cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1568576.v1
title: The postcranial anatomy of <i>Yacarerani boliviensis</i> and the phylogenetic significance of the notosuchian postcranial skeleton

description: ABSTRACTIn this contribution, we describe new specimens of <i>Yacarerani boliviensis</i> from the Cajones Formation (Upper Cretaceous) of Bolivia. We focus on the postcranial anatomy of <i>Y. boliviensis</i>, because this anatomical region is completely unknown in other sphagesaurid notosuchians up to the present. At least eight individuals representing almost the entire postcranial skeleton are described. Although the postcranial anatomy of <i>Yacarerani</i> resembles that of other notosuchians in many features, five autapomorphic characters were identified: pedicles of the atlas bearing a lateral bulge; absence of rounded depressions on the dorsal surface of the anterior to middle dorsal vertebrae; coracoid bearing an oblique crest on its lateral surface; lateromedially compressed anterior ungual phalanges; and femur with a shallow depression for the M. puboischiofemoralis internus 1 and M. caudifemoralis longus. Observed variation in the postcranial anatomy of basal mesoeucrocodylians was incorporated as new characters in a phylogenetic analysis, expanding the postcranial information used in current phylogenetic data sets. The phylogenetic analysis depicts <i>Yacarerani</i> forming a clade with <i>Adamantinasuchus</i>, which is positioned at the base of Sphagesauridae. This family is well nested among a clade of ’advanced notosuchians,’ and <i>Mariliasuchus</i> is recovered as its sister group. The cladistic analysis recovered new postcranial synapomorphies for Notosuchia and less inclusive clades, although the fact that many taxa lack postcranial remains limits the number of unambiguous postcranial synapomorphies within Notosuchia.SUPPLEMENTAL DATA—Supplemental materials are available for this article for free at www.tandfonline.com/UJVPCitation for this article: Leardi, J. M., D. Pol, F. E. Novas, and M. Suarez Riglos. 2015. The postcranial anatomy of Yacarerani boliviensis and the phylogenetic significance of the notosuchian postcranial skeleton. Journal of Vertebrate Paleontology. DOI: 10.1080/02724634.2014.995187.
DOI: 10.6084/m9.figshare.1568579.v1
title: Challenges facing European agriculture and possible biotechnological solutions

description: Agriculture faces many challenges to maximize yields while it is required to operate in an environmentally sustainable manner. In the present study, we analyze the major agricultural challenges identified by European farmers (primarily related to biotic stresses) in 13 countries, namely Belgium, Bulgaria, the Czech Republic, France, Germany, Hungary, Italy, Portugal, Romania, Spain, Sweden, UK and Turkey, for nine major crops (barley, beet, grapevine, maize, oilseed rape, olive, potato, sunflower and wheat). Most biotic stresses (BSs) are related to fungi or insects, but viral diseases, bacterial diseases and even parasitic plants have an important impact on yield and harvest quality. We examine how these challenges have been addressed by public and private research sectors, using either conventional breeding, marker-assisted selection, transgenesis, cisgenesis, RNAi technology or mutagenesis. Both national surveys and scientific literature analysis followed by text mining were employed to evaluate genetic engineering (GE) and non-GE approaches. This is the first report of text mining of the scientific literature on plant breeding and agricultural biotechnology research. For the nine major crops in Europe, 128 BS challenges were identified with 40% of these addressed neither in the scientific literature nor in recent European public research programs. We found evidence that the private sector was addressing only a few of these “neglected” challenges. Consequently, there are considerable gaps between farmer’s needs and current breeding and biotechnology research. We also provide evidence that the current political situation in certain European countries is an impediment to GE research in order to address these agricultural challenges in the future. This study should also contribute to the decision-making process on future pertinent international consortia to fill the identified research gaps.
DOI: 10.6084/m9.figshare.1568573
title: Transcriptomic analysis of skeletal muscle from beef cattle exposed to illicit schedules containing dexamethasone: identification of new candidate biomarkers and their validation using samples from a field monitoring trial

