Long-range ozone transport and its impact on respiratory and cardiovascular health in the north of Portugal

Ozone dynamics depend on meteorological characteristics such as wind, radiation, sunshine, air temperature and precipitation. The aim of this study was to determine ozone trajectories along the northern coast of Portugal during the summer months of 2005, when there was a spate of forest fires in the region, evaluating their impact on respiratory and cardiovascular health in the greater metropolitan area of Porto. We investigated the following diseases, as coded in the ninth revision of the International Classification of Diseases: hypertensive disease (codes 401-405); ischemic heart disease (codes 410-414); other cardiac diseases, including heart failure (codes 426-428); chronic obstructive pulmonary disease and allied conditions, including bronchitis and asthma (codes 490-496); and pneumoconiosis and other lung diseases due to external agents (codes 500-507). We evaluated ozone data from air quality monitoring stations in the study area, together with data collected through HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model analysis of air mass circulation and synoptic-scale zonal wind from National Centers for Environmental Prediction data. High ozone levels in rural areas were attributed to the dispersion of pollutants induced by local circulation, as well as by mesoscale and synoptic scale processes. The fires of 2005 increased the levels of pollutants resulting from the direct emission of gases and particles into the atmosphere, especially when there were incoming frontal systems. For the meteorological case studies analyzed, peaks in ozone concentration were positively associated with higher rates of hospital admissions for cardiovascular diseases, although there were no significant associations between ozone peaks and admissions for respiratory diseases.

A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem

In this article, we introduce a semi-parametric Bayesian approach based on Dirichlet process priors for the discrete calibration problem in binomial regression models. An interesting topic is the dosimetry problem related to the dose-response model. A hierarchical formulation is provided so that a Markov chain Monte Carlo approach is developed. The methodology is applied to simulated and real data.

Risk of Giardia infection for drinking water and bathing in a peri-urban area in Sao Paulo, Brazil

A high incidence of waterborne diseases is observed worldwide and in order to address contamination problems prior to an outbreak, quantitative microbial risk assessment is a useful tool for estimating the risk of infection. The objective of this paper was to assess the probability of Giardia infection from consuming water from shallow wells in a peri-urban area. Giardia has been described as an important waterborne pathogen and reported in several water sources, including ground waters. Sixteen water samples were collected and examined according to the US EPA (1623, 2005). A Monte Carlo method was used to address the potential risk as described by the exponential dose response model. Giardia cysts occurred in 62.5% of the samples (0.1-36.1 cysts/l). A median risk of 10-1 for the population was estimated and the adult ingestion was the highest risk driver. This study illustrates the vulnerability of shallow well water supply systems in peri-urban areas.

A new model of outbred genetically selected mice which present a strong acute inflammatory response in the absence of complement component C5

Mice selected for a strong (AIRmax) or weak (AIRmin) acute inflammatory response present different susceptibilities to bacterial infections, autoimmune diseases and carcinogenesis. Variations in these phenotypes have been also detected in AIRmax and AIRmin mice rendered homozygous for Slc11a1 resistant (R) and susceptible (S) alleles. Our aim was to investigate if the phenotypic differences observed in these mice was related to the complement system. AIRmax and AIRmin mice and AIRmax and AIRmin groups homozygous for the resistance (R) or susceptibility (S) alleles of the solute carrier family 11a1 member (Slc11a1) gene, formerly designated Nramp-1. While no difference in complement activity was detected in sera from AIRmax and AIRmin strains, all sera from AIRmax Slc11a1 resistant mice (AIRmax(RR)) presented no complement-dependent hemolytic activity. Furthermore, C5 was not found in their sera by immunodiffusion and, polymerase chain reaction and DNA sequencing of its gene demonstrated that AIRmax(RR) mice are homozygous for the C5 deficient (D) mutation previously described in A/J. Therefore, the C5D allele was fixed in homozygosis in AIRmax(RR) line. The AIRmax(RR) line is a new experimental mouse model in which a strong inflammatory response can be triggered in vivo in the absence of C5.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.