new, combined properties as semi‐automatic, cascaded, 1D and 2D multidimensional transfer functions (MD‐TFs). By interactively incorporating new (raw or derived) properties, the dimensionality of the MD‐TF space grows during the exploration procedure and is virtually unlimited. The final visualization is achieved by an enhanced color mixing step which improves saturation and contrast.
Graffinity: Visualizing Connectivity in Large Graphs
Authors: Kerzner E. , Lex A. , Sigulinsky C.L. , Urness T. , Jones B.W. , Marc R.E. , Meyer M. 
Published: July 2017

AbstractMultivariate graphs are prolific across many fields, including transportation and neuroscience. A key task in graph analysis is the exploration of connectivity, to, for example, analyze how signals flow through neurons, or to explore how well different cities are connected by flights. While standard node‐link diagrams are helpful in judging connectivity, they do not scale to large networks. Adjacency matrices also do not scale to large networks and are only suitable to judge connectivity of adjacent nodes. A key approach to realize scalable graph visualization are queries: instead of displaying the whole network, only a relevant subset is shown. Query‐based techniques for analyzing connectivity in graphs, however, can also easily suffer from cluttering if the query result is big enough. To remedy this, we introduce techniques that provide an overview of the connectivity and reveal details on demand. We have two main contributions: (1) two novel visualization techniques that work in concert for summarizing graph connectivity; and (2) Graffinity, an open‐source implementation of these visualizations supplemented by detail views to enable a complete analysis workflow. Graffinity was designed in a close collaboration with neuroscientists and is optimized for connectomics data analysis, yet the technique is applicable across domains. We validate the connectivity overview and our open‐source tool with illustrative examples using flight and connectomics data.
Graph Layouts by t‐SNE
Authors: Kruiger J. F. , Rauber P. E. , Martins R. M. , Kerren A. , Kobourov S. , Telea A. C. 
Published: July 2017

AbstractWe propose a new graph layout method based on a modification of the t‐distributed Stochastic Neighbor Embedding (t‐SNE) dimensionality reduction technique. Although t‐SNE is one of the best techniques for visualizing high‐dimensional data as 2D scatterplots, t‐SNE has not been used in the context of classical graph layout. We propose a new graph layout method, tsNET, based on representing a graph with a distance matrix, which together with a modified t‐SNE cost function results in desirable layouts. We evaluate our method by a formal comparison with state‐of‐the‐art methods, both visually and via established quality metrics on a comprehensive benchmark, containing real‐world and synthetic graphs. As evidenced by the quality metrics and visual inspection, tsNET produces excellent layouts.
Comparative Visual Analysis of Structure‐Performance Relations in Complex Bulk‐Heterojunction Morphologies
Authors: Aboulhassan A. , Sicat R. , Baum D. , Wodo O. , Hadwiger M. 
Published: July 2017

AbstractThe structure of Bulk‐Heterojunction (BHJ) materials, the main component of organic photovoltaic solar cells, is very complex, and the relationship between structure and performance is still largely an open question. Overall, there is a wide spectrum of fabrication configurations resulting in different BHJ morphologies and correspondingly different performances. Current state‐of‐the‐art methods for assessing the performance of BHJ morphologies are either based on global quantification of morphological features or simply on visual inspection of the morphology based on experimental imaging. This makes finding optimal BHJ structures very challenging. Moreover, finding the optimal fabrication parameters to get an optimal structure is still an open question. In this paper, we propose a visual analysis framework to help answer these questions through comparative visualization and parameter space exploration for local morphology features. With our approach, we enable scientists to explore multivariate correlations between local features and performance indicators of BHJ morphologies. Our framework is built on shape‐based clustering of local cubical regions of the morphology that we call patches. This enables correlating the features of clusters with intuition‐based performance indicators computed from geometrical and topological features of charge paths.
Visualizing Probabilistic Multi‐Phase Fluid Simulation Data using a Sampling Approach
Authors: Hummel M. , Jöckel L. , Schäfer J. , Hlawitschka M. W. , Garth C. 
Published: July 2017