description: Growth promoters (GPs) such as the glucocorticoid dexamethasone (DEX) and the β-adrenergic agonist clenbuterol (CLEN) are still used abusively in beef cattle production. Transcriptomic markers for indirect detection of such GPs have been discussed in either experimentally treated animals or commercial samples separately. In the present study we examine the transcriptomic signature of DEX alone or in combination with CLEN in skeletal muscle of experimentally treated beef cattle, and, furthermore, compare them with previously screened commercial samples from a field-monitoring study, as well as with proteomics data representing the same set of samples. Using DNA microarray technology, transcriptomic profiling was performed on 12 samples representing three groups of animals: DEX (0.75 mg/animal/day, <i>n</i> = 4), a combination of DEX (0.66 mg/animal/day) and CLEN (from 2 to 6 mg/animal/day, <i>n</i> = 4) and a control group (<i>n</i> = 4). Analyses showed the differential expression of 198 and 39 transcripts in DEX and DEX–CLEN groups, respectively. Both groups had no common modulated genes in between, neither with the proteomics data. Sixteen candidate genes were validated via qPCR. They showed high correlation with the corresponding microarray data. Principal component analysis (PCA) on both the qPCR and normalised microarray data resulted in the separation of treated animals from the untreated ones. Interestingly, all the PCA plots grouped the DEX-positive samples (experimental or commercial) apart from each other. In brief, this study provides some interesting glucocorticoid-responsive biomarkers whose expression was contradictory to what is reported in human studies. Additionally, this study points out the transcriptomic signature dissimilarity between commercial and experimentally treated animals.
DOI: 10.6084/m9.figshare.1568570
title: Bayesian nonparametric dynamic state space modeling with circular latent states

description: State space models are well-known for their versatility in modeling dynamic systems that arise in various scientific disciplines. Although parametric state space models are well studied, nonparametric approaches are much less explored in comparison. In this article we propose a novel Bayesian nonparametric approach to state space modeling, assuming that both the observational and evolutionary functions are unknown and are varying with time; crucially, we assume that the unknown evolutionary equation describes dynamic evolution of some latent circular random variable. Based on appropriate kernel convolution of the standard Weiner process, we model the time-varying observational and evolutionary functions as suitable Gaussian processes that take both linear and circular variables as arguments. Additionally, for the time-varying evolutionary function, we wrap the Gaussian process thus constructed around the unit circle to form an appropriate circular Gaussian process. We show that our process thus created satisfies desirable properties. For the purpose of inference we develop a Markov-chain Monte Carlo (MCMC)-based methodology combining Gibbs sampling and Metropolis–Hastings algorithms. Applications to a simulated data set, a real wind speed data set, and a real ozone data set demonstrated quite encouraging performances of our model and methodologies.
DOI: 10.6084/m9.figshare.1568573.v1
title: Transcriptomic analysis of skeletal muscle from beef cattle exposed to illicit schedules containing dexamethasone: identification of new candidate biomarkers and their validation using samples from a field monitoring trial

