cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4585243.v3
title: Crawford_2010_Ambystoma_annulatum.xlsx

description: Objective: The primary objective of this study was to determine the most important variable(s) influencing breeding wetland use by Ringed Salamanders in east-central Missouri, which can subsequently be incorporated into conservation recommendations for this imperiled species. <br>Methods: To determine Ringed Salamander occupancy of potential breeding wetlands, we sampled a total of 38 wetlands during the fall 2010 breeding season (September–October) in east-central Missouri (U.S.A.; 38.6878, –90.7492). Each wetland was sampled for three consecutive nights with six - eight double-throated minnow traps. We identified all amphibians to species and recorded total numbers for each species captured; all animals were then released at the site of capture. For each wetland location, data were collected on four site covariates: (1) FISH – presence/absence of predatory fish; (2) LEAF – leaf litter depth (mm); (3) COV – canopy cover (%); and (4) BUFFER – minimum amount of forest cover between the wetland and an open area. To determine whether a site contained predatory fish, we recorded when fish were captured in the minnow traps used for amphibian sampling. Leaf litter depth and canopy cover were measured at four equidistant points around the wetland (approximately 1 m from the wetland edge) and the four values were then averaged. Leaf litter depth was measured with a hand ruler and canopy cover measurements were taken with a densiometer. To calculate the minimum buffer distance for each wetland, a GPS waypoint was taken at each wetland and subsequently plotted using ArcGIS 10.0 (ESRI, Redlands, CA). The distance between the wetland and nearest open area (agricultural field, paved road, etc.) was then measured. Data layers for land use/land cover were obtained from the Missouri Spatial Data Information Service (http://msdis.missouri.edu/index.htm). Additionally, data were collected on three sampling covariates: (1) PRECIP – amount of precipitation in the 24 hr preceding sampling; (2) AVGTEMP – average temperature in the 24 hr preceding sampling; and (3) TIME – day of survey. Temperature and rainfall data were obtained from the National Climatic Data Center (http://www.ncdc.noaa.gov). This research was conducted under MDC permit #14468. This project conformed to the legal requirements for the use of vertebrates in research and animal care methods followed protocols from Guidelines for Use of Live Amphibians and Reptiles in Field Research compiled by ASIH, HL, and SSAR (document can be accessed at: http://www.aaalac.org/accreditation/Guidelines_for_Use_of_Live_Amphibians_and_Reptiles.pdf).
DOI: 10.6084/m9.figshare.4585219.v1
title: Quadrature Methods for Bayesian Optimal Design of Experiments with Non-Normal Prior Distributions

description: Many optimal experimental designs depend on one or more unknown model parameters. In such cases, it is common to use Bayesian optimal design procedures to seek designs that perform well over an entire prior distribution of the unknown model parameter(s). Generally, Bayesian optimal design procedures are viewed as computationally intensive. This is because they require numerical integration techniques in order to approximate the Bayesian optimality criterion at hand. The most common numerical integration technique involves pseudo Monte Carlo draws from the prior distribution(s). For a good approximation of the Bayesian optimality criterion, a large number of pseudo Monte Carlo draws is required. This results in long computation times. As an alternative to the pseudo Monte Carlo approach, we propose using computationally efficient Gaussian quadrature techniques. Since, for normal prior distributions, suitable quadrature techniques have already been used in the context of optimal experimental design, we focus on quadrature techniques for non-normal prior distributions. Such prior distributions are appropriate for variance components, correlation coefficients and any other parameters that are strictly positive or have upper and lower bounds. In this article, we demonstrate the added value of the quadrature techniques we advocate by means of the Bayesian D-optimality criterion in the context of split-plot experiments, but we want to stress that the techniques can be applied to other optimality criteria and other types of experimental designs as well.
DOI: 10.6084/m9.figshare.4585147
title: A self-consistent top–down model for differentiation in bimodal suites: application to the Sonju Lake Intrusion–Finland granite system (MN)