AbstractEulerian Method of Moment (MoM) solvers are gaining popularity for multi‐phase CFD simulation involving bubbles or droplets in process engineering. Because the actual positions of bubbles are uncertain, the spatial distribution of bubbles is described by scalar fields of moments, which can be interpreted as probability density functions. Visualizing these simulation results and comparing them to physical experiments is challenging, because neither the shape nor the distribution of bubbles described by the moments lend themselves to visual interpretation.In this work, we describe a visualization approach that provides explicit instances of the bubble distribution and produces bubble geometry based on local flow properties. To facilitate animation, the instancing of the bubble distribution provides coherence over time by advancing bubbles between time steps and updating the distribution. Our approach provides an intuitive visualization and enables direct visual comparison of simulation results to physical experiments.
Uncertainty Footprint: Visualization of Nonuniform Behavior of Iterative Algorithms Applied to 4D Cell Tracking
Authors: Wan Y. , Hansen C. 
Published: July 2017

AbstractResearch on microscopy data from developing biological samples usually requires tracking individual cells over time. When cells are three‐dimensionally and densely packed in a time‐dependent scan of volumes, tracking results can become unreliable and uncertain. Not only are cell segmentation results often inaccurate to start with, but it also lacks a simple method to evaluate the tracking outcome. Previous cell tracking methods have been validated against benchmark data from real scans or artificial data, whose ground truth results are established by manual work or simulation. However, the wide variety of real‐world data makes an exhaustive validation impossible. Established cell tracking tools often fail on new data, whose issues are also difficult to diagnose with only manual examinations. Therefore, data‐independent tracking evaluation methods are desired for an explosion of microscopy data with increasing scale and resolution. In this paper, we propose the uncertainty footprint, an uncertainty quantification and visualization technique that examines nonuniformity at local convergence for an iterative evaluation process on a spatial domain supported by partially overlapping bases. We demonstrate that the patterns revealed by the uncertainty footprint indicate data processing quality in two algorithms from a typical cell tracking workflow – cell identification and association. A detailed analysis of the patterns further allows us to diagnose issues and design methods for improvements. A 4D cell tracking workflow equipped with the uncertainty footprint is capable of self diagnosis and correction for a higher accuracy than previous methods whose evaluation is limited by manual examinations.
CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences
Authors: Liu Zhicheng , Kerr Bernard , Dontcheva Mira , Grover Justin , Hoffman Matthew , Wilson Alan 
Published: July 2017

AbstractEvent sequence datasets with high event cardinality and long sequences are difficult to visualize and analyze. In particular, it is hard to generate a high level visual summary of paths and volume of flow. Existing approaches of mining and visualizing frequent sequential patterns look promising, but have limitations in terms of scalability, interpretability and utility. We propose CoreFlow, a technique that automatically extracts and visualizes branching patterns in event sequences. CoreFlow constructs a tree by recursively applying a three‐step procedure: rank events, divide sequences into groups, and trim sequences by the chosen event. The resulting tree contains key events as nodes, and links represent aggregated flows between key events. Based on CoreFlow, we have developed an interactive system for event sequence analysis. Our approach can compute branching patterns for millions of events in a few seconds, with improved interpretability of extracted patterns compared to previous work. We also present case studies of using the system in three different domains and discuss success and failure cases of applying CoreFlow to real‐world analytic problems. These case studies call forth future research on metrics and models to evaluate the quality of visual summaries of event sequences.
On the Stability of Functional Maps and Shape Difference Operators
Authors: Huang R. , Chazal F. , Ovsjanikov M. 
Published: July 2017

