Effective exposure to solar UV in building workers: influence of local and individual factors.

Excessive exposure to solar UV light is the main cause of skin cancers in humans. UV exposure depends on environmental as well as individual factors related to activity. Although outdoor occupational activities contribute significantly to the individual dose received, data on effective exposure are scarce and limited to a few occupations. A study was undertaken in order to assess effective short-term exposure among building workers and characterize the influence of individual and local factors on exposure. The effective exposure of construction workers in a mountainous area in the southern part of Switzerland was investigated through short-term dosimetry (97 dosimeters). Three altitudes, of about 500, 1500 and 2500 m were considered. Individual measurements over 20 working periods were performed using Spore film dosimeters on five body locations. The postural activity of workers was concomitantly recorded and static UV measurements were also performed. Effective exposure among building workers was high and exceeded occupational recommendations, for all individuals for at least one body location. The mean daily UV dose in plain was 11.9 SED (0.0-31.3 SED), in middle mountain 21.4 SED (6.6-46.8 SED) and in high mountain 28.6 SED (0.0-91.1 SED). Measured doses between workers and anatomical locations exhibited a high variability, stressing the role of local exposure conditions and individual factors. Short-term effective exposure ranged between 0 and 200% of ambient irradiation, indicating the occurrence of intense, subacute exposures. A predictive irradiation model was developed to investigate the role of individual factors. Posture and orientation were found to account for at least 38% of the total variance of relative individual exposure, and were also found to account more than altitude on the total variance of effective daily exposures. Targeted sensitization actions through professional information channels and specific prevention messages are recommended. Altitude outdoor workers should also benefit from preventive medical examination.

RFLP clusters of Mycobacterium tuberculosis strains from the Indian Ocean Region: local and South Asian characteristics

This is the first study describing the genetic polymorphism of Mycobacterium tuberculosis strains in the Indian Ocean Region. Using IS6110 RFLP analysis, 475 M. tuberculosis isolates from Madagascar, Comoros, Mauritius, Mozambique and La Reunion were compared. Of the 332 IS6110 profiles found, 43 were shared by clusters containing 2-65 strains. Six clusters were common to at least two countries. Of 52 families of strains with similar IS6110 profiles, 10 were common to at least two countries. Interestingly, another characteristic was the frequency (16.8%) of IS6110 single-copy strains. These strains could be distinguished using the DR marker. This preliminary evaluation suggests genetic similarity between the strains of the Indian Ocean Region. However, additional markers would be useful for epidemiological studies and to assess the ancient transmission of strains between countries of this region.

Vaccination with Trypanosoma rangeli modulates the profiles of immunoglobulins and IL-6 at local and systemic levels in the early phase of Trypanosoma cruzi experimental infection

In America, there are two species of Trypanosoma that can infect humans: Trypanosoma cruzi, which is responsible for Chagas disease and Trypanosoma rangeli, which is not pathogenic. We have developed a model of vaccination in mice with T. rangeli epimastigotes that protects against T. cruzi infection. The goal of this work was to study the pattern of specific immunoglobulins in the peritoneum (the site of infection) and in the sera of mice immunized with T. rangeli before and after challenge with T. cruzi. Additionally, we studied the effects triggered by antigen-antibodies binding and the levels of key cytokines involved in the humoral response, such as IL-4, IL-5 and IL-6. The immunization triggered the production of antibodies reactive with T. cruzi in peritoneal fluid (PF) and in serum, mainly IgG1 and, to a lesser magnitude, IgG2. Only immunized mice developed specific IgG3 antibodies in their peritoneal cavities. Antibodies were able to bind to the surface of the parasites and agglutinate them. Among the cytokines studied, IL-6 was elevated in PF during early infection, with higher levels in non-immunized-infected mice. The results indicate that T. rangeli vaccination against T. cruzi infection triggers a high production of specific IgG isotypes in PF and sera before infection and modulates the levels of IL-6 in PF in the early periods of infection.