description: Growth promoters (GPs) such as the glucocorticoid dexamethasone (DEX) and the β-adrenergic agonist clenbuterol (CLEN) are still used abusively in beef cattle production. Transcriptomic markers for indirect detection of such GPs have been discussed in either experimentally treated animals or commercial samples separately. In the present study we examine the transcriptomic signature of DEX alone or in combination with CLEN in skeletal muscle of experimentally treated beef cattle, and, furthermore, compare them with previously screened commercial samples from a field-monitoring study, as well as with proteomics data representing the same set of samples. Using DNA microarray technology, transcriptomic profiling was performed on 12 samples representing three groups of animals: DEX (0.75 mg/animal/day, <i>n</i> = 4), a combination of DEX (0.66 mg/animal/day) and CLEN (from 2 to 6 mg/animal/day, <i>n</i> = 4) and a control group (<i>n</i> = 4). Analyses showed the differential expression of 198 and 39 transcripts in DEX and DEX–CLEN groups, respectively. Both groups had no common modulated genes in between, neither with the proteomics data. Sixteen candidate genes were validated via qPCR. They showed high correlation with the corresponding microarray data. Principal component analysis (PCA) on both the qPCR and normalised microarray data resulted in the separation of treated animals from the untreated ones. Interestingly, all the PCA plots grouped the DEX-positive samples (experimental or commercial) apart from each other. In brief, this study provides some interesting glucocorticoid-responsive biomarkers whose expression was contradictory to what is reported in human studies. Additionally, this study points out the transcriptomic signature dissimilarity between commercial and experimentally treated animals.
DOI: 10.6084/m9.figshare.1568569
title: Linear and non-linear modelling of the cytotoxicity of TiO<sub>2</sub> and ZnO nanoparticles by empirical descriptors

description: Titanium oxide (TiO<sub>2</sub>) and zinc oxide (ZnO) nanoparticles are among the most widely used in different applications in daily life. In this study, local regression and classification models were developed for a set of ZnO and TiO<sub>2</sub> nanoparticles tested at different concentrations for their ability to disrupt the lipid membrane in cells. Different regression techniques were applied and compared by checking the robustness of the models and their external predictive ability. Additionally, a simple classification model was developed, which predicts the potential for disruption of the studied nanoparticles with good accuracy (overall accuracy, specificity, and sensitivity &gt;80%) on the basis of two empirical descriptors. The present study demonstrates that empirical descriptors, such as experimentally determined size and tested concentrations, are relevant to modelling the activity of nanoparticles. This information may be useful to screen the potential for harmful effect of nanoparticles in different experimental conditions and to optimize the design of toxicological tests. Results from the present study are useful to support and refine the future application of <i>in silico</i> tools to nanoparticles, for research and regulatory purposes.
DOI: 10.6084/m9.figshare.1568570.v1
title: Bayesian Nonparametric Dynamic State Space Modeling with Circular Latent States

description: State space models are well-known for their versatility in modeling dynamic systems that arise in various scientific disciplines. Although parametric state space models are well-studied, nonparametric approaches are much less explored in comparison. In this article we propose a novel Bayesian nonparametric approach to state space modeling assuming that both the observational and evolutionary functions are unknown and are varying with time; crucially, we assume that the unknown evolutionary equation describes dynamic evolution of some latent circular random variable.Based on appropriate kernel convolution of the standard Weiner process we model the time-varying observational and evolutionary functions as suitable Gaussian processes that take both linear and circular variables as arguments. Additionally, for the time-varying evolutionary function, we wrap the Gaussian process thus constructed around the unit circle to form an appropriate circular Gaussian process. We show that our process thus created satisfies desirable properties.For the purpose of inference we develop an MCMC based methodology combining Gibbs sampling and Metropolis-Hastings algorithms. Applications to a simulated dataset, a real wind speed dataset and a real ozone dataset demonstrated quite encouraging performances of our model and methodologies.
DOI: 10.6084/m9.figshare.1568569.v2
title: Linear and non-linear modelling of the cytotoxicity of TiO<sub>2</sub> and ZnO nanoparticles by empirical descriptors

description: Titanium oxide (TiO<sub>2</sub>) and zinc oxide (ZnO) nanoparticles are among the most widely used in different applications in daily life. In this study, local regression and classification models were developed for a set of ZnO and TiO<sub>2</sub> nanoparticles tested at different concentrations for their ability to disrupt the lipid membrane in cells. Different regression techniques were applied and compared by checking the robustness of the models and their external predictive ability. Additionally, a simple classification model was developed, which predicts the potential for disruption of the studied nanoparticles with good accuracy (overall accuracy, specificity, and sensitivity &gt;80%) on the basis of two empirical descriptors. The present study demonstrates that empirical descriptors, such as experimentally determined size and tested concentrations, are relevant to modelling the activity of nanoparticles. This information may be useful to screen the potential for harmful effect of nanoparticles in different experimental conditions and to optimize the design of toxicological tests. Results from the present study are useful to support and refine the future application of <i>in silico</i> tools to nanoparticles, for research and regulatory purposes.
DOI: 10.6084/m9.figshare.1568573.v2
title: Transcriptomic analysis of skeletal muscle from beef cattle exposed to illicit schedules containing dexamethasone: identification of new candidate biomarkers and their validation using samples from a field monitoring trial