AbstractIn this paper, we provide stability guarantees for two frameworks that are based on the notion of functional maps—the framework of shape difference operators and the one of analyzing and visualizing the deformations between shapes. We consider two types of perturbations in our analysis: one is on the input shapes and the other is on the change in scale. In theory, we formulate and justify the robustness that has been observed in practical implementations of those frameworks. Inspired by our theoretical results, we propose a pipeline for constructing shape difference operators on point clouds and show numerically that the results are robust and informative. In particular, we show that both the shape difference operators and the derived areas of highest distortion are stable with respect to changes in shape representation and change of scale. Remarkably, this is in contrast with the well‐known instability of the eigenfunctions of the Laplace–Beltrami operator computed on point clouds compared to those obtained on triangle meshes.
Biological monitoring of dermal and air exposure to cobalt at a Swedish hard metal production plant: does dermal exposure contribute to uptake?
Authors: Klasson Maria , Lindberg Magnus , Bryngelsson Ing‐Liss , Arvidsson Helena , Pettersson Carin , Husby Bente , Westberg Håkan 
Published: July 2017

SummaryBackgroundOccupational exposure to cobalt is well established in hard metal manufacture. Cobalt is known to cause contact allergy, asthma, hard metal lung disease, and lung cancer. The relationship between skin exposure and uptake determined in blood has not been extensively investigated.ObjectiveTo examine whether skin and inhalable air exposure to cobalt contributes to uptake, determined as cobalt in blood, in a hard metal manufacturing factory.MethodsThe amount of cobalt on the skin found with an acid wash technique, the air concentrations of inhalable cobalt and cobalt blood concentrations were determined and correlated in exposed workers.ResultsWe found a significant rank correlation for cobalt concentrations on the skin, in inhalable air, and in blood (0.376–0.498). Multiple linear regression showed significant regression coefficients for cobalt skin exposure and blood (B = 0.01, p < 0.05) and for inhalable cobalt in air and blood (B = 49.1, p < 0.001). According to our model based on data from the regression analyses, a twofold increase in skin exposure levels at different air concentrations caused a 3–14% increase in blood levels.ConclusionsOur data suggest that skin exposure to cobalt in the hard metal industry could affect the total uptake at the same order of magnitude as air exposure.
Knowing When Help Is Needed: A Developing Sense of Causal Complexity
Authors: Kominsky Jonathan F. , Zamm Anna P. , Keil Frank C. 
Published: July 2017

AbstractResearch on the division of cognitive labor has found that adults and children as young as age 5 are able to find appropriate experts for different causal systems. However, little work has explored how children and adults decide when to seek out expert knowledge in the first place. We propose that children and adults rely (in part) on “mechanism metadata,” information about mechanism information. We argue that mechanism metadata is relatively consistent across individuals exposed to similar amounts of mechanism information, and it is applicable to a wide range of causal systems. In three experiments, we show that adults and children as young as 5 years of age have a consistent sense of the causal complexity of different causal systems, and that this sense of complexity is related to decisions about when to seek expert knowledge, but over development there is a shift in focus from procedural information to internal mechanism information.
The Burden of the “False‐Negatives” in Clinical Development: Analyses of Current and Alternative Scenarios and Corrective Measures
Authors: Burt T , Button KS , Thom HHZ , Noveck RJ , Munafò MR 
Published: July 2017

AbstractThe “false‐negatives” of clinical development are the effective treatments wrongly determined ineffective. Statistical errors leading to “false‐negatives” are larger than those leading to “false‐positives,” especially in typically underpowered early‐phase trials. In addition, “false‐negatives” are usually eliminated from further testing, thereby limiting the information available on them. We simulated the impact of early‐phase power on economic productivity in three developmental scenarios. Scenario 1, representing the current status quo, assumed 50% statistical power at phase II and 90% at phase III. Scenario 2 assumed increased power (80%), and Scenario 3, increased stringency of alpha (1%) at phase II. Scenario 2 led, on average, to a 60.4% increase in productivity and 52.4% increase in profit. Scenario 3 had no meaningful advantages. Our results suggest that additional costs incurred by increasing the power of phase II studies are offset by the increase in productivity. We discuss the implications of our results and propose corrective measures.