BAY 41-2272 activates host defence against local and disseminated Candida albicans infections

In our previous study, we have found that 5-cyclopropyl-2-[1-(2-fluoro-benzyl)-1H-pyrazolo[3,4-b]pyridine-3-yl]-pyrimidin-4-ylamine (BAY 41-2272), a guanylate cyclase agonist, activates human monocytes and the THP-1 cell line to produce the superoxide anion, increasing in vitro microbicidal activity, suggesting that this drug can be used to modulate immune functioning in primary immunodeficiency patients. In the present work, we investigated the potential of the in vivo administration of BAY 41-2272 for the treatment of Candida albicans and Staphylococcus aureus infections introduced via intraperitoneal and subcutaneous inoculation. We found that intraperitoneal treatment with BAY 41-2272 markedly increased macrophage-dependent cell influx to the peritoneum in addition to macrophage functions, such as spreading, zymosan particle phagocytosis and nitric oxide and phorbol myristate acetate-stimulated hydrogen peroxide production. Treatment with BAY 41-2272 was highly effective in reducing the death rate due to intraperitoneal inoculation of C. albicans, but not S. aureus. However, we found that in vitro stimulation of peritoneal macrophages with BAY 41-2272 markedly increased microbicidal activities against both pathogens. Our results show that the prevention of death by the treatment of C. albicans-infected mice with BAY 41-2272 might occur primarily by the modulation of the host immune response through macrophage activation.

Modelling of Mercury’s surface composition and remote detection from the orbit with the BepiColombo Mercury Planetary Orbiter

It can be assumed that the composition of Mercury’s thin gas envelope (exosphere) is related to thecomposition of the planets crustal materials. If this relationship is true, then inferences regarding the bulkchemistry of the planet might be made from a thorough exospheric study. The most vexing of allunsolved problems is the uncertainty in the source of each component. Historically, it has been believedthat H and He come primarily from the solar wind, while Na and K originate from volatilized materialspartitioned between Mercury’s crust and meteoritic impactors. The processes that eject atoms andmolecules into the exosphere of Mercury are generally considered to be thermal vaporization, photonstimulateddesorption (PSD), impact vaporization, and ion sputtering. Each of these processes has its owntemporal and spatial dependence. The exosphere is strongly influenced by Mercury’s highly ellipticalorbit and rapid orbital speed. As a consequence the surface undergoes large fluctuations in temperatureand experiences differences of insolation with longitude. We will discuss these processes but focus moreon the expected surface composition and solar wind particle sputtering which releases material like Caand other elements from the surface minerals and discuss the relevance of composition modelling

Web-based Implementation of Winter Maintenance Decision Support System Using GIS and Remote Sensing, May 2005

Winter maintenance, particularly snow removal and the stress of snow removal materials on public structures, is an enormous budgetary burden on municipalities and nongovernmental maintenance organizations in cold climates. Lately, geospatial technologies such as remote sensing, geographic information systems (GIS), and decision support tools are roviding a valuable tool for planning snow removal operations. A few researchers recently used geospatial technologies to develop winter maintenance tools. However, most of these winter maintenance tools, while having the potential to address some of these information needs, are not typically placed in the hands of planners and other interested stakeholders. Most tools are not constructed with a nontechnical user in mind and lack an easyto-use, easily understood interface. A major goal of this project was to implement a web-based Winter Maintenance Decision Support System (WMDSS) that enhances the capacity of stakeholders (city/county planners, resource managers, transportation personnel, citizens, and policy makers) to evaluate different procedures for managing snow removal assets optimally. This was accomplished by integrating geospatial analytical techniques (GIS and remote sensing), the existing snow removal asset management system, and webbased spatial decision support systems. The web-based system was implemented using the ESRI ArcIMS ActiveX Connector and related web technologies, such as Active Server Pages, JavaScript, HTML, and XML. The expert knowledge on snow removal procedures is gathered and integrated into the system in the form of encoded business rules using Visual Rule Studio. The system developed not only manages the resources but also provides expert advice to assist complex decision making, such as routing, optimal resource allocation, and monitoring live weather information. This system was developed in collaboration with Black Hawk County, IA, the city of Columbia, MO, and the Iowa Department of transportation. This product was also demonstrated for these agencies to improve the usability and applicability of the system.

