Framework for scenario development in LCA

This article is based on the work of the SETAC-Europe LCA Working Group ‘Scenario Development in LCA', which has started its work in April 1998. The goal of the Working Group is to focus on the use of scenarios in Life Cycle Assessment (LCA). This article presents the results of the first phase of the Working Group. The previous definitions of scenarios include three common basic elements: the definition of alternative future circumstances, the path from the present to the future, and the inclusion of uncertainty in the concept. We define a scenario in LCA as "a description of a possible future situation relevant for specific LCA applications, based on specific assumptions about the future, and (when relevant) also including the presentation of the development from the present to the future.' On the basis of the scenario definition we distinguish between two basic approaches for scenario development in LCA studies: What-if scenarios and Cornerstone scenarios. What-if scenarios are used to gain operational information and to compare two or more alternatives in a well-known situation with a short time horizon where the researcher is familiar with the decision problem and can set defined hypothesis on the basis of existing data. The Cornerstone scenario approach offers strategic information for long term planning, new ways of seeing the world, and also guidelines in the field of study. Results of a study using the Cornerstone scenario approach often serve as a basis for further, more specific research where the scenarios can be defined according to What-if scenarios. The frames of the scenarios are defined in the first phase of LCA, the goal and scope definition. Scenario development does, however, influence all of the following phases of LCA. The frames of the scenarios form the basis for modelling product systems and environmental impacts associated with products and services, which are not exactly known due to lacking information on parts of the life cycl

Development of a Sandwich ELISA to Measure Exposure to Occupational Cow Hair Allergens

Background: Cow hair and dander are important inducers of occupational allergies in cattle-exposed farmers. To estimate allergen exposure in farming environments, a sensitive enzyme immunoassay was developed to measure cow hair allergens. Methods: A sandwich ELISA was developed using polyclonal rabbit antibodies against a mixture of hair extracts from different cattle breeds. To assess the specificity of the assay, extracts from other mammalian epithelia, mites, molds and grains were tested. To validate the new assay, cow hair allergens were measured in passive airborne dust samples from the stables and homes of farmers. Dust was collected with electrostatic dust fall collectors (EDCs). Results: The sandwich ELISA was found to be very sensitive (detection limit: 0.1 ng/ml) and highly reproducible, demonstrating intra-and interassay coefficients of variation of 4 and 10%, respectively. The assay showed no reactivity with mites, molds and grains, but some cross-reactivity with other mammalian epithelia, with the strongest reaction with goat. Using EDCs for dust sampling, high concentrations of bovine allergens were measured in cow stables (4,760-559,400 mu g/m(2)). In addition, bovine allergens were detected in all areas of cattle farmer dwellings. A large variation was found between individual samples (0.3-900 mu g/m(2)) and significantly higher values were discovered in changing rooms. Conclusion: The ELISA developed for the detection of cow hair proteins is a useful tool for allergen quantification in occupational and home environments. Based on its low detection limit, this test is sensitive enough to detect allergens in passive airborne dust. Copyright (C) 2011 S. Karger AG, Base

Translational value of choroid plexus imaging for tracking neuroinflammation in mice and humans

Neuroinflammation is a pathophysiological hallmark of multiple sclerosis and has a close mechanistic link to neurodegeneration. Although this link is potentially targetable, robust translatable models to reliably quantify and track neuroinflammation in both mice and humans are lacking. The choroid plexus (ChP) plays a pivotal role in regulating the trafficking of immune cells from the brain parenchyma into the cerebrospinal fluid (CSF) and has recently attracted attention as a key structure in the initiation of inflammatory brain responses. In a translational framework, we here address the integrity and multidimensional characteristics of the ChP under inflammatory conditions and question whether ChP volumes could act as an interspecies marker of neuroinflammation that closely interrelates with functional impairment. Therefore, we explore ChP characteristics in neuroinflammation in patients with multiple sclerosis and in two experimental mouse models, cuprizone diet-related demyelination and experimental autoimmune encephalomyelitis. We demonstrate that ChP enlargement—reconstructed from MRI—is highly associated with acute disease activity, both in the studied mouse models and in humans. A close dependency of ChP integrity and molecular signatures of neuroinflammation is shown in the performed transcriptomic analyses. Moreover, pharmacological modulation of the blood–CSF barrier with natalizumab prevents an increase of the ChP volume. ChP enlargement is strongly linked to emerging functional impairment as depicted in the mouse models and in multiple sclerosis patients. Our findings identify ChP characteristics as robust and translatable hallmarks of acute and ongoing neuroinflammatory activity in mice and humans that could serve as a promising interspecies marker for translational and reverse-translational approaches

EAACI guidelines on the diagnosis of IgE‐mediated food allergy

This European Academy of Allergy and Clinical Immunology guideline provides recommendations for diagnosing IgE‐mediated food allergy and was developed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. Food allergy diagnosis starts with an allergy‐focused clinical history followed by tests to determine IgE sensitization, such as serum allergen‐specific IgE (sIgE) and skin prick test (SPT), and the basophil activation test (BAT), if available. Evidence for IgE sensitization should be sought for any suspected foods. The diagnosis of allergy to some foods, such as peanut and cashew nut, is well supported by SPT and serum sIgE, whereas there are less data and the performance of these tests is poorer for other foods, such as wheat and soya. The measurement of sIgE to allergen components such as Ara h 2 from peanut, Cor a 14 from hazelnut and Ana o 3 from cashew can be useful to further support the diagnosis, especially in pollen‐sensitized individuals. BAT to peanut and sesame can be used additionally. The reference standard for food allergy diagnosis is the oral food challenge (OFC). OFC should be performed in equivocal cases. For practical reasons, open challenges are suitable in most cases. Reassessment of food allergic children with allergy tests and/or OFCs periodically over time will enable reintroduction of food into the diet in the case of spontaneous acquisition of oral tolerance

From Russia with Love: The Impact of Relocated Firms on Incumbent Survival

We identify the impact of local firm concentration on incumbent performance with a quasi natural experiment. When Germany was divided after World War II, many firms in the machine tool industry fled the Soviet occupied zone to prevent expropriation. We show that the regional location decisions of these firms upon moving to western Germany were driven by non-economic factors and heuristics rather than existing industrial conditions. Relocating firms increased the likelihood of incumbent failure in destination regions, a pattern that differs sharply from new entrants. We further provide evidence that these effects are due to increased competition for local resources

Optics and Quantum Electronics

Contains table of contents on Section 3 and reports on nineteen research projects.Defense Advanced Research Projects Agency Grant F49620-96-0126Joint Services Electronics Program Grant DAAH04-95-1-0038National Science Foundation Grant ECS 94-23737U.S. Air Force - Office of Scientific Research Contract F49620-95-1-0221U.S. Navy - Office of Naval Research Grant N00014-95-1-0715Defense Advanced Research Projects Agency/National Center for Integrated Photonics TechnologyMultidisciplinary Research InitiativeU.S. Air Force - Office of Scientific ResearchNational Science Foundation/MRSECU.S. Navy - Office of Naval Research (MFEL) Contract N00014-91-J-1956National Institutes of Health Grant R01-EY11289U.S. Navy - Office of Naval Research (MFEL) Contract N00014-94-0717Defense Advanced Research Projects Agency Contract N66001-96-C-863

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis