Effects of particulate matters on inflammatory markers in the general adult population

Summary: Particulate air pollution is associated with increased cardiovascular risk. The induction of systemic inflammation following particle inhalation represents a plausible mechanistic pathway. The purpose of this study was to assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers in 6183 adults in Lausanne, Switzerland. The results show that short-term exposure to PM10 was associated with higher levels of circulating IL-6 and TNF-α. The positive association of PM10 with markers of systemic inflammation materializes the link between air pollution and cardiovascular risk. Background: Variations in short-term exposure to particulate matters (PM) have been repeatedly associated with daily all-cause mortality. Particle-induced inflammation has been postulated to be one of the important mechanisms for increased cardiovascular risk. Experimental in-vitro, in-vivo and controlled human studies suggest that interleukin 6 (IL-6) and tumor-necrosis-factor alpha (TNF-α) could represent key mediators of the inflammatory response to PM. The associations of short-term exposure to ambient PM with circulating inflammatory markers have been inconsistent in studies including specific subgroups so far. The epidemiological evidence linking short-term exposure to ambient PM and systemic inflammation in the general population is scarce. So far, large-scale population-based studies have not explored important inflammatory markers such as IL-6, IL-1β or TNF-α. We therefore analyzed the associations between short-term exposure to ambient PM10 and circulating levels of high-sensitive CRP (hs-CRP), IL-6, IL-1β and TNF-α in the population-based CoLaus study. Objectives: To assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers, including hs-CRP, IL-6, IL-1β and TNF-α, in adults aged 35 to 75 years from the general population. Methodology: All study subjects were participants to the CoLaus study (www.colaus.ch) and the baseline examination was carried out from 2003 to 2006. Overall, 6184 participants were included. For the present analysis, 6183 participants had data on at least one of the four measured circulating inflammatory markers. The monitoring data was obtained from the website of Swiss National Air Pollution Monitoring Network (NABEL). We analyzed data on PM10 as well as outside air temperature, pressure and humidity. Hourly concentrations of PM10 were collected from 1 January 2003 to 31 December 2006. Robust linear regression (PROC ROBUSTREG) was used to evaluate the relationship between cytokine inflammatory and PM10. We adjusted all analyses for age, sex, body mass index, smoking status, alcohol consumption, diabetes status, hypertension status, education levels, zip code, and statin intake. All data were adjusted for the effects of weather by including temperature, barometric pressure, and season as covariates in the adjusted models. We performed simple and multiple logistic regression analyses. Descriptive statistical analysis used the Wilcoxon rank sum test (for medians). All data analyses were performed using SAS software (version 9.2; SAS Institute Inc., Cary, NC, USA), and a two-sided significance level of 5% was used. Results: PM10 levels averaged over 24 hours were significantly and positively associated with continuous IL-6 and TNF-α levels, in the whole study population both in unadjusted and adjusted analyses. For each cytokine, there was a similar seasonal pattern, with wider confidence intervals in summer than during the other seasons, which might partly be due to the smaller number of participants examined in summer. The associations of PM10 with IL-6 and TNF-α were also found after having dichotomized these cytokines into high versus low levels, which suggests that the associations of PM10 with the continuous cytokine levels are very robust to any distributional assumption and to potential outlier values. In contrast with what we observed for continuous IL-1β levels, high PM10 levels were significantly associated with high IL-1β. PM10 was significantly associated with IL-6 and TNF-α in men, but with TNF-α only in women. However, there was no significant statistical interaction between PM10 and sex. For IL-6 and TNF-α, the associations tended to be stronger in younger people, with a significant interaction between PM10 and age groups for IL-6. PM10 was significantly associated with IL-6 and TNF-α in the healthy group and also in the "non-healthy" group, although the statistical interaction between healthy status and PM10 was not significant. Conclusion: In summary, we found significant independent positive associations of short-term exposure to PM10 with circulating levels of IL-6 and TNF-α in the adult population of Lausanne. Our findings strongly support the idea that short-term exposure to PM10 is sufficient to induce systemic inflammation on a broad scale in the general population. From a public health perspective, the reported association of elevated inflammatory cytokines with short-term exposure to PM10 in a city with relatively clean air such as Lausanne supports the importance of limiting urban air pollution levels.

Kytkentäisen lähiverkon palvelutason mittaaminen

Tässä diplomityössä tutkittiin yrityksen Ethernet-lähiverkon palvelutasoa, palveluiden saatavuuden näkökulmasta. Tutkimus pohjautui käytännön tarpeeseen. Palvelun saatavuuteen verkon osalta vaikuttavat sen käyttöaste, virheet ja viiveet. Työssä käytettiin valmiita kaupallisia ohjelmia verkon hallintaan ja verkkostatistiikan keräämiseen. Työssä selvitettiin teoriapohjaa laitteiden, kytkentätekniikoiden, palvelulaatuprotokollien (QoS), tietoliikenneprotokollien, RMON:in, SNMP:in ja VLAN:in osalta, jotka yhdessä muodostavat kytkentäisen lähiverkon palvelutason. Työn tuloksena todettiin mittauskohteena olevan lähiverkon palvelutason olevan hyvällä tasolla. Työn tuloksista pääteltiin tulevaisuuden suurimpana haasteena olevan lähiverkkoja yhdistävien yhteyksien nostaminen selvästi paremmalle suoritustasolle. Lähiverkkojen teoreettinen suorituskyky onkin useimmiten riittävä, mutta lähiverkkojen hallinnassa on parantamisen varaa. Työssä toteutettiin seurantajärjestelmä, jolla on helppo seurata lähiverkon palvelutason kehitystä jatkossa.