description: Growth promoters (GPs) such as the glucocorticoid dexamethasone (DEX) and the β-adrenergic agonist clenbuterol (CLEN) are still used abusively in beef cattle production. Transcriptomic markers for indirect detection of such GPs have been discussed in either experimentally treated animals or commercial samples separately. In the present study we examine the transcriptomic signature of DEX alone or in combination with CLEN in skeletal muscle of experimentally treated beef cattle, and, furthermore, compare them with previously screened commercial samples from a field-monitoring study, as well as with proteomics data representing the same set of samples. Using DNA microarray technology, transcriptomic profiling was performed on 12 samples representing three groups of animals: DEX (0.75 mg/animal/day, <i>n</i> = 4), a combination of DEX (0.66 mg/animal/day) and CLEN (from 2 to 6 mg/animal/day, <i>n</i> = 4) and a control group (<i>n</i> = 4). Analyses showed the differential expression of 198 and 39 transcripts in DEX and DEX–CLEN groups, respectively. Both groups had no common modulated genes in between, neither with the proteomics data. Sixteen candidate genes were validated via qPCR. They showed high correlation with the corresponding microarray data. Principal component analysis (PCA) on both the qPCR and normalised microarray data resulted in the separation of treated animals from the untreated ones. Interestingly, all the PCA plots grouped the DEX-positive samples (experimental or commercial) apart from each other. In brief, this study provides some interesting glucocorticoid-responsive biomarkers whose expression was contradictory to what is reported in human studies. Additionally, this study points out the transcriptomic signature dissimilarity between commercial and experimentally treated animals.
DOI: 10.6084/m9.figshare.1568569.v1
title: Linear and non-linear modelling of the cytotoxicity of TiO<sub>2</sub> and ZnO nanoparticles by empirical descriptors

description: Titanium oxide (TiO<sub>2</sub>) and zinc oxide (ZnO) nanoparticles are among the most widely used in different applications in daily life. In this study, local regression and classification models were developed for a set of ZnO and TiO<sub>2</sub> nanoparticles tested at different concentrations for their ability to disrupt the lipid membrane in cells. Different regression techniques were applied and compared by checking the robustness of the models and their external predictive ability. Additionally, a simple classification model was developed, which predicts the potential for disruption of the studied nanoparticles with good accuracy (overall accuracy, specificity, and sensitivity &gt;80%) on the basis of two empirical descriptors. The present study demonstrates that empirical descriptors, such as experimentally determined size and tested concentrations, are relevant to modelling the activity of nanoparticles. This information may be useful to screen the potential for harmful effect of nanoparticles in different experimental conditions and to optimize the design of toxicological tests. Results from the present study are useful to support and refine the future application of <i>in silico</i> tools to nanoparticles, for research and regulatory purposes.
DOI: 10.6084/m9.figshare.1568567
title: Effect of organic cultivation of rooibos tea plants (<i>Aspalathus linearis</i>) on soil nutrient status in Nieuwoudtville, South Africa

description: The shoots of rooibos (<i>Aspalathus linearis</i> (Burm.f.) R.Dahlgren) plants, cultivated organically by small-scale farmers in Nieuwoudtville, are harvested for the production of tea. These practices could lead to decreasing soil fertility. It was hypothesised that soil from cultivated rooibos plots will have lower nutrient concentrations than soil from adjacent uncultivated plots. Soil and shoot samples were collected in December 2005, 2006 and 2009 from cultivated fields of increasing plot age and from adjacent uncultivated plots on three farms, and analysed for nutrient concentration. Compared with the uncultivated plots, no measured soil nutrients including concentrations of phosphorus (P), exchangeable potassium (K), magnesium (Mg) and calcium (Ca), and soil carbon (C) decreased in cultivated plots over the five-year period of assessment. Soil C correlated positively with concentrations of soil exchangeable K, Mg and Ca, and sodium (<i>P</i>&lt;0.001), indicating that soil C is an important indicator of soil fertility. Foliar P increased, and consequently the nitrogen:P ratio decreased in cultivated relative to uncultivated plants, implying higher P-uptake by cultivated plants. Overall, organic rooibos cultivation in Nieuwoudtville appears to be sustainable in terms of maintaining soil nutrition because soil nutrient status did not decrease over the five-year period.
DOI: 10.6084/m9.figshare.1568570.v2
title: Bayesian Nonparametric Dynamic State Space Modeling with Circular Latent States

description: ABSTRACTState space models are well-known for their versatility in modeling dynamic systems that arise in various scientific disciplines. Although parametric state space models are well studied, nonparametric approaches are much less explored in comparison. In this article we propose a novel Bayesian nonparametric approach to state space modeling, assuming that both the observational and evolutionary functions are unknown and are varying with time; crucially, we assume that the unknown evolutionary equation describes dynamic evolution of some latent circular random variable. Based on appropriate kernel convolution of the standard Weiner process, we model the time-varying observational and evolutionary functions as suitable Gaussian processes that take both linear and circular variables as arguments. Additionally, for the time-varying evolutionary function, we wrap the Gaussian process thus constructed around the unit circle to form an appropriate circular Gaussian process. We show that our process thus created satisfies desirable properties.For the purpose of inference we develop a Markov-chain Monte Carlo (MCMC)-based methodology combining Gibbs sampling and Metropolis–Hastings algorithms. Applications to a simulated data set, a real wind speed data set, and a real ozone data set demonstrated quite encouraging performances of our model and methodologies.
DOI: 10.6084/m9.figshare.1568573.v3
title: Transcriptomic analysis of skeletal muscle from beef cattle exposed to illicit schedules containing dexamethasone: identification of new candidate biomarkers and their validation using samples from a field monitoring trial

description: Growth promoters (GPs) such as the glucocorticoid dexamethasone (DEX) and the β-adrenergic agonist clenbuterol (CLEN) are still used abusively in beef cattle production. Transcriptomic markers for indirect detection of such GPs have been discussed in either experimentally treated animals or commercial samples separately. In the present study we examine the transcriptomic signature of DEX alone or in combination with CLEN in skeletal muscle of experimentally treated beef cattle, and, furthermore, compare them with previously screened commercial samples from a field-monitoring study, as well as with proteomics data representing the same set of samples. Using DNA microarray technology, transcriptomic profiling was performed on 12 samples representing three groups of animals: DEX (0.75 mg/animal/day, <i>n</i> = 4), a combination of DEX (0.66 mg/animal/day) and CLEN (from 2 to 6 mg/animal/day, <i>n</i> = 4) and a control group (<i>n</i> = 4). Analyses showed the differential expression of 198 and 39 transcripts in DEX and DEX–CLEN groups, respectively. Both groups had no common modulated genes in between, neither with the proteomics data. Sixteen candidate genes were validated via qPCR. They showed high correlation with the corresponding microarray data. Principal component analysis (PCA) on both the qPCR and normalised microarray data resulted in the separation of treated animals from the untreated ones. Interestingly, all the PCA plots grouped the DEX-positive samples (experimental or commercial) apart from each other. In brief, this study provides some interesting glucocorticoid-responsive biomarkers whose expression was contradictory to what is reported in human studies. Additionally, this study points out the transcriptomic signature dissimilarity between commercial and experimentally treated animals.