GUINEA-BISSAU: The Role of Local and International NGOs in Environmental Preservation and Sustainability of the Bijagos Archipelago

Bijagos Archipelago in Guinea-Bissau is at present subject to numerous external impacts that affect its centuries old balance. Since 1975 Guinean society has been using its natural resources in an uncontrolled way over the territory and especially in the coastal area. The archipelago has been increasingly raising interest, most of which is incompatible with the guarantee for a long-term sustainable development. It has also displayed a general impoverishment as far as resource preservation is concerned, due to internal demographic pressure of a population that has doubled since 1981 and to external pressure related to neighboring migrations and consequent depletion of non-renewable resources. This article aims to analyze the actions of local and international NGOs in the preservation and sustainability of the Bijagos Archipelago. We seek through an interdisciplinary approach to analyze the phenomena that are configured within the strategies of NGOs, on the assumption that these issues are articulated in the field of geography and sociology, as well as in politics and international cooperation. It is proposed new challenges to environmental issues, especially in a current situation shaken by constant instability internal and external policies.

The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

On the complementariness of infrasound and seismic sensors for monitoring snow avalanches

The paper analyses and compares infrasonic and seismic data from snow avalanches monitored at the Vallée de la Sionne test site in Switzerland from 2009 to 2010. Using a combination of seismic and infrasound sensors, it is possible not only to detect a snow avalanche but also to distinguish between the different flow regimes and to analyse duration, average speed (for sections of the avalanche path) and avalanche size. Different sensitiveness of the seismic and infrasound sensors to the avalanche regimes is shown. Furthermore, the high amplitudes observed in the infrasound signal for one avalanche were modelled assuming that the suspension layer of the avalanche acts as a moving turbulent sound source. Our results show reproducibility for similar avalanches on the same avalanche path.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Dissection of local and systemic transcriptional responses to phosphate starvation in Arabidopsis.

Phosphate is a crucial and often limiting nutrient for plant growth. To obtain inorganic phosphate (P(i) ), which is very insoluble, and is heterogeneously distributed in the soil, plants have evolved a complex network of morphological and biochemical processes. These processes are controlled by a regulatory system triggered by P(i) concentration, not only present in the medium (external P(i) ), but also inside plant cells (internal P(i) ). A 'split-root' assay was performed to mimic a heterogeneous environment, after which a transcriptomic analysis identified groups of genes either locally or systemically regulated by P(i) starvation at the transcriptional level. These groups revealed coordinated regulations for various functions associated with P(i) starvation (including P(i) uptake, P(i) recovery, lipid metabolism, and metal uptake), and distinct roles for members in gene families. Genetic tools and physiological analyses revealed that genes that are locally regulated appear to be modulated mostly by root development independently of the internal P(i) content. By contrast, internal P(i) was essential to promote the activation of systemic regulation. Reducing the flow of P(i) had no effect on the systemic response, suggesting that a secondary signal, independent of P(i) , could be involved in the response. Furthermore, our results display a direct role for the transcription factor PHR1, as genes systemically controlled by low P(i) have promoters enriched with P1BS motif (PHR1-binding sequences). These data detail various regulatory systems regarding P(i) starvation responses (systemic versus local, and internal versus external P(i) ), and provide tools to analyze and classify the effects of P(i) starvation on plant physiology.

Local and Regional Scale Determinants of Biodiversity Patterns in Boreal Agricultural Landscapes

This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.