Tratamento estatístico dos parâmetros da qualidade das águas da bacia do alto curso do Rio das Velhas

Water quality was monitored at the upper course of the Rio das Velhas, a major tributary of the São Francisco basin located in the state of Minas Gerais, over an extension of 108 km from its source up to the limits with the Sabara district. Monitoring was done at 37 different sites over a period of 2 years (2003-2004) for 39 parameters. Multivariate statistical techniques were applied to interpret the large water-quality data set and to establish an optimal long-term monitoring network. Cluster analysis separated the sampling sites into groups of similarity, and also indicated the stations investigated for correlation and recommended to be removed from the monitoring network. Principal component analysis identified four components, which are responsible for the data structure explaining 80% of the total variance of the data. The principal parameters are characterized as due to mining activities and domestic sewage. Significant data reduction was achieved.

Identification of Summer Origins of Songbirds Migrating through Southern Canada in Autumn

Stable hydrogen isotopes (δD) in flight feathers were measured to investigate the summer origins of five species of boreal-breeding warblers captured during fall migration at Canadian Migration Monitoring Network (CMMN) stations spread across southern Canada. Mean δD varied among stations and species within stations, but there was broad overlap in δD values. Although isotope ratios indicate that migrants at each station come from a wide range of latitudes, they are unable to provide much longitudinal discrimination. Band recoveries are sparse, but indicate that in general western Canadian warblers move southeast in fall, eastern birds move southwest, and there is a transition zone in the Great Lakes region. Combining knowledge of migratory direction with isotope results increases discrimination of breeding areas. Isotope results support fall migratory movements by Blackpoll Warbler (Dendroica striata) and Northern Waterthrush (Seiurus novaboracensis) that are more easterly than for other species, and in all study species, birds from more northern regions passed through southern Canada later in the season. Migration monitoring stations capture birds from broad areas of latitude, and migrants passing through each province appear to come from largely different portions of the Canadian breeding range, so a few stations placed in each province should suffice collectively to sample birds from most of the boreal forest. Migration monitoring in southern Canada, therefore, has the potential to monitor status of boreal forest birds in Canada that are unsampled by other monitoring programs.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

Alternative explanations for rising dissolved organic carbon export from organic soils

Since 1988, there has been, on average, a 91% increase in dissolved organic carbon (DOC) concentrations of UK lakes and streams in the Acid Waters Monitoring Network (AWMN). Similar DOC increases have been observed in surface waters across much of Europe and North America. Much of the debate about the causes of rising DOC has, as in other studies relating to the carbon cycle, focused on factors related to climate change. Data from our peat-core experiments support an influence of climate on DOC, notably an increase in production with temperature under aerobic, and to a lesser extent anaerobic, conditions. However, we argue that climatic factors may not be the dominant drivers of DOC change. DOC solubility is suppressed by high soil water acidity and ionic strength, both of which have decreased as a result of declining sulphur deposition since the 1980s, augmented during the 1990s in the United Kingdom by a cyclical decline in sea-salt deposition. Our observational and experimental data demonstrate a clear, inverse and quantitatively important link between DOC and sulphate concentrations in soil solution. Statistical analysis of 11 AWMN lakes suggests that rising temperature, declining sulphur deposition and changing sea-salt loading can account for the majority of the observed DOC trend. This combination of evidence points to the changing chemical composition of atmospheric deposition, particularly the substantial reduction in anthropogenic sulphur emissions during the last 20 years, as a key cause of rising DOC. The implications of rising DOC export for the carbon cycle will be very different if linked primarily to decreasing acid deposition, rather than to changes in climate, suggesting that these systems may be recovering rather than destabilising.

