Forecasting nano law: defining nano

Law and science have partnered together in the recent past to solve major public health issues, ranging from asbestos to averting the threat of a nuclear holocaust. This paper travels to a legal and health policy frontier where no one has gone before, examining the role of precautionary principles under international law as a matter of codified international jurisprudence by examining draft terminology from prominent sources including the Royal Commission on Environmental Pollution (UK), the Swiss Confederation, the USA (NIOSH) and the OECD. The research questions addressed are how can the benefits of nanotechnology be realized, while minimizing the risk of harm? What law, if any, applies to protect consumers (who comprise the general public, nanotechnology workers and their corporate social partners) and other stakeholders within civil society from liability? What law, if any, applies to prevent harm?

Forecasting changes in population genetic structure of alpine plants in response to global warming.

Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways because of adaptation to their environment. Here, we introduced ancestry distribution models, that is, statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25 to 4 °C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a north-east direction was predicted, the magnitude of displacement was species-specific. For a temperature increase of 2 °C, contact zones were predicted to move by 92 km on average (minimum of 5 km, maximum of 212 km) and by 188 km for an increase of 4 °C (minimum of 11 km, maximum of 393 km). Intra-specific turnover-measuring the extent of change in global population genetic structure-was generally found to be moderate for 2 °C of temperature warming. For 4 °C of warming, however, the models indicated substantial intra-specific turnover for ten species. These results illustrate that, in spite of unavoidable simplifications, ancestry distribution models open new perspectives to forecast population genetic changes within species and complement more traditional distribution-based approaches.

Species distributions and interactions in a changing world : from understanding to forecasting

Les écosystèmes fournissent de nombreuses ressources et services écologiques qui sont utiles à la population humaine. La biodiversité est une composante essentielle des écosystèmes et maintient de nombreux services. Afin d'assurer la permanence des services écosystémiques, des mesures doivent être prises pour conserver la biodiversité. Dans ce but, l'acquisition d'informations détaillées sur la distribution de la biodiversité dans l'espace est essentielle. Les modèles de distribution d'espèces (SDMs) sont des modèles empiriques qui mettent en lien des observations de terrain (présences ou absences d'une espèce) avec des descripteurs de l'environnement, selon des courbes de réponses statistiques qui décrive la niche réalisée des espèces. Ces modèles fournissent des projections spatiales indiquant les lieux les plus favorables pour les espèces considérées. Le principal objectif de cette thèse est de fournir des projections plus réalistes de la distribution des espèces et des communautés en montagne pour le climat présent et futur en considérant non-seulement des variables abiotiques mais aussi biotiques. Les régions de montagne et l'écosystème alpin sont très sensibles aux changements globaux et en même temps assurent de nombreux services écosystémiques. Cette thèse est séparée en trois parties : (i) fournir une meilleure compréhension du rôle des interactions biotiques dans la distribution des espèces et l'assemblage des communautés en montagne (ouest des Alpes Suisses), (ii) permettre le développement d'une nouvelle approche pour modéliser la distribution spatiale de la biodiversité, (iii) fournir des projections plus réalistes de la distribution future des espèces ainsi que de la composition des communautés. En me focalisant sur les papillons, bourdons et plantes vasculaires, j'ai détecté des interactions biotiques importantes qui lient les espèces entre elles. J'ai également identifié la signature du filtre de l'environnement sur les communautés en haute altitude confirmant l'utilité des SDMs pour reproduire ce type de processus. A partir de ces études, j'ai contribué à l'amélioration méthodologique des SDMs dans le but de prédire les communautés en incluant les interactions biotiques et également les processus non-déterministes par une approche probabiliste. Cette approche permet de prédire non-seulement la distribution d'espèces individuelles, mais également celle de communautés dans leur entier en empilant les projections (S-SDMs). Finalement, j'ai utilisé cet outil pour prédire la distribution d'espèces et de communautés dans le passé et le futur. En particulier, j'ai modélisé la migration post-glaciaire de Trollius europaeus qui est à l'origine de la structure génétique intra-spécifique chez cette espèce et évalué les risques de perte face au changement climatique. Finalement, j'ai simulé la distribution des communautés de bourdons pour le 21e siècle afin d'évaluer les changements probables dans ce groupe important de pollinisateurs. La diversité fonctionnelle des bourdons va être altérée par la perte d'espèces spécialistes de haute altitude et ceci va influencer la pollinisation des plantes en haute altitude. - Ecosystems provide a multitude of resources and ecological services, which are useful to human. Biodiversity is an essential component of those ecosystems and guarantee many services. To assure the permanence of ecosystem services for future generation, measure should be applied to conserve biodiversity. For this purpose, the acquisition of detailed information on how biodiversity implicated in ecosystem function is distributed in space is essential. Species distribution models (SDMs) are empirical models relating field observations to environmental predictors based on statistically-derived response surfaces that fit the realized niche. These models result in spatial predictions indicating locations of the most suitable environment for the species and may potentially be applied to predict composition of communities and their functional properties. The main objective of this thesis was to provide more accurate projections of species and communities distribution under current and future climate in mountains by considering not solely abiotic but also biotic drivers of species distribution. Mountain areas and alpine ecosystems are considered as particularly sensitive to global changes and are also sources of essential ecosystem services. This thesis had three main goals: (i) a better ecological understanding of biotic interactions and how they shape the distribution of species and communities, (ii) the development of a novel approach to the spatial modeling of biodiversity, that can account for biotic interactions, and (iii) ecologically more realistic projections of future species distributions, of future composition and structure of communities. Focusing on butterfly and bumblebees in interaction with the vegetation, I detected important biotic interactions for species distribution and community composition of both plant and insects along environmental gradients. I identified the signature of environmental filtering processes at high elevation confirming the suitability of SDMs for reproducing patterns of filtering. Using those case-studies, I improved SDMs by incorporating biotic interaction and accounting for non-deterministic processes and uncertainty using a probabilistic based approach. I used improved modeling to forecast the distribution of species through the past and future climate changes. SDMs hindcasting allowed a better understanding of the spatial range dynamic of Trollius europaeus in Europe at the origin of the species intra-specific genetic diversity and identified the risk of loss of this genetic diversity caused by climate change. By simulating the future distribution of all bumblebee species in the western Swiss Alps under nine climate change scenarios for the 21st century, I found that the functional diversity of this pollinator guild will be largely affected by climate change through the loss of high elevation specialists. In turn, this will have important consequences on alpine plant pollination.

BIOMOD - a platform for ensemble forecasting of species distributions

BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package

Forecasting the effects of global warming on biodiversity

The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations. in this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche-theory models that group species by habitat (more specifically, by environmental conditions under which a species can persist or does persist), (3) general circulation models and coupled ocean-atmosphere-biosphere models, and (4) specics-area curve models that consider all species or large aggregates of species. After outlining the different uses and limitations of these methods, we make eight primary suggestions for improving forecasts. We find that greater use of the fossil record and of modern genetic studies would improve forecasting methods. We note a Quaternary conundrum: While current empirical and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our eight suggestions also point to constructive synergies in the solution to the different problems.

Flowering date of taxonomic families predicts phenological sensitivity to temperature: Implications for forecasting the effects of climate change on unstudied taxa.

PREMISE OF THE STUDY: Numerous long-term studies in seasonal habitats have tracked interannual variation in first flowering date (FFD) in relation to climate, documenting the effect of warming on the FFD of many species. Despite these efforts, long-term phenological observations are still lacking for many species. If we could forecast responses based on taxonomic affinity, however, then we could leverage existing data to predict the climate-related phenological shifts of many taxa not yet studied. METHODS: We examined phenological time series of 1226 species occurrences (1031 unique species in 119 families) across seven sites in North America and England to determine whether family membership (or family mean FFD) predicts the sensitivity of FFD to standardized interannual changes in temperature and precipitation during seasonal periods before flowering and whether families differ significantly in the direction of their phenological shifts. KEY RESULTS: Patterns observed among species within and across sites are mirrored among family means across sites; early-flowering families advance their FFD in response to warming more than late-flowering families. By contrast, we found no consistent relationships among taxa between mean FFD and sensitivity to precipitation as measured here. CONCLUSIONS: Family membership can be used to identify taxa of high and low sensitivity to temperature within the seasonal, temperate zone plant communities analyzed here. The high sensitivity of early-flowering families (and the absence of early-flowering families not sensitive to temperature) may reflect plasticity in flowering time, which may be adaptive in environments where early-season conditions are highly variable among years.

Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

Predictors of temporary and permanent work disability in patients with inflammatory bowel disease: results of the swiss inflammatory bowel disease cohort study.

BACKGROUND: Inflammatory bowel disease can decrease the quality of life and induce work disability. We sought to (1) identify and quantify the predictors of disease-specific work disability in patients with inflammatory bowel disease and (2) assess the suitability of using cross-sectional data to predict future outcomes, using the Swiss Inflammatory Bowel Disease Cohort Study data. METHODS: A total of 1187 patients were enrolled and followed up for an average of 13 months. Predictors included patient and disease characteristics and drug utilization. Potential predictors were identified through an expert panel and published literature. We estimated adjusted effect estimates with 95% confidence intervals using logistic and zero-inflated Poisson regression. RESULTS: Overall, 699 (58.9%) experienced Crohn's disease and 488 (41.1%) had ulcerative colitis. Most important predictors for temporary work disability in patients with Crohn's disease included gender, disease duration, disease activity, C-reactive protein level, smoking, depressive symptoms, fistulas, extraintestinal manifestations, and the use of immunosuppressants/steroids. Temporary work disability in patients with ulcerative colitis was associated with age, disease duration, disease activity, and the use of steroids/antibiotics. In all patients, disease activity emerged as the only predictor of permanent work disability. Comparing data at enrollment versus follow-up yielded substantial differences regarding disability and predictors, with follow-up data showing greater predictor effects. CONCLUSIONS: We identified predictors of work disability in patients with Crohn's disease and ulcerative colitis. Our findings can help in forecasting these disease courses and guide the choice of appropriate measures to prevent adverse outcomes. Comparing cross-sectional and longitudinal data showed that the conduction of cohort studies is inevitable for the examination of disability.

Separation of free amino acids in human plasma by capillary electrophoresis with laser induced fluorescence: potential for emergency diagnosis of inborn errors of metabolism.

Free amino acids (AAs) in human plasma are derivatized with 3-(4-carboxybenzoyl)quinoline-2-carboxaldehyde (CBQCA) and analyzed by capillary electrophoresis (CE) with laser induced fluorescence (LIF) detection. The labeling procedure is significantly improved over results reported previously. Derivatization can be completed in 40 min, with concentrations as low as 4 x 10(-8) M successfully labeled in favourable cases. Twenty-nine AAs (including 2 internal standards) are identified and can be reproducibly separated in 70 min. Migration time RSD values for 23 of these AAs were calculated and found in the range from 0.5 to 4%. The rapid derivatization procedure and the resolution obtained in the separation are sufficient for a semi-quantitative, emergency diagnosis of several inborn errors of metabolism (IEM). Amino acid profiles for both normal donor plasma samples and plasma samples of patients suffering from phenylketonuria, tyrosinemia, maple syrup urinary disease, hyperornithinemia, and citrullinemia are studied.

Advanced trauma life support, 8th edition, the evidence for change.

The American College of Surgeons Committee on Trauma's Advanced Trauma Life Support Course is currently taught in 50 countries. The 8th edition has been revised following broad input by the International ATLS subcommittee. Graded levels of evidence were used to evaluate and approve changes to the course content. New materials related to principles of disaster management have been added. ATLS is a common language teaching one safe way of initial trauma assessment and management.

Genomik und personalisierte Medizin [Genomics and personalized medicine].

Personalized medicine has a substantial potential to transform the way diseases will be predicted, prevented and treated. The field will greatly benefit from novel DNA sequencing technologies, in particular commoditization of individual whole genome sequencing. This evolution cannot be stopped, and the medical and scientific community, as well as the society at large, have the responsibility to anticipate the expected benefits from this revolution, but also the potential risks associated with it. Massive investments will be needed for the potential of personalized medicine to be realized, and for the field to come to maturity. In particular, a paradigm change in the way clinical research is done is needed. Switzerland and its Western part pro-actively anticipate these changes.