Definitions and outcome measures for mucous membrane pemphigoid: recommendations of an international panel of experts

Mucous membrane pemphigoid encompasses a group of autoimmune bullous diseases with a similar phenotype characterized by subepithelial blisters, erosions, and scarring of mucous membranes, skin, or both. Although knowledge about autoimmune bullous disease is increasing, there is often a lack of clear definitions of disease, outcome measures, and therapeutic end points. With clearer definitions and outcome measures, it is possible to directly compare the results and data from various studies using meta-analyses. This consensus statement provides accurate and reproducible definitions for disease extent, activity, outcome measures, end points, and therapeutic response for mucous membrane pemphigoid and proposes a disease extent score, the Mucous Membrane Pemphigoid Disease Area Index.

Future water quality monitoring--adapting tools to deal with mixtures of pollutants in water resource management.

Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigation measures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicals co-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and to derive combined effect estimates suitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measures integrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at the Danube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis of findings will be organised to provide guidance for future solution-oriented environmental monitoring and explore more systematic ways to assess mixture exposures and combination effects in future water quality monitoring.

Extracting more out of relocation data: building movement models as mixtures of random walks

We present a framework for fitting multiple random walks to animal movement paths consisting of ordered sets of step lengths and turning angles. Each step and turn is assigned to one of a number of random walks, each characteristic of a different behavioral state. Behavioral state assignments may be inferred purely from movement data or may include the habitat type in which the animals are located. Switching between different behavioral states may be modeled explicitly using a state transition matrix estimated directly from data, or switching probabilities may take into account the proximity of animals to landscape features. Model fitting is undertaken within a Bayesian framework using the WinBUGS software. These methods allow for identification of different movement states using several properties of observed paths and lead naturally to the formulation of movement models. Analysis of relocation data from elk released in east-central Ontario, Canada, suggests a biphasic movement behavior: elk are either in an "encamped" state in which step lengths are small and turning angles are high, or in an "exploratory" state, in which daily step lengths are several kilometers and turning angles are small. Animals encamp in open habitat (agricultural fields and opened forest), but the exploratory state is not associated with any particular habitat type.

Table 1 of experts and representatives interviewed

In a modern society it is generally accepted that the major cause for environmental problems is the current consumption pattern in industrialized countries, thus it is crucial to understand underlying processes and search for solutions in order to consciously progress towards sustainable consumption. In this paper the exclusive role of municipalities in promoting sustainable consumption is recognized. By analyzing the example of the situation of municipalities in Latvia, the reason for focusing on local level when dealing with sustainable consumption issues, as well as main obstacles and possibilities for municipalities' progress towards sustainability are revealed. Promotion of sustainable consumption cannot be based solely on eco-efficiency. Sufficiency strategy plays a crucial role. Since positive social environment for sufficiency dimension is vitally important, local level holds exclusively crucial role for its implementation - the potential of municipalities here is unbounded. Although local authorities already have many tools available, they are insufficiently discovered. Insufficiently exploited tools are property tax relief as support mechanism, establishment of advisory boards, green procurement, promotion of social entrepreneurship and collaborative consumption, as well as delegation of municipalities' functions to NGOs, thus encouraging nonmaterial wellbeing by strengthening social ties and community activities.

Sensing colour stability and mixtures of powder paprika using optical reflectance and image analysis.

The production and industry of paprika present several problems related to quality and to production costs. One of the main difficulties is to obtain an objective and quick method for predicting quality. Quality in powder paprika involves: quantity of carotenoids and the appearance and stability of colour. The method used currently for determining quality is the measurement of absorbance at 460 nm wavelength, of an acetone extract of carotenoids, but there is no information about the appearance of the paprika or the stability of its colour with time. " Another important problem is the presence of mixtures of powdered paprika produced in the Spanish region of "La Vera", which has a peculiar way of production, with a high '' quality and price, with other products of lower quality. It is necessary to obtain methods which are able to detect the fraud.

Conditional density approximations with mixtures of polynomials

Mixtures of polynomials (MoPs) are a non-parametric density estimation technique especially designed for hybrid Bayesian networks with continuous and discrete variables. Algorithms to learn one- and multi-dimensional (marginal) MoPs from data have recently been proposed. In this paper we introduce two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate and study the methods using data sampled from known parametric distributions, and we demonstrate their applicability by learning models based on real neuroscience data. Finally, we compare the performance of the proposed methods with an approach for learning mixtures of truncated basis functions (MoTBFs). The empirical results show that the proposed methods generally yield models that are comparable to or significantly better than those found using the MoTBF-based method.

Evidence of expert’s evidence is evidence

Date of Acceptance: 06/06/2015

In vitro cloning of complex mixtures of DNA on microbeads: Physical separation of differentially expressed cDNAs

We describe a method for cloning nucleic acid molecules onto the surfaces of 5-μm microbeads rather than in biological hosts. A unique tag sequence is attached to each molecule, and the tagged library is amplified. Unique tagging of the molecules is achieved by sampling a small fraction (1%) of a very large repertoire of tag sequences. The resulting library is hybridized to microbeads that each carry ≈106 strands complementary to one of the tags. About 105 copies of each molecule are collected on each microbead. Because such clones are segregated on microbeads, they can be operated on simultaneously and then assayed separately. To demonstrate the utility of this approach, we show how to label and extract microbeads bearing clones differentially expressed between two libraries by using a fluorescence-activated cell sorter (FACS). Because no prior information about the cloned molecules is required, this process is obviously useful where sequence databases are incomplete or nonexistent. More importantly, the process also permits the isolation of clones that are expressed only in given tissues or that are differentially expressed between normal and diseased states. Such clones then may be spotted on much more cost-effective, tissue- or disease-directed, low-density planar microarrays.

Educating a New Cadre of Experts Specializing in Digital Collections and Digital Curation: Experiential Learning in Digital Library Curriculum

Integration of experiential learning into the library and information science (LIS) courses has been a theme in LIS education, but the topic deserves renewed attention with an increasing demand for professionals in the digital library field and in light of the new initiative announced by the Library of Congress (LC) and the Institution of Museum and Library Services (IMLS) for national residency program in digital curation. The balance between theory and practice in digital library curricula, the challenges of incorporating practical projects into LIS coursework, and the current practice of teaching with hands on activities represent the primary areas of this panel discussion.

DSC study of transitions involved in thermal treatment of foamable mixtures of PE and EVA copolymer with azodicarbonamide

The transitions and reactions involved in the thermal processing of binary mixtures of polyethylene and poly(ethylene-co-vinyl acetate) copolymers with different concentrations of a foaming agent (azodicarbonamide) were studied using differential scanning calorimetry (DSC). The effect of ZnO as a kicker also was discussed. The temperature at the maximum rate and the heat evolved were measured for all the processes—melting, transitions, and reactions—all the mixtures prepared were measured and compared. Azodicarbonamide decomposed differently depending on the polymeric matrix. These data can be very useful for the plastic processing industry.