description: The Sonju Lake Intrusion (SLI) is a 1200-meter thick layered mafic intrusion that directly underlies an equally large silicic pluton, the Finland granophyre (FG) within the Beaver Bay Complex of the Mid-Continent Rift (MN, USA). The SLI, with a simple mineralogical and compositional stratigraphy, provides an excellent case study for examining the changes in iron isotope ratios (<i>δ</i><sup>56</sup>Fe). Here new Fe isotope data along with <sup>87</sup>Sr/<sup>86</sup>Sr for a set of stratigraphically controlled samples from the SLI and FG are presented. The Fe isotope data show systematic changes within two differentiation sequences found in the lowermost FG as well as the upper portion of the SLI. Specifically, <i>δ</i><sup>56</sup>Fe is observed to start at low values and increase to heavy values going stratigraphically up through each differentiation sequence. Within the middle portion of the SLI, <i>δ</i><sup>56</sup>Fe varies between 0 and 0.1. Two samples from the SLI bottom are isotopically lighter than the middle SLI. The origin of the Fe isotope variations is discussed in terms of recently proposed explanations. A quantitative model shows that the observed spatial variation is consistent with the prediction of a temperature gradient model. Using present constraints on equilibrium phase partitioning, the iron isotope variations do not appear consistent with production by fractional crystallization. Based on these observations, a top–down sill emplacement process coupled with <i>in situ</i> differentiation remains a viable alternative model for forming this layered intrusion.
DOI: 10.6084/m9.figshare.4585243.v4
title: Crawford_2010_Ambystoma_annulatum.xlsx

description: Objective: The primary objective of this study was to determine the most important variable(s) influencing breeding wetland use by Ringed Salamanders in east-central Missouri, which can subsequently be incorporated into conservation recommendations for this imperiled species. <br>Methods: To determine Ringed Salamander occupancy of potential breeding wetlands, we sampled a total of 38 wetlands during the fall 2010 breeding season (September–October) in east-central Missouri (U.S.A.; 38.6878, –90.7492). Each wetland was sampled for three consecutive nights with six - eight double-throated minnow traps. We identified all amphibians to species and recorded total numbers for each species captured; all animals were then released at the site of capture. For each wetland location, data were collected on four site covariates: (1) FISH – presence/absence of predatory fish; (2) LEAF – leaf litter depth (mm); (3) COV – canopy cover (%); and (4) BUFFER – minimum amount of forest cover between the wetland and an open area. To determine whether a site contained predatory fish, we recorded when fish were captured in the minnow traps used for amphibian sampling. Leaf litter depth and canopy cover were measured at four equidistant points around the wetland (approximately 1 m from the wetland edge) and the four values were then averaged. Leaf litter depth was measured with a hand ruler and canopy cover measurements were taken with a densiometer. To calculate the minimum buffer distance for each wetland, a GPS waypoint was taken at each wetland and subsequently plotted using ArcGIS 10.0 (ESRI, Redlands, CA). The distance between the wetland and nearest open area (agricultural field, paved road, etc.) was then measured. Data layers for land use/land cover were obtained from the Missouri Spatial Data Information Service (http://msdis.missouri.edu/index.htm). Additionally, data were collected on three sampling covariates: (1) PRECIP – amount of precipitation in the 24 hr preceding sampling; (2) AVGTEMP – average temperature in the 24 hr preceding sampling; and (3) TIME – day of survey. Temperature and rainfall data were obtained from the National Climatic Data Center (http://www.ncdc.noaa.gov). This research was conducted under MDC permit #14468. This project conformed to the legal requirements for the use of vertebrates in research and animal care methods followed protocols from Guidelines for Use of Live Amphibians and Reptiles in Field Research compiled by ASIH, HL, and SSAR (document can be accessed at: http://www.aaalac.org/accreditation/Guidelines_for_Use_of_Live_Amphibians_and_Reptiles.pdf).
DOI: 10.6084/m9.figshare.4585144
title: Application of Bayesian networks for hazard ranking of nanomaterials to support human health risk assessment