Buffering of recovery from acidification by organic acids

In the United Kingdom, as in other regions of Europe and North America, recent decreases in surface water sulphate concentrations, due to reduced sulphur emissions, have coincided with marked increases in dissolved organic carbon (DOC) concentrations. Since many of the compounds comprising DOC are acidic, the resulting increases in organic acidity may have the potential to offset the benefits of a decrease in mineral (sulphate) acidity. To test this, we used a triprotic model of organic acid dissociation to estimate the proportional organic acid buffering of reduced mineral acidity as measured in the 22 lakes and streams monitored by the UK Acid Waters Monitoring Network. For an average non-marine sulphate decrease of 30 μeq l− 1 over 15 years from 1988–2003, we estimate that around 28% was counterbalanced by rising strong organic acids, 20% by rising alkalinity (partly attributable to an increase in weak organic acids), 11% by falling inorganic aluminium and 41% by falling non-marine base cations. The situation is complicated by a concurrent decrease in marine ion concentrations, and the impact this may have had on both DOC and acidity, but results clearly demonstrate that organic acid increases have substantially limited the amount of recovery from acidification (in terms of rising alkalinity and falling aluminium) that have resulted from reducing sulphur emissions. The consistency and magnitude of sulphate and organic acid changes are consistent with a causal link between the two, possibly due to the effects of changing acidity, ionic strength and aluminium concentrations on organic matter solubility. If this is the case, then organic acids can be considered effective but partial buffers to acidity change in organic soils, and this mechanism needs to be considered in assessing and modelling recovery from acidification, and in defining realistic reference conditions. However, large spatial variations in the relative magnitude of organic acid and sulphate changes, notably for low-deposition sites in northwestern areas where organic acid increases apparently exceed non-marine sulphate decreases, suggest that additional factors, such as changes in sea-salt deposition and climatic factors, may be required to explain the full magnitude of DOC increases in UK surface waters.

Using non-homogeneous Poisson models with multiple change-points to estimate the number of ozone exceedances in Mexico City

In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Poisson process has rate function lambda(t), t >= 0, which depends on some parameters that must be estimated. We take into account two cases of rate functions: the Weibull and the Goel-Okumoto. We consider models with and without change-points. When the presence of change-points is assumed, we may have the presence of either one, two or three change-points, depending of the data set. The parameters of the rate functions are estimated using a Gibbs sampling algorithm. Results are applied to ozone data provided by the Mexico City monitoring network. In a first instance, we assume that there are no change-points present. Depending on the adjustment of the model, we assume the presence of either one, two or three change-points. Copyright (C) 2009 John Wiley & Sons, Ltd.

Estimating the number of ozone peaks in Mexico City using a non-homogeneous Poisson model

In this paper, we consider the problem of estimating the number of times an air quality standard is exceeded in a given period of time. A non-homogeneous Poisson model is proposed to analyse this issue. The rate at which the Poisson events occur is given by a rate function lambda(t), t >= 0. This rate function also depends on some parameters that need to be estimated. Two forms of lambda(t), t >= 0 are considered. One of them is of the Weibull form and the other is of the exponentiated-Weibull form. The parameters estimation is made using a Bayesian formulation based on the Gibbs sampling algorithm. The assignation of the prior distributions for the parameters is made in two stages. In the first stage, non-informative prior distributions are considered. Using the information provided by the first stage, more informative prior distributions are used in the second one. The theoretical development is applied to data provided by the monitoring network of Mexico City. The rate function that best fit the data varies according to the region of the city and/or threshold that is considered. In some cases the best fit is the Weibull form and in other cases the best option is the exponentiated-Weibull. Copyright (C) 2007 John Wiley & Sons, Ltd.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.

Implementação de um Módulo de Supervisão para um Sistema de Detecção de Vazamentos em Dutos de Petróleo

The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic Structure of Populations of the Rice-Infecting Pathogen Rhizoctonia solani AG-1 IA from China

Sheath blight disease (SBD) on rice, caused by Rhizoctonia solani AG-1 IA, is one of the most devastating rice diseases on a global basis, including China (in Eastern Asia), the world's largest rice-growing country. We analyzed the population genetics of nine rice-infecting populations from China using nine microsatellite loci. One allopatric population from India (Southern Asia) was included in the analyses. In total, 300 different multilocus genotypes were found among 572 fungal isolates. Clonal fractions within rice fields were 16 to 95%, suggesting that sclerotia were a major source of primary inoculum in some fields. Global Phi(ST) statistics (Phi(ST) = 42.49; P <= 0.001) were consistent with a relatively high level of differentiation among populations overall; however, pairwise comparisons gave nonsignificant R(ST) values, consistent with contemporary gene flow among five of the populations. Four of these populations were located along the Yangtze River tributary network. Gene flow followed an isolation-by-distance model consistent with restricted long-distance migration. Historical migration rates were reconstructed and yielded values that explained the current levels of population subdivision. Except for one population which appeared to be strictly clonal, all populations showed evidence of a mixed reproductive mode, including both asexual and sexual reproduction. One population had a strictly recombining structure (all loci were in Hardy-Weinberg equilibrium) but the remaining populations from China and the one from India exhibited varying degrees of sexual reproduction. Six populations showed significant F(IS) values consistent with inbreeding.

Condições hidrológicas de uma bacia hidrográfica com diferentes usos do solo na região de taquaritinga, SP

In areas where human activities, as agriculture, are developed land use contributes to physical, chemical and biological characteristics of water. This study aimed to identify physical and chemical variations of the water monitoring network in 4 first magnitude watersheds with different land use/occupation in the hydrographic basin of the Glori Farm Creek in the city of Taquaritinga, State of Sao Paulo, from February to July, 2005. The methodology consisted of weekly sample water collections to naalyze turbidity, temperature, dissolved oxygen, pH and electric conductivity. The characterization of the hydrological conditions of the watersheds showed that agricultural activities, including the productive system of the sugarcane cultivation, have affected the quality of water resources.