Modelling SO2 concentration at a point with statistical approaches

In this paper, the results obtained by inter-comparing several statistical techniques for modelling SO2 concentration at a point such as neural networks, fuzzy logic, generalised additive techniques and other recently proposed statistical approaches are reported. The results of the inter-comparison are the fruits of collaboration between some of the partners of the APPETISE project funded under the Framework V Information Societies and Technologies (IST) programme. Two different cases for study were selected: the Siracusa industrial area, in Italy, where the pollution is dominated by industrial emissions and the Belfast urban area, in the UK, where domestic heating makes an important contribution. The different kinds of pollution (industrial/urban) and different locations of the areas considered make the results more general and interesting. In order to make the inter-comparison more objective, all the modellers considered the same datasets. Missing data in the original time series was filled by using appropriate techniques. The inter-comparison work was carried out on a rigorous basis according to the performance indices recommended by the European Topic Centre on Air and Climate Change (ETC/ACC). The targets for the implemented prediction models were defined according to the EC normative relating to limit values for sulphur dioxide. According to this normative, three different kinds of targets were considered namely daily mean values, daily maximum values and hourly mean values. The inter-compared models were tested on real cases of poor air quality. In the paper, the inter-compared techniques are ranked in terms of their capability to predict critical episodes. A ranking in terms of their predictability of the three different targets considered is also proposed. Several key issues are illustrated and discussed such as the role of input variable selection, the use of meteorological data, and the use of interpolated time series. Moreover, a novel approach referred to as the technique of balancing the training pattern set, which was successfully applied to improve the capability of ANN models to predict exceedences is introduced. The results show that there is no single modelling approach, which generates optimum results in terms of the full range of performance indices considered. In view of the implementation of a warning system for air quality control, approaches that are able to work better in the prediction of critical episodes must be preferred. Therefore, the artificial neural network prediction models can be recommended for this purpose. The best forecasts were achieved for daily averages of SO2 while daily maximum and hourly mean values are difficult to predict with acceptable accuracy

Identification of the Eph receptor pathway as a novel target for eicosapentaenoic acid (EPA) modification of gene expression in human colon adenocarcinoma cells (HT-29)

Abstract Background The health benefits of polyunsaturated fatty acids (PUFAs), particularly those of the n-3 series are well documented. The mechanisms by which these effects are mediated are not fully clarified. Methods We used microarrays to assess the effects on gene expression in HT29 colon adenocarcinoma cells of exposure to the n-3 fatty acid eicosapentaenoic acid (EPA). HT29 cells were cultured with EPA (150 μM) for up to 24 hr prior to harvesting and isolation of RNA. Microarray results were analyzed within the statistical package 'R', and GeneGo MetaCore was used to identify key pathways of altered gene expression. Results EphB4, Vav2 and EphA1 gene expression were identified as significantly altered by EPA treatment. Statistically significant changes in gene expression after HT29 exposure to EPA were confirmed in a second experiment by real-time RT-PCR (TaqMan), This experiment also compared the effects of exposure to EPA to arachadonic acid (AA, n-6). Corresponding changes in protein expression were also assessed by Western blotting. Conclusions Eph receptor mediated signaling is an entirely novel signaling pathway through which EPA may promote a wide range of health benefits, in particular in relation to reduction of colorectal cancer progression.</p

Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki

Five neural network (NN) models, a linear statistical model and a deterministic modelling system (DET) were evaluated for the prediction of urban NO2 and PM10 concentrations. The model evaluation work considered the sequential hourly concentration time series of NO2 and PM10, which were measured at two stations in central Helsinki, from 1996 to 1999. The models utilised selected traffic flow and pre-processed meteorological variables as input data. An imputed concentration dataset was also created, in which the missing values were replaced, in order to obtain a harmonised database that is well suited for the inter-comparison of models. Three statistical criteria were adopted: the index of agreement (IA), the squared correlation coefficient (R2) and the fractional bias. The results obtained with various non-linear NN models show a good agreement with the measured concentration data for NO2; for instance, the annual mean of the IA values and their standard deviations range from 0.86±0.02 to 0.91±0.01. In the case of NO2, the non-linear NN models produce a range of model performance values that are slightly better than those by the DET. NN models generally perform better than the statistical linear model, for predicting both NO2 and PM10 concentrations. In the case of PM10, the model performance statistics of the NN models were not as good as those for NO2 over the entire range of models considered. However, the currently available NN models are neither applicable for predicting spatial concentration distributions in urban areas, nor for evaluating air pollution abatement scenarios for future years

Serum prohepcidin concentration:no association with iron absorption in healthy men; and no relationship with iron status in men carrying HFE mutations, hereditary haemochromatosis patients undergoing phlebotomy treatment, or pregnant women

Hepcidin plays a major role in iron homeostasis, but understanding its role has been hampered by the absence of analytical methods for quantification in blood. A commercial ELISA has been developed for serum prohepcidin, a hepcidin precursor, and there is interest in its potential use in the clinical and research arena. We investigated the association between serum prohepcidin concentration and iron absorption in healthy men, and its relationship with iron status in men carrying HFE mutations, hereditary haemochromatosis patients, and pregnant women. Iron absorption was determined in thirty healthy men (fifteen wild-type, fifteen C282Y heterozygote) using the stable isotope red cell incorporation technique. Iron status was measured in 138 healthy men (ninety-one wild-type, forty-seven C282Y heterozygote), six hereditary haemochromatosis patients, and thirteen pregnant women. Mean serum prohepcidin concentrations were 214 (SD 118) ng/ml [208 (SD 122) ng/ml in wild-type and 225 (SD 109) ng/ml in C282Y heterozygotes] in healthy men, 177 (SD 36) ng/ml in haemochromatosis patients, and 159 (SD 59) ng/ml in pregnant women. There was no relationship between serum prohepcidin concentration and serum ferritin in any subject groups, nor was it associated with efficiency of iron absorption. Serum prohepcidin is not a useful biomarker for clinical or research purposes

Iron absorption in male C282Y heterozygotes

Background: The suggestion that carriers of the HFE C282Y mutation absorb nonheme iron more efficiently than do carriers of the wild type has public health implications for countries where the C282Y mutation is common and foods are fortified with iron. Objective: We investigated the effect of C282Y heterozygosity on nonheme-iron absorption from a diet high in bioavailable iron and from iron-fortified cereals. Design: The subjects were recruited from a parallel study investigating the relation between HFE mutations, habitual diet, and iron status. Iron absorption was measured in 15 wild-type carriers and 15 C282Y heterozygotes aged ≥40 y. Each subject consumed 3 meals of high iron bioavailability (labeled with Fe-57) for 2 d and 2 meals with fortified cereal products (labeled with Fe-54) for the next 3 d. Iron absorption was measured from isotope incorporation into red blood cells 14 d after the last labeled meal and was corrected for utilization of absorbed iron by means of an intravenous infusion of Fe-58. Results: Absorption of Fe-57 with the high-iron-bioavailability diet was 6.8 ± 6.8% (0.6 ± 0.6 mg/d) in the wild-type carriers and 7.6 ± 3.2% (0.7 ± 0.3 mg/d) in the C282Y heterozygotes. Absorption of Fe-54 with cereal products was 4.9 ± 2.0% (0.7 ± 0.3 mg/d) in the wild-type carriers and 5.3 ± 1.3% (0.8 ± 0.2 mg/d) in the C282Y heterozygotes. Conclusions: There was no overall significant difference between C282Y heterozygotes and wild-type men in iron absorption from either dietary nonheme iron or fortified cereal products