description: In this study, a Bayesian Network (BN) was developed for the prediction of the hazard potential and biological effects with the focus on metal- and metal-oxide nanomaterials to support human health risk assessment. The developed BN captures the (inter) relationships between the exposure route, the nanomaterials physicochemical properties and the ultimate biological effects in a holistic manner and was based on international expert consultation and the scientific literature (e.g., <i>in vitro</i>/<i>in vivo</i> data). The BN was validated with independent data extracted from published studies and the accuracy of the prediction of the nanomaterials hazard potential was 72% and for the biological effect 71%, respectively. The application of the BN is shown with scenario studies for TiO<sub>2</sub>, SiO<sub>2</sub>, Ag, CeO<sub>2</sub>, ZnO nanomaterials. It is demonstrated that the BN may be used by different stakeholders at several stages in the risk assessment to predict certain properties of a nanomaterials of which little information is available or to prioritize nanomaterials for further screening.
DOI: 10.6084/m9.figshare.4585243.v6
title: Capture data for Ringed Salamanders in east-central Missouri (2010)

description: Objective: The primary objective of this study was to determine the most important variable(s) influencing breeding wetland use by Ringed Salamanders in east-central Missouri, which can subsequently be incorporated into conservation recommendations for this imperiled species. <br>Methods: To determine Ringed Salamander occupancy of potential breeding wetlands, we sampled a total of 38 wetlands during the fall 2010 breeding season (September–October) in east-central Missouri (U.S.A.; 38.6878, –90.7492). Each wetland was sampled for three consecutive nights with six - eight double-throated minnow traps. We identified all amphibians to species and recorded total numbers for each species captured; all animals were then released at the site of capture. For each wetland location, data were collected on four site covariates: (1) FISH – presence/absence of predatory fish; (2) LEAF – leaf litter depth (mm); (3) COV – canopy cover (%); and (4) BUFFER – minimum amount of forest cover between the wetland and an open area. To determine whether a site contained predatory fish, we recorded when fish were captured in the minnow traps used for amphibian sampling. Leaf litter depth and canopy cover were measured at four equidistant points around the wetland (approximately 1 m from the wetland edge) and the four values were then averaged. Leaf litter depth was measured with a hand ruler and canopy cover measurements were taken with a densiometer. To calculate the minimum buffer distance for each wetland, a GPS waypoint was taken at each wetland and subsequently plotted using ArcGIS 10.0 (ESRI, Redlands, CA). The distance between the wetland and nearest open area (agricultural field, paved road, etc.) was then measured. Data layers for land use/land cover were obtained from the Missouri Spatial Data Information Service (http://msdis.missouri.edu/index.htm). Additionally, data were collected on three sampling covariates: (1) PRECIP – amount of precipitation in the 24 hr preceding sampling; (2) AVGTEMP – average temperature in the 24 hr preceding sampling; and (3) TIME – day of survey. Temperature and rainfall data were obtained from the National Climatic Data Center (http://www.ncdc.noaa.gov). This research was conducted under MDC permit #14468. This project conformed to the legal requirements for the use of vertebrates in research and animal care methods followed protocols from Guidelines for Use of Live Amphibians and Reptiles in Field Research compiled by ASIH, HL, and SSAR (document can be accessed at: http://www.aaalac.org/accreditation/Guidelines_for_Use_of_Live_Amphibians_and_Reptiles.pdf).
DOI: 10.6084/m9.figshare.4585144.v1
title: Application of Bayesian networks for hazard ranking of nanomaterials to support human health risk assessment

description: In this study, a Bayesian Network (BN) was developed for the prediction of the hazard potential and biological effects with the focus on metal- and metal-oxide nanomaterials to support human health risk assessment. The developed BN captures the (inter) relationships between the exposure route, the nanomaterials physicochemical properties and the ultimate biological effects in a holistic manner and was based on international expert consultation and the scientific literature (e.g., <i>in vitro</i>/<i>in vivo</i> data). The BN was validated with independent data extracted from published studies and the accuracy of the prediction of the nanomaterials hazard potential was 72% and for the biological effect 71%, respectively. The application of the BN is shown with scenario studies for TiO<sub>2</sub>, SiO<sub>2</sub>, Ag, CeO<sub>2</sub>, ZnO nanomaterials. It is demonstrated that the BN may be used by different stakeholders at several stages in the risk assessment to predict certain properties of a nanomaterials of which little information is available or to prioritize nanomaterials for further screening.
DOI: 10.6084/m9.figshare.4585147.v1
title: A self-consistent top–down model for differentiation in bimodal suites: application to the Sonju Lake Intrusion–Finland granite system (MN)

description: The Sonju Lake Intrusion (SLI) is a 1200-meter thick layered mafic intrusion that directly underlies an equally large silicic pluton, the Finland granophyre (FG) within the Beaver Bay Complex of the Mid-Continent Rift (MN, USA). The SLI, with a simple mineralogical and compositional stratigraphy, provides an excellent case study for examining the changes in iron isotope ratios (<i>δ</i><sup>56</sup>Fe). Here new Fe isotope data along with <sup>87</sup>Sr/<sup>86</sup>Sr for a set of stratigraphically controlled samples from the SLI and FG are presented. The Fe isotope data show systematic changes within two differentiation sequences found in the lowermost FG as well as the upper portion of the SLI. Specifically, <i>δ</i><sup>56</sup>Fe is observed to start at low values and increase to heavy values going stratigraphically up through each differentiation sequence. Within the middle portion of the SLI, <i>δ</i><sup>56</sup>Fe varies between 0 and 0.1. Two samples from the SLI bottom are isotopically lighter than the middle SLI. The origin of the Fe isotope variations is discussed in terms of recently proposed explanations. A quantitative model shows that the observed spatial variation is consistent with the prediction of a temperature gradient model. Using present constraints on equilibrium phase partitioning, the iron isotope variations do not appear consistent with production by fractional crystallization. Based on these observations, a top–down sill emplacement process coupled with <i>in situ</i> differentiation remains a viable alternative model for forming this layered intrusion.
DOI: 10.6084/m9.figshare.4585243.v5
title: Capture data for Ringed Salamanders in east-central Missouri (2010).

description: Objective: The primary objective of this study was to determine the most important variable(s) influencing breeding wetland use by Ringed Salamanders in east-central Missouri, which can subsequently be incorporated into conservation recommendations for this imperiled species. <br>Methods: To determine Ringed Salamander occupancy of potential breeding wetlands, we sampled a total of 38 wetlands during the fall 2010 breeding season (September–October) in east-central Missouri (U.S.A.; 38.6878, –90.7492). Each wetland was sampled for three consecutive nights with six - eight double-throated minnow traps. We identified all amphibians to species and recorded total numbers for each species captured; all animals were then released at the site of capture. For each wetland location, data were collected on four site covariates: (1) FISH – presence/absence of predatory fish; (2) LEAF – leaf litter depth (mm); (3) COV – canopy cover (%); and (4) BUFFER – minimum amount of forest cover between the wetland and an open area. To determine whether a site contained predatory fish, we recorded when fish were captured in the minnow traps used for amphibian sampling. Leaf litter depth and canopy cover were measured at four equidistant points around the wetland (approximately 1 m from the wetland edge) and the four values were then averaged. Leaf litter depth was measured with a hand ruler and canopy cover measurements were taken with a densiometer. To calculate the minimum buffer distance for each wetland, a GPS waypoint was taken at each wetland and subsequently plotted using ArcGIS 10.0 (ESRI, Redlands, CA). The distance between the wetland and nearest open area (agricultural field, paved road, etc.) was then measured. Data layers for land use/land cover were obtained from the Missouri Spatial Data Information Service (http://msdis.missouri.edu/index.htm). Additionally, data were collected on three sampling covariates: (1) PRECIP – amount of precipitation in the 24 hr preceding sampling; (2) AVGTEMP – average temperature in the 24 hr preceding sampling; and (3) TIME – day of survey. Temperature and rainfall data were obtained from the National Climatic Data Center (http://www.ncdc.noaa.gov). This research was conducted under MDC permit #14468. This project conformed to the legal requirements for the use of vertebrates in research and animal care methods followed protocols from Guidelines for Use of Live Amphibians and Reptiles in Field Research compiled by ASIH, HL, and SSAR (document can be accessed at: http://www.aaalac.org/accreditation/Guidelines_for_Use_of_Live_Amphibians_and_Reptiles.pdf).
DOI: 10.6084/m9.figshare.4585108
title: Classification of sphingosine kinase inhibitors using counter propagation artificial neural networks: A systematic route for designing selective SphK inhibitors

description: Accurate and robust classification models for describing and predicting the activity of 330 chemicals that are sphingosine kinase 1 (SphK1) and/or sphingosine kinase 2 (SphK2) inhibitors were derived. The classification models developed in this work assist in finding selective subspaces in chemical space occupied by particular groups of SphK inhibitors. A combination of a genetic algorithm (GA) and a counter propagation artificial neural network (CPANN) was utilized to select the most efficient subsets of the molecular descriptors. The optimized models in this work reasonably separate active inhibitors of SphK1 from active SphK2 inhibitors. Generally, the CPANN models in this work were used to classify the compounds according to their therapeutic targets and activities. The simplicity of the chosen descriptors and their relative importance sheds some light on the structural features necessary to induce selective inhibitory activity to the studied molecules. The areas under the receiver operating characteristic (ROC) curves for the GA–CPANN models in this work were 0.934 and 0.922 for active SphK1 and SphK2 inhibitors, respectively. Generally, the results in this work suggest some important molecular features and pharmacophores that could help medicinal chemists develop selective and potent SphK inhibitors.
DOI: 10.6084/m9.figshare.4585108.v1
title: Classification of sphingosine kinase inhibitors using counter propagation artificial neural networks: A systematic route for designing selective SphK inhibitors

description: Accurate and robust classification models for describing and predicting the activity of 330 chemicals that are sphingosine kinase 1 (SphK1) and/or sphingosine kinase 2 (SphK2) inhibitors were derived. The classification models developed in this work assist in finding selective subspaces in chemical space occupied by particular groups of SphK inhibitors. A combination of a genetic algorithm (GA) and a counter propagation artificial neural network (CPANN) was utilized to select the most efficient subsets of the molecular descriptors. The optimized models in this work reasonably separate active inhibitors of SphK1 from active SphK2 inhibitors. Generally, the CPANN models in this work were used to classify the compounds according to their therapeutic targets and activities. The simplicity of the chosen descriptors and their relative importance sheds some light on the structural features necessary to induce selective inhibitory activity to the studied molecules. The areas under the receiver operating characteristic (ROC) curves for the GA–CPANN models in this work were 0.934 and 0.922 for active SphK1 and SphK2 inhibitors, respectively. Generally, the results in this work suggest some important molecular features and pharmacophores that could help medicinal chemists develop selective and potent SphK inhibitors.
DOI: 10.6084/m9.figshare.4585066
title: MicroRNA expression profiles identify disease-specific alterations in systemic lupus erythematosus and Sjögren's syndrome

description: Supplementary materials for the work entitled "MicroRNA expression profiles identify disease-specific alterations in systemic lupus erythematosus and Sjögren's syndrome". All data available in Excel format.
DOI: 10.6084/m9.figshare.4585042
title: databases and R code (10112016).rar

description: <b>Objective:</b> To illustrate the ability of hierarchical Bayesian spatio-temporal models in capturing different geo-temporal structures in order to explain hospital risk variations using three different conditions: Percutaneous Coronary Intervention (PCI), Colectomy in Colorectal Cancer (CCC) and Chronic Obstructive Pulmonary Disease (COPD). <b>Research Design:</b> This is an observational population-based spatio-temporal study, from 2002 to 2013, with a two-level geographical structure, Autonomous Communities (AC) and Health Care Areas (HA). Setting: The Spanish National Health System, a quasi-federal structure with 17 regional governments (AC) with full responsibility in planning and financing, and 203 HA providing hospital and primary care to a defined population. <b>Methods:</b> A poisson-log normal mixed model in the Bayesian framework was fitted using the INLA efficient estimation procedure. Measures: The spatio-temporal hospitalization relative risks, the evolution of their variation, and the relative contribution (fraction of variation) of each of the model components (AC, HA, year and interaction